Volume 12 Issue 4

Design, Modelling and Simulation of an Improved Manual Tyre- Changer Machine

Authors- Emomotimi Obonika Waratimi, Alexander N. Okpala,
Godfrey Ayeabu Sibete, Philip Yemi Olisa

Abstract-The conceptual designs for the manual tyre-changer machine (MTCM) was generated, detail design of the MTCM as well as proper material selection for the MTCM was carried out, and ultimately, the performance of the designed and fabricated MTCM was modeled and simulated. The results from the analysis showed that the design of improved manual tyre changer machine has mechanical advantage of bead breaker arm of 8.67, wall thickness of bead breaker arm of 4.8738mm, allowable bending stress of 80 N/mm2, allowable shear stress 40 N/mm2, shank diameter of bolt at A 10.84949mm, shank diameter of bolt at B 11.3743mm, height/thickness of nut at A and B 9.6mm, length of a side of the outer square section of insertion/extraction arm based on bending stress is 46.296mm, length of a side of the inner square section of mount/demount arm based on bending stress 38.58mm, angle of twist of a 60mm × 60mm × 5mm insertion/extraction arm while inserting/extracting a tyre on 16” × 7” rim was selected due to its lower angle of twist of 3.6848×10-9 rad. The circular pitch for the pinion gear was determined as 9.426mm.The circular pitch for the driven gear is determined as 6.284mm.The module for the pinion gear was determined as 3mm.The module for the driven gear was determined as 2.4mm.The number of teeth for pinion gear is determined as 20.The number of teeth for driven gear was determined as 30. The torque on driven gear is 4340.02N-mm and the force acting on gear teeth was determined as 144. 67N. The contact stress for the pinion gear was determined as 4.00N/m2. The ANSYS simulation results also showed that the maximum value of equivalent stress for the MTCM roller bearing was 3.2406Pa, the maximum value of equivalent elastic strain for the MTCM roller bearing was 7.8388 x 10-10m/m and the maximum value of total deformation for the MTCM roller bearing was 5.7215 x 10-8m. Conclusion and recommendations were made that ANSYS simulation tool applied in this study have shown that it is possible to predict how the machine components will behave in a real case and allows the engineer to see where the stresses, strains and total deformations will be the greatest and how the machine will behave with such occurrence to provide better reference for redesign of the machine.

Stress Pattern Analysis of Rectangular Polystyrene Specimen Using Photoeslasticity Method

Authors- Om Prakash Sondhiya, Roopesh Tiwari

Abstract-Photoelasticity is a non-destructive testing technique of visualizing of stress on a model subjected to load, due to the property of material called as birefringence or double refraction. The crystalline solid have a property of birefringence that is change in refractive indices of the material on application of load. The change of refractive indices generates fringe pattern on the axis perpendicular to the application of load. The fringe pattern thus obtained is analyzed and calculations of stresses within the model are analyzed. This synopsis provides the extent to which photoelasticity technique has been explored in various field of science and research. The objective of this project is to provide a suitable understanding of the technique and the extent of research work done in this field. A literature search was conducted, using keywords photoelasticity, nondestructive testing, principal stress and fringe pattern. The article and research paper were shortlisted for reading and data analysis, articles related to photoelasticity and stress measurement techniques. This research work gives the review of photoelasticity in various fields of research.

DOI: /10.61463/ijset.vol.12.issue4.191

Formulation of Corn Wraps

Authors- Jaya Upraity

Abstract-The current research aims to substitute wheat flour with corn flour and quinoa flour to produce gluten free bakery products such as bread biscuits and wraps to use in autism disease and celiac cases nutrition. Quinoa flour (Q) and wheat flour were substituted at 20, 30 and 50% for corn flour as a control (C) was evaluated. This research studied the effect of substituting corn flour and quinoa flour with wheat flour on the nutritional, physical and sensory qualities of the flour and bakery product which was developed (corn wraps). The results showed that protein, ash, fiber, fat and mineral elements levels are higher in the quinoa flour and corn flour, causing rise in protein, ash, fiber and fat in the composite flour, thus improving the nutritional characteristics of the product. Also, the results showed a decrease in physical and sensory characteristics with increased levels of quinoa flour to corn flour in corn wraps. Generally, replacement levels 20 and 30% of quinoa flour showed acceptable results in the sensory and physical properties in corn wraps with a significant improvement in the nutritional qualities. It can be concluded that wheat can be easily replaced by quinoa and corn flour as wheat is the major cause of teen obesity nowadays.

Development of a New Type of Air-Barrier Slabs to Mitigate the Thermal Bridging Activity

Authors- Md Asfaq Hafiz, Md Ashiqul Islam, Sk Md Imdadul Islam, Md Shoriful Islam

Abstract-Flat concrete roofs, a common global roofing system, are particularly susceptible to high temperatures during summer due to extended sun exposure. This often results in increased indoor temperatures on top floors, leading to a significant rise in cooling costs – a concern with both individual and national economic implications. Despite available solutions, like insulation, the cost of implementation post-construction can be prohibitive. This is especially true in South Asia, where vast urban areas consist predominantly of concrete structures and comprehensive heat control measures are seldom in place. Heat absorption by a top floor is influenced by factors such as seasonal changes, sun exposure, and the physical and thermal properties of construction materials. This study introduces a cost-effective strategy: the application of an additional layer of Surkhi. Surkhi, a fine powder made from grinding burnt bricks or clay pots, is a pozzolanic material common in South Asian construction. An air gap is maintained between this layer and the concrete slab. Additionally, asbestos and mud pots are placed between the Surkhi and the slab, creating a mix of non-entrapped and entrapped air spaces.

Students’ Perceptions and Self-Efficacy towards Mobile Learning in Higher Education: A Post-COVID Era Study in Malaysia

Authors- Nirumala Rothinam, Juliana Binti Jelani, Nurlisa Sarah Binti Mohammad Azmi, Associate Professor Dr. Samikkanu Jabamoney S/O Ishak Samuel

Abstract-This study investigates university students’ perceptions and self-efficacy towards mobile learning (m-learning) in the post-COVID era. Conducted at a private university in Malaysia, the research employed a descriptive survey design with a sample of 84 undergraduate students. The study utilized an adapted questionnaire to measure various aspects of m-learning perception and self-efficacy. Results indicate generally positive attitudes towards m-learning, with students appreciating its flexibility and accessibility. However, challenges such as potential distractions and technical issues were also identified. The findings contribute to the growing body of knowledge on m-learning in higher education and offer insights for educators and policymakers in developing effective m-learning strategies.

Real-Time Monitoring of Battery Parameters for a Solar Powered E-Vehicle

Authors- Assistant Professor Murthy.S.E, Punitha.S, Arun.M, Suriyakumar.A, Vasanth.S

Abstract-With the growing demand for sustainable transportation options, solar-powered electric vehicles (EVs) have received a lot of attention. In this research, we propose a system that combines solar energy harvesting, storage, and utilization to power electric automobiles. The system propulsion is provided by a Brushless DC (BLDC) motor, which is connected to a solar energy storage system integrated with a boost converter to increase output power. An Arduino-based display allows for real-time monitoring of solar input voltage, boost output voltage, and battery voltage. Data is transferred to the cloud via an ESP8266 module, allowing for remote monitoring and control using the Blynk mobile app. This research seeks to demonstrate the viability and efficiency of solar-powered EVs while also providing a sustainable and environmentally friendly form of transportation.

Instrument Cluster Utilizing Technical Specifications

Authors- Vedant Dandekar, Ritik Patel, Pratik Jain

Abstract-Accident Detection in Two Wheelers is a tool which helps to detect accidents occurring intwo wheeler vehicles using IoT. This system features several components such as automatic vehicle tracking, accident detection algorithms, crash alert notifications, and an interface for driver safety control. The accident detection process begins by collecting location data from two wheelers as they move along the road network. Initially, the system uses GPS-enabled devices and sensors to collect position information which is then processed with advanced algorithms to anticipate an imminent collision risk. A crash alert notification is sent to involved drivers if any possible collision occurs on the route so that necessary preventive measures can be taken promptly ahead of time. To further enhance safety, an interface has also been developed for driver assistance where the rider can control his vehicle using voice commands or gestures input such as lean slant control for cornering and braking assistance systems during emergency situations. In addition, data collected from the accident detection system can be used in future analytics and research related applications such as developing better police traffic databases, suggesting safer routes based on past accidents or to understand true root cause of motorcycle run-offs. Moreover, it may also be used to suggest smarter regulations focusing on reducing human errors or encouraging innovation related to higher road safety standards. In conclusion, Accident Detection in Two Wheelers helps significantly reduce human errors related to motorcycling cases and thus supporting riders on their journeys leading towards safer roads ahead.

DOI: /10.61463/ijset.vol.12.issue4.194

Design and Implementation of Bridge type Dual Input Single Output DC-DC Converter for Micro grid Applications

Authors- Assistant Professor Mrs.P. Rekha, Mounica K, Iyyappan R, Suriya SK, Mozhiyarasan R

Abstract-This paper proposes a bridge-type dual-input single-output (DISO) DC-DC converter tailored for micro grid applications. The innovative converter design integrates the functionalities of boost, buck-boost converters, enabling efficient power conversion from two independent DC sources to a regulated DC output voltage suitable for micro grid integration. The bridge configuration utilizes switching elements to control the power flow from each input, achieving the desired voltage conversion with high efficiency. To validate the performance of converter’s, a detailed software simulation was conducted using the MATLAB/Simulink platform and incorporating key parameters such as the equivalent series resistance of passive elements and overall efficiency. Additionally, a hardware prototype of the improved converter was developed and successfully tested in a laboratory. The proposed converter has several advantages over current topologies, such as fewer components, a more compact design and better energy efficiency. These merits position the bridge-type DISO DC-DC converter as a highly effective solution for modern micro grid applications.

Asking for Empathy in Technology- Write “Dayan”

Authors- Savita Singh

Abstract-“I wrote Dayan (witch) 10 times to emotional voices from machine ….. Brain is calm and relaxed. I am surprised why?”

DOI: /10.61463/ijset.vol.12.issue4.195

Impact of Social Media in Library and Information Services: A Brief Study

Authors- Chitransh Dixit, Kanchan Lata Dixt, Chandra Kumar Dixit, Praveen Kumar Pandey

Abstract-This paper explore the Social media use for online library services, Social media a Digital Platforms the enable to library users to create and share own view, Social networking sites is an Online platform for the Library User. This study finds out the characteristics of social media like a Impact Society, Online Platforms, User Generated, Global, Impact of Society. The Role of Social media like a Marketing of Library product and services. Library Reference Services, Library Online Platform, Library Portal, Sharing the Data, Library Services Feedback by uses through the like post and comments, Library promotion of Library Events and user program, Collaboration to each other and Cost Effective Marketing of Library product and Services.

DOI: /10.61463/ijset.vol.12.issue4.196

National Institutes of Technology’s Information Libraries and their Services: A Study

Authors- Chitransh Dixit, Kanchan Lata Dixit, Chandra Kumar Dixit, Praveen Kumar Pandey

Abstract-Technical education is very important for the development of any country. Many institutions are established in India for this purpose. The National Institute of Technology is one of India’s finest institutions for science and engineering, and their library is crucial to advancing technical education. The present study is conducted to trace out the status of NITs lnformation and its various services which are provided to the users. The paper will also cover the different types of collection available in library. The findings of the paper show that NITs information have a rich collection both in print and non print format. To meet the needs and goals of NIT users, lnformation offer a variety of specialized services to users.

DOI: /10.61463/ijset.vol.12.issue4.197

Library and Information Services in the Changing Environment

Authors- Chitransh Dixit, Kanchan Lata Dixt, Chandra Kumar Dixit, Praveen Kumar Pandey

Abstract-Various changes have been taking place in the field of library as an organization. Major three changes taking place in the library field are i.e. Technological change, Dissemination change and Managerial Change. To manage these changes, professional must have three qualities i.e. knowledge, skill and attitude.

DOI: /10.61463/ijset.vol.12.issue4.198

The Role and Evolution of Libraries in the Information Age

Authors- Chitransh Dixit, Kanchan Lata Dixit, Chandra Kumar Dixit, Praveen Kumar Pandey

Abstract-The primary purpose of the paper is to explore the multifaceted roles that libraries have played throughout history and to emphasize their enduring importance in contemporary society. The present paper delineates the role of libraries as learning institutions that have existed in our society since ancient times. It discusses the activities of libraries, stakeholders (users), and the integration of technology such as library networks, library portals, online reference services, and online catalogues. The paper aims to highlight the significance of libraries in fulfilling the informational needs of their users and their importance in contemporary society. Understanding is provided about what libraries are, their need, purpose, and importance. In the modern age, with an abundance of information, libraries play a crucial role in maintaining and disseminating relevant information as required. The paper is findings are Libraries have transformed from private collections in ancient times (e.g., the Library of Alexandria) to public and university libraries during the Renaissance and the 19th-century modern library movement. Monastic libraries played a crucial role in preserving knowledge through the medieval period.

