Stock market prediction using DQN with DQNReg loss function
There have been many developments in predicting stock market prices using reinforcement learning. Recently, Google released a paper that designed a new loss function, specifically for meta-learning reinforcement learning. In this paper, implementation is done using this loss function to the reinforcement learning model, whose objective is to predict the stock price based on certain parameters. The reinforcement learning used is an encoderdecoder framework that is useful for extracting features from long sequence prices. The DQNReg loss function is implemented in the encoder-decoder model as it could provide strong adaptation performance in a variety of settings. The model can buy and sell the index, and the reward is the portfolio return after the days trading has concluded. To maximize yield the model must optimize reward function. The DQNReg loss implemented DQN network and the Huber loss DQN network is compared with the Sharpe ratio considered for return. 2024 selection and editorial matter, Arvind Dagur, Karan Singh, Pawan Singh Mehra & Dhirendra Kumar Shukla; individual chapters, the contributors.
Artificial Intelligence, Blockchain, Computing and Security: Volume 1, Vol-1, pp. 58-63.
Sebastian A., Department of Computer Science Christ University, Bangalore, India; Habis K.V., Department of Computer Science Christ University, Bangalore, India; Shukla S., Department of Computer Science Christ University, Bangalore, India
Security and privacy aspects in intelligence systems through blockchain and explainable AI
AI security; Blockchain; Explainable AI; Healthcare analytics; Intelligence systems
Explainable AI (XAI) is a method of creating artificial intelligence (AI) systems that are transparent and understandable to humans. By allowing people to understand how the system arrived at its conclusions or suggestions, XAI systems strive to make AI more accountable, trustworthy, and ethical. Responsibility, trust, ethics, regulation, and innovation are some of the societal ramifications of XAI. By making AI systems more transparent, XAI fosters accountability. This means that consumers will be able to understand how the system made its decisions and hold it accountable if something goes wrong. By making the decision-making process more transparent, XAI fosters trust between people and AI systems. This boosts user trust in the system and encourages wider adoption of AI technologies. It also contributes to the ethical design of AI systems by making the decision-making process public in order to uncover and mitigate biases and other ethical issues that may occur in AI systems. It aids regulators and policymakers in understanding and regulating AI systems. XAI gives insight into how AI systems operate, which can assist regulators in developing laws that promote ethical and responsible AI use. Because XAI can help developers better and innovate new systems by making it easier for them to design new AI systems and by providing insights into how AI systems work. The proposed chapter will focus on important aspects of algorithmic bias and changing notions of privacy in XAI, which will necessitate the need for AI systems that can adapt accountability, trust, ethics, and compliance with regulations, as well as produce better innovation that can benefit humanity. More openness, greater control over personal data, new types of data privacy, and newer privacy networks are all required. To address algorithmic bias in XAI, it is critical to build the system so that it is aware of the possibility of bias and actively mitigates it. This can involve employing diverse and representative data, inspecting the system for unwanted features, offering detailed explanations, and incorporating a wide range of stakeholders in the system's development and deployment. The envisaged report provides a framework that combines XAI and blockchain to provide a secure and transparent way to store and track the provenance of data used by XAI systems, validate the performance of AI models stored on the blockchain on decentralized systems so that the models are stored and executed on a distributed network of nodes rather than a centralized server, and create a token-based economy that encourages data sharing and AI development. Tokens can be used to compensate individuals and organizations who contribute data or algorithms to the blockchain or who employ AI models stored on the blockchain. Overall, the combination of XAI and blockchain can lead to more trustworthy, transparent, and decentralized AI systems. This approach can have a significant impact on various industries such as finance, healthcare, and supply chain management by increasing efficiency, reducing costs, and improving data privacy and security. 2024 Elsevier Inc. All rights reserved.
Thiruthuvanathan M.M.; Pradeep Kumar K.; Nasar N.; K.K S.; Joseph P.M.
XAI Based Intelligent Systems for Society 5.0, pp. 365-400.
