Exploring the Balance Between Automated Decision-Making and Human Judgment in Managerial Contexts
Artificial intelligence; Machine learning; Managerial decision-making
The study delves into the dynamic and evolving discussion surrounding the balance between automated and human judgment within the realm of managerial decision-making. The primary objective of this research is to gain insight into how AI is evolving to mitigate ethical biases that are inherent in managerial decision-making. To accomplish this goal, the study adopts a theoretical approach, supported by qualitative analysis through an extensive review of existing literature. By systematically investigating AI techniques for managerial decision-making, the research contributes to a broader understanding of how AI is progressing to promote ethically sound managerial decisions in future. The findings from this study are pertinent to business leaders, policymakers, and researchers, offering guidance as they navigate the intricate relationship between automation and human judgment in todays managerial landscape. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Lecture Notes in Networks and Systems, Vol-946, pp. 159-167.
Springer Science and Business Media Deutschland GmbH
Alex V.P., CHRIST (Deemed to be University), Bengaluru, India; Anirudh H.V., CHRIST (Deemed to be University), Bengaluru, India; Siby A., CHRIST (Deemed to be University), Bengaluru, India
Tertiary Packaging Issues and Their Influence on Repurchase Intention and Loyalty of Customers Towards E-Retailers
his thesis investigates the significance of tertiary packaging in the context of e-retail business and its influence on customer preference, repurchase intention, and loyalty towards e-retailers. With the rapid growth of e-retail, it is expected to become the dominant form of retail worldwide, surpassing traditional brick and mortar establishments. While e-retail offers convenience and flexibility to customers, intensifying competition among e- retailers raises concerns about how they will effectively manage it. As e- retailers resort to increased marketing efforts to attract customers, certain aspects, including tertiary packaging, may be inadvertently overlooked. Tertiary packaging plays a critical role in the e-retail process, and this study analyses its impact on customer perception and satisfaction. By exploring the issues related to tertiary packaging that affect customers, this research aims to provide insights to e-retailers for developing a more efficient and sustainable tertiary packaging model. The anticipated outcomes of this research are expected to enhance e-retailers' ability to attract customers, increase repurchase intention, and foster loyalty towards the e-retailer, ultimately contributing to their long-term success in the evolving e-commerce landscape.
Endurance and Evolution: Exploring Levels of Resilience Among Indian Breast Cancer Survivors
breast cancer; India; phenomenology; posttraumatic growth; quality of life; resilience; trauma
Resilience for Indian women with breast cancer involves maintaining positivity and adaptability amid the complex challenges affecting their physical, emotional, and social well-being. However, research focused on resilience amongst this population in Indian settings is limited. Therefore, the aim of the study is to explore the experience of levels, patterns, and processes of resilience in Indian women living with breast cancer. A qualitative phenomenological approach was used to study resilience. Thirty-three participants from two hospitals underwent semistructured interviews, including survivors, women in cancer therapy, and family members. Data collected via audio recordings were analyzed using reflective thematic analysis techniques. The finding describes four themes of experience of resilience in women living with breast cancer. (a) Cancer diagnosis is a life-changing experience. Breast cancer diagnosis and therapy cause existential crisis, psychological distress, and social stigma. (b) Restoring healthy perception in an adverse event. Navigating challenges and achieving a balance between internal and external factors. (c) Types of supportthe pathway to resilience. Enhanced their resilience through internal support including attributes, past experiences, sociodemographic factors, and brain fitness. External support includes family, friends, religious or spiritual advisors, medical care, role models, other cancer survivors, and comfortable environments. (d) Learning and growing from the experience. Gained a better perspective on life, ultimately resulting in a new normal and finding meaning in the experience. Data show breast cancer survivors experience dynamic resilience, highlighting the need for culturally tailored interventions and supportive avenues within cancer care by healthcare providers and policymakers. The Author(s) 2024.
Alexander A.; Kuruveettissery S.; Ramesh R.S.; Srinath B.S.; Appachu S.; Thippeswamy R.
