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                <text>Anonymization Based Deep Privacy Preserving Convolutional Autoencoder Learning Technique for High Dimensional Data Clustering in Big Data Cloud</text>
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                <text>Advanced Networking; Anonymization; Big Data Clustering; Deep Learning Architecture; High Dimensional Big Data; Reconstruction Error</text>
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                <text>Data Clustering is a primary research focus in large data-driven application domains in the big data cloud as performance of the clustering dynamic data with high dimensionality is highly challenging due to major concern in the effectiveness and efficiency on data representation. Machine learning is a conventional approach to distribute the data into soft partition still it leads to increasing sparsity of data and increasing difficulties in distinguishing distance between data points. In addition, securing the personnel and confidential information of the user is also becoming vital. In order to tackle those issues, a new anonymization based deep privacy preserving learning paradigm has been presented in this paper. The proposed model is represented as deep privacy preserving convolutional auto encoder learning architecture for secure high dimensional data clustering on inferring the distribution of the data over time. Initially dimensionality reduction and feature extraction is carried out and those extracted feature has been taken for clustering on generation of objective function to produce maximum margin cluster. Those clusters are further fine tuned to feature refinement on the hyper parameter of various layers of deep learning model network to establish the minimum reconstruction error by feature refinement. Softmax layer minimizes the intra cluster similarity and inter cluster variation in the feature space for cluster assignment. Hyper parameter tuning using stochastic gradient descent has been enabled in the output layer to make the data instance in the cluster to be close to each other by determining the affinity of the data on new representation. It results significant increase in the clustering performance on the discriminative informations. Detailed experimental analysis has been performed on benchmarks datasets to compute the proposed model performance with conventional approaches. The performance outcome represents that anonymization based deep privacy preserving clustering learning architecture can produce good scalability and effectiveness on high dimensional data. 2023 American Institute of Physics Inc.. All rights reserved.</text>
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                <text>Kiruthika B.; Srinivasan B.; Poornima N.V.; Prabhusundhar P.</text>
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                <text>AIP Conference Proceedings, Vol-2909, No. 1</text>
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                <text>American Institute of Physics Inc.</text>
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                <text>&lt;a href="https://doi.org/10.1063/5.0183809" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1063/5.0183809&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179877724&amp;amp;doi=10.1063%2F5.0183809&amp;amp;partnerID=40&amp;amp;md5=96ae1d7a6261b97d8dc50453f13beb6f" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179877724&amp;amp;doi=10.1063%2f5.0183809&amp;amp;partnerID=40&amp;amp;md5=96ae1d7a6261b97d8dc50453f13beb6f&lt;/a&gt;</text>
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                <text>ISSN: 0094243X; ISBN: 978-073544750-9 | CS; 2023-20234; Vol-1; 00261-00262</text>
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                <text>Kiruthika B., Gobi Arts &amp;amp; Science College, Gobichettipalayam, India; Srinivasan B., Gobi Arts &amp;amp; Science College, Gobichettipalayam, India; Poornima N.V., Christ University, Bangalore, India; Prabhusundhar P., Gobi Arts &amp;amp; Science College, Gobichettipalayam, India</text>
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                <text>FADA: Flooding Attack Defense AODV Protocol to counter Flooding Attack in MANET</text>
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                <text>Denial of Service (DoS); FADA Protocol; Flooding attack; MANET; Throughput</text>
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                <text>The intrinsic nature of a Mobile Ad hoc Network (MANET) makes it difficult to provide security and it is more vulnerable to network attacks. Denial of Service (DoS) attack can be executed using Flooding attack, that has the potential to bring down the entire network. This attack works by delivering an excessive number of unwanted packets that consumes too much battery life, storage space, and bandwidth, that eventually lowers the system's performance. In order to flood the network, the attacker injects fake packets into it. Both Control Packet flooding and Data flooding attacks are taken into account in this study. FADA (Flooding Attack Defense AODV) protocol is proposed to counter flooding attack that promotes greater utilization of existing resources. This research identifies the attack-causing node, isolates it and protects the network against flooding attack. Attack Detection Rate, Attack Detection Accuracy, End-to-end delay and Throughput are few metrics used for evaluation of the proposed model. NS-2.35 is used to demonstrate the efficiency of the suggested protocol and the results prove that the proposed model increases system's throughput while decreasing attack. The simulation results have shown that the proposed FADA protocol performs better than the existing models taken into consideration.   2023 IEEE.</text>
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                <text>Kiruthika M.; Krishnasamy L.; Samuel P.; Kanagaraj K.</text>
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                <text>Proceedings of IEEE 2023 5th International Conference on Advances in Electronics, Computers and Communications, ICAECC 2023</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>2023-01-01</text>
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                <text>&lt;a href="https://doi.org/10.1109/ICAECC59324.2023.10560115" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICAECC59324.2023.10560115&lt;/a&gt;
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                <text>ISBN: 979-835030544-9</text>
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                <text>Kiruthika M., School of Computing, SRM Institute of Science and Technology, Department of Computational Intelligence, Tamilnadu, Kattankulathur, India; Krishnasamy L., School of Engineering and Technology, Christ University, Department of Computer Science and Engineering, Karnataka, Bengaluru, India; Samuel P., School of Computing, SRM Institute of Science and Technology, Department of Computational Intelligence, Tamilnadu, Kattankulathur, India; Kanagaraj K., School of Computing, SRM Institute of Science and Technology, Department of Computational Intelligence, Tamilnadu, Kattankulathur, India</text>
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                <text>Investigation on Preserving Privacy of Electronic Medical Record using Split Learning</text>
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                <text>Healthcare; Patient data; Privacy; Security; Split Learning</text>
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                <text>Artificial Intelligence is deployed in multiple areas, including healthcare. Utmost research is done in AI enabled healthcare industry because of the demands like accurate result, data security, exact prediction, huge volume of data, etc. In conventional deep learning models, the training happens with the dataset that are stored in a single device. This requires a huge storage space and highly efficient machines to train the data. Usage of big data, demands for innovative models that can be deployed and used in confined storage. Split learning is one such collaborative distributed deep learning model that allows the data to be stored in a split fashion. Split learning supports desirable features like less storage, more privacy to raw data, ability to work with resource constraints, etc., making it suitable for storing electronic medical record of patients. This paper discusses the advantages of using split learning for healthcare, the possible configurations of split learning that supports data privacy in healthcare and finally discusses the open research challenges in implementing split learning for healthcare.  2024 The Authors. Published by Elsevier B.V.</text>
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                <text>Kiruthika M.; Kumar A.; Krishnasamy L.; Sarveshwaran V.</text>
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                <text>Procedia Computer Science, Vol-233, pp. 614-622.</text>
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                <text>Elsevier B.V.</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.procs.2024.03.251" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.procs.2024.03.251&lt;/a&gt;
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                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 18770509</text>
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                <text>English</text>
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                <text>Kiruthika M., Department of Computational Intelligence, School of Computing, SRM Institute of Science and Technology, Tamilnadu, Kattankulathur, 603203, India; Kumar A., Punjab National Bank, New Delhi, 110075, India; Krishnasamy L., Department of Computer Science and Engineering, School of Engineering and Technology, Christ University, Karnataka, Bengaluru, 560074, India; Sarveshwaran V., Department of Computational Intelligence, School of Computing, SRM Institute of Science and Technology, Tamilnadu, Kattankulathur, 603203, India</text>
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                <text>Kiruthika, D.; Fulgen, Maria; Nambiraj, L.</text>
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                <text>Kiruthika D., Dr. SNS Rajalakshmi College of Arts and Science (Autonomous), Department of Commerce with Computer Applications, Tamil Nadu, Coimbatore, India; Fulgen M., Christ Deemed to Be University, Department of Commerce, Bengaluru, India; Nambiraj L., Dr. SNS Rajalakshmi College of Arts and Science (Autonomous), Department of Commerce with Computer Applications, Tamil Nadu, Coimbatore, India</text>
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                <text>Kishore P.S., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, India; Gujjarappa R., Department of Chemistry, National Institute of Technology Manipur, Langol, Manipur, Imphal, 795004, India; Putta V.P.R.K., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, India; Polina S., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, India; Singh V., Department of Chemistry, Central University of Punjab, Punjab, Bathinda, 151001, India; Malakar C.C., Department of Chemistry, National Institute of Technology Manipur, Langol, Manipur, Imphal, 795004, India; Pujar P.P., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, India</text>
