Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals
subject: Brain signal; Brain-computer interface; Convolutional neural networks; Hand motion recognition; Machine learning
description: Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG) headsets in the form of EEG signals; these signals can be recorded, processed and classified into different hand movements, which can be used to control other IoT devices. Classification of hand movements will be one step closer to applying these algorithms in real-life situations using EEG headsets. This paper uses different feature extraction techniques and sophisticated machine learning algorithms to classify hand movements from EEG brain signals to control prosthetic hands for amputated persons. To achieve good classification accuracy, denoising and feature extraction of EEG signals is a significant step. We saw a considerable increase in all the machine learning models when the moving average filter was applied to the raw EEG data. Feature extraction techniques like a fast fourier transform (FFT) and continuous wave transform (CWT) were used in this study; three types of features were extracted, i.e., FFT Features, CWT Coefficients and CWT scalogram images. We trained and compared different machine learning (ML) models like logistic regression, random forest, k-nearest neighbors (KNN), light gradient boosting machine (GBM) and XG boost on FFT and CWT features and deep learning (DL) models like VGG-16, Dense-Net201 and ResNet50 trained on CWT scalogram images. XG Boost with FFT features gave the maximum accuracy of 88%. 2022 CRL Publishing. All rights reserved.
creator: Altameem A.; Sachdev J.S.; Singh V.; Poonia R.C.; Kumar S.; Saudagar A.K.J.
source: Computer Systems Science and Engineering, Vol-42, No. 3, pp. 1095-1107.
publisher: Tech Science Press
date: 2022-01-01
rights: All Open Access; Hybrid Gold Open Access
relation: ISSN: 2676192; CODEN: CSSEE
format: Online
language: English
type: Article
coverage: Altameem A., Department of Computer Science, College of Applied Studies, King Saud University, Riyadh, 11495, Saudi Arabia; Sachdev J.S., Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, 303007, India; Singh V., Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, 303007, India; Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Kumar S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Saudagar A.K.J., Information Systems Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia

Mathematical foundations based statistical modeling of software source code for software system evolution
subject: Bidirection encoders transformers; Knowledge graphs; Requirements management; Software development; Transfer learning
description: Source code is the heart of the software systems; it holds a wealth of knowledge that can be tapped for intelligent software systems and leverage the possibilities of reuse of the software. In this work, exploration revolves around making use of the pattern hidden in various software development processes and artifacts. This module is part of the smart requirements management system that is intended to be built. This system will have multiple modules to make the software requirements management phase more secure from vulnerabilities. Some of the critical challenges bothering the software development community are discussed. The background of Machine Learning approaches and their application in software development practices are explored. Some of the work done around modeling the source code and approaches used for vulnerabilities understanding in software systems are reviewed. Program representation is explored to understand some of the principles that would help in understanding the subject well. Further deeper dive into source code modeling possibilities are explored. Machine learning best practices are explored inline with the software source code modeling. 2022 the Author(s), licensee AIMS Press.
creator: Althar R.R.; Alahmadi A.; Samanta D.; Khan M.Z.; Alahmadi A.H.
source: Mathematical Biosciences and Engineering, Vol-19, No. 4, pp. 3701-3719.
publisher: American Institute of Mathematical Sciences
date: 2022-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 15471063; PubMed ID: 35341270
format: Online
language: English
type: Article
coverage: Althar R.R., Department of Data Science, CHRIST University, Karnataka, Bangalore, India, QMS, First American India Private Ltd., Karnataka, Bangalore, India; Alahmadi A., Department of Computer Science and Information, Taibah University, Madinah, Saudi Arabia; Samanta D., Department of Computer Science, CHRIST University, Bangalore, India; Khan M.Z., Department of Computer Science and Information, Taibah University, Madinah, Saudi Arabia; Alahmadi A.H., Department of Computer Science and Information, Taibah University, Madinah, Saudi Arabia

