MADeGen: Multi-Agent based Deep Reinforcement Learning for Sequential Keyphrase Generation
Actor-critic; Adaptive reward; Extraction agent; Generation agent; Keyphrase generation; Multi-agent; Reinforcement learning
Keyphrase generation is an essential tool in the field of natural language processing for information retrieval, document summarization, and text recommendation applications, extracting succinct and representative phrases from the text document. Traditional keyphrase extraction methods applied the supervised or unsupervised learning fail to capture the sequential keyphrase generation in a dynamic environment. The keyphrase generation approaches lack focus on explicitly discriminating the present and absent keyphrases, leading to the inadequate generation of semantically rich absent keyphrases. Hence, this work utilizes the potential benefits of reinforcement learning with the design of a distinguished reward function for present and absent keyphrases for sequential decision-making in the keyphrase generation. Thus, this work presents a novel keyphrase generation system, MADeGen, utilizing Multi- Agent Deep Reinforcement Learning (MADRL). In particular, a multi-agent reinforcement system collaboratively enables the generation of representative and coherent keyphrases by the evaluation metric-aware cooperative reward function analysis and adaptively training the agents. The proposed MADeGen incorporates two major phases, such as multi-agent modelling and actor critic-based policy optimization towards accurate keyphrase generation. In the first phase, the proposed approach designs two learning agents, including the extraction agent and generation agent, with the incorporation of a pre-trained language model. In the multi-agent system, the generation agent is the finetuned version of the extraction agent with the integration of the Wikipedia source. Secondly, the evaluation-aware adaptive reward function is designed to evaluate each agent's generated keyphrases with reference to ground-truth keyphrases. In subsequence, the cooperative reward analysis triggers the actor critic-based policy optimization for the generation agent in the multi-agent system to precisely generate the semantically relevant keyphrases with the assistance of an external web source. Experimental results on several benchmark datasets, such as Inspec, PubMed, and wiki20, illustrate the effectiveness of the proposed MADeGen compared to the existing keyphrase extraction models, yielding state-of-the-art performance in keyphrase extraction tasks. The proposed MADeGen proves its higher performance in the present as well as absent keyphrase extraction as 0.367 and 0.438 F1-score, respectively, while testing on the Inspec dataset. (2024), (Intelligent Network and Systems Society). All Rights Reserved.
International Journal of Intelligent Engineering and Systems, Vol-17, No. 6, pp. 69-85.
Jose J., Christ Deemed to be University, Bangalore, India; Soundarabai P.B., Christ Deemed to be University, Bangalore, India
The impact of the COVID-19 pandemic on e-learning adoption in an emerging market: a longitudinal study using the UTAUT model
Behavioral intention; Covid-19; E-learning; Longitudinal study; PLS-SEM; UTAUT
Purpose: The COVID-19 pandemic provided unprecedented impetus to the evolution of the e-learning learning ecosystem by compelling students to adopt e-learning systems. This paper aims to use the UTAUT model to provide insight into the differences in factors influencing the adoption of e-learning systems before and after the pandemic. Design/methodology/approach: This longitudinal study uses two surveys conducted among graduate students in the city of Bengaluru in India. One prior to the start of the COVID-19 pandemic and a second in its aftermath. PLS-SEM is used to analyze both data sets to draw insights into the constructs that influence Behavioral intention to adopt e-learning systems. The moderating effect of gender is also analyzed. Findings: Pre COVID-19, Facilitating Conditions, Performance Expectancy and Effort Expectancy (quadratic behavior) were dominant factors influencing the adoption of e-learning technologies. Post pandemic, Performance Expectancy and Social Influence are drivers of e-learning adoption. Effort Expectancy and Facilitating Conditions grouped as Ease of Use is a significant driver of e-learning adoption post pandemic. Gender is found to not have a moderating influence. Originality/value: The unique longitudinal study of the differences in factors influencing students intention to adopt e-learning pre- and post-COVID-19 can prove useful to policy makers in the higher education sector. Academics can use the post-pandemic e-learning models findings in multiple contexts such as generational cohorts, educational contexts and social contexts. 2024, Emerald Publishing Limited.
https://doi.org/10.1108/JABS-07-2024-0373 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209716409&doi=10.1108%2fJABS-07-2024-0373&partnerID=40&md5=54a8e378fd60578a972fcab0f2157938
Nair M.S., Congruence Systems, Bangalore, India; Nair J., St. Josephs Institute of Management, Bangalore, India; Chellasamy A., School of Business and Management, Christ University, Bangalore, India
Esther reimagined: feminist essence in Sara Josephs narrative
biblical women; feminism; liberation; voice and agency of women
Gynocentric approaches to biblical women uncover narratives of liberation and empowerment. These perspectives highlight the gaps and omissions in the representation of women within the overarching metanarrative of the Bible. Sara Josephs novel, Esther, serves as a feminist reimagining of the biblical story of Esther, offering a pluralistic lens through which to examine the experiences and lives of women against the backdrop of patriarchy. This paper utilises the feminist hermeneutic method to critically engage with the narrative, drawing on the feminist frameworks established by scholars such as Elizabeth Fiorenza and Esther Fuchs. It argues that biblical women can be reinterpreted as positive role models, saviours, heroines, and vital contributors to an extraordinary narrative of survival and redemption. 2024 Informa UK Limited, trading as Taylor & Francis Group.
International Studies in Catholic Education
Davis A.M., Department of English and Cultural Studies, Christ Deemed University, Bangalore, India; Abhaya N.B., Department of English and Cultural Studies, Christ Deemed University, Bangalore, India
Exploring the factors of learning organization in school education: therole of leadership styles, personalcommitment, andorganizational culture
Leadership styles; Learning organization; Organizational culture; Personal commitment; School education
Purpose: This study aims to test the conceptual model of the factors of learning organization and explore the degree of mediation of organizational culture in the relationship between leadership styles, personal commitment, and learning organization in school education. Design/methodology/approach: The learning organization profile (LOP) and OCTAPACE profile served to measure learning organization and organizational culture, respectively. The researchers developed scales to measure principals leadership styles and teachers personal commitment. Data included 750 school teachers. Findings: This study found a good fit in the proposed conceptual model. The organizational culture had a significant mediating effect on the path of leadership styles and learning organization and a significant mediating effect on the path of personal commitment and learning organization. Originality/value: To promote a more comprehensive learning culture, school principals should consider two specific organizational mechanisms: the intangible cultural components (such as corporate values, beliefs, and norms) and the tangible structural components (such as organizational structure and workflow systems). These two domains play a crucial role in creating a conducive learning environment. 2024, Jacqueline Kareem, Harold Andrew Patrick and Nepoleon Prabakaran.
https://doi.org/10.1108/CEMJ-12-2023-0457 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209391291&doi=10.1108%2fCEMJ-12-2023-0457&partnerID=40&md5=4204c282539bf24f2db248eba8afe5a3
Kareem J., School of Education, CHRIST (Deemed to be University), Bangalore, India; Patrick H.A., CMS Business School, Jain University, Bangalore, India; Prabakaran N., CMS Business School, Jain University, Bangalore, India
Accumulation of heavy metals (Cr, Cu, As, Cd, Pb, Zn, Fe, Ni, Co) in the water, soil and plants collected from Edayar Region, Ernakulam, Kerala, India
ICP-MS; industrialisation; toxicity; urbanization
The accumulation of heavy metals in the environment is a significant concern due to their potential toxicity and persistence. This study investigates the levels of heavy metal contamination in the water, soil and plants of the Edayar region in Ernakulam, Kerala, India. The region has experienced industrialization and urbanization, leading to concerns about heavy metal pollution. The study aims to assess the concentrations of chromium (Cr), copper (Cu), arsenic (As), cadmium (Cd), lead (Pb), zinc (Zn), iron (Fe), nickel (Ni) and cobalt (Co) in water, soil, aquatic and terrestrial plants. Samples were collected from various locations within the Edayar region, and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was conducted to quantify heavy metal concentrations. The findings of this study will contribute to the assessment of heavy metal pollution in the Edayar region. Plants with a high diversity index were taken for analysis from both aquatic and terrestrial habitats. Scoparia dulcis L. seems to specialize in metal accumulation, possibly for protective purposes. Synedrella nodiflora Gaertn demonstrates adaptability to metal-rich environments through robust metal uptake and tolerance mechanisms. Alternanthera philoxeroides (Mart.) Griseb, on the other hand, appears to have developed mechanisms to manage heavy metal exposure. The results indicate significant levels of heavy metal contamination across all samples, with the highest concentrations detected in soil, followed by water and plants. Chromium and lead levels in soil exceeded the permissible limits set by international standards, posing potential risks to human health and the ecosystem. The accumulation patterns in plants varied, with higher bioaccumulation factors observed for zinc and copper, suggesting their preferential uptake. This study highlights the urgent need for remediation strategies and continuous monitoring to mitigate the impact of heavy metal pollution in the Edayar region. The results will help in understanding the environmental impact of human activities. Copyright: The Author(s).
Plant Science Today, Vol-11, No. 4, pp. 907-923.
https://doi.org/10.14719/pst.3385 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207806084&doi=10.14719%2fpst.3385&partnerID=40&md5=5c4e083282e789bdf0a99ac753f23e3b
Syamlal C.A., Department of Life Sciences, Christ University, Karnataka, Bengaluru, 560029, India; Sayantan D., Department of Life Sciences, Christ University, Karnataka, Bengaluru, 560029, India
Efficient one-pot green synthesis of carboxymethyl cellulose/folic acid embedded ultrafine CeO2 nanocomposite and its superior multi-drug resistant antibacterial activity and anticancer activity
Antibacterial activity; Biocompatibility; Carboxymethyl cellulose; CeO2; Folic acid
Due to the prevalence of drug-resistant bacteria and the ongoing shortage of novel antibiotics as well as the challenge of treating breast cancer, the therapeutic and clinical sectors are consistently seeking effective nanomedicines. The incorporation of metal oxide nanoparticles with biological macromolecules and an organic compound emerges as a promising strategy to enhance breast cancer treatment and antibacterial activity against drug-resistant bacteria in various biomedical applications. This study aims to synthesize a unique nanocomposite consisting of CeO2 embedded with folic acid and carboxymethyl cellulose (CFC NC) via a green precipitation method using Moringa oleifera. Various spectroscopic and microscopic analyses are utilized to decipher the physicochemical characteristics of CFC NC and active phytocompounds of Moringa oleifera. Antibacterial study against MRSA (Methicillin-resistant Staphylococcus aureus) demonstrated a higher activity (95.6%) for CFC NC compared to its counterparts. The impact is attributed to reactive oxygen species (ROS), which induces a strong photo-oxidative stress, leading to the destruction of bacteria. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of CFC NC are determined as 600g/mL and 1000g/mL, respectively. The anticancer activity against breast cancer cell resulted in the IC50 concentration of 10.8?g/mL and 8.2?g/mL for CeO2 and CFC NC respectively.The biocompatibility test was conducted against fibroblast cells and found 85% of the cells viable, with less toxicity. Therefore, the newly synthesized CFC NC has potential applications in healthcare and industry, enhancing human health conditions. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
Boopathi T.S.; Rajiv A.; Patel T.S.G.M.; Bareja L.; Salmen S.H.; Aljawdah H.M.; Arulselvan P.; Suriyaprakash J.; Thangavelu I.
Springer Science and Business Media Deutschland GmbH
ISSN: 16157591; PubMed ID: 39503917; CODEN: BBEIB
Boopathi T.S., Department of Chemistry, Amrita School of Physical Sciences, Amrita Vishwa Vidyapeetham, Coimbatore, 641112, India, Functional Materials Laboratory, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, 641112, India; Rajiv A., Department of Physics, Faculty of Sciences, JAIN (Deemed-to-Be University), Karnataka, Bangalore, 562112, India; Patel T.S.G.M., Department of Community Medicine, Parul University, Gujarat, PO Limda, Tal. Waghodia, Vadodara, 391760, India; Bareja L., Centre of Research Impact and Outcome, Chitkara University, Punjab, Rajpura, 140417, India; Salmen S.H., Department of Botany and Microbiology, College of Science, King Saud University, PO Box-2455, Riyadh, 11451, Saudi Arabia; Aljawdah H.M., Department of Zoology, College of Science, King Saud University, PO Box-2455, Riyadh, 11451, Saudi Arabia; Arulselvan P., Department of Chemistry, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Tamil Nadu, Chennai, 602 105, India; Suriyaprakash J., Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter, Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices, School of Information and Optoelectronic Science and Engineering, South China Normal University, Guangzhou, 510006, China; Thangavelu I., Department of Chemistry, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560029, India
Purification and Biochemical Characterization of Beta-Hexosaminidase B from Freshwater CnidarianHydra vulgaris Ind-Pune
Cnidarian; Hydra vulgaris; Lysosomal hydrolases; ?-N-Acetylhexosaminidase
Beta-N-acetylhexosaminidase (Hex) is a vital lysosomal hydrolase found in all living organisms, playing a crucial role in cellular homeostasis. Dysfunctions in this enzyme are implicated in severe pathological conditions such as Tay-Sachs and Sandhoff diseases in humans. In this paper, we report the purification and biochemical characterization of hexosaminidase from the soluble extracts obtained from the polyps of Hydra vulgaris Ind Pune. The Hydra Hex was purified by two-step sequential chromatography (hydrophobic interaction and gel filtration). Our results suggested that the enzyme isoform purified from Hydra is HexB, most likely to be a homodimer with a subunit mass of 65 kD. The pH optimum was in the range of 5.0 to 6.0 and the temperature optimum in the range of 50 C to 60 C. pH stability and temperature stability were found to be 5.0 and 40C respectively. The homology modelling studies corroborated the homodimeric nature of Hydra HexB, and indicated its structural resemblance to human HexB. This study offers new insights into the biochemical characteristics of Hydra HexB, providing a foundational framework for extensive investigations on this and other lysosomal hydrolases in Hydra. In a broader context, our results significantly contribute to establishing Hydra as a potential model organism to study the lysosomal biogenesis pathway. (2024), (Association of Carbohydrate Chemists and Technologists). All Rights Reserved.
Kukkemane K.; Krishnapati L.S.; Vuruputuri R.M.; Ranganatha K.S.; Kumar N.S.
Trends in Carbohydrate Research, Vol-16, No. 3, pp. 60-75.
Association of Carbohydrate Chemists and Technologists
Kukkemane K., Protein Biochemistry and Glycobiology Laboratory, Department of Biochemistry, School of Life Sciences, University of Hyderabad, Telangana, Hyderabad, 500046, India, Department of Life Sciences, School of Sciences, CHRIST University, Karnataka, Bengaluru, 560029, India; Krishnapati L.S., Protein Biochemistry and Glycobiology Laboratory, Department of Biochemistry, School of Life Sciences, University of Hyderabad, Telangana, Hyderabad, 500046, India; Vuruputuri R.M., Protein Biochemistry and Glycobiology Laboratory, Department of Biochemistry, School of Life Sciences, University of Hyderabad, Telangana, Hyderabad, 500046, India; Ranganatha K.S., Protein Biochemistry and Glycobiology Laboratory, Department of Biochemistry, School of Life Sciences, University of Hyderabad, Telangana, Hyderabad, 500046, India; Kumar N.S., Protein Biochemistry and Glycobiology Laboratory, Department of Biochemistry, School of Life Sciences, University of Hyderabad, Telangana, Hyderabad, 500046, India, University of Bremen, Bremen, Germany
Women entrepreneurs vs. women employees: a comparative study of personality traits and success factors of women in India
employees; entrepreneurs; India; personality traits; success; women
In the current study, the researchers evaluate the relationship between personality traits, as defined by the Big Five personality traits, and success factors of women: as entrepreneurs and employees. The findings are based on data collected from 100 women employees and 100 women entrepreneurs. Data was collected using structured questionnaires and analysed using IBM SPSS. The findings suggest that there are statistically significant differences between women entrepreneurs and women employees on certain dimensions of personality. The evaluation of the relationship between the personality traits and success factors revealed that in the case of entrepreneurs, personality traits were significant in predicting success. As nations work to improve gender ratios in the labour force and as the number of women entrepreneurs grows, a better understanding of what constitutes success and the factors that could influence success are critical in supporting female participation in the economy, as entrepreneurs and employees. Copyright 2024 Inderscience Enterprises Ltd.
International Journal of Entrepreneurship and Small Business, Vol-53, No. 4, pp. 544-556.
https://doi.org/10.1504/IJESB.2024.142440 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208396783&doi=10.1504%2fIJESB.2024.142440&partnerID=40&md5=82e1ab9b90340c14bfbbc29c19d0cde2
Mathew J., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Arvind T., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Nair S., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India
BYJUS; EdTech; Layoffs; Toxic work culture
Learning outcomes: This case study provides students/managers an opportunity to learn about the following: to infer the challenges involved in the downsizing of employees; to asses and evaluate BYJUS organizational culture; and to determine the impact of workplace toxicity. Case overview/synopsis: The focus of this case is the controversy faced by BYJUS due to its mass layoffs and toxic work culture. This case discusses the CEOs dilemma in resolving the controversy. Two rounds of mass layoffs at BYJUS are discussed in detail. The industrial dispute filed by Employees Union against BYJUS accusing it of denying due compensation to laid-off employees is also discussed. This case consists of a section explaining the toxic work culture at BYJUS, which is supported by employee complaints. The CEOs justification and apology have been illustrated in this case. The case ends with a closing dilemma and challenges faced by the CEO. Complexity academic level: The case is best suited for undergraduate students studying Human Resources Management subjects in Commerce and Business Management streams. The authors suggest that the instructor inform students to read the case before attending the 90-min session. It can be executed in the classroom after discussing the theoretical concepts. Supplementary material: Teaching notes are available for educators only. Subject code: CSS 6: Human Resource Management. 2024, Emerald Publishing Limited.
Emerald Emerging Markets Case Studies, Vol-14, No. 4, pp. 1-12.
https://doi.org/10.1108/EEMCS-12-2023-0507 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208532331&doi=10.1108%2fEEMCS-12-2023-0507&partnerID=40&md5=907e3af4a570a4eca54359e2b4c24d02
Saldanha A., Department of Marketing, St Josephs Institute of Management, Bangalore, India; Aranha R., School of Business and Management, Christ University, Bangalore, India
Cyber-Threat Landscape in Healthcare Industry and Legal Framework Governing Personal Health Information in India
cyber-threats; cybersecurity; electronic health records (EHR); healthcare; personal health information
2021 and 2022 have been the years of frequent cyberattacks. India remains in the top 25 countries severely affected by the continuous cyber-attacks and tops the list. The healthcare department is amongst the most affected area. In 2020, the healthcare department suffered a severe impact with around 348K cyber-attacks alone on Indian healthcare infrastructure. The recent occurrence of cyber-attack on AIIMS hospital in December 2022 followed by several other incidences of data breaches have made the concerned authorities pro-active on exercising vigilance and reforming the legal and technical system to protect the health infrastructure. This paper has been developed on extensive literature and focuses on describing the nature of electronic health records, the risks they are exposed to along with as to why they are so susceptible to these cyber-risks. Furthermore, the paper also deals with different kinds of threats affecting the privacy and security of electronic health records specifically. The paper analyzes Indian legal framework, briefly compares it with international legal framework (specifically US & EU) and highlights the shortcomings in Indian legislative framework followed by laying down certain recommendations primarily highlighting the possible changes required in Indian legal framework and practices that can be adopted at organizational level to overcome and mitigate such risks. N. Raizada, P. Srivastava, 2024.
