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                <text>Enhanced sunflower optimisation; Gait recognition; GAIT-IT; GAIT-ITS; Improved convolutional neural network; Median filter; Modified bidirectional LSTM; Parkinsons disease</text>
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                <text>The majority of people affected by Parkinsons disease (PD) are middle-aged and older. The condition causes a variety of severe symptoms, including tremors, limited flexibility, and slow movements. As Parkinsons disease develops with changing symptoms and growing severity, the importance of computer-aided diagnosis based on algorithms cannot be highlighted. Gait recognition technology appears to be a potential path for Parkinson's disease identification since it captures unique properties of a persons walking pattern without requiring active participation, providing stability and non-intrusiveness. To begin,the median filter is used to remove noise from the input images received during data collection. This paper describes a new method for finding local and global features in gait images to assess the severity of Parkinsons disease.Local features are extracted using a stacked autoencoder, and global features are obtained using an Improved Convolutional Neural Network (ICNN). The Enhanced Sunflower Optimisation (ESO) technique is used to improve the CNN model's performance by optimizing hyperparameters such as batch size, learning rate, and number of convolutional layers. To classify PD severity, a modified bidirectional LSTM (MBi-LSTM) classifier receives input in the form of a combination of local and global features. The proposed model's performance is completely evaluated with the GAIT-IT and GAIT-IST datasets, which include key measures such as accuracy, precision, recall, and the F-measure. This study improves the diagnosis of Parkinsons disease by introducing a non-intrusive real-time monitoring system capable of early detection and prevention.  Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.</text>
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                <text>International Journal of Information Technology (Singapore), Vol-16, No. 6, pp. 3963-3971.</text>
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                <text>Reshma S., Dept of Artificial Intelligence and Machine Learning, Dayananda Sagar College of Engineering, Bangalore, India; Chennakesavulu M., Department of Electronics and Communication Engineering, Rajeev Gandhi Memorial College of Engineering and Technology (Autonomous), Andhra Pradesh, Nandyal, 518501, India; Patil S.S., Rajarambapu Institute of Technology, Rajaramnagar, Uran Islampur, India; Lamani M.R., CHRIST(Deemed to Be University), Kanmanike, Kumbalgudu, Mysore Road, Karnataka, Bangalore, 560074, India</text>
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                <text>International Journal of Minerals, Metallurgy and Materials, Vol-20 (10), pp. 967-971. ISSN-1674-4799</text>
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                <text>Electrical and mechanical properties of vapour grown gallium monotelluride crystals</text>
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                <text>electrical conductivity; gallium monotelluride; microhardness; physical vapour deposition; spherulites; whiskers</text>
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                <text>The physical vapour deposition (PVD) of gallium monotelluride (GaTe) in different crystalline habits was established in the growth ampoule, strongly depending on the temperature gradient. Proper control on the temperatures of source and growth zones in an indigenously fabricated dual zone furnace could yield the crystals in the form of whiskers and spherulites. Optical and electron microscopic images were examined to predict the growth mechanism of morphologies. The structural parameters of the grown spherulites were determined by X-ray powder diffraction (XRD). The stoichiometric composition of these crystals was confirmed using energy dispersive analysis by X-rays (EDAX). The type and nature of electrical conductivity were identified by the conventional hot probe and two probe methods, respectively. The mechanical parameters, such as Vickers microhardness, work hardening index, and yield strength, were deduced from microindentation measurements. The results show that the vapour grown p-GaTe crystals exhibit novel physical properties, which make them suitable for device applications.  2013 University of Science and Technology Beijing and Springer-Verlag Berlin Heidelberg.</text>
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                <text>Reshmi P.M.; Kunjomana A.G.; Chandrasekharan K.A.</text>
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                <text>International Journal of Minerals, Metallurgy and Materials, Vol-20, No. 10, pp. 967-971.</text>
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                <text>ISSN: 16744799</text>
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                <text>Reshmi P.M., Crystal Research Centre, Department of Physics, Christ University, Bangalore 560 029, India; Kunjomana A.G., Crystal Research Centre, Department of Physics, Christ University, Bangalore 560 029, India; Chandrasekharan K.A., Crystal Research Centre, Department of Physics, Christ University, Bangalore 560 029, India</text>
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                <text>Spherulitic crystallization of ?-In2Te3 by physical vapour deposition</text>
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            <name>Subject</name>
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                <text>chalcogenides; PVD; SEM; spherulites; supersaturation; XRD</text>
