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Application and challenges of optimization in Internet of Things (IoT)
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Application Areas, Benefits, and Research Challenges of Converging Blockchain and Machine Learning Techniques
In recent years, machine learning (ML) has become a hot topic of research and application. ML model and huge amount of data growth difficulties still follow ML development. With the lack of new data and constant training, published ML models may soon become obsolete; unscrupulous data contributors may upload incorrectly labelled data, leading to poor training results; and data leakage and abuse are all possible outcomes. These issues can be effectively addressed by using blockchain, a new and rapidly evolving technology. With the advancement of various smart devices and the field of artificial intelligence and machine learning, interdisciplinary collaboration with blockchain technology may be incredibly valuable for future investigations. Collaborative ML and blockchain convergence can be studied here, with emphasis on how these two technologies can be combined and their application areas. On the other hand, look at the existing researchs shortcomings and future enhancements. The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024. -
Application of AI-Based Learning in Automated Applications and Soft Computing Mechanisms Applicable in Industries
The term artificial intelligence is used to describe a method through which computers may teach themselves new skills and develop themselves, without the help of humans or any predetermined instructions. Machines are fed data and trained to look for patterns; these patterns are then used as templates for further learning. They get the agency to choose their own actions and alter their habits accordingly. The term soft computing refers to a group of computational techniques that draw inspiration from both AI and natural selection. Solutions to difficult real-world situations that have no simple computer solution are provided, and they are both practical and cost-effective. Soft computing is an area of study in mathematics and computer science that has been around since the early 1990s. The idea for this project sprang from the fact that people can think of solutions that are close to the ones in the actual world. It is via the use of approximations that the science of soft computing is able to solve difficult computational challenges. Industrial automation is used by a diverse variety of industries and companies to improve the effectiveness of their processes by leveraging a number of technology developments. Many routine tasks are being changed by industrial applications. Industrial automation that reduces breakdowns and repairs quickly might help a business save money. 2024 selection and editorial matter, Nidhi Sindhwani, Rohit Anand, A. Shaji George and Digvijay Pandey; individual chapters, the contributors. -
Application of Artificial Intelligence on Smart Tourism Eco Space: An Integrated Approach in Post-COVID-19 Era
The AI-integrated approach in recent times has evolved with innovative techniques and gained much importance in the post-COVID-19 scenario. This chapter extends contemporary and exponential research findings for Smart Tourism Practices and the Application of AI-enabled systems for the Tourism Ecosystem. It highlights for various service segments like hotels, motels, resorts, restaurants, cafes, airlines, and destinations under this large umbrella known as the hospitality sector. Smart tourism eco space capacitates an ICT-enabled system consolidates tourism resources and information technologies. Perhaps, with multiple challenges, a successful implementation of smart tourism approaches empowers and supports a smart system in place. The tourism eco space is highly vulnerable, and this situation in the service sector creates an intense requirement of a comprehensive view of digitally enabled smart tourism eco space with innovative mechanisms to remain contact-free with less human intervention. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Application of experiential, inquiry-based, problem-based, and project-based learning in sustainable education
This chapter explores integrating pedagogical approaches for sustainable teaching and learning, emphasizing the capacity to meet present requirements without compromising the future. It highlights the merits of experiential, inquiry-based, problem-based, and project-based methods in sustainable practices in education. Experiential learning emphasizes practical application and reflection, whereas inquiry-based learning promotes inquiry and exploration. Problem-based learning immerses students in real-world sustainability challenges and interdisciplinary collaboration, whereas project-based learning enables students to take on leadership roles. Integrating these techniques offers a variety of options for addressing complex environmental issues. Future obstacles include integrating technology and ensuring equitable access. Integrated educational practices require learner-centred approaches, collaboration, and continuous feedback, empowering students to become proactive sustainability advocates and promoting positive change for a sustainable future. 2024, IGI Global. All rights reserved. -
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. -
Application of machine intelligence-based knowledge graphs for software engineering
This chapter focuses on knowledge graphs application in software engineering. It starts with a general exploration of artificial intelligence for software engineering and then funnels down to the area where knowledge graphs can be a good fit. The focus is to put together work done in this area and call out key learning and future aspirations. The knowledge management system's architecture, specific application of the knowledge graph in software engineering like automation of test case creation and aspiring to build a continuous learning system are explored. Understanding the semantics of the knowledge, developing an intelligent development environment, defect prediction with network analysis, and clustering of the graph data are exciting explorations. 2021, IGI Global. -
