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                <text>Professional quality of life of nurses with 6-8 years of work experience</text>
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                <text>Aggression; Empathy; Nurses; Professional quality of life; Self-efficacy</text>
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                <text>The current research investigation was undertaken to understand the relationship of professional quality of life of nurses with self-efficacy, empathy and aggression. Professional quality of life is the quality one feels in relation to their work as a helper (Stamm 2010). It includes the positive component of compassion satisfaction and two negative components of burnout and secondary traumatic stress. Nursing professionals with 6-8 years of work experience and employed in Punjab, India were taken for the purpose of the study. Fantasy seeking was found to be a positive predictor of compassion satisfaction explaining 4% of variance. Self-efficacy and empathic concern were found to be negative predictors while verbal aggression was found to be a positive predictor of burnout. Together the three predictors accounted for 17% of variance in burnout. Personal distress was a positive predictor of secondary traumatic stress explaining 8% of variance. Implications are discussed with in light of professional quality of life of nurses who hold a considerable amount of work experience in the nursing profession.  2021 Ecological Society of India. All rights reserved.</text>
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                <text>Kaur H.</text>
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                <text>Indian Journal of Ecology, Vol-48, pp. 113-118.</text>
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                <text>Ecological Society of India</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113722595&amp;amp;partnerID=40&amp;amp;md5=989db62e049bc4d9c46aa36fbdb13ca7" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113722595&amp;amp;partnerID=40&amp;amp;md5=989db62e049bc4d9c46aa36fbdb13ca7&lt;/a&gt;</text>
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                <text>ISSN: 3045250</text>
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                <text>Kaur H., CHRIST (Deemed to be University), Delhi NCR, 201 003, India</text>
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                <text>Creating a sustainable future: insights into brand marketing in the luxury fashion industry</text>
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                <text>attitude; Brand Management; branding; Consumer Behaviour; fashion industry; luxury; Marketing; purchase intention; Relationship Marketing; Sales; Sharma Nitika, International Management InstituteNew Delhi, India; Sustainability; Sustainability; sustainability challenges; sustainable luxury fashion</text>
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                <text>This paper aims to develop a conceptual framework that elucidates the factors that impact sustainable luxury brand marketing, specifically focusing on the luxury fashion industry. The framework aims to highlight the role played by the industry in promoting economic, social, and environmental sustainability. By examining these factors, the study seeks to contribute to a better understanding of how luxury fashion brands can effectively incorporate sustainability into their marketing strategies, thereby fostering a more sustainable and responsible approach to luxury consumption. Applying the theoretical framework derived from the literature review and systematic mapping approach, we examine its relevance in the luxury fashion market. This exploration allows us to assess its practical applicability and gather empirical evidence regarding sustainable brand marketing in this context. This research will give an in-depth analysis of the major elements influencing the consumption of sustainable luxury goods. The findings expand our understanding of the sustainable practices adopted by luxury fashion brands, providing valuable insights for academia and the industry. This studys implications are profound: luxury brand managers can enhance brand value through insights on sustainable fashion consumption drivers, while sustainable brands gain strategies for audience engagement and loyalty.  2024 The Author(s). Published by Informa UK Limited, trading as Taylor &amp;amp; Francis Group.</text>
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                <text>Kaur H.; Choudhary S.; Manoj A.; Tyagi M.</text>
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                <text>Cogent Business and Management, Vol-11, No. 1</text>
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                <text>&lt;a href="https://doi.org/10.1080/23311975.2024.2328391" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1080/23311975.2024.2328391&lt;/a&gt;
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                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 23311975</text>
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                <text>Kaur H., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Delhi, India; Choudhary S., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Delhi, India; Manoj A., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Delhi, India; Tyagi M., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Delhi, India</text>
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          <element elementId="50">
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                <text>A Qualitative Exploration of the role of intersectionality in health disparities faced by Indian transgender persons</text>
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          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="81324">