Thiruthuvanathan M.M., Department of Computer Science Engineering, School of Engineering and Technology, CHRIST University, Kengeri Campus, Karnataka, Bangalore, India; Pradeep Kumar K., Department of Computer Science Engineering, School of Engineering and Technology, CHRIST University, Kengeri Campus, Karnataka, Bangalore, India; Nasar N., Department of Computer Science Engineering, School of Engineering and Technology, CHRIST University, Kengeri Campus, Karnataka, Bangalore, India; K.K S., Department of Computer Science Engineering, School of Engineering and Technology, CHRIST University, Kengeri Campus, Karnataka, Bangalore, India; Joseph P.M., Department of Computer Science, Modern College of Business and Science, Muscat, Oman
Gaze and Queer Autonomy? Representations and Possibilities on New Visual Media Landscapes in the Indian Context
Representations of sexuality in Indian mainstream cinema tend to reinforce sexual differences, imbalances, and certain stereotypes that put queer identities in a disadvantageous position. The shift and transition from the monopoly of the state to an era of popular forms of entertainment enabled the centrality of debates on representations and sexuality. The study examines the representations of queerness that flourished on new visual media landscapes such as the OTT platforms Netflix and Amazon Prime Video that engaged in a new dialogue on queer representations and possibilities. The study attempts to analyze Super Deluxe (2019), Made in Heaven (2019) and Ajeeb Daastans (2021), as they become the representative form of cinema that marked the shift and engaged in a new dialogue on queer representations and possibilities. The study reads queer representation in light of the frameworks of gaze and homophyly to understand why they might offer different opportunities for representation and gaze. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
The Digital Popular in India: Mainstreaming the Marginal, pp. 127-141.
Tanupriya, Department of English and Cultural Studies, School of Arts and Humanities, CHRIST (Deemed to Be University), Delhi NCR, Ghaziabad, India; Singh A., Department of English and Cultural Studies, School of Arts and Humanities, CHRIST (Deemed to Be University), Delhi NCR, Ghaziabad, India
Current status and future trends on the use of innovative technologies for recovering bioactive from insects
Bioactive compounds; Cold atmospheric pressure plasma; Emerging technology; Functional food; High hydrostatic pressure; Insect processing
Edible insects hold great potential as human food owing to their nutritional, economic and environmental value. Though, the negative perceptions of insects limit their intake by majority of the insects, their efficient processing and utilization in food products have steadily increased their demand in recent years. This chapter deals with the emerging and advanced extraction techniques for recovering functional and bioactive compounds from insects, considering the various factors which might influence the optimum yields. Apart from their production yields, it is of utmost significance to preserve their nutritional and sensory qualities for their effective utilization in functional food products. In this regard, various emerging technologies such as enzymatic hydrolysis, cold atmospheric pressure plasma, ultrasound-assisted extraction, high hydrostatic pressure have been explored. Mechanisms of action along with their benefits and drawbacks have been thoroughly described in the later part of the chapter which will provide insight to the readers for the selection of optimum technology for insect processing. Overall, this chapter provides the readers a comprehensive view about alternatives to conventional techniques for postprocessing of insects and optimization for case-specific technology. 2024 Elsevier Inc. All rights reserved.
Surya Ulhas R.; Sharma H.; Malaviya A.; Rajauria G.
Insects as Food and Food Ingredients: Technological Improvements, Sustainability, and Safety Aspects, pp. 145-159.
