KMSBOT: enhancing educational institutions with an AI-powered semantic search engine and graph database
Educational search engine; Natural language process; Neo4j; Recommendation system; Text processing
In the rapidly evolving field of education, a semantic search engine is essential to efficiently retrieve knowledge experts data. Universities and colleges continuously generate a vast amount of educational and research data. A semantic search engine can assist students and staff in efficiently searching for required information in such a big data pool. The existing systems have limitations in providing personalized recommendations that align with the individual learning objectives of students and scholars, thus hindering their educational experience. To address this, this paper proposed a KMSBOT. This novel recommendation system effectively summarizes academic data and provides tailored information for students, research scholars, and faculty, enhancing educational experiences. This paper meticulously details the development of KMSBOT, which comprises a neo4j-based knowledge graph technique, the NLP method for data structuring, and the KNN machine learning model for classification. The system employs a three-module approach, utilizing data structuring, NLP processing, and semantic search engine integration. By leveraging Neo4j, NLTK, and BERT in Python, this proposed work ensures optimal performance metrics such as time, accuracy, and loss value. The proposed solution addresses traditional recommendation systems limitations and contributes to a brighter future, improving user satisfaction and engagement in academic environments. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
Subramanian D.V.; Chandra J.; Immanuel V.A.; Rohini V.
Springer Science and Business Media Deutschland GmbH
Subramanian D.V., Department of Computer Science, Christ University, Bengaluru, India; Chandra J., Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Immanuel V.A., Department of Computer Science, Christ University, Bengaluru, India; Rohini V., Department of Computer Science, Christ University, Karnataka, Bengaluru, India
Design of automatic follicle detection and ovarian classification system for ultrasound ovarian images
Accuracy; Active contour; Biomedical instrumentation; Detection of PCOS; Follicle; Modified Otsu; Sensing systems; Ultrasound image
Polycystic Ovary Syndrome (PCOS) is a common reproductive and metabolic disorder characterized by an increased number of ovarian follicles. Accurate diagnosis of PCOS requires detailed ultrasound imaging to assess follicles size, number, and position. However, noise often needs to be improved on these images, complicating manual detection for radiologists and leading to potential misidentification. This paper introduces an automated diagnostic system for integration with ultrasound imaging equipment to enhance follicle identification accuracy. The system consists of two main stages: preprocessing and follicle segmentation. Preprocessing employs an adaptive Frost filter to reduce noise, while follicle segmentation utilizes a region-based active contour combined with a modified Otsu method. Unlike the conventional Otsu method, where the threshold value is selected manually, the modified Otsu method automatically selects initial threshold values using an iterative approach. After segmentation, features are extracted from the segmented results. An SVM classifier then categorizes the ovarian image as normal, cystic, or polycystic. Experimental results demonstrate that the proposed methods Follicle Identification Rate is 96.3% and the False Acceptance Rate is 2%, which significantly improves classification accuracy, highlighting its potential advantages for clinical application. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Saranya R., Department of Computer Science with Data Analytics, PSG College of Arts & Science, Tamil Nadu, Coimbatore, India; Sridevi R., Department of Computer Science, CHRIST University, Karnataka, Bangalore, India
Predicting Consumers' Usage Intention Towards User-Generated Content: A Hybrid SEM-ANN Approach
atti-tude; information quality; moderation; need for cognition; neural network; perceived usefulness; source credibility; usage intention; User-generated content
With the change in the communication pattern, end-users are engaging in creating content and refer-ring to the content created by other users while making purchase decisions. This research aims at modelling factors affecting consumers' usage intention (UI) towards user-generated content (UGC) using Need for Cogni-tion (NfC) as a moderator of the proposed relationships. The factors affecting consumers' UI involve perceived usefulness (PU), source credibility (SC), information quality (IQ) and NfC. Further, a novel attempt has been made by using the neural network approach to assess the predictive accuracy of the model. A structured ques-tionnaire was used to collect data from 298 consumers through a survey. Data were analysed using two-stage structural equation modelling (SEM) and artificial neural network (ANN). All the independent variables viz., PU, SC, IQ and NfC significantly affect attitude towards UGC, which in turn affects UI. Results of multi-group anal-ysis and a series of chi-square difference tests reveal that a NfC significantly moderates the relationship be-tween PU and attitude, as well as that between SC and attitude. The root mean square error values from the neural network analysis suggest that the models show good predictive accuracy. This study provides a novel assessment of the usage of a hybrid SEM-ANN approach for understanding of UGC by incorporating NfC as a moderator in shaping consumers' attitudes and intentions to use UGC. 2024 World Scientific Publishing Co.
Mathur S.; Tewari A.; Shrivastava A.K.; Verma V.C.; Vishnoi S.K.; Sharma P.
