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                <text>Conversational Agents and Chatbots: Current Trends</text>
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                <text>Languages facilitate the communication and interaction process among people. Computers learn to communicate with humans intelligently with the help of conversational agents and chatbots based on Natural Language Processing (NLP). Conversational agents and chatbots are gaining popularity in various applications. The development of chatbots or conversational agents is tightly coupled with an organizations customer service requirement. However, the background procedures that power the bots brain are more or less dependent on Artificial Intelligence-based processes. NLP mechanisms powered by various Deep Learning techniques are often used in the training and development of such intelligent agents. These bots inevitably become more competent as they interact with more people. The interactions between a customer and the bot are usually used as data in further training iterations. Chatbots are likely to respond with faster and more precise suggestions leading to solutions for frequently asked questions. Therefore, the current trends indicate the need for a supplementary system rather than substituting human agents existing customer service. The customer experience and intelligence of the chatbots are improved with the help of data analysis and training with the use of Deep Learning techniques. The chapter covers the current trends of conversational agents and chatbots, how the various Artificial Intelligence techniques have transformed the development of multiple architectures of these intelligent systems, and it compares the different state-of-the-art NLP-based chatbot architectures.  2024 selection and editorial matter, Anitha S. Pillai and Roberto Tedesco.</text>
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                <text>Joseph A.; Eapen N.G.</text>
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                <text>Machine Learning and Deep Learning in Natural Language Processing, pp. 17-52.</text>
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                <text>2023-01-01</text>
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                <text>&lt;a href="https://doi.org/10.1201/9781003296126-4" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1201/9781003296126-4&lt;/a&gt;
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                <text>ISBN: 978-100096085-3; 978-103226463-9</text>
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                <text>Joseph A., Department of Data Science, CHRIST Deemed to be University, Pune Lavasa Campus, India; Eapen N.G., Department of Data Science, CHRIST Deemed to be University, Pune Lavasa Campus, India</text>
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                <text>Workforce Forecasting Using Artificial Intelligence</text>
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                <text>Workforce forecasting predicts an organizations future demand and supply of the workforce. Each organization has its strategies to manage and track the appropriate workforce. The adequate forecasting technique for the workforce involves data analysis and pattern mining from various data points. Some of the critical attributes considered for the analysis and the forecasting of the workforce requirement include the data such as demographics, economic trends, and labor market conditions; these help in calculating informed predictions about future workforce requirements [1,2]. The primary aim of workforce forecasting is to ensure that an organization has suitable employees with the appropriate skills to meet its business needs by helping organizations make informed decisions about staffing levels, employee training, and other workforce management strategies.  2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar.</text>
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                <text>Joseph A.; Johnson A.; Cheriyan A.</text>
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                <text>Artificial Intelligence in Forecasting: Tools and Techniques, pp. 146-172.</text>
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                <text>&lt;a href="https://doi.org/10.1201/9781003399292-11" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1201/9781003399292-11&lt;/a&gt;
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                <text>ISBN: 978-104005150-4; 978-103250615-9</text>
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                <text>Joseph A., Department of Data Science, CHRIST (Deemed to be University), Lavasa Campus, Pune, India; Johnson A., Department of Data Science, CHRIST (Deemed to be University), Lavasa Campus, Pune, India; Cheriyan A., School of Business and Management (BBA), CHRIST (Deemed to be University), Lavasa Campus, Pune, India</text>
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                <text>The role of incentives in fostering green behaviour among the emerging workforce</text>
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                <text>Green behaviour refers to those behaviours that are pro-environmental in nature. Green behaviour is essential in an organization to ensure that the organization is meeting its organizational sustainability. Employees at all levels must support and participate in green behaviour. One way of encouraging employees to participate in green behaviour is by inducing them through incentives. This chapter dwells on why it is important to introduce green incentives in the workplace to encourage green behaviour. A short survey was conducted among employees in the Indian subcontinent to understand whether incentives can act as a catalyst in motivating green behaviour in the organization. It explores the advantages and disadvantages of bringing green incentives in the organization and the guidelines a company must keep in mind while designing an attractive green incentive system to motivate employees to engage in green behaviour  2024, IGI Global. All rights reserved.</text>
