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                <text>Exploring Socio-Political Factors and Quality of Life Among LGBT Individuals in India</text>
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                <text>The quality of life of queer individuals in India is a result of a complex sociopolitical climate which is what this study aims to explore through qualitative methodology. Previous research has explored the social factors that impact the wellbeing of LGBT individuals in western countries, while the impact of politics on the wellbeing of marginalized groups is still largely unexplored. Through thematic analysis, this study found that family support and peer networks are the two most important social structures that determine the quality of life of LGBT emerging adults in India, whereas the impact of politics on wellbeing depends on the level of political awareness of the participants and their socio-political privilege in terms of caste, class and gender. However, there were significant differences in the relevant factors that affect the quality of life for cisgender and transgender participants which leaves room for further research. The findings indicate intra-community conflicts and changing dynamics within the community, and there needs to be extensive research on understanding the intersectionality of different identities within the community and their impact on the lives of queer individuals.  2024 Taylor &amp;amp; Francis Group, LLC.</text>
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                <text>Bhattacharyya A., Department of Psychology, CHRIST (Deemed to be University) Delhi-NCR Campus, Ghaziabad, India; Rakesh K.R., Department of Psychology, CHRIST (Deemed to be University) Delhi-NCR Campus, Ghaziabad, India</text>
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                <text>humidity; Internet of Things; Precision farming; predictive analytics; remote sensing; Sensory computing</text>
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                <text>Internet of Things (IoT) technology will have an impact on every area in the future as it will make everything intelligent, which will affect everyone's daily lives. It is a network composed of many devices that can configure themselves. The use of IoT in smart farming is transforming traditional agricultural practices by reducing crop loss, improving them, and making them more cost-effective for farmers. The study's goal is to propose a technological model for soil health monitoring that uses smart sensors and intelligent methods to communicate with farmers through a variety of channels. Farmers will benefit from the real-time farm data (temperature, humidity, soil moisture, UV index, and IR) that allows them to practice smart farming while increasing crop yields and conserving resources.   2023 IEEE.</text>
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                <text>3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023 - Proceedings, pp. 563-570.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Bhattacharyya A., Deemed to Be University, Kalinga Institute of Industrial Technology, India; Saini T., Deemed to Be University, Kalinga Institute of Industrial Technology, India; Sharma V., CHRIST (Deemed to Be University), Department of Computational Sciences, Delhi NCR, India; Mishra S., Deemed to Be University, Kalinga Institute of Industrial Technology, India</text>
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                <text>Intelligent Multi-modal Data Processing, pp. xix-xx.</text>
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                <text>Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics, pp. xxv-xxvi.</text>
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                <text>Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications, pp. xv-xix.</text>
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                <text>Bhattacharyya S., Rajnagar Mahavidyalaya, Birbhum, India; Dutta P., Visva Bharati University, Santiniketan, India; Samanta D., CHRIST University, Bangalore, India; Mukherjee A., RCC Institute of Information Technology, Kolkata, India; Pan I., RCC Institute of Information Technology, Kolkata, India</text>
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                <text>Fractional Order Ant Colony Optimization; Hyperspectral Image Segmentation; Kruskal-Wallis test; Peak signal-to-noise ratio; Qutrits</text>
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                <text>Hyperspectral images contain a wide variety of information, varying from relatively large regions to smaller manmade buildings, roads and others. Automatic clustering of various regions in such images is a tedious task. A multilevel quantum inspired fractional order ant colony optimization algorithm is proposed in this paper for automatic clustering of hyperspectral images. Application of fractional order pheromone updation technique in the proposed algorithm produces more accurate results. Moreover, the quantum inspired version of the algorithm produces results faster than its classical counterpart. A new band fusion technique, applying principal component analysis and adaptive subspace decomposition, is successfully proposed for the pre-processing of hyperspectral images. Score Function is used as the fitness function and K-Harmonic Means is used to determine the clusters. The proposed algorithm is implemented on the Xuzhou HYSPEX dataset and compared with classical Ant Colony Optimization and fractional order Ant Colony Optimization algorithms. Furthermore, the performance of each method is validated by peak signal-to-noise ratio which clearly indicates better segmentation in the proposed algorithm. The Kruskal-Wallis test is also conducted along with box plot, which establishes that the proposed algorithm performs better when compared with other algorithms.  2020 IEEE.</text>
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                <text>Bhattacharyya S.; Dutta T.; Dey S.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>&lt;a href="https://doi.org/10.1109/CEC48606.2020.9185589" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/CEC48606.2020.9185589&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092034048&amp;amp;doi=10.1109%2FCEC48606.2020.9185589&amp;amp;partnerID=40&amp;amp;md5=15fba68e45c0d425a17d568d730eac07" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092034048&amp;amp;doi=10.1109%2fCEC48606.2020.9185589&amp;amp;partnerID=40&amp;amp;md5=15fba68e45c0d425a17d568d730eac07&lt;/a&gt;</text>
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                <text>Bhattacharyya S., Christ (Deemed to Be University), Department of Computer Science Engineering, Bangalore, Karnataka, India; Dutta T., University Institute of Technology, Burdwan University, Department of Computer Science Engineering, West Bengal, India; Dey S., Sukanta Mahavidyalaya Dhupguri, Department of Computer Science, Jalpaiguri, West Bengal, India</text>
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              <elementText elementTextId="191695">
                <text>[No abstract available]</text>
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                <text>Bhattacharyya S.; Jose I.</text>
