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                <text>Phishing attack detection using Machine Learning</text>
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                <text>Machine learning; Phishing; Random forest classification</text>
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                <text>Phishing is a type of digital assault, which adversely affects people where the client is coordinated to counterfeit sites and hoodwinked to screen their touchy and private data which integrates watchwords of records, monetary data, ATM pin-card data, etc. Recently safeguarding touchy records, it's fragile to cover yourself from malware or web phishing. AI is an investigation of information examination and logical investigation of calculations has demonstrated outcomes. Contradicting phishing sprinters with remarkable perception and felonious outcomes comparable as care shops, and custom against phishing approaches. This paper examines the association of Machine Literacy routes in identifying phishing assaults and records their advantages and drawbacks. There are countless Machine Learning calculations that have been dug to proclaim the relevant decision that act as against phishing apparatuses. We made a phishing section framework that extracts capacities that are expected to descry phishing. We likewise utilize numeric outline, as well as an overall investigation of customary Machine Learning methodologies comparable as Decision Tree, Random Forest, Multi-layer Perceptron's, XG Boost Classifier, SVM, Light BGM Classifier, Cat Boost Classifier, and covering grounded highlights choice, which contains the metadata of URLs and assists with deciding if a site is licit or not.  2022 The Authors</text>
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                <text>Pandiyan S S.; Selvaraj P.; Burugari V.K.; Benadit P J.; P K.</text>
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                <text>Measurement: Sensors, Vol-24</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.measen.2022.100476" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.measen.2022.100476&lt;/a&gt;
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                <text>ISSN: 26659174</text>
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                <text>Pandiyan S S., CHRIST (Deemed to Be University), Bangalore, India; Selvaraj P., School of CSE, VIT-AP University, Amaravati, India; Burugari V.K., Department of CSE, Koneru Lakshmaiah Education Foundation, K L University, Guntur, India; Benadit P J., CHRIST (Deemed to Be University), Bangalore, India; P K., Department of DSBS, SRM Institute of Science and Technology, Kattankulathur, Chennai, India</text>
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                <text>An Enhanced Pathfinder Algorithm for Optimal Integration of Solar Photovoltaics and Rapid Charging Stations in Low-Voltage Radial Feeders</text>
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                <text>Electrical distribution network; EV Charging stations; Optimization; Pathfinder algorithm; Solar systems</text>
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                <text>Most low-voltage (LV) feeders have large distribution losses, poor voltage profiles, and inadequate voltage stability margins owing to their radial construction and high R/X ratio branches, and they may not be able to handle substantial solar photovoltaics (SPVs) and EV penetration. Thus, optimal integration of SPVs and rapid charging stations (RCSs) can solve this problem. This paper offers an extended pathfinder algorithm (EPFA) with guiding elements and three followers' life lifestyle procedures based on animal foraging, exploitation, and killing. First, the EV load penetration was used to evaluate the LV feeder performance. Subsequently, the required RCSs and SPVs were appropriately integrated to match the EV load penetration and optimise feeder performance. An Indian 85-bus real-time system was used for simulations. The losses and GHG emissions increased by 150% and 80%, respectively, without the SPVs and RCS for zero-to-full EV load penetration. RCSs allocation alone reduced the losses by 40.1%, whereas simultaneous SPVs and RCSs allocation reduced the losses by 66%. However, the GHG emissions decreased by 13.7% and 54.33%, respectively. This study shows that SPVs and RCS can enhance the LV feeder performance both technically and environmentally. In contrast, EPFA outperformed the other algorithms in terms of the global solution and convergence time.  The Author(s).</text>
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                <text>Pandraju T.K.S.; Janamala V.</text>
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                <text>Journal of Solar Energy Research, Vol-8, No. 4, pp. 1680-1690.</text>
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              <elementText elementTextId="92804">
                <text>University of Tehran</text>
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                <text>&lt;a href="https://doi.org/10.22059/jser.2023.359041.1300" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.22059/jser.2023.359041.1300&lt;/a&gt;
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                <text>ISSN: 25883097</text>
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                <text>Pandraju T.K.S., Department of Electrical and Electronics Engineering, Dhanekula Institute of Engineering and Technology, Andhra Pradesh, Vijayawada, 521139, India; Janamala V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bangalore, 560074, India</text>