DOI: /10.61463/ijset.vol.12.issue4.199

Study the Effects of Trailing Edge Geometry on Airfoil Performance

Authors- Vedant Chaudhari

Abstract-The primary objective of this paper is to investigate the impact of trailing edge geometry on airfoil performance. The chosen airfoil, such as NACA 652415, serves as the basis for four distinct cases, each involving variations in the trailing edge. This leads to alterations in the airfoil geometry and NACA series. In the first case, the trailing edge is configured to be sharp. In the second case, the trailing edge is rounded by inscribing a circle with a specific radius. The third case involves considering a circumcircle at the trailing edge point and drawing tangents connecting the airfoil. The fourth case introduces changes to the dimensions of the circle. The project utilizes IMIME software for meshing and CFD++ for CFD analysis, both developed by Metacomp Technologies. The analysis is centred around examining key aerodynamic parameters, including the coefficient of lift, coefficient of drag, pitching moment, drag polar, coefficient of pressure, and the location of the Centre of pressure. These investigations are conducted across a range of angles of attack to comprehensively understand the airfoil’s performance under varying conditions. This investigation utilizes IMIME software for meshing and CFD++ for CFD analysis, both developed by Metacomp Technologies.

DOI: /10.61463/ijset.vol.12.issue4.200

Exploring Avenues to Mitigate Threshold Voltage Variations in Ferro-Electric Field Effect Transistor (FeFET)

Authors- Assistant Professor Shailesh Madhav Keshkamat

Abstract-Ultralow-power and high-performance electronic devices are in huge demand due to the requirements of advanced technologies such as the Internet of Things (IoT), mobile smart devices, and wearable electronics. This has brought out to the fore the applications of Ferro-Electric FET (FEFET) which find huge potential in data computing along with global connectivity. However, the FEFET is besought with anomalies dealing with the threshold voltage arising on account of various factors. While few factors are inherently material property dependent, others are incorporated inadvertently due to the processes in fabrication. There is tremendous scope for the enhancement of performance parameters especially the variations of threshold voltage. While the material dependent anomalies can be overcome by the use of compound belonging to group III-V or group II-VI elements, the scope to modify the existing fabrication processes also has to be further finetuned. This paper deals initially with the concept of negative capacitance which becomes the foundation for the FEFET, and also the underlying mechanism of polarization in the multiple domains. Even though the concept of negative capacitance was in existence for long time, the technological advancement of the particular era could not foster further growth of the same. Then the Memory-Resistor, i.e., Memristor is explored to correlate with the necessities of the FEFET, which like the negative-capacitance was relegated to the background on account of scientific limitations. These phenomena, which when dealt with at the microscopic level, help in understanding the causes for the variations of the threshold voltage of the FEFET. Hence, this paper delves into the various methodologies in-vogue to be explored for the mitigation of the threshold voltage alterations. These solutions could then lead to the development of large-scale high-performance devices for various applications ranging from biomedical signal processing to neuromorphic computing. Furthermore, it would also be interesting to note the behaviour of the device owing to the continuous drive to miniaturize the devices. Moreover, the effects which for now are apparently evaluated in 2 dimensions, could in the near future necessitate the validation using 3 dimensional equations.

Hardness Evaluation of Petroleum Pipelines coated with Developed Cu, Ni, Cr Metallic Paints

Authors- Danladi King Garba, Ojoye Ololade Mariam, Shuaibu Ochetengu Yakubu

Abstract-Corrosion is an unsightly occurrence whose appearance is nothing compared to the potentially devastating damage, economic loss, health and safety effects of ignored and unmanaged cases. To tackle corrosion of both underground and on-ground petroleum pipeline, metallic paints were developed and produced with a combination of alkyd gloss paints and highly corrosion resistant metal powders such as Copper, Nickel and Chromium. The produced metallic paints are tested and investigated to ascertain viability for application, optimized mechanical properties such as hardness. Vickers micro-indentation test was used for assessing coating hardness of all varying samples under HV0.5 load. This method of hardness measurement was chosen as it is a non-destructive method with a high level of accuracy, suitable for small samples and thin sections. This is a step towards minimizing and protecting petroleum pipelines against the recurring challenges of corrosion.

Design and Analysis of Bare Framed Building Being Fixed Base and Base Isolated Using Lead Rubber Bearing Under Different Soil Conditions

Authors- Assistant Professor T S Prashanth Hathwar, Lokesh S

Abstract-In this study, Response Spectrum Method for the design of seismically isolated bare framed building has been carried out by using Lead Rubber Bearings (LRB) with the influence of soil conditions. The objective of this project is to resist the building by providing LRB as base isolators. The major natural disaster is earthquake, many structures damage due to poor design against seismic actions. There are different ways of designing to resist structure from earthquake, in this project the concept used is LRB as base isolator and LRB is more effective and widely used as base isolation for buildings. Different soil conditions with base isolation is compared and discussed for G+14 bare framed building situated in zone IV to select the suitable soil type. Comparison of analysis results between fixed base and isolated base is done using ETABS v 18.1.0. Finally, comparison of analysis results such as base shear, maximum bending moment, storey shear, storey displacements, storey drifts and storey accelerations at various storey levels of building are presented.

Removal of Hydrogen Sulphide from Biogas Using Coconut Shell – Cow Bone Activated Carbon

Authors- Michael Eyitayo Opeyemi, Dr. Wunuken Carlos Solomon, Associate Professor Achara Nnorom

Abstract-This study evaluates the effectiveness of coconut shell-cow bone activated carbon in removing Hydrogen Sulphide (H2S) from biogas. The activated carbon samples, prepared using different weight-based mixing ratios (1:0, 0:1, 2:1, 1:2, 1:1), were tested for H2S adsorption performance. Raw biogas was generated from anaerobic digestion of poultry waste, and gas chromatography was used to analyze H2S concentrations in raw and treated samples. The raw biogas had an H2S concentration of 8.19%, while treated samples showed reduced concentrations of 5.64%, 7.09%, 6.61%, 7.04%, and 5.15% for the respective activated carbon samples. The results indicate that activated carbon derived from coconut shells and cow bones is effective for H2S removal, contributing to sustainable biogas purification technology. Future research should focus on further investigating the adsorption mechanisms and optimizing strategies for enhanced biogas purification.

Financial Planning and Inclusion in Rural India: An Analysis of Trends and Recommendations

Authors- Anand Vijay, Mr. Mohit vijay, Mr. parvesh K

Abstract-This journal article aims to explore the unique challenges and opportunities associated with financial planning in rural India. By examining the socio-economic landscape, financial literacy levels, and the availability of financial services in rural areas, this paper seeks to propose effective strategies to improve financial inclusion and economic stability among rural populations.

DOI: /10.61463/ijset.vol.12.issue4.201

Review of Dense Grade Bituminous Mixes with Natural Fiber Modified Coal Ash Incorporation

Authors- Scholar Gopal Singh, Assistant Professor Hariram Sahu

Abstract-Coal-fired thermal power plants in India generate significant fly ash and bottom ash, posing environmental hazards. This review explores repurposing these byproducts in bituminous paving materials, with bottom ash as fine aggregate, fly ash as mineral filler, and sisal fibers to enhance engineering properties. The methodologies adhere to Ministry of Road Transport and Highways (MORTH, 2013) specifications, focusing on dense graded bituminous macadam (DBM) with a nominal maximum aggregate size of 26.5 mm. Sisal fibers coated with slow-setting emulsion (SS1) improve the mix, showing optimal performance with VG30 bitumen. Key findings include a Marshall stability of 15 kN, optimal bitumen content of 5.57%, and optimal fiber content and length of 0.5% and 10 mm, respectively. Performance tests reveal enhanced moisture susceptibility, indirect tensile strength, and creep behavior. This sustainable approach offers a viable alternative to traditional materials, promoting resource-efficient and resilient infrastructure development.

DOI: /10.61463/ijset.vol.12.issue4.202

Experimental Study of Dense Grade Bituminous Mixes with Natural Fiber Modified Coal Ash Incorporation

Authors- Scholar Gopal Singh, Assistant Professor Hariram Sahu

Abstract-Coal-fired thermal power plants in India generate significant fly ash and bottom ash, posing environmental hazards. This review explores repurposing these byproducts in bituminous paving materials, with bottom ash as fine aggregate, fly ash as mineral filler, and sisal fibers to enhance engineering properties. The methodologies adhere to Ministry of Road Transport and Highways (MORTH, 2013) specifications, focusing on dense graded bituminous macadam (DBM) with a nominal maximum aggregate size of 26.5 mm. Sisal fibers coated with slow-setting emulsion (SS1) improve the mix, showing optimal performance with VG30 bitumen. Key findings include a Marshall stability of 15 kN, optimal bitumen content of 5.57%, and optimal fiber content and length of 0.5% and 10 mm, respectively. Performance tests reveal enhanced moisture susceptibility, indirect tensile strength, and creep behavior. This sustainable approach offers a viable alternative to traditional materials, promoting resource-efficient and resilient infrastructure development.

DOI: /10.61463/ijset.vol.12.issue4.203

Python-based Deepfake Detection: Ensuring Image Authenticity

Authors- Muhammed Shaan M, Vishnu V, Navaneeth Sudevan

Abstract-With the proliferation of deepfake technology posing significant threats to the authenticity of digital imagery, the need for robust detection methods has become paramount. This paper presents an innovative approach leveraging Python-based techniques for the detection of deepfake images. By harnessing the power of deep learning algorithms and computer vision methodologies, our system aims to discern the subtle artifacts and inconsistencies inherent in manipulated images. We discuss the implementation of various Python libraries and frameworks tailored for deepfake detection, emphasizing their effectiveness in identifying forged content across diverse datasets. Furthermore, we evaluate the performance of our approach through rigorous experimentation, demonstrating promising results in terms of accuracy, efficiency, and scalability. Our research contributes to the ongoing efforts in combating the proliferation of deceptive imagery and underscores the pivotal role of Python in advancing forensic techniques for image authenticity verification.

An Overview of Fast Ion Conductors

Authors- Suhail Iqbal Wani

Abstract-Fast ion conductors are considered to have great potential in the field of science and technology to create avenues in energy storage and conversion process. However, it is not yet known why only a few materials can supply remarkably higher ionic conductivity than typical solids or how one can design super-ionic conductors following simple procedures. Analysing the past studies, here I have put emphasis on the origin, classification, preparation, and applications of super-ionic conductors. The studies show that fast diffusion in fast ion conductors does not occur through isolated ion hopping as is typical in solids, but instead proceeds through concerted migrations of multiple ions with low energy barriers. Furthermore, I clarify that the low energy barriers of the concerted ionic diffusion are a result of exceptional mobile ion configurations and firm mobile ion interactions in fast ion conductors. This review provides best possible route to understand the concept and mechanism of super-ionic conductors which can pave way for universal strategy to design solid materials into fast ion conductors.

DOI: /10.61463/ijset.vol.12.issue4.204

Formulation of Herbal Pest Repellent

Authors- Nihar Ranjan, Dr. K. Arivoli, Associate Professor Dr. S. Aghizion Inbakani

Abstract-Due to the invasive-destructive nature, morphological and biological variations in insects, there is a need for developing an effective control strategy. In the present study an attempt was made to develop a suitable formulation of an herbal pesticide towards effective biological control of scale insects using herbal preparations. The prepared formulations were subjected to evaluation tests at varying concentrations on the insect pest. Insects treated with plant extract exhibited highest rate of mortality. Results indicate that herbal preparation can effectively be used for the management of scale insects as an eco-friendly approach.

Robotic Arm for Object Sorting Based on Colour and Shape

Authors- Joyal Francis, K A Harikrishnan, K R Narayan, Rahul Prasad, Sharika T R

Abstract-This paper shows how we made a new robot arm that can sort things by their color and shape. The arm can handle three colors and three shapes at once using smart ways to see and move things around. It works fast and gets things right, which is great for factories. The robot arm uses special tricks to spot colors and shapes, so it can sort stuff without any problems. It also uses smart computer programs to learn about different objects and places, so it can do a good job no matter what. We made sure it’s easy to use too. People running the machine can tell it what to sort and keep an eye on how it’s doing. One of the best things about this robot arm is that it can work with lots of different colors and shapes so it fits in well with other machines in a factory. We built it using new computer languages like Python and C++, so it can work on all kinds of systems and is easy to set up in different factories. We also followed all the rules for making good software, so it works really well and doesn’t break down in factories.

Finite Element Analysis of Reinforced Concrete Under Corrosion Using Different Diameter of Steel Rod in Serviceability Conditions Based on IS 456 Guidelines

Authors- Sonu Chouhan, Professor Sachin Sironiya

Abstract-Reinforcement corrosion is a prevalent factor contributing to the degradation of cement in reinforced concrete structures. Various researchers have conducted studies on the corrosion mechanisms involved and the subsequent impact on the structural behavior of deteriorated reinforced concrete elements. However, the existing knowledge is predominantly derived from experimental examinations of artificially corroded specimens, and the effects of natural corrosion on structural behavior may differ. This paper seeks to enhance the numerical comprehension of the structural consequences arising from natural corrosion deterioration, specifically emphasizing the residual anchorage capacity between deformed bars and concrete. Additionally, the study aims to explore potential correlations between visual inspection data and structural damage.