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                <text>Indigenous Empowerment through Human-Machine Interactions: The Challenges and Strategies from Business Lenses;pp.273-288</text>
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                <text>Kismawadi E.R., IAIN Langsa, Indonesia; Irfan M., Christ University, India; Harahap I., Universitas Islam Negeri Sumatera Utara, Indonesia</text>
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                <text>The objective of this study is to examine the potential incorporation of Artificial Intelligence (AI) technology into financial management practices that are based on Islamic principles, with a particular emphasis on ensuring Shariah compliance. The literature analysis methodological approach is employed to identify the opportunities and challenges associated with the adoption of AI in the Islamic Finance (IF) environment. The results indicate that the implementation of AI can enhance the efficacy, transparency, and precision of IF operations. However, there are numerous challenges associated with Shariah compliance and ethics. The findings of this study emphasize the importance of establishing a regulatory framework that is consistent with Shariah principles in order to ensure the successful implementation of AI in Islamic financial institutions (IFI). The need for collaboration between finance experts and academics to ensure that the technology is implemented in accordance with Shariah principles, as well as the expansion of training for IF (Islamic Finance) practitioners regarding the implications of AI, are among the recommendations. Future research should examine the influence of more specific AI implementation strategies on Islamic conformance and operational efficacy in the context of IF.  2025 Early Ridho Kismawadi, Mohammad Irfan and Isnaini Harahap. All rights reserved.</text>
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                <text>This study aims to explore the application of sustainability assurance in increasing sharia compliance and social responsibility of Islamic financial institutions. By highlighting methodologies, challenges, and best practices, this study evaluates how sustainability assurance can support sustainability reporting that is transparent, credible, and compliant with sharia principles. The results of the study show that sustainability assurance contributes significantly to sharia compliance by verifying sustainability reports involving environmental, social, and governance (ESG) aspects. The study also identified key challenges, including the lack of sustainability reporting standards specific to Islamic finance and the need to strengthen the capacity of Islamic financial institution practitioners regarding sustainability assurance. The implications of this study include practical guidance for Islamic financial institutions in formulating effective and sharia- based sustainability policies.  2025, IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>Kliman, Harvey J.; Romero, Roberto; Meyyazhagan, Arun; Avila, Cecilia; Chaiworapongsa, Tinnakorn; Awonuga, Awoniyi; Tarca, Adi L.</text>
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                <text>Journal of Perinatal Medicine;</text>
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                <text>Kliman H.J., Department of Obstetrics, Gynecology &amp;amp; Reproductive Sciences, Yale University School of Medicine, New Haven, CT, United States; Romero R., United States Department of Health and Human Services, Pregnancy Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States, Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, United States, Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, United States, Department of Obstetrics and Gynecology, George Washington University, Washington, United States; Meyyazhagan A., Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, United States, Department of Life Sciences, Christ University, Bengaluru, India; Avila C., Department of Obstetrics &amp;amp; Gynecology, State University of New York, Stony Brook Medicine, Stony Brook, NY, United States; Chaiworapongsa T., Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, United States; Awonuga A., Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, United States; Tarca A.L., Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, United States, Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, United States</text>
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                <text>To evaluate the correlation between a simple two-dimensional (2D) sonographic method and the gold-standard three-dimensional (3D) method for estimating placental volume during early to mid-pregnancy. Placental volume was measured using both 2D and 3D ultrasound techniques in 58 pregnant patients between 11 and 22 weeks of gestation. All participants had normal term pregnancy outcomes. The correlation between the two methods was analyzed using Pearson's correlation coefficient. A strong positive correlation was observed between the 2D and 3D placental volume estimates (Pearson's r=0.93, p&amp;lt;0.001), indicating high agreement between the two measurement approaches. The simpler 2D sonographic method shows excellent correlation with the 3D gold-standard technique and may serve as a feasible alternative for placental volume assessment, particularly in low-resource settings where access to advanced equipment is limited.  2026 the author(s)</text>