Alexander A., Department of Psychology, CHRIST (Deemed to be University), Bengaluru, India, Division of Molecular Medicine, St John's Research Institute, St John's Medical College, Bengaluru, India; Kuruveettissery S., Department of Psychology, CHRIST (Deemed to be University), Bengaluru, India; Ramesh R.S., Department of Surgical Oncology, St. John's Medical College, Bengaluru, India; Srinath B.S., Sri Shankar Cancer Hospital and Research Centre, Bengaluru, India; Appachu S., Sri Shankar Cancer Hospital and Research Centre, Bengaluru, India; Thippeswamy R., Sparsh Hospital, Bengaluru, India
Beyond numbers - Recent understanding of emotional needs of persons diagnosed with cancer 2007-2018
Epidemiology; prevalence; psycho-oncology India; two-stage study
Epidemiology is a vital tool of public health. The usefulness of epidemiology is not only about numbers of persons' ill in the community but also to understand the associations, the presentation, identification of new syndromes, to map the historical trends, and calculate morbid risk. The emotional impact of the diagnosis of cancer is well-recognized. Indian cancer research relating to the psychosocial aspects has been largely limited to counting the numbers with psychiatric syndromes. The review covers 12 years of the Indian research in psycho-oncology to understand the different aspects of epidemiology. During the review period, there are growing number of epidemiological studies (29); psychiatric morbidity ranges from 41.7% to 46%; and prevalence rate ranges from 4.4% to 97.8% for anxiety and 1.2%-89.9% for depression; majority of the studies have used one-stage screening for assessment, which is not the ideal method of identifying mental disorders. The severity of the disorders is presented only in nine studies. Quality of life is the most common associated dimension of the studies. There is the absence of studies of posttraumatic growth, resilience, and spirituality. This review calls for greater rigor in the planning of studies of emotional impact, especially the use of two-stage method, longitudinal studies, studies of different types of cancer and in different stages, include additional measures such as disease burden, coping, resilience, spirituality, and the family/social factors to understand the emotional aspects of living with cancer. There is a need for describing the emotional aspects of living with cancer (lived-in experiences) beyond the clinical syndromes. 2020 Indian Journal of Palliative Care.
Alexander A.; Sreenath K.; Srinivasa Murthy R.
Indian Journal of Palliative Care, Vol-26, No. 1, pp. 120-128.
All Open Access; Gold Open Access; Green Open Access
https://doi.org/10.4103/IJPC.IJPC_86_19 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079403561&doi=10.4103%2fIJPC.IJPC_86_19&partnerID=40&md5=22877ad23892e4677623c17e7ae66744
Alexander A., Department of Psychology, CHRIST, Deemed to Be University, India, Division of Molecular Medicine, St John's Research Institute, 100 Feet Road John Nagar, Koramangala, Bengaluru, Karnataka, 560 034, India; Sreenath K., Department of Psychology, CHRIST, Deemed to Be University, India; Srinivasa Murthy R., Mental Health Consultant, SVMS -Palliative Care, Mysuru, Karnataka, India
Determinants of Quality of Life in Women with Breast Cancer: A Systematic Review
Breast cancer; Breast cancer treatment and management; Quality of life
The morbidity and mortality rates associated with breast cancer are a major public health concern globally. The resulting impairment in the patients quality of life (QOL) affects their health, symptoms, and well-being in physical, social, psychological, environmental, and sexual functioning. The aim of this study was to systematically review the literature addressing the determinants of QOL in breast cancer patients. A search of 6 electronic medical databases was undertaken. Employing a rigorous systematic protocol, eligible articles were analyzed and a total of 22 studies that met all eligibility criteria were included in the systematic review. The total sample size was 7,041 women ranging from 30 to 66 years. The determinants of QOL were found to cluster into 10 areas. These include the degree of pain, type and stage of cancer treatment, medical health, cognitive and behavioural factors, emotional health, physical activity and appearance, social factors, age and menopausal status, education and employment status, and ethnicity and religion. The types of breast cancer treatment and psychological parameters were the most common determinants of QOL in breast cancer patients. These insights can help formulate proactive interventions that can be used by patients, caregivers, and healthcare professionals to build protective capacities and alleviate challenges to ensure superior quality of life in women with breast cancer. 2022,Journal of International Women''s Studies. All Rights Reserved.
Alexander A.E.; Da Costa E.L.; Rema M.K.
Journal of International Women's Studies, Vol-24, No. 7
Alexander A.E., Christ University, India; Da Costa E.L., Dept. of Neurology at AIIMS, New Delhi, India; Rema M.K., Kristu Jayanti College (Autonomous), India
Interventions for the improvement of social skills in autism spectrum disorder in India: A systematic review
Autism spectrum disorder; Intervention; Social skills
Background: The increasing prevalence of Autism Spectrum Disorders (ASD) in India is in a gaping contrast with the existing interventions in India. Though several interventions have proved their efficiency in foreign countries, such studies within India are scarce. Aims: This review attempts to systematically examine the different intervention practices that include improvement of social skills in ASD that is practiced in India as revealed through published literature on the same. Methods: Studies published from 2000 to 2020 were selected for the study. Evidence is presented for nine treatment categories: Behavior-based interventions, Developmental Interventions, TEACHH approach, Parent-mediated Interventions, speech-based Interventions, electronics-based interventions, augmentative and alternative communication, play-based interventions and Yoga-based interventions. These studies were drawn from databases Ebsco, Proquest, PubMed, MEDLINE, science direct and Google Scholar. Though a definitive conclusion cannot be drawn without a meta-analysis, the available evidence is gathered and evaluated in the present review. Results: The review has proved to be a reliable summary of the interventions that include improvement of social skills in ASD that is practiced in India. Conclusions: Parent-mediated interventions may be more appropriate for the resource-poor settings of India, when developmental interventions may be more appropriate for the resourcerich settings of India. The scarcity of published literature on the topic in India is also a significant factor that highlighted itself through the research. 2021, Indian Association for Child and Adolescent Mental Health. All rights reserved.
