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                <text>Mannan, Pallak Mallika; Chukkali, Surekha</text>
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                <text>Ageism, Culture and Willingness to Work with Older Adults Among Youth in India</text>
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                <text>Signals and Communication Technology;Volume;Part F76;pp.557-563</text>
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                <text>Mannan P.M., Department of Psychology, Christ (Deemed to be University), Delhi NCR, Ghaziabad, India; Chukkali S., Department of Psychology, Christ (Deemed to be University), Delhi NCR, Ghaziabad, India</text>
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                <text>Ageism is a phenomenon prevalent around the world today. It can be understood as the prejudiced attitudes, beliefs and discriminatory behaviour held towards people on the basis of their age. The present study aimed to explore the mindset of students aged 1825 in Delhi-NCR to know their perspective towards elderly in both, personal and professional domains. It seeks to identify and understand whether attitude of young adults towards older adults, awareness of ageism, the quality and quantity of intergroup contact, and filial piety attitudes influence their willingness to work with older adults. Individuals currently enrolled in an onsite course in a UGC-recognised University in Delhi-NCR participated in the study. The Facts on Aging Quiz (FAQ), Fraboni Scale of Ageism, Ambivalent Ageism Scale (benevolent and hostile attitudes) and Working with Older Adults Scale (WOAS) were administered on 200 participants. Filial piety and intergroup contact were also measured. Regression analysis highlighted the significant predictors of WOAS dimensions, namely, attitude, perceived behavioural control, subjective norm and working intentions. Intergroup contact frequency and quality along with compassionate reverence aspect of filial piety were significant contributors across the dimensions. The study has implications for intergenerational teams and diversity management training programs in organisations.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.</text>
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                <text>Springer Science and Business Media Deutschland GmbH</text>
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                <text>ISSN: 18604862;</text>
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                <text>Manners, Ovica; Aman, Shireen; Saji, Janita; Singh, Bholey; Pani, Balaram; Yadav, Ram Sagar; Rao, M.C.; Dubey, Vikas</text>
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                <text>Photoluminescence, Judd-Ofelt and Thermoluminescence studies on bright red emitting CaY2O4:Eu3+ phosphor for display applications</text>
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                <text>Journal of Molecular Structure;Volume;1352;Issue;;Article No.;144360;</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.molstruc.2025.144360" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.molstruc.2025.144360&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105018972103?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105018972103?origin=resultslist&lt;/a&gt;</text>
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                <text>Manners O., Department of Physics, North-Eastern Hill University, Meghalaya, Shillong, 793 022, India; Aman S., Department of Physics, North-Eastern Hill University, Meghalaya, Shillong, 793 022, India; Saji J., Department of Sciences and Humanities, School of Engineering and Technology, CHRIST University, Bengaluru, 560074, India; Singh B., Department of Chemistry, Swami Shraddhanand College, University of Delhi, Delhi, 110036, India; Pani B., Department of Chemistry, Bhaskaracharya College of Applied Sciences, University of Delhi, New Delhi, 110075, India; Yadav R.S., Institute of Science, Banaras Hindu University, Varanasi, 221 005, India; Rao M.C., Deparrment of Physics, Andhra Loyola College, Vijayawada, 520008, India; Dubey V., Department of Physics, North-Eastern Hill University, Meghalaya, Shillong, 793 022, India</text>
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                <text>The Eu3+-doped CaY2O4 phosphors were synthesised via high-temperature solid-state method. The XRD analysis suggests an Orthorhombic-like phase of the phosphor, with Eu3+ ions effectively substituting Y3+ sites, while the crystallite size analysis (Scherrer and W-H) reveals dopant-induced grain growth accompanied by strain relaxation. The photoluminescence spectra show an intense red-emission at 610 nm under a broad UV-to-blue excitation, with 466 nm emerging as the most efficient excitation wavelength, highlighting compatibility with blue LED sources. Concentration quenching behaviour suggests excitation-wavelength dependence, with optimum Eu3+ concentration at 1.5 mol% under deep UV-excitation (257 nm), and 2 mol% under near-UV/visible (393532 nm) excitations. Dexter analysis indicates the dipole-dipole interactions dominated quenching in the visible region, while the unusually low Q value under deep UV-excitation suggests the host-activator transfer. The Judd-Ofelt analysis indicates a non-centrosymmetric Eu3+ environment, and CIE coordinates (x = 0.643, y = 0.356) with ?94 % high colour purity demonstrates the saturated red emission. Thermoluminescence study exhibits multiple traps with near-linear UV dose response, supporting dosimetric potential. The combined broad excitation, high emission intensity, and colour purity make the CaY2O4: Eu3+ a promising red phosphor for display and LED applications.  2025 Elsevier B.V.</text>
