Mining Heterogeneous Lung Cancer from Computer Tomography (CT) Scan with the Confusion Matrix
Computer tomography (CT); LBP features; preprocessing; processing; smoothening
Early detection of any sort of cancer, particularly lung cancer, which is one of the worlds most lethal illnesses, can save many lives. Life expectancy can be improved and the degree of mortality reduced by adopting the early forecast. While there are different methods like X-ray and CT scans to detect lung cancer cells, CT images resulted as more favored. The 2D images are used for more accurate medical results, such as CT scans. The proposed approach here will address how to interpret the CT images for the Mining Heterogeneous Lung Cancer from Computer Tomography (CT) Scan with the Confusion Matrix. This research will explore how the image conversion can be achieved through different methods of image processing to obtain better results from CT images. The Confusion Matrix helps to estimate inequality in a picture pattern. After the evaluation of the processed images by Confusion Matrix, a final accuracy with a result of 93% is obtained. 2023 Scrivener Publishing LLC.
Data Engineering and Data Science: Concepts and Applications, pp. 317-333.
Dominic D., School of Computer Science and Engineering, Christ (Deemed to be University), Bengaluru, India; Balachandran K., School of Computer Science and Engineering, Christ (Deemed to be University), Bengaluru, India
Mining the web data for classifying and predicting users' requests
Classification; Customer; E-commerce; Prediction; Product Recommendation; Segmentation; Trend
Consumers are the most important asset of any organization. The commercial activity of an organization booms with the presence of a loyal customer who is visibly content with the product and services being offered. In a dynamic market, understanding variations in client?s behavior can help executives establish operative promotional campaigns. A good number of new consumers are frequently picked up by traders during promotions. Though, several of these engrossed consumers are one-time deal seekers, the promotions undeniably leave a positive impact on sales. It is crucial for traders to identify who can be converted to loyal consumer and then have them patronize products and services to reduce the promotion cost and increase the return on investments. This study integrates a classifier that allows prediction of the type of purchase that a customer would make, as well as the number of visits that he/she would make during a year. The proposed model also creates outlines of users and brands or items used by them. These outlines may not be useful only for this particular prediction task, but could also be used for other important tasks in e-commerce, such as client segmentation, product recommendation and client base growth for brands. Copyright 2018 Institute of Advanced Engineering and Science. All rights reserved.
Girish S.; Ramamurthy B.; Senthilnathan T.
International Journal of Electrical and Computer Engineering, Vol-8, No. 4, pp. 2390-2398.
Institute of Advanced Engineering and Science
All Open Access; Green Open Access; Hybrid Gold Open Access
https://doi.org/10.11591/ijece.v8i4.pp2390-2398 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049571427&doi=10.11591%2fijece.v8i4.pp2390-2398&partnerID=40&md5=1a91b08884f0e6b1ef3f2be356ef3aab
Girish S., Department of Computer Science, Christ University, Hosur Road, Bengaluru, Karnataka, India; Ramamurthy B., Department of Computer Science, Christ University, Hosur Road, Bengaluru, Karnataka, India; Senthilnathan T., Department of Computer Science, Christ University, Hosur Road, Bengaluru, Karnataka, India
Mirabijalones S-W, rotenoids from rhizomes of white Mirabilis jalapa Linn. and their cell proliferative studies
Cytotoxicity; Mirabijalones S-W; Mirabilis jalapa Linn; MTT; Nyctaginaceae; Rotenoids
Five undescribed (2-6) rotenoid derivatives along with three known rotenoids (1, 7 and 8) were isolated from the rhizomes of white colored variety of Mirabilis jalapa Linn. The structures of these undescribed compounds were elucidated based on UV, IR, HR-MS (ESI), 1D and 2D NMR spectroscopic techniques. Selected compounds were evaluated for their cell viability and proliferation in two cancer cell lines namely, cervical (HeLa), breast (SKBR-3) and normal lung fibroblast (WI-38). Among them, the compounds Boeravinone C (1), Mirabijalone S (2), Mirabijalone T (3) and 4, 6, 11-trihydroxy-9-methoxy-10-methylchromeno [3, 4-b] chromen-12(6H)-one (8) showed moderate cytotoxicity against HeLa cells with IC50 values in the 8.40 ? 12.9 ?M range, and compound 8 exhibited cytotoxicity against SKBR-3 cells with IC50 value of 17.6 ?M. Molecular docking studies of isolated compounds were performed with three apoptosis proteins, 3H11, 2AR9 and 1X0X. These results revealed that the isolated compounds were found to interact with Caspase 8 and 9 along with the anti-apoptotic protein Survivin. Since these compounds exhibit cytotoxic effects against SKBR3 and HeLa cells, they are expected to show apoptosis and may be further utilized for wet lab apoptotic studies. 2021 Phytochemical Society of Europe
Sharathna P.; Alisha V.; Sasikumar P.; Ajesh V.; Ayisha F.; Shibi I.G.; Sivan V.V.; Kaustabh Kumar M.; Ravi S. L.; Radhakrishnan K.V.