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                <text>Different morphologies of indium telluride (In2Te3) including novel spherulites were crystallized using the physical vapour deposition (PVD) method, by varying the difference in the growth and source zone temperature (?T) of a dual zone horizontal furnace assembled indigenously. Whiskers and kinked needles of In2Te3were grown at ?T = 250 K and 300 K respectively, maintaining the growth zone at 500 C. At high supersaturation (? T = 400 K), spherulitic crystals were obtained. The stoichiometric composition of these crystals has been confirmed using energy dispersive analysis by x-rays (EDAX). The structure of ?-In2Te3 spherulitic crystals is identified as zinc blende with lattice parameter a = 6.159  from x-ray diffraction (XRD) studies. The scanning electron microscope (SEM) images revealed the radial structure of the grown spherulites. The growth mechanism for the spherulitic crystallization of ?-In2Te3 crystals has been discussed based on the theoretical models. Copyright  2011 WILEY-VCH Verlag GmbH &amp;amp; Co. KGaA, Weinheim.</text>
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                <text>Reshmi P.M.; Kunjomana A.G.; Chandrasekharan K.A.</text>
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                <text>Crystal Research and Technology, Vol-46, No. 2, pp. 153-158.</text>
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                <text>&lt;a href="https://doi.org/10.1002/crat.201000183" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1002/crat.201000183&lt;/a&gt;
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                <text>ISSN: 15214079; CODEN: CRTED</text>
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                <text>Reshmi P.M., Crystal Research Centre, Department of Physics, Christ University, Bangalore 560 029, India; Kunjomana A.G., Crystal Research Centre, Department of Physics, Christ University, Bangalore 560 029, India; Chandrasekharan K.A., Crystal Research Centre, Department of Physics, Christ University, Bangalore 560 029, India</text>
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                <text>Growth and characterization of chalcogenide crystals by vapour method</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="190250">
                <text>Chalcogenides; EDAX; Furnace; Hardness; PVD; SEM</text>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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              <elementText elementTextId="190251">
                <text>A horizontal linear gradient two zone furnace was designed and employed to grow single crystals of indium telluride by Physical Vapour Deposition (PVD) method. It was calibrated for various trials including, series and parallel combinations of coils, and set temperatures. Systematic growth runs for chalcogenide crystals were performed by varying the source and growth temperatures. Crystals of different sizes and morphologies were obtained. The morphology and chemical analysis of the grown crystals were investigated by Scanning Electron Microscope (SEM) and Energy Dispersive Analysis using X-rays (EDAX). The hardness of the crystals was estimated using a Vickers microhardness tester.  2011 American Institute of Physics.</text>
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            <elementTextContainer>
              <elementText elementTextId="190252">
                <text>Reshmi P.M.; Kunjomana A.G.; Chandrasekharan K.A.</text>
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              <elementText elementTextId="190253">
                <text>AIP Conference Proceedings, Vol-1349, No. PART A, pp. 1323-1324.</text>
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            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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                <text>&lt;a href="https://doi.org/10.1063/1.3610223" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1063/1.3610223&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052496627&amp;amp;doi=10.1063%2F1.3610223&amp;amp;partnerID=40&amp;amp;md5=a170a6e2569ee738d59432ae9e70e617" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052496627&amp;amp;doi=10.1063%2f1.3610223&amp;amp;partnerID=40&amp;amp;md5=a170a6e2569ee738d59432ae9e70e617&lt;/a&gt;</text>
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              <elementText elementTextId="190256">
                <text>Restricted Access</text>
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                <text>ISSN: 15517616; ISBN: 978-073540905-7</text>
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              <elementText elementTextId="190261">
                <text>Reshmi P.M., Research Centre, Department of Physics, Christ University, Bangalore 560 029, India; Kunjomana A.G., Research Centre, Department of Physics, Christ University, Bangalore 560 029, India; Chandrasekharan K.A., Research Centre, Department of Physics, Christ University, Bangalore 560 029, India</text>
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      <name>Article</name>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="138485">
                <text>Vapour growth and characterization of beta indium sesquitelluride crystals</text>
              </elementText>
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          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="138486">
                <text>?-In&lt;sub&gt;2&lt;/sub&gt;Te&lt;sub&gt;3&lt;/sub&gt;; Characterization; Crystal morphology; Physical vapour deposition</text>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="138487">
