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ALIGNING INVESTMENTS WITH VALUES: CREATING PORTFOLIOS BASED ON CORPORATE SOCIAL RESPONSIBILITY AND NIM
Purpose: This research discusses the importance of corporate social responsibility (CSR) and its link to a financial performance metric called net interest margin (NIM) in the context of non-banking financial companies (NBFCs). CSR initiatives can lead to long-term sustainability and improved financial performance, attracting investors seeking to align their investments with their values. Need for the Study: The research composes portfolios based on financial companies CSR performance and NIM ratios to help investors understand the difference between CSR and financial performance, making investment decisions based on their portfolio goals and values. Striking a balance between sustainability and the financial performance of financial companies, will help investors find a suitable balance between portfolios for investment purposes. Methodology: The authors used data from 55 financial companies for daily returns from 20142015 to 20212022 and used descriptive statistics to measure the performance of portfolios. Findings: The findings suggest that financial companies in India have improved their CSR scores over time, indicating an increased focus on integrating socially responsible practices into their operations. The data also show that NBFCs are catching up with banks regarding CSR scores, and some NBFC portfolios even outperform banks regarding returns. However, the study also highlights the need for some companies to focus more on CSR and business operations. Practical Implications: The results serve as a benchmark for financial companies to assess their relative CSR performance, highlighting the need for companies to focus on integrating socially responsible practices into their operations and guiding areas where companies can improve. 2024 by Ishfaq Hussain Bhat, Shilpi Gupta and Satinder Singh Published under exclusive licence by Emerald Publishing Limited. -
Internet of things: Service-oriented architecture opportunities and challenges
Internet of Things is now a subject that is increasingly growing on both the job and modern devices. It is a concept that maybe not just get the potential to influence how we live but in addition how we work. Intelligent systems in IoT machines in many cases are used by various events; consequently, simultaneous information collection and processing are often anticipated. Such a characteristic that is exclusive of systems has imposed brand new challenges towards the designs of efficient data collection processes. This article is to be discussing various layers in Internet of things. Those layers are sensing layer, network layer, service layer and application layer. Various data processing techniques are integrated along with data filtering and data conversion. Protocol transformation is also feeling the major challenges faced by enterprises wanting to shift to the style in brand new technology. Springer Nature Singapore Pte Ltd. 2020. -
Haptics: Prominence and Challenges
Derived from a Greek word meaning sense of touch, Haptic is a communication technology which applies tactile sensation for human-computer interaction with computers. Haptic technology, or haptics, is a tangible feedback technology that takes benefit of a users sense of touch by applying forces, sensations, or motions to the user. These objects are used to methodically probe human haptic capabilities, which would be complex to achieve without them. This innovative research tool gives an understanding of how touch and its core functions work. The article will provide a detailed insight into the working principles, uniqueness of the technology, its advantages and disadvantages along with some of its devices and notable applications. Future challenges and opportunities in the field will also be addressed. 2020, Springer Nature Switzerland AG. -
Risk management of future of Defi using artificial intelligence as a tool
This chapter explores AI's pivotal roles in managing risks within DeFi, emphasizing strategic implementation to enhance risk assessment, management, and decisionmaking processes for a better user experience. The convergence of AI and DeFi presents unprecedented opportunities, fostering transparency and decentralization. Drawing from diverse sources, the study evaluates AI's effectiveness, particularly in machine learning, in addressing emerging risks. It focuses on how AI can guide DeFi's future while managing market and credit risks through tasks like data preparation, modeling, stress testing, and validation. Additionally, AI aids in data quality assurance, text mining, and fraud detection. Emphasis is placed on identifying and managing risks that could hinder DeFi's future, highlighting key AI techniques. Given the financial industry's ongoing transformation, these insights are increasingly vital. 2024, IGI Global. All rights reserved. -
Study of micro and small enterprises' readiness in implementing industry 4.0: A study in marathwada district of maharashtra, india
