International Journal of Science, Engineering and TechnologyPerformance Enhancement of Vertical Handoff Algorithm in Heterogeneous Network
Authors -Research Scholar Ravneet Kaur, HOD Ravi Malik
Abstract- –The evolution of the next-generation wireless network has led to the increasing demand for handheld devices to enjoy mobility through “Always Best Connected” services. In the next-generation wireless network, seamless best-possible access to a network, which has a widely varying set of network characteristics, requires rigorous mobility management. The vertical handover facilitates users to roam across different networks with the seamless network connection. The vertical handover process that supports mobility can be initiated as mobile controlled handoff or as a network controlled handoff process. Associating the user with a suitable wireless network using a vertical handover process through wide network integration is a challenging and difficult problem that has drawn the attention of many researchers.
Fog Drive Disaster Backup as a Service for Cloud Server using IOTand Fog Computing
Authors -Asst. Prof. S.Chinnathurai, M. Sangeetha, J. Shalini, S. Subashini, S. Suvitha
Abstract- –Data storage and service delivery are mainly realized by cloud data centers deployed around the world. However, data centers are facing failure threats caused by disasters such as disk failure, threat. Fault tolerance is a major concern in clouds in order to guarantee the reliability and the availability, also the data backup and recovery is one of the most important issues in cloud computing environments, and the need of efficient techniques for the data recovery are increasing by the days. This project proposes a primary and backup resource allocation model called Fog Drive that provides a probabilistic protection guarantee for virtual machines counter to multiple failures of physical machines in a cloud provider to minimize the required total capacity. This project set up a flexible data backup operation, using Disaster Backup Data as a Service (BDaaS) solutions, mixing them up with Fog Drive local storage device.
LSB Modification Techniques of Audio Steganography for Secure Communication
Authors -M. Tech. Scholar Priyanka Joshi, Asst. Prof. Ashwini Bade
Abstract- –This paper presents the application of steganography techniques for data hiding in host audio file. Audio steganography is more secured way of techniques than Text and Image Steganography due to its vast size of audio files, it can store more information than other techniques. The main aim of this paper is to present a method of embedding text-based data into a host audio file using the method of least significant bit modification for data hiding without change in quality i.e. of audio file. A method of embedding text in a host audio file through steganography is presented. In it, the audio file is sampled first and then a specific bit of each alternate sample is changed to embed the textual information in an audio file. The audio file can be considering of any type of music styles (pop, rock, techno, jazz). We propose secure communication through Audio with Text based Information using Steganography. Steganography is a method which works by changing a few bits of secret message; we will use specific bit values to represent characters. The resulting audio file will look mostly like the original. We can then send the secret message at the receiver using emails end where the message can be retrieved by knowing which bits are to be decode. In this assignment we will be writing a MATLAB application that will enable us to encode and decode secret messages with another person. The Major goal of this paper is to provide secure communication between authorized people (Sender and receiver).
A Comparative Study of Feed Forward neural networks, Genetic Algorithm and Multimodal Deep Learning for Movie Recommendation
Authors -Mr. Rokadep. P., Miss. Gaikwad T.B., Miss. Kulkarni G.P.
Abstract- — Expression Reviews in the form of sentiments or rating for item used or movie seen is the part of human habit. These reviews are easily available on different social websites. Based on the interest pattern of user, it is important to recommend him the items. Till today’s, a lot many recommendations System are designed using several machine learning algorithms. Still, faster convergence speed, prediction accuracy, suitable recommendation system that must be resolved using hybrid algorithm. In this report we propose a system that uses Feed Forward Neural Network. In this research we obtained for proposed technique are compared using the testing parameters like precision, recall, accuracy, mean absolute error with the result of feed forward neural network, multi modal deep learning, genetic algorithm.
LSB Modification Techniques of Audio Steganography for Secure Communication
Authors -M. Tech. Scholar Priyanka Joshi, Asst. Prof. Ashwini Bade
Abstract- –This paper presents the application of steganography techniques for data hiding in host audio file. Audio steganography is more secured way of techniques than Text and Image Steganography due to its vast size of audio files, it can store more information than other techniques. The main aim of this paper is to present a method of embedding text-based data into a host audio file using the method of least significant bit modification for data hiding without change in quality i.e. of audio file. A method of embedding text in a host audio file through steganography is presented. In it, the audio file is sampled first and then a specific bit of each alternate sample is changed to embed the textual information in an audio file. The audio file can be considering of any type of music styles (pop, rock, techno, jazz). We propose secure communication through Audio with Text based Information using Steganography. Steganography is a method which works by changing a few bits of secret message; we will use specific bit values to represent characters. The resulting audio file will look mostly like the original. We can then send the secret message at the receiver using emails end where the message can be retrieved by knowing which bits are to be decode. In this assignment we will be writing a MATLAB application that will enable us to encode and decode secret messages with another person. The Major goal of this paper is to provide secure communication between authorized people (Sender and receiver).
Smart Dustbin using Arduino IDE
Authors – Ravi Yadav(Technical Trainer)
Abstract- – The level of intelligence possessed by both humans and objects continues to rise. While the concept of smart cities is intriguing, there is a pressing need for intelligent approaches to waste management. The Smart Dustbin was conceived as a solution for use in intelligent buildings, such as colleges, hospitals, and bus stops. Because of this, it is believed that the Smart Trashcan is an upgrade on the traditional dustbin by making it smart via the use of sensors and logics. Via ultrasonic sensors for waste level monitoring and delivering message to the user updating the state of the bin using GSM module, smart dustbins are a novel concept of implementation that makes a regular dustbin smart. Smart dustbins are also known as intelligent garbage cans. As soon as the trash can is brimming, a system for collecting intelligent solid waste will be activated. It is not uncommon to see rubbish scattered in and around the wastebaskets as it has been known to happen. Insects that might transmit illness, such as mosquitoes, flies, bees, and driving ants, may make their home in the area around dust bins that have not been adequately managed. The surroundings of a garbage can are also likely to contribute to an increase in the amount of pollutants in the air. The contamination of the air caused by a trashcan may lead to the production of germs and viruses, both of which can lead to life-threatening illnesses in humans.
Structural Analysis of Steel Plate Shear
Wall using ANSYS
Authors – Research Scholar Piyush Kumar Jaiswal, Asst. Prof. Rahul Sharma
Abstract- – The SPSW structures are used as lateral load resisting structure in various countries like Japan, USA. Due to architectural or other requirements, it becomes essential to incorporate opening on SPSW. The incorporation of SPSW affects its strength. The objective of current research is to investigate the effect of circular opening on lateral load resisting behavior of SPSW using techniques of Finite Element Analysis. The modeling and structural FEA analysis is conducted using ANSYS simulation package. The strength of SPSW with and without opening is evaluated in the basis of stress and deformation. The FEA results have shown that incorporation of any opening in SPSW increases stress and deformation. The lateral deformation found to increase with increase in lateral load. The maximum distortion is obtained at this critical zone. The deformation of SPSW with circular opening is 31.2% higher than SPSW without opening.
