Volume 11 Issue 3 | International Journal of Science, Engineering and Technology

Prevalence and Determinants of Burnout Syndrome among Skilled Healthcare Workers in a District Hospital, Rwanda.

Authors- Sylvain Ndayisenga, Japheths Ogendi, Emmanuel Ndayambaje

Abstract- This study aimed to assess the prevalence and determinants of burnout syndrome among healthcare workers at the district hospital level in Rwanda. A cross sectional study design with quatative approach was used to respond to the research questions. Within a period of 3 weeks, by using a self reported questionnaire the data were collected among 110 healthcare workers within 15 departments. Of 110 healthcare workers, 79 (71.8%) were female whereas 31(28.2%) were male, giving female to male ratio of 5:2. The age ranged from 20 to 60 with a mean age of 35.7 years old; with slightly over half 62 (56.4%) healthcare professionals obtained bachelor’s degree.

Determination of the Gross Alpha and Beta Activity Levels Due to Consumption of two Drinkable Water Sources in Yagai, Jalingo Local Government Area of Taraba State, Nigeria

Authors- Idris Iliyasu Kirim, Mohd. Gambo Abdullahi, Andeyabin Saleh, Adamu Hassan Abubakar , Suleiman Idris, Ayuba Abarshi, Bakari Umar Faruk

Abstract- Water is an essential component of human life and water pollution is the contamination of water sources by substance which could make the water abnormal for cooking, drinking, cleaning, swimming, and many more. These pollutants may include trash, bacteria, chemicals and parasites all of which could fall out of human activities. This study determined the alpha and beta radioactivity levels of three (3) dug wells and sachets water samples collected from six different locations of Yagai area in Jalingo, Taraba Nigeria. The values of the gross alpha radioactivity ranges between 2.10±0.01mBq/L to 3.50±0.04mBq/L with a mean value of 2.83mBq/L and 11.40±0.40mBq/L to 18.20±0.20mBq/L with a mean of 15.07mBq/L for sachet and dug well water samples respectively and values of the gross beta radioactivity also ranges between 24.4±0.3mBq/L to 43.20±0.01mBq/L with a mean value of 34.5± 0.11 and 39.4±0.50mBq/L to 54.20±0.6mBq/L with a mean value of 46.63± 0.60 for sachet and dug well water samples respectively. The world health organization standard for acceptable alpha and beta concentration level is 500mBq/L and 1000mBq/L for alpha and beta concentrations respectively. Results obtained are below the world health organization standard suggesting that the two drinking water sources in Yagai may be considered relatively safe for drinking.

Weigh the Pros and Cons of Using Artificial Intelligence in Education

Authors- Norbert Annuš

Abstract- Artificial intelligence is advancing at incredible speed and becoming part of our everyday lives. This is thanks to the technological advances of the last decade and the spread of digitalization in countless areas. Education is another area where information and communication technologies are an integral part of everyday life. It is therefore inevitable that artificial intelligence is ignored in the field of education. Artificial intelligence-based technologies offer a number of benefits for students and teachers alike. But excessive digitalization has its dangers, so the question is: how far will we benefit from artificial intelligence in education? In this research we will try to answer this question. By examining the results of various international research studies, we discuss the benefits and potential risks of artificial intelligence in the educational process. Our aim is to help educators understand the pros and cons that may influence their decisions to implement artificial intelligence in everyday education.

IOT Based Heart Attack Detection and Health Monitoring of Paralysis Patient

Authors- Nikhil Bhagat, Gorde Rohit, Phadol Kanchan, Prof.Yogesh Patani, Dr. Deepak Kadam

Abstract- In today’s world, many people are losing their lives due to heart attacks and the shortage of specialist doctors available to take immediate action. Hence this system provides the implementation of heart rate monitoring and controlling of a patient. For this, we have used the technology called the “internet of things” to detect and monitor the heart rate of a patient. In this system, the patient will be equipped with the hardware consisting of sensors and other devices for measuring the heartbeat along with the notification unit to notify and provide data in real-time. The heartbeat sensor with advance measuring technique will calculate the heartbeat of the patient, and transmit it over the internet that can be easily accessed by the patient itself. It also calculate the sweat through sweat sensor, which is beinged considered in case of heart attack. The heartbeat limits are set on a system that informs about the high and low rate of heartbeat. It also provides continuous data foe analyzing the chance of an attack on a patient. We all know that the paralysis condition is a loss of muscle function in the body parts. These people in most cases are not able to convey their needs as they are neither able to speak properly nor do they convey through sign language due to loss in motor control by their brain. so, to overcome such type of difficulties we come up with the system that help disable person in displaying a massage over the LED by just simple motion of his hand or any part of his body which has motion ability. The user just needs to tilt a device in particular angle to convey a massage. Tilting a device in different direction convey different massage. In this way the automated paralysis patient care system truly automates the care taking ability of the patient which ensure a timely attention to the patient and thus for a good health of the patient.

Generator’s Fuel and Battery Levels Monitoring in Base Station Cell Sites Using IoT-Based Technology with SMS Alerts: A NEXTTEL Cameroon Perspective

Authors- Kometa Denis Mbowoh, Vamobi Eric Bewor

Abstract- In striving to improve the cost-effective management of Telecommunication Network Cell Sites, leveraging novel technologies like IoT-Based technologies becomes an absolute necessity. These cellular networks cell sites require power to function. Due to power insufficiency in Cameroon, the power requirements of each cell site are met by the electrical power generators installed there. Fuel and battery levels of a generator installed in every cell site are manually checked by the site operators, and this approach is ineffective. There have been cases where sites have been claimed to have been shut down for hours due to the site operators’ negligence and unethical behaviour, causing a significant loss to Nexttel Cameroon. Our proposed system is made up of both hardware and software created to address the serious problem of fuel theft and the site operators’ irresponsible and unprofessional behaviours. A fuel level sensor, battery sensor, microcontroller, GSM module, power supply, and other components make up the hardware portion, whilst the receiving section is made up of the site operator’s mobile phone and a personal computer. The algorithm and C-coded program are both included in the software component. The system was carefully designed and tested; obtained results demonstrate that the system perfectly monitors the level of the fuel and the battery health of the generators in the targeted cell site and would lower the cost of maintaining cell sites, boost availability, and enable remote monitoring and alerting of the generators powering the base stations.

Speech Emotion Recognition using Deep Learning

Authors- Huzaif Ahmed Shariff, Karthik R, Lavanya S, Keerthana Patel K N, Madhushree R

Abstract- Speech emotion recognition is a tremendously fascinating but also very difficult problem in human-computer interaction. This subject has attracted a lot of interest recently. Many methods have been used in the field of speech emotion recognition to extract emotions from signals, including a number of well-known speech analysis and classification methods. This work provides an overview of the deep learning technique, which is based on feature extraction, model creation and recognizes the emotion in the speech where input as features that are extracted from the speech signals, selected, and then the emotions are recognized in the traditional way of speech emotion recognition, which is a very laborious and time-consuming process.

Comparative Analysis of Geojute and Geo-Textile Compressive Strength

Authors- Arpan Gupta, Prof. Vinay deulakar

Abstract- The existing soil at a particular location may not be suitable for the construction due to poor bearing capacity and higher compressibility. Particularly clays exhibit generally undesirable engineering properties. They tend to have low shear strengths and also loose shear strength further upon wetting or other physical disturbances. The improvement of soil at a site is indispensable due to rising cost of the land, and huge demand for high rise buildings. So recent research could be beneficial in finding the different ways of utilizing waste materials in most efficient ways like rice husk ash, fly ash, used tyres, etc. So replacement of natural soils aggregates and cement with solid industrial by-product is highly desirable.

Medical Insurance Cost Prediction Using Machine Learning

Authors- Asst. Prof. Ms. Madhuri Thorat, Mohasin Patel, Yog Kute, Muskan Sharma, Shweta Bhosale

Abstract- A policy that helps to cover all loss or lessen loss in terms of costs brought on by various hazards is insurance. The price of insurance is influenced by a number of factors. The expression of the cost of an insurance policy is influenced by these considerations of many aspects. The insurance industry can use machine learning (ML) to improve the efficiency of insurance. Machine learning (ML) is a well-known research field in the fields of computational and applied mathematics. When it comes to utilizing historical data, ML is one of the computational intelligence components that may be addressed in a variety of applications and systems. ML has several restrictions, so; In the healthcare sector, predicting medical insurance costs using ML techniques is still a challenge, so this paper offers a computational intelligence method for forecasting healthcare insurance expenses using machine learning algorithms. Linear regression, Decision Tree regression, Gradient boosting regression, and streamlet are all used in the proposed study methodology. For the goal of cost prediction, we used a medical insurance cost dataset that we downloaded from the KAGGLE repository.

