Journals of Universiti Tun Hussein Onn Malaysia (UTHM)
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DLinear Model for Microclimate Prediction of Coffee-Pine Agroforestry
Get PDFDate fruit is one of the most important economical and cultural agricultural crops in the Middle East that plays a critical role in trade and food sustainability. These merits have attracted increasing interest from researchers and the food industry to improve food sustainability. The advent and integration of computer vision and artificial intelligence (AI) technologies have rapidly accelerated the progress in the development of automated classification, quality assessment, and grading for date fruits. This study offers an inclusive comparative analysis for ten pre-trained convolutional neural network (CNN) models used to classify fifteen different date fruit cultivars. The dataset obtained from two publicly available datasets. They contain images of cultivars from Saudi Arabia and Pakistan. The images are first preprocessed to enhance their quality, segmented, augmented to overcome the imbalance problem, standardized, and normalized to be fed then to the CNNs. Transfer learning was applied to fine-tune the pre-trained models using MATLAB 2023a software package. The performance of models were evaluated based on the overall accuracy, per-class accuracy, training time, execution time, and average inference time per image. Results showed that DarkNet-50 achieved the highest accuracy (99.33%), while MobileNet-V2 and ShuffleNet provided the best balance between accuracy and efficiency, hence they are well-suited for real-time or embedded applications
Enhancing Pressure Vessel Design Optimization with a Hybrid CSA-PSO Algorithm
Get PDFThe optimization of the Pressure Vessel Design Problem (PVDP) plays a crucial role in various engineering applications where structures with the most efficient material utilization are required. However, the intricate interplay between design parameters and strict constraints presents a significant barrier for classical optimization algorithms to efficiently traverse the convoluted landscape of PVDP. Applying metaheuristic algorithms has been introduced as a solution to tackle these problems. The techniques introduced have the potential to confront the difficulties associated with nonlinearity, multimodality, and complex constraints that are frequently encountered in complex engineering optimization problems. This work carries out a comprehensive and comparative analysis of the performance of well-established metaheuristic algorithms in solving the PVDP. The methods under consideration at present are Big Bang –Big Crunch (BB-BC), Cuckoo Search Algorithm (CSA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Vibrating Particles System (VPS), and Water Evaporation Optimization (WEO). Third, we introduced the CSA-PSO algorithm. Through extensive numerical experiments, their rates of convergence, the quality of the solutions, and the amount of computation required are compared and analyzed, revealing their relative pros and cons in terms of the PVDP. As a result, the knowledge of how metaheuristic algorithms perform on the PVDP can be exploited when selecting optimization methods
A Comparative Study of Species Richness and Abundance in Protected Areas of Malawi
Get PDFMalawi is a country in the southern part of Africa and has more than 50% of her people living in poverty. In most cases they depend on natural resources to support their daily livelihood. This heavy reliance on natural resources increases the threat on biodiversity richness and abundance. The aim of this study was to understand current state of biodiversity richness and abundance in three protected areas (Mulanje forest reserve (Southern region), Lilongwe nature sanctuary (Central region) and Mzuzu botanic garden (Northern region)) and the effectiveness of conservation efforts that are in place. Assessing species richness and abundance is crucial in determining population trends, conservation planning, and monitoring programs in the management of protected areas (PAs). A cross sectional descriptive and explorative study with a mixed method approach was carried in these three protected areas. A questionnaire and focus group discussions (FGDs) were utilised to collect data. The study was conducted among forest reserve managers, plant identification specialists, game rangers and community members in the three protected areas. Data was collected using structured questionnaires and interview guides and analysed using Microsoft excel software. The results showed that there is low species richness and abundance in the protected areas due to anthropogenic activities. