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Development of high performance polymer composites by additive manufacturing
Additive manufacturing, often known as 3D printing, is a process that involves the manufacture of physical things in a manner that is similar to building them up layer by layer. As a result of its utilization of automated procedures to generate complicated three-dimensional forms, which are either difficult or impossible to produce using conventional methods, fused deposition modeling is a typical approach that uses heat to assist in the extrusion process. The term "high-performance polymer" refers to a group of polymer materials that are known to maintain their desirable mechanical, thermal, and chemical properties when subjected to harsh environments such as high temperatures, high pressures, and corrosive chemicals. This chapter starts off with a brief introduction of conductive and high-performance polymer composites, followed by a rundown of how these materials are utilized in the 3D printing process. 2023, IGI Global. All rights reserved. -
Role of women in food and agricultural development: Breaking barriers for sustainable growth
The role of women in food and agricultural development in India is vital as it has an essential impact on the country's agricultural development. Despite all the contributions, they often face major obstacles, such as limited access to resources such as land, credit, innovation, and technology, and addressing these barriers is important. In this chapter, the authors have examined areas and levels of farm women's participation, such as the crops they grow, post- harvest activities, the workload they carry, and, despite all the struggles, how the women are underestimated. Their contribution is not limited to crop cultivation but also includes dairy, poultry, fishing, aquaculture, and forestry such as the wood processing sector. Due to men moving towards urban areas for better jobs and quality of life, women in rural areas are pressured to work in the fields; due to this, agriculture is feminized, and women shoulder a heavier workload than men. The underrepresentation of women is also seen in the employment rate and the pay they receive during seasonal, non- seasonal, and part- time employment. 2024, IGI Global. All rights reserved. -
Self-Induced Versus Structured Corporate Social Responsibility: The Indian Context
Adoption of Corporate Social Responsibility (CSR) ranks among the top priorities of the corporates in contemporary times. It is treated as a core business practice across the corporate globe. In the year 2013, the Ministry of Corporate Affairs, Government of India enacted mandatory CSR rules under the Companies Act, 2013 and imposed statutory obligations on the companies operating in India to implement CSR activities. With this, India became one of the first countries in the world to legislate minimum regulatory spends on CSR practices. This chapter aims to evaluate the response of this legislation since the introduction of mandatory CSR rules in India. It looks into the important trends in corporate social responsibility spending of companies in India and also maps the CSR expenditure with various Sustainable Development Goals (SDGs). This chapter forms a case for deliberation for policymakers, practitioners, scholars and business organization to understand the implications of mandatory CSR as well as how Indian companies have responded to this CSR rule. The findings also provide important insights for the other countries promulgating statutory approaches to implement CSR in their own countries. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Big Data Preprocessing for Modern World: Opportunities and Challenges
Big data is an often misunderstood business term in the modern world. Multiple devices are connected to the internet and a democratization of available technologies. The data is generated almost exponential rate. This data is generated in large quantities, at a high speed and belongs to myriad categories. Coupled with advances in storage and processing hardware, it can derive insights from these bigger number of data but it works effectively. The data is to be transformed in the form of understandable and useable insights by algorithms and models. The data mining steps require data that is cleaned and structured to a larger extent. This is achieved by using various algorithms, processes and applications known as data pre-processing techniques. This article reviews the various data pre-processing techniques from a big data point of view. 2019, Springer Nature Switzerland AG. -
Internet of things for building a smart and sustainable environment: A survey
In the previous decade, internet of things (IoT) has emerged as a transformative force in the quest to create smarter and more sustainable environments. By interconnecting a large array of sensors, devices, and infrastructure, IoT technology enables the real-time collection, analysis, and utilization of data to optimize resource management, improve decision-making, and reduce environmental impact. In smart cities, homes, industries, and agricultural settings, IoT plays a pivotal role in achieving resource efficiency, environmental preservation, and economic growth. However, its widespread adoption also poses several challenges related to privacy, security, and interoperability. As IoT continues to evolve, it promises to shape a future where sustainability and technological innovation go hand in hand, making a path toward more resilient, efficient, and livable environments. 2024, IGI Global. All rights reserved. -
