Browse Items (11810 total)
Sort by:
-
Interpreting the Evidence on Life Cycle to Improve Educational Outcomes of Students Based on Generalized ARC-GRU Approach
Research on the effects of teachers' fatigue on students' learning has been significantly less common than research on the effects of teachers' fatigue on teachers' own performance. Therefore, the purpose of this research is to see if teachers' emotional weariness has any bearing on their students' performance in the classroom. Consideration is given to a student's grades and their impressions of whether or not the system receive assistance from teachers, as well as to the student's general outlook on school, confidence in their own abilities, and faith in the availability of faculty support. Data preparation, feature extraction, and model training are the first steps in the proposed approach. Indicators of the quality of the education being provided are eliminated (by outlier removal and feature scaling). k-mean clustering approach is a technique of clustering which is commonly used in feature extraction. Following feature extraction, GARCH-GRU models are trained. The proposed approach is superior to two popular alternatives, ARCH and GRU. Using the provided method, the system were able to achieve a maximum accuracy of 97.07%. 2024 IEEE. -
Interrogating Populist Tendencies within the Left Rhetoric in Kerala
After the disintegration of the Soviet Union, there has been an increasing shift from class-based politics to politics based on mobilising "people" within the left-wing political praxis and rhetoric. Such tendencies are visible even within the left rhetoric in Kerala. In the particular context of Kerala, this process is enmeshed with sub-nationalist sentiments and concerns around vikasanam (development). It is possible that this tendency can metamorphose into different directions, depending on the tactical priorities of the left in Kerala. 2022 Economic and Political Weekly. All rights reserved. -
Intersecting Ecocriticism and Gender in Selected Writings of Easterine Kire
The research study, Intersecting Ecocriticism and Gender in Selected newlineWritings of Easterine Kire, analyses the intersection of histories, identities, gender, and ecology to understand the larger context of marginalisation and newlinerepresentation. Indigenous literature often subverts Western worldviews and mainstream discourses with counter-discourse narratives by placing their stories at the centre. In recent times, literature from Indigenous societies has established a position in which Indigenous people represent, resist, newlinedecolonise, and construct their identity. The Indigenous Naga community has experienced marginalisation for decades, having suffered multiple oppressions of their history, stories, knowledge, and lack of rights; however, contemporary literary writings challenged the silencing system through writing back and representation. In her fictional works, Naga author Easterine Kire explores the possibilities of reviving and restoring the Angami Naga community and their newlinelost cultures and identities. Focusing on analysing three important themes: Peoplestories, Ecopolitics, and Gender politics, the study represents Naga histories, emerging identities, gender, and ecological concerns as interpreted in the fiction of Easterine Kire. The objective is to represent Indigenous Naga voices using fictional narratives of Easterine Kire to reclaim, revive, and redefine Indigenous culture and history from an insider s perspective. It also examines how intersecting narratives contribute to the larger context of Naga identity construction. newlineEasterine Kire s writing is a culturally conscious and decolonial strategy in newlinewhich she incorporates her community s oral tradition and storytelling in her fictional narratives. Easterine Kire s narrative engages in a deep conscious cultural revival and reinvention of her community s cultural heritage. -
Intersection of AI and business intelligence in data-driven decision-making
In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed required for effective decision-making in this data-rich environment. As a result, many businesses need help to leverage their data to drive sustainable growth and remain competitive. Intersection of AI and Business Intelligence in Data-Driven Decision-Making presents a transformative solution to this pressing challenge. By exploring the convergence of artificial intelligence (AI) and BI, our book provides a comprehensive framework for leveraging AI-powered BI to revolutionize data analysis, predictive modeling, and decision-making processes. Readers will gain valuable insights into practical applications, emerging trends, and ethical considerations, inspiring and exciting them about the potential of AI in driving business success. Through in-depth discussions, case studies, and best practices, this book equips professionals, researchers, and students with the knowledge and tools needed to navigate the complexities of AI-powered business intelligence. Whether you're looking to predict trends, analyze consumer behavior, or optimize supply chains, this book offers actionable strategies and techniques for implementing AI-powered BI solutions in your organization. 2024 by IGI Global. All rights reserved. -