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                <text>CaY&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;4&lt;/sub&gt;: Eu&lt;sup&gt;3+&lt;/sup&gt; phosphor; Dosimetry; Judd-Ofelt; Synthesis; w-LEDs</text>
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                <text>Elsevier B.V.</text>
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                <text>ISSN: 222860; CODEN: JMOSB</text>
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              <elementText elementTextId="208870">
                <text>Restricted Access; Hardcopy may be available in the library</text>
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                <text>Mannooparambil, Joseph Mathew; Saju, Roshan Koshy; Varghese, Rohan Thomas; Reena, Melbin J</text>
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                <text>A Hybrid Clustering Approach for Enhanced Classification Efficiency in Data Analytics</text>
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                <text>01-01-2025</text>
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              <elementText elementTextId="275477">
                <text>Proceedings of 2025 IEEE International Conference on Contemporary Computing and Communications, InC4 2025;</text>
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                <text>&lt;a href="https://doi.org/10.1109/InC465408.2025.11256425" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/InC465408.2025.11256425&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105030344478?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105030344478?origin=resultslist&lt;/a&gt;</text>
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                <text>Mannooparambil J.M., Christ University, Department of Computer Science and Engineering, Bengaluru, India; Saju R.K., Christ University, Department of Computer Science and Engineering, Bengaluru, India; Varghese R.T., Christ University, Department of Computer Science and Engineering, Bengaluru, India; Reena M.J., Christ University, Department of Computer Science and Engineering, Bengaluru, India</text>
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                <text>Clustering is a fundamental technique in data analytics that groups data points with similar characteristics into clusters. It is crucial for uncovering hidden patterns, trends, and structures in datasets. Clustering reduces the complexity of large datasets by summarizing data into representative clusters. This simplification makes it easier to analyze and interpret data, especially when dealing with high-dimensional datasets. By identifying meaningful groups, clustering provides actionable insights that supports decision-making. For instance, businesses can make concrete decisions about product recommendations, pricing strategies, or resource allocation based on cluster analysis. The approach described in the paper offers an efficient method for combining K-means and Gaussian Mixture Model (GMM) clustering techniques. The method combines two wellknown clustering techniques, K-means and GMM, to leverage their respective strengths. K-means is known for its simplicity and efficiency, while GMM can model complex data distributions with varying covariance structures. Instead of directly integrating the results of K-means and GMM, the approach uses a simplified averaging technique to converge the cluster labels obtained independently from both methods. This suggests that the method may involve assigning weights to the cluster labels obtained from K-means and GMM and then averaging them to obtain final cluster assignments. Overall, this approach presents a promising direction for combining K-means and GMM clustering techniques, offering a streamlined integration process that simplifies the consideration of varying covariance types in GMM. The effectiveness of the method is evaluated through empirical studies and comparisons with existing clustering approaches.   2025 IEEE.</text>
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                <text>Clustering; Evaluation Metrics; Gaussian Mixture Model; Integration; K-means; Visualization</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>ISBN: 979-833152118-9;</text>
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                <text>Artificial intelligence in developing countries: The impact of generative artificial intelligence (AI) technologies for development</text>
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                <text>artificial intelligence; developing countries; fourth industrial revolution; generative AI; technological change</text>
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                <text>Surfing Shoulder Surfing is a secret phrase-based attack which is a serious worry of protection in data security. Alphanumeric passwords are more helpless to attacks like shoulder surfing, dictionary attacks, etc., than graphical passwords. The creation of more muddled, challenging to-break passwords can be made simpler for clients with graphical authentication by consolidating the visuals and memory-based strategies like recall and recognition. In an imaged-based password, the user can choose pixels from the image to use as a secret key in the grid-based strategy, the user-selected image would show up on the screen with a framework overlay on it, and the client can pick explicit lattices to set their secret phrase. Besides, graphical passwords are powerless against shoulder surfing attacks, and due to this, clients are given a one-time made password via email. We investigated the limitations of image-based and grid-based authentication techniques and propose a grid-based graphical authentication system that addresses the limitations of image-based and grid-based techniques. The results of the grid-based graphical technique, as well as the image-based and grid-based approaches, have likewise been differentiated and analyzed. The convenience objective of our authentication system is to assist users in making better password selections, hence boosting security and broadening the usable password field. This method can be employed in many different contexts, such as forensic labs, banking, military, and other scenarios.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.</text>
