RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501EEG based Emotion Recognition and Classification: a Review1101155010.47392/irjash.2021.131ENRamprasad KumawatDepartment of Electrical and Electronics Engineering, Mandsaur Univesity, Mandsaur, Madhya Pradesh, India.Manish JainAssociate Professor, Department of Electrical and Electronics Engineering, Mandsaur Univesity, Mandsaur, Madhya Pradesh, India.Journal Article19700101<em>Emotion plays a vital role in medical research and interpersonal communication. Essentially feeling can be communicated verbally like discourse or non-verbally like outward appearance and physiological signals. A human emotion is complex physiological state which involves a physiological response, a person’s experience and behavioral change. EEG measures electric current that are generated due to neuronal activities in the human brain. This paper provides an overview of comparative study of various techniques of emotion recognition from EEG signals. Our analysis is based on extracted features and classification methods of emotion recognition. We intended that, this study will be useful for newly researchers those entering in the field of emotion recognition.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Converging Blockchain and AI technology-based Automated and Decentralized (A&D) Trust Management System using Face Detection11151155110.47392/irjash.2021.132ENPujah BalasubramaniamMeenakshi Sundararajan Engineering College, Chennai, Tamil Nadu, India.Gokilavani SagadevanMeenakshi Sundararajan Engineering College, Chennai, Tamil Nadu, India.Journal Article19700101<em>Face detection systems are growing exponentially. Newly emerged technologies are also being involved in the management applications. But they had failed to compensate at least anyone of the essential aspects of the system such as scalability, security, personalization, etc. This paper presents a fundamental platform that provides the ways and techniques to intelligently use the integration of Artificial Intelligence and Blockchain in which AI is used to detect and recognize the face and Blockchain maintains the tamper-proof records. This convergence will provide a tamper-proof and rapidly working A&D access management system for a trust management system that can be used for attendance in an organization & for many other purposes.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Channels Based Platform for Text and Video Conferencing16201155210.47392/irjash.2021.133ENRohit MotghareDepartment of Information Technology, S.B Jain Institute of Technology, Maharashtra, IndiaPrashik WasnikDepartment of Information Technology, S.B Jain Institute of Technology, Maharashtra, India.Pooja WakodeDepartment of Information Technology, S.B Jain Institute of Technology, Maharashtra, India.Kunal RokdeDepartment of Information Technology, S.B Jain Institute of Technology, Maharashtra, India.Vikki ChaudhariDepartment of Information Technology, S.B Jain Institute of Technology, Maharashtra, India.Journal Article19700101<em>Communication has become the essential part of our lives over various technologies. As the large the number of users gets connected to internet everyday it becomes one of the problem to provide better communication services to every users. Text messaging has become common and many users are getting attracted towards video meetings. Application has problem in connecting large number of users in a video meeting for the purpose of communication. In this project report a new approach to make communication easier has been proposed. Users can quickly register themselves and then can access the applications which provide users the channels functionality. A user can either create their channel or else join other channels. Inside channels they can communicate using text messaging and also video conferencing with large number of users present in a channel. Users can share their screen and text each other while attending video meeting. Application can also generate attendance report of users in channels who attended video meeting</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Footprints of Educational Technology in Higher Education21261155310.47392/irjash.2021.134ENHemalatha B DResearch Scholar, Political Science Department, Mangalore University, Mangalore, KarnatakaJournal Article19700101<em>Education is a powerful weapon which prepares the individual to face the difficulties of life, come out of poverty fear, and help to achieve status in society. At present scenario</em><em>, continuous learning and updating is very essential for everyone. As per the frequent changes in technology people also should learn continuously. Maximum members of present generation are stepping into the higher education and are growing fast due to the availability of plenty of learning resources outside the classroom. Education becomes more global by the help of internet and technological devices, applications used by the institutions, teachers and the students are really appreciable in making each and every one smart enough to lead the life in modern era. To reach the fullest potential we should encourage the use of Technology in present education. In this paper author made an attempt of analysing overall outcome of technology in education fields. </em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Classification of Brain Magnetic Resonance Images using ICA-MLP27291155510.47392/irjash.2021.135ENPranati SatapathyResearch Scholar, PG Department of CSA, Utkal University, Bhubaneswar, Odisha, India.Sarbeswara HotaAssociate Professor, Department of CA, Siksha O Anusandhan Deemed to be University, Bhubaneswar, Odisha, India.Sanjay Kumar JenaAssistant Professor, Department of CSE, Siksha O Anusandhan Deemed to be University, Bhubaneswar, Odisha, India.Journal Article19700101<em>The central nervous system controls all the functions of the body. The brain is the vital organ of our body and it can be suffered from various diseases. In order to treat various brain diseases, the physicians use Magnetic Resonance Imaging (MRI) technique in recent days for the treatment. Manual analysis and classification of brain images into normal or deceased is a tedious task. So different supervised learning techniques are used in this purpose. In this paper, Independent Component Analysis (ICA) has been used for feature reduction and Multilayer Perceptron (MLP) has been used for classification task. The experimental study is conducted on two of the brain image datasets i.e. Glioma and Alzheimer and the results suggested that ICA-MLP produced better results than MLP</em><em>.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Analyzing Of Clustering Algorithms for Achieving High Evaluation Metrics30371155810.47392/irjash.2021.136ENSarumathi S.Professor, Department of Information Technology, K. S. Rangasamy College of Technology, Tamil Nadu, India.Navinkumar K.Department of Information Technology, K. S. Rangasamy College of Technology, Tamil Nadu, India.Vadivel Kumar T.Department of Information Technology, K. S. Rangasamy College of Technology, Tamil Nadu, India.Sharan Viswanathan R.Department of Information Technology, K. S. Rangasamy College of Technology, Tamil Nadu, India.Journal Article19700101<em>In the real data world, there are various clustering algorithms available in data mining. The data available from the different data sources may be huge in instances, attributes and in different formats. The clustering algorithms available are assessed based on how the algorithm cluster the given data and find its parametric values. The clustering of data may end in inappropriate results if the algorithm is not chosen wisely. This paper proposes a comparison between diverse clustering algorithms such as K Means clustering, Mini-Batch K Means clustering, Hierarchical clustering, Bagging and Boosting by figuring out clustering strategies using high dimensional datasets on each algorithm above. After the process of data cleaning in dataset, we have clustered the datasets and compared the summary of each to showcase the comparability of difference in their strategical values such as Clustering tendency, clustering quality and data driven approach for evaluating the number of clusters, Normalized Mutual Information (NMI) metric and provide an idea to choose the algorithm for clustering the data effectively. And as a result, Local Clustering Coefficient (LCC) with K-means clustering bunching method performs better than the other clustering algorithms and the results are reported.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Causal Discovery using Dimensionality Reduction Partial Association Tree38431159510.47392/irjash.2021.137ENSreeraman YResearch Scholar, Dept. of CSE, Pondicherry Engineering College, Puducherry, India.S. Lakshmana PandianAssociate Professor, Dept. of CSE, Pondicherry Engineering College, Puducherry, India.Journal Article19700101<em>Decision tree is a model to classify data based on labelled attribute values. This model is a supervised learning approach through which one can classify a new entry into an appropriate class. If we want to know the cause behind this classification then decision tree cannot provide the same. When we infer causes behind the classification then they will provide a rich knowledge for better decision making. Causal Bayesian Networks, Structural Equation Models, Potential Outcome Models are the some of the models that are used to get causal relationships. These models need experimental data. But it is not possible/ it is very expensive to conduct full experiments. So a model is needed to identify causes from effects from observational data rather than experimental data. In this paper a novel approach is proposed for causal inference rule mining which can infer the causes from observational data in a faster way and also scalable. Statistical tools and techniques named partial association test, correlation are used to develop the model. A new way of constructing a tree called Dimensionality Reduction Partial Association Tree (DRPAT) is introduced. Sometimes the existing causality cannot be extracted where low associated dimensions are involved in data and hiding the underlying causality and this model extracts causal association in case of hidden causality in data.. The model is applied on “Cardiovascular Disease dataset” sourced from Kaggle Progression System. The result is a Partial Association Tree. From this tree one can get a set of causal rules which can form a basis for better data analytics and then the better decision making.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501EduAR– an AR based Learning Application44471161210.47392/irjash.2021.138ENKshitij JetheDepartment of Information Technology, S.B. Jain Institute of Technology, Management and Research, Nagpur, India.Aniket HedauDepartment of Information Technology, S.B. Jain Institute of Technology, Management and Research, Nagpur, India.Rohit KolankarDepartment of Information Technology, S.B. Jain Institute of Technology, Management and Research, Nagpur, India.Sahil DhobleDepartment of Information Technology, S.B. Jain Institute of Technology, Management and Research, Nagpur, India.Divyanshu MataghareDepartment of Information Technology, S.B. Jain Institute of Technology, Management and Research, Nagpur, India.Journal Article19700101<em>Being one of the hot technologies of the era Augmented reality is exponentially developing various day to day activities and learning application is one of them. EduAR is an android application that overlays the virtual objects in a physical environment. EduAR as the title suggests it will be related to education and Augmented reality. Our project will be basically for preschool and kindergarten kids. In this application we are going to provide two main features, User will put camera on the particular word for alphabet and there will be a 3D visual of the particular word in the form of image it will be a static image but will be presented are displayed in a magical way as simplifying and visualizing something new leads to easier understanding. Another feature is that the user will put a camera on the particular object or image and then it will display on screen what object is it children can have fun using this application to explore new things. This application will mainly focus on the development of young children to help them prepare for preschool and beyond.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Medicinal Plant Identification Using Deep Learning48531161310.47392/irjash.2021.139ENGeerthana R.Dept. of Computer Science & Engineering,Velammal College of Engineering and Technology Tamilnadu, India.Nandhini P.Dept. of Computer Science & Engineering,Velammal College of Engineering and Technology Tamilnadu, India.Suriyakala R.Department of Computer Science & Engineering, Velammal College of Engineering and Technology Tamilnadu, India.Journal Article19700101<em>In this paper, our main aim is to create a Medicinal plant identification system using Deep Learning concept. This system will classify the medicinal plant species with high accuracy. Identification and classification of medicinal plants are essential for better treatment. In this system we are going to use five different Indian medicinal plant species namely Pungai, Jamun (Naval), Jatropha curcas, kuppaimeni and Basil. We utilize dataset contains 58,280 images, includes approximately 10,000 images for each species. We use leaf texture, shape, and color, physiological or morphological as the features set of the data. The data are collected by us. We use CNN architecture to train our data and develop the system with high accuracy. Several model architectures were trained, with the best performance reaching a 96.67% success rate in identifying the corresponding medicinal plant. The significantly high success rate makes the model a very useful advisory or early warning tool.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Pest Detection for Rice Using Artificial Intelligence54601171010.47392/irjash.2021.140ENMadhavi GAssistant Professor, Dept.of ECE, MGIT, Gandipet, Hyderabad, Telangana, IndiaJhansi Rani A.Professor, Dept.of ECE, V.R.Siddhartha Engineering College, Vijayawada, Andhra Pradesh, IndiaSrinivasa Rao S.Associate Professor, Dept.of ECE, MGIT, Gandipet, Hyderabad, Telangana, IndiaJournal Article19700101<em>Agriculture not only provides food for humans, but it is also a major source of revenue for any nation. Millions of dollars are spent every year to protect rice crops from insects and pests that cause damage during harvest and storage. Early pest detection, which allows the crop to be protected from pest attack, is one form of crop protection. The best way to learn about the health of a crop is to examine it regularly. If pests are discovered, adequate steps may be taken to prevent the crop from suffering a major loss of yield. Early detection will help to reduce the use of pesticides and direct the pesticide selection process. It has grown into a large field of science, with a lot of work being done around the world to detect pests automatically. The typical way of inspecting the fields is with the naked eye. A farmer must manually search and assess over a vast landscape of fields, risking overlooking different affected areas and conducting thorough research across large lots. To analyse the entire area, several human experts are needed, which is both costly and time-consuming. This proposed system is mainly intended to develop an Intelligent IT-driven system using various Artificial Intelligence and Computer Vision Algorithms for precision farming, enabling the delivery of information directly to the farmer's phone, providing the details of damage localization, crop health, and needs for fertilizer and pesticide application.