Statistic analysis of IPL match score and winner inning wise using machine learning algorithms
Cricket analytics; Data analysis; IPL score prediction; Machine learning; Predictive modeling
This study explains the statistical analysis of cricket match score prediction using machine learning. According to recent changes in data science and sports, the use of sports-based machine learning and data mining shows the importance of process in outcome performance and prediction. The scope of this research paper is to evaluate current measurements used in the previous work to understand the estimation the ways used to model and analyze data and characterize the variables that govern performance using statistical methods. Actually, this research article will present a reliable statistical tool for data analysis using machine learning algorithms. At present, sports organizations produce enough statistical information on every player, team, match, and season for particular related sports. The first sports researchers were thought to be experts, coaches, team managers, and analysts. Sports organizations want to do statistical analysis of player from their previous data stored on their database using different data mining and machine learning algorithms. Sports data helps coaches and managers in many ways, such as predicting results, analyzing player performance, and skills, and evaluating strategies. Forecasts help managers and organizations make decisions to win teams and competitions. The current evaluation of research shows that primary studies of data mining systems can predict outcomes and evaluate the strengths and weaknesses of each system. Statistical analyses are made for each match for result predictions. Although in many respects this application is very limited. These are prime factors which important to examine machine learning algorithms in these situations to see if the application can give the nearest results in analysis. This research aims to give solutions that will help to make predictions more accurate and precise than previous methods, using more accurate data and machine learning. 2024, Taru Publications. All rights reserved.
Preety; Ray S.K.; Yadav M.; Khare A.; Mishra V.
Journal of Interdisciplinary Mathematics, Vol-27, No. 2, pp. 245-258.
https://doi.org/10.47974/JIM-1819 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188539125&doi=10.47974%2fJIM-1819&partnerID=40&md5=44273e83e4dd30c8839e4fb2646fd185
Preety, Department of Computer Science, Christ University, Uttar Pradesh, Ghaziabad, India; Ray S.K., Department of Mathematics and Statistics, Dr. Akhilesh Das Gupta Institute of Technology & Management, Delhi, India; Yadav M., Department of Information Technology, Galgotias College of Engineering and Technology, Uttar Pradesh, India; Khare A., Department of Computer Science and Engineering, Galgotias University, Uttar Pradesh, India; Mishra V., Department of Computer Science, Christ University, Uttar Pradesh, Ghaziabad, India
Sentence Classification Using Attention Model for E-Commerce Product Review
Deep Learning; Linear Support Vector Machine (LSVC); Logistic Regression (LR); Machine Learning; Multinomial Nae Bayes (MNB); N-Gram; Natural Language Processing (NLP); Neural Networks; Random Forest (RF); Text Classification; TF-IDF
The importance of aspect extraction in text classification, particularly in the e-commerce sector. E-commerce platforms generate vast amounts of textual data, such as comments, product descriptions, and customer reviews, which contain valuable information about various aspects of products or services. Aspect extraction involves identifying and classifying individual traits or aspects mentioned in textual reviews to understand customer opinions, improve products, and enhance the customer experience. The role of product reviews in e-commerce is discussed, emphasizing their value in aiding customers' purchase decisions and guiding businesses in product stocking and marketing strategies. Reviews are essential for boosting sales potential, maintaining a good reputation, and promoting brand recognition. Customers extensively research product reviews from different sources before purchasing, making them vital user-generated content for e-commerce businesses. The current work provided an efficient and novel classification model for sentence classification using the ABNAM model. The automated text classification models available cannot categorize the data into sixteen distinct classes. The technologies applied for the mentioned work contain TF-IDF, N-gram, CNN, linear SVM, random forest, Nae bays, and ABNAM with significant results. The best-performing ML method for the successful classification of a given sentence into one of the sixteen categories is achieved with the proposed model named the based Neural Attention Model (ABNAM), which has the highest accuracy at 97%. The research acclaimed ABNAM as a novel classification model with the highest-class categorizations. 2024 Nagendra N and Chandra J. This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
Journal of Computer Science, Vol-20, No. 5, pp. 535-547.
