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                <text>Portable and Automated Healthcare Platform Integrated with IoT Technology</text>
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                <text>Artificial intelligence; Data analysis; IoT; Machine learning; Real time systems; Wearable sensors</text>
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                <text>The diverse applications of Internet of Things (IoT), Artificial Intelligence (AI) in Bioelectronics - face recognition, pulse wave monitoring and insulin level measurements have been discussed in this chapter. This chapter also emphasizes on the IoT and its applications in biological sensors. The chapter focuses on IoT systems, such as neural networks and other channels that are integrated into a secure healthcare monitoring system in order to make the system operate as a smart model in healthcare sector that determines the priority based on health parameters gathered from the sensor nodes. In this work, the different approaches of IoT with distinct methodologies are also deliberated.  2024 Scrivener Publishing LLC.</text>
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                <text>Preetham Noel P.; Kishorekumar R.</text>
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                <text>Internet of Things in Bioelectronics: Emerging Technologies and Applications, pp. 251-261.</text>
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                <text>&lt;a href="https://doi.org/10.1002/9781394241903.ch12" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1002/9781394241903.ch12&lt;/a&gt;
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                <text>Preetham Noel P., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Bengaluru, India; Kishorekumar R., Department of Electronics and Communication Engineering, School of Engineering and Technology, Christ University, Bengaluru, India</text>
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                <text>Statistical Data Analysis of Anticorrosion and Antifouling: Unveiling Insights from Performance and Trends</text>
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                <text>CA (contact angle); CAH (contact angle hysteresis); MIC (microbiologically influenced corrosion); Polymers; SLIPS (slippery lubricant-infused porous surfaces); WCA (water contact angle)</text>
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                <text>This chapter provides intended insights about the current antifouling and anticorrosion conventional coatings, each with a distinct quality, that fall short of fully satisfying the contemporary requirements of material preservation in a marine environment. To solve these issues and accomplish the required goals, a number of novel terminologies and procedures have been investigated and several recently published research works were referred to and briefly examined in order to provide appropriate conclusions. In order to explore new methodologies that provide total protection for materials from biofouling and corrosion in maritime environments, this study looks into the complex realm of antifouling and anticorrosion methods.  2024 Scrivener Publishing LLC.</text>
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                <text>Preetham Noel P.; Kumar K.P.; Mani Joseph P.; Pillai V.J.</text>
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                <text>Novel Anti-Corrosion and Anti-Fouling Coatings and Thin Films, pp. 459-473.</text>
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                <text>&lt;a href="https://doi.org/10.1002/9781394234318.ch16" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1002/9781394234318.ch16&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207991010&amp;amp;doi=10.1002%2F9781394234318.ch16&amp;amp;partnerID=40&amp;amp;md5=c92d389c3c35d912a0151ffab9edb01b" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207991010&amp;amp;doi=10.1002%2f9781394234318.ch16&amp;amp;partnerID=40&amp;amp;md5=c92d389c3c35d912a0151ffab9edb01b&lt;/a&gt;</text>
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                <text>ISBN: 978-139423431-8; 978-139423428-8</text>
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                <text>Preetham Noel P., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Kumar K.P., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Mani Joseph P., Department of Mathematics and Computer Science, Modern College of Business and Science, PC, Muscat, Oman; Pillai V.J., Department of Electronics and Communication Engineering, CHRIST (Deemed to be University), Karnataka, Bangalore, India</text>
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                <text>Photometric identification of objects from galaxy evolution explorer survey and sloan digital sky survey</text>
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          <element elementId="49">
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              <elementText elementTextId="139634">
                <text>Dust; Extinction; galaxies:Photometry; galaxy; General; hertzsprungrussell and colour; magnitude diagrams; stars:General; techniques:Photometric</text>
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                <text>We have used Galaxy Evolution Explorer (GALEX) and Sloan Digital Sky Survey (SDSS) observations to extract seven band photometric magnitudes for over 80 000 objects in the vicinity of the North Galactic Pole. Although these had been identified as stars by the SDSS pipeline, we found through fitting with model spectral energy distributions that most were, in fact, of extragalactic origin. Only about 9 per cent of these objects turned out to be mainsequence stars and about 11 per cent were white dwarfs and red giants collectively, while galaxies and quasars contributed to the remaining 80 per cent of the data. We have classified these objects into different spectral types (for the stars) and into different galactic types (for the galaxies). As part of our fitting procedure, we derive the distance and extinction to each object and the photometric redshift towards galaxies and quasars. This method easily allows for the addition of any number of observations to cover a more diverse range of wavelengths, as well as the addition of any number of model templates. The primary objective of this work is to eventually derive a three-dimensional extinction map of the Milky Way Galaxy.  2013 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.</text>
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                <text>Preethi K.; Gudennavar S.B.; Bubbly S.G.; Murthy J.; Brosch N.</text>
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                <text>Monthly Notices of the Royal Astronomical Society, Vol-437, No. 1, pp. 771-776.</text>
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                <text>Oxford University Press</text>
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                <text>&lt;a href="https://doi.org/10.1093/mnras/stt1935" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1093/mnras/stt1935&lt;/a&gt;
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                <text>All Open Access; Bronze Open Access; Green Open Access</text>
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                <text>ISSN: 358711; CODEN: MNRAA</text>
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                <text>Preethi K., Department of Physics, Christ University, Bangalore 560 029, India; Gudennavar S.B., Department of Physics, Christ University, Bangalore 560 029, India; Bubbly S.G., Department of Physics, Christ University, Bangalore 560 029, India; Murthy J., Indian Institute of Astrophysics, Bangalore 560 034, II Block, Koramangala, India; Brosch N., The Wise Observatory and the School of Physics and Astronomy, The Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel</text>
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                <text>Analysis of Fine Needle Aspiration Images by Using Hybrid Feature Selection and Various Machine Learning Classifiers</text>
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                <text>Breast cancer; Classification; Feature selection; Fine needle aspiration cytology; Machine learning</text>
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                <text>Women die of breast cancer most often worldwide. Breast tissue samples can be examined by radiologists, surgeons, and pathologists for evidence of this cancer. Fine needle aspiration cytology (FNAC) can be used to detect this cancer through a visual microscopic examination of breast tissue samples. This sample must be examined by a cytopathologist in order to determine the patient's risk of breast cancer. To determine if a tumor is malignant, the nuclei of the cells must be characterized by their chromatin texture patterns. A machine learning method is used in order to categorize FNA images into two classes, respectively Malignant and Benign. For detecting abnormalities, numerous feature collection methods and machine learning means are applied here. Using features extracted from the FNA image set, UCI machine learning datasets are used to validate the proposed approach. This paper compares three classification methodologies, namely random forests, Naive Bayes, and artificial neural networks, by examining their accuracy, specificity, precision, and sensitivity, respectively. With the ANN and PCA along with the Chi-square selection method, 99.1% of the classifiers are correctly classified.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Introduction: Deep learning methodologies can achieve forefront results on testing deep vision issues, for instance, picture portrayal, an object area, face affirmation, Natural Language Processing, Visual Data Processing and online life examination. ConvNet, Stochastic Hopfield network with hidden units, generative graphical model and sort of artificial neural network castoff to absorb competent information coding in an unproven way are deep learning plans used in deep vision issues. Objection: This paper gives a succinct survey of without a doubt the most critical Deep learning structures. Deep vision assignments, for instance, object revelation, face affirmation, Natural Language Processing, Visual Data Processing, web-based life examination and their utilization of this task are discussed with a short record of the historic structure, central focuses and impairments. Future headings in arranging Deep learning structures for Deep vision issues and the troubles included are analysed. Method: This paper consists of surveys. In Section two, Deep Learning Approaches and Changes are audited. In section three, we tend to portray the uses of Applications of deep learning in deep vision. In Section four, Deep learning challenges and directions are mentioned. At long last, Section five completes the paper with an outline of the results. Results and Conclusion: Though deep learning can recall a huge proportion of data and info, its feeble cognitive and perception of the data makes it a disclosure answer for certain applications. Deep learning despite everything encounters issues in showing various erratic facts modalities at the equal period. Multimodal profound learning is an extra notable heading in progressing deep learning research.  IJCRR.</text>