                <text>Health Disparities; Indian; Interpretative Phenomenological Analysis; Intersectionality; Transgender Persons</text>
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                <text>Transgender persons in India represent a minority and are subjected to varying levels of disparities, including those in health. These disparities for a transgender person are multi-axial and have a complex origin and manifestation that can only be assessed and explored through an intersectional lens where efforts are made to understand the collision of multiple and different identities and the role these identities play in a transgender person's life. This study aimed to explore the role of intersectionality in the health disparities as experienced by Indian transgender persons. Twelve transgender persons from rural, semi-rural, and urban residences were interviewed. The data was analysed through interpretative phenomenological inquiry. Following the same, five sub themes were emerged. 'Social and health disparities among Indian transgender persons' emerged as a group experiential theme in the analysis. The sub- themes were religion, place of residence, age, socio-economic status, and colour, which play a role in disparities of their physical as well as mental health treatment, henceforth resulting in the development of 'pervasive transphobia' in the Indian healthcare system as per the experiences lived by the participants. Following the findings of this study, we may assert that Indian transgender people perceive that they are disproportionately affected by health disparities. Henceforth, there is an urgency to unfold such disparities in health through the lens of intersectionality.  2024 Sapienza Universita Editrice. All rights reserved.</text>
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                <text>Kaur H.; Singh T.</text>
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            <description>A related resource from which the described resource is derived</description>
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                <text>Psychology Hub, Vol-41, No. 1, pp. 23-34.</text>
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                <text>Sapienza Universita Editrice</text>
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                <text>&lt;a href="https://doi.org/10.13133/2724-2943/18227" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.13133/2724-2943/18227&lt;/a&gt;
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                <text>ISSN: 2723973X</text>
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                <text>English</text>
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                <text>Kaur H., Department of Psychology, Banaras Hindu University, Varanasi, India, Christ (Deemed to be) University, Delhi NCR, India; Singh T., Department of Psychology, Banaras Hindu University, Varanasi, India</text>
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                <text>Modeling the impact of political risk components on major macroeconomic variables</text>
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                <text>Emerging markets; Frontier markets; Governance indicators; Macroeconomic variables; Panel data; Political risk</text>
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                <text>The risks of the political conditions prevailing in an economy are found to have a significant impact on its stock market. Such political risks can distort the entire economy. This study investigated the impact of political risk on major macroeconomic variables which are the indicators of growth in any economy by considering the various components of political risk as given by World Bank's worldwide governance indicators. Using a panel data approach, it modeled the major macroeconomic variables of eleven emerging and frontier Asian economies with various components of political risk. The study found that irrespective of the inter-linkages among different macroeconomic variables, they were not affected by the same political risk components. Most importantly, it revealed that GDP did not respond to any of the political risk components, whereas the exchange rate was found to be affected by all the political risk components. The study also found that FDI, inflation, and real interest rate were affected by one or more political risk components.  2019 AESS Publications. All Rights Reserved.</text>
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              <elementText elementTextId="131236">
                <text>Kaur S.; Krushali S.; Accamma C.G.; Cheriyan N.K.</text>
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                <text>Corporate Governance is a broad term in todays competitive world. It is a series of processes, policies, rules, and regulations by which companies are managed and governed. In this perspective, the study attempts to analyze the impact of corporate governance on the financial performance of Information Technology (IT) Companies in India. Specifically, the study analyzed the impact of Board size, Board Composition, and Audit Committee Independence on Return on Assets and Return on Equity, which are considered as measures of financial performance. The findings of the study revealed that there is a significant and positive impact of Corporate Governance on Financial performance of IT companies, and Audit Committee Independence shows the most significant effect on Financial performance. The finding of the study endeavors to contribute to the limited literature available in the context of corporate governance in IT companies in India.  BEIESP.</text>
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                <text>International Journal of Recent Technology and Engineering, Vol-8, No. 3, pp. 7460-7464.</text>
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                <text>ISSN: 22773878</text>