The mathematical and machine learning models to forecast the COVID-19 outbreaks in Bangladesh
subject: 97M10; COVID-19; Epidemiology; FBProphet; Forecasting; Machine Learning; SARS-CoV-2; SEIRD
description: The COVID-19 virus mutates in many different variants after its outbreak. Although several vaccines have been developed by many countries and implemented worldwide, it is difficult to prevent the outbreaks due to the pops out of different variants from its regular mutations. This study is an attempt to develop models which could precisely forecast the COVID-19 outbreaks in Bangladesh. In this study, we have developed a SEIRD based machine learning model to forecast the next possible one year outbreaks scenario in this country. We have tested the accuracy of this model by fitting the results with the considered historical data from March 08, 2020 to October 14, 2021. Also, we have validated this model by predicting the future inside the existing dataset, which is almost similar to the real dataset. It is observed that the final future forecasting results are very realistic compared to the current outbreak situation. Additionally, we have shown that the classical SEIRD model cannot predict the COVID-19 future outbreaks even it does not fit with the real datasets of outbreaks. Moreover, another machine learning time series forecasting model, FBProphet, has been implemented to forecast the future outbreaks of Bangladesh. Finally, we have analyzed and compared the forecasting results and hence identify the limitations of the proposed models which can improve future research in this field. 2022 Taru Publications.
creator: Babu M.A.; Ahmmed M.M.; Ferdousi A.; Mostafizur Rahman M.; Saiduzzaman M.; Bhatnagar V.; Raja L.; Poonia R.C.
source: Journal of Interdisciplinary Mathematics, Vol-25, No. 3, pp. 753-772.
publisher: Taru Publications
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 9720502
format: Online
language: English
type: Article
coverage: Babu M.A., Department of Quantitative Sciences, International University of Business Agriculture and Technology, Dhaka, 1230, Bangladesh; Ahmmed M.M., Department of Mathematics, American International University - Bangladesh (AIUB), Dhaka, 1229, Bangladesh; Ferdousi A., Department of Computer Science, Eastern University, Ashulia, Savar, Dhaka, Bangladesh; Mostafizur Rahman M., Department of Mathematics, American International University - Bangladesh (AIUB), Dhaka, 1229, Bangladesh; Saiduzzaman M., Department of Quantitative Sciences, International University of Business Agriculture and Technology, Dhaka, 1230, Bangladesh; Bhatnagar V., Department of Computer Applications, Manipal University Jaipur, Rajasthan, India; Raja L., Department of Computer Applications, Manipal University Jaipur, Rajasthan, India; Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India

Return and volatility spillover between India, UK, USA and European stock markets: The Brexit impact
subject: Brexit referendum; Diversification; GARCH BEKK; Portfolio; Volatility transmission
description: The 2016 Brexit referendum created potential turmoil in financial markets. The purpose of this study is to examine the impact of the Brexit referendum on the return and volatility spillover between the EU, the UK, and the USA stock markets and the Indian stock market during the pre- and post-Brexit referendum period. The VAR and bivariate GARCH BEKK models were employed. The study results suggest that before the Brexit referendum, Indian stock market returns made no significant return spillover on the other markets. On the contrary, following the referendum, Indian stock returns significantly spilled over to France, Germany, the UK, and the USA stock market returns. The study results also identified a substantial increase in the bidirectional volatility spillover between India-France, India-UK, and India-USA during the post-Brexit referendum period. Therefore, the investors opportunity to invest simultaneously in India, UK, EU, and US stock markets for portfolio diversification is limited. India was affected mainly by its own past shocks before the Brexit referendum. However, after the Brexit referendum, Indian markets are getting more and more integrated with other markets. In order to reap the diversification benefits, a prudent investment strategy will need to be developed in the future, especially during times of economic and political uncertainty and market crisis. Sangeetha G Nagarakatte, Natchimuthu Natchimuthu, 2022
creator: Nagarakatte S.G.; Natchimuthu N.
source: Investment Management and Financial Innovations, Vol-19, No. 1, pp. 121-134.
publisher: LLC CPC Business Perspectives
date: 2022-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 18104967
format: Online
language: English
type: Article
coverage: Nagarakatte S.G., School of Commerce, Finance and Accountancy, Department of Commerce, Christ University, India; Natchimuthu N., School of Commerce, Finance and Accountancy, Department of Commerce, Christ University, India

A short review on environmental impacts and application of iron ore tailings in development of sustainable eco-friendly bricks
subject: Bricks; Eco-friendly; Environment; Iron ore tailings; Sustainable
description: Increased mining activity of iron ore has led to the generation of voluminous wastes of various nature, especially during the different stages of its extraction and production. The improper disposal of such waste causes negative impact on the environment. One such waste which is generated during the beneficiation process of iron ore is waste iron ore tailings, which is also termed as IOT. Further, dumping of IOT on open ground creates huge dumping sites. This dumping sites have been a concern to the environment and human population in its close vicinity. Therefore, a need to effectively use IOT has become one of the subjects of interest for many researchers. This article provides a short review of environmental problems caused due to improper disposal of IOT, and also reviews on the reuse methods of IOT in the construction sector, which helps to alleviate the environmental pollution associated with improper disposal of IOT. Furthermore, reuse of IOT in construction sector reduces the exploitation of the virgin materials for production of construction material, and thus reducing depletion of natural resources. Based on the existing literatures and findings it was observed that the use of IOT to develop stable building blocks using unconventional methods showed great potential and improved performance, when compared with conventional materials such as clay fired bricks. 2021
creator: HK T.; Hossiney N.
source: Materials Today: Proceedings, Vol-61, pp. 327-331.
publisher: Elsevier Ltd
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 22147853
format: Online
language: English
type: Article
coverage: HK T., Department of Civil Engineering, CHRIST (Deemed to be University), Bangalore, India; Hossiney N., Department of Civil Engineering, CHRIST (Deemed to be University), Bangalore, India