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                <text>Preethi N.; Singh W.J.</text>
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                <text>International Journal of Current Research and Review, Vol-13, No. 6, pp. 85-92.</text>
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                <text>ISSN: 22312196</text>
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                <text>Preethi N., Department of Data Science, CHRIST (Deemed to be University), Pune, Lavasa, India; Singh W.J., Department of Computer Applications, Kumaraguru College of Technology, Coimbatore, Tamilnadu, India</text>
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                <text>Discussion on ostracised transgender individuals and entrepreneurship through review of literature</text>
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                <text>Transgender individuals are the most deteriorated individuals in society. They face a wide range of trodden lives and setbacks in their everyday life. They encounter challenges and difficulties from the time they violate the social norms, they are also humiliated from their biological families and are sent to live a life of their own. In India, the Mughal period was termed to be the golden years for transgender individuals. It was after colonisation and implementation of the Criminal Tribes Act 1871 transgender individuals were treated brutally and eventually begging and sex work became their only source of income. Alongside, entrepreneurship proved to be a success factor as it brought the shunned women into the mainstream society. Thereby, entrepreneurship increases social capital and thus encourages transgenders in job creation activities. Despite a dire situation, there are transgender individuals who have faced all odds and have proved to set benchmarks in the society in varied fields. There are sporadic transgender individual entrepreneurs in the country who have paved their way into the entrepreneurial world, which is an important area to be explored. The study focuses on literature relating to transgender individuals, challenges faced by transgender individuals, entrepreneurial motivations and also transgender entrepreneurs.  2020 SERSC.</text>
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                <text>Preethi Sarah J.P.; Karthigai Prakasam C.</text>
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                <text>International Journal of Advanced Science and Technology, Vol-29, No. 5, pp. 4985-4997.</text>
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                <text>Preethi Sarah J.P., Department of Commerce, CHRIST (Deemed to be University), Bangalore, India; Karthigai Prakasam C., Department of Commerce, CHRIST (Deemed to be University), Bangalore, India</text>
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                <text>Sartrean Insights on Understanding the Repercussions of Rape Trauma in the Gripping Narratives of Roxanne Gay and Neesha Arter</text>
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                <text>Women have been subjugated to violence from time immemorial. One of the most horrific forms of violence is sexual violence and rape. Their voice was not heard until the rise of second wave feminism which began around 1970. Women started to write about their experiences in the form of memoirs to bring to light the atrocities of rape and the implications of trauma and its impact. Sexual assault inflicts profound psychological and emotional wounds that give rise to a condition referred to as Rape Trauma. Rape Trauma Syndrome includes of a wide range of physical and psychological signs such as insomnia, nightmare, flashbacks, anxiety, and depression and so on and they last for a long period of time in one?s life. The research uses two memoirs written by American women, Roxanne Gay?s Hunger: A Memoir of my Body (2017) and Neesha Arter?s Controlled: The worst Night of my Life and its Aftermath (2015). The research uses Sartre?s perspective on embodiment, freedom, self to analyse rape trauma. The research uses Jean Paul Sartre?s concept to analyse the immense effects of rape trauma on the lives of the two women as documented in their memoirs. Using the framework provided by Constance L. Mui, the research delineates how rape trauma destroys the fundamental project of the protagonists and how rape trauma annihilates an individual from her own body and isolates her from the world.  2024 Sciedu Press. All rights reserved.</text>