Elevating Exam Fairness: Advanced Proctoring and Monitoring in a Secure Offline Environment

Authors- Jonathan Jobby, Paul Thomas, Pranav Asokan, Professor Shyama R

Abstract-Offline Computer-Based Tests (CBTs) present unique challenges in ensuring test integrity and security within an offline framework. This paper presents the design and implementation of a novel Offline CBT Controller, a software solution aimed at enhancing the security of offline exams by seamlessly integrating various security measures. The system combines USB blocking, internet restrictions, and user activity monitoring to prevent malpractices during offline exams, thereby ensuring a secure testing environment. The project prioritizes user experience by providing a user-friendly interface for administrators to configure and manage security settings efficiently. The Offline CBT Controller is designed to address the specific security requirements of offline CBT environments, such as those found in practical computer lab exams. By implementing robust security measures, including USB blocking and internet restrictions, the system prevents unauthorized access to external resources during exams, thereby minimizing the risk of cheating. Additionally, user activity monitoring allows administrators to track and log system activities, providing a comprehensive activity history for auditing purposes. Key features of the Offline CBT Controller include its compatibility with various operating systems and its ability to seamlessly integrate with existing exam infrastructure. The system is developed using Java programming language, making it platform-independent and easy to deploy across different environments. Furthermore, the project emphasizes the importance of adherence to software development best practices to ensure the reliability and effectiveness of the solution.

DOI: /10.61463/ijset.vol.12.issue4.205

Investigating the Nexus between French and English Writing Skills among Moroccan EFL Learners: A Correlational Study

Authors- Imad Hamdanat, Lamiae Azzouzi, Insaf Khoudri

Abstract-This empirical study investigates the potential association between writing proficiency in French and English among Moroccan undergraduate EFL learners. Employing a correlational design, the study examined the relationship between these writing skills through standardized tests and statistical analyses (Pearson’s correlation, Kendall’s tau-b, and regression). The results revealed no statistically significant correlation, suggesting that French writing proficiency does not have a significant explanatory power for English writing skills. These findings contribute to the understanding of cross-linguistic transfer in EFL writing, highlighting the need to consider factors beyond structural similarity between languages. While limitations include sample size and design, the study underscores the importance of cross-linguistic transfer in EFL pedagogy. Future research with more diverse samples and employing longitudinal or interventionist approaches can provide a more comprehensive understanding of how prior language learning shapes EFL writing development.

DOI: /10.61463/ijset.vol.12.issue4.206

Optimization Techniques for Hybrid AC-DC Grid: A Review

Authors- Research Scholar M.Vijay Kumar

Abstract-With the advancement of Distributed Energy Re- sources (DERs) Hybrid AC/DC grid have got the importance due to its simple configuration where AC sub grids, DC sub grids and storage systems are grouped into several clusters. Component sizing and cost minimization, power quality, power management and load shedding are important objectives in control and management of Hybrid AC/DC grid. Hybrid AC/DC grid operates in two modes grid connected and off grid (Islanded mode), disturbances occur during transition from one mode to other which are to be addressed. Optimization techniques are applied in several fields to get the best or most favorable solutions, this paper reviews the basic configurations of Hybrid AC/DC grid, modes of operation and control techniques, optimization techniques with their objectives that are applied to Hybrid AC/DC grid.

DOI: /10.61463/ijset.vol.12.issue4.207

Langchain IQ: Intelligent Content and Query Processing

Authors- Assistant Professor Sunil Ghane, Roshan Sawant, Ganesh Supe, Chinmay Pichad

Abstract-The purpose of this research is to introduce and evaluate a comprehensive framework called langchain(component of Large Language Model), designed to optimize data analysis and visualization processes across various business domains. The framework integrates advanced computational techniques with user-friendly interfaces to meet the growing demand for efficient information processing tools in research and industry settings. Design/Methodology/Approach: The framework consists of three primary components: PDF answering, CSV analytics, and data visualization using the LIDA library. Integration of advanced technologies such as the Mistral 7B model for language processing, Faiss for similarity search, and the LIDA library for data visualization. Detailed implementation steps include content processing, embedding using OpenAI embeddings, storage and retrieval using Faiss, and query handling using Mistral 7B. This involves breaking down PDF and CSV content into chunks, embedding them, and utilizing advanced algorithms for efficient data retrieval and visualization. Findings/Result: The fine-tuned Mistral 7B model significantly enhances data extraction speed compared to traditional models like Llama. Users can effectively query and extract specific information from PDFs and CSVs using natural language, facilitated by advanced AI models. The LIDA library automates the generation of insightful visualizations from processed data, enhancing data interpretation and decision-making. Originality/Value: Introducing langchain as a versatile framework that addresses the complexities of data analysis and visualization and it’s use in business analysis. Paper Type: Technical Research.

Thermal Analysis of TES System Using ANSYS

Authors- Research Scholar Dhanraj Digodiya, Assistant Professor Khemraj Beragi

Abstract-The current research aims to evaluate the fluid flow and thermal characteristics of a thermal energy storage (TES) system that employs phase change materials (PCMs). This study utilizes computational fluid dynamics (CFD) tools to achieve this goal. A three-dimensional model of the TES storage unit is meticulously developed and analyzed using the ANSYS simulation package. Through comprehensive CFD analysis, detailed heat flux and temperature distribution plots are generated. These plots provide critical insights into the thermal behavior and efficiency of the TES system. By examining these plots, the study effectively evaluates the heat transfer performance and fluid dynamics within the storage unit. This evaluation is essential for optimizing the design and functionality of TES systems, contributing to advancements in energy storage technologies and improving their practical applications in various fields.

Review on Impact of Led Lights on Seed Germination and Seedling Growth

Authors- Rahul Belgaonkar, Shweta Patil

Abstract-TThis review focuses on the role of Light-Emitting Diodes (LEDs) in enhancing seed germination and early plant growth. It investigates the effects of different LED wavelengths on various plant species, particularly blue, red, and far-red lights. This review compares these LEDs with traditional lighting methods, such as fluorescent and UV light, and discusses the specific benefits of LEDs in supporting plant development. These findings suggest that LED technology has a significant potential to improve agricultural productivity, and further research is recommended to refine these techniques and explore broader horticultural applications.

DOI: /10.61463/ijset.vol.12.issue4.208

Mathematical Modelling of Dried Oyster Mushroom (Pleurotus flabellatus)

Authors- Suresh Chandra, Shobhi Choudhary, Alka Singh, Ruchi Verma

Abstract-This work was conducted to assess the drying kinetics of oyster mushroom (Pleurotus flabellatus). Mushrooms were dried in sun drying, poly house drying, tray drying and vacuum drying. Oyster mushrooms were subjected to four pretreatments prior to drying. Drying took place in the falling rate period, and the drying behaviour was adequately described by the Lewis, Page, Peleg and Henderson & Pabis’s equation. The experimental drying data were fitted to different theoretical models to predict the drying kinetics. Results indicated that the Pabis and Henderson model offered the best fit for experimental drying data for sun drying (average R2 = 0.97) and Lewis model for tray drying (average R2 = 0.9498).

DOI: /10.61463/ijset.vol.12.issue4.209

Design of a DC Servomotor Output-Feedback Controller to Manipulate a Robotic Arm

Authors- Tat Dat Dong, Anh Tuan Hoang, Van Huong Ngo, Van Quyen Dinh, Van Huy Khuat

Abstract-This report presents a detailed analysis on the design of an output feedback controller for a DC servomotor to manipulate the twist JT6 motion of the Kawasaki RS080N-B robotic arm. The system consists of four parts: the electrical circuit, the Servomotor, the gearbox, and the robot arm. A mathematical model is derived for the system with the Pittman N2314 24V DC motor to control the robotic arm motion via a gearbox. The design process of a closed-loop output-feedback controller for the given system is analysed, followed by numerical validations. The controller had successfully met all the criteria related to overshoot, rise time, settling time, as well as managing uncertainties and disturbances.

Personal Health Care System

Authors- Muhammed Nihal, K Mahesh, Shyam K.S, Professor T.Sobha

Abstract-Healthcare management systems have become increasingly crucial in providing personalized and efficient health services to individuals. In this paper, we present a novel HealthCare Management System (HCMS) that integrates various cutting-edge technologies to offer a comprehensive solution for personalized healthcare. The HCMS encompasses features such as stroke prediction, chatbot assistance, diet prediction, health awareness games, workout recommendation, hospital booking, location-based services, and 247 support, making it a versatile tool for both users and healthcare providers. Leveraging machine learning algorithms, the stroke prediction model accurately assesses an individual’s risk of stroke, enabling early intervention and prevention strategies. The chatbot offers instant assistance and guidance on health-related queries, enhancing accessibility to healthcare information. Additionally, the diet prediction module provides tailored dietary recommendations based on individual preferences and requirements. Health awareness games and workout recommendations promote healthy lifestyles and physical well-being. The hospital booking feature streamlines the process of scheduling appointments and accessing medical services, while location-based services ensure users can easily locate healthcare facilities based on ratings and proximity. Finally, 247 support offers continuous assistance and ensures prompt resolution of queries or concerns. The HCMS aims to revolutionize healthcare delivery by providing a unified platform for individuals to manage their health effectively while promoting preventive care and overall well-being.

Study of Oxidative Stability of Rice Bran Oil & Sunflower Oil during Frying

Authors- Aishwarya Sarangi, Jyotsna Mayee Dash, Pratibha Rani Deep, Assistant Professor Ruby Pandey, Assistant Professor Shantanu Bhattacharyya

Abstract-It is well known that constantly use of oil for frying leads to quality deterioration resulting from undesirable chemical changes taking place in oil which impose harmful health effects. Therefore, in this study an evaluation was carried out to check the quality deterioration of rice bran oil (RBO) and Sunflower oil (SFO) during frying. The study was aimed to determine the free fatty acid (FFA) content, peroxide value and color changes during repeated frying cycles in RBO and SFO. The measurement and analysis were performed till 6th frying cycles where one frying cycle lasts for 30minutes during which potato chips were continuously fried in oil heated to frying temperature. The findings of the study revealed that FFA and acid value in fresh and used oil (6th cycle) increased from 0.6- 1 and 0.66-1.45 in Rice bran oil and 0.62-0.88 in Sunflower oil respectively. The increase in acidity was almost found to be double after repeated frying. However, it can still be considered suitable for consumption as it was within the critical limit of 2-3% The peroxide value (PV) which is the indicator of oxidative rancidity also increased significantly with an increased in the frying cycle number. The PV was found to increase from 4.83meq/kg and 1.49meq/kg for edible grade oil and sunflower seed oil. The oil’s color darkened over time, as evidenced by measurements of color parameters in Hunter “Lab” space, with a ∆E change from 10.69 to 32.17 between the 1st and 6th frying cycle in SFO and from 6.26- 35.6 in RBO respectively.

DOI: /10.61463/ijset.vol.12.issue4.210

Urban Road Safety and Sustainable Transportation Policy through the Hierarchy of Hazard Controls

Authors- Naveen Singh Rathore, Assistant Professor Mr. Vinay Deulkar

Abstract-Governments globally have endorsed Vision Zero, declaring that no person should be killed or permanently injured on public roads. Concurrently, the wider social, public health, and environmental implications of urban structure and transport choices have gained intense policy attention, as cities aim to transition toward sustainable accessibility. This is especially the case as research reveals a range of counter-intuitive road safety dynamics; many narrow approaches to road safety management appear to trigger adverse risk compensation and negative externality effects, potentially running counter to broader sustainability goals. Recognizing the urgent need to integrate road safety with broader urban sustainability measures, this synopsis presents a review of road safety literature using the established Hazard Control Hierarchy. In doing so, we identify and categorize opportunities to more effectively combine Vision Zero with broader sustainable accessibility policy objectives. We synthesize the literature against the Hazard Control Hierarchy to devise a framework to more effectively integrate the work of professional disciplines which shape the safety and sustainability of the urban built environment.

Diabetic Retinopathy Detection: A Survey

Authors- Amrutha Muralidharan Nair, Alvin C Alias, Jerrit Jaison, Kshama Prakash Kamath, Nihal Jagadeesh

Abstract-Diabetic retinopathy (DR) is a significant cause of global visual impairment, highlighting the need for advanced detection techniques. This survey paper thoroughly examines the application of Deep Learning (DL) algorithms in detecting DR, emphasizing their efficiency, accuracy, and potential for early intervention. It is designed to assist individuals affected by or at risk of visual impairments, aiming to enhance the detection process with cutting-edge technologies. By reviewing various methodologies—including deep learning, and artificial intelligence, the paper outlines the strengths and limitations of each approach. The survey investigates emerging trends, challenges, and opportunities in DR detection, offering valuable insights for researchers, practitioners, and policymakers. It explores advancements in image processing techniques, such as fundus image enhancement and noise reduction, and examines the role of convolutional neural networks (CNNs) in feature extraction and classification. Additionally, the paper discusses the integration of the Internet of Things (IoT) with DL techniques, highlighting the potential for real-time data acquisition and analysis in telemedicine. The paper analyzes key contributions from recent research, including systems that utilize data augmentation to improve detection accuracy, employ ensemble learning techniques to enhance predictive performance, and incorporate novel feature extraction methods to identify DR lesions. It also addresses the limitations of current systems, such as the dependence on large annotated datasets and the difficulties in achieving high sensitivity and specificity. By synthesizing key findings and styles, this survey aims to give a panoramic understanding of the current state of diabetic retinopathy detection and foster future advancements. The paper draw the inference by emphasizing the necessity for ongoing research and technical development to improve the precision, effectiveness, and accessibility of DR screening and diagnostic tools, ultimately contributing to better patient outcomes and reducing the global burden of blindness caused by diabetic retinopathy.

