Tumor Infiltration of Microrobot using Magnetic torque and AI Technique
ANFIS; CNN; Disease Prediction; Machine learning
Because of their surroundings and lifestyle alternatives, human beings, these days be afflicted by a huge style of illnesses. thus, early contamination prediction will become crucial. on the other hand, primarily based just on signs, docs warfare to make correct forecasts. The most challenging issue is accurately forecasting illnesses, which is why machine learning is essential to accomplish this task. To identify concealed patterns within vast amounts of medical data, disease information is processed using data mining techniques. We evolved a extensive contamination prediction primarily based on the affected person's signs. We rent the device getting to know techniques Convolutional Neural network (CNN) and ANFIS to exactly count on sickness (adaptive community-based totally fuzzy inference machine). For an correct forecast, this trendy illness prediction considers the character's way of life picks and fitness history. ANFIS outperforms CNN's set of rules in phrases of popular infection prediction, with an accuracy price of 96.7%. additionally, CNN consumes extra memory and processing energy than ANFIS because it trains and assessments on facts from the UCI repository. The Anaconda notebook is a suitable tool for implementing Python programming as it contains a range of libraries and header files that enhance the accuracy and precision of the process. 2023 IEEE.
Shalini R.; Mishra L.; Athulya S.; Chimankar A.G.; Kandavalli S.R.; Keshav Kumar K.; Selvan R.S.
ViTECoN 2023 - 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, Proceedings
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ViTECoN58111.2023.10157336 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165534220&doi=10.1109%2fViTECoN58111.2023.10157336&partnerID=40&md5=ecb0e66b1c15e33dea8bbf8b83f3e250
Shalini R., School of Computing Sciences, Vels Institute of Science Technology and Advanced Studies, Department of BCA & IT, Chennai, India; Mishra L., Khwaja Moinuddin Chishti Language University, Department of Electronics and Communication Engineering, Uttar Pradesh, India; Athulya S., Christ Deemed to Be University, Faculty of Engineering, Department of Computer Science and Engineering, Bangalore, India; Chimankar A.G., Chatrapati Shivaji BCA and BCS College, Department of B.Sc. Computer Science, Maharashtra, India; Kandavalli S.R., Sri Padmavati Mahila Visva Vidyalayam, Department of Electronics and Communication Engineering, Tirupati, India; Keshav Kumar K., G. Narayanamma Institute of Technology and Science, Department of Humanities and Mathematics, Hyderabad, India; Selvan R.S., Annamacharya Institute of Technology & Sciences, Department of Electronics and Communication Engineering, Tirupati, India
Synthesis and characterization of Cr2AlC MAX phase for photocatalytic applications
Cationic dyes; Cr2AlC MAX phase; Degradation; Photocatalysis
MAX phase, a layered ternary carbide/nitride, displays both ceramic and metallic properties, which has significantly attracted the materials research. In this work, Cr2AlC MAX phase powder with high purity was fabricated via a facile and cost-effective pressure-less sintering methodology and utilized for photocatalytic degradation of different organic pollutants for the first time. Various characterization techniques were used for confirming the morphological and other physico-chemical properties of the catalyst. Cr2AlC MAX phase with a low band gap of 1.28 eV has shown 99% efficiency in the degradation of malachite green, an organic pollutant under visible light irradiation. The scavenger studies conclude that, O2?and h+ as the active species during the photocatalytic reaction. Furthermore, the kinetic study revealed that the reaction obeys pseudo-first-order kinetics and can be reused for four cycles without losing the activity. This novel approach can give new insight into the potential application of MAX phase materials in the field of wastewater treatment under visible light irradiation. 2021 Elsevier Ltd
Shalini Reghunath B.; Davis D.; Sunaja Devi K.R.
ISSN: 456535; PubMed ID: 34467941; CODEN: CMSHA
https://doi.org/10.1016/j.chemosphere.2021.131281 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109470646&doi=10.1016%2fj.chemosphere.2021.131281&partnerID=40&md5=a419f5bded7834fa7a7d856d9582ebd5
Shalini Reghunath B., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, Karnataka, India; Davis D., Department of Physics and Nanotechnology, Faculty of Engineering and Technology, SRM Institute of Science and Technology (Deemed to be University), Chennai, 603203, Tamil Nadu, India; Sunaja Devi K.R., Department of Chemistry, CHRIST (Deemed to be University), Bangalore, 560029, Karnataka, India
Fabrication of bismuth ferrite/graphitic carbon nitride/N-doped graphene quantum dots composite for high performance supercapacitors
Asymmetric supercapacitor; Bismuth ferrite; Graphene quantum dots; Graphitic carbon nitride; Nanocomposite
Supercapacitors are potential energy storage devices with a broad range of applications. In this study, we are investigating a bismuth ferrite/graphitic carbon nitride/N-doped graphene quantum dots composite as an electrode material for supercapacitor applications. XRD patterns of the composite exhibit the different crystalline phases of the individual component and confirm the rhombohedral structure of the composite. The wafer-like structure of bismuth ferrite is produced via hydrothermal technique supported on 2D structures viz. graphitic carbon nitride and N-doped graphene quantum dots. Compared to bismuth ferrite and bismuth ferrite/graphitic carbon nitride (g-CN) binary composite, the bismuth ferrite/g-CN/N-doped graphene quantum dots demonstrates a superior specific capacitance of 1472 F g?1 at 1 A g?1 current density. After 3000 charging-discharging cycles, the device maintains its cycling stability with 87% capacitance retention. A supercapacitor device is assembled utilizing bismuth ferrite/graphitic carbon nitride/N-doped graphene quantum dots and activated carbon as electrodes. This device shows a significantly improved performance with an energy density of 53.1 Wh kg?1 and a power density of 705.4 W kg?1. As a result, the composite electrode developed in this study is proved to be a potential electrode material for high-performance energy storage devices. 2022
Shalini Reghunath B.; Rajasekaran S.; Devi K R S.; Saravanakumar B.; William J.J.; Pinheiro D.; Govindarajan D.; Kheawhom S.