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                <text>The prominence revolution took place in the 1980s, and then the Green HRM practises movement blew over the sustainable development literature in the 1990s. This represents an excellent practice because it newlineincorporates sustainable development principles into the operational processes newlineof the human resources department. According to Mishra (2017), Green HRM is a tactical instrument for arranging human resource competences and promoting ideas that motivate businesses to embrace sustainable strategies. newlineThe term human resource management (HRM) is used to describe a set of practices, procedures, and methods that are focused on managing and optimizing the performance of personnel within a business, thereby providing the organization with a competitive advantage. Despite the fact that green human resource management has grown to be a major source of concern, India has only relatively handful of first-hand studies done in this area. While conventional HRM concentrates on functions to provide an organisation a competitive edge, green HRM places an emphasis on the capture and retention of green efforts to meet corporate objectives. newlineGreen HRM in India is plagued by a variety of issues. The study has chosen a few traits from the research at hand that may be utilised to create Green HRM practices for sustainable development. It stands to reason for contemporary businesses to take environmental responsibility seriously (Jackson, Renwick, Jabbour and Camen, 2011). Numerous studies show that environmental newlineinitiatives increase production and provide companies a competitive edge (Bombiak and Marciniuk-Kluska, 2018). Although organizational solutions quotmoved beyond pollution control and the mitigation of environmental degradationquot, Saeed, Jun, Nubuor, Priyankara and Jayasuriya (2018) have highlighted its significance in the New Millennium Era.</text>
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                <text>atmospheric circulation model; Caputo fractional derivative; CaputoFabrizio fractional derivative; sliding mode controller</text>
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                <text>The earths surface is heated by the large-scale movement of air known as atmospheric circulation, which works in conjunction with ocean circulation. More than (Formula presented.) variables are involved in the complexity of the weather system. In this work, we analyze the dynamical behavior and chaos control of an atmospheric circulation model known as the Hadley circulation model, in the frame of Caputo and CaputoFabrizio fractional derivatives. The fundamental novelty of this paper is the application of the Caputo derivative with equal dimensionality to models that includes memory. A sliding mode controller (SMC) is developed to control chaos in this fractional-order atmospheric circulation system with uncertain dynamics. The proposed controller is applied to both commensurate and non-commensurate fractional-order systems. To demonstrate the intricacy of the models, we plot some graphs of various fractional orders with appropriate parameter values. We have observed the influence of thermal forcing on the dynamics of the system. The outcome of the analytical exercises is validated using numerical simulations.  2022 by the authors.</text>
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                <text>Premakumari R.N.; Baishya C.; Veeresha P.; Akinyemi L.</text>
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                <text>Premakumari R.N., Department of Studies and Research in Mathematics, Tumkur University, Tumkur, 572103, India; Baishya C., Department of Studies and Research in Mathematics, Tumkur University, Tumkur, 572103, India; Veeresha P., Center for Mathematical Needs, Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Akinyemi L., Department of Mathematics, Lafayette College, Easton, 18042, PA, United States</text>
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                <text>Thematic Mutual Funds: Performance and Benchmark Analysis Leveraging AI in Futuristic New-Age Investment Themes</text>
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                <text>Premalatha K.P., CMS Business School, JAIN (Deemed-To-Be University), Faculty of Management Studies, Bangalore, 560009, India; Patil S.R., CMS Business School, JAIN (Deemed-To-Be University), Faculty of Management Studies, Bangalore, 560009, India; Renuka S., JAIN (Deemed-To-Be University), Faculty of Management Studies, Bangalore, 560009, India; Yadav R.A., MBA CHRIST (Deemed-To-Be University), School of Business and Management, Bangalore, India</text>
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                <text>Young investors love thematic mutual funds. By 2022, AUM will reach 1.73 lakh crore. These funds have a great possibility of long-term growth since they are timing the market and investing wisely. This research uses AI-driven analytics to examine a select thematic mutual fund that has done well despite risk, diversity, and market volatility concerns. Five actively managed themes were chosen from various fund firms. Infrastructure, ESG, Technology, Banking and Financial Services, and Pharma &amp;amp; Healthcare. We evaluated the best strategies in each topic using qualitative and AI-enhanced quantitative success metrics, including Alpha, Beta, Standard Deviation, Rolling Return, and Sharpe Ratio. We compared themes to key metrics to evaluate their performance over five years (2018-2022). Themed mutual funds perform well for future savings. In particular, AI-driven asset selection algorithms that were market-appropriate outperformed other purchasers. The findings demonstrate the importance of economic cycle-based themes and clever distribution strategies to maximize profits. This research illuminates investment choices and illustrates how AI-enabled active investing might improve market forecasts, volatility, and returns in themed mutual funds.   2025 IEEE.</text>