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                <text>Manocha R., Department of Psychology, School of Psychological Sciences, Christ University, Nalagaddenahalli, Peenya, Bengaluru, 560073, India; Jose K.A., Department of Psychology, School of Psychological Sciences, Christ University, Nalagaddenahalli, Peenya, Bengaluru, 560073, India</text>
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                <text>Monetary policy and its transmissions have been debated by various schools of thought. The purpose of this paper is to empirically tests whether monetary policy has supply side effect influencing Indian economys total factor productivity. This study uses ARDL model to ascertain the long run relationship between monetary policy proxies and total factor productivity (TFP). Cointegration tests reveal that total factor productivity has a relationship with all of the monetary policy proxies. The ARDL results reveal a negative relationship between TFP and some monetary policy proxies in the short run, but a positive effect in the long run. These results showcase the possible supply side transmission of monetary policy in India, which can help in determining an optimal policy so as to augment TFP, an important driver of economic growth. The study only focusses on the Indian economy and spillover effects of other Asian economies on Indias TFP can also be examined.  The Author(s), under exclusive licence to The Indian Econometric Society 2024.</text>
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                <text>Manogna R.L.; Desai D.</text>
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                <text>Journal of Quantitative Economics, Vol-22, No. 1, pp. 45-61.</text>
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                <text>Manogna R.L., Department of Economics and Finance, BITS Pilani K K Birla Goa Campus, Sancoale, India; Desai D., Department of Economics, Christ University, Bangalore, India</text>
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                <text>Political Empowerment via Social Media? Following Political Influencers, Internal Political Efficacy, and Participation Among Youth</text>
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                <text>Manogna B.S., Christ University, Bengaluru, India; Paul G.R., Christ University, Bengaluru, India; Syed S.M., Vignans Foundation for Science, Technology and Research University, India; Sharma A., Lovely Professional University, India; Babu G.N.P.V., Christ University, Bengaluru, India; Kumar A., Mianz International College Mal Maldives</text>
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                <text>As the generations are moving ahead, do political leaders need to have an active presence on social platforms? The purpose of the study is to examine the impact of the online presence of politics on youth and whether there is any impact of online presence on national political efficacy. The study relies on secondary data collected from the extensive literature of scholarly articles to check the influence of social presence and its impact on the current generation. The findings of the study have revealed that social media has a significant influence on shaping ones opinion, regardless of age, and harnessing the social presence can be utilized as a proper tool to influence social opinion polls, and the study underscores the importance of digital engagement by political leaders. A strong, authentic presence on social media could serve not just for image building but for actively shaping public discourse and enhancing democratic participation, especially among younger demographics. While many studies explore political communication, this work situates itself uniquely in the digital-native context, focusing on evolving generational expectations of political visibility online.  2026 The authors.</text>
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                <text>Automation and the integration of artificial intelligence (AI) are reshaping modern business operations. This evolution has historical roots, with a growing emphasis on efficiency and cost reduction. AI's transformative role in supply chain optimization is evident through key technologies and applications, which empower businesses to make data-driven decisions, enhance customer experiences, and reduce costs. Real-world examples illustrate how companies leverage AI to streamline operations and deliver products and services with precision.  2024, IGI Global.</text>
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                <text>Utilization of AI Technology in Supply Chain Management, pp. 77-94.</text>
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                <text>Manohar Bhanushali M., VPM's Dr. V.N. Bedekar Institute of Management Studies, Thane, India; Bhardwaj S., RIMT University, India; Singh N.K., GNIOT Institute of Management Studies, India; Vijayalakshmi P., Jain University, India; Mazumdar N., University of Science and Technology, Meghalaya, India; Acharjee P.B., Christ University, India</text>