Journal of Physics and Chemistry of Solids, Vol-171
https://doi.org/10.1016/j.jpcs.2022.110985 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138124473&doi=10.1016%2fj.jpcs.2022.110985&partnerID=40&md5=ae344d980d72316e819df1c1072c2bb4
Shalini Reghunath B., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Rajasekaran S., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Devi K R S., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Saravanakumar B., Department of Physics, Dr. Mahalingam College of Engineering and Technology, Tamilnadu, Pollachi, 642003, India; William J.J., Department of Physics, Dr. Mahalingam College of Engineering and Technology, Tamilnadu, Pollachi, 642003, India; Pinheiro D., Department of Chemistry, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Govindarajan D., Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand; Kheawhom S., Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand, Research Unit of Advanced Materials for Energy Storage, Chulalongkorn University, Bangkok, 10330, Thailand, Bio-Circular-Green-economy Technology & Engineering Center (BCGeTEC), Faculty of Engineering, Chulalongkorn University, Bangkok, 10330, Thailand
Real-time Litter Recognition Using Improved YOLOv4 Tiny Algorithm
fully connected layer; litter; object detection; prediction time; YOLOv4-Tiny
Littered roads have become a familiar sight in India. The main reason is the increasing population and inefficient waste disposal system. Since garbage collectors cannot pick litter in all the places, there is a need for an efficient way to detect it. Hence, a machine learning-based object detection model is used. In this, we have applied an improved YOLOv4-Tiny algorithm to detect the garbage, classify it and make the detection process easier on custom datasets. We have improved the algorithm in terms of the object prediction time, this is done by replacing a max pooling layer with one of two layers present in a fully connected layer. When an input is given, the algorithm detects the litter in the image with a bounding box around it along with the label and confidence score. The proposed model reduces the prediction time by 0.517 milliseconds less than the original algorithm employed which concludes that the object is predicted faster. 2022 IEEE.
Shalini V.; Tangade S.; Prajna P.K.; Sangeetha J.P.; Azam F.; Anoop G.L.
MysuruCon 2022 - 2022 IEEE 2nd Mysore Sub Section International Conference
https://doi.org/10.1109/MysuruCon55714.2022.9972356 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145347420&doi=10.1109%2fMysuruCon55714.2022.9972356&partnerID=40&md5=770727b3bd0f9a0ea00f103ad5a04248
Shalini V., Reva University, School of Electronics and Commn. Engg, Bangalore, India; Tangade S., Christ (Deemed to Be University), Dept. of Cse, Bangalore, India; Prajna P.K., Reva University, School of Electronics and Commn. Engg, Bangalore, India; Sangeetha J.P., Reva University, School of Electronics and Commn. Engg, Bangalore, India; Azam F., School of Comp. Science & Engineering, Reva University, Bangalore, India; Anoop G.L., Christ (Deemed to Be University), Dept. of Cse, Bangalore, India
Explainable Artificial Intelligence: Frameworks for Ensuring the Trustworthiness
and Transparency; Autonomy; Control; Data Privacy; Fairness; Reliability; Safety and Security
The growing computer power and ubiquity of big data are allowing Artificial Intelligence (AI) to gain widespread adoption and applicability in a wide range of sectors. The absence of an explanation for the conclusions made by today's AI algorithms is a significant disadvantage in crucial decision-making systems. For example, existing black-box AI systems are vulnerable to bias and adversarial assaults, which can taint the learning and inference processes. Explainable AI (XAI) is a recent trend in AI algorithms that gives explanations for their AI conclusions. Many contemporary AI systems have been shown to be vulnerable to undetectable assaults, biased against underrepresented groups, and deficient in user privacy protection. These flaws damage the user experience and undermine people's faith in all AI systems. This study proposes a systematic way to tie the social science notions of trust to the technology employed in AI-based services and products. 2024 IEEE.
TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024
Shama U., Christ University, Banglore, India; Sharma V., Christ University, Banglore, India; Gupta V., Christ University, Banglore, India
A Road to Become Successful in The Fashion Industry of China: A Case Study of Zara
Zara issues in China, Zara improvement tactics in China
In this research, it was found that Zara is facing issues while maintain its profitability and also while maintaining its large stores. Existing information collected from websites and articles show that Zara provides inferior quality products, does not have factory in China, focuses less on e-commerce activities and contributes directly to environment pollution through waste generation in China. These are reasons that the organization is losing its brand image in China. To improve its current condition, it is recommended that Zara should improve its products, focus more on marketing, develop factories in China and reduce environment pollution. The Electrochemical Society
Shameem A.; Poornachandrika T.S.; Giri P.; Bakshi P.K.
ECS Transactions, Vol-107, No. 1, pp. 18227-18234.
https://doi.org/10.1149/10701.18227ecst https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134042467&doi=10.1149%2f10701.18227ecst&partnerID=40&md5=0a0c4483c28572a96333b0b391cc5e60
Shameem A., Department of Commerce, AMET Deemed to be University, Tamil Nadu, Chennai, India; Poornachandrika T.S., CBIT- School of Management Studies, Chaitanya Bharathi Institute of Technology, Hyderabad, India; Giri P., School of Business and Management, Christ (Deemed to be University), Delhi NCR, India; Bakshi P.K., Department of Commerce, PGDAV College Evening of University of Delhi, Delhi, India
Hydrogen Sulfide-Induced Activatable Photodynamic Therapy Adjunct to Disruption of Subcellular Glycolysis in Cancer Cells by a Fluorescence-SERS Bimodal Iridium Metal-Organic Hybrid
activatable PDT; ATP reduction; clinical validation; disrupting glycolysis; enhanced apoptosis; H2S depletion; stimuli-responsive activation
The practical application of photodynamic therapy (PDT) demands targeted and activatable photosensitizers to mitigate off-target phototoxicity common in always on photosensitizers during light exposure. Herein, a cyclometalated iridium complex-based activatable photodynamic molecular hybrid, Cy-Ir-7-nitrobenzofurazan (NBD), is demonstrated as a biomedicine for molecular precision. This design integrates a hydrogen sulfide (H2S)-responsive NBD unit with a hydroxy-appended iridium complex, Cy-Ir-OH. In normal physiological conditions, the electron-rich Ir metal center exerts electron transfer to the NBD unit, quenches the excited state dynamics, and establishes a PDT-off state. Upon exposure to H2S, Cy-Ir-NBD activates into the potent photosensitizer Cy-Ir-OH through nucleophilic substitution. This mechanism ensures exceptional specificity, enabling targeted phototherapy in H2S-rich cancer cells. Additionally, we observed that Cy-Ir-NBD-induced H2S depletion disrupts S-sulfhydration of the glyceraldehyde-3-phosphate dehydrogenase enzyme, impairing glycolysis and ATP production in the cellular milieu. This sequential therapeutic process of Cy-Ir-NBD is governed by the positively charged central iridium ion that ensures mitochondria-mediated apoptosis in cancer cells. Dual-modality SERS and fluorescence imaging validate apoptotic events, highlighting Cy-Ir-NBD as an advanced theranostic molecular entity for activatable PDT. Finally, as a proof of concept, clinical assessment is evaluated with the blood samples of breast cancer patients and healthy volunteers, based on their H2S overexpression capability through SERS and fluorescence, revealing Cy-Ir-NBD to be a promising predictor for PDT activation in advanced cancer phototherapy. 2024 American Chemical Society.
Shamjith S.; Murali V.P.; Joesph M.M.; Fathima T.S.; Chandana R.; Jayarajan R.O.; Maiti K.K.
ACS Applied Materials and Interfaces, Vol-16, No. 21, pp. 27114-27126.
