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                <text>The adoption of electric vehicles (EVs) is increasing rapidly as a response to the urgent need to reduce greenhouse gas emissions and dependence on fossil fuels. However, the deployment of a reliable and cost-effective EV charging infrastructure remains a challenge. To address this challenge, this paper proposes the development of an effective charging station using multiport converter and photovoltaic cell integration. A promising approach in the transportation sector is an efficient charging station with multiport converter and photovoltaic cell integration. A multiport converter, photovoltaic cells, a battery energy storage system, and an electric vehicle charging port constitute the proposed charging station. The power flow between the photovoltaic cells, the battery energy storage system, and the electric vehicle charging port is controlled by the multiport converter. The excess energy generated by the photovoltaic cells is stored in the battery energy storage system. The proposed charging station is designed and analysed using MATLAB/Simulink. The simulation results show that the proposed charging station is capable of providing an electric vehicle a reliable and consistent power supply. In contrast to conventional charging stations, the proposed charging station is also capable of offering a faster charging rate.  2024 Nova Science Publishers, Inc. All rights reserved.</text>
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                <text>The reliable verification systems are required to verify and confirm the identity of an individual requesting their service. Secure access to the buildings, laptops, cellular phones, ATM etc. is an example of such applications. In the absence of robust verification systems, these systems are vulnerable to the wiles of an impostor. The traditional ways of authentications are passwords (knowledge ?? based security) and the ID Cards (token ?? based security). These methods can be easily breached due to the chance of stolen, lost or forget. The development and progress of biometrics technology, the fear of stolen, lost or forget can be eliminated. Biometrics refers to the automatic identification (or verification) of an individual (or a claimed identity) by using certain physiological or behavioral traits associated with the person. The biometrics identifies the person based on features vector derived from physiological or behavioural characteristics such as uniqueness, permanence, accessibility, collectability with minimum cost. The physiological biometrics are Fingerprint, Hand Scan, Iris Scan, Facial Scan and Retina Scan etc., and behavioural biometric are Voice, Keystroke, Gait, Signature etc., The physiological biometrics measures the specific part of the structure or shape of a portion of a subjects body. But the behavioural biometric are more concerned with mood and environment. Chapter one presents the introduction to biometrics and its various traits. Further description like structure of the biometric system, different approaches are discussed. Also the design issues in biometric system such as universality, collectability, distinctiveness, permanence, acceptability, uniqueness, performance, circumvention etc., are discussed. Chapter two gives a detailed survey of biometric techniques. It includes the literature survey of fingerprint and face biometric traits and various approaches. In Chapter three, the algorithm of Fingerprint Verification based on Dual Tree Complex Wavelet Transformation (DTCWT) is proposed. The original fingerprint is cropped and resized to apply the DTCWT. The features of Fingerprint are obtained by applying different levels of DTCWT. Performance analysis is discussed with the FRR, FAR and TSR. Chapter four discusses another highly recommended source of authentication such as face recognition. In this chapter, the algorithm of Performance Comparison of Face Recognition using Transform Domain Techniques (PCFTD) is proposed. The face databases L ?? Spacek, JAFFE and NIR are considered. The features of face are generated using wavelet families such as Haar, Symelt and DB1 by considering approximation band only. The face features are also generated using magnitudes of FFTs. The test image features are compared with database features using Euclidian Distance (ED). The performance parameters such as FAR, FRR, TSR and EER computed using wavelet families and FFT. The methodology described in this paper is accurate, simple, fast and better than the existing algorithms. Chapter five presents conclusion and future work.</text>
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                <text>Patent Number: 202141033078, Applicant: Nanjunda K N.&#13;
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                <text>Only a few clinical procedures include the use of clinical methods for the early detection, observing, evaluation, and treatment evaluation of a range of medical illnesses. Knowing the analysis of medical images in computer vision necessitates being acquainted with the core concepts and uses of deep learning and artificial neural networks. The A rapidly expanding area of study is the Deep Learning Approach (DLA) in medical image processing. DLA is often used in medical imaging to determine if an ailment is present or not. By producing speedier, more accurate results in real time, deep learning algorithms may make the jobs of radiologists and orthopaedic surgeons easier. But the standard deep learning approach has reached its efficiencies. While offering an ideal solution known as boost-Net, we study numerous optimization strategies to increase the effectiveness of deep neural networks in this research. From a selection of well-known deep learning models, Champion-Net was selected as the deep learning model. The musculoskeletal radiograph-bone classification (MURA-BC) dataset is used in this investigation. Utilizing the train and test datasets, Enhance-Net's classification precision was evaluated.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.</text>