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                <text>Sumedha Journal of Management, Vol.8, Issue 1, pp.155-173, ISSN No: 2277-6753.</text>
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                <text>&lt;a href="https://www.indianjournals.com/ijor.aspx?target=ijor:sjm&amp;amp;volume=8&amp;amp;issue=1&amp;amp;article=013" target="_blank" title="An ideal MBA syllabus model -An Indian perspective" rel="noreferrer noopener"&gt;https://www.indianjournals.com/ijor.aspx?target=ijor:sjm&amp;amp;volume=8&amp;amp;issue=1&amp;amp;article=013&lt;/a&gt;</text>
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                <text>Smart detection of rice purity and its grading</text>
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                <text>Artificial rice; Classification; Data mining; Image processing; Pre-processing</text>
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                <text>The main food in India is Rice. Be it the breakfast, lunch, dinner or some snacks, for everything the most preferred ingredient in Rice. In compared with north Indians, Rice is most used by South Indians. Today's youngsters from villages are migrating to cities in search of jobs after their education. Even farmers have stopped their cultivation and are working towards different business. So, the yield of rice is reduced in India. One more reason for this is because of the poor monsoon. Government is finding it challenging to supply rice to all its consumers. It is expected, because for Rice the consumers are more compared to its production. Government has decided to import the rice from the neighboring countries. This neighboring country knows the demand of rice in India and started supplying contaminated rice. Currently our Government has no technology to check the quality of the rice which they are getting imported, so the result is plastic rice arrived in India. Indirectly, India is in huge loss in terms of money and damages for its citizens health. So, there is a need of automated system to detect the quality of the rice that are imported. Another use of such automated system is that most of the people are not able to identify the type of the rice and the quality of the rice. This system helps even common man a facility in identifying the type and quality of rice.  2017 IEEE.</text>
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                <text>Manohar M.; Chatrapathy K.; Sowmya M.S.</text>
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                <text>Proceedings of the 2017 3rd International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2017, pp. 71-73.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>&lt;a href="https://doi.org/10.1109/ICATCCT.2017.8389108" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICATCCT.2017.8389108&lt;/a&gt;
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                <text>ISBN: 978-153861144-9</text>
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                <text>Manohar M., Dept. of CSE, Faculty O/Engineering, Christ University, Bangalore, India; Chatrapathy K., Dept. of ISE, School O/Engineering and Technology, Jain University, Bangalore, India; Sowmya M.S., Dept. of ISE, School O/Engineering and Technology, Jain University, Bangalore, India</text>
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                <text>A Self-Attention Bidirectional Long Short-Term Memory for Cold Start Movie Recommendation Models</text>
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                <text>Bidirectional Long Short-Term Memory; Lemmatization; Movie recommendation; Self-attention; Stemming; Term frequency-inverse document frequency</text>
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                <text>Movie recommendation systems are useful tools that help users find relevant results and prevent information overload. On the other hand, the user cold-start issue has arisen because the system lacks sufficient user data. Furthermore, they are not very scalable for use in extensive real-world applications. One of the key strategies to address the sparsity and cold-start problems is to leverage other sources of information, including item or user profiles or user reviews. Processing client feedback is typically a challenging process that involves challenging the interpretation and analysis of the textual data. Thus, this research implements an efficient deep learning-based recommendation architecture. Following the acquisition of textual data from the Amazon product reviews database, stop word removal, lemmatization, and stemming techniques are applied to the data pre-processing which eliminate inconsistent and redundant data, facilitating the process of interpreting and utilising data. Then, the Term Frequency-Inverse Document Frequency (TF-IDF) method is applied to extract the feature values from the pre-processed text data. The extracted feature values are fed to the Self-Attention Bidirectional Long Short-Term Memory (SA-BiLSTM) that utilises the matrix factorization method framework's information sources. The SA-BiLSTM model obtained 95.93% of recall, 94.76% of precision, and 97.84% of accuracy on the amazon product reviews database.  2023 IEEE.</text>
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              <elementText elementTextId="170636">
                <text>Manohar M.; Reddy R.A.; Alzubaidi L.H.; Hameed Abdul Hussein A.; Buvaneswari P.R.</text>
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                <text>IEEE 1st International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023</text>