Deep Learning Approach for Intrusion Detection
Authors – Udit Narayan Pushpad, Prof. Lokendra Singh Songare
Abstract- – On sometimes, random harmful activities for a single machine or the whole network may be seen on the internet. It is getting more difficult to keep up with the rapid expansion of computer connections. Concerns about security may be observed on the internet just as they are in person. The intrusion detection system (IDS) is designed to identify and investigate such hostile behaviour occurring across a network. The intrusion detection system (IDS) aids in detecting system attacks and identifying attackers. Various machine learning (ML) techniques have been applied to intrusion detection systems in the past with the goal of enhancing intruder detection outcomes and increasing IDS accuracy. In this paper, we provide a method for developing an efficient intrusion detection system (IDS) that makes use of principal component analysis (PCA) and the CNN classification algorithm. PCA may be used to organize data by reducing its dimensionality, while random forest can categorize data. The tests will be run on the KDD Knowledge Discovery Dataset Knowledge Discovery Dataset using the proposed system. When compared to other methodologies such as SVM, Naive Bayes, and Decision Tree, the proposed methodology clearly outperforms them in terms of accuracy. Using our suggested strategy, we obtained the following results: The performance time is 3.24 minutes, the accuracy rate is 96.78 percent, and the error rate (percentage) is 0.21 percent.
Hostel Automation Using Face Detection and
Voice Interface
Authors – Mr. Waghmare A.I., Mr. Sandip Bagul, Mr. Ganesh More
Abstract- – When it comes to housing for children’s education, questions like safety and quality arise? The child’s health is also of greatest concern to parents due to the recent situation. In this proposed hostel automation systems with parents who can log in and check their child’s track record. This system removes human errors as well as reduces administrative work. Parents can also interact with the system using voice interfaces. If the child was absent in the hostel, the parents are automatically notified and the student is also alerted if they do not arrive on time. Students can also make suggestions, feedback and raise their grievances through the system so that issues like ragging can also be dealt with. Student attendance is marked by face recognition.
Leaf Disease Detection Using Artificial Intelligence
Authors – Asst. Prof. Deepika. B, Ashvika.V, Eniya. A, Indira. T
Abstract- – Crop diseases are a primary risk to meals security, however their fast identity stays tough in lots of components of the sector because of the dearth of the important infrastructure. This has to be decreased robotically with none human invention for that cause we cross for Artificial Intelligence. In this mission we use deep studying techniques (CNN) to locate the ailment and classifying it. With the invent of plant sicknesses, the yield is affected adversely. Hence its miles crucial to perceive the ailment at its earliest degrees and discover a treatment to get rid of the ailment. This may be done through focused on the ailment places, with the perfect amount and attention of pesticide through estimating ailment severity the use of picture processing techniques. In this mission k nearest neighbor classifier technique has been used to phase the picture the picture into 3 photos primarily based totally on color.
Control Fire Accident In Firework Industry Using Iot
Authors – Asst. Prof. Mr. Mani P , Shajith Husain K, Viswa K , Shreeram R, Thanush Raja R
Abstract- – Safety of an individual is essential worry in any industry particularly in wafers manufacturing plant. Today wellbeing of labourer is a significant test. The wellbeing and life of the labourers are basic because of the climate and its effect. The saltine processing plant endangers the existence of the specialists through delivering fire and smoke. The existence of labourers in saltine processing plant is temperamental and step by step the tension on them increments. The requirement for a creative methodology ascends to protect the specialists and to build the efficiency. Individuals in firecrackers manufacturing plant ought to mindful of fire mishaps with the goal that they can safeguard themselves prior to anything occur. The principle objective is to give high dependable security framework and to diminish fire mishap in wafer processing plant. This undertaking centres the wellbeing of the specialists. The primary intention of this task is to protect the labourers from the fire mishaps. The IOT is cost low and powerful for remote transmission of information. This venture will lessen the responsibility of human in security upkeep. This venture is proposed in view of remote checking framework and powerful minimal expense framework. The features of this framework are simple structure up, high-unwavering quality, strong capacity and better extendibility. This framework is popular ways to deal with lessen the misfortune in the business and to tackle the ongoing issue. The remote correspondence distance is restricted in the business and gives incredible security to the business.
Voice Controlled Robotic Vehicle Using 8051 Microcontrollers
Authors – Mr. Abhale B.A., Mr. Krishna Ranshinge, Mr. Kapil Mohite
Abstract- – The voice-controlled vehicle was created to make human work easier, since we live in an artificial intelligence-driven world where robots perform many tasks. The human voice is used to drive the vehicle. A stable android mobile application built with android studio software transmits the speech. It’s essentially a Wi-Fi link. Using the mobile application, we can operate the vehicle with our voice from anywhere. The voice- controlled robot vehicle project has military, surveillance, and human applications in scope. It’s a voice-activated wireless robot vehicle. The project’s main goal is to guide the robotic vehicle to a specific location. In addition, the project’s main goal is to use voice to control the robot. It is now possible to have human robot interaction. The aim of a voice controlled Robot is to listen to the user’s commands and act on them.
GSM Based Vehicle Theft Detection Using Face Recognition
Authors – Prof. Ashwini Bade, Aman Vishwakarma, Pratiksha Kalokhe, Yukta Bhosale, Prajakta Jorwar
Abstract- – In recent years, GPS and GSM modem detection, as well as car tracking systems, have become more popular. Face recognition based on a vehicle theft detection system would be ideal. It provides the most complete solution to problems. Face recognition technology is used in the Python Module to identify and recognize faces in real time. Face recognition technology has the ability to assist in the resolution of a wide variety of issues. A vehicle is a device or system that is used to lock and detect other cars. They may be able to determine the presence or absence of an automated owner by utilizing a Smartphone application that recognizes and compares faces within their data. If the vehicle is in good working order. Alternatively, someone tampered with the car in an attempt to disable or damage the mechanism that delivers the message and places the phone call. This device protects vehicles by allowing consumers to view theft details and download them to a USB drive. The data includes position, pose, illumination, background quality, and gender.
A Machine Learning Method for Publishing Location Data in Privacy Maintenance
Authors – Esha Sharma, B. Hemanth Kumar, CH. Sathvik Reddy, P. Nithya Sri, Associate Prof. Dr. G. Ramakrishna
Abstract- – Publishing datasets plays an essential role in open data research and promoting transparency of government agencies. However, such data publication might reveal users’ private information. One of the most sensitive sources of data is spatiotemporal trajectory datasets. Unfortunately, merely removing unique identifiers cannot preserve the privacy of users. Adversaries may know parts of the trajectories or be able to link the published dataset to other sources for the purpose of user identification. Therefore, it is crucial to apply privacy preserving techniques before the publication of spatiotemporal trajectory datasets. In this paper, we propose a robust framework for the anonymization of spatiotemporal trajectory datasets termed as machine learning based anonymization (MLA). A variation of k-means algorithm is also proposed to preserve the privacy in overly sensitive datasets. Moreover, we improve the alignment process by considering multiple sequence alignment as part of the MLA. The framework and all the proposed algorithms are applied to T-Drive, Geolife, and Gowalla location datasets. The experimental results indicate a significantly higher utility of datasets by anonymization based on MLA framework.
Acute Portal Evaluator by Using NLP & ML
Authors -Kalyani Goswami, Achal Zade, Rajashri Thombare, Asst. Prof. Prof. R. B. Ghate
Abstract- – Nowadays, automated grading of subjective or descriptive responses is required. As a result, we’re developing software to automate the evaluation of responses through natural language processing and machine learning. Each response is graded based on the number of words used, their relevance, and the sentence’s grammatical meaning. We can save money by automating the manual checking procedure while also reducing the instructors’ workload. This program also cuts down on assessment time.
