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Distributed Maximum Power Point Tracking for Mismatched Modules of Photovoltaic Array
The multiple peaks in the output P-V characteristics of the photovoltaic (PV) module and the complete loss of shaded modules generation due to the existing bypass diode-based scheme are eliminated through the implementation of proven distributed maximum power point tracking (DMPPT). Considering the unique behavior of each PV Module, the artificial neural network is used in the DMPPT algorithm to track the MPP at every instant by learning the unique behavior of each PV module in this chapter. This eliminates the effect of manufacturing dispersion. Though the unique MPP is identified, the inability of the DMPPT algorithm in maintaining the PV modules in its own MPP is eliminated by the compensator circuits which are introduced in the array configuration along with the DMPPT in this chapter. These compensators enabled the maintenance of each PV module in its own MPP by providing the deficient current of each module and the deficient voltage of each string. So, this configuration increases the output power by including the generation of shaded modules instead of bypassing it. The results show that the proposed configuration avoids the multiple peak condition in P-V characteristics and improves the efficiency of the PV array under partially shaded conditions. 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Intelligent Wearable Electronics: A New Paradigm in Smart Electronics
In the last decade or so, the wearable electronics technology has seen an unprecedented growth which is expected to reach around USD 51.60 billion by the year 2022 with a CAGR of 15.51%. Intelligent wearable electronics is a combination of wide range of technologies like computation, communication, sensors, cloud computing, and display to cite a few. Integration of various technologies resultin systems which are multifunctional along with higher complexity of design presenting a unique challenge for the technologists. With Internet of Things (IoTs) becoming ubiquitous and 5G technologies around the corner, the wearable devices are no longer simple passive systems providing the user limited information, but rather they are multifunctional, powerful, and intelligent devices which make use of complex sensing and signal processing elements along with cloud computing and data analytics to provide real-time data interpretation. In this chapter, we review the recent developments of intelligent wearable electronics (WE) with emphasis on their working principle and design at various levels of abstraction, that includes material, device, and system levels, along with signal processing and communication protocol for external communication. Further, the design and development of smart wearable electronics which involves multivariant problem-solving at various abstraction levels is explained. In addition, we elucidate popular classes of smart wearables like wearable textiles, healthcare wearable electronics, and WE in education. Furthermore, we explore the primary performance constraints of typical WE systems such as battery life (energy), system architecture, communication protocols, and integration with cloud computing to, mention a few. This chapter concludes by elucidating various challenges in developing WE and the future directions of this industry. 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Pattern of Carbon Dioxide Emission, Economic Growth and Energy Consumption in South-Asian Countries: An Empirical Analysis
The main aim of this chapter is to analyse the pattern of environmental pollution as represented by per capita carbon dioxide emission (PCCO2), per capita gross domestic product (PCGDP) and per capita energy consumption (PCEC) and their nexus in case of South-Asian countries for the time period 19912014. Econometric tools such as panel co-integration and fully modified ordinary least squares have been used to study the relations. A positive significant relationship has been observed between PCGDP and PCCO2 emission. In addition, an increase in PCEC also has a positively significant impact on PCCO2 emission. Therefore, the governments of all the countries need to come together and take steps to curb the rising carbon emission since neither the problem nor the responsibility is restricted to one country alone. There is a need for countries to increase the consumption of renewable energy and explore alternate options that are fewer dependents on coal or any other fossil fuel. On priority, economies in South-Asian region should focus on sustainable economic activities by balancing growth of economy with clean environment. 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
An Empirical Study of Blockchain Technology, Innovation, Service Quality and Firm Performance in the Banking Industry
Despite the potential promises that blockchain technology (BT) offers to the financial services sector, its large-scale implementations are still in a nascent stage. There is no consensus on what benefits BT may bring, and there is always a possibility of difference between expected benefits and experienced real-world impact. Since the actual impact can be assessed only after large-scale implementations by financial institutions, there is little empirical evidence available in the literature. In this context, this research seeks to explore the potential impact of BT by developing and empirically testing a model. For this purpose, we have identified four dimensions of BT, namely, Decentralization, Transparency, Trustlessness, and Security. The impact of BT on innovation, service quality, and firm performance is assessed based on the extent to which these dimensions are present in the organization. The linkages of the latent constructs are estimated by analyzing the primary data collected from senior managers of various banks in India. The findings of this study provide several important considerations regarding the implementation of BT. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. -
