Sourabh Shastri

Sourabh Shastri
University of Jammu · Department of Computer Science and Information Technology

Ph.D.

About

36
Publications
79,555
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312
Citations
Citations since 2016
29 Research Items
312 Citations
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Introduction
Sourabh Shastri completed his Ph.D. degree in Computer Science from University of Jammu under the guidance of Professor Vibhakar Mansotra. Presently, he is working as Sr. Assistant Professor in Department of Computer Science and IT, Kathua Campus, University of Jammu, Jammu & Kashmir, India. His research areas are: Algorithms and Data Structures, Data Mining, Machine Learning and Deep Learning. Contact Email: sourabhshastri@gmail.com

Publications

Publications (36)
Article
Ensemble learning is one of the powerful machine learning approaches that is generally used to strengthen models by combining the performances of several weak learners. It holds a great potential for solving umpteen problems in healthcare domain by enabling health systems to use data analytically for identifying best practices that improves healthc...
Article
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Coronary artery disease (CAD) is the most prominent disease that is responsible for increasing mortality and morbidity rate from past few decades. Early and accurate detection of CAD (a type of cardiovascular diseases) is among the most pressing needs of society. In this research work, experiments have been carried out with Cleveland dataset in fou...
Article
Full-text available
The catastrophic phase of Covid-19 turns the table over with the spread of its disastrous transmission network throughout the world. Covid-19 associated with mucormycosis fungal infection accompanied by opportunistic comorbidities have emerged the myriad of complications and manifestations. We searched the electronic databases of Google Scholar, Pu...
Article
Many countries around the world have been influenced by Covid-19 which is a serious virus as it gets transmitted by human communication. Although, its syndrome is quite similar to the ordinary flu. The critical step involved in Covid-19 is the initial screening or testing of the infected patients. As there are no special detection tools, the demand...
Article
Full-text available
The syndrome called COVID‐19 which was firstly spread in Wuhan, China has already been declared a globally “Pandemic.” To stymie the further spread of the virus at an early stage, detection needs to be done. Artificial Intelligence‐based deep learning models have gained much popularity in the detection of many diseases within the confines of biomed...
Chapter
A year after its first report in Wuhan, COVID-19 is still spreading throughout the world, and it affected more than 155 million persons with more than 3.2 million deaths. The inclusion of artificial intelligence and machine learning to mitigate its effects is the most pressing need. In this work, two deep learning models are used to predict the num...
Chapter
The catastrophic phase of the novel coronavirus disease of 2019–2021 (COVID-19) has shaken the world with its massive death toll. This havoc has changed the lifestyle of mankind around the world. To mitigate its mortality and morbidity rate, the inclusion of machine learning (ML) and deep learning (DL) methods can play a vital role. In this study,...
Article
The pandemic of novel coronavirus disease 2019 (Covid-19) has left the world to a standstill by creating a calamitous situation. To mitigate this devastating effect the inception of artificial intelligence into medical health care is mandatory. This study aims to present the educational perspective of Covid-19 and forecast the number of confirmed a...
Article
The pandemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is spreading all over the world. Medical health care systems are in urgent need to diagnose this pandemic with the support of new emerging technologies like artificial intelligence (AI), internet of things (IoT) and Big Data System. In this dichotomy study, we divide our r...
Article
The ensemble is an efficacious machine learning framework that combines variety of algorithms for better performance and effective prediction. Over the past few years, numerous researchers proposed wide variety of ensemble methodologies in the field of healthcare industry. In the present research paper, a nested ensemble has been suggested based on...
Chapter
Full-text available
The present research work discovers knowledge from maternal health data of India by predicting the future values of maternal health parameters. The literature survey indicated that the present condition of maternal health in India is still pathetic, therefore, to forecast the maternal health parameters in advance, for proper planning as regards the...
Article
Covid-19 is a highly contagious virus which almost freezes the world along with its economy. Its ability of human-to-human and surface-to-human transmission turns the world into catastrophic phase. In this study, our aim is to predict the future conditions of novel Coronavirus to recede its impact. We have proposed deep learning based comparative a...
Article
records and recent advances in machine learning, various automated disease diagnosis tools have been developed and proposed in healthcare sector. In the present study, an ensemble methodology using voting and boosting techniques has been proposed for optimal selection of features and prediction of infants' data of India. Methods/Analysis: For featu...
Article
Full-text available
Data Mining is an important sub-process of Knowledge Discovery in Databases (KDD) or Knowledge Discovery Process (KDP) methodology that is mainly used for applying various data mining techniques and algorithms on the target data. In this research paper, the authors have made an attempt to discover knowledge by classifying the maternal healthcare da...
Article
Full-text available
Knowledge Discovery in Databases (KDD) is a splendid methodology of discovering knowledge from gigantic databases by using its various stages viz. Data Selection, Data Preprocessing, Data Transformation, Data Mining and Interpretation/Evaluation. Data Mining is a vital sub-process of KDD methodology that is particularly used to apply the various mi...
Chapter
Full-text available
This paper focuses on the issues apposite to the use of maternal health and child immunization data and throws light on how the KDD (Knowledge Discovery in Databases) process makes use of maternal health and child immunization data for model building and decision making at various levels in healthcare sector. Data mining techniques and algorithms p...
Article
Full-text available
Data Mining and Machine Learning are the emerging research fields that are gaining popularity in many areas including healthcare, education, spam filtering, manufacturing, CRM, fraud detection, intrusion detection, financial banking, customer segmentation, research analysis and many others due to their infinite applications and methodologies to dis...
Article
