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A Case Study on Zonal Analysis of Cybercrimes Over a Decade in India
Human intelligence has transformed the world through various innovative technologies. One such transformative technology is the internet. The world of the internet, known as cyberspace, though powerful, is also where most crimes occur. Cybercrime is one of the significant factors in cybersecurity, which plays a vital role in information technology and needs to be addressed with high priority. This chapter is a case study where we analyze cybercrimes in India. The data collected from NCRB for 2010 to 2020 are a primary source for the analysis. A detailed analysis of cybercrime across India is done by dividing locations into seven zones: central, east, west, north, south, northeast, and union territories. Cybercrimes reported in each zone are examined to identify which zone requires immediate measures to be taken to provide security. The work also identifies the top ten states which rank high in cybercrime. The main aim of this chapter is to provide a detailed analysis of crimes that occurred and the measures taken to curb them. Along with the primary data, secondary data from CERT-In are also used to provide an analysis of measures taken for handling cybercrime over a decade. The outcome facilitates various stakeholders to better bridge the gap in handling cybercrime incidences, thus helping in incidence prevention and response services as well as security quality management services. 2023 selection and editorial matter, Narasimha Rao Vajjhala and Kenneth David Strang; individual chapters, the contributors. -
Digital education for a resilient new normal using artificial intelligenceapplications, challenges, and way forward
As society and technology advance to meet Industry 4.0 requirements, the educational system has also undergone many transformative changes in the past decade. Education is regarded as one of the most important tools for developing individuals, families, businesses, and the economy. New digital technologies are making a great revolution by transforming all aspects of education in teaching, learning, assessment, and feedback. The COVID-19 pandemic has led to the proliferation of digital education and its replacement of traditional education in the educational system. The developments in artificial intelligence (AI) are indispensable in all sectors, including education. AI-integrated learning helps management, teachers, students, parents, and other stakeholders gain insight into their performance to impact the process positively. This chapter aims to throw light on the emerging need and technologies used for digital education and to examine the role of AI in education with examples from the perspectives of teaching, learning, and assessment in the new normal. The application of AI in education and its effectiveness is explored through six publicly available datasets along with strengths, weaknesses, opportunities, challenges, and the future of digital education. This chapter discusses several examples and benefits of AI applications that enhance the educational experience and also emphasizes the need to align it with technology and curriculum to achieve the intended learning outcomes. 2023 Elsevier Ltd. All rights reserved. -
Conclusion
We all can agree at one point: the COVID-19 pandemic has had a massive and unanticipated impact on all the lives of all tourists. The global tourism and hospitalityindustry has been heavily damaged, but the societal impact cannot be overlooked. Consumer behavior, and ultimately consumer spending, has been and will continue to change, and company planning must adapt to these new realities. The major findings of this edited book in the contexts of tourism, destination recovery and crisis management thus have value for the industry and for researchers seeking to understand these changes. Chapter 1 analyses evolution of tourism and hospitality during times of crisis and how these businesses might rebound. Academics in the field of tourism and hospitality can use this collection to understand the most recent studies on crises and recovery. The impact of the COVID-19 crisis on tourism and hospitality was examined in several published pieces. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
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. -
Human Resource Management in Digital India
The business entities of today are aware of the vital role played by technological interventions in value creation. HR technological interventions are no exceptions either. These interventions are aligned to business goals and help businesses achieve their bottom lines. Nevertheless, some business owners are apprehensive about the way forward while adopting technology. This chapter focuses on the various technologies that aid HR functions, its implementation framework keeping in perspective the key apprehensions, considerations and competency requirements. The chapter highlights few Indian organizations that have adopted it. The findings show that emphasis is laid on business value creation for stakeholders due to HR technology adoption. 2023 by World Scientific Publishing Co. Pte. Ltd. All right reserved. -
Community Resilience and Crisis Management: Stakeholders Perspective of the Tourism Industry
