Support Vector Machine Performance Improvements by Using Sine Cosine Algorithm
subject: Machine learning; Parameter optimization; Radiusmargin error; Sine cosine algorithm; Support vector machine (SVM)
description: The optimization of parameters has a crucial influence on the solution efficacy and the accuracy of the support vector machine (SVM) in the machine learning domain. Some of the typical approaches for determining the parameters of the SVM consider the grid search approach (GS) and some of the representative swarm intelligence metaheuristics. On the other side, most of those SVM implementations take into the consideration only the margin, while ignoring the radius. In this paper, a novel radiusmargin SVM approach is implemented that incorporates the enhanced sine cosine algorithm (eSCA). The proposed eSCA-SVM method takes into the account both maximizing the margin and minimizing the radius. The eSCA has been used to optimize the penalty and RBF parameter in SVM. The proposed eSCA-SVM method has been evaluated against four binary UCI datasets and compared to seven other algorithms. The experimental results suggest that the proposed eSCA-SVM approach has superior performances in terms of the average classification accuracy than other methods included in the comparative analysis. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
creator: Zivkovic M.; Vukobrat N.; Chhabra A.; Rashid T.A.; Venkatachalam K.; Bacanin N.
source: Lecture Notes on Data Engineering and Communications Technologies, Vol-114, pp. 791-803.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 23674512
format: Online
language: English
type: Book chapter
coverage: Zivkovic M., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia; Vukobrat N., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia; Chhabra A., Guru Nanak Dev University, Amritsar, India; Rashid T.A., Computer Science and Engineering Department, University of Kurdistan Hewler, KRG, Erbil, Iraq; Venkatachalam K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Bacanin N., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia

Political Optimizer-Based Optimal Integration of Soft Open Points and Renewable Sources for Improving Resilience in Radial Distribution System
subject: Interoperable-photovoltaic system; Loss minimization; Political optimizer; Radial distribution system; Resilience; Soft open points
description: A novel and simple meta-heuristic optimization technique viz., political optimizer (PO) is proposed in this paper to identify the size and optimal location of solar photovoltaic (SPV) system. The main objective is to minimize the distribution loss and is solved using proposed PO. The computational efficiency of PO is compared with the literature, and its superiority is highlighted in terms of global solution at initial stage. The physical requirements of SPV system via soft open points (SOPs) among multiple laterals are solved considering radiality constraints in second stage. The proposed concept of interoperable-photovoltaic (I-PV) system has been applied on standard IEEE 69-bus system and has shown the effectiveness in performance enhancement of the system. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
creator: Sreenivasulu Reddy D.; Janamala V.
source: Lecture Notes on Data Engineering and Communications Technologies, Vol-114, pp. 439-449.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 23674512
format: Online
language: English
type: Book chapter
coverage: Sreenivasulu Reddy D., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to be University), KA, Bangalore, 560074, India; Janamala V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to be University), KA, Bangalore, 560074, India

A Framework for Enhancing Classification in BrainComputer Interface
subject: Adaboost; Braincomputer interface (BCI); Channel selection using recursive feature elimination; Common spatial pattern (CSP)
description: Over the past twenty years, the various merits of braincomputer interface (BCI) have garnered much recognition in the industry and scientific institutes. An increase in the quality of life is the key benefit of BCI utilization. The majority of the published works are associated with the examination and assessment of classification algorithms due to the ever-increasing interest in electroencephalography-based (EEG) BCIs. Yet, another objective is to offer guidelines that aid the reader in picking the best-suited classification algorithm for a given BCI experiment. For a given BCI system, selecting the best-suited classifier essentially requires an understanding of the features to be utilized, their properties, and their practical uses. As a feature extraction method, the common spatial pattern (CSP) will project multichannel EEG signals into a subspace to highlight the variations between the classes and minimize the similarities. This work has evaluated the efficacy of various classification algorithms like Naive Bayes, k-nearest neighbor classifier, classification and regression tree (CART), and AdaBoost for the BCI framework. Furthermore, the work has offered the proposal for channel selection with recursive feature elimination. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
creator: Subramanian S.C.; Daniel D.
source: Lecture Notes on Data Engineering and Communications Technologies, Vol-111, pp. 651-665.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 23674512
format: Online
language: English
type: Book chapter
coverage: Subramanian S.C., Department of Computer Science and Engineering, Christ (Deemed To Be University), Bengaluru, India, Department of Computer Science and Engineering, Sri Venkateswara College of Engineering, Tamil Nadu, Sriperumbudur, India; Daniel D., Department of Computer Science and Engineering, Christ (Deemed To Be University), Bengaluru, India

A Systematic Literature Review on Image Preprocessing and Feature Extraction Techniques in Precision Agriculture
subject: Computer vision; Feature extraction; Image preprocessing; Precision agriculture; Soil pH and soil nutrition
description: Revolutions in information technology have been helping agriculturists to increase the productivity of the cultivation. Many techniques exist for farming, but precision agriculture (PAg) is one technique that has gained popularity and has become a valuable tool for agriculture. Nowadays, farmers find it difficult to get expert advice regarding crops on time. As a solution, image processing techniques (IPTs) embedded PAg applications are developed to support farmers for the benefit of agriculture. In recent years, IPT has contributed a lot to provide a significant solution in PAg. This systematic review provides an understanding on preprocessing and feature extraction in PAg applications along with limitations. Preprocessing and feature extraction are the major steps of any application using IPTs. This study gives an overall view of the different preprocessing, feature extraction, and classification methods proposed by the researchers for PAg. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
creator: Sharmila G.; Rajamohan K.
source: Lecture Notes on Data Engineering and Communications Technologies, Vol-114, pp. 333-354.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 23674512
format: Online
language: English
type: Book chapter
coverage: Sharmila G., Department of Computer Science, CHRIST (Deemed To Be University), Bangalore, 560029, India; Rajamohan K., Department of Computer Science, CHRIST (Deemed To Be University), Bangalore, 560029, India

XGBoost Design byMulti-verse Optimiser: An Application forNetwork Intrusion Detection
subject: Computer networks; Intrusion detection; Machine learning; Multi-verse optimiser; Optimisation; Parameter tuning
description: This article presents the results of an experimental study, which aims to assess the efficiency of the performance of a novel multi-verse optimiser algorithm for the optimisation of parameters of a network intrusion detection system event classifier. The article gives an overview of computer network intrusion detection, outlines common issues faced by software solutions tackling this problem, and proposes using a machine learning algorithm to help solve some of these common issues. An XGBoost classification model with a multi-verse optimisation algorithm for adaptive search and optimisation is used to solve the network intrusion detection system event classifier hyper-parameter optimisation problem. Results of this experimental study are presented and discussed, the improvements compared to previous solutions is shown, and a possible direction of future work in this domain is given in the conclusion. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
creator: Tair M.; Bacanin N.; Zivkovic M.; Venkatachalam K.; Strumberger I.
source: Lecture Notes on Data Engineering and Communications Technologies, Vol-126, pp. 1-16.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 23674512
format: Online
language: English
type: Book chapter
coverage: Tair M., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia; Bacanin N., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia; Zivkovic M., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia; Venkatachalam K., Christ (Deemed to be University), Bangalore, India; Strumberger I., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia

Deducing Water Quality Index (WQI) by Comparative Supervised Machine Learning Regression Techniques for India Region
subject: Biological oxygen demand; Dissolved oxygen; Machine learning; Regression; Supervised; Water Quality Index
description: Water quality is of paramount importance for the wellbeing of the society at large. It plays avery important role in maintaining the health of the living being. Several attributes like biological oxygen demand (BOD), power of hydrogen (pH), dissolved oxygen (DO) content, nitrate content (NC) and so on help to identify the appropriateness of the water to be used for different purposes. In this research study, the focus is to deduce the Water Quality Index (WQI) by means of artificial intelligence (AI)-based machine learning (ML) models. Six parameters, namely BOD, DO, pH, NC, total coliform (CO) and electrical conductivity (EC) are used to measure, analyze and predict WQI using nine supervised regression machine learning techniques. Bayesian Ridge regression (BRR) and automatic relevance determination regression (ARD regression) yielded a low mean squared error (MSE) value when compared to other regression techniques. ARD regression model parameters as independent a priori so that non-zero coefficients do not exploit vectors that are not just sparse, but they are dependent. In the estimation process, BRR contains regularization parameters; regularization parameters are not set hard but are adjusted to the relevant data. Due to these reasons, ARD regression and BRR models performed better. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
creator: Kokatnoor S.A.; Reddy V.; Balachandran K.
source: Lecture Notes on Data Engineering and Communications Technologies, Vol-114, pp. 727-742.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 23674512
format: Online
language: English
type: Book chapter
coverage: Kokatnoor S.A., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Reddy V., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Balachandran K., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bangalore, India

