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                <text>Hyperledger Fabric as a Secure Blockchain Solution for Healthcare 4.0 Framework</text>
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                <text>Blockchain; Distributed Ledger Technology; Hyperledger Fabric platform; Zero-knowledge proof</text>
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                <text>The healthcare sector deals with extremely sensitive information that must be administered in a safe and confidential way. The objective of the proposed framework is to utilize Blockchain Technology (BT) for tracking medical prescriptions and the implementation is carried out using the Hyperledger Fabric platform, an enterprise-grade open-source distributed ledger technology platform designed for Bigdata applications. Multiple entities, including patients, e-pharmacies, pharmacies, doctors and hospitals can establish connections by introducing several nodes in the Fabric chain. A web-centered application is provided for doctors, connecting them with participating pharmacies, hospitals and e-pharmacies through which, they can share patient prescription. Pharmacies and e-pharmacies have access to this data and can notify patients about the availability of prescribed medicines. Additionally, reminders for refills, such as heart medication, can be sent for patients requiring long-term medication. Patients can also try with nearby pharmacies and the availability of their prescribed medicines. The inclusion of a wallet feature in the application enables patients to use mobile tokens for making purchases. Patient data is treated with the utmost confidentiality, kept private, and accessed only upon request and with the consent of the concerned parties. This privacy is ensured through the use of zero-knowledge proof. Patients retain access to their complete medical history, facilitating interactions with doctors without the need for repetitive information sharing.  2023 IEEE.</text>
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                <text>2023 International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2023, pp. 530-536.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Joy S., New Horizon College of Engineering, Department of Electronics and Communication Engineering, Bengaluru, 560103, India; Baby Chithra R., New Horizon College of Engineering, Department of Electronics and Communication Engineering, Bengaluru, 560103, India; Neethu P., School of Engineering and Technology(SoET), Christ(Deemed to Be University), Department of Ece, Bangalore, India; Anju M.I., Faculty of Engineering and Technology, Srm Institute of Science and Technology, Dept of Ece, India; Patil K.A., New Horizon College of Engineering, Department of Electronics and Communication Engineering, Bengaluru, 560103, India; Pal Cheema A., New Horizon College of Engineering, Department of Electronics and Communication Engineering, Bengaluru, 560103, India; Lal M.K., Amrita School of Engineering, Dept of Ece, Karnataka, Bangalore, India</text>
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                <text>Athul Ghosh, P.; Chidambaram, S.</text>
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                <text>Hyperspectral Image Classification using Archimedes Optimized 3D CNN layers</text>
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                <text>Proceedings of 5th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2025;pp.151-157</text>
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                <text>Athul Ghosh P., Christ University, School of Engineering and Technology, Department of Ece, Bangalore, India; Chidambaram S., Christ University, School of Engineering and Technology, Department of Ece, Bangalore, India</text>
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                <text>Background: Hyperspectral Image (HSI) classification involves analyzing images captured across numerous spectral bands to identify and categorize materials or objects. By exploiting spectral information, HSI enables precise detection of materials based on their unique spectral signatures. This extensive spectral information allows for accurate identification of materials and land cover types, making HSI classification essential for various applications. This research developed an optimization-based Deep Learning (DL) framework for effective classification of HSI. The methodology begins with a preprocessing step using Minimum Noise Fraction (MNF), a technique that leverages the noise covariance structure of the dataset to reduce dimensionality while preserving the most informative spectral features. To enhance classification performance, a novel model is proposed, known as Archimedes Optimization Algorithm-3D Convolutional Neural Network (AOA based 3D CNN). Archimedes Optimization Algorithm (AOA) is applied to fine-tune learning rate of 3D Convolutional Neural Network (3D CNN), thereby optimizing training convergence and enhancing accuracy. Result: The proposed AOA based 3D CNN approach exhibits outstanding performance, achieving 95.6% accuracy, 95.9% TPR, 94.1% TNR, 94.9% PPV, a Kappa coefficient of 95.4%, and an F1-score of 95.5%.Keywords: These results highlight the model's effectiveness, adaptability and robustness for HSI classification.   2025 IEEE.</text>
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                <text>deep learning; HSI classification; Hyperspectral images; MNF; optimization</text>
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                <text>Hyperspectral Image Classification Using Denoised Stacked Auto Encoder-Based Restricted Boltzmann Machine Classifier</text>
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                <text>Hyperspectral images; Noise; PyTorch; Restricted Boltzmann Machine; Stacked Auto Encoder</text>
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                <text>This paper proposes a novel solution using an improved Stacked Auto Encoder (SAE) to deal with the problem of parametric instability associated with the classification of hyperspectral images from an extensive training set. The improved SAE reduces classification errors and discrepancies present within the individual classes. The data augmentation process resolves such constraints, where several images are produced during training by adding noises with various noise levels over an input HSI image. Further, this helps in increasing the difference between multiple classes of a training set. The improved SAE classifies HSI images using the principle of Denoising via Restricted Boltzmann Machine (RBM). This model ambiguously operates on selected bands through various band selection models. Such pre-processing, i.e., band selection, enables the classifier to eliminate noise from these bands to produce higher accuracy results. The simulation is conducted in PyTorch to validate the proposed deep DSAE-RBM under different noisy environments with various noise levels. The simulation results show that the proposed deep DSAE-RBM achieves a maximal classification rate of 92.62% without noise and 77.47% in the presence of noise.  2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.</text>
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                <text>Yuvaraj N.; Praghash K.; Arshath Raja R.; Chidambaram S.; Shreecharan D.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-647 LNNS, pp. 213-221.</text>
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                <text>Springer Science and Business Media Deutschland GmbH</text>
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                <text>ISSN: 23673370; ISBN: 978-303127408-4</text>
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                <text>Yuvaraj N., Research and Publications, ICT Academy, IIT Madras Research Park, Chennai, India; Praghash K., Department of Electronics and Communication Engineering, CHRIST University, Bengaluru, India; Arshath Raja R., Research and Publications, ICT Academy, IIT Madras Research Park, Chennai, India; Chidambaram S., Department of Electronics and Communication Engineering, CHRIST University, Bengaluru, India; Shreecharan D., Department of Electronics and Communication Engineering, CHRIST University, Bengaluru, India</text>
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                <text>Hyperspectral multi-level image thresholding using qutrit genetic algorithm</text>
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                <text>Hyperspectral images contain rich spectral information about the captured area. Exploiting the vast and redundant information, makes segmentation a difficult task. In this paper, a Qutrit Genetic Algorithm is proposed which exploits qutrit based chromosomes for optimization. Ternary quantum logic based selection and crossover operators are introduced in this paper. A new qutrit based mutation operator is also introduced to bring diversity in the off-springs. In the preprocessing stage two methods, called Interactive Information method and Band Selection Convolutional Neural Network are used for band selection. The modified Otsu Criterion and Masi entropy are employed as the fitness functions to obtain optimum thresholds. A quantum based disaster operation is applied to prevent the quantum population from getting stuck in local optima. The proposed algorithm is applied on the Salinas Dataset, the Pavia Centre Dataset and the Indian Pines dataset for experimental purpose. It is compared with classical Genetic Algorithm, Particle Swarm Optimization, Ant Colony Optimization, Gray Wolf Optimizer, Harris Hawk Optimization, Qubit Genetic Algorithm and Qubit Particle Swarm Optimization to establish its effectiveness. The peak signal-to-noise ratio and Sensen-Dice Similarity Index are applied to the thresholded images to determine the segmentation accuracy. The segmented images obtained from the proposed method are also compared with those obtained by two supervised methods, viz., U-Net and Hybrid Spectral Convolutional Neural Network. In addition to this, a statistical superiority test, called the one-way ANOVA test, is also conducted to judge the efficacy of the proposed algorithm. Finally, the proposed algorithm is also tested on various real life images to establish its diversity and efficiency.  2021 Elsevier Ltd</text>
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                <text>Dutta T., Department of Computer Science &amp;amp; Engineering, Assam University, Silchar, Assam, India; Dey S., Department of Computer Science, Sukanta Mahavidyalaya, Dhupguri, Jalpaiguri, West Bengal, India; Bhattacharyya S., Department of Computer Science &amp;amp; Engineering, Christ University, Bangalore, Karnataka, India; Mukhopadhyay S., Department of Computer Science &amp;amp; Engineering, Assam University, Silchar, Assam, India; Chakrabarti P., Techno India NJR Institute of Technology, Udaipur, Rajasthan, India</text>
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                <text>I am less biased than others: themediating effect of career exploration on decision styleandbiasblind spot</text>
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                <text>Priya. L J., Department of Management Studies, National Institute of Technology Tiruchirappalli, Tiruchirappalli, India; Kumar. P A., School of Business and Management, Christ University, Bangalore, India; Vilvanathan L., Department of Management Studies, National Institute of Technology Tiruchirappalli, Tiruchirappalli, India</text>
