Konigsberg (55.2 o North latitude and 22 o East longitude) was a city in Russia situated on the Pregel River,which served as the residence of the dukes of Prussia in the 16th century. Today,the city named Kaliningrad,is in Lithuania which recently separated from U.S.S.R.It serves as a major industrial and commercial centre of western Russia.The river Pregel flowed through the town,dividing it into four regions,as in the following picture.In the eighteenth century, seven bridges connected the four regions.The problem was to start from anyone of the land areas,walk across each bridge exactly once and return to the starting point.This problem was first solved in 1736 by the prolific Swiss Mathematician Leonhard Euler, who, as a consequence of his solution invented the branch of Mathematics now known as Graph Theory.
Inverse Hilbert Fractal-Metamaterial Rings for Microstrip Antennas and Wideband Applications
A Novel Metamaterial (MTM) property is obtained using a fractal pattern known as Inverse Hilbert. The Mu-negative(MNG) characteristics have been recovered by adopting NRW method. This MTM characteristic is studied for 2.45 GHz using FR4 epoxy as substrate. The dimension of the substrate is 30mm36mm 1.6mm. This fractal metamaterial structure can be amalgamated with an optimized Microstrip antenna (MSA) for improvement in antenna parameters and can be used for RF energy harvesting. 2022 IEEE.
2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022 - Proceedings, pp. 1398-1399.
Institute of Electrical and Electronics Engineers Inc.
Panicker R., Christ University, Bangalore, India; Suganthi S., Christ University, Bangalore, India
Inverse Problem for the Forgotten and the Hyper Zagreb Indices of Trees
The Forgotten Zagreb Index; The hyper Zagreb Index; Topological Index
Let G = (E(G); V (G)) be a (molecular) graph with vertex set V (G) and edge set E(G). The forgotten Zagreb index and the hyper Zagreb index of G are defined by F(G) = P u2V (G) d(u)3 and HM(G) = P uv2E(G)(d(u) + d(v))2 where d(u) and d(v) are the degrees of the vertices u and v in G, respectively. A recent problem called the inverse problem deals with the numerical realizations of topological indices. We see that there exist trees for all even positive integers with F(G) > 88 and with HM(G) > 158. Along with the result, we show that there exist no trees with F(G) lt; 90 and HM(G) lt; 160 with some exceptional even positive integers and hence characterize the forgotten Zagreb index and the hyper Zagreb index for trees. 2022 The authors.
Communications in Combinatorics and Optimization, Vol-7, No. 2, pp. 203-209.
https://doi.org/10.22049/CCO.2021.27034.1182 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126260410&doi=10.22049%2fCCO.2021.27034.1182&partnerID=40&md5=483a5fdd4df4f1ddc3b545611639a9ec
Kureethara J.V., Department of Mathematics, Christ University, Bangalore, India; Asok A., Department of Mathematics, Christ University, Bangalore, India; Cangul I.N., Department of Mathematics, Bursa Uludag University, Bursa, 16059, Turkey
Inverted LPDA for Broadband Radio Astronomy Observation between 150 and 800 Mhz
Beam Pattern; LPDA; Radio Transients; RFI
Radio transients are celestial objects that vary their brightness in time. The brightness can vary from a few milliseconds to a few hours and exhibit emissions across Radio waves to X-rays and even in Gamma rays. Sophisticated search techniques such as single pulse search, clustering, advanced AI, and digital signal processing are used to detect the radio signals emitted from these transient sources. A study of the signals from the transient sources helps to understand their origin and nature. This paper describes the details of a new antenna designed to detect radio transients at low frequencies between 150 MHz and 800 MHz at RRI Gauribidanur Observatory. 2025 IEEE.