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                <text>&lt;em&gt;&lt;strong&gt;Kadhai Padalkalum Samoohavum /&lt;/strong&gt;&lt;/em&gt;</text>
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                <text>Thevaneyan Achakam</text>
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                <text>Enhancing the energy efficiency for prolonging the network life time in multi-conditional multi-sensor based wireless sensor network</text>
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                <text>clustering; energy efficiency; signal strength verification; Wireless sensor networks</text>
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                <text>A wireless sensor network is one of the networks that is highly demanding by various real-time networking applications nowadays. A huge amount of sensor nodes is deployed in the network randomly and distributed. Most of the applications using wireless sensor network (WSN) are surveillance monitoring applications like a forest, home, healthcare, environment, and remote monitoring systems. Based on the application usage, the type of sensor, a number of sensor nodes are deployed in such a manner where the sensors can be used effectively. But the sensor nodes are restricted in the battery and sensing region. Thus, the battery of the sensor nodes is decreased based on the nodes function. The energy level of the sensor nodes highly affects the network lifetime. Improving the energy efficiency in WSN is one of the most important challenging tasks. Most of the earlier research works have proposed various methods, techniques, and routing protocols, but they are application dependent and as a common method. So, this paper is motivated to propose a Multi-Conditional Network Analysis (MCNA) framework for saving the energy level of the sensor nodes by reducing energy consumption. The MCNA framework involves two different clustering processes with cluster head selection, choosing the best nodes based on the signal strength, and the best route for data transmission. The data transmission is done by cluster based on source-destination based. The simulation results proved that the proposed MCNA framework outperforms the other existing methods.  2022 Northeastern University, China.</text>
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                <text>Kocherla R.; Chandra Sekhar M.; Vatambeti R.</text>
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                <text>Journal of Control and Decision, Vol-10, No. 1, pp. 72-81.</text>
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                <text>Taylor and Francis Ltd.</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129172106&amp;amp;doi=10.1080%2F23307706.2022.2057362&amp;amp;partnerID=40&amp;amp;md5=d7f519f319ac4ef2a730343cec65b6c0" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129172106&amp;amp;doi=10.1080%2f23307706.2022.2057362&amp;amp;partnerID=40&amp;amp;md5=d7f519f319ac4ef2a730343cec65b6c0&lt;/a&gt;</text>
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                <text>ISSN: 23307706</text>
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                <text>Kocherla R., Research scholar, Department of CSE, Presidency University, Bangalore, India; Chandra Sekhar M., Department of CSE, Presidency University, Bangalore, India; Vatambeti R., Department of CSE, CHRIST (Deemed to be University), Bangalore, India</text>
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                <text>Efficient Routing Strategies for Energy Management in Wireless Sensor Network</text>
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                <text>Wireless Sensor Network (WSN) refers to a group of distributed sensors that are used to examine and record the physical circumstances of the environment and coordinate the collected data at the centre of the location. This WSN plays a significant role in providing the needs of routing protocols. One of the important aspects of routing protocol in accordance with Wireless Sensor Network is that they should be efficient in the consumption of energy and have a prolonged life for the network. In modern times, routing protocol, which is efficient in energy consumption, is used for Wireless Sensor Network. The routing protocol that is efficient in energy consumption is categorized into four main steps: CM  Communication Model, Reliable Routing, Topology-Based Routing and NS  Network Structure. The network structure can be further classified as flat/hierarchical. The communication model can be further classified as query, coherent/non-coherent, negotiation-based routing protocol system. The topology-based protocol can be further classified as mobile or location-based. Reliable routing can be further classified as QoS (Quality of service) or multiple-path based. A survey on routing protocol that is energy-efficient on Wireless Sensor Network has also been provided in this research.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.</text>
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                <text>Kocherla R.; Chandra Sekhar M.; Vatambeti R.</text>
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                <text>EAI/Springer Innovations in Communication and Computing, pp. 79-99.</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-3-030-78750-9_6" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-3-030-78750-9_6&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139568380&amp;amp;doi=10.1007%2F978-3-030-78750-9_6&amp;amp;partnerID=40&amp;amp;md5=d87188a8685d519e6d5131d9296bcc02" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139568380&amp;amp;doi=10.1007%2f978-3-030-78750-9_6&amp;amp;partnerID=40&amp;amp;md5=d87188a8685d519e6d5131d9296bcc02&lt;/a&gt;</text>
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                <text>Kocherla R., Department of CSE, Presidency University, Bangalore, India; Chandra Sekhar M., Department of CSE, Presidency University, Bangalore, India; Vatambeti R., Department of CSE, CHRIST (Deemed to be University), Bangalore, India</text>
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                <text>In these days, Wireless Sensor Networks (WSN) shows a huge impact on all appliances but one of the huge challenges in WSN is management of energy because the nodes in the network run with battery power. As the replacement of energy drained nodes is difficult, and frequent failure of links may occur and it incurs huge data loss. To avoid this issue the we proposed a Hybrid Krill Herd and Spider Monkey with Grid-Based Data Dissemination (HKHSM-GBDD) protocol with the Shortest Energy Resourceful Routing (SERR) mechanism to develop an efficient and better wireless communication channel. The presented HKHSM framework is utilized to classify malicious and energy drained nodes in earlier stage and to detect the link failure. Furthermore, the SERR mechanism is processed to recover the link and route maintenance. This novel proposed protocol has improved packet delivery ratio and energy consumption. It also enhances energy state of sensor nodes by mounting its lifetime and rerouting. Finally, the competence of the proposed mechanism is compared with existing works and it shows significant improvement over existing algorithms for the considered parameters.  2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.</text>
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                <text>The Dynamics of Power in Utopias Falling to

 Dystopias:

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                <text>Urban Communities are exposed to different disaster risks. The paper aims at understanding the interrelation of spatial planning and the resilience of the urban communities for earthquakes and floods. Various spatial planning components were used to evaluate the community resilience to earthquake and flood in the city of Pune of Maharashtra state in India. It has been identified that spatial planning contributes to a greater extent in determining community resilience. Spatial planning results in differential resilience among communities. In the study area, economically weaker households are found to be more vulnerable to disaster risk due to their spatial locations and limited accessibility to share the resources. These factors are found to be contributing to reduced resilience in the city.  2022 The Authors</text>
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                <text>Kodag S.; Mani S.K.; Balamurugan G.; Bera S.</text>
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                <text>Progress in Disaster Science, Vol-14</text>
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                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 25900617</text>
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                <text>Kodag S., Jamshetji Tata School of Disaster Studies, Tata Institute of Social Sciences, Mumbai, India; Mani S.K., Department of Civil Engineering, CHRIST (Deemed to be University), Bangalore, India; Balamurugan G., Department of Geology, School of Earth Sciences, Central University of Tamil Nadu, Thiruvarur, India; Bera S., Centre for Geoinformatics, Jamsetji Tata School of Disaster Studies, Tata Institute of Social Sciences, Mumbai, India</text>
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                <text>Kodancha P., Department of Psychology, CHRIST University, Bengaluru, India, Department of Clinical Psychology, National Institute of Mental Health and Neuro Sciences (NIMHANS), 560029, Bengaluru, India; Baboo S., School of Education, CHRIST University, Bengaluru, India; Rajeev A., School of Psychological Sciences, CHRIST University, Bengaluru, India</text>
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                <text>Parents of children with Autism Spectrum Disorder (ASD) often experience heightened emotional distress, difficulties in adjustment, and a compromised quality of life. While the severity of ASD symptoms has been consistently linked to these negative outcomes, the psychological mechanisms underlying these associations remain underexplored. The present study examines the mediating roles of parental stress and adjustment in the relationship between ASD severity and parental quality of life. A cross-sectional correlational study design was employed with 52 parents of children with ASD in Bengaluru, India. Participants completed standardised measures assessing ASD severity, parental stress, adjustment, and quality of life. Data was analysed using Pearsons correlations and mediation analysis with SmartPLS, and ethical approval was obtained prior to data collection. Findings indicate that greater parent-reportASD severity is associated with increased parental stress and adjustment difficulties, while higher stress and poorer adjustment are linked to lower QoL. Mediation analysis demonstrated that parental stress significantly mediated the relationship between ASD severity and QoL (? = ? 