Industry 4.0 aims tp transform the development of global value chains and the development of a digital revolution, with intelligent machines capable of communicating via wireless connections and a connection thought system, resulting in autonomous decision-making. Although large sized firms are adopting Industry 4.0, the small and micro enterprises are facing great difficulties in adopting them. This study aims to identify the areas in which Enterprises need to focus for improving their level of readiness and develop strategies and plans to adopt Industry 4.0 technologies successfully. 219 samples were collected using snowball sampling from Marathwada District in Maharashtra, India. factor analysis was conducted using SPSS and different factors acting as barriers to implementation of Industry 4.0 technologies were identified. 2023 by IGI Global. All rights reserved. -
Customer perspective on a curated gift-box service: A study in Sikkim, India
Due to the proliferation of choices and brands, accessibility to information, and new communication mediums, consumer behavior, particularly decision-making processes, has been altered by the spending power of various segments. In the Indian environment, although product appearance has been identified as a significant factor in influencing customer behavior, its effect on decision making when combined with other factors such as cost, features, and intrinsic psychological factors has not been studied thoroughly. This study aims to highlight consumers' perspective on a curated gift-box service in Sikkim. Focusing on gifting during special occasions, impulse buying, and self-gift opportunities, this study stands on the possibility that there is a need for such service in the market. 2023, IGI Global. -
Vocational training course preferences among Sikkimese youth
Unemployment is one of the major issues in modern times. High unemployment rates affect a country's economic growth, mental wellbeing of an individual and his/her family members, and create unrest in society. Vocational training is one of the most crucial elements in the competitive and developing world. Through the provision of real-world experience, vocational training aids in developing skills. This study aims to highlight the aspirations of the people of Sikkim concerning vocational training and find its challenges and hindrances. With the help of a structured questionnaire, responses were taken from the youth of Sikkim, India and their perception about opting for different vocational training courses were taken. Upon analyzing the data, it was found that males are more inclined towards cooking and baking classes, repair of mobiles, laptops and other electronic accessories, and repair of bikes and automobiles. Females, on the other hand, wanted to focus on makeup and beautician courses, jewelry design, floriculture, and towards repair of mobile and computers. 2023, IGI Global. -
Application of green logistics in supply chain of auto parts: A south indian scenario
Green supply chain concept is used to reduce environmental degradation and emissions of air, water, and waste by incorporating green practices into business operations. Growing impacts of global warming, climate change, waste, and air pollution problems have prompted experts all over the world to think more environment friendly and find the best possible approach for "Green" solutions. green supply chain management is one of the factors that motivates organizations to be more sustainable. This study focuses on the green supply chain management in the auto parts industry in South Indian. Data from three green initiatives: recyclable packaging, green warehouse management and milk run approach for logistics is taken and compared with nongreen approaches. It is found that there is significant reduction in costs by adopting the green approaches. With environmental issues growing all the time, green supply chain deserves to be a long-term community concern in developing countries. 2023 by IGI Global. All rights reserved. -
Perception about inventory management and control at quick service restaurants
India's quick service restaurant market has expanded significantly in recent years. For small-scale QSRs, inventory management continues to be an essential challenge. Inventory management enhances the efficiency of business operations by influencing the stockpile and supply of essential products and materials. The research aims to highlight the importance of inventory control and management in QSRs. Primary data was collected from 120 operational QSRs in Bangalore in Karnataka and 30 from Kottayam in Kerala. It was found that most of the respondents felt that proper inventory management and control could help to improve their service quality and help to reduce costs. It has been found that the factors service, savings, and risk have a strong positive correlation with inventory cost. Several techniques and strategies like techniques for cooking with no waste, menu planning with fewer ingredients, networks for local sourcing, matching demand and supply through seasonal planning have been identified to increase the performance of QSRs. 2024, IGI Global. All rights reserved. -
An efficient design and comparison of machine learning model for diagnosis of cardiovascular disease