Abhishek, R.; Pillai, Vinay Jha; Thiagaraj, Prabu
2025 IEEE Microwaves, Antennas, and Propagation Conference, MAPCON 2025;
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1109/MAPCON65020.2025.11425964 https://www.scopus.com/pages/publications/105036377877?origin=resultslist
Abhishek R., Christ (Deemed to Be University), Dept of Electronics and Communication, Bangalore, India, Raman Research Institute, Bangalore, India; Pillai V.J., Christ (Deemed to Be University), Dept of Electronics and Communication, Bangalore, India; Thiagaraj P., Raman Research Institute, Bangalore, India
Investigate the distinctive link between a balanced scorecard and organizational performance in ITand non-IT sectors
Balanced scorecard; Company performance; Performance measurement
Purpose: The purpose of this research is to examine how the implementation of a balanced scorecard (BSC) affects business outcomes in both information technology (IT) and non-IT sectors. Design/methodology/approach: Partial least squares structural equation modeling (PLS-SEM) was used to test the hypothesis. A random sample was used to collect 170 responses from the IT companies and 166 from non-IT companies by using the questionnaire method. The questionnaire was distributed to the top- and middle-level managers in Bangalore city, and we used SmartPLS software to explore the relationship between our research constructs. Findings: The results of this study indicate that a BSC has a significant and positive impact on organizational performance in IT and non-IT sectors. The main distinction in this study is that all BSC perspectives [learning and growth perspective, internal business process (IBP) perspective, customer perspective (CP) and financial perspective (FP)] have a significant, direct and indirect impact on IT companies. On the other hand, solely three BSC perspectives (IBP perspective, CP and FP) have a significant impact on non-IT companies, while learning and growth perspective has an insignificant impact on the FP. Originality/value: This study provides a critical theoretical and practical contribution of a BSC on business performance in IT and non-IT industries. 2024, Emerald Publishing Limited.
Zairbani A.; Doddaullarthi Basavaraj C.; SriSai V.; Jaya Prakash S.K.; Anitha Kumari P.
International Journal of Quality and Reliability Management
https://doi.org/10.1108/IJQRM-07-2023-0239 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205541495&doi=10.1108%2fIJQRM-07-2023-0239&partnerID=40&md5=989ebeb55ccf59e7adb0ceddd901f99b
Zairbani A., Department of International Business and Entrepreneurship, GITAM School of Business, Gandhi Institute of Technology and Management (GITAM), Bengaluru, India; Doddaullarthi Basavaraj C., Department of Accounting and Finance, GITAM School of Business, Gandhi Institute of Technology and Management (GITAM), Bengaluru, India; SriSai V., School of Business and Management, Christ University, Bengaluru, India; Jaya Prakash S.K., Department of Finance, GITAM School of Business, Gandhi Institute of Technology and Management (GITAM), Bengaluru, India; Anitha Kumari P., Department of Human Resource Management, GITAM School of Business, Gandhi Institute of Technology and Management (GITAM), Bengaluru, India
Zairbani, Abdulkader; Doddaullarthi Basavaraj, Chetanraj; SriSai, Velaga; Jaya Prakash, Senthil Kumar; Anitha Kumari, P.