Consumer perception and factors influencing consumption of millets
subject: Awareness; Consumption pattern; Factors; Kerala; Millet
description: Consumers purchase intention and preferences are influenced by price, quality, health-related benefits, and awareness about the product. This paper aims to know and understand the consumer perception of millets and to recognize the factors that influence their purchase. The primary data was collected through an online questionnaire covering fourteen districts of Kerala, India. Factor Analysis, Friedman test, T-test, and One-way ANOVA were used for testing the objectives and hypothesis. Factors identified were grouped as perceived value, essential nutrients, and a healthy lifestyle. Friedman test revealed that there wasa significant difference among the mean values of most nutritious cereals, and maize was the most preferred cereal over others in Kerala. Based on the findings, the study recommends certain strategies like food manufacturing companies could introduce variety of millet-based snacks. In addition to this, the concerned food and health department could also devise certain policies that would be aimed at promoting millet-based food. 2022, Kerala Agricultural University. All rights reserved.
creator: Mohan A.R.; George A.; George G.
source: Journal of Tropical Agriculture, Vol-59, No. 2, pp. 177-182.
publisher: Kerala Agricultural University
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 0971636X
format: Online
language: English
type: Article
coverage: Mohan A.R., CHRIST (Deemed to be University), Karnataka, Bengaluru, 560 029, India; George A., CHRIST (Deemed to be University), Karnataka, Bengaluru, 560 029, India; George G., CHRIST (Deemed to be University), Karnataka, Bengaluru, 560 029, India

Derris Indica Leaves Extract as a Green Inhibitor for the Corrosion of Aluminium in Alkaline Medium
subject: Aluminium corrosion; Derris indica; Green inhibitors; Potentiodynamic polarization studies
description: The corrosion inhibitive effect of Derris indica leaves extract (DILE) on aluminium in 1 M NaOH is investigated at different temperatures. For this purpose, weight loss studies and electrochemical methods including potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS) technique are employed. Surface analysis of the treated and untreated aluminium coupons are done by using metallurgical microscopy. About 60.2% of maximum corrosion inhibition efficiency is attained with an optimum inhibitor concentration of 1.2 g/L. Both weight loss and electrochemical studies confirmed that DILE plays a crucial role in the formation of a protective layer over metal surfaces. Also, electrochemical measurements revealed that DILE behaves as a mixed type of corrosion inhibitor. The kinetic parameters and thermodynamic parameters are calculated using Arrhenius theory and transition state theory. Langmuir adsorption isotherm was found to be the best fit and physical adsorption mechanism was proposed. En ineered Science Publisher LLC 2022
creator: Nambiar N.K.; Brindha D.; Punniyakotti P.; Venkatraman B.R.; Angaiah S.
source: Engineered Science, Vol-17, pp. 167-175.
publisher: Engineered Science Publisher
date: 2022-01-01
rights: All Open Access; Bronze Open Access
relation: ISSN: 2576988X
format: Online
language: English
type: Article
coverage: Nambiar N.K., Electro-Materials Research Laboratory, Centre for Nanoscience and Technology, Pondicherry University, Puducherry, 605014, India, Department of Chemistry, CHRIST (Deemed to be University), Bengaluru, 560029, India; Brindha D., PG & Research Dept. of Chemistry, Periyar EVR College, Trichy, 620023, India; Punniyakotti P., Electro-Materials Research Laboratory, Centre for Nanoscience and Technology, Pondicherry University, Puducherry, 605014, India; Venkatraman B.R., PG & Research Dept. of Chemistry, Periyar EVR College, Trichy, 620023, India; Angaiah S., Electro-Materials Research Laboratory, Centre for Nanoscience and Technology, Pondicherry University, Puducherry, 605014, India

Financial well-being A Generation Z perspective using a Structural Equation Modeling approach
subject: Financial behavior; Financial fragility; Financial literacy; Financial technology; India
description: The current pandemic situation in the global economy has urged the need to revolutionize the financial services industry with a keen eye on consumers financial needs for sound financial decisions, which is necessary for financial well-being. The purpose of the study is to assess the financial well-being of Indian Gen Z students in relation to financial literacy, financial fragility, financial behavior, and financial technology. In addition, the study also tries to determine how Gen Z students financial well-being is influenced by other factors such as gender, age, parental education, employment status, and monthly income in India. The study uses the scientific data analysis approach, Partial Least Squares-SEM model to estimate, predict, and assess the hypotheses. A sample of 271 University students from India was surveyed using a self-administered structured questionnaire. Questions were incorporated to understand the effect of financial literacy, technology, fragility, behavior, demographic and parental characteristics on financial well-being. The results indicate that financial behavior is positively related to financial well-being, while financial fragility is negatively associated. However, financial literacy and financial technology do not significantly affect financial well-being. The results also show that financial well-being is significantly influenced by gender, parental education, employment status, and monthly income change. Understanding Indian Gen Z student financial well-being will expand the students understanding of the importance of financial literacy for well-planned financial behavior and informed decisions, hence high levels of financial well-being. Government and financial institutions can more effectively identify gaps and deficiencies in student financial well-being. 2022 LLC CPC Business Perspectives. All rights reserved.
creator: Shankar N.; Vinod S.; Kamath R.
source: Investment Management and Financial Innovations, Vol-19, No. 1, pp. 32-50.
publisher: LLC CPC Business Perspectives
date: 2022-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 18104967
format: Online
language: English
type: Article
coverage: Shankar N., School of Business and Management, CHRIST University, India; Vinod S., Department of Computer Science, CHRIST University, India; Kamath R., School of Business and Management, CHRIST University, India