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                <text>Kaura P., Institute of Management, Christ (Deemed to be University), NCR, Dehli, India; Dharwal M., School of Business Studies, Sharda University, Greater Noida, India; Kaur H., S.S. Bhatnagar University, Institute of Chemical Engineering and Technology, Punjab University, Chandigarh, India; Kaur P., Punjabi University, Patiala, Punjab, India</text>
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                <text>Assessing global perceptions of India: Policy implications drawn from foreign tourism narratives</text>
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                <text>exploratory factor analysis; India; mixed method; outer perspective; tourist destination</text>
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                <text>This study scrutinizes Indias growing appeal as a tourist destination, accentuated by government initiatives and innovative tourism policies like the e-visa program, Incredible India Campaign 2.0 and digital advancements in the travel sector. With the diminishing impact of COVID-19, there is a noticeable surge in various forms of tourism  inbound, outbound and domestic. The primary focus is to understand the driving factors behind the choice of India as a destination for inbound tourists. This research delves into these motivations, providing a global perspective on Indias attractiveness. A mixed-method approach was employed, utilizing convenience sampling for data collection. The quantitative analysis was based on a survey, informed by a literature review, comprising 390 respondents from 10 diverse Indian destinations. Additionally, 25 qualitative interviews were conducted, aiming to enrich and triangulate the quantitative findings. Exploratory factor analysis (EFA) revealed five predominant motivations among inbound tourists: culinary interests, spiritual pursuits, budget-consciousness, cultural curiosity and natural allure. These findings were substantiated through thematic analysis. The outcomes have significant practical ramifications for destination managers and tourism policy developers in India. By understanding these key motivators, they can devise targeted strategies for enhancing the appeal of India to these specific tourist segments. This study not only aids in refining tourism promotion efforts but also contributes to the academic discourse on tourist motivation offering a fresh international perspective on Indias image as a tourist destination.  by the author, licensee University of Lodz  Lodz University Press, Lodz, Poland.</text>
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                <text>Kaurav R.P.S., FORE School of Management, New Delhi, India; Kainthola S., Institute of Hotel Management, Catering &amp;amp; Nutrition  PUSA, New Delhi, India; Baber R., Christ University, Bengaluru, India; Tiwari P., GLA University, Mathura, India</text>
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                <text>Machine Learning Based Optimal Feature Selection for Pediatric Ultrasound Kidney Images Using Binary Coati Optimization</text>
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                <text>Binary coati optimisation algorithm (BCOA); Chronic kidney disease (CKD); Feature selection (FS); Optimisation algorithm; Texture</text>
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                <text>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.</text>
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                <text>Kausar F.; Ramamurthy B.</text>
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                <text>International Journal of Intelligent Engineering and Systems, Vol-17, No. 6, pp. 1300-1313.</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208113146&amp;amp;doi=10.22266%2Fijies2024.1231.94&amp;amp;partnerID=40&amp;amp;md5=fe7d1e209b17077c8524f1e946ee92f0" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208113146&amp;amp;doi=10.22266%2fijies2024.1231.94&amp;amp;partnerID=40&amp;amp;md5=fe7d1e209b17077c8524f1e946ee92f0&lt;/a&gt;</text>
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                <text>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</text>
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                <text>Optimizing Kidney Ultrasound images through Pre-Processing Filters</text>
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                <text>edge detection; enhancement; Filters; Kidney images; Mean Standard Error (MSE); noise; Peak-Signal-Noise-Ratio (PSNR); Pre-processing; quality; Ultrasound (US)</text>
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                <text>Medical image processing and analysis have greatly advanced in the past decade, significantly contributing to the diagnosis of various diseases.However, It is crucial to address the need for effective data management in the medical field due to the significant rise in data generation and storage. It necessitates the exploration of compression methods as a means of achieving efficient data handling. Consideration should be given to image processing approaches to minimize redundancy. Ultrasound imaging has gained importance in recent years, but the presence of artifacts in ultrasound images has complicated diagnoses. An evaluation has been performed to identify appropriate Pre-processing techniques for kidney images before extracting kidney features. Observing the sensitivity and calculating the PSNR and MSE of the filtered image are used to assess the applied methods. The results indicate that the median filter is ideal for image quality enhancement, while the Sobel filter is highly effective in detecting kidney edges.  2023 IEEE.</text>
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                <text>Kausar F., CHRIST (Deemed to Be University), Department of Computer Science, Bengaluru, 560029, India; Ramamurthy B., CHRIST (Deemed to Be University), Department of Computer Science, Bengaluru, 560029, India</text>