Multi-Cancer Detection and Classification Using Machine Learning

Authors- Theophilus Addo, Nathaniel Ofori, Joseph Boateng Owusu-Afari, Gifty Bondzie

Abstract-Cancer is a very deadly disease, accounting for millions of deaths around the globe, but the process of diagnosing it is fraught with misclassifications, delays and false positives. According to research, early detection and treatment of cancer greatly increases the chances of successful treatment and patient survival. A report from Johns Hopkins Hospital indicates that as many as one in every five cancer cases is wrongly classified, which suggests the need to create a system that accurately detects and classifies cancer. This project work focused on the development of a robust system, including a web and mobile application for the detection and classification of cancer using medical image analysis. Our work utilizes the CNN model for the development of the machine learning model. The CNN model is a layered architecture that extracts relevant high-level features from images for classification. The system was developed to detect and classify eight types of cancers, namely Leukemia, Brain Cancer, Breast Cancer, Cervical Cancer, Kidney Cancer, Lung and Colon Cancer, Lymphoma, and Oral Cancer. The Multi Cancer Image Dataset from Kaggle was utilized to train and test the models. The dataset contained eight types of cancers grouped into different classes. Each class contained 2000 images for training and 500 images for testing. Pre-processing techniques were applied to normalize and standardize the images to ensure the correct format and resolution. The CNN architecture was designed and trained on the dataset, leveraging its ability to automatically extract relevant features from the images. Nine CNN models were trained, with eight responsible for classifying each cancer type while the other model detects the cancer type. The system was designed to perform two levels of classification for each image. The first level is the detection of the type of cancer, and the second level is the classification of the cancer type. The trained models were assessed using evaluation metrics such as accuracy, precision and recall. The results demonstrated the effectiveness of the developed system in accurately detecting and classifying the eight types of cancer and the potential to alleviate the errors faced with the manual examination of cancer diagnosis. All the models obtained accuracies above 90%. The CNN models achieved an impressive overall accuracy, outperforming existing methods. The developed system can direct healthcare professionals to make accurate and timely decisions regarding cancer diagnosis and treatment strategies.

Laboratory Evaluation on Geotextile Usage in Asphalt Pavement

Authors- Scholar Dharavath Raghupathi, Assistant Professor Kalvala Abhiram

Abstract-This paper reports the rutting opposition assessment of geosynthetics built up black-top asphalt through lab wheel following tests. The tests estimated the surface trench profundity and base deformity of the asphalt when stacked by a moving wheel reproducing a truck wheel load. Groove profundities were estimated as a component of the quantity of stacking cycles. The geogrid and the geotextile reinforcement’s capacity to spread the load out over a larger area were monitored and evaluated. The consequences of the built up examples were contrasted with unreinforced examples with evaluate the benefits of utilizing geosynthetics in expanding the trench obstruction of black-top asphalt.

Cherub- The First Responder UAS Wireless Data Gatherer (UAS 6.0)

Authors- Vivian Gomes, Aadhya Krishna

Abstract-The First Responder UAS Wireless Data Gatherer Challenge seeks to enhance public safety capabilities through advanced technologies in uncrewed aerial systems (UAS). This paper presents an innovative UAS solution designed to provide real- time situational awareness and data gathering in environments lacking fixed communications infrastructure. The system leverages artificial intelligence, radio communications, and Internet of Things technologies to improve operational efficiency, safety, and data management for first responders. The UAS platform features a durable frame, high-capacity batteries, integrated solar panels, and multi-spectral cameras, LiDAR, and environmental sensors for comprehensive data collection. Advanced radio communication modules support mesh networking and mobile ad-hoc network configurations. AI-driven autonomous navigation and machine learning models enable real-time data processing, threat detection, and situational awareness. The communication network features mesh networking protocols, allowing UAS units to form resilient and adaptive communication paths. Each UAS acts as a relay node, extending communication range and ensuring data transmission. High-bandwidth radio modules facilitate real-time data transfer, while ground stations collect data and relay it to the central command center. The data processing flow begins with real-time data collection, followed by edge computing for immediate insights and cloud integration for detailed analysis and long- term storage. The system is designed to operate in various environmental conditions, with protective measures such as superhydrophobic coatings, fire- resistant materials, and UV-resistant coatings. The UAS addresses disaster response, urban search and rescue, and environmental monitoring scenarios. It aligns with public safety needs by providing real-time surveying, communication, and data analysis. The proposal demonstrates an understanding of the benefits and risks of implementing the UAS, incorporating robust risk management measures and integrates advanced AI, robust communication technologies, and comprehensive cybersecurity measures, offering an effective solution for first responder data collection, analysis, and reporting, exceeding the expectations of the challenge and providing tools to save lives and improve operational efficiency in challenging environments.

DOI: /10.61463/ijset.vol.12.issue4.211

Improving Health through HaLite Salt Commercialization in Nigeria

Authors- Shukurat M. Bello, Usman Kabir Murtala, Bashir Muhammad, Hafiz Musa Usman, Asmau Suraj Murtala, Nasir jibril Muaz, Abba Sani Aliyu

Abstract-This conceptual paper explores the development of a business model for the production of lite salt, a low-sodium alternative to traditional table salt. Lite salt offers health-conscious consumers a way to reduce their sodium intake while still enjoying the taste of salt. The paper outlines key components of the business model, including market analysis, production process and distribution channels. By providing insights into the viability and potential challenges of a lite salt production business, this paper aims to inspire entrepreneurs and stakeholders interested in entering the health food industry. There is a growing demand for low-sodium alternatives to regular salt, driven by health awareness, government initiatives, and dietary trends. The global market for reduced-sodium salt substitutes is projected to reach $2.3 billion by 2027,with a CAGR of 5.7%.

Chat GPT and Its Integration with the Academic Libraries Ecosystem

Authors- Chitransh Dixit, Kanchan Lata Dixit, Chandra Kumar Dixit, Praveen Kumar Pandey, Deepali Chauhan, Shavej Ali Siddiqu

Abstract-In the ever-changing landscape of knowledge repositories, this chapter addresses the symbiotic relationship between ChatGPT, an advanced artificial intelligence language model, and the traditional institution of the library. The chapter discusses about ChatGPT’s incorporation with the library ecosystem, where it emerges as a dynamic force altering conventional ideas of information access. ChatGPT takes front stage in the virtual symposia within the library, providing a conversational interface that changes user interaction. Beyond the limitations of traditional search methods, ChatGPT transforms into an interactive guide, traversing the library’s vast archives of both digital and physical materials. The chapter looks into the specific ways in which this technology improves information retrieval, collaborative research, and the overall library experience. While applauding the benefits of this technological integration, the chapter also discusses ethical questions, privacy concerns, and the possible influence on human connection within the library. The balance between convenience and ethical usage becomes a major topic, mirroring the wider problems that libraries are facing as they embrace artificial intelligence. Finally, the chapter contends that ChatGPT’s symposium in the library is a transformational story rather than a technological convergence. It welcomes a new era in which artificial intelligence enhances the user experience, transforming libraries into dynamic hubs for collaborative learning.

DOI: /10.61463/ijset.vol.12.issue4.212

Navigating the Digital Literacy Challenges and Opportunities

Authors- Chitransh Dixit, Kanchan lata Dixit, Chandra Kumar Dixit, Praveen Kumar Pandey, Deepali Chauhan, Shavej Ali Siddiqui

Abstract-Digital literacy is to the ability to use, understand, and navigate digital technology and information effectively. It encompasses various skills and competencies necessary to interact with the digital world, including the use of computers, smartphones, the internet, and digital devices. The digital age has ushered in a new era of profound transformation, where the digital landscape offers both formidable challenges and remarkable opportunities. This chapter delves into the multifaceted world of the digital age, exploring the hurdles it poses and the myriad possibilities it offers.

DOI: /10.61463/ijset.vol.12.issue4.213

E-Resources in Academic Libraries

Authors- Chitransh Dixit, Kanchan lata Dixit, Chandra Kumar Dixit, Praveen Kumar Pandey, Deepali Chauhan, Shavej Ali Siddiqui

Abstract-The purpose of this paper is to know the types, characteristics, importance, problems, usage of e-resources and also know the comparisons with print resources. There are many types of electronic resources, like e-books, e-journals, e-magazines, e-newspapers, e- references, e-theses, and dissertations, which are stored in a computer as a electronic form, which is called database. Nowadays, e-resources are becoming more important for every library across the globe due to their recent updates and ability to be accessed from anywhere. Therefore, this topic selected to study because such resources are valuable for research and development activities.

DOI: /10.61463/ijset.vol.12.issue4.214

Utilization of Open Source Software in Academic Libraries

Authors- Chitransh Dixit, Kanchan lata Dixit, Chandra Kumar Dixit, Praveen Kumar Pandey, Deepali Chauhan, Shavej Ali Siddiqui

Abstract-Utilization of Open Source Software Packages in Libraries Over the course of the last several years, open source software (OSS), which may be obtained without difficulty, has amassed a large amount of popularity and attention. This is an attempt to describe the idea of open source software (OSS) in general and describes essential OSS for integrated library systems (ILS), digital library systems (DLS), and content management systems (CMS) in particular. This article demonstrates the open-source software (OSS) that library professionals can employ in their libraries to deliver cutting-edge services to their patrons at absolutely no additional expense.

DOI: /10.61463/ijset.vol.12.issue4.215

RFID Solution for Libraries and Management System

Authors- Chitransh Dixit, Kanchan lata Dixit, Chandra Kumar Dixit, Praveen Kumar Pandey, Deepali Chauhan, Shavej Ali Siddiqui

Abstract-This chapter explores the transformative impact of Radio Frequency Identification (RFID) technology on library operations and services. It delves into how RFID enhances efficiency, speed, and security in libraries, leading to improved inventory management and user satisfaction. The chapter discusses the role of RFID in streamlining transactions, tracking misplaced documents, and enabling automated material handling. It also highlights the potential of hybrid technology and the advent of book ATMs for 24/7 access. The global scenario of RFID implementation in libraries is examined with case studies from institutions like IIT Delhi, SIRD, and IGCAR. The chapter also addresses the challenges libraries may face during RFID implementation, such as budget constraints, privacy concerns, system robustness, staff training, and end-user confusion. This comprehensive analysis provides valuable insights for libraries considering the adoption of RFID technology.

DOI: /10.61463/ijset.vol.12.issue4.216

Research on Aerodynamic Characteristics of Iak 52 Aircraft Propellers According to the Rotation Characteristic

Authors- Trong Son Phan, Dang Hoang Long Phan, The Son Nguyen, Van Quyen Dinh

Abstract-This paper presents an investigation of computational model to calculate propeller characteristics, creating the algorithms and a program, thereby assessing the impact of certain factors on the propeller characteristics. Introduces the results the dependence of the propeller characteristics IAK 52 aircraft (thrust coefficient, thrust, and useful power on the propeller) on the rotation speed. The results accurately reflect the physics of the nonstop flow interacting with propeller.

Integrated College Management System for Timetables and Staff Information

Authors- Krishnapreethi J, Meera Roy, Rohan Joseph, Professor Eldhose P Sim

Abstract-Crafting timetables for universities is a labor-intensive endeavor, demanding considerable time and human resources each semester. With the complexity inherent in managing various branches, academic years, and student batches, the manual creation of timetables can stretch over six months, placing a significant burden on administrative staff. Moreover, the need for frequent adjustments, particularly in response to faculty absences or scheduling conflicts, further complicates the process, often leading to inefficiencies and increased stress for schedulers. Recognizing these challenges, this paper presents an innovative algorithmic solution aimed at revolutionizing timetable generation in academic institutions. By shifting towards a software-based approach, this method harnesses the computational power of computers to streamline data processing and enhance accuracy, providing substantial time and stress relief for manual schedulers. The proposed algorithmic solution offers a transformative approach to timetable generation, leveraging adaptable algorithms to meet the diverse scheduling requirements of different universities. By embracing customization, the software can be tailored to accommodate varying academic structures and constraints while maintaining a standardized codebase for efficient optimization. This adaptability not only enhances the flexibility and scalability of the solution but also ensures compatibility with evolving university needs. Ultimately, by embracing this software-driven approach, universities can streamline the timetable generation process, improve resource allocation, and enhance overall operational efficiency.