Nutraceuticals to prevent and manage cardiovascular diseases
Unhealthy lifestyle and diet are the key risk factors to cardiovascular diseases. A healthy cardiac and vascular system can prevent cardiovascular-related diseases like hypertension, atherosclerosis, and heart stroke. Identifying pharmacologically important metabolites had paved the way to contemporary medicine. People are more attracted to them as they are majorly plant-based metabolites such as polysaccharides, polyphenols, polysterols, and vitamins as cardio-protectors. Preclinical, clinical, and animal studies provide substantial data confirming nutraceuticals as a promising therapeutic agent in curing cardiovascular diseases. This chapter summarizes on major bioactive molecules as nutraceuticals with preclinical and clinical studies, emphasising their cardiovascular protective roles. 2023 Elsevier Inc. 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. -
GUIDELINES TO CARRY OUT TEACHING INTERNSHIP
The volume presented chapters on fundamental aspects of teaching internship to the cases of internship in countries across the Global South to the Global North. In addition, it discussed research insights into teaching internship practices and assessment of teaching internship. The previous chapter dealt with important templates useful for carrying out internships. The present chapter attempts to provide certain guidelines for carrying out internships. These guidelines might help those involved in organising teaching internships at schools. Understanding the steps of organising and deliberations on each stage of the internship process helps the stakeholders reap maximum benefit from the internship. Future researchers may focus on understanding the effectiveness of these guidelines when implemented. 2023 selection and editorial matter G.S. Prakasha and Anthony Kenneth; individual chapters, the contributors. -
TEACHING INTERNSHIP THE WAY FORWARD
This is the last chapter of the volume. Thus, it presents the summary of the volume, which includes the storyline on teaching internship with an analytical argument across the chapters. It presents an overview of all the internship models discussed in the first part of the volume and then about its second part, which is essentially the research insights and practicing guidelines of the teaching-internship. The chapter concludes with a discussion of moving forward. Moving forward discusses future possible trends in teaching internship, which include internships in virtual spaces and other innovations, which might replace the current teaching internship practices. 2023 selection and editorial matter G.S. Prakasha and Anthony Kenneth; individual chapters, the contributors. -
SAMPLE TEMPLATES FOR ORGANIZING TEACHING INTERNSHIP
The previous chapter discussed assessment in internship, while this chapter introduces various templates for such assessments and presentations in teaching internship. There are various tasks provided to preservice teachers, such as making reflections, observations, and lesson plans. These tasks are evaluated during the completion of the internship. A rubric for this evaluation is also provided in this chapter. The chapter also provides templates for a permission letter seeking leave and a template for successful completion of internship. The templates provided in this chapter can serve as a valuable resource for teacher educators, researchers and stakeholders in the field of teacher education for internship practices. 2023 selection and editorial matter G.S. Prakasha and Anthony Kenneth; individual chapters, the contributors. -
TEACHING INTERNSHIP IN INDIA
The chapter provides a detailed account of the evolution of education at different time periods from the Vedic, Buddhism, and Mughals to the present day, exploring any presence of teacher education. However, the official teacher education institutes were opened during the pre-independence era under British rule. The number of institutes has increased over the years with the reformation of numerous educational policies, such as the National Education Policy and Commissions (Kothari Commission, Mudaliar Commission, The University Education Commission, etc.). The chapter also offers insights into the emergence of internships, the regulating body for teacher education in India, and their significance, along with the requisites for a teacher in India. The universal model of internship as declared by NCTE is introduced towards the end, followed by the conclusion and drawbacks of a teaching internship in India. 2023 selection and editorial matter G.S. Prakasha and Anthony Kenneth; individual chapters, the contributors. -
RESEARCH INSIGHTS ON TEACHER EDUCATION
Teacher education is an important academic domain, as it determines the quality of school education through the teachers produced by teacher education. The changing demands and nature of learners at school force teachers to adapt themselves constantly. This requires change in the methods of teacher training and its curriculum. Thus, researchers specialised in the area of teacher education must find innovative approaches to train preservice and in-service teachers to meet the changing demands. The present chapter presents the research conducted on the developmental aspects of teacher education across the globe in the last two decades. The chapter organises the research inputs in five different areas for ease of understanding: research related to the application of sociological, psychological and technological theories to teacher education practices, research related to transformational changes, research on teacher and teaching competence and research pertaining to teacher reflection. This would help teacher educators, schoolteachers, trainee teachers and policy makers to organise and implement effective teacher training programmes. 2023 selection and editorial matter G.S. Prakasha and Anthony Kenneth; individual chapters, the contributors. -