Geospatial crime analysis and forecasting with machine learning techniques
subject: Crime analysis; Crime density; Crime prediction; Forecasting; Hotspot detection; Kernel density estimation; Machine learning algorithms; Social media
description: People use social media to engage, connect, and exchange ideas, for professional interests, and for sharing images, videos, and other contents. According to the investigation, social media allows researchers to examine individual behavior features and geographic and temporal interactions. According to studies, criminology has become a prominent subject of study globally, using data gathered from online social media sites such as Facebook, News feed articles, Twitter, and other sources. It is possible to obtain useful information for the analysis of criminal activity by using spatiotemporal linkages in user-generated content. The study refers to the application of text-based data science by gathering data from several news sources and visualizing it. This research is motivated by the abovementioned work from various social media crimes and government crime statistics. This chapter looks at 68 various crime keywords to help you figure out what kind of crime you are dealing with concerning geographical and temporal data. For categorizing crime into subgroups of categories with geographical and time aspects using news feeds, the Naive Bayes classification algorithm is used. For retrieving keywords from news feeds, the Mallet package is used. The hotspots in crime hotspots are identified using the K-means method. The KDE approach is utilized to address crime density and this methodology has solved the difficulties that the current KDE algorithm has. The study results demonstrated equivalence between the suggested crimes forecasting model as well as the ARIMA model. 2022 Elsevier Inc. All rights reserved.
creator: Prathap B.R.
source: Artificial Intelligence and Machine Learning for EDGE Computing, pp. 87-102.
publisher: Elsevier
date: 2022-01-01
rights: Restricted Access
relation: ISBN: 978-012824054-0; 978-012824055-7
format: Online
language: English
type: Book chapter
coverage: Prathap B.R., Computer Science and Engineering, CHRIST, Karnataka, Bengaluru, India

Revisiting the efficacy of policies in the Indian primary healthcare sector: Interventions and approaches during the COVID-19 pandemic
subject: COVID-19; Government policies; Healthcare workers; Primary healthcare; Public health
description: The COVID-19 pandemic has wracked even the most modern healthcare systems worldwide and has influenced Indias healthcare sector and vastly affected the governments and corporate stakeholders healthcare reform plans; hence, this chapter is intended to unfold the paradigm shift in Indias primary healthcare industry due to the pandemic in the last one and half years. This chapter described Indias experience with the coronavirus during the first and second waves and tried examining the public health difficulties in the COVID era. It provides a timeline of significant events of the pandemics growth in India and worldwide and how India responded to the situations through their economic and healthcare policies. We also go through some of the pandemics impacts and Indias recovery approach and strategies for its revival. All possibly available secondary data like Scopus, Web of Science, Medline/PubMed, and Google Scholar search engines, newspapers, government websites, etc., were excavated to meet this purpose; secondary sources were used to analyze the data. This chapter also examined the effect of COVID-19 on healthcare workers in India. This chapter critically examined the primary healthcares role during this pandemic and the governments policies and processes to deal with COVID-19 and any other unforeseen situations which the country may encounter in the future. 2022 Elsevier Inc. All rights reserved.
creator: Rai R.; Singh P.
source: Lessons from COVID-19: Impact on Healthcare Systems and Technology, pp. 139-169.
publisher: Elsevier
date: 2022-01-01
rights: Restricted Access
relation: ISBN: 978-032399878-9; 978-032399944-1
format: Online
language: English
type: Book chapter
coverage: Rai R., School of Business and Management, CHRIST University, Karnataka, Bengaluru, India; Singh P., School of Management and Commerce, Poornima University, Rajasthan, Jaipur, India

Impact of Innovative Technology on Quality Education: The Resourceful Intelligence for Smart Society Development
subject: Innovative technology; Quality education; Resourceful intelligence; Smart society
description: Quality education is the systematic learning and execution road map that build confidence among the learners and develop employability skills. Innovative techniques are the central facilitators of providing quality education for the younger generation. The economists, scientists, management experts, and research initiators are putting their efforts to develop a certain sustainable system in quality education through innovative technology. This is about digital equity, customized education, activity-based classroom, where the young mind is to be in synchronizing with the technology to explore new possibilities of learning and accomplishment. The research initiative reveals the system of implementing the innovative technology for quality education that has a direct impact on smart society development. The principal outcomes of the research initiative include the innovative ideas that transform the traditional education system into a dynamic education framework. The framework includes the integration of tools and techniques for standard mode of operations that reflects the productive and realistic education system. The researchers gracefully interconnected the concepts, methods, and applications of a quality education system that will open up new vistas for future research initiatives in the area of digital education, industry-institution collaboration, developing smart society, and economy of a nation at large. There is significant level of impact of innovative technology on quality education that leads to independent employability skills, creative, and innovative projects for facilitating future generation. All the influencing factors of resourceful intelligence together have great impact on smart society development that leads to provide modern facilities for the residents of smart society and create favorable environment for the future generations. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
creator: Kanti Podder S.; Thomas B.; Samanta D.
source: Lecture Notes on Data Engineering and Communications Technologies, Vol-132, pp. 293-301.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 23674512
format: Online
language: English
type: Book chapter
coverage: Kanti Podder S., Department of Management and Commerce, Dayananda Sagar College of Arts, Science and Commerce, Bangalore, India; Thomas B., Department of CSE, CHRIST Deemed to be University, Bangalore, India; Samanta D., Department of Computer Science, CHRIST Deemed to be University, Bangalore, India