Security, Threats, and Trust concerns regarding the Internet of Things
Authors – Lecturer Sameena Shaik, Lecturer Sangeetha Komandur
Abstract- – Life in the current world has been made easier by an array of devices and equipment which are interlinked to enhance their complimentary performance. Defense, Transport, Healthcare, Energy etc. all use devices that rely on each other and the ability to inter-communicate and complement each other in operations. These are possible through the internet of things that refers to the interconnectivity of interrelated computing devices, digital and mechanical machines with people, objects, and animals via UIDs. IoT enables data transfer over networks without the necessity of the interaction between humans or between humans and computing devices. These capabilities don’t exist without risks and threats that related to IoT. Despite the continued growth of IoT and especially with phase 4.0 acting as a catalyst to its growth, there still are vulnerabilities that affect trust on IoT as risks and threats lead to cyber-attacks. Various research has outlined these risks, and some have gone forward to suggest solutions and areas of research in the effort to make IoT more secure. Through reviewing some of these works, this paper seeks to create a more comprehensive perspective of the works alongside a critical look at their strengths and weaknesses in the propositions made; and then suggesting a unified resolution regarding research on the area.
A Review Article Localization and Traffic Density Short Term Forecasting in Non Motorized Vehicle Comprehensive Case Analysis
Authors – Mohammad Hashim Khan, HOD Mr. Vinay Deulkar
Abstract- -Non-motorized transport (NMT) is the use of a bicycle or walking to travel from one place to another. It is gaining popularity especially in the developed countries due to low transport externalities such as emissions and traffic congestion alongside its benefits to physical and mental health. In this paper, a comprehensive review of the existing literature related to NMT is presented focusing on the factors including built environment, geography, and weather, the health, and environmental benefits of NMT, and the motivational approach for increasing the use of NMT. The built environment, geography and weather, and socioeconomic factors significantly affect the use of NMT as a travel mode. This study reviewed some unique characteristics of NMT especially in developing countries to provide a clear understanding of the dynamics of NMT.
Energy Management Strategies of Hybrid Energy Storage System: Challenges & Application
Authors – M.Tech. Scholar Neetu Singh, HOD AshwaniKumar , Assistant Professor Shilpi
Abstract- – In India, the demand for oil resources is increasing at a faster rate than in other nations. By the end of 2040, the estimated demand for oil resources is expected to reach 9.8 million barrels per day. 65% of the increase in demand may be attributed to automobile mobility. Estimates of 260 million cars, 185 million two-wheeled and three-wheeled vehicles, and 30 million trucks are also predicted. Rather than reducing global warming, however, greenhouse gas emissions remain a major source of concern today. According to a decision made by the UN Security Council, the global temperature should be lowered. By 2050, greenhouse gas emissions must be decreased by at least half compared to what they were in the year 2000. As a result, the automotive industry is searching for a more environmentally friendly alternative. Electric vehicles (EVs) emit no pollutants and are the greatest solution. There are often a number of start-stop-go situations that require both average and instantaneous power delivery throughout driving cycles. When it comes to everyday car power requirements, batteries still outperform other more advanced energy storage systems (ESSs). However, the downsides, such as higher thermal heating, starting and operating costs, time for recharging, and reduced travel distance, power density, and working life duration, persist in batteries.. Because of this, relying solely on battery power to power a vehicle is inefficient. The above-mentioned issues can be alleviated by the use of hybrid electrical sources. In order to meet urgent vehicle power requirements, a hybrid ESS (Ultra capacitor, or UC) with a longer life cycle and improved power density has been included.
Thermal Analysis of Extended Surfaces (Fins) of the Air-Cooled IC Engine: A Review
Authors – PG Scholar Abhay Raj Singh Sikarwar, Prof. S. K. Sharma
Abstract- – In this research paper authors have investigated the research work of the previous researchers. One of the most significant issues in engine design is heat dissipation. The cooling process of an air-cooled engine is mostly determined by the cylinder head and block fin design. High thermal stresses and poorer engine efficiency will result from insufficient heat removal from the engine. Fins are extended surfaces used to transmit heat between two fluids, or between a solid and a fluid. Fins come in a variety of shapes and sizes, including angular, circular, and rectangular fins. The engine piston chamber is the most vulnerable portion of any car, as it is subjected to significant thermal shocks and thus thermal stresses. Mainly ANSYS has been used by various authors to evaluate the performance of fins in two-wheeler engines.
GSM Based Vehicle Theft Detection Using Face Recognition
Authors – Prof. Ashwini Bade, Aman Vishwakarma, Pratiksha Kalokhe, Yukta Bhosale, Prajakta Jorwar
Abstract- – In recent years, GPS and GSM modem detection, as well as car tracking systems, have become more popular. Face recognition based on a vehicle theft detection system would be ideal. It provides the most complete solution to problems. Face recognition technology is used in the Python Module to identify and recognize faces in real time. Face recognition technology has the ability to assist in the resolution of a wide variety of issues. A vehicle is a device or system that is used to lock and detect other cars. They may be able to determine the presence or absence of an automated owner by utilizing a Smartphone application that recognizes and compares faces within their data. If the vehicle is in good working order. Alternatively, someone tampered with the car in an attempt to disable or damage the mechanism that delivers the message and places the phone call. This device protects vehicles by allowing consumers to view theft details and download them to a USB drive. The data includes position, pose, illumination, background quality, and gender.
VHDL Based Design of Convolutional Encoder Using Vedic Mathematics and Viterbi Decoder
Authors – Deshpande Netra Narayan, Prof. Vallabh S. Bhatlavande (Guide)
Abstract- – As in mathematics, multiplication is the most used operation. An ancient Vedic sutra named ‘urdhavtriyagbhyam’ is used for multiplication which gives a difference in actual process of multiplication itself. It enables parallel generation of partial products and eliminates unwanted multiplication steps. This paper presents the design of convolution encoder using vedic mathematics and Viterbi decoder using parallel processing. The coding follows a fast multiplication process and achieves a less computational complexity over its conventional multiplier resulting in a smaller number of devices utilization. Convolution encoding with Viterbi decoding is a good forward error correction technique suitable for channels affected by noise degradation. The simulation and synthesis of proposed design are done through XILINX 14.2i ISE simulator tool and coding is in Verilog with Spartan 3A as the target FPGA.
Estimation of Electricity Saving in VCRS Based air conditioner by Using Solar Energy
Authors – M.Tech.Scholar Sonu Kushwah, Prof. Yogesh Parkhi
Abstract- – The development of renewable energy is on the rise worldwide because of the growing demand on energy, high oil prices, and concerns of environmental impacts. In recent years, progress on solar-powered air conditioning has increased as nowadays, air conditioning system is almost a must in every building if we want to have a good indoor comfort inside the building. Therefore, this paper focuses in the design and construction of a VCRS based air conditioner by using solar energy. The air conditioning system can be operated on solar and can be used in non-electrified areas. As we all known, solar energy is cost effective, renewable and environmentally friendly.
Saving of Electricity in VCRs Based Refrigerator by Using Solar Energy
Authors – M.Tech. Scholar Anshul Trivedi, Prof. Yogesh Parkhi
Abstract- – Research has demonstrated that solar energy is an ideal source for low temperature heating applications such as space and domestic hot water heating. The use of solar energy to provide refrigeration is rather less intuitive. The negative environmental impacts of burning fossil fuels have forced the energy research community to seriously consider renewable sources, such as naturally available solar energy. Solar refrigeration technologies harness the energy of the sun and use it to run a cooling system. This type of solar application is an attractive option for the preservation of food and the refrigeration of vaccines and medicines in areas with a high intensity of solar radiation and no electricity supply.
