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                <text>Training multi-layer perceptron with enhanced brain storm optimization metaheuristics</text>
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                <text>Algorithm hybridization; Artificial neural network; Brain storm optimization; Metaheuristics; Optimization</text>
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                <text>In the domain of artificial neural networks, the learning process represents one of the most challenging tasks. Since the classification accuracy highly depends on the weights and biases, it is crucial to find its optimal or suboptimal values for the problem at hand. However, to a very large search space, it is very difficult to find the proper values of connection weights and biases. Employing traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local optima. Most commonly, back-propagation is used for multi-layer-perceptron training and it can lead to vanishing gradient issue. As an alternative approach, stochastic optimization algorithms, such as nature-inspired metaheuristics are more reliable for complex optimization tax, such as finding the proper values of weights and biases for neural network training. In this work, we propose an enhanced brain storm optimization-based algorithm for training neural networks. In the simulations, ten binary classification benchmark datasets with different difficulty levels are used to evaluate the efficiency of the proposed enhanced brain storm optimization algorithm. The results show that the proposed approach is very promising in this domain and it achieved better results than other state-of-the-art approaches on the majority of datasets in terms of classification accuracy and convergence speed, due to the capability of balancing the intensification and diversification and avoiding the local minima. The proposed approach obtained the best accuracy on eight out of ten observed dataset, outperforming all other algorithms by 1-2% on average. When mean accuracy is observed, the proposed algorithm dominated on nine out of ten datasets.  2022 Tech Science Press. All rights reserved.</text>
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                <text>Bacanin N.; Alhazmi K.; Zivkovic M.; Venkatachalam K.; Bezdan T.; Nebhen J.</text>
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                <text>Computers, Materials and Continua, Vol-70, No. 2, pp. 4199-4215.</text>
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              <elementText elementTextId="114018">
                <text>Tech Science Press</text>
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                <text>2022-01-01</text>
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                <text>&lt;a href="https://doi.org/10.32604/cmc.2022.020449" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.32604/cmc.2022.020449&lt;/a&gt;
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                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 15462218</text>
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                <text>Bacanin N., Singidunum University, Danijelova, Belgrade, 11000, Serbia; Alhazmi K., National Center for Robotics and IoT, Communication and Information Technology Research Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh, 12371, Saudi Arabia; Zivkovic M., Singidunum University, Danijelova, Belgrade, 11000, Serbia; Venkatachalam K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Bezdan T., Singidunum University, Danijelova, Belgrade, 11000, Serbia; Nebhen J., Prince Sattam Bin Abdulaziz University, College of Computer Engineering and Sciences, Alkharj, 11942, Saudi Arabia</text>
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                <text>Transfer Learning-Based Osteoporosis Classification Using Simple Radiographs</text>
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          <element elementId="49">
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            <description>The topic of the resource</description>
            <elementTextContainer>
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                <text>BMD; CNN models; DXA; X-rays</text>
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                <text>Osteoporosis is a condition that affects the entire skeletal system, resulting in a decreased density of bone mass and the weakening of bone tissues micro-architecture. This leads to weaker bones that are more susceptible to fractures. Detecting and measuring bone mineral density has always been a critical area of focus for researchers in the diagnosis of bone diseases such as osteoporosis. However, existing algorithms used for osteoporosis diagnosis encounter challenges in obtaining accurate results due to X-ray image noise and variations in bone shapes, especially in low-contrast conditions. Therefore, the development of efficient algorithms that can mitigate these challenges and improve the accuracy of osteoporosis diagnosis is essential. In this research paper, a comparative analysis was conducted Assessing the accuracy and efficiency of the latest deep learning CNN model, such as VGG16, VGG19, DenseNet121, Resnet50, and InceptionV3 in detecting to Classify Normal and Osteoporosis cases. The study employed 830 X-ray images of the Spine, Hand, Leg, Knee, and Hip, comprising Normal (420) and Osteoporosis (410) cases. Various performance metrics were utilized to evaluate each model. The findings indicate that DenseNet121 exhibited superior performance with an accuracy rate of 93.4% Achieving an error rate of 0.07 and a validation loss of only 0.57 compared with other models considered in this study.  2023, International journal of online and biomedical engineering. All Rights Reserved.</text>