(Mes-Acr-Me)+ClO4 Catalyzed Visible Light-Supported, One-Pot Green Synthesis of 1,8-Naphthyridine-3-Carbonitriles
subject: 1,8-Naphthyridines; 9-Mesityl-10-methylacridinium perchlorate; Blue LED; Excellent yield; Multicomponent reaction
description: Abstract: A novel, four-component one-pot green synthesis of biologically active 1,8-naphthyridines by a reaction of diverse aromatic aldehyde, malononitrile, 4-hydroxy substituted 1,6-dimethylpyridin-2(1H)-one, corresponding aniline in EtOH catalyzed by 9-Mesityl-10-methylacridinium perchlorate [(Mes-Acr-Me)+ClO4] under visible light generated from a 24W Blue LED wavelength 450460nm at 26C is reported. In contrast with the reported procedure, our methodology is diverse, versatile and has several favourable factors such as metal-free, excellent yields, shorter reaction durations, chromatography free and straightforward extraction process. Graphical Abstract: [Figure not available: see fulltext.]. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
creator: Tabassum S.; Govindaraju S.; Kendrekar P.
source: Topics in Catalysis
publisher: Springer
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 10225528
format: Online
language: English
type: Article
coverage: Tabassum S., Department of Chemistry, Surana College, South End Road, Basavanagudi, Bengaluru, 560004, India; Govindaraju S., Department of Sciences and Humanities, School of Engineering and Technology, CHRIST (Deemed to be University), Kumbalagodu, Mysore Road, Bengaluru, 560074, India; Kendrekar P., Lipid Nanostructures Laboratory, Centre for Smart Materials, School of Natural Sciences, University of Central Lancashire, Preston, PR1 2HE, United Kingdom

The Impact of Website Design on Online Customer Buying Satisfaction and Loyalty to E-Tailers: An Exploratory Study of E-Tailers in India
subject: Adoption; Customer satisfaction; E-commerce; Loyalty; Website design
description: The popularity of e-tailers has distorted the retail industry in India. Websites are becoming an important means through which customers get product information and purchase items for their needs. This research paper focuses on four dimensions (i.e., user interface, convenience, personalized recommendations, and perceived security of the website) to assess their impact on online customer satisfaction with and loyalty towards e-tailers. The study questionnaire used established measures. The data was collected from four large cities in India, namely Chennai, Mumbai, Kolkata, and Delhi. Analysis of the survey results suggests that perceived website security is the most important dimension for customer loyalty. E-tailers have to ensure adequate security provisions in their websites to build up consumer perceptions of trust and so repeat business loyalty. Copyright 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
creator: Chakraborty D.; Banerjee J.; Mehta P.; Singh N.P.
source: Information Resources Management Journal, Vol-35, No. 1
publisher: IGI Global
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 10401628
format: Online
language: English
type: Article
coverage: Chakraborty D., Symbiosis Institute of Business Management, Nagpur, India, Symbiosis International University (Deemed), India; Banerjee J., Christ University, India; Mehta P., Symbiosis International University (Deemed), India, Symbiosis Centre for Management Studies, Nagpur, India; Singh N.P., Mvn University, India

Photocatalytic degradation of methylene blue and metanil yellow dyes using green synthesized zinc oxide (Zno) nanocrystals
subject: Coconut husk extract; Photocatalysis; UV light; ZnO
description: In this work, ZnO nanocrystals (NCs) have been effectively synthesized by a simple, efficient and cost-effective method using coconut husk extract as a novel fuel. The synthesized NCs are characterized by UV-Vis, XRD, FT-IR, SEM, EDX, Raman and PL studies. The obtained ZnO were found to be UV-active with a bandgap of 2.93 eV. The X-ray diffraction pattern confirms the crystallinity of the ZnO with hexagonally structured ZnO with a crystallite size of 48 nm, while the SEM analysis reveals the hexagonal bipyramid morphology. Photocatalytic activities of the synthesized ZnO NCs are used to degrade methylene blue and metanil yellow dyes. 2021 by the authors. Licensee MDPI, Basel, Switzerland.
creator: Priyadharshini S.S.; Shubha J.P.; Shivalingappa J.; Adil S.F.; Kuniyil M.; Hatshan M.R.; Shaik B.; Kavalli K.
source: Crystals, Vol-12, No. 1
publisher: MDPI
date: 2022-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 20734352
format: Online
language: English
type: Article
coverage: Priyadharshini S.S., Department of Chemistry, SJB Institute of Technology, Kengeri, Bangalore, 560060, India; Shubha J.P., Department of Chemistry, Don Bosco Institute of Technology, Mysore Road, Bangalore, 560074, India; Shivalingappa J., Department of Chemistry, SJB Institute of Technology, Kengeri, Bangalore, 560060, India; Adil S.F., Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia; Kuniyil M., Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia; Hatshan M.R., Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia; Shaik B., Department of Advanced Materials Engineering for Information and Electronics, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Gyeonggi-do, Yongin-si, 446-701, South Korea; Kavalli K., Department of Mechanical and Automobile Engineering, School of Engineering and Technology, CHRIST University, Bangalore, 560074, India