International Journal of Quality and Reliability Management;Volume;42;Issue;5;pp.1363-1380
https://doi.org/10.1108/IJQRM-07-2023-0239 https://www.scopus.com/pages/publications/105002583077?origin=resultslist
Investigating and analyzing the causality amid tourism, environment, economy, energy consumption, and carbon emissions using TodaYamamoto approach for Himachal Pradesh, India
Applied autoregressive distributed lag (ARDL); Energy consumption; Environmental degradation; Environmental Kuznets curve (EKC); Tourism development
Himachal Pradesh is a preferred tourist destination with a Compound Annual Growth Rate (CAGR) of 10.76% between 201112 and 202021. The increasing trend of CAGR has boosted the tourism economy in the state while impacting the local environment. The negative impacts have recently increased due to changes in climatic patterns and increased tourism influx during the post-pandemic period. In this context, the present study analyzed the impact of tourism on the environment, economy, and energy consumption using the Environmental Kuznets Curve (EKC) hypothesis. The novelty of this study is to the existing literature on sustainable tourism development through investigating the interrelationship between tourism, environment, economy, energy consumption, and carbon emissions by employing the TodaYamamoto (TY) technique. This study will be a pioneering scientific investigation with quantitative results in the western Himalayan states of India, encompassing Jammu & Kashmir, Uttarakhand, and Himachal Pradesh. The annual data for each variable, such as per capita carbon emission (CEP), per capita Gross State Domestic Product (GSDP), per capita GSDP square, per capita energy consumption (ECP), and per capita tourism receipts (TRP), was collected from 2010 to 2021. This study exhibited an inverted-U EKC in the state, signifying the initial stage of economic development and extensive exploitation of natural resources for tourism. The TY results indicated an inter-causal relationship and feedback association among the variables in the study area. Thus, increased TRP would lead to an upsurge in energy consumption affecting the environmental quality due to increased carbon emissions. Such environmental degradation in the state would negatively impact the tourism sector in the long run. The research findings would guide planners and policymakers in promoting sustainable tourism. 2023, The Author(s), under exclusive licence to Springer Nature B.V.
Environment, Development and Sustainability
Springer Science and Business Media B.V.
Manisha K., Department of Architecture, National Institute of Technology, Himachal Pradesh, Hamirpur, 177005, India, School of Architecture, Christ (Deemed to be University), Kengeri, Mysore Road, Karnataka, Bangalore, 560074, India; Singh I., Department of Architecture, National Institute of Technology, Himachal Pradesh, Hamirpur, 177005, India; Chettry V., Department of Architecture, Planning & Design, Indian Institute of Technology (BHU) Varanasi, Uttar Pradesh, Varanasi, 221005, India
Himachal Pradesh is a preferred tourist destination with a Compound Annual Growth Rate (CAGR) of 10.76% between 201112 and 202021. The increasing trend of CAGR has boosted the tourism economy in the state while impacting the local environment. The negative impacts have recently increased due to changes in climatic patterns and increased tourism influx during the post-pandemic period. In this context, the present study analyzed the impact of tourism on the environment, economy, and energy consumption using the Environmental Kuznets Curve (EKC) hypothesis. The novelty of this study is to the existing literature on sustainable tourism development through investigating the interrelationship between tourism, environment, economy, energy consumption, and carbon emissions by employing the TodaYamamoto (TY) technique. This study will be a pioneering scientific investigation with quantitative results in the western Himalayan states of India, encompassing Jammu & Kashmir, Uttarakhand, and Himachal Pradesh. The annual data for each variable, such as per capita carbon emission (CEP), per capita Gross State Domestic Product (GSDP), per capita GSDP square, per capita energy consumption (ECP), and per capita tourism receipts (TRP), was collected from 2010 to 2021. This study exhibited an inverted-U EKC in the state, signifying the initial stage of economic development and extensive exploitation of natural resources for tourism. The TY results indicated an inter-causal relationship and feedback association among the variables in the study area. Thus, increased TRP would lead to an upsurge in energy consumption affecting the environmental quality due to increased carbon emissions. Such environmental degradation in the state would negatively impact the tourism sector in the long run. The research findings would guide planners and policymakers in promoting sustainable tourism. The Author(s), under exclusive licence to Springer Nature B.V. 2023.