                <text>Physical Vapour Deposition (PVD) provides stoichiometric crystals of different morphology, depending upon the materials, geometry of ampoules, temperature profiles, growth parameters and kinetics of crystallization. The crystal forms such as needles, platelets and spherulites of beta indium sesquitelluride (?-In2Te3) were produced by controlling the temperature of source and growth zones. The X-Ray Diffraction (XRD) and chemical analysis of the spherulitic crystals confirmed zinc blende structure with beta phase. Their resistivity (135.16 ? cm) at room temperature (300 K) was determined by van der Pauw method. The temperature dependence of DC conductivity was investigated using the conventional two-probe technique. The variation of dielectric constant (?1) and dielectric loss (tan ?) with temperature has been studied for different frequencies (1 kHz-1 MHz). The AC conductivity, ?ac(?) was found to vary with angular frequency as ?s, where s is the frequency exponent. The values of s lie very close to unity and show a slight decrease with increase in temperature, which indicate a Correlated Barrier Hopping (CBH) between centres forming Intimate Valence Alternation Pairs (IVAP). The activation energy for conduction ranges from 0.187 eV to 0.095 eV. The microhardness of ?-In2Te3 spherulites is found to be 353.5 kg/mm2, which is higher than that of other semiconducting chalcogenides. The results thus obtained on crystals grown from vapour phase open up ample possibilities for radiation detector applications.  2014 Elsevier B.V.</text>
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                <text>Reshmi P.M.; Kunjomana A.G.; Chandrasekharan K.A.; Teena M.</text>
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              <elementText elementTextId="138489">
                <text>Journal of Crystal Growth, Vol-394, pp. 1-6.</text>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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              <elementText elementTextId="138490">
                <text>2014-01-01</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.jcrysgro.2014.01.055" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.jcrysgro.2014.01.055&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894667333&amp;amp;doi=10.1016%2Fj.jcrysgro.2014.01.055&amp;amp;partnerID=40&amp;amp;md5=4c7da93cb0dfea91bcad7ad47beee24e" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894667333&amp;amp;doi=10.1016%2fj.jcrysgro.2014.01.055&amp;amp;partnerID=40&amp;amp;md5=4c7da93cb0dfea91bcad7ad47beee24e&lt;/a&gt;</text>
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              <elementText elementTextId="138492">
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                <text>ISSN: 220248; CODEN: JCRGA</text>
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            <description>A language of the resource</description>
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              <elementText elementTextId="138495">
                <text>English</text>
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              <elementText elementTextId="138497">
                <text>Reshmi P.M., Crystal Research Centre, Department of Physics, Christ University, Bangalore 560 029, India; Kunjomana A.G., Crystal Research Centre, Department of Physics, Christ University, Bangalore 560 029, India; Chandrasekharan K.A., Crystal Research Centre, Department of Physics, Christ University, Bangalore 560 029, India; Teena M., Crystal Research Centre, Department of Physics, Christ University, Bangalore 560 029, India</text>
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                <text>Recent years have seen a significant increase in attention in multimodal biometric systems for personal identification especially in unconstrained environments. This paper presents a multimodal recognition system by combining feature level fusion of ear and profile face images. Multimodal biometric systems by combining face and ear can be used in an extensive range of applications because we can capture both the biometrics in a non-intrusive manner. Local texture feature descriptor, BSIF is used to extract discriminative features from biometric templates. Feature level and score level fusion is experimented to improve the performance of the system. Experimental results on different public datasets like GTAV, FEI, etc., show that the proposed method gives better performance in recognition results than individual modality.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-843, pp. 279-288.</text>
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                <text>Resmi K.R., CHRIST (Deemed to be) University, Bengaluru, India; Joseph A., Santhigiri College, Kerala, Thodupuzha, India; George B., Santhigiri College, Kerala, Thodupuzha, India</text>
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                <text>Ear Recognition Using Rank Level Fusion of Classifiers Outputs</text>
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                <text>BSIF; decision level fusion; ear biometrics; GLBP; HOG; rank level fusion</text>
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                <text>An individuals authentication plays a vital role in our daily life. In the last decade, biometric-based authentication has become more prevalent than traditional approaches like passwords and pins. Ear recognition has gained attention in the biometric community in recent years. Researchers defined several features for the identification of a person from ear image. The features play a vital role in the success of classification models. This paper considers an ensemble of features for designing a new classification model. The features are assessed in isolation as well as through feature-level fusion. Subsequently, a rank-level fusion for classification is introduced. The experiments are conducted on both constrained and unconstrained ear datasets. The results are promising and open up new possibilities in machine learning-based ear recognition  2023, International journal of online and biomedical engineering.All Rights Reserved.</text>
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                <text>Resmi K.R.; Joseph S.M.; Raju G.; Swain D.; Das O.P.; Acharya B.</text>
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                <text>International journal of online and biomedical engineering, Vol-19, No. 3, pp. 127-143.</text>
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                <text>&lt;a href="https://doi.org/10.3991/ijoe.v19i03.36831" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.3991/ijoe.v19i03.36831&lt;/a&gt;
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              <elementText elementTextId="101652">
                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 26268493</text>
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                <text>Resmi K.R., CHRIST University, Bengaluru, India; Joseph S.M., Mahatma Gandhi College, Iritty, India; Raju G., CHRIST University, Bengaluru, India; Swain D., Department of Computer Science and Engineering, Pandit Deendayal Energy University, Gandhinagar, India; Das O.P., GSK India Global Services Private Limited, Bangalore, India; Acharya B., Department of Computer Engineering-AI, Marwadi University, Rajkot, India</text>
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                <text>Ear Recognition Using Pretrained Convolutional Neural Networks</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="183664">
                <text>Convolutional neural network; Deep learning; Ear recognition; Pretrained networks</text>
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                <text>Ear biometrics, which involves the identification of a person from an ear image, is challenging under unconstrained image capturing scenarios. Studies in Ear biometrics reported that the Convolutional Neural Network is a better alternative to classical machine learning with handcrafted features. Two major concerns in CNN are the requirement of enormous computing resources and large datasets for training. The pretrained network concept helps to use CNN with smaller datasets and is less demanding on hardware. In this paper, three pre-trained CNN models, AlexNet, VGG16, and ResNet50 are used for ear recognition. The fully connected classification layers of the nets are trained with AWE, an unconstrained ear dataset. Alternatively, the CNN layers output (the CNN features) are extracted, and an SVM classification model is built. To improve the classification accuracy, the training dataset size is increased through data augmentation. Data augmentation improved the classification accuracy drastically. The results show that ResNet50, with the fully connected classification layer, results in higher accuracy.  2021, Springer Nature Switzerland AG.</text>
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                <text>Resmi K.R.; Raju G.</text>
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                <text>Communications in Computer and Information Science, Vol-1440 CCIS, pp. 720-728.</text>
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              <elementText elementTextId="183671">
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                <text>ISSN: 18650929; ISBN: 978-303081461-8</text>
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                <text>Resmi K.R., School of Computer Sciences, M G University, Kerala, India; Raju G., Department of Computer Science and Engineering, Christ (Deemed to be University), Bengaluru, India</text>
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                <text>A Novel Approach to Automatic Ear Detection Using Banana Wavelets and Circular Hough Transform</text>
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          <element elementId="49">
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              <elementText elementTextId="187099">
                <text>adaptive histogram equalization; banana wavelets; biometric; ear detection; hough transform; skin segmentation</text>
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                <text>Ear is an attractive biometric trait that maintain their structure with increasing age. Because of the complex geometry of ear, its detection is very difficult. This paper proposes a modified algorithm for automatic detection of 2D ear images using Banana wavelets and Hough transform. Banana wavelets derived from bank of stretched and curved Gabor wavelets are used to identify curvilinear ear structure. Addition of a preprocessing stage, prior to application of banana wavelets is found to improve the detection results further. The proposed algorithm is brought in to comparison with three existing algorithms and evaluated on standard databases. In addition to manual detection accuracy, this paper also calculates the efficiency of the proposed method using automatic classification techniques. The features like LBP and Gabor extracted from segmented ear image is used by different classifiers to determine whether the segmented portion of the image is class Ear or Non ear.  2019 IEEE.</text>
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                <text>Resmi K.R.; Raju G.</text>
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                <text>2019 International Conference on Data Science and Communication, IconDSC 2019</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>ISBN: 978-153869319-3</text>
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                <text>Resmi K.R., School of Computer Science, Mahatma Gandhi University, Kottayam, India; Raju G., Department of Computer Science and Engineering, Christ Deemed To be University, Bengaluru, India</text>
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                  <text>MPHIL</text>
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                <text>Assessing Opportunities and Constraints of Community Engagement in Tourism Development at Hampi</text>
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                <text>Retheesh  P T</text>
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                <text>Tourism</text>
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                <text>Community Based Tourism will create a momentous milestone in improving the

