347 20 16481 Dublin Core 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/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core 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/. Title A name given to the resource Explorations of the links between multiculturalism and religious diversity Description An account of the resource This chapter explores the complex intersections of multiculturalism and religious diversity in educational settings. It examines the religious landscape in the context of education and how religious diversity is addressed in educational policies and procedures. It discusses the role of faith in education, highlighting its importance and potential limitations. Furthermore, it explores the interplay between multiculturalism and religious diversity, identifying potential challenges and opportunities. Strategies for addressing these challenges and leveraging the opportunities are discussed, including intercultural dialogue, curriculum integration, and parent and community engagement. The chapter presents case studies that illustrate the complexities of multiculturalism and religious diversity in educational practices, analyzing their successes and challenges. Lessons learned from these case studies and implications for future practice are discussed, emphasizing the need for policy development, curriculum design, teacher training, and community engagement. 2023 by IGI Global. All rights reserved. Creator An entity primarily responsible for making the resource Singha S.; Singha R.; Ruben V.M. Source A related resource from which the described resource is derived The Role of Faith and Religious Diversity in Educational Practices, pp. 120-148. Publisher An entity responsible for making the resource available IGI Global Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/978-1-6684-9184-3.ch006" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/978-1-6684-9184-3.ch006</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173447911&doi=10.4018%2F978-1-6684-9184-3.ch006&partnerID=40&md5=7ac978cfbbcbb2472952814d7352ba92" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173447911&doi=10.4018%2f978-1-6684-9184-3.ch006&partnerID=40&md5=7ac978cfbbcbb2472952814d7352ba92</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166849185-0; 978-166849184-3 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Singha S., Kristu Jayanti College (Autonomous), India; Singha R., Christ University (Deemed), India; Ruben V.M., Christ University (Deemed), India Dublin Core 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/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core 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/. Creator An entity primarily responsible for making the resource Tiwari, Akshra; Dass, Teresa Mahima; Tiwari, Vibha; Alapatt, Bosco Paul Title A name given to the resource Exploratory Analysis and Pattern Recognition in Energy Production and Demand: A Data-Driven Approach Using Multi-Source Energy Metrics Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 International Conference on Engineering Innovations and Technologies, ICoEIT 2025;pp.1418-1423 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICoEIT63558.2025.11211558" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICoEIT63558.2025.11211558</a> <a href="https://www.scopus.com/pages/publications/105025045981?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105025045981?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Tiwari A., School of Sciences, Christ University, Delhi, India; Dass T.M., School of Sciences, Christ University, Delhi, India; Tiwari V., Centre for Artificial Intelligence, Madhav Inst. of Tech & Science, Gwalior, India; Alapatt B.P., School of Sciences, Christ University, Delhi, India Description An account of the resource Hydropower is a leading renewable energy source due to its high efficiency and low operational costs. However, it still faces significant environmental, operational, and forecasting challenges. This paper explores the use of machine learning (ML) models such as SARIMA, Random Forest (RF), and Neural Basis Expansion Analysis for Time Series (NBEATS) to optimize hydropower operations. By analyzing diverse data sets, including hydrometeorological data, plant operations, sensor inputs, and other energy production and demand metrics such as solar, wind, coal, nuclear, and storage, ML enhances decision-making in areas such as inflow forecasting, predictive maintenance, and environmental sustainability. The paper presents an exploratory analysis of 48 -hour energy production and demand patterns across multiple sources (Hydro, Coal, Solar, Wind, Nuclear, and Storage), offering insights into interdependencies and system behavior. It also reviews current ML applications in hydropower, highlights challenges such as data quality and model interpretability, and discusses emerging technologies such as reinforcement learning, explainable AI (XAI), and digital twins as promising future directions. 2025 IEEE. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833152595-8; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core 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/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core 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/. Creator An entity primarily responsible for making the resource Thulasi, V.; Sathya, P. Title A name given to the resource Exploratory Analysis of Anthropometric and Demographic Factors Influencing PCOS: A Study on BMI, Weight, and Waist Ratio Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems;Volume;1638 LNNS;pp.181-196 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-95-3309-1_13" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-95-3309-1_13</a> <a href="https://www.scopus.com/pages/publications/105036735654?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105036735654?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Thulasi V., Christ (Deemed to be University), Bengaluru, India; Sathya P., Christ (Deemed to be University), Bengaluru, India Description An account of the resource Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder affecting women of reproductive age, often leading to hormonal imbalances, obesity, and an increased risk of metabolic and cardiovascular diseases. This study examines the impact of PCOS on anthropometric and demographic variables such as Body Mass Index (BMI), weight, height, and waist ratio, using a comprehensive dataset. By comparing these factors between individuals with and without PCOS, the study aims to identify significant differences and correlations, thereby contributing to a deeper understanding of PCOS and informing clinical management strategies. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. Subject The topic of the resource Age distribution; Anthropometric measurements; BMI; Metabolic health; Polycystic Ovary Syndrome (PCOS); Weight Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981953308-4; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core 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/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core 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/. Title A name given to the resource Exploratory analysis of legal case citation data using node embedding Subject The topic of the resource Graph embedding; Legal citation network; Network analysis; Node embed-ding, Node2vec Description An account of the resource Legal case citation network is primary tool to understand mutable landscape of the legal domain. These networks are also used to study legal knowledge transfer, similar precedents and inter-relationship among laws of a judiciary. These networks are often very huge and complex due to the multidimensional texture of this domain. In recent years, network embedding using deep learning emerges as a promising breakthrough for analyzing networks. This paper presents a novel approach of learning vector representation for a legal case based on its citation context in the network using node2vec algorithm. These vector embedding are further used in understanding similarities between cases. Paper highlights that the tSNE reduced representation of the obtained vectors facilitates visual exploration and provides insights into the complex citation network. Suitability of node embedding for application of machine learning algorithm is demonstrated by clustering the node vectors for finding similar cases. ICIC International 2019. Creator An entity primarily responsible for making the resource Lodha S.; Wagh R. Source A related resource from which the described resource is derived ICIC Express Letters, Vol-13, No. 10, pp. 883-889. Publisher An entity responsible for making the resource available ICIC International Date A point or period of time associated with an event in the lifecycle of the resource 2019-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.24507/icicel.13.10.883" target="_blank" rel="noreferrer noopener">https://doi.org/10.24507/icicel.13.10.883</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072955918&doi=10.24507%2Ficicel.13.10.883&partnerID=40&md5=38f6f4a293acd4e6eb63fd2bd7b514aa" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072955918&doi=10.24507%2ficicel.13.10.883&partnerID=40&md5=38f6f4a293acd4e6eb63fd2bd7b514aa</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 1881803X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Lodha S., Department of Computer Science, CHRIST (Deemed to Be University), Bangalore, Karnataka, 560029, India; Wagh R., Department of Computer Science, CHRIST (Deemed to Be University), Bangalore, Karnataka, 560029, India Dublin Core 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/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core 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/. Title A name given to the resource Exploratory Architectures Analysis of Various Pre-trained Image Classification Models for Deep Learning Subject The topic of the resource deep learning; image classification; neural network Description An account of the resource The image classification is one of the significant applications in the area of Deep Learning (DL) with respective to various sectors. Different types of neural network architectures are available to perform the image classification and each of which produces the different accuracy. The dataset and the features used are influence the outcome of the model. The research community is working towards the generalized model at least to the domain specific. On this gesture the contemporary survey of various Deep Learning models is identified using knowledge information management methods to move further to provide optimal architecture and also to generalized Deep Learning model to classify images narrow down to the sector specific. The study systematically presents the different types of architecture, its variants, layers and parameters used for each version of Deep Learning model. Domain specific applications and limitations of the type of architecture are detailed. It helps the researchers to select appropriate Deep Learning architecture for specific sector. 2024 by the authors. Creator An entity primarily responsible for making the resource Deepa S.; Zeema J.L.; Gokila S. Source A related resource from which the described resource is derived Journal of Advances in Information Technology, Vol-15, No. 1, pp. 66-78. Publisher An entity responsible for making the resource available Engineering and Technology Publishing Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.12720/jait.15.1.66-78" target="_blank" rel="noreferrer noopener">https://doi.org/10.12720/jait.15.1.66-78</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183348264&doi=10.12720%2Fjait.15.1.66-78&partnerID=40&md5=835724298bb9f8c31d2fdd872094d8e3" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183348264&doi=10.12720%2fjait.15.1.66-78&partnerID=40&md5=835724298bb9f8c31d2fdd872094d8e3</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 17982340 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Deepa S., Department of Computer Science, Christ University, Bangalore, India; Zeema J.L., Department of Computer Science, Christ University, Bangalore, India; Gokila S., Department of Computer Applications, Hindustan Institute of Technology and Science, Chennai, India Dublin Core 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/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core 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/. Creator An entity primarily responsible for making the resource Manuel, Manju; Kanchi, Suvardhan; Losetty, Venkatramana Title A name given to the resource Exploring a GE/Nafion/Co-MOF nanosheets/CuO NPs/GOx powered electrochemical biosensor for ultrasensitive detection of rebaudioside A Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Nanoscale Advances;Volume;8;Issue;1;pp.167-180 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1039/d5na00591d" target="_blank" rel="noreferrer noopener">https://doi.org/10.1039/d5na00591d</a> <a href="https://www.scopus.com/pages/publications/105022739012?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105022739012?