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Prediction of ground water quality in western regions of Tamilnadu using LSTM network
Assessing and safeguarding groundwater quality is critical for sustaining life in water-scarce regions like western Tamil Nadu. The motivation behind this study stems from the pressing need to address water quality challenges in a region grappling with scarcity. Despite existing efforts, a notable research gap exists in predictive tools that comprehensively capture the nuanced temporal variations and trends in groundwater quality. This is where the LSTM network steps in, showcasing exceptional accuracy in short-term predictions and discerning long-term trends. This research uses Long Short-Term Memory (LSTM) networks, a variant of recurrent neural networks, to predict groundwater quality in South Indian Regions, especially in Tamil Nadu. Extensive data, encompassing parameters such as pH, dissolved oxygen, turbidity, and various chemical constituents, were gathered over an extended timeframe. The LSTM model was then trained on this historical dataset, factoring in temporal dependencies and seasonality inherent in groundwater quality data. The validation process rigorously tests the LSTM model against actual groundwater quality measurements. The results were impressive, as the model demonstrated a remarkable ability to unravel the complex variations in groundwater quality. 2024 Elsevier B.V. -
Studies on thermal, structural, electrical and optical properties of Se-Te-Sb chalcogenide glasses /
Glasses, an intriguing state of matter, known to mankind since ages, have seen systematically reported investigations only in the 20th century. Of the various kinds of glasses such as silicates, oxides, halides, chalcogenide etc., a large spectrum of commercial and technological applications of chalcogenide glasses(ChG), have made them a subject of great interest and studied for more than four decades now. -
10-camphor sulfonic acid: A simple and efficient organocatalyst to access anti-SARS-COV-2 Benzoxanthene derivatives
10-Camphor sulfonic acid (10-CSA) has gained popularity as an organocatalyst due to its broad range of solubility and user-friendliness. Affordable multicomponent reactions (MCRs) for the preparation of benzoxanthenes (4a-4 h) (5a-5i) are presented in this work. Extensive investigations and records have been conducted on the diverse biological features exhibited by xanthenes and benzoxanthenones, such as their antiviral, antibacterial, and anti-inflammatory capabilities.Using ?-naphthol, dimedone, and aldehydes, we demonstrate a cost-effective and environmentally friendly catalytic method. Under ideal circumstances, the 10-CSA catalyzes one-pot reaction, procuring impressive amounts of benzoanthenes (8595 %). All the synthesized compounds were characterized by 1H NMR and 13C NMR. A wide variety of suitable chemicals, simple work-up procedures, and solvent-free synthesis outperforms numerous existing methods for procuring biologically relevant benzoxanthene derivatives are some of the interesting features of this organocatalyzed bronsted acid process. Therefore this synthesis is industrially inevitable. Furthermore, computational studies such as molecular docking and ADMET data analysis were performed on a number of the synthesized benzoxanthene molecules. This has led to the identification of the most potent synthetic against the SARS-CoV-2 spike protein. Additionally, to mimic how medicinal compounds interact to target proteins, computational docking and dynamics techniques were used. These studies showed that, in terms of binding affinity and other crucial traits, 4a, 4b, and 5a are potential possibilities. Overall, the current study should be of great help in the development of benzoxanthene analogs which can be potential drugs for treatment of COVID-19. 2024 Elsevier B.V. -
EDUCATION AND SKILL REQUIREMENTS: A STUDY OF INFORMATION TECHNOLOGY INDUSTRY IN BANGALORE
India is passing through the crucial phase of demographic transition wherein a majority of its population is in the working age, giving India a never before opportunity to cash in on a huge demographic dividend. This brings spotlight on the human capital benefits that can accrue as a result of this phase with 54% of Indias 1.2 billion population under the age of 25. It is highly imperative for India to cash in on this critical phase through the creation and capitalization of knowledge, competency and the skill base of its people or the Human Capital and pave the way for faster economic growth and development of its economy. The study takes in to consideration the Information Technology industry, wherein Indias prowess has been widely celebrated with Indian software engineers doing exceedingly well and there has been an apparent unstoppable outflow of jobs to India from U.S and Europe. India has become the undisputed global hub for outsourcing and technology mediated work. This has been possible primarily because of the rich pool of technically proficient English speaking workforce with superior logical and reasoning skills. One of the prime reasons for this has been the vast network of academic infrastructure in India churning out more than 500,000 technical graduates annually (NASSCOM, 2012). But multiple surveys by NASSCOM and CII have shown severe