Interval-Valued Fuzzy Trees and Cycles
Interval-valued fuzzy tree (IVFT) and interval-valued fuzzy cycle (IVFC) are defined in this chapter. We characterize interval-valued fuzzy trees. We also prove that if G is an IVFG whose underlying crisp graph is not a tree then G is an IVFT if and only if G contains only ? strong arcs and weak arcs. It is shown that an IVFG G whose underlying crisp graph is a cycle is an IVFC if and only if G has at least two ? strong arcs. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Interventions for the improvement of social skills in autism spectrum disorder in India: A systematic review
Background: The increasing prevalence of Autism Spectrum Disorders (ASD) in India is in a gaping contrast with the existing interventions in India. Though several interventions have proved their efficiency in foreign countries, such studies within India are scarce. Aims: This review attempts to systematically examine the different intervention practices that include improvement of social skills in ASD that is practiced in India as revealed through published literature on the same. Methods: Studies published from 2000 to 2020 were selected for the study. Evidence is presented for nine treatment categories: Behavior-based interventions, Developmental Interventions, TEACHH approach, Parent-mediated Interventions, speech-based Interventions, electronics-based interventions, augmentative and alternative communication, play-based interventions and Yoga-based interventions. These studies were drawn from databases Ebsco, Proquest, PubMed, MEDLINE, science direct and Google Scholar. Though a definitive conclusion cannot be drawn without a meta-analysis, the available evidence is gathered and evaluated in the present review. Results: The review has proved to be a reliable summary of the interventions that include improvement of social skills in ASD that is practiced in India. Conclusions: Parent-mediated interventions may be more appropriate for the resource-poor settings of India, when developmental interventions may be more appropriate for the resourcerich settings of India. The scarcity of published literature on the topic in India is also a significant factor that highlighted itself through the research. 2021, Indian Association for Child and Adolescent Mental Health. All rights reserved. -
Interventions to help students find a deeper purpose during their academic journey
This comprehensive exploration delves deeply into academic interventions aimed at guiding students toward a more profound sense of purpose throughout their educational journeys. It emphasizes that education offers a unique opportunity for students to discover their passions, interests, and aspirations beyond textbooks and exams. The interventions discussed, including mentorship, career counseling, experiential learning, and self-discovery exercises, are meticulously designed to empower students to recognize their distinct strengths and interests. These interventions not only aim to facilitate academic excellence but also enable students to pursue careers aligned with their core values and aspirations. The exploration scrutinizes effective strategies, programs, and support mechanisms, addressing challenges students face when making career choices, and culminates in recommendations for educators, career counselors, and policymakers interested in enriching students' educational experiences and fostering purpose-driven learners. 2024, IGI Global. -
Into the Dark World of User Experience: A Cognitive Walkthrough Study
In this age of AI, the unison of man and machine is going to be more prominent than ever, thus creating a need to understand the underlying framework that is adopted by app designers and developers from a psychological point of view. Research on the various benefits and harmful effects of user experience design and furthermore developing interventions and regulations to moderate the use of dark strategies in digital tools is the need of the hour. This paper calls for an ethical consideration of designing the experience of users by looking at the unethical practices that exist currently. The purpose of the study was to understand the cognitive, behavioural and affective experience of dark patterns in end users. There is a scarcity in the scientific literature with regard to dark patterns. This paper adopts the methodology of user cognitive walkthrough with 6 participants whose transcripts were analysed using thematic network analyses. The results are presented in the form of a thematic network. A few examples of the themes found are the experience of manipulation in users, rebellious attitudes, and automatic or habitual responses. These findings provide a basis for an in-depth understanding of dark patterns in user experience and provide themes that will help future researchers and designers develop ethical and more enriching user experiences for users. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Intricate Plane of Adversarial Attacks in Sustainable Territory and the Perils faced Machine Intelligent Models