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Manuel M., Department of Chemistry, CHRIST University, Bengaluru, 560 029, India, Centre for Renewable Energy and Environmental Sustainability, CHRIST University, Bengaluru, 560 029, India; Kanchi S., Department of Chemistry, CHRIST University, Bengaluru, 560 029, India, Centre for Renewable Energy and Environmental Sustainability, CHRIST University, Bengaluru, 560 029, India; Losetty V., Department of Chemistry, Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, 600 062, India Description An account of the resource Rebaudioside A (Reb A) is a natural, non-nutritive sweetener highly prevalent in the global sweetener market and widely preferred by consumers. In this study, an advanced electrochemical biosensor was developed for sensing Reb A, using a modified graphite rod electrode extracted from discharged ZnC batteries. The electrode was fabricated using a layer-by-layer strategy with Nafion, Co-MOF nanosheets, CuO NPs, and glucose oxidase (GOx) enzyme. The nanomaterials were characterized by UV-vis, FTIR, DLS, zeta potential measurements, XRD, Raman, SEM, TEM, EDS, and XPS techniques. Electrochemical characterization via Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS) revealed a significant enhancement in electrical conductivity and increased electroactive surface area. The designed biosensor exhibited a sharp oxidation peak at 0.16 V due to ester bond cleavage in Reb A, which was further amplified in the presence of GOx, resulting from hydroxyl oxidation and hydrogen peroxide generation. Differential pulse voltammetry (DPV) demonstrated a linear response over a concentration range of 2.014 M (R2 = 0.993) with a limit of detection (LOD) of 0.23 M. The sensor displayed excellent analytical performance, with repeatability, reproducibility (RSD = 3.9%), and stability. Additionally, recovery studies confirmed its accuracy, ranging from 97% to 98.17%. Further, the molecular docking studies confirmed strong Reb AGOx interactions (?7.26 kcal mol?1), supporting the biosensor's specificity. The developed biosensor demonstrates excellent analytical performance, making it highly suitable for routine laboratory analysis of sweeteners in complex food matrices. This journal is The Royal Society of Chemistry, 2026 Publisher An entity responsible for making the resource available Royal Society of Chemistry Relation A related resource ISSN: 25160230; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Format The file format, physical medium, or dimensions of the resource online Dublin Core 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/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core 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/. Creator An entity primarily responsible for making the resource Siddiqui, Ayesha Anam Irshad; Deshmukh, Prapti D.; Upreti, Kamal; Kumari, Puja; Nijhawan, Pratham Title A name given to the resource Exploring advancements in space object detection through computer vision Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Smart Cyber-Physical Systems: Innovations and Real-World Implications;pp.1-19 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003542513-1" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003542513-1</a> <a href="https://www.scopus.com/pages/publications/105017511439?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105017511439?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Siddiqui A.A.I., G.Y. Pathrikar College of Computer Science and Information Technology, MGM University, Aurangabad, India; Deshmukh P.D., G.Y. Pathrikar College of Computer Science and Information Technology, MGM University, Aurangabad, India; Upreti K., Department of Computer Science, School of Sciences, CHRIST (Deemed to be University), Delhi NCR, India; Kumari P., Gautam Buddha University, Greater Noida, Uttar Pradesh, India; Nijhawan P., CHRIST (Deemed to be University), Delhi NCR, India Description An account of the resource [No abstract available] Publisher An entity responsible for making the resource available CRC Press Relation A related resource ISBN: 978-100354251-3; 978-103289293-1; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core 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/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core 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/. Title A name given to the resource Exploring Advances in Machine Learning and Deep Learning for Anticipating Air Quality Index and Forecasting Ambient Air Pollutants: A Comprehensive Review with Trend Analysis Subject The topic of the resource air pollutants; AQI; Artificial Neural Network; Linear Regression; Prediction Description An account of the resource India and the rest of the world are growing more and more worried about polluted atmosphere on a daily basis. A comprehensive prevision and prognostication of air quality parameters is vital due to the major harm that air pollution causes to both the environment and public health, causing concern on a global scale. In-depth analyses of the methods for predicting ambient air pollutants, like carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter with diameters less than 10? (PM10) and less than 2.5? (PM2.5), and ozone (O3), are provided in this work in tandem with the modeling of the Air Quality Index (AQI).To further enhance the anticipated precision and applicability of these models, the assessment additionally employs trend analysis to determine precedents and new trends in air quality. This paper offers insights into recent advances in algorithms using deep learning and machine learning for anticipating AQI and forecasting pollutant concentrations by combining current research in this topic. In order to inform policy decisions and measures aimed at reducing air pollution and its adverse effects on public health, trend analysis integration affords a more thorough comprehension of the dynamics of air quality. 2024 IEEE. Creator An entity primarily responsible for making the resource Rajan D.; Rohini V. Source A related resource from which the described resource is derived 2024 15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICCCNT61001.2024.10725099" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCCNT61001.2024.10725099</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211171976&doi=10.1109%2FICCCNT61001.2024.10725099&partnerID=40&md5=81e37958607ee4de99469b0352c11b14" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211171976&doi=10.1109%2fICCCNT61001.2024.10725099&partnerID=40&md5=81e37958607ee4de99469b0352c11b14</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835037024-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Rajan D., Christ (Deemed to be University), Department of computer science, Bangalore, India, Cmr Institute of Technology, Department of Mca, Bangalore, India; Rohini V., Christ (Deemed to be University), Department of computer science, Bangalore, India Dublin Core 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/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core 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/. Title A name given to the resource Exploring AI and ML Strategies