A Study on Emotion Identification from Music Lyrics
The widespread availability of digital music on the internet has led to the development of intelligent tools for browsing and searching for music databases. Music emotion recognition (MER) is gaining significant attention nowadays in the scientific community. Emotion Analysis in music lyrics is analyzing a piece of text and determining the meaning or thought behind the songs. The focus of the paper is on Emotion Recognition from music lyrics through text processing. The fundamental concepts in emotion analysis from music lyrics (text) are described. An overview of emotion models, music features, and data sets used in different studies is given. The features of ANEW, a widely used corpus in emotion analysis, are highlighted and related to the music emotion analysis. A comprehensive review of some of the prominent work in emotion analysis from music lyrics is also included. 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Analytical Study of Security Enhancement Methods on Diverse Cloud Computing Platforms
Cloud storage is a convenient and virtually limitless storage option for the bulk of data technology is producing in recent times. Data security in cloud is not so robust as data owners need to depend upon the service providers for the safe storage. In this paper, we have identified few broadly used cloud computing paradigms: mobile cloud, cloud-based IoT and multi-tenant cloud. Mobile cloud helps reduce the data storage overhead on the mobile device and give users access to their personal data as and when required through cloud access. Cloud-based IoT helps the network of IoT devices, which is growing exponentially, to create on-demand cloud repositories. Multi-tenant cloud platforms are cloud environment accessed by more than one user. Few recent and related research work which aims at enhanced security from all these three paradigms is discussed and analysed. Encryption and similar network securing methods are used for mobile cloud and cloud-based IoT. For multi-tenant cloud, the objective is to keep the user spaces separate to keep their resources confidential. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Computational Aspects of Business Management with Special Reference to Monte Carlo Simulation
Business management is concerned with organizing and efficiently utilizing resources of a business, including people, in order to achieve required goals. One of the main aspects in this process is planning, which involves deciding operations of the future and consequently generating plans for action. Computational models, both theoretical and empirical, help in understanding and providing a framework for such a scenario. Statistics and probability can play an important role in empirical research as quantitative data is amenable for analysis. In business management, analysis of risk is crucial as there is uncertainty, vagueness, irregularity, and inconsistency. An alternative and improved approach to deterministic models is stochastic models like Monte Carlo simulations. There has been a considerable increase in application of this technique to business problems as it provides a stochastic approach and simulation process. In stochastic approach, we use random sampling to solve a problem statistically and in simulation, there is a representation of a problem using probability and random numbers. Monte Carlo simulation is used by professionals in fields like finance, portfolio management, project management, project appraisal, manufacturing, insurance and so on. It equips the decision-maker by providing a wide range of likely outcomes and their respective probabilities. This technique can be used to model projects which entail substantial amounts of funds and have financial implications in the future. The proposed chapter will deal with concepts of Monte Carlo simulation as applied to Business Management scenario. A few specific case studies will demonstrate its application and interpretation. 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Queering Doctor Who and Supernatural: An ecofeminist response to Bill Potts and Charlie Bradbury
Both Bill Potts from Doctor Who and Charlie Bradbury from Supernatural are iconic lesbian characters who have irreversibly changed the landscape of the long-running shows in which they are featured: the first queer character to appear on Doctor Who as a companion since Captain Jack Harkness, Bill Potts, is the shows first lesbian character to feature in a starring role. Her story arc is bookended by her relationship with Heather, who is first encountered in Bills first episode on the series and who returns to save Bills life at the end of her time as the Doctors companion. Heathers association with what appears to be water or oil-but is eventually revealed to be an alien life force resembling a liquid-is a significant factor in her transition from human to trans-human, and the elemental force that she becomes may be related to the transcendentalist roots of ecocritical discourse. Similarly, Charlie Bradburys role as the Queen of Moondor, a Live Action Role Playing arena, and her subsequent encounter with the faerie Gilda may be viewed in the context of the correlation of geek culture and the return to the natural, pre-industrial/pre-technological world of the episode LARP and the Real Girl (2013). These analyses are examined through an ecofeminist lens that consists primarily of approaches to ecofeminism in the twenty-first century. As Greta Gaard observes in her 2011 essay Ecofeminism Revisited: Rejecting Essentialism and Re-Placing Species in a Material Feminist Environmentalism, " ecofeminism in the late twentieth century declined because of charges of gender essentialism. However, given the emergence of areas such as animal studies, vegan studies, and speciesism, ecocriticism has again risen to prominence in the field of gender studies, and perhaps one way of avoiding the charge of essentialism is to place ecofeminist criticism within the larger framework of questions relating to a pluralistic and queer sense of gender and sexual identities. In this, both Bill and Charlie lend themselves to interpretations based on emerging discourses in ecocritical queer studies. 2021 selection and editorial matter, Douglas A. Vakoch. -