The tourism industry is very vulnerable and has been extensively impacted by varied types of crisis. An attempt is made to precipitate and reflect on the nature of tourism disasters indicating an imperative need for an integrated approach to deal with crisis with disaster planning and a response system. Destinations at crisis impacts humankind causing environmental impacts and economic downfall and largely impacts the local community to recover from the disaster. This chapter examines varied impacts affecting the tourism industry and addressed negative impacts like the Economic crisis and loss of brand image in the post-crisis situation. The conceptual framework indicates Community Resilience model towards destination development and Resilience Building. The role of key stakeholders supporting e-governance and financial resilience pertaining to tourism business is further examined. The chapter explores mechanisms to re-establish the brand image during the restoration phase and have indicated possible strategies and suggestions in the recovery phase of an affected region. Disaster risk reduction is a significant and major phenomenon in handling all kinds of crisis management, therefore this chapter will be an essential reading for tourism education and destination managers who are engaged in destination crisis planning and disaster management. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
Recent development on self-powered and portable electrochemical sensors: 2D materials perspective
Electrochemical sensors have attracted tremendous research interest due to their simplicity and compatibility to be integrated with standard electronic technologies and capability to produce electrical signals that can be effectively acquired, processed, stored, and analyzed. Due to the incredible electronic and physical properties derived from the 2D structure, two dimensional (2D) nanomaterials such as graphene, phosphorene black phosphorus, transition metal dichalcogenides (TMDCs), and others have proven to be attractive for the fabrication of high-performance electrochemical sensors. The book chapter is focused in the unique characteristics of 2D materials leading toward excellent sensing performance, the structural and molecular designing of various 2D materials, structure-property relationships, various sensing applications employing disparate 2D nanostructures with an emphasis on highlighting various prototypical and prominent research paths. 2023 Elsevier Inc. All rights reserved. -
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. -
Health informatics and its contribution to health sectors
In most developed countries, healthcare sectors take more than 10% of the GDP, and it is one of the most significant and most rapidly growing sectors globally. With such growth of the healthcare department, data management becomes challenging; a robust platform helps to address these challenges. Health Informatics (HI) is an upcoming development, an interdisciplinary field in healthcare sectors; it combines the Internet of Things (IoT) and Artificial Intelligence (AI) in the healthcare software, which helps boost the overall operational efficiency of the healthcare departments. These AI algorithms integrated into IoT devices help acquire, store, retrieve, and use health and medical-related data. Patient data are enormous in healthcare sectors, and it is required for various purposes by hospital administrators, insurance agents, doctors, nurses, and other health departments. Accessing and managing these datasets often becomes challenging; HI is one of those innovations that has helped address these challenges to a large extent. The chapter discusses informatics, related definitions, HI, and its relation with other disciplines. The chapter also provides an educational overview of the evolution of HI, different HI technologies, benefits and challenges of HI to its various stakeholders. It ends with some thoughts on HI's future growth. The Institution of Engineering and Technology 2023. All rights reserved. -
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. -
Recruitment Analytics: Hiring in the Era of Artificial Intelligence
Introduction: Traditional recruitment system relied heavily on the applicants curriculum vitae (CV). This system, besides becoming redundant, has proved to be a futile exercise leading to the hiring of candidates that eventually turn out to be misfits. CVs were the only source of candidates data available for the recruiters a few years back. Face-to-face interviews was considered to be the ultimate solution for hiring suitable candidates. However, evidence suggests that interview scores and job performances do not complement each other. Advancement in artificial intelligence (AI) has introduced several techniques in the recruitment process. Purpose: This chapter underscores the drawbacks of the traditional recruitment process. Evidence suggests that the traditional recruitment process is prone to subjectivity and is time-consuming. Surprisingly, despite the disadvantages, the integration of AI into the recruitment process is still slow. This chapter highlights the need to harness AI and the advantage technology could bring to the recruitment process. Some of the techniques that are garnering attention and widely used by organisations, such as chatbots, gamification, virtual employment interviews, and resume screening are described to enable the readers to understand with less effort. Chatbots and gamification techniques are described through process flow charts. We also describe the various types of interviews that could be conducted through virtual platforms and the modality by which the resume screening technique operates. Today, we are at a juncture wherein it is pertinent to acknowledge the superiority of technology-driven processes over traditional ones. This chapter will help the readers to understand the modus operandi to implement chatbots, gamification, virtual interviews and online resume screening techniques besides their advantages. Scope: Although chatbots, resume screening, virtual interviews, and gamification are used in other areas, too, such as training and development, marketing, etc., in this chapter, we restrict solely to employee recruitment processes. Methodology: Scoping review is used to examine the existing literature from various databases such as Google