for Crop Health Monitoring and Management Description An account of the resource This chapter offers a thorough examination of machine learning (ML) and artificial intelligence (AI) approaches designed especially for agricultural crop health monitoring. The story starts with a basic introduction to AI and ML ideas and then covers supervised and unsupervised learning approaches, the fundamentals of reinforcement learning, and the significance of high-quality data preparation in agricultural settings. This chapter explores the use of deep learning architectures and neural networks, explaining how they can be used to simulate human brain activity and how they can be used in picture identification to identify crop diseases. A detailed analysis is conducted of the practical aspects of ML for agriculture, encompassing feature engineering and model assessment methodologies. Additionally, the chapter highlights the ethical issues involved in the proper application of AI/ML models in agricultural contexts. These kinds of applications. In conclusion, the chapter discusses obstacles, offers predictions for future developments, and discusses new lines of inquiry for AI and ML research related to crop health monitoring. Through this thorough research, the chapter seeks to offer insightful information on the transformative potential of AI/ML approaches in supporting efficient and sustainable agriculture practices for improved crop health management. (Publisher name) (publishing year) all right reserved. Creator An entity primarily responsible for making the resource Nanjundan P.; Indu P.V.; Thomas L. Source A related resource from which the described resource is derived Sustainable Farming through Machine Learning Enhancing: Productivity and Efficiency, pp. 1-15. Publisher An entity responsible for making the resource available CRC Press Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003484608-1" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003484608-1</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212009880&doi=10.1201%2F9781003484608-1&partnerID=40&md5=b37fce903fbdd9fb5fbe53860b9fef42" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212009880&doi=10.1201%2f9781003484608-1&partnerID=40&md5=b37fce903fbdd9fb5fbe53860b9fef42</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-104025478-3; 978-103277749-8 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Nanjundan P., Department of Data Science, CHRIST University, Pune Lavasa Campus, Maharashtra, Lavasa, India; Indu P.V., Department of Data Science, CHRIST University, Pune Lavasa Campus, Maharashtra, Lavasa, India; Thomas L., Department of Psychology, CHRIST University, Pune Lavasa Campus, Maharashtra, Lavasa, India Dublin Core 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/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core 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/. Creator An entity primarily responsible for making the resource Vinay, M.; Jayapriya, J.; Deepa, S.; Kokilavani, T.; Rashmi, R.; Dangayach, Harshit Title A name given to the resource Exploring AI-Driven Accessibility Solutions: A Comprehensive Study on Assistive Tools for the Visually Impaired Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived CCIC 2026 - Contemporary Computing Innovations Conference 2026; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/CCIC68129.2026.11486060" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CCIC68129.2026.11486060</a> <a href="https://www.scopus.com/pages/publications/105038682375?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105038682375?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vinay M., Christ (Deemed to be University), Department of Computer Science, Bangalore, India; Jayapriya J., Christ (Deemed to be University), Department of Computer Science, Bangalore, India; Deepa S., Christ (Deemed to be University), Department of Computer Science, Bangalore, India; Kokilavani T., Christ (Deemed to be University), Department of Computer Science, Bangalore, India; Rashmi R., Christ (Deemed to be University), Department of Computer Science, Bangalore, India; Dangayach H., Christ (Deemed to be University), Department of Computer Science, Bangalore, India Description An account of the resource Artificial intelligence (AI) has significant access to visually impaired persons, which enables more freedom in digital interactions. This article examines the role of AI-operated equipment, including chatbots, speech recognition, and natural language processing (NLP) models, to improve communication, education, and navigation for blind users. It undergoes the largest progress of AI-driven accessibility solutions, especially in examination and interactive virtual scriptures. Despite the remarkable progress, challenges in speech remain accreditation accuracy, user interface targeted, and real -time treatment efficiency. The study highlights the ongoing research trends, identifies significant intervals, and emphasizes the need for better training data, adaptive AI interfaces, and improved user experience to promote more inclusion in education and the professional environment. 2026 IEEE. Subject The topic of the resource Artificial Intelligence; education; NLP; scribe; speech recognition; visually impaired Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-831952966-4; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core 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/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core 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/. Creator An entity primarily responsible for making the resource Kumar, Santosh; Arora, Amit Kumar; Sharma, Prashant; Bag, Akash Title A name given to the resource Exploring AI-Driven Economic Decision Making and Role in Promoting Green Investment Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived AI and Automation in Green Investment Platforms: Next-Generation ESG;pp.169-184 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-7138-2.ch009" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-7138-2.ch009</a> <a href="https://www.scopus.com/pages/publications/105037781638?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105037781638?