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Knowledge Discovery in Databases (KDD) is a magnificent process of discovering informative patterns and knowledge from enormous amount of unorganized databases by using the techniques and algorithms of data mining and machine learning. In the present paper, the authors have made an attempt to discover novel knowledge from the child immunization dat...
Article
Full-text available
Time Series data is a well-ordered collection of measurements taken at regular intervals. The objective of time series modelling is to forecast a number of future measures based on the study and analysis of past and present data. Different time series techniques used for prediction are Averaging Methods, Exponential Smoothing, ARIMA, Regression etc...
Article
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Page replacement algorithms choose pages to swap out from the memory when a new page needs memory for allocation. A cluster of algorithms have developed for page replacement. Each algorithm has the objective to minimize the number of page faults. With minimum page faults, the performance of the process is increased. In this paper, study and analysi...
Article
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In present times, healthcare domain has vast amount of data from prescriptions, treatment costs and outcomes, diagnostic tests, patient care records, insurance claims, immunization laws, available vaccines and many other fields because data gets collected on daily basis. The resultant healthcare data has certain characteristics that make its analys...
Article
Full-text available
Data mining is one of the most essential steps of Knowledge Discovery process that is required to extract interesting patterns from enormous size of data. In this paper, we have used the BCG coverage data i.e. Percentage of live births who received Bacillus Calmette Guerin (BCG) a vaccine against tuberculosis and forecast the BCG coverage percentag...
Article
Full-text available
The analysis of algorithms is a subject that has always arouses enormous inquisitiveness. It helps us to determine the efficient algorithm in terms of time and space consumed. There are valid methods of calculating the complexity of an algorithm. In general, a suitable solution is to calculate the run time analysis of the algorithm. The present stu...
Article
Full-text available
Voice over Internet Protocol (VoIP) is a technology that came as an option for the public switch telephone network (PSTN) to make a phone call through internet.Voice over Internet Protocol that is based on digital technologies is a group of hardware and software that uses the Internet Protocol (IP) to transmit voice as packets over an IP network. I...
Conference Paper
Full-text available
Data Mining is a process of discovering previously unknown patterns based around some interestingness criteria. Different techniques of data mining like classification, clustering, association rules etc. are applied to find out novel trends, patterns and relationships from huge volumes of data. In this research paper, an attempt has been made to cl...
Article
Full-text available
The analysis of algorithms is a subject that has always arouses enormous inquisitiveness. It helps us to determine the efficient algorithm in terms of time and space consumed. There are valid methods of calculating the complexity of an algorithm. In general, a suitable solution is to calculate the run time analysis of the algorithm. The present stu...
Article
Full-text available
Disk scheduling is a policy of operating system to decide which I/O request is going to be satisfied foremost. The goal of disk scheduling algorithms is to maximize the throughput and minimize the response time. The present piece of investigation documents the comparative analysis of six different disk scheduling algorithms viz. First Come First Se...
Article
Full-text available
Immunization plays a vital role in the lives of children by protecting them against infectious diseases such as Measles, Polio, Tuberculosis, Hepatitis B, Diphtheria, whopping cough, Tetanus etc. There are different programmes and facilities for newborn and child health under National Health Mission (NHM). However, despite these schemes and program...
Article
Full-text available
In this paper, we have used time series data mining on public healthcare services data. We have specifically applied exponential smoothening methods in order to predict the future requirement of various types of services in the state of Jammu & Kashmir. Exponential Smoothening model is one of the most popular forecasting methods that we have used t...
Article
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With the rapid applications of ICT in public healthcare system, there is growing clamor for data analytics for effective implementation of programmes and policies and efficient use of resources available. The public healthcare system of India has grown leap bound but policy formulation on the basis of public healthcare data is still not being carri...
Article
Full-text available
Data Mining is a method for extracting patterns from historical data. In this paper, we forecast the number of tourists in J&K state for the next five years that should totally depend upon the historical time series data of tourists in J&K state. For this, Exponential Smoothing model and IBM SPSS Modeler 16.0 data mining tool are used. Exponential...
Article
Full-text available
Analysis of algorithms is an issue that has always stimulate enormous curiosity. There are logical techniques of estimating the complexity of an algorithm. Generally, a more convenient solution is to estimate the run time analysis of the algorithm. The present piece of investigation documents the comparative analysis of six different sorting algori...
Article
Full-text available
Scheduling is a policy of operating system used for controlling the order of the process which is to be executed by the CPU. The goal of scheduling is to increase CPU utilization and to finish the entire task in least possible time. The present piece of investigation documents the comparative analysis of four different CPU scheduling algorithms viz...
Article
Full-text available
Data mining is a technique that plays a major role to explore and analyze the data in order to find out valuable information from enormous quantity of data. In this paper, we predict the pilgrimage in numbers to Shri Mata Vaishno Devi, Katra, J&K based on the historical twenty nine years yearly time series data by using ARIMA model and IBM SPSS Mod...
Article
Full-text available
The present piece of investigation documents the comparative analysis of five different sorting algorithms of data structures viz. Bubble Sort, Selection Sort, Insertion Sort, Quick Sort and Shell Sort by comparing their running times calculated by using Turbo C compiler. This comparison was accompanied by the review of various important parameters...

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Projects (2)
Project
IoT, Arduino, and Raspberry Pi. Smart Home, City & Farming, Wearable Devices, and Connected Health.
Project
deep learning, artificial intelligence, computer vision, medical image analysis