Journal of Information and Knowledge Management
https://doi.org/10.1142/S0219649224501065 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213248484&doi=10.1142%2fS0219649224501065&partnerID=40&md5=acaa578acddc1ce4ce86b6387f141de2
Mathur S., School of Business and Management, Christ University, Delhi NCR Campus, U.P., Ghaziabad, India; Tewari A., School of Management, Babu Banarasi das University, U.P., Lucknow, India; Shrivastava A.K., International Management Institute Kolkata, West Bengal, Kolkata, India; Verma V.C., BBA Department, Siddharth University, U.P., Siddharth Nagar, India; Vishnoi S.K., Department of Marketing, Institute of Management Studies, U.P., Ghaziabad, India; Sharma P., School of Business Studies, Sharda University, U.P., Greater Noida, India
The complexities of home and belonging in the Gulf-Malayalee experience: a close reading of Salim Ahameds Pathemari (2015)
belonging; Gulf Malayalee; Home; Indian diaspora; return migration; reverse migration
This paper explores the interaction between home, belonging, and migration by closely reading Salim Ahameds 2015 Malayalam film, Pathemari. The paper briefly traces migration history from Kerala to the Gulf and its impact on Keralas housing boom, influencing its socioeconomic and cultural landscape. Through this, the paper examines how Gulf Malayalees navigate the multifaceted and contested concept of home despite being physically and emotionally displacedthe paradox of belonging and unbelonging, in their attempts to secure a material home while working as blue-collared Malayalee migrants in the Gulf. 2024 Informa UK Limited, trading as Taylor & Francis Group.
Komban A.P., Department of English and Cultural Studies, Christ University, Bangalore, India; Nayar CV A., Department of English and Cultural Studies, Christ University, Bangalore, India
Intention to use fintech services: An investigation into the moderation effects of quality of internet access and digital skills
Attitude; Behavioural intention; Digital skills; Perceived behavioural control; Quality of internet access
This paper aims to investigate the moderating influence of the quality of access to internet and digital skills on the factors that influence the intention to use fintech services among the young working population in India. We use the Theory of Planned Behavior to examine the intention to adopt financial technology in a rapidly technologically transformative Indian landscape. We conducted an empirical investigation on 324 young workers in India using the survey method. The TPB model's relevance in an Indian context is validated. Attitude, perceived behavioral control, and subjective norms together accounted for 48.7% of the variation in the intention to use fintech services. The quality of internet access significantly moderated the positive effect of young workers' attitudes on their intention to use fintech. Digital skills significantly moderated the positive effects of attitude and perceived behavioral control on intentions to use fintech services. India is considered a very fast adopter of digital technology. In India, the use of electronic channels in financial service delivery is on the rise. With the wide geographic dispersion and huge population, the quality of internet access and digital skills can influence the intention to use fintech services. There can be vast differences in the behavioral mindset of people in a developing country like India compared to that of a developed one regarding the use and adoption of digital platforms for accessing financial services. Developers and regulators must adopt approaches and policies that consider these behavioral factors. This paper examines the Theory of Planned Behaviour in the context of a rapidly transforming behavioural context in India with the adoption of technology-based financial services. The importance of quality internet access and digital skills as factors moderating the adoption of technology is examined in this paper, unlike many previous studies. 2024 Conscientia Beam. All Rights Reserved.
Humanities and Social Sciences Letters, Vol-12, No. 3, pp. 543-555.
Ravi R., School of Business and Management, Christ University, Bengaluru, India, Department of Management and Professional Studies, Rajagiri College of Social Sciences, Cochin, India; Pandey N.N., School of Business and Management, Christ University, Bengaluru, India
Inter-State Migration, Footloose Labour and Accessibility to Health Care: An Exploration among Metro Workers of a Camp in Bengaluru
Footloose Labour; Health Awareness; Health Care; Metro Train Constructions Workers; Migration; Social Work
The neoliberal political economy that India adopted in 1991 has brought in huge Foreign Direct Investments, which has led to a perceptible increase in the number of migrants in the major cities of India due to various structural reasons in their place of origin and rapid developmental activities in the cities. Bengaluru has the second largest migrant population after Mumbai, and as per the labour department of the government of Karnataka; there are more than 65 lakh migrant workers in Karnataka, who are involved in various developmental projects, including the metro railway project in Bangalore. Even though the Karnataka Building and Other Construction Workers Welfare Board (KBOCWWB) offers certain social security, including health care for registered migrants, they must wait more than a year to get these benefits. With privatisation and increased out-of-pocket expenditure for health related issues, the migrants face a major hurdle in surviving at the migrated workplaces. Many of them are unaware of welfare boards, and the number of migrants who are registered with them is very small. This paper aims to understand the accessibility of health facilities for migrant workers working in the Bengaluru Metro Project. This research will understand the legal, economic and psychological aspects related to the health status of migrant workers through qualitative study. The study used in-depth interviews to elicit responses from selected inter-state migrant workers to understand their access towards health facilities. The thematic analysis of the interview transcripts revealed a substantive gap in workers access to health facilities. The unregulated working conditions have added more stress to the workers, and due to poverty and unemployment back home, these hurdles are not forcing them to go back. More awareness creating interventions from the government can transform their lives. (2024), (University of Duisburg). All rights reserved.