Solutions for Recycling and the Reuse of Ash and Slag Waste from Vietnam’s Power Plants towards Sustainable Development
Authors – HS Bui, TH Bui
Abstract- – It is necessary to study on separating the ash and slag (waste) and the coal (reuse) in the boilers in the coal-fired power plants in Vietnam. In order to meet the increasing energy demand for annual economic growth of about 7-8% per year at a reasonable price, Vietnam is required to continue to build coal-fired thermal power plants. However, the amount of ash generated by the plants is very much. According to statistics data, coal-fired power plants across the country discharged nearly 7.6 million tons of ash and slag in 2020. The process of combustion of coal in boilers is always optimized but always exist a significant source of unburnt carbon. The major aim of this research is that collects data of ash and suggests one technology to treat the ash to get the unburnt carbon to reuse by separating the unburnt coal from ash. This will be an important source of raw materials for many industries..
Planning and Working Analysis of Faecal Sludge Treatment Plant
Authors – Miss V. Jeevitha, B.E., Prof.K. Soundhirarajan Head
Abstract- – The problems posed by fecal sludge (FS) are multidimensional because most cities rapidly urbanize, which results in the increase in population, urban settlement, and waste generation. Issues concerning health and waste treatment have continued to create alarming situations. These issues had indeed interfered with the proper steps in managing FS, which contaminates the environment. FS can be used in agriculture as fertilizer because it is an excellent source of nutrients. The recent decline in crop production due to loss of soil organic component, erosion, and nutrient runoff has generated interest in the recycling of FS into soil nutrients through stabilization and composting. However, human feces are considerably liable to spread microorganisms to other persons. Thus, sanitation, stabilization, and composting should be the main objectives of FS treatment to minimize the risk to public and environmental health. This review presents an improved FS management (FSM) and technology option for soil amendment that is grouped into three headings, namely, (1) collection, (2) treatment, and (3) composting. The main problems associated with the collection and treatment of FS, such as inadequate tools and improper treatment processes, are summarized, and the trends and challenges that concern the applicability of each of the technologies in developing urban centers are critically reviewed. Stabilization during pretreatment before composting is suggested as the best method to reduce pathogens in FS. Results are precisely intended to be used as a support for decisions on policies and strategies for FSM and investments for improved treatment facilities. Treated water can be used for irrigation purpose which enhances the crop growth or end product water can be released into the river or lake or pond.
Importance of Training and Development for Mechanical Engineer Employees: A Review
Authors – Amit Kumar Gupta
Abstract- – Now a day’s fast-paced, competitive industry, training has become a buzzword. Organizations that engage in excellent human resource training and development tend to achieve benefit both short-term and long-term. Due to organizational, technical, and social dynamics, employees tend to become absolute, making the need to adapt to constant learning and upgrading of skill and knowledge important. As a result, efficient management of training and development programs is critical for businesses and get the most out of their investment. As a result, the purpose of this study is to offer a conceptual study that has been developed and created on the advantages of an employee training and development program. The article also seeks to determine the many aspects of employee training and how they impact the output and performance of the company. Employees will be capable of supporting the business in attaining its competitive position in today’s global market with appropriate training and development opportunities, as well as effective employee performance evaluation techniques.
IOT Based Home Automation from Google Assistant
Authors – Aditya Patil, Rahul Nikam, Pranay Patil, Rushikesh Gramopadhye, Prof. Miss. Sonake V. V.
Abstract- – In the market there are many devices to control Home Appliances like Bulb, Fan, Motor etc. but making our own is awesome. The idea behind “IOT Based Home Automation from Google Assistant” is to control the Home appliances from any place and any distance with voice command and also using Android phone. In this project we are using Google assistant, IFTTT and Blynk app for operating our project. We shall use IFTTT to make a chain between Google Assistant and Blynk app IFTTT is a cloud based free IoT web server which is used to create virtual switches if you say any phase in the Google Assistant then it will generate a trigger in IFTTT. It will send the signal to Blynk Cloud server through web sockets. Blynk is a platform with IOS and Android apps to control Arduino. Blynk library is an extension that runs on your hardware. It handles connectivity device authentication in the cloud and command processing between Blynk app, cloud and hardware. It will control the node MCU (ESP8266) to turn on or turn off the respective relays. The device connected to the respective relay can be turned on or turned off as per the user’s voice command to the Google assistant.
Mechanical Automation of Public Garden Based on Solar Panel System
Authors – Aditya Patil, Rahul Nikam, Pranay Patil, Rushikesh Gramopadhye, Prof. Miss. Sonake V. V.
Abstract- – In the market there are many devices to control Home Appliances like Bulb, Fan, Motor etc. but making our own is awesome. The idea behind “IOT Based Home Automation from Google Assistant” is to control the Home appliances from any place and any distance with voice command and also using Android phone. In this project we are using Google assistant, IFTTT and Blynk app for operating our project. We shall use IFTTT to make a chain between Google Assistant and Blynk app IFTTT is a cloud based free IoT web server which is used to create virtual switches if you say any phase in the Google Assistant then it will generate a trigger in IFTTT. It will send the signal to Blynk Cloud server through web sockets. Blynk is a platform with IOS and Android apps to control Arduino. Blynk library is an extension that runs on your hardware. It handles connectivity device authentication in the cloud and command processing between Blynk app, cloud and hardware. It will control the node MCU (ESP8266) to turn on or turn off the respective relays. The device connected to the respective relay can be turned on or turned off as per the user’s voice command to the Google assistant.
Mechanical Automation of Public Garden Based on Solar Panel System
Authors – Ibrahim Hussain Shah
Abstract- – Internal of things is a bridge between human & devices. In this paper automation of watering to cops & water tank has to be implemented. In this world automated technology takes place everywhere. For the aspect of making all system better, this system is designed for garden maintenance. Nowadays misusage of electricity & water resources is a main problem. Sometimes due to carelessness of authorities, lamps are left ON which causes wastage electricity. Water wastage is another problem. To overcome this problem, our project helps to save electricity & water resources. Firstly microcontroller switches around 4:00pm, doing water supply to drinking water the gardens few hours before opening of garden for public. The garden gate is opened by running the motor unit which is driven by motor driver. Around 6:00pm, Lights are switches on depending on the output of LDR. Garden stays open for approximately 3 hours & by 8:40pm buzzer is sounded to point closing of garden alert to visitors. The garden gate is closed at 9:00 & one of the two lamps is switches off. In morning all lamps are off depend on LDR result. Microcontroller is employed to control all actions of other devices.
Effect of Filler Rod on Microstructure and Mechanical Properties of Bimetallic Weld Joint: A Review
Authors – M. Tech. Scholar Lokesh, Asst. Prof. Manoj Kumar
Abstract- -Friction Stir Welding (FSW) technique is a solid state metal joining process. The metal on welding does not melt and recast. Some of the defects commonly encountered in FSW are tunnel defect, kissing bond, cracks, pin holes and pipping defects. The defects occur because of improper metal mixing and lower heat input in the weld nugget zone. Only a literature has focused on the area of filler material and the process parameters on producing a defect free weld with optimal responses. There are different issues which should be tended to while welding the bimetallic metals because of the variety in the properties of the base metal. The coefficient of warm extension, substance organization and mechanical properties influence the weld ability of the joint. For keeping up this issue buttering method is utilized for such joints. It is very hard to choose the consumable cathode for buttering layers, which will fulfill the necessity of attractive mechanical properties and synthetic organization. Carbon relocation is one of the significant issues for buttering layer affidavit.
