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Solvability of nonlinear coupled system of Urysohn-Volterra quadratic integral equations in generalized Banach Algebras
Get PDFIn this work, we investigate the solvability of a new class of nonlinear coupled systems of UrysohnVolterra quadratic integral equations involving the generalized fractional kernel functions. By using the LeraySchauder version of the fixed point theorem in the vectorial Banach algebra space, we prove the existence of solutions of the proposed system under suitable conditions. We investigate the stability analysis of the proposed system. Moreover, we establish some special examples and particular cases
An Analysis of Periodic Motion Using Fractional Calculus
Get PDFFractional calculus has gained significant attention from engineers because of its ability to generalisethe concept of derivatives to non-integer orders. This study explores the applications of fractional calculus in engineering mathematics, particularly focusing on the analysis of periodic motion. Although extensive research has been conducted in this domain, the proposed models and algorithms are still in their early stages of development. This study examines the harmonic oscillator problem using a fractional derivative damping term, which is proportional to the velocity, instead of the conventional damping term. This paper presents a series of solutions comparing fractional-order solutions and damping ratios, not only for semi-derivatives but also for a range of fractional orders. An association between the fractional order (α) and damping ratio (η) has been elucidated to minimise the computational duration necessary for resolving the fractional equation of motion pertaining to a one-dimensional simple harmonic oscillator. The roots obtained using this method can be applied to solve the simple harmonic oscillations of a mass between two springs with transverse oscillations. This investigation’s outcomes advance our understanding of fractional harmonic oscillator behaviour andhighlight the efficacy of fractional calculus in tackling intricate engineering challenges
THANKS AND GOODBYE: A CORPUS-ASSISTED DISCOURSE ANALYSIS ON EMOTIONAL DISTRESS IN BTS’ SUGA’S K-POP COMPOSITIONS
Get PDFMental health issues have become prevalent among music artists, more specifically among Korean pop (K-pop) idols. Bangtan Boys’ (BTS) Agust D (aka Suga), for a time adopted his alter ego to voice out his inner turmoil. Using corpus discourse analysis grounded on emotion-focused therapy framework, we analysed the linguistic patterns used by Agust D in his trilogy of mixtapes i.e., Agust D, D-2, and D-day released in 2016, 2020, and 2023. Findings showed his creative use of language in describing his contrasting emotions e.g., fear and anger. Linguistic evidence suggests that his anger is a primary maladaptive emotion which channelled self-criticism triggered by fear and shame, and denial of his feelings was a form of self-defence. Changes in the linguistic patterns were significant as they presented his state of mental well-being, coming to terms with his inner struggles, and fully embracing his true self
Culturalism and Religious fundamentalism: Lexicalisation of counter-ideologies on same-sex sexualities in selected Nigerian newspapers
Get PDFAgainst the backdrop of cultural conservatism and legal restrictions on same-sex relationships, this study examines how language use foregrounds cultural and religious ideologies surrounding same-sex sexualities as depicted in selected Nigerian newspapers. Drawing on Fairclough’s approach to critical discourse analysis (CDA), the study explores how language is used to construct, represent, and perpetuate specific ideologies regarding same-sex sexualities within the Nigerian context. A total of 50 opinion articles on same-sex sexualities were randomly sampled from five purposively selected Nigerian newspapers (Vanguard, The Punch, The Guardian, Nigerian Tribune and The Sun). The newspapers were selected based on their preponderant coverage of the discourses on same-sex sexualities between 2013 and 2015. Data were subjected to critical discourse analysis. Findings reveal that different lexical strategies, such as lexical relations, repetition, negative evaluative adjectives foreground pro- and anti-culturalist ideologies as well as religious fundamentalism and secularism. The study reveals the conflicting ideologies surrounding same-sex sexualities in the Nigerian context
Ensemble deep learning and machine learning: applications, opportunities, challenges, and future directions
Get PDFThe convergence of ensemble deep learning and machine learning has become a critical strategy for tackling intricate challenges across diverse fields such as healthcare, finance, and autonomous systems. Ensemble approaches, which combine the strengths of multiple models, are known for enhancing predictive accuracy, robustness, and generalizability. This paper investigates the applications of ensemble techniques, emphasizing their role in improving diagnostic precision in medical imaging, advancing fraud detection mechanisms in financial services, and refining decision-making in autonomous vehicles. Recent advancements in ensemble methods, including stacking, boosting, and bagging, have shown to outperform single models in various contexts. However, several challenges accompany the opportunities offered by ensemble learning, such as high computational demands, issues with model interpretability, and the potential for overfitting. This study explores ways to address these challenges, including the creation of more efficient algorithms and the incorporation of explainable AI (XAI) frameworks to enhance transparency and user trust. Furthermore, we discuss the future impact of cutting-edge technologies like quantum computing and federated learning on the evolution of ensemble techniques. The future of ensemble deep learning and machine learning is set to be shaped by the proliferation of big data, advancements in computational hardware, and the need for real-time, scalable solutions. This paper provides an extensive review of the current state of ensemble learning, identifies significant challenges, and suggests future research directions to fully harness the potential of these techniques in addressing real-world problems
Educational Background and Workplace Context: Shaping Iranian EFL Teachers' Attitudes Towards Online Teaching