Sethuraman V.; Srinivas V.; Bathirasamy V.
Social Work and Society, Vol-22, No. 1, pp. 1-15.
Sethuraman V., CHRIST University, India; Srinivas V., CHRIST University, India; Bathirasamy V., CHRIST University, India
Enhancing CNN Weights for Improved Routing in UAV Networks for Catastrophe Relief with MSBO Algorithm
catastrophe relief; CNN; Modified smell bees optimization (MSBO); optimization algorithms; routing protocols; UAV networks
UAVs have become key in various applications lately, from catastrophe relief to environmental monitoring. The plan of powerful and reliable directing protocols in UAV networks is seriously hampered by the dynamic and habitually eccentric mobility patterns of UAVs. This study proposes a novel technique to beat these challenges by utilizing the Modified Smell Bees Optimization (MSBO) algorithm to upgrade the weights of CNNs. This studys principal objective is to further develop UAV network routing decisions by using CNNs ability for design recognition and the Modified SBOs optimization abilities. Our methodology comprises of randomly relegating CNN weights to a populace of bees at start, evaluating their wellness by fitness of directing performance, and iteratively fine-tuning these weights utilizing local and global search procedures got from bee searching. Broad simulations and performance evaluations show that our recommended approach incredibly expands the general dependability of UAVs, brings down communication latency, and improves directing productivity. Future exploration in UAV network improvement gives off an impression of being going in a promising direction with the integration of CNNs for pattern recognition and the Modified SBO for weight enhancement. In addition to progressing UAV routing conventions, this work sets out new open doors for machine learning applications of bio-inspired optimization algorithms. 2024 River Publishers.
Gupta S.K.; Ul Din S.M.; Upreti K.; Mahajan S.; Date S.S.
Journal of Mobile Multimedia, Vol-20, No. 5, pp. 1117-1152.
https://doi.org/10.13052/jmm1550-4646.2056 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214506466&doi=10.13052%2fjmm1550-4646.2056&partnerID=40&md5=e0f9f9d5b6979a9801ebbae3839eb4ad
Gupta S.K., Department of Electronics and Communication Engineering, Central University of Jammu, Jammu, Samba, 181143, India; Ul Din S.M., Department of Electronics and Communication Engineering, Indian Institute of Technology, Chhattisgarh, Bhilai, 491002, India; Upreti K., Department of Computer Science, Christ University, Delhi NCR, 201003, India; Mahajan S., Amity School of Engineering and Technology (ASET), Amity University, Gurugram, Haryana, Panchgaon, 122412, India; Date S.S., Department of Artificial Intelligence and Data Science, CSMSS Chh, Shahu College of Engineering, Maharashtra, Chh. Sambhajinagar, India
Extended Slash Modified Lindley Distribution to Model Economic Variables Showing Asymmetry
Data fitting; Income data; Lindley distribution; Maximum likelihood estimation; Slash Lindley distribution
This article introduces a novel probability distribution to model economic variables with high kurtosis and heavy tails showing a decreasing trend. From a mathematical viewpoint, it corresponds to the distribution of the ratio of two independent random variables, one with the modified Lindley distribution and another with the beta distribution. In some sense, it can be described as an extended three-parameter version of the Lindley distribution that has the ability to model data with high kurtosis. After presenting this distribution in more in-depth details, a comprehensive analysis is given, including its associated functions, moments, skewness, and kurtosis characteristics. Furthermore, a parametric estimation work is carried out. A simulation approach is used to validate the performance of the obtained estimates. The applicability of the proposed distribution is demonstrated by fitting real-world data into various socioeconomic scenarios. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Gillariose J., Department of Statistics and Data Science, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Joseph J., SCAPS, Marian College Kuttikkanam, Kuttikkanam P.O, Peermade, Kerala, Idukki District, India; Chesneau C., Department of Mathematics, LMNO, University of Caen, Caen, 14032, France
Fluorescence bioimaging applications of europium-doped strontium aluminate nanoparticles
Biocompatibility; Europium; Fluorescence bioimaging; Nanoparticles; Strontium aluminate