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                <text>Proceedings - 2020 5th International Conference on Research in Computational Intelligence and Communication Networks, ICRCICN 2020, pp. iii-iv.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099175158&amp;amp;doi=10.1109%2FICRCICN50933.2020.9296171&amp;amp;partnerID=40&amp;amp;md5=1cf67c077ab425e5b2b59a448b58ab8b" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099175158&amp;amp;doi=10.1109%2fICRCICN50933.2020.9296171&amp;amp;partnerID=40&amp;amp;md5=1cf67c077ab425e5b2b59a448b58ab8b&lt;/a&gt;</text>
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                <text>All Open Access; Bronze Open Access</text>
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                <text>Bhattacharyya S., CHRIST (Deemed to Be University), Bangalore, India; Jose I., CHRIST (Deemed to Be University), Bangalore, India</text>
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                <text>Identification of emission-line stars in transition phase from pre-main sequence to main sequence</text>
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          <element elementId="49">
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                <text>Be; Methods: Statistical; Stars: Emission-line; Stars: Evolution; Techniques: Photometric</text>
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                <text>Pre-main-sequence (PMS) stars evolve into main-sequence (MS) phase over a period of time. Interestingly, we found a scarcity of studies in existing literature that examine and attempt to better understand the stars in PMS to MS transition phase. The purpose of this study is to detect such rare stars, which we named as 'transition phase' (TP) candidates-stars evolving from the PMS to the MS phase. We identified 98 TP candidates using photometric analysis of a sample of 2167 classical Be (CBe) and 225 Herbig Ae/Be (HAeBe) stars. This identification is done by analysing the near-and mid-infrared excess and their location in the optical colour-magnitude diagram. The age and mass of 58 of these TP candidates are determined to be between 0.1-5 Myr and 2-10.5 M?, respectively. The TP candidates are found to possess rotational velocity and colour excess values in between CBe and HAeBe stars, which is reconfirmed by generating a set of synthetic samples using the machine learning approach.   2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.</text>
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                <text>Bhattacharyya S.; Mathew B.; Banerjee G.; Anusha R.; Paul K.T.; Kartha S.S.</text>
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                <text>In our previous study (Bhattacharyya et al., 2022), HD 54786, the optical counterpart of the MAXI J0709-159 system, was identified to be an evolved star, departing from the main sequence, based on comparisons with non-X-ray binary systems. In this paper, using color-magnitude diagram (CMD) analysis for High-Mass X-ray Binaries (HMXBs) and statistical t-tests, we found evidence supporting HD 54786s potential membership in both Be/X-ray binaries (BeXRBs) and supergiant X-ray binaries (SgXBs) populations of HMXBs. Hence, our study points towards dual optical characteristics of HD 54786, as an X-ray binary star and also belonging to a distinct evolutionary phase from BeXRB towards SgXB. Our further analysis suggests that MAXI J0709-159, associated with HD 54786, exhibits low-level activity during the current epoch and possesses a limited amount of circumstellar material. Although similarities with the previously studied BeXRB system LSI +61? 235 (Coe et al., 1994) are noted, continued monitoring and data collection are essential to fully comprehend the complexities of MAXI J0709-159 and its evolutionary trajectory within the realm of HMXBs.  2024 Societe Royale des Sciences de Liege. All rights reserved.</text>
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                <text>We present a follow-up study on the recent detection of two X-ray flaring events by MAXI/Gas Slit Camera observations in soft and hard X-rays from MAXI J0709-159 in the direction of HD 54786 (LY CMa), on 2022 January 25. The X-ray luminosity during the flare was around 1037 erg s-1 (MAXI), which got reduced to 1032 erg s-1 (NuSTAR) after the flare. We took low-resolution spectra of HD 54786 from the 2.01 m Himalayan Chandra Telescope and the 2.34 m Vainu Bappu Telescope (VBT) facilities in India, on 2022 February 1 and 2. In addition to H? emission, we found emission lines of He i in the optical spectrum of this star. By comparing our spectrum of the object with those from the literature we found that He i lines show variability. Using photometric studies we estimate that the star has an effective temperature of 20,000 K. Although HD 54786 is reported as a supergiant in previous studies, our analysis favors it to be evolving off the main sequence in the color-magnitude diagram. We could not detect any infrared excess, ruling out the possibility of IR emission from a dusty circumstellar disk. Our present study suggests that HD 54786 is a Be/X-ray binary system with a compact object companion, possibly a neutron star.   2022. The Author(s). Published by the American Astronomical Society.</text>
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                <text>Bhattacharyya S., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, India; Mathew B., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, India; Ezhikode S.H., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, India; Muneer S., Indian Institute of Astrophysics, Koramangala, Bangalore, India; G. S., Indian Institute of Astrophysics, Koramangala, Bangalore, India; G. M., Indian Institute of Astrophysics, Koramangala, Bangalore, India; Arun R., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, India, Indian Institute of Astrophysics, Koramangala, Bangalore, India; Anilkumar H., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, India; Banerjee G., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, India; Kumar S P., Indian Institute of Astrophysics, Koramangala, Bangalore, India; Kartha S.S., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, India; Paul K.T., Department of Physics and Electronics, CHRIST (Deemed to Be University), Hosur Main Road, Bangalore, India; Velu C., Indian Institute of Astrophysics, Koramangala, Bangalore, India</text>
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                <text>Intelligent Environmental Data Monitoring for Pollution Management discusses evolving novel intelligent algorithms and their applications in the area of environmental data-centric systems guided by batch process-oriented data. Thus, the book ushers in a new era as far as environmental pollution management is concerned. It reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, followed by a review of intelligent tools and techniques which can be used in this direction. In addition, it discusses novel intelligent algorithms for effective environmental pollution data management that are on par with standards laid down by the World Health Organization. To learn more about Elseviers Series, Intelligent Data-Centric Systems, please visit this link: https://www.elsevier.com/books-and-journals/book-series/intelligent-data-centric-systems-sensor-collected-intelligence.  2021 Elsevier Inc. All rights reserved.</text>
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