Autonomous Braking System for Automobile Powered by Artificial Intelligence and Reinforcement Learning

Authors- Sukhwinder Sharma, P Hrithika Kundar, Saksha K Bangera, Sandesh R Bhat, Shrinit R Poojary

Abstract-The rising number of accidents and injuries on the roads has created a pressing need for systems that can provide safety and protection to passengers while ensuring high performance in adverse conditions. Traditional braking systems may not always respond in time to prevent collisions, particularly in adverse conditions or emergencies. These systems rely on the driver to apply the brakes manually, which can result in delayed response times or even complete failure to apply the brakes in time. Additionally, these systems do not take into account factors such as road conditions, vehicle speed, and driver reaction time. To overcome these limitations and meet the needs, the Autonomous Braking System has been introduced in commercial vehicles, providing rapid brake response according to the driver’s need and safety. This system employs an intelligent control strategy that uses image processing technology based on object detection with the help of haarcascading object detection technique. Computer vision, a crucial component of this system, allows for the detection of path which is being followed by vehicle using Canny’s lane detection technique, obstacles and objects in the vehicle’s path. This information is then used to make decisions about when and how to apply the brakes, ensuring quick and safe stops. Reinforcement learning is also a key element of the system, allowing it to learn from its experiences and make better decisions over time. This involves providing feedback on the system’s performance and using it to adjust its behavior and improve its performance over a period of time. The haarcascading technique here recognizes captured objects as potential obstacles, feeding this information into the algorithm to take appropriate decisions. Overall, the Intelligent Braking System promises to significantly improve safety and performance in commercial vehicles.

Plant Features Identification and Disease Recognition System

Authors- Joseph Shal, Samson Thomas, Sankar Mohan V, Professor Joseph George

Abstract-In recent times, the agricultural industry has experienced a surge in technological advancements aimed at improving productivity and sustainability. One notable innovation in this regard is the creation of applications for detecting plant diseases, offering farmers and agronomists a promising solution. This abstract introduces a pioneering plant disease detection application poised to revolutionize agriculture by providing rapid, precise, and accessible identification of crop diseases. The proposed application utilizes artificial intelligence (AI) and machine learning algorithms to analyze images of diseased plants taken with smartphone cameras. Upon image upload, the application employs advanced image processing techniques to recognize symptoms indicative of various plant diseases. Drawing from a comprehensive database of known plant diseases and their symptoms, the application promptly delivers users a diagnosis along with recommended treatment and management strategies. Key attributes of the application include real-time disease detection, offline functionality, and user-friendly interfaces. Catering to both inexperienced farmers and seasoned agronomists. Furthermore, the application encourages community involvement by allowing users to share their experiences, insights, and solutions for combating plant diseases. The significance of this application extends beyond individual farmers as it has the potential to revolutionize agricultural practices globally. By enabling early detection and swift management of plant diseases, the application can mitigate crop losses, reduce dependence on chemical interventions, and promote sustainable farming practices. Additionally, the application serves as an invaluable educational resource, empowering farmers with the knowledge and tools to protect their crops against diseases. In summary, the development of a plant disease detection application signifies a paradigm shift in agriculture, merging state-of-the-art technology with the enduring challenge of pest and disease control. By harnessing the capabilities of AI and mobile technology, this application holds tremendous promise for improving crop health, enhancing food security, and fostering a more resilient agricultural ecosystem.

Auto Dimming Headlamps for Cars

Authors- Jithi P V, Melani A L, Jobin Jose, Sebin George

Abstract-This abstract presents a revolutionary deep learning-enabled adaptive headlamp system designed to enhance safety and comfort for drivers and pedestrians. Leveraging advanced sensors and neural networks, the system dynamically adjusts headlamp intensity, focus, and direction based on ambient light, oncoming vehicles, road curvature, and vehicle speed. Key features include automatic dimming for oncoming vehicles, speed-sensitive brightness adjustment, and customizable settings for personalized preferences. Seamlessly integrated with existing vehicle electronics, this system optimizes energy usage while maximizing performance. In conclusion, this innovative technology represents a significant advancement in automotive safety, offering improved visibility, reduced glare, and a more enjoyable driving experience.

Implementation and Parameters Analysis of High Throughput Cryptographic Modified Secure Hash Algorithm-III

Authors- Scholar Birendra Prasad Sah, Professor Dr.Bharti Chourasia

Abstract-With certain characteristics that make it suitable for use in cryptography, a cryptographic hash work is a unique kind of hash work. A hash is a bit string with a settled size that is created by a numerical calculation that is meant to be a constrained capacity—that is, a capacity that is impractical to change. Secure hash algorithms are a type of cryptographic function that is used to protect data. It functions by using a hash function, which is an algorithm made up of bitwise operations, modular additions, and compression functions, to change the data. The implementation of secure hash algorithm-III for password security is presented in this paper. Verilog code and the Xilinx ISE 14.7 program are used for simulation. The suggested SHA-3 provides better area and delay than earlier attacks, according to the results.

Analysis of Composite Beams Using Ansys

Authors- Research Scholar Mohd. Anas Ansaria, Associate Professor Mohd. Anas

Abstract-This paper employs ANSYS, a finite element analysis (FEA) software, to explore the structural analysis of composite beams. These beams typically comprise carbon and glass fiber mats embedded in a polyester epoxy resin matrix, delivering superior mechanical properties such as high strength-to-weight ratios, stiffness, and durability. This makes them highly suitable for diverse engineering applications, including aerospace, automotive, and civil engineering. The research focuses on investigating stress distribution, strain behavior, and potential failure points under various loading conditions. Methodologically, it involves defining material properties, creating geometric models, specifying composite layups, meshing, applying boundary conditions and loads, conducting simulations, and post-processing results to ensure accuracy and reliability. ANSYS simulations demonstrate that composite beams exhibit exceptional strength-to-weight ratios, essential for applications requiring robust yet lightweight structural components. The study examines three beams: Beam 1 (carbon and glass fiber mat), Beam 2 (with wood ash filler), and Beam 3 (with wood dust filler). Beam 1 displayed the highest compressive load capacity at 81.67 kN, followed by Beam 2 at 78.75 kN, and Beam 3 at 75.83 kN. Stress-strain relationships indicated linear elastic behavior up to the yield point, with slight nonlinearity approaching ultimate strength. Deformation patterns confirmed the materials’ anisotropic nature, showcasing their ability to endure significant loads with minimal deformation. This study validates ANSYS as an effective tool for analyzing composite beam performance, paving the way for further research and optimization of composite materials in engineering applications.

Thermal Analysis of Composite Pipes

Authors- Research Scholar Farooq Omar, Associate Professor Mohd. Anas

Abstract-This dissertation investigates the thermal performance and structural integrity of composite pipes under varying thermal conditions. Utilizing both experimental methods and ANSYS simulation software, the study evaluates the influence of different composite materials, including carbon fiber, glass fiber, and polyester epoxy resin, on thermal behavior. The inclusion of wood ash and wood dust as filler materials is also examined for its effects on thermal conductivity and mechanical properties. The findings demonstrate that while the inclusion of novel fillers like wood ash can enhance thermal stability, the mechanical properties of the composites need to be carefully considered for specific applications. The use of advanced simulation tools like ANSYS has been validated, ensuring that theoretical predictions closely match experimental results, thus offering a reliable approach for future research and development in composite materials. Background or Challenges: Composite materials, known for their high strength-to-weight ratio, corrosion resistance, and thermal stability, are essential in industries like aerospace, automotive, and energy, where effective temperature management is critical. Understanding the thermal behavior of composite pipes is pivotal for optimizing their design, improving thermal efficiency, and ensuring long-term durability. Methods: The methodology involves fabricating composite pipes with distinct configurations and conducting tensile tests at room temperature, 50°C, and 75°C to measure tensile strength and modulus of elasticity. The study also employs ANSYS simulation software to model and analyze the thermal behavior of the composite pipes. Findings: The results indicate that the tensile strength and modulus of elasticity of composite pipes decrease with increasing temperature. Carbon fiber composites show superior mechanical properties and thermal stability compared to glass fiber composites. The addition of wood ash and wood dust as filler materials enhances thermal stability but slightly reduces mechanical strength. Both experimental and ANSYS simulation results consistently show that the tensile strength and modulus of elasticity of composite pipes decrease as the temperature increases. Conclusion: The study provides valuable insights into the thermal behavior of composite pipes, crucial for their application in industries requiring robust thermal management and structural integrity. The findings highlight the importance of material selection and the potential benefits of incorporating novel fillers like wood ash in enhancing thermal stability. The validation of theoretical predictions against experimental results confirms the reliability of ANSYS for predicting the thermal behavior of composite materials.

Significance of Digital Banking Adoption in Rajasthan: A Systematic Literature Review

Authors- Abhilasha Gupta, Professor Harsh Purohit

Abstract-Through conducting a systematic literature review, this paper aims to uncover the role of digital banking adoptions in Rajasthan, India. The paper looks at the current literature to propose the factors to adopt and to resist, the advantages and disadvantages of digital banking in the region of Rajasthan. Some of the common factors cover technological innovation, access to finance, customers perception, policies and directives, and social and economic effects. It can be concluded that the acquisition of innovative technology, the government’s support and interest in the subject and high financial illiteracy act as the main factors that influence the implementation of the digital banking system. However, there are challenges exist like insufficient development of the digital environment, low levels of digital competence, and problems with the regulation of digital processes. The consequences of the digital banking system are, therefore, gigantic in the socio-economic growth of society: economic growth, eradications of poverty, and opportunities of job creation. Thus, the review highlights the need for special efforts to overcome the obstacles and build on the opportunities of digital banking. Further research should be targeted towards long-term results of the virtual classroom and ways to circumvent current obstacles.

Harnessing Wind Energy with H-Rotor Blades for Low Scale Power Generation

Authors- Joseph Benedict Bassey, Victor Koko Willie

Abstract-Rural lighting and electrification remains a challenge to most communities with no access to grid based electricity. However, standalone power systems remain one of the highly recommended alternatives. In this paper, the utilization of wind energy is envisaged as a veritable alternative energy source for the development of low scale standalone power system. Here, the H-rotor blade type was identified and used in the development of wind turbine for electric power generation. A brushed DC motor is used as a generator and the production of the system saw several fabrication processes such as cutting, welding, riveting, machining and drilling operations being performed. The battery bank system for power storage was incorporated using the lithium ion battery type. The system was tested in a relatively low wind speed area and its performance was considered satisfactory, providing marginal power to charge phones and power led bulbs. Hence, the system is recommended for used in rural homes.

Use of Bamboo in Integreted Roads an Innovative Concept with Polymer Composite

Authors- Aman D. Kurundwad, Atharv S. Kajave, Aniket Kharade, Omkar S. Chavan

Abstract-Steel is traditionally used as reinforcement in concrete. But because of cost and availability, replacement of steel with some other suitable materials as reinforcement is now a major concern. Though bamboo has been used as a construction material, especially in developing country, until today its use as reinforcement in concrete is very limited due to various uncertainties. Since bamboo is a natural, cheap and also readily available material, it can be a substitute of steel in reinforcing of concrete. For low volume road we can replace steel with bamboo and construct the road surface like rigid pavement. It is found that life span of bamboo reinforced surface is more than unpaved road and less than rigid pavement reinforced with steel. Life span of bamboo reinforced road can be increase by suitable treatment of bamboos A thin bonded BC overlay may be an economical means to restore the riding quality of a CP. One of the main benefits of such an overlay is the reduction of dynamic impact loading, which in turn, increases the service life of the pavement structure by delaying its rate of deterioration. Polymer-modified cement concrete pavement can not only improve the problem of insufficient durability of asphalt pavement, but also improve the joint damage and cracks of cement concrete pavement. This paper is review of the techniques used in the construction process of bamboo reinforced pavement.

Approximation Method for Gauss-Chebyshev Polynomial Functions

Authors- Sellu K., Assistant Professor Bangura R. M.

Abstract-Random maps most times occur because of it chaotic nature within a dynamic system. Authors have proven the existence of a nonzero solution, but we provide a more rigorous proof of its existence by using both positivity and the preservation of integral properties. We present numerical results of a strong rate of convergence of the Gauss-Chebyshev polynomial functions method.

Heart Disorders Detector and Alerting System Using IoMT

Authors- Gokulraj, Sarah Ruby Christina, Kirubakar, Ranjith Kumar, Kamalesh

Abstract-Nowadays healthcare environment has developed science and knowledge based on Wireless-Technology oriented. This is especially for monitoring to detect heart disorders alerting system using IOMT. So we are introducing an innovative project to stop sudden death rates by using our project. This project includes temperature, pulse, and ECG sensors with leads for analyzing ECG waveform. To find the patient’s health Alert will be sent to Medical professionals if any disorders occur. This project helps to alert medical professionals when patients are in critical situations.