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                <text>Dodamani P.S.; Danti A.</text>
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              <elementText elementTextId="100977">
                <text>International journal of online and biomedical engineering, Vol-19, No. 8, pp. 66-87.</text>
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              <elementText elementTextId="100978">
                <text>International Association of Online Engineering</text>
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            <name>Date</name>
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                <text>2023-01-01</text>
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                <text>&lt;a href="https://doi.org/10.3991/ijoe.v19i08.39235" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.3991/ijoe.v19i08.39235&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164622680&amp;amp;doi=10.3991%2Fijoe.v19i08.39235&amp;amp;partnerID=40&amp;amp;md5=b3a7889c49ececa313337be7417578f5" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164622680&amp;amp;doi=10.3991%2fijoe.v19i08.39235&amp;amp;partnerID=40&amp;amp;md5=b3a7889c49ececa313337be7417578f5&lt;/a&gt;</text>
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            <elementTextContainer>
              <elementText elementTextId="100981">
                <text>All Open Access; Gold Open Access</text>
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          </element>
          <element elementId="46">
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            <description>A related resource</description>
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              <elementText elementTextId="100982">
                <text>ISSN: 26268493</text>
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            <name>Format</name>
            <description>The file format, physical medium, or dimensions of the resource</description>
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              <elementText elementTextId="100983">
                <text>Online</text>
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            <description>A language of the resource</description>
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              <elementText elementTextId="100984">
                <text>English</text>
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                <text>Dodamani P.S., Christ University, Karnataka, Bangalore, India; Danti A., Christ University, Karnataka, Bangalore, India</text>
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                <text>Transference of Love-type Wave Through Cobalt Ferrite Cofe2O4 Layer Structure, Governed by an Imperfect Interface</text>
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                <text>An analytical discussion of the wave transmission in a piezomagnetic (Cobalt ferrite) thin plate resting on an elastic substrate is presented in the problem. It is presumed that the geometrys interface is not ideal. The flaw of the considered structure is used to describe by following the linear spring model. The calculative method of the upper material is Direct Sturm-Liouville. Dispersion relations are drived for each of the magnetically open and magnetically short cases. Love-type wave velocity profiles have been depicted on graphs for various influencing factors, such as heterogeneity in the substrate, layer thickness, and interface imperfections. It has been demonstrated that raising these parameters raises the Love waves phase velocity. Furthermore, it is found that compared to substrate heterogeneity, layer thickness has less of an impact on the waves velocity profile. Additionally, it has been shown how the aforementioned cases compare when imperfect parameters are varied. It is discovered that the velocity in the open case is greater than that in the short case. The results have potential applications in the design of piezomagnetic semiconductor devices controlled by electric fields and are of great significance for developing surface acoustic wave (SAW) gyroscopes.  2024 American Institute of Physics Inc.. All rights reserved.</text>
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                <text>Seema; Singhal A.</text>
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              <elementText elementTextId="160819">
                <text>AIP Conference Proceedings, Vol-3242, No. 1</text>
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              <elementText elementTextId="160820">
                <text>American Institute of Physics</text>
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                <text>2024-01-01</text>
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                <text>&lt;a href="https://doi.org/10.1063/5.0234299" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1063/5.0234299&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206373677&amp;amp;doi=10.1063%2F5.0234299&amp;amp;partnerID=40&amp;amp;md5=a8923976a2d64de49895f2a90c19794e" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206373677&amp;amp;doi=10.1063%2f5.0234299&amp;amp;partnerID=40&amp;amp;md5=a8923976a2d64de49895f2a90c19794e&lt;/a&gt;</text>
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                <text>Restricted Access</text>
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                <text>ISSN: 0094243X</text>
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              <elementText elementTextId="160826">
                <text>English</text>
