DDoS Intrusions Detection in Low Power SD-IoT Devices Leveraging Effective Machine Learning
subject: DDoS attacks; Decision making; Low power IoT; Machine learning; SDN
description: Security and privacy are significant concerns in software-defined networking (SDN)-applied Internet of Things (IoT) environments, due to the proliferation of connected devices and the potential for cyberattacks. Hence, robust security mechanisms need to be developed, including authentication, encryption, and distributed denial of service (DDoS) attack detection, tailored to the constraints of low-power IoT devices. Selecting a suitable tiny machine learning (TinyML) algorithm for low-power IoT devices for DDoS attack detection involves considering various factors such as computational complexity, robustness in dealing with heterogeneous data, accuracy, and the specific constraints of the target IoT device. In this paper, we present a two-fold approach for the optimal TinyML algorithm selection leveraging the hybrid analytical network process (HANP). First, we make a comparative analysis (qualitative) of the machine learning algorithm in the context of suitability for TinyML in the domain of SD-IoT devices and generate the weights of suitability for TinyML applications in SD-IoT. Then we evaluate the performance of the machine learning algorithms and validate the results of the model to demonstrate the effectiveness of the proposed method. Finally, we see the effect of dimensionality reduction with respect to features and how it affects the precision, recall, accuracy, and F1 score. The results demonstrate the effectiveness of the scheme. 1975-2011 IEEE.
creator: Ali J.; Song H.H.; Sharma V.; Al-Khasawneh M.A.
source: IEEE Transactions on Consumer Electronics
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 983063; CODEN: ITCED
format: Online
language: English
type: Article
coverage: Ali J., Ajou University, Department of Ai Convergence Network, Suwon, South Korea; Song H.H., Department of Information Systems, University of Maryland, Baltimore County (UMBC), 1000 Hilltop Circle, Baltimore, 21250, MD, United States; Sharma V., Christ University, India; Al-Khasawneh M.A., Skyline University College, University City Sharjah, School of Computing, Sharjah, 1797, United Arab Emirates, Applied Science Private University, Applied Science Research Center, Amman, Jordan, Jadara University Research Center, Jordan

Effect of Social Cognitive Skills Training (SCST) on Cognitive and Affective Theory of Mind in Adolescents
subject: adolescents; affective theory of mind; cognitive theory of mind; social cognition; Social cognitive skills training
description: Social cognitive skills training (SCST) in a therapeutic setup can result in more positive outcomes when incorporated with psychotherapy, especially among adolescents with minor social-cognitive impairments, and it may result in multifarious benefits to mitigate their social-cognitive dysfunction. This research focuses on the effect of SCST on the cognitive and affective theory of mind for adolescents with low social cognition. Quasi-experimental research with a pre-test-post-test design was used. Edinburgh Social Cognition test (ESCoT) was used for pre-and post-testing one week before and post-SCST training. The significant findings reveal a positive impact of SCST on the affective theory of mind and cognitive theory of mind in the experimental group. No significant changes were found in the control group (waitlisted). The results help validate the SCST module to improve an adolescents cognitive and affective theory of mind in social cognition. Further implications are discussed. 2024, Institute for Human Rehabilitation. All rights reserved.
creator: Jacob L.; Reddy J.
source: Human Research in Rehabilitation, Vol-14, No. 2, pp. 274-283.
publisher: Institute for Human Rehabilitation
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 22329935
format: Online
language: English
type: Article
coverage: Jacob L., Christ University, Bengaluru, India; Reddy J., Christ University, Bengaluru, India

A Quasi-Experimental Study on the Effectiveness of Integrated Electroencephalogram Neurofeedback Training and Group Psychotherapy for Harmful Alcohol Use: Neurocognitive and Clinical Outcomes
subject: craving; executive functions; harmful alcohol use; neurofeedback; psychotherapy; stress
description: Introduction. This study investigates the efficacy of integrating electroencephalogram (EEG) neurofeedback training and group psychotherapy for individuals with harmful alcohol use (AUDIT-10 scores 1013). Methods. Seventy-six participants were purposively sampled and divided into treatment (EEG neurofeedback training and group psychotherapy) and control groups. Baseline assessments measured alcohol consumption (AUDIT-10), stress (perceived stress scale [PSS]), neurocognition (NIMHANS neuropsychological battery), craving (PACS), and visual analog scale. The treatment group underwent 20 sessions of EEG neurofeedback (Peniston-Kulkosky and Scott-Kaiser modification protocols) and four sessions of group psychotherapy (motivational interviewing [MI], psychoeducation). Result/Discussion. A repeated measures ANOVA showed significant improvement in postcondition scores for the treatment group compared to controls, who exhibited deterioration over time. The study provides evidence supporting the efficacy of integrated EEG neurofeedback training and group psychotherapy in mitigating harmful alcohol use progression. Conclusion. By addressing stress, cognition, and cravings, this intervention offers crucial support to individuals with problematic drinking. 2024. Panicker et al.
creator: Panicker S.G.; George T.S.; Bennett C.N.
source: NeuroRegulation, Vol-11, No. 3, pp. 255-273.
publisher: International Society for Neurofeedback and Research
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 23730587
format: Online
language: English
type: Article
coverage: Panicker S.G., School of Psychological Sciences, Christ University, Bengaluru, India; George T.S., School of Psychological Sciences, Christ University, Bengaluru, India; Bennett C.N., School of Psychological Sciences, Christ University, Bengaluru, India