Manisha, Keerti; Singh, Inderpal; Chettry, Vishal
Environment, Development and Sustainability;Volume;27;Issue;4;pp.8731-8766
https://doi.org/10.1007/s10668-023-04252-3 https://www.scopus.com/pages/publications/105001071512?origin=resultslist
Investigating Educators Behavioural Intentions Towards Smart Tools in Education
This study explores pre-service and in-service teachers behavioral intention to adopt smart tools by examining their perceptions of usefulness, ease of use, enjoyment, and contextual readiness. Using a quantitative survey design, data was collected from 42 participants across the Delhi-NCR region through purposive sampling. A composite score of 15 Likert-scale items was used to measure behavioural intention, followed by quartile-based analysis, independent samples t-tests (for gender), and one-way ANOVA (for age groups). While results revealed no statistically significant differences across gender and age, the quartile distribution indicated a varied spectrum of intention, with participants broadly categorised into low, moderate, and high-intention groups. The study highlights the need for teacher training programs to go beyond technical instruction. It advocates for a more nuanced, context-aware approach to technology readiness in teacher education that bridges the gap between vision and practice in the evolving ecosystem of Education 5.0. 2026 by IGI Global Scientific Publishing. All rights reserved.
Prakasha, G.S.; Rawat, Sanskriti; Ashton-Bell, Robert Linton Tavis; Lapina, Maria
Smart Business and Education in the Age of VUCA and BANI;pp.107-124
https://doi.org/10.4018/979-8-3373-7922-7.ch005 https://www.scopus.com/pages/publications/105027176821?origin=resultslist
Prakasha G.S., Christ University, Bangalore, India; Rawat S., Christ University, Bangalore, India; Ashton-Bell R.L.T., Christ University, Bangalore, India; Lapina M., North-Caucasus Federal University, Russian Federation
Investigating Factors for an Inclusive Workforce for Women in the Logistics and Supply Chain Industry
gender diversity; human-centric approach; inclusive workforce for women; logistics and supply chain
This study seeks to identify and analyze the major factors that contribute to an inclusive workforce for women in the area of logistics and supply chain. It further addresses the need for gender diversity and inclusivity in a traditionally male-dominated field by adopting a human-centric approach. This study employs a combination of Fuzzy Delphi Method (FDM) and Fuzzy Best Worst Method (FBWM) for methodically identifying and prioritizing factors that influence inclusiveness for women in the logistics and supply chain industry. FDM gathers experts' opinions and achieves a consensus on the identified relevant factors. Subsequently, FBWM is used to analyze the factors, providing a clear priority ranking based on their relative significance. The analysis identified potential factors that are crucial for fostering an inclusive workforce in the logistics and supply chain industry for women. The factors were classified into three main categories: employee growth and culture, inclusive business ecosystems, and accessibility and diversity factors. Based on the global weights, the top three ranked factors are: gender-inclusive supply chain practices, skill development workshops, and supporting women-owned businesses. This study is original in terms of gender inclusiveness in the logistics and supply chain industry. The innovative combination of multiple methods stipulates a robust methodology for identifying and analyzing the factors that impact inclusiveness, offering a novel contribution to the literature and practical applications in this field. 2025 The Author(s). Corporate Social Responsibility and Environmental Management published by ERP Environment and John Wiley & Sons Ltd.
Agarwal, Vernika; Srivastava, Shefali; Dwivedi, Ashish; Paul, Sanjoy Kumar; Patil, Anchal
Corporate Social Responsibility and Environmental Management;Volume;33;Issue;1;pp.321-344
All Open Access; Hybrid Gold Open Access
https://doi.org/10.1002/csr.70157 https://www.scopus.com/pages/publications/105016126320?origin=resultslist
Agarwal V., Apeejay School of Management, New Delhi, India; Srivastava S., Operations and Decision Sciences, Christ University, Bengaluru, India; Dwivedi A., Jindal Global Business School, O.P. Jindal Global University, Sonipat, India; Paul S.K., UTS Business School, University of Technology Sydney, Sydney, Australia; Patil A., IMI Delhi, New Delhi, India
Investigating Factors in Quality of Work-life in Indian Garment Industry at Bangalore
Factors; Garments; Labour; Market; Quality of Work Life (QWL); Stress
The Indian manufacturing sector has a long way to go in enhancing work-life standards for employees. Low standards of work-life hamper the productivity of an organization. Most employees of garment manufacturing units in Bengaluru are from outer rural areas. They come in search of employment in garment units. Though there are labour acts and labour laws, most of the manufacturing units provide poor job environments for employees. This leads to fluctuations in the performance of employees and would have detrimental effects on their health and performance, resulting in attrition. Quality of work life is the solution. This paper aims at unravelling factors leading to recognition of work-life standards so those garment units can work in that dimension to solve their productivity issues and also improve the happiness of their employees. A descriptive approach was made to attain objectives with survey-based data collection. The collected data were subjected to exploratory factor analysis and multiple regression analysis. The study found welfare and safety lead to a quality of work-life in garment units. More cross-sectoral studies are suggested to understand the blend of factors defining the quality of work life and arrive at a generalized model nation-wide. This generalization in the long term should be a key decision-making point for safety and welfare policy development in the world. 2022 The authors.