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                <text>This study analyzes three distinct convolutional neural network (CNN) models, ResNet, Parallel CNN, and VGG16, for object classification using the Star-Galaxy Classification dataset. The dataset comprises a vast collection of celestial object images, including galaxies, stars, and quasars. The effectiveness of each CNN model is evaluated based on accuracy, a commonly used performance metric. The results reveal that the Parallel CNN model achieved the highest accuracy of 90.08% in classifying celestial objects, followed by VGG16 with an accuracy of 86%, and ResNet with an accuracy of 83%. Specifically, the Parallel CNN model demonstrates superior performance in classifying galaxies and stars. These findings provide valuable insights into the strengths and weaknesses of each model for this specific classification task, guiding the development of more effective CNN models for similar applications in cosmology and other fields. This research contributes to the growing literature on CNN models' application in astronomy and underscores the importance of selecting appropriate models to achieve high accuracy in object classification tasks. The study's insights can be utilized to inform the development of more effective CNN models for similar tasks and facilitate advancements in astronomical research.  2023 IEEE.</text>
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                <text>Premanand N., Christ University, Department of Computer Science, Bengaluru, India; Tarun V.G., Christ University, Department of Computer Science, Bengaluru, India; Pawar S., Christ University, Department of Computer Science, Bengaluru, India; Jawakar D.N., Christ University, Department of Computer Science, Bengaluru, India; Utsav, Christ University, Department of Computer Science, Bengaluru, India; Deepa S., Christ University, Department of Computer Science, Bengaluru, India; Jayapriya J., Christ University, Department of Computer Science, Bengaluru, India; Vinay M., Christ University, Department of Computer Science, Bengaluru, India</text>
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                <text>AI technology disruption; digital marketing industry; job insecurity; job mobility; turnover intention</text>
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                <text>The rapid integration of AI technology into the digital marketing sector has prompted a need to understand its effects on employee perspectives and behaviors. This study investigates how AI adoption influences job insecurity, turnover intention, and job mobility among digital marketing professionals. Addressing concerns about AI rendering roles obsolete is crucial for fostering a supportive work environment. Turnover intention, influenced by AI adoption and potential job dissatisfaction, offers insights into employees' commitment to the industry. Job mobility, influenced by growth prospects and alignment with AI-driven workplaces, sheds light on career aspirations. Our study involving 303 employees of digital marketing industry in India reveals that AI disruption significantly impacts turnover intention, with job insecurity mediating this effect. Additionally, mistreatment by superiors increases turnover intention. Overall, this research underscores the profound impact of AI technology on employees' attitudes, behaviors, and career decisions in digital marketing, providing valuable insights into their perceptions and engagement   2024 IEEE.</text>
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                <text>ISBN: 979-835038427-7</text>
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                <text>Premnath H., Christ (Deemed to Be University), Pune, India; Lohani R., Christ (Deemed to Be University), Pune, India</text>
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              <elementText elementTextId="126968">
                <text>Connected k-forcing sets of graphs and splitting graphs</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="126969">
                <text>Connected k-forcing number; K-forcing number; Zeroforcing number</text>
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            <description>An account of the resource</description>
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                <text>The notion of k-forcing number of a graph was introduced by Amos et al. For a given graph G and a given subset I of the vertices of the graph G, the vertices in I are known as initially colored black vertices and the vertices in V (G) ? I are known as not initially colored black vertices or white vertices. The set I is a k-forcing set of a graph G if all vertices in G eventually colored black after applying the following color changing rule: If a black colored vertex is adjacent to at most k-white vertices, then the white vertices change to be colored black. The cardinality of a smallest k-forcing set is known as the k-forcing number Zk (G) of the graph G. If the sub graph induced by the vertices in I are connected, then I is called the connected k-forcing set. The minimum cardinality of such a set is called the connected k-forcing number of G and is denoted by Zck (G). This manuscript is intended to study the connected k-forcing number of graphs and the splitting graphs.  2020 the author(s).</text>
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                <text>Premodkmuar K.P.; Dominic C.; Chacko B.</text>
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              <elementText elementTextId="126972">
                <text>Journal of Mathematical and Computational Science, Vol-10, No. 3, pp. 656-680.</text>