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                <text>Purpose: This study primarily investigated the tendency of management students to exhibit bias blind spots on three biases related to career decision-making. Second, it also explores how different decision styles, namely rational and intuitive, relate to bias blind spots, considering career exploration as a key factor that might influence this relationship. Design/methodology/approach: To gather data from 277 second-year MBA students specializing in management and business administration from two southern states of India. SPSS software was used to measure the bias blind spot score, and partial least squares structural equation modeling (PLS-SEM) was used to test the hypotheses. Findings: The research findings highlight that students exhibit a bias blind spot tendency during self and environment exploration, and the decision styles indirectly affect bias blind spots through the mediating effects of career exploration. Originality/value: These findings have implications for future research in career psychology, career guidance, and social psychology and for developing interventions to enhance career exploration behavior and decision-making styles to mitigate cognitive biases in career decision-making.  2025, Emerald Publishing Limited.</text>
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                <text>The current study aims to explore gaming behaviour among young adults in India and its effects on their physical and emotional health, productivity, interactions, and social life. Data were collected from 12 avid gamers through in-depth semi-structured interviews. A thematic analysis was conducted to identify the global theme and organise themes from the data. The global theme was the exploration of contemporary gaming behaviour. The habit theme included the origin of the game, practice, and change over time, while the effects theme focused on the physical and emotional health, productivity, interactions, and social life of young adults who engaged in gaming. The findings suggest that gaming behaviour has become an established habit among young adults in India, significantly affecting various aspects of their lives. The study highlights the need for increased awareness of the potential negative consequences of excessive gaming and emphasises the importance of moderation in gaming.  2024 Informa UK Limited, trading as Taylor &amp;amp; Francis Group.</text>
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                <text>Sathiyaseelan A., School of Psychological Sciences, Christ University, Bangalore, India; Balasundaram S., School of Business and Management, Christ University, Bangalore, India; Patangia B., School of Psychological Sciences, Christ University, Bangalore, India; M A., School of Psychological Sciences, Christ University, Bangalore, India</text>
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                <text>The purpose of this paper is to examine the antecedents of e-banking loyalty and evangelism via threefold construct of WEQUAL (usability, information quality, and service interaction) of public sector banks operating in India. Moreover, it also investigates the mediating role of consumers' trust on the website quality of these banks and their impact on e-banking loyalty and evangelism. The data was collected from 243 respondents through online questionnaire. In order to develop the model and test the hypotheses, partial least square structural equation modeling (PLS-SEM) was done through Smart PLS version 3.2.9. Results assert that website quality of banks positively influences the trust of consumers via usability, information quality, and service interaction. Also, consumer trust plays a mediation role between WEBQUAL constructs and e-banking loyalty and evangelism.  2021 IGI Global. All rights reserved.</text>
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                <text>Davis A.R., Christ University, India; Das R., Mahindra University, India</text>
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                <text>This research employs an autobiographical approach to reflect on ethnographic challenges from the perspective of a woman ethnographer in Kerala, India. South Asia is not just a geographical concept but also a metaphor of exclusion, silencing, and marginalisation of underserved populations (Dutta &amp;amp; Visweswararv, 2019). Drawing on Jyothsna Latha Belliappas arguments on positionality and reflexivity, the findings show that ethnographic frameworks should be adapted to reflect intersectional realities and socio-cultural dynamics. Even though scholarly studies on feminist ethnography exist, there remains a huge gap in scholarship concerning how women researchers navigate kinship and religion in gendered spaces. As a woman ethnographer in the field for five months, I unlearned, re-learned, and co-learned how female nature is inscribed in various cultural locations (Sobritchea, 2002). Rethinking ethnography functions as a knowledge production system rather than merely writing a thick description of the study area.  2026 by IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>The great impact of media technologies in reordering almost every facet of modern life has been noted by theorists for over a century now, particularly since the idea of the global village imagined by media theorists, and enabled by globalisation and digital technology has become an inescapable reality. The new experience of time and space bears upon various dimensions of life, including the nature of work, the organisation of time and the place of leisure within these rhythms. This article attempts to engage with this very weighty body of scholarship in a modest way, through ethnographic research, to understand how mobile phones and internet technologies structure the experience of everyday life for low-income migrant workers in Bengaluru. The sites include a construction site and a hookah bar, and the study focuses on mobile gaming and the structuring of migrant social networks.  2024 South Asian University.</text>
