An IOT based system to track feasible business model /
Patent Number: 202241051204, Applicant: Amrita Chaurasia. E-commerce that spans international borders makes it possible for smaller businesses to more swiftly penetrate many international marketplaces. The purpose of this article is to investigate the ways in which effective market creation influences the international performance of small and medium-sized businesses (SMEs) that are involved in international e-commerce. Using the effectuation theory as a foundation, we propose that businesses can generate demand in foreign markets by developing innovative new ways for customers to interact and engage with them in the digital world.
https://drive.google.com/file/d/1N9o9iePfCzoT9GrbcgDNt4SuVQn7VawT/view
Optimized Load Balancing Technique for Software Defined Network
Load balancing; Performance enhancement; SDN; Software-defined networks
Software-defined networking is one of the progressive and prominent innovations in Information and Communications Technology. It mitigates the issues that our conventional network was experiencing. However, traffic data generated by various applications is increasing day by day. In addition, as an organization's digital transformation is accelerated, the amount of information to be processed inside the organization has increased explosively. It might be possible that a Software-Defined Network becomes a bottleneck and unavailable. Various models have been proposed in the literature to balance the load. However, most of the works consider only limited parameters and do not consider controller and transmission media loads. These loads also contribute to decreasing the performance of Software- Defined Networks. This work illustrates how a software-defined network can tackle the load at its software layer and give excellent results to distribute the load. We proposed a deep learning-dependent convolutional neural networkbased load balancing technique to handle a software-defined network load. The simulation results show that the proposed model requires fewer resources as compared to existing machine learning-based load balancing techniques. 2022 Tech Science Press. All rights reserved.
Kumar A.; Anand D.; Jha S.; Joshi G.P.; Cho W.
Computers, Materials and Continua, Vol-72, No. 1, pp. 1409-1426.
Kumar A., Department of Computer Science and Engineering, Chandigarh University, Punjab, Mohali, 140413, India; Anand D., Department of Computer Science and Engineering, Chandigarh University, Punjab, Mohali, 140413, India; Jha S., School of Computational Sciences, CHRIST (Deemed to be University), Ghaziabad, 201003, India; Joshi G.P., Department of Computer Science and Engineering, Sejong University, Seoul, 05006, South Korea; Cho W., Department of Automotive ICT Convergence Engineering, Daegu Catholic University, Gyeongsan, 38430, South Korea
Magnetohydro-convective instability in a saturated DarcyBrinkman medium with viscous dissipation
The influence of dissipation with viscosity on magnetohydro-convective instability in a saturated DarcyBrinkman medium is examined. The bottom boundary is designated as adiabatic, whereas the top boundary is isothermal. Numerical linear stability analysis investigates normal modes that disturb the horizontal base flow at different inclinations. The case study shows that the most unstable disturbances are horizontal rolls, normal modes characterized by a wave vector perpendicular to the main flow direction. The horizontal rolls are the favored instability mode. Barletta et al. also showed that horizontal rolls are more unstable than any other oblique roll mode in the hydromagnetic scenario. This finding provides insights into the behavior of MHD fluid flow and heat transfer in porous media, with implications for applications in geoscience, engineering, and environmental science. Graphical abstract: (Figure presented.) The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2024.
European Physical Journal B, Vol-97, No. 7
Springer Science and Business Media Deutschland GmbH
Kumar A., Department of Mathematics, National Institute of Technology, Telangana, Warangal, 506004, India; Bhargavi D., Department of Mathematics, National Institute of Technology, Telangana, Warangal, 506004, India; Siddheshwar P.G., Centre for Mathematical Needs, Department of Mathematics, CHRIST (Deemed to Be University), Karnataka, Bengaluru, 560029, India
Evaluation of forecasting accuracy of an equity valuation model: a case of ZEE
forecasted prices; growth rate; money control; over-priced; regression analysis; target price; underpriced; ZEE Entertainment Enterprises Limited; ZEEL
Investing can prove to be a very enriching and enjoyable experience if one sticks to certain principles and guidelines. The research is based on secondary data pulled out from Money Control website for ZEE Entertainment Enterprises Limited (ZEEL). The identification of target prices is important and involves precision in the price points that are forecasted. The expected growth rate for the next year is figured out to forecast the financial statement for the next year. Regression analysis has been used to estimate growth rate. Regression analysis was done on the income data for the past years for the media entertainment company, and the target prices have been identified. By taking a careful look at the forecasted prices and the prevailing prices, an investor can figure out whether the stock is under-priced or over-priced. 2023 Inderscience Enterprises Ltd.