participation level of local communities in the arena of Heritage tourism as well as all the various

branches of the travel and expedition industry. Whose heritage is being preserved, by whom, and

for what purposes? (Shepherd 2006). This study particularly gives due emphasis on evaluating

the level of participation from the resident???s part by assessing various development strategies

offered by the respective authorities. The study also tries to address all the possible streams

where the community can easily thrive and it also addresses the major obstacles which restricts

their entry, indicating an inclusive approach towards community participation through

community based tourism (CBT). Lack of cooperation among stakeholders was identified as

challenges of CBT, (Tamir 2015). Tourism market of Hampi is developing year by year but the

standard of living of the underprivileged community is always remains the same without any

improvement and this is the core problem mentioned in the study.

Quantitative research technique was used for the study with the help of a structured

questionnaire which was used for collecting data. The collected data was analyzed with the help

of quantitative data analysis software, SPSS. This research tries to bring out the various reasons

behind the low level of community involvement in tourism industry with relevant evidence from

the analyzed data. The study indicates the hopelessness of the community towards the major

development strategies forwarded by the authorities especially Hampi Master Plan. It also

addresses the poor level of education and lack of information about the potential of tourism

employability and its scope in the field of community development. A unique relic of medieval

commerce and religious faith into a lifeless ruin, (John and Michell2012) this study pinpoints the

inefficiency of the tourism boards and poor functioning of other responsible authorities too. It

VII

also invokes the possibilities of promoting Agro-Tourism along with the existing Heritage

tourism. There is enough scope for further study in the light of execution of CBT model as well

as assessing the scope of Agro tourism in Hampi. This suggestion is propounded mainly because

of the structural phase of the economy that is more than 70% of the working population is

involved in agriculture and its allied sectors. There is a noticeable gap between the expectations

of the local residents and what they are actually receiving from the authorities moreover, these

entire gaps may hamper the idea of inclusive approach. If effective training and regular

awareness creation program is initiated by the responsible authorities, it will create a better