Fall Detection for Elderly People Using Machine Learning
Authors – Mrs. Pooja D. Kalyankar, Prof. Vallabh S. Bhatlavande (Guide)
Abstract- – Old people are more prone to falls. Since two decades, falls have been greatly investigated by medical institutions to minimize the impact of the fall and also reduce the consequences eg: Cost of hospitalization, etc. However, the problem of elderly falling does not only concern health-professionals but has also drawn the interest of the scientist community. Falls have always been the object of many research studies and the purpose of many commercial products. Recently, researchers have been trying to detect the falls even before they happen. These studies have successfully handled the problem of fall detection keeping sensing methods at bay. Early Fall Prediction systems have come into existence despite minimal clinical studies due to restrictions. In this context, the main contribution of this article is to give a thorough overview on elderly falls and to suggest a general classification of fall-related systems based on their sensor deployment. An extensive research scheme has been done from fall detection to fall prevention systems have been also conducted based on this common ground classification. Data processing techniques for fall detection and fall prevention tracks are also emphasized. The aim of this study is to deliver medical technologists in the field of public health a good understanding regarding fall-related systems.
Prediction of Diabetics using Machine Learning
Authors – Associate Prof. Hemamalini.S ,Essak Koil Gunaseelan.S, Jagannathan.T.N, Joseph Raja.J
Abstract- – Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method for that. One of these methods is using artificial intelligence systems and in particular is the use of Artificial Neural Networks (ANN). So in this paper, we used artificial neural networks to predict whether a person is diabetic or not. The criterion was to minimize the error function in neural network training using a neural network model. After training the ANN model, the average error function of the neural network was equal to 0.01 and the accuracy of the prediction of whether a person is diabetics or not was 87.3%.
Medical Image Diagnosis by Histogram Feature and Neural Network
Authors – Monika Manjhi, Asst. Prof. Sumit Sharma
Abstract- – Image diagnosis for medical practioner help to understand the patient condition as per symptoms. This analysis is depends on experience of doctor. To improve health services automation is involve for the medical image diagnosis as per type of report / disease. This paper has proposed a mathematical model that extract visual features from the image for the training dataset. Extracted information is further process to normalize data as different feature has different value set. Normalized values were used for the training of neural network and gives an trained model that classify input testing image into infected / normal category. Experiment was done on real dataset of malaria images. Result shows that proposed model has increased the comparing parameter values than other existing model.
Forecast Bit Coin Price & Analysis Using Deep Learning & Block chain
Authors – Rohan Chawre, Fardin Khan, Yogita Thorat, Nikita Nimbekar, Achal Pise, Ashwini Raut, Rashmi Ghate
Abstract- – Time collection expectation performs a significant process within side the Bit coin marketplace due to risky attributes. As of late, profound neural agencies with reducing facet methods, for example, companies have induced concentrates on that display fruitful execution in specific fields In this paper, a collection empowered Long Short-Term Memory (LSTM) with specific time span fashions is proposed for foreseeing Bit coin cost. In spite of the reality that hour and second informational series are displayed to offer mild shifts, daily statistics has typically a deterministic shift. As such, then simple-enabled LSTM community layout took within side the singular features and impact on cost forecasts from each informational series. Test consequences with actual global size facts display that this mastering structure efficaciously forecasts prices, particularly in unstable time any such surprising cost fall.
Secure Messaging Application
Authors – Dr. Priyanka Dubey
Abstract- – The online chatting application is a web-based management application. In this system, the user can review the chatting system. In this system, the owner can make their account online and have a good conversation in the chat. The emergence of computer networks and telecommunication technologies allow people to communicate in a new way. Chatting is a method of using technology to ring people and ideas together despite the geographical barriers. The technology has been available for years, but the acceptance was quite recent. The group chat application will allow multiple users to connect to the server and chat with all other online users. The app works in a broadcast fashion. This means that messages from a user are broadcasted to other users. Messaging apps are surging in popularity. The past few years have brought apps like WhatsApp, Telegram, etc. It is the server that used local host to host to host website.
Analyzing Tweets about Food using a Machine Learning Classification Algorithm
Authors – M.Tech. Scholar Rema Varma, Asst.Prof. Megha Gupta Jat
Abstract- – Most individuals exchange knowledge through social media nowadays. Twitter users offer opinions as tweets. Daily live news, brand, product, company, and location reviews let communities communicate. This article does sentiment analysis utilising actual data from Twitter API and eliminating bogus news from kaggle twitter data sets. What’s harder to analyse? Input twitter data will be tokenized and stop words removed. After applying feature extraction techniques to input data, each word is prioritised for positive/negative classification. After that, noisy data into training models. This article compares machine learning classifiers for Twitter sentiment analysis. KFC and McDonald’s are both popular study topics with 14,000 tweets. We trained with 10000 tweets and tested with 4000. These models’ results were evaluated using our suggested method’s parameters. This research analyses performance in sentiment analysis.
An Application of Convolutional Neural Networks to the Detection of Glaucoma
Authors – M.Tech. Scholar Akanksha Kumayu, Asst. Prof. Lokendra Jat, Asst. Prof. Megha Gupta Jat
Abstract- – Glaucoma is a condition that pertains to the vision of human eye. This sickness is known as the irreversible condition that leads into the visual degradation. Many deep learning(DL) models have been created for the appropriate identification of glaucoma so far. SO here we have shown an architecture for the appropriate glaucoma identification based on the deep learning with making use of the convolutional neural network (CNN). The separation between the patterns created for the glaucoma and the non glaucoma may be discovered out with the help of the CNN. The CNN gives a hierarchical structure of the pictures for distinction. Proposed work may be reviewed using total six levels. Here we also applied the dropout method for the effective performance in the glaucoma identification. The datasets utilised for the experiments are the SCES and the ORIGA. Accuracy values of 99.12% were achieved for the proposed technique when applied to the ORIGA dataset, and 99.37% were obtained when applied to the SCES dataset. Moreover, during the evaluation in which we made use of the most recent and cutting-edge tools, we determined that the accuracy was 86% for ORIGA and 91% for the SCES dataset.
Fibre Reinforced Concrete
Authors – M.Tech.Scholar Salim, Asst. Prof. Sonu Mor
Abstract- – In several civil engineering applications, fiber reinforced concrete (FRC) has shown to be quite effective. Slabs on grade, architectural panels, precast goods, offshore buildings, and structures in seismic zones, thin and thick repairs, crash barriers, footings, hydraulic structures, and several more applications have all seen success with the usage of fiber reinforced concrete too far. As a practical means of enhancing concrete’s performance, fiber reinforced concrete (FRC) is gaining popularity. Fibers are currently being specified in tunneling, bridge decks, pavements, loading docks, thin unbonded overlays, concrete pads, and concretes slabs. These applications of fiber reinforced concrete are becoming increasingly popular and are exhibiting excellent performance. Concrete that has been reinforced with fibers (also known as FRC) has more structural stability. It has uniformly dispersed, short discrete fibers that are randomly orientated. Polypropylene fiber (PPF) is one kind of fiber. An insight of fiber reinforced concrete’s strength is provided by this study. Fiber reinforced concrete’s mechanical characteristics and durability.
