Semarak International Journal of Machine Learning

Innovative Machine Learning Applications in Non-Revenue Water Management: Challenges and Future Solution

Thu, 18 Apr 2024 00:00:00 +0000

The escalating global concerns surrounding Non-Revenue Water (NRW) necessitate a paradigm shift in water management strategies, and innovative machine learning (ML) applications emerge as a transformative solution. This paper investigates the intersection of ML and NRW management, recognizing the pressing need to curb water losses due to leaks, theft, and inaccuracies. As water utilities grapple with the economic and environmental repercussions of NRW, this paper explores the potential of ML algorithms, such as predictive analytics to revolutionize traditional approaches. The discussion encompasses the intricate landscape of challenges, including data quality issues, model interpretability, and the inherent complexity of implementation. Recognizing the multidisciplinary nature of these challenges, the journal emphasizes the collaborative efforts required to harmonize technological innovation with practical implementation. As the world confronts the imperative to optimize water resources, this paper posits that innovative ML applications present a pivotal opportunity to not only enhance the accuracy and efficiency of NRW management but also to foster a more sustainable and resilient water infrastructure. Through a comprehensive grasp of challenges and a proactive pursuit of remedies, stakeholders can establish sustainable, resilient, and equitable water management systems. This paper acts as a valuable reference, providing a detailed discussion encompassing Europe, China, Japan, South Korea, and specific states within Malaysia, with a specific focus on non-revenue water (NRW) systems.

Fuzzy Predator-Prey Systems by Extended Runge-Kutta Method with Polynomial Interpolation Technique

Nor Atirah Izzah Zulkefli, Yeak Su Hoe, Nor Afifah Hanim Zulkefli — Sat, 27 Apr 2024 00:00:00 +0000

The growing significance of uncertainty quantification in mathematical modeling of physical phenomena is evident, with fuzzy sets emerging as an alternative approach. This paper focuses on exploring a numerical method for addressing fuzzy differential equations in two-dimensional problems like fuzzy predator-prey systems. The numerical solution employed the extended Runge-Kutta fourth-order method. To overcome challenges related to polynomial fuzzy differential equations, a combination of the polynomial interpolation technique and the extended Runge-Kutta fourth-order method was applied, mitigating the issues associated with high-degree polynomials. The proposed approach for fuzzy predator-prey systems is briefly described, accompanied by a numerical example. The obtained results underscore the efficacy of the extended Runge-Kutta fourth-order method with polynomial interpolation, showcasing its remarkable accuracy and potential as an alternative method for addressing various uncertainty-related problems.

Dimensions Affecting Consumer Acceptance towards Artificial Intelligence (AI) Service in the Food and Beverage Industry in Klang Valley

Siew Har Ong, Sai Xin Ni, Ho Li Vern — Sat, 27 Apr 2024 00:00:00 +0000

Artificial Intelligence (AI) is a computational approach that aims to approximate human intellect in a more simplified way in order to address technical issues that are beyond the scope of traditional computer approaches. According to the evolution of technology, AI had made their presence in almost every business such as food and beverage. The presence of AI is benefiting food makers and merchants by assisting them in better understanding their consumer through AI. Therefore, the objectives of the research to focusing on factors that affects consumer’s acceptance towards AI service in the food and beverage industry. Factors that include convenience and service quality adopted from is known as AISAQUAL. It consists of 6 dimensions which are efficiency, security, availability, enjoyment, contact and anthropomorphism. In this study, a total of 401 respondents were collected, specifically respondents who had experienced AI service in the food and beverage industry. All data collected was analyze through Statistical Package for Social Science (SPSS) and various type of analysis which include reliability test, normality test, Pearson Correlation Test and Regression test were used in this study to measure the data collected. In short, the result shown that there is a relationship betweenconvenience, security, contact, availability and anthropomorphism towards consumer acceptance on AI in the food and beverage industry. Meanwhile efficiency and enjoyment dimensions were not affecting much on consumer acceptance towards AI service in the food and beverage industry in Klang Valley.

Delving into the Revolutionary Impact of Artificial Intelligence on Mechanical Systems: a Review

Hashem Shatnawi, Mohammad N. Alqahtani — Sat, 27 Apr 2024 00:00:00 +0000

Artificial intelligence technology has become a highly advanced field in science and technology, extensively utilized in business and everyday activities. Artificial intelligence is widely used in engineering, especially in the automotive industry, autonomous vehicles, optimizing heat exchangers' operational settings, and assisting firefighters in rescuing victims in low visibility situations. This work examines the applications of artificial intelligence in mechanical systems, particularly focusing on its utilization in automobiles, heat exchangers, safety and fire systems, and other mechanical systems. Artificial intelligence in mechanical systems enhances precision, minimizes inefficiencies, and substantially cuts manufacturing expenses. Consequently, artificial intelligence will enhance mechanical systems, boosting their production and efficiency.

Artificial Intelligence and Islam: A Bibiliometric-Thematic Analysis and Future Research Direction

Mon, 29 Apr 2024 00:00:00 +0000

The present study examines the growing relationship between Artificial Intelligence (AI) and Islam. This analysis underscores the significance of investigating scholarly output in this field using bibliometric analysis. The study employs the Bibliometrix and Biblioshiny tools to demonstrate the diverse applications of AI in Islamic contexts and the challenges and opportunities that have arisen as a result of the COVID 19 pandemic. Furthermore, it emphasises the need for additional research to explore trends, key contributors, research themes, and future agendas in AI- Islam studies. Since the onset of the COVID 19 pandemic, there has been a noticeable shift in research focus towards AI-Islam, resulting in the emergence of four distinct niches: AI in education, Islamic banking, mobile banking, and Islamic ethics. Researchers are exploring the potential of AI tools in education, investigating the application of AI in Islamic banking, grappling with challenges and opportunities in mobile banking, and scrutinising the ethical implications of AI in the Islamic context.