Surya Ulhas R., Faculty of Biological Sciences, University of Jena (Friedrich-Schiller-Universit), Jena, Germany; Sharma H., Dairy Technology Division, ICAR-National Dairy Research Institute, Haryana, Karnal, India; Malaviya A., Department of Life Sciences, School of Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India, QuaLife Biotech Private Limited, Karnataka, Bengaluru, India; Rajauria G., School of Microbiology, School of Food and Nutritional Sciences, University College Cork, Cork, Ireland, SUSFERM Centre for Sustainable Fermentation and Bioprocessing Systems for Food and the Bioeconomy, University College Cork, Cork, Ireland
Machine learning and deep learning techniques for breast cancer detection using ultrasound imaging
Artificial intelligence; Breast cancer classification; Computer-aided diagnosis (CAD); Deep learning; Magnetic resonance imaging (MRI); Mammogram; Radiology; Ultrasound
One of the greatest causes leading to death in women is breast cancer. Its prompt and precise identification can reduce the mortality risk associated with the disease. With the help of computer-based detection, radiologists can identify irregularities. To identify and diagnose numerous illnesses and anomalies, medical photographs are sources of important information. Various techniques help radiographers to examine the internal system, and these techniques have generated a significant amount of attention across several fields of research. Each of these approaches holds a great deal of relevance in many healthcare sectors. Using artificial intelligence techniques, this article aims to present a study that highlights current developments in the detection and classification of breast cancer. The categorization of breast cancer using many medical imaging modalities is discussed in this article. It initially offers a summary of the various machine learning methodologies, followed by a summary of the various deep learning algorithms used in the detection and characterization of metastatic breast tumors. To give an insight into the field, we also give a quick summary of the various imaging techniques. The chapter concludes by summarizing the upcoming developments and difficulties in the diagnosis and classification of breast cancer. 2024 Elsevier Inc. All rights reserved.
Ajmani P.; Sharma V.; Rai R.H.; Kalra S.
Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images, pp. 235-257.
Ajmani P., Vivekananda Institute of Professional Studies-TC, GGSIPU, New Delhi, India; Sharma V., Computer Science Department, CHRIST (Deemed to be University), Delhi-NCR, India; Rai R.H., School of Physiotherapy, Delhi Pharmaceutical Sciences and Research University (DPSRU), New Delhi, India; Kalra S., School of Physiotherapy, Delhi Pharmaceutical Sciences and Research University (DPSRU), New Delhi, India
Applications of Digital Technologies and Artificial Intelligence in Cryptocurrency - A Multi-Dimensional Perspective
blockchain; Cryptocurrency; deep learning; FinTech technologies; hybrid analytics approach; machine learning; security attacks; sensitivity analysis
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.
Fintech and Cryptocurrency, pp. 221-249.
Jaisingh W., School of Information Science, Presidency University, Karnataka, Bangalore, India; Preethi N., Department of Data Science, Christ University, Karnataka, Bangalore, India; Kavitha R.K., Department of Computer Applications, Kumaraguru College of Technology, Tamil Nadu, Coimbatore, India
Paradigm shift from AI to XAI of Society 5.0: Machine-centric to human-centric
Artificial intelligence; eXplainable AI; Human-centric; Machine-centric
Artificial intelligence (AI), the Internet of things (IoT), and robotics have gained significant momentum to meet expectations in many applications. Data management has become a tedious job as businesses grow. The interruption of AI in business functions and a growing web-based service economy in the last decade have led the IoT to grow faster, reducing the tedious job. Timely interruption of eXplainable artificial intelligence (XAI) reduces the technical complexities. On the one hand, the AI of Industry 4.0 promises the easiness of business functions. On the other hand, XAI of Society 5.0 tends to ease people's social life. This chapter ascertains the impact of AI on significant business functions and tries to bring out challenges AI faces and ethical values that must be considered in business functions. This chapter also tries to shed some light on the evolution of XAI of Society 5.0 and reasons for the shift from AI to XAI or machine-centric to human-centric and concludes by highlighting the future of XAI. 2024 Elsevier Inc. All rights reserved.
XAI Based Intelligent Systems for Society 5.0, pp. 3-28.
Paul Frank M., Department of Commerce, Christ (Deemed to Be University), Karnataka, Bengaluru, India; George G., Department of Commerce, Christ (Deemed to Be University), Karnataka, Bengaluru, India
Doctoral Research by Youth: Analyzing the Role of Socio-Demographic Variables on Flourishing and Grit
Academic achievement; Demographic variables; Doctoral attrition; Doctoral education; Flourishing; Grit
The study examines the importance of socio-demographic variables like age, gender, family environment, and relationship with parents and friends in deter-mining non-cognitive traits such as flourishing and grit, during the tenure of doctoral research. The cross-sectional correlational study comprises 400 Ph.D. scholars from a Central University in India, who were given a personal data sheet, the Flourishing Scale and the Grit Scale, for assessment. The results of the F-test showed that flourishing was significantly related to age, family environment and relationship with friends, and grit was significantly related to family environment and relationship with friends. Analysis using Pearson correlation found a weak correlation between flourishing and the three subscales of grit, namely ambition, consistency of interest, and perseverance of effort. Findings suggest that the socio-demographic variables are important contributors in the long-term goal-oriented behaviors and that flourishing and grit are two related but not correlated variables that influence completion and attrition of the doctoral research. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
Deb S.; Sunny A.M.; Thomas S.; Deb S.; Ashra F.G.; Sujith V.S.; Paul D.