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                <text>This study was ICT integration in universities in relation to ICT challenges and work motivation of lecturers in Harare, Zimbabwe. There exists varying rates of ICT newlineintegration in universities and this has a negative impact on the teaching and learning newlineprocesses. The major aim of the study was to assess the relationship between ICT integration, ICT Challenges and work motivation of lecturers. The findings of the study is expected to show how universities could isolate challenges and tailor-make strategies of overcoming them whilst at the same time getting deeper insight into human behavior in an organisation and its contribution towards ICT integration. The thesis was therefore conducted to match availability of ICTs and their utilization as newlinethis had a direct bearing on the curriculum delivery as well as empowering learners to newlineengage in meaningful, challenging and enlightening tasks since ICTs have the potential to play a powerful role in every university- both inside and outside lecture room/classroom. Institutional responses to ICT influences have inevitably brought about a lot of changes in the teaching / learning processes. The research approach adopted was quantitative. The sample included 200 lecturers drawn from a population of 600 lecturers consisting of two private and four state universities. Harare was conveniently chosen as it is the capital city of Zimbabwe and has the greatest number of state and private universities. Two questionnaires one on ICT integration and another one on ICT challenges were designed by the researcher and the third one on Work Motivation Questionnaire was adopted from Agrawal (1988) and standardized for the Zimbabwean context. The major challenges associated with slow newlineuptake were analysed and assessed in terms of their impact on the teaching and learning newlineprocesses and the motivation of lecturers was also evaluated together with demographic newlinefeatures to find predictors of successful ICT integration in universities.</text>
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            <name>Description</name>
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                <text>A set S ? V of a graph G = (V, E) is a co-secure dominating set if for every u ? S, there exists v ? V \ S such that uv ? E and (S \ {u}) ? {v} is a dominating set of G. The minimum cardinality of a co-secure dominating set of G is the co-secure domination number and is denoted by ?cs(G). In this paper we initiate the evaluation of a domination parameter known as the ideal co-secure domination and is defined as follows: A set D ? V is an ideal co-secure dominating set of a graph G = (V, E) if for every u ? D and for every v ? V \ D such that uv ? E, (D \ {u}) ? {v} is a dominating set of G. The minimum cardinality of an ideal co-secure dominating set of G is the ideal co-secure domination number and is denoted by ?ics(G). We look to determine the ideal co-secure domination number of some families of standard graphs and obtain sharp bounds. We also provide the conditions necessary for the trees to have ideal co-secure domination number equal to n - 2.  2020 Author(s).</text>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
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              <elementText elementTextId="185379">
                <text>Theresa S.; Sangeetha V.</text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="185380">
                <text>AIP Conference Proceedings, Vol-2236</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="185381">
                <text>American Institute of Physics Inc.</text>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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              <elementText elementTextId="185382">
                <text>2020-01-01</text>
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            <name>Identifier</name>
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                <text>&lt;a href="https://doi.org/10.1063/5.0006826" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1063/5.0006826&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085680361&amp;amp;doi=10.1063%2F5.0006826&amp;amp;partnerID=40&amp;amp;md5=7cd8dc3cc1b14f944c867acf6b660572" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085680361&amp;amp;doi=10.1063%2f5.0006826&amp;amp;partnerID=40&amp;amp;md5=7cd8dc3cc1b14f944c867acf6b660572&lt;/a&gt;</text>
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            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
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              <elementText elementTextId="185384">
                <text>Restricted Access</text>
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                <text>ISSN: 0094243X; ISBN: 978-073541995-7</text>
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            <name>Format</name>
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              <elementText elementTextId="185386">
                <text>Online</text>
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            <name>Language</name>
            <description>A language of the resource</description>
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              <elementText elementTextId="185387">
                <text>English</text>
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            <name>Type</name>
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                <text>Conference paper</text>
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                <text>Theresa S., Department of Mathematics, CHRIST (Deemed to Be University), Bengaluru, India; Sangeetha V., Department of Mathematics, CHRIST (Deemed to Be University), Bengaluru, India</text>
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