Simulation and Application of a TPM System for Oil Drilling Equipment

Authors- Samy Farahat, Khaled Elkilany, Mohamed Hassan

Abstract-The current research introduces a comprehensive model to implement the Total Productive Maintenance (TPM) methodology in a maintenance system of the crude oil industry. The application was carried out to improve the availability of a well drilling electric equipment through improving the effectiveness of the maintenance activities. Technology advancements are always utilized to implement equipment repair solutions. This paper introduces the application of the Causal Loop Diagram (CLD) modeling technique and its use in integration with the TPM system methodology. The aim is to enhance the up time of drilling machines. Implementing sophisticated maintenance techniques to enhance a work system may ultimately be impractical and expensive due to the required implementation cost, timeframe and resources needed. Hence, implementing modeling methods that are verified and validated can potentially improve the timeframe and lower the expenses required to demonstrate the practicality of the introduced systems. The present study utilized the CLD simulation technique to construct a TPM maintenance model. The results demonstrate that implementing TPM enhances the electrical maintenance system by increasing equipment availability and decreasing stoppages and maintenance cost. The necessary actions were undertaken to establish the TPM system using a deployment strategy, building on the prior knowledge of its feasibility. Different stakeholders of the system including engineering, maintenance, and managerial staff participated in the deployment of the system.

DOI: /10.61463/ijset.vol.12.issue4.217

Crop Yield Prediction Using Machine Learning

Authors- R. Kathiresan [AP], Lokesh P

Abstract-Precision agriculture, an innovative practice that utilizes advanced technologies to optimize field-level management in crop farming, has revolutionized the industry. By accurately predicting crop yields, farmers are empowered to make well-informed decisions, increase productivity, and minimize environmental impact. However, traditional methods of crop yield prediction often fall short in providing precise and real- time insights. To address this issue, we propose a ground breaking project that leverages the power of machine learning techniques to predict crop yields with exceptional accuracy. Our approach involves the use of hybrid machine learning models that combine Decision tree and Multi-Layer Perceptron (MLP) algorithms. By integrating these models, we can harness the strengths of both techniques and achieve superior results in crop yield prediction. Furthermore, we have developed a user- friendly web interface to facilitate seamless interaction with our predictive model. This interface serves as an intuitive platform for farmers and agricultural experts to input relevant data, enabling them to explore predicted yield trends, assess potential risks, and optimize fertilization and harvesting schedules. With this innovative tool at their disposal, users can make data-driven decisions and maximize their agricultural outcomes.

Test of Weak Cosmic Censorship Conjecture of Rotating Hairy Black Holes

Authors- Swapan Kumar Majhi

Abstract-The destruction of event horizon of a black hole might provide us information about black holes which violates the weak cosmic censorship hypothesis. In this study, we investigate the weak cosmic censorship conjecture (WCCC) test of hairy rotating black hole. By examining the particle incident on an extremal rotating hairy black hole, we showed that under certain parameter space, one cannot destroy the event horizon and hence weak cosmic censorship hypothesis is preserved. Otherwise the event horizon could be destroyed and distant observer can get access to the gravity of the black holes. We need to fine tune the quantum parameters(hairy parameters) to get information about the black hole.

Social Status and School Environment as Determinant of Emotional Intelligence among In-School Adolescents in Ibadan North Local Government Area of Oyo State

Authors- Akintayo Samson Olukunle, Osundiran Toluwanimi Esther

Abstract-Emotional intelligence is very vital in the family support system and school environment. This heralded the investigation into social support and school environment as determinants of emotional intelligence among in-school adolescents in Ibadan North local Government area of Oyo State. This study adopted a descriptive research design of correlational type with a random sample of 300 in-school adolescents across four secondary schools in Ibadan North Local Government Areas in Oyo State. Three research questions were generated, data was collected using Singh (2004) Emotional Intelligence scale, Social Support Scale by Zimet, Dahlem, Zimet, and Farley (1988) and School Environment Scale by Debbie et al (2007). The research questions were tested at 0.05 level of significance through Pearson Product Moment Correlation and Multiple Regression Analysis. The result showed that there was a significant relationship between emotional intelligence and social support (r = 0.584, p< 0.01), and school environment (r= .466, p<0.01). The independent variables (social support and school environment) also had joint and relative contribution in the prediction of Academic performance. Among others, it was recommended that teachers and facilitators should inculcate into learners the opportunity for shaping the ingredients of emotional intelligence, parents, family members and relatives should understand that giving their children or adolescents the necessary social support will help boost their level of emotional intelligence and School owners and administrators should ensure that a conducive school environment is catered for to enable their students acquire a high level of emotional intelligence.

Exploring Causes of Delay in Payment from Parties Involved in Road and Highway Projects in India

Authors- Pratyush Singh, Assistant Professor Mr. Vinay Deulkar

Abstract-Construction is an essential process for all of the developing countries. Moreover, highway and infrastructure construction projects are rigid development in a country. Delay is a common phenomenon in the construction industry which directly impacts the cost and quality of the project. Delays can only be reduced when the causes and its influences are identified and analyzed. In the past, most researchers have been working on finding the causes of delay in the construction project through several method and analysis. Nevertheless, the study on the delay causes and its influences towards the infrastructure and highway construction project is still limited and require more precise attention on it. The main objective of the study is to find the significant factors causes delay in the construction project especially in highway and road construction projects.

3D Modeling for the Hajj and Umrah Pilgrims

Authors- Professor Dr Om Prakash

Abstract-A 3D simulation model is generated that can be used for a virtual representation of people who are performing Hajj and Umrah so that future travellers can gather necessary information to perform religious ceremonies and be well prepared before arrival to the holy places. Traffic and pedestrian management in the areas is also presented. The purpose is to speed up the calculation of all events of interest to the authorities in a simulator, such as the behaviour of vehicles, pedestrians on the streets, and worshippers. Two GPU solution alternatives and one CPU solution alternative are proposed, and the performance of the proposed solutions is also compared.

Identifying Key Influencers on X: A Network Analysis of User Behavior through Social Relationships

Authors- Assistant Professor Fereidoon Bidollahkhany, Assistant Professor Mehdi Basiri

Abstract-In the contemporary digital landscape, users engage extensively with these platforms. The significance of these networks and their profound impact on users has prompted in-depth analyses in this dynamic field. Such investigations are essential to harness the potential of this domain for enhancing user services. Within social networks, individuals are deeply influenced by their peers, driving researchers to identify influential figures within the X platform for the extraction of user behavior patterns. To determine influential users, our study used a variety of X network relationships for comprehensive network analysis. Employing indicators from social network analysis, we determined the impact coefficient for each relationship model. Subsequently, we established the hierarchy of these relationship models. Our research findings emphasize the importance of retweeting among the four interactive relationship types: retweeting, pointing, answering, and following. Retweeting plays a greater role in shaping the communication graph and effectiveness compared to pointing, answering, and following.

DOI: /10.61463/ijset.vol.12.issue4.218

Detecting Fake Profiles Using Neural Networks

Authors- S. Nafisa Afreen

Abstract-Here, we use machine learning, in the form of an artificial neural network, to calculate the probability that a user’s friend request on Face book is genuine, real or not. The relevant libraries and classes are also described. Further, we talk about the sigmoid function and how the weights are calculated and applied. In the end, we think about the most crucial aspects of the social network page to consider while implementing the proposed solution.

DOI: /10.61463/ijset.vol.12.issue4.219

Security, Privacy, and Identity Issues in Smart Cities

Authors- Nischith. Bashettiyavar

Abstract-Smart cities leverage advanced technologies such as the Internet of Things (IoT), Big Data, and Artificial Intelligence (AI) to enhance urban living. However, the integration of these technologies raises significant concerns regarding security, privacy, and identity. This paper explores these issues by identifying the risks associated with smart city technologies and proposing strategies to mitigate them. The motivation behind this work stems from the increasing adoption of smart city initiatives worldwide and the need to protect citizens’ data and identities. The primary objectives are to assess vulnerabilities in smart city infrastructure, analyze potential threats, and recommend comprehensive security frameworks. This study’s findings provide valuable insights for policymakers, developers, and urban planners to build more secure and resilient smart cities.

Climate Change Impact on Thermal Comfort Perception and Occupant Adaptive Behaviour in Buildings

Authors- Chime Charles

Abstract-The discomfort faced by occupants of buildings due to climate change has escalated the combined effect of high solar radiation and humidity levels in the warm-humid climate. Thermal comfort is a subjective feeling whereby occupants feel satisfied with the environment. Thermal comfort depends on the heat physiology of the person. A person must keep his core body temperature constant and therefore has to be able to transfer the excess heat produced by his metabolism into the surroundings. The thermal comfort temperature is related to the local climate condition, culture context, and type of subjects. When a change occurs, causing thermal discomfort, people react in such a way that their thermal comfort is re-established. In this research Occupants were asked to assess environmental conditions in terms of thermal comfort by filling in the questionnaire. the top indoor air temperature threshold can be defined as 30°C; when the indoor air temperature was higher than 28°C, none of windows was closed, occupants would feel hot. The solar radiation in the afternoon did have an obvious influence on it. Although the windows were opened, the influence on the indoor air temperature was high, when the outdoor air temperature greatly decreased it cause the indoor air temperature to decrease. Occupants find it more tolerable to control the windows, use personal fans or change clothing, rather than working in the office building which is fully controlled by centralised air-condition system because health related issues like pneumonia and airborne diseases. Recommendations were made for behavioural adaptation which is a significant adjustment method that can help occupant re-establish their comfort and reduce energy consumption.

Adequate Dimensions for Planar GaAs/Ag Diodes for Microwave Frequencies Using a Series Resistance Approach

Authors- Laith M. Al Taan, Yussra M. Abdullh, Huda M. Abd Alqader

Abstract-This work involved calculating the precise dimensions of a Schottky device (GaAs/Ag) that operates at microwave frequencies. The series resistance model was used to determine the closest elliptical shape to the lowest discontinuity value. The metals studied included Gold, Copper, Silver, and Aluminum. When the depletion capacity Cj was fixed, the lowest series resistance (Rs~6.4) was observed for Silver at a cutoff frequency of ~4000GHz. On the other hand, the series resistance was higher for the other metals and had a lower cutoff frequency. The IV electrical characteristics displayed the diode model’s behavior as a rectifier, with an ideality factor reaching1.2 .

DOI: /10.61463/ijset.vol.12.issue4.220

The Two-Echelon for Meat Products Location-Routing Problem with Picking Up and Delivery by Using Constraint Programming

Authors- Ly Van Tran, Tuan Minh Le, Nhi Tran Tuyet Nguyen, Son Vu Truong Dao

Abstract-Using distribution centers as intermediate facilities and meat product pickup and delivery limitations, this research offers a novel extension to the two-echelon site routing issue. The recently described variation, LRP-MPPD-2E (Location – Routing Problem with Multi-Productsm Pickup and Delivery), addresses complex, practical supply chain applications. The Constraint Programming method with a unique modeling approach was used in the actual instance of G-Kitchen to address this challenge. This paper promotes sustainability and benefits local communities in addition to better service levels, cost savings, higher competitiveness, and economic development by tackling the Two-Echelon Vehicle Routing Problem (2E – VRP). Long-term corporate success and community growth are supported by the more dependable, efficient, and sustainable transportation ecosystem that is fostered by the successful use of 2E-VRP.

DOI: /10.61463/ijset.vol.12.issue4.221

Geospatial Analysis of Urban Growth in Ikire, Osun State, Nigeria between 2000 and 2020

Authors- Kafayat Olaniyan, Simeon Ogunlade

Abstract-Today’s world is dealing with an ongoing flow of development, and this growth in development is an evolving process that hastens urbanization. In developing nations where development takes priority over urban planning, the current urbanization issues are widespread. Using remote sensing techniques, this study examines the urban growth of Ikire town between 2000 and 2020 with a view to monitoring its urbanization for a sustainable development. The Landsat imageries of year 2000, 2010 and 2020 were used to accessed the study area. Five categories of land cover were identified in Landsat images from the years 2000, 2010, and 2020. Utilizing attribute and statistical data generated from the classification outcome and used for post-classification comparison across the years, the extent of urban land use was ascertained. The results showed that Ikire experienced remarkable growth between 2000 and 2020, with its area increasing from 27.418 km2 (8.9%) in 2000 to roughly 48.500 km2 (15.7%) in 2020 and it was projected to have grown to 117.682 km2 (38%) in the year 2060. The vegetation decreased from 203.198km2 (65.9%) in 2000 to 175.371km2 (56.9%) in 2020 as a result of this growth. As a result of people’s need for food and shelter, agriculture has grown over the years of this study. Additionally, bare land experienced a slight decline from 19.3% in 2000 to 118.0% in 2020 which leads to continuous development and urban expansion. The study’s conclusions showed that the built-up area has grown in size over the past 20 years, and this has an effect on the surrounding ecosystem.