Handbook of Youth Development: Policies and Perspectives from India and Beyond, pp. 531-544.
Deb S., Department of Applied Psychology, Pondicherry University (A Central University), Puducherry, India; Sunny A.M., PGCE Teacher Trainee, UCL Institute of Education, London, United Kingdom; Thomas S., Teacher of Psychology, St. Georges College, Weybrigde, United Kingdom; Deb S., Department of Psychology, CHRIST (Deemed to be University), Bengaluru, India; Ashra F.G., Department of Applied Psychology, Pondicherry University (A Central University), Puducherry, India; Sujith V.S., Department of Applied Psychology, Pondicherry University (A Central University), Puducherry, India; Paul D., Department of Applied Psychology, Pondicherry University (A Central University), Puducherry, India
Challenges and Solutions of Using Social Internet of Things (SIoT) in Healthcare and Medical Domains
The revolutionary idea that combines social networks with the Internet of Things (IoT) is called the Social Internet of Things (SIoT). SIoT is a term that refers to the modelling of social networks formed by connecting people and things. SIoT was designed to assist organizations in achieving specific goals, such as boosting usability, scalability, and productivity and satisfying business service requirements. The application layer of the SIoT model performs several tasks like managing the relationship, discovering the services, configuring services, and managing reliability among the devices. The information collected about SIoT is categorized by identifying the relationships between devices. SIoT creates an event identity based on data from IoT applications. This identity may then be transferred with the SIoT network and made available to other IoT apps. Thus, the SIoT network offers guidance services for reusing data from IoT applications across many IoT applications and customizing IoT solutions to meet the unique needs of individual users, hence boosting overall communication. SIoT technology entails the more efficient use of recent data to create favorable patient outcomes in healthcare and medicine. The enormous volume of data generated by SIoT-connected devices has allowed various developments and applications in the healthcare domain. SIoT leverages sensors and other connected devices in these domains to boost social solutions efficiency. Without question, sensors used for creating this kind of network model that can collect vast amounts of data are on the verge of becoming a pervasive part of our lives. If the processing and management are not carried out optimally in SIoT, there is a significant risk that the data will lose its efficacy. This chapter examines SIoT challenges and approaches in the healthcare and medical domain. SIoT approaches may assist users in detecting a patients aberrant behaviour. These approaches are capable of detecting and forecasting patients health states. The SIoTs relational models, such as community sharing, equality matching, and equality matching, also provide IoT services to users. The sensing layers functionalities are compared to those of the network layer and application when assessing SIoT services. The proposed hierarchical network model uses gateways, switches, and IoT devices to establish social relationships. CISCO packet tracer is used to construct and operate this mainly built social network for healthcare. This specially designed social network for the healthcare domain can easily be implemented and controlled by any hospital management. 2023 selection and editorial matter, Gururaj H L, Pramod H B, and Gowtham M; individual chapters, the contributors.
Advances in SIoT (Social Internet of Things), pp. 91-109.
Arulkumar N., Department of Computer Science, Christ Deemed to be University, Bangalore, India
Youth and Media Literacy in the Age of Social Media
Media literacy; News literacy; Youth development; Youth education
Living in the age of information means information is all pervasive, uncensored, unreliable, and with the potential to influence. The unfettered access to information and communication through social media is a double-edged sword in the hands of youth. The impact of this was explored from sociocultural and mental health perspectives. Specifically, the role of media literacy in combating the challenges posed by usage of social media was explored in this chapter. Various theories, frameworks, models, and components of media literacy were analysed. Impact of the various media literacy interventions on the youth, case studies of specific information literacy programs across regions, and other relevant critiques were reviewed and consolidated. Further to this, recommendations have been presented on creating robust in-school, and outside-school media literacy programs for the youth. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
Handbook of Youth Development: Policies and Perspectives from India and Beyond, pp. 255-268.