ASSESSMENTS IN TEACHING INTERNSHIP
Teaching internship assessment is a blurred area in teacher education, as it involves multiple items to assess and require multiple measurement tools. The present chapter attempts to mention various teaching internship assessment practices prevailing in teacher education programmes across the globe. It also discusses a few established training assessment frameworks, assessment standards of a few countries, new experiments assessing internships as per the review of literature, value added assessment models, overall internship effectiveness, assessment after teacher training programme, and current teaching internship assessment practices of a few countries. While exploring the assessment, the chapter also details various components considered by teacher education institutes of assessment in teaching internships. The chapter provides a birds eye view of teaching internship assessment and helps the stakeholders to note, reflect, and create an indigenous effective assessment method for teaching internships. 2023 selection and editorial matter G.S. Prakasha and Anthony Kenneth; individual chapters, the contributors. -
Innovative instructional strategies that motivate students to learn during the pandemic
Coronavirus disease (COVID-19) has spread all over the world affecting public health at the outset of 2020. This has slowed down almost every sector of human life including education. However, few of the private educational institutes have risen to the occasion immediately and have continued providing education online. Teachers were forced to adapt themselves to teach online. Students started to attend online classes from home. Inevitably, parents had to invest in purchasing computers or smartphones and internet connections to support their children's education. Though all these changes began with an overwhelming spirit from all stakeholders, in no time it has become a monotony. This has led to the present study to find innovative instructional strategies that can motivate learners to learn and sustain interest in learning during pandemics. The present study employs a qualitative research design to address this issue. 2022, IGI Global. -
Covid-19 and school management
The breakout of COVID-19 from Wuhan, China has shaken the world economy, giving a traumatic experience to people across the world. Most of the countries have locked down their business enterprises. Schools have started teaching online, and teachers have moved to online teaching in no time. School managers are making quick decisions on various challenges faced by their schools. These uncertain conditions have led to the present study. The present study explores the impact of COVID-19 on various dimensions of school management, such as finance, infrastructure, staff training, student enrollment, student retention, student welfare activities, co-curricular activities, and challenges and opportunities; how to maintain efficiency amidst COVID-19 pandemic; and how to reduce the pandemic effect in schools. This research employed the phenomenological qualitative method to address the research problems. The data was collected from the semi-structured online interview and review of related literature. The study describes the effect of COVID-19 on various dimensions of school management. 2022, IGI Global. All rights reserved. -
Gamification in teacher education: Teacher educators and trainee teachers' perspectives in India
Gamification emerged as a teaching-learning pedagogy in recent years. Its usage increased during the Covid-19 lockdown and continued post-pandemic time. Its usage ranges from online to offline tools; teachers lack its awareness as a pedagogy. The present study aimed to understand perspectives of teacher educators and teacher trainees on inclusion of gamification pedagogical training in teacher preparation programmes. The study employed a mixed-method approach and included qual-quant sequential explanatory research design. Researchers conducted semi-structured interviews with six teacher educators and six trainee teachers and collected the opinion of 200 teacher educators and trainee teachers. The study employed inductive thematic analysis and Chi-square analysis for qualitative and quantitative data respectively. Findings revealed six main themes and twelve sub-themes. Chi-square revealed a gender science-stereotype amid association between teacher educators and teacher trainees' opinion. Senior teacher educators did not believe in the importance of gamification inclusion in teacher preparation. 2024, IGI Global. All rights reserved. -
A novel approach using steganography and cryptography in business intelligence