Kutafin Law Review, Vol-11, No. 3, pp. 452-490.
Kutafin Moscow State Law University (MSAL)
All Open Access; Hybrid Gold Open Access
Raizada N., CHRIST University, Bengaluru, India; Srivastava P., Rashtriya Raksha University, Gandhinagar, India
Managing coworker conflict: investigating the effect of workplace phubbing and mindfulness on employee deviant and negligent behavior
Coworker conflict; Employee deviant behavior; Employee negligence; Mindfulness; Phubbing
Purpose: This study aims to examine the influence of workplace phubbing on employee deviant behavior and negligence, while also investigating the mediating role of coworker conflict. Additionally, the study explores the moderating effect of workplace mindfulness on the relationship between workplace phubbing, the mediators and employee deviant behavior and negligence. Design/methodology/approach: Data were gathered from employees in the service sector in the UAE using an online survey questionnaire. A total of 374 participants submitted complete responses. The studys hypotheses were tested through regression-based moderated path analysis, incorporating conditional process modeling and nonlinear bootstrapping. Findings: The study indicates that experiencing phubbing at work contributes to feelings of coworker conflict, which subsequently leads to increased interpersonal deviance and employee negligence. Moreover, workplace mindfulness weakens the positive influence of being phubbed on coworker conflict, interpersonal deviance and employee negligence. Originality/value: To the best of the authors knowledge, no previous studies have examined the negative impact of being phubbed at the individual employee level within the service industry. This study aims to contribute to both theory and practice by elucidating the mediating mechanism of coworker conflict and exploring the moderating effects of workplace mindfulness. 2024, Emerald Publishing Limited.
https://doi.org/10.1108/EBHRM-04-2024-0124 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209748375&doi=10.1108%2fEBHRM-04-2024-0124&partnerID=40&md5=87a52de155eec37b0cecfe96578b8b02
Alagarsamy S., Manipal Academy of Higher Education Dubai Campus, School of Business, Academic City, Dubai, United Arab Emirates; Mehrolia S., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Vinod S., Manipal Academy of Higher Education Dubai Campus, School of Business, Academic City, Dubai, United Arab Emirates
REMEMBERING PLACE: The Temporality of Trauma in Rudraprayag after the 2013 Flash Floods
afterwardsness; compensation; disaster; temporality; trauma
The 2013 flash floods reproduced an everyday that was textural, the returning past of the event combined with gestures from within the everyday, to disorient survivors of the event. I attempt in this essay to analyze the return of the event as producing psycho-spatial affects, drawn from the psyches own propensity to return while repressing the event that causes the return, described within psycho-analytic literature as afterwardsness. Such afterwardsness is conditioned by the sheer incomprehensibility of environmental change that took place in just three days in the Mandakini Valley between June 15 and June 17, 2013. Following the flood, delays with the recovery process, and particularly with the process of compensation, exacerbate this trauma, leading to an extension of the temporality of trauma infinitely forward. (2024), (American Anthropological Association). All rights reserved.
Cultural Anthropology, Vol-39, No. 4, pp. 592-615.
https://doi.org/10.14506/ca39.4.05 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209718466&doi=10.14506%2fca39.4.05&partnerID=40&md5=e1abce3fcd1836c5baeb5822f93aebba
Efficient Mitosis Segmentation and Detection in Breast Cancer Histopathological Images Using YOLOv5 Model
breast cancer; deep learning; histopathological images; mitosis cells; segmentation; YOLO-v5
Mitosis count serves as a critical biomarker in breast cancer research, aiding in the prediction of aggressiveness, prognosis, and grade of the disease. However, accurately identifying mitotic cells amidst shape and stain variations, while distinguishing them from similar objects like lymphocytes and cells with dense nuclei, presents a significant challenge. Traditional machine learning methods have struggled with this task, particularly in detecting small mitotic cells, leading to high inter-rater variability among pathologists. In recent years, the rise in deep learning has reduced the subjectivity of mitosis detection. However, Deep Learning models face challenges with segmenting and classifying mitosis due to its intricate morphological variations, cellular heterogeneity, and overlapping structures. In response to these challenges, this study presents an Intelligent Mitosis Segmentation and Detection in Breast Cancer Histopathological Images Using Deep Learning (IMSD-BCHIDL) Model. The purpose of the IMSD-BCHIDL technique is to segment and classify mitosis in the histopathological images. To accomplish this, the IMSD-BCHIDL technique mainly employs YOLO-v5 model, which proficiently segments and classifies the mitosis cells. In addition, InceptionV3 is applied as a backbone network for the YOLO-v5 model, which helps in capturing extensive contextual details from the input image and results in improved detection tasks. For demonstrating the greater solution of the IMSD-BCHIDL method of the IMSD-BCHIDL technique, a wide range of experimental analyses is made. The simulation values portrayed the improved solution of the IMSD-BCHIDL system with other recent DL models. 2024 by the authors.