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                <text>Seema, Christ University, Karnataka, Bengaluru, 560029, India; Singhal A., Christ University, Karnataka, Bengaluru, 560029, India</text>
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                <text>Transformation of hydrocarbon soot to graphenic carbon nanostructures</text>
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              <elementText elementTextId="133042">
                <text>Camphor; Graphenic carbon; Hydrocarbon soot; Kerosene; Liquid paraffin</text>
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                <text>Graphenic carbon nanostructures were synthesized from different precursors of petroleum and agricultural origin by oxidative scissoring. In the present study soot, an environmental pollutant is converted to a value-added product by facile synthesis techniques. The physicochemical changes of the nanostructures are investigated by means of XRD, AFM, FTIR, Raman spectroscopy, XPS analyses SEM-EDS and TEM analysis. XRD analysis confirms the formation of few layer oxidized carbon nanostructures with smaller lateral dimensions. Raman spectra reveal the existence of graphenic layer with a fewer defect. AFM and SEM analyses reveal the formation of stacked tiny fragments of graphenic carbon lamellae. XPS and IR analyses confirm the incorporation of oxygen functionalities into the carbon backbone.  2018 by the authors.</text>
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                <text>Biointerface Research in Applied Chemistry, Vol-8, No. 3, pp. 3187-3192.</text>
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                <text>ISSN: 20695837</text>
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                <text>Krishnan R., Materials Research Laboratory, Department of Physics and electronics, Christ University, Bengaluru, Karnataka, India; Balachandran M., Materials Research Laboratory, Department of Physics and electronics, Christ University, Bengaluru, Karnataka, India</text>
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                <text>Transformation of India as investor of outward fdi: A systematic investigation of literature</text>
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                <text>Besides the economic transformation and industrial up-gradation, Indian enterprises have steadily intensified their overseas investment venture during recent years. A systematic literature review performed to inspect the strategic motives and Outward FDI (OFDI) impact on emerging economies like India. This paper explores relevant theories, strategic rationale, and economic policies that propel the present OFDI trend from India. The effort taken by the Indian government to promote innovations were Cross border commercial and industrial collaboration. These efforts flagged the way for more Outward FDI possibilities in the future (Welch, 1988). This study comprises the literature works till the year 2019, which includes research journals and reports. The analysis observes that knowledge-based industries drive India's Outward FDI and examine whether knowledge-based industries contribute to sustaining long-term domestic and international growth (Pradhan J.P., 2005; Narayanan, 2016).  Indian Institute of Finance.</text>
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                <text>Sukanya R.; Suresh G.</text>
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                <text>Finance India, Vol-35, No. 3, pp. 979-988.</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115155537&amp;amp;partnerID=40&amp;amp;md5=ab1e78e46fce0073a56d23d65021f216" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115155537&amp;amp;partnerID=40&amp;amp;md5=ab1e78e46fce0073a56d23d65021f216&lt;/a&gt;</text>
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                <text>ISSN: 9703772</text>
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                <text>Sukanya R., NMKRV College for Women and PhD. Research Scholar, CHRIST (Deemed to be University), 45/1, 22nd Cross, Jayanagar, III Block, Bengaluru, Karnataka, 560011, India; Suresh G., CHRIST (Deemed to be University), Hosur Road, Bhavani Nagar, S.G. Palya, Central Campus, Bangalore, Karnataka, 560029, India</text>
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                <text>Transformational educational leaders inspire school educators commitment</text>
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                <text>leadership styles; personal commitment; school education; self-development; student development</text>
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                <text>Introduction: Transformational school leaders play an important role in promoting educational innovation and restructuring by creating a vision for the future, building a culture of collaboration, and empowering others to become leaders themselves. Through their leadership style, they inspire and motivate others to work towards a common goal, leading to positive change and growth within the educational system. The aim of this study is to measure the impact of transformational leadership on various types of commitment that school teachers have in Bengaluru, India. Methods: A survey was conducted using standardised instruments to measure the leadership style of principals and personal commitment of teachers. The data was collected from 1,173 school teachers through a questionnaire and analysed using SPSS V23 statistical software. Results: The study found that transformational leadership had a significant impact on the different types of commitment that teachers possess in school education. The three domains of commitment - commitment towards the institution, student development, and self-development - were positively influenced by transformational leadership. Discussion: Transformational school leaders play an important role in promoting educational innovation and restructuring by creating a vision for the future, building a culture of collaboration, and empowering others to become leaders themselves. This study provides evidence that transformational leadership has a positive impact on different types of commitment among school teachers in Bengaluru, India. Leaders of school management are advised to take into account the three domains of commitment of their teachers to facilitate organisational learning through more integrative methods. Copyright  2023 Kareem, Patrick, Prabakaran, B, Tantia, M. P. M. and Mukherjee.</text>