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                <text>Dynamic optimal network reconfiguration under photovoltaic generation and electric vehicle fleet load variability using self-adaptive butterfly optimization algorithm</text>
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          <element elementId="49">
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                <text>butterfly optimization algorithm; dynamic reconfiguration; electric vehicle fleet; electrical distribution network; power loss; renewable energy</text>
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                <text>Currently, electrical distribution networks (EDNs) have used modern technologies to operate and serve many types of consumers such as renewable energy, energy storage systems, electric vehicles, and demand response programs. Due to the variability and unpredictability of these technologies, all these technologies have brought various challenges to the operation and control of EDNs. In this case, in order to operate effectively, it is inevitable that effective power redistribution is required in the entire network. In this paper, a multi-objective based dynamic optimal network reconfiguration (DONR) problem is formulated using power loss and voltage deviation index considering the hourly variation of load, photovoltaic (PV) power, and electric vehicle (EV) fleet load in the network. This paper introduces recently introduced meta-heuristic butterfly optimization algorithm (BOA) and it's improve variant of self-adaptive method (SABOA) for solving the DONR problem. The simulation study of IEEE 33-bus EDN under different conditions has proved the effectiveness of DONR, and its adoptability for real-time applications. In addition, by comparing different performance indicators (such as mean, standard deviation, variance, and average calculation time) of 50 independently run simulations, the efficiency of SABOA can be evaluated compared with other heuristic methods (HMs). Comparative studies show that SABOA is better than PSO, TLBO, CSA and FPA in the frequent occurrence of global optimal values.   2021 Walter de Gruyter GmbH, Berlin/Boston 2021.</text>
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                <text>Pandraju T.K.S.; Janamala V.</text>
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                <text>International Journal of Emerging Electric Power Systems, Vol-22, No. 4, pp. 423-437.</text>
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                <text>De Gruyter Open Ltd</text>
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                <text>&lt;a href="https://doi.org/10.1515/ijeeps-2021-0009" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1515/ijeeps-2021-0009&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107230791&amp;amp;doi=10.1515%2Fijeeps-2021-0009&amp;amp;partnerID=40&amp;amp;md5=3b3a492733af519b75a5c6a5eb7b4399" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107230791&amp;amp;doi=10.1515%2fijeeps-2021-0009&amp;amp;partnerID=40&amp;amp;md5=3b3a492733af519b75a5c6a5eb7b4399&lt;/a&gt;</text>
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                <text>ISSN: 21945756</text>
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                <text>Pandraju T.K.S., Department of Electrical and Electronics Engineering, Dhanekula Institute of Engineering and Technology, Andhra Pradesh, Vijayawada, 521 139, India; Janamala V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560 074, India</text>
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                <text>Self-adaptive Butterfly Optimization for Simultaneous Optimal Integration of Electric Vehicle Fleets and Renewable Distribution Generation</text>
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                <text>Effective optimal network reconfiguration; Loss minimization; Radial distribution system; Self-adaptive butterfly optimization algorithm; Solar photovoltaic system</text>
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                <text>Fuel prices and environmental concerns have prompted an increase in the use of electric vehicle (EV) technology in recent years. Charging stations (CSs) are a great way to support this shift to sustainability. This has increased the demand for EV charging on electrical distribution networks (EDNs). However, optimal EV charging stations along with renewable energy sources (RES) integration can maintain EDN performance. This paper proposes a novel hybrid approach based on self-adaptive butterfly optimization algorithm (SABOA) for optimal integration of EV CSs and RES problems under various EV load growth scenarios. A multi-objective function is created from distribution losses, GHG emissions, and VSI. The ideal locations for CSs and RES are found using SABOA while minimizing the proposed multi-objective function. The simulation results on IEEE 33-bus EDN validate the suggested technique's superiority in terms of global optima. This type of hybrid strategy is required for optimal real-time integration of EV CSs and RES, taking into account emerging high EV load penetrations.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-608, pp. 777-784.</text>
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                <text>Pandraju T.K.S., Department of Electrical and Electronics Engineering, Dhanekula Institute of Engineering and Technology, Andhra Pradesh, Vijayawada, 521 139, India; Janamala V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to be University), Karnataka, Bengaluru, 560074, India</text>