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                <text>Joseph A.; Jose N.</text>
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                <text>Building Sustainable Human Resources Management Practices for Businesses, pp. 291-303.</text>
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                <text>IGI Global</text>
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                <text>&lt;a href="https://doi.org/10.4018/979-8-3693-1994-9.ch018" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/979-8-3693-1994-9.ch018&lt;/a&gt;
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                <text>ISBN: 979-836931995-6; 979-836931994-9</text>
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                <text>Joseph A., Christ University, India; Jose N., Christ University, India</text>
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                <text>Influence of pulse reverse current parameters on electrodeposition of copper-graphene nanocomposite coating</text>
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                <text>Copper-graphene nanocomposite coating; Corrosion resistance; Crystallographic texture; Microhardness; Pulse reverse electrodeposition</text>
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                <text>This work focuses on the influence of pulse reverse current parameters such as duty cycle and frequency on the microstructure and properties of graphene reinforced copper nanocomposite (Cu-Gr) coating. Graphene nanosheets were prepared by a liquid phase exfoliation technique and characterized using FE-SEM and Raman spectroscopy. Cu-Gr nanocomposite coating on stainless steel was prepared by pulse reverse electrodeposition method. The influence of pulse reverse current parameters such as duty cycle and frequency on the coating structure and texture was analyzed. By reducing the duty cycle and increasing frequency, a high amount of graphene co-deposition was achieved. A duty cycle of 40%, frequency of 1000 Hz and stirring speed of 500 rpm produced Cu-Gr coatings with maximum graphene codeposition. XRD analysis showed that the change in duty cycle and pulse frequency influenced the crystal structure, preferred orientation, and crystallite size of the deposit. A high pulse frequency improved the compactness of the composite coating, while longer pulse off-time and application of reverse pulse resulted in highly oriented (220) texture of pure Cu and Cu-Gr nanocomposite coatings. Due to graphene co-deposition, the copper grains became more refined, and hence the microhardness of the composite coating showed a tremendous increase compared to pure Cu coating. The Tafel polarization and electrochemical impedance studies revealed that pulse reverse electrodeposited Cu-Gr coating has higher corrosion resistance than pure Cu coating due to strong (220) texture and barrier effect of graphene.  2021 The Authors</text>
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                <text>Joseph A.; Kirubasankar B.; Mathew A.M.; Narayanasamy M.; Yan C.; Angaiah S.</text>
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                <text>Applied Surface Science Advances, Vol-5</text>
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                <text>Elsevier B.V.</text>
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                <text>Joseph A., Electro-Materials Research Laboratory, Centre for Nanoscience and Technology, Pondicherry University, Puducherry, 605014, India, School of Materials Science and Engineering, National Institute of Technology Calicut, Kozhikode, 673601, India; Kirubasankar B., Electro-Materials Research Laboratory, Centre for Nanoscience and Technology, Pondicherry University, Puducherry, 605014, India, School of Materials Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, China; Mathew A.M., Department of Chemistry, Christ University, Bangalore, 560029, India; Narayanasamy M., Electro-Materials Research Laboratory, Centre for Nanoscience and Technology, Pondicherry University, Puducherry, 605014, India, School of Materials Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, China; Yan C., School of Materials Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, China; Angaiah S., Electro-Materials Research Laboratory, Centre for Nanoscience and Technology, Pondicherry University, Puducherry, 605014, India</text>
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                <text>In today's digital age, manual attendance tracking is plagued by inefficiency and the potential for inaccuracies, often leading to proxy attendance. The main aim of this research work is to manage and monitor the student's attendance by using face recognition technology. This proposed model is mainly categorized four major modules. First module is database creation. Second module is face detection. Then third module is face recognition and final module is automatic attendance updating process. Student images are compiled to create a comprehensive database, ensuring inclusivity across the class roster. The system utilizes the face recognition library, which relies on deep learning based algorithms for face detection and recognition during testing. This face recognition part Convolutional Neural Network algorithm is used. The system matches detected faces with the known database and marks attendance, ensuring a streamlined and accurate attendance tracking process. This innovative approach has the potential to revolutionize attendance management in educational settings, offering a contactless and efficient solution while mitigating proxy attendance concerns. The proposed model is to compare the accuracy level of face recognition.   2023 IEEE.</text>