VLSI Architecture of Filter for Image Denoising with Performance Enhancement
Authors – Research Scholar Aarti Sharma, Asst. Prof. Shweta Garde
Abstract- – Image and video signals are adulterated by motivation clamor during obtaining or transmission. Consequently there is a requirement for an efficient and consumer friendly motivation commotion expulsion procedure. Because of the commotion issue the general exhibition down or here and there it disappointment. This paper presents an efficient VLSI filter execution for picture denoising with execution upgrade. The test pictures are of various size and goal. The denoising execution is estimated; unbiasedly top sign to commotion proportion and abstractly visual nature of picture and it is found that Daubechies 6-tap wavelet filter wavelets beat. Simulation is performed using MATLAB and VLSI –Xilinx 14.7 software. The image process to be visualizes using the MATLAB software and the filter architecture to be optimized using the Xilinx version-14.7.
Library Management System Using RFID Technology
Authors – Prof. Prachi Admane, Mr. Akshay Patil, Mr. Ajay Rathod , Mr. Suraj Patil, Mrs. Aishwarya
Abstract- – Radio frequency identification (RFID) is a rapidly emerging technology which allows productivity and convenience. Radio Frequency Identification (RFID) is a new generation of Auto Identification and Data collection technology which helps to automate business processes and allows identification of large number of tagged objects like books, using radio waves. This paper proposes RFID Based Library Management System that would allow fast transaction flow and will make it easy to handle the issue and return of books from the library without much intervention of Manual book keeping which benefits by adding properties of traceability and security. The proposed system is based on RFID readers and passive RFID tags that are able to electronically store information that can be read with the help of the RFID reader. This system would be able to issue and return books via RFID tags and also calculates the corresponding fine associated with the time period of the absence of the book from the library database.
E-Commerce in Yemen: Reality and Challenges
Authors – Marwan M. Al-Falah, Prof. Ahmed Al-Nasheri
Abstract- – This study aims to understand the development of electronic commerce and analyze the current trends of electronic commerce in Yemen as a model for the least developed countries. There are very few studies on the adoption of e-commerce in Yemen. Therefore, in this study, we presented the latest factual data and trends related to its various aspects. As well as finding a set of guidelines or recommendations on the best practices of e-commerce adoption that may help Yemeni e-commerce companies.
An Alarm based Driver Drowsiness
Detection system
Authors – G.Prethija, V.Subbulakshmi
Abstract- – Normally when a person doesn’t get proper rest, they fall asleep while driving and this leads to fatal accidents. The objective of the detection system is to overcome the problem related to accidents when drivers experiencing fatigue which leads to a need to design a system that keeps the driver focused on the roads. This is a different approach for measuring the drowsiness .The eye lid closure is computed to detect drowsiness. So, when the closure of eye exceeds a certain threshold then the driver is identified to be drowsy. A deep learning method namely CNN technique is used to estimate the driver status and controls the car accordingly. Several OpenCV libraries (including Haar-cascade) are used for implementation.
Photovoltaic MPPT Based on Multilayer Extreme Learning Machine
Authors – Moh. Khatib, Lecturer Bambang Sri Kaloko, Lecturer Bambang Sujanarko
Abstract- – This article will discuss the system design to maximize photovoltaic power, using MPPT technique based on Multilayer Extreme Learning Machines (ML-ELM). The system is designed using the training data output from the Incremental Conductance (IC) method. By including the irradiance value and temperature time function, ML-ELM produces good performance, which is characterized by a faster turnaround time and 10% higher energy gain than the IC method.
Influence of Residential and Industrial Discharges on Physical and Chemical Parameters of Valliyaru River, Kanyakumari District, Tamilnadu, India
Authors – Asst. Prof. A. Kumar , Asst. Prof. Y. C. Viji, Asst. Prof. A.J Sunija
Abstract- – Valliyaru is one of the major water sources of Kanyakumari District, India. Originating from Vellimalai hills; the southernmost tip of Western Ghats of India, this perennial river travels across 18 km, before pouring into Arabian Sea. It flows through thickly populated and vast agricultural area, serving as a source of water for domestic and agricultural needs. The physical, chemical and microbial parameters of the river were measured at five different locations in its course, from March to August, during the south west monsoon period of 2013. The results of these measurements are compared with World Health Organization (WHO) standards. Regression analyses for 22 different water quality parameters were performed and the correlation coefficients were calculated. Study reveals that most parameters obey WHO standards and the water from the river is well suited for agriculture and domestic application.
Education in AI Era: A Novel Approach to Enhance Learning and Development
Authors -Hitesh Hinduja, Shubham Kakde, Aravind Naidu
Abstract- – The increasing importance of education has led to enormous growth in the education industry. India itself has a population of around 500 million in the age group of 5-24 years, hence providing a great opportunity for the growth of the education sector. Due to its major impact, this industry has witnessed some major investments and developments in the past and it still has a lot of potential for further development. The fundamental objective of this paper is to understand the modern education system and cater to the issues in the system by developing AI-empowered solutions. In this paper, we have addressed some of the major challenges faced by students, teachers, and university management. Furthermore, we propose solutions that facilitate Artificial Intelligence to develop intelligent teaching and learning systems. We believe that adaptation of the proposed ideas will aid in the growth and development of the current education system.
Applications of SOHAM Transform in Chemical Sciences
Authors -Dinkar P. Patil, Prinka S. Wagh, Pratiksha Wagh
Abstract- – We use Soham integral transform to solve the problems in chemical sciences.
Review on Power System DG Protection and Power Scheduling Using Breaker Triggering Time Controlling
Authors – M. Tech scholar Amit Yadav, Asst. Prof. Deepak Bhataniya
Abstract- – One of the biggest changes happening to the distribution system is the introduction of distributed generation. One of the drivers behind this movement is the need to integrate renewable energy sources into the distribution system. Traditional protection schemes used is the distribution system need to be re-evaluated with the integration of DG associated with customer loads. The interconnection protection varies widely depending on factors such as: generator size, point of interconnection to the utility system (distribution or sub-transmission), type of generator (inductor, synchronous, asynchronous) and interconnection transformer configuration. Newer DG systems are utilizing electronic power converters which results in special consideration for DG protection. The impact of DG on existing systems must be examined through detailed simulations and protection studies. Examples of interconnection protection schemes are examined.
Raspberry Pi-GPIO Basics with LED Light
Authors – Dr. Priyanka Dubey
Abstract- – These days computer is the basic need for every people in every field across the world. Raspberry pi is small size or credit card sized computer. The Raspberry Pi is a small computer that can do lots of things. You plug it into a monitor and attach a keyboard and mouse. There is a Broadcom BCM2835 SOC to integrate major functional element into single chip. We can control any hardware equipment through Raspberry Pi by using GPIO pins. Python programming languages are preferred to program the Raspberry Pi. It allows monitoring and controlling of hardware equipment. There are three series of Raspberry Pi, and several generations of each have been released. Raspberry Pi SBCs feature a Broadcom system on a chip (SoC) with an integrated ARM-compatible central processing unit (CPU) And on-chip graphics processing unit (GPU), while Raspberry PI Pico has a RP2040 system on chip with an integrated ARM-compatible central processing unit (CPU)). Raspberry pi is a series of small single-board computers developed in the United Kingdom by the Raspberry Pi foundation in association with Broadcom. The Raspberry pi project originally learned towards the promotion of teaching basic computer in schools and in developing countries. This paper explains the Raspberry Pi with the explanation of GPIO pins, and through it showing the working or blinking of LED light. The main task of doing it is that through it we can make home automation project, by which home smart gadgets can be controlled from anywhere with the help of relay. The paper mainly emphasis on the home automation project with the help of LED light and the coding is used to accomplish the task. The Raspberry Pi has two zones of GPIO pins, which are the connections between the Raspberry Pi, and the real world. Output pins are like switches that the Raspberry Pi can turn on and off. It can also send a signal to another device.