Krishna Kishore S.V.; Banerjee J.; Kiran P.; Moorthy V.
Thailand and the World Economy, Vol-40, No. 3, pp. 109-128.
Krishna Kishore S.V., School of Business and Management, CHRIST University, India; Banerjee J., Amity Business School, Amity University, India; Kiran P., School of Business, Management and Economics, Westminster International University, Uzbekistan; Moorthy V., School of Business and Management, CHRIST University, India
Investigating Funding Inequities, Resource Allocation, and Institutional Biases Impacting Marginalized K- 12 Students
Investigating funding inequities in K- 12 education reveals how resource allocation and institutional biases disproportionately affect marginalized students. Many schools serving low- income and minority populations often receive significantly fewer financial resources than their wealthier counterparts. This stark disparity not only imcts the quality of education but also limits access to essential programs and support services. Additionally, institutional biases, both implicit and explicit, can further exacerbate these inequities, influencing decisions related to student discipline, curricular offerings, and support services. It is crucial to analyze how these systemic issues perpetuate cycles of disadvantage, affecting student achievement and overall well- being. Efforts focused on reforming funding formulas, enhancing community engagement, and promoting equitable practices within schools must be foundational to ensuring all students have the opportunity to thrive academically.. 2026 by IGI Global Scientific Publishing. All rights reserved.
Bridging Socioeconomic, Gender, and Disability Gaps in K-12 Education;pp.1-28
https://doi.org/10.4018/979-8-3373-4511-6.ch001 https://www.scopus.com/pages/publications/105038336134?origin=resultslist
Ghosh O., Christ University, India; Kumar B., Radha Govind University, India
Investigating key biological traits of Malva parviflora influencing its competitive invasion in wheat crops
Biological traits; Field boundary; Invasive weeds; Little mallow; Wheat
Plant invasion is a major concern for ecologists and agriculturists. Early detection of potential invaders (weeds) would save energy and resources that would otherwise be used to tackle them after they had spread. A study was initiated at the ICAR-Indian Agricultural Research Institute, New Delhi, on the basis of the early detection and rapid response (EDRR) strategy. For this study, we choose the little mallow (Malva parviflora L.), a newly introduced Malvaceae family weed in the agricultural fields of Delhi and adjoining regions of India. The above-ground allometric parameters ofM. parviflora populations in the main field and the field boundary were compared. The findings revealed that the EDRR approaches established by this study provided useful information to corroborate the weed species' invasion. The canopy diameter, plant height, and the number of leaves M. parviflora differed between the field boundaries (25.72cm, 24.40cm, 58.97, respectively) and main field (12.79cm, 49.08cm, 18.85, respectively) populations in all three locations, except the canopy diameter was comparable in location 2. Furthermore, neighborhood analysis showed that the M. parviflora had greater acclimatization with a variety of neighbors (38 plant species), i.e., legumes, noxious weeds, and seasonal dominant weeds. Malva parviflora has become a dominant weed along the field boundary. However, it has the potential to spread to the main field and become a serious weed in winter crops in the future. The EDRR methodologies developed in this study can be used to assess the invasion of new weeds in a variety of habitats. Plant Science and Biodiversity Centre, Slovak Academy of Sciences (SAS), Institute of Zoology, Slovak Academy of Sciences (SAS), Institute of Molecular Biology, Slovak Academy of Sciences (SAS) 2025.
Govindasamy, Prabhu; Kichu, Watiyangla; Raj, Rishi; Das, Tapas Kumar; Govindasamy, Venkadasamy; Torres, Ubaldo; Bagavathiannan, Muthukumar
Springer Science and Business Media Deutschland GmbH
https://doi.org/10.1007/s11756-025-02069-1 https://www.scopus.com/pages/publications/105021446267?origin=resultslist
Govindasamy P., ICAR- National Research Centre for Banana, Tamil Nadu, Tiruchirappalli, 620 102, India, ICARIndian Agricultural Research Institute, New Delhi, 110 012, India; Kichu W., Christ University, Bangalore, 560 029, India; Raj R., ICARIndian Agricultural Research Institute, New Delhi, 110 012, India; Das T.K., ICARIndian Agricultural Research Institute, New Delhi, 110 012, India; Govindasamy V., ICARIndian Agricultural Research Institute, New Delhi, 110 012, India; Torres U., Texas A & M University, College Station, 77483, TX, United States; Bagavathiannan M., Texas A & M University, College Station, 77483, TX, United States
Investigating Key Contributors to Hospital Appointment No-Shows Using Explainable AI
AI; Artificial Intelligence; Explainable; Health Analytics; Health Informatics; Healthcare; Hospital; Interpretable; LIME; Machine Learning; No-Shows; SHAP; XAI
The healthcare sector has suffered from wastage of resources and poor service delivery due to the significant impact of appointment no-shows. To address this issue, this paper uses explainable artificial intelligence (XAI) to identify major predictors of no-show behaviours among patients. Six machine learning models were developed and evaluated on this task using Area Under the Precision-Recall Curve (AUC-PR) and F1-score as metrics. Our experiment demonstrates that Support Vector Classifier and Multilayer Perceptron perform the best, with both scoring the same AUC-PR of 0.56, but different F1-scores of 0.91 and 0.92, respectively. We analysed the interpretability of the models using Local Interpretable Model-agnostic Explanation (LIME) and SHapley Additive exPlanations (SHAP). The outcome of the analyses demonstrates that predictors such as the patients' history of missed appointments, the waiting time from scheduling time to the appointments, patients' age, and existing medical conditions such as diabetes and hypertension are essential flags for no-show behaviours. Following the insights gained from the analyses, this paper recommends interventions for addressing the issue of medical appointment no-shows. 2024 IEEE.
Yiye V.; Ugbomeh O.; Ezenkwu C.P.; Ibeke E.; Sharma V.; Alkhayyat A.
2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024
Yiye V., Robert Gordon University, School of Creative and Cultural Business, Aberdeen, United Kingdom; Ugbomeh O., Robert Gordon University, School of Creative and Cultural Business, Aberdeen, United Kingdom; Ezenkwu C.P., Robert Gordon University, School of Computing, Engrg.,and Tech, Aberdeen, United Kingdom; Ibeke E., Robert Gordon University, School of Computing, Engrg.,and Tech, Aberdeen, United Kingdom; Sharma V., Christ University, Computer Science Department, India; Alkhayyat A., Islamic University, College of Technical Engineering, Najaf, Iraq
Investigating MnSe@Y2O3 nanocomposite as an electrode for asymmetric hybrid supercapacitor
Asymmetric hybrid device; Energy density; Gel electrolyte; Metal oxides; Metal selenides
In this research work, manganese selenide (MnSe) and yttrium oxide (Y2O3) nanoparticles have been synthesized by facile melt diffusion and hydrothermal technique which are then composited by ultrasonication. The composite MnSe@Y2O3 has been analyzed as a supercapacitor electrode. The growth structure of the composite was scrutinized systematically by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), high resolution transmission electron microscopy (HRTEM), and selected area diffraction pattern (SAED). The Trasatti and Dunn's plots have been also plotted to calculate the capacitive and diffusive contribution. The device is fabricated with PVA-KOH gel electrolyte. Also, the fabricated device MnSe@Y2O3||AC has exhibited a specific capacity of 48.39 C/g at 1 A/g through the potential window of 01.7 V. The wide potential window is evidence for high energy density. This also provides elevated energy density of 19 Wh/kg, at high power density of 1445 W/kg, and has shown brilliant cyclic stability of 70.16 % even after 5000 charge/discharge cycles. 2024 Elsevier B.V.