All Open Access; Hybrid Gold Open Access
https://doi.org/10.3844/jcssp.2024.535.547 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188239085&doi=10.3844%2fjcssp.2024.535.547&partnerID=40&md5=b28053f96307a12a68fb5e458856566a
Nagendra N., Department of Computer Science, Christ Deemed to be University, Bengaluru, India; Chandra J., Department of Computer Science, Christ Deemed to be University, Bengaluru, India
Enhanced Jaya Optimization Algorithm with Deep Learning Assisted Oral Cancer Diagnosis on IoT Healthcare Systems
Computer-assisted diagnoses; Deep learning; Healthcare; Internet of Things; Jaya Optimization Algorithm; Medical imaging; Oral cancer
Recently, healthcare systems integrate the power of deep learning (DL) models with the connectivity and data processing capabilities of the Internet of Things (IoT) to enhance the early recognition and diagnosis of disease. Oral cancer diagnosis comprises the detection of cancerous or pre-cancerous abrasions in the oral cavity. Timely identification is essential for successful treatment and enhanced prognosis. Here is an overview of the key aspects of oral cancer diagnosis. One potential benefit of utilizing DL for oral cancer detection is that it analyses huge counts of data fast and accurately, and it could not need clear programming of the rules for recognizing abnormalities. This can create the procedure of detecting oral cancer more effective and efficient. Thus, the study presents an Enhanced Jaya Optimization Algorithm with Deep Learning Based Oral Cancer Classification (EJOADL-OCC) method. The presented EJOADL-OCC method aims to classify and detect the existence of oral cancer accurately and effectively. To accomplish this, the presented EJOADL-OCC method initially exploits median filtering for the noise elimination. Next, the feature vector generation process is performed by the residual network (ResNetv2) model with EJOA as a hyperparameter optimizer. For accurate classification of oral cancer, a continuously restricted Boltzmann machine with a deep belief network (CRBM-DBN) model. The simulated validation of the EJOADL-OCC algorithm is tested by the series of simulations and the outcome demonstrates its supremacy over present DL approaches. 2024, American Scientific Publishing Group (ASPG). All rights reserved.
Rajkumar R.; Valluru D.; Siva Satya Sreedhar P.; Ramshankar N.; Sujatha S.; Somasundaram R.; Sudha M.; Navaneethan S.
Journal of Intelligent Systems and Internet of Things, Vol-11, No. 2, pp. 97-110.
American Scientific Publishing Group (ASPG)
https://doi.org/10.54216/JISIoT.110209 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189005327&doi=10.54216%2fJISIoT.110209&partnerID=40&md5=8e7251f6e1c2adb87150893aa151d51a
Rajkumar R., Department of ECE, Vel Tech Rangarajan Dr. Saguthala R&D institute of Science and Technology, Tamil Nadu, Chennai, India; Valluru D., Department of IT, MLRITM Engineering College, Hyderabad, India; Siva Satya Sreedhar P., Department of Information Technology, Seshadri Rao Gudlavalleru Engineering College, Krishna district, Andhra Pradesh, Gudlavalleru, India; Ramshankar N., Department of Computer Science and Engineering, R. M. D. Engineering College, Kavaraipettai, Tamil Nadu, Tiruvallur, India; Sujatha S., Department of Electronics and communication Engineering, Christ University, School of Engineering and Technology, Bangalore, India; Somasundaram R., Management Studies Department, Kongu Engineering College, Erode, 638060, India; Sudha M., Department of ECE, Paavai Engineering College (Autonomous), Tamilnadu, Namakkal, India; Navaneethan S., Department of ECE, Saveetha Engineering College, Tamil Nadu, Chennai, India
Bacillus cereus-mediated biofermentation of Sardine offal waste: A novel approach to enhance nutritional value by Response Surface Methodology optimization
Bacteria; Fish waste; Prebiotics; Response surface methodology; Solid state fermentation
The rising protein demand in the aquaculture sector has significantly impacted fishmeal supply and pricing. Excessive use of fishmeal can lead to environmental issues and negatively impact marine biodiversity and human food security. Consequently, finding alternative fishmeal in aquaculture is crucial for economic and environmental sustainability. The present study aimed to determine how Bacillus cereus (MT355408) could enhance nutritional value of Sardine fish waste, which could replace fish meal in the market. Solid-state fermentation (SSF) represents a biotechnological method that utilizes microbes to convert discarded fish byproducts into valuable products. The bacterial ability to produce enzymes was studied and optimised for its maximum production to be used as an inoculum for the SSF technique. Different prebiotic sources were also studied for better upliftment of bacteria in the solid-state surface. A single-factor analysis was conducted to investigate the influence of varying prebiotic concentrations, inoculum quantity, and fermentation duration on protein breakdown. After studying the single-factor tests, a further response surface model was employed for better yield. The results indicated that the highest protein yield could be achieved with a fermentation time of 132.893 hours, a prebiotic quantity of 25%, and an inoculum quantity of 5.3%. The study's findings also affirmed that the model was vital in enhancing the crude protein content during fermentation. In conclusion, the model's results contribute valuable insights into fermentation processes, offering practical implications for enhancing protein content and digestibility in similar contexts. 2024, Applied and Natural Science Foundation. All rights reserved.