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                <text>Kareem J.; Patrick H.A.; Prabakaran N.; Valarmathi B.; Tantia V.; Pramod Kumar M.P.M.; Mukherjee U.</text>
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                <text>Frontiers in Education, Vol-8</text>
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                <text>Frontiers Media S.A.</text>
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                <text>&lt;a href="https://doi.org/10.3389/feduc.2023.1171513" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.3389/feduc.2023.1171513&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160079695&amp;amp;doi=10.3389%2Ffeduc.2023.1171513&amp;amp;partnerID=40&amp;amp;md5=cd1c6d83b5420ae2d5fdb47e6c257202" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160079695&amp;amp;doi=10.3389%2ffeduc.2023.1171513&amp;amp;partnerID=40&amp;amp;md5=cd1c6d83b5420ae2d5fdb47e6c257202&lt;/a&gt;</text>
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              <elementText elementTextId="101415">
                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 2504284X</text>
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                <text>Kareem J., School of Education, Christ University, Bengaluru, India; Patrick H.A., CMS Business School, Jain University, Bengaluru, India; Prabakaran N., CMS Business School, Jain University, Bengaluru, India; Valarmathi B., School of Education, Christ University, Bengaluru, India; Tantia V., School of Education, Christ University, Bengaluru, India; Pramod Kumar M.P.M., School of Education, Christ University, Bengaluru, India; Mukherjee U., CMS Business School, Jain University, Bengaluru, India</text>
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          <element elementId="50">
            <name>Title</name>
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            <elementTextContainer>
              <elementText elementTextId="109398">
                <text>Transformational Impact of COVID-19 on Savings and Spending Patterns of Indian Rural Households</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="109399">
                <text>COVID-19; financial strategy; rural households; savings motive; spending pattern</text>
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            <description>An account of the resource</description>
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                <text>COVID-19 has spread across the globe at a shocking level and significantly affects the world economy. The pandemic has significantly impacted rural households, the primary workforce for industrialized urban areas, in every sector of rural businesses, including agriculture. Furthermore, the dearth of employment in the primary industry has also adversely influenced rural inhabitants livelihood and financial decisions. COVID-19 changed the perception of people regarding their income and expenditure. This study is intended to analyse the transformation of savings and spending of rural households during COVID-19. A questionnaire was developed using a Likert scale to elicit study variables, and the collected data were analysed using structural equation modelling. The results showed that all types of savings had a positive and significant relationship with the savings motive of rural households during COVID-19. Further, customary and spontaneous spending had a positive and significant relationship spending pattern of rural households. Rural inhabitants were interested in compromising their spending and other forms of savings to have more emergency savings. Earlier studies have examined either the savings or the spending pattern of rural households, and studies on both savings and spending by rural households are very few. The present study thus adds to the existing literature in the field.  The Author(s) 2022.</text>
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                <text>Gopal S.; Mallyasami P.</text>
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                <text>SAGE Open, Vol-12, No. 1</text>
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                <text>SAGE Publications Inc.</text>
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                <text>&lt;a href="https://doi.org/10.1177/21582440221079885" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1177/21582440221079885&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126583507&amp;amp;doi=10.1177%2F21582440221079885&amp;amp;partnerID=40&amp;amp;md5=13c38bf16e285d7b0ea764a4560a5748" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126583507&amp;amp;doi=10.1177%2f21582440221079885&amp;amp;partnerID=40&amp;amp;md5=13c38bf16e285d7b0ea764a4560a5748&lt;/a&gt;</text>
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              <elementText elementTextId="109406">
                <text>All Open Access; Gold Open Access</text>