Simulated Cluster-Based Covid-19 Control-mechanism through Smartphone-Based Body Area Networks
Authors – Dr. Gatete Marcel, Harubwira Flaubert
Abstract- – Since its emergence in December 2019, Corona Virus disease-2019 (COVID-19 has impacted several countries in the world, and it’s now growing as a global public threat. To control this type of virus and reduce its spreading among the world population is somehow difficult due to its various routes of transmission i.e. direct contact, droplet, and possible aerosol transmissions, and to various factors including increasing population density, closer social contact, and interactions. Other factors which make COVID-19 control difficult, it is its regular variants that have been identified and have often raised so many problems as more people become at risk of getting sick. COVID-19 vaccines do not work as even vaccinated people have chances to get attacked too and even contaminate other people. To detect the presence of this virus, the healthcare sector in collaboration with Information Technology partners has invented various Covid-19-presence detection devices using various algorithms that have played major roles in its containment. In this research work, we use a different approach, through simulations, we develop a Cluster-Based Covid-19 Control-mechanism through Smartphone-Based Body Area Networks (CCCSBAN) protocol, through this mechanism we simulate a body sensor that can detect Covid-19 and its variants on people’s Body Temperature (BT), Oxygen Saturation (OS), Blood Pressure (BP),and Respiratory Rate (RR) on user’s smartphones. This novel scheme divides the populations into multiple clusters based on the severity of their vital signs; a computationally efficient approach; its sub-module, is used to enable an effective cluster-based quarantine strategy. The presence of the virus is detected by the biosensor which can detect the presence of tiny amounts of the virus and its variants. This proposed mechanism is a reliable mechanism which can provide information to people and advice them to undertake a medical COVID test and self-isolate or get isolated by authorities. This successful prototype can be further developed and its effectiveness demonstrated through experiments on real social contact networks in hardware by IT geeks in partnership with heart-care institutions. It can then be delivered to hospitals, with future applications in other essential worker and high-traffic settings including aged care, quarantine hotels, airports, and schools. This instant COVID-19 detection, once implemented on real devices would reduce the risk of asymptomatic spreading to prevent outbreaks and recurring lockdown.
A Study of Problems of Working Women’s in Kolhapur District Using Statistical Methods
Authors – Associate Prof. Prakash S. Chougule, Asst. Prof. Smt. A. S. Bhosale, Smt. Sonam. A. Amate,
Miss Amruta A. Shete, Miss. Amruta D. Herle, Miss. Rani D. Suryavanshi
Abstract- – The role of working women has changed throughout the world due to economic conditions and social demands. These has results in a scenario in which working women have tremendous pressure to develop a carrier as robust as their male counterparts while sustaining active engagement in personal life . the ever increasing work pressure is taking a ring on the working women living them with less time for themselves . the increasing responsibilities on the personal front with technology blessing like advanced mobile phones note pads etc. The work life balance is term used to describe practices in achieving a balance between professional work and family work lives. The demands and pressures of work make difficult to stretch time for balancing work life activities. In this background the present study was undertaken to determine the work life balance of working women. The sample consists of 100 career women working in Kolhapur city the data was collected from respondent through well designed questionnaire. Personal life also create as stress on personal and professional front in this knowledge age this affect the persons physical, emotional and social well –being thus achieving work life balance is a necessity for working women to have good quality of life this paper is an attempt to explore the tough challenges faced by working women in maintaining of balance between their personal and professional life.
Vehicle Tracking for Theft Detection Using Embedded Systems
Authors – Nanthaan Jayaprakash, Mughundhan S, Mohamad Tharick S
Abstract- – The quantity of private vehicles is expanding step by step and consequently the significance of following and burglary anticipation. As of late the vehicle global positioning frameworks are getting wide ubiquity and can be utilized in following in the event of taken vehicles. Ongoing applications like Vehicle Tracking System is created utilizing Arduino board with a microcontroller. It have fostered a vehicle global positioning framework with a Smartphone which is more affordable and dependable when contrasted with the current framework as there is no requirement for additional equipment. The goal is to foster an application for following vehicles, which will help the taxi proprietors to follow their vehicle constantly and to anticipate the area of the vehicle on account of a faltering GPS (Global Positioning System). Time series forecast calculation is utilized to foresee the area of the vehicle assuming GPS is in off mode. The vehicle global positioning framework introduced will refresh the GPS directions of the vehicle proceeded to the cloud, and this information can be utilized for anticipating the area of the vehicle if there should arise an occurrence of crisis. This framework can likewise be utilized to create the bills in the wake of completing the cargo as the distance voyaged, which can be determined from the scope and longitude information. The GPS information can be planned to the Google guides to follow the area progressively. Contrasted and the current framework, this framework is enjoying the benefit of area forecast from the noteworthy area information, and the expense is decreased by close to half.
Solar Passive Features of Himurja Office Building at Shimla
Authors – Shashi Dhar
Abstract- – The Solar Passive HIMURJA building is one of the excellent solar passive designed buildings in India. It has been integrated with a number of Solar Passive features like Thermosyphoning Air Heating Panels, Sun Spaces, double glazed windows on the southern facade. It has an air lock lobby at the entrance; the northern wall and the roof are insulated with 40 mm thick glass wool and have no windows on this side. The monitoring results show that these solar passive features are keeping the indoors comfortable throughout the winters.The Solar Passive HIMURJA building is one of the excellent solar passive designed buildings in India. It has been integrated with a number of Solar Passive features like Thermosyphoning Air Heating Panels, Sun Spaces, double glazed windows on the southern facade. It has an air lock lobby at the entrance; the northern wall and the roof are insulated with 40 mm thick glass wool and have no windows on this side. The monitoring results show that these solar passive features are keeping the indoors comfortable throughout the winters.
A Novel Approach to Classification Capacity Urban and Rural Roads with Detection of Traffic Noise across Higher Density
Authors – Harish Kumar Verma, Prof. Jitendra Chouhan
Abstract- – A comprehensive methodology for modelling the heterogeneous traffic is presented in this article. Considering the no-lane discipline and the presence of various sizes of vehicles, several microscopic and macroscopic traffic variables are analyzed for their suitability in describing the heterogeneous traffic. Applicability in the modelling process and the feasibility in collecting field data are the important criteria used in deciding the suitable traffic variables. In place of occupancy, its variant termed as area occupancy was found to be suitable in describing the heterogeneous traffic. Vehicle size, mechanical characteristics, lateral distribution of vehicles and the lateral gaps maintained by them are found to be more suitable microscopic traffic variables. Data on these variables have been used in modifying the cell structure and the updating procedures of the KNN-based traffic flow model. A customized data collection technique has been used in collecting the field data on these variables. The modified KNN model with the relevant parameter values has been used in simulating the flow.