Brain image classification using time frequency extraction with histogram intensity similarity
subject: Convolutional neural network; Differential deep learning; Histogram
description: Brain medical image classification is an essential procedure in Computer-Aided Diagnosis (CAD) systems. Conventional methods depend specifically on the local or global features. Several fusion methods have also been developed, most of which are problem-distinct and have shown to be highly favorable in medical images. However, intensity-specific images are not extracted. The recent deep learning methods ensure an efficient means to design an end-to-end model that produces final classification accuracy with brain medical images, compromising normalization. To solve these classification problems, in this paper, Histogram and Time-frequency Differential Deep (HTF-DD) method for medical image classification using Brain Magnetic Resonance Image (MRI) is presented. The construction of the proposed method involves the following steps. First, a deep Convolutional Neural Network (CNN) is trained as a pooled feature mapping in a supervised manner and the result that it obtains are standardized intensified pre-processed features for extraction. Second, a set of time-frequency features are extracted based on time signal and frequency signal of medical images to obtain time-frequency maps. Finally, an efficient model that is based on Differential Deep Learning is designed for obtaining different classes. The proposed model is evaluated using National Biomedical Imaging Archive (NBIA) images and validation of computational time, computational overhead and classification accuracy for varied Brain MRI has been done. 2022 CRL Publishing. All rights reserved.
creator: Renukadevi T.; Saraswathi K.; Prabu P.; Venkatachalam K.
source: Computer Systems Science and Engineering, Vol-41, No. 2, pp. 645-660.
publisher: Tech Science Press
date: 2022-01-01
rights: All Open Access; Hybrid Gold Open Access
relation: ISSN: 2676192; CODEN: CSSEE
format: Online
language: English
type: Article
coverage: Renukadevi T., Department of Computer Technology-UG, Kongu Engineering College, Erode, India; Saraswathi K., Department of Computer Technology-UG, Kongu Engineering College, Erode, India; Prabu P., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Venkatachalam K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India

Wireless Sensor Data Acquisition and Control Monitoring Model for Internet of Things Applications
description: This article focuses on providing solutions for one important application termed as agriculture. In India, one major occupation for people living in urban and rural areas is agriculture where an economic rate depends only on the crops they yield. In such cases, if an intelligent monitoring device is not integrated then it becomes difficult for the farmers to grow their crops and to accomplish marginal income from what they have invested. Also existing methods have been analyzed in the same field where some devices have been installed and checked for increasing the productivity of horticulture crops. But existing methods fail to install an intelligent monitoring device that can provide periodic results within short span of time. Therefore, a sensor based technology with Internet of Things (IoT) has been implemented in the projected work for monitoring major parameters that support the growth and income of farmers. Also, an optimization algorithm for identifying the loss in different crops has been incorporated for maximizing the system boundary and to transmit data to farmers located in different areas. To prove the cogency of proposed method some existing methods have been compared and the results prove the projected technique produces improved results for about 58%. 2022 SulaimaLebbe Abdul Haleem et al.
creator: Abdul Haleem S.; Kshirsagar P.R.; Manoharan H.; Prathap B.; Hemalatha S.; Pradeep Kumar K.; Tirth V.; Islam S.; Katragadda R.; Amibo T.A.
source: Scientific Programming, Vol-2022
publisher: Hindawi Limited
date: 2022-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 10589244; CODEN: SCIPE
format: Online
language: English
type: Article
coverage: Abdul Haleem S., Department of Information and Communication Technology, South Eastern University of Sri Lanka (SEUSL), Oluvil, Sri Lanka; Kshirsagar P.R., Department of Artificial Intelligence, G. H. Raisoni College of Engineering, Nagpur, 440016, India; Manoharan H., Department of Electronics and Communication Engineering, Panimalar Institute of Technology, Poonamallee, Tamil Nadu, Chennai, India; Prathap B., Department of Computer Science and Engineering, CHRIST University, Bangalore, India; Hemalatha S., Department of Computer Science and Engineering, Panimalar Institute of Technology, Chennai, India; Pradeep Kumar K., Department of Computer Science and Engineering, Panimalar Institute of Technology, Chennai, India; Tirth V., Mechanical Engineering Department, College of Engineering, King Khalid University, Asir, Abha, 61411, Saudi Arabia; Islam S., Civil Engineering Department, College of Engineering, King Khalid University, Asir, Abha, 61411, Saudi Arabia; Katragadda R., Department of Business Management, V. R. Siddhartha Engineering College, Andhra Pradesh, Vijayawada, India; Amibo T.A., School of Chemical Engineering, Jimma Institute of Technology, Jimma University, Oromia, Jimma, Ethiopia