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                <text>Lee M.C.C., School of Psychology, Massey University, Auckland, Albany, 0745, New Zealand; Lin M.-H., Department of Psychology, Sunway University, Bandar Sunway, Selangor, Petaling Jaya, 47500, Malaysia; Srinivasan P.M., Department of Psychology, Christ University, Karnataka, Bengaluru, 560029, India; Carr S.C., School of Psychology, Massey University, Auckland, Albany, 0745, New Zealand</text>
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                <text>The critical shifts in the utility, implementation, and enforcement of human rights have been achieved as a result of the rise of cutting-edge technological innovation. As a result, there has been a plethora of research on the expansion of beneficiaries of the human rights and the subject matter of such rights. The authors of this chapter contend that in this era of technology, we need to reevaluate our approach to human rights, broaden the scope of those to whom obligations relating to human rights apply by including corporations and other organizations, and be ready to consider the possibility that artificial intelligence will become a topic of discussion in public relations and fundamental rights. In this chapter, a three-pronged approach to thinking about digital rights is presented. This method takes into consideration the subtle structural impact that considering human rights in the digital age has on the job that the courts do.  2024 by IGI Global. All rights reserved.</text>
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                <text>applications; Artificial intelligence; data analysis; deep learning; machine learning; predictive models; sleep disorder management; sleep disorders; sleep disorders diagnosis; sleep medicine; sleep monitoring; sleep quality; sleep therapy; sleep tracking; treatment</text>
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                <text>Disruptions to sleep have a substantial influence on people's overall health and quality of life. The conventional techniques for diagnosing and managing sleep disorders usually rely on subjective assessments and qualitative evaluations, that may have some accuracy and efficacy limitations. Nevertheless, recent developments in the field of artificial intelligence (AI) have presented new opportunities for better diagnosing and treating problems with insomnia. The paper reviews in depth the uses of AI in the domain of medical sleep medicine. We look at the use of algorithmic techniques for deep learning and machine learning for identifying indicators of sleep-related issues, the assessment of sleep quality, sleep tracking, and the establishment of individualized sleep therapeutics. We also discuss how AI is being used to construct forecasting models that may be used to identify individuals who are at risk of experiencing sleep issues and improve treatment strategies. In addition, we talk about the challenges and potential outcomes of incorporating AI-based techniques into clinical practice. Overall, our research highlights how AI has the potential to transform the field of sleeping medicine and improve outcomes for people with sleep-related conditions.  2023 IEEE.</text>
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                <text>Randles S., Manchester Metropolitan Universitys Faculty of Business and Law, United Kingdom; Wadham H., Manchester Metropolitan University Business School, United Kingdom; Skritsovali K., Liverpool John Moores University Business School, United Kingdom; Hart C., Department of Strategy, Enterprise and Sustainability, Manchester Metropolitan University, United Kingdom; Hoque S., Manchester Metropolitan University, United Kingdom; Kettleborough H., Manchester Metropolitan University Business School, United Kingdom; Klapper R., Manchester Metropolitan University, United Kingdom; Marron R., Manchester Metropolitan University Business School, United Kingdom; Taylor D., Manchester Metropolitan University Business School, Institute of Enterprise and Entrepreneurs, United Kingdom, Christ University, India; Walley L., Manchester Metropolitan University Business School, United Kingdom</text>
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                <text>In the modern technology-driven era, it is important to consider a new model of education to keep pace with Industry 4.0. In view of this, the present paper critically explores the issues, discusses potential solutions along with a comprehensive analysis of the applications of technologies such as Internet of Things (IoT) in modern education specially Education 4.0, and examines the potential of these technologies to transform the education sector. The challenges faced by previous education models are analysed along with how they pave the way to the inclusion of IoT in education, leading to Education 4.0. The potential benefits of IoT in improving learning outcomes, enhancing student engagement and retention, and supporting teachers are also highlighted. In addition, it addresses the ethical and privacy concerns associated with the use of these technologies and suggests areas for future research.  2023 A. K. Biswal et al.</text>
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                <text>Biswal A.K., School of Computer Engineering, Kalinga Institute of Industrial Technology (Deemed to be University), Bhubaneswar, India; Avtaran D., School of Computer Engineering, Kalinga Institute of Industrial Technology (Deemed to be University), Bhubaneswar, India; Sharma V., CHRIST (Deemed to be University), NCR, Delhi, India; Grover V., Noida Institute of Engineering &amp;amp; Technology, Greater Noida, India; Mishra S., School of Computer Engineering, Kalinga Institute of Industrial Technology (Deemed to be University), Bhubaneswar, India; Alkhayyat A., College of Technical Engineering, The Islamic University, Najaf, Iraq</text>