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                <text>In this paper, a new and simple nature-inspired meta-heuristic search algorithm, namely butterfly optimization algorithm (BOA), is proposed for solving the optimal location and sizing of solar photovoltaic (SPV) system. An objective function for distribution loss minimization is formulated and minimized via optimally allocating the SPV system on themain feeder. At the first stage, the computational efficiency of BOA is compared with various other similar works and highlights its superiority in terms of global solution. In thesecond stage, the interoperability requirement of SPV system while determining the location and size of SPV system among multiple laterals in a distribution system is solved without compromises in radiality constraint. Various case studies on standard IEEE 33-bus system have shown the effectiveness of proposed concept of interline-photovoltaic (I-PV) system in improving the distribution system performance in terms of reduced losses and improved voltage profile via redistributing the feeder power flows effectively.  2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-204, pp. 201-209.</text>
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                <text>Pandraju T.K.S., Department of Electrical and Electronics Engineering, Dhanekula Institute of Engineering &amp;amp; Technology, Vijayawada, Andhra Pradesh, 521139, India; Janamala V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to be University), Bangalore, Karnataka, 560074, India</text>
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                <text>A study of consumers' attitude towards online private label brands using the Tri - Component model</text>
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                <text>Online private label products seem to be a promising and profitable deal for the Indian online retailers. The purpose of this paper was to understand the consumers' attitude and buying behaviour towards online private label brands. For this purpose, we empirically tested a model comprising of variables such as cognitive, affective, behavioural, purchase intention, and actual buying behaviour. Data were gathered by using a schedule. A sample of 400 respondents was gathered, and the hypotheses were tested by performing structural equation modelling. The findings highlighted that the cognitive, affective, and behavioural factors of attitude influenced each other strongly as well as the purchase intention. In addition, the results obtained revealed that purchase intention led to the buying of online private label brands. It is expected that the findings of this study will enable the marketers of online private label brands to be more informed about the consumers' attitude formation process. Furthermore, it will help them to understand the areas related to private label brands, which need their attention.  1964-2018 Associated Management Consultants.</text>
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                <text>Indian Journal of Marketing, Vol-48, No. 5, pp. 7-20.</text>
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                <text>International Journal of Engineering Research and Technology, Vol-12, No. 3, pp. 440-445.</text>
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                <text>An efficient load balancing in cloud computing using hybrid Harris hawks optimization and cuckoo search algorithm</text>
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                <text>Cloud computing; Hybrid Harris hawks optimization-cuckoo search algorithm; Load balancing; Quality of service; Service level agreement; Task scheduling</text>
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                <text>Cloud computing has rapidly emerged as a burgeoning research field in recent times. However, despite this growth, a comprehensive examination of this domain reveals persistent issues in the application of cloud-based systems concerning workload distribution. The abundance of resources and virtual machines (VMs) within cloud computing underscores the importance of efficient task allocation as a critical process. Within the infrastructure as a service (IaaS) architecture, load balancing (LB) remains a pivotal but challenging task. The occurrence of overloaded or underloaded hosts/servers during cloud access is undesirable, as it leads to operational delays and system performance degradation. To address LB issues effectively, it is imperative to deploy a proficient access scheduling algorithm capable of distributing tasks across the available resources. A novel approach was introduced by combining the Harris hawks optimization and cuckoo search algorithm (HHO-CSA), with a specific focus on critical service level agreement (SLA) parameters, particularly deadlines, to uphold LB in a cloud environment. The primary objective of the hybrid HHO-CSA methodology is to provide task attributes, resource allocation, VMs prioritization, and quality of service (QoS) to clients within cloud computing applications. The outcome analysis reveals that the proposed hybrid HHO-CSA algorithm results in a resource utilization reduction of 52%, with an execution time of 529.84 ms and a makespan of 638.88 ms. These values outperform those of existing SLA-based LB algorithms. Effective task scheduling plays a pivotal role in ensuring the seamless execution of tasks within a cloud system, while LB significantly aligns with the SLAs available to users. Drawing insights from the existing literature, the suggested hybrid HHO-CSA method addresses the research gap by effectively mitigating the challenges.  2023, Accent Social and Welfare Society. All rights reserved.</text>
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                <text>Pani A.K.; Manohar M.; Thomas M.; Kumar P.</text>