The issue of model security and reliability in Artificial Intelligence (AI) is a concern due to adversarial attacks. In order to tackle this issue, researchers have developed sustainable defense strategies, but certain challenges remain. These challenges involve transferability, higher computing costs, and adaptability. Striking a balance between accuracy and robustness is difficult, as defense mechanisms often come with trade-offs between the two. Real-world situations demonstrate the practical implications of sustainable adversarial AI. For example, it improves the security of self-driving vehicles, enhances the accuracy of medical imaging diagnoses, and incorporates AI-driven defenses into network intrusion detection and phishing detection systems. It is crucial to consider ethical aspects throughout this process. Future trends in adversarial AI research for cybersecurity will involve ensemble defense mechanisms, adversarial learning from limited data, and hybrid attacks. By embracing the evolving landscape, researchers and practitioners can develop sustainable AI systems that are more secure and resilient, effectively countering adversarial threats. 2023 IEEE. -
Intrinsic betterness and reason based extrinsic preference towards social shopping: A study among college students in Bangalore
The main purpose of this study is to analyze the Intrinsic and Extrinsic factors and its impact on the social shopping of student community in the city of Bangalore. Bangalore is one of the most popular cities in the down south. This city attracts a mix of various cultures from various countries of the world. Thus, this city and population would be apt to study the social shopping pattern considering the Intrinsic and Extrinsic factors. The data was collected from the student community, perusing their college education in the city of Bangalore. Using convenient sampling method, a sample size of 225 was drawn from educational institutions in the city of Bangalore. The research work makes use of both first hand and second-hand data. The reliability of the data is acceptable as the Cronbach's alphas value is more than. 6. The drafted questionnaire was subjected to expert opinion before the data collection process. The study results make it clear that both intrinsic and extrinsic values motivate the consumers to get involved in the social shopping. But comparatively consumers are more influenced by those factors present in the external environment. It can be concluded by saying that, youngsters are quite smart before putting themselves into the purchase behavior, as they are in a group of friends, they get influenced by various experiences and comments shared by many. In a way social shopping is better, as too many minds generate ideas for a single purchase. 2018 Transilvanian Association for the Literarure and Culture of Romanian People (ASTRA). All rights reserved. -
Introduction
[No abstract available] -
Introduction
[No abstract available] -
Introduction
In the digital era, signal processing has found application in daily life from medical diagnosis to social networking. The digital domain has evolved as the preferred choice in communication system design due to its advantages over analog systems, such as high-speed transmission, improved quality, and effortless copying with high precision. The advancement of digital media brings new opportunities. The internet boom of this millennium has allowed digital data to move around the world in real time. Efficient segmentation, recognition, and analysis of multidimensional data such as hyperspectral images, medical imaging, data analysis in social media, and audio signals are still challenging issues. Digital data produced through data-processing algorithms has the fundamental advantages of transportability, proficiency, and accuracy of information content; but such data is also at significant risk because perfect illegal replicas can be made in unlimited numbers. 2021 John Wiley & Sons Ltd. -
INTRODUCTION
World politics in the twenty-first century represents a complex arena characterised by a diversity of paradigms. These paradigms entail a dynamic interplay of conventional and newer ways of engagement. Today, the globalising world witnesses newer imaginations of space and interactions where state actors continue to enjoy a preeminent status, adopting policies based on imaginations of space in terms of connectivity and gateways while maintaining their territorial integrity. They devise a whole array of mechanisms to define, redefine and secure their interests as well as elevate their aspirations of assuming newer responsibilities and bigger roles. What we witness today is dynamic endeavours by the states to hold on to and amplify their traditional roles and carving out newer contours of forging and consolidating relationships in the global framework of international relations. This also leads to the construction of new geo-strategic and economic hotspots. This complex interplay of the traditional and the newer interactions creates both synergies and discord. The Indo-Pacific represents such a hotspot in contemporary world politics, and Indias engagement with Southeast Asia is a significant area of interest therein. 2024 Taylor & Francis. -
INTRODUCTION
The twenty-first century has been witnessing a global federal resurgence, distinguished by conversations focusing on interdependencies, multiculturalism, overlapping jurisdictions, multilateralism, multiple centres of policy-making and multiple notions of citizenship. Any assessment of cooperative federalism needs to go beyond institutional structures by incorporating images of diversity, pluralism, identity, issues of empowerment and democratization. Cooperative federalism facilitates cooperation among the national, state and local governments. It perceives the federation and the states as complementary parts of an arrangement where sovereignty is shared. 2024 selection and editorial matter, M.J. Vinod, Stefy V Joseph, Joseph Chacko Chennatuserry and Dimitris N. Chryssochoou; individual chapters, the contributors. -
INTRODUCTION
[No abstract available] -
Introduction to blockchain for internet of things
[No abstract available] -
Introduction to Data Mining and Knowledge Discovery
Data mining is a process of discovering some necessary hidden patterns from a large chunk of data that can be stored in multiple heterogeneous resources. It has an enormous use to make strategic decisions by business executives after analyzing the hidden truth of data. Data mining one of the steps in the knowledge-creation process. A data mining system consists of a data warehouse, a database server, a data mining engine, a pattern analysis module, and a graphical user interface. Data mining techniques include mining the frequent patterns and association learning rules with analysis, sequence analysis. Data mining technique is applicable on the top of various kinds of intelligent data storage systems such as data warehouses. It provides some analysis processes to make some useful strategic decisions. There are various issues and challenges faced by a data mining system in large databases. It provides a great place to work for data researchers and developers. Data mining is the process of classification, which can be executed based on the examination of training data (i.e., objects whose class label is predefined). With the help of an expert set of previous class objects with known class labels, it can find a model that can predict a class object with an unknown class label. These classification models can be classified into a variety of categories, including nearest neighbor, neural network, and others. Bayesian model, decision tree, neural network Random forest, decision trees Support vector machine, random forest SVM (support vector machine), for example. By analyzing the most common class among k closest samples, the K-Nearest Neighbor (KNN) technique aids in predicting of the class object with the unknown class label. Its an easy-to-use strategy that yields a solid classification result from any distribution. The Naive Bayes theory helps to perform the classification. It is one of the fastest classification algorithms, capable of efficiently handling real-world discrete data. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Introduction to quantum machine learning
Quantum Machine Learning (QML) is popularly known to be an integrative approach to learning of the Quantum Physics (QP) and Machine Learning (ML). In this chapter, an outline of the fundamental ideas and features related to quantum machine learning is laid out. The different facets of quantum algorithms are discussed in this chapter. In addition to this, the basic features of quantum reinforcement learning and quantum annealing are also provided in this chapter. Finally, the chapter deliberates about the advancement of quantum neural networks to through light in the direction of QML. 2020 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved. -
INTRODUCTION TO TEACHING INTERNSHIP: An Analytical Approach
The introduction chapter presents the transition that teaching internship models underwent from the 20th century to the 21st century. It addresses the need for acquiring the teaching knowledge required of a teacher trainee suitable to the present time. It provides a glimpse of internship practices in other professions like medicine, law and business to provide an analytical base to understand the teaching internship. A successful teaching practicum is determined by its outcome and the experiences offered at the internship site. The chapter also sheds light on the expectations and benefits of teaching internship. It also clarifies the terms used in teaching internship for a common understanding from the stakeholders. It explores the idea of mentor and mentorship in teaching internship. The chapter concludes by providing an overview of the succeeding chapters in the volume. 2023 selection and editorial matter G.S. Prakasha and Anthony Kenneth; individual chapters, the contributors.