Fluorescence bioimaging is widely used for physiological studies to visualise intercellular molecular events due to its highly selective, sensitive, and non-destructive nature. However, its application in in vivo live imaging is often limited by the scarcity of biocompatible fluorescent probes possessing optimal properties. Our study focuses on developing europium-based nanoparticles for in vivo bioimaging, especially imaging of plants. Eu-doped strontium aluminate nanoparticles were synthesised through a conventional solid-state reaction. Structural characterisation of samples using XRD confirmed the prevalence of SrAl2O4 as the prominent phase. The FTIR spectrum, SEM and TEM images were recorded for further characterization. Photoluminescence studies showed orange red emission of sample. The antibacterial activity of the nanophosphors was studied, demonstrating no antibacterial activity against Escherichia coli and Pseudomonas aeruginosa. Furthermore, in vitro cytotoxicity studies conducted using Neuro-2A cells showed no indications of cytotoxicity associated with europium doped strontium aluminate nanoparticles. When incorporated into the plant tissue culture medium, these nanoparticles were found to have no effect on seed germination and plant growth, and it demonstrated no phytotoxicity. Imaging studies have shown the uptake of nanoparticles by plants and their subsequent transport through the vascular system. Our results emphasise the direct integration of nanophosphors into plant tissues from the growth medium, eliminating the necessity for traditional staining methods in fluorescence bioimaging. Incorporation of nanophosphors into living organisms holds promise for non-invasive and long-term fluorescence imaging, with potential applications in biological studies and diagnostics. The outstanding fluorescence properties and biocompatibility of europium doped strontium aluminate nanoparticles broaden its potential for various applications in fluorescence bioimaging. 2024 Elsevier Ltd and Techna Group S.r.l.
Thomas N.M.; George N.; Viji M.O.; Bins K.C.; Chakrapani P.S.B.; Anila E.I.
https://doi.org/10.1016/j.ceramint.2024.12.141 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212319525&doi=10.1016%2fj.ceramint.2024.12.141&partnerID=40&md5=30ce7eb2d6fbf17b9c28f375aafa1438
Thomas N.M., Department of Physics, Morning Star Home Science College, Angamaly, Kerala, Ernakulam, 683573, India, Center for Nano-Bio Polymer Science and Technology, Department of Physics, St. Thomas College, Palai, Arunapuram, Kerala, Kottayam, 686574, India, Optoelectronic and Nanomaterials' Research Lab, Department of Physics, Union Christian College, Aluva, Kerala, Ernakulam, 683102, India; George N., Department of Biotechnology, St. Joseph's College (Autonomous), Irinjalakuda (Affiliated to the University of Calicut), Kerala, 680121, India; Viji M.O., Department of Biotechnology, St. Joseph's College (Autonomous), Irinjalakuda (Affiliated to the University of Calicut), Kerala, 680121, India; Bins K.C., Centre for Neuroscience, Department of Biotechnology, Cochin University for Science and Technology, Kerala, Kochi, 682022, India; Chakrapani P.S.B., Centre for Neuroscience, Department of Biotechnology, Cochin University for Science and Technology, Kerala, Kochi, 682022, India; Anila E.I., Optoelectronic and Nanomaterials' Research Lab, Department of Physics, Union Christian College, Aluva, Kerala, Ernakulam, 683102, India, Department of Physics and Electronics, Christ (Deemed to be University), Karnataka, Bangalore, 560029, India
Employee relations: a comprehensive theory based literature review and future research agenda
A systematic review (SPAR-4-SLR) protocol; Conceptual framework; Employee relations; Theory based-review
This study aims to conduct a systematic and integrative literature review to consolidate the extensive information on employee relations accumulated over the past century, thereby offering new insights into domain-specific phenomena. The research followed a four-phase search strategy in accordance with the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol. The keyword search utilized terms such as 'employee relations,' 'employee relation,' 'employment relation,' and 'employment relations' in the Scopus and Web of Science databases. By employing an integrative approach along with specific inclusionexclusion criteria, the researchers synthesized articles from leading journals in the field of employee relations, categorizing them based on geographical region, article types, prominent authors and their affiliations, and the most cited research articles. In the final stage, the researchers presented new insights through a conceptual framework utilizing the ADO-TCCM approach, which encompasses antecedents, outcomes, theories, context, methodology, mediators, and moderators of employee relations. This study synthesizes findings and reorganizes key themes into innovative frameworks, providing fresh perspectives on various aspects of employee relations. Ultimately, it offers valuable insights into the critical factors that strengthen long-term employee-employer relationships. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.