Journal of Advances in Information Technology, Vol-15, No. 10, pp. 1184-1192.
Lijo J., Department of Computer Science, Christ University, Karnataka, Bengaluru, India, School of Computer Applications, Dayananda Sagar University, Karnataka, Bengaluru, India; Saleema J.S., Department of Statistics and Data Science, Christ University, Karnataka, Bengaluru, India
Breeding distrust during artificial intelligence (AI) era: howtechnological advancements, jobinsecurity and job stress fuel organizational cynicism?
Job insecurity; Job involvement; Job stress; Layoff; Organizational cynicism; Psychological capital; Technological advancements
Purpose: This study examines how technological advancements and psychological capital contribute to job stress. Furthermore, the paper examines how job insecurity, job stress and job involvement influence the cynicism of recently laid-off employees. Despite various research studies, there is a lack of understanding of employees views on their work future and its probable influence on their job behaviors in this era of technology. Design/methodology/approach: A quantitative method was used to collect a sample of 403 recently laid-off employees. The research tool of this study was a questionnaire, and the sampling technique was stratified random sampling. IBM SPSS and AMOS software were utilized to ensure the trustworthiness and accuracy of constructs via factor analysis. The proposed hypotheses were tested using structural equation modeling. Findings: The analysis showed that technological advancements, specifically in job-related stress, job involvement and job insecurity, significantly affect organizational cynicism. Job involvement is negatively associated with employees cynicism. Practical implications: The current study adds to the comprehension of shifts in the perceived behavior of employees toward their organizations due to factors like the adoption of new technology in the organization, job stress, job insecurity and job involvement. Accordingly, there will be a need to form a favorable working atmosphere so that employees can perform their jobs with positive psychology and without any insecurity or stress. Originality/value: The study is thought to contribute to the literature in terms of measuring organizational cynicism while layoffs continue due to AI advancements. 2024, Emerald Publishing Limited.
Sharma K.; Davidson B.G.J.; George J.P.; Muttungal P.V.
https://doi.org/10.1108/EBHRM-05-2024-0159 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208940841&doi=10.1108%2fEBHRM-05-2024-0159&partnerID=40&md5=cfea09b4cf9eb519699c5e88c51355f4
Sharma K., School of Business and Management, Christ University, Bangalore, India; Davidson B.G.J., School of Business, University of the Fraser Valley, Abbotsford, Canada, Department of Marketing, Strategy, and Entrepreneurship, University Canada West, Vancouver, Canada, Department of Business Administration, Acsenda School of Management, Vancouver, Canada; George J.P., School of Business and Management, Christ University, Bangalore, India; Muttungal P.V., Department of Psychology, Christ University, Bangalore, India
Employee experience, well-being and turnover intentions in the workplace
Purpose: This study aims to examine the role of employee experience in influencing employee well-being and turnover intentions within organizations. The mediating role of well-being will also be investigated, along with an exploration of whether these relationships differ across genders, specifically in the Indian corporate context. Design/methodology/approach: A descriptive, quantitative study was conducted using structured questionnaires to gather data from 111 employees in the Indian corporate sector. The study used a non-probability judgment sampling method. Data was analyzed through SPSS for descriptive and inferential statistics, and partial least squares was used to explore mediation and model fit. Findings: The study found a significant impact of employee experience on well-being, as well as a negative correlation between both employee experience and turnover intention and well-being and turnover intention. Well-being was found to partially mediate the relationship between employee experience and turnover intention. Gender-based analysis revealed no significant differences in the relationships between these variables for men and women. Originality/value: This research highlights the universal applicability of employee experience as a predictor of well-being and turnover intention, irrespective of gender. By establishing that gender does not moderate these relationships, this study provides new insights challenging traditional assumptions about gender disparities in workplace outcomes. 2024, Emerald Publishing Limited.