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kumar S., Sharda University, India; Arora A.K., School of Business and Management, Christ University, Bengaluru, India; Sharma P., Dewan Institute of Management Studies, Meerut, India; Bag A., School of Law and Justice, Adamas University, Barasat, India Description An account of the resource Artificial Intelligence has assumed a disruptive role in the sphere of economic decision-making, specifically in the field of capital allocation towards green investments that would meet global sustainability requirements. Using machine-learning algorithms, neural networks, and big-data analytics, AI can offer greater accuracy in predicting economic patterns and risk assessment of the environment, and using AI can diversify portfolios with low-carbon assets, commercializing the old dichotomy between the financial value of profit and the eco-friendliness. This study discusses the transformations that AI-based tools are ready to make to the traditional economic paradigms, including the predictive analytics in terms of renewable-energy valuation, natural-language processing that would analyze sustainability reporting, or both in combination, a means of creating a paradigm shift where green investments would no longer be considered an act of charity, but rather a data-driven necessity of constructing long-term values. 2026 by IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833737140-5; 979-833737138-2; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Dublin Core 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/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core 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/. Creator An entity primarily responsible for making the resource Bijeesh, T.V.; Bejoy, B.J.; Thiruthuvanthan, Michael Moses; Raju, G. Title A name given to the resource Exploring Applications, Datasets, Algorithms, and Technologies in Satellite Image Processing Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Journal of Computer Science;Volume;21;Issue;9;pp.2029-2048 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.3844/jcssp.2025.2029.2048" target="_blank" rel="noreferrer noopener">https://doi.org/10.3844/jcssp.2025.2029.2048</a> <a href="https://www.scopus.com/pages/publications/105023118979?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105023118979?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Bijeesh T.V., Department of Computer Science and Engineering, CHRIST University, India; Bejoy B.J., Department of Computer Science and Engineering, CHRIST University, India; Thiruthuvanthan M.M., Department of Artificial Intelligence, Machine Learning and Data Science, CHRIST University, India; Raju G., Department of Computer Science and Engineering, CHRIST University, India Description An account of the resource Amidst an era filled with complex local and global problems, satellite data presents itself as a revolutionary tool with unmatched potential to tackle practical problems in a variety of fields. This article investigates how satellite imagery, which is available through open data programs and repositories, is a valuable tool for applications including wildlife conservation, urban planning, precision agriculture, and disaster management. It highlights the unique perspective that satellite data offers. Various sources for data acquisition, the applications that are suitable for a chosen satellite data and commonly used algorithms and techniques are discussed. Through case studies, the paper demonstrates how quick and reliable data provided by satellites can be used to solve complex real-world problems. The benefits of satellite data are emphasized, including its affordability, ability to monitor in real-time, and ability to support sustainable behaviours and policy-making. The study explores cutting-edge technologies, highlighting cloud computing and GIS integration as well as machine learning algorithms to build robust solutions using satellite data. The immense potential of satellite data is accompanied by challenges, including data integration, computational complexity, and ethical considerations. These challenges underscore the need for standardization and continuous efforts to fully realize the potential of satellite data in sustainable development and informed decision-making. 2025 Bijeesh TV, Bejoy BJ, Michael Moses Thiruthuvanthan and Raju G. Subject The topic of the resource Classification; Deep Learning; Remote Sensing; Satellite Data Publisher An entity responsible for making the resource available Science Publications Relation A related resource ISSN: 15493636; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Hybrid Gold Open Access Format The file format, physical medium, or dimensions of the resource online Dublin Core 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/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core 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/. Title A name given to the resource Exploring ARIMA Models with Interacted Lagged Variables for Forecasting Subject The topic of the resource Autoregressive Integrated Moving Average model; Interactions among lagged variables Description An account of the resource Including interactions among the explanatory variables in regression models is a common phenomenon. However, including interactions existing among lagged variables in autoregressive models has not been explored so far. In this paper, Autoregressive Integrated Moving Average (ARIMA) model with interactions among the lagged variables is proposed for improving forecast accuracy. The methodology for identifying the interacted lagged variables and including them in the ARIMA model is suggested. Using five different data sets of different types, the paper explores the effect of interacted lagged variables in ARIMA model. The experimental results exhibit that when interactions do actually exist, ARIMA model with interactions improves the forecast accuracy as compared to ARIMA model without interactions. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Thangarajan B.; Nagaraja M.S.; Dhandra B.V. Source A related resource from which the described resource is derived Trends in Mathematics, Vol-Part F2357, pp. 735-745. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-41420-6_61" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-41420-6_61</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187166729&doi=10.1007%2F978-3-031-41420-6_61&partnerID=40&md5=1c3de07337533d2b8499ed788c764205" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187166729&doi=10.1007%2f978-3-031-41420-6_61&partnerID=40&md5=1c3de07337533d2b8499ed788c764205</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 22970215 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Thangarajan B., CHRIST (Deemed to be University), Bengaluru, India; Nagaraja M.S., CHRIST (Deemed to be University), Bengaluru, India; Dhandra B.V., CHRIST (Deemed to be University), Bengaluru, India Dublin Core 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/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core 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/. Title A name given to the resource Exploring artificial intelligence techniques for diabetic retinopathy detection: A case study Description An account of the resource There is a notable increase in the prevalence of Diabetic Retinopathy (DR) globally. This