Nanomaterials-Based Chemical Sensing
subject: Functionalization; Heavy metal ion; Nanocarbon; Nanocarbon-based materials; Nanotechnology; Sensing strategies; Water contamination
description: Nanotechnology is an achievement in the modern period because of its adaptable properties as per its size alterations. Nanomaterials with their size ranging from 1 to 100nm hold incredible novel properties and functionalities because of their molecular arrangements in nano-scale. Nanotechnologies add to pretty much every field of science, including material science, materials chemistry, physics, biology, software and computational engineering and so on. Lately, nanotechnology has been applied to different fields with promising outcomes, particularly in the field of detecting and remediation of toxicity levels, imperilling the ecological solidness just as it does to human wellbeing. One of the principal research interests using nanomaterials is detecting poisonous heavy metal ions. Carbon-based nanomaterials, which are remarkable in view of their toxic-free nature, high surface area and biocompatibility, are valuable for ecological treatments. Heavy metal pollution of water resources is a major issue that poses danger to health and wellbeing. Carbon-based nanomaterials have incredible potential for the detection as well as treatment of heavy metals from water sources in light of their large surface area, nano-scale and accessibility towards various functionalities as they are simpler to be chemically altered and hence reused. Apart from the conventional gas sensors based on SnO2, Fe2O3, In2O3 etc., gas sensors based on nanocarbons materials like carbon nanotubes (CNTs), nanosheets of graphene, carbon nano-fibres etc. exhibit high efficacy when it comes to gas-sensing strategy. Likewise, nanocarbon with hybrids of noble metals or semiconducting oxides can lead to a better performance considering gas-sensing applications. Here in this review, we describe the progress of carbon-based nanomaterials in toxicity detection and remediation. In addition to that, recent trends in nanomaterials-based sensing revealed the advancement of gas sensors based on nanocarbons. 2022, Th…
creator: Joseph N.; Manoj B.
source: Materials Horizons: From Nature to Nanomaterials, pp. 131-147.
publisher: Springer Nature
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 25245384
format: Online
language: English
type: Book chapter
coverage: Joseph N., Department of Physics & Electronics, CHRIST (Deemed to be University), Bangalore, India; Manoj B., Department of Physics & Electronics, CHRIST (Deemed to be University), Bangalore, India

Fabrication of disposable sensor strips for point-of-care testing of environmental pollutants
subject: Biosensor; Carbon nanotube/cellulose composite paper; CNT; Disposable sensor; Fabrication; Inkjet printing; Point-of-care testing; Pollutant; Screen printing; Wax printing
description: Biosensors are potentially used in detection of trace amount of environmental pollutants. Nanostructured materials are being widely explored for its application in the field of biosensors for monitoring environmental pollutants. Advances in biosensor technology with the use of micro-/nanomaterials can detect and analyze living and chemical matter with high specificity, which is relatively fast, sensitive, accurate, and inexpensive for the determination of chemical and biological contaminants. Recent finding shows that carbon nanotubes (CNTs) and nanomaterial-based biosensors utilizing the electrochemical and optical properties are being used for the analysis of contaminants at an incredible sensitivity and accuracy. In this chapter, the application of CNT-based biosensors and the fabrication of paper-based sensors in monitoring hazardous environmental pollutants are discussed. 2022 Elsevier Inc. All rights reserved.
creator: Rao G.; Rao A.; Nandeshwarappa B.P.; Ningegowda R.; Mudnakudu-Nagaraju K.K.; Chandrashekharappa S.
source: Carbon Nanomaterials-Based Sensors: Emerging Research Trends in Devices and Applications, pp. 77-94.
publisher: Elsevier
date: 2022-01-01
rights: Restricted Access
relation: ISBN: 978-032391174-0; 978-032398419-5
format: Online
language: English
type: Book chapter
coverage: Rao G., Department of Biochemistry, Bangalore University, Karnataka, Bengaluru, India; Rao A., Department of Mechanical Engineering, Christ University, Karnataka, Bengaluru, India; Nandeshwarappa B.P., Department of Studies in Chemistry, Davangere University, Karnataka, Davangere, India; Ningegowda R., Department of Chemistry, Jyoti Nivas College Autonomous, Karnataka, Bangalore, India; Mudnakudu-Nagaraju K.K., Department of Biotechnology and Bioinformatics, Faculty of Life Sciences, JSS Academy of Higher Education and Research, Karnataka, Mysore, India; Chandrashekharappa S., Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research (NIPER) Raebareli, Uttar Pradesh, Lucknow, India, Institute for Stem Cell Science and Regenerative Medicine, NCBS, TIFR, GKVK-Campus, Karnataka, Bengaluru, India

Analysis of the spread of infectious diseases with the effects of consciousness programs by media using three fractional operators
subject: Awareness programs; Fixed point theorem; Fractional derivatives; Infectious diseases; q-Homotopy analysis transform technique
description: In this chapter, the mathematical model spread of infectious diseases exemplifying the effects of awareness programs by media is studied with the help of newly proposed fractional operators. The solution for the system of equations exemplifying the model is obtained with the help of the q-homotopy analysis transform technique (q-HATT). The projected method is an elegant amalgamation of the q-homotopy analysis scheme and the Laplace transform. Three fractional operators are employed in this study to show their essence in generalizing the models associated with power-law distribution: kernel singular, nonlocal, and nonsingular. The fixed-point theorem employed to present the existence and uniqueness for the hired arbitrary-order model and converges for the solution is derived with Banach space. The projected scheme springs the series solution rapidly convergent, and it can guarantee the convergence associated with the homotopy parameter. Moreover, for diverse fractional-order, the physical nature has been captured in plots. 2022 Elsevier Inc. All rights reserved.
creator: Veeresha P.
source: Methods of Mathematical Modelling: Infectious Diseases, pp. 113-135.
publisher: Elsevier
date: 2022-01-01
rights: Restricted Access
relation: ISBN: 978-032399888-8; 978-032399947-2
format: Online
language: English
type: Book chapter
coverage: Veeresha P., Centre for Mathematical Needs, Department of Mathematics, CHRIST (Deemed to Be University), Bengaluru, India

A novel secured ledger platform for real-time transactions
subject: Blockchain technology; Cloud computing; Hashing; Ledger platform; Log book technology; Real-time transaction; Secured ledger; Validator
description: The present disclosure relates to a new centralized ledger technology with a centralized validation process. It offers a single platform for all categories of real-time transactions and validations, unlike existing conventional blockchain technology. It offers three levels of hashing placed at the generator, server, and validator end for data security from data tampering and two levels of encryption for communication lines between generator-server and server-validator for packet security. This system ensures trustworthiness, authenticity, and CIA (confidentiality, integrity, and availability) to its end users while being real-time in execution. The proposed system does not follow a chain-based file architecture. Due to this, no concept of chain break arises, and the problems that arise as a result of chain break in the blockchain are avoided. 2022 Elsevier Inc. All rights reserved.
creator: Mukhopadhyay D.; Chakraborty T.; Saha A.; Mukherjee R.
source: Blockchain Technology for Emerging Applications: A Comprehensive Approach, pp. 91-106.
publisher: Elsevier
date: 2022-01-01
rights: Restricted Access
relation: ISBN: 978-032390193-2; 978-032390194-9
format: Online
language: English
type: Book chapter
coverage: Mukhopadhyay D., Department of Computer Science and Engineering, School of Engineering and Technology, Christ Deemed to be University, Karnataka, Bangalore, India; Chakraborty T., Department of Electronics and Communication Engineering, School of Engineering and Technology, Adamas University, West Bengal, Kolkata, India; Saha A., Department of Computer Science and Engineering, School of Engineering and Technology, Adamas University, West Bengal, Kolkata, India; Mukherjee R., Department of Computer Science and Engineering, School of Engineering and Technology, Adamas University, West Bengal, Kolkata, India

Blockchain: Opportunities in the healthcare sector and its uses in COVID-19
subject: Blockchain; COVID-19; Healthcare; Hospital; Medical; Pandemic; Security; Technology
description: As the world grapples with the COVID-19 pandemic and major populations are getting vaccinated, increasing realization processes healthcare industry needs to be augmented. It includes managing supply chains, healthcare records, and patient care. With a scarcity of time and resources, adaptation of blockchain technology will help mitigate the pressures on existing infrastructure. A blockchain distributed ledger helps to exchange health information securely without complex intermediation of trust with secure access. The organizations and persons in the blockchain network can verify and authorize the data, thus protecting patient identity, privacy, medical information system, and reducing transaction costs. The chapter examines managing and protecting electronic medical records and personal health records data using blockchain. It also analyses issues in healthcare, blockchain implementation, and its uses in the COVID-19 pandemic. The authors put forward the idea that even after the world is free of the Coronavirus, there will be pressures on the healthcare industry and Blockchain technology is the way to alleviate this pressure. 2022 Elsevier Inc. All rights reserved.
creator: Arumugam S.K.; Sharma A.M.
source: Lessons from COVID-19: Impact on Healthcare Systems and Technology, pp. 61-94.
publisher: Elsevier
date: 2022-01-01
rights: Restricted Access
relation: ISBN: 978-032399878-9; 978-032399944-1
format: Online
language: English
type: Book chapter
coverage: Arumugam S.K., Department of Professional Studies, School of Commerce, Finance and Accountancy, Christ University, Karnataka, Bangalore, India; Sharma A.M., Symbiosis Centre for Management Studies, Karnataka, Bengaluru, India, Symbiosis International (Deemed University), Maharashtra, Pune, India

GutBrain Axis: Role in Hunger and Satiety
subject: Hunger; Metabolic disorder; Microbiome; Obesity; Probiotics; Satiety
description: The human gastrointestinal tract consists of nearly 100 trillion microorganisms, referred as gut microbiota or gut microbiome. The microbial colonization in the human gut begins at the time of birth and its colonization increases with age which is influenced by factors like age, diet, and antibiotic treatment. Gut microbiota is believed to play a major role in human health as well as various physiological activities like metabolism, nutrition, physiology, etc. Imbalance of the normal gut microbiota has been linked with gastrointestinal conditions such as inflammatory bowel disease (IBD), irritable bowel syndrome (IBS) as well as wider systemic manifestations of disease such as obesity, type 2 diabetes, and atopy. Gutbrain axis, a two-way (bi-directional) connection and communication between the gut and the brain has potentially huge influence over our health which integrates neural, hormonal, and immunological signaling between the gut and the brain. There is growing evidence on the influence of gastrointestinal (GI) microbiota that modulates appetite, feeding, and metabolism as well as regulates the mechanisms of digestion. Gut hormones like Ghrelin, Cholecystokinin (CCK), Pancreatic Polypeptide (PP), Peptide YY (PYY), Glucagon-Like Peptide 1 (GLP-1), Oxyntomodulin (OXM), Glucagon, Gastric Inhibitory Polypeptide (GIP), and Amylin have been identified in the gastrointestinal system which have a fundamental role in coordinating digestive process within the gastrointestinal system, thus regulating feeding behavior and energy balance. Studies have indicated that the modulation in gut microbiota regulates the production of ghrelin and PYY in overweight and obese patients and helps in promoting weight loss and improves glucose regulation. Considering the importance of the role of gut microbiota on hunger and satiety, this chapter was written where we have discussed the gutbrain axis and its role in hunger and satiety. Further, mechanism of appetite regulation by gut micr…
creator: Krishna K.V.; Malviya S.; Bhattacharyya D.; Malaviya A.
source: Probiotic Research in Therapeutics: Volume 5: Metabolic Diseases and Gut Bacteria, Vol-5, pp. 1-27.
publisher: Springer Nature
date: 2022-01-01
rights: Restricted Access
relation: ISBN: 978-981168444-9; 978-981168443-2
format: Online
language: English
type: Book chapter
coverage: Krishna K.V., Applied and Industrial Biotechnology Laboratory (AIBL), Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Malviya S., National Centre for Biological Sciences (NCBS), TATA Institute of Fundamental Research, GKVK Campus, Bengaluru, India; Bhattacharyya D., Applied and Industrial Biotechnology Laboratory (AIBL), Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Malaviya A., Applied and Industrial Biotechnology Laboratory (AIBL), Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India