Bharathi A.N.; Devi V.K.; Sambasivam S.; Albaqami M.D.; Kumar M.K.; Velsankar K.; Sudhahar S.
Journal of Alloys and Compounds, Vol-1009
https://doi.org/10.1016/j.jallcom.2024.176867 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205898653&doi=10.1016%2fj.jallcom.2024.176867&partnerID=40&md5=0c677a470cef213d3abe622624daaea5
Bharathi A.N., Department of Physics, Alagappa University, Karaikudi, 630 003, India; Devi V.K., Department of Physics, Alagappa University, Karaikudi, 630 003, India; Sambasivam S., National Water and Energy Center, United Arab Emirates University, Al Ain, 15551, United Arab Emirates; Albaqami M.D., Department of Chemistry, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia; Kumar M.K., Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, 560 029, India; Velsankar K., Department of Plant Pathology, College of Agriculture, Guizhou University, Guiyang, 550025, China; Sudhahar S., Department of Physics, Alagappa University, Karaikudi, 630 003, India
Investigating Personalized Learning Paths to Address Educational Disparities Using Advanced Artificial Intelligence Systems
Adaptive Algorithms; Bias Mitigation; Content Embedding; Cosine Similarity; Cultural Nuances; Cultural Relevance Score; Cultural Sensitivity; Data Auditing; Diversity in Training Datasets; Named Entity Recognition (NER); Natural Language Processing (NLP); Personalized Learning Paths; Sentiment Analysis
This innovative study reimagines the role of Natural Language Processing (NLP) in individualized education by highlighting the critical need to incorporate cultural subtleties. While natural language processing (NLP) offers great potential for improving classroom instruction, current research frequently fails to account for the complex issues caused by cultural variation. This research fills a significant need by providing a novel framework for the detection and incorporation of cultural subtleties into individualized learning programs. Further research into common biases is driving the development of natural language processing models with greater cultural sensitivity and awareness, such as gender bias in Named Entity Recognition (NER) and sentiment bias in cultural preferences. In order to correct past biases and promote gender neutrality in educational content, the research makes use of an adaptive NER algorithm and a diverse training dataset. Similarly, to guarantee nuanced and fair sentiment evaluations, the study suggests regularly evaluating and retraining sentiment algorithms with datasets that represent multiple cultures. A Cultural Relevance Score of 0.9, Adaptive Content Embedding vectors [0.3, 0.6, -0.2.], and an impressive Cosine Similarity of 0.85 are some of the evaluation measures that highlight the effectiveness of the research. These measurements show encouraging gains, which confirms that the research might help make schools more welcoming and sensitive to different cultures. The research has the potential to revolutionize individualized education by making it more accessible and engagingfor students from all backgrounds. 2024 IEEE.
Chauhan M.; Rahman H.; Ibrahim U.M.M.; Reddy D.S.; Padmanabhan A.S.; Thirumalaikumari T.; Babu G.C.