increase is caused due to type2 diabetes, diabetes mellitus (DM). Among people, diabetes leads to vision loss or Diabetic Retinopathy. Early detection is very much necessary for timely intervention and appropriate treatment on vision loss among diabetic patients. This chapter explores how Artificial Intelligence (AI) methods are helpful in automated detection of diabetic retinopathy. In this chapter deep learning algorithm is proposed that is used to extract important features from retinal images and classify the images to identify the presence of DR. The model is evaluated using various metrics like specificity, sensitivity etc. The results of the case study provide an AI driven solution to existing methods used to identify DR and this can improve the early detection and appropriate treatment at the right time. 2024, IGI Global. All rights reserved. Creator An entity primarily responsible for making the resource Vijayalakshmi A.; Unnisa S.; Joshi H. Source A related resource from which the described resource is derived Intersection of AI and Business Intelligence in Data-Driven Decision-Making, pp. 351-366. Publisher An entity responsible for making the resource available IGI Global Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-5288-5.ch013" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-5288-5.ch013</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215355494&doi=10.4018%2F979-8-3693-5288-5.ch013&partnerID=40&md5=6c53adbc4ae3249e886e85d9463e214b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215355494&doi=10.4018%2f979-8-3693-5288-5.ch013&partnerID=40&md5=6c53adbc4ae3249e886e85d9463e214b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-836935289-2; 979-836935288-5 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vijayalakshmi A., Christ University, India; Unnisa S., Mount Carmel College, India; Joshi H., Christ University, India Dublin Core 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/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core 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/. Title A name given to the resource Exploring BERT and Bi-LSTM for Toxic Comment Classification: A Comparative Analysis Subject The topic of the resource BERT; bi-LSTM; natural language processing; toxicity Description An account of the resource This study analyzes on the classification of toxic comments in online conversations using advanced natural language processing (NLP) techniques. Leveraging advanced natural language processing (NLP) techniques and classification models, including BERT and Bi-LSTM models to classify comments into 6 types of toxicity: toxic, obscene, threat, insult, severe toxic and identity hate. The study achieves competitive performance. Specifically, fine-tuning BERT using TensorFlow and Hugging Face Transformers resulted in an AUC ROC rate of 98.23%, while LSTM yielded a binary accuracy of 96.07%. The results demonstrate the effectiveness of using transformer-based models like BERT for toxicity classification in text data. The study discusses the methodology, model architectures, and evaluation metrics, highlighting the effectiveness of each approach in identifying and classifying toxic language. Additionally, the paper discusses the implementation of a userfriendly interface for real-time toxic comment detection, leveraging the trained models for efficient moderation of online content. 2024 IEEE. Creator An entity primarily responsible for making the resource Tarun V.G.; Sivasakthivel R.; Ramar G.; Rajagopal M.; Sivaraman G. Source A related resource from which the described resource is derived 2nd IEEE International Conference on Data Science and Information System, ICDSIS 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICDSIS61070.2024.10594466" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICDSIS61070.2024.10594466</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200159414&doi=10.1109%2FICDSIS61070.2024.10594466&partnerID=40&md5=7aa5f4344bab4bf065edd20db9257776" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200159414&doi=10.1109%2fICDSIS61070.2024.10594466&partnerID=40&md5=7aa5f4344bab4bf065edd20db9257776</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038166-5 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Tarun V.G., Christ (Deemed To Be University), School Of Sciences, Department Of Computer Science, Karnataka, Bengaluru, India; Sivasakthivel R., Christ (Deemed To Be University), School Of Sciences, Department Of Computer Science, Karnataka, Bengaluru, India; Ramar G., Christ (Deemed To Be University), School Of Sciences, Department Of Computer Science, Karnataka, Bengaluru, India; Rajagopal M., Christ (Deemed To Be University), School Of Business And Management, Department Of Lean Operations And Systems, Karnataka, Bengaluru, India; Sivaraman G., M.G.R. College, Department Of Computer Science, Tamil Nadu, Hosur, India Dublin Core 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/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core 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/. Title A name given to the resource Exploring best practices in mobile app design patterns and tools: A user-centered approach Description An account of the resource Design patterns are reusable solutions to common design problems that provide a consistent user experience across different apps. This article explores the best practices in mobile app design patterns and tools with a focus on the user-centered approach to design. Design patterns such as navigation bars, tab bars, list views, and card views are discussed, along with design tools such as Sketch, Figma, Adobe XD, and InVision. The problem is to ensure that mobile app design is centered around the needs and preferences of the user, rather than the designer or the technology, and that the right design patterns and tools are used to create interfaces that are familiar and easy to use. The chapter emphasizes the importance of conducting user research to understand the needs and preferences of the target audience and using design patterns and tools to create interfaces that are familiar and easy to use. Mobile apps have become an integral part of our lives, and designing a successful mobile app is a challenging task that requires a thorough understanding of user needs and preferences. 