Application of Nanomaterials in Fuel Cell and Photovoltaic System
The emerging appliances and components of nanotechnology facilitate pioneering and cost-efficient strategies to meet the ever-growing energy demands. Employment of nanomaterials fetched innovative approaches for processing, storing, and exchange of energy owing to its nanosized and well-defined structure. This review presents an overview of the involvement of nanomaterials that made breakthroughs in the field of fuel cell and photovoltaic technologies. While the morphologies and unique dimensions of nanostructures offered novel electrolytes and high surface area for fuel cell catalysts; the probability of quick separation and collection of photogenerated charge carriers was enhanced in solar cells. This book chapter will focus on the recent research and developments for improving efficiency and lower device fabrication cost in nano-enabled fuel and solar cells. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Application of neuroscience methods in HRDM for brain-based human capital optimization
For years, human resource development and management (HRDM) has used behavioral assessments to gauge employee potential. However, advancements in cognitive behavioral neuroscience (CBN) have opened up new possibilities for understanding how the human mind works. This chapter explores the practical applications of neuroscience methods like EEG, ERP, MRI, and fMRI, as well as neurofeedback and biofeedback, in talent identification, leadership development, and employee well-being. Importantly, these insights can be directly applied in HRDM practices, leading to more effective talent management, leadership development, and improved employee well-being. While recognizing the ethical considerations involved with these technologies, the chapter presents a compelling vision for a future where HRDM practices are informed by a deeper understanding of the brain, enabling the workforce to reach its full potential. 2024 by IGI Global. All rights reserved. -
Applications of artificial intelligence in Echo Global Logistics
Echo Global Logistics is a premier provider of business process outsourcing, using technology to meet its clients logistics and transportation needs. They deliver substantial transportation savings to clients while providing top-tier service, thanks to state-of-the-art web-based technologies, dedicated service teams, and significant purchasing power. The most significant business risk in 2023 will be supply chain interruptions, which can impact cash flow, growth, and shareholder value. Echo Global Logistics has introduced an innovative self-service website called Echo Ship, designed for shippers of less-than-truckload (LTL) shipments. Echo Ship simplifies LTL shipping with excellent visibility, outstanding functionality, and a quick, user-friendly design. Logistics is evolving at Echo Global Logistics, with patented technology incorporating the latest developments in the most flexible and reliable transport management system (TMS) currently available. This TMS is developed using Artificial Intelligence (AI), machine learning, and complex load-matching algorithms. Echos unique software is user-friendly, adaptable, and highly scalable, addressing the evolving needs of carriers and shippers regarding transportation management, enabling customers to move their goods swiftly, securely, and affordably. A transportation management company leverages AI to provide supply chain solutions that optimize transportation and logistics needs. The list of services also encompasses executive dashboard presentations, rate negotiation, transportation procurement, shipment execution and tracking, carrier management, carrier selection, reporting, compliance, and comprehensive shipment reports, Over the next five years, supply chain companies anticipate a twofold increase in the use of machine automation in their operations. Similarly, there is a projected 40% compound annual growth rate (CAGR) over the next seven years, going from $1.67 billion in 2018 to $12.44 billion in 2024. Supply chain executives are often time-constrained, making it challenging to attend numerous meetings for solution implementation. Actionable insights from integrated AI tools can remove bottlenecks and unlock real-time value. This is vital because supply chain businesses require more action rather than excessive analysis. This chapter delves into the AI and supply chain practices at Echo Global Logistics, illustrating how AI-based solutions reduce costs, enhance supply chains, boost productivity, and improve service quality. It aims to determine whether the company can transform its products and services, creating new value propositions for Echo Global Logistics customers with the aid of AI. 2024 by Elsevier Inc. All rights reserved, including those for text and data mining, AI training, and similar technologies. -
Applications of artificial intelligence techniques in modern banking sectors
AI-powered decision-making instruments are cutting-edge technology that has the potential to displace conventional banking procedures. This chapter emphasizes the critical role artificial intelligence (AI) has played in guiding the banking industry toward expansion. AI techniques including robotics, deep learning, facial recognition, natural language processing, and more are used to achieve this goal. This chapter provides an overview of the use of AI approaches in several banking functional domains, such as loan approval, customer lifecycle management, customer services, alarm systems, and so on. It also highlights the benefits and difficulties that AI-driven financial apps provide. In summary, artificial intelligence (AI) has enormous promise in banking, but it also confronts several obstacles that, if correctly recognized and overcome, might broaden its use. This chapter is an invaluable tool for researchers, lawmakers, and bank officials who want to learn more about the unrealized potential of artificial intelligence in banking. 2024, IGI Global. All rights reserved. -