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                <text>2020-01-01</text>
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                <text>&lt;a href="https://doi.org/10.28919/jmcs/4446" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.28919/jmcs/4446&lt;/a&gt;
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                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 19275307</text>
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                <text>Premodkmuar K.P., Research Center of Mathematics, St. Josephs College, Devagiri, Calicut, Kerala, India; Dominic C., Department of Mathematics, CHRIST (Deemed to be University), Karnataka, India; Chacko B., Research Center of Mathematics, St. Josephs College, Devagiri, Calicut, Kerala, India</text>
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                <text>Graphs with large diameter and their two distance forcing number</text>
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            <name>Subject</name>
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              <elementText elementTextId="121244">
                <text>2-distance forcing number; 2-distance forcing set; diameter</text>
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                <text>For a given simple graph G = (V,E), the two distance forcing number Z2d (G) is defined as the minimum cardinality among all Z2d-sets in G. This paper examine about Z2d (G) of some graphs with large diameter. Also we determine the 2-distance forcing number of some complement graphs.  2021 the author(s).</text>
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                <text>Premodkumar K.P.; Dominic C.; Chacko B.</text>
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                <text>Journal of Mathematical and Computational Science, Vol-11, No. 2, pp. 1810-1837.</text>
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                <text>Premodkumar K.P., Department and Research Center of Mathematics, St. Josephs College, Devagiri, Calicut, Kerala, India; Dominic C., Department of Mathematics, CHRIST (Deemed to be University), Karnataka, India; Chacko B., Department and Research Center of Mathematics, St. Josephs College, Devagiri, Calicut, Kerala, India</text>
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                <text>Motivated from the graph parameters namely zero forcing number, k-forcing number and the connected k-forcing number, in this article, we introduce a new parameter known as the 2-distance forcing number. Assume that each vertex of a graph G = (V (G), E(G)) is colored as either white or black. Consider the set Z2d of black colored vertices of the graph G. The color change rule changes the color of a white vertex v to black if the white vertex v is the only 2-distance white neighbor of a black vertex u. The set Z2d is called a two distance forcing set of G if all vertices of the graph G will be turned black after limited applications of the color change rule. The 2-distance forcing number of G, denoted by Z2d (G), is the minimum of | Z2d | over all 2-distance forcing sets Z2d ? V (G). This manuscript is intended to study the 2-distance forcing number of some graphs. We find the exact value of the 2-distance forcing number of graphs such as the pineapple graph, gear graph, jelly fish graph, helm graph, sunflower graph, comet graph and the n-pan graph.  2020 the author(s).</text>
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                <text>Journal of Mathematical and Computational Science, Vol-10, No. 6, pp. 2233-2248.</text>
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                <text>Presannakumar K., Department of Computer Science, School of Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Mohamed A., School of Computer Sciences, Mahatma Gandhi University, Kerala, Kottayam, 686560, India</text>
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                <text>Environmental Sound Classification (ESC) remains challenging due to the diverse and overlapping acoustic characteristics of real-world environments. Traditional models relying on single-feature representations such as Mel spectrograms often fail to capture the full range of spectral and temporal details. This paper introduces a novel algorithm Weighted Attention-based Spectrogram Fusion (WASF) that adaptively integrates Mel spectrograms, Cochleograms, and Correlograms using a hierarchical attention mechanism across channel, temporal, and frequency dimensions. Compared to traditional fusion techniques, WASF uses a learnable attention mechanism to dynamically weight each feature's importance over time and frequency, improving the model's capacity to focus on important acoustic cues. In addition, an overlapping pre-patching strategy is proposed to preserve local temporal continuity, enhancing transformer-based modeling. Proposed model demonstrates superior performance with 95.71 % accuracy on UrbanSound8K, 93.97 % on ESC-50, and 94.91 % on ESC-10 datasets. Extensive ablation studies and interpretability analysis validate the effectiveness of each component, demonstrating robustness across diverse acoustic environments and noise conditions. The computational efficiency and interpretable attention patterns make our approach suitable for real-time deployment in smart city applications, surveillance systems, and assistive technologies.  2025 Elsevier B.V.</text>
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