BERT-Based Secure and Smart Management System for Processing Software Development Requirements from Security Perspective
subject: Bidirectional encoder transformers; Knowledge graphs; Requirements management; Software development; Transfer learning
description: Software requirements management is the first and essential stage for software development practices, from all perspectives, including the security of software systems. Work here focuses on enabling software requirements managers with all the information to help build streamlined software requirements. The focus is on ensuring security which is addressed in the requirements management phase rather than leaving it late in the software development phases. The approach is proposed to combine useful knowledge sources like customer conversation, industry best practices, and knowledge hidden within the software development processes. The financial domain and agile models of development are considered as the focus area for the study. Bidirectional encoder representation from transformers (BERT) is used in the proposed architecture to utilize its language understanding capabilities. Knowledge graph capabilities are explored to bind together the knowledge around industry sources for security practices and vulnerabilities. These information sources are being used to ensure that the requirements management team is updated with critical information. The architecture proposed is validated in light of the financial domain that is scoped for this proposal. Transfer learning is also explored to manage and reduce the need for expensive learning expected by these machine learning and deep learning models. This work will pave the way to integrate software requirements management practices with the data science practices leveraging the information available in the software development ecosystem for better requirements management. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
creator: Althar R.R.; Samanta D.
source: Lecture Notes on Data Engineering and Communications Technologies, Vol-132, pp. 427-440.
publisher: Springer Science and Business Media Deutschland GmbH
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 23674512
format: Online
language: English
type: Book chapter
coverage: Althar R.R., Data Science Department, CHRIST (Deemed to be University), Karnataka, Bangalore, India, Specialist-QMS, First American India Private Ltd., Karnataka, Bangalore, India; Samanta D., Department of Computer Science, CHRIST (Deemed to be) University, Karnataka, Bangalore, India

Rare-earth-activated phosphor for laser lighting
subject: Eu3+doped phosphor; Synthesis and characterization; Y2Ba3B4O12 (YBB)
description: The chapter describes that Y2Ba3B4O12 doped with europium ions were synthesized by a modified conventional solid-state reaction method. The formations of the phosphor crystal structure are confirmed via the X-ray diffraction technique. The luminescence measurement upon excitation in ultraviolet and emission in visible range shows the characteristics of Eu3+ excitation and emission. The occurrence of the charge transfer band is explained in detail. The emission spectrum of Eu3+ ions consists mainly of several groups of lines in the 550-725nm region, due to the transitions from the 5D0 level to the levels 7FJ (J=0, 1, 2, 3, 4) of Eu3+ ions. The phenomena of concentration quenching are explained on the basis of electron-phonon coupling and multipolar interaction. The purity of the red emission is also checked, and it makes Eu3+-doped poly-borate-based phosphor as a promising candidate for laser lighting application. 2022 Elsevier Inc. All rights reserved.
creator: Dubey V.; Dubey N.; Kaur J.; Saji J.
source: Rare-Earth-Activated Phosphors: Chemistry and Applications, pp. 403-407.
publisher: Elsevier
date: 2022-01-01
rights: Restricted Access
relation: ISBN: 978-032389856-0; 978-032388605-5
format: Online
language: English
type: Book chapter
coverage: Dubey V., Department of Physics, Bhilai Institute of Technology Raipur, Chhattisgarh, Naya Raipur, 493661, India; Dubey N., Department of Physics, Govt. V.Y.T. PG. Autonomous College Durg, Chhattisgarh, Durg, India; Kaur J., Department of Physics, Govt. V.Y.T. PG. Autonomous College Durg, Chhattisgarh, Durg, India; Saji J., Department of Sciences and Humanities, Faculty of Engineering, Christ (Deemed to be University), Karnataka, Bangalore, India

Analytical modeling of reconfigurable transistors
description: A functionally enhanced transistor is a potential candidate for further advancing electronics and Moore's law beyond the classical scaling. This chapter discusses these kinds of multifunctional transistors called reconfigurable field-effect transistor (RFET) and reconfigurable tunnel field-effect transistor (RTFET). The RFET works on the principle of Schottky barrier tunneling, and the RTFET works on the principle of band-to-band tunneling. Both devices can be configured as an n-type and p-type device based on the biasing. This chapter explains the working and performance comparison of RFET and RTFET in detail with the help of technology computer-aided design (TCAD) simulations. Further, the potential and current models of a single-gated RFET and double-gated RTFET are presented in this chapter. The presented analytical models are compared and verified with TCAD simulations. The potential in the channel regions of RFET and RTFET is modeled by solving a two-dimensional (2D) Poisson's equation. Because the working principle of both devices is different, two different formulas are utilized for modeling the current in the device. The current model for the RFET is developed by integrating Landauer's formula, whereas the current model for RTFET is obtained by integrating band-to-band generation rate over the tunneling volume. The procedure, technique, and assumptions followed to obtain the potential and current models of RFET and RTFET are detailed in this chapter. 2022 selection and editorial matter, Ashish Raman, Deep Shekhar and Naveen Kumar; individual chapters, the contributors.
creator: Ranjith R.; Suja K.J.; Komaragiri R.S.
source: Sub-Micron Semiconductor Devices: Design and Applications, pp. 355-372.
publisher: CRC Press
date: 2022-01-01
rights: Restricted Access
relation: ISBN: 978-100057723-5; 978-036764809-1
format: Online
language: English
type: Book chapter
coverage: Ranjith R., Department of Electronics and Communication Engineering, School of Engineering and Technology CHRIST (Deemed to be University), Bangalore, India; Suja K.J., Department of Electronics and Communication Engineering, National Institute of Technology Calicut, Kozhikode, India; Komaragiri R.S., Department of Electronics and Communication Engineering, School of Engineering and Applied Science Bennett University, Greater Noida, India

