Volume 3, Special Issue ICITCA-2021 5S, May 2021


EEG based Emotion Recognition and Classification: a Review

Ramprasad Kumawat; Manish Jain

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue ICITCA-2021 5S, Pages 1-10

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.

Converging Blockchain and AI technology-based Automated and Decentralized (A&D) Trust Management System using Face Detection

Pujah Balasubramaniam; Gokilavani Sagadevan

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue ICITCA-2021 5S, Pages 11-15

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.

Channels Based Platform for Text and Video Conferencing

Rohit Motghare; Prashik Wasnik; Pooja Wakode; Kunal Rokde; Vikki Chaudhari

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue ICITCA-2021 5S, Pages 16-20

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

Footprints of Educational Technology in Higher Education

Hemalatha B D

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue ICITCA-2021 5S, Pages 21-26

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, 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.

Classification of Brain Magnetic Resonance Images using ICA-MLP

Pranati Satapathy; Sarbeswara Hota; Sanjay Kumar Jena

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue ICITCA-2021 5S, Pages 27-29

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.

Analyzing Of Clustering Algorithms for Achieving High Evaluation Metrics

Sarumathi S.; Navinkumar K.; Vadivel Kumar T.; Sharan Viswanathan R.

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue ICITCA-2021 5S, Pages 30-37

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.

Causal Discovery using Dimensionality Reduction Partial Association Tree

Sreeraman Y; S. Lakshmana Pandian

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue ICITCA-2021 5S, Pages 38-43

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.

EduAR– an AR based Learning Application

Kshitij Jethe; Aniket Hedau; Rohit Kolankar; Sahil Dhoble; Divyanshu Mataghare

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue ICITCA-2021 5S, Pages 44-47

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.

Medicinal Plant Identification Using Deep Learning

Geerthana R.; Nandhini P.; Suriyakala R.

International Research Journal on Advanced Science Hub, 2021, Volume 3, Issue Special Issue ICITCA-2021 5S, Pages 48-53

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.