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                <text>Transforming Pediatric Healthcare with CKD using AI: A Systematic Mapping</text>
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              <elementText elementTextId="172999">
                <text>Abnormalities; AI; Children; chronic kidney disease (CKD); Deep Learning; Machine Learning; Ultrasound (US)</text>
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                <text>Artificial intelligence has been used on a much larger scale, from self-driving cars to biometrics. The daily lifestyle of civilization has changed dramatically due to scientific growth. AI has been pushed to a wide range of applications rather than limited to certain areas and has benefited the health industry, resulting in improved outcomes. Heuristics, support vector machines, artificial neural networks, and natural language processing are some of the AI approaches employed. Kidney diseases and treatment can be challenging, especially when working with youngsters. Children with Chronic Kidney Disease (CKD) experience a wide range of symptoms classified as either transitory or nosologic. Some of its traits influence not only during childhood but also during adulthood in the long run. This study will focus on strategies utilized to identify, predict, and categorize the impacts of pediatric kidney disorders in terms of aetiology, clinical features, and medicines that might assist children in transition to adulthood smoothly.   2023 IEEE.</text>
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                <text>Kausar F.; Ramamurthy B.</text>
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                <text>Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications</text>
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                <text>ISBN: 979-835033577-4</text>
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                <text>Kausar F., CHRIST(Deemed to Be Univeristy), Dept. Computer Science, Bangalore, India; Ramamurthy B., CHRIST(Deemed to Be Univeristy), Dept. Computer Science, Bangalore, India</text>
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                <text>Recent trends in photocatalytic water splitting using titania based ternary photocatalysts-A review</text>
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                <text>Hydrogen evolution reaction; Photocatalytic water splitting; Renewable energy; S-Scheme photocatalyst; TiO&lt;sub&gt;2&lt;/sub&gt; based ternary photocatalysts; Z-Scheme</text>
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                <text>A Time-series investigation is a simple technique for dividing information from reconsideration perceptions on a solitary unit or individual at ordinary stretches over countless perceptions. Timeseries examination can be considered to be the model of longitudinal plans. The most widely used method is focused on a class of Auto-Regressive Moving Average (ARMA) models. ARMA models could examine various examination questions, including fundamental cycle analysis, intercession analysis, and long-term therapy impact analysis. The model ID process, the meanings of essential concepts, and the factual assessment of boundaries are all depicted as specialized components of ARMA models. To explain the models, Multiunit time-series plans, multivariate time-series analysis, the consideration of variables, and the study of examples of intra-individual contrasts across time are all ongoing improvements to ARMA demonstrating techniques. [1]  2022 IEEE.</text>
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                <text>HAPPINESS INDEX OF HIGHER EDUCATION STUDENTS TOWARDS ONLINE LEARNING IN INDIA</text>
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                <text>Happiness Index; Higher Education; Online learning; Students; students' perception</text>
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                <text>World Happiness Index generally indicates the level of happiness and satisfaction among the residents in a given country. Since we all know that worldwide new ecosystem of online education has evolved there are many countries which have done pretty well with respect to adopting of technology in the education others have been lacking behind and hence causing more inequality in the online education space. To understand the students' perception and satisfaction regarding the online learning this study was conducted to assess the relationships of the happiness index (HI) and related parameters which were retrieved from existing literatures and self-prepared parameters. Accordingly, the world happiness index signifies a direct relationship with the social economic development factors leading to the general well-being of individuals and societies that include the full development of healthcare, politics, and higher employment. The question arises has the online learning lived up to its potential? The Indian Education System is heterogeneous comprising of private and public universities. The study was on conducted in the National Capital Region of India, (NCR). The data was collected from various types of universities' students irrespective of the gender, caste, creed and religion. The study aims to understand the perception of the students and challenges faced by them during the online learning. It is very important to know the views of the students along with teachers to get the true ground reality of online learning in India. Since the pandemic have hit overall the world education sector was hit too. All the educational institutions were closed for about nearly 1.5 years. There was drastic shift in the paradigm from traditional learning to the online learning. To understand the students' perception data is being collected from around 268 students of the Delhi NCR region. The study is quantitative. The questionnaire was distributed to the both Government and Private Universities to understand students' satisfaction regarding online learning. The data was being analyzed in the graph form. The study says the future of online learning is possible provided students have access to devices and better connectivity.  2022 Zeitschrift fur Psychologie / Journal of Psychology.All rights reserved.</text>