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                <text>International Journal of Advanced Technology and Engineering Exploration, Vol-10, No. 105, pp. 1050-1062.</text>
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                <text>All Open Access; Gold Open Access</text>
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                <text>Pani A.K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Manohar M., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Thomas M., School of Computer Science, RV University, Bengaluru, India; Kumar P., Department of Computer Science and Engineering, Motihari College of Engineering, Bihar, India</text>
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                <text>Inverse Hilbert Fractal-Metamaterial Rings for Microstrip Antennas and Wideband Applications</text>
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                <text>A Novel Metamaterial (MTM) property is obtained using a fractal pattern known as Inverse Hilbert. The Mu-negative(MNG) characteristics have been recovered by adopting NRW method. This MTM characteristic is studied for 2.45 GHz using FR4 epoxy as substrate. The dimension of the substrate is 30mm36mm 1.6mm. This fractal metamaterial structure can be amalgamated with an optimized Microstrip antenna (MSA) for improvement in antenna parameters and can be used for RF energy harvesting.  2022 IEEE.</text>
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                <text>Panicker R.; Suganthi S.</text>
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                <text>2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings, pp. 1398-1399.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Panicker R., Christ University, Bangalore, India; Suganthi S., Christ University, Bangalore, India</text>
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                <text>Progression of Metamaterial for Microstrip Antenna Applications: A Review</text>
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                <text>Fractal; Metamaterial; Nicolson-Ross-Weir (NRW) method; Split ring resonators (SRRs)</text>
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                <text>This article provides an overview of the evolution of metamaterials (MTM) and all the aspects related to metamaterial development for antenna applications. It will be a useful collection of information for antenna researchers working in metamaterials applications. It gives an insight into the various metamaterial structures utilized along with miniature antenna designs. Different types of design parameters studied by the previous researchers are showcased to understand better perception of the metamaterial usage.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Smart Innovation, Systems and Technologies, Vol-289, pp. 193-201.</text>
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                <text>Panicker R., Christ University, Bangalore, India; Suganthi S., RF &amp;amp; Microwave Research Laboratory, Electronics, and Communication Engineering, Christ University, Bangalore, India</text>
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                <text>Successful turnarounds: the role of appropriate entrepreneurial strategies</text>
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                <text>Causes of organizational decline; Organizational decline; Successful turnarounds; Turnaround strategies</text>
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                <text>Purpose  The purpose of this paper is to report on a research study aimed at comparing the causes of organisational decline and turnaround strategies involved in cases of successful and unsuccessful turnarounds, with a view to identifying the differences, if any, between the two groups, which in turn is expected to provide useful information to academics, practitioners and policy makers. Design/methodology/approach  Since turnaround is a business phenomenon of general interest, their stories are often published in business periodicals, which are a rich source of data on them. In order to tap this data source, the present paper employed a method of content analysis for the proposed investigation on the cause of organisational decline and turnaround strategies used. In order to quantify the data, a three-point scale was developed, where the presence of a cause/strategy is rated as 3, its ambivalence as 2 and its absence as 1, whose validity was assessed through the inter-rater agreement indices. The data thus generated are amenable to statistical analyses, using which the more commonly prevalent causes of organisational decline and the strategies commonly employed for turnaround by the successful and unsuccessful companies are identified. Findings  The findings of the present study have generated a few useful insights. First, the primary causes for organisational decline are the internal weaknesses of the organisation; in fact the external changes can adversely affect the organisation only if it is internally weak. Second, organisational decline caused by multiple factors (which is usually the case) can be managed effectively by adopting a variety of strategies; hence a single-pronged strategy is often found to be ineffective. Third, the more successful turnarounds had a diverse portfolio of strategies including those of institution-building, often employed in a phased manner, consistent with the stage theories of turnaround. Research limitations/implications  The limitations of this research arise mainly from the generation of data from published sources and the consequent biases, which can be managed, to a large extent, by using multiple sources for the same case for reducing the publishers biases as well as by having multiple raters for identifying the researchers biases, if any. Originality/value  The study has highlighted the need for addressing the internal causes of organisational decline on a priority-basis rather than blaming the external factors, besides pointing to the need for adopting a variety of strategies for dealing with the diversity of causes affecting the organisations health, particularly the need for institutionalising the changes. These findings can be of help especially to turnaround managers and policy-makers in dealing with organisational decline and thus contribute to the creation and enhancement of economic value.  2015,  Emerald Group Publishing Limited.</text>
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                <text>Panicker S.; Manimala M.J.</text>
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                <text>Journal of Strategy and Management, Vol-8, No. 1, pp. 21-40.</text>
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                <text>Emerald Group Publishing Ltd.</text>
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                <text>&lt;a href="https://doi.org/10.1108/JSMA-06-2014-0050" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1108/JSMA-06-2014-0050&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937562038&amp;amp;doi=10.1108%2FJSMA-06-2014-0050&amp;amp;partnerID=40&amp;amp;md5=beb216860c52ab84d6458c9c627c8395" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937562038&amp;amp;doi=10.1108%2fJSMA-06-2014-0050&amp;amp;partnerID=40&amp;amp;md5=beb216860c52ab84d6458c9c627c8395&lt;/a&gt;</text>
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                <text>ISSN: 1755425X</text>
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                <text>Panicker S., Christ University, Bangalore, India; Manimala M.J., Indian Institute of Management, Bangalore, India</text>
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                <text>A Scoping Review on Integration of Electroencephalogram Neurofeedback Training for Alcohol Use Disorder: Clinical and Neurocognitive Outcomes</text>
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                <text>alcohol use disorder; neurofeedback training; relapse; response inhibition; stress</text>
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                <text>Background. The conventional treatment for alcohol use disorder (AUD) consists of dual treatment encompassing pharmacotherapy and psychotherapy. Nonetheless, the impact of these treatments on clinical and neurocognitive outcomes is only low to medium efficacy. Research studies substantiate the integration of electroencephalogram neurofeedback training (EEG-NFT) as an add-on tool with significant improvements in clinical and neurocognitive outcomes. Methods. A scoping review of the existing literature on EEG-NFT and AUD, which are open access, including review papers and empirical studies in the English language, and with human subjects are deemed worthy of the scope of this study. The keywords electroencephalogram neurofeedback training, alcohol use disorder, stress, neurocognition, and relapse were used. The primary sources of the literature search were Science Direct, Scopus, PubMed, and Google Scholar. A total of 35 articles have been included in the scoping review. Studies from the last 15 years were considered for the same. Results. This review revealed that EEG-NFT is a promising tool with significant improvements in stress levels, cognitive deficits, and relapse rates for individuals with AUD when used in integration with conventional treatments. Conclusion. Chronic alcohol use affects cognitive functions, escalates relapse rate, and increases stress experienced by the individual. The present study highlights the significance of NFT as a potent add-on treatment modality to improve clinical and cognitive outcomes, thereby facilitating abstinence and reducing relapse rates in individuals with AUD. Copyright:  2023.</text>
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                <text>Panicker S.G.; Bennett C.N.</text>
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                <text>NeuroRegulation, Vol-10, No. 3, pp. 179-185.</text>
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              <elementText elementTextId="93262">
                <text>International Society for Neurofeedback and Research</text>
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                <text>&lt;a href="https://doi.org/10.15540/nr.10.3.179" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.15540/nr.10.3.179&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174577974&amp;amp;doi=10.15540%2Fnr.10.3.179&amp;amp;partnerID=40&amp;amp;md5=0666157d48c10b47ea7916ba6c28e1fd" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174577974&amp;amp;doi=10.15540%2fnr.10.3.179&amp;amp;partnerID=40&amp;amp;md5=0666157d48c10b47ea7916ba6c28e1fd&lt;/a&gt;</text>
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              <elementText elementTextId="93265">
                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 23730587</text>
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                <text>Panicker S.G., Department of Psychology, CHRIST (Deemed to be University), Bangalore, India; Bennett C.N., Department of Psychology, CHRIST (Deemed to be University), Bangalore, India</text>
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                <text>A Quasi-Experimental Study on the Effectiveness of Integrated Electroencephalogram Neurofeedback Training and Group Psychotherapy for Harmful Alcohol Use: Neurocognitive and Clinical Outcomes</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="85623">