International Journal of Organizational Analysis
https://doi.org/10.1108/IJOA-06-2024-4567 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208217011&doi=10.1108%2fIJOA-06-2024-4567&partnerID=40&md5=b629e4c797cdc790994211ed8b26a31a
Nair S., School of Business and Management, CHRIST University, Bangalore, India; Hawaldar A., School of Business and Management, CHRIST University, Bangalore, India; Kumar A., School of Business and Management, CHRIST University, Bangalore, India
Machine learningbased approaches for enhancing human resource management using automated employee performance prediction systems
Artificial intelligence; Decision making; Employee performance; Human resource; Machine learning; Random Forest
Purpose: This study focuses on enhancing the accuracy and efficiency of employee performance prediction to enhance decision making and improve organisational productivity. By introducing advance machine learning (ML) techniques, this study aims to create a more reliable and data-driven approach to evaluate employee performance. Design/methodology/approach: In this study, nine machine learning (ML) models were used for forecasting employee performance: Random Forest, AdaBoost, CatBoost, LGB Classifier, SVM, KNN, XGBoost, Decision Tree and one Hybrid model (SVM + XGBoost). Each ML model is trained on an HR data set covering various features such as employee demographics, job-related factors and past performance records, ensuring reliable performance predictions. Feature scaling techniques, namely, min-max scaling, Standard Scaler and PCA, have been used to enhance the effectiveness of employee performance prediction. The models are trained to classify data, predicting whether an employees performance meets expectations or needs improvement. Findings: All proposed models used in the study can correctly categorize data with an average accuracy of 94%. Notably, the Random Forest model demonstrates the highest accuracy across all three scaling techniques, achieving optimise accuracy, respectively. The results presented have significant implications for HR procedures, providing businesses with the opportunity to make data-driven decisions, improve personnel management and foster a more effective and productive workforce. Research limitations/implications: The scope of the used data set limits the study, despite our models delivering high accuracy. Further research could extend to different data sets or more diverse organisational settings to validate the models effectiveness across various contexts. Practical implications: The proposed ML models in the study provide essential tools for HR departments, enabling them to make more informed data driven decisions with regard to employee performance. This approach can enhance personnel management, improve workforce productivity and fostering a more effective organisational environment. Social implications: Although AI models have shown promising outcomes, it is crucial to recognise the constraints and difficulties involved in their use. To ensure the fair and responsible use of AI in employee performance prediction, ethical considerations, privacy problems and any biases in the data should be properly addressed. Future work will be required to improve and broaden the capabilities of AI models in predicting employee performance. Originality/value: This study introduces an exclusive combination of ML models for accurately predicting employee performance. By employing these advanced techniques, the study offers novel insight into how organisations might transition from a conventional evaluation method to a more advanced and objective, data-backed approach. 2024, Emerald Publishing Limited.
https://doi.org/10.1108/IJOA-07-2024-4643 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208648589&doi=10.1108%2fIJOA-07-2024-4643&partnerID=40&md5=2a6ff2e9a716209b7c9761a9f1e09907
Uppal A., Symbiosis Law School, Noida, Constituent of Symbiosis International (Deemed) University, Noida, India; Awasthi Y., School of Commerce, Finance and Accountancy, Christ University, Bengaluru, India; Srivastava A., Department of Management, Institute of Technology and Science, Ghaziabad, India
Antecedents and Trajectories of the Child and Adolescent Mental Health Crisis: Assimilating Empirically Guided Pathways for Stakeholders
Importance: Amid and following the COVID-19 pandemic, there has been a growing focus on understanding the underlying etiology of the mental health crisis in children and youth. However, there remains a dearth of empirically driven literature to comprehensively explore these issues. This narrative review delves into current mental health challenges among children and youth, examining perspectives from both pre-pandemic and pandemic periods. Observations: Research highlights reveal concerning statistics, such as 1 in 5 children experience mental health disorders. The pandemic exacerbated these issues, introducing stressors such as job losses and heightened anticipatory anxiety. Race relations have emerged as a significant public health concern, with biases impacting students, particularly affecting Asian, black, and multiracial individuals. Substance use trends indicate a rise in overdose deaths, particularly among adolescents, with cannabis use linked to adverse outcomes. Increased screen time and income disparities further compound mental health challenges. Conclusions and Relevance: Proposed public health mitigation strategies include improving access to evidence-based treatments, implementing legislative measures for early identification and treatment of developmental disorders, and enhancing suicide prevention efforts. School-based interventions and vocational-technical education are crucial, alongside initiatives targeting sleep hygiene, social media usage, nutrition, and physical activity. Educating health care professionals about both physical and mental health is essential to address workforce burnout and effectively manage clinical complexities. 2024 Physicians Postgraduate Press, Inc.
Gupta M.; Ladegard K.; Gupta N.; Khurana P.; Krasner A.
Primary Care Companion for CNS Disorders , Vol-26, No. 5
https://doi.org/10.4088/PCC.24nr03747 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208165532&doi=10.4088%2fPCC.24nr03747&partnerID=40&md5=7665f0c8932a9745d6e4faa5d5143eb3
Gupta M., Southwood Childrens Behavioral Healthcare, Pittsburgh, PA, United States; Ladegard K., Department of Behavioral Health Services, Denver Health Medical Center, Denver, CO, United States; Gupta N., Department of Psychiatry, Daytons Children Hospital, Dayton, OH, United States; Khurana P., Department of Psychology, Christ University, Delhi, India; Krasner A., Yale School of Medicine, New Haven, CT, United States
Beyond Binary: Exploring the Dynamics of Bi-Curiosity Propulsion and Persistence Among Young Women
Bi-curiosity; hetero-divergence; sexual identity questioning
Sexual identity fails to adhere to the dichotomous models, transcending to a more fluid quality than normative compulsory heterosexuality. The present study investigates the experience of bi-curiosity, focusing on its initiation among young women residing in urban India. Bi-curiosity, a sexual orientation questioning marked by exploratory experiences, is a possible but not a necessary precursor to bisexuality. This qualitative study explores on the psychological and social factors contributing to a bi-curious orientation. It focuses on the subjective processes of development and maintenance of sexual identity questioning. Three organizing themes emerged from the Reflective Thematic Analysis: (a.) Affective Indicators, (b.) Social Experiences, and (c.) Intimacy in friendships. While sexual identity questioning was propelled by more psychological factors, like physical attraction, fantasy, experienced jealousy toward men, and comfort with the same sex, social and environmental factors contribute significantly. Individual experiences with patriarchy, social attitudes toward same-sex relationships, and their representation on media platforms often reinforce the process. Another important contributor was womens close friendships with the same sex, which are sites for physical closeness, emotional intimacy, and personal growth, and share these characteristics with romantic relationships. These factors emerged as important reinforcers to the development and maintenance of sexual identity questioning. 2024 Taylor & Francis Group, LLC.