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                <text>Kaushik P.; Thomas P.</text>
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                <text>Zeitschrift fur Psychologie / Journal of Psychology, Vol-230, No. 1</text>
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                <text>Hogrefe Verlag GmbH &amp;amp; Co. KG</text>
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                <text>&lt;a href="https://doi.org/10.5281/zenodo.6979524" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.5281/zenodo.6979524&lt;/a&gt;
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                <text>ISSN: 21908370</text>
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                <text>Kaushik P., CHRIST, Deemed To Be University, Karnataka, Bengaluru, India; Thomas P., CHRIST, Deemed To Be University, Karnataka, Bengaluru, India</text>
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                <text>Respiratory motion prediction of lung tumor using artificial intelligence /</text>
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                <text>Kaushik Pratim Das - 1942054</text>
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                <text>An Analysis Conducted Retrospectively on the Use: Artificial Intelligence in the Detection of Uterine Fibroid</text>
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                <text>DCNN; Deep Learning; Fibroids; Magnetic resonance imaging; Ultrasonography</text>
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                <text>The most frequent benign pelvic tumors in women of age of conception are uterine fibroids, sometimes referred to as leiomyomas. Ultrasonography is presently the first imaging modality utilized as clinical identification of uterine fibroids since it has a high degree of specificity and sensitivity and is less expensive and more widely accessible than CT and MRI examination. However, certain issues with ultrasound based uterine fibroid diagnosis persist. The main problem is the misunderstanding of pelvic and adnexal masses, as well as subplasmic and large fibroids. The specificity of fibroid detection is impacted by the existing absence of standardized image capture views and the variations in performance amongst various ultrasound machines. Furthermore, the proficiency and expertise of ultra sonographers determines the accuracy of the ultrasound diagnosis of uterine fibroids. In this work, we created a Deep convolutional neural networks (DCNN) model that automatically identifies fibroids in the uterus in ultrasound pictures, distinguishes between their presence and absence, and has been internally as well as externally validated in order to increase the reliability of the ultrasound examinations for uterine fibroids. Additionally, we investigated whether Deep convolutional neural networks model may help junior ultrasound practitioners perform better diagnostically by comparing it to eight ultrasound practitioners at different levels of experience.  2024 IEEE.</text>
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                <text>Kaushik R.; Sharma K.P.; Malik S.; Shanbhog M.</text>
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                <text>2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2024</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <elementText elementTextId="167608">
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                <text>&lt;a href="https://doi.org/10.1109/ICRITO61523.2024.10522120" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICRITO61523.2024.10522120&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193846764&amp;amp;doi=10.1109%2FICRITO61523.2024.10522120&amp;amp;partnerID=40&amp;amp;md5=67fe94a68db99724c0847cd071bae735" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193846764&amp;amp;doi=10.1109%2fICRITO61523.2024.10522120&amp;amp;partnerID=40&amp;amp;md5=67fe94a68db99724c0847cd071bae735&lt;/a&gt;</text>
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                <text>ISBN: 979-835035035-7</text>
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                <text>Kaushik R., Christ(Deemed to Be Univeristy), Delhi Ncr Campus, Department of Computer Science, Ghaziabad, India; Sharma K.P., Gla University, Department of Computer Engineering and Application, Mathura, India; Malik S., Christ(Deemed to Be Univeristy), Delhi Ncr Campus, Department of Computer Science, Ghaziabad, India; Shanbhog M., Christ(Deemed to Be Univeristy), Delhi Ncr Campus, Department of Computer Science, Ghaziabad, India</text>
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                <text>Multi-class SVM based network intrusion detection with attribute selection using infinite feature selection technique</text>
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            <description>The topic of the resource</description>
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                <text>15A06; 15A09; 17B10; 17B15; 18A10; 18C05; 18C10; 18D35; Anomaly detection; Infinity feature selection; Intrusion detection system; Machine learning; Multiclass support vector machine; Support vector machine</text>