                <text>craving; executive functions; harmful alcohol use; neurofeedback; psychotherapy; stress</text>
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                <text>Introduction. This study investigates the efficacy of integrating electroencephalogram (EEG) neurofeedback training and group psychotherapy for individuals with harmful alcohol use (AUDIT-10 scores 1013). Methods. Seventy-six participants were purposively sampled and divided into treatment (EEG neurofeedback training and group psychotherapy) and control groups. Baseline assessments measured alcohol consumption (AUDIT-10), stress (perceived stress scale [PSS]), neurocognition (NIMHANS neuropsychological battery), craving (PACS), and visual analog scale. The treatment group underwent 20 sessions of EEG neurofeedback (Peniston-Kulkosky and Scott-Kaiser modification protocols) and four sessions of group psychotherapy (motivational interviewing [MI], psychoeducation). Result/Discussion. A repeated measures ANOVA showed significant improvement in postcondition scores for the treatment group compared to controls, who exhibited deterioration over time. The study provides evidence supporting the efficacy of integrated EEG neurofeedback training and group psychotherapy in mitigating harmful alcohol use progression. Conclusion. By addressing stress, cognition, and cravings, this intervention offers crucial support to individuals with problematic drinking.  2024. Panicker et al.</text>
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                <text>Panicker S.G.; George T.S.; Bennett C.N.</text>
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                <text>NeuroRegulation, Vol-11, No. 3, pp. 255-273.</text>
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                <text>International Society for Neurofeedback and Research</text>
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                <text>&lt;a href="https://doi.org/10.15540/nr.11.3.255" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.15540/nr.11.3.255&lt;/a&gt;
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              <elementText elementTextId="85630">
                <text>All Open Access; Gold Open Access</text>
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                <text>An unglazed transpired solar collector is a system that can leverage the abundant solar energy for various purposes. The solar collector is available in flat or corrugated form and is seen to be installed as an exterior layer of building facades. The cladding thus made absorbs radiation from the sun and heats up air being sucked by fan and flowing through perforations. In this paper, the focus has been to understand the correlation of plate temperature, exit temperature, the velocity distribution in the chamber and perforation location when air flows past a flat unglazed transpired solar collector (UTC). The establishment of correlations was carried out in the dataset of flow variables obtained after solving the problem using Navier-Stokes (NS) equations along with the standard k-? turbulence model and shear stress transport (SST) k-? model. An attempt has also been made to compute Pearsons correlation coefficient of any two flow variables to understand their strong and weak correlations. A linear regression analysis has been done to predict the response variables against the response obtained in CFD solver by using an open source software Rstudio . A strong correlation among cavity vertical velocity, perforation location and temperature has been established. From the study, it is noted that the location of a perforation has a strong correlation with the cavity vertical velocity and a weak correlation exists with temperature and plate temperature.  2020, Pushpa Publishing House. All rights reserved.</text>
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                <text>Panigrahi S.P., Department of Mechanical Engineering, Faculty of Engineering, Christ (Deemed to be University), Bangalore, India; Maharana S.K., Department of Aeronautical Engineering, Acharya Institute of Technology, Bangalore, India</text>
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                <text>An unglazed transpired solar collector is a system that can leverage the abundant solar energy for various purposes. The solar collector is available in flat or corrugated form and is seen to be installed as an exterior layer of building facades. The cladding thus made absorbs radiation from the sun and heats up air being sucked by fan and flowing through perforations. In this research the focus has been to understand the correlation of plate temperature, exit temperature, the velocity distribution in the chamber and perforation location when air flows past an unglazed transpired solar collector (UTC). The establishment of correlations was carried out in the dataset of flow variables obtained after solving the problem using Navier-Stokes (NS) equations along with standard two-equation (k-?) turbulence models and Shear Stress Transport (SST ) k-? models for turbulent flow. The same problem was also solved using NS equation using laminar model. An attempt has also been made to compute Pearsons correlation coefficient of any two variables to understand their strong and weak correlations. A linear regression analysis was done through an open source software Rstudio for a dataset produced during the computational modeling using a commercial CFD solver, Ansys Fluent. At the end a Monte Carlo simulation has been done to predict the likelihood of using the flat UTC for drying as well as to understand the dependency of system efficiency on plate exit temperature, suction velocity and freestream temperature.  BEIESP.</text>
