Blockchain for Securing Healthcare Data Using Squirrel Search Optimization Algorithm
Blockchain; Healthcare; Key generation; Multi-objective squirrel search optimization algorithm; Security
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.
Jaishankar B.; Vishwakarma S.; Mohan P.; Pundir A.K.S.; Patel I.; Arulkumar N.
Intelligent Automation and Soft Computing, Vol-32, No. 3, pp. 1815-1829.
All Open Access; Hybrid Gold Open Access
https://doi.org/10.32604/IASC.2022.021822 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122209823&doi=10.32604%2fIASC.2022.021822&partnerID=40&md5=b2c242f827213e2d2fd7150897c3ef3d
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
Promoting Sustainability Through Corporate Social Responsibility: Insights and Barriers of Medium-Sized Manufacturing Enterprises in India
Corporate sustainability; CSR; Effective corporate social responsibility; Medium-sized manufacturing enterprises; Partial least square structure equation modelling
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.
International Journal of Social Ecology and Sustainable Development, Vol-13, No. 1
https://doi.org/10.4018/IJSESD.2022010107 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125074639&doi=10.4018%2fIJSESD.2022010107&partnerID=40&md5=547a9bc43deda878c9a16063f86e7816
Dawar G., Christ University (Deemed), Delhi, India, Delhi Technological University, India; Singh S., Delhi Technological University, India
The influences of lateral groups on 4-cyanobiphenyl-benzonitrile- based dimers
aggregation; cyanobiphenyl; dimers; fluorescence; Liquid crystals; molecular dynamic simulation; nematic phase
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.
Srinatha M.K.; Zeba A.; Ganjiwale A.; Gowda A.; Hegde G.; Alaasar M.; Shanker G.
Liquid Crystals, Vol-49, No. 2, pp. 217-229.
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
Machine Learning Technique to Detect Radiations in the Brain
Brain morphology; Electromagnetic field radiations; Image processing; Machine learning; Segmentation
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, provided the original work is properly cited.
Gothai E.; Baseera A.; Prabu P.; Venkatachalam K.; Saravanan K.; SathishKumar S.
Computer Systems Science and Engineering, Vol-42, No. 1, pp. 149-163.
https://doi.org/10.32604/CSSE.2022.020619 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121609894&doi=10.32604%2fCSSE.2022.020619&partnerID=40&md5=bf5b14750fa5d3b433c59a2534f30d31
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
Pt Nanospheres Decorated Graphene-?-CD Modified Pencil Graphite Electrode for the Electrochemical Determination of Vitamin B6
Electro-catalytic oxidation; Graphene; Pencil graphite electrode; Vitamin B6; ?-CD
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.
Rison S.; Mathew A.T.; George L.; Maiyalagan T.; Hegde G.; Varghese A.
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
Wireless Sensor Data Acquisition and Control Monitoring Model for Internet of Things Applications
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.
Abdul Haleem S.; Kshirsagar P.R.; Manoharan H.; Prathap B.; Hemalatha S.; Pradeep Kumar K.; Tirth V.; Islam S.; Katragadda R.; Amibo T.A.
https://doi.org/10.1155/2022/9099163 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125857423&doi=10.1155%2f2022%2f9099163&partnerID=40&md5=d4a9c53be3a1e2f429be7b99cc39f93f
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
Brain image classification using time frequency extraction with histogram intensity similarity
Convolutional neural network; Differential deep learning; Histogram
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.
Renukadevi T.; Saraswathi K.; Prabu P.; Venkatachalam K.
Computer Systems Science and Engineering, Vol-41, No. 2, pp. 645-660.
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
Photocatalytic degradation of methylene blue and metanil yellow dyes using green synthesized zinc oxide (Zno) nanocrystals
Coconut husk extract; Photocatalysis; UV light; ZnO
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.
Priyadharshini S.S.; Shubha J.P.; Shivalingappa J.; Adil S.F.; Kuniyil M.; Hatshan M.R.; Shaik B.; Kavalli K.
https://doi.org/10.3390/cryst12010022 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121728734&doi=10.3390%2fcryst12010022&partnerID=40&md5=54ce5e8088f58d2c1e5ce42a0be840ae
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
The Impact of Website Design on Online Customer Buying Satisfaction and Loyalty to E-Tailers: An Exploratory Study of E-Tailers in India
Adoption; Customer satisfaction; E-commerce; Loyalty; Website design
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.
Chakraborty D.; Banerjee J.; Mehta P.; Singh N.P.