Cardiovascular disease has a significant global impact. Cardiovascular disease is the primary cause of disability and mortality in most developed countries. Cardiovascular disease is a condition that disturbs the structures and functionality of the heart and can also be called heart disease. Cardiovascular diseases require more precise, accurate, and reliable detection and forecasting because even a small inaccuracy might lead to fatigue or mortality. There are very few death occurrences related to cardio sickness, and the amount is expanding rapidly. Predicting this disease at its early stage can be done by employing Machine Learning (ML) algorithms, which may help reduce the number of deaths. Data pre-processing can be employed here to eliminate randomness in data, replace missing data, fill in default values if appropriate, and categorize features for forecasting and making decisions at various levels. This research investigates various parameters that are related to the cause of heart disease. Several models discussed here will come under the supervised learning type of algorithms like Support Vector Machine (SVM), K-nearest neighbor (KNN), and Nae Bayes (NB) algorithm. The existing dataset of heart disease patients from the Kaggle has been used for the analysis. The dataset includes 300 instances and 13 parameters and 1 label are used for prediction and testing the performance of various algorithms. Predicting the likelihood that a given patient will be affected by the cardiac disease is the goal of this research. The most important purpose of the study is to make better efficiency and precision for the detection of cardiovascular disease in which the target output ultimately matters whether or not a person has heart disease. 2023, Bentham Books imprint. All rights reserved. -
A thorough investigation of various goals and responses for mobile software-defined networks
Cloud computing has caused some companies to modify their IT infrastructure and maintenance procedures and may eliminate their current hardware altogether. Conventional methods of setting up a switch or router may be error-prone and unable to make full use of the capabilities of current network architectures. As many intelligent networking designs as possible must be developed for intellectualization, activation, and customization in future networks. Due to software-defined networking (SDN) technology, it's possible to control, secure, and optimize network resources, eliminating the rigid coupling between the control plane and the data plane in traditional network architectures. Here, the chapter explores the problems, difficulties, and potential solutions associated with software-defined networks (SDN), a novel concept in computer networking. Through SDN, the network gains the ability to be programmable, quick, and adaptable thanks to its separation of data and its ability to control traffic. 2023, IGI Global. All rights reserved. -
Exploring the dynamics of financial behaviors in romantic partnerships
Financial well-being is a multifaceted concept that is influenced by various factors, including individual and relational dynamics. While households are indeed vital to understanding economic dynamics, they often do not provide sufficient insight into the complex decision-making processes of romantic partners. In light of this, the chapter places its focus squarely on romantic partners as the primary unit of analysis within households, considering romantic partners to be the building blocks of the households. This chapter seeks to address a critical aspect of financial well-being by focusing on the complex dynamics of financial behaviors within romantic partnerships. By delving into the unique challenges and opportunities faced by couples in managing their finances, this chapter strives to bridge the gap by summing the current state of our knowledge proposes a comprehensive conceptual model to elucidate the factors affecting financial behaviors and, consequently, financial well-being among romantic partners. 2024, IGI Global. All rights reserved. -
A Comprehensive Study on Computer-Aided Cataract Detection, Classification, and Management Using Artificial Intelligence
The day-to-day popularity of computer-aided detection is increasing medical field. Cataract is a main cause of blindness in the entire world. Compared with the other eye diseases, computer-aided development in the area of cataract is remaining underexplored. Several researches are done for automated detection of cataract. Many study groups have proposed many computer-aided systems for detecting cataract, classifying the different type, identification of stages, and calculation of lens power selection prior to cataract surgery. With the advancement in the artificial intelligence and machine learning, future cataract-related research work can undergo very useful achievements in the coming days. The paper studies various recent researches done related to cataract detection, classification, and grading using various artificial intelligence techniques. Various comparisons are done based on the methodology used, type of dataset, and the accuracy of various methodologies. Based on the comparative study, research gap is identified, and a new method is proposed which can overcome the disadvantages and gaps of the studied work. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Spatio-temporal Model for the Analysis and Classification of Soil Using the IoT