TRA-BOT: An Intelligent Traffic Monitoring System

Authors- Sankeeth Kurian, Sneha B Nair, Merlin Mariyam Reji, Gayathri M Nair

Abstract- – Traffic congestion occurs due to many factors, including traffic violations, unforeseen accidents, and unbalanced traffic flow. Our proposed system detects road accidents, traffic violations, and traffic flow based on density through the use of image processing and AI-ML-DL techniques. Road accidents are one of the major concerns in traffic safety because the number of vehicles on the roads is increasing day by day, despite the use of traditional traffic management. A lot of valuable lives are being lost because of these accidents where immediate, necessary services are unavailable. Our system can detect these accidents and alert the necessary authorities in time. Here, video footage of an accident is being sent to the police and hospital authorities. For that, we have developed a web page using Django and Python programming to send the video footage to the corresponding login credentials of both the police and the hospital. The decision to be taken by them can be either accepted or rejected. Perhaps due to the inaccuracies of the trained dataset, the decision can be rejected. This is implemented as one of the intelligence parts of the project. Along with that, for the accident prediction system, we developed the intelligence part of traffic violations (over-speed detection) and traffic flow based on density detection based on the given dataset (also made as real- time using laptop and its front camera) as two separate modules that predict the occurrence of any accident. Thereby, it also provides an alert SMS to the control room of the police authority if any traffic violation or high traffic density is found, so that they can take actions or precautions to prevent the occurrence of an accident. The intelligence part of accident detection is implemented as a hardware part using a Raspberry Pi (4GB) and R-Pi camera, thereby making it real-time.

Smart Attendance System Using Face Recognition

Authors- Ankit Kumar, Ashish Shukla, Shiva Singh, Shubham Sinha

Abstract- – In the digital age, face recognition technologies are employed in almost every business. Systems for face recognition can also be used in businesses, organizations, and educational institutions to monitor attendance. This system aims to develop a facial recognition-based class attendance system because the current manual attendance system is challenging to maintain. The option of proxy attendance is also present. As a result, this system is increasingly in demand. The four processes of this system are database creation, face detection, face recognition, and attendance updating. The database is created using images of the students in the class. The live streaming video from the classroom reveals and identifies faces. The attendance will be saved in a Database or as a file Attendance.CSV as well we can use Excel sheet.

Facial Expression Recognition using Facial Movement Features

Authors- Dr.M.Praneesh, M.Selva Kumar, B.Udaya Kumar

Abstract- – Facial expression is an important channel for human communication and can be applied in many real applications. One critical step for facial expression recognition (FER) is to accurately extract emotional features. Current approaches on FER in static images have not fully considered and utilized the features of facial element and muscle movements, which represent static and dynamic, as well as geometric and appearance characteristics of facial expressions. This paper proposes an approach to solve this limitation using ‘salient’ distance features, which are obtained by extracting patch-based 3D Gabor features, selecting the ‘salient’ patches, and performing patch matching operations. The experimental results demonstrate high correct recognition rate (CRR), significant performance improvements due to the consideration of facial element and muscle movements, promising results under face registration errors, and fast processing time. The comparison with the state-of-the-art performance confirms that the proposed approach achieves the highest CRR on the JAFFE database and is among the top performers on the Cohn-Kanade (CK) database.

Design and Implementation of Orthogonal Matching Pursuit

Authors- Research Scholar Rukmini Kumari, Associate Prof. & HOD Dr. Bharti Chourasia

Abstract- – Orthogonal Matching Pursuit (OMP) is a widely used algorithm for sparse signal recovery. It is an iterative algorithm that solves the problem of finding the sparsest solution of an underdetermined linear system. OMP provides an efficient and effective way to find the sparsest solution of an underdetermined linear system by iteratively selecting the most correlated columns of a dictionary matrix that are most likely to contribute to the sparse solution. This paper presents the study of VLSI implementation of the Orthogonal Matching Pursuit (OMP) for high speed FPGA Application. Simulation is performed using the Xilinx 14.7 software.

Study of Academic Procrastination among Adolescents in Relation to Anxiety

Authors- Assistant Professor Dr. Navkiran Kaur

Abstract- – The present study analyses the relationship between academic procrastination and anxiety of 10th class adolescents. The total sample of 100 adolescents of senior secondary schools of Moga district was taken. Sample was collected through random sampling technique. The study test of academic procrastination by Dr. Ashok K Kalia and Manju Yadav (2013)and anxiety scale by Sinha’s Comprehensive Anxiety Test by (2000) were administered. The major findings of the study revealed that there exists no significant difference between academic procrastination and anxiety among adolescents and there exist significant relationships between academic procrastination and anxiety among adolescents.

Skill Based Job Recommendation System

Authors- Mansi Vinayak Makhi, Pooja Dhumal, Urmila Jagdhane, Shruti Mane

Abstract- – Data science’s subfield of machine learning focuses on creating algorithms that can learn from and make predictions based on the data. By suggesting jobs based on a candidate’s skill set, recommender systems can be extremely useful in helping college graduates realize their career goals. There are many websites today that offer a ton of information on work opportunities, but this chore is very time consuming for students because they must sift through a lot of material to find the appropriate job. And many students are unaware of the types of jobs that would be best for them. These days, the Technology industries are booming. This study looks at the users resume, compares the degree knowledge, soft skills, hard skills, and projects he has completed, and only then does the system suggest jobs for that user.

Seismic Analysis of RCC Building with or Without Floating Column

Authors- M.Tech. Scholar Anupam Soni, Prof. Rakesh Sakale

Abstract- – The growth in population, there is a rising problem with space in metropolitan areas in the contemporary day. This creates a demand for a column-free area that can improve the aesthetics and other functional needs. The floating columns are put on hold as a result of this novel idea. Modern multi-story construction practice are common around the world, including in contemporary urban India, and feature buildings with floating columns. Buildings with unusual elements, like floating columns, need a considerably more technical work in the structural design, yet they may not be as excellent as ones with straightforward architectural aspects. In this study seismic analysis of RCC building with or without floating column has been done.

Use of Fly Ash and E-Waste in Partial Replacement of Cement

Authors- M.Tech. Scholar Rahul Faraiya, Prof. Sanjeev Agrawal

Abstract- – Concrete is one of the most popular building materials available. Dams, bridges, skyscrapers, sewage and water systems, and public buildings—all of these and more are shaped by the design and construction of concrete. Fly ash, with its round, smooth particles, enhances workability right out of the gate. “The improved workability allows for a lower water-to-cement ratio, which in turn leads to increased compressive strength. Utilizing industrial and agricultural waste resources is crucial for achieving sustainable growth and producing a greener concrete material in the building sector. There are a variety of factors contributing to the unsustainable nature of today’s concrete construction market. Therefore, in this study an experimental analysis on the use of fly ash and e-waste in partial replacement of cement has been done.

Design and Analysis of Tornado Strainer

Authors- Associate Prof. Dr.C.Nithyanandam, Prof. Dr.K.Siva, R.Sakthi, S. Sanjai

Abstract- – Industry equipment used to split gas and solids usually includes fuel-solids tornado strainer. The writing has introduced computational examinations due to their modern-day importance. Through reading variations in pressure and speed, these research intention to understand tornado overall performance and make predictions approximately it. Computational fluid dynamics (CFD) is castoff to put on tornado gas movement and element gesture. A typhoon screen became utilized in this overview to gather dirt. Dust debris is separated from an air movement by using the tornado strainer. The duct series box turned into wherein that debris settled at the lowest of the tornado. The typhoon strainer mathematical boundary has been deliberate in mild of the contemporary trendy tornado plan gadget. The tornado strainer makes use of seven geometrical parameters: gulf level, delta width, outlet size, cone-tip breadth, general length, body stage, and tornado frame distance across. As according to those plan boundaries, a robust model has been made. Moreover, tornado strainer series performance has been predicted the usage of the computational fluid dynamics technique for a variety of dirt particle sizes. Stress and speed contours have been developed on the premise of this simulation. Strain drop and proficiency outcomes are contrasted and the outcomes.

Use of Machine Learning Algorithms for Detecting Crop Disease

Authors- Sanskruti Magdum, Chaitanya Vibhute, Mr. Amol Rindhe

Abstract- – Crop pests are a significant agricultural issue because of how seriously and widely they damage crop productivity. Over the greater area of the farm, manual disease detection requires more time and effort. In order to avoid yield losses, it’s critical to identify plant illnesses. It requires a significant amount of labor, knowledge of plant diseases, and a lengthy amount of time. Since agriculture is so many people’s primary occupation in India, illness detection in the fields is a significant concern. Finding effective ways to combat those while reducing the usage of pesticides is therefore necessary. In this project, we’ve outlined a method for spotting plant diseases using pictures. Better crop management and productivity are produced using ML- Neural Network approaches. Even though these diseases still require manual monitoring, improvements in automatic monitoring have reduced the requirement for physical labor and human error. Hence, the suggested system offers a straightforward, effective, and quick method of identifying pests in rice fields.