Security Threats and Privacy Issues in Cloud Data
The quick advancement of Web-based applications has led to a huge amount of information being scanned and gathered for business examination or scholarly research purposes, which may disregard individual protection. Organizations, industries and individuals data are at stake. In this paper, utilizing on the Web Personal Health Record (PHR) as contextual analysis, first demonstrate the need of inquiry ability approval that lessens the security introduction coming about because of the list items, and build up a versatile structure for authorized private keyword Search (APKS) over encoded cloud information. This particular model proposes two novel answers for APKS given on-going cryptographic crude, hierarchical predicate encryption (HPE). Our answers empower efficient multi-dimensional watchword looks with a run question, permit assignment and renouncement of hunt abilities. Additionally, the proposed system improves the question protection which conceals clients inquiry watchwords against the server. Actualize our plan on an advanced workstation, and exploratory outcomes exhibit its appropriateness for reasonable use. Privacy has seen advancement lately as information mining of the datasets in a dispersed huge information condition has turned into a successful worldwide business which is none other than data management or data analytics which ensures the security of data. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Estimation of secured wireless sensor networks and its significant observation for improving energy efficiency using cross- learning algorithms
Wireless sensor networks (WSNs) have as of late been created as a stage for various significant observation and control applications. WSNs are continuously utilized in different applications, for example, therapeutic, military, and mechanical segments. Since the WSN is helpless against assaults, refined security administrations are required for verifying the information correspondence between hubs. Because of the asset limitations, the symmetric key foundation is considered as the ideal worldview for verifying the key trade in WSN. The sensor hubs in the WSN course gathered data to the base station. Despite the fact that the specially appointed system is adaptable with the variable foundation, they are exposed to different security dangers. Grouping is a successful way to deal with vitality productivity in the system. In bunching, information accumulation is utilized to diminish the measure of information that streams in the system. 2021 by IGI Global. -
An Extensive Time Series Analysis of Covid-19 Data Sets on the Indian States
Pandemic influenza coronavirus is causing a great loss to mankind. It is creating a chaos on the global economy. Fight against this unseen enemy is affecting all the sectors of the global economy. Mankind is quivering with fear and scared to do something. This study gives a detailed presentation of the current position of virus escalation in India. Sentiment analytics from Twitter data is evaluated on sentiment, emotions and fear opinions are analyzed in the study. The analysis is on red, orange and green zones in several states of India and also gave a comprehensive interpretation on various phases of lockdown. Confirmed, active, recovered and deceased cases in all states are modeled to predict the increase of number of cases. Textual, geographical and graphical analytics are extensively described in the research study. Time series analysis is broadly elaborated as a case study till July 22, 2020, forecasting the impact of virus on Maharashtra, Kerala, Gujarat, Delhi and Tamil Nadu. This study will favor the administrative system to control the disease spread across the nation. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
AI in e-learning
This current research chapter focuses on the different areas of e-learning where AI can be implemented to make e-learning a better experience. E-learning is a 24/7 platform where learners can gain knowledge at the convenience of their home and timeframe. AI can help such learners with different adaptive technologies in clarifying the doubt, identifying the problem area of the learner and providing them a customized learning solution. Adaptive learning suggested that the learning pace is different for different learners. It must be made sure that the educational supplies and amenities provided must fit the requirement of each learner; else, it will lose its essence. There are different AI features to enhance the learning experience of e-learning. The providers must keep this in mind that the acquired information about learners must be wisely used while implementing the AI technology to e-learning mode so that the blended model can provide an enriching experience to the end-user. Cognitive learning can be a key to constructive, collaborative and contextualized execution of AI-enabled learning processes. Maximization of AI effectiveness as a tool of e-learning can be brought only when it is implemented to overall program pedagogy and is monitored for continuous improvement. The Institution of Engineering and Technology 2021. -
DNA-based authentication to access internet of things-based healthcare data