Pt Nanospheres Decorated Graphene-?-CD Modified Pencil Graphite Electrode for the Electrochemical Determination of Vitamin B6
subject: Electro-catalytic oxidation; Graphene; Pencil graphite electrode; Vitamin B6; ?-CD
description: An electrochemical sensor for Vitamin B6 determination has been prepared by the electrochemical deposition of Pt nanospheres on graphene-?-CD coated Pencil Graphite Electrode (PGE). Cyclic voltammetric (CV) and electrochemical impedance spectroscopic (EIS) studies were employed to explore the electrochemical properties of the modified electrode. The physicochemical properties of the modified electrodes were characterized by X-ray photoelectron spectroscopy (XPS), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and optical profilometric studies. The experimental conditions such as effect of scan rate, concentration and pH were optimized. The linear dynamic range for the determination of Vitamin B6 was found to be 5nM to 205nM. The low level of detection limit (1.2nM) implies the high sensitivity of the process. The suggested method was effectively employed for the electrocatalytic evaluation of Vitamin B6 in different juice samples. Graphical Abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
creator: Rison S.; Mathew A.T.; George L.; Maiyalagan T.; Hegde G.; Varghese A.
source: Topics in Catalysis
publisher: Springer
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 10225528
format: Online
language: English
type: Article
coverage: Rison S., Christ Academy Institute For Advanced Studies, Christ Nagar, Bangalore, 560083, India, Department of Chemistry, CHRIST (Deemed To Be University), Bangalore, 560029, India; Mathew A.T., Department of Chemistry, CHRIST (Deemed To Be University), Bangalore, 560029, India; George L., Department of Chemistry, CHRIST (Deemed To Be University), Bangalore, 560029, India; Maiyalagan T., SRM Institute of Science and Technology, Kattankulathur, 603203, India; Hegde G., Department of Chemistry, CHRIST (Deemed To Be University), Bangalore, 560029, India, Centre for Advanced Research and Development (CARD), CHRIST (Deemed To Be) University, Bangalore, 560029, India; Varghese A., Department of Chemistry, CHRIST (Deemed To Be University), Bangalore, 560029, India

Machine Learning Technique to Detect Radiations in the Brain
subject: Brain morphology; Electromagnetic field radiations; Image processing; Machine learning; Segmentation
description: The brain of humans and other organisms is affected in various ways through the electromagnetic field (EMF) radiations generated by mobile phones and cell phone towers. Morphological variations in the brain are caused by the neurological changes due to the revelation of EMF. Cellular level analysis is used to measure and detect the effect of mobile radiations, but its utilization seems very expensive, and it is a tedious process, where its analysis requires the preparation of cell suspension. In this regard, this research article proposes optimal broadcasting learning to detect changes in brain morphology due to the revelation of EMF. Here, Drosophila melanogaster acts as a specimen under the revelation of EMF. Automatic segmentation is performed for the brain to attain the microscopic images from the prejudicial geometrical characteristics that are removed to detect the effect of revelation of EMF. The geometrical characteristics of the brain image of that is microscopic segmented are analyzed. Analysis results reveal the occurrence of several prejudicial characteristics that can be processed by machine learning techniques. The important prejudicial characteristics are given to four varieties of classifiers such as nae Bayes, artificial neural network, support vector machine, and unsystematic forest for the classification of open or nonopen microscopic image of D. melanogaster brain. The results are attained through various experimental evaluations, and the said classifiers perform well by achieving 96.44% using the prejudicial characteristics chosen by the feature selection method. The proposed system is an optimal approach that automatically identifies the effect of revelation of EMF with minimal time complexity, where the machine learning techniques produce an effective framework for image processing. This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium,…
creator: Gothai E.; Baseera A.; Prabu P.; Venkatachalam K.; Saravanan K.; SathishKumar S.
source: Computer Systems Science and Engineering, Vol-42, No. 1, pp. 149-163.
publisher: Tech Science Press
date: 2022-01-01
rights: All Open Access; Hybrid Gold Open Access
relation: ISSN: 2676192; CODEN: CSSEE
format: Online
language: English
type: Article
coverage: Gothai E., Department of Computer Science and Engineering, Kongu Engineering College, Erode, 638060, India; Baseera A., School of Computing Science and Engineering, VIT Bhopal University, Bhopal, 466114, India; Prabu P., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Venkatachalam K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Saravanan K., Department of Computer Science and Engineering, Erode Sengunthar Engineering College, Thudupathi, 638057, India; SathishKumar S., Department of EEE, M.Kumarasamy College of Engineering, Tamilnadu, Karur, 639113, India