Design and Analysis of Tornado Strainer

Authors- Associate Prof. Dr.C.Nithyanandam, Prof. Dr.K.Siva, R.Sakthi, S. Sanjai

Skill Based Job Recommendation System

Authors- Mansi Vinayak Makhi, Pooja Dhumal, Urmila Jagdhane, Shruti Mane

Productivity Forecasting of Employees’ Performance Using Machine Learning & Adaptive Neuro-Fuzzy Inference System

Authors- Abdalrhman Bormah, Osman Taylan,

Abstract- – The productivity of employees has been considered as a crucial factor that threatens/diminishes the company revenues and growth. Investigating the productivity of the workforce of a garment company has been occupying the focus of this research. Moreover, the garments industry is one of the most labor-intensive industries, and studying the actual productivity of employees is an important source for decision-making. Additionally, the productivity of the manpower is associated with influencers such as workload, incentives, overtime, and the capacity of the manpower versus task requirements. Based on theories and experiments, it has been found that employees’ productivity could be affected by those mentioned factors and other variables such as the convenience of the surrounding environments, and workplace layout. Considering the power of artificial intelligence (AI) and machine learning (ML) techniques, starting by examining a set of regression algorithms, linear regression (LR), Regression Trees (RT), Support Vector Machines (SVM), Gaussian Processes Regression (GPR), and Ensemble of Trees Regression (ET) methods are used to predict the employees’ productivity. Also, artificial neural networks (ANNs) are employed with a couple of training algorithms which are Levenberg-Marquardt (LM) & Bayesian Regularization (BR). The last application is the adaptive neuro-fuzzy inference system (ANFIS) via Hybrid and Backpropagation optimization. All the above models are studied to configure the impact of six independent predictors on productivity. In conclusion, medium regression trees give the RMSE of 0.10926 for training, and R-squared value of 0.69, Exponential Gaussian processes regression 0.10627 for RMSE for the training and 0.6 for R-squared respectively. The ANNs of Bayesian Regularization produced a value of 0.120476814 for RMSE and a value of 0.72248 for R-Squared.

Isolation and Characterization of Microflora from Bluetooth (ear buds) of young students at MIET, Meerut

Authors- Aastha Sharma, Shivani Singh, Muskan Khan, Sakshi Saini, Sonia Sharma, Alka Sagar, Asad Amir

Abstract- – A cell phone is a long-range special telecommunication device, which is most unprecedentedly obligatory accessory of professional and social life all over the world. Blue tooth ear buds are style statement for youngsters as these help in listening music as they are easy to carry and are more likely to stay than wired ear phones. Due to constant use serve as breeding ground for variety of microbes. Therefore, it is interesting to identify these microbes. The present work was designed to isolate and characterize the microbes associated with ear buds of blue tooth devices along with investigating the antibacterial activities of leaf extracts from fruits trees. The leaf extracts from fruit plants were subjected to qualitative phytochemical screening and the agar well diffusion method was used for antibacterial assays. The results of phytochemical tests indicate that all tested crude extracts contained polyphenols, flavonoids, triterpenes, and steroids. Agar well diffusion method has been used to determine the antimicrobial activities and minimum inhibitory concentrations (MIC) of different plant extracts against Gram-positive bacteria, Gram-negative bacteria and one fungus isolated from ear buds of Bluetooth devices. The extracts exhibited both antibacterial and antifungal activities against tested microorganisms. The litchi leaf extract showed significant antibacterial activity 0.18mm against all tested bacterial strains with inhibition zones ranging from 25.2 ± 1.4 to 15.8 ± 1.2 mm, respectively among all tested plant extracts. The results indicated that the plant extracts significantly affected the cell membrane of Gram-positive and Gram-negative bacteria. In conclusion, plant extracts are of great value as natural antimicrobials and can be a potential source of disinfectants.

Offline Handwriting Recognition Using HDARnet

Authors- Jenifa Mary S, Roopa M, Shailaja R, Yogeshwari R, Dr. L. R. Sudha

Abstract- — This paper deals with recognizing the alphabets and digits from handwritten characters using a newly proposed deep learning model HDARnet. There are many areas where we need to recognize the words, alphabets and digits like postal address, and bank cheques. The advantage of offline recognition is that it can be done at any time after the document has been written, even years later. Although many techniques have been proposed, it is still a challenging research problem due to the variance in the styles of handwriting and ambiguity of strokes from person to person. Our model contains a fine-tuned four layered CNN in which sub-sampling layer is removed and included batch normalization after every convolution layer. The proposed model was evaluated by training and testing with EMNIST (Extended Modified National Institute of Standards and Technology) dataset which is the largest open-source dataset widely used by researchers for handwritten digits and alphabets recognition. It contains 6,97,932 training and 1,16,323 validation images of size 28×28. The efficiency of the proposed model is assessed with the performance measure accuracy. The obtained result shows that the HDARnet is superior to the systems employing conventional three-layer CNN.

Bidirectional Single Power Converter Using Low Battery Voltage

Authors- PG Scholar Durgesh Kumar Vishwakarma, Asst. Prof. Abhijeet Patil, Asst. Prof. Vivek Yadav

Abstract- – This paper present an improved bidirectional grid-associated single-power-conversion converter brings about high power quality and high efficiency. Simulation is done using MATLAB Simulink software. Simulated results show significant improvement than existing.

Bidirectional Single Power Converter Using Low Battery Voltage

Authors- PG Scholar Durgesh Kumar Vishwakarma, Asst. Prof. Abhijeet Patil, Asst. Prof. Vivek Yadav

Smart Energy Meter and Billing System using IoT

Authors- M.Srinivas

Abstract- – It is a difficult job for the electricity board officials to manually take meter readings and calculate bill as it is time consuming and requires manpower. Billing consumers for energy consumption is not uniform. It is a tedious job for the electricity board official to manually go and take meter readings of big industrialists and reset their maximum demand after recording it. Even the latest energy meter is not tampering proof. Hence considering all these factors it is possible to design an energy meter that is tamper proof, supports automatic metering and billing system , and at the same time helps in finding the fault location of transmission lines. The same meter can be used to take the readings of industrialist which sends these readings to a secured data location and automatically reset it after recording it. Considering all these features that can be done by a single energy meter it is called a SMART ENERGY METER.

Revolutionizing Education: Harnessing The Power
Of Vr And Ai For Enhanced Student Engagement

Authors- Anvar Sadath A K

Abstract- – This research proposal aims to explore the integration of virtual reality (VR) technologies with artificial intelligence (AI) algorithms in education to create immersive educational experiences that simulate real-world scenarios and enhance student engagement. The objectives of this research include assessing the current state of VR and AI technologies in education, investigating the impact of integrating VR with AI on student engagement and learning outcomes, exploring the effectiveness of simulating real-world scenarios using VR and AI in promoting critical thinking skills, identifying challenges and limitations in implementing VR and AI in education, and providing recommendations and guidelines for effective integration. The methodology involves conducting a literature review to examine existing research, designing and developing a prototype educational VR application with AI algorithms, conducting a quantitative experimental study to measure student engagement, learning outcomes, and critical thinking skills, analyzing the data using statistical methods, conducting qualitative analysis through interviews or focus groups, and ensuring ethical considerations. The expected outcomes include an assessment of the impact of VR and AI integration, identification of challenges and limitations, and the provision of guidelines for effective integration. The research will be conducted over a 12-month timeline, including literature review, design and development, experimental study, data analysis, qualitative analysis, and compilation of research findings. The findings of this research will contribute to understanding the effective utilization of VR and AI in education, benefiting educators, policymakers, and researchers in enhancing teaching and learning practices.

The Cameroon Anglophone Crisis in the Wake of Covid 19 Pandemic: Reflections beyond the Ceasefire

Authors- PhD Di (Fh) Di Günther Maier, PhD Augustin Nguh

Abstract- – When the United Nations Secretary General Antonio Guterres proposed a “global ceasefire” on the 23 March 2020; his appeal received mixed reactions from various warring parties across the world. Citing the “fury of the virus” Guterres’ request had significant ramification on the perception of contemporary conflicts with the question of public health becoming an important rallying call for cessation of hostilities. This paper seeks to examine the relationship between conflict, conflict management and public health. It specifically looks at the Anglophone crisis in Cameroon as a case study given the Southern Cameroons Defense Forces (SOCADEF) were among the first armed groups to agree to the call for a global ceasefire. The paper interrogates how historical grievances and challenges of public health among the Anglophone Cameroonians combined with the nature of the ongoing conflict has left the region and its residents in a potentially vulnerable position while experiencing the pandemic. The authors question whether stopping violence without adopting other measures to cover for the unique socio -political, economic, and public health challenges in the separatist -controlled regions as well as Cameron as a whole will be an effective means of dealing with the current pandemic in the West African nation. The study thus concludes with a set of recommendations that address the gaps in the existing linear approach to confronting COVID 19 in regions experiencing conflicts.