Data security and privacy are always considered as critical aspects, especially in healthcare. The advent of technologies such as the Internet of Things (IoT) has encouraged a great deal of attention in this digital era and helped to improve e-health services. IoT-based services in healthcare and their applications have led to potential growth of quality services in healthcare. However, the sensitive nature of healthcare data and IoT devices which store and collect real-time data makes it even more vulnerable to various attacks. With the development of digitalized data and IoT-based e-health systems, authentication mechanisms are essential to ensure both usability and security. Considering these aspects, a novel, secure user authentication scheme is proposed that uses user ID, unique ID (AADHAAR), password, DNA steganography, and hash function. An One Time Password method is also proposed to strengthen the device authentication. The Scyther tool is used for security analysis and to validate the claims. 2021 Elsevier Inc. All rights reserved. -
Artificial Intelligence and Internet of Things readiness: Inclination for hotels to support a sustainable environment
The idea of Smart Cities has been one of the key driving factors for the urban transformation to a low carbon climate, sustainable economy and mobility in recent years because of the alarming situation of global warming. One of the industries with swift growth is hotel sector and hence is one of the key contributors to carbon emission and leaves environment footprints. The new emerging concept of sustainable tourism is envisaged as an important part of the Smart Cities paradigm. Improving sustainability by saving energy is becoming a primary task toady for many hotels. A great opportunity is provided by Artificial Intelligence (AI) and Internet of Things (IoT) to assimilate different systems on a platform by encouraging and assisting hotel guests to operate through single device and optimizing hotel operations. Current research focuses to identify the strategic positions of a hotel in terms of sustainability, AI and IoT technology. Components that will be considered by Hotels for the strategic intention of adopting AI and IoT for environmental sustainability. Different development and modification needed to be taken if management wants high sustainability readiness and/or IoT readiness. This conceptual paper constructs on the comprehensive study and systematic review of different area where the hotels can feasibly implement AI and IoT for improving sustainably. 2021 Elsevier Inc. All rights reserved. -
The Learning Organization for attaining inclusive growth: A new paradigm for the emerging educational market
This chapter aims to apply the concept of the learning organization for the higher educational institutions (HEIs) for attaining inclusive growth. For the theoretical underpinning, the concept of the professional learning community has been considered because there exists only a very thin difference with the learning organization concept. The researchers used a qualitative approach to analyze the literature resources to find the most promising variables associated with the learning organization and used Dedoose (qualitative software) to select the variables. It is found that variables such as knowledge management, inspired learning, team learning, and transcending organizational boundaries are the most important variables associated with a learning organization. The corporates which have implemented LO have been very successful and one of them is Royal Dutch Shell. The Indian Higher Educational Institutions are the backbone of the Indian economy. However, there is no yardstick to measure success. LO can be implemented to check the growth. This research work will serve as a base for motivating future researchers to make use of the LO concept for drafting educational policy for inclusive growth. If all HEIs are learning organizations, India will soon be a highly rich country. Indian HEI has not practised the concept of learning organization. Henceforth, the suggestions and recommendations will be a new yardstick, which can be used to measure the present status and to frame strategies to improvise and scale success. 2022 selection and editorial matter, Sudhir Rana and Avinash K Shrivastava. -
Fruit Waste as Sustainable Resources for Polyhydroxyalkanoate (PHA) Production
Production of polyhydroxyalkanoate (PHA) using commercially available carbon sources like glucose or sucrose makes the bioprocess economically nonviable, thereby hindering its commercialization. As an alternative to this issue, inexpensive and easily available agro-industrial wastes are now being exploited as feedstock for PHA production. Fruit wastes are generally discarded as they are considered to be the non-product leftovers which do not have any economic value when compared with the cost of their collection and recovery steps for reuse. But through the use of appropriate technological applications, these wastes can be converted to valuable by-products, which can increase the value of the products much higher than the cost associated with recovery steps. By recycling and reprocessing the fruit wastes, they can be channeled into many applications, and thereby the amount of fruit wastes discharged into the environment can be completely reduced along with their detrimental effects. Large amounts of fruit wastes are produced by fruit-based industries. The waste products can be both solids and liquids, and these wastes are of high nutritional and biomass values for microorganism; thus their addition to waterbodies can make them highly polluted (high BOD or COD). These fruit-based wastes still have a promising potential for bioconversion into products of commercial importance or can be successfully exploited as cheap raw materials for industrial production of commercially important metabolites. This chapter deals with the strategies for production of PHA from fruit waste substrates, extraction and characterization of PHA, and their applications in diverse sectors. The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2021. -
Exosomes as an emerging nanoplatform for functional therapeutics