https://doi.org/10.1021/acsami.4c02761 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193550318&doi=10.1021%2facsami.4c02761&partnerID=40&md5=a3c98ef71695e183c55fbf07f4d32c64
Shamjith S., Chemical Sciences & Technology Division (CSTD), Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science & Technology (CSIR-NIIST), Industrial Estate, Pappanamcode, Kerala, Thiruvananthapuram, 695019, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India; Murali V.P., Chemical Sciences & Technology Division (CSTD), Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science & Technology (CSIR-NIIST), Industrial Estate, Pappanamcode, Kerala, Thiruvananthapuram, 695019, India; Joesph M.M., Department of Life Sciences, Christ University, Bangalore, 560029, India; Fathima T.S., Chemical Sciences & Technology Division (CSTD), Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science & Technology (CSIR-NIIST), Industrial Estate, Pappanamcode, Kerala, Thiruvananthapuram, 695019, India; Chandana R., Chemical Sciences & Technology Division (CSTD), Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science & Technology (CSIR-NIIST), Industrial Estate, Pappanamcode, Kerala, Thiruvananthapuram, 695019, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India; Jayarajan R.O., Chemical Sciences & Technology Division (CSTD), Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science & Technology (CSIR-NIIST), Industrial Estate, Pappanamcode, Kerala, Thiruvananthapuram, 695019, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India; Maiti K.K., Chemical Sciences & Technology Division (CSTD), Organic Chemistry Section, CSIR-National Institute for Interdisciplinary Science & Technology (CSIR-NIIST), Industrial Estate, Pappanamcode, Kerala, Thiruvananthapuram, 695019, India, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
An objective function based technique for devignetting fundus imagery using MST
Average gradient of illumination component; Devignetting; Error of enhancement; Fundus imagery; Illumination correction; Modified sigmoid transform (MST); Objective function
Fundus photography is a powerful imaging modality that is utilized for detecting macular degeneration, retinal neoplasms, choroid disturbances, glaucoma and diabetic retinopathy. As the illumination source in fundus imaging is situated at the center of the fundus camera, the illumination at the peripheral regions of the images would be relatively less than the center, which is termed vignetting. Vignetting adversely affects the performance of computerized methods for analyzing fundus imagery. A devignetting method for fundus imagery based on the Modified Sigmoid Transform (MST) is proposed in this paper. Gain (A) and centering parameter (?) of MST have a crucial influence on its performance. For low values of the gain, local contrast is penalized, and the overall dynamic range is compressed. When the value of gain is very high, the images after the illumination correction will have a washed out appearance. The optimum value of gain is determined in this paper from an objective method based on two statistical indices, Average Gradient of Illumination Component (AGIC) and Error of Enhancement (EME). MST with gain value defined via objective methods is able to correct the uneven illumination in fundus images without penalizing the local contrast. The proposed method is compared with illumination equalization model, homomorphic filtering and Adaptive Gamma Correction (AGC) and was found to be superior in terms of naturality uniformity of background illumination, and computational speed. 2018
Informatics in Medicine Unlocked, Vol-14, pp. 82-91.
https://doi.org/10.1016/j.imu.2018.10.001 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063113770&doi=10.1016%2fj.imu.2018.10.001&partnerID=40&md5=397867d4f7a3de513dde9ed18dc3c689
Shamsudeen F.M., School of Computer Science, MG University, Kottayam, India, Department of Computer Applications, TKM College of Engineering, India; Raju G., Department of Computer Science and Engineering, Faculty of Engineering, Christ (deemed to be University), Kanminike, Kumbalagod Post, Bengaluru, 560074, India
Plant Disease Detection and Classification using Emperor Penguin Optimizer (EPO) based Region Convolutional Neural Network (RCNN)
computer vision; crop yield; deep learning (DL); Emperor Penguin Optimizer (EPO); Plant Disease Detection; Region Convolutional Neural Network (RCNN)
Agriculture stands as India's most crucial industry, despite grappling with a 35% annual loss in crop yield attributed to plant diseases. Traditionally, the detection of plant diseases has been a laborious process, hampered by insufficient laboratory infrastructure and expert knowledge. Plant disease detection methods that are automated provide a useful way to expedite the labor-intensive process of keeping an eye on large-scale agricultural fields and recognizing disease symptoms as soon as they appear on plant leaves. Current developments in deep learning (DL) and computer vision have highlighted the benefits of creating autonomous models for plant disease identification based on visible symptoms on leaves. In this study, we propose a novel method for detecting and classifying plant diseases by combining the Emperor Penguin Optimizer (EPO) with a Region Convolutional Neural Network (RCNN). The suggested methodology uses EPO to improve the discriminative power of features extracted from plant pictures, allowing for a more robust and accurate classification procedure. The Classification Region Convolutional Neural Network (RCNN) is used to leverage spatial correlations within the image, allowing for exact disease region localization. The goal of this integration is to increase the overall efficiency and dependability of plant disease detection systems. The investigations made use of the well-known PlantVillage dataset, which comprises 54,305 data of different plant disease types in 38 categories. Furthermore, an analysis was carried out in comparison with similar advanced investigations. According to the experiment results, RCNN-EPO outperformed in terms of classification accuracy, achieving 94.552%. 2024 IEEE.
Shanbhog M.; Bhatia N.; Singh A.S.; Pavithra M.
Shanbhog M., Christ (Deemed to Be University), School of Sciences, Department of Computer Science, Delhi NCR, India; Bhatia N., Panipat Institute of Engineering and Technology, Department of Information Technology, Haryana, Panipat, India; Singh A.S., MIT-ADT, School of Computing, Department of Information and Technology, Maharashtra, Pune, India; Pavithra M., Panimalar Engineering College, Department of Computer Science and Business Systems, Chennai, India
Bibliometric Analysis: A Trends and Advancement in Clustering Techniques on VANET
Bibliometric analysis; Cluster formation; Cluster head; Cluster stability; Clustering; VANET; VOS viewer
In recent years, Traffic management and road safety has become a major concern for all countries around the globe. Many techniques and applications based on Intelligent Transportation Systems came into existence for road safety, traffic management and infotainment. To support the Intelligent Transport System, VANET has been implemented. With the highly dynamic nature of VANET and frequently changing topology network with high mobility of vehicles or nodes, dissemination of messages becomes a challenge. Clustering Technique is one of the methods which enhances network performance by maintaining communication link stability, sharing network resources, timely dissemination of information and making the network more reliable by using network bandwidth efficiently. This study uses bibliometric analysis to understand the impact of Clustering techniques on VANET from 2017 to 2022. The objective of the study was to understand the trends & advancement in clustering in VANET through bibliometric analysis. The publications were extracted from the Dimension database and the VOS viewer was used to visualize the research patterns. The findings provided valuable information on the publication author, authors country, year, authors organization affiliation, publication journal, citation etc. Based on the findings of this analysis, the other researchers may be able to design their studies better and add more perception or understanding to their empirical studies. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Lecture Notes in Networks and Systems, Vol-995, pp. 251-263.