0.165, p =.035), whereas parental adjustment did not emerge as a significant mediator (? = ? 0.116, p =.165). The direct effect of parent-reportASD severity on QoL was non-significant (? = 0.108, p =.410). Additionally, parents reporting greater engagement in leisure activities showed higher QoL, highlighting the potential role of adaptive coping and self-care. These findings underscore parental stress as a key mechanism influencing parental well-being and suggest that interventions targeting stress management and leisure engagement may enhance QoL among parents of children with ASD.  The Author(s), under exclusive licence to Springer Nature India Private Limited 2026.</text>
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                <text>Kodandappa R., Department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bangalore, 560074, India; Nagaraja S., Department of Mechanical Engineering, MVJ College of Engineering, Karnataka, Bangalore, 560067, India; Chowdappa M.M., Department of Mechanical Engineering, Bangalore Institute of Technology, Karnataka, Bangalore, 560004, India; Krishnappa M., Department of Mechanical Engineering, S.E.A. College of Engineering and Technology, Karnataka, Bangalore, 560049, India; Poornima G.S., Department of Chemistry, New Horizon College of Engineering, Karnataka, Bangalore, 560103, India; Ammarullah M.I., Department of Mechanical Engineering, Faculty of Engineering, Universitas Diponegoro, Central Java, Semarang, 50275, Indonesia, Undip Biomechanics Engineering &amp;amp; Research Centre (UBM-ERC), Universitas Diponegoro, Central Java, Semarang, 50275, Indonesia</text>
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                <text>Kodavathungal Mohammed, Isha Fathima; Mathew, Joswin Joseph; Nagaraju, Shamanth</text>
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                <text>Lecture Notes in Networks and Systems;Volume;1829 LNNS;pp.1-13</text>
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                <text>Kodavathungal Mohammed I.F., Department of Information Technology, CHRIST University, Bangalore, India; Mathew J.J., Department of Information Technology, CHRIST University, Bangalore, India; Nagaraju S., Department of Computer Science and Engineering, CHRIST University, Bangalore, India</text>
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                <text>Real-time monitoring of breath biomarkers such as ammonia, alcohol, and volatile organic compounds (VOCs) is important for early disease diagnosis of metabolic and organ-related diseases. Traditional disease diagnosis techniques are invasive, time-consuming, expensive and not suitable for using in remote areas. To overcome these limitations, this paper proposes the design and development of an IoT-based Smart Breath Analyzer for real-time monitoring and analysis of ammonia, alcohol, and volatile organic compounds (VOC) concentration present in exhaled human breath. The system consists of different kinds of gas sensors connected to an ESP32 microcontroller for measuring gas concentration, which is processed and sent to Blynk application via Wi-Fi for visualization and disease prediction. A trained machine learning model is used in the system which classifies biomarker patterns that may be associated with conditions such as kidney disorders, respiratory issues, or alcohol influence, based on literature-derived thresholds. The system is presented as a proof-of-concept screening tool rather than a clinical diagnostic solution. The results are showed on an OLED display and accessed via a mobile app developed using the Blynk IoT platform. This non-invasive, affordable, and scalable solution improves continuous health monitoring and early diagnosis.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.</text>
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                <text>Engineering Advanced Materials for Manufacturing, Energy, and Smart Systems;pp.375-393</text>
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                <text>Kodidasu Pranathi, MLR Institute of Technology, India; Abdul Gafoor, MLR Institute of Technology, India; Shaik Mohammed Adib Ayub, MLR Institute of Technology, India; M. Arthi, Saveetha Institute of Medical and Technical Sciences, India; Emad M. Elsehly, Faculty of Science, Damanhour University, Egypt; Shijo Thomas, Christ University, India</text>
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                <text>The natural composites are widely preferred nowadays in versatile application due to easily degradable and moderate mechanical properties when compare to polymer matrix composites. The kenaf fiber are used as reinforcement in composites wherever high flexural strength and modulus is required whereas sisal fiber is preferred for tensile strength, impact and wear resistance. In our work hybrid composite comprising kenaf and sisal as reinforcement and epoxy as matrix is fabricated and its mechanical properties are explored and compared with the conventional composite fabricated using only kenaf or sisal as reinforcement. The hybrid composite shows excellent flexural strength but inferior tensile strength when compare to conventional composite. The failure of the specimens are investigated using scanning electron microscopy (SEM). In this chapter detailed insight is presented for emphasizing the need for tailored fiber selection and processing to achieve optimal mechanical properties.  2026 by IGI Global Scientific Publishing.</text>