Journal of Applied and Natural Science, Vol-16, No. 1, pp. 158-171.
https://doi.org/10.31018/jans.v16i1.5264 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188462650&doi=10.31018%2fjans.v16i1.5264&partnerID=40&md5=9727ef96b952f9ce66f29a28fd56b311
Samuel R.A., Department of Life Sciences, CHRIST (Deemed to be) University, Central Campus, Hosur Road, Karnataka, Bangalore, 560029, India; Paari K.A., Department of Life Sciences, CHRIST (Deemed to be) University, Central Campus, Hosur Road, Karnataka, Bangalore, 560029, India
A bibliometric analysis of sustainability and organizations performance
Bibliometric analysis; Co-citation analysis; Organizations performance; Sustainability
The incorporation of sustainability into an organizations performance is becoming an emerging topic to work upon. Moreover, conventional economic systems have had significant negative consequences for sustainable management, as well as imbalanced wealth distribution, which has resulted in natural catastrophes and population disparity. Sustainability practices in the current environment represent better quality performances and affect organizations performance. This research highlights the key areas and current evolution in the notion of sustainable development and organizational performance, as well as recommendations for further studies. Using the bibliometric analysis we examine a sample of 1442 articles published in Scopus between 1994 till 2021. The researcher identifies prominent authors, publications, and journals by employing a variety of network analysis techniques such as term co-occurrence, co-citation, and bibliography coupling with the help of VOS viewer. To the best of the authors knowledge, no other study has examined bibliographic data on sustainability and organizations performance; hence, this research is a one-of-a-kind addition to the literature. The Author(s), under exclusive licence to Springer Nature B.V. 2024.
Environment, Development and Sustainability
Springer Science and Business Media B.V.
Mishra P., GLA University, Mathura, India; Guru Sant T., GLA University, Mathura, India; Kumar K., Christ University, Bengaluru, India
Evidence of microRNAs origination from chloroplast genome and their role in regulating Photosystem II protein N (psbN) mRNA
chloroplast; miRNA; nuclei; photosystem II protein N; RACE-PCR
The microRNAs are endogenous, regulating gene expression either at the DNA or RNA level. Despite the availability of extensive studies on microRNA generation in plants, reports on their abundance, biogenesis, and consequent gene regulation in plant organelles remain naVve. Building on previous studies involving pre-miRNA sequencing in Abelmoschus esculentus, we demonstrated that three putative microRNAs were raised from the chloroplast genome. In the current study, we have characterized the genesis of these three microRNAs through a combination of bioinformatics and experimental approaches. The gene sequence for a miRNA, designated as AecpmiRNA1 (A. esculentus chloroplast miRNA), is potentially located in both the genomic DNA, i.e., nuclear and chloroplast genome. In contrast, the gene sequences for the other two miRNAs (AecpmiRNA2 and AecpmiRNA3) are exclusively present in the chloroplast genome. Target prediction revealed many potential mRNAs as targets for AecpmiRNAs. Further analysis using 5N RACE-PCR determined the AecpmiRNA3 binding and cleavage site at the photosystem II protein N (psbN). These results indicate that AecpmiRNAs are generated from the chloroplast genome, possessing the potential to regulate mRNAs arising from chloroplast gene(s). On the other side, the possibility of nuclear genome-derived mRNA regulation by AecpmiRNAs cannot be ruled out. 2024, Termedia Publishing House Ltd.. All rights reserved.
Anand A.; Chauhan S.; Chodon A.; Vimala Kumar K.V.; Saravanakumar S.; Pandi G.
Biotechnologia, Vol-105, No. 1, pp. 19-32.
All Open Access; Gold Open Access; Green Open Access
https://doi.org/10.5114/bta.2024.135639 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190791270&doi=10.5114%2fbta.2024.135639&partnerID=40&md5=cf08c7db4dbc1bdf231f3190247311bb
Anand A., Department of Plant Biotechnology, School of Biotechnology, Madurai Kamaraj University, Madurai, India, Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Chauhan S., Department of Plant Biotechnology, School of Biotechnology, Madurai Kamaraj University, Madurai, India; Chodon A., Department of Plant Biotechnology, School of Biotechnology, Madurai Kamaraj University, Madurai, India; Vimala Kumar K.V., Department of Plant Biotechnology, School of Biotechnology, Madurai Kamaraj University, Madurai, India; Saravanakumar S., Department of Plant Biotechnology, School of Biotechnology, Madurai Kamaraj University, Madurai, India; Pandi G., Department of Plant Biotechnology, School of Biotechnology, Madurai Kamaraj University, Madurai, India
The forgotten half: addressing the psychological challenges of wives of individuals with alcohol use disorder (AUD) in low- and middle-income countries