International Journal of Accounting, Auditing and Performance Evaluation, Vol-19, No. 2, pp. 234-249.
https://doi.org/10.1504/IJAAPE.2023.132396 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168708619&doi=10.1504%2fIJAAPE.2023.132396&partnerID=40&md5=a20133a8e2672e0257d2b2f6701b9579
Kumar A., School of Business & Management, Christ University, Delhi-NCR, 201003, India; Chaudhry S., School of Business & Management, Christ University, Delhi-NCR, 201003, India; Sao A., RICS School of Built Environment, Amity University, Noida, India
Impact of Abuse on Mental Health and Happiness Among Students: Mediating Role of Family Environment
Child abuse; family environment; mediation; mental health
Background: Child abuse and neglect is an issue of concern for public health professionals. The impact of abuse may lead to poor physical and mental health conditions. Family environment may impact coping and recovery among victims of abuse. The association between child abuse, mental health, happiness, and family environment is complex. The study examines the association and pathways between child abuse exposure, mental health and happiness, while exploring the potentially mediating effect of the family environment. Methods: Data were collected from 571 high school students from Kerala, India, by using various tools, including a semi-structured questionnaire, Depression and Anxiety Youth Scale, and happiness scale. A mediation analysis using structural equation modeling (SEM) was carried out to test the objectives of the study. Results: The analysis shows that mental health, happiness, and family environment are correlated with abuse experience. The mediation analysis further shows that the indirect effect of abuse on mental health via the family environment was significant (? = 0.013, 95% CI [0.002, 0.033]). The indirect effect of abuse on happiness via the family environment was significant (? = 0.019, 95% CI [0.044, 0.003]). Furthermore, the total effect of abuse on mental health (? = 0.266, 95% CI [0.164, 0.354]) and abuse on happiness (? = 0.152, 95% CI [0.259, 0.050]) was significant. Conclusion: The study reveals that abuse experiences impact happiness and mental health outcomes among students. The family environment mediates the relationship between child abuse and mental health, and between child abuse and happiness. 2023 The Author(s).
Journal of Indian Association for Child and Adolescent Mental Health, Vol-19, No. 3, pp. 266-272.
All Open Access; Hybrid Gold Open Access
Kumar A., Department of Psychology, CHRIST University, Karnataka, Bengaluru, India; Deb S., Rajiv Gandhi National Institute of Youth Development, Ministry of Youth Affairs and Sports, GoI, Tamil Nadu, Sriperumbudur, India; Bhagyalakshmi KC, Department of Psychology, CHRIST University, Karnataka, Bengaluru, India
Experimenting with resilience and scalability of wifi mininet on small to large SDN networks
Today everything is getting digitized where people want to be wireless by all aspects. There is a high demand of WiFi in every sector. Highest influence on network planning of newly developed network infrastructure is of SDN to meet the futuristic needs of upcoming technology. As a result, newly developed networks have become more adaptive to dynamic circumstances along with enhanced flexibility. Being globally connected, it is inevitable to obtain adequate services from data centers through Wi-Fi support on SDN Networks, which is still a dream. Thus, the target of the experiment performed and presented by the authors of this paper is to implement WiFi support on SDN. Further, authors have also demonstrated the scalability and resilience of SDN based WiFi Network on Mininet by testing performance parameters in various dynamic scenarios. This paper will have a high impact on the end users as SDN technology can be implemented as last mile technology using WiFi SDN. BEIESP.
International Journal of Recent Technology and Engineering, Vol-7, No. 6, pp. 201-207.
Blue Eyes Intelligence Engineering and Sciences Publication
Kumar A., CHRIST, Bangalore, India; Goswami B., CHRIST, Bangalore, India; Augustine P., CHRIST, Bangalore, India
Verification and validation of MapReduce program model for parallel K-means algorithm on Hadoop cluster
Grep; Hadoop; K-means; Machine learning; MapReduce; Terasort; Wordcount
With the development of information technology, a large volume of data is growing and getting stored electronically. Thus, the data volumes processing by many applications will routinely cross the petabyte threshold range, in that case it would increase the computational requirements. Efficient processing algorithms and implementation techniques are the key in meeting the scalability and performance requirements in such scientific data analyses. So for the same here, we have p analyzed the various MapReduce Programs and a parallel clustering algorithm (PKMeans) on Hadoop cluster, using the Concept of MapReduce. Here, in this experiment we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Means Clustering Algorithm. We have found that as the number of nodes increases the execution time decreases, but also some of the interesting cases has been found during the experiment and recorded the various performance change and drawn different performance graphs. This experiment is basically a research study of above MapReduce applications and also to verify and validate the MapReduce Program model for Parallel K-Means algorithm on Hadoop Cluster having four nodes. 2013 IEEE.