Phytochemistry Letters, Vol-44, pp. 178-184.
https://doi.org/10.1016/j.phytol.2021.06.017 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109004524&doi=10.1016%2fj.phytol.2021.06.017&partnerID=40&md5=8ef001731a67e0ae61cc850ffb87e4fa
Sharathna P., Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science and Technology (NIIST), Thiruvananthapuram-19, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad-002, India; Alisha V., Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science and Technology (NIIST), Thiruvananthapuram-19, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad-002, India; Sasikumar P., Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science and Technology (NIIST), Thiruvananthapuram-19, India; Ajesh V., Department of Chemistry, CHRIST (Deemed to Be University), Hosur Road, Bengaluru, 560029, India; Ayisha F., Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science and Technology (NIIST), Thiruvananthapuram-19, India; Shibi I.G., Department of Chemistry, Sree Narayana College, Chempazhanthy, Thiruvananthapuram, India; Sivan V.V., M. S. Swaminathan Research Foundation-Community Agrobiodiversity Centre (MSSRF-CAbC), Puthurvayal, Wayanad, Kerala, India; Kaustabh Kumar M., Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science and Technology (NIIST), Thiruvananthapuram-19, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad-002, India; Ravi S. L., Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science and Technology (NIIST), Thiruvananthapuram-19, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad-002, India; Radhakrishnan K.V., Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science and Technology (NIIST), Thiruvananthapuram-19, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad-002, India
MIST-based Tuning of Cyber-Physical Systems Towards Holistic Healthcare Informatics
Body Area Network; Cyber-Physical Systems; Healthcare Informatics; MIST; Recommender Systems
The entire world seems shaken and disrupted since the strike of Covid-19 ever since its outbreak towards the end of 2019 and its continued perils. During this unprecedented event of the century, people's health emerged as the most vulnerable and affected area either directly or indirectly by the coronavirus and its new variants. Disrupting almost all spheres of life, patients' health and care systems required timely support from healthcare professionals to provide the needed medical advice on one hand and a prescriptive mechanism to avoid another impending casualty. Similarly, a proactive approach became desirable from the health ministry, pharmaceutical firms, medical insurance companies, and other stakeholders in fine-tuning their offerings to the patients as per the recommender systems. The devices to measure the vitals of a person, became more efficient and ergonomically sound with the advent of wearable gadgets. These devices monitored the physical activities of the user and transferred the vital signals wirelessly to any base computing device and cloud-based repositories. This mechanism, however, was reported to fail in addressing the issues with non-communicating or stand-alone devices that were used by the masses in developing countries including India. If the real-time data could be used from these devices, the healthcare diagnosis and analysis of a patient's medical condition could have taken a progressive dimension with the addition of missing data points. This research thus aims to fill the information gap and proposes a transforming approach towards existing non-communicating devices used to measure the vitals like blood pressure, oxygen level, blood sugar, etc. The proposed MIST-based Cyber-Physical System shall create extensive scalability towards the retrieval of the vital details from the devices which were otherwise captured offline previously and were unused at multiple critical points of healthcare processes. 2022 IEEE.
Sharma D.; Singhal T.K.; Singh D.; Qadir A.
8th International Conference on Advanced Computing and Communication Systems, ICACCS 2022, pp. 1752-1757.
Institute of Electrical and Electronics Engineers Inc.
Sharma D., School of Business and Management, Christ University, U.P., Delhi-NCR, Ghaziabad, India; Singhal T.K., School of Business and Management, Christ University, U.P., Delhi-NCR, Ghaziabad, India; Singh D., School of Business and Management, Christ University, U.P., Delhi-NCR, Ghaziabad, India; Qadir A., School of Business and Management, Christ University, U.P., Delhi-NCR, Ghaziabad, India
Misuse of Internet Among School Children: Risk Factors and Preventative Measures
Misuse of internet; Neurodevelopment; Prevention; Psychosocial; Risk factors; School children
The Internet has been one of the most transformative and rapidly growing technologies. In recent years, it has improved the quality of life in areas such as communication, education, recreation. On the contrary, there are growing concerns about the use of the Internet that have created adverse consequences in the areas of social life, interpersonal relationships, family environment, and school activities. School-going children were vulnerable to such unhealthy outcomes due to readily available high-speed Internet and ease of access to different Internet platforms, which resulted in risky behaviours, decreased academic performance, poor nutrition, decreased sleep quality, and a high incidence of inter-social conflicts. While the majority of the research has focused on the adolescent population in terms of problematic Internet use, only a few studies have identified the vulnerabilities of school-going children in the same context. The research also confirmed that the risk factors for problematic Internet use start as early as middle childhood. Heightened risky use of the Internet was observed in children with neurodevelopmental concerns. This study explores risk factors associated with problematic Internet use among school-going children, identifying relevant warning signs followed with preventative measures. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.
Child Safety, Welfare and Well-being: Issues and Challenges, Second Edition, pp. 321-334.
Reddy K.J., Department of Psychology, Centre for Research, Christ University, Bangalore, India; Balasubramanian G., Aadya Tathva, India, QPR Institute, Certified Seizure First Aid Professional from Epilepsy Foundation, United States, National Council for Mental Wellbeing, United States, Indian Epilepsy Association (IEA), Bangalore, India, International Association of Applied Psychology (IAAP), Canada
Mitigating Mental Health Burden of Youth During COVID-19 Through Resilience and Hope: Evidences from India and Germany
Anticipatory Crisis; COVID-19; Hope; Mental Health; Resilience; Stress
In the global crisis caused by the COVID-19 pandemic, young professionals and graduating students experience considerable psychological adversity due to the uncertainty surrounding their futures. Given the positive psychological outcomes and the potential to alleviate stress, we examine the role of resilience and hope in causing a substantial variance in the stress response to anticipation of crisis among Indians living in India and Germany. Resilience, hope, crisis apprehension, and the psychological response to the COVID-19 pandemic were measured among participants from India and Germany (n = 650) via an online survey using non-probability convenient sampling. Parallel mediation and conditional indirect effects showcase the differential roles of resilience and hope among socio-culturally similar but geographically divergent groups. Hope mediates the effect of pandemic-led crisis apprehension on perceived stress among those residing in India; resilience operates to mitigate stress among those from Germany. Findings highlight the contradistinctive role of resilience and hope in reducing stress and imply an urgent need for promotion of ameliorative practices. Resilience effectively mitigates the psychological burden of the COVID-19 crisis and can be promoted to reskill individuals; however, elevating hope in a crisis obligates prudence. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
Handbook of Youth Development: Policies and Perspectives from India and Beyond, pp. 515-529.
Mukherjee T., Work and Organizational Psychologist, Muenster, Germany; Deb S., Ministry of Youth Affairs and Sports (MYAS), Government of India (GOI), Sriperumbudur Tamil Nadu, Pennalur, 602 105, India; Deb S., Department of Psychology, CHRIST (Deemed to Be University), Bengaluru, India
Mitigating post-harvest losses through IoT-based machine learning algorithms in smart farming
This research paper explores the transformative potential of Internet of Things (IoT) technology in mitigating the longstanding issue of post-harvest losses within the agriculture sector. These losses, which encompass both quantitative and qualitative deterioration of food commodities from harvest to consumption, have posed persistent challenges, resulting in economic losses and food wastage. By delving into the current landscape of post-harvest losses and the application of IoT technology, the paper offers valuable insights into how IoT can be harnessed to reduce these losses effectively. It not only highlights the benefits and existing IoT solutions but also addresses the inherent challenges, providing recommendations for their resolution. Moreover, the research introduces a machine learning-based model, specifically Random Forest ML, to identify and prevent losses in tandem with IoT devices, empowering farmers with timely alert messages for informed decision-making, thus fostering a more sustainable and efficient agricultural ecosystem. 2024 Author(s).
Kanna R.R.; Priya T.M.; Sivakumar V.; Nataraj C.; Thomas J.
AIP Conference Proceedings, Vol-3161, No. 1
https://doi.org/10.1063/5.0229500 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204010477&doi=10.1063%2f5.0229500&partnerID=40&md5=868f046d8561d500a5b299f2ac2dfb7e
Kanna R.R., Department of Computer Science, CHRIST (Deemed to Be University), Bangalore, India; Priya T.M., Department of Computer Science, CHRIST (Deemed to Be University), Bangalore, India; Sivakumar V., School of Computing, Faculty of Computing Engineering and Technology, Asia Pacific University of Technology and Innovation, Kuala Lumpur, Malaysia; Nataraj C., School of Engineering, Faculty of Computing Engineering and Technology, Asia Pacific University of Technology and Innovation, Kuala Lumpur, Malaysia; Thomas J., Department of Sociology and Social Work, CHRIST (Deemed to Be University), Bangalore, India
Mitigation of harmonics for five level multilevel inverter with fuzzy logic controller
cascade H-bridge multilevel inverters; fuzzy logic controller; selective pulse width modulation technique; total harmonic distortion
Introduction. The advantages of a high-power quality waveform and a high voltage capability of multilevel inverters have made them increasingly popular in recent years. These inverters reduce harmonic distortion and improve the voltage output. Realistically speaking, as the number of voltage levels increases, so does the quality of the multilevel output-voltage waveform. When it comes to industrial power converters, these inverters are by far the most critical. Novelty. Multilevel cascade inverters can be used to convert multiple direct current sources into one direct current. These inverters have been getting a lot of attention recently for high-power applications. A cascade H-bridge multilevel inverter controller is proposed in this paper. A change in the pulse width of selective pulse width modulation modulates the output of the multilevel cascade inverter. Purpose. The total harmonic distortion can be reduced by using filters on controllers like PI and fuzzy logic controllers. Methods. The proposed topology is implemented with MATLAB/Simulink, using gating pulses and pulse width modulation methodology and fuzzy logic controllers. Moreover, the proposed model also has been validated and compared to the hardware system. Results. Total harmonic distortion, number of power switches, output voltage and number of DC sources are analyzed with conventional topologies. Practical value. The proposed topology has been very supportive for implementing photovoltaic based multilevel inverter, which is connected to large demand in grid and industry. M.S. Sujatha, S. Sreelakshmi, E. Parimalasundar, K. Suresh.
Sujatha M.S.; Sreelakshmi S.; Parimalasundar E.; Suresh K.
Electrical Engineering and Electromechanics, Vol-2023, No. 4, pp. 52-56.
National Technical University "Kharkiv Polytechnic Institute"
All Open Access; Gold Open Access; Green Open Access
Sujatha M.S., Department of Electrical & Electronics Engineering, Sree Vidyanikethan Engineering College, AP, Tirupati, 517102, India; Sreelakshmi S., Department of Electrical and Electronics Engineering, Jawaharlal Nehru Technological University Anantapur, AP, Anantapuramu, 517102, India; Parimalasundar E., Department of Electrical & Electronics Engineering, Sree Vidyanikethan Engineering College, AP, Tirupati, 517102, India; Suresh K., Department of Electrical and Electronics Engineering, Christ (Deemed to be University), Bangalore, India
Mixed convection 3D radiating flow and mass transfer of eyring-powell nanofluid with convective boundary condition
Brownian motion; Convective conditions; Eyring-Powell fluid; Thermal radiation; Thermophoresis; Three dimensional flows
Three-dimensional mixed convection flow, heat and mass transfer of Eyring-powell fluid over a convectively heated stretched sheet is inspected in this paper. The encouragement of Brownian motion, thermophoresis, convective condition and thermal radiations are accounted. Appropriate transformations are used to reduce the principal PDE's into set of coupled highly nonlinear ODE's which are then solved numerically using RKF fourth-fifth order method. The consequence of several parameters on flow, heat and mass transfer characteristics are deliberated with the help of graphs and tables. It is observed that the temperature and concentration profiles diminish for higher values mixed convection parameter. Further, the temperature and its related boundary layer thickness is increases with increasing the Biot number and thermal radiation effects. 2018 Trans Tech Publications, Switzerland.
Kumar P.B.S.; Mahanthesh B.; Gireesha B.J.; Manjunatha S.
Defect and Diffusion Forum, Vol-388, pp. 158-170.
https://doi.org/10.4028/www.scientific.net/DDF.388.158 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063086573&doi=10.4028%2fwww.scientific.net%2fDDF.388.158&partnerID=40&md5=2bbce3adf1a03adfc1a86a3506e62305
Kumar P.B.S., Department of Studies and Research in Mathematics, Kuvempu University, Shankaraghatta, Shimoga, Karnataka, 577 451, India; Mahanthesh B., Department of Mathematics, Christ University, Bangalore, 560029, India; Gireesha B.J., Department of Studies and Research in Mathematics, Kuvempu University, Shankaraghatta, Shimoga, Karnataka, 577 451, India; Manjunatha S., Department of Engineering Mathematics, Faculty of Engineering, Christ University, Mysore Road, Bengaluru, 560074, India
Mixed convection in the stagnation-point flow over a vertical stretching sheet in the presence of thermal radiation
Boundary layer flow; Dusty fluid; Free stream velocity; Mixed convective parameter; Numerical solution; Stretching porous surface; Thermal radiation
An unsteady two-dimensional stagnation-point mixed convection flow of a viscous, incompressible dusty fluid towards a vertical stretching sheet has been examined. The stretching velocity and the free stream velocity are assumed to vary linearly with the distance from the stagnation point. The problem is analyzed using similarity solutions. The similarity ordinary differential equations were then solved numerical by using the RKF-45 method. The effects of various physical parameters on the velocity profile and skin-friction coefficient are also discussed in this paper. Some important findings reported in this work reveal that the effect of radiation has a significant impact on controlling the rate of heat transfer in the boundary layer region.
Manjunatha S.; Gireesha B.J.; Bagewadi C.S.
International Journal of Applied Mechanics and Engineering, Vol-20, No. 4, pp. 871-888.
https://doi.org/10.1515/ijame-2015-0056 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973151716&doi=10.1515%2fijame-2015-0056&partnerID=40&md5=9213000470825d1363f62a92374ca166
Manjunatha S., Department of Engineering Mathematics, Christ University Faculty of Engineering, Kanminike, Kumbalgodu, Mysore Road, Bengaluru, Karnataka-State, 560074, India; Gireesha B.J., Department of Studies and Research in Mathematics, Kuvempu University, Shankaraghatta, Shimoga, Karnataka, 577 451, India; Bagewadi C.S., Department of Studies and Research in Mathematics, Kuvempu University, Shankaraghatta, Shimoga, Karnataka, 577 451, India
Mixed radiated magneto Casson fluid flow with Arrhenius activation energy and Newtonian heating effects: Flow and sensitivity analysis
Arrhenius activation energy; Homotopy analysis method; Newtonian heating; Sensitivity analysis; Stefan blowing
The characteristics of Stefan blowing effects in a magneto-hydrodynamic flow of a Casson fluid past a stretching sheet are investigated. The effects of radiation, heat source/sink, Newtonian heating, Arrhenius activation energy and binary chemical reaction are considered for heat and mass transfer analysis. The homotopy analysis method (HAM) was utilised to solve the transformed non-dimensionalized equations analytically. The impact of various physical parameters affecting the flow are investigated. Further, the relationship of various parameters on the skin friction and rate of heat and mass transfer was explored using correlation and probable error. A sensitivity analysis was carried out based on the Response Surface Methodology to analyse the effect of Stefan blowing parameter, magnetic parameter and stretching/shrinking parameter on the reduced Nusselt number and reduced Sherwood number. A constant positive sensitivity for the reduced Nusselt number towards the Stefan blowing parameter for all levels of magnetic parameter and stretching/shrinking parameter was found. Further, the reduced Sherwood number indicated a negative sensitivity towards the Stefan blowing parameter. 2020 Faculty of Engineering, Alexandria University
Abdelmalek Z.; Mahanthesh B.; Md Basir M.F.; Imtiaz M.; Mackolil J.; Khan N.S.; Nabwey H.A.; Tlili I.
Alexandria Engineering Journal, Vol-59, No. 5, pp. 3991-4011.
https://doi.org/10.1016/j.aej.2020.07.006 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088968806&doi=10.1016%2fj.aej.2020.07.006&partnerID=40&md5=8c6ba6c68d08e7857f6a1a8425f79c9e
Abdelmalek Z., Institute of Research and Development, Duy Tan University, Da Nang, 550000, Viet Nam, Faculty of Medicine, Duy Tan University, Da Nang, 550000, Viet Nam; Mahanthesh B., Department of Mathematics, CHRIST (Deemed to be University), Bangalore, 560029, Karnataka, India; Md Basir M.F., Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, UTM Johor Bahru, 81310, Malaysia; Imtiaz M., Department of Social and Behavioral Sciences, National University of Medical Sciences, Rawalpindi, Pakistan; Mackolil J., Department of Mathematics, CHRIST (Deemed to be University), Bangalore, 560029, Karnataka, India; Khan N.S., Department of Mathematics, Abdul Wali Khan University, Mardan, 23200, Khyber Pakhtunkhwa, Pakistan; Nabwey H.A., Department of Mathematics, College of Science and Humanities in Al-Kharj, Prince Sattam bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia, Department of Basic Engineering Science, Faculty of Engineering, Menoufia University, Shebin El-Kom, 32511, Egypt; Tlili I., Department of Mechanical and Industrial Engineering, College of Engineering, Majmaah University, Al-Majmaah, 11952, Saudi Arabia
ML Algorithms and Their Approach on COVID-19 Data Analysis
classification; covid analysis; covid data visualization; Machine learning; regression; supervised learning; un-supervised learning
This chapter begins with characterizing Supervised Learning and Unsupervised learning and investigates Machine Learning algorithms in every one of the sub domains of Regression, Classification, Clustering, and so forth. It also talks about the engineering of calculations like Linear Regression, Logistic Regression, K-Means, K Nearest Neighbors, Hierarchical, DB Scan, Decision Tree, Random Forest Regression, and Random Forest classifier. Utilization of every algorithm to investigate the dataset will be displayed by carrying out it on renowned dataset model, and output of each piece of code is displayed with their preview. This section likewise takes care of the issue of predicting the future number of COVID-19 cases and the precision behind each model or algorithm is shown and investigated utilizing different measurements dependent on situation or issue articulation, for example, either issue is on forecast or order. This chapter does not focus on the solution of COVID-19 data analysis or expectation, rather it will be followed and will task different models dependent on need with conclusive target being clear comprehension of the Machine Learning algorithms and its execution in Python. 2023 Scrivener Publishing LLC.
Data Engineering and Data Science: Concepts and Applications, pp. 335-349.
Ashok K., Department of CS, Kyungpook National University, Daegu, South Korea; Reddy P.A., Department of CSE, Christ University, Karnataka, Bangalore, India; Kumar K.P., Department of CSE, Christ University, Karnataka, Bangalore, India
ML based sign language recognition system
Automated SLR; Classification models; Feature extraction; Preprocessing; Segmentation
This paper reviews different steps in an automated sign language recognition (SLR) system. Developing a system that can read and interpret a sign must be trained using a large dataset and the best algorithm. As a basic SLR system, an isolated recognition model is developed. The model is based on vision-based isolated hand gesture detection and recognition. Assessment of ML-based SLR model was conducted with the help of 4 candidates under a controlled environment. The model made use of a convex hull for feature extraction and KNN for classification. The model yielded 65% accuracy. 2021 IEEE.
2021 International Conference on Innovative Trends in Information Technology, ICITIIT 2021
https://doi.org/10.1109/ICITIIT51526.2021.9399594 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104831889&doi=10.1109%2fICITIIT51526.2021.9399594&partnerID=40&md5=46dea1c1a1f0e4fb41987b4917a0c61b
Amrutha K., CHRIST(Deemed to Be University), Dept. of Computer Science, Bangalore, India; Prabu P., CHRIST(Deemed to Be University), Dept. of Computer Science, Bangalore, India
ML in drug delivery-current scenario and future trends
Machine learning (ML) has enabled transformative applications and emerged as a domain-agnostic decision-making tool as a virtue of its rapid democratization. The authors believe that a systematic assortment of important publications on this issue is indispensable in this context. In terms of data ingestion, data curation, data preprocessing, data handling, and model cross-validation, this review gathers together several studies that have demonstrated a minimum ML framework approach. In general, ML models are described as black-box models, with limited information supplied about their transparency. The authors propose techniques based on the US Food and Drug Administration (FDA)'s current good ML practice (GMLP) in order to improve the ML framework and minimize the aforementioned gap, especially for data. Considering this, the conversation around a model's logic and interpretability are additionally provided. Explicitly, the authors explore the challenges and constraints that ML execution confronts throughout the development of pharmaceuticals. In this context, a structural approach in statistics is presented to allow the scientist to assess the quality of data and incorporate important ideas and techniques that would be implemented in modern ML. The data analytics tetrahedron proposed here can be applied to data of any size. To further contextualize, selected case studies capturing good practices are highlighted to provide pharmaceutical scientists, pharmaceutical ML enthusiasts, readers, reviewers, and regulatory authorities an exposure to fundamental and cuttingedge techniques of ML and data science with respect to chemistry, manufacture, and control (CMC) of drug products. In addition, the authors believe that leveraging ML within CMC procedures can assist in improving decision-making, increasing quality, and enhancing the speed of pharmaceutical product development. IOP Publishing Ltd 2023. All rights reserved.
Muthudoss P.; Ali H.; Ramasamy G.; Allada R.; Fink E.; Kalaiselvan V.; Jayakrishnan B.; Shahane S.; Ramalingam M.; Kanakaraj L.; Kaliappan I.; Paudel A.
Advances in Drug Delivery Systems for Healthcare: From concept to clinic, pp. 9-.
Muthudoss P., A2Z4.0 Research and Analytics Private Limited, Chennai, 600062, India; Ali H., Christ University, Bangalore, 560029, India; Ramasamy G., Christ University, Bangalore, 560029, India; Allada R., Novugen Pharma (Malaysia) Sdn Bhd, Hicomglenmarie Industrial Park, 3, Jalan Jururancang U1/21, Selangor, 40150, Malaysia; Fink E., Research Center Pharmaceutical Engineering GmbH (RCPE), Inffeldgasse 13, Graz, 8010, Austria; Kalaiselvan V., Indian Pharmacopoeia, Commission, Ministry of Health and Family Welfare, Government of India, Sector 23, Rajnagar, 201002, India; Jayakrishnan B., Business School, Vellore Institute of Technology (VIT), Chennai Campus, Kekottaiyur, 600127, India; Shahane S., The Machine Learning Company, Maharashtra, India; Ramalingam M., Chettinad School of Pharmaceutical Sciences, Chettinad Academy of Research and Education, Chettinad Health City, Chennai, 603103, India; Kanakaraj L., Chettinad School of Pharmaceutical Sciences, Chettinad Academy of Research and Education, Chettinad Health City, Chennai, 603103, India; Kaliappan I., SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, India; Paudel A., Graz University of Technology, Institute of Process and Particle Engineering, Inffeldgasse 13/3, Graz, 8010, Austria
ML-Based Prediction Model for Cardiovascular Disease
Cardiovascular disease (CVD); Logistic regression; Nae Bayes; Random forest
In this paper, the prediction of cardiovascular disease model based on the machine learning algorithm is implemented. In medical system applications, data mining and machine learning play an important role. Machine learning algorithms will predict heart disease or cardiovascular disease. Initially, online datasets are applied to preprocessing stage. Preprocessing stage will divide the data from baseline data. In the same way, CVD events are collected from data follow-ups. After that, data will be screened using the regression model. The regression model consists of logistic regression, support vector machine, nae Bayes, random forest, and K-nearest neighbors. Based on the techniques, the disease will be classified. Before classification, a testing procedure will be performed. At last from results, it can observe that accuracy, misclassification, and reliability will be increased in a very effective way. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Lecture Notes in Networks and Systems, Vol-490, pp. 91-98.
Springer Science and Business Media Deutschland GmbH
Nagavelli U., Dayananda Sagar Research Foundation, University of Mysore (UoM), Karnataka, Mysore, India; Samanta D., Dayananda Sagar Research Foundation, University of Mysore (UoM), Karnataka, Mysore, India, Department of Computer Science, CHRIST Deemed to be University, Karnataka, Bangalore, India; Thomas B., Department of Computer Science, CHRIST Deemed to be University, Karnataka, Bangalore, India
MLLR based speaker adaptation for indian accents
Automatic speech recognition (ASR); HMM (hidden markov model); Linear transformations; Maximum likelihood linear regression (MLLR); Speaker adaptation
Speech Recognition has become an inherent and important feature of today's mobile based apps. Speech input is a very popular option for people with limitations of using the keyboard / mouse in a computer system. Nowadays, more voice messages are used than written text as they also convey the emotions of the speakers. As solutions are developed with native speakers of a language, many of the English input systems have higher accuracy for native speakers than for people with English as their second language (L2), especially for Asian population. The complexity increases since the accent and intonation of Indian speakers are varied from region to region and state to state. This paper analyses an effective speaker adaptation mechanism implemented with Indian speaker profiles and with a very small amount of adaptation data. This research is to facilitate a speaker adaptive system for the speech disabled users with limited disabilities like stuttering and/or unintelligible speech due to illness like cerebral palsy. Experimental results show improvements in the recognition accuracy for speakers speaking small sentences. 2017 University of Bahrain. All rights reserved.
International Journal of Computing and Digital Systems, Vol-6, No. 5, pp. 293-301.
https://doi.org/10.12785/IJCDS/060508 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104911803&doi=10.12785%2fIJCDS%2f060508&partnerID=40&md5=c9e9cbf48c5864d71fd361c3855030b5
Balaji V., Department of Computer Science, Christ University, Bangalore, India; Sadashivappa G., Department of Telecommunication Engineering, R V College of Engineering, Bangalore, India
MMOF: A Multi-Metric Objective Function for Congestion Detection Under Varying Transmission Ranges in RPL-Based WSN
Congestion detection in RPL; Multi-metric objective function; RPL congestion; RPL congestion using Cooja; Transmission range
The Routing Protocol for Low Power Lossy Networks (RPL) is prone to congestion under high traffic. The single-path routing strategy and single-parent selection make RPL energy and resource-efficient only when the traffic is low and uniform. Two Objective Functions (OFs) are defined for RPL, which use single routing metrics-Expected Transmission Count (ETX) and hop count, to select the best parent and path toward the root. However, considering a single metric for OFs is unsuitable for detecting congestion in Lossy Networks (LLNs) applications as each metric has limitations. The current study proposes a novel Multi-Metric Objective Function (MMOF) that combines these two metrics and removes the weakness of the existing OFs. The proposed MMOF works under the nodes' varying transmission ranges (Tx ranges) to reduce the congestion. By changing Tx ranges, we show that the congestion in a fixed topology RPL network reduces, and MMOF can detect this congestion state more accurately than the existing OFs. The research introduces a successful transmission probability metric that makes MMOF more efficient in detecting congestion than ETX and Hop-Count. We prove that considering these two parameters individually is misleading and cannot contribute 100% to detect congestion state. Increasing transmission range can decrease congestion, and MMOF can detect this state transition with 100% accuracy. Simulation results in Cooja show that MMOF outperforms these two metrics and that the robust metric shows a linear relationship with the Tx range. Finally, two quality of service (QoS) parameters are derived to prove the method's efficiency and novelty. The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.
Srivastava V., Department of Computer Science, Banasthali Vidyapith, Raj, India; Paul A., Department of Computer Science, Banasthali Vidyapith, Raj, India; Sinha S., Department of Computer Science, CHRIST Deemed to Be University, Bengaluru, India
Mn2(CO)10 catalyzed visible-light-promoted synthesis of 1H-pyrazole-4-carboxamides; A sustainable multi-component statergy with antibacterial and cytotoxic evaluations
1H-pyrazole-4-carboxamides; Antimicrobial activity; Cytotoxicity; E. coli; P. aeruginosa
Multicomponent reactions play a pivotal role in synthesizing 1H-pyrazole-4-carboxamides, underscoring its significance in sustainable organic synthesis. These compounds, valued for their diverse biological activities, have garnered substantial attention in pharmaceutical research. A facile, rapid one-pot strategy to access an extensive array of 1H-pyrazole-4-carboxamide derivatives, utilizing substituted aldehydes, cyanoacetamide, and hydrazine hydrate as substrates and a readily accessible Mn2(CO)10 as photocatalyst in EL: H2O (1:1). Among the synthesized series, products 4b, 4 g, 4k showed remarkable antibacterial activity against E coli, P aeruginosa, S. aureus in agar medium and excellent cytotoxicity with Human colorectal carcinoma (HCT-116), Liver cancer cells (Hep-G2) and breast adenocarcinoma (MCF-7) cell lines. The current method is characterized by its affordability, non-toxicity, easy access to starting materials, and notably with minimal waste generation. Additionally, remarkable aspects include its mild operating conditions, environmentally friendly nature, and the ability to accommodate a wide range of both electron-donating and electron-withdrawing groups. 2024 The Author(s)
Govindaraju S.; Ramaraj S.G.; Servesh A.; Rajprasad J.; Kumar N.; Sadaiyandi V.; Tabassum S.
Journal of Organometallic Chemistry, Vol-1022
All Open Access; Hybrid Gold Open Access
https://doi.org/10.1016/j.jorganchem.2024.123384 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204361538&doi=10.1016%2fj.jorganchem.2024.123384&partnerID=40&md5=8622fe571b78b52e8356e14a984176ed
Govindaraju S., Department of Sciences and Humanities, Christ University, School of Engineering and Technology, Kumbalagodu, Mysore Road, Bengaluru, 560074, India; Ramaraj S.G., Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Japan, Department of Materials Physics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMTS), Thandalam, Tamilnadu, Chennai, 602105, India; Servesh A., Department of Chemistry, Christ University, Hosur Road, Bengaluru, 560029, India; Rajprasad J., Department of Civil Engineering, College of Engineering and Technology, SRM Institute of Science and Technology, Tamilnadu, Kattankulathur, 603203, India; Kumar N., Department of Electronics & Communication Engineering, Graphic Era Deemed to be University, Uttarakhand, Dehradun, 248002, India; Sadaiyandi V., Department of physics and nanotechnology, SRM Institute of Science and Technology kattankulathur, Tamilnadu, Chengalpattu, India; Tabassum S., Department of Chemistry, Surana College - Autonomous, South End Road, Basavanagudi, Bengaluru, 560004, India
MnO2 anchored NTi3C2 MXene as a bifunctional electrode for enhanced water splitting
Energy; Hydrogen evolution reaction; MnO2; Overall water splitting; Oxygen evolution reaction; Ti3C2 MXene
The domain of energy research is vigorously exploring a wide array of materials, from advanced carbon-based substances like graphene and carbon nanotubes to emerging contenders like MXenes. Ti3C2 MXene offers exceptional performance in electrochemistry, benefiting from its remarkable electronic conductivity, considerable surface area, chemical stability, cost-effectiveness, hydrophilicity, and eco-friendliness. However, it undergoes self-accumulation, which diminishes the number of electrochemically active sites, resulting in decreased performance. In this study, MnO2 particles are intricately anchored onto the surfaces and within the layers of nitrogen-doped Ti3C2 (NTi3C2), resulting in the creation of innovative interface engineered NTi3C2/MnO2 nanosheets. Due to its distinctive heterostructure and favourable interfacial interaction, the NTi3C2/MnO2 electrode shows better performance in both the hydrogen and oxygen evolution reactions, exhibiting low overpotentials of 130 mV and 289 mV, respectively, at a current density of 10 mA cm?2. Furthermore, it requires a cell voltage of 1.7 V to achieve a current density of 10 mA cm?2 during the overall water splitting process. The NTi3C2/MnO2 composite also maintains sustained durability for a period of 4 h. This enhanced electrochemical activity of NTi3C2/MnO2 can be due to the synergistic effects resulting from the intricate contact between NTi3C2 and MnO2. This research presents a simple methodology for designing MXenes-based multicomponent electrodes for electrochemical water splitting reactions and its potential application for electrochemical water splitting. 2024 Hydrogen Energy Publications LLC
International Journal of Hydrogen Energy, Vol-71, pp. 1283-1292.
https://doi.org/10.1016/j.ijhydene.2024.05.323 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193966862&doi=10.1016%2fj.ijhydene.2024.05.323&partnerID=40&md5=7001b60c99b4d2182a0aa6aef77b40ac
Mathew S., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Devi K R S., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India
MnO2 Nanoclusters Decorated on GrapheneModified Pencil Graphite Electrode for Non-Enzymatic Determination of Cholesterol
Cholesterol; Electrooxidation; Graphene; MnO2; Pencil graphite electrode
Electrochemically deposited MnO2 on graphene coated Pencil Graphite Electrode (PGE) has been used to develop a facile electrochemical sensor for the determination of Cholesterol. Cyclic voltammetric (CV) studies and electrochemical impedance spectroscopic (EIS) technique were used to investigate the electrochemical properties of the modified sensing platform. The physicochemical properties of the modified electrodes were characterized by X-ray photoelectron spectroscopy (XPS), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM), X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR). The experimental conditions such as effect of scan rate, concentration and pH were optimized. The linear dynamic range for the determination of Cholesterol was found to be 120?10 M2400?10 M under optimum conditions. The ultralow level of detection limit (0.42 nM) demonstrates the high sensitivity of the proposed method. The developed method was successfully applied for the non-enzymatic determination of Cholesterol in human blood samples at ultralow levels. 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim
Rison S.; Akshaya K.B.; Bhat V.S.; Shanker G.; Maiyalagan T.; Joice E.K.; Hegde G.; Varghese A.
Electroanalysis, Vol-32, No. 10, pp. 2128-2136.
https://doi.org/10.1002/elan.202000049 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087736425&doi=10.1002%2felan.202000049&partnerID=40&md5=58a24c1bdb09675732de1e7e17197ff4
Rison S., Christ Academy Institute for Advanced Studies, Christ Nagar, Bangalore, 560083, India, Department of Chemistry, CHRIST Deemed to be University, Bangalore, 560029, India; Akshaya K.B., Department of Chemistry, CHRIST Deemed to be University, Bangalore, 560029, India; Bhat V.S., Centre for Nano-materials and Displays, B.M.S. College of Engineering, Bull Temple Road, Bengaluru, 560019, India; Shanker G., Department of Chemistry, JnanaBharati Campus, Bangalore University, Bangalore, India; Maiyalagan T., Department of Chemistry, SRM Institute of Science and Technology, Kattankulathur, 603203, India; Joice E.K., Christ Academy Institute for Advanced Studies, Christ Nagar, Bangalore, 560083, India; Hegde G., Centre for Nano-materials and Displays, B.M.S. College of Engineering, Bull Temple Road, Bengaluru, 560019, India; Varghese A., Department of Chemistry, CHRIST Deemed to be University, Bangalore, 560029, India