artificial intelligence-AI; low-and middle-income countries (LMICs); machine learning (ML); mental healthcare; psychological challenges; virtual reality (VR); wives of individuals with alcohol use disorder
https://doi.org/10.3389/fpsyt.2024.1377394 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189649190&doi=10.3389%2ffpsyt.2024.1377394&partnerID=40&md5=d170c04cb72bdb41d1462001ccca1018
Joseph A.P., Department of Sociology & Social Work, Christ (Deemed to be University), Karnataka, Bangalore, India, School of Social Work, Marian College Kuttikkanam Autonomous, Kuttikkanam, Kerala, India; Babu A., School of Social Work, Marian College Kuttikkanam Autonomous, Kuttikkanam, Kerala, India, School of Social Work, Tata Institute of Social Sciences Guwahati Off-Campus, Assam, Jalukbari, India; Prakash L.T.O., Department of Sociology & Social Work, Christ (Deemed to be University), Karnataka, Bangalore, India
A Comprehensive Study on Parametric Optimization of Plasma-Sprayed Cr2C3 Coatings on Al6061 Alloy
AA6061 aluminum alloy substrate; Analysis of variance; Bond strength; Cr2C3 coatings; Design of experiments; Fracture analysis; Microhardness; Plasma spray; Porosity
Plasma spray, a widely employed thermal spray method, is known for enhancing coatings with heightened microhardness, density, and bonding strength. In this study, Taguchis approach was applied to optimize processing parameters for plasma spray-coated surfaces, aiming to reduce porosity, increase hardness, and fortify the connection between Cr2C3 coatings. The design of experiments method facilitated the optimization of process parameters, utilizing signal-to-noise ratios and ANOVA analysis to assess the significance of each processing parameter and identify optimal parameter combinations. Powdered feed rate and stand-off distance emerged as the two most critical processing variables influencing permeability and hardness, contingent on signal-to-noise ratios. S/N ratio analysis was employed to determine the optimal processing parameters for permeability, hardness, and bonding strength. For porosity, the optimal stand-off distance, powdered feed rate, and current density were identified as 60rpm, 50g/min, and 460ampsmm/s, respectively. Exemplary process conditions for hardness included a powdered feed rate of 60g/min, a stand-off distance of 80rpm, and a current density of 480 amps. Lastly, for strength properties, the ideal process variables were a stand-off distance of 80rpm, a current density of 480amps, and a powdered feed rate of 60g/min. Despite small differences between projected R2 and modified R2 values in statistical data on permeability, hardness, and bonding strength, the proximity to the one emphasizing the fit of the linear regression used for analysis was evident. Fracture results from the binding strength test postulate mixed adhesion-cohesion type failures in the Cr2C3 coatings. The Institution of Engineers (India) 2024.
Kumar G.S.P.; Keshavamurthy R.; Santosh M.S.; Reddy S.N.; Tambrallimath V.
Journal of The Institution of Engineers (India): Series D
https://doi.org/10.1007/s40033-024-00692-x https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188444673&doi=10.1007%2fs40033-024-00692-x&partnerID=40&md5=bc5c3fd17c6fe6292bf5f535de0a6f64
Kumar G.S.P., Department of Automobile Engineering, CHRIST University, Bengaluru, 560074, India; Keshavamurthy R., Department of Mechanical Engineering, Dayananda Sagar College of Engineering, Bengaluru, 560078, India; Santosh M.S., Department of Automobile Engineering, CHRIST University, Bengaluru, 560074, India; Reddy S.N., Department of Automobile Engineering, CHRIST University, Bengaluru, 560074, India; Tambrallimath V., Department of Automobile Engineering, Dayananda Sagar College of Engineering, Bengaluru, 560078, India
Analysis of the Performance of a 5-Level Modular Multilevel Inverter for a Solar Grid-Connected System
five-level; matlab-simulink; multilevel inverter; photovoltaic; total harmonic distortion
The main purpose of a multilevel inverter is to combine numerous levels of DC voltage to create a nearly sinusoidal voltage. The synthesized output waveform has more stages as the number of levels rises, creating a staircase ripple which resembles the preferred waveform. As the number of voltage levels rises, the output waves harmonic distortion diminishes and eventually approaches zero. In particular, the performance analysis of a five-level inverter with variable loads is highlighted in this paper. This topology has fewer devices than traditional multilevel inverters for the same five output levels, which makes it more affordable due to lesser driver circuits. The proposed modular five level topology is simulated using both high frequencies switching pulse width modulation and basic frequency switching modulation techniques. The output voltage, current waveform, and total harmonic distortion are examined and compared using simulink to confirm the viability of the modular multilevel inverter topology. 2024, TUBITAK. All rights reserved.