2013 4th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2013
https://doi.org/10.1109/ICCCNT.2013.6726852 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894488015&doi=10.1109%2fICCCNT.2013.6726852&partnerID=40&md5=bc9ec99c84e42a1d59e93b69c36233ed
Kumar A., Department of Computer Science and Engineering, Christ University, Faculty of Engineering Bangalore, Karnataka, India; Kiran M., Department of Computer Science and Engineering, Christ University, Faculty of Engineering Bangalore, Karnataka, India; Prathap B.R., Department of Computer Science and Engineering, Christ University, Faculty of Engineering Bangalore, Karnataka, India
A scientometric analysis of social entrepreneurship
Authors productivity; Entrepreneurs; Entrepreneurship; Institute/university productivity; Publication pattern; Scientometric Analysis; Social entrepreneurship
Impactful studies in social entrepreneurship area has garnered attention of the researchers in recent times. The interest and importance is generated in this area because of its nature in addressing social problems and welfare of the communities and societies. The study aims at providing insight on scientometric analysis in the domain of social entrepreneurship. The study further identifies researchers exploring sub domai ns considering parameters like publication language, outlook of publication patterns that changed every year, contextual journals to perform a literature review, primary subject areas in which research is being conducted, most productive institutes/universities, most productive countries where research is being conducted in the domain of social entrepreneurship and the most prolific authors in the area of social entrepreneurship. This study is a pathfinder for researchers with plans to conduct studies in social entrepreneurship domain by leading them to relevant scholarly journals and authors for greater impact. IJSTR 2019.
Kumar A.; Kiran P.; Krishna Kishore S.V.
International Journal of Scientific and Technology Research, Vol-8, No. 12, pp. 342-347.
International Journal of Scientific and Technology Research
Kumar A., Faculty of Management, VNS Group of Institutions, Bhopal, Madhya Pradesh, India; Kiran P., CHRIST Institute of Management, CHRIST Deemed to be University, Bangalore, Karnataka, India; Krishna Kishore S.V., CHRIST Institute of Management, CHRIST Deemed to be University, Bangalore, Karnataka, India
Improved Acceptance model: Unblocking Potential of Blockchain in Banking Space
Decentralization; immutability and cryptocurrencies; ledger; Smart contracts
Over the past ten years, blockchain has emerged as the new buzzword in the banking sector.The new technology is being adopted globally in many industries, including the business sector,because of its unique uses and features. However, no adoption model is available to help with this process.This research paper examines the new technology known as blockchain, which powers cryptocurrencies like Bitcoin and others. It looks at what blockchain technology is, how it works especially in the banking sector, and how it can change and upend the financial services sector. It outlines the features of the technology and discusses why these can have a significant effect on the financial industry as a whole in areas like identity services, payments, and settlements in addition to spawning new products based on things like 'smart contracts'. The adoption variables found in the literature study were used to gather, test, and evaluate the official papers that are currently available from regulatory organizations, practitioners, and research bodies. This study was able to classify adoption factors into three categories - supporting, impeding, and circumstantial - identify a new adoption factor, and determine the relative relevance of the factors. Consequently, an institutional adoption paradigm for blockchain technology in the banking sector is put out. In light of this, it is advised to conduct additional research on using the suggested model at banks using the new technology in order to assess its suitability. 2024 IEEE.
Kumar A.; Mallik S.; Mishra S.; Sharma V.; Hewage P.; Iwendi C.
4th International Conference on Innovative Practices in Technology and Management 2024, ICIPTM 2024
Institute of Electrical and Electronics Engineers Inc.
Kumar A., Kalinga Institute of Industrial Technology, India; Mallik S., Kalinga Institute of Industrial Technology, India; Mishra S., Kalinga Institute of Industrial Technology, India; Sharma V., Christ (Deemed to Be University), Department of Computational Sciences, Delhi NCR, India; Hewage P., University of Bolton, School of Creative Technologies, United Kingdom; Iwendi C., University of Bolton, School of Creative Technologies, United Kingdom
Democratising Intelligent Farming Solutions to Develop Sustainable Agricultural Practices
In this chapter, the transformative potential of democratising intelligent farming solutions is discussed, primarily in the context of the sustainable farming. Technologies including the Internet of Things (IoT), global positioning systems (GPS), Unmanned Aerial Vehicles (UAVs), computer vision, and artificial intelligence (AI) have redefined farming activities. Such advances have allowed decision-making and optimised resource utilisation to be driven by real-time data. The democratisation of AI tools are meant to make AI-driven agriculture accessible to all. As such, this chapter discusses the interplay of bottom-up and top-down approaches, highlighting their roles in promoting the accessibility of AI tools and their benefits to farmers. The integration of such AI tools would transform contemporary agriculture into agriculture 4.0. This revolution would be characterised by real-time data, predictive analytics, and precision farming techniques. Further, the integration of technology such as wireless networks and the global navigation satellite system (GNSS) increases precision and the ability to monitor farming activities. The idea of democratising intelligent farming solutions is meant to herald agriculture 4.0, which would improve crop quality, climate resilience of crops, and the income of farmers. It would also improve broader macroeconomic aspects by promoting education and information and communication technology (ICT) skills and potentially reducing income inequality gap while promoting socio-economic well-being. 2025 selection and editorial matter, Sirisha Potluri, Suneeta Satpathy, Santi Swarup Basa, and Antonio Zuorro; individual chapters, the contributors. All rights reserved.
AI in Agriculture for Sustainable and Economic Management, pp. 53-66.
Kumar A., Christ University, Pune, India; Nanjundan P., CHRIST University, Lavasa Campus, Pune, India; Thomas L., CHRIST University, Lavasa Campus, Pune, India
Organizational contributions to emergency preparedness and response in Varanasi: A comprehensive analysis
Disaster preparedness; Emergency response strategies; Organizational role; Varanasi
India's unique geographical diversity and status as the world's most populous nation make it exceptionally susceptible to a wide array of hazards, both natural and human-induced. This vulnerability is further compounded by the intersection of diverse disasters and the dense population, leading to significant human and material losses. In response to these challenges, effective emergency preparedness plans are indispensable, requiring meticulous risk assessments, strategic resource allocation, capacity building initiatives, and active engagement of community-oriented organizations. Continuous monitoring and adaptation are essential for bolstering resilience and safeguarding socio-economic stability. Furthermore, the examination of developmental and disaster-specific organizations' roles in preparedness and response necessitates a systematic shift towards proactive paradigms, fostering an anticipatory culture rather than a reactive one. This study aims to dissect the intricate web of organizational efforts crucial for emergency preparedness in Varanasi, one of the world's oldest cities. By delving into these critical mechanisms, our goal is to enhance collective readiness against potential emergencies, safeguarding the city's rich heritage and its inhabitants. Through a mixed-method approach, this research illuminates the multifaceted involvement of organizations across various sectors, unraveling a complex tapestry of challenges that impede practical disaster preparedness. We scrutinize the coordination among governmental and non-governmental entities, funding dynamics, and grassroots alliances, revealing untapped resources for disaster resilience. Additionally, we analyze the strategies adopted by the national emergency preparedness and response force, highlighting both successes and shortcomings. Moreover, this study underscores the unique competencies of individuals involved in disaster preparedness, while identifying structural and functional gaps within organizational frameworks. Conversely, non-profit organizations face distinct challenges, including fundraising constraints and donor-imposed limitations, hindering their ability to develop comprehensive emergency preparedness and response capacities compared to public and private entities. In summary, this research serves as a comprehensive exploration of organizational dynamics in emergency preparedness within Varanasi, offering valuable insights into the complexities of disaster management efforts. By addressing these challenges, we aim to pave the way for more effective and inclusive disaster preparedness strategies, ultimately enhancing the resilience of Varanasi and similar communities globally. 2024 Elsevier Ltd
Kumar A.; Prasad J.B.; Mani S.K.; Tiwana A.S.