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                <text>Joseph A., (Deemed to Be University), Department of Cse Christ, India; Nair A., (Deemed to Be University), Department of Cse Christ, India; Koshy A.B., (Deemed to Be University), Department of Cse Christ, India; Nallaballi M., School of Engineering and Technology Christ (Deemed to Be University), India; Jayapandian N., School of Engineering and Technology Christ (Deemed to Be University), India</text>
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                <text>Autism or autism spectrum disorder (ASD) is a developmental disorder comprising a group of psychiatric conditions originating in childhood that involve serious impairment in different areas. This paper aims to detect the principal genes which cause autism. Those genes are identified using a multi-layer perceptron network with sigmoid as an activation function. The multi-layer perceptron model selected sixteen genes through different feature selection techniques and also identified a combination of genes that caused the disease. From the background study, it is observed that CAPS2 and ANKUB1 are the major disease-causing genes but the accuracy of the model is less. The selected 16 genes along with CAPS2 and ANKUB1 produce more accuracy than the existing model which proved 95% prediction rate. The analysis of the proposed model shows that the combination of the predicted genes along with CAPS2 and ANKUB1 will help to identify autism at an early stage.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Smart Innovation, Systems and Technologies, Vol-282, pp. 269-279.</text>
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                <text>ISSN: 21903018; ISBN: 978-981169668-8</text>
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                <text>Joseph A., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Nizar Banu P.K., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India</text>
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                <text>Basic human values of Indian management professionals: a demographic profile</text>
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                <text>basic human values; conservation; demographic factors; managers; MANOVA; openness to change; recruiters; respect for humanity; Schwartz; self-enhancement</text>
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                <text>This study tries to check the degree of basic human values among management professionals in India with considerable cultural and linguistic differences and how it varies across the different demographic influences. We have checked the impact of demographic variables like gender, age, education, type of organisation, place of residence, and work experience on basic human values. Hypotheses testing were conducted using MANOVA. It was inferred that the perception regarding the degree of basic human values differs among different management professionals based on their age, gender, education, type of organisation, and place of residence. Surprisingly, the work experience of the person does not have a significant influence on basic human values. Consequently, we imply that the demographics of an individual carve their basic human values. The findings and inferences of the proposed study will be of great importance to policymakers and recruiting managers to fetch the right candidate. Copyright  2023 Inderscience Enterprises Ltd.</text>
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                <text>International Journal of Business Governance and Ethics, Vol-17, No. 6, pp. 689-704.</text>
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                <text>ISSN: 14779048</text>
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                <text>Joseph A., School of Arts and Humanities, CHRIST (Deemed to be University), Bangalore, 560029, India; Raju S., School of Management, National Institute of Technology Karnataka, Mangalore, Surathkal, 575025, India; Rofin T.M., National Institute of Industrial Engineering (NITIE), Maharashtra, Mumbai, 400087, India</text>
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                <text>Suicidal behavior prediction using data mining techniques</text>
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                <text>Classification; Data Mining; Depression; Prediction; Risk Factors; Suicide</text>
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                <text>Background: Suicide is one of the most serious public health problem that has affected many people. After being recognized as a public health priority by the WHO (World Health Organization) various studies have been going out for its prevention. It is one of a serious health problem and it is preventable and can be controlled by proper interventions and study in the field. The objective of the study is to create a prediction model for individuals who are at higher risk of suicide by studying the different predictors of suicide such as depression, anxiety, hopelessness, stress etc. by using data mining techniques for the prediction. Study Design: Systematic review and predictive analysis for suicidal behavior. Methods: The research applies data mining process to analyze the data and on the basis of analysis create the model to predict suicidal behaviors present in the individual. Prediction is done on the basis of analysis of risk factors which are Depression, anxiety, hopelessness, stress, or substance misuse which is calculated by using various psychological measures such as Beck hopelessness scale,suicidal ideation subscale,hospital anxiety and depression scale.Various data mining algorithms for classification are compared for the purpose of prediction. Results: Six different data mining classification algorithms which are namely Classification Via Regression, Logistic Regression. Random Forest, Decision Table, SMO are compared and Classification Via Regression was found to the highest accuracy in prediction. Conclusions: Data required for the development of such a model requires continuous monitoring and needs to be updated on a periodic basis to increase the accuracy of prediction.  IAEME Publication.</text>