Abhyankar S., MSc Clinical Psychology, CHRIST (Deemed to be University), Bangalore, India; Gopal B., CHRIST (Deemed to be University), Bangalore, India
We are Treated as Outsiders in Our Own City: Lived Experiences of Intersectional Stigma Against Sex Workers in Kolkata, India
Discrimination; India; Kolkata; Sex work; Stigma
Introduction: Sex workers in India experience intersectional stigma related to their gender identity, sexuality, and profession. The objective of the present study is to analyze the lived experiences of intersectional stigma against sex workers in Kolkata. Methods: We interviewed 30 cisgender female sex workers in March 2023 in Kolkata, India. Interviews were digitally audio recorded, translated from Bengali into English, and transcribed and coded using thematic analysis. Results: We identified five main themes regarding intersectional stigma: (1) internalized stigma regarding the shame associated with being a female sex worker, (2) perceived stigma of sex work as a dirty profession, associated with lower caste status, (3) enacted stigma against sex workers who are mothers, (4) enacted stigma against the children of sex workers, and (5) reduction of stigma through unionization/labor organizing. Conclusions: Intersectional stigma against sex workersis impacted by negative attitudes regarding gender, caste status, single motherhood, and occupation. We identified internalized stigma as a source of shame for sex workers. Sex workers also were perceived to beengaged in afilthy profession, associated with lower caste status. Those sex workers who were mothers experienced discrimination, as did their children. Respondents reported how collectivization has helped to address these experiences of stigma anddiscrimination. Policy Implications: Addressing the intersectional stigma against sex workers in Kolkata necessitates a shift in social attitudes.Findings underscore the urgent need for stigma reduction interventions and socialpolicies, including (1) labor protections for sex workers, (2) individual/community-level interventions for sex workers, and (3) media campaigns to address stigma reduction. By understanding the lived experiences of sex workers, we may develop better interventions to reduce stigma in the lives of sex workers in Kolkata and throughout India. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Acharya A., Department of Economics, Christ University, Bangalore, India; Azhar S., Graduate School of Social Service, Fordham University, 113 W. 60 Street, Room 721a, New York, 10023, NY, United States
Machine Learning Based Optimal Feature Selection for Pediatric Ultrasound Kidney Images Using Binary Coati Optimization
Binary coati optimisation algorithm (BCOA); Chronic kidney disease (CKD); Feature selection (FS); Optimisation algorithm; Texture
Chronic kidney disease (CKD) one of the most dangerous illnesses. Early detection is vital for improving survival rates and underscoring the need for an intelligent classifier to differentiate between normal and abnormal kidney ultrasound images. Features extracted from an image have a significant impact on classification accuracy. In this study, we present a Binary Coati optimization algorithm (BCOA) for feature selection in CKD, which focuses on reducing the high dimensionality features extracted from ultrasound images, including GLCM, GLRLM, GLSZM, GLDM, NGTDM, and first order, by employing BCOA-S shaped and BCOA-V shaped transfer functions that convert BCOA from a continuous search space to a binary form, which helps in the selection of optimal features to improve the classification performance while reducing the feature dimensionality. The reduced feature was evaluated using six machine-learning classifiers: Random Forest, Support Vector Machine, Decision tree, K-nearest Neighbor, XG-boost, and Nae Bayes. The efficiency of the proposed framework was assessed based on accuracy, precision, recall, specificity, f1 score and AUC curve. BCOA-V outperformed in terms of accuracy, precision, recall, specificity, F1 score and AUC curve by 99%,100%,97%,100%, 98%, and 98%, respectively. This makes it a superior choice for CKD diagnosis and is a valuable tool for feature selection in medical diagnosis. (2024), (Intelligent Network and Systems Society). All rights reserved.
International Journal of Intelligent Engineering and Systems, Vol-17, No. 6, pp. 1300-1313.
https://doi.org/10.22266/ijies2024.1231.94 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208113146&doi=10.22266%2fijies2024.1231.94&partnerID=40&md5=fe7d1e209b17077c8524f1e946ee92f0
Kausar F., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Ramamurthy B., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India