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            <elementTextContainer>
              <elementText elementTextId="170638">
                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>2023-01-01</text>
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                <text>&lt;a href="https://doi.org/10.1109/AIKIIE60097.2023.10390324" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/AIKIIE60097.2023.10390324&lt;/a&gt;
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            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="170641">
                <text>Restricted Access</text>
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            </elementTextContainer>
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                <text>ISBN: 979-835031646-9</text>
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          <element elementId="42">
            <name>Format</name>
            <description>The file format, physical medium, or dimensions of the resource</description>
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            <description>A language of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="170644">
                <text>English</text>
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          </element>
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            <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>
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                <text>Manohar M., Christ (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India; Reddy R.A., School of Computer Science and Artificial Intelligence, Sr University, Warangal, India; Alzubaidi L.H., The Islamic University, Najaf, Iraq; Hameed Abdul Hussein A., College of Pharmacy Ahl Al Bayt University, Karbala, Iraq; Buvaneswari P.R., School of Electrical and Electronic Engineering Vit Bhopal University, Sehhore, India</text>
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          <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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      <name>Conference Paper</name>
      <description>Faculty Publications- Conference Papers</description>
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        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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          <element elementId="50">
            <name>Title</name>
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                <text>An Abstractive Text Summarization Using Decoder Attention with Pointer Network</text>
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            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="170620">
                <text>Abstractive text summarization; Decoder Attention; Deep learning; Pointer network; Recall Oriented Understudy for Gisting Evaluation</text>
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                <text>Nowadays, large amounts of unstructured data are currently trending on social media and the Web. Text summarising is the process of extracting pertinent information in a concise manner without altering the content's core meaning. Summarising text by hand requires a lot of time, money, and effort. Although deep learning algorithms are commonly applied in abstractive text summarization, further research is clearly needed to fully understand their conjunction with semantic-based or structure-based approaches. The resume dataset is taken for this research work, which is gathered from Kaggle and the dataset includes 1,735 Resumes. This paper presents a unique framework based on the combination of semantic data transformations and deep learning approaches for improving abstractive text summarization. In an attempt to tackle the problem of unregistered words, a solution called Decoder Attention with Pointer Network (DA-PN) has been introduced. This method incorporates the use of a coverage mechanism to prevent word repetition in the generated text summaries. DA-PN is utilized for protecting the spread of increasing errors in generated text summaries. The performance of the proposed method is estimated using the evaluation indicator Recall Oriented Understudy for Gisting Evaluation (ROUGE) and attains an average of 26.28 which is comparatively higher than existing methods.  2023 IEEE.</text>
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              <elementText elementTextId="170622">
                <text>Manohar M.; Sunil G.; Al-Attabi K.; Mohammed I.H.; Buvaneswari P.R.</text>
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            <elementTextContainer>
              <elementText elementTextId="170623">
                <text>IEEE 1st International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023</text>
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              <elementText elementTextId="170624">
                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>2023-01-01</text>
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                <text>&lt;a href="https://doi.org/10.1109/AIKIIE60097.2023.10389942" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/AIKIIE60097.2023.10389942&lt;/a&gt;
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            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="170627">
                <text>Restricted Access</text>
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            </elementTextContainer>
