Papers by Dr KAMAL ALASKAR
Sanshodhak, 2024
Predicting floods is crucial in minimizing the
harmful consequences of floods, particularly with
... more Predicting floods is crucial in minimizing the
harmful consequences of floods, particularly with
changing weather patterns and increasing urban
development. This review article explores how
transfer learning methods and ensemble machine
learning have been utilized to improve the accuracy
and reliability of flood prediction advancements.
Conventional flood prediction techniques often
encounter problems like inadequate data sharing and
restricted geographical suitability. Ensemble machine
learning approaches like boosting, stacking, and
bagging can address these difficulties and improve
prediction accuracy. Transfer learning methods offer
advantages by using data from one location to build
models in another, effectively tackling issues linked
to limited data access.
This research integrates current studies on AIbased
urban flood control systems with real-time
data integration to provide a thorough summary of
recent progress in flood prediction. Important
patterns, challenges, and chances in the industry are
emphasized following a comprehensive examination
of the current literature. Ultimately, the report
provides suggestions for future research paths and
developing more accurate and reliable flood
prediction systems.
Current World Environment
The production of electronic devices in the Information and Communication Technology (ICT) sector... more The production of electronic devices in the Information and Communication Technology (ICT) sector has seen a massive increase in the past few decades due to changes in the lifestyle of individuals across the globe. The Covid-19 pandemic has been like a catalyst in this process, where the demand has reached its peak due to work-from-home activities. A huge amount of electronic waste generated is by the ICT sector which is not efficiently managed and ultimately risks human health and the environment. The challenges arise in the pathway of efficient and sustainable recycling of electronic waste due to improper defined rules and regulations, unskilled personnel handling electronic waste, high cost of recycling, poor coordination between manufacturers, customers, and government bodies, and the prevailing of informal sector. The present review investigates the current scenario of electronic waste around the globe, strategies developed to manage the electronic waste and methods to be adopt...
IoT Based Mobile App for Continuous Health Monitoring of the Person
2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)
Migration letters, Feb 8, 2024
The study aims to assess artificial intelligence's effects on select HRM functions and to validat... more The study aims to assess artificial intelligence's effects on select HRM functions and to validate the proposed conceptual framework through empirical analysis showing the connection between HRM function as well as artificial intelligence. Questionnaire consisting of closed-ended questionnaires were distributed in order to achieve these goals. The reliability, validity, and correlation analysis were used to assess the factors that make up the suggested model. The hypothesis was further tested and the suggested model was validated using regression analysis. Findings show that all variables account for 89% of HRM explanation, with a R square (R2) of 0.890. The ANOVA values for the regression model, indicate validation at a 95% confidence level. The beta (β) values of all factors are 0.902 and 0.545 in the coefficient summary, which is a reasonable representation of their influence on HRM. These strong AI-based HR apps are a valuable tool for any type of business, even though they lack cognitive capacities of humans. This study will help most businesses to successfully integrate AI-related techniques into hiring, according to our research, as AI will permeate every aspect of HR in the near future and should be seen as a good thing since it makes life better.
We are all familiar with the growth rate of the public Web. Regardless of the metric used to meas... more We are all familiar with the growth rate of the public Web. Regardless of the metric used to measure its growth attached networks, servers, users or pages the growth rate continues to exhibit an exponential pattern. In the same vein, the adoption rate of intranet and extranet data warehouses (i.e., Web warehouses) has exhibited a similar pattern, although the pattern has lagged public adoption. While data warehouse and business intelligence vendors have offered Web-enabled versions. All over world there are hundreds of private tour operators (PTOs) managing tour for hajj pilgrims. According to the visiting Indian Ministry 138,000 Indian pilgrims performed hajj during 2007.Out of above mentioned figure ,000 through the Hajj committee and 38,000 through PTOs. In India there are about 397 registered PTOs up to 2007. We introduce the UML Profile for Modeling DWH Usage for modeling the different kinds of DWH usage on a conceptual level. It uses features of UML intended for the purpose of creating abstract, general models. The profile distinguishes four perspectives of usage, and allows to model details of the users. The UML Profile is applied to example illustrating Hajj pilgrims private tour.
ISET INTERNATIONAL CONFERENCE ON APPLIED SCIENCE & ENGINEERING (CASE 2021)
In the sphere of medicine, IOT is meant to keep people safe and healthy plays a crucial part in c... more In the sphere of medicine, IOT is meant to keep people safe and healthy plays a crucial part in communicating with doctors and patients through the use of health monitoring equipment and lowering healthcare costs in the future years. The internet of things (IoT) is making the world a smarter and more efficient village by allowing a variety of sensors and smart gadgets to gather and analyse data for a variety of reasons. As a result of these smart things, the healthcare system is growing wiser. When basic health facilities lack comprehensive medical care infrastructure, emerging countries gain. However, there is currently no specialized architecture for smart health units that can allow for this gathering and transferring patient health information to headquarters hospitals where live patient assistance is offered. Here, a smart IoT-based healthcare system is proposed, which includes a smart medical kit linked to sensors and a server for frequent health tracking. This smart medical kit is associated with sensors to measure the health parameters like body temperature, blood pressure, and heart rate for the effective function of the body. The proposed idea can alert the patient and their relatives in case of any abnormalities in their health parameters and also get suggestions from the doctor without physical contact with the doctor.
TIJ's Research Journal of Science & IT Management - RJSITM, 2015
Now Cloud computing is evolved as a method to add capabilities to applications without licensing ... more Now Cloud computing is evolved as a method to add capabilities to applications without licensing new software, investing in new hardware or infrastructure or training new personnel. It provides common business applications online that are accessed from a web browser, while the software and data are stored on the servers. This paper explores different research papers published in different Journals based on cloud computing. A review is carried out and selected papers are presented here by arranging them in scenario that helps to understand a concepts of Cloud Computing, its services and applications in different sectors.
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Papers by Dr KAMAL ALASKAR
harmful consequences of floods, particularly with
changing weather patterns and increasing urban
development. This review article explores how
transfer learning methods and ensemble machine
learning have been utilized to improve the accuracy
and reliability of flood prediction advancements.
Conventional flood prediction techniques often
encounter problems like inadequate data sharing and
restricted geographical suitability. Ensemble machine
learning approaches like boosting, stacking, and
bagging can address these difficulties and improve
prediction accuracy. Transfer learning methods offer
advantages by using data from one location to build
models in another, effectively tackling issues linked
to limited data access.
This research integrates current studies on AIbased
urban flood control systems with real-time
data integration to provide a thorough summary of
recent progress in flood prediction. Important
patterns, challenges, and chances in the industry are
emphasized following a comprehensive examination
of the current literature. Ultimately, the report
provides suggestions for future research paths and
developing more accurate and reliable flood
prediction systems.