Control of chaos and intermittent periodic motions in Rayleigh-Bard convection using a feedback controller
subject: Chaos; Feedback controller; Meclaurin series; Periodic motion; Rayleigh-Bard convection
description: Control of regular convective motion, chaos and periodic motion in the Rayleigh-Bard system is studied by considering a feedback control mechanism that considers the dependence of the heating (cooling) of the two boundary plates on one another. This set up ensures that the different flow regimes (convective, chaotic and periodic) in the system have no mechanical interference and the control remains an external mechanism. The rheostatic influence of feedback control on these flows is demonstrated by investigating in detail the critical Rayleigh number in the case of regular convective motion and the Hopf-Rayleigh number in the case of chaotic motion. For mild coupling between lower and upper boundary temperatures, periodic motions are intermittently observed in an otherwise chaotic regime at times when the system arrives at a situation (fuelling zone) wherein it needs to conserve energy in order to sustain chaos at subsequent times. For strong coupling between the boundary temperatures, an interesting situation arises wherein chaos makes a delayed and brief appearance and gives way to a prolonged spell of periodic motion. Features of the classical Rayleigh-Bard system are retained but each regime makes a delayed appearance. The Author(s), under exclusive licence to Springer Nature B.V. 2024.
creator: Kanchana C.; Siddheshwar P.G.; Laroze D.
source: Nonlinear Dynamics
publisher: Springer Science and Business Media B.V.
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 0924090X; CODEN: NODYE
format: Online
language: English
type: Article
coverage: Kanchana C., Instituto de Alta Investigaci, Universidad de Tarapac Casilla 7 D, Arica, 1000000, Chile; Siddheshwar P.G., Centre for Mathematical Needs, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Laroze D., Instituto de Alta Investigaci, Universidad de Tarapac Casilla 7 D, Arica, 1000000, Chile

Assessing the Determinants of Metaverse Adoption for E-Commerce Retailing
subject: Metaverse shopping; PLS-SEM; sense of immersion; technological anxiety; UTAUT2
description: The advent of metaverse technology has impacted the retail sector, shaping e-commerce platforms into a new form of metaverse-based online shopping environments. The metaverse e-commerce experience is new to shoppers, making it crucial to comprehend consumer reactions to this technology in the context of retail. This study explores the shopping intention and potential use of the metaverse for shopping using the UTAUT2 model and metaverse-based context-specific antecedents. Using a structured questionnaire, data from 1340 consumers were collected and analyzed through PLS-SEM. The findings indicated that factors such as performance expectancy, effort expectancy, social influence, hedonic motivation, and facilitating conditions influence shopping intention in the e-commerce metaverse. The metaverse-related antecedents, namely, a sense of immersion and imagination, have a positive influence, whereas technological anxiety and perceived security and privacy concerns have a negative impact on e-commerce shopping intention in the metaverse. It was also found that shopping intention influences the potential use of metaverse for shopping and that stickiness to traditional shopping negatively moderates this relationship. This unique research explores consumer buying behavior in the metaverse. It provides marketers, e-commerce managers, designers, and developers of metaverse platforms with the antecedents of the potential use of the metaverse for shopping insights. Consumer policymakers can also draw insights from this study. 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.
creator: Pillai R.; Sivathanu B.; Rana N.P.; Struweg I.
source: Journal of Computer Information Systems
publisher: Taylor and Francis Ltd.
date: 2024-01-01
rights: All Open Access; Hybrid Gold Open Access
relation: ISSN: 8874417
format: Online
language: English
type: Article
coverage: Pillai R., Pune Institute of Business Management, Pune, India; Sivathanu B., Christ University, Bangalore, India; Rana N.P., Queens University Belfast, Belfast, United Kingdom, Chandragupt Institute of Management Patna, Bihar, India; Struweg I., University of Johannesburg, Johannesburg, South Africa