Review on Event Management App for College

Authors- Mansi Maurya, Saket Lokhande, Vinod Patil, Sanket Kedar,Prof. Mrs. Manisha Patil

Abstract- – This program provides a fix for typical issues that arise during college events and activities. Poor outreach causes many events to go undetected, which lowers attendance. Students could also be ignorant of historical occurrences. Teachers and planners find it difficult to maintain track of attendance and certificate distribution as a result, which presents a hurdle. By alerting students in real-time about future events, webinars, and club activities, the program resolves these problems. Additionally, it provides a thorough account of all previous activities, making it simpler for pupils to make up for lost chances. The tool makes managing attendance easier by enabling instructors and planners to keep track of attendance electronically. This decreases the possibility of mistakes and eliminates the necessity for human record-keeping. The program also makes it easier to distribute certificates by streamlining and automating the procedure. Overall, this program provides a comprehensive answer to issues that frequently arise during college events and activities. It offers a user-friendly interface that makes managing and taking part in events simple for educators, students, and event organizers. Keywords: Android Application, Android Studio, Event Management, Firebase.

Performance Analysis of SLL reduction for Wireless Smart Antenna Systems Using Genetic Algorithms

Authors- Rani Yadav, Piyush Moghe, Tamashri Dharsiya

Abstract- – The demand for wireless communications constantly grows the need arises for better coverage, improved capacity, and higher transmission quality. Thus, a more efficient use of the radio spectrum is required. Smart antenna systems are capable of efficiently utilizing the radio spectrum and promise an effective solution to the present wireless system problems while achieving reliable and robust high speed high-data-rate transmission. Smart antennas dynamically adapt to changing traffic requirements whose adaptive beam forming approach can be studied with the help of different adaptive algorithms. The fundamental idea behind smart antennas is to improve the performance of the wireless communication system by increasing the gain in a chosen direction. This can be achieved by pointing the main lobes of the antenna-beam patterns towards the desired users. Smart antenna system combines multiple antenna elements with a signal processing capability to automatically optimize its radiation and/or reception pattern in response to the signal environment. In this paper proposed a very simple and powerful method for the synthesis of linear array antenna. This method reduced the desired level of side lobe level (SLL) as well as to steer the main beam at different-different angle. Anew method for adaptive beam forming for a linear antenna arrays using genetic algorithm (GA) are also proposed. Genetic Algorithm is an iterative stochastic optimizer that works on the concept of survival of the population values based on the fitness value. An adaptive genetic algorithm has been used in linear array to optimize the excitation levels of the elements resulting in a radiation pattern with minimum side lobe level. These algorithm can determinate the various values of side lobe level and phase excitation for each antenna to steer the main beam in specific directio.

Climate Change And Sustainable Design Strategies In School Buildings

Authors- Chime, CharlesC1.,Ojeah Ijeoma2

Abstract- – One of the most significant challenges of improving sustainability at the global level is the management of climate change and the reduction of greenhouse gas emissions. Climate change poses one of the most substantial threats to humanity, and global greenhouse gas emissions has led to severe global warming effect, which causes heat waves, increase of hurricanes, reduction of the ice surface, coastal invasions, loss of biodiversity, and loss of drinking water. Due to climate change, the rise in global temperature causes an increased need for coolingto satisfy occupants’ thermal comfort. To address this issue, several definitions of climate change and adoption of sustainable development for the construction industry have been developed to minimize the impact of building construction on the environment and climate. In this regard, application of sustainabledesign strategies, based on the local climate to achieve active cooling measuresto decrease the conventional cooling need and ensure thermal comfort are, thus, becoming highlyrelevant and vitally important. This research focuses on specific aspects of building as a measure to reduce the effect of climate change through sustainable design strategies and the investigation were carried out by physical measurement and readings were recorded with Data logger (TA298).The result shows that indoor climatic conditions in building were influenced by local climate and sustainable design variables. Recommendations were made to adopt and promote sustainable architectural design strategies in the new design or renovation of building projects in order to reducing greenhouse gas emissions and satisfy the cooling need of occupants’ in buildings located in warm humid climate zone of Nigeria.

A Review on Analysis and Design of Code Exceeding Structures Using is 16700

Authors- M.Tech. Scholar Hitesh Dhuware, Dr. Rakesh Patel

Abstract- – Due to population growth and limited available space in cities, the construction of tall buildings has become a necessity. When designing tall buildings, the focus is often on achieving the required stiffness rather than just strength. Proper selection of the structural system and design is crucial to ensure sufficient lateral stiffness, as tall buildings are primarily affected by lateral loads such as wind and seismic forces. Various factors, including building height, plan aspect ratio, slenderness ratio, geometry, and damping, influence the behavior of high-rise buildings and must be considered during the design process. Analyzing the wind loads and structural behavior of tall buildings can be challenging, especially when dealing with unique aerodynamic shapes or flexible buildings that are prone to motion-induced forces. Different countries develop their own codes and standards for the analysis and design of tall buildings. In India, high-rise constructions have been carried out according to various Indian standards and building codes. However, the existing codes and standards may not adequately address all the specific challenges associated with tall buildings. To address this gap, a new code called IS 16700-2017 “Criteria for Structural Safety of Tall Concrete Buildings” has recently been introduced in India.

A Review on Analysis and Design of Code Exceeding Structures Using is 16700

Authors- M.Tech. Scholar Hitesh Dhuware, Dr. Rakesh Patel

A Comprehensive Analysis of PID Based Electric Vehicle Model Design in Matlab 2015 Software

Authors- Sabeer Pinjari, Prof. Madhu Upadhyay

Abstract- – For the problem of pure electric vehicle drive control, a speed-current double closed loop control strategy was proposed by using the PID theory, and the vehicle simulation model was established in Matlab/Simscape. The performance of the drive control strategy was verified by starting operation condition and NEDC cycle in the simulation model. Simulation results show that the pure electric vehicle drive control strategy based on the adaptive PID can execute the driving instructions quickly and accurately and the vehicle can operate stably without static speed error, so the control strategy can improve the vehicle driving performance effectively.

Study of Effects of Copper Slag and Kota Stone Dust in Concrete

Authors- Chanda Chouhan, Pawan Dubey, Rakesh Sakale

Abstract- -This experimental study investigates the physical properties and effects of copper slag and Kota stone dust in concrete. The objective is to assess the feasibility of utilizing these industrial by-products as partial replacements for traditional construction materials in concrete mixtures. The study explores the potential benefits and drawbacks associated with incorporating copper slag and Kota stone dust in terms of the resulting physical and mechanical properties and performance of concrete. The experimental program involves the preparation of concrete specimens with varying proportions of copper slag and Kota stone dust as replacement materials for fine aggregates and cement, respectively. The physical properties of the resulting concrete mixtures, such as compressive strength, tensile strength, Flexural strength and permeability, are evaluated through a series of standardized tests. The findings reveal that the addition of copper slag and Kota stone dust affects the fresh and hardened properties of concrete. The results indicate that the incorporation of copper slag improves certain aspects of concrete, such as enhanced workability and increased compressive strength.

Analysis of Motor Imagery EEG Classification Based on Neural Network

Authors- M. Tech. Scholar Amitesh Raj, Prof. & HOD. Dr Bharti Chourasia

Abstract- -This paper proposed the neural network-based classification algorithms for the prediction of EEG signals bands. The neural network algorithm is a variant of a multilayer neural network for the extraction of features used discrete wavelet transform function. The discrete wavelet transform function decomposed the electroencephalogram signal in different sub-bands for the processing. They represent bands into varied frequency range. The proposed algorithms are simulated in MATLAB software and used the standard dataset of BCI competition-IV dataset for the analysis of performance. The proposed algorithm compares with machine learning classifiers for disease detection. The performance of the proposed algorithms improved the efficiency of the brain-computer interface system.

Research on the start-up process of steam turbine in a thermal power plant in Viet Nam

Authors- HS Bui,TH Bui

Abstract- -Steam turbine is a very important equipment in a thermal power plant, but it has a very complicated structure as well as a very thorough and meticulous operation according to a rigorous process. The steam turbine shall be started according to the procedure in the manual given by the turbine manufacturer. The manual describes the order of steps to be performed and provides the values of the parameters that need to be maintained during turbine start-up.The paper describes the starting process of steam turbines and the current starting method of steam turbines in power plants in Vietnam thereby building an optimal start-up one.