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                <text>Only a few clinical procedures include the use of clinical methods for the early detection, observing, evaluation, and treatment evaluation of a range of medical illnesses. Knowing the analysis of medical images in computer vision necessitates being acquainted with the core concepts and uses of deep learning and artificial neural networks. The A rapidly expanding area of study is the Deep Learning Approach (DLA) in medical image processing. DLA is often used in medical imaging to determine if an ailment is present or not. By producing speedier, more accurate results in real time, deep learning algorithms may make the jobs of radiologists and orthopaedic surgeons easier. But the standard deep learning approach has reached its efficiencies. While offering an ideal solution known as boost-Net, we study numerous optimization strategies to increase the effectiveness of deep neural networks in this research. From a selection of well-known deep learning models, Champion-Net was selected as the deep learning model. The musculoskeletal radiograph-bone classification (MURA-BC) dataset is used in this investigation. Utilizing the train and test datasets, Enhance-Net's classification precision was evaluated.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.</text>
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                <text>Manoharan G., School of Business, SR University, Telangana, Warangal, India; Solanke D.R., Department of Applied Electronics, SGB Amravati University, Maharashtra, Amravati, 444602, India; Acharjee P.B., CHRIST University, Pune, India; Nayak C.K., Faculty of Emerging Technologies, Sri Sri University, Odisha, Cuttack, India; Sharma M.K., Rungta College of Pharmaceutical Sciences and Research, Chhattisgarh, Bhilai, 490024, India; Sahu D.N., Department of MCA, Gangadhar Meher University, Odisha, Sambalpur, India</text>
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                <text>A probabilistic inference algorithm for early detection of age related macular degeneration</text>
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                <text>Age related macular degeneration; Bayesian network; Probabilistic inference</text>
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                <text>Age Related Macular Degeneration or ARMD is a retinal disorder that causes blindness over people of older age group. ARMD is associated with age and is a leading cause of blindness around the world. There is no specific medicine to fully cure ARMD but its development can be controlled by regular exercises and a healthy lifestyle if it is detected early. With a rising population of old age group of people, it becomes important to detect ARMD as early as possible in order to contain its development further. This research attempts to develop an algorithm based on probabilistic inference through Bayesian Network by analyzing large datasets collected from previous cases where datasets include elements of risk factors that could cause ARMD along with eye images. Unlike most of the approaches in detecting ARMD this work not only analyses eye images but also includes analysis of various factors causing the disorder. To include the study and analysis of the presence of factors causing ARMD is sensible because those factors are good indicators when the need is an early detection.  2020, Engg Journals Publications. All rights reserved.</text>
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                <text>Manoharan H.; Rajesh R.</text>
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                <text>Indian Journal of Computer Science and Engineering, Vol-11, No. 1, pp. 76-80.</text>
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                <text>Manoharan H., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Rajesh R., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, Karnataka, India</text>
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                <text>India-Maldives Development Partnership: Promises and Possibilities</text>
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                <text>Indias approach towards Development Partnership with the external world has been inclusive, humanistic, unconditional, comprehensive and futuristic. India-Maldives Development Partnership has to be seen in the context of India-Maldives relations that have been described as close, cordial and multi-dimensional. The Maldives undoubtedly occupies a very special place in Indias Neighborhood First policy. Indias development partnership with the Maldives goes with the `SAGAR (Security and Growth for All in the Region) vision of the Government of India. The partnership is characterised by transparency and as per the needs and priorities of the Maldivians. It touches every facet of the development of the Maldives to enhance stability and prosperity of the atoll state. Involving about US$ 3 billion in terms of grants, loans, budgetary support, capacity building and training assistance, the development partnership support is intended to reach the beneficiaries directly via the local councils. However, there are various challenges in the process of implementation of the projects under the development partnership. Yet, the future of the partnership looks promising. The main objective of the paper is to answer the following questions: What is the context of development partnership between India and Maldives? In what manner India has extended development assistance to its neighbour? Are there any challenges in the process of rendering such assistance? What is the way forward?  2024 Indian Council of World Affairs.</text>
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                <text>India's Development Partnership: Expanding Vistas, pp. 111-124.</text>
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