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Analysis of Tool Wear and Surface Roughness in Turning Operation of EN 31Steel by Taguchi Approach61671171210.47392/irjash.2021.141ENSalman KhurshidAlamDepartment of Mechanical Engineering1, Kalinga University, Naya Raipur (CG), India.Gaurav TamrakarDepartment of Mechanical Engineering, Kalinga University, Naya Raipur (C.G).Journal Article19700101<em>In the field of material removal, metal cutting is one of the most important manufacturing methods. The parametric optimization of the turning mechanism is the subject of this article. Cutting speed, feed rate, and cut depth are specific input parameters. MINITAB 18 uses a L9 orthogonal array to design the combination of these parameters. Turning operations are based on the Design of Experiment are used to assess tool wear and surface roughness. The Taguchi method was used to design and optimize the experiment. ANOVA was used to assess which cutting parameters have a major impact on surface roughness and tool wear. To optimize surface roughness and finish, EN 31 is used as a workpiece and SNMG120408MS is used as a carbide cutting tools wear .Cutting speed (40, 60, and 90 m/min), feed rate (0.1, 0.15, and 0.2 mm/rev), and cut depth are the turning parameters (0.5, 0.75 and 1.0 mm). Arm wear at each cutting edge of the tool is determined by toolmaker microscope and surface roughness is measured by Talysurf profilometer (Taylor Hobson Surtronic 3). Cutting speed is the most important tool parameter, according to the findings.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Malicious Traffic Flow Detection in IOT Using Ml Based Algorithms68761172410.47392/irjash.2021.142ENSri Vigna Hema VAssistant Professor, Information Technology, Bannari Amman Institute of Technology, Sathyamangalam, Erode, India.Devadharshini SInformation Technology, Bannari Amman Institute of Technology, Sathyamangalam, Erode, India.Gowsalya PInformation Technology, Bannari Amman Institute of Technology, Sathyamangalam, Erode, India.Journal Article19700101<em>Identifying the malicious traffic flows in Internet of things (IOT) is very important to monitor and avoid unwanted errors or the unwanted flows in the network. So, for a security to this network various machine learning algorithms (ML) has been introduced by various analyst to avoid this flow of error in the network. But, owing to the unsuitable selection of features, the ML models which introduced previously suffer from misclassify errors. So, there arises a need to study the problem of feature selection more depth to predict the accurate traffic flow observation in the network. To overcome this problem, a new structure in machine learning (ML) is introduced. So, for thisa novel features selection metric CorrAUC is suggested. So, based on this metric approach, a new feature selection algorithm CorrAUC is develop and design, it is based on wrapper technique to get features accurately by filtering to predict flow of traffic is suggested. Then, we applied multicriteria decision method called VIKOR which is used for validating the features selected for recognition the flow of traffic errors in the network. We estimate our approach by using the NSL-KDD dataset and three different ML algorithms.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Development of Battery Pack for Electric kart77821190710.47392/irjash.2021.143ENRavindra ParabDept. of Electrical&amp; Electronics Engineering, Malwa Institute of Technology, IndoreSudhanshu ChaturvediSchool of Mechatronics Engineering, Symbiosis University of Applied Sciences, Indore, India.Anuj ChouhanSchool of Mechatronics Engineering, Symbiosis University of Applied Sciences, Indore, India.Chinmay WayalSchool of Mechatronics Engineering, Symbiosis University of Applied Sciences, Indore, India.Siddharth ChandnaniSchool of Mechatronics Engineering, Symbiosis University of Applied Sciences, Indore, India.Journal Article19700101<em>This paper deals with development and application of Battery Pack for an Electric Kart. A Battery Pack is an integral part of an Electric Kart. This paper highlights the challenges in the development of a battery pack and its application. Since there is a gradual shift towards the electric vehicle from the traditional combustion engine vehicles, there is a requirement of research and improvement in the field of batteries used in an Electric Kart. This paper purely focuses on the development of a battery pack with nominal range and power output with phenomenal charging rate; keeping in mind the economic perspective of the power pack.