gap between employment and employability of technical graduates with only 25% of technical graduates suitable for employment, the rest lacking in skills which the industry wants. In order to solve this paradox, the study was initiated to examine the skill requirements of new recruits in the IT sector. It aims at bringing about the differences, if any between the perception of academia and the industry on the importance of specific skill sets for new IT recruits. The study also explores if there is any disconnect between what the industry perceives to be the available skill sets among the new IT recruits and what the academia perceives to have imparted in terms of those skill sets to their students. In order to capture the perception of the academia and the industry, the study takes in to account their responses on a five-point likert scale on the desired level and actual level of proficiency of new IT recruits on technical, business, interpersonal and management skills. The study found that there were significant differences in the perception of IT Managers and Academicians on the desired level of proficiency of new IT recruits in 4 out of 7 skill sets analyzed, which were Interpersonal and Management Skills, Emerging Technologies Skills, IT Infrastructure Skills and Critical Thinking and Problem Solving Skills. IT Managers and Academicians differed in their views on the actual level of proficiency of new IT recruits too, as significant differences were found in their responses to 5 out of the 7 skill sets which were Interpersonal and Management Skills, Emerging Technologies Skills, Technical Management Skills, IT Infrastructure Skills and Critical Thinking and Problem Solving Skills. It surely does call for an active and productive partnership between the industry and the academia through meaningful communication, coordination and rigorous steps to bridge the gap and eventually to sustain and strengthen the inherent advantage that India has in the field of Information Technology. -
Toward knowledge societies in the gandhian perspective and the civil rights movement
Mohandas K Gandhi and Martin Luther King, Jr as disciples of nonviolence fought against oppression. Gandhi and King strove to learn beyond what their schools taught them and became better educated men. Gandhi had a vision and King a dream. Through education Gandhi helped those who had Kings dream to connect the dream with the vision to deal with the awful reality of injustice and helped to make the world a better place. This paper through the four Pillars of Learning will demonstrate how Gandhi impacted the Civil Rights Movement with his vision and how leaders of the Civil Rights Movement and King among them appropriated the vision of Gandhi and used nonviolence as a tool to deal with the oppression under which they lived. 2019 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore). -
A Bibliometric Analysis of Asset Allocation for Retirement
Allocation of investment assets is key in attaining a sustainable retirement portfolio. In this research article, the authors analyzed the most recent research publications in the area related to asset allocation for retirement and identified those which have the highest impact. The authors research was conducted using the bibliometric analysis technique of research articles collected from the Scopus database. Most of the research articles were published in reputed journals in the United States, United Kingdom, Australia, and Germany. It was also observed that most of the highly cited research articles in the research area of asset allocation for retirement are focused on financial literacy, increase in retirement age, aging, and pension reforms. The authors findings identified six research themes in asset allocation for retirement such as 1) asset allocation for retirement planning, 2) methods to increase efficiency, 3) investment preferences for retirement savings 4) financial literacy and retirement planning, 5) reforms on retirement savings, and 6) annuities for retirement income. Furthermore, nineteen future research directions are also provided. In conclusion, the authors aim to assist future researchers in identifying highly cited articles, key authors, contributing countries and research themes in asset allocation for retirement. Overall, the analysis provides comprehensive information in addressing research questions in the field of asset allocation for retirement. Copyright 2024 With Intelligence LLC. -
High-Speed Parity Number Detection Algorithm inRNS Based onAkushsky Core Function
The Residue Number System is widely used in cryptography, digital signal processing, image processing systems and other areas where high-performance computation is required. One of the computationally expensive operations in the Residue Number System is the parity detection of a number. This paper presents a high-speed algorithm for parity detection of numbers in Residue Number System based on Akushsky core function. The proposed approach for parity detection reduces the average time by 20.39% compared to the algorithm based on the Chinese Remainder Theorem. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Nurses' perception about Human Resource Management system and prosocial organisational behaviour: Mediating role of job efficacy