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                <text>Joseph A.; Ramamurthy B.</text>
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                <text>International Journal of Mechanical Engineering and Technology, Vol-9, No. 4, pp. 293-301.</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045951449&amp;amp;partnerID=40&amp;amp;md5=74f2c78c8b63037785fb7ed22ef9b8a1" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045951449&amp;amp;partnerID=40&amp;amp;md5=74f2c78c8b63037785fb7ed22ef9b8a1&lt;/a&gt;</text>
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                <text>ISSN: 9766340</text>
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                <text>English</text>
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                <text>Joseph A., Department of computer science, Christ University, Bangalore, Karnataka, India; Ramamurthy B., Department of computer science, Christ University, Bangalore, Karnataka, India</text>
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          <element elementId="50">
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                <text>Lifestyle Diseases Prevalent in Urban Slums of South India</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="183902">
                <text>Diabetes; Health; Heart disease; Hypertension; Logistic regression; Slums; Urban health</text>
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            <name>Description</name>
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                <text>Lifestyle diseases have always been considered to be a malady of the middle and upper classes of society. Recent findings indicate that these chronic non-communicable diseases are common among the lower socioeconomic classes as well. The objective of this study was to assess the prevalence of lifestyle diseases in three cohorts of urban slums, namely, waste pickers living in non-notified slums, communities living in notified slums, and BBMP Pourakarmikas, and to identify the risk factors among the three cohorts contributing to the common lifestyle diseases including hypertension, diabetes, and cardiovascular diseases. In this study, the data was collected by conducting health camps, followed by analysis of the data using logistic regression, HosmerLemeshow test and ROC Curve Analysis. The prevalence of hypertension was found 13.35%, diabetes-8.53% and cardiovascular disease-3.59%. These were significantly associated with substance abuse, high BMI, and age.  2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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              <elementText elementTextId="183904">
                <text>Joseph A.A.; Joshi H.; Vanlalchunga M.V.; Ray S.</text>
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            </elementTextContainer>
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            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="183905">
                <text>Lecture Notes in Networks and Systems, Vol-290, pp. 356-365.</text>
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              <elementText elementTextId="183906">
                <text>Springer Science and Business Media Deutschland GmbH</text>
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              <elementText elementTextId="183907">
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                <text>&lt;a href="https://doi.org/10.1007/978-981-16-4486-3_40" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-16-4486-3_40&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115116416&amp;amp;doi=10.1007%2F978-981-16-4486-3_40&amp;amp;partnerID=40&amp;amp;md5=a68fddf45022bbb7e331790b3cf89cf4" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115116416&amp;amp;doi=10.1007%2f978-981-16-4486-3_40&amp;amp;partnerID=40&amp;amp;md5=a68fddf45022bbb7e331790b3cf89cf4&lt;/a&gt;</text>
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            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="183909">
                <text>Restricted Access</text>
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              <elementText elementTextId="183910">
                <text>ISSN: 23673370; ISBN: 978-981164485-6</text>
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              <elementText elementTextId="183912">
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              <elementText elementTextId="183914">
                <text>Joseph A.A., Department of Statistics, CHRIST (Deemed To Be University), Bangalore, India; Joshi H., Department of Statistics, CHRIST (Deemed To Be University), Bangalore, India; Vanlalchunga M.V., Department of Statistics, CHRIST (Deemed To Be University), Bangalore, India; Ray S., Department of Statistics, CHRIST (Deemed To Be University), Bangalore, India</text>
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              <name>Title</name>
              <description>A name given to the resource</description>
              <elementTextContainer>
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      <description>Faculty Publications -Articles</description>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="135801">
                <text>Gender Issues and Related Social Stigma Affecting Patients with a Disorder of Sex Development in India</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="135802">
                <text>Disorders of sex development; Gender bias; Gender dysphoria; Gender identity; Social stigma</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="135803">