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                <text>Abstract conceptualisation; Augmented reality (AR); Bring your own device (BYOD); Central nervous system (CNS); Cognitive skills; Comprehending axis; Experiential learning theory (ELT); Learner's space; Learning accommodation; Learning curve; Learning styles; Learning way; Neuroplasticity; Neuropsychic system; Neuroscience; Peripheral nervous system (PNS); Student portfolio; Transformation axis; Virtual reality (VR)</text>
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                <text>An application of Kolb's experiential learning theory (ELT) in real situations as a blend of Bloom's taxonomy of education is given as a case study conducted about more than 15 years ago. The world has changed since then with revolutionary developments in the techno-world. Student portfolio is regarded as the documentary evidence created by the student to diagnose the student's strengths and weaknesses to assist him or her in learning. In light of this case study and developments in technology, further scope in the application of the ELT model is discussed. It is also recognised that technology to facilitate experiential learning using virtual reality or augmented reality tools is to be made more user-friendly in terms of affordability and that neuroplasticity has an important role to play in this. A case for more research in neuroscience to analyse learning styles is raised.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved.</text>
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                <text>Neuro-Systemic Applications in Learning, pp. 3-25.</text>
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                <text>This book chapter delves into the influence of servant leadership on the profitability of social entrepreneurship, a phenomenon widely recognized by thriving startups worldwide. It generates hypothesis about the effect of seven facets of servant leadership viz., empowerment, conceptualization, followers influence, emotional convalescence, follower's growth and succession, value-creation for the community, and ethical behavior on social entrepreneurship profitability. The data was received through e-mail survey from 158 entrepreneurs located in Bengaluru. Hypothesis testing was done using multi-regression analysis technique. Results of the study specify that the seven dimensions of servant leadership except conceptualization have significant impact on the social entrepreneurship profitability. Further, the study continues with discussion of the inferences for practice by the social entrepreneurship, suggestions for future studies, and the continuous advancement of leadership tactics as well as styles that support upcoming social entrepreneurship ventures.  2024, IGI Global. All rights reserved.</text>
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                <text>This chapter explores the transformative potential of Industry 5.0 by leveraging real-time monitoring and decision-making capabilities through the use of IIoT dashboards. It extends in examining how IIoT dashboards enable organizations to gain real-time insights into their operations, facilitating data-driven decision-making and improving overall efficiency. By embracing IIoT dashboards, businesses can effectively transform Industry 5.0, unlocking new levels of productivity, agility, and competitiveness. In this chapter, important challenges such as data integration, data security, scalability, and user experience are identified. It highlights key considerations for implementing IIoT dashboards and offers practical methods for successful adoption of this technology. Remarkable achievements in implementing this technology include applications such as crude oil production with IIoT and edge computing, as well as IIoT-enabled smart agriculture dashboards. Adopting IIoT dashboards may involve initial costs, but they offer long-term benefits and cost-effectiveness, particularly in the era of Industry 5.0 transformation.  2024 selection and editorial matter, C Kishor Kumar Reddy, P R Anisha, Samiya Khan, Marlia Mohd Hanafiah, Lavanya Pamulaparty and R Madana Mohana.</text>
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                <text>Most educational institutions have adapted to the mode of online teaching which has resulted in an increase of online video recordings. Learner community can be benefited with the ability to retrieve required information from the online class recordings. In this paper, we propose a methodology for converting video transcript data into useful information repositories for the purpose of retrieving class transcripts relevant to user's information needs. We focus on the online video recording transcript data. We also discuss challenges in transcribing which are crucial to understand preliminary processing. Our dataset consists of transcripts from diverse subject domains deeper experimental insights. We use interactive transcripts obtained from ASR (automatic speech recognition) services and non-interactive human generated transcripts. State-of-the-art methods for keyword retrieval: Latent Dirichlet Topic Modelling (LDA), Term Frequency (TF.IDF) and Text Rank (graph based) are applied on the video transcript data. Further, cosine similarity metric is applied to obtain the similarity measure between the transcript documents and keywords.  2022 IEEE.</text>
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                <text>Fernandes D., Christ Deemed to Be University, Department of Computer Science, Bangalore, India; Wagh R.S., Christ Deemed to Be University, Department of Computer Science, Bangalore, India</text>
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