Alexander A.E.; Padmakumari P.; Padavan I.D.
Journal of Indian Association for Child and Adolescent Mental Health, Vol-17, No. 2, pp. 178-203.
Indian Association for Child and Adolescent Mental Health
Alexander A.E., Department of Psychology, Christ (Deemed to be University), Bengaluru, India; Padmakumari P., Department of Psychology, Christ (Deemed to be University), Bengaluru, India; Padavan I.D., Auxillium School, Bengaluru, India
Online Education and English Language Learning Among Tribal Students of Kerala
Kerala, a South Indian state has tribal population in all her districts. About 1.5% of the total population of the state constitute tribal population. They depend upon natural environment and resources for their survival. Children from the same community usually depend on government funded schools for their education. Education for this deprived section during COVID 19 Pandemic was a massive exclusion and an uphill task. Digital divide and medium of communication (Standard Malayalam) were some of the critical concerns to knowledge acquisition among tribal children. This paper primarily focuses on the challenges of online education among tribal students with a clear emphasis on the English language acquisition. This study was conducted in four most tribal populated districts of the State, namely, Wayanad, Malappuram, Palakkad, and Idukki. This is a qualitative explorative study that explores the experiences of the tribal students' English language learning challenges from the teachers' perspective in these districts. The Electrochemical Society
ECS Transactions, Vol-107, No. 1, pp. 19453-19457.
https://doi.org/10.1149/10701.19453ecst https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134040868&doi=10.1149%2f10701.19453ecst&partnerID=40&md5=28673fb73c3fd3875212f955bfa58673
Alexander M.M., Department of English Studies, CHRIST (Deemed to be University), India; John C., Department of Sociology and Social Work, CHRIST (Deemed to be University), India; Babu K.S., Department of English Studies, CHRIST (Deemed to be University), India
Effectiveness of emotion recognition training on social and emotional skills in young children with autism spectrum disorder
The rising prevalence of Autism Spectrum Disorders necessitates the determination of novel intervention methods for its management. Since deficits in social skills are one of the most prominent features in ASD, efficient interventions for improving social skills become necessary. Several studies suggest a strong relationship between emotional skills and the acquisition of social skills. Objectives: The objective of this study was to find out the effectiveness of emotion recognition training on the social and emotional skills of children with ASD by obtaining quantitative results from the participants after emotion recognition training and then following up in-depth through a qualitative thematic analysis after interview with selected parents of the participants. Method: In the quantitative phase, a sample of ten children within three to six years of age who are diagnosed with ASD were selected for the study. The emotion recognition training followed the modified and adapted version of the hands-on activities from the ‘Let’s Face It’ curriculum which was validated after a pilot study. Each child was given 20 to 30 sessions of training. The participants were assessed for their social skills using VABS-3 and emotional skills were assessed using CDDC, before, during, and after the training. The qualitative phase involved an interview with the parent using a semi-structured guide. Results: The quantitative and qualitative results indicated that there is a significant difference in the social skills and emotional skills of the children after the training. The results also showed a sufficient generalization of the skills achieved. Incidental finding revealed reduction of problem behaviours. Conclusions: The study clearly shows that emotion recognition training is effective in improving social and emotional skills in children with ASD.
Effectiveness of emotion recognition tranining on socail and emotional skills in young children with autism spectrum disorder
The rising prevalence of Autism Spectrum Disorders necessitates the determination of newlinenovel intervention methods for its management. Since deficits in social skills are one of the most prominent features in ASD, efficient interventions for improving social skills become necessary. Several studies suggest a strong relationship between newlineemotional skills and the acquisition of social skills. Objectives: The objective of this study was to find out the effectiveness of emotion recognition training on the social newlineand emotional skills of children with ASD by obtaining quantitative results from the newlineparticipants after emotion recognition training and then following up in-depth through a qualitative thematic analysis after interview with selected parents of the participants. Method: In the quantitative phase, a sample of ten children within three to six years of age who are diagnosed with ASD were selected for the study. The emotion newlinerecognition training followed the modified and adapted version of the hands-on newlineactivities from the Let s Face It curriculum which was validated after a pilot study. Each child was given 20 to 30 sessions of training. The participants were assessed for their social skills using VABS-3 and emotional skills were assessed using CDDC, newlinebefore, during, and after the training. The qualitative phase involved an interview with newlinethe parent using a semi-structured guide. Results: The quantitative and qualitative newlineresults indicated that there is a significant difference in the social skills and emotional newlineskills of the children after the training. The results also showed a sufficient newlinegeneralization of the skills achieved. Incidental finding revealed reduction of problem behaviours. Conclusions: The study clearly shows that emotion recognition training is effective in improving social and emotional skills in children with ASD.