Information Resources Management Journal, Vol-35, No. 1
https://doi.org/10.4018/IRMJ.287902 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121416502&doi=10.4018%2fIRMJ.287902&partnerID=40&md5=953a4f121bb713271deacdb2d0256c96
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
(Mes-Acr-Me)+ClO4 Catalyzed Visible Light-Supported, One-Pot Green Synthesis of 1,8-Naphthyridine-3-Carbonitriles
1,8-Naphthyridines; 9-Mesityl-10-methylacridinium perchlorate; Blue LED; Excellent yield; Multicomponent reaction
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.
Tabassum S.; Govindaraju S.; Kendrekar P.
https://doi.org/10.1007/s11244-022-01583-9 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124739905&doi=10.1007%2fs11244-022-01583-9&partnerID=40&md5=5cc5bcf5db27657099ce3f95e39dfced
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
Financial well-being A Generation Z perspective using a Structural Equation Modeling approach
Financial behavior; Financial fragility; Financial literacy; Financial technology; India
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.
Investment Management and Financial Innovations, Vol-19, No. 1, pp. 32-50.
https://doi.org/10.21511/imfi.19(1).2022.03 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125864122&doi=10.21511%2fimfi.19%281%29.2022.03&partnerID=40&md5=7b08e2f62fb1f852534be99a5ae500ad
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
Derris Indica Leaves Extract as a Green Inhibitor for the Corrosion of Aluminium in Alkaline Medium
Aluminium corrosion; Derris indica; Green inhibitors; Potentiodynamic polarization studies
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
Nambiar N.K.; Brindha D.; Punniyakotti P.; Venkatraman B.R.; Angaiah S.
Engineered Science, Vol-17, pp. 167-175.
https://doi.org/10.30919/es8d540 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121988934&doi=10.30919%2fes8d540&partnerID=40&md5=40350c6aa067d93aa31a97cc561ec059
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
Consumer perception and factors influencing consumption of millets
Awareness; Consumption pattern; Factors; Kerala; Millet
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.
Journal of Tropical Agriculture, Vol-59, No. 2, pp. 177-182.
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
A short review on environmental impacts and application of iron ore tailings in development of sustainable eco-friendly bricks
Bricks; Eco-friendly; Environment; Iron ore tailings; Sustainable
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
Materials Today: Proceedings, Vol-61, pp. 327-331.
https://doi.org/10.1016/j.matpr.2021.09.522 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124264478&doi=10.1016%2fj.matpr.2021.09.522&partnerID=40&md5=e7ec9da2c1a2e5f9443b400b2546b852
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
Return and volatility spillover between India, UK, USA and European stock markets: The Brexit impact
Brexit referendum; Diversification; GARCH BEKK; Portfolio; Volatility transmission
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
Investment Management and Financial Innovations, Vol-19, No. 1, pp. 121-134.
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
The mathematical and machine learning models to forecast the COVID-19 outbreaks in Bangladesh
97M10; COVID-19; Epidemiology; FBProphet; Forecasting; Machine Learning; SARS-CoV-2; SEIRD
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.
Babu M.A.; Ahmmed M.M.; Ferdousi A.; Mostafizur Rahman M.; Saiduzzaman M.; Bhatnagar V.; Raja L.; Poonia R.C.
Journal of Interdisciplinary Mathematics, Vol-25, No. 3, pp. 753-772.
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
Mathematical foundations based statistical modeling of software source code for software system evolution
Bidirection encoders transformers; Knowledge graphs; Requirements management; Software development; Transfer learning
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.
Althar R.R.; Alahmadi A.; Samanta D.; Khan M.Z.; Alahmadi A.H.
Mathematical Biosciences and Engineering, Vol-19, No. 4, pp. 3701-3719.
American Institute of Mathematical Sciences
https://doi.org/10.3934/mbe.2022170 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124794243&doi=10.3934%2fmbe.2022170&partnerID=40&md5=57925132fd06f3bc9a526f681401319f
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
Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals
Brain signal; Brain-computer interface; Convolutional neural networks; Hand motion recognition; Machine learning
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.
Altameem A.; Sachdev J.S.; Singh V.; Poonia R.C.; Kumar S.; Saudagar A.K.J.