El-Cezeri Journal of Science and Engineering, Vol-11, No. 1, pp. 103-108.
https://doi.org/10.31202/ecjse.1240222 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189566281&doi=10.31202%2fecjse.1240222&partnerID=40&md5=633400437683b18fbfea3397cf4f0e3d
Ezhilvannan P., Department of EEE, Sree Vidyanikethan Engineering College, Tirupati, India; Krishnan S., Department of EEE, Christ deemed to be University, Bengaluru, India
Building a sustainable relationship between customers and marketers
brand building; confirmatory factor analysis; CRM; customer relationship management; ethical marketing; promises delivery; sustainable relationship
Finding new customers is costlier than retaining the existing customers for the business. Therefore, building a strong relationship with customers helps marketers to retain their existing customers. Incorporating ethical and moral values into marketing activities offer a way to build a strong relationship. This study identifies the factors that bind customers and marketers into a sustainable relationship in the Indian context. This study constitutes a framework to understand and apply sustainable relationship marketing in the personal care industry. This study touches certain marketing disciplines such as marketing mix policy, transparency in trades, building trust, product delivery, promises delivery, and sustainable relationship. The convenience sampling technique used for the selection of respondents from the Mohali City of Punjab, and interview them. The finding suggests that promises delivery is the most important factor for a sustainable relationship. If promises are delivered effectively then the life of the relationship will be longer. Copyright 2024 Inderscience Enterprises Ltd.
International Journal of Business and Globalisation, Vol-36, No. 45718, pp. 241-258.
https://doi.org/10.1504/IJBG.2024.137390 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188579988&doi=10.1504%2fIJBG.2024.137390&partnerID=40&md5=5ae28a309bd1a26a925cfb00136c087c
Kushwaha B.P., VIT Business School, Vellore Institute of Technology, Vellore, 632014, India; Singh R.K., School of Management, Graphic Era Hill University, Dehradun, 248002, India; Varghese N., School of Business and Management, CHRIST (Deemed to be University), Lavasa, Pune, 412112, India
LET US DREAMS MIGRATION TO A GLOBAL VIRTUAL CONFERENCE: DELIVERING A SOCIAL ENTREPRENEURIAL EVENT
Community empowerment; COVID-19 pandemic; Cross-cultural; Event planning model; International conference; Social entrepreneurship; Transnational; Virtual conference
This case study applies Rudolph et al.s social entrepreneurship model to describe the migration of Let Us Dreams (LUD) face-to-face social entrepreneurial conference to a virtual platform during the COVID-19 pandemic. LUD Triennial International Conference focused on community service initiatives in the areas of education, health, and social services for the purpose of impacting local and international communities in a transformative way. Organizers experienced many positive outcomes (e.g., high attendance and participant satisfaction), human capital, and leadership development of its collaborative volunteer planning teams, and the empowerment of local and global communities. The discussion section elaborates on the social entrepreneurship model findings, and other lessons learned, and provides recommendations for others planning to deliver a virtual or hybrid conference in multicultural contexts. 2024 Cognizant, LLC.
Thomas L.; Curl A.L.; Thameling C.L.; Vijaya R.; Custer S.
Event Management, Vol-28, No. 2, pp. 215-228.
Thomas L., Department of Psychology, Christ University, Maharashtra, India; Curl A.L., Department of Family Science & Social Work, Miami University, Oxford, OH, United States; Thameling C.L., Communication Program, University of Louisiana at Monroe, United States; Vijaya R., Department of Psychology, Christ University, Maharashtra, India; Custer S., Department of Psychology, Miami University, Oxford, OH, United States
Big Data De-duplication using modified SHA algorithm in cloud servers for optimal capacity utilization and reduced transmission bandwidth; [Big Data Deduplicaci utilizando algoritmo SHA modificado en servidores en la nube para una utilizaci tima de la capacidad y un ancho de banda de transmisi reducido]
Cloud Servers; De-duplication; Preprocessing; SHA; Target
Data de-duplication in cloud storage is crucial for optimizing resource utilization and reducing transmission overhead. By eliminating redundant copies of data, it enhances storage efficiency, lowers costs, and minimizes network bandwidth requirements, thereby improving overall performance and scalability of cloud-based systems. The research investigates the critical intersection of data de-duplication (DD) and privacy concerns within cloud storage services. Distributed Data (DD), a widely employed technique in these services and aims to enhance capacity utilization and reduce transmission bandwidth. However, it poses challenges to information privacy, typically addressed through encoding mechanisms. One significant approach to mitigating this conflict is hierarchical approved de-duplication, which empowers cloud users to conduct privilegebased duplicate checks before data upload. This hierarchical structure allows cloud servers to profile users based on their privileges, enabling more nuanced control over data management. In this research, we introduce the SHA method for de-duplication within cloud servers, supplemented by a secure pre-processing assessment. The proposed method accommodates dynamic privilege modifications, providing flexibility and adaptability to evolving user needs and access levels. Extensive theoretical analysis and simulated investigations validate the efficacy and security of the proposed system. By leveraging the SHA algorithm and incorporating robust pre-processing techniques, our approach not only enhances efficiency in data deduplication but also addresses crucial privacy concerns inherent in cloud storage environments. This research contributes to advancing the understanding and implementation of efficient and secure data management practices within cloud infrastructures, with implications for a wide range of applications and industries. 2024; Los autores.
https://doi.org/10.56294/dm2024245 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190825623&doi=10.56294%2fdm2024245&partnerID=40&md5=111365f3580bee4fbef0a04e7db92be2
Bhojan R., Department of Mathematics and Computer Science, The Papua New Guinea University of Technology, Papua New Guinea; Rajagopal M., Lean Operations and Systems, School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Ramesh R., Department of Computer Science, KPR College of Arts Science and Research, Tamilnadu, India
EGMM: removal of specular reflection with cervical region segmentation using enhanced Gaussian mixture model in cervix images
Cervical region; Colposcopy; Enhanced Gaussian mixture model; Mexican axolotl optimization; Specular reflection
Colposcopy is a crucial imaging technique for finding cervical abnormalities. Colposcopic image evaluation, particularly the accurate delineation of the cervix region, has considerable medical significance.Before segmenting the cervical region, specular reflection removal is an efficient one. Because, cervical cancer can be found using a visual check with acetic acid, which turns precancerous and cancerous areas whiteand these could be viewed as signs of abnormalities. Similarly, bright white regions known as specular reflections obstruct the identification of aceto-whiteareas and should therefore be removed. So, in this paper, specular reflection removal with segmentingthe cervix region ina colposcopy image is proposed. The proposed approach consists of two main stages, namely, pre-processing and segmentation. In the pre-processing stage, specular reflections are detected and removed using a swin transformer. After that, cervical regions are segmented using an enhanced Gaussian mixture model (EGMM). For better segmentation accuracy, the best parameters of GMM are chosen via the adaptive Mexican Axolotl Optimization (AMAO) algorithm. The performance of the proposed approach is analyzed based on accuracy, sensitivity, specificity, Jaccard index, and dice coefficient, and the efficiency of the suggested strategy is compared with various methods. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
https://doi.org/10.1007/s11042-024-19035-9 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190708576&doi=10.1007%2fs11042-024-19035-9&partnerID=40&md5=ecfbc67782ec0e407bb5d6de20ccc995
Mukku L., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Bangalore, India; Thomas J., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Bangalore, India
Speculative investment decisions in cryptocurrency: a structural equation modelling approach
Cryptocurrency; domain knowledge; impulsive; negative consequences; self-control; speculative investment decision; subjective norm
Cryptocurrency markets are inclined towards speculative usage due to the inherent high risk of financial loss and the potential for substantial gains during transaction completion. In response to this phenomenon, this study represents the inaugural effort to explore the influence of variables such as subjective norms, domain knowledge, impulsive investment tendencies, and self-control on decisions related to speculative investments. Utilising structural equation modelling with a dataset of 367 responses in India, the study is the first of its kind. The research reveals that subjective norms and domain knowledge play a significant role in influencing impulsive investment and self-control. Additionally, impulsive investment exhibits significant associations with decisions involving speculative investments. This insight underscores the complexity wherein individuals, despite exercising self-control, may still engage in speculative decisions that lead to adverse consequences. The findings have practical implications for investors and regulators, offering valuable insights into investment behaviours within the cryptocurrency realm. 2024 Informa UK Limited, trading as Taylor & Francis Group.
Kumar Sharma R.; Khan S.; Singh R.; Birari A.
Kumar Sharma R., Management Department, CHRIST University, Bengaluru, India; Khan S., Indian Institute of Information Technology Allahabad, Allahabad, Jhalwa, India; Singh R., Indian Institute of Information Technology Allahabad, Allahabad, Jhalwa, India; Birari A., Management Department, CHRIST University, Bengaluru, India
The SDG conundrum in India: navigating economic development and environmental preservation
economic growth; environmental sustainability; India; SDGs; trade-offs
The paper explores the complex interplay between economic development and environmental sustainability in the context of Indias pursuit of the Sustainable Development Goals (SDGs). It examines the inherent contradictions and trade-offs involved, particularly in agriculture, industrialisation, and infrastructure sectors. The paper highlights how economic growth, essential for improving living standards, often conflicts with environmental objectives. The paper underscores the importance of integrating economic, environmental, and social objectives to achieve a sustainable and inclusive future for India. 2024 Informa UK Limited, trading as Taylor & Francis Group.
International Journal of Environmental Studies, Vol-81, No. 2, pp. 961-976.