Educational Achievement of Socially and Economically Disadvantaged Children from Urban Slums of Bengaluru City
In the Indian context, marginalized and oppressed individuals often reside in slums newlineand on the streets, facing poor living conditions and inadequate facilities. While newlineurban areas boast elite lifestyles characterized by high levels of educational newlineattainment, access to the latest technologies, and substantial incomes, marginalized groups experience a significant lack of basic living standards and encounter limited access to essential services such as education, healthcare, and employment newlineopportunities. Education, in particular, poses one of the greatest challenges in slum newlineareas. Various factors, including socio-economic background, family characteristics, newlineand educational opportunities, can influence the academic performance of slum children. Additionally, teachers perceptions and classroom practices play crucial roles. The current study aims to explore how family characteristics, socio-economic background, educational opportunities, and teachers perceptions impact the educational achievements of slum children in Bengaluru city. To investigate educators perspectives on socially and economically disadvantaged children, a questionnaire was administered to teachers. The study utilized a mixed-method newlineresearch design to address its research questions. Quantitative data were collected newlinefrom 100 slum children and 100 non-slum children aged 6 to 14 years. During semistructured interviews, the researcher used an open-ended questionnaire to gather newlineresponses from principals and teachers. Thirty-six teachers working with various newlineschool boards in the Byrasandra and Siddapura areas were included in this study. newlineAdditionally, class observations were conducted to assess classroom interactions, the rapport between teachers and students, and levels of student involvement. A newlinepurposive random sampling technique was employed to select participants from the newlinestudy population. Data were meticulously collected and analyzed.
Spoofing Face Detection Using Novel Edge-Net Autoencoder for Security
auto-encoder; digital security; edge detection; edge net; face authentication; Image processing
Recent security applications in mobile technologies and computer systems use face recognition for high-end security. Despite numerous security tech-niques, face recognition is considered a high-security control. Developers fuse and carry out face identification as an access authority into these applications. Still, face identification authentication is sensitive to attacks with a 2-D photo image or captured video to access the system as an authorized user. In the existing spoofing detection algorithm, there was some loss in the recreation of images. This research proposes an unobtrusive technique to detect face spoofing attacks that apply a single frame of the sequenced set of frames to overcome the above-said problems. This research offers a novel Edge-Net autoencoder to select convoluted and dominant features of the input diffused structure. First, this pro-posedmethodistestedwiththeCross-ethnicityFaceAnti-spoofing (CASIA), Fetal alcohol spectrum disorders (FASD) dataset. This database has three models of attacks: distorted photographs in printed form, photographs with removed eyes portion, and video attacks. The images are taken with three different quality cameras: low, average, and high-quality real and spoofed images. An extensive experimental study was performed with CASIA-FASD, 3 Diagnostic Machine Aid-Digital (DMAD) dataset that proved higher results when compared to existing algorithms. 2023, Tech Science Press. All rights reserved.
Alharbi A.H.; Karthick S.; Venkatachalam K.; Abouhawwash M.; Khafaga D.S.
Intelligent Automation and Soft Computing, Vol-35, No. 3, pp. 2773-2787.
All Open Access; Hybrid Gold Open Access
https://doi.org/10.32604/iasc.2023.030763 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137350144&doi=10.32604%2fiasc.2023.030763&partnerID=40&md5=a2d99d8905f8911367cd4774450a6eb4
Alharbi A.H., Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia; Karthick S., Department of Electrical Electronics and Communication Engineering, GITAM School of Technology, GITAM Deemed to be University, Bengaluru Campus, Karnataka, 560065, India; Venkatachalam K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Abouhawwash M., Department of Mathematics, Faculty of Science, Mansoura University, Mansoura, 35516, Egypt, Department of Computational Mathematics, Science, and Engineering (CMSE), Michigan State University, East Lansing, 48824, MI, United States; Khafaga D.S., Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia
The computational model of nanofluid considering heat transfer and entropy generation across a curved and flat surface
The entropy generation analysis for the nanofluid flowing over a stretching/shrinking curved region is performed in the existence of the cross-diffusion effect. The surface is also subjected to second-order velocity slip under the effect of mixed convection. The Joule heating that contributes significantly to the heat transfer properties of nanofluid is incorporated along with the heat source/sink. Furthermore, the flow is assumed to be governed by an exterior magnetic field that aids in gaining control over the flow speed. With these frameworks, the mathematical model that describes the flow with such characteristics and assumptions is framed using partial differential equations (PDEs). The bvp4c solver is used to numerically solve the system of non-linear ordinary differential equations (ODEs) that are created from these equations. The solutions of obtained through this technique are verified with the available articles and the comparison is tabulated. Meanwhile, the interpretation of the results of this study is delivered through graphs. The findings showed that the Bejan number was decreased by increasing Brinkman number values whereas it enhanced the entropy generation. Also, as the curvature parameter goes higher, the speed of the nanofluid flow diminishes. Furthermore, the increase in the Soret and Dufour effects have enhanced the thermal conduction and the mass transfer of the nanofluid. 2023, The Author(s).