Scholar, IEEE, Proquest, Emerald, Elsevier, and JSTOR databases are used for extracting relevant articles. Findings: Automation and analytics in recruitment and selection remove bias which is otherwise increasingly found in manual hiring processes. Also, previous studies have observed that candidates engage in impression management tactics in traditional face-to-face interviews. However, through automated recruitment processes, the influence of these tactics can be eliminated. AI-based virtual interviews reduce human bias. It also helps recruiters to hire talents across the globe. Gamification improves the candidates perception of the work and work environments. Through gamified techniques, the recruiters can understand whether a candidate possesses the required job skills. Chatbots are an interactive technique that can respond to interviewees queries. Resume screening techniques can save the recruiters time by screening and selecting the most appropriate candidates from a large pool. Hence, the chosen candidates alone can be referred to the next stage of the recruitment cycle. AI improves the efficiency of the recruitment process. It reduces mundane tasks. It saves time for the human resources (HR) team. 2023 by V. R. Uma, Ilango Velchamy and Deepika Upadhyay. -
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. -
Introduction
[No abstract available] -
Denial of Service Attacks in the Internet of Things
A DoS attack is the most severe attack on IoT and creates a crucial challenge for the detection and mitigation of such attacks. A DoS attack occurs at multiple layers of the IoT protocol stack and exploiting the protocol vulnerabilities disrupts communication. Traditional mechanisms employ single-layer detection of DoS attacks, which individually detect and mitigate attacks. However, it is essential to establish a general framework for detecting DoS attacks in a real-time environment and coping with diversified applications. This can be achieved by fetching attack features of multiple layers to create a pool of numerous attacks and then designing a system that detects the attack when fed with specific attack features. This chapter comprehensively analyzes the research gap in the DoS attack detection techniques proposed. Secondly, we offer a two-stage framework for DoS attack detection, comprising Fuzzy Rule Manager and Neural Network (NN), to detect cross-layer DoS attacks in real time. The Input Data Type (IDT) is derived using a fuzzy rule manager that can identify the type of input dataset as usual or attack in real time. This IDT is passed to the NN along with the real-time dataset to increase detection accuracy and decrease false alarms. 2024 selection and editorial matter, Vinay Chowdary, Abhinav Sharma, Naveen Kumar and Vivek Kaundal; individual chapters, the contributors. -
A Review of Deep Learning Methods in Automatic Facial Micro-expression Recognition
Facial expression analysis to understand human emotion is the base for affective computing. Until the last decade, researchers mainly used facial macro-expressions for classification and detection problems. Micro-expressions are the tiny muscle moments in the face that occur as responses to feelings and emotions. They often reveal true emotions that a person attempts to suppress, hide, mask, or conceal. These expressions reflect a persons real emotional state. They can be used to achieve a range of goals, including public protection, criminal interrogation, clinical assessment, and diagnosis. It is still relatively new to utilize computer vision to assess facial micro-expressions in video sequences. Accurate machine analysis of facial micro-expression is now conceivable due to rapid progress in computational methodologies and video acquisition methods, as opposed to a decade ago when this had been a realm of therapists and assessment seemed to be manual. Even though the research of facial micro-expressions has become a longstanding topic in psychology, this is still a comparatively recent computational science with substantial obstacles. This paper a provides a comprehensive review of current databases and various deep learning methodologies to analyze micro-expressions. The automation of these procedures is broken down into individual steps, which are documented and debated. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Synthesis and catalytic applications of metal boride ceramics
Metal borides belong to the class of high-temperature ceramics and have conventionally been used for high-temperature applications. However, in the past few decades, new variants of metal borides have emerged, with high catalytic capabilities. Owing to their tuneable structural, compositional, and morphological properties, metal borides have huge potential for industrially relevant catalytic applications. This chapter compiles the existing knowledge on the ever-expanding family of metal borides. Various synthesis strategies that are commonly adopted for the fabrication of metal borides, both in crystalline and amorphous/nanocrystalline forms, are discussed in detail. The chapter also aims to explain the origin of catalysis in metal borides. Some of the most prominent catalytic applications of metal borides are vividly discussed in this chapter. At the end of this chapter, a brief outlook is provided for future research initiatives with metal borides. 2023 Elsevier Ltd. All rights reserved. -
Review of Medical Drones in Healthcare Applications