A Comparative Study of the Nonlinear Optical Properties of CaO Nanoparticles and rGO-CaO Nanocomposites
subject: Nanocomposites; Nonlinear optical properties; Reverse saturable absorption; Z-scan
description: Recently, graphene-based materials decorated with metal/metal oxide nanoparticles have gained significant interest among researchers owing to their wide range of technological applications. In this study, we synthesized reduced graphene oxide-calcium oxide nanocomposites (rGO-CaO) using a one-pot solvothermal technique. The third-order nonlinear optical (NLO) properties of CaO nanoparticles and (rGO-CaO) nanocomposites were explored by performing a single-beam Z-scan experiment. Since the samples exhibited reverse saturation absorption behavior (RSA) and a negative nonlinear index of refraction, CaO nanoparticles are promising candidates for nonlinear optical limiting and optical switching applications. Indian Association for the Cultivation of Science 2024.
creator: Rekha S.; Sreeja V.G.; Vinitha G.; Anila E.I.
source: Indian Journal of Physics
publisher: Springer
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 9731458
format: Online
language: English
type: Article
coverage: Rekha S., Department of Physics, Maharajas College, Kerala, Ernakulam, 68011, India; Sreeja V.G., Department of Physics, St. Teresas College (Autonomous), Kerala, Ernakulam, 68011, India; Vinitha G., Division of Physics, School of Advanced Sciences, VIT University, Chennai, 600127, India; Anila E.I., Christ (Deemed to Be University, Bangalore, 560029, India

Facial Expression Recognition Using Pre-trained Architectures
subject: CNN; facial expression recognition; FER2013; pre-trained architectures
description: In the area of computer vision, one of the most difficult and challenging tasks is facial emotion recognition. Facial expression recognition (FER) stands out as a pivotal focus within computer vision research, with applications in various domains such as emotion analysis, mental health assessment, and humancomputer interaction. In this study, we explore the effectiveness of ensemble methods that combine pre-trained deep learning architectures, specifically AlexNet, ResNet50, and Inception V3, to enhance FER performance on the FER2013 dataset. The results from this study offer insights into the potential advantages of ensemble-based approaches for FER, demonstrating that combining pre-trained architectures can yield superior recognition outcomes. 2024 by the authors.
creator: Reghunathan R.K.; Ramankutty V.K.; Kallingal A.; Vinod V.
source: Engineering Proceedings, Vol-62, No. 1
publisher: Multidisciplinary Digital Publishing Institute (MDPI)
date: 2024-01-01
rights: All Open Access; Hybrid Gold Open Access
relation: ISSN: 26734591
format: Online
language: English
type: Article
coverage: Reghunathan R.K., Department of Computer Science, CHRIST University, Bangalore, 560029, India; Ramankutty V.K., Department of Computer Science, CHRIST University, Bangalore, 560029, India; Kallingal A., Department of Computer Science, CHRIST University, Bangalore, 560029, India; Vinod V., Idea Elan India Pvt. Ltd., Hyderabad, 500082, India

Sexual violence in cyberspace: breaking the silence of international law
subject: breaking the silence; criminal law; cybersexual violence; cyberspace; international law; sexual violence
description: The increasing dependence of the world on digital technology and the internet has consequently led to the juxtaposition of the problematic social structure in online transactions and communications. This has resulted in increasing cases of cybersexual violence against women. The article argues that the effects of cybercrimes are transnational and, therefore, the traditional domestic criminal law is rather inept in preventing crime and punishing offenders. This increases the obligation of international law, which has so far remained silent on the issue. The articles conclusion suggests that the proposed World Convention on Cybercrime should include cybersexual violence as a core crime. This would serve as a beginning for addressing the threat, effect, and extent of the crime of cybersexual violence. The article concludes that the masculinist normative structure of international law is to blame for its culture of silence. Copyright 2024 Inderscience Enterprises Ltd.
creator: Shreya; Dev S.
source: International Journal of Public Law and Policy, Vol-10, No. 4, pp. 383-397.
publisher: Inderscience Publishers
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 20447663
format: Online
language: English
type: Article
coverage: Shreya, School of Law, Christ University, Karnataka, Bangalore, India; Dev S., School of Law, Christ University, Karnataka, Bangalore, India

Saraca asoca (Roxb.) de Wilde, a sacred tree: its nutritional value, elemental composition and anti-nutritional content
subject: antinutritional factors; elemental composition; nutritional; Saraca asoca
description: The sacred Saraca asoca (Roxb.) de Wilde tree holds significant medicinal value and is utilized in ayurvedic preparations to treat various health conditions. This research investigated the nutritional, elemental and antinutritional properties of S. asoca leaves and flowers. The nutritional qualities of the tree parts were examined using the muffle furnace and micro-Kjeldahl techniques. Titration techniques were used to assess the antinutritional content of plants, whereas EDX (Energy dispersive X-ray) was used to determine the mineral content. Phytochemical analysis revealed the presence of tannins, phenols and flavonoids, along with antioxidant properties that could neutralize free radicals generated by metabolic processes in the body. Nutritional analysis indicated that the floral parts of S. asoca had higher moisture, carbohydrate and crude fat content than the leaves. Conversely, the leaves had elevated ash levels, crude fiber and protein. Leaf samples showed higher concentrations of minerals like calcium, phosphorus, sodium, iodine, iron and manganese compared to the floral samples. In contrast, flower samples exhibited higher potassium, copper, silicon and zinc levels. These findings highlight the rich nutritional profile, abundant phytochemicals and essential minerals in both tree parts, with low anti-nutrient content. This information could be instrumental in developing phytopharmaceuticals and nutritious food products. Additionally, utilizing these tree parts could offer a cost-effective way to enhance nutrient intake and address nutritional deficiencies in humans and animals. Copyright: The Author(s).
creator: Suresh M.; Pappuswamy M.
source: Plant Science Today, Vol-11, No. 4, pp. 788-797.
publisher: Horizon e-Publishing Group
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 23481900
format: Online
language: English
type: Article
coverage: Suresh M., Department of Life Sciences, Christ Deemed to be University, Bengaluru, 560 029, India; Pappuswamy M., Department of Life Sciences, Christ Deemed to be University, Bengaluru, 560 029, India