Applications of artificial intelligence to neurological disorders: Current technologies and open problems
Neurological disorders are caused by structural, biochemical, and electrical abnormalities involving the central and peripheral nervous system. These disorders may be congenital, developmental, or acute onset in nature. Some of the conditions respond to surgical interventions while most require pharmacological intervention and management, and are also likely to be progressive in nature. Owing to a high global burden of the most common neurological disorders, such as dementia, stroke, epilepsy, Parkinsons disease, multiple sclerosis, migraine, and tension-type headache, there exist multiple challenges in early diagnosis, management, and prevention domains, which are further amplified in regions with inadequate medical services. In such situations, technology ought to play an inevitable role. In this chapter, we review artificial intelligence (AI) and machine learning (ML) technologies for mitigating the challenges posed by neurological disorders. To that end, we follow three steps. First, we present the taxonomy of neurological disorders, derived from well-established findings in the medical literature. Second, we identify challenges posed by each of the common disorders in the taxonomy that can be defined as computational problems. Finally, we review AI/ML algorithms that have either stood the test of time or shown the promise to solve each of these problems. We also discuss open problems that are yet to have an effective solution for the challenges posed by neurological disorders. This chapter covers a wide range of disorders and AI/ML techniques with the goal to expose researchers and practitioners in neurological disorders and AI/ML to each others field, leading to fruitful collaborations and effective solutions. 2022 Elsevier Inc. All rights reserved. -
Applications of Digital Technologies and Artificial Intelligence in Cryptocurrency - A Multi-Dimensional Perspective
The paradigm shift requires spreading the light of decentralized ledger technology, extraordinarily implementing cryptocurrencies, and being visible as a game-changer. Blockchain technology, along with cryptocurrencies like Bitcoin, Ethereum, and Litecoin, is a tool for global economic transformation that is rapidly gaining traction in the finance industry. However, these technologies have had low popularity in the consumer market. Many platforms have been misunderstood and ignored when there is an obvious hole in among them. The basic idea behind cryptocurrency is that it is a network-based, totally virtual exchange medium that utilizes cryptographic algorithms such as Secure Hash Algorithm 2 (SHA-2) and Message Digest 5 (MD5) to secure the data. Transactions within the blockchain era are secure, transparent, traceable, and irreversible. Cryptocurrencies have gained a reputation in practically all sectors, including the monetary sector, due to these properties. The uncertainty and dynamism of their expenses, however, hazard investments substantially despite cryptocurrencies growing popularity amongst approval bodies. Studying cryptocurrency charge prediction is fast becoming a trending subject matter in the global research community. Several device mastering and deep mastering algorithms, like Gated Recurrence Units (GRUs), Neural nets (NNs), and nearly short-term memory, were employed by the scientists to analyze and forecast cryptocurrency prices. As a part of this chapter, we discuss numerous aspects of cryptographic protection and their related issues. Specifically, the research addresses the state-of-the-art by examining the underlying consensus mechanism, cryptocurrency, attack style, and applications of cryptocurrencies from a unique perspective. Secondly, we investigate the usability of blockchain generation by examining the behavioral factors that influence customers decision to use blockchain-based technology. To identify the best crypto mining strategy, the research employs an Analytic Hierarchy Process (AHP) and Fuzzy-TOPSIS hybrid analytics framework. Furthermore, it identifies the top-quality mining methods by evaluating providers overall performance during cryptocurrency mining. 2023 Scrivener Publishing LLC. -
Applications of Machine Learning and Deep Learning Models in Brain Imaging Analysis
Brain imaging is an umbrella term including many non-invasive techniques that objectively monitor brain function. Such monitoring leads to understanding how the brain works by presenting selected stimuli. More importantly, brain function monitoring allows physicians to diagnose and predict brain disorders. In the last decade, several machine learning and deep learning models have been developed by researchers to process and analyse brain imaging data for the diagnosis, detection, and prediction of brain disorders, such as stroke, schizophrenia, autism, psychosis, and Alzheimers. This chapter reviews the various applications and properties of machine learning and deep learning models for brain image analysis. The chapter also highlights the deep learning models that have either understood the test of time or shown the promise to solve challenging problems involving brain imaging data. The review also discusses various open issues yet to have practical solutions or methodologies with the help of machine learning and deep learning. The research covers a wide range of imaging modalities, disorders and models to expose researchers and practitioners in neurological disorders and machine learning and deep learning to each others field, hopefully leading to fruitful collaborations and practical solutions for processing brain images. 2024 selection and editorial matter, Anitha S. Pillai and Bindu Menon; individual chapters, the contributors. -