platform for inclusive approach.</text>
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                <text>A modified invasive weed optimization for MPPT of PV based water pumping system driven by induction motor</text>
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          <element elementId="49">
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                <text>induction motor; invasive weed optimization; P&amp;amp;O; PV; sensorless; vector control; water pumping</text>
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                <text>A novel approach called Modified Invasive Weed Optimization (MIWO) technique has been developed and combined with the Perturb and Observes (P&amp;amp;O) algorithm to enhance the extraction of maximum power from photovoltaic (PV) panels in the presence of partial shading conditions. The conventional P&amp;amp;O algorithm falls short in extracting the maximum power from PV systems under partial shading conditions due to the existence of multiple maximum points. In such scenarios, optimization techniques can be employed to search for the global maximum point. The proposed MIWO-based P&amp;amp;O algorithm updates the reference voltage to ensure that the PV system operates at the Maximum Power Point (MPP) based on the prevailing weather conditions. This MIWO based PV system is further fed to water pumping system. A PV-based water pumping system is utilized for both irrigation and domestic purposes. Additionally, a sensorless vector control-based induction motor is employed in this study to drive the pump. The objective of this research is to demonstrate the achievement of an efficient PV-based water pumping system without the need for battery storage. Various results based on MIWO are compared with PSO and GWO. The results are presented based on various water pumping applications and the availability of solar irradiance during rapid climate changes. MATLAB/Simulink simulations, along with hardware-based experiments, are provided to validate the effectiveness of the proposed method under both transient and steady-state conditions.  2024 IOP Publishing Ltd.</text>
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            <name>Creator</name>
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              <elementText elementTextId="77651">
                <text>Revathi V.M.; Subramani K.; Krishnakumar S.; Alawadi A.H.; Senthil Kumar R.; Malla S.G.</text>
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              <elementText elementTextId="77652">
                <text>Engineering Research Express, Vol-6, No. 3</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="77653">
                <text>Institute of Physics</text>
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                <text>ISSN: 26318695</text>
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                <text>Revathi V.M., Department of Mathematics, Bannari Amman Institute of Technology, Tamil Nadu, Sathyamangalam, India; Subramani K., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Krishnakumar S., Sethu Institute of Technology, Tamil Nadu, Kariapatti, India; Alawadi A.H., College of Technical Engineering, The Islamic University, Najaf, Iraq; Senthil Kumar R., AAA College of Engineering and Technology, Tamil Nadu, Sivakasi, India; Malla S.G., ERG Foundation, Visakhapatnam Andhra Pradesh, Anakapalli, India</text>
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      <name>Article</name>
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          <element elementId="50">
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            <description>A name given to the resource</description>
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              <elementText elementTextId="93863">
                <text>Role of mixed molecular weight PEO-PVDF polymers in improving the ionic conductivity of blended solid polymer electrolytes</text>
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          <element elementId="49">
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            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="93864">
                <text>Blend polymer electrolyte; Dielectric constant; Dielectric relaxation; Ion concentration factor; Ion hopping rate; Ionic conductivity</text>
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            <name>Description</name>
            <description>An account of the resource</description>
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                <text>Blended solid polymer electrolytes (BSPE) were prepared by mixing different molecular weight polymers PEO6 (Mw = 1 106 g/mol), PEO5 (Mw = 1 105 g/mol), and PVDF (Mw = 5.25 105 g/mol) complexed with lithium salt. Conductivity and dielectric studies at different temperatures were carried out on these BSPE systems by varying the wt% of PEO5 and PVDF with respect to PEO6, keeping the wt% of lithium salt constant. The electrical characterizations of BSPE systems have been investigated using impedance spectroscopy in the frequency range 0.1106 Hz. The conductivity data shows that inclusion of PEO5 and PVDF into the PEO6 matrix improved the overall lithium-ion dynamics in the polymer matrix. The composition, PEO6 (94 wt%)-PEO5 (3 wt%)/PVDF (3 wt%)-LiClO4, exhibited maximum conductivity of 6.44 10?4 Scm?1 at 303 K. TheDC conductivity variation with temperature of BSPE systems follows Arrhenius relation and variation of AC conductivities with frequency obeys Jonschers power law. The real and imaginary part of dielectric constant and the dielectric relaxation were also investigated.  2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</text>
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            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="93866">
                <text>Revathy C.; Sunitha V.R.; Money B.K.; Joseph R.; Radhakrishnan S.</text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="93867">
                <text>Ionics, Vol-29, No. 10, pp. 4025-4035.</text>
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            <name>Publisher</name>
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              <elementText elementTextId="93868">
                <text>Springer Science and Business Media Deutschland GmbH</text>
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                <text>&lt;a href="https://doi.org/10.1007/s11581-023-05141-5" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s11581-023-05141-5&lt;/a&gt;