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                <text>Graph Mining is becoming one of the most dominant fields of research. There are plenty methods to index, re-index and to search the features throughout the index but still from the literature study there is no specific frame work which can sum up all three so that indexing and updating the index with new feature can be done in consistent intervals according to the arrival of new features. PLANO is the frame work which has the latest algorithms to look into the data and index. In this paper, Time and Memory efficiency of the proposed algorithms in the PLANO framework is tested statistically and compared with the existing algorithms memory and time usage.  Research India Publications.</text>
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                <text>International Journal of Applied Engineering Research, Vol-10, No. 12, pp. 31613-31628.</text>
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                <text>Research India Publications</text>
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                <text>ISSN: 9734562</text>
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                <text>Pankaj Moses Monickaraj A., Dept. of Computer Science and Engg, Christ University, India; Raj Kumar J.B., Dept. of Computer Science and Engg, Bharathiar University, India; Vivekanandan K., BSMED, Bharathiar University, India; Boopalan E.D., Dept. of Statistics, Bharathiar University, India</text>
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                <text>Large power factors in wide band gap semiconducting rFeO3 materials for high-temperature thermoelectric applications</text>
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                <text>Boltzmann transport equation; Density functional theory; First-principles calculations; Orthoferrites; Thermoelectricity</text>
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                <text>While most of the thermoelectric materials work well only at low and mid temperatures, high-temperature thermoelectric materials (T &amp;gt; 900 K) are equally important for the operation of deep-spacecraft missions, nuclear reactors, and high-temperature industrial reactors. To accomplish this demand, this work provides insights into wide band gap semiconducting RFeO3 (rare-earth orthoferrites) for high-temperature thermoelectric applications. Using the first-principles density functional theory calculations, we have demonstrated the coexistence of extremely flat and corrugated flat bands near the Fermi region in a wide band gap material. The presence of such features enhances and sustains the thermopower, electrical conductivity, and power factor, which are the crucial factors for the efficiency of thermoelectric materials. Semiclassical Boltzmann formalism was then employed to study the transport properties of four orthorhombic RFeO3 materials (R = Pr, Nd, Sm, and Gd). Our results reveal high Seebeck coefficients (thermopower) along with the large electrical conductivities over the high hole doping carrier concentration and in the high-temperature region (T &amp;gt; 900 K). Furthermore, significantly large power factors are obtained with very low theoretical minimum lattice thermal conductivity in the range 1.41?1.51 W m?1 K?1. These huge power factors directly suggest the maximum power output in RFeO3, which we believe is a more appropriate performance index than the figure of merit, especially for high-temperature thermoelectric applications. We also emphasize that the outcomes of our work would be certainly useful for experimentalists in designing high-temperature thermoelectric materials.  2020 American Chemical Society</text>
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                <text>Panneerselvam I.R.; Baldo C., III; Sahasranaman M.; Murugesan S.; Rangaswamy N.; Rajendra Pai S.D.K.; Selvarathinam Y.</text>
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                <text>ACS Applied Energy Materials, Vol-3, No. 11, pp. 11193-11205.</text>
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                <text>American Chemical Society</text>
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                <text>&lt;a href="https://doi.org/10.1021/acsaem.0c02128" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1021/acsaem.0c02128&lt;/a&gt;
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                <text>ISSN: 25740962</text>
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                <text>Panneerselvam I.R., Young Scientist Training Program Fellow, Asia Pacific Center for Theoretical Physics, Pohang, 37673, South Korea; Baldo C., III, Young Scientist Training Program Fellow, Asia Pacific Center for Theoretical Physics, Pohang, 37673, South Korea, Department of Physics, Mapua University, Manila, 1002, Philippines; Sahasranaman M., Chemistry Division, School of Advanced Sciences, Vellore Institute of Technology (VIT), Chennai, 600127, India; Murugesan S., PG and Research Department of Physics, Paavendhar College of Arts and Science, Salem, Tamil Nadu, 636121, India; Rangaswamy N., Division of Physics, School of Advanced Sciences, Vellore Institute of Technology (VIT), Chennai, 600127, India; Rajendra Pai S.D.K., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, Karnataka, 560029, India; Selvarathinam Y., Department of Physics, Loyola College of Arts and Science, Namakkal, Tamil Nadu, 636 202, India</text>
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