International Conference Intelligent Sustainable Systems 

About: International Conference Intelligent Sustainable Systems is an academic conference. The conference publishes majorly in the area(s): Computer science & Feature extraction. Over the lifetime, 585 publications have been published by the conference receiving 3056 citations.

Depression detection using emotion artificial intelligence

Abstract: Depression is a leading cause of mental ill health, which has been found to increase risk of early death. Moreover it is a major cause of suicidal ideation and leads to significant impairment in daily life. Emotion artificial intelligence is a field of ongoing research in emotion detection, specifically in the field of text mining. The advent of internet based media sources has resulted in significant user data being available for sentiment analysis of text and images. This paper aims to apply natural language processing on Twitter feeds for conducting emotion analysis focusing on depression. Individual tweets are classified as neutral or negative, based on a curated word-list to detect depression tendencies. In the process of class prediction, support vector machine and Naive-Bayes classifier have been used. The results have been presented using the primary classification metrics including F1-score, accuracy and confusion matrix.

A Study on Support Vector Machine based Linear and Non-Linear Pattern Classification

Abstract: The best way to acquire knowledge about an algorithm is feeding it data and checking the result. In a layman's language machine learning can be called as an ideological child or evolution of the idea of understanding algorithm through data. Machine learning can be subdivided into two paradigms, supervised learning and unsupervised learning. Supervised learning is implemented to classify data using algorithms like support vector machines (SVM), linear regression, logistic regression, neural networks, nearest neighbor etc. Supervised learning algorithm uses the concepts of classification and regression. Linear classification was earlier used to form the decision plane but was bidimensional. But a particular dataset might have required a non linear decision plane. This gave the idea of the support vector machine algorithm which can be used to generate a non linear decision boundary using the kernel function. SVM is a vast concept and can be implemented on various real world problems like face detection, handwriting detection and many more. This paper surveys the various concepts of support vector machines, some of its real life applications and future aspects of SVM.

HealthSense: A medical use case of Internet of Things and blockchain

Abstract: Blockchain and Internet of things are the most promising and upcoming technologies. Blockchain is a distributed, peer to peer database forming a chain between multiple blocks of data. The internet of things works on a similar paradigm where multiple devices are connected to the internet forming a network of networks. Combined together they offer solutions for various problems, especially in the field of healthcare where quick reporting of data or results is of utmost importance. Recent studies have proven that delays in providing healthcare are directly linked to patient confidence and chances of recovery. An unreliable storage of health records has only aggravated the problem. Our paper aims to provide a solution for these issues by proposing a Blockchain-Internet of things model where a bio-sensor measures and collects real time data with respect to a patient's medical status and stores it in the blockchain. In this way quick reporting and tamper proof storage of data occurs. By deploying a smart contract the final hospital bill can be calculated along with insurance coverage. This would negate the need of third party providers and create a transparent system. Our paper also proposes the use of Inter planetary file system to store discharged patients records thus reducing the load on the actual blockchain. Overall this will surely benefit patients and doctors alike by creating a safe and transparent environment along with quick response to a patient's need.

FPSMM : Fuzzy probabilistic based semi morkov model among the sensor nodes for realtime applications

Abstract: Emerging technology in terms of hardware and software over wireless sensor network result in various applications The main limitation of sensor nodes are less life span, more energy consumption. Many papers has explained about the stochastic model but nothing came out well. This leads to the motivation of our research work by proposing fuzzy based semi morkov model. This proposed model is very apt for more power management in evebt driven condition. The performance analysis part shows that our proposed work contribute better life time performance.

A Report on the Impact of Information Technology and Social Media on Covid–19

Abstract: The destruction caused by the COVID -19 virus to the human race is beyond the imagination. This article elucidates how COVID–19 is identified as a threat to human life. The statistical report is given for the some of the countries which are highly affected by this pandemic. The medical advancements and the impact of insufficient medical facilities, are available even in the well-developed nations. The role of Information Technology (IT) in the development of various effective algorithms for the diagnosis and prevention of the disease is discussed. This research article also covers the responsibilities of the various social mediaalong with their vulnerable efforts in carrying awareness to society.