Yadav R., Indian Institute of Management Ranchi, Ranchi, 835303, India; Sinha M., Christ University, Bengaluru, 560029, India; Srivastava A., Symbiosis Institute of Business Management-Pune, Symbiosis International Deemed University, Pune, India
Unveiling Green Supply Chain Practices: A Bibliometric Analysis and Unfolding Emerging Trends
circular economy; green supply chain management; resilience; reverse logistics; supply chain management; sustainability; sustainable supply chain management
Supply chain management is a multi-dimensional approach. Growing eco-consciousness has forced businesses to optimize operations and incorporate green practices across all the stages of supply chain in manufacturing and service sectors. Reviewing the past research literature propels us to understand its current and future prospects. Employing a systematic analysis, this research explores the intellectual structure of green supply chain practices and their connection to performance outcomes in various industries. This study covers a systematic literature review, content analysis, and bibliometric analysis on green supply chain management using VosViewer. It utilizes a PRISMA-guided screening method for identification, screening, eligibility and inclusion of literature from the literature available since 1999. The bibliometric analysis reveals key contributors, thematic clusters, prevailing theoretical frameworks, and emerging research trends in the domain of green supply chain management. China, followed by the United States and the United Kingdom, emerged as leading contributors to research in this area, driven by rapid economic growth, heightened environmental concerns, and well-established academic and industrial infrastructures. The study identifies eight thematic clusters within green supply chain management, including the triple bottom line, circular economy, and carbon emissions. The most highly cited papers within these clusters were examined for their methodologies, tools, and key findings, highlighting the prominent theories utilized in this field. Moreover, the research discusses how advanced technologies such as AI, blockchain, and big data analytics are poised to transform supply chains by enhancing decision-making and mitigating risks, thus playing a pivotal role in the future of green supply chain management. Copyright 2024 CA Rajkiran, Shaeril Michel Almeida.
Organizations and Markets in Emerging Economies, Vol-15, No. 11720, pp. 378-417.
https://doi.org/10.15388/omee.2024.15.18 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213409549&doi=10.15388%2fomee.2024.15.18&partnerID=40&md5=e5a049f8d8a2eb646c4178c9bef83ba2
Rajkiran C.A., Christ Deemed to be University, India; Almeida S.M., Christ Deemed to be University, India
We wear multiple hats: Exploratory study of role of special education teachers of public schools in India
inclusive education; India; qualitative research; role of special education teachers; special education teachers
The role of special education teachers (SETs) is multifaceted. A gap was recognised in the literature in the lack of studies on the roles and responsibilities of SETs in India and the field realities of carrying out the role. The aim was to explore to what extent the special education teachers fulfil their roles and responsibilities. The following is an exploratory study, using open-ended questions that interviewed 12 SETs from five public schools in Delhi, India. The policy documents shared that the SETs were responsible for direct instruction to special needs students, parentteacher collaboration and documentation, including IEPs for students with special needs. But in practice, there were not any clear-cut boundaries, the SETs played multiple rolesSubject teacher, taking substitution periods, para teachers, these were keeping the SETs away from their core responsibilities. The results of the study demonstrated an undervaluation of the work of SETs and lack of support from the principal and regular teachers. The results concluded with recommendations for policy proposal with regards to defining the role of all stakeholders in an inclusive education school and improvements for the teacher education program. 2024 National Association for Special Educational Needs.
Khanna R., School of Education, CHRIST (Deemed to be University), Bangalore, India; Kareem J., School of Education, CHRIST (Deemed to be University), Bangalore, India
Revolutionizing Biodegradable and Sustainable Materials: Exploring the Synergy of Polylactic Acid Blends with Sea Shells
additive manufacturing; biodegradability; flexural; PLA; sea shell; tensile
This study explores the mechanical properties of a novel composite material, blending polylactic acid (PLA) with sea shells, through a comprehensive tensile test analysis. The tensile test results offer valuable insights into the materials behavior under axial loading, shedding light on its strength, stiffness, and deformation characteristics. The results suggest that the incorporation of sea shells decrease the tensile strength of 14.55% and increase the modulus of 27.44% for 15 wt% SSP (sea shell powder) into PLA, emphasizing the reinforcing potential of the mineral-rich sea shell particles. However, a potential trade-off between decreased strength and reduced ductility is noted, highlighting the need for a delicate balance in material composition. The study underscores the importance of uniform sea shell particle distribution within the PLA matrix for consistent mechanical performance. These results offer a basis for additional PLA-sea shell blend optimization, directing future efforts to balance strength, flexibility, and other critical attributes for a range of applications, including biomedical devices and sustainable packaging. This investigation opens the door to more sustainable and mechanically strong materials in the field of additive manufacturing by demonstrating the positive synergy between nature-inspired materials and cutting-edge testing techniques. 2024 The Authors.
Prashanth K.P.; Rudresh M.; Venkatesh N.; Shivarathri P.G.; Rajappa S.