Springer Science and Business Media Deutschland GmbH
Shandilya A., CHRIST (Deemed to Be University), Bengaluru, India; Gupta V., CHRIST (Deemed to Be University), Bengaluru, India; Anand G., CHRIST (Deemed to Be University), Bengaluru, India
An AHP-TOPSIS Approach for Optimizing the Mechanical Performance of Natural Fiber-Based Green Composites
Natural fibers have emerged as an effective replacement for synthetic fibers in the fabrication of green composites to be used for producing various components in automotive, aerospace, and other applications. In this proposed study, the mechanical properties of banana and coir fiber-based green composites have been optimized by using a hybrid AHP-TOPSIS approach. Corn starch along with glycerol has been used as the matrix material for fabricating the green composites. The mechanical properties such as tensile strength, flexural strength, and impact strength of the developed green composite have been optimized with a focus on the utilization of this composite in automotive and aerospace applications. Three different weight percentages (0%, 5%, and 10%) of banana and coir fibers was considered for the fabrication of green composites. The constituents of the green composite have been taken as the input variables whereas the mechanical properties of the green composite are considered as the output variables for designing the experiment. The design of the experiment consisted of nine different combinations of input and output variables. Results of the study revealed that 5 wt.% of banana fiber, 10 wt.% of coir fiber, and 85 wt.% of corn starch provide the optimum mechanical performance of the developed green composites. 2022 A. N. Shankar et al.
Shankar A.N.; Jagota V.; Jamadon N.H.; Raffik R.; Suneetha V.L.; Samori I.A.; Karnan L.
Advances in Materials Science and Engineering, Vol-2022
https://doi.org/10.1155/2022/1263237 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140824162&doi=10.1155%2f2022%2f1263237&partnerID=40&md5=8f2e0a75ad87bbb782a74353dcfc83be
Shankar A.N., Department of HSE & Civil Engineering, University of Petroleum & Energy Studies, Dehradun, India; Jagota V., Department of Mechanical Engineering, Madanapalle Institute of Technology and Science, Andhra Pradesh, Madanapalle, India; Jamadon N.H., Department of Mechanical and Manufacturing Engineering, Faculty of Engineering and Built Environment, National University of Malaysia, Bangi, 43600, Malaysia; Raffik R., Department of Mechatronics Engineering, Kumaraguru College of Technology, Tamil Nadu, Coimbatore, India; Suneetha V.L., Department of Physics, R. V. R. & J. C. College of Engineering, Andhra Pradesh, Chowdavaram, India; Samori I.A., School of Engineering Sciences, University of Ghana, Accra, Ghana; Karnan L., Department of Computer Science, CHRIST (Deemed to Be University), Bengaluru, India
Comparative Performance Analysis of Machine Learning and Deep Learning Techniques in Pneumonia Detection: A Study
Accuracy; Deep Learning; Machine Learning; performance; Pneumonia
Pneumonia is a bacterial or viral infection that inflames the air sacs in one or both lungs. It is a severe life-threatening disease, making it increasingly necessary to develop accurate and reliable artificial intelligence diagnosis models and take early action. This paper evaluates and compares various Machine Learning and Deep Learning models for pneumonia detection using chest X-rays. Six machine learning models -Logistic Regression, KNN, Decision Tree, Random Forest, Naive Bayes, and Support Vector Machines - and three deep learning models - CNN, VGG16, and ResNet - were created and compared with each other. The results exhibit how just the model choice can significantly affect the quality and inerrancy of the final diagnostic tool. 2023 IEEE.
Shankar A.P.; Shah S.; Ghosh S.; Ismail Z.; Vinay M.; Jayapriya J.; Deepa S.
2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023
https://doi.org/10.1109/ICCCNT56998.2023.10306711 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179854381&doi=10.1109%2fICCCNT56998.2023.10306711&partnerID=40&md5=bd9df23d5b55d6e62c6aea602b492e2a
Shankar A.P., Christ University, Karnataka, Bengaluru, India; Shah S., Christ University, Karnataka, Bengaluru, India; Ghosh S., Christ University, Karnataka, Bengaluru, India; Ismail Z., Christ University, Karnataka, Bengaluru, India; Vinay M., Christ University, Karnataka, Bengaluru, India; Jayapriya J., Christ University, Karnataka, Bengaluru, India; Deepa S., Christ University, Karnataka, Bengaluru, India
Work from home during covid-19-disequilibrium of mental health and well-being among employees
Leibniz Research Centre for Working Environment and Human Factors
https://doi.org/10.17179/EXCLI2021-4029 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114231320&doi=10.17179%2fEXCLI2021-4029&partnerID=40&md5=3766747e8bfee95beb54670419718fa0
Shankar N., School of Business and Management, CHRIST University, Hosur Road, Bengaluru, Karnataka, 560029, India
Hycons Renewable Private Limited: Viable Biogas Production from Paddy Straws: A Capital Budgeting Decision
Capital budgeting; funding techniques; net present value; sensitivity analysis
The case revolves around the decision to be taken by Mr Sashikant Hegde, Managing Director, Hycons Renewable Private Ltd, on the project viability of a business proposal. The proposal was to start a manufacturing plant in Punjab to produce compressed biogas using paddy straws. Hegde firmly believed that the company would do well considering the growth of the CNG market in India, as the oil and natural gas sector in India is among the top 10 core industries in the country and plays an important role in the existence of other important sectors as well. The proposal would benefit Hycons to establish its presence in northern India, but the project viability and funding of the investment remained an unanswered question. 2023 Lahore University of Management Sciences.
Shankar N., School of Business and Management, CHRIST University, Karnataka, Bangalore, India; Ramdas R., School of Business and Management, CHRIST University, Karnataka, Bangalore, India
Trends and patterns in fintech research: A bibliometric perspective
The traditional financial industry landscape has changed dramatically due to the quick development of financial technology, or Fintech, which has raised interest in academic study. In order to examine trends and patterns in Fintech research during the given time frame of 1980-2023, this study uses a bibliometric approach. Through a thorough analysis of an extensive library of academic publications, this study seeks to offer a complete grasp of the major topics, significant writers, and developing fields in the Fintech industry. Utilizing bibliometric methods and techniques, the methodology aims to derive meaningful insights from co- authorship patterns, citation networks, and metadata. By identifying the most cited papers, most contributing countries, and prolific writers, the study uses advanced data analytics to illuminate the intellectual framework of Fintech research. The findings of this research contribute to the identification of pivotal research clusters, highlighting the evolution of Fintech themes over time. 2024 by IGI Global.
Building Climate Neutral Economies Through Digital Business and Green Skills, pp. 259-276.
Shankar N., Christ University, India; Saha S., Reva University, India; Saha S.K., Christ University, India
Impact of green bonds issuance on stock prices - Evidence from India
Environment; Event Study; Green Bonds; Investors; Stock Prices
Today, with the increasing global warming, many companies are trying to adopt sustainable ways of producing the product and preserve the atmosphere. A green bond is one such financial tool that helps companies to raise the funds for social and eco-friendly projects. Keeping this in view and the Indian market emerging as the second-largest bond market in terms of green bond issuance; this paper aims to identify the impact on stock prices due to the issuance of green bonds by the companies. We conduct an event study to understand how the stock prices are subject to volatility due to green bond issuance during the period 2018-2021. The data is collected from secondary sources like Economic Times, Business Standard, Climate Bond Initiative, and the BSE website. The event window is assumed to be [-30,30], [-15, 15] and [-7, 7] days. Using Cumulative Average Abnormal returns and t-tests we understand the volatility of stock prices due to green bond issuance. The empirical results show that green bonds have a short-term impact on stock prices. Overall, the study can be a great input for the investors to understand the behavior of stocks due to the issuance of green bonds. 2023 Author(s).
AIP Conference Proceedings, Vol-2763, No. 1
https://doi.org/10.1063/5.0159422 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176792149&doi=10.1063%2f5.0159422&partnerID=40&md5=9a2c3d6898b14d340dac3f3716b75cb9
Shankar N., School of Business and Management, CHRIST (Deemed to Be University), Hosur road, Karnataka, Bangalore, India; Sharma S., School of Business and Management, CHRIST (Deemed to Be University), Hosur road, Karnataka, Bangalore, India
Financial well-being A Generation Z perspective using a Structural Equation Modeling approach
Financial behavior; Financial fragility; Financial literacy; Financial technology; India
The current pandemic situation in the global economy has urged the need to revolutionize the financial services industry with a keen eye on consumers financial needs for sound financial decisions, which is necessary for financial well-being. The purpose of the study is to assess the financial well-being of Indian Gen Z students in relation to financial literacy, financial fragility, financial behavior, and financial technology. In addition, the study also tries to determine how Gen Z students financial well-being is influenced by other factors such as gender, age, parental education, employment status, and monthly income in India. The study uses the scientific data analysis approach, Partial Least Squares-SEM model to estimate, predict, and assess the hypotheses. A sample of 271 University students from India was surveyed using a self-administered structured questionnaire. Questions were incorporated to understand the effect of financial literacy, technology, fragility, behavior, demographic and parental characteristics on financial well-being. The results indicate that financial behavior is positively related to financial well-being, while financial fragility is negatively associated. However, financial literacy and financial technology do not significantly affect financial well-being. The results also show that financial well-being is significantly influenced by gender, parental education, employment status, and monthly income change. Understanding Indian Gen Z student financial well-being will expand the students understanding of the importance of financial literacy for well-planned financial behavior and informed decisions, hence high levels of financial well-being. Government and financial institutions can more effectively identify gaps and deficiencies in student financial well-being. 2022 LLC CPC Business Perspectives. All rights reserved.