The release of a division of extracellular entities with 40-100 nm dimension from both tumor and varied mesenchymal stem cells during pathologic conditions is termed as exosomes that are shown to actively participate in chemical signaling events occurring in multicellular organisms infection. Exosomes act as a vehicle for shifting amino acids, lipids, and genetic components that are readily engulfed by far-flanging cells (or adjacent cells) at the site of release for remolding the receptor cell functions once the biological contents get activated. Furthermore, pathogens too display the dispense of exosomes to temper the hosts immune response and trigger the infection rate, making them apt investigation markers for diseases. Additionally, aiding in antigen presentation and immune response stimulation, exosomes are significant in showing contrasting role as initiating anticarcinogenic responses and involving in promoting tumorigenesis as they are released from tumor cells. Due to their site specificity, cell lineage property, and encapsulation of specific constituents, exosomes can be potentially utilized as a precious investigatory and prognostic tool along with a possible carrier of drugs and gene shipment for curative goal. Since exosome groundwork is at the infancy stage, deeper insight is required to know its composition, formation, and targeting mechanism along with its significant role in disease diagnosis and treatment. This states, as mentioned previously, we have tried to focus solely on the functional and clinical implications of exosomes in-depth in this review. 2021 Elsevier B.V. All rights reserved. -
MoS2, a new perspective beyond graphene
Owing to the fascinating structural, optical, electrical, chemical properties, graphene has created new paradigm in the field of nanoscience and the common crystalline structures that can be exfoliated include the layered van der Waals (vdW) solids such as boron nitride, transition metal dichalcogenides (TMDCs), black phosphorus, and the layered ionic solids. Here, we bring forth the state-of-art-of materials dominated by their two-dimensional (2D) geometry beyond graphene. Being one of the most well-studied families of vdW layered materials, molybdenum disulphide (MoS2) belonging to TMDC family has gained considerable research interest. The present work is focused on attempts to optimize and characterize this material with unique properties for a host of applications. The work resolves the hydrothermal growth of hexagonal MoS2 nanoflakes with attracting optical and magnetic properties providing strong evidence for the spin orbit split valence bands of these nanostructures. The enhanced electrocatalytic activity, excitation wavelength dependent down-conversion and up-conversion photoluminescence, growth of structural polymorphs using simple hydrothermal method, and the efficient anticancer properties of MoS2 nanostructures providing greater insight into energy and biomedical applications are also discussed. The improved catalytic activity of MoS2-based nanostructures reveals the increasing number of accessible active sites, formation of large surface area and is greatly beneficial for accomplishing a clean, environmental-friendly, inexpensive hydrogen mission for energy storage and conversion applications. The synergistic effect of the MoS2 nanocomposites was able to impede angiogenesis, tumor growth, and epithelial to mesenchymal transition, elucidating the anticancer efficacy. Understanding and exploiting such unique properties of these 2D materials paves new horizons toward novel technological advances in electronic and medical field. 2021 Elsevier Inc. All rights reserved. -
Experimental investigation of tribocorrosion
This chapter discusses various techniques available for evaluation of tribocorrosion behavior of industrial components, their applications, and limitations. Numerous influential factors of tribocorrosion, their mechanisms, and their characteristics have been discussed at length. Further, a case study of tribocorrosion behavior of aluminum-based in situ metal matrix composites have been deliberated comprehensively. 2021 Elsevier Inc. All rights reserved. -
Digital Transformation in Higher Education: Impact of Instructor Training on Class Effectiveness During COVID-19
Digital technology is transforming society and business like never before. Digital technology has made inroads into all sections of society, especially with the pandemic restricting interaction and movement in the physical space. Education systems and institutions have witnessed a drastic change in their pedagogy. Education institutions adopting digital technologies can become drivers of growth and development for their ecosystems bringing significant changes in education, engagement, and management of class activities of educational institutions. The education system will have to adapt and evolve to take advantage of the new technologies and tools and develop strategies to play an active role in the digital transformation process. In the wake of the COVID-19 situation, higher education institutions have adopted digital platforms for teaching and learning. The study attempts to understand the instructors/academician/teachers training process adopted by selected higher education institutions in India to facilitate migration to digital platforms. Further, the study analyses the challenges faced in the new normal of education and the levels of training process initiated by institutions for teaching faculty. The authors have tried to analyse how this has enabled instructors to meet the challenges of conducting online classes and increase class effectiveness. The study unfolded the impact of high-level institutional training on class effectiveness and how individual digital preparedness is essential in engaging virtual classrooms. Further, the positive impact of training in reducing anxiety in engaging online sessions and the extent of motivation to continue online teaching as it has become inevitable with the second wave of the pandemic were examined across age and gender. An attempt is made to suggest few strategies for continued effective online class engagement as India battles through the second wave of the pandemic. 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.