                <text>Children with disorders of sex development (DSD) manifest at birth with malformed genitalia or later with atypical pubertal development. Those born with malformed genitalia are often diagnosed at birth. However, in resource-poor countries like India, where not all births are supervised by healthcare workers, some of these children remain undiagnosed until puberty or even later. The aim of this study was to assess the gender issues and psychosocial problems of children with DSD. Participants included 205 children with DSD (103 with 46,XX DSD and 102 with 46,XY DSD). Both the children with DSD and their parents underwent semistructured interviews by a clinical psychologist. The birth of a child with DSD was perceived as a major medical and social problem by parents from all socioeconomic strata. Mothers were distressed as many believed the DSD condition was transmitted through the mother. Children who were not diagnosed and treated during infancy or early childhood experienced considerable social discrimination not only from relatives and friends but also from medical and paramedical staff in hospitals. Several patients had been operated during infancy without an etiological diagnosis and without provision of adequate information to the parents. Some children had problems related to complications of surgery. Most teenage patients with 5?-reductase-2 deficiency reared as females presented with gender dysphoria, while children with androgen insensitivity (except for one) or with gonadal dysgenesis developed a gender identity concordant with their gender of rearing. Parents of children with DSD preferred a male gender assignment for their children (if that was possible) because of the social advantages of growing up male in a patriarchal society.  2016, Springer Science+Business Media New York.</text>
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            <elementTextContainer>
              <elementText elementTextId="135804">
                <text>Joseph A.A.; Kulshreshtha B.; Shabir I.; Marumudi E.; George T.S.; Sagar R.; Mehta M.; Ammini A.C.</text>
              </elementText>
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              <elementText elementTextId="135805">
                <text>Archives of Sexual Behavior, Vol-46, No. 2, pp. 361-367.</text>
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            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="135806">
                <text>Springer New York LLC</text>
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                <text>&lt;a href="https://doi.org/10.1007/s10508-016-0841-0" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s10508-016-0841-0&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-84988624576&amp;amp;doi=10.1007%2Fs10508-016-0841-0&amp;amp;partnerID=40&amp;amp;md5=f51ff1f5118d99258c617433813ffccc" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-84988624576&amp;amp;doi=10.1007%2fs10508-016-0841-0&amp;amp;partnerID=40&amp;amp;md5=f51ff1f5118d99258c617433813ffccc&lt;/a&gt;</text>
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            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
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              <elementText elementTextId="135809">
                <text>Restricted Access</text>
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                <text>ISSN: 40002; PubMed ID: 27649694; CODEN: ASXBA</text>
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            <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>
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              <elementText elementTextId="135812">
                <text>English</text>
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                <text>Joseph A.A., Department of Psychiatry, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India; Kulshreshtha B., Department of Endocrinology, Ram Manohar Lohia Hospital, New Delhi, India; Shabir I., Department of Endocrinology, All India Institute of Medical Sciences, New Delhi, India; Marumudi E., Department of Endocrinology, All India Institute of Medical Sciences, New Delhi, India; George T.S., Department of Psychology, Christ University, Bangalore, India; Sagar R., Department of Psychiatry, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India; Mehta M., Department of Psychiatry, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India; Ammini A.C., Department of Endocrinology, All India Institute of Medical Sciences, New Delhi, India</text>
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            <element elementId="50">
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                <text>A Comparative Study of Collaborative Movie Recommendation System</text>
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            <description>The topic of the resource</description>
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                <text>Clustering; Collaborative Filtering; Content-based Filtering; Machine Learning; Movie Recommendation; User ratings</text>
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                <text>The number of movies available has expanded, making it challenging to select a film that uses current technology to meet users' needs. Following the widespread use of internet services, recommendation systems have become commonplace. The objective for all recommendation systems now is to employ filtering and clustering algorithms to recommend content users are interested in. Suggestions for a media commodity like movies are offered to consumers by locating user profiles of people with comparable likes which makes users' preferences initially determined to allow them to rate movies of their choosing. After a period of use, the recommender system understands the user and offers films that are more likely to receive higher ratings. A comparison study on the existing models helps to understand future scope and improvements for more personalized models for movie recommendation. In comparison to previous models, the MovieLens dataset gives a dependable model that is exact and delivers more customized movie suggestions. In this paper, an approach to do a detailed study and review the user preferences based on item and content of movies has been made to understand the filtering techniques of the collaborative recommendation system to increase accuracy and give highly rated movies as recommendations to the user is carried and based on the results the recommendation system is built with a content-based filtering technique.  2022 IEEE.</text>