Get PDFIn the constantly evolving field of education, this comprehensive study delves into the attitudes of Iranian English as a Foreign Language (EFL) teachers towards online teaching, with a particular focus on the influence of their educational levels and workplace settings. The research, which involved 160 diverse EFL teachers, meticulously examines the multifaceted dimensions of this pivotal issue. At the heart of this inquiry lies the questionnaire 'Teachers' Attitude Towards Online Teaching' (TAtOT), which Kianinezhad (2023) fastidiously tailored and validated for application among Iranian EFL teachers. The study uncovers compelling findings, demonstrating a direct correlation between educators' educational backgrounds and their attitudes towards online teaching. Notably, teachers with advanced degrees exhibit markedly more favorable attitudes, underscoring the importance of higher education in shaping educators' readiness for online teaching. Furthermore, the research unveils significant distinctions in attitudes based on educators' workplace contexts. Educators in schools manifest more positive attitudes, while those in institutes and universities also express favorable perspectives. These findings hold significant implications for educational institutions, policymakers, and educators themselves. They emphasize the necessity for tailored professional development programs, supportive policy frameworks, and proactive engagement by educators in continuously enhancing their digital competencies. Since the digital transformation of education continues to shape the learning landscape, this research offers invaluable insights to guide the effective integration of technology and online teaching methods, ensuring a brighter and more inclusive future for language education in the digital age
Investment in Malaysian Stock Market and the Inflation Rate
Get PDFThe increasing concern on the rising inflation rate in Malaysia had motivated the need for the study on the investment return for the Malaysian stock market to compare against the inflation rate in Malaysia. The study had reflected towards the literature review to identify the potential pattern for the study creating the expectations to observe the positive correlation between the inflation rate and the portfolio return of the stock investment as well as the higher KLSE market index growth rate over the inflation rate in the country. With this, the resign design through the quantitative method had been introduced with reference to the application of the correlation analysis and regression analysis to test for the hypothesis for the study. In addition, the comparative analysis will be used as part of the quantitative analysis to understand the potential difference in the inflation rate against the KLSE market index growth rate. The outcome for the quantitative findings had concluded that there is very weak negative correlation being observed between the two variables, but the regression analysis failed to show any significant in the relationship between the two variables disagreeing with the previous studies. On the other hand, the KLSE market index growth had been significantly higher than the inflation rate in Malaysia suggesting that the stock investment in Malaysia could be beneficial for the investors to beat the inflation rate in Malaysia. With this, the objective of the study is being achieved with the suggestion towards the potential future research study being proposed for the future researchers
Gemini or ChatGPT? Capability, Performance, and Selection of Cutting-edge Generative Artificial Intelligence (AI) in Business Management
Get PDFThe research paper investigates the comparative functionalities, effectiveness, and selection criteria of Gemini and ChatGPT within the field of business management. Both AI platforms offer specialized advantages applicable across various domains, including market research, strategic planning, operations management, customer service, marketing, human resources, and decision-making. Gemini utilizes Google's vast index to excel in real-time market analysis, strategic planning, and data-driven decision-making. Its robust analytical capabilities facilitate swift identification of market trends, competitor analysis, and precise forecasting. Conversely, ChatGPT specializes in providing qualitative insights, analyzing customer feedback, and facilitating creative content generation, making it particularly valuable for customer interactions and marketing efforts. Regarding performance, both models significantly enhance operational efficiency, data analysis, and customer service automation. Gemini's proficiency lies in processing extensive datasets for insights and optimization, whereas ChatGPT's adaptability and conversational skills elevate customer experiences and creative content production. The paper delineates selection criteria tailored to specific business requirements and contexts. Considerations such as data sensitivity, bias mitigation, cost-effectiveness, accessibility, customization, and integration are pivotal in selecting between Gemini and ChatGPT. While Gemini may be favoured for its factual precision and integration within the Google ecosystem, ChatGPT offers flexibility, conversational capabilities, and potential for self-hosting. Comprehending the distinct strengths and limitations of each AI model is crucial for effectively harnessing their capabilities across diverse business management scenarios. The research delivers valuable insights for businesses seeking to optimize their operations and decision-making processes through AI integration
Does Brand Image Matter in Developing Long-Term Relationship in Mobile Financial Service Industry?
Get PDFIn the current highly competitive mobile financial service market, all organizations must establish long-term relationships with their clients and achieve the highest level of loyalty. Despite many studies, maintaining long-term relationships remains a formidable challenge. This study investigates how brand image moderates the association between relationship quality and brand loyalty. A theoretical framework was established, and structural equation modeling was utilized to examine the relationships. Data was collected from 257 respondents from 6 upazilas using systematic random sampling. The data was analyzed using SmartPLS-based structural equation modeling. The findings indicated a notable connection among trust, commitment, and brand loyalty. The results indicated that brand image moderates the impact of satisfaction and communication on brand loyalty. Lastly, brand image has a positive but insignificant moderating impact on security to brand loyalty association. These outcomes have both theoretical and practical consequences
A Modified Fourth Derivative Block Method and its direct applications to third-order initial value problems
Get PDFA theoretical order eight Modified Fourth Derivative four-step block method (MFDFBM) has been derived, analysed and numerically applied to solve multiple problems originating from Fluid Dynamics, engineering and other sciences. The MFDFBM was derived by applying collocation and interpolation techniques to a power series approximation. Further introducing fourth derivative terms at each of the collocating points yields a block method with an improved order of accuracy. It was observed that the order of the block method increases with the number of fourth derivative terms introduced into the integration interval. Numerical experiments are presented to test MFDFBM on numerical examples, including non-linear homogeneous thin film flow (NHTFF) problems and two non-linear initial value problems(IVPs). The experiments confirm the good impact of adding the fourth derivative terms, which help improve the order of accuracy of the derived MFDFBM, thereby minimising error and agreeing with analytical solution up to at least seven decimal places