International Journal of Disaster Risk Reduction, Vol-110
https://doi.org/10.1016/j.ijdrr.2024.104654 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85198128314&doi=10.1016%2fj.ijdrr.2024.104654&partnerID=40&md5=856fb6b753014d43b9ce2860729bc2d4
Kumar A., Centre For Electoral Management Studies, School of Development Studies, Tata Institute of Social Sciences, Mumbai, India; Prasad J.B., Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India; Mani S.K., Department of Civil Engineering, Christ University, Bengaluru, India; Tiwana A.S., Department of Geography, Mata Gujri College (Autonomous), Fatehgarh Sahib, Punjab, India, School of Development Studies, Tata Institute of Social Sciences, Mumbai, India
Enhanced Secure Technique for Detecting Cyber Attacks Using Artificial Intelligence and Optimal IoT
The Internet of Things (IoT) is a broad term that refers to the collection of information about all of the items that are linked to the Internet. It supervises and controls the functions from a distance, without the need for human interaction. It has the ability to react to the environment either immediately or via its previous experiences. In a similar vein, robots may learn from their experiences in the environment that is relevant to their applications and respond appropriately without the need for human interaction. A greater number of sensors are being distributed across the environment in order to collect and evaluate the essential information. They are gaining ground in a variety of industries, ranging from the industrial environment to the smart home. Sensors are assisting in the monitoring and collection of data from all of the real-time devices that are reliant on all of the different types of fundamental necessities to the most advanced settings available. This research study was primarily concerned with increasing the efficiency of the sensing and network layers of the Internet of Things to increase cyber security. Due to the fact that sensors are resource-constrained devices, it is vital to provide a method for reacting, analysing, and transmitting data collected from the sensors to the base station as efficient as possible. Resource requirements, such as energy, computational power, and storage, vary depending on the kind of sensing devices and communication technologies that are utilised to link real-world objects together. Sensor networks' physical and media access control layers, as well as their applications in diverse geographical and temporal domains, are distinct from one another. Transmission coverage range, energy consumption, and communication technologies differ depending on the application requirements, ranging from low constraints to high resource enrich gadgets. This has a direct impact on the performance of the massive Internet of Things environment, as well as the overall network lifetime of the environment. Identifying and communicating matching items in a massively dispersed Internet of Things environment is critical in terms of spatial identification and communication. 2022 Anand Kumar et al.
Kumar A.; Rahmath M.; Raju Y.; Reddy Vulapula S.; Prathap B.R.; Hassan M.M.; Mohamed M.A.; Asakipaam S.A.
Security and Communication Networks, Vol-2022
Kumar A., Cambridge Institute of Technology, North Campus, Karnataka, Bangalore, 562110, India; Rahmath M., Department of Computer Science, Prince Sattam Bin Abdulaziz University, Wadi Ad-Dawasir, Saudi Arabia; Raju Y., Department of Computer Science and Engineering, Vignana Bharathi Institute of Technology, Telangana, Hyderabad, India; Reddy Vulapula S., Department of IT, Vignana Bharathi Institute of Technology, Hyderabad, India; Prathap B.R., Department of Computer Science and Engineering, Christ University, Bangalore, India; Hassan M.M., Department of Biology, College of Science, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia; Mohamed M.A., Department of Medical Instruments Engineering Techniques, AI-Turath University, Baghdad, 10021, Iraq, Department of Medical Instruments Engineering Techniques, Al-Farahidi University, Baghdad, 10021, Iraq; Asakipaam S.A., Department of Electrical and Electronics Engineering, Tamale Technical University, Tamale, Ghana
Economic and sustainable management of wastes from rice industry: combating the potential threats
Rice husk; Rice husk ash; Rice mill wastewater; Value-added products; Waste management
Rice is one of the imperative staple foods, particularly in the developing countries. The exponential boom in human population has resulted in the continuous expansion in the rice industry in order to meet the food demands. The various stages of paddy processing release huge quantity of solid wastes, mainly rice husk, rice husk ash and liquid wastes in the form of rice industry wastewater. The discharge of the rice industry wastewater imparts a substantial threat to the aquatic bodies and the nearby surrounding and, thus, consequently demands eco-benign treatment plan. As a result, different strategies are needed to enhance the effluent quality and minimize the operational cost of the treatment process. Therefore, efficient technological approach targeting the minimization of pollution as well as assuring the economic prosperity should be implemented. In this review article, several aspects related to the rice industry discussing the significant challenges involved in the generation of both solid and liquid wastes, mitigation experiments and future prospects have been meticulously elaborated. Furthermore, the article also focuses on the various processes utilized for reducing the pollution load and promoting the practice of reuse and recycle of waste rather than the discharge action for the sake of sustainability and the emergence of novel techniques for the generation of energy and value-added products. 2017, Springer-Verlag GmbH Germany.
Kumar A.; Roy A.; Priyadarshinee R.; Sengupta B.; Malaviya A.; Dasguptamandal D.; Mandal T.
Environmental Science and Pollution Research, Vol-24, No. 34, pp. 26279-26296.