Journal of Renewable Materials, Vol-12, No. 12, pp. 2115-2134.
https://doi.org/10.32604/jrm.2024.055437 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213426808&doi=10.32604%2fjrm.2024.055437&partnerID=40&md5=34c6698022509c317bc23ace8c9deb19
Prashanth K.P., Department of Mechanical Engineering, Acharya Institute of Technology, Bangalore, 560107, India; Rudresh M., Department of Robotics and Artificial Intelligence, Dayananda Sagar College of Engineering, Bangalore, 560111, India; Venkatesh N., Department of Mechanical Engineering, University of Visvesvaraya College of Engineering, Bangalore, 560001, India; Shivarathri P.G., Department of Chemistry, New Horizon College of Engineering, Bangalore, 560103, India; Rajappa S., Department of Sciences and Humanities, Christ (Deemed to be University), Bangalore, 560074, India
Damaged Relay Station: EEG Neurofeedback Training in Isolated Bilateral Paramedian Thalamic Infarct
EEG neurofeedback training; neuropsychological rehabilitation; stroke; thalamic infarcts
Stroke is a major public health concern and leads to significant disability. Bilateral thalamic infarcts are rare and can result in severe and chronic cognitive and behavioral disturbances - apathy, personality change, executive dysfunctions, and anterograde amnesia. There is a paucity of literature on neuropsychological rehabilitation in patients with bilateral thalamic infarcts. Mr. M., a 51 years old, married male, a mechanical engineer, working as a supervisor was referred for neuropsychological assessment and rehabilitation with the diagnosis of bilateral paramedian thalamic infarct after seven months of stroke. A pre-post comprehensive neuropsychological assessment of his cognition, mood, and behavior was carried out. The patient received 40 sessions of EEG-Neurofeedback Training. The results showed significant improvement in sleep, motivation, and executive functions, however, there was no significant improvement in memory. The case represents the challenges in the memory rehabilitation of patients with bilateral thalamic lesions. 2024 Neurology India, Neurological Society of India.
Neurology India, Vol-72, No. 6, pp. 1277-1279.
ISSN: 283886; PubMed ID: 39691007; CODEN: NURYA
https://doi.org/10.4103/neuroindia.NI_605_20 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212770452&doi=10.4103%2fneuroindia.NI_605_20&partnerID=40&md5=232cca814ebe7e583285277a11ec8aca
Afsar M., Department of Psychology, School of Humanities and Social Sciences, Christ (Deemed to be University), Delhi NCR, India; Rajeswaran J., Department of Clinical Psychology, National Institute of Mental Health and Neuro Sciences, Karnataka, Bangalore, India
RCBAM-CNN: Rebuild Convolution Block Attention Module-based Convolutional Neural Network for Lung Nodule Classification
Computed tomography; data augmentation; horizontal flips; rebuild convolution block attention module-based convolutional neural network; U-Net
Lung cancer remains the leading cause of cancer-related deaths worldwide. Pulmonary nodules, indicative of tumor growth, present significant diagnostic challenges due to their varying sizes and shapes. Computed Tomography (CT) is commonly used for lung cancer screening due to its high sensitivity and efficacy in detecting these nodules. However, differentiating between benign and malignant nodules can be difficult due to their overlapping characteristics. To address this challenge, we propose a Rebuild Convolution Block Attention Module-based Convolutional Neural Network (RCBAM-CNN) designed to accurately classify lung nodules from CT scans. The RCBAM-CNN integrates a Rebuild Convolution Block Attention Module (RCBAM), which includes reshaped layers and redefined spatial attention mechanisms to enhance the networks focus on relevant features while minimizing noise. The performance of the proposed method is evaluated using the LIDC-IDRI dataset. Data augmentation techniques, including rotation, rescaling, and both vertical and horizontal flips, are applied to improve the models robustness and generalization. Subsequently, U-Net is employed for precise image segmentation, ensuring accurate delineation of nodule regions. The proposed RCBAM-CNN demonstrates exceptional performance, achieving an accuracy of 99.72%, surpassing existing methods such as adaptive morphology with a Gabor Filter (GF) and Capsule Network-based CNN. This approach represents a significant advancement in lung nodule classification, offering improved diagnostic accuracy and reliability. 2024 River Publishers.
Jain D.; Hundekari S.; Upreti K.; Jain N.; Rose M.; Singh N.; Singhai R.; Kumar M.
Journal of Mobile Multimedia, Vol-20, No. 5, pp. 1039-1066.