Aims: To examine the relationship between nurses' perception about human resource management system and prosocial organisational behaviour through job efficacy. Background: Literature suggests that non-profit organisations are often confronted with financial constraints on one side and the expectation of delivering high-quality services on the other. Employees voluntarily engaging in service-oriented behaviours help to bridge this gap to some extent, and human resource management system plays a significant role in eliciting the requisite behaviours. In this article, the case of nurses from non-profit hospitals has been undertaken to examine the aspects of human resource management system that needs focus while promoting prosocial organisational behaviours among the nurses for ensuring better service delivery. Method: Cross-sectional design was employed. Data were collected from 387 nurses working in non-profit hospitals in India through questionnaires and were analysed with the help of structural equation modelling. Findings: In the absence of sophisticated human resource system in non-profit hospitals, the study found that nurses' perception about human resource management system is positively related to prosocial organisational behaviours, and job efficacy partially mediates the relationship. Conclusion: Positive perceptions such as involvement with the job and communication as well as supervisors' support are essential human resource practices for fostering self-efficacy and, thus, improving prosocial organisational behaviour of nurses working in non-profit hospitals. Implication for Nursing Management: Non-profit hospitals should focus on nurses' participation and supervisory support, which would provide a better human touch approach to patient care and also improve service quality. The findings shed light on the nursing management of non-profit hospitals in terms of human resource management that has to be given much attention for institutionalizing prosocial organisational behaviour. 2021 John Wiley & Sons Ltd -
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An investigation into the causes of non compliance with labour laws by zimbabwean local authorities
The current research; which I carried out in Mashonaland East Province of Zimbabwe between 2012 and 2014 was prompted by the surge newlinein labour related disputes in sub-national governments in Zimbabwe as well as the evident poor levels of compliance to labour laws by local authorities which also happen to be a poorly rated sector of the economy in terms of service delivery. In carrying out the study, I was guided by the following newlineresearch objectives: to identify the challenges being faced by Zimbabwean newlinelocal authorities in complying with the labour laws, to establish the extent to which non compliance affects labour relations in local government in Zimbabwe, to ascertain the impact of non-compliance on service delivery and finally to assess the government monitoring aspect. The targeted population for the study comprised all the ten local authorities and ministry of local government employees from the province. The study mainly newlineemployed the exploratory research design and I found that non-compliance with labour laws by Zimbabwean local authorities was not only as a result of the quality of labour relations and management systems (internal controls and corruption) but also lack of governmental financial support, political newlineinterference, skills migration (brain drain), increased poverty (economic meltdown) and high unemployment rate. In light of the research findings, I recommend that the government formulates deliberate policies to re-engage the international community as this will help attract foreign direct investment; thereby reducing poverty, unemployment, skills migration and corruption. I also recommend an increase in the financial support by government to its sub national governments. There should also be total newlinedecentralization of all sub national governments to ensure efficiency and newlinenon-interference with local authorities operations. -
Performance evaluation of diesel engine using genetic algorithm
?Abstract: Engine analysis and optimization is not a new approach to the field of automobiles. It has always been a keen focus in the research of experts domestically as well as internationally, the control of Air-Fuel Ratio (AFR) in transient operating conditions of engine. For the last few decades, the industry and economic expansion of developed countries has showed a clean increase in the vehicle production as well as transport volume. Global warming, acid rain, greenhouse effect and air pollution problems related to emission of CO2, NOx, PM, CO and unburned HC, together with the consumption of fossil fuels, unite to create serious problems at a global level. Therefore it is a research study considering all these current issues and taking it to a new level of optimization for the output of a better efficiency, better economy and less pollution. Performance of Diesel Engine is evaluated by parameters like Power, Torque and Specific Fuel Consumption. 2018, Blue Eyes Intelligence Engineering and Sciences Publication. All rights reserved. -
A Survey on Arrhythmia Disease Detection Using Deep Learning Methods