2023, IGI Global. All rights reserved. Creator An entity primarily responsible for making the resource Rajendran R.K.; Mohana P.T. Source A related resource from which the described resource is derived Designing and Developing Innovative Mobile Applications, pp. 371-380. Publisher An entity responsible for making the resource available IGI Global Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/978-1-6684-8582-8.ch020" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/978-1-6684-8582-8.ch020</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163361697&doi=10.4018%2F978-1-6684-8582-8.ch020&partnerID=40&md5=34e0618e47d4fedd2084374aa043bd9b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163361697&doi=10.4018%2f978-1-6684-8582-8.ch020&partnerID=40&md5=34e0618e47d4fedd2084374aa043bd9b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166848584-2; 978-166848582-8 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Rajendran R.K., CHRIST University (Deemed), India; Mohana P.T., CHRIST University (Deemed), India Dublin Core 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/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core 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/. Title A name given to the resource Exploring Bio Signals for Smart Systems: An Investigation into the Acquisition and Processing Techniques Subject The topic of the resource Bio-signals; Brain Computer Interface; Electrodes; Electrooculogram Analog Digital Instrument; Human Computer Interface; Man Machine Interface Description An account of the resource Bio signals play a vital role in terms of communication in the absence of normal communication. Bio signals were automatically evolved from the body whenever any actions took place. There are lots of different types of bio signal based research going on currently from several researchers. Signal acquisition, processing the signals and segmenting the signal were totally different from one technique to another. Placing electrodes and its standard measurements were varied. The signals gathered from each subject may be varied due to their involvement. Each and every trial of signals can generate different patterns. Each and every pattern generated from the activities also has a different meaning. In this study we planned to analyze the basic measurement techniques handled to record the bio signals like Electrooculogram. 2023 IEEE. Creator An entity primarily responsible for making the resource Sivasakthivel R.; Rajagopal M. Source A related resource from which the described resource is derived International Conference on Sustainable Computing and Smart Systems, ICSCSS 2023 - Proceedings, pp. 690-694. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICSCSS57650.2023.10169374" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICSCSS57650.2023.10169374</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166265172&doi=10.1109%2FICSCSS57650.2023.10169374&partnerID=40&md5=a1591580598c51b7840ae49121326e97" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166265172&doi=10.1109%2fICSCSS57650.2023.10169374&partnerID=40&md5=a1591580598c51b7840ae49121326e97</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835033360-2 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Sivasakthivel R., Christ (Deemed to Be University), School of Sciences, Department of Computer, Science, Karnataka, Bengaluru, India; Rajagopal M., Christ (Deemed to Be University), School of Business and Management, Department of Lean Operations and Systems, Karnataka, Bengaluru, India Dublin Core 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/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core 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/. Creator An entity primarily responsible for making the resource Palanisamy, Sathyadevi; Vijayaraghavan, Priya; Wang, Yen-Yun; Yao, Yi-Wen; Huang, Bo-Cheng; Chen, Wen-Liang; Kao, Chai-Lin; Yuan, Shyng-Shiou F.; Wang, Yun-Ming Title A name given to the resource Exploring boronate-appended hyperbranched amino-functionalized dendrimer-empowered sensors for the potential recognition of FSH in age-categorized human plasma samples Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Applied Materials Today;Volume;48;Issue;;Article No.;103006; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.apmt.2025.103006" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.apmt.2025.103006</a> <a href="https://www.scopus.com/pages/publications/105023144334?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105023144334?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Palanisamy S., Department of Chemistry, National Taiwan Normal University, Taipei, 11677, Taiwan, Department of Biological Science and Technology, Institute of Molecular Medicine and Bioengineering, B), National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan; Vijayaraghavan P., Department of Biological Science and Technology, Institute of Molecular Medicine and Bioengineering, B), National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan, Department of Chemistry, CHRIST University, Karnataka, Bengaluru, 560029, India; Wang Y.-Y., College of Dental Medicine, School of Dentistry, Kaohsiung Medical University, Kaohsiung, 807, Taiwan, Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung, 807, Taiwan; Yao Y.-W., Department of Medicinal and Applied Chemistry, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Huang B.-C., Department of Surgery, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan, Drug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Chen W.-L., Department of Biological Science and Technology, Institute of Molecular Medicine and Bioengineering, B), National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan; Kao C.-L., Department of Medicinal and Applied Chemistry, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Yuan S.-S.F., Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan, Faculty and College of Medicine, Translational Research Center and Department of Obstetrics and Gynecology, Kaohsiung Medical University, Kaohsiung Medical University Hospital, Kaohsiung, 807, Taiwan; Wang Y.-M., Department of Biological Science and Technology, Institute of Molecular Medicine and Bioengineering, B), National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan, Center for Neurotechnology and Assistive Technology, Kaohsiung Medical University, Kaohsiung, 807, Taiwan Description An account of the resource Boronic acids can act as ideal saccharide receptors as they possess a high affinity for diols and readily form cyclic-boronate esters when reacting in an aqueous medium. Here, we present hydrophilic amino-functionalized boronic acid dendrimer (Af-BAD) for the first time, with significantly enhanced sensitivity towards Follicle Stimulating Hormone (FSH) detection. In this study, newly synthesized Af-BAD was dip-coated on a gold substrate to create an impedance-type sensing working electrode. The effects of Af-BAD coating on the gold chip, the sensing properties for FSH recognition, sensitivity, and stability were measured by the charge transfer resistance across the electrochemical setup. The impedimetric measurements were conducted in the presence of [Fe(CN)6]3-/[Fe(CN)6]4- redox reporter at pH 7.4. The increments in the charge-transfer