Computer Systems Science and Engineering, Vol-42, No. 3, pp. 1095-1107.
https://doi.org/10.32604/csse.2022.023256 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124945126&doi=10.32604%2fcsse.2022.023256&partnerID=40&md5=3e9a4ac7e2155cc4705f1e8f9b8b6b63
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
Juice Jacking: Security Issues and Improvements in USB Technology
Authentication; Cyber-attack; Hacker; Keystroke dynamics; Malicious code; Security; USB code
For a reliable and convenient system, it is essential to build a secure system that will be protected from outer attacks and also serve the purpose of keeping the inner data safe from intruders. A juice jacking is a popular and spreading cyber-attack that allows intruders to get inside the system through the web and theive potential data from the system. For peripheral communications, Universal Serial Bus (USB) is the most commonly used standard in 5G generation computer systems. USB is not only used for communication, but also to charge gadgets. However, the transferal of data between devices using USB is prone to various security threats. It is necessary to maintain the confidentiality and sensitivity of data on the bus line to maintain integrity. Therefore, in this paper, a juice jacking attack is analyzed, using the maximum possible means through which a system can be affected using USB. Ten different malware attacks are used for experimental purposes. Various machine learning and deep learning models are used to predict malware attacks. An extensive experimental analysis reveals that the deep learning model can efficiently recognize the juice jacking attack. Finally, various techniques are discussed that can either prevent or avoid juice jacking attacks. 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Singh D.; Biswal A.K.; Samanta D.; Singh D.; Lee H.-N.
Sustainability (Switzerland), Vol-14, No. 2
https://doi.org/10.3390/su14020939 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122918121&doi=10.3390%2fsu14020939&partnerID=40&md5=56901912d1f0dbfb066d5a7198c94f86
Singh D., Department of Computer Application, Institute of Technical Education and Research (ITER), Siksha OAnusandhan (SOA) Deemed to be University, Odisha, Bhubaneswar, 751030, India; Biswal A.K., Department of Computer Science and Engineering, Institute of Technical Education and Research (ITER), Siksha OAnusandhan (SOA) Deemed to be University, Odisha, Bhubaneswar, 751030, India; Samanta D., Department of Computer Science, CHRIST University, Karnataka, Bangalore, 560029, India; Singh D., School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, 61005, South Korea; Lee H.-N., School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, 61005, South Korea
Weakly nonlinear stability analysis of salt-finger convection in a longitudinally infinite cavity
This paper is a two-dimensional linear and weakly nonlinear stability analyses of the three-dimensional problem of Chang et al. ["Three-dimensional stability analysis for a salt-finger convecting layer,"J. Fluid Mech. 841, 636-653 (2018)] concerning salt-finger convection, which is seen when there is sideways heating and salting along the vertical walls along with a linear variation of temperature and concentration on the horizontal walls. A two-dimensional linear stability analysis is first carried out in the problem with the knowledge that the result could be different from those of a three-dimensional study. A two-dimensional weakly nonlinear stability analysis, that is, then performed points to the possibility of the occurrence of sub-critical motions. Stability curves are drawn to depict various instability regions. With the help of a detailed stability analysis, the stationary mode is shown to be the preferred one compared to oscillatory. Local nonlinear stability analysis of the system is done in a neighborhood of the critical Rayleigh number to predict a sub-critical instability region. The existence of a stable solution at the onset of a weakly nonlinear convective regime is indicated, allowing one to perform a bifurcation study in the problem. Heat and mass transports are discussed by analyzing the Nusselt number, Nu, and Sherwood number, Sh, respectively. A simple relationship is obtained between the Nusselt number and the Sherwood number exclusively in terms of the Lewis number, Le. 2022 Author(s).
Chou Y.-D.; Hwang W.-S.; Solovchuk M.; Siddheshwar P.G.; Sheu T.W.-H.; Chakraborty S.
https://doi.org/10.1063/5.0070705 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123755988&doi=10.1063%2f5.0070705&partnerID=40&md5=ff8da4b8c2d7d08134f3be2d1a0111ef
Chou Y.-D., Department of Engineering Science and Ocean Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 10617, Taiwan; Hwang W.-S., Department of Engineering Science and Ocean Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 10617, Taiwan; Solovchuk M., Institute of Biomedical Engineering and Nanomedicine, National Health Research Institute, No. 35, Keyan Road Zhunan, 35053, Taiwan; Siddheshwar P.G., Centre for Mathematical Needs, Department of Mathematics, CHRIST (Deemed to Be University), Bengaluru, 560029, India; Sheu T.W.-H., Department of Engineering Science and Ocean Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 10617, Taiwan; Chakraborty S., Department of Engineering Science and Ocean Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 10617, Taiwan