A Theoretical Review of Vibration-Based Fault Detection Techniques: Machine Learning Approaches and Their Challenges in Industrial Applications

Authors- Research Scholar Sandeep Yadav, Assistant Professor Khemraj Beragi

Abstract-The rapid evolution of industrial machinery and the increasing complexity of maintenance tasks have led to significant advancements in fault detection and predictive maintenance methods. Central to these developments is vibration analysis, which has been significantly enhanced by integrating machine learning (ML) and deep learning (DL) techniques. These advanced analytical tools provide powerful capabilities for real-time fault diagnosis and predictive maintenance, transforming how industries manage equipment reliability and failure prevention. This paper presents a detailed theoretical review of recent research in vibration-based fault detection, focusing on the effectiveness of various ML and DL algorithms. The review examines a range of methods, including Support Vector Machines (SVMs), Convolutional Neural Networks (CNNs), and Decision Trees, highlighting their strengths and applications. By analyzing recent innovations, the paper demonstrates how these techniques have improved fault detection accuracy and predictive capabilities in diverse industrial settings. The review also critically evaluates the performance of these methodologies in different operational environments, from manufacturing to aerospace, and categorizes state-of-the-art algorithms and their practical uses. It addresses key challenges, such as the need for large labeled datasets, sensitivity to operational variations, and model generalizability issues. Through this comprehensive analysis, the paper synthesizes current knowledge and provides insights for future research. It highlights the importance of overcoming existing challenges and suggests potential research directions to develop more adaptive and robust fault detection systems. This review serves as a foundational resource for advancing vibration-based fault detection and predictive maintenance, aiming to enhance industrial equipment reliability and operational efficiency.

From Cloud to Edge: Empowering Intelligent Applications with Cloud-Native Technologies

Authors- Ramakrishna Manchana

Abstract-Edge computing’s potential for real-time, data-driven applications is often hindered by traditional architectures’ limitations in scalability and resource management. Cloud-native edge computing, integrating cloud technologies like containerization and orchestration, offers a solution. This paper explores cloud-native edge computing’s architectural patterns, key technologies, benefits, and challenges. We highlight advantages like improved scalability and resource efficiency while addressing security and heterogeneity concerns. Real-world use cases across various industries demonstrate its transformative impact. The paper concludes by outlining future research opportunities in this rapidly evolving field.

DOI: /10.61463/ijset.vol.12.issue4.223

Determination of the Properties and Potentials of Hybrid Vegetable Oil from Nigerian Origin for Biodiesel Production

Authors- Ayodeji Kolade Oladele, Wunuken Carlos Solomon, Sani Umar Muhammad

Abstract-Rising pump prices, emission legislations and emission of greenhouse gases have prompted the need for a suitable and renewable alternative to petro diesel. Biodiesel, being one of such alternatives needs is characterized by environmental friendliness and fewer emissions; apart from the afore mentioned, it needs to have more improved properties. This research is aimed at determining the properties and potentials of hybrid (Jatropha-Neem) vegetable oil from Nigerian origin for biodiesel production. Jatropha and Neem oils were sourced, characterized and then blended in step percentages of 20%. Together with an equal percentage of both oils, seven samples of hybridized Jatropha-Neem oil mixture were characterized for suplhur and free fatty acid. Characterized samples were considered and the Jatropha-Neem 60:40 oil combination was chosen as the oil feed stock combination for biodiesel transesterification. The choice was ascertained based on fair values of sulphur and Free Fatty Acid (FFA).

DOI: /10.61463/ijset.vol.12.issue4.224

Exploring the Efficacy of Pomegranate Extract in Disease Prevention and Therapeutic Management

Authors- Vishal Goswami, Yogendra Kumar Saraswat, Amit Parashar

Abstract-Pomegranate (Punica granatum) has long been revered for its therapeutic properties, and study is increasingly focused on its potential health benefits. This review investigates pomegranate’s numerous advantages, including antioxidant and anti-inflammatory activities and anticancer and heart-protecting characteristics. We will look at the unique components in pomegranates, such as Punicalin, Ellagitannins (precursors of ellagic acid), and Anthocyanidins (aglycone forms of anthocyanins), how they support excellent health. We will also discuss the scientific evidence supporting the usage of Pomegranates’ antioxidants may help lower the risk of heart disease, fight cancer, control diabetes, and protect against brain illnesses. We will also highlight new study topics and ideas for future studies on the potential of this incredible fruit.

DOI: /10.61463/ijset.vol.12.issue4.225

Wastewater Treatment by Using Pressurized Anaerobic Baffled Reactor (PABR)

Authors- Md. Shoriful Islam, Redowan Hossain, Mehedi Hassan

Abstract-An novel development in wastewater treatment technology, the pressured Anaerobic Baffled Reactor (PABR) combines the principles of anaerobic digestion with pressured operation to improve treatment efficiency. In contrast to conventional anaerobic systems, PABRs function at higher pressures, which lengthens the biomass’s retention period and improves the breakdown of organic contaminants. The reactor is divided into several compartments by a series of baffle walls that are utilized by the PABR technology. Wastewater is subjected to a series of treatment procedures as it passes through various compartments, gradually lowering the amount of contaminants present. By increasing the solubility of gases like carbon dioxide and methane, pressurization raises the anaerobic digestion process’s general efficiency. This leads to increased production of biogas, which may be used as a sustainable energy source, and decreased.

DOI: /10.61463/ijset.vol.12.issue4.226

Implementation and development of Automatic Load Shifter for Constant Single Phase Power Supply

Authors- Mr.Shahuraj Sable, Tejas Puri, Maaz Khan, Rohan Nimbalkar, Amar Antad

Abstract-Ensuring stable power supply in developing nations necessitates the automation of electrical generation processes due to frequent outages. These interruptions, which significantly impact industrial and commercial operations reliant on continuous power, often require manual intervention during phase changeovers. However, manual handling can lead to time inefficiencies and potential damage to equipment due to human errors in reconnecting phases. A switch box for phase changeover is employed to manage power supply interruptions among three phases. When power outage occurs in any phase, manual intervention is needed to switch to an alternate phase. Similarly, when the interrupted phase is restored, the switch must be turned off and the source reassigned to the original phase.

Forecasting of Landuse and Land Cover Changes by Applying Support Vector Machine Using Landsat Satellite Imagery

Authors- Priyanka Gupta, Sharda Haryani, V.B. Gupta

Abstract-The primary goal of this study is to identify the LULC classes for the Madhya Pradesh, India, Mandsaur district. The research was conducted using multi spectrum satellite images. The paper uses support vector machine approach based on pixel by pixel supervised categorization of Landsat satellite pictures taken over 20 years between 2003 and 2023 using Arc-GIS tool. To predict general changes, different classifications of land use and land cover features such as populated regions, water bodies, agricultural land, woods, and desert terrain are taken into account. To do this, remotely sensed Landsat 5 photographs from 2003 and Landsat 8 photos from 2023 were employed for change detection. This paper used the support vector machine technique to compare the LULC classes for the Mandsaur region. The supervised classification findings validated with Support Vector Machine (SVM) provided kappa coefficients of 0.835 and 0.803 for the years 2023 and 2003, respectively. The use of Support Vector Machine (SVM) algorithms should have a significant positive impact on land cover classification.

DOI: /10.61463/ijset.vol.12.issue4.227

ER Fuzzy Logic Prototype for Electronic Banking Fraud Detection

Authors- Mohammed Usman, Gregory Maksha Wajiga, Umar Uwaisu Abubakar, Musa Adamu Girei

Abstract-The landscape of online payments has significantly transformed over the years, with an increasing number of individuals opting for electronic payment platforms instead of traditional banking methods. From point-of-sale systems to mobile and virtual banking services, various trends have emerged to facilitate seamless transactions for consumers. However, the rise of electronic fraud poses a serious threat to Nigeria’s financial system, resulting in substantial economic losses and hindering the widespread adoption of cashless technologies due to escalating fraudulent activities. This study aims to educate the public about the issues related to payment fraud across different channels and to assist financial institutions in implementing more effective monitoring and preventive strategies against fraud. In this research, five key features of electronic banking transactions were identified and utilized to establish a universe of discourse, membership functions, and their corresponding linguistic variables for the fuzzy system. These were classified using Fuzzy Inference System (FIS) to enable the detection system to evaluate and categorize transactions as either fraudulent or legitimate.

DOI: /10.61463/ijset.vol.12.issue4.228

An Examination of Privacy and Security Concerns in Social Networks

Authors- Research Scholar Sheena Wahid Khan, Professor Manju Mandot

Abstract-Nowadays, social media is a part of everyday existence. Individuals are able to engage, speak, and have common interests, which enable them to build publicly viewable online profiles. These are the standard features that the majority of social networking sites provide. Regrettably, people frequently do not even realize that their personal information is disclosed through profiles. There are several ways in which users’ personal information might be compromised. This document discusses a number of the security issues related to using social networks. Furthermore, the problem the relationship between privacy and security is explained, highlighting how they intersect and impact each other. Some important recommendations are made to enhance users’ security and privacy on social networks in light of these talks. This inquiry aims to enlighten readers on the security and privacy concerns faced by social network users. Through this research, users will gain valuable insights to make informed decisions and protect themselves online.

DOI: /10.61463/ijset.vol.12.issue4.229

Segmentation and Classification of Liver Cancer Using Deep Learning Models

Authors- Vinay Kumar T M, T Nikhil, Varun Kumar V

Abstract-This rеsеarch papеr proposеs a robust dееp lеarning modеl for mеdical imagе sеgmеntation, spеcifically targеting thе dеlinеation of livеr tumors in CT mеdical imagеs. Thе implеmеntеd modеl еmploys a U-Nеt architеcturе, a wеll- еstablishеd framеwork for sеgmеntation tasks. Thе study utilizеs a curatеd datasеt, namеly thе ‘3dircadb’ datasеt, acquirеd from Kagglе, and introducеs a custom data gеnеrator for еfficiеnt data loading and prеprocеssing. Thе rеsеarchaims to еnhancе thе accuracy and prеcision of livеr tumor sеgmеntation, crucial for diagnostic and trеatmеnt planning in thе fiеld of mеdical imaging. Thе еvaluation mеtrics, including Pixеl Accuracy (26.58%), Truе Positivе Accuracy (99.68%), and Dicе Coеfficiеnt (0.89), indicatе promising rеsults. Thе confusion matrix analysis furthеr undеrscorеs thе modеl’s pеrformancе, rеvеaling dеtailеd insights into thе classification outcomеs. Thе binary classification problеm, distinguishing bеtwееn “Malignant” and “Benign” is еffеctivеly addrеssеd, as dеmonstratеd bythе confusion matrix intеrprеtation. Thе modеl еxhibits a high truе positivе ratе, еnsuring that thе majority of tumors arе corrеctly idеntifiеd, whilе maintaining a low falsе nеgativе ratе. Thе rеsеarch contributеs to thе advancеmеnt of mеdical imagе sеgmеntation tеchniquеs, offеring a valuablе tool for clinicians in thе accuratе dеtеction and dеlinеation of livеr tumors.

DOI: /10.61463/ijset.vol.12.issue4.230

A Comparison of RPL Attacks in the Internet of Things

Authors- M.Tech Scholar Vikas Kumar Gupta, Professor Santosh Nagar, Professor Anurag Shrivastava

Abstract-Routing Protocol for Low Power and Lossy Networks (RPL) is the routing protocol for IoT and Wireless Sensor Networks. RPL is a lightweight protocol, having good routing functionality, but has basic security functionality. This may make RPL vulnerable to various attacks. Providing security to IoT networks is challenging, due to their constrained nature and connectivity to the unsecured internet. This survey presents the elaborated review on the security of Routing Protocol for Low Power and Lossy Networks (RPL). This survey is built upon the previous work on RPL security and adapts to the security issues and constraints specific to Internet of Things. An approach to classifying RPL attacks is made based on Confidentiality, Integrity, and Availability. Along with that, we surveyed existing solutions to attacks which are evaluated and given possible solutions (theoretically, from various literature) to the attacks which are not yet evaluated. We further conclude with open research challenges and future work needs to be done in order to secure RPL for Internet of Things (IoT).

Development and Validation of a Scale for Assessing Entrepreneurial Challenges

Authors- Assistant Professor Dr.A.Sudhanraj

Abstract-In particular, the study on entrepreneurship in India sees intention, motivation, behavior, and characteristics as interchangeable. This article argues that entrepreneurial challenges should be considered separately and measured objectively to draw meaningful conclusions. The authors propose developing a scale tailored to the Indian context to measure these challenges. The study’s sample consisted of 85 potential women entrepreneurs. Using factor analysis through the principal components method, six key dimensions of entrepreneurial challenges were identified: financial sustainability, organizational effectiveness, decision-making, personal risk, leadership and team building, and dealing with competition. The strength of these dimensions was assessed using a Likert-type five-point rating scale.

DOI: /10.61463/ijset.vol.12.issue4.231

Exploring the Applications of LaMDA and LLama Language Models in Education and Content Applications

Authors- Professor Dr. Satya Singh, Ratnesh Kumar Sharma

Abstract-Recent advancements in natural language processing (NLP) have led to the development of powerful language models such as LaMDA (Language Model for Dialogue Applications) and LLama (Linguistic Knowledge and Memory Augmented Agents). These models, trained on large-scale datasets, demonstrate remarkable capabilities in understanding and generating human-like text. In this paper, we investigate the potential applications of LaMDA and LLama in the field of education and content creation. We explore how these models can be utilized to enhance learning experiences, automate content generation, and facilitate interactive dialogue systems. Through case studies and experimental evaluations, we demonstrate the effectiveness and limitations of LaMDA and LLama in various educational and content-related tasks. Our findings highlight the transformative impact of advanced language models on education and content applications, paving the way for innovative approaches to knowledge dissemination and communication.