resistance were monitored upon increasing the FSH concentrations from 25 fg/mL to 100 pg/mL. The device achieved good sensitivity with a calculated detection limit of 4.01 fg/mL and acceptable linearity. The observed behavior was linear concerning the tested concentrations. An attempt at a real application to serum samples was also successfully conducted. Meanwhile, the level of tolerance of boronic acid dendrimer with other competing glycoproteins and monosaccharides was also tested. In this study, we also compared human plasma FSH levels in female oral cancer patients and normal controls using the Af-BAD modified device and the clinically used ELISA method. With a sound understanding of boronate materials and their affinity, amino functionalized multi-boronic acid dendrimer was developed as a highly selective conjugate toward glycoprotein FSH detection. Copyright 2025. Published by Elsevier Ltd. Subject The topic of the resource Biosensor; Clinical sample; Dendrimer; Electrochemistry; Gold chip Publisher An entity responsible for making the resource available Elsevier Ltd Relation A related resource ISSN: 23529407; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online https://archives.christuniversity.in/files/original/6ed9fac131e607d382ca1bdf0b373079.pdf d12c51de5b67c5b222fe4525944a0838 Dublin Core 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/. Title A name given to the resource MPHIL Mphil Mphil Thesis Dublin Core 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/. Title A name given to the resource Exploring Caregiving Experiences and Needs of Mothers of Children with Cerebral Palsy Creator An entity primarily responsible for making the resource ASHILIN MARY MATHEW Date A point or period of time associated with an event in the lifecycle of the resource 2019 Source A related resource from which the described resource is derived Social Work Description An account of the resource Parents play a major role while caring for a child with Cerebral Palsy (CP). Each child with CP and their caregivers needs constant professional support in terms of medical care, psycho-education, guidance and support in order to achieve maximum functioning. Mothers of children with cerebral palsy are vulnerable because the caregiving may affect their personal and marital life, work, finances, relationships, and other responsibilities. Therefore, it is important to understand their experiences this study explores caregiving experiences and needs of mothers of a child with cerebral palsy. This qualitative exploratory study used semi-structured open-ended interviews for data collection from 25 mothers of children with Cerebral Palsy who attended regular clinical assessments at Unit of Hope OP clinic. The data were analyzed in Atlas. ti 8 trial version using thematic analysis. Six major themes emerged from the thematic analysis which includes: pathways of care, challenges in taking care of the child, impact (subjective and objective) on mothers and their family, coping mechanism and psycho-social needs. Mothers expressed that they experience unpreparedness; unsupportive interaction; insecurity/uncomfortable on caregiving by others; challenges in decision making, finding the right care, meeting individual family member???s needs; they had inappropriate expectations of improvement, difficulties in treatment adherence and lack of knowledge, lack of respite, lack of support from family members/relatives, changes in the family system, changes in personal life. Mothers had caregiver burden and emotional challenges. The mothers adopted both maladaptive and adaptive coping strategies. In this study, mothers expressed various needs like the need for professional support, the need for respite care, and the need for family support. In conclusion, having a child with cerebral palsy negatively affect the mothers. During the caregiving process, they have some unmet needs which need to be addressed. The findings of the study emphasize that it is important to understand the caregiving experiences and needs of mothers of children with cerebral palsy to plan interventions to support these mothers in caring for their child. Dublin Core 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/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core 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/. Title A name given to the resource Exploring challenges in online higher education for AI integration using MICMAC analysis Description An account of the resource The consequence of Covid-19 has affected the traditional higher education system. Acknowledging the significant role of online education in national development for accessibility and quality education, countries around the world have understood its importance in current digital era. Indian policymakers have been giving due importance to enhancing the education quality, however the progress made by the country in higher education is not adequate. Amidst all the inadequacies of traditional education system, artificial intelligence (AI) technologies are bringing new ray of hope to democratize education system. This chapter is subjected to identify the challenges in online education and suggest specific ways to address each of them. The challenges are categorized into internal and external challenges/barriers. These challenges have been modeled with the expertise of educationalist's opinions and interpretive structural modeling to create a hierarchy of the barriers using MICMAC analysis and categorize these barriers into four clusters. 2024, IGI Global. All rights reserved. Creator An entity primarily responsible for making the resource Nagariya R.; Sharma P.; Saxena A.; Saxena P.; Pancholi G. Source A related resource from which the described resource is derived Integrating Generative AI in Education to Achieve Sustainable Development Goals, pp. 370-385. Publisher An entity responsible for making the resource available IGI Global Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-2440-0.ch021" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-2440-0.ch021</a> <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85198185459&doi=10.4018%2F979-8-3693-2440-0.ch021&partnerID=40&md5=d20cd75142dd44e6eece6b45403d9440" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85198185459&doi=10.4018%2f979-8-3693-2440-0.ch021&partnerID=40&md5=d20cd75142dd44e6eece6b45403d9440</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-836932441-7; 979-836932440-0 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Nagariya R., Christ University, India; Sharma P., Birla Institute of Technology, Mesra, India; Saxena A., Amity University, Jaipur, India; Saxena P., S.P. Mandali's Prin. L.N. Welingkar Institute of Management, Development, and Research, India; Pancholi G., Amity University, Jaipur, India