International Conference on E-Mobility, Power Control and Smart Systems: Futuristic Technologies for Sustainable Solutions, ICEMPS 2024
Chauhan M., Symbiosis Law School-NOIDA, India, Symbiosis International (Deemed University), Pune, India; Rahman H., Malang, Indonesia; Ibrahim U.M.M., Malang, Indonesia; Reddy D.S., Vardhaman College of Engineering, Department of Mathematics, Telangana, Hyderabad, India; Padmanabhan A.S., Law Christ University, Bangalore, India; Thirumalaikumari T., Saveetha College of Liberal Arts and Sciences, Chennai, India; Babu G.C., Gokaraju Rangaraju Institute of Engineering and Technology, Department of Cse, Telangana, Hyderabad, India
Investigating Risk Factors for Enhanced Portfolio Performance: An AI Approach for Indian Midcap Market Analysis
Machine learning; Nifty midcap mutual funds; Nifty midcap100; Portfolio optimisation; Risk-return dynamics; Sharpe ratio
This research investigates the potential of machine learning (ML) for constructing portfolios that outperform human-based management, specifically focusing on the Indian midcap market. The study compares AI-based portfolio compositions, optimised using various risk measures, to the holdings of top midcap mutual funds. In this research, the top five midcap mutual funds sectoral distributions, portfolio compositions, and AI-generated portfolios are examined. According to the research, there is significant performance potential in the AI-generated portfolio, particularly when taking shorter investment horizons into account. Portfolios that maximise the Sharpe ratio produced the best returns throughout the course of the test period for four out of the six sectors, according to the research statistics. Additionally, in order to shed light on the effectiveness and possible advantages of our strategy, our study compares the suggested technique to existing investing strategies that concentrate on particular corporations as well as well-established market benchmarks. The research shows that, particularly when taking shorter investment horizons into account, the AI-generated portfolio has great performance potential. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Rai, Shashank Kumar; Awasthi, Yashmita; Singh, Shanu; Ahuja, Shivam
Lecture Notes in Networks and Systems;Volume;1294 LNNS;pp.173-195
https://doi.org/10.1007/978-981-96-3253-4_13 https://www.scopus.com/pages/publications/105010648861?origin=resultslist
Rai S.K., Christ University, Bengaluru, India; Awasthi Y., Christ University, Bengaluru, India; Singh S., Christ University, Bengaluru, India; Ahuja S., Christ University, Bengaluru, India
Investigating Salt-Finger Convection Under Time-Dependent Gravity Modulation in Micropolar Liquids
gravity modulation; micropolar fluid parameters; salt-finger convection; solutal Rayleigh number; stability analysis; Venezian method
This paper investigates how gravity modulation affects salt-finger convection in a micropolar liquid layer confined between two parallel, infinitely long plates separated by a thin gap. The system is heated and has solute added from above. The study uses linear stability analysis to examine when and how salt-finger convection, driven by the salt-finger process, begins. To analyze this, the partial differential equations governing the system are solved numerically using normal mode analysis. The Venezian approach is applied to find the critical Rayleigh number and the solutal Rayleigh number, which are key to understanding the onset of convection. Also, the paper explores how different micropolar fluid parameterssuch as the coupling parameter, micropolar heat conduction parameter, couple stress parameter, and inertia parameteraffect the system when gravity modulation is present. It is found that gravity modulation can either stabilize or destabilize convection, depending on its frequency. At very high frequencies (approaching infinity), the effect of gravity modulation becomes minimal, having little impact on the convection process. The paper also examines the relationship between the critical Rayleigh number and the solutal Rayleigh number, which are related to heat and solute concentration, respectively. 2024 Wiley Periodicals LLC.
https://doi.org/10.1002/htj.23252 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212301373&doi=10.1002%2fhtj.23252&partnerID=40&md5=5c919125546f1bdfa83094e9d3988147
Jayan D., Department of Mathematics, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Tom C., Department of Mathematics, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Arun Kumar N., Department of Mathematics, CHRIST (Deemed to be University), Karnataka, Bengaluru, India
Jayan, Devika; Tom, Clair; Arun Kumar, N.
Heat Transfer;Volume;54;Issue;3;pp.1782-1795
https://doi.org/10.1002/htj.23252 https://www.scopus.com/pages/publications/105002267883?origin=resultslist