Alharbi S.O.; Smarandache F.; Elsiddieg A.M.A.; Alqahtani A.M.; Khan M.R.; Puneeth V.; Becheikh N.
Alharbi S.O., Mathematics Department, College of Science Al-Zulfi, Majmaah University, Majmaah, 11952, Saudi Arabia; Smarandache F., Mathematics, Physics, and Natural Science Division, The University of New Mexico, 705 Gurley Ave., Gallup, 87301, NM, United States; Elsiddieg A.M.A., Department of Mathematics, College of Science and Humanities, Prince Sattam bin Abdul-Aziz University, Al-Kharj, 11942, Saudi Arabia; Alqahtani A.M., Department of mathematical sciences, College of Science, Princess Nourah Bint Abdulrahman University, P. O. Box 84428, Riyadh, 11671, Saudi Arabia; Khan M.R., Department of Mathematics, Quaid-I-Azam University, Islamabad, 44000, Pakistan; Puneeth V., School of Sciences, CHRIST University, Delhi NCR, Ghaziabad, 201003, India; Becheikh N., College of Engineering, Northern Border University, Arar, 73222, Saudi Arabia
A comparative study of the impact of thermal indices on Indian coral ecosystem
Coral reefs have been the diversified ecosystem in the planet. Advantages are opportunities in tourism, coastal protection and fisheries production. Corals, as key ingredient is sourced got drug manufacturing. Its distribution is evident in locations of where sea water temperature ranges between 16C to 30C. Their presence is >0.2% of ocean area and supports >25% of marine species. India has five reef formations. Globally, last two decades have seen an increase in reporting reef deterioration. The reason significantly attributed to be climate change, apart other challenges such as pollution, sedimentation, oil spillage, etc. Such events lead to widespread mortality of corals. Mortality during bleaching events are inevitable and varied; depends on intensity of such events. The primary reason is due to significant rise in average sea surface temperature (SST). Recovery takes time after such events, and it becomes worse with recurring events. The reefs of Indian seas have reported events of severe bleaching during 1998, 2010 and 2016. IPCC reviews show mass bleaching will be prominent in future due to elevated SST. This work tries to compare the HS values of a few regions. The data collected is from 2001 to 2017. A few significant observations are drawn which could further help us to extend the work to take help from Artificial Intelligence to make predictions for the future. This study uses the indices derived out of SST to look at relative risk faced by Indian reefs. The need for comprehensive and localized actions will be discussed. 2021 Author(s).
https://doi.org/10.1063/5.0066549 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116836355&doi=10.1063%2f5.0066549&partnerID=40&md5=17918f5b59a09c2f872448d8f9edecb8
Ali H., Christ (Deemed to Be University), Karnataka, Bangalore, India; Goswami M., Christ (Deemed to Be University), Karnataka, Bangalore, India
Machine Learning-Enabled NIR Spectroscopy. Part 3: Hyperparameter by Design (HyD) Based ANN-MLP Optimization, Model Generalizability, and Model Transferability
Artificial Neural Network Multilayer Perceptron (ANN-MLP); data-driven modelling; design of experiments (DoE); hyperparameter optimization; model generalizability; model lifecycle management; model transferability; near infrared (NIR); process monitoring; statistical process control (SPC); target drift detection
Data variations, library changes, and poorly tuned hyperparameters can cause failures in data-driven modelling. In such scenarios, model drift, a gradual shift in model performance, can lead to inaccurate predictions. Monitoring and mitigating drift are vital to maintain model effectiveness. USFDA and ICH regulate pharmaceutical variation with scientific risk-based approaches. In this study, the hyperparameter optimization for the Artificial Neural Network Multilayer Perceptron (ANN-MLP) was investigated using open-source data. The design of experiments (DoE) approach in combination with target drift prediction and statistical process control (SPC) was employed to achieve this objective. First, pre-screening and optimization DoEs were conducted on lab-scale data, serving as internal validation data, to identify the design space and control space. The regression performance metrics were carefully monitored to ensure the right set of hyperparameters was selected, optimizing the modelling time and storage requirements. Before extending the analysis to external validation data, a drift analysis on the target variable was performed. This aimed to determine if the external data fell within the studied range or required retraining of the model. Although a drift was observed, the external data remained well within the range of the internal validation data. Subsequently, trend analysis and process monitoring for the mean absolute error of the active content were conducted. The combined use of DoE, drift analysis, and SPC enabled trend analysis, ensuring that both current and external validation data met acceptance criteria. Out-of-specification and process control limits were determined, providing valuable insights into the models performance and overall reliability. This comprehensive approach allowed for robust hyperparameter optimization and effective management of model lifecycle, crucial in achieving accurate and dependable predictions in various real-world applications. Graphical Abstract: [Figure not available: see fulltext.]. 2023, The Author(s).
Ali H.; Muthudoss P.; Chauhan C.; Kaliappan I.; Kumar D.; Paudel A.; Ramasamy G.
Ali H., Christ (Deemed to Be University), Karnataka, Bangalore, 560029, India; Muthudoss P., A2Z4.0 Research and Analytics Private Limited, Tamilnadu, Chennai, 600062, India, NuAxon Bioscience Inc., Bloomington, 47401-6301, IN, United States, School of Pharmaceutical Sciences, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Velan Nagar P.V. Vaithiyalingam Road Pallavaram 600117, Tamilnadu, Chennai, India; Chauhan C., The Machine Learning Company, Pune, India; Kaliappan I., School of Pharmacy, Hindustan Institute of Technology and Science (HITS), Padur, Tamilnadu, Chennai, 603 103, India; Kumar D., Department of Pharmaceutical Engineering & Technology, IIT (BHU), Uttar Pradesh, Varanasi, 221011, India; Paudel A., Research Center Pharmaceutical Engineering GmbH (RCPE), Inffeldgasse 13, Graz, 8010, Austria, Graz University of Technology, Institute of Process and Particle Engineering, Inffeldgasse 13/3, Graz, 8010, Austria; Ramasamy G., Christ (Deemed to Be University), Karnataka, Bangalore, 560029, India
Machine LearningEnabled NIR Spectroscopy. Part 2: Workflow for Selecting a Subset of Samples from Publicly Accessible Data
artificial neural network-multilayer perceptron (ANN-MLP); data quality; machine learning; NIR spectroscopy
Abstract: An increasingly large dataset of pharmaceuticsdisciplines is frequently challenging to comprehend. Since machine learning needs high-quality data sets, the open-source dataset can be a place to start. This work presents a systematic method to choose representative subsamples from the existing research, along with an extensive set of quality measures and a visualization strategy. The preceding article (Muthudoss et al. in AAPS PharmSciTech 23, 2022) describes a workflow for leveraging near infrared (NIR) spectroscopy to obtain reliable and robustdata on pharmaceutical samples. This study describes the systematic and structured procedure for selecting subsamples from the historical data. We offer a wide range of in-depth quality measures, diagnostic tools, and visualization techniques. A real-world, well-researched NIR dataset was employed to demonstrate this approach. This open-source tablet dataset (http://www.models.life.ku.dk/Tablets) consists of different doses in milligrams, different shapes, and sizes of dosage forms, slots in tablets, three different manufacturing scales (lab, pilot, production), coating differences (coated vs uncoated), etc. This sample is appropriate; that is, the model was developed on one scale (in this research, the lab scale), and it can be great to investigate how well the top models are transferable when tested on new data like pilot-scale or production (full) scale. A literature review indicated that the PLS regression models outperform artificial neural network-multilayer perceptron (ANN-MLP). This work demonstrates the selection of appropriate hyperparameters and their impact on ANN-MLP model performance. The hyperparameter tuning approaches and performance with available references are discussed for the data under investigation. Model extension from lab-scale to pilot-scale/production scale is demonstrated. Highlights: We present a comprehensive quality metrics and visualization strategy in selecting subsamples from the existing studies A comprehensive assessment and workflow are demonstrated using historical real-world near-infrared (NIR) data sets Selection of appropriate hyperparameters and their impact on artificial neural network-multilayer perceptron (ANN-MLP) model performance The choice of hyperparameter tuning approaches and performance with available references are discussed for the data under investigation Model extension from lab-scale to pilot-scale successfully demonstrated Graphical Abstract: [Figure not available: see fulltext.]. 2023, The Author(s).
Ali H.; Muthudoss P.; Ramalingam M.; Kanakaraj L.; Paudel A.; Ramasamy G.
Ali H., Christ (Deemed to Be University), Karnataka, Bangalore, 560029, India; Muthudoss P., A2Z4.0 Research and Analytics Private Limited, Tamilnadu, Chennai, 600062, India; Ramalingam M., Chettinad School of Pharmaceutical Sciences, Chettinad Academy of Research and Education, Chettinad Health City, Tamilnadu, Chennai, 603103, India; Kanakaraj L., Chettinad School of Pharmaceutical Sciences, Chettinad Academy of Research and Education, Chettinad Health City, Tamilnadu, Chennai, 603103, India; Paudel A., Research Center Pharmaceutical Engineering GmbH (RCPE), Inffeldgasse 13, Graz, 8010, Austria, Institute of Process and Particle Engineering, Graz University of Technology, Inffeldgasse 13/3, Graz, 8010, Austria; Ramasamy G., Christ (Deemed to Be University), Karnataka, Bangalore, 560029, India
DDoS Intrusions Detection in Low Power SD-IoT Devices Leveraging Effective Machine Learning
DDoS attacks; Decision making; Low power IoT; Machine learning; SDN
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.
Ali J.; Song H.H.; Sharma V.; Al-Khasawneh M.A.
IEEE Transactions on Consumer Electronics
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/TCE.2024.3472707 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206344971&doi=10.1109%2fTCE.2024.3472707&partnerID=40&md5=44d404dc7c55e8009a82ef4c770011b9
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
Mapping location and identity in the works of indian english novelists:
This thesis examines the context of location in relation to constructs of identity in Salman Rushdie s MC, Vikram Seth s ASB and Amitav Ghosh s TSL. It is contended that articulation of selfhood is achieved through its interaction with narrative constructions of space and these depictions serve to map representations of nation. Writers migrant experiences are shown to have a bearing on the aesthetics and geopolitics of these representations. Even though these texts challenge the reductive processes of homogenization at work in the formation of nationalcultural identities, it is contended that they foreground transnational lifestyles and identities.Some of the questions that the thesis asks are: Does the cultural-geographical location of the writer shape the aesthetics of the work? If so, to what extent? In what ways does the diasporic newlineexperience influence the (re)presentation of mediated and inter-connected spaces? How is a newlinecharacter, who does not share the author s diasporic location and experience, depicted? Do the works cater to a Western readership by presenting a palatable version that is only purportedly transnational? Or, are the writers lapsing into a master narrative of universalism? newlineThe creative paradigm allows for the unfolding of the enigma of identity by the interplay of the questions surrounding place - Where am I and what is my place in the world, which reveals who I am. There are real geographies of social action, as well as metaphorical spaces and sites of power that have to be understood in their own right and in the context of shared loci that come together to construct identity. Thus, a comparative study of the novels is conducted on various registers such as dynamics of space, negotiation of borders and boundaries, delineation of multiple identities and representation of nation via language and history. The thesis argues for newlineaesthetic negotiation of borders across locations that maybe geographic and psychic; in order to grapple with and empower subjectivities.
Wireless Network Security Using Load Balanced Mobile Sink Technique
load balancing mechanism; networks lifetime; optimization; power consumption; Wireless sensor network
Real-time applications based on Wireless Sensor Network (WSN) technologies are quickly increasing due to intelligent surroundings. Among the most significant resources in the WSN are battery power and security. Clustering stra-tegies improve the power factor and secure the WSN environment. It takes more electricity to forward data in a WSN. Though numerous clustering methods have been developed to provide energy consumption, there is indeed a risk of unequal load balancing, resulting in a decrease in the networks lifetime due to network inequalities and less security. These possibilities arise due to the cluster heads limited life span. These cluster heads (CH) are in charge of all activities and control intra-cluster and inter-cluster interactions. The proposed method uses Lifetime centric load balancing mechanisms (LCLBM) and Cluster-based energy optimization using a mobile sink algorithm (CEOMS). LCLBM emphasizes the selection of CH, system architectures, and optimal distribution of CH. In addition, the LCLBM was added with an assistant cluster head (ACH) for load balancing. Power consumption, communications latency, the frequency of failing nodes, high security, and one-way delay are essential variables to consider while evaluating LCLBM. CEOMS will choose a cluster leader based on the influence of the fol-lowing parameters on the energy balance of WSNs. According to simulated find-ings, the suggested LCLBM-CEOMS method increases cluster head selection self-adaptability, improves the networks lifetime, decreases data latency, and bal-ances network capacity. 2023, Tech Science Press. All rights reserved.
Alkanhel R.; Abouhawwash M.; Sangeethaa S.N.; Venkatachalam K.; Khafaga D.S.
Intelligent Automation and Soft Computing, Vol-35, No. 2, pp. 2135-2149.
https://doi.org/10.32604/iasc.2023.028852 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134324099&doi=10.32604%2fiasc.2023.028852&partnerID=40&md5=ae3843437ca19d923bac770554ef0157
Alkanhel R., Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia; Abouhawwash M., Department of Mathematics, Faculty of Science, Mansoura University, Mansoura, 35516, Egypt, Department of Computational Mathematics, Science, and Engineering (CMSE), Michigan State University, East Lansing, 48824, MI, United States; Sangeethaa S.N., Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, 638401, India; Venkatachalam K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, 560074, India; Khafaga D.S., Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
A PV-Powered Single Phase Seven-Level Invertera's Photocurrent and Injected Power
Harmonics; MPPT; Proportional Integral; PV inverter; Seven level inverter
The PV inverter in this study is linked to the grid and its performance analysis is evaluated using a PI controller. It is a single phase multi-level PV inverter. The major objective of this research is to increase efficiency and eliminate harmonics caused by DC link voltage fluctuations created by Maximum Power Point Tracking (MPPT) during foggy situations. PV inverters generate and inject actual power into the main grid. This study uses a transformer-less photovoltaic inverter to cut down on losses, cost, and size. A transformer-less multilayer inverter is described in this paper. There is no high-frequency leakage current since that inverter can distribute both actual and reactive electricity. MATLAB/Simulink software was used to analyze and assess the effects of various PV-based seven-level techniques on the devicea's Maximum Power Point Tracking (MPPT) performance. The Authors, published by EDP Sciences, 2024.
Alkhafaij M.A.; Davala K.; Edwin Prabhakar P.B.; Jeshurun S.B.; Ramy Riad A.-F.; Senthil Kumar R.
https://doi.org/10.1051/e3sconf/202456405009 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203842044&doi=10.1051%2fe3sconf%2f202456405009&partnerID=40&md5=8214f998ba40f786a9c2e4b4b57eda38
Alkhafaij M.A., College of MLT, Ahl Al Bayt University, karbala, Iraq; Davala K., Department of EEE, GRIET, Bachupally, Telangana, Hyderabad, India; Edwin Prabhakar P.B., New Prince Shri Bhavani College of Engineering and Technology, Chennai, India; Jeshurun S.B., School of Business and Management, CHRIST University, Bangalore, India; Ramy Riad A.-F., Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Babylon, Babylon, Iraq; Senthil Kumar R., AAA College of Engineering & Technology, tamil Nadu, Sivakasi, India
Next-Generation Connectivity in A Heterogenous Railway World
Global System for Mobile communication - Railway (GSM-R) is widely used for operational communications between train and signaler. However, there is a need to define a successor that addresses: obsolescence, radio spectrum demand and the enabling of a range of emerging digital applications such as radio-based signaling and Automatic Train Control (ATC). Therefore, the International Union of Railways (UIC) started the initiative to develop the Future Railway Mobile Communication System (FRMCS). This article describes an Adaptable Communication System (ACS) that is being developed jointly by industry and railway operators as a possible successor covering all types of railways and all aspects of the FRMCS. A pragmatic approach is suggested that considers diverse railway settings and makes use of various radio access technologies. Countries, geographical regions and infrastructure managers differ concerning available radio technologies, but use of a suitable ACS could pave the way towards innovation in the railway sector. For this adaptive concept we discuss several network models and enhancements including satellite communications (SatCom), Software-Defined Networking (SDN) integration and antenna systems that support multiple bearers in one. For SatCom a software defined radio (SDR) prototype using random access is presented that is able to fulfill the requirements of ETCS. We found that SDN can be used for dynamically changing the access technology for critical and non-critical railway use cases. Furthermore, we present an antenna prototype that can be used for 5G, GSM, WLAN and LTE in parallel which saves limited mounting surface on the train. 1979-2012 IEEE.
Allen B.; Barth B.; Grec M.; Erl S.; Geier U.; Keil K.; Kumar N.; Seetharamdoo D.; Zaballa E.O.
IEEE Communications Magazine, Vol-61, No. 4, pp. 34-40.
https://doi.org/10.1109/MCOM.001.2200130 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144782653&doi=10.1109%2fMCOM.001.2200130&partnerID=40&md5=122b641372c45956e22139f771ddc2b7
Allen B., Network Rail, United Kingdom, University of Surrey, United Kingdom; Barth B., German Aerospace Center (DLR), Germany; Grec M., German Aerospace Center (DLR), Germany; Erl S., German Aerospace Center (DLR), Germany; Geier U., Kontron, Austria; Keil K., Db Netz Ag and Neovendi GmbH, Germany; Kumar N., Railenium, France, Christ University, India; Seetharamdoo D., Railenium, France, University Gustave Eiffel, France; Zaballa E.O., Railenium, France, Technical University of Denmark, Denmark