Integrating Block chain Technology in Various
IoT Applications

Authors- Tammina Dharanidhara Chowdary, Darapu Karthik, D Sri Krishna Sai Pavan Srikar, Dr. T. Venkat Narayana Rao

Abstract- -Two distinct types of ever-evolving computing networks have contributed to the development of the Internet over the past few years: Internet of Things and Blockchain Technology. The Internet of Things is a collection of various digital devices with sensors and software for a wide range of monitoring and analysis tasks. A specialized data storage system called a blockchain ledger is used to keep track of “well-formed” digital transactions. A distributed network of computing nodes is a blockchain network. A strength of a blockchain network is that each node should have its own copy of the ledger and participate in validating transactions. Education, health care, finance, agriculture, industry, and the environment are just a few of the industries that stand to gain from integrating blockchain technology and the Internet of Things. Scaling, interoperability, and security goals are complicated by IoT technologies’ diverse, complex, dynamic, and heterogeneous computing and communication requirements, which can be optimized and enhanced by blockchain technologies. Numerous blockchain and Internet of Things (IoT) network coordination models have recently been proposed, evaluated, and presented to businesses. The Internet of Things (IoT) and Blockchain technology have been the subject of numerous studies. Notwithstanding, a more top to bottom assessment uncovers that not many applications effectively meet the security prerequisites of an association. Naturally, combining block chain technology with an existing Internet of Things (IoT) that can satisfy an organization’s security requirements is not a good idea. In this article, we look at various IoT operations frameworks, how they work with blockchain technology, and the most important security considerations security personnel need to keep in mind when IoT and BCN are used.

Implementation of Virtual Reality Using Smart Technology

Authors- M Sindhu, CH Sai Nidhi, T Thirupathi Rao, Asst. Prof. Mr. Theegala Thukaram Goud

Abstract- -Immersive films, 360-degree videos, or spherical movies are produced using a panorama that concurrently records in every direction. Within this innovative piece of teaching, we evaluate the efficiency of 360-degree video use in instruction. To help students connect course material to real-world experiences, we use a variety of learning activities. The pedagogic order for each exercise was prepared by the students as they watched 360-degree videos with virtual reality headsets in class. We gauge the extent to which students find this cutting-edge didactic material useful as a teaching tool. Those who used the 360-degree videos fully immersive features and those that were shot in situations similar to their professional environment learned more about their field overall. They gain a stronger sense of location, positive affection, and a greater enjoyment of the subject matter addressed in the 360-degree movie, all of which will benefit them in the future professional lives. As an outcome of the experiment, we draw the conclusion that 360-degree videos are highly beneficial in teaching and that their use will be a significant trend in the years to come.

Implementation of Weather Monitoring Station Using Raspberry PI

Authors- B. Mukesh, B. Sai Teja, Asst. Prof. K. Siva Kumar Gowda

Abstract- -This paper focuses on how important weather monitoring stations are to our daily life and other activities. For farmers and coastal communities who depend on weather forecasts to schedule their activities and get ready for disasters like cyclones, it emphasizes the need of having advance weather knowledge. In this study, we investigate the operation of a weather station powered by a Raspberry Pi, a tiny credit card-sized computer that connects to a computer or television and is controlled by a keyboard and mouse. With the use of the Raspberry Pi, a data processing and forecasting tool, we are able to predict important meteorological factors including humidity, temperature, soil moisture, and rain detection. The study aims to demonstrate the capabilities of the Raspberry Pi and how it makes effective data collection and analysis possible. And the collected data is moved to the cloud with the use of Thing Speak.

An Overview of Techniques for Enhancing Energy Efficiency in (WSN) Wireless Sensor Networks

Authors- M. Tech. Scholar Varsha Baghel, Assistant Professor Mahendra Choudhary

Abstract- -This study addresses the persistent challenge of placing sensor nodes in remote locations, which significantly impacts their lifespan due to reliance on battery power. Factors such as continuous monitoring, periodic control messages, and frequency of occurrences have substantial implications for sensor node longevity. To address this issue, a comprehensive literature review is conducted to explore energy efficiency methods employed in prior studies aimed at extending the lifespan of wireless sensor networks.

An E-Voting System Based on Blockchain Technology

Authors- Banavath Prashanth, Medipally Shravya, Asst. Prof. S.Bhavana

Abstract- – Internet voting is becoming more popular because it can save money and make it easier for people to vote. Instead of using paper ballots or going to a polling station, people can vote online from anywhere with an internet connection. However, some people are worried about the risks of online voting. If there is a problem, it could affect a lot of votes. To make online voting safe and reliable, blockchain technology is being used. This technology helps protect votes and make sure they are counted correctly. This article explains how blockchain can be used for online voting and what challenges still need to be solved. Overall, using blockchain for voting could help solve some of the problems we have with elections, but there are still some issues that need to be addressed.

Empirical Study of Newton’s Law of Cooling by Aboodh Transform

Authors- Prof. Dr. Dinesh Verma , Principal Dr. Khoob Singh , Asst. Prof. Dr. Amit Pal Singh

Abstract- -Newton’s Law of cooling explains the rate of cooling of a body. The rate at which an object cools down is directly proportional to the temperature difference between the object and its surroundings. Newton’s Law of cooling are generally analyzed by adopting Laplace transform method. The paper inquires the Newton’s Law of cooling by Aboodh transform technique. The purpose of paper is to prove the applicability of Aboodh transform to analyze Newton’s Law of cooling.

Design and Performance Analysis of Floating Point Multiplier Using Karatsuba Algorithm for Different Bit Lenghts

Authors- M. Tech. Scholar Manish Kumar, Prof. & HOD Dr. Bharti Chourasia

Abstract- -Multiplication is one of the most important operations in computer arithmetic. Division, squaring, and computing reciprocal are only a few of the many operations that use multiplication. Additionally, the utilization of digital signal processing applications including correlation, filtering, frequency analysis, and image processing makes multiplication efficiency vital. In order to make multiplication simpler, algorithms were created to increase efficiency and decrease cost. The effectiveness of the Karatsuba algorithm is examined in this paper in terms of the quantity of multiplication and the overall processing time for various bit lengths. As we all know, algorithms comprise a series of steps/instructions, devised to solve a computational problem. VHDL software is used for simulation of implemented proposed algorithm.

A Comprehensive Observation Wireless Sensor Networks

Authors- Kartar Yadav, Asst. professor Amit Thakur

Abstract- -Wireless sensor networks (WSNs) have gained a substantial attention in wireless research community as these networks are envisioned to support a large number of practical applications. Due to salient features of sensor networks, the security design for WSN is significantly challenging. Despite a good number of available surveys on this particular topic, we feel that there is a gap in the existing literature in terms of timeliness, emphasis, and comprehensiveness. This paper reviews the state-of-the-art for secure WSN routing protocols that illustrates the issues and challenges in the context design matters. Further, we propose the schematic taxonomy of key design issues for WSN routing protocols. We also define design factors categorization relevant to secure routing: basic, essential, and optional. The similarities and differences of secure routing approaches are summarized on the basis of key design attributes, security objectives, and attacks prevention. Finally, we outline possible future research trends on secure routing design in WSN.

Antenna Analysis and Its Performance Evaluation

Authors- Aditya Gupta, Asst Professor Ashish Suryavanshi

Abstract- -The micro-strip patch antennas has advantages over conventional antenna because of this is it widely used in conformal, compact, and low- cost wireless applications. The literature survey of last decades of micro-strip patch antenna demonstrates that the different method is used to plan a small size micro-strip patch antenna. In this manuscript a review is conducted on different antenna designing techniques like, Fractal geometry, slot cutting, G shapes, edge tapering, and H shape.

Artificial Intelligence and Internet of Things for cyber security and Threat Detection

Authors- Sreeja Voma, Anuragh Kamble, Prof. Dr. Syed Jahangir Badashah

Abstract- -The expansion of Internet of Things (IoT) devices has revolutionized our daily lives, but it has also brought about new cyber security challenges. Traditional security measures are insufficient to cope with the evolving threat landscape. To address these challenges, the integration of Artificial Intelligence (AI) with IoT devices has emerged as a promising solution. This research paper provides an advanced review of the state-of-the-art AI and IoT-based cyber security and threat detection systems. It explores the underlying technologies, recent advancements, practical implementations, challenges, and future directions in this rapidly evolving field.

A Critical Review, Current Challenges, and Future Trends of Next Generation Smart Agriculture using IoT and AI

Authors- Daroju Abhinai Kumar,Eppili Jatin,Sarvade Keerthan, Dr.T.Venkat Narayana Rao

Abstract- -Farmers have recently demonstrated a strong interest in smart agricultural approaches. This is influenced by a number of variables, including the ubiquitous availability of inexpensive, low-powered Internet. Wireless Internet of Things (IoT)-based sensors are used to remotely monitor and report crop, weather, and field conditions. This makes it possible to manage resources effectively, for as by using fewer harmful pesticides and using less water for irrigation. Furthermore, owing to recent advancements in artificial intelligence, farmers may be able to deploy autonomous farming equipment and generate better future projections based on present and prior conditions, which would assist farmers minimize crop diseases and insect infestation. When utilized together, these two enabling technologies have changed traditional farming approaches. This research report offers: (a) A thorough instruction on the smart agricultural developments already available.

Defensive Deep Neural Networks Using De-trigger Auto Encoder to Prevent Backdoor Attacks

Authors- Channam Sai Ganesh, Asst. Prof. Bolla Sujith Kumar

Abstract- A backdoor attack is a method that causes misrecognition in a deep neural network by training it on additional data that have a specific trigger. Training a deep neural network with additional data using a specific trigger results in false positives for backdoor attacks. The network will misrecognizes backdoor samples with triggers as the target class, but correctly recognizes normal samples without specific triggers as the correct class. This article proposes a defense against backdoor attacks using de-triggered auto encoders. A de-trigger auto encoder is used to eliminate triggers in the backdoor samples and alter the classification results to find backdoor samples. Tensor Flow was used as the machine learning library and the experimental datasets were his MNIST, Fashion-MNIST and CIFAR-10.

Prediction and Forecasting Glass Fiber
Performance Using ANOVA Method

Authors- Jeewan Parmar, Prof. Mahroof Ahmed

Abstract- GFRC is a cement matrix made up of cement, sand, water and admixtures, and contains short glass fibers. Facade panels, pipes and channels are examples of non-structural elements that have been extensively used. Light weight (which lowers dead load), fire resistance, an attractive appearance, and tensile strength are just a few of the benefits of GFRC. Trial tests for concrete with and without glass fiber are conducted using cubes, beams, and cylinders to measure the differences in compressive strength, flexural strength, and split tensile strength. Because glass fiber may be molded and sculpted in a number of ways, its demand is growing in India due to rising building activity and other causes. Compared to other reinforcing materials, it is a more affordable and cost-effective solution.

Improving Personalization in Online Marketing through the Usage of Machine Learning

Authors- Kartik Sai Valluru, Muddasani Harshith, Prof. & HOD. Dr. Thota Venkat Narayana Rao

Abstract- The purchase cycle on the internet has expanded dramatically in recent years. Customers spend more time on social media, leading to massive data generation and digital footprints online. The application of machine learning accelerates and simplifies data collecting and processing. According to a recent survey, most selling firms do not effectively target their target market through personalization. This study’s objective is to ascertain how machine learning may be utilized to the challenge of personalized experience in the context of online advertising and what impact that would have on newly emerging businesses. The main motive is to obtain a Literature Review (LR) using large data and machine learning. Prior studies have tried to provide useful recommendations for boosting strategies to personalize in online marketing. The result is that machine learning fastens the marketing process when used with the right objective. This is done so that machine learning can automatically acquire, analyze, and gather data from each user to the best of its ability. As a result, a promotion system that completely meets customer wants is made possible. Overall, the authors’ findings suggest that integrating large data and machine learning might help marketing companies create more efficient personalized marketing tactics so they can pinpoint the right customers. According to the authors, future research on personalization for enterprises should be conducted.

Blockchain Technology Evolutionary Game Analysis Preventing Supply Chain Financial Risks

Authors- T Keerti Chandana, B Adhithi Krishna, Asst. Prof. S.Bhavana

Abstract- An evolutionary game was created to analyze the situations that affect decisions of financial products while calculating the profit of the business based on risk in the financial chain. By contrasting changes in security policies before and after the introduction of blockchain technology, a sample of small and medium-sized businesses and financial institutions examines blockchain solutions for resolving financial concerns. This article examines how blockchain technology is used in financial products with the goal of lowering financial risks. The study discovered that, above all, blockchain technology may reduce financial organizations’ risk and alleviate financial problems. A financial institution’s decision to approve an investment transaction is heavily influenced by credit risk. Financial institutions’ operational risk can be decreased, and using blockchain technology can boost revenue. Second, traditional firms and small and medium-sized enterprises are at risk of financial difficulties due to the tight regulatory framework generated by blockchain technology. Even while small and medium-sized businesses might gain a lot from integration, they won’t choose failure. The drawbacks of micro and medium-sized businesses not receiving loans from financial institutions even though they meet the standards are eliminated by doing this. This will result in a more balanced relationship between financial institutions and SMEs. Financial institutions will accept applicants for jobs, SMEs will honour agreements, and there will be more effective wealth distribution. As a result, blockchain technology not only lowers the financial risk for financial institutions but also aids in resolving small and medium-sized businesses’ financial issues.

Smart Attendance System Using IOT

Authors- Arruri Bharath, Attem Varun Yadav, Asst. Prof. Ms. P. Sandhya Priyanka

Abstract- In many of the organizations and educational institutions now-a-days to keep a track of the employees and the students about their attendance, many applications have been in the existence. Few of them include the biometric which is implemented by making use of the sensor technology. The Smart Attendance System is the one which make use of the Internet of Things with the latest technology implemented through –Raspeberry Pi, Pip installer, Face Net. The image processing method is the foundation of this project Smart Attendance Using IOT. The idea of our venture is to give ongoing participation of understudies in the class to the faculty information base. In this case, we are going to process the image with a camera that is exactly on top of the class entrance. This camera will catch picture of its close by encompassing and just identify the facial piece of that specific picture and send this picture data to our handling frameworks. The entire work is done using the PYTHON scripting. Presently according to the calculation which we are utilizing for picture handling and location, this caught picture will go through different separating and covering methods to get the de sired reasonable picture design. After that, our algorithm will compare the input image to the reference points to find the desired image. It will then eventually find the student and send the student’s attendance via IOT to the faculty database.

Medication Of Genes Using DNA Sequence With Machine Learning

Authors- Kunal Verma, Prof. Mahroof Ahmed

Abstract- Due to ever increasing quantities of waste substances and industrial byproducts, strong waste management is the high concern in the world. Scarcity of land-filling house and because of its ever growing cost, recycling and utilization of industrial by-products and waste substances has turned out to be an pleasing proposition to disposal. One such industrial spinoff is Waste Foundry Sand (WFS). WFS is important byproduct of metal casting enterprise and effectively used as a land filling fabric for many years. In this work compare to normal and WFS compressive strength. With found its properties based case study.

Medication Of Genes Using DNA Sequence With Machine Learning

Authors- Dr. Mahesh Gowda N M , Sindhu V , Sushmitha S , T Rukmini ,Varshini M C

Abstract- The field of personalized medicine has gained significant momentum in recent years, aiming to provide tailored treatment plans for individuals based on their unique genetic makeup. In this paper, we propose a novel approach for medication recommendation using DNA-based information and machine learning techniques. Our study leverages the vast amount of genomic data available and employs advanced algorithms to identify genetic markers that can predict an individual’s response to specific medications. By analyzing DNA sequences and incorporating relevant clinical data, our model aims to accurately predict the efficacy and potential side effects of different drugs for a given patient. The proposed system holds the potential to transform the way medications are authorized, improving patient outcomes, minimizing adverse reactions, and optimizing therapeutic interventions. We present the design and development of the DNA-based medication recommendation system, with its evaluation using realworld genomic and clinical datasets. The results demonstrate the potential of proposed approach to provide personalized medication recommendations, ultimately enhancing the efficiency and precision of medical treatments.

Diagnosing Breast Cancer and cancer using Deep Learningand Machine Learning methods

Authors- Keerthidhar Kudikala,Manoj Reddy Maram, Asst.Prof. P. Sandhya Priyanka

Abstract- Breast cancer, a prevalent and potentially fatal disease that affects one out of every eight women, can now be detected using advanced microarray technology and large datasets. This study utilized machine learning algorithms and Deep Learning to analyze microarray data, which consisted of two sets containing different protein types for 95 individuals, 43 of whom had recurring breast cancer and 52 who did not. The data was processed using Python programming language. The proposed work focuses on machine learning techniques such as Adaboost and Gradient Boosting Machine were employed and the IoT devices that are used to detect the breast cancer. The results revealed that the logistic regression method yielded the most accurate results (91.29%) before applying any feature reduction techniques, while the Random Forest method also achieved good results (69.25%). In terms of the first dataset, the SVM algorithm demonstrated the highest accuracy rate of 91.25% in both approaches. Conversely, the second dataset displayed an accuracy rate of 89.87% in RLR and 81.87% in LTE. The maximum accuracy rate for the first dataset was 95.69%, while the second dataset achieved a rate of 65.72%. Consequently, it can be concluded that it does not enhance classification accuracy.