The Cardiovascular conditions are now one of the foremost common impacts on human health. Report from WHO, says that in India 45% of deaths are caused due to heart diseases. So, heart disease detection has more importance. Manual auscultation was used to diagnose cardiovascular problems just a few years ago. Nowadays computer-assisted technologies are used to identify diseases. Accurate detection of the disease can make recovery simpler, more effective, and less expensive. In this proposed work, 11years of research works on arrhythmia detection using deep learning are integrated. Moreover, here presents a comprehensive evaluation of recent deep learning-based approaches for detecting heart disease. There are a number of review papers accessible that focus on traditional methods for detecting cardiac disease. This article addresses some essential approaches for categorizing ECG signal images into desired classes, such as pre-processing, feature extraction, feature selection, and classification. However, the reviewed literatures consolidated details have been summarized. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
IOT based application for monitoring electricity power consumption in home appliances
Internet of Things is one of the emerging techniques that help in bridging the gap between the physical and cyber world. In the Internet of Things, the different smart objects connected, communicate with each other, data is gathered from the smart objects and based on the need of the users, and the data gathered are queried and sent back to the user. IoT helps in monitoring electrical and physical parameters. Electricity consumption from electronic devices is one among such parameters that need to be monitored. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper proposes a Wi-Fi enabled simple low cost electricity monitoring device that can monitor the electricity consumption on home appliances which helps to analyses the consumption of electricity on a daily and weekly basis. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
A Mixed-Methods Study of Training in Evidence-Based Practice in Psychology Among Students, Faculty, and Practitioners in India and the United States
The current mixed-method study in India and the United States assessed understanding of what evidencebased practice in psychology (EBPP) is, how EBPP training and implementation occurs, and perceived barriers and needs related to EBPP training. Graduate students (India, n = 282; United States, n = 214), faculty (India, n = 24; United States, n = 67), and practitioners (India, n = 24; United States, n = 49) were surveyed, and focus groups with students (India, n = 31; United States, n = 12), faculty (India, n = 10, United States, n = 9), and practitioners (India, n = 28; United States, n = 17) were held. Individuals across countries and across the professional continuum were only somewhat aware of EBPP, largely equating it to just using empirically supported treatments. In both the United States and India, EBPP training was largely infused across the curriculum, though a sizable percentage of participants did report only limited exposure to EBPP training. Participants perceived themselves as engaging in EBPP. The biggest barriers to EBPP training (largely shared across countries) were hesitancy about EBPP, investing the time in training, and being wedded to a single school of thought. Indian participants also noted a limitation in primarily relying on data from Western countries. EBPP training needs identified included desire for greater flexibility within EBPP, receiving more theoretical foundation in EBPP, and more applied EBPP training. Results demonstrated advances in EBPP training in the past 15 years since the release of American Psychological Associations task force report but also provide areas for growth in training, specifically surrounding balancing research evidence with clients cultural context as well as ways to promote lifelong EBPP learning. 2024 American Psychological Association -
Intersecting Ecocriticism and Gender in Selected Writings of Easterine Kire
The research study, Intersecting Ecocriticism and Gender in Selected newlineWritings of Easterine Kire, analyses the intersection of histories, identities, gender, and ecology to understand the larger context of marginalisation and newlinerepresentation. Indigenous literature often subverts Western worldviews and mainstream discourses with counter-discourse narratives by placing their stories at the centre. In recent times, literature from Indigenous societies has established a position in which Indigenous people represent, resist, newlinedecolonise, and construct their identity. The Indigenous Naga community has experienced marginalisation for decades, having suffered multiple oppressions of their history, stories, knowledge, and lack of rights; however, contemporary literary writings challenged the silencing system through writing back and representation. In her fictional works, Naga author Easterine Kire explores the possibilities of reviving and restoring the Angami Naga community and their newlinelost cultures and identities. Focusing on analysing three important themes: Peoplestories, Ecopolitics, and Gender politics, the study represents Naga histories, emerging identities, gender, and ecological concerns as interpreted in the fiction of Easterine Kire. The objective is to represent Indigenous Naga voices using fictional narratives of Easterine Kire to reclaim, revive, and redefine Indigenous culture and history from an insider s perspective. It also examines how intersecting narratives contribute to the larger context of Naga identity construction. newlineEasterine Kire s writing is a culturally conscious and decolonial strategy in newlinewhich she incorporates her community s oral tradition and storytelling in her fictional narratives. Easterine Kire s narrative engages in a deep conscious cultural revival and reinvention of her community s cultural heritage. -