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                <text>Proceedings of the International Conference on Electronics and Renewable Systems, ICEARS 2022, pp. 1579-1583.</text>
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                <text>Joseph A.A., Christ (Deemed to Be University), Department of Data Science, India; Nair A.M., Christ (Deemed to Be University), Department of Data Science, India</text>
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                <text>Swarm Intelligence Decentralized Decision Making In Multi-Agent System</text>
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              <elementText elementTextId="173853">
                <text>Artificial Intelligence; Blockchain; Decentralize; Multi -agent; Optimization; Swarm Intelligence</text>
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                <text>This research aims to understand how groups of agents can make decisions collectively without relying on a central authority. The research could focus on developing algorithms and models for distributed problem solving, such as consensus-reaching and voting methods, or for coordinating actions among agents in a decentralized manner. The research could also look into the application of these methods in various fields like distributed robotics, swarm intelligence, and multi-agent systems in smart cities and transportation networks. Swarm intelligence in decentralization is an emerging field that combines the principles of swarm intelligence and decentralized systems to design highly adaptive and scalable systems. These systems consist of a large number of autonomous agents that interact with each other and the environment through local communication and adapt their behaviors based on environmental cues. The decentralized nature of these systems makes them highly resilient and efficient, with potential applications in areas such as robotics, optimization, and block chain technology. However, designing algorithms and communication protocols that enable effective interaction among agents without relying on a centralized controller remains a key challenge. This article proposes a model for swarm intelligence in decentralization, including agents, communication, environment, learning, decision-making, and coordination, and presents a block diagram to visualize the key components of the system. The paper concludes by highlighting the potential benefits of swarm intelligence in decentralization and the need for further research in this area.  2023 IEEE.</text>
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                <text>Proceedings of the 8th International Conference on Communication and Electronics Systems, ICCES 2023, pp. 1425-1430.</text>
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                <text>ISBN: 979-835039663-8</text>
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                <text>Joseph A.A., Christ (Deemed to Be University), Department of Cse, India; Nambiar G.S., Christ (Deemed to Be University), Department of Cse, India; Jayapandian N., Christ (Deemed to Be University), Department of Cse, India</text>
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              <elementText elementTextId="92063">
                <text>The Cartesian product of wheel graph and path graph is antimagic</text>
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          <element elementId="49">
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            <description>The topic of the resource</description>
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                <text>antimagic labeling; Graph labeling; magic labeling</text>
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                <text>Suppose each edge of a simple connected undirected graph is given a unique number from the numbers 1, 2, . . ., q, where q is the number of edges of that graph. Then each vertex is labelled with sum of the labels of the edges incident to it. If no two vertices have the same label, then the graph is called an antimagic graph. We prove that the Cartesian product of wheel graph and path graph is antimagic.  2023 Azarbaijan Shahid Madani University.</text>
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                <text>Joseph A.K.; Kureethara J.V.</text>
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              <elementText elementTextId="92067">
                <text>Communications in Combinatorics and Optimization, Vol-8, No. 4, pp. 639-647.</text>
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                <text>&lt;a href="https://doi.org/10.22049/CCO.2022.27645.1307" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.22049/CCO.2022.27645.1307&lt;/a&gt;
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                <text>ISSN: 25382128</text>
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                <text>Joseph A.K., Department of Mathematics, Christ University, Bangalore, India; Kureethara J.V., Department of Mathematics, Christ University, Bangalore, India</text>
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                <text>The times of jeopardising free speech</text>
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              <elementText elementTextId="74883">
                <text>democracy; expression; free speech; India; media; press freedom</text>