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                <text>This study aimed to explore the existence of hook-up behaviour among emerging adults in the Indian metropolitan cities of Bangalore, Mumbai, Delhi and Kolkata. The study used a survey design. The sexual behaviour subsection of the Sexual Behaviour Questionnaire was used to assess the frequency of the various types of hook-up behaviour. The results indicated that the participants frequency of hook-up behaviour was 55.13%. Overall hook-up behaviour was higher for males, whereas females reported the highest incidence of hook-up behaviour for kissing. Hook-up behaviour was highest for emerging adults living independently in apartments, followed by those living in paying guests/hostels and living with family. The findings provide evidence for a hook-up culture in Indian metropolitan cities.  2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.</text>
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                <text>Kohli B.; Malu B.; Janarthanan J.; Nanda A.; Ann A.; Kothari A.</text>
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                <text>Sexuality and Culture, Vol-26, No. 6, pp. 2107-2121.</text>
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                <text>Kohli B., CHRIST (Deemed to be University), Bangalore, India; Malu B., CHRIST (Deemed to be University), Bangalore, India, O P Jindal Global University, Sonipat, India; Janarthanan J., CHRIST (Deemed to be University), Bangalore, India; Nanda A., CHRIST (Deemed to be University), Bangalore, India; Ann A., CHRIST (Deemed to be University), Bangalore, India; Kothari A., CHRIST (Deemed to be University), Bangalore, India</text>
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                <text>Self-Care, burnout, and compassion fatigue in oncology professionals</text>
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                <text>Burnout; compassion fatigue; self-care</text>
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                <text>Context: With the rising number of cancer cases in India, the stress levels of the treating team have increased. It has affected their self-care and made them susceptible to problems like burnout and compassion fatigue that adversely affect the quality of patient care. Aims: The aim of the study was to assess and compare the levels of burnout, compassion fatigue, and self-care in three groups of oncology professionals (clinical oncologists, nurses, and psychologists). Settings and Design: The study included 134 oncology professionals working in New Delhi, Bengaluru, and Mumbai. Methods and Material: Sociodemographic data sheet, Professional Quality of Life Scale V and Self-Care Assessment Worksheet were used. Statistical Analysis Used: Kruskal-Wallis, Mann-Whitney U test, and Correlation Analysis. Results: The majority of the professionals reported moderate levels of burnout (60.4%) and compassion fatigue (56%). Oncology nurses reported an elevated risk as they scored significantly higher on these domains and had a lower degree of self-care. Interestingly, psychologists reported comparatively lower levels of burnout and compassion fatigue, despite the fact that they interact with the patients at a deeper level, looking after their psychological and emotional needs. Young age and a poor degree of self-care were identified as major risk factors. Conclusions: The moderate levels of burnout and compassion fatigue, though not severe, are a cause of concern and cannot be overlooked. The study highlights the need for self-care in this regard and suggests that individual and institutional level interventions, particularly for nurses and young professionals, would prove useful.  2020 Wolters Kluwer Medknow Publications. All rights reserved.</text>
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                <text>Kohli D.; Padmakumari P.</text>
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                <text>Indian Journal of Occupational and Environmental Medicine, Vol-24, No. 3, pp. 168-171.</text>
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                <text>&lt;a href="https://doi.org/10.4103/ijoem.IJOEM_201_19" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4103/ijoem.IJOEM_201_19&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098208187&amp;amp;doi=10.4103%2Fijoem.IJOEM_201_19&amp;amp;partnerID=40&amp;amp;md5=a62399ec7a90e174f4ca75eb75b153fb" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098208187&amp;amp;doi=10.4103%2fijoem.IJOEM_201_19&amp;amp;partnerID=40&amp;amp;md5=a62399ec7a90e174f4ca75eb75b153fb&lt;/a&gt;</text>
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                <text>All Open Access; Green Open Access</text>
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                <text>ISSN: 9732284; CODEN: IJIDA</text>
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                <text>Kohli D., M.Sc. Clinical Psychology, Department of Psychology, CHRIST (Deemed to Be University), 302, 3rd Floor, Shambhavi Sovereign, Perampalli Road, Vidhyaratna Nagar, Manipal, Karnataka, 576104, India; Padmakumari P., M.Sc. Clinical Psychology, Department of Psychology, CHRIST (Deemed to Be University), 302, 3rd Floor, Shambhavi Sovereign, Perampalli Road, Vidhyaratna Nagar, Manipal, Karnataka, 576104, India</text>
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