A Study on Experimental Analysis of Best Fit Machine Learning Approach for Smart Agriculture
By 2050, the population is projected to exceed nine billion, necessitating a 70% increase in agricultural output to meet the need. Land, water, and other resources are running out due to the growing world population, making it impossible to maintain the demandsupply cycle. The yield of cultivation is also declining as a result of people's ignorance of the growing crop illnesses. Given that food is the most basic human requirement, future research should focus on revitalizing the agricultural sector. Farming may be made more productive for farmers by applying the right artificial intelligence technologies and datasets. Agronomics can benefit greatly from artificial intelligence. So that we can farm more effectively and be as productive as possible, we need to adopt a better strategy. The objective of this paper is to experimentally analyze the machine learning algorithms and methods already in use and forecast the most effective approach to use in each agricultural sector. In this article, we will present the challenges farmers face when using traditional farming methods and how artificial intelligence is revolutionizing agriculture by replacing the traditional methods. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
NDC Pebbling Number for Some Class of Graphs
Let G be a connected graph. A pebbling move is defined as taking two pebbles from one vertex and the placing one pebble to an adjacent vertex and throwing away the another pebble. A dominating set D of a graph G = (V, E) is a non-split dominating set if the induced graph < V ? D > is connected. The Non-split Domination Cover(NDC) pebbling number, ?ns(G), of a graph G is the minimum of pebbles that must be placed on V(G) such that after a sequence of pebbling moves, the set of vertices with a pebble forms a non-split dominating set of G, regardless of the initial configuration of pebbles. We discuss some basic results and determine ?ns for some families of standard graphs. 2024 the Author(s), licensee Combinatorial Press. -
Vision Based Vehicle-Pedestrian Detection and Warning System
Road Sense must be respected and obeyed by both the pedestrian and the driver. Moreover, urbanization has led to a steadfast rise in the fleet of vehicles, their speed, as well as non-compliance with road safety measures, and other such factors have provoked an inescapable increase of accidents in road traffic involving pedestrians. Pedestrian collisions can be predicted and prevented. At the very basic, there has to be vehicle and pedestrian detection along with speed estimation, which can be further applied to Vehicle-Pedestrian Collisions and various emerging fields like Industrial Automation, Transportation, Automotive, Security/Surveillance, or in Dangerous environments. This paper reviews the literature on vehicle and pedestrian detection based on two significant categories: pre-processing phase and detection phase, with a detailed comparative analysis. The papers reviewed cover video-based surveillance systems. 2022 IEEE. -
A Video Surveillance-based Enhanced Collision Prevention and Safety System
Road traffic crashes that result in fatalities have become a global phenomenon. Therefore, it is imperative to use caution and vigilance while being on the road. Human mistake, going over the speed limit, being preoccupied while driving or walking, disobeying safety precautions, and other factors can also contribute to such unforeseen accidents or injuries, which can result in both bodily and material loss. So, safety is what we seek to achieve. Furthermore, as the number of automobiles has increased, so too have collisions between vehicles and pedestrians. Using computer vision and deep learning approaches, this research seeks to anticipate such encounters. The data often comes from traffic surveillance cameras in video formats. We have therefore concentrated on video sequences of vehicle-pedestrian collisions. We begin with a detection phase that includes the identification of vehicles and pedestrians; for this phase, we employed YOLO v3 (You Only Look Once). YOLO v3 has 80 classes, but we only took six of them: person, car, bike, motorcycle, bus, and truck. Following detection, the Euclidean distance approach is used to determine the interspace between the vehicle and the pedestrian. The closer the distance between a vehicle and a pedestrian, the more likely it is that they will collide. As a result, pedestrians in risk are located, and once we are aware of the pedestrians in danger, we search for nearby safer regions to alert them to head to the nearest location that is secure. Grenze Scientific Society, 2023.