The influences of lateral groups on 4-cyanobiphenyl-benzonitrile- based dimers
subject: aggregation; cyanobiphenyl; dimers; fluorescence; Liquid crystals; molecular dynamic simulation; nematic phase
description: Cyanobiphenyl-based compounds are known to display RT or low melting liquid crystals in a single-component system or composites. Herein, we discuss the influence of laterally substituted groups (-CN, -F, -H) on 4-[?-(4-cyanobiphenyl-4-yloxy)alk-1-yloxy]benzonitrile. Three series of new dimers were synthesised by using 4-cyano-4-hydroxybiphenyl connected via flexible spacers with different number of carbon atoms to 4-hydroxyphthalonitrile/ 2-fluoro-4-hydroxy benzonitrile/ 4-hydroxy benzonitrile. Their self-assembly in LC phases assessed by polarising optical microscopy (POM), differential scanning calorimetry (DSC) and X-ray diffraction studies, and their behaviours are compared with related non-substituted (-H) model compound. UV-Visible and fluorescent experiments confirm the strong aggregation, the intensities of emission decrease as we move from CN?F?H substitutions. A representative dimer from each series covering the aspect of polarity and flexibility have been simulated using 1000 minimisation steepest descent and CHARMM force filed to examine their self-assembly. This work helps to understand the influence of lateral groups, connecting spacers on the LC behaviour of dimers. 2022 Informa UK Limited, trading as Taylor & Francis Group.
creator: Srinatha M.K.; Zeba A.; Ganjiwale A.; Gowda A.; Hegde G.; Alaasar M.; Shanker G.
source: Liquid Crystals, Vol-49, No. 2, pp. 217-229.
publisher: Taylor and Francis Ltd.
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 2678292; CODEN: LICRE
format: Online
language: English
type: Article
coverage: Srinatha M.K., Department of Chemistry, Bangalore University, Jnana Bharathi Campus, Bangalore, India; Zeba A., Department of Life Science, Bangalore University, Jnana Bharathi Campus, Bangalore, India; Ganjiwale A., Department of Life Science, Bangalore University, Jnana Bharathi Campus, Bangalore, India; Gowda A., Raman Research Institute, C.V. Raman Avenue, Bangalore, India; Hegde G., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bangalore, India; Alaasar M., Department of Chemistry, Faculty of Science, Cairo University, Giza, Egypt; Shanker G., Department of Chemistry, Bangalore University, Jnana Bharathi Campus, Bangalore, India

Promoting Sustainability Through Corporate Social Responsibility: Insights and Barriers of Medium-Sized Manufacturing Enterprises in India
subject: Corporate sustainability; CSR; Effective corporate social responsibility; Medium-sized manufacturing enterprises; Partial least square structure equation modelling
description: The current study aims to explore if effective corporate social responsibility leads to corporate sustainability in medium-sized manufacturing enterprises. Using the factors, an exploratory examination was performed to assess their suitability in Indian context, and data were collected from 121 manufacturing companies using structured questionnaire based on pretested scale, and the proposed relationships were tested through partial least square structural equation modelling (PLS-SEM). The results show overall model fit and empirical examinations support causal relationships between effective corporate social responsibility and corporate sustainability (CS). The results indicated that effective CSR mediated the relationships between corporate sustainability and integration of CSR into corporate policy and priority of the board towards CSR. The results of this study are useful for medium-sized enterprises to establish a formal approach towards CSR and meet the needs of business and society in the 21st century. Copyright 2022, IGI Global.
creator: Dawar G.; Singh S.
source: International Journal of Social Ecology and Sustainable Development, Vol-13, No. 1
publisher: IGI Global
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 19478402
format: Online
language: English
type: Article
coverage: Dawar G., Christ University (Deemed), Delhi, India, Delhi Technological University, India; Singh S., Delhi Technological University, India