Unveiling the therapeutic potential of azopyridine derivatives for trypsin inhibition: a DFT and In-Vitro approach
subject: Anti-inflammatory; anti-trypsin; azopyridine; pharmacophore; soft molecule
description: Heterocyclic azo derivatives have emerged as promising scaffolds for drug development. This study focused on the synthesis, computational analysis, and biological evaluation of a series of azopyridine derivatives (1a, 1d, 1 g, 1 h, 1 m, 1p, and 1s) as potential trypsin inhibitors. Density Functional Theory calculations indicated that derivative 1 h exhibited the lowest HOMO-LUMO energy gap 3.167 eV and was characterised as a soft molecule, suggesting strong binding capabilities. Molecular docking studies confirmed that 1 h binds favourably to the active site of trypsin with a glide score of ?6.581 kcal/mol and binding energy of ?29.95 kcal/mol. Along with docking studies, the stability of the trypsin-1 h complex was further analyzed using molecular dynamic simulations at 200 ns. The results showed that the ligand molecule 1 h bound strongly at the active site of trypsin. In-vitro enzyme assays determined the IC50 value of the molecule as 100 M, demonstrating enhanced potency. These results indicate that AzPy derivatives, particularly 1 h, hold considerable promise as therapeutic agents for inflammatory disorders and cancer, paving the way for further exploration in drug development and targeted therapies. Further research is warranted to explore 1hs efficacy, safety, and structure-activity relationships. Highlights: DFT studies were used to classify molecules based on their softness and hardness. Molecular docking, simulation, and in-vitro studies have identified potential anti-trypsin activity of candidate molecules. Experimental and computational calculations were in close agreement. 2024 Informa UK Limited, trading as Taylor & Francis Group.
creator: John A.M.; Suresh S.C.; Baby A.; Jayaram S.; Sarojini S.; Thomas R.; Balakrishnan S.P.
source: Molecular Physics
publisher: Taylor and Francis Ltd.
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 268976; CODEN: MOPHA
format: Online
language: English
type: Article
coverage: John A.M., Department of Chemistry, School of Sciences, Christ University, Bengaluru, India; Suresh S.C., Inter-University Centre for Bioscience and Department of Biotechnology & Microbiology, Kannur University, Kannur, India; Baby A., Department of Chemistry, School of Sciences, Christ University, Bengaluru, India; Jayaram S., Department of Life Sciences, School of Sciences, Christ University, Bengaluru, India; Sarojini S., Department of Life Sciences, School of Sciences, Christ University, Bengaluru, India; Thomas R., Department of Chemistry, St. Berchmans College (Autonomous), Changanassery, India; Balakrishnan S.P., Department of Chemistry, School of Sciences, Christ University, Bengaluru, India

AI-Based Feature Extraction Approaches for Dual Modalities of Autism Spectrum Disorder Neuroimages
subject: Artificial Intelligence; Autism Spectrum Disorder; Feature Extraction; Functional MRI; MRI; Structural MRI
description: High-dimensional data, lower detection accuracy, susceptibility to manual errors, and the requirement of clinical experts are some drawbacks of conventional classification models available for Autism Spectrum Disorder (ASD) detection. To address these challenges and explore the affiliated information from advanced imaging modalities such as Magnetic Resonance Imaging (MRI) in structural MRI (sMRI) and resting state-functional MRI (rs-fMRI), the study applied an Artificial Intelligence (AI) approach. In this context, AI is used to automate the feature extraction process, which is crucial in the interpretation of medical images for diagnosis. The work aims to apply AI-based techniques to extract the features and identify the impact of each feature in the Autism diagnosis. The morphometric features were extracted using sMRI images and rs-fMRI scans were employed to fetch functional connectivity features. Surface-based, region-based, and seed-based analyses are performed for the whole brain, followed by feature selection techniques such as Recursive Feature Elimination (RFE) with correlation, Principal Component Analysis (PCA), Independent Component Analysis (ICA), and graph theory are implemented to extract and distinguish features. The effectiveness of the extracted features was measured as classification accuracy. Support Vector Machine (SVM) with RFE is the best classification model, with 88.67% accuracy for high-dimensional data. SVM is a supervised learning model that outperforms other classification models due to its capability to handle high-dimensional data with a larger feature set. Medical imaging modalities provide detailed insights and visual differences related to various cognitive conditions that must be recognized accurately for efficient diagnosis. The study presented an empirical analysis of various Feature extraction approaches and the significance of the extracted features in high-dimensional data scenarios for Autism classification. 2024 Meenakshi M…
creator: Malviya M.; Chandra J.; Nagendra N.
source: Journal of Computer Science, Vol-20, No. 11, pp. 1495-1503.
publisher: Science Publications
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 15493636
format: Online
language: English
type: Article
coverage: Malviya M., Department of Computer Science Christ, Deemed to be University, Bangalore, India; Chandra J., Department of Computer Science Christ, Deemed to be University, Bangalore, India; Nagendra N., Department of Computer Science Christ, Deemed to be University, Bangalore, India