Jain D., Department of CSE-AIML, ABES Engineering College, U.P, Ghaziabad, India; Hundekari S., School of Engineering and Technology, Pimpri Chinchwad University, Pune, India; Upreti K., Christ University, Delhi NCR Campus, Ghaziabad, India; Jain N., Vivekananda School of Engineering and Technology, VIPS-TC, Delhi, Pitampura, India; Rose M., G. D. Goenka University, Haryana, Gurgaon, India; Singh N., G. D. Goenka University, Haryana, Gurgaon, India; Singhai R., IIPS, Devi Ahilya University, Indore, India; Kumar M., Gurukula Kangri University, Uttarakhand, Haridwar, India
IDENTITIES AT THE DINNER TABLE: COMMENSALITY, SELF-PERCEPTION, AND RELATIONSHIPS IN ANNE CHERIANS A GOOD INDIAN WIFE
commensality; food; food culture; identity; migration
Food studies is rapidly gaining ground as a multidisciplinary area of research. Within it, literary food studies brings an interdisciplinary perspective as works of literature are viewed through the lens of food that is informed by frameworks and concepts that are rooted in a variety of fields including cultural anthropology, sociology, and more. one such concept that is in focus here is that of commensality that is associated with food and food practices. Commensality, drawing from notions of conviviality, refers to the practice of sharing a table and consuming food together. Deeper meanings of communal identities come to the fore in this social practice, leading it to shape how identities are understood and projected. Commensality can be a complex site of belonging and alienation depending on the context, and this paper seeks to explore the representation of the same in Anne Cherians A Good Indian Wife (2008). Leila, the titular Indian wife in the novel, moves to the US from India after her marriage to Neel and grapples with finding her place in the foreign land. With this displacement comes the endeavor to reaffirm her new identity, which now includes the role of being a wife and the aspect of being an immigrant. Neel also deals with complicated feelings towards the projection of his identity. With food playing a crucial role in the everyday experiences of their lives, commensality becomes a point of enquiry into how they see themselves and how their relationships with each other and themselves evolve through the course of the narrative. 2024 Nayana George.
Studies in Linguistics, Culture and FLT, Vol-12, No. 3, pp. 154-169.
Konstantin Preslavsky University of Shumen
https://doi.org/10.46687/DRAZ7186 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213694459&doi=10.46687%2fDRAZ7186&partnerID=40&md5=61291e62049d9848ecbe46cdf5339b76
George N., Christ University, Bengaluru, India
Nonlinear Dynamics in Distributed Ledger Blockchain and analysis using Statistical Perspective
Blockchain Technology; Data Transmission Optimization; Deep Regression Analysis; Healthcare Data Storage; Nonlinear Dynamics
More and more in healthcare is blockchain technology applied for safe and open data storage. Still, it is understudied how deeply regression analysis combined with nonlinear dynamics into distributed ledger systems performs. This kind of approach may help to increase data transfer efficiency and help storage management in blockchain systems. Data speed and storage efficiency restrictions make current blockchain systems difficult to handle for large amounts of healthcare data. Conventional methods find poor data retrieval and transfer due to the great complexity and nonlinear characteristics of healthcare data. Combining nonlinear dynamics with deep regression analysis, this paper proposes a fresh approach for maximizing data transfer and storage in blockchain systems. Inspired by nonlinear dynamics ideas, a deep regression model aimed at maximizing block storage and forecast data transmission requirements was assessed on a simulated healthcare dataset using a distributed ledger system with 1,000 blocks and a 500 GB total dataset size. Performance criteria covered transmission efficiency and storage consumption. The proposed technique improved data transmission efficiency by thirty percent over current techniques. Another clear improvement was using storage; block size needs fell 25%. The best model, according to numerical research, lowered an average transmission time from 120 to 84 minutes and storage overhead from 200 to 150 GB. 2024, International Publications. All rights reserved.
Acharjee P.B.; Purushothaman G.; Vijayammal B.K.P.; Dwivedi V.K.; Gupta S.; Akalyadevi K.
Communications on Applied Nonlinear Analysis, Vol-31, No. 6S, pp. 233-251.