The Internet of Things (IoT) is an evolving trend in the field of computer applications where various hardware and software are connected together to address a specific problem. With the help of the IoT, the world has become smart and enabled itself to connect various objects (e.g., cars, computers, mobile phones, and smart appliances) with distinctive Internet protocol addresses, which allows them to interact with one another, thus accomplishing various procedures. Applications of the IoT include but are not restricted to smart cities, healthcare, industry, and robotics. Amongst a huge list of applications furnished by the IoT, agricultural IoT is the theme of this chapter. The IoT in agriculture transforms entities such as crops, soils, and livestock in a smart way by utilizing underlying technologies such as embedded systems, pervasive computing, sensor networks, ubiquitous computing, ad hoc networks, various wireless communication technologies, Internet protocols and other advanced technologies. The research here focuses on the most important agriculture entity soil. It is the soil that determines the yield of a crop. The more fertile the soil, more qualitative is the yield. The main idea behind the research is to identify the soil most suitable for agriculture. Using a spatio-temporal model, the soil samples collected from various parts of the country are classified into agricultural soil and non-agricultural soil. This classification is done by the aid of features such as the pH of the soil, and its humidity, moisture, and temperature collected from IoT sensors. The chapter begins with an introduction to the usage of IoT technology in different areas of agriculture followed by an account of the proposed state-of-the-art model, and its results, analysis, and a conclusion. 2022 selection and editorial matter, Vikram Bali, Vishal Bhatnagar, Deepti Aggarwal, Shivani Bali, and Mario JosDiv; individual chapters, the contributors. -
Women in higher education institutions: Challenges faced by women in HEI and emerging opportunities
A multitasking Queen plays a heterogeneous role in each and everyone 's tremendous journey of life right from the beginning until the end. As a wife, mother, sister, daughter, mentor, philosopher, friend, lover, and most importantly, 'first teacher', her contributions are noteworthy. Nobody can even dream up life without a woman. Women are capable enough in learning, teaching, and sustenance throughout their life. The art of learning and teaching encompasses the art of living. As a teacher, she is a source of inspiration, knowledge, and reason for the future. The first smile, step, voice, and any word are being routed by the first teacher called mother cum woman. This chapter explores women in higher education institutions. 2022, IGI Global. All rights reserved. -
Counseling and psychotherapy in india: Professionalism amidst changing times
India is a melting pot of diversity in castes, communities, geographical regions, languages, religions, and practices, within a geographical area of 32,87,263 kilometers, with 28 states and seven union territories. Although the notions of counseling and psychotherapy are Western, the process of mentoring and assisting individuals through their developmental issues was already present in ancient models of care in India, such as the Guru Shishya System,1 the Joint Family Network,2 and traditional healing. Counseling and psychotherapy do not exist as completely distinct disciplines in India. Although counseling grew out of a strong guidance format and led to a proliferation of trained and lay counselors and psychotherapy arose from a strong theoretical clinical psychology background, these differences are blurred in society. As Arulmani (2007) points out: all that is termed as counseling today was embedded within a complex support system of social relationships (p. 70). Although these fields progressed, difficulties with accreditation exist. The Indian Association of Clinical Psychologists (IACP), along with other bodies such as the Counseling Association of India, offer discussions of matters related to psychotherapy counseling and clinical psychology, and provide the code of conduct in India (IACP, 1993). Varma (1982) highlighted seven distinct features of the Indian population that strongly infiuence how counseling and psychotherapy are practiced and received by clients: Mutual interdependence, lack of psychological sophistication involving introspective and verbal abilities, social distance between the doctor and the patient due to class hierarchies, religious belief in rebirth and fatalism and related accountability, guilt attributed to misdeeds in past life and social approval-related shame, and lower emphasis on confidentiality as society can be therapeutic allies. India is a collectivistic society wherein the self is relational (Roland, 2005), though recent socio-economic changes have resulted in a contradictory mix of traditional and modern elements in families (Murthy, 2003). Shah and Isaac (2005) note that relationship problems dominate themes in clinical interviews and in the process of individual, couple and family therapy sessions in India. 2013 by Taylor & Francis Group, LLC. -
Organizing data using lists: A sequential data structure