Influence of non-linear thermal radiation on the dynamics of homogeneous and heterogeneous chemical reactions between the cone and the disk
subject: artificial neural network; cone-disk apparatus; homogeneous and heterogeneous reactions; non-linear thermal radiation; ternary hybrid nanofluid
description: Purpose: The current work presents a theoretical framework to boost heat transmission in a ternary hybrid nanofluid with homogeneous and heterogeneous reactions in the conical gap between the cone and disk apparatus. Furthermore, the impacts of non-linear thermal radiation on the ternary hybrid nanofluid composed of white graphene, diamond, and titanium dioxide dispersed in water are analyzed. Originality/value: The combination of cone and disk systems is crucial for designing efficient heat exchange devices in the field of biomedical science for various purposes. For instance, in medical devices, the cone-disk apparatus is used to study the flow and heat transfer characteristics for better design and functionality. Hence, a sincere attempt has been made to study the impact of homogeneous and heterogeneous reactions on the nanofluid flow between the cone and disk in the presence of non-linear thermal radiation. Design/methodology/approach: The mathematical model's governing equations are partial differential equations (PDEs) which are then transformed into non-linear ordinary differential equations through appropriate similarity transformations. These transformed resultant equations are approximated by the Runge-Kutta-Fehlberg fourth/fifth order (RKF45) technique. The influence of essential aspects on the flow field, heat, and mass transfer rates was analyzed using a graphical representation. Findings: The interesting part of this research is to discuss the power of parameters in three cases, namely, (1) rotating cone/disk, (2) rotating cone/stationary disk, and (3) stationary cone/rotating disk. Furthermore, the thermal variation of the fluid is analyzed by an artificial neural network with the help of the Levenberg-Marquardt backpropagation algorithm. The regression analysis, mean square error, and error histogram of the neural network are analyzed using this algorithm. From the graph, it is perceived that the flow field climbed up significantly with an increase i…
creator: Manjunatha S.; Saadeh R.; Kuttan B.A.; Tanuja T.N.; Zaib A.; Khan U.; Ishak A.; Hussain S.M.
source: High Temperature Materials and Processes, Vol-43, No. 1
publisher: Walter de Gruyter GmbH
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 21910324; CODEN: HTMPE
format: Online
language: English
type: Article
coverage: Manjunatha S., Department of Mathematics, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560076, India; Saadeh R., Faculty of Science, Zarqa University, Zarqa, 13110, Jordan; Kuttan B.A., Department of Mathematics, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560076, India; Tanuja T.N., Department of Mathematics, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560076, India, Department of Mathematics, REVA University, Karnataka, Bengaluru, 560064, India; Zaib A., Department of Mathematical Sciences, Federal Urdu University of Arts, Science & Technology, Gulshan-e-Iqbal, Karachi, 75300, Pakistan; Khan U., Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia (UKM), Selangor, Bangi, 43600, Malaysia, Department of Mathematics, Faculty of Science, Sakarya University, Serdivan, Sakarya, 54050, Turkey, Department of Computer Science and Mathematics, Lebanese American University, Byblos, Lebanon, Department of Mechanics and Mathematics, Western Caspian University, Baku, 1001, Azerbaijan; Ishak A., Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia (UKM), Selangor, Bangi, 43600, Malaysia; Hussain S.M., Department of Mathematics, Faculty of Science, Islamic University of Madinah, Madinah, 42351, Saudi Arabia

Time Efficient Hash Key Generation for Blockchain Enabled Framework
subject: Blockchain; blockchain optimization; hashing; hashing function; hashing key; supply chain framework; supply chain lead time
description: Blockchain, in general, helps organizations to improve the transparency and governance by removing its shortfalls and building better control overall. Blockchain network, public or private, is a competent technology when used in order with an optimized hashing technique. In a blockchain network, one of the common issues is performance while registering any transactions. Blockchain must need to do some preliminary checks to avoid double-spending before registering the transaction. Here, we implement one of the optimization aspects of the hashing technique, which can contribute to the blockchain mining processes and save time. It enables the blockchain to perform efficiently and reliably. In addition, we examine how well different hashing algorithms perform when added to the blockchain network's processes. In this research, we analyze several hashing techniques that are employed in the blockchain and are also applied in the supply chain domain due to their efficacy in mitigating past attacks. Our proposed hashing technique allows a blockchain network to improve security and its overall processes. The proposed hashing technique achieves approx. 10-90% performance gain improvements over other existing technique. Our proposed hashing technique allows a blockchain network to improve security and its overall processes. The study also examines how the supply chain management contributes in increasing of overall lead time where process optimization or technological enhancement plays key roles in minimizing the time of some or all the processes. Lead time is one of the common issues of supply chain which impacts on overall order delivery time. We address on how the conjunction of blockchain with optimized hashing technique can address supply chain lead time issues. 2013 IEEE.
creator: Sinha S.K.; Mukhopadhyay D.
source: IEEE Access, Vol-12, pp. 155867-155884.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 21693536
format: Online
language: English
type: Article
coverage: Sinha S.K., Christ University, Department of Computer Science and Engineering, Bengaluru, 560074, India; Mukhopadhyay D., Christ University, Department of Computer Science and Engineering, Bengaluru, 560074, India

EVALUATION OF THE ENVIRONMENTAL EFFECTS OF MEDICAL WASTE AND ITS INCREASE AFTER COVID-19 PANDEMIC
subject: environmental impact; groundwater pollution; hazardous waste; heavy metals and mitigation strategies; improper disposal; medical waste; public health
description: Medical waste is a special course of harmful contaminants. Improper treatment would cause tributary environmental pollution, expressly when countering to communal health tragedies. However, there are quite few explores on the peer group of medical waste, and there is a deficiency of basic considerate of its spatial-temporal heterogeneity. The purpose of this study is to conduct a systematic estimation of the effectiveness of these incongruous discarding procedures in expressions of water eminence and wellbeing. The research is centred on municipal areas characterised by vital medical waste production, which has the probable to taint groundwater and water sources. A complex approach is exploited in the procedure, which comprises of water sample collection, laboratory analysis, field surveys, and GIS-based spatial mapping. Medical waste disposal hotspots, such as healthcare facilities, waste collection points, and disposal sites, will be acknowledged through field surveys. Inspects will be showed on water samples poised from a variability of sources, including lakes, rivers, and groundwater wells, to find pathogens, medical residues, heavy metals, and organic pollutants, which are all gauges of medical waste contamination. The test centre analysis will utilise chic policies to portion the deliberation of pollutants in water samples, thereby gauging the likely hazards they pose to marine ecosystems and human health. Longitudinal visualisation of uncleanness distribution through GIS-based mapping facilitates the credentials of vulnerable areas and potential pathways for pollutant transport. The findings of this research will offer significant helps to our understanding of the extent of environmental deterioration resulting from the inadequate disposal of medical refuse into urban water sources. The results of this study will provide valuable insights for the creation of alertness campaigns, regulatory frameworks, and mitigation strategies that are operative in talking t…
creator: Sharma B.; Sailaja M.; Bansal R.; Soujanya K.; Nerlekar T.; Acharjee P.B.; Rajagopal R.
source: Journal of Environmental Protection and Ecology, Vol-25, No. 6, pp. 1833-1845.
publisher: Scibulcom Ltd.
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 13115065
format: Online
language: English
type: Article
coverage: Sharma B., Geeta University, Panipat, India; Sailaja M., Department of CSE, Ravindra College of Engineering for Women, Kurnool, India; Bansal R., Department of Mittal School of Business, Lovely Professional University, Punjab, Phagwara, India; Soujanya K., Department of BBA, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, Guntur, India; Nerlekar T., Department of Civil Engineering, Dr. D. Y. Patil Institute of Technology, Pimpri, Pune, India; Acharjee P.B., Department of Computer Science, CHRIST University, Bangalore, India; Rajagopal R., Department of Computer Science and Engineering, Alliance School of Advanced Computing, Alliance University, Karnataka, Bengaluru, India

Is carbon neutrality a reality for India?
description: India, the third-largest carbon dioxide emitter in the world, aims to achieve zero emissions by 2070. India is committed to its Panchamrit and has launched various initiatives such as green bonds, carbon credits, carbon market, investing in green hydrogen, etc. However, given the present scenario with respect to the dependency on coal-based power generation and lack of green financing, the present article assesses the different solutions and their practicality in achieving carbon neutrality. (2024), (Indian Academy of Sciences). All rights reserved.
creator: Banerjee S.; Tayal Y.
source: Current Science, Vol-127, No. 8, pp. 895-897.
publisher: Indian Academy of Sciences
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 113891; CODEN: CUSCA
format: Online
language: English
type: Article
coverage: Banerjee S., Department of Economics, CHIRST (Deemed to be University), Bengaluru, 560 029, India; Tayal Y., Department of Economics, CHIRST (Deemed to be University), Bengaluru, 560 029, India