Blockchain for Securing Healthcare Data Using Squirrel Search Optimization Algorithm
subject: Blockchain; Healthcare; Key generation; Multi-objective squirrel search optimization algorithm; Security
description: The Healthcare system is an organization that consists of important requirements corresponding to security and privacy, for example, protecting patients medical information from unauthorized access, communication with transport like ambulance and smart e-health monitoring. Due to lack of expert design of security protocols, the healthcare system is facing many security threats such as authenticity, data sharing, the conveying of medical data. In such situa-tion, block chain protocol is used. In this manuscript, Efficient Block chain Network for securing Healthcare data using Multi-Objective Squirrel Search Optimization Algorithm (MOSSA) is proposed to generate smart and secure Healthcare system. In this the block chain is a decentralized and the distributed ledger device that consists of various blocks linked with digital signature schemes, consensus mechanisms and chain of hashing, offers highly reliable storage capabilities. Further the block chain parameters, such as block size, transac-tion size and number of block chain channels are optimized with the help of MOSSA. With the evolution of the MOSSA provide new features for enhancing security and scalability. The simulation process is executed in the JAVA platform. The experimental result of the proposed method shows higher throughput of 26.87%, higher efficiency of 34.67%, lowest delay of 22.97%, lesser computational overhead of 37.03%, higher storage cost of 34.29% when compared to the existing method such as Block chain-ECIES-HSO, Block chain-hybrid GO-FFO, Block chain-SDN-HSO algorithm for healthcare technologies. 2022, Tech Science Press. All rights reserved.
creator: Jaishankar B.; Vishwakarma S.; Mohan P.; Pundir A.K.S.; Patel I.; Arulkumar N.
source: Intelligent Automation and Soft Computing, Vol-32, No. 3, pp. 1815-1829.
publisher: Tech Science Press
date: 2022-01-01
rights: All Open Access; Hybrid Gold Open Access
relation: ISSN: 10798587
format: Online
language: English
type: Article
coverage: Jaishankar B., Department of Electronics and Communication Engineering, KPR Institute of Engineering and Technology, Coimbatore, 641407, India; Vishwakarma S., Department of Computer Science and Engineering, National Institute of Technology, Arunachal Pradesh, 791112, India; Mohan P., Data Science and Analytics Centre, Karpagam College of Engineering, Coimbatore, 641032, India; Pundir A.K.S., Department of Electronics and Communication Engineering, Arya College of Engineering and Information Technology, Kukas, 302028, India; Patel I., Department of Electronics and Communication Engineering, B V Raju Institute of Technology, Narsapur, 502313, India; Arulkumar N., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India

Optimized Load Balancing Technique for Software Defined Network
subject: Load balancing; Performance enhancement; SDN; Software-defined networks
description: Software-defined networking is one of the progressive and prominent innovations in Information and Communications Technology. It mitigates the issues that our conventional network was experiencing. However, traffic data generated by various applications is increasing day by day. In addition, as an organization's digital transformation is accelerated, the amount of information to be processed inside the organization has increased explosively. It might be possible that a Software-Defined Network becomes a bottleneck and unavailable. Various models have been proposed in the literature to balance the load. However, most of the works consider only limited parameters and do not consider controller and transmission media loads. These loads also contribute to decreasing the performance of Software- Defined Networks. This work illustrates how a software-defined network can tackle the load at its software layer and give excellent results to distribute the load. We proposed a deep learning-dependent convolutional neural networkbased load balancing technique to handle a software-defined network load. The simulation results show that the proposed model requires fewer resources as compared to existing machine learning-based load balancing techniques. 2022 Tech Science Press. All rights reserved.
creator: Kumar A.; Anand D.; Jha S.; Joshi G.P.; Cho W.
source: Computers, Materials and Continua, Vol-72, No. 1, pp. 1409-1426.
publisher: Tech Science Press
date: 2022-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 15462218
format: Online
language: English
type: Article
coverage: Kumar A., Department of Computer Science and Engineering, Chandigarh University, Punjab, Mohali, 140413, India; Anand D., Department of Computer Science and Engineering, Chandigarh University, Punjab, Mohali, 140413, India; Jha S., School of Computational Sciences, CHRIST (Deemed to be University), Ghaziabad, 201003, India; Joshi G.P., Department of Computer Science and Engineering, Sejong University, Seoul, 05006, South Korea; Cho W., Department of Automotive ICT Convergence Engineering, Daegu Catholic University, Gyeongsan, 38430, South Korea

Product specific determinants of electronic gadget purchase intention - a case of the purchase behaviour of Indian youth
subject: Brand image; Brands; COO; Corporate identity; Country of origin; Electronic gadgets; Product design; Product evaluation; Purchase behaviour; Purchase intention; Youth
description: This study investigated the impact of product specific features of electronic gadgets on the purchase intention on the Indian youth. The study was quantitative in nature and data was collected from 650 young electronic gadget consumers in Bengaluru, India using structured questionnaires. Descriptive statistics and structural equation modelling (SEM) were used for data analysis. Brand image, product design, and country of origin are referred as product evaluation attributes; and corporate identity were identified as the determinants of purchase intention. Respondents were neutral regarding the role of product evaluation attributes and corporate identity in their purchases, but acknowledged these factors' importance. Findings implied a positive and significant influence of product evaluation attributes on the corporate identity of companies, and purchase intention of the youth. However, corporate identity did not influence purchase intention, clearly indicating that only product specific features, such as brand, design and country of origin are considered when youngsters purchase gadgets. Copyright 2022 Inderscience Enterprises Ltd.
creator: Kulkarni S.; James L.
source: International Journal of Management Practice, Vol-15, No. 2, pp. 205-234.
publisher: Inderscience Publishers
date: 2022-01-01
rights: Restricted Access
relation: ISSN: 14779064
format: Online
language: English
type: Article
coverage: Kulkarni S., School of Business and Management, CHRIST (Deemed to be University), Bannerghatta Road Campus, Karnataka, Bangalore, 560076, India; James L., School of Business and Management, CHRIST (Deemed to be University), Central Campus, Karnataka, Bangalore, 560029, India