Computer programming aims to organize and process data to get the desired result. Software developer chooses a programming language for application development based on the data processing capabilities of the language. The list is one of the sequential data structures in Python. A list is limited to a particular data type, such as numbers or strings. Occasionally, a list may include data of mixed types, including numbers and strings. Elements in the list can be accessed by using the index. Usually, a list's elements are enclosed within square brackets and divided using commas. The list may be referred to as a dynamic-sized array, which denotes that its size increases as additional data is added and that its size is not predefined. List data structure allows repetition; hence, a single data item may appear several times in a list. The list assists us in solving several real-world problems. This chapter deals with the list's creation and manipulation, the complexity of processing the list, sorting, stack, and queue operations. 2023, IGI Global. All rights reserved. -
Trends in Terahertz Biomedical Applications
Terahertz radiation has drawn enormous attention in recent times due to its various application possibilities. This chapter reviews various emerging trends and well-established technologies in Terahertz biomedical. Due to its extraordinary sensing capabilities, non-invasive, non-ionizing properties, sensitive instrumentations for spectroscopy and imaging, Terahertz has found various biomedical sensing applications from biomolecules, proteins to cells and tissues. This chapter highlights terahertz device engineering, system technologies, range of materials, aiming at various biomedical applications. It also includes emerging topics such as terahertz biomedical imaging, pattern recognition and tomographic reconstruction by machine learning and artificial intelligence, for possible biomedical imaging applications. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Brief Review onDifferent Machine Learning-Based Intrusion Detection Systems
In the contemporary cybersecurity landscape, the proliferation of complex and sophisticated cyber threats necessitates the development of robust Intrusion Detection Systems (IDS) for safeguarding network infrastructures. These threats make it more challenging to maintain the communitys availability, integrity, and confidentiality. To ensure a secure network, community administrators should implement multiple intrusion detection systems (IDS) to monitor and detect unauthorized and malicious activities. An intrusion detection system examines the networks traffic by analyzing data flowing through computers to identify potential security threats or malicious activities. It alerts administrators when suspicious activities are detected. IDS generally performs two types of malicious activity detection: misuse or signature-based detection, which entails collecting and comparing information to a database of known attack signatures, and anomaly detection, which detects any behavior that differs from the standard activity and assumes it to be malicious. The proposed paper offers an overview of how different Machine Learning Algorithms like Random forest, k - Nearest Neighbor, Decision tree, Support Vector Machine, Naive Bayes, and K- means are used for IDS and how these algorithms perform on different well-known datasets, and Their accuracy and performance are evaluated and compared, providing valuable insights for future work. kNN shows an accuracy of 90.925% for Denial of Service Attacks and 98.244% for User To Root attacks. The SVM algorithm shows an accuracy of 93.051% for Probe attacks and 80.385% accuracy for remote-to-local attacks. According to our implementation, these two algorithms work better than the others. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
AI-based online interview bot with an interactive dashboard
In recent years, video interviews have become increasingly popular in the recruitment process due to their convenience and efficiency. However, evaluating a candidates communication skills and perceived personality traits from a video interview can be challenging. The agent utilizes natural language processing and computer vision techniques to analyze the candidates verbal and nonverbal behavior during the interview. Specifically, the agent focuses on linguistic features such as fluency, grammar, and vocabulary, as well as nonverbal cues such as facial expressions and body language. Based on these features, the agent predicts the candidates communication skills and perceived personality traits. To validate the effectiveness of the agent, a Talk was conducted with a group of participants who completed video interviews with and without the agent. The results show that the agents predictions of communication skills and perceived personality traits are highly correlated with the ratings given by human evaluators. Additionally, the agent is able to provide valuable insights into the candidates performance that may not be immediately apparent to human evaluators. Overall, the intelligent video interview agent proposed here has the potential to improve the recruitment process by providing more accurate and objective evaluations of candidates communication skills and perceived personality traits. 2025 selection and editorial matter, A. Vadivel, K. Meena, P. Sumathy, Henry Selvaraj, P. Shanmugavadivu and Shaila S. G.; individual chapters, the contributors.