Pant S., Via News Didi, Jalandhar, India; Nataraj B.M., Department of Psychology, CHRIST (Deemed to be University), Bengaluru, India; Reddy K.J., Department of Psychology, CHRIST (Deemed to be University), Bengaluru, India
Garbage Management and Monitoring System Using IOT Applications
Internet Protocol; Sensible Garbage Bin; Ultrasonic Sensors
The main purpose of this application, in addition to boosting the vision of a smart city, is to reduce humankinds effort and resources while simultaneously enhancing the vision. The squashing of the dustbin will occur on a regular schedule. It will be possible to manage waste more efficiently when these sensible garbage bins are implemented on a large scale and replace our previously designed dumpster, as it eliminates the need for waste to be piled up on the roadside in the first place. When managing the trash containers, wireless sensor systems in networks (WSN) in connection with the IoT technologies are used. On the other hand, sensors are used to monitor the container contents in real-time, with results displayed on the website, and the sensed contents are then evaluated to determine the optimal container distribution. This allows for the processing of a variety of waste types depending on the needs of the customer. As a result of installing ultrasonic sensors in each bin, garbage levels are continuously checked. As a result of this notification, the bin will be cleared. 2023, Bentham Books imprint.
Kumaraswamy A.; Kolli C.S.; Aurelia S.; Vasantha Kumar P.; Lakshminarayana M.
Pragmatic Internet of Everything (IOE) for Smart Cities: 360-Degree Perspective, pp. 125-140.
Kumaraswamy A., Sri Venkateswara College of Engineering, Tamilnadu, Sriperumbudur, India; Kolli C.S., Department of Computer Science, Gandhi Institute of Technology and Management, Andhra Pradesh, Visakhapatnam, India; Aurelia S., Department of Computer Science, CHRIST University, Karnataka, Bengaluru, India; Vasantha Kumar P., School of Excellence in Law, The Tamil Nadu Dr. Ambedkar Law University, Chennai, India; Lakshminarayana M., Department of Medical Electronics Engineering, M S Ramaiah Institute Of Technology, Karnataka, Bengaluru, India
Role of AI in the inventory management of agri-fresh produce at HOPCOMS
Inventory management is vital for maintaining the efficiency of supply chain management. Fruits and vegetables being perishable in nature should involve inventory management to avoid wastage and loss in terms of over stocking and stock out situations. The present study focuses on the role of artificial intelligence (AI)-powered inventory management of fruits and vegetables at HOPCOMS, a cooperative society founded in Bangalore. In the road to satisfy the customers, it is necessary for the society to come up with different strategies to manage the inventories in which a retailer confronts overstock and stock out situation, affecting the profit of the society. Therefore, a study was conducted with the help of structured questionnaire among 122 retailers of HOPCOMS outlets in Bangalore. The results obtained from the study suggest that inventory valuation method positively influences AI-powered demand forecasting and customer order fulfillment, and AI-powered demand forecasting is positively related to customer order fulfillment. 2023, IGI Global. All rights reserved.
Advanced Machine Learning Algorithms for Complex Financial Applications, pp. 115-131.