A stakeholder theory approach to analysing strategies for improving pandemic vaccine supply chain performance
subject: COVID-19; healthcare organisations; hospitals; strategies; vaccine supply chain; vaccine supply chain performance; VSC
description: This study aims to formulate strategies that impact the vaccine supply chain (VSC). This study measures the VSC performance using the proposed strategy concerning stakeholders theory. From the literature review and experts consent, the strategies are classified into six broad strategies as-VSC traceability, VSC visibility, VSC velocity, digitalising VSC, localising VSC, and vaccine inventory. A questionnaire is developed for surveying healthcare organisations and hospitals. All six proposed hypotheses got accepted. The developed model satisfies all the model fit parameters. Strategies like VSC traceability, VSC visibility, VSC velocity, digitalising VSC, localising VSC, and vaccine inventory have positively impacted vaccine supply chain performance. This research will be helpful for healthcare professionals and organisations for the faster delivery of the vaccine. This research will also help policymakers in improving the performance of VSC. This study is also the first to use the stakeholder theory approach for measuring VSC performance. Copyright 2024 Inderscience Enterprises Ltd.
creator: Baral M.M.; Mukherjee S.; Nagariya R.; Chittipaka V.
source: International Journal of Productivity and Quality Management, Vol-43, No. 2, pp. 181-201.
publisher: Inderscience Publishers
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 17466474
format: Online
language: English
type: Article
coverage: Baral M.M., Department of Operations, GITAM School of Business, GITAM (Deemed to be University), Andhra Pradesh, Visakhapatnam, India; Mukherjee S., Department of Operations, GITAM School of Business, GITAM (Deemed to be University), Andhra Pradesh, Visakhapatnam, India; Nagariya R., School of Business and Management, CHRIST (Deemed to be University), Delhi-NCR, Uttar Pradesh, Ghaziabad, India; Chittipaka V., School of Management Studies, Indira Gandhi National Open University, Delhi, India

Bivariate iterated FarlieGumbelMorgenstern stressstrength reliability model for Rayleigh margins: Properties and estimation
subject: dependence stressstrength; Iterated FGM; Monte-Carlo simulation; Rayleigh distribution; reliability
description: In this paper, we propose bivariate iterated FarlieGumbelMorgenstern (FGM) due to[Huang and Kotz (1984). Correlation structure in iterated Farlie-Gumbel-Morgenstern distributions. Biometrika 71(3), 633636. https://doi.org/10.2307/2336577] with Rayleigh marginals. The dependence stressstrength reliability function is derived with its important reliability characteristics. Estimates of dependence reliability parameters are obtained. We analyse the effects of dependence parameters on the reliability function. We found that the upper bound of the positive correlation coefficient is attaining to 0.41 under a single iteration with Rayleigh marginals. A comprehensive comparison between classical FGM with iterated FGM copulas is graphically examined to assess the over or under estimation of reliability with respect to ? and ?. We propose a two-phase estimation procedure for estimating the reliability parameters. A Monte-Carlo simulation study is conducted to assess the finite sample behaviour of the proposed reliability estimators. Finally, the proposed estimators are examined and validated with real data sets. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
creator: Chandra N.; James A.; Domma F.; Rehman H.
source: Statistical Theory and Related Fields, Vol-8, No. 4, pp. 315-334.
publisher: Routledge
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 24754269
format: Online
language: English
type: Article
coverage: Chandra N., Department of Statistics, Ramanujan School of Mathematical Sciences, Pondicherry University, Puducherry, India; James A., Department of Statistics and Data Science, CHRIST University, Bengaluru, India; Domma F., Department of Economics, Statistics and Finance Giovanni Anania, University of Calabria, CS, Arcavacata of Rende, Italy; Rehman H., Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States

Ergos: redefining storage infrastructure and market access for small farmers in India
subject: Agriculture value chain; AgriTech; AgriTech ecosystem; Business development; Digital farming; Enterprise resource planning; Entrepreneurial skills; Entrepreneurship; Ergos; Grainbank; India; Tech entrepreneurship
description: Learning outcomes: After completion of the case study, students will be able to analyse the path of the entrepreneurship from idea generation to market development to scaling up business, examine the impact of start-ups like Ergos on Indias agriculture value chain, discuss the challenges faced by tech entrepreneurs in growing a business, identify problems solved by Grain Bank Model and evaluate digitisation of farmings custodial services such as warehousing, market linkages and loans. Case overview/synopsis: The case study discusses how founders of Ergos, India-based leading digital AgriTech start-up, Kishor Kumar Jha and Praveen Kumar, started one of the unique models in the AgriTech landscape in India. After noticing the grim condition of small and marginal farmers in Bihar, India. Kishor and Praveen decided to put their banking and corporate experience to use in the farming sector. Ergos aimed to empower farmers by providing them with a choice on when, how much quantity, and at what price they should sell their farm produce, thus maximising their income. As a result, Ergos launched the grain bank model, which provided farmers with doorstep access of end-to-end post-harvest supply chain solutions by leveraging a robust technology platform to ensure seamless service delivery. Ergos faced many challenges in its journey related to financing, marketing and distribution. Amidst these developments, it remained to be seen how Kishor and Praveen would be able to realise their goal to serve over two million farmers across India by 2025 and create a sustainable income for them through its GrainBank Platform. Complexity academic level: This case study was written for use in teaching graduate and postgraduate management courses in entrepreneurship and business strategy. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 3: Entrepreneurship 2024, Emerald Publishing Limited.
creator: Kumari S.; Vineeth M.
source: Emerald Emerging Markets Case Studies, Vol-14, No. 4, pp. 1-39.
publisher: Emerald Publishing
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 20450621
format: Online
language: English
type: Article
coverage: Kumari S., Department of Economics, Faculty of Humanities and Social Sciences, Christ (Deemed to be University), Bengaluru, India; Vineeth M., Department of Economics, Faculty of Humanities and Social Sciences, Christ (Deemed to be University), Bengaluru, India