Charting Industry 4.0 Routes Incubation Centers: A Study on Atal Incubation Centre
description: Start-ups have garnered significant attention in India, as well as many other areas of the world, in the past few years. Start-ups may produce significant solutions through innovative and adaptable technology, acting as vehicles for socioeconomic growth and transformation. Some businesses were created in recent times, but the ecosystem was still in its infancy, with just a few investments and a limited number of support programs such as incubators. As business environments have evolved, there are signs that the function of incubators has shifted and extended to a center giving training, with over 20, 000 start-ups and a year-on-year growth rate of 10-12%, India boasts the worlds second largest start-up ecosystem. Since business settings have changed, there are indications that the purpose of incubators has moved and expanded to a center for training and support, connecting, and consulting to new enterprises in all fields of specialization rather than just a business center with office space. According to incubators, the major worry or problem was establishing suitable infrastructure with specialized technology that met the demands of the companies. In terms of investment, incubators were concerned about the schemes rigidity. Some incubators opted to extend financing or make grants rather than make equity investments. This issue originated largely from the regulatory complexities of incubators at educational institutions that make equity-based investments in businesses. Start-ups do not exist in isolation, but rather as a component of the larger economy. In terms of the regulatory framework, it is thought that enhancing the execution of existing start-up regulations and eliminating inefficiency within the administration is critical to making it easier for start-ups to do business. Start-ups would benefit from less paperwork and documentation, improved access to information, more standardized operational processes, and clear criteria. 2023 Taylor and Francis Group, LL…
creator: Choudhary K.; Mahajan J.; George F.J.P.; Saxena A.
source: Principles of Entrepreneurship in the Industry 4.0 Era, pp. 153-171.
publisher: CRC Press
date: 2022-01-01
rights: Restricted Access
relation: ISBN: 978-100073863-6; 978-103218386-2
format: Online
language: English
type: Book chapter
coverage: Choudhary K., School of Business and Management, CHRIST (Deemed to be University), Pune, India; Mahajan J., School of Business and Management, CHRIST (Deemed to be University), Pune, India; George F.J.P., School of Business and Management, CHRIST (Deemed to be University), Pune, India; Saxena A., School of Business and Management, CHRIST (Deemed to be University), Pune, India

Phytochemistry and Pharmacological Activities of Coriandrum sativum L.
subject: biomolecules; coriander; cultivation; essential oils; pharmacological activities
description: Coriandrum sativum L. is a pharmaceutically significant herb that is used for culinary purposes and in herbal formulations. It is an annual herb from the family Apiaceae (Umbelliferae) with unique taxonomic characters. Generally called Dhania or kutumbari, it is cultivated worldwide for its distinct flavors and medicinal properties. Coriander is a rich reservoir of nutrients and significant biochemicals. The phenomenal healing properties of coriander can be attributed to the phytochemicals present in essential oils produced in various parts of the plants, such as leaves, flowers, fruit, and seed. The essential oils are rich in biochemicals like Linalool, (E)-2-decenal, 2-Decenoic acid, camphor, etc. These biomolecules altogether contribute to many pharmacological activities like analgesic, anticancer, anticonvulsant, antidiabetic, anthelmintic, antihypertensive, antimicrobial, anti-mutagenic, antioxidant, anxiolytic, diuretic, hypnotic activity. There are many scientifically proven reports to suggest its importance for usage. The present chapter summarizes the nutrition, biochemicals, and the scientifically proven pharmacological activities of Coriandrum sativum L as well as its cultivation and processing. 2022 by Nova Science Publishers, Inc.
creator: Akshatha B.; Sudheer W.N.; Praveen N.
source: Coriandrum sativum: Origin, Uses and Nutrition, pp. 55-80.
publisher: Nova Science Publishers, Inc.
date: 2022-01-01
rights: Restricted Access
relation: ISBN: 978-168507955-0
format: Online
language: English
type: Book chapter
coverage: Akshatha B., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Sudheer W.N., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India; Praveen N., Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India