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                <text>Revathy C., Department of Electrical &amp;amp; Electronics Engineering, PES University, -560085, Karnataka, Bangalore, India; Sunitha V.R., Department of Sciences and Humanities, School of Engineering and Technology, Christ (Deemed to be University), -560074, Karnataka, Bangalore, India; Money B.K., Department of Sciences and Humanities, School of Engineering and Technology, Christ (Deemed to be University), -560074, Karnataka, Bangalore, India; Joseph R., Department of Electrical &amp;amp; Electronics Engineering, PES University, -560085, Karnataka, Bangalore, India; Radhakrishnan S., Department of Science and Humanities, PES University, -560085, Karnataka, Bangalore, India</text>
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              <elementText elementTextId="72161">
                <text>Engineered biocorona on microplastics as a toxicity mitigation strategy in marine environment: Experiments with a marine crustacean Artemia salina</text>
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                <text>The marine environment has become a major sink for microplastics (MPs) wastes. When MPs interact with biological macromolecules, the biocorona forms on their surface, which can alter their biological reactivity and toxicity. In this study, we investigated the impact of biocorona formation on the toxicity of aminated (NH2) and carboxylated (COOH) polystyrene MPs towards the marine crustacean Artemia salina. Biocoronated MPs were prepared using cell-free extracts (CFEs) from microalgae Chlorella sp. (phytoplankton) and the brine shrimp Artemia salina (zooplankton). The results revealed that biocorona formation effectively reduced the toxicity of MPs. Pristine NH2-MPs exhibited higher reactive oxygen species production (ROS) (182%) compared to COOH-MPs (162%) in Artemia salina. Notably, NH2-MPs coronated with brine shrimp CFE exhibited a substantial reduction in ROS production (127%) than those coronated with algal CFE, with COOH-MPs showing a similar trend (120%). Biocorona formation also significantly decreased malondialdehyde (MDA) levels and antioxidant activity compared to pristine MPs. Molecular docking and dynamics simulations demonstrated a strong binding between polystyrene and acetylcholinesterase (AChE). In vitro studies indicated that pristine NH2-MPs exhibited more reduction in AChE activity (84%) compared to COOH-MPs (95%). However, no significant reduction in AChE activity was observed upon exposure to MPs coronated with either algal or brine shrimp cell-free extracts. Independent action modeling indicated an antagonistic interaction for MPs coronated with both the CFEs. Pearson correlation and cluster heatmap analysis suggested that the toxicity reduction in Artemia salina might be driven by decreased oxidative stress followed by the corona formation. Overall, this study provides valuable insights into the potential of biomolecules from phytoplankton and zooplankton to reduce MPs toxicity in Artemia salina, while highlighting their role in modulating the toxicity of other marine pollutants.  2024 The Author(s)</text>
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                <text>Rex M C., Centre for Nanobiotechnology, VIT, Tamil Nadu, Vellore, 632014, India; Bairoliya A., Centre for Nanobiotechnology, VIT, Tamil Nadu, Vellore, 632014, India; Gairola S., Centre for Nanobiotechnology, VIT, Tamil Nadu, Vellore, 632014, India; Sureshkumar P., R V College of Engineering, Karnataka, Bengaluru, India; Niranjan V., R V College of Engineering, Karnataka, Bengaluru, India; Nag A., Department of Life Sciences, Christ University, Karnataka, Bengaluru, India; Mukherjee A., Centre for Nanobiotechnology, VIT, Tamil Nadu, Vellore, 632014, India</text>
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                <text>An Analysis of Sentiment Using Aspect-Based Perspective</text>
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                <text>Aspect-based sentiment analysis; Convolutional neural network; Deep learning; Natural language processing</text>
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                <text>Opinions play a major role in almost every human practice. Finding product and service reviews is made easy online. Product reviews are readily available in huge quantities. Considering each review and making a concise decision about a product is not feasible or even possible. Aspect-based sentiment analysis (ABSA) is one of the best solutions to this problem. Summary and online reviews analysis is delivered in this paper. ABSA has made extensive use of machine learning techniques. Recent years have seen deep learning take off due to the growth of computer processing power and digitalization. When applied to various deep learning techniques, numerous NLP tasks produced futuristic results. An overview of various deep learning models used in the field of ABSA is presented in this chapter after an introduction to ABSA.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Cognitive Science and Technology, pp. 809-818.</text>
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                <text>Rexi F.A., Christ University, Bengaluru, India; Preethi N., Christ University, Bengaluru, India</text>
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                <text>Dynamics of newtonian fluids and nanofluids in various geometries &#13;
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                <text>Identifying and recognition of breaking news in most of the TV channels in different backgrounds with varying positions from a static image plays a significant role in journalism and multimedia image processing. Now a days its very challenging to isolate only breaking news from headlines due to overlapping of many categories of news, keeping all this in mind, a novel methodology is proposed in this paper for detecting specific text as a breaking news from a given multimedia image. Basic digital image processing techniques are used to detect text from the images. The methods like MSER (Maximally Stable Extremal Regions) and SWT (Stroke Width Transform) are used for text detection. The proposed work focuses on extraction of text in breaking news images also discusses the different methods to overcome existing challenges in text detection along with different types of breaking news datasets collected from various news channels are used to identify text from images and comparative study of different text detection methods. The comparative study proves that MSER and SWT is a better technique to detect text in images. Finally using OCR (Optical Character Recognition) technique to extract the breaking news text from the detected regions will help in easy indexing and analysis for journalism and common people. Extensive experiments are carried out to demonstrate the effectiveness of the proposed approach.  2019, Springer Nature Singapore Pte Ltd.</text>