Drone technology has an immense potential to provide various efficient solutions in the healthcare sector. It has been used in different applications ranging from transportation to rescue. The recent benefits of drone technology to assist emergency situations have achieved academic attention, which results in extensive practical implementation and simulation. However, it still needs to come into a reality beyond a certain extent. The involvement of drones in the healthcare industry has grown to be smart and intelligent for providing better medical care, fast transport and delivery of medicines, and search and rescue operations. The most important reason behind the evolution of drones is the replacement of human service, which is required during the global health crisis. Recent technology such as the Internet of Things, artificial intelligence, and the 5G network joined hands with drone technology, resulting in a great benefit to the healthcare industry. Drones are needed to battle the coronoavirus by delivering medicines and test samples. It is also involved in remote pandemic management in the form of helping the authorities to monitor social gatherings, by broadcasting the awareness messages and nearby hospitals details, for spraying virus protection liquid on the street, and many more. Therefore, this chapter proposes the intricacies of the Internet of medical drones in the healthcare sector, in hopes of empowering and eliciting more aggressive investigation. 2023 selection and editorial matter, Saravanan Krishnan and M. Murugappan; individual chapters, the contributors. -
Blockchain technology toward green internet of thingsan exploratory survey
Over the past couple of decades, there has been a spike in industrial activity across the entire world, which has led to an increase in the utilization of fossil fuels. During the same era, technological innovations have triggered an increase in both climate change and carbon legacies. The use of energy by the Internet of Things (IoT) has resulted in a fresh dilemma, which has oriented our priority toward the design of an IoT ecosystem that is more ecological and sustainable. Institutions of higher learning and business corporations have shown interest in the green IoT because it facilitates improved energy-efficient delivery of services and simplifies the process to generate and make consumable use of renewable energy. Blockchain technology is gaining interest from energy producers, entrepreneurial ventures, investment firms, legislatures, and scientists since it is incredibly flexible, safe, and secure. This chapter focuses on the significance of blockchain technology in the green IoT community, highlights the critical considerations that need to be taken into account, and explores how blockchain technology renders the IoT ecosphere healthier and greener. In addition to this, it places an emphasis on the inherent necessity of establishing a long-term IoT infrastructure that takes utilization of the appropriate blockchain technology to another level altogether. 2023 Elsevier Inc. All rights reserved. -
Plant- based Metabolites as Source of Antimicrobial Therapeutics: Prospects and Challenges
Plants are used as traditional medicines from ancient times to today as they are the largest living storehouses of bio- chemicals and pharmaceuticals known on Earth (Abdallah, 2011). The World Checklist of Vascular Plants (WCVP) database reported in April 2021 that there are 1,383,297 plant names with 996,093 plants identified at species level, constituting 342,953 accepted vascular plant species (Govaerts et al., 2021). Around 10% of the reported vascular plants are used as medicines (Salmer- Manzano et al., 2020). According to the MPNS, 33,443 species are recorded as being used for medicinal purpose (MNPS, 2021). Medicinal plants are those that have therapeutic properties which can pose pharmacological effect on the human or animal body (Namdeo, 2018). About 80% of the world's population depends on plant- based medicine for treatment of diseases (Okoye et al., 2014). The medicinal property of a plant is attributed to rich and diverse secondary metabolites (Allemailem, 2021). Secondary metabolites are intermediates or products of primary metabolism that are not involves directly in the growth and development of the plant (Jain et al., 2019). Plants generate secondary metabolites in response to stresses posed by biotic factors (bacteria, fungi, viruses, parasites, pests, weeds, and herbivore animals) and abiotic environmental factors (temperature, salinity, drought, UV radiation etc.) so as to adapt and survive in response to environmental stimuli during their life time (Yang et al., 2018). 2023 selection and editorial matter, Arti Gupta and Ram Prasad; individual chapters, the contributors. -
Detection of Alzheimers Disease Stages Based on Deep Learning Architectures from MRI Images
Acquiring, utilizing and storing information of any sort is known as memory. The power of memory makes the life of mankind to be more alive and reasonable. Thus, the loss of one such great capability is a rather painful phase of human life which can be destructed by multiple reasons such as diseases and disorders. One such disease is Alzheimers disease (AD). Alzheimers disease progressively damages brain cells and degrades mental activity that leads to mental illness. The accurate diagnosis of AD at earlier stages will help to prevent the disease before the brain gets damaged completely. In analyzing neurodegenerative disorders, neuroimaging plays an important role in diagnosing subjects with AD, mild cognitive impairment (MCI), and cognitively normal (CN). In this study, advanced deep learning (DL) architectures with brain imaging techniques were employed to maximize the diagnostic accuracy of the model developed. The proposed method works with convolutional neural networks (CNNs) to analyze the MRI input-output modalities. The method is evaluated using Alzheimers Disease Neuroimaging Initiative (ADNI) dataset. Binary classification is done on AD and MCI subjects from CN. This method is efficient to analyze multiple classes with a less amount of training data. 2023 selection and editorial matter, Jyotismita Chaki; individual chapters, the contributors.