Stabilization of Black Cotton Soil Using Rock Salt

Authors- Abhishek Yadav, Prof. Rajesh Jain

Abstract- Soil modification has emerged as a new area for research in the geotechnical engineering and the main purpose of most of researches is to determine optimum amount of additive with considering economy and effectiveness. In present study, black cotton salt has been used as an additive. The effect of addition of black cotton salt on properties of fine grained black cotton soil is determined in laboratory. This soil exhibits volume change behaviour with variation in the water content. Volume changes has caused reduction in sustainability of structure supported on black cotton soil. From experimental results, it will be observed that plastic limit, liquid limit, plasticity index swelling pressure and swelling index decrease or increases with addition of salt in soil. Optimum moisture content and maximum dry density tests will also be carried out with addition of salt in the soil.

Durability Study of Concrete Using Foundary Waste Sand

Authors- Kunal Verma, Prof. Mahroof Ahmed

System for Face Recognition Based Smart Attendance

Authors- Kotte Vishruth, Bashetty Rohan Raj,Vanam Ajay,K. Asst.Prof.K.Siva Kumar Gowda

Abstract- In order for students to learn as much as possible, attendance systems were implemented in educational institutions. There are two ways to track a student’s attendance in a particular class. The first option is to call the number and have students sign a document with their roll number. As a direct result of this, it was necessary to modify this system in order to make it more user-friendly, quicker, and more effective. This is a mechanized framework that makes it simple for educators to monitor everybody in the class participation without disturbing the example or fooling around. Face identification is one example of a situation in which this idea can be implemented to effectively identify and prevent proxy attendance while also reducing time consumption. The primary objective of this project is to implement an automated attendance system that is made possible by the Open CV/Python libraries and the Raspberry Pi 3B+.Any field in which an attendance system is present and plays a significant role can benefit from the proposed system. Additionally, this project ought to be described as an engineering solution for all colleges and universities to track and manage attendance because the project’s goals and design criteria were met.

Overview and Evolution of High-Efficiency Video Coding

Authors- R Suraj, Janjirala Adarsh, Javadi Adarsh Kumar, Assistant Professor T. Sravani

Abstract- High-Efficiency Video Coding (HEVC), or H.265, is a special way to make videos take up less space on devices like phones and computers. It’s like using a magic spell to make the videos smaller without losing too much quality. This is important because it means we can fit more videos on our devices, and they will still look good when we watch them. HEVC is a big deal in the world of videos because it has changed how we make them smaller and better. HEVC is a way to make videos take up less space on computers and the internet. It does this by using smart methods to squish the video down without losing quality. This makes it easier to watch videos online without waiting for them to load and saves space on our devices. Videos can be watched on lots of different things like phones, tablets, computers, and smart TVs. But each thing is different and can show the video differently. Video compression helps make sure the video can work on all the different things and still look good. So, no matter what you watch it on, it will work and look great! Sometimes we need to talk to people far away using cameras and computers. We also need cameras to watch over things to keep them safe. But we need to make the videos smaller so they can be sent quickly. This helps us see what’s happening right away without having to wait. We use special computer programs to make the videos small while still looking good. Video compression is like squeezing a big video into a smaller size[fig 1] so it can be sent and shown more easily. It helps make sure we can watch videos in really good quality without taking up too much space or using too much internet.

Factors Affecting Tourists’ Selection of Smart Tourism Destinations in Vietnam: An Empirical AnalysisFactors Affecting Tourists’ Selection of Smart Tourism Destinations in Vietnam: An Empirical Analysis

Authors- Tung Thanh Nguyen, Thong Tri Truong, Ly Thi Da Nguyen

Abstract- This quantitative research article investigates the factors influencing tourists’ choice of smart tourism destinations in Vietnam. The study aims to identify and analyze the key factors that play a significant role in tourists’ decision-making process when selecting smart tourism destinations. The research methodology employed a survey questionnaire administered to a sample of tourists visiting Vietnam. The data collected was analyzed using statistical techniques such as descriptive analysis, correlation analysis, and multiple regression analysis. The results revealed several factors that significantly influenced tourists’ choice of smart tourism destinations in Vietnam, including technological infrastructure, information and communication technology (ICT) services, perceived benefits, and destination image. These findings provide valuable insights for tourism policymakers and industry stakeholders to enhance their understanding of tourists’ preferences and develop effective strategies to promote smart tourism in Vietnam.

Intrusion Protection System

Authors- Ms. Sadhna Devede , Prof. Mr. Shivank Soni

Abstract- Intrusion Protection System (IPS) defined as a Device or software application which monitors the network or system activities and finds if there is any malicious activity occur. Outstanding growth and usage of internet raises concerns about how to communicate and protect the digital information safely. In today’s world hackers use different types of attacks for getting the valuable information. Many of the intrusion Protection techniques, methods and algorithms help to detect those several attacks. The main objective of this paper is to provide a complete study about the intrusion Protection, types of intrusion Protection methods, types of attacks, different tools and techniques, research needs, challenges and finally develop the IPS Tool for Research Purpose That tool are capable of detect and prevent the intrusion from the intruder.

Smart Energy Meter and Billing System using IoT

Authors- M.Srinivas

Abstract- It is a difficult job for the electricity board officials to manually take meter readings and calculate bill as it is time consuming and requires manpower. Billing consumers for energy consumption is not uniform. It is a tedious job for the electricity board official to manually go and take meter readings of big industrialists and reset their maximum demand after recording it. Even the latest energy meter is not tampering proof. Hence considering all these factors it is possible to design an energy meter that is tamper proof, supports automatic metering and billing system , and at the same time helps in finding the fault location of transmission lines. The same meter can be used to take the readings of industrialist which sends these readings to a secured data location and automatically reset it after recording it. Considering all these features that can be done by a single energy meter it is called a SMART ENERGY METER.

Case Study of WPSA with Partial Replacement
of Cement

Authors- Jeevanjot Singh,Mohit, Gurpreet Singh

Abstract- It is imperative to discover a workable method to reuse waste and diminish our utilization of natural resources in order to address the economic aspects pertaining to waste disposal, which makes up nearly half of the cost incurred in treating wastewater. The focus of this paper is to analyze the differences in properties between fresh and hardened concrete through the utilization of waste paper sludge ash as a substitute for cement. WPSA can contribute to the enhancement of strength performance (measuring the strength of concrete structures), as well as the workability and water absorption properties of each mixture. Several testing methodologies were utilized to verify the concrete’s adequacy for its application as a structural element. The study demonstrated that the use of WPSA might play a role in improving the overall strength of concrete.

Utilizing Digital Image Analysis for Forecasting Financial Market Sequences

Authors- Prabhas Gurazada, Shiva Kashyap Yellavajhala, Gandla Anoop, Asst. Prof. K.Siva Kumar Gowda

Abstract- Financial market sequence prediction is a vital and intricate undertaking within the domain of quantitative finance, holding significant importance in investment decision-making processes. It involves the application of advanced mathematical and statistical models to analyze historical market data, identify patterns, and forecast future market movements. The accurate prediction of market sequences is crucial for investors and financial institutions seeking to optimize their investment strategies, mitigate risks, and capitalize on emerging opportunities. By leveraging sophisticated quantitative techniques and cutting-edge algorithms, financial professionals can gain valuable insights into market trends, enabling informed decision-making and the potential for enhanced financial performance.

IOT – Enabled Smart Cities

Authors- P. Praveen Kumar, T. Nithinsai, B. Ajay, Asst. Prof. K. Siva Kumar Gowda

Abstract- IoT has changed the creation of smart cities, by integrating different urban systems including energy, transportation, waste management, and security for the public. By integrating various devices, sensors, and infrastructure, IoT technology creates a network that continuously produces and shares useful data. This adoption of IoT devices facilitates effective data gathering, analysis, and decision-making, reducing waste and environmental impact. Networked sensors in smart grids optimize energy consumption, while IoT-enabled transportation systems offer real-time traffic monitoring and intelligent parking solutions. IoT technology also enhances public safety by enabling real-time monitoring and response. Surveillance cameras with IoT connectivity can detect potential threats or criminal behaviour, providing law enforcement agencies with better situational awareness. Networked emergency response systems can recognize events and act swiftly, potentially saving lives. IoT technology also plays a significant role in effective trash management. Sensing-enabled smart bins track garbage levels, improve collection routes, and collect data on noise levels and air quality, enabling proactive actions to improve urban dwellers’ living standards. By adopting IoT for smart cities, the future will be more connected and affluent, as the world continues to urbanize.