ISSN: 9441344; PubMed ID: 29032530; CODEN: ESPLE
Kumar A., Department of Chemical Engineering, National Institute of Technology, Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India; Roy A., Department of Chemical Engineering, National Institute of Technology, Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India; Priyadarshinee R., Department of Biotechnology, National Institute of Technology, Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India; Sengupta B., Department of Chemical Engineering, National Institute of Technology, Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India; Malaviya A., Department of Life Science, Christ University, Hosur Road, Karnataka, 560029, Bengaluru, India; Dasguptamandal D., Department of Biotechnology, National Institute of Technology, Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India; Mandal T., Department of Chemical Engineering, National Institute of Technology, Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India
A Novel Deep Learning Approach for Retinopathy Prediction Using Multimodal Data Fusion
Clustering; Deep Learning; Multimodal; Retinopathy
In contemporary research on mild cognitive disorders (MCI) and Alzheimer's disease (AD), the predominant approach involves the utilization of double data modalities for making predictions related to AD stages. However, there is a growing recognition of the potential benefits that could be derived from the fusion of multiple data modalities to obtain a more comprehensive perspective in the analysis of AD staging. To address this, we have employed deep learning techniques to holistically assess data from various sources, including, genetic (single nucleotide polymorphisms (SNPs)), imaging (magnetic resonance imaging (MRI)), and clinical tests, with the objective of categorizing patients into distinct groups: AD, MCI, and controls (CN). For the analysis of imaging data, convolutional neural networks have been employed. Moreover, we have introduced a novel approach for data interpretation, enabling the identification of the most influential features learned by these deep models. This interpretation process incorporates clustering and perturbation analysis, shedding light on the crucial aspects of the data contributing to our classification results. Our experimentation, conducted on the dataset (i.e., ADNI), has yielded compelling results. Furthermore, our findings have underscored the significant advantage of integrating multi-modality data over solely relying on double modality models, as it has led to improvements in terms of accuracy, precision, recall, and mean F1 scores. 2024, Ismail Saritas. All rights reserved.
Kumar A.; Sharma N.Kr.; Reshmi B.; Saini R.; Thanganadar H.; Singhal A.; Rao P.V.
International Journal of Intelligent Systems and Applications in Engineering, Vol-12, No. 11s, pp. 70-77.
Kumar A., School of Computing Science & Engineering, Galgotias University, India; Sharma N.Kr., Department of MCA, IIMT College of Engineering, Gr.Noida, Dr. A.P.J. Abdul Kalam Technical University, UP, Lucknow, India; Reshmi B., Department of Computer Science and Engineering, Ahalia School of Engineering and Technology, Kerala, Palakkad, India; Saini R., Department of Computer Science and Engineering, G. B. Pant Institute of Engineering and Technology, Pauri Garhwal, Uttarakhand, India; Thanganadar H., Department of Health Informatics, College of Public Health and Tropical Medicine, Jazan University, Jazan, 45142, Saudi Arabia; Singhal A., School of Sciences, Christ (Deemed to be University) Delhi-NCR, Uttar Pradesh, Ghaziabad, 201003, India; Rao P.V., Gokaraju Rangaraju Institute of Engineering and Technology(GRIET), Bachupally, Hyderabad, 500090, India
Neuro-Leadership: A New Paradigm in Leadership Thought
leadership; neuroleadership; neuroscience; theories
Leadership is not a static occurrence. It is a dynamic one that constantly evolves. Leadership is seen as a means to enhance ones personal, professional, and social lives. Organizations believe that leaders bring in unique assets to the organization; which contribute to the bottom line of the company. The conclusions drawn from research findings on leadership portray an image of a process that is far more sophisticated and complex than the condensed view, popularly accepted. This chapter will provide a comprehensive evaluation of different approaches to leadership and highlight the importance of a new paradigm. Ground breaking insights have started to surface regarding neurosciences and brain functioning that has significantly influenced leadership thought. The traditional approaches of leadership could not adapt to the world of unlimited information which needed continuous evolution; however, our brain can adapt and change leading to the emergence of neuro-leadership. The chapter will trace the journey of neuroleadership and its increasing relevance in the current scenario, especially in terms of employee and organization performance. 2024 by Nova Science Publishers, Inc.
New Research on Leadership Styles and Performance, pp. 105-115.