Boora S., Media Studies, CHRIST University, Bangalore, India; Karakunnel M.T., Media Studies, CHRIST University, Bangalore, India
Effectiveness of Financial Inclusion through PMJDY Scheme: A Study of the PMJDY Beneficiaries in Tamil Nadu
Beneficiary satisfaction; financial inclusion; structural equation model
The study explored whether various banking dimensions, viz. savings and borrowings, literacy and promotions, bank facilities and other bank services, contributed to the PMJDY beneficiaries' satisfaction in the Coimbatore region. Moreover, the study examined whether the satisfaction of the beneficiaries obtained through banking dimensions led to the frequent usage of bank accounts under the PMJDY. The data were collected from 380 beneficiaries of PMJDY from 12 administrative blocks in the Coimbatore district of Tamil Nadu, the Southern part of India. Factor analysis and Structural Equation Modeling (SEM) were used for the analysis. The results showed that the banking dimensions, viz. savings and borrowings and literacy and promotions, had positively influenced the beneficiaries' satisfaction. There was a linkage between the beneficiaries' satisfaction with frequent bank accounts under the PMJDY in rural areas of the Coimbatore region. It was found that an enriched banking service through politeness and benevolence of bank employees would enhance satisfaction, which helped the bank to acquire and retain existing beneficiaries for a thriving business environment. 2024 The Society of Economics and Development, except certain content provided by third parties.
Palamalai S.; Khanna S.; Sampath B.; Maity B.; Kumar M.
Indian Journal of Economics and Development, Vol-20, No. 1, pp. 80-87.
The Society of Economics and Development
https://doi.org/10.35716/IJED-23218 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190789055&doi=10.35716%2fIJED-23218&partnerID=40&md5=b5a58114cff7493cd5f097b13da28a28
Palamalai S., School of Management, Presidency University, Karnataka, Bengaluru, 560064, India; Khanna S., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Sampath B., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India; Maity B., School of Management, Presidency University, Karnataka, Bengaluru, 560064, India; Kumar M., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560029, India
Death of Vernaculars and Language Hegemony: An ethnography of the higher education sector in 21st century India
English language hegemony; HE in India; knowledge traffic; language departments; techno-globalisation; vernaculars
The paper examines how new age pedagogies and neoliberal policies consciously work towards naturalizing English languages hegemony in institutions of Higher Education (IHE) in India. An ethnographic study the paper foregrounds the precarious positioning of non-English Indian languages vis-vis the pervading discourses of internationalization and education as job/skill oriented. Hegemony of English in the present is coupled with a restructuring of language departments as well as fleeting market demands for human capital. The paper also brings into question the role of the Internet and related technologies in reorganizing the linguistic dynamics of HE. Instead of democratizing, the Internet produces new monopolies in knowledge production, controls knowledge traffic from global North to South and further legitimizes the language hegemony. The paper argues that, in the last two decades, the neoliberal rupture has been leading HE institutions to a death of vernaculars within their physical, cultural and academic spaces. 2024, Hiroshima University,Research Institute for Higher Education,. All rights reserved.
Higher Education Forum, Vol-21, pp. 201-221.
Hiroshima University,Research Institute for Higher Education,
https://doi.org/10.15027/55015 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188653539&doi=10.15027%2f55015&partnerID=40&md5=d887e20de75c4dedfb04e0b6fb88e59f
Kumaramkandath R., CHRIST (Deemed to be University), Bangalore, India
A Lightweight Multi-Chaos-Based Image Encryption Scheme for IoT Networks
Chaotic systems; data encryption; image encryption; Internet of Things (IoT); key mixing; network security
The swift development of the Internet of Things (IoT) has accelerated digitalization across several industries, offering networked applications in fields such as security, home automation, logistics, and quality control. The growth of connected devices, on the other hand, raises worries about data breaches and security hazards. Because of IoT devices' computational and energy limits, traditional cryptographic methods face issues. In this context, we emphasize the importance of our contribution to image encryption in IoT environments through the proposal of Multiple Map Chaos Based Image Encryption (MMCBIE), a novel method that leverages the power of multiple chaotic maps. MMCBIE uses multiple chaotic maps to construct a strong encryption framework that considers the inherent features of digital images. Our proposed method, MMCBIE, distinguishes itself by integrating multiple chaotic maps like Henon Chaotic Transform and 2D-Logistic Chaotic Transform in a novel combination, a unique approach that sets it apart from existing schemes. Compared to other chaotic-based encryption systems, this feature renders them practically indistinguishable from pure visual noise. Security evaluations and cryptanalysis confirm MMCBIE's high-level security properties, indicating its superiority over existing image encryption techniques. MMCBIE demonstrated superior performance with NPCR (Number of Pixel Changing Rate) score of 99.603, UACI (Unified Average Changing Intensity) score of 32.8828, MSE (Mean Square Error) score of 6625.4198, RMSE (Root Mean Square Error) score of 80.0063, PSNR (Peak Signal to Noise Ratio) score of 10.2114, and other security analyses. 2013 IEEE.
Jain K.; Titus B.; Krishnan P.; Sudevan S.; Prabu P.; Alluhaidan A.S.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ACCESS.2024.3377665 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188416922&doi=10.1109%2fACCESS.2024.3377665&partnerID=40&md5=3f8b8945b75f849edaa90132baae5a02
Jain K., Amrita Vishwa Vidyapeetham, Amritapuri Campus, Center for Cybersecurity Systems and Networks, Kollam, 690525, India; Titus B., Amrita Vishwa Vidyapeetham, Amritapuri Campus, Center for Cybersecurity Systems and Networks, Kollam, 690525, India; Krishnan P., Amrita Vishwa Vidyapeetham, Amritapuri Campus, Center for Cybersecurity Systems and Networks, Kollam, 690525, India; Sudevan S., Amrita Vishwa Vidyapeetham, Amritapuri Campus, Center for Cybersecurity Systems and Networks, Kollam, 690525, India; Prabu P., Christ (Deemed to Be University), Department of Computer Science, Bengaluru, 560029, India; Alluhaidan A.S., Princess Nourah Bint Abdulrahman University, College of Computer and Information Sciences, Department of Information Systems, Riyadh, 11564, Saudi Arabia
EASM: An efficient AttnSleep model for sleep Apnea detection from EEG signals
CNN; Focal loss; Multi-head attention; Temporal context encoder
This paper addresses the crucial task of automatic sleep stage classification to assist sleep experts in diagnosing sleep disorders such as sleep apnea and insomnia. The proposed solution presents a novel attention-based deep learning model called, Efficient Attention-sleep Model (EASM), designed specifically for sleep apnea detection using EEG signals. EASM incorporates a streamlined architecture that includes a modified Muti-Resolution Convolutional Neural Network (MRCNN), Adaptive Feature Recalibration (AFR), and a simplified Temporal Context Encoder (TCE) module to reduce complexity. To mitigate overfitting, ridge regression is utilized, which incorporates a penalty term to enhance model generalization. Furthermore, the proposed EASM utilizes a class-balanced focal loss function to address data imbalance issues. The effectiveness of EASM is evaluated on two publicly available datasets, SLEEP EDF-20 and SLEEP EDF-78. Comparative analysis of EASM against state-of-the-art models demonstrates its superior performance in terms of accuracy, training time, and model complexity. Notably, the proposed model achieves a 50% reduction in training time and a 55.7% decrease in complexity compared to the Attnsleep model. The EASM achieves a classification accuracy of 85.8% with minimum loss when compared to the Attnsleep model. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Singh M.; Chauhan S.; Rajput A.K.; Verma I.; Tiwari A.K.
Singh M., Christ (Deemed to be University), Delhi-NCR Campus, India; Chauhan S., Dronacharya Govt. College, Gurugram, India; Rajput A.K., ABV-Indian Institute of Information Technology & amp; Management, Gwalior, India; Verma I., Christ (Deemed to be University), Delhi-NCR Campus, India; Tiwari A.K., ABV-Indian Institute of Information Technology & amp; Management, Gwalior, India
Analytical Estimation and Experimental Validation of the Bending Stiffness of the Transmission Line Conductors
Bending Stiffness; Inter Wire Friction; Revised Slip Theory; Transverse Load
The bending stiffness of transmission line conductors can vary significantly, ranging from maximum stiffness when behaving monolithically to minimum stiffness when wires behave loosely. This large range makes it challenging to estimate stiffness accurately at intermittent bending stages. To address this issue, a mathematical model that accounts for both frictional forces between wires in the same layer and the clenching effects of helical wires from preceding layers is proposed in this paper. The proposed model estimates cable bending stiffness as a function of axial load and curvature for multilayered strands by considering slip caused by wire behavior. To evaluate the bending stiffness, experiments were conducted on Panther and Moose Indian Power Transmission line conductors. The proposed slip model considers Coulomb frictional effects and clenching effects caused by Hertzian contact forces, filling the void in the estimation procedure. Additionally, the model considers the wire stretch effect, a parameter not previously accounted for in cable research. The predicted numerical results of the proposed model were found to vary within a maximum of 7% from the experimental tests. The proposed mathematical model thus offers a more accurate and comprehensive way of estimating the bending stiffness of transmission line conductors, addressing the existing limitations in the estimation procedure. 2024 College of Engineering, Universiti Teknologi MARA (UiTM), Malaysia.
Dulabhai H.P.; Parthasarathy N.S.; Hebbar G.S.
Journal of Mechanical Engineering, Vol-21, No. 1, pp. 23-43.
https://doi.org/10.24191/jmeche.v21i1.25357 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188162171&doi=10.24191%2fjmeche.v21i1.25357&partnerID=40&md5=8c3edf6bfcd77cf2624dc6fde5930484
Dulabhai H.P., Department of Mechanical and Automobile Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560074, India; Parthasarathy N.S., Department of Mechanical and Automobile Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560074, India; Hebbar G.S., Department of Mechanical and Automobile Engineering, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560074, India