Applications of neuroscience in education practices: A research review in cognitive neuroscience
The human brain is the most complex and mysterious organ in the body responsible for learning. Applications of neuroscience and genetics need to be comprehended to modulate teaching and learning practices in education. Considering the scope for application of advanced sciences in education practices, this book chapter simplifies and reviews ten critical research findings relevant for students and teachers for classroom applications and for modulating learning patterns for different age groups. The concept is also relevant for parents and the academic fraternity at large. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
Approaches on redesigning entrepreneurship education
All over the world there is an emergence of a self-reliant life. This instilled a spark in entrepreneurship, especially during the wake of a pandemic world. The paradigm shift from dependency to self-reliance demands a set of skills and techniques as prerequisites to thrive in this competitive world. This chapter introduces a couple of innovative pedagogy strategies that can be inculcated in educational institutions, which will give rise to efficient entrepreneurs who can face adversaries and make an efficient contribution to society. The chapter aims to integrate realistic learning activities for fostering capability development in entrepreneurship education. Capability enhancement in entrepreneurship education includes activities that improve the knowledge, skills, and talents of potential entrepreneurs. The chapter aims to develop a model that further illustrates how the educational entrepreneurial experience could be explored. 2023, IGI Global. -
Are Indian higher education institutions doing their bit towards empowerment of mid-career women?: A study of public and private universities in India
Gender diversity and empowerment of mid-career women in the workplace have rightfully gained importance over the last decade. However, there is a paucity of research pertaining to the position of mid-career women in higher education institutions (HEI) in India. The data suggest that while there has been an increase in the number of women in the academic sphere, yet there is a visible lack of women in the top academic leadership positions across Indian HEIs. This chapter explores the HR practices adopted by top public and private universities to support women's career progression. Using a mixed-method approach, the chapter identifies barriers to women 's growth in academia. And finally, the authors make suggestions for promoting female academicians by comparing existing practices to those practised in gender-equal countries across the globe. 2022, IGI Global. All rights reserved. -
Are you the one to stick around despite the high rate of attrition? Typical personality traits using Myers-Briggs framewor
Most employees say they have unfavourable sentiments about their organization, yet they often seem hesitant to follow through with their decision to leave. This presents a painful dichotomy for organizations that look for long term manpower solutions. This study examined the relationships between the Myers-Briggs' four personality dimensions (extraversion/introversion, sensing/intuition, thinking/feeling, and judging/perceiving) and the behaviour of employees to stick around with the organization for years even amidst a high attrition rate. After compiling all these observations, the authors propose the following five strategies for employers to take into consideration: Leveraging the power of belongingness, form addictive positive work environment, capitalise on the spillover effect, communicate with either the heart or the head, andprioritise having experiences above an employee status. This research will offer an introspection to both employees and the employers. 2023, IGI Global. All rights reserved. -
ARise to the occasion: Elevating customer engagement
Augmented reality (AR) is being used to transform the landscape of online retail by enhancing customer engagement and experience. This chapter delves into how AR's unique capabilities, such as virtual try-on and interactive product visualisation, can overcome the limitations of traditional online shopping and create deeper connections between brands and consumers. It explains how AR personalises the customer journey by providing customised product recommendations and immersive virtual experiences that drive purchase decisions. By analysing past implementations and future trends, this chapter demonstrates how ARM can usher in a new era of customer engagement and personalised experiences in online retail. 2024, IGI Global. All rights reserved. -
Artemisinin: A potent antimalarial drug
Artemisinin is known to be a potent antimalarial drug which is naturally obtained from the plant Artemisia annua L. Malaria is a global health problem with nearly 1.2 billion people at high risk. In 2001, WHO recognised artemisinin based combination therapies (ACTs), as the frontline drugs to fight against malaria and therefore, artemisinin is the most effective anti-malarial drug. It appears to be a safe drug with no adverse reactions or noticeable side effects, even for pregnant women. However, access to ACTs by malarial patients, especially in poor countries, is inadequate due to high volatility in price, unpredictable demand and low yield from A. annua. The huge gap in demand and supply has motivated researchers to explore artemisinin production in alternative systems like bacteria, yeast and tobacco. Scientists have been successful in producing this wonder molecule in heterologous hosts. Challenges associated with large-scale production and drug resistance against artemisinin has also been discussed to present a comprehensive picture of artemisnin production, application and limitations. 2019 Scrivener Publishing LLC. All rights reserved.