Intelligent Farming Robot
Authors – Syed Ghouse
Abstract- – The purpose of this paper is to demonstrate how traditional agriculture can be transformed into smart agriculture by using a smart device that is outfitted with sophisticated updated technologies, enabling it to carry out nearly all farming tasks quickly and easily and produce the anticipated results of high-quality work and increased productivity. The Arduino will be connected to a variety of sensors that are used to remotely operate the robot and set a timer for each task that it is intended to carry out. The goal of this project is to develop a smart gadget that will help farms become more productive, enhance crop quality overall, and make farming job safer and easier so that future generations will want to engage in it in agriculture and develop it. The little farm robot’s design, implementation, and successful operation are the intended goals of this work. As it is anticipated that this robot, which is fitted with an accurate sensor, would be able to determine the separations between each seedling while the planting process is taking place. After programming the robot and connecting it to the computer, it should also be able to coordinate irrigation and fertilizing activities according to the needs of the plant using the data stored in the electronic chip. The desired outcomes of this project are the design, implementation, and successful operation of the mini farm robot. As it is expected that this robot, equipped with an accurate sensor, will be able to calculate the distances between each seedling and another during the planting period. It is also expected to have the ability to organize irrigation and fertilization operations according to the need of the plant, through the information stored in the electronic chip after programming the robot and connecting it to the computer.
Genetic Algorithm Based Routing and Adamic Adar Trust for Secured IOT Network
Authors – Research Scholar Shailendra Kumar Tiwari, Asscoiate Prof. Dr.Ravindra Kumar Tiwari
Abstract- – IOT devices ave plays an important role in daya to day life. So its network need lot of protection from attackers who may increase the load. This paper has developed a genetic algorithm based model that estimates the trust value of the nodes on the basis of social trust evaluation function adamic adar. At the same time network communication need packet transfer, hence each of such packets path is identify by the genetic algorithm. As IOT network is dynamic in nature, so genetic algorithm provides a good path in short time. Experiment was done on different artificial network conditions and results shows that proposed model has improved the work performance.
Applications of KUSHRE Transform in Chemical Sciences
Authors – M.Tech. Scholar Punam Solanki, Asst. Prof. Ramiz Sheikh
Abstract- – Plant disease detection systems may be able to automatically find problems on leaves and stems by using imaging technology. This would improve the health of farm plants. These devices watch the leaves or stem of the plant and let the user know if anything changes. This study looks at different ways to find plant diseases. Convolutional neural networks (CNNs) that use deep learning are better at classifying images. This Thesis uses pre-trained deep learning to find plant diseases. It was inspired by CNN’s success with image classification. This work is important in two ways: Predictions for a dataset can be made using the most powerful large-scale architectures we have today, like AlexNet and GoogleNet, which are used to find sick people and for baseline and transfer learning. Using data from CNN’s website, a model was made and tested. Training, testing, and tests show that the recommended architecture can increase the GoogleNet model to 99.10 percent. It is more accurate than other models.
Detection of Plant-Leaf Diseases with the Application of Deep Learning Techniques
Authors – Dinkar P. Patil, Prinka S. Wagh, Pratiksha Wagh
Abstract- – We use Kushare integral transform to solve the problems in chemical sciences.
Food Review of Twitter Data Analysis using Machine Learning Classification Technique
Authors – M. Tech. Scholar Anil Verma, Assistant Professor Megha Jat
Abstract- – Nowadays, maximum people share information through social media around the world. For example, twitter platform where users post their opinions, read posts in form of tweets. such as daily live news, brand, product review, companies review, places and everything because this is a way of interacting with communities. Aim of this paper we are performing a sentiment analysis using collecting real data from twitter API and removing the fake news from kaggle twitter data sets. which are more difficult to analyze? Data will be preprocessed with tokenizations and stop words will be removed from twitter data set of given input data set. After then applied feature extraction algorithms of given input data and priority to each word is assigned to classify positive, negative. After that the noisy data into several models for training of data. For this sentiment analysis we are comparing different machine learning classifiers with twitter data in this paper. In the KFC and McDonal’s both are data sets which are more popular subjects and 14000 tweets for our research. we have used 10000 tweets for training purposes and 4000 tweets for testing purposes. Find the result from these models was tested using different parameters from our proposed method. Using this study, we can contribute to the field of sentiment analysis by analyzing performance.
Wormhole Attack Detection in MANET Using a Trusted Method
Authors – M. Tech. Scholar Anil Verma, Assistant Professor Megha Jat
Abstract- – Nowadays, maximum people share information through social media around the world. For example, twitter platform where users post their opinions, read posts in form of tweets. such as daily live news, brand, product review, companies review, places and everything because this is a way of interacting with communities. Aim of this paper we are performing a sentiment analysis using collecting real data from twitter API and removing the fake news from kaggle twitter data sets. which are more difficult to analyze? Data will be preprocessed with tokenizations and stop words will be removed from twitter data set of given input data set. After then applied feature extraction algorithms of given input data and priority to each word is assigned to classify positive, negative. After that the noisy data into several models for training of data. For this sentiment analysis we are comparing different machine learning classifiers with twitter data in this paper. In the KFC and McDonal’s both are data sets which are more popular subjects and 14000 tweets for our research. we have used 10000 tweets for training purposes and 4000 tweets for testing purposes. Find the result from these models was tested using different parameters from our proposed method. Using this study, we can contribute to the field of sentiment analysis by analyzing performance.
Design and Fabrication of Steering System for Trike
Authors -Asst. Prof.Vipul Jain, Asst. Prof. Amit Kesheorey, Asst. Prof. Hitesh Koshti
Abstract- – This work consists of designing, drafting, analysis, prototyping, general iterations related to linkages. The steering system of a vehicle consists of two subsystems; A steering rod that matches the angles of rotation of all steering wheels, and an actuating subsystem that connects the driver’s steering wheel to a movable element of the steering rod. In vehicles with rigid steering axles, the most commonly used tie rod is a simple mechanism; we will design this mechanism as an anti-Ackermann linkage mechanism involving 6 joints. An Anti-Ackermann steering linkages for short wheelbase, three wheel vehicles base been developed. Link coordinate steering angle of each wheel, coordinate steering angle of each wheel in the range of 180 degrees with minimum misalignment between wheels. Control of steering angles is accomplished using a single linear actuator. Control complexity is lower compared to four wheel systems using individually controlled steering actuators for each wheel. For the electric wheelchair base, a prototype linkage was designed and tested to achieve a minimum turning radius while maintaining maximum stability.
The Role of Reg Tech in Streamlining Compliance and Risk Management
Authors -Kinil Doshi
Abstract- – Expression Reviews in the form of sentiments or rating for item used or movie seen is the part of human habit. These reviews are easily available on different social websites. Based on the interest pattern of user, it is important to recommend him the items. Till today’s, a lot many recommendations System are designed using several machine learning algorithms. Still, faster convergence speed, prediction accuracy, suitable recommendation system that must be resolved using hybrid algorithm. In this report we propose a system that uses Feed Forward Neural Network. In this research we obtained for proposed technique are compared using the testing parameters like precision, recall, accuracy, mean absolute error with the result of feed forward neural network, multi modal deep learning, genetic algorithm.
DOI: /10.61463/ijset.vol.10.issue3.268