An Efficient Technique for One-Dimensional Fractional Diffusion Equation Model for Cancer Tumor
subject: cancer tumor model; Caputo-fractional derivative; Laplace transforms; q-homotopy analysis transform method
description: This study intends to examine the analytical solutions to the resulting one-dimensional differential equation of a cancer tumor model in the frame of time-fractional order with the Caputo-fractional operator employing a highly efficient methodology called the q-homotopy analysis transform method. So, the preferred approach effectively found the analytic series solution of the proposed model. The procured outcomes of the present framework demonstrated that this method is authentic for obtaining solutions to a time-fractional-order cancer model. The results achieved graphically specify that the concerned paradigm is dependent on arbitrary order and parameters and also disclose the competence of the proposed algorithm. 2024 The Authors.
creator: Archana D.K.; Prakasha D.G.; Veeresha P.; Nisar K.S.
source: CMES - Computer Modeling in Engineering and Sciences, Vol-141, No. 2, pp. 1347-1363.
publisher: Tech Science Press
date: 2024-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 15261492
format: Online
language: English
type: Article
coverage: Archana D.K., Department of Mathematics, Davangere University, Davangere, 577007, India; Prakasha D.G., Department of Mathematics, Davangere University, Davangere, 577007, India; Veeresha P., Center for Mathematical Needs, Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Nisar K.S., Department of Mathematics, College of Science and Humanities in Alkharj, Prince Sattam bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia, Saveetha School of Engineering, SIMATS, Chennai, 602105, India

https://archives.christuniversity.in/items/show/13496
title: Novel HGDBO: A Hybrid Genetic and Dung Beetle Optimization Algorithm for Microarray Gene Selection and Efficient Cancer Classification; [Nuevo HGDBO: Un Algoritmo Hrido de Optimizaci Genica y de Escarabajos Peloteros para la Selecci de Genes en Microrrays y la Clasificaci Eficiente del Ccer]
subject: Dung Beetle Optimization; Evolutionary Computation; Gene Feature Selection; Genetic Algorithm; Hybrid Algorithm; Microarray Data
description: Introduction: ovarian cancer ranked as the seventh most common cancer and the eighth leading cause of cancer-related mortality among women globally. Early detection was crucial for improving survival rates, emphasizing the need for better screening techniques and increased awareness. Microarray gene data, containing numerous genes across multiple samples, presented both opportunities and challenges in understanding gene functions and disease pathways. This research focused on reducing feature selection time in large gene expression datasets by applying a hybrid bio-inspired method, HGDBO. The goal was to enhance classification accuracy by optimizing gene subsets for improved gene expression analysis. Method: the study introduced a novel hybrid feature selection method called HGDBO, which combined the Dung Beetle Optimization (DBO) algorithm with the Genetic Algorithm (GA) to improve microarray data analysis. The HGDBO method leveraged the exploratory strengths of DBO and the exploitative capabilities of GA to identify relevant genes for disease classification. Experiments conducted on multiple microarray datasets showed that the hybrid approach offered superior classification performance, stability, and computational efficiency compared to traditional methods. Ovarian cancer classification was performed using Nae Bayes (NB) and Random Forest (RF) algorithms. Results and Discussion: the Random Forest model outperformed the Nae Bayes model across all metrics, achieving higher accuracy (0,96 vs. 0,91), precision (0,95 vs. 0,91), recall (0,97 vs. 0,90), F1 score (0,95 vs. 0,91), and specificity (0,97 vs. 0,86). Conclusions: these results demonstrated the effectiveness of the HGDBO method and the Random Forest classifier in improving the analysis and classification of ovarian cancer using microarray gene data. 2024; Los autores.
creator: Alluri V.L.; Kanadam K.P.; Helen Josephine V.L.
source: Data and Metadata, Vol-3
publisher: Editorial Salud, Ciencia y Tecnologia
date: 2024-01-01
rights: Restricted Access
relation: ISSN: 29534917
format: Online
language: English
type: Article
coverage: Alluri V.L., Acharya Nagarjuna University, Department of Computer Science and Engineering, AP, Guntur, India; Kanadam K.P., R.V.R & J.C. College of Engineering, Department of Computer Applications, AP, Guntur, India; Helen Josephine V.L., Christ University, Business Analytics, School of Business and Management, Karnataka, Bangalore, India