Raghavendra A.N., CHRIST University (Deemed), India; Amalanathan S., CHRIST University (Deemed), India
Algorithmic Strategies for Solving Complex Problems in Financial Cryptography
Complex functions; Financial cryptography; Polynomial functions; Private key; Public key; Recursive functions
Cryptography is used in applications where subversion of the communication system could lead to financial loss, which is known as financial cryptography. In contrast to classical encryption, which has mostly been utilized for military and diplomatic purposes throughout recorded history, financial cryptography focuses on privacy and security. The techniques and algorithms required for the security of financial transfers as well as the development of new money types are included in financial cryptography. Financial cryptography includes proof of work and several auction mechanisms. Spam is being restricted by using hashcash. The applications of financial cryptography have been observed to be highly diverse. Financial cryptography is incredibly difficult and calls for knowledge from many different, incompatible, or at the very least, hostile disciplines. The higher risk factor that efforts to build financial cryptography systems will reduce or eliminate crucial strategies that they are trapped among financial application and cryptography, or between accountants and programmers. Digital finance is playing a big role in how financial services are organized globally. Digitalization, data analysis, and increased processing power enable a wide range of new financial services and transactions. The importance of economic development has attracted a lot of attention to this economic development enabled by digital financial technology (Fintech). Cryptography has begun to expand swiftly in the Fintech sector, and both investors and financial bankers are becoming more favorable toward digital assets. The observed market factors are directly related to how people behave when they engage in financial activity. The result analysis in this behavioral strategies of financial cryptography from a specific market analysis is still limited, despite the abundance of research and theories on the underlying motives of peoples behavior in financial frameworks. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
Rajasekar V.; Venu K.; Sharma V.; Saracevic M.
Homomorphic Encryption for Financial Cryptography: Recent Inventions and Challenges, pp. 207-219.
Rajasekar V., Department of CSE, Kongu Engineering College, Perundurai, India; Venu K., Department of CSE, Kongu Engineering College, Perundurai, India; Sharma V., CHRIST (Deemed to be University), Delhi-NCR, India; Saracevic M., Department of Computer Sciences, University of Novi Pazar, Novi Pazar, Serbia
Machine learning approaches towards medical images
Clinical imaging relies heavily on the current medical services' framework to perform painless demonstrative therapy. It entails creating usable and instructive models of the human body's internal organs and structural systems for use in clinical evaluation. Its various varieties include signal-based techniques such as conventional X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US) imaging, and mammography. Despite these clinical imaging techniques, clinical images are increasingly employed to identify various problems, particularly those that are upsetting the skin. Imaging and processing are the two distinct patterns of clinical imaging. To diagnose diseases, automatic segmentation using deep learning techniques in the field of clinical imaging is becoming vital for identifying evidence and measuring examples in clinical images. The fundamentals of deep learning techniques are discussed in this chapter along with an overview of successful implementations. 2023, IGI Global. All rights reserved.
Gayathri S.P.; Ramasamy S.S.; Vijayalakshmi S.
Structural and Functional Aspects of Biocomputing Systems for Data Processing, pp. 124-145.
Gayathri S.P., The Gandhigram Rural Institute (Deemed), India; Ramasamy S.S., International College of Digital Innovation (ICDI), Chiang Mai University, Thailand; Vijayalakshmi S., Department of Data Science, Christ University (Deemed), India
Synthesis, Characterization of Chromium Oxide Powders and Coatings
APS; Chromium oxide; EDS; Plasma sprayable powder; SEM; Spray dryer; XRD
The chromium oxide powders are transformed into plasma sprayable particles by using synthetic polymers for agglomeration. In order to carry out the agglomeration process, spray drying technique was employed. This research work highlights the significance of the process variables that control the synthesis of plasma spray powder and consequently, the properties that were suited for plasma sprayoating. Energy Dispersive Spectroscopy (EDS) was used to characterize the elemental composition, while scanning electron microscopy (SEM) was used to analyse the morphology and powder grain sizes and X-ray diffraction (XRD) was used to identify the phase structure. And for the development of coatings on the substrates, Atmospheric plasma spray (APS) technique was used. The plasma sprayable powders were created with the intention of investigating for use as corrosion-resistant coatings. 2023 Trans Tech Publications Ltd, All Rights Reserved.
Jaiswal V.; Ekka H.; Choudhary S.; Souza C.D.; Joy B.; Sanjai S.G.