In the information technology community, communication is a vital issue. And image transfer creates a major role in the communication of data through various insecure channels. Security concerns may forestall the direct sharing of information and how these different gatherings cooperatively direct data mining without penetrating information security presents a challenge. Cryptography includes changing over a message text into an unintelligible figure and steganography inserts message into a spread media and shroud its reality. Both these plans are successfully actualized in images. To facilitate a safer transfer of image, many cryptosystems have been proposed for the image encryption scheme. This chapter proposes an innovative image encryption method that is quicker than the current researches. The secret key is encrypted using an asymmetric cryptographic algorithm and it is embedded in the ciphered image using the LSB technique. Statistical analysis of the proposed approach shows that the researcher's approach is faster and has optimal accuracy. 2021, IGI Global. -
Computational Aspects of Business Management with Special Reference to Monte Carlo Simulation
Business management is concerned with organizing and efficiently utilizing resources of a business, including people, in order to achieve required goals. One of the main aspects in this process is planning, which involves deciding operations of the future and consequently generating plans for action. Computational models, both theoretical and empirical, help in understanding and providing a framework for such a scenario. Statistics and probability can play an important role in empirical research as quantitative data is amenable for analysis. In business management, analysis of risk is crucial as there is uncertainty, vagueness, irregularity, and inconsistency. An alternative and improved approach to deterministic models is stochastic models like Monte Carlo simulations. There has been a considerable increase in application of this technique to business problems as it provides a stochastic approach and simulation process. In stochastic approach, we use random sampling to solve a problem statistically and in simulation, there is a representation of a problem using probability and random numbers. Monte Carlo simulation is used by professionals in fields like finance, portfolio management, project management, project appraisal, manufacturing, insurance and so on. It equips the decision-maker by providing a wide range of likely outcomes and their respective probabilities. This technique can be used to model projects which entail substantial amounts of funds and have financial implications in the future. The proposed chapter will deal with concepts of Monte Carlo simulation as applied to Business Management scenario. A few specific case studies will demonstrate its application and interpretation. 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Big data analytics lifecycle
Big data analysis is the process of looking through and gleaning important insights from enormous, intricate datasets that are too diverse and massive to be processed via conventional data processing techniques. To find patterns, trends, correlations, and other important information entails gathering, storing, managing, and analyzing massive amounts of data. Datasets that exhibit the three Vs-volume, velocity, and variety-are referred to as "big data. " The vast amount of data produced from numerous sources, including social media, sensors, devices, transactions, and more, is referred to as volume. The rate at which data is generated and must be processed in real-time or very close to real-time is referred to as velocity. Data that is different in its sorts and formats, such as structured, semi-structured, and unstructured data, is referred to as being varied. 2024, IGI Global. All rights reserved. -
Natural Language Processing in Medical Applications
Medical applications of machine learning are very new, and there are still several obstacles that limit their widespread use. There is still a need to address issues like high dimensionality data and a lack of a standard data schema. An intriguing way to explore the possibilities of machine learning in healthcare is to apply it to the difficult problem of cardiovascular disease diagnosis. At the present day, cardiovascular disorders account for the majority of deaths worldwide. It is often too late to adopt appropriate treatment for many of them because they progress for a long time without showing any symptoms. Because of this, its crucial to get checked up on routinely so that any developing diseases can be caught early. If the sickness is caught early enough, effective therapy can be put into place to stop the progression of the illness. This is done with the intention of analysing data from many sources and making use of NLP to overcome data heterogeneity. This paper evaluates the usefulness of several machine learning methods (such as the Naive Bayes (NB), Transductive Neuro-Fuzzy Inference, and Terminated Ramp-Support Vector Machine (TR-SVM)) for healthcare applications and suggests using Natural Language Processing (NLP) to address issues of data heterogeneity and the transformation of plain text. The implementation, testing, comparison of performance and analysis of the parameters of the algorithms used for diagnosis have simplified the process of selecting an algorithm better suited to a certain instance. TWNFI is particularly effective on larger datasets, while Terminated Ramp-Support Vector Machine is well suited to lesser datasets with a lower number of magnitudes due to performance difficulties. 2024 Scrivener Publishing LLC.