Study Of Structural Audit Of Wadi Flyover At Nagpur Amravati Road

Authors- Mohammad Owais Kausar, Prof H. B. Dahake

Abstract- The flyover on the Nagpur-Amravati Road is an important piece of infrastructure that requires regular assessment to ensure its structural integrity and safety. The aim of this study is to make a structural analysis of the gateway, to evaluate its current status, to identify potential disadvantages and to recommend necessary improvements. The research included a literature review to gather insight into setting standards, methods, and best practices. Various methods have been used to assess the health and performance of the rotations, including visual inspection, non-destructive testing, and design. The findings revealed a variety of concerns that required immediate attention, including corrosion, fatigue, and design issues.The study concludes with recommendations for repairs, maintenance strategies and risk management to prolong the life of transits and ensure the safety of passengers. The findings of this study support the knowledge on structural analysis and provide insight into similar projects.

Importance of Non-Verbal Communication in Business Negotiations: A Step up towards Sustainable Entrepreneurship

Authors- Assistant Professor Mudra Mittal, Assistant Professor Vikas Kumar, Assistant Professor Shivani Sharma

Abstract- This article highlights the significance of understanding body language signals in business negotiations. Non-verbal body language, including posture, clothing, gestures, eye contact, facial expressions, and physiological responses, can reveal the opponent’s physical and emotional state, complement, or weaken spoken words, and help determine the accuracy of what was said. These signals can be conscious or unintentional, and their interpretation can greatly influence the outcome of the conversation.

Exploring Prospects and Challenges in the Indian Textile Industry

Authors- Assistant Professor Anu Devi, Assistant Professor Minakshi Kakran, Assistant Professor Rajni Kant

Abstract- The Indian textile sector stands as a cornerstone of the Indian economy, contributing approximately 7% of the total GDP and over 12% of the manufacturing sector, with export earnings exceeding 13%. It ranks as the second-largest employer in India, following the agriculture sector. Globally, India holds a significant position, representing 5.2% of textile exports and 3.7% of apparel exports. Directly, it employs around 45 million individuals, with another 60 million engaged indirectly through associated activities. Projections indicate promising growth, with the domestic home textile market expected to achieve a Compound Annual Growth Rate (CAGR) of 4%, reaching $13 billion, and the technical textile market poised to grow at a CAGR of 10%, reaching $42 billion within the same timeframe. India secures the second position in textile exports, commanding a 7% share, and the sixth position in apparel exports with a 3% share globally. Post-COVID, there’s been a noticeable surge in demand, amplified by government support through attractive schemes like Production Linked Incentive (PLI) and Mega Investment Textile Parks (MITRA). These initiatives aim to propel the sector towards surpassing the ambitious $250 billion target by 2025-26, as outlined in recent reports. The impending release of the new textile policy is anticipated to be a game-changer, yet a strategic roadmap is imperative to realize the industry’s full potential and meet the set targets within the stipulated timeline.”

The Development of 5g Technology and its Implications for the Industry

Authors- Assistant Professor Shivani Berman, Assistant Professor Kehkasha Mirza, Assistant Professor Mayank Verma, Assistant Professor Ravi Gautam

Abstract- The development of 5G technology is very important in today’s technological world. These technologies are bringing about significant changes in the way we interact with the digital world and are changing the way we use technology. The speed offered by 5G technology makes it possible to carry out data transfers very quickly, opening up opportunities for new applications and services in various sectors. The implications of the development of 5G technology on industry are huge and can affect various aspects, such as productivity, efficiency, and innovation. In the production sector, 5G technology makes it possible to speed up the production process and increase efficiency by using industrial technology 4.0. Within the service sector, 5G technology makes it possible to provide faster and high-quality services, such as more stable and faster video streaming services. On the other hand, the development of 5G technology also carries implications that must be considered, such as security and privacy issues. However, it is important for the industry to ensure that the 5G technology used meets established security standards to avoid security and privacy concerns. The development of 5G technology is very important in today’s technological world. These technologies are bringing about significant changes in the way we interact with the digital world and are changing the way we use technology. The speed offered by 5G technology makes it possible to carry out data transfers very quickly, opening up opportunities for new applications and services in various sectors. The implication of the development of 5G technology on industry are huge and can affect various aspects, such as productivity, efficiency, and innovation. In the production sector, 5G technology makes it possible to speed up the production process and increase efficiency by using industrial technology 4.0. Within the service sector, 5G technology makes it possible to provide faster and high-quality services, such as more stable and faster video streaming services. On the other hand, the development of 5G technology also carries implications that must be considered, such as security and privacy issues. The speed offered by 5G technology makes it easier to carry out attacks and access personal data. Therefore, it is important for the industry to ensure that the 5G technology used meets the established security standards. The development of 5G technology brings significant changes in the industry and opens up new opportunities in various sectors. The implication of the development of 5G technology is huge and affect productivity, efficiency, and innovation. However, it is important for the industry to ensure that the 5G technology used meets established security standards to avoid security and privacy concerns.

Role of Caste Category in Indian Politics

Authors- Assistant Professor Mayank Verma, Assistant Professor Shivani Burman, kehkasha Mirza, Ravi Gautam

Abstract- Caste is an essential part of Indian society. Caste is almost present in every political and social process in India. Caste has played both integrative and disintegrative role in Indian society. Identity politics has lead to emergence of caste in electoral politics. Some scholars see rise of caste in political process as a factor which has strengthened the democracy in India, because a large section of people come out to cast their votes to support their candidates who belongs to their caste. Caste based politics gave voices to those section of people who were underrepresented .While on the other hand many scholars see caste as a disintegrative factor for long term development of Indian society. They are opined of instead of caste, development should be an integrative factor in Indian political system. It is reality of our Indian societies that caste has deeply rooted in almost every aspect of our life. Many political parties have been emerged along the caste lines. Their whole politics is based on their caste group instead of developmental politics. Our many public policies are caste driven, while at same time we are trying to make caste free Indian societies. In contemporary time in electoral politics caste has entrenched too much. Political parties give ticket to candidates keeping the caste equations. Even the compositions of council of ministers are formed along keeping all type of caste calculated cost-benefit. Dr. Bhim Rao Ambedkar in a constituent assembly debate had said that caste is not a positive factor for development of Indian societies.

Reflecting on the Dominance of Indians Time Honored Embroidery Techniques

Authors- Assistant Professor Reena Tyagi

Abstract- Traditional embroidery is a captivating art form passed down through generations, showcasing cultural heritage worldwide. Artisans use needle and thread to create intricate designs, each stitch crafted meticulously for stunning textures. From Indian kantha to Japanese sashiko, diverse styles reflect unique cultural identities. Motifs inspired by nature, mythology, and everyday life hold deep symbolic significance, preserving cultural narratives. Artisans infuse personal stories into their creations, making fabric come alive with beauty and meaning. Besides aesthetics, embroidery serves practical purposes, adorning clothing, accessories, and home furnishings with elegance and cultural pride.

Applique Craft of Orissa in India: Continuty, Changes & Challenges

Authors- Assistant Professor Minakshi Kakran, Assistant Professor Anu Devi, Assistant Professor Binnu Pundir

Abstract- Appliqué, originating from French culture, is a distinctive form of embroidery that involves attaching smaller pieces or patches of fabric onto a larger fabric or surface. Unlike traditional embroidery, which often involves stitching onto the fabric directly, appliqué typically utilizes one entire piece of fabric. The term “appliqué” itself denotes “something applied” or an addition that has been affixed onto the base fabric. This technique offers a versatile way to embellish textiles, adding depth, texture, and visual interest to various items like Tarasa banners, Chandua canopies, Chhattri umbrellas, animal puppets, wall hangings, shrine covers, parasols, bags, pouches, cushion covers, and lanterns. The most intricate appliqué techniques are seen in Samiana canopies and Chhattri umbrellas, showcasing remarkable artistic skills. These crafts are typically passed down through generations within families. The Pipli appliqué style predominantly features cut cloth patches fashioned into floral, avian, and animal motifs, which are then sewn onto items like bedcovers, cushions, and lampshades. Traditionally, the primary colors of black, white, red, and yellow are used, although additional hues have been incorporated over time to enhance the craft’s vibrancy.

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The Development of 5g Technology and its Implications for the Industry

Role of Caste Category in Indian Politics

Reflecting on the Dominance of Indians Time Honored Embroidery Techniques

Applique Craft of Orissa in India: Continuty, Changes & Challenges

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