DOI: /10.61463/ijset.vol.12.issue4.232

Healthcare Information Security for Electronic Medical Records by Adapting Ethical Hacking

Authors- Research Scholar S.Sivashankar, Associate Professor Dr.G.Kalpana

Abstract-The adaptation of ethical hacking in healthcare information security, particularly for electronic medical records (EMRs), is increasingly recognized as a vital strategy to combat cyber threats. Recent studies propose an artificial intelligence-based ethical hacking method tailored for health information systems (HISs), demonstrating its superiority over traditional methods in identifying vulnerabilities and attack pathways more efficiently. This approach not only enhances the detection of exploits but also addresses the unique challenges faced by healthcare organizations, which are often targeted due to the sensitive nature of health data. Moreover, the implementation of penetration testing, a key component of ethical hacking, is recommended to bolster cybersecurity measures in healthcare, despite existing prejudices against hacking practices. The integration of advanced encryption techniques further supports the protection of sensitive medical data by ensuring confidentiality and integrity. Collectively, these findings underscore the importance of ethical hacking as a proactive measure in safeguarding EMRs and enhancing overall healthcare cybersecurity. This paper provides a brief explanation of implementing healthcare information security for electronic medical records with the help of ethical hacking tools is an effective approach to safeguarding sensitive patient information. By identifying vulnerabilities, improving incident response and disaster recovery planning, and ensuring compliance with regulatory requirements, healthcare organizations can protect EMRs from cyber-attacks and data breaches. As the healthcare industry continues to evolve and rely more heavily on digital technologies, the importance of ethical hacking in healthcare will only continue to grow. By embracing ethical hacking tools and techniques, healthcare organizations can stay one step ahead of malicious hackers and ensure the confidentiality, integrity, and availability of EMRs.

DOI: /10.61463/ijset.vol.12.issue4.233

Modeling and Design of Grid DFIG System in Matlab

Authors- Sekdiya, Assistant Professor Raghunandan Singh Baghel

Abstract-The Doubly Fed Induction Generator (DFIG) based wind turbine with variable speed variable-pitch control scheme is the most popular wind power generator in the wind power industry. This machine can be operated either in grid connected or standalone mode. The paper offers discussion of RSC and GSC control scheme of wind turbine for cumulative modernization of wind turbine technology through literature survey of wind turbine configuration, mainly of double fed induction generator (DIFG).This paper gives proper understanding of control schemes, characteristics and limitation of DIFG.

Data – Intensive Applications on Cloud

Authors- Sriram Santosh Aripirala

Abstract-The rapid growth of Internet and World Wide Web has led to vast amounts of information available online. Processing Terabytes of data in Data-Intensive applications has always been a challenge. Modern scientific computing involves organizing, moving, visualizing, and analyzing massive amounts of data from around the world, as well as employing large-scale computation. The distributed systems that solve large-scale problems will always involve aggregating and scheduling many resources. Data must be located and staged, cache and network capacity must be available at the same time as computing capacity, etc. The technologies, the middleware services, and the architectures that are used to build useful high-speed, wide area distributed systems, constitute the field of data intensive computing. A variety of system architectures have been implemented for data-intensive applications such as Map Reduce architecture which is now available in an open-source implementation called Hadoop. This paper explores some of the technologies and infrastructure (such as Amazon EC2) built for this purpose. This paper also evaluates the analysis of some platforms.

DOI: /10.61463/ijset.vol.12.issue4.234

Maya Angelou’s Multifaceted Themes: Exploring Identity, Resistance, and Beauty in African-American Literature

Authors- Eirini Eleftheriou, Katerina T. Frantzi

Abstract-This study undertakes a thorough examination of the diverse themes permeating Maya Angelou’s literary works, delving into the realms of racism, feminism, self-actualization, and the portrayal of Black identity. Employing a mixed-methods approach, the research combines thematic analysis and an extensive literature review to unravel the intricate layers of meaning within Angelou’s texts. The aim is to contribute nuanced insights to the existing body of knowledge by identifying recurring patterns and shedding light on the significance of these themes in the broader socio-cultural context. Through thematic analysis, the study systematically uncovers the multifaceted narratives present in Angelou’s poems and autobiographical narratives. Additionally, sentiment analysis of specific words, notably “woman” and “mother,” has been incorporated into the research methodology. Using the R Programming Language, sentiment analysis offers a nuanced understanding of the emotional nuances associated with these crucial terms within Angelou’s works. The literature review draws from the scholarship of Suhadi (2016), Jingal & Bangu (2017), Du (2014), Guha (2015), Palupi (2014), and Sunday & Ekpo (2018), providing theoretical insights and contextualizing Angelou’s themes within the existing academic discourse. By intertwining quantitative and qualitative analyses, this study not only enriches our understanding of Maya Angelou’s thematic expressions but also unveils the emotional resonance embedded in her choice of words. Through sentiment analysis, the study offers a unique perspective on the emotional dimensions associated with the terms “woman” and “mother” in Angelou’s literary corpus.

DOI: /10.61463/ijset.vol.12.issue4.235

Analysing the Vast Majority of Available Literature of Enhancing of Operating System through Machine Learning

Authors- Research Scholar Praveen Kumar Mishra, Associate Professor Dr Manish Kumar

Abstract-In the current age of the Fourth Industrial Revolution (4IR or Industry 4.0), the digital world has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data, business data, social media data, health data, etc. To intelligently analyze these data and develop the corresponding smart and automated applications, the knowledge of artificial intelligence (AI), particularly, machine learning (ML) is the key. Various types of machine learning algorithms such as supervised, unsupervised, semi-supervised, and reinforcement learning exist in the area. Besides, the deep learning, which is part of a broader family of machine learning methods, can intelligently analyze the data on a large scale. In this paper, we present a comprehensive view on these machine learning algorithms that can be applied to enhance the intelligence and the capabilities of an application. Thus, this study’s key contribution is explaining the principles of different machine learning techniques and their applicability in various real-world application domains, such as cybersecurity systems, smart cities, healthcare, e-commerce, agriculture, and many more. We also highlight the challenges and potential research directions based on our study. Overall, this paper aims to serve as a reference point for both academia and industry professionals as well as for decision-makers in various real-world situations and application areas, particularly from the technical point of view.

DOI: /10.61463/ijset.vol.12.issue4.236

Optimality in Nash Equilibrium for the Multilevel Environment

Authors- Research Scholar Rakesh Kumar, Associate Professor Dr Krishnandan Prasad

Abstract-We have work done provides game theory applications for two equivalent symmetric matrices and skew symmetric matrices. It may be impossible for agents with non-conflicting interests to learn a portfolio coordinating strategy when there are several perishable equilibria. If the agents get loud payoffs on their own and are unaware of the game, the issue is made worse. Therefore, recognizing the game and learning to play are the two interrelated challenges that multiagent reinforcement learning addresses. We introduce optimum adaptive learning, the first convergent method, in this study to the optimal Nash equilibrium. It is simple to set the algorithm’s parameters to reach convergence, as demonstrated by the convergence proof we present. Our research introduces optimum adaptive learning, which is the initial method that reaches the ideal equilibrium of Nash. We present a proof of convergence and demonstrate how simple it is to adjust the algorithm’s parameters in order to reach convergence.

DOI: /10.61463/ijset.vol.12.issue4.237

A Novel Scheme for Marketing by Study Customer Behavior Using Data Mining Technique

Authors- Research Scholar Mrs. Anusha Mardia, Assistant Professor Dr. Dilip Kumar Choudhary

Abstract-In the rapidly evolving landscape of marketing, companies increasingly rely on sophisticated techniques to target their campaigns effectively. This paper presents a novel framework for customer segmentation and targeted marketing using advanced data mining and machine learning techniques. With the proliferation of customer data, traditional methods of segmentation have proven insufficient for accurately identifying and targeting potential customers. This study explores various data mining techniques, including Support Vector Machines (SVM), Logistic Regression, K-Nearest Neighbors (KNN), Decision Trees, Random Forests, and Gradient Boosting Classifiers, to develop a robust model for predicting customer behavior based on historical data. Various studies on consumer purchasing behaviors have been presented and used in real problems. Data mining techniques are expected to be a more effective tool for analyzing consumer behaviors. However, the data mining method has disadvantages as well as advantages. Therefore, it is important to select appropriate techniques to mine databases. The objective of this paper is to know consumer behavior, his psychological condition at the time of purchase and how suitable data mining method apply to improve conventional method. Moreover, in an experiment, association rule is employed to mine rules for trusted customers using sales data in a super market industry.

DOI: /10.61463/ijset.vol.12.issue4.238

Advanced Data Visualization Methods and Tools in Cloud Platforms

Authors- Rohini Isarapu, Sharathchandra Gowda

Abstract-With the current big data solutions from providers including Google Cloud Platform (GCP), Amazon Web Services (AWS), Microsoft Azure among others, organizations can utilize powerful data visualization tools that lead to beneficial interpretation from raw data. Specifically, this paper discusses how these tools and platforms offer unique methods of data visualization, through Google Data Studio, Looker, BigQuery BI Engine, Amazon QuickSight, AWS Glue, and Power BI. All of these platforms have custom-specific options that vary depending on the business and its needs and incorporate real-time data processing, application of machine learning, and compatibility with other cloud solutions. This paper specifically discusses the application of these approaches in the context of telecommunications processes and shows what benefits the use of such tools can bring in terms of network monitoring, customer experience optimization, and fraud prevention. For instance, with BigQuery connected to Data Studio, telecom networks can visualize the patterns in the traffic flow and anticipate possible outages. Customer satisfaction and performance can be monitored using AWS QuickSight, which has built-in machine learning functionality, while Azure Synapse Analytics has useful tools for identifying fraudulent behaviors based on call detail records (CDRs). Moreover, this paper provides a comparison of these tools with emphasis on their main characteristics, their charging structure and the kind of environments they fit in the telecommunications industry. With these efficient and sophisticated cloud-based visualization applications, telecom companies can enhance their business productivity and hence customer satisfaction and service level.

DOI: /10.61463/ijset.vol.12.issue4.239

A Review on Phytoremediation of N-Hexane Contamination

Authors- Dr. E. M. Denise, Ememem E.I

Abstract-N-hexane, a highly volatile and flammable liquid hydrocarbon, presents a significant environmental and health challenge due to its widespread industrial use and potential for contamination. The potential of n-Hexane in phytoremediation lies in its ability to enhance the uptake and degradation of contaminants by plants, thereby accelerating the remediation process and reducing the overall environmental impact of pollution. This review delves into the multifaceted implications of N-hexane pollution, encompassing its sources, environmental impacts, and risks to human health. Furthermore, it explores the potential of phytoremediation as a sustainable approach to mitigate N-hexane contamination, offering insights into its effectiveness, challenges, and future prospects. In response to these challenges, phytoremediation has emerged as a promising and environmentally sustainable approach for mitigating N-Hexane pollution, such include, Site-Specific Plant Selection, genetic engineering Rhizosphere Optimization etc. By illuminating the intersection between N-hexane pollution and phytoremediation, this review aims to contribute to the development of holistic strategies for environmental management and protection.

Computer-Aided Design and Analysis of Load Deflection Behaviour of Diaphragm Spring Used In Clutch Assembly

Authors- Assistant Professor Vipul Jain, Assistant Professor Anant Dixit, Assistant Professor Deepak Bhonde

Abstract-In the present work standard Diaphragm, spring is considered for numerical analysis of force concerning its maximum displacement of twice that of its height the results obtained are quite satisfying the one which is proposed by Almen J. O. in 1936 and is modeled in CATIA V5R12 software and then further analyzed in ANSYS 14.0 simulation software. For proper analysis, the displacement is provided to the upper edge of the spring, and rest all directions for that edge are fully constrained. The base edge is also provided with fully constrained motion in the vertical direction but having free boundary conditions in the rest of the directions. The results in form of reaction force are then obtained through an ANSYS solver. It is then concluded that FEA results are in good agreement with the numerically obtained data and can be considered for this kind of application in the future too. Different graphs representing load-deflection values are drawn and percentage deviation of FEA results concerning numerical results are studied and summarized in conclusion.

Intelligent Edge Computing for IoT: Integrating Machine Learning and Data Mining

Authors- Professor Dr S Murali krishna

Abstract-The integration of Intelligent Edge Computing into the Internet of Things (IoT) represents a paradigm shift in data processing and analytics, allowing for real-time insights and enhanced operational efficiencies. This approach distributes computing resources closer to data sources, minimizing latency and bandwidth usage while improving security and data privacy. By leveraging machine learning (ML) and data mining (DM) techniques at the edge, devices can independently process and analyze large volumes of data, leading to timely decisions and actions in various applications such as smart cities, healthcare, and industrial automation. This paper explores the synergistic relationship between Intelligent Edge Computing, ML, and DM, highlighting the capabilities each brings to IoT infrastructure. It investigates challenges such as resource constraints, data management, and security issues associated with deploying these technologies at the edge. Furthermore, it discusses diverse application scenarios, offering a comprehensive understanding of how integrating ML and DM can optimize performance, improve user experiences, and drive innovations in IoT systems, ultimately paving the way for future advancements in intelligent digital ecosystems.