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                <text>Ridwan A.; Danti A.; Raghavendra S.P.; Aqlan H.A.A.; Arunkumar N.B.</text>
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                <text>Communications in Computer and Information Science, Vol-1037, pp. 118-130.</text>
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              <name>Title</name>
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                  <text>Articles</text>
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      <name>Article</name>
      <description>Faculty Publications -Articles</description>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Acetylcholine esterase inhibition activity of leaf extract of Saraca asoca using zebrafish as model organism</text>
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          <element elementId="49">
            <name>Subject</name>
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                <text>Acetylcholine esterase (AChE); Alzheimers disease; Molecular docking; Saraca asoca; Zebrafish</text>
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          <element elementId="41">
            <name>Description</name>
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                <text>Alzheimers disease, also called as Senile Dementia, is a progressive neurogenerative disease that slowly destroys important mental functions like memory, reasoning and thinking. A plethora of factors including genetics, lifestyle, environment, age etc. play a part in determining its incidence. One of the commonly used techniques to slow down the progression of Alzheimers is to reduce the functioning of Acetylcholinesterase (AChE) enzyme which breaks down the neurotransmitter acetylcholine. Plants have been found to be natural sources of AChE inhibitors. Hence the present investigation was an attempt to screen Ashoka plant (Saraca asoca) for such inhibitors. Zebrafish (Danio rerio) was used as a model organism due to its genetic similarities with humans. Both in vivo and in vitro analyses using zebrafish indicated inhibitory action of the leaf extract on AChE. Gas Chromatography- Mass spectrometry (GCMS) analysis of the methanolic leaf extract and further docking studies of prominent phytochemicals revealed the AChE inhibitory potential of molecules like Stigmasterol, ?-sitosterol, Vitamin E etc. Hence these molecules can be thought of as targets in the therapy of Alzheimers disease.  2020 World Research Association. All rights reserved.</text>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
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                <text>Rijo R.; Tilling B.R.; Mehul V.A.; Sumit P.; Suma S.</text>
              </elementText>
            </elementTextContainer>
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            <name>Source</name>
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              <elementText elementTextId="124422">
                <text>Research Journal of Chemistry and Environment, Vol-24, No. 6, pp. 88-94.</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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                <text>World Research Association</text>
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            <name>Date</name>
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                <text>2020-01-01</text>
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          <element elementId="43">
            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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                <text>&lt;a href="" target="_blank" rel="noreferrer noopener"&gt;&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087353100&amp;amp;partnerID=40&amp;amp;md5=32c19a03e25fb091002d66cb96bdfcd9" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087353100&amp;amp;partnerID=40&amp;amp;md5=32c19a03e25fb091002d66cb96bdfcd9&lt;/a&gt;</text>
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          <element elementId="47">
            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="124426">
                <text>Restricted Access</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="46">
            <name>Relation</name>
            <description>A related resource</description>
            <elementTextContainer>
              <elementText elementTextId="124427">
                <text>ISSN: 9720626</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="42">
            <name>Format</name>
            <description>The file format, physical medium, or dimensions of the resource</description>
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              <elementText elementTextId="124428">
                <text>Online</text>
              </elementText>
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            <name>Language</name>
            <description>A language of the resource</description>
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              <elementText elementTextId="124429">
                <text>English</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="51">
            <name>Type</name>
            <description>The nature or genre of the resource</description>
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              <elementText elementTextId="124430">
                <text>Article</text>
              </elementText>
            </elementTextContainer>
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            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
            <elementTextContainer>
              <elementText elementTextId="124431">
                <text>Rijo R., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, India; Tilling B.R., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, India; Mehul V.A., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, India; Sumit P., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, India; Suma S., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, 560029, India</text>
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