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                <text>Press freedom is at stake in India, which holds a dismal rank of 159 among 180 countries in the Press Freedom Index 2024. While dissent and democracy ideally go hand in hand, a glance at the present situation in India suggests that these terms are perceived as antonyms in practice. The state is exerting its repressive power over dissenters, particularly targeting media outlets that do not align with the states interests. The media has a great responsibility and obligation to the citizens to bring out real stories with diligence and truthfulness. In India, the depiction of socioeconomic and political realities is mostly done at utmost risk and with an air of uneasiness. The truth remains elusive to the majority of the public, as they receive information from a restrained source constantly under government surveillance. This article aims to analyse the current situation of media and democracy in India with reference to freedom of speech and expression. The writing is an outcome of analysing the past and present sociopolitical contexts in India concerning the concept of free speech.  The Author(s) 2024.</text>
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                <text>Media, Culture and Society, Vol-46, No. 8, pp. 1737-1750.</text>
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                <text>SAGE Publications Ltd</text>
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                <text>&lt;a href="https://doi.org/10.1177/01634437241282179" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1177/01634437241282179&lt;/a&gt;
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                <text>Joseph A.P., Department of Sociology and Social Work, Christ (Deemed to be University), Bengaluru, India, School of Social Work, Marian College Kuttikkanam Autonomous, Kerala, Kuttikkanam, India; Babu A., School of Social Work, Marian College Kuttikkanam Autonomous, Kerala, Kuttikkanam, India, School of Social Work, Tata Institute of Social Sciences Guwahati Off-Campus, Assam, India</text>
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                <text>Frontiers in Psychiatry, Vol-15</text>
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                <text>Joseph A.P., Christ University, Karnataka, Bangalore, India, School of Social Work, Marian College Kuttikkanam Autonomous, Kuttikkanam, India; Babu A., School of Social Work, Marian College Kuttikkanam Autonomous, Kuttikkanam, India, Tata Institute of Social Sciences Guwahati Off-Campus, Jalukbari, Assam, India; Prakash L.T.O., Christ University, Karnataka, Bangalore, India</text>
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                <text>artificial intelligence-AI; low-and middle-income countries (LMICs); machine learning (ML); mental healthcare; psychological challenges; virtual reality (VR); wives of individuals with alcohol use disorder</text>
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                <text>Frontiers in Psychiatry, Vol-15</text>
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                <text>Joseph A.P., Department of Sociology &amp;amp; Social Work, Christ (Deemed to be University), Karnataka, Bangalore, India, School of Social Work, Marian College Kuttikkanam Autonomous, Kuttikkanam, Kerala, India; Babu A., School of Social Work, Marian College Kuttikkanam Autonomous, Kuttikkanam, Kerala, India, School of Social Work, Tata Institute of Social Sciences Guwahati Off-Campus, Assam, Jalukbari, India; Prakash L.T.O., Department of Sociology &amp;amp; Social Work, Christ (Deemed to be University), Karnataka, Bangalore, India</text>
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                <text>Background: Couple interventions focus on resolving relationship issues and improving partners' intimacy. Several intervention models are used on different occasions to deal with the issues. The present systematic review and meta-analysis investigated the effectiveness of such couple interventions dealing with marital distress. Methods: Using the PRISMA guidelines for reporting systematic reviews and meta-analyses, a search was carried out to identify published articles in the areas of study. The meta-analysis investigated the effectiveness of couple interventions by comparing the post-intervention assessments of the experimental and control groups. Results: The systematic review helped to identify twelve empirical studies published within the last ten years in the following databases: ScienceDirect, EBSCO, APA PsycINFO, NCBI, ProQuest, and Google Scholar. Meta-analysis showed a statistically significant overall effect size (Cohen's d = 0.85, 95% CI: 0.56-1.14). Cochran's Q showed that there was a substantial difference between the studies. There were signs of publication bias. Conclusion: The current study revealed an overall large effect size, indicating that different couple interventions had a noticeable impact on distressed couples who received interventions as opposed to couples who did not receive any interventions.  2025 Joesph et al.</text>
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                <text>Joseph B.; Joseph V.K.; Rajan S.K.</text>
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                <text>Iranian Journal of Public Health, Vol-54, No. 1, pp. 112-123.</text>
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                <text>Tehran University of Medical Sciences</text>
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                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 22516085</text>
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                <text>Joseph B., School of Psychological Sciences, CHRIST University, Bangalore, India; Joseph V.K., School of Psychological Sciences, CHRIST University, Bangalore, India; Rajan S.K., School of Psychological Sciences, CHRIST University, Bangalore, India</text>
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