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                <text>An intrusion detection mechanism is a software program or a device that monitors the network and provides information about any suspicious activity. This paper proposes a multi-class support vector machine (SVM) based network intrusion detection using an infinite feature selection technique for identifying suspicious activity. Single and multiple classifiers generally have high complexity. To overcome all the limitations of single and multiple classifiers, we used a multi-class classifier using an infinite feature selection technique, which performed well with multiple classes and gave better results than other classifiers in terms of accuracy, precision, recall, and f_score. Infinite feature selection is a graph-based filtering approach that analyses subsets of features as routes in a graph. We used a standard dataset, namely the UNSW_NB15 data set generated by the IXIA perfect-storm tool in the Australian Centre for Cyber Security. This dataset has a total of nine types of attacks and 49 features. The comparative analysis of the manuscript work is done against eight different techniques, namely, hybrid intrusion detection system (HIDS), C5, one-class support vector machine, and others. The proposed work gave better simulation results using the 2015a Matlab simulator.  2021 Taru Publications.</text>
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              <elementText elementTextId="119788">
                <text>Kaushik R.; Singh V.; Kumari R.</text>
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                <text>Journal of Discrete Mathematical Sciences and Cryptography, Vol-24, No. 8, pp. 2137-2153.</text>
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              <elementText elementTextId="119790">
                <text>Taylor and Francis Ltd.</text>
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                <text>&lt;a href="https://doi.org/10.1080/09720529.2021.2009189" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1080/09720529.2021.2009189&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121849325&amp;amp;doi=10.1080%2F09720529.2021.2009189&amp;amp;partnerID=40&amp;amp;md5=afc29c113f3a505b7496bd8acbb49e57" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121849325&amp;amp;doi=10.1080%2f09720529.2021.2009189&amp;amp;partnerID=40&amp;amp;md5=afc29c113f3a505b7496bd8acbb49e57&lt;/a&gt;</text>
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                <text>Kaushik R., Amity Institute of Information Technology, Amity University Rajasthan, Rajasthan, Jaipur, 303002, India; Singh V., Department of Computer Science Engineering, Manipal University Jaipur, Rajasthan, Jaipur, 302002, India; Kumari R., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India</text>
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                <text>As a result of technological advancements, society is becoming increasingly computerized. Massive open online courses and other forms of remote instruction continue to grow in popularity and reach. COVID-19's global impact has boosted the demand for similar courses by a factor of ten. The ability to successfully assign distant online examinations is a crucial limiting factor in this next stage of education's adaptability. Human proctoring is now the most frequent method of evaluation, which involves either forcing test takers to visit an examination centre or watching them visually and audibly throughout tests via a webcam. However, such approaches are time-consuming and expensive. In this paper, we provide a multimedia solution for semi-automated proctoring that does not require any extra gear other than the student's computer's webcam and microphone. The system continuously monitors and analyses the user based on gaze detection, lip movement, the number of individuals in the room, and mobile phone detection, and captures audio in real time through the microphone and transforms it to text for assessment using speech recognition. Access the words gathered by speech recognition and match them for keywords with the questions being asked for higher accuracy using Natural Language Processing. If any inconsistencies are discovered, they are reported to the proctor, who can investigate and take appropriate action. Extensive experimental findings illustrate the correctness, resilience, and efficiency of our online exam proctoring system, as well as how it allows a single proctor to simultaneously monitor several test takers.   2023 Author(s).</text>
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                <text>Kaushik R., Department of Computer Science, CHRIST (Deemed to Be University), Karnataka, Bangalore, India; Singh V., Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, India, Norwegian University of Science and Technology, esund, Norway; Kumari R., ICFAI Business School (IBS), Bangalore, Off-Campus Center, ICFAI Foundation for Higher Education (IFHE) University, Karnataka, Bangalore, India</text>
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                <text>Location privacy &amp;amp; data security in VANET are now becoming most important in todays paradigm of information age. Unauthorized access to location information of vehicles may pose a significant security threat, thus it is necessary to secure this information from intruders. In proposed work, Artificial intelligence based RF range approximation is used with multi key controlled cryptography for enhancement of location privacy and data security in service location protocol of VANETS.  2022 Taru Publications.</text>
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                <text>Journal of Discrete Mathematical Sciences and Cryptography, Vol-25, No. 7, pp. 2195-2203.</text>
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                <text>Kaushik S., Amity Institute of Information Technology (AIIT), Amity University Rajasthan, Rajasthan, Jaipur, India; Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Khatri S.K., Amity University Uttar Pradesh, Uttar Pradesh, Noida, India</text>
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