Kumar A.A., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Nair S., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Chacko E., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bangalore, India
How blockchain enables financial transactions in the banking sector
banking; bitcoin; blockchain; decentralisation; ecosystem; finance; financial market; fintech; technology
Blockchain technology is the most important technological revolution of the second decade of the 21st century. The banking sector is one of the major sectors where blockchain has played a significant role in recording and processing various financial transactions, inter-bank transfers, and digital format agreements through a distributed ledger system. It harms the transactional costs, which influence the financial markets. The global financial system being the most popular sector is prone to many errors and frauds. Blockchain technology can help prevent these problems by enabling a decentralised network that permits all parties to review. The present study attempted to analyse the problems in existing banking financial transactions, understand the importance of transparency and study the usage of blockchain in the banking sector. It suggests a research model for solving financial transaction problems by applying blockchain technology. The study uplifts the security and transparency of blockchain technology throughout the paper. Copyright 2022 Inderscience Enterprises Ltd.
Kumar A.S.; Katta Lakshmi Narayan Setty V.; Ravi G.
International Journal of Business and Globalisation, Vol-31, No. 1, pp. 1-6.
https://doi.org/10.1504/IJBG.2022.124545 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135767809&doi=10.1504%2fIJBG.2022.124545&partnerID=40&md5=6e37d5e83db841eb77f409aafc452a51
Kumar A.S., Department of Professional Studies, CHRIST (Deemed to be University), Bangalore Central Campus, Karnataka, Bengaluru, India; Katta Lakshmi Narayan Setty V., Department of Commerce, St. Josephs College (Autonomous), Karnataka, Bengaluru, India; Ravi G., Department of Commerce, St. Josephs College (Autonomous), Karnataka, Bengaluru, India
An empirical evaluation of stress and its impact on the engineering colleges faculty members in Tamil Nadu
Causes of stress; Coping strategies; Effects of stress; Factor analysis; Faculty; Higher education; Level of stress; Stress; Unaided private engineering and technology; UPET; Work environment
The present study examined the specific causes, levels and effects of stress experienced by faculty members who worked in unaided private engineering and technology (UPET) colleges in the state of Tamil Nadu, India. Factor analysis and structural model were used to evaluate the relationship between the causes, subsequent effects at different level of stress and the appropriate personal and organisational stress coping strategies. Primary data were collected from 560 faculty members by employing convenience sampling method during the academic year 20172018. The study revealed that causes of stress influencing considerably the level of stress and the level of stress explained the high influence on the effect of stress variables. Both effects of stress and causes of stress were negatively influencing the stress coping strategies of personal as well as organisational level strategies. Copyright 2020 Inderscience Enterprises Ltd.
International Journal of Public Sector Performance Management, Vol-6, No. 6, pp. 908-929.
https://doi.org/10.1504/IJPSPM.2020.110986 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095992975&doi=10.1504%2fIJPSPM.2020.110986&partnerID=40&md5=30f853e6e0d6e29b604cb7a210e914e7
Kumar A.S., Department of Professional Studies, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Seranmadevi R., School of Management, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Tamil Nadu, India
Regression analysis and features of negative activation energy for MHD nanofluid flow model: A comparative study
Negative activation energy; Porous medium; Regression analysis; Successive linearization method
This article elucidates the impact of activation energy on magnetohydrodynamic (MHD) stagnation point nanofluid flow over a slippery surface in a porous regime with thermophoretic and Brownian diffusions. Negative activation energy is scarce in practice, but the impact of negative activation energy could not be neglected as it is noticed in chemical processes. The rate of some Arrhenius-compliant reactions is retarded by increasing the temperature and is therefore associated with negative activation energies, such as exothermic binding of urea or water. In some processes, the temperature dependence of the pressure-induced unfolding and the urea-induced unfolding of proteins at ambient pressure give negative activation energies. The present mathematical model is solved with successive linearization method (a spectral technique). A comparison of results is made for negative and positive values of activation energy. Apart from it, the quadratic multiple regression model is discussed briefly and explained with bar diagrams. It is observed that with rise in unsteadiness parameter from 0 to 1 (taking positive activation energy), skin friction and Sherwood number are increased by 9.36% and 19% respectively, and Nusselt number is decreased by 26%. However, for negative activation energy, 9.36% and 112% enhancement is observed in skin friction and Sherwood number, respectively. 2023 The Authors
Kumar B.; Prachi; Singhal A.; Nandkeolyar R.; Kumar P.; Chamkha A.J.