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Agricultural Development Using Mobile App for Farmers83881202310.47392/irjash.2021.144ENKunal BawankuleDepartment of Information Technology, S.B Jain Institute of Technology, Maharashtra, India.Charudutta TekadeDepartment of Information Technology, S.B Jain Institute of Technology, Maharashtra, India.Shubham Bark BarkDepartment of Information Technology, S.B Jain Institute of Technology, Maharashtra, India.Pankaj VishwakarmaDepartment of Information Technology, S.B Jain Institute of Technology, Maharashtra, India.Journal Article19700101 <br /> <em>Most of the day-to-day activities are done using mobile apps, even the same for the farmers. The mobile apps have given many benefits to farmers starting from better land management judgements to quality yield. Farmers are using different types of apps to review the health of the crops during the crop cycle. Some of the mobile applications are developed to help the farmers in lots of ways like horticulture, crop management etc. Also, some mobile framer applications inform the farmers about the weather forecast, agricultural field opportunities, expert suggestions, answer to the questions, etc. Aloof, some of the apps also offer details related to the quality of soil, the utilization of fertilizer’s, etc.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501An IoT Based Smart Wearable Device for Women Safety89951215010.47392/irjash.2021.145ENPenchalaiah N.Assistant Professor, Dept. of Computer Science Engineering, Annamacharya Institute of Technology and Sciences, Rajampet, Andhra Pradesh, India.Susmitha M.Department of Computer Science Engineering, Annamacharya Institute of Technology and Sciences, Rajampet, Andhra Pradesh, India.Vinay Kumar Reddy C.Department of Computer Science Engineering, Annamacharya Institute of Technology and Sciences, Rajampet, Andhra Pradesh, India.Pavan Kalyan Rao D. V.Department of Computer Science Engineering, Annamacharya Institute of Technology and Sciences, Rajampet, Andhra Pradesh, India.Sreelekha D.Department of Computer Science Engineering, Annamacharya Institute of Technology and Sciences, Rajampet, Andhra Pradesh, India.Journal Article19700101<em>Women are subjected to an increasing amount of harassment these days, which is troubling. The situation is extremely serious in both developing and developing countries. As a result, it poses a serious threat to women's empowerment as well as a country's fiscal development. We are developing IoT software and an Android app to make women's movement safer in this project. By pressing the device's emergency button, women will receive immediate and comprehensive safety assistance. In the event of an incident, this system will monitor the user's location in real-time and send it to a local police station and volunteer. This device will also provide the user with the location of the nearest safe zone. Furthermore, this interface can be used both online and offline. If the user does not have access to the internet, the computer can also be used to contact the nearest police station and volunteer assistance. Arduino uno, GPS, GSM, Bluetooth, and other components make up the system. The combination of both of these factors makes this product both inexpensive and simple to use.</em>RSP Science HubInternational Research Journal on Advanced Science Hub2582-437603Special Issue ICITCA-2021 5S20210501Testing of Safe, Barium Free Mixture for Green Flare89921215110.47392/irjash.2021.146ENHari Ram GPG Scholar, Department of Mechanical Engineering, Mepco Schlenk Engineering College, Sivakasi, India.Asok S.P.Senior Professor, Department of Mechanical Engineering, Mepco Schlenk Engineering College, Sivakasi, India.S.Lionel BenestonAssistant Professor (Sr.Grade), Department of Mechanical Engineering, Mepco Schlenk Engineering College, Sivakasi, India.Journal Article19700101<em>The pollution caused due to the fire work is becoming one of the major problems in both environmental safety and human health. The greenhouse gases released during the burning of crackers causes global warming and eventually increase the temperature of the Earth’s atmosphere. The pollutants from burning the crackers cause health hazard in human being. The particulate matters in the dust such as PM2.5 and PM10 are easily inhaled by the human beings and affect the human health. So a new mixture which has less pollutant, particulate matter as compared with the existing mixture is formed with the help of Boron Carbide as fuel and Potassium Nitrate as the oxidizer. The newly formed mixture is completely Barium free and is much safer to handle than the Barium nitrate. The Boron carbide is implemented in the smoke flare and was found to have the performance as same as the existing composition. So the alternative for the Barium nitrate is proposed and various tests are done for the new mixture.</em>