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                <text>Background: In the somatoform and dissociative spectrum, family functioning has been poorly researched based on the search in PubMed, Google Scholar, Science Direct, PROQUEST, EBSCO and Cochrane Reviews. In Psychogenic Non-Epileptic Seizures (PNES) primarily, family functioning has been understood as a comparison between Epileptic Seizures (ES) and PNES. However, an attempt to study different aspects of family functioning and its ability to influence the newlinemanifestation of the disorder is yet to be made. Methods: This study attempted to understand different family functions qualitatively by interviewing both the patients and family members of these patients. Nine patients and seven families of these patients participated in the study. Braun and Clarke s thematic model was used. Latent thematic analysis was used to analyse the data. Based on the analysis, major and sub-themes were used to develop family intervention and a family psychoeducational model. Both were developed with the help of the GUIDED Checklist to report health interventions; the TIDieR format and Delphi newlinetechnique was used to collect the expert opinion of the developed intervention. newlineResults: Two sets of results and analyses were compiled with qualitative data, that is, for patients and families. Major themes and sub-themes were developed for both, including family interaction, attachment, poor communication, structural-systemic aspects, distressful family aspects, negative newlineexpressed emotions, cultural aspects, nature of the illness, family s views of the illness and coping mechanisms. These themes indicated the importance of family functioning and its impact on the manifestation of the disorder. newlineConclusion: The researcher concludes that family dysfunction can impact the manifestation of the disorder. Hence, an additional family intervention or psychoeducation is essential for holistic newlinetreatment.</text>
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                <text>Green nanotechnology, which uses carbon nanomaterials for environmental remediation, is the pioneer among the prevailing approaches for the production and characterization. In the present study, highly fluorescent carbon dots (CDs) from Ruta Graveolens (ARH-CD) is developed, and its efficacy as a fluorescent sensor and biomarker is investigated. They act as a fluorescence sensor for Hg2+ over an extensive concentration range of 1 picomolar (pm) to 1 molar (m), with a detection limit as low as 26.75 pm. The studies reveal ARH-CD as an effective biomarker for intracellular toxicity analysis and a fluorescent probe for multi-colored (blue, green, and red) imaging of HEK293 cell lines. After 24 h of incubation, it is found that the ARH material reveals noticeable biocompatibility and visible fluorescence, with a viability of 98.88% at 5 gmL?1 and over 78.33% even at a concentration of 100 gmL?1. The IC50 value for the MTT assay for cell viability results is calculated to be 224.56  4.67 g, which further confirms the appreciable biocompatibility of the ARH-CD. The obtained samples are effective in being inspected for the intracellular detection of Hg2+ and serve as a possible candidate for cell imaging.  2024 Wiley-VCH GmbH.</text>
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                <text>Joseph N., Department of Electronics, St Joseph's University, 36 Lalbagh Road, Karnataka, Bengaluru, 5600027, India; Balachandran M., Nanocarbon Research Group, Materials Science Research Laboratory, Department of Physics and Electronics, Christ University, Karnataka, Bengaluru, 560029, India</text>
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                <text>Background: The caregivers of persons with motor neuron disease (MND) have several needs that are usually not voiced on any platform. Aim: To explore the lived experience of spouses of persons with MND, identify their needs and develop guidelines for better home-based care. Method: An exploratory study with 3-point in-depth interviews among 13 participants was conducted. Participants were the spouses of persons with MND under treatment at a national quaternary referral center. The interpretative phenomenological analysis identified participants needs. These needs, with literature review synthesis, guided the drafting of guidelines, which was validated by experts. Results: The needs were emotional, social, care systems, and skills. The guidelines developed contained 2 sections (1) Information for the spouses: understanding MND, communication, symptom management, marital relationship, palliative care, and everyday life made easier. (2) Well-being of the spouse caregivers: well-being of the spouse caregivers, self-care, mental health, supporting carers in palliative care, where to find help. Conclusion: The guidelines can be developed as a manual for the caregivers and for training healthcare professionals working with neurodegenerative conditions.  The Author(s) 2022.</text>
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                <text>Warrier M.G.; Thomas P.T.; Sadasivan A.; Nashi S.; Vengalil S.; Nalini A.</text>
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                <text>Journal of Patient Experience, Vol-9</text>
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                <text>All Open Access; Green Open Access</text>
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                <text>Internet of things; Remote monitoring; Transformer health monitoring system; Transformer winding deformation</text>
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                <text>Internet of Things platforms deployed on the system will exhibit numerous benefits such as real time monitoring, faster operation and cost effectiveness. A system oriented IoT platform is developed which features database connotation, web services, setup portal, cloud hosting, drivers or listener for programming languages and hardware devices. The functional parameters of transformer in electrical power system vary around the limit and beyond, which is observed by the IoT platform for remote analysis and to report deformation in the winding. The frequency response measurement from the transformer terminal unit is send to cloud database which is then fetched to remote application through IoT client. At remote monitoring tool, the diagnostic algorithm is executed to estimate the location and extent of deformation. IoT based frequency response analyzer and transformer diagnostic tools developed reports the status of the transformer health condition. Depending upon the extent of deformation, the transformer is isolated from power system.  Springer Nature Switzerland AG 2020.</text>
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                <text>Venkataswamy R.; Rao K.U.; Meena P.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-80, pp. 165-183.</text>
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                <text>Venkataswamy R., Department of Electrical &amp;amp; Electronics Engineering, Faculty of Engineering, Christ (Deemed to be University), Bangalore, India; Rao K.U., Department of Electrical &amp;amp; Electronics Engineering, R. V. College of Engineering, Bangalore, India; Meena P., Department of Electrical &amp;amp; Electronics Engineering, B. M. S. College of Engineering, Bangalore, India</text>
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