Propulsion and Power Research, Vol-12, No. 2, pp. 273-283.
https://doi.org/10.1016/j.jppr.2023.02.005 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153075409&doi=10.1016%2fj.jppr.2023.02.005&partnerID=40&md5=f7b91d4f1dc60135d146cb462b123f44
Kumar B., School of Mathematics, Thapar Institute of Engineering and Technology, Punjab, Patiala, 147004, India; Prachi, Department of Applied Sciences and Humanities, RIT, Roorkee, 247667, India; Singhal A., School of Sciences, Christ (Deemed to be University), Delhi NCR, 201003, India; Nandkeolyar R., Department of Mathematics, National Institute of Technology, Jamshedpur, 831014, India; Kumar P., Department of Applied Mechanics, Indian Institute of Technology, Delhi, 110016, India; Chamkha A.J., Faculty of Engineering, Kuwait College of Science and Technology, Doha District, Kuwait
Application of AI-Based Learning in Automated Applications and Soft Computing Mechanisms Applicable in Industries
The term artificial intelligence is used to describe a method through which computers may teach themselves new skills and develop themselves, without the help of humans or any predetermined instructions. Machines are fed data and trained to look for patterns; these patterns are then used as templates for further learning. They get the agency to choose their own actions and alter their habits accordingly. The term soft computing refers to a group of computational techniques that draw inspiration from both AI and natural selection. Solutions to difficult real-world situations that have no simple computer solution are provided, and they are both practical and cost-effective. Soft computing is an area of study in mathematics and computer science that has been around since the early 1990s. The idea for this project sprang from the fact that people can think of solutions that are close to the ones in the actual world. It is via the use of approximations that the science of soft computing is able to solve difficult computational challenges. Industrial automation is used by a diverse variety of industries and companies to improve the effectiveness of their processes by leveraging a number of technology developments. Many routine tasks are being changed by industrial applications. Industrial automation that reduces breakdowns and repairs quickly might help a business save money. 2024 selection and editorial matter, Nidhi Sindhwani, Rohit Anand, A. Shaji George and Digvijay Pandey; individual chapters, the contributors.
Kumar B.M.; Talukdar V.; Khan H.; Talukdar S.B.; Koujalagi A.; Kumar R.G.; Gupta A.
Robotics and Automation in Industry 4.0: Smart Industries and Intelligent Technologies, Vol-45689, pp. 110-131.
Kumar B.M., Department of MCA, Dayananda Sagar College of Engineering, Bengaluru, India; Talukdar V., Kaziranga University, Jorhat, India; Khan H., Department of Computer Science and Engineering, Rungta College of Engineering and Technology, Bhilai, India; Talukdar S.B., School of Computer Science and Engineering, VIT Bhopal, Bhopal, India; Koujalagi A., Department of Computer Science and Engineering, Godavari Institute of Engineering and Technology (Autonomous), Rajamahendravaram, India; Kumar R.G., Department of Computer Science and Engineering CHRIST, (Deemed to be University), School of Engineering and Technology, Kengeri Campus, Bangalore, India; Gupta A., Department of Computer Science and Engineering, Vaish College of Engineering, Rohtak, India
Implementation of Recent Advancements in Cyber Security Practices and Laws in India
cyber crime; Cyber security; data protection; information technology; law
In the past few decades, a large number of scholars and experts have found that wireless connectivity technologies and systems are susceptible to many kinds of cyber attacks. Both governmental organizations and private firms are harmed by these attacks. Cybersecurity law is a complex and fascinating area of law in the age of information technology. This essay aims to outline numerous cyber hazards as well as ways to safeguard against them. In both local and international economic contexts, it is critical to establish robust regulatory and legal structures that address the growing concerns about fraud on the internet, security of information, and intellectual property protection. Additionally, it covers cybercrime's different manifestations and security in a global perspective. Due to recent technical breakthroughs and a growth in access to the internet, cyber security is now utilized to safeguard not just a person's workstation but also their own mobile devices, including tablets and mobile phones, that have grown into crucial tools for data transmission. The community of security researchers, which includes members from government, academia, and industry, must collaborate in order to comprehend the new risks facing the computer industry. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Kumar B.V.; Singh M.; Arora V.; Malik K.; Nomani M.Z.M.; Kapila D.
Lecture Notes in Electrical Engineering, Vol-1273 LNEE, pp. 1050-1058.
Kumar B.V., School of Computer Science and Artificial Intelligence, SR University, Telangana, Warangal, India; Singh M., Sharda School of Law, Sharda University, Greater Noida, India; Arora V., Sharda School of Law, Sharda University, Greater Noida, India; Malik K., Department of Law, CHRIST (Deemed to Be University) Delhi NCR Campus, Ghaziabad, India; Nomani M.Z.M., Faculty of Law, Aligarh Muslim University, UP, Aligarh, 202001, India; Kapila D., Department of Computer Science and Engineering, Lovely Professional University, Punjab, Phagwara, India