Investment Management and Financial Innovations, Vol-19, No. 1, pp. 32-50.
https://doi.org/10.21511/imfi.19(1).2022.03 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125864122&doi=10.21511%2fimfi.19%281%29.2022.03&partnerID=40&md5=7b08e2f62fb1f852534be99a5ae500ad
Shankar N., School of Business and Management, CHRIST University, India; Vinod S., Department of Computer Science, CHRIST University, India; Kamath R., School of Business and Management, CHRIST University, India
A mathematical model that describes the relation of low-density lipoprotein and oxygen concentrations in a stenosed artery
Endothelium; Finite element method; Hypoxia; Recirculation; Wall shear stress
The cellular activities of the endothelium layer between lumen and intima are significantly linked to the origin of the disease atherosclerosis. Three stages of atherosclerosis were investigated in this study (40%-mild, 50%-modest, and 60%-acute) concerning the coronary arterial segment. The essence of the hemodynamic factors like flow velocity, pressure, and wall shear stress has been investigated, as well as the interrelationships between them. At all degrees of stenosis, the biophysical relationship between convection-diffusion of low-density lipoproteins (LDL) and convection-diffusion of oxygen in the bloodstream is investigated. The Finite Element Methods (FEM) are used to solve the modeled partial differential equation systems. The method adopted is numerical in nature providing accurate graphical solutions to the framed systems. The physical effects of the deposition of LDL on the arterial wall, like a decrease in the diameter of the lumen, and toughening of the walls, are analyzed through the evaluation of the physical parameters. The study revealed that the deposition of LDL molecules in the post stenotic region leads to the depletion of oxygen in the region leading to the rapid dysfunctioning of the endothelial layer of the lumen-intima boundary. 2022 World Scientific Publishing Company.
Shankar Narayan S.; Anuradha B.; Sunanda S.; Puneeth V.; Ijaz Khan M.; Abdullah A.; Guedri K.; Jameel M.
International Journal of Modern Physics B, Vol-36, No. 26
Shankar Narayan S., Department of Mathematics, Cmr Institute of Technology, Bangalore, 560 037, India, Department of Mathematics, Dayananda Sagar University, Bangalore, 560 114, India; Anuradha B., Department of Mathematics, Dayananda Sagar University, Bangalore, 560 114, India; Sunanda S., Department of Mathematics, Vellore Institute of Technology, Vellore, 632 014, India; Puneeth V., Department of Mathematics, Christ (Deemed to Be University), Bangalore, 560 029, India; Ijaz Khan M., Department of Mathematics and Statistics, Ripah International University I-14, Islamabad, 44000, Pakistan, Mathematical Modelling and Applied Computation Research Group (MMAC), Department of Mathematics, King Abdulaziz University, Jeddah, Saudi Arabia; Abdullah A., Department of Mathematics, Taif University, Taif, 21944, Saudi Arabia; Guedri K., Mechanical Engineering Department, College of Engineering and Islamic Architecture, Umm Al-Qura University, P.O. Box 5555, Makkah, 21955, Saudi Arabia; Jameel M., Department of Civil Engineering, College of Engineering, King Khalid University, Asir, P.O. Box 960, Abha, 61421, Saudi Arabia
THE ANALYSIS OF THE FLOW OF BLOOD IN A STENOSED ARTERY THROUGH SIMULATION: A COMPARISON AMONG VARIOUS NON-NEWTONIAN MODELS
atherosclerosis; Coronary artery; low-density lipoprotein; rheology; stenosis
This paper focuses on the dual quality of blood, Newtonian and non-Newtonian, in particular by exploring the energy curves. Careful investigation of the dual property of blood has been made by considering two different geometries to represent a stenosed arterial segment. We present a cautious assessment of non-Newtonian blood rheology impacts in arterial stream simulations by coupling the Newtonian and non-Newtonian models. The flow of energy through the two flow dimensions is meticulously investigated using velocity (kinetic energy), pressure, and wall shear stress (pressure energy). Besides, the proper implementation of an interface boundary condition (IBC) was emphasized to ensure consistency with the flow conditions downstream of a backward-facing step. The integration of the Newtonian and non-Newtonian models adjoins the novelty of the current research. The energy curves are obtained by implementing five different non-Newtonian models to designate a suitable non-Newtonian model for blood flow investigations. The combination of the non-Newtonian models enforced in this research is novel and particular attention is paid to the energy curves obtained. The conclusion was to elect the Carreau model as a suitable non-Newtonian rheological model for the blood flow study. This study was able to finalize the fact that the coupling of Newtonian and non-Newtonian models is necessary to obtain accurate results. For the sinusoidal waveform considered for the velocity, Carreau and the Power law models yield better results, eliminating the other non-Newtonian models from the list. With a better inlet condition imposed in the form of the Fourier series for pressure and velocity, the Carreau model yields the best results. 2024 World Scientific Publishing Company.
Shankar Narayan S.; Bhattacharjee A.; Saha S.; Puneeth V.; Singhal A.; Sayfutdinovna Abdullaeva B.
Journal of Mechanics in Medicine and Biology, Vol-24, No. 7
Shankar Narayan S., Department of Mathematics and Statistics, Ramaiah University of Applied Sciences, Bengaluru, 560058, India; Bhattacharjee A., Department of Mathematics, Dayananda Sagar University, Bengaluru, 560058, India; Saha S., Department of Mathematics, Vellore Institute of Technology, Vellore, 632014, India; Puneeth V., Department of Computational Science, CHRIST (Deemed to be University), Ghaziabad, 201003, India; Singhal A., Department of Computational Science, CHRIST (Deemed to be University), Ghaziabad, 201003, India; Sayfutdinovna Abdullaeva B., Doctor of Pedagogical Sciences, Vice-Rector for Scientific Affairs, Tashkent State Pedagogical University, Tashkent, Uzbekistan
Possibilities for the Flow of Water and Blood through a Graphene Layer in a Geometry Analogous to Human Arterioles: An Observational Study
Newtonian; permeability; porosity; viscosity; von mises stress; wall shear stress
Atherosclerosis and aneurysm are two non-communicable diseases that affect the human arterial network. The arterioles undergo dimensional changes that prominently influence the flow of oxygen and nutrients to distal organs and organ systems. Several studies have emerged discussing the various possibilities for the circumstances surrounding the existence of these pathologies. In the present work, we analyze the flow of blood across the stenosis and the aneurysmic sac in contrast with the flow of water to explore alterations in the flow characteristics caused by introduction of the graphene layer. We investigate the blood flow past the graphene layer with varying porosity. The study is undertaken to replace usage of a stent along a blocked artery by inserting a thin layer of graphene along the flow channel in the post-pathological section of the geometry. To explain the flow, a 2D mathematical model is constructed, and the validity and exclusivity of the models solution are examined. When the artery wall is assumed to be inelastic, the computation of the mathematical system is evaluated using a finite element method (FEM) solver. We define a new parameter called critical porosity (Formula presented.) to explore the flow possibilities through the graphene layer. The findings indicate that the flow pattern was adversely affected by the graphene layer that was added to the flow field. The negative impact on the flow could be due to the position of the graphene layer placed. The (Formula presented.) values for the flow of blood across healthy arteriole, stenosed arteriole, and aneurysmic arteriole segments were (Formula presented.) and (Formula presented.) respectively. The critical porosity values were achieved with precision in terms of linear errors (Formula presented.), (Formula presented.), and (Formula presented.), respectively. The consequences of the present study disclose various possible ways to utilize graphene and its compounds in the medical and clinical arena, with a prior exploration of the chemical properties of the compound. The idea and the methodology applied for the present study are novel as there have been no previous research works available in this direction of the research field. 2023 by the authors.
Shankar Narayan S.; Saeed A.M.; Fatima N.; Al-Duais F.S.; Alharbi K.A.M.; Puneeth V.; Gorji M.R.; Kheder N.B.; Abdelmohsen S.A.M.
Applied Sciences (Switzerland), Vol-13, No. 3
https://doi.org/10.3390/app13032000 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148028726&doi=10.3390%2fapp13032000&partnerID=40&md5=67bd6dfba36ac2ac76a1e6f10a9a0ba7
Shankar Narayan S., Department of Mathematics & Statistics, Faculty of Mathematical & Physical Sciences (FMPS), Ramaiah University of Applied Sciences, Bengaluru, 560058, India; Saeed A.M., Department of Mathematics, College of Science, Qassim University, Buraydah, 52571, Saudi Arabia; Fatima N., Department of Mathematics and Sciences, Prince Sultan University, Riyadh, 11586, Saudi Arabia; Al-Duais F.S., Mathematics Department, College of Humanities and Science in Al Aflaj, Prince Sattam bin Abdulaziz University, Al Aflaj, 16278, Saudi Arabia; Alharbi K.A.M., Mechanical Engineering Department, College of Engineering, Umm Al-Qura University, Makkah, 24382, Saudi Arabia; Puneeth V., Department of Computational Sciences, CHRIST University, Bengaluru, 560029, India; Gorji M.R., Faculty of Medicine and Health Sciences, Ghent University, Ghent, 9000, Belgium; Kheder N.B., Department of Mechanical Engineering, College of Engineering, University of Hail, Hail, 81451, Saudi Arabia; Abdelmohsen S.A.M., Biophysics Department, Faculty of Science, Cairo University, Cairo, 12613, Egypt