Solid State Phenomena, Vol-350, pp. 41-49.
https://doi.org/10.4028/p-QVU6Kk https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204693890&doi=10.4028%2fp-QVU6Kk&partnerID=40&md5=2967ece070b80ab46a5bdb18dfd8ad56
Jaiswal V., CHRIST (Deemed to be University), Department of Mechanical & Automobile Engineering, Bangalore, India; Ekka H., CHRIST (Deemed to be University), Department of Mechanical & Automobile Engineering, Bangalore, India; Choudhary S., CHRIST (Deemed to be University), Department of Mechanical & Automobile Engineering, Bangalore, India; Souza C.D., CHRIST (Deemed to be University), Department of Mechanical & Automobile Engineering, Bangalore, India; Joy B., CHRIST (Deemed to be University), Department of Mechanical & Automobile Engineering, Bangalore, India; Sanjai S.G., CHRIST (Deemed to be University), Department of Mechanical & Automobile Engineering, Bangalore, India
Intelligent Optimized Delay Algorithm for Improved Quality of Service in Healthcare Social Internet of Things
Internet of Things (IoT) interconnects billions of devices by establishing a network that adheres to International Organization of Standardization (ISO) standards. These devices communicate with each other by sharing data regulated by the application. This is performed to accomplish a task or service that the application demands. The social or human-like behaviors are adapted in the IoT environment forming the Social IoT (SIoT). The SIoT integrates social networks in IoT-connected devices, making them unique and identifiable. Recent advancements in networking, intelligent network management, battery management, remote sensing, sensors, and other related technologies convinced users and designers to adopt IoT even for large-scale applications where the data involved is enormous. Leveraging the advancements in medical IoT, which focuses on healthcare to patients, can improve its service by removing redundant manual processes, long wait times, and providing other automated services. The advancements in real-time healthcare IoT devices and wearables make a strong case for implementing SIoT in the healthcare domain. SIoT in the healthcare domain has the potential to benefit users on a large scale. This chapter comprehends the challenges and solutions of using SIoT in medical and healthcare solutions from a networking quality of service (QoS) perspective. In addition, this chapter compares the intelligent algorithm, which can be used to improve the QoS of SIoT. Achieving higher QoS is necessary for healthcare services, especially while handling data from emergency and intensive care units. These data cannot tolerate errors and delays. Intelligent network management has become unavoidable in the health and medical services to achieve a higher degree of QoS system, which indirectly decreases data transfer time. The data from the sensor devices sent across the network leads to data loss and delay in data transmission due to congestion in the network and gateway devices. The optimized algorithms incorporated with the delay-based algorithm improves the QoS predominantly and reduces the delay in data transfer. Similarly, the particle swarm optimization algorithm allocates resources over the network and dynamically makes the network adapt to increased and reduced data flow, which reduces the delay and improves the QoS. Intelligent optimized delay algorithm (IODA) is proposed to improve the network performance by reducing the delay and using available bandwidth for data transfer in SIoT. 2023 selection and editorial matter, Gururaj H L, Pramod H B, and Gowtham M; individual chapters, the contributors.
Advances in SIoT (Social Internet of Things), pp. 39-53.
Anija Starry B., Department of Computer Science, Christ University, Bangalore, India; Nismon Rio R., Department of Computer Science, Christ University, Bangalore, India
Does the cryptocurrency index provide diversification opportunities with MSCI world index and MSCI emerging markets index? Cryptocurrency and portfolio diversificaiton
The study is extending the ongoing discussion on Bitcoin as a diversification asset with the stock market. Some studies analysed cryptocurrencies as a diversification asset, and few challenged the same. During times of turbulence, it is crucial to gauge further diversification opportunities. Henceforth, the study revisits the opportunities of hedging and diversification with the crypto market from a broader perspective. Markets Index to Bitwise 10 Crypto Index Fund (BITW). The study has contributed methodologically to the existing literature by applying DY with symmetric and asymmetric dynamic conditional volatility models. The results provide in-depth shreds of evidence that BITW is insulated, neither taking volatilities from other countries nor contributing to the volatilities of other countries. The study provides insight to policymakers and investors.The study captures the spillover from MSCI World Index and MSCI Emerging Markets Index to Bitwise 10 Crypto Index Fund (BITW). The study has contributed methodologically to the existing literature by applying DY with symmetric and asymmetric dynamic conditional volatility models. The results provide in-depth shreds of evidence that BITW is insulated, neither taking volatilities from other countries nor contributing to the volatilities of other countries. The study provides insight to policymakers and investors. 2023, IGI Global. All rights reserved.
Advanced Machine Learning Algorithms for Complex Financial Applications, pp. 94-114.
Yadav M.P., Amity University, India; Sharma S., FIIB Delhi, India; Parmar B., CHRIST University (Deemed), India
Suicide and Youth: Positive Psychology Perspective
Adolescents; Crisis management; Intervention; Positive psychology; Preventive; Suicide; Suicide prevention; Young adults
Suicidality and self-harm among adolescents and young adults need immediate attention and support. This is often seen as a cry for help where a feeling of entrapment experienced by individuals pushes them to see self-harm as a coping mechanism. Lack of social support and co-morbid emotional disorders influences suicidal ideation into planning and action. A general feeling of helplessness that gets triggered often leads to anguish. These emotions get internalized and directed inwards leading to self-directed anger which facilitates a suicidal act. Early detection and identification can prevent the loss of lives and help individuals to learn effective ways of coping. Gatekeeper Training for caregivers, teachers, and their peers will help in detecting the early signs of suicide risk. Intervention based on positive psychology will help not only in crisis management but also as preventive and maintenance therapy in holistic mental health. The concepts of hope, forgiveness, self-compassion, gratitude, and resilience can be incorporated into the intervention programs to build a better therapeutic system for youths dealing with suicidality. Practicing effective coping mechanisms every day and making it a ritual of ones daily life is the need of the hour. Integrating adaptive ways of emotional expression and learning matured means to deal with painful emotions and trauma is what needs to be incorporated into the intervention plan. The chapter focuses on these aspects and aims to make a connection between assessing and easy identification of youths in distress related to suicidality and providing a holistic intervention to help them cope with the situation. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
Handbook of Youth Development: Policies and Perspectives from India and Beyond, pp. 327-342.
Banerjee T., Department of Psychology, CHRIST (Deemed to Be University), Bengaluru, India; Reddy K.J., Department of Psychology, CHRIST (Deemed to Be University), Bengaluru, India
A Narrative Review on Experience and Expression of Anger Among Infertile Women
Anger suppression; Infertility; Psychosocial intervention
Infertility is stressful among women though there are several technological advancements in treating infertility. Anger is a powerful emotion resulting due to stigma and oppression due to infertility, especially among women. Studies have also proven that women have a poor quality of life in the context of infertility. Women are prone to suppressing anger rather than dealing with anger in the present. Psychosocial intervention and psychoeducation help women manage anger and maintain healthy quality of life. Springer Nature Switzerland AG 2023.
Handbook of Anger, Aggression, and Violence, pp. 1005-1024.
Subramani D., Department of Psychology, CHRIST (Deemed to be University), Yeshwanthpur Campus, Bengaluru, India; Rathnasabapathy M., Department of Psychology, School of Social Sciences and Languages, VIT University Chennai Campus, Vellore Institute of Technology, Chennai, India
Transformative Learning, Community and Leadership for Sustainability Action
Randles S.; Wadham H.; Skritsovali K.; Hart C.; Hoque S.; Kettleborough H.; Klapper R.; Marron R.; Taylor D.; Walley L.
The Bloomsbury Handbook of Sustainability in Higher Education: An Agenda for Transformational Change, pp. 87-108.
Randles S., Manchester Metropolitan Universitys Faculty of Business and Law, United Kingdom; Wadham H., Manchester Metropolitan University Business School, United Kingdom; Skritsovali K., Liverpool John Moores University Business School, United Kingdom; Hart C., Department of Strategy, Enterprise and Sustainability, Manchester Metropolitan University, United Kingdom; Hoque S., Manchester Metropolitan University, United Kingdom; Kettleborough H., Manchester Metropolitan University Business School, United Kingdom; Klapper R., Manchester Metropolitan University, United Kingdom; Marron R., Manchester Metropolitan University Business School, United Kingdom; Taylor D., Manchester Metropolitan University Business School, Institute of Enterprise and Entrepreneurs, United Kingdom, Christ University, India; Walley L., Manchester Metropolitan University Business School, United Kingdom