https://doi.org/10.52783/cana.v31.1218 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212703272&doi=10.52783%2fcana.v31.1218&partnerID=40&md5=1b3d612b4fe5b979efdb83bc5b3255f9
Acharjee P.B., Department of Computer Science, CHRIST University, Karnataka, Bangaluru, India; Purushothaman G., Department of Mathematics, St. Joseph's College of Engineering, Tamilnadu, Chennai, India; Vijayammal B.K.P., Department of Science and Humanities (General Engineering Division), R.M.K. College of Engineering and Technology, Puduvoyal, India; Dwivedi V.K., Department of Mathematics, Vishwavidyalaya Engineering College, Surguja (C.G.), Ambikapur, India; Gupta S., Department of Accounting, College of Business Administration, University of Hail, Saudi Arabia; Akalyadevi K., Department of Mathematics, Bannari Amman Institute of Technology, Sathyamangalam, Erode, India
Sensitivity analysis of thermal optimisation within conical gap between the cone and the surface of disk with particle deposition
Cone-disk apparatus; Exponential source/sink; Particle deposition; Radiation; Ternary nanofluid
This work examines the thermal and flow characteristics of TiO2+AgBr+GO/EG trihybrid nanofluid in the conical gap that exists between a disc and a cone. Effect of thermophoresis and particle deposition are examined to perceive the mass dissipation change on the surface. The governing equations of the problem are in the form of partial differential equations which are converted to nonlinear ordinary differential equations by applying proper scaling similarity transformations, and then the resultant equations are approximated numerically by using RKF45 technique. The interesting part of this research is to discuss the impact of various pertinent parameters on three cases namely: (1) rotating cone/disk (2) rotating cone/stationary disk and (3) stationary cone/rotating disk. The flow field, heat and mass transfer rates were analysed using graphical representations. Additionally, sensitivity analysis is performed on derived rate of heat transfer as a response function for input factors for different parameters. From the graph, it is perceived that flow field increases significantly with increase in the values of Reynolds numbers for both cone and disk rotations. Also, it is seen that temperature upsurges significantly for ascendent values of solid volume fraction of nanoparticles. It is also noticed that the sensitivity of the Nusselt number towards n is more for all the values of source/sink and for middle level values of n. Akadiai KiadZrt 2024.
Manjunatha S.; Ammani Kuttan B.; Tanuja T.N.
Journal of Thermal Analysis and Calorimetry
Springer Science and Business Media B.V.
Manjunatha S., Department of Mathematics, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560076, India; Ammani Kuttan B., Department of Mathematics, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560076, India; Tanuja T.N., Department of Mathematics, CHRIST (Deemed to be University), Karnataka, Bengaluru, 560076, India
WORKFORCE DIVERSITY: A SPOTLIGHT ON EMPLOYEE SUSTAINABILITY EXCELLENCE IN INDIA
demographics; diversity; employee sustainability; television media; workforce
This research paper explores a crucial yet often underestimated nexus: the relationship between workforce diversity and employee sustainability in the vibrant television media industry. Through an in-depth examination of diverse dimensions such as age, gender, culture, and socio-behavioral factors, it illuminates how these elements intricately influence the long-term viability of employees within this rapidly evolving sector. The paper's standout feature lies in its rigorous statistical analyses, which uncover the nuanced connections between workforce diversity and employee sustainability. By grounding its findings in empirical evidence, the paper transcends mere conjecture, offering a robust framework for comprehending and tackling this pressing issue. Moreover, the spotlight on the Indian media industry brings a unique perspective, given its extraordinary growth trajectory and substantial economic impact. Readers stand to gain invaluable insights into the dynamics of diversity within this context, potentially yielding transferable lessons and strategies for other industries and regions. In its culmination, the paper presents a synthesis of actionable recommendations and conclusive insights, serving as a practical guide for organizations seeking to harness diversity as a catalyst for long-term employee sustainability. With its blend of academic rigor and real-world relevance, this paper is indispensable reading for industry practitioners, policymakers, and scholars alike. 2024 Sciendo. All rights reserved.
Aiswarya B.; Ramasundaram G.; Sudha P.; Poondy R.
Foundations of Management, Vol-16, No. 1, pp. 273-294.
https://doi.org/10.2478/fman-2024-0017 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213060863&doi=10.2478%2ffman-2024-0017&partnerID=40&md5=ab232096fced062743b76f873bba8a7f
Aiswarya B., Loyola Institute of Business Administration, Loyola College, Chennai, India; Ramasundaram G., Department of Management Studies, Saveetha Engineering College, Chennai, India; Sudha P., Business and Management, Christ (Deemed to be University), Bangalore, India; Poondy R., Loyola Institute of Business Administration, Loyola College, Chennai, India
Exploring evolution, development, and contribution of International Journal of Industrial and Systems Engineering (20052022): a bibliometric study
bibliometrics; industrial management; Scopus; system engineering; VOS viewer
International Journal of Industrial and Systems Engineering (IJISE) reached its 18th year of publishing in 2023. A comprehensive assessment of 1,096 publications using the bibliometric data analysis technique is performed to understand growth of the journal for the past 18 years. Different indicators like co-occurrence of all keywords, co-authorship, citation and co-citation analysis of authors, countries, and institutions is performed through VOS Viewer software. The findings of the study emphasise contribution of IJISE to knowledge domain. Copyright 2024 Inderscience Enterprises Ltd.
International Journal of Industrial and Systems Engineering, Vol-48, No. 4, pp. 441-469.
https://doi.org/10.1504/IJISE.2024.143711 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214668416&doi=10.1504%2fIJISE.2024.143711&partnerID=40&md5=42f26bb3430c6c5757b61d8036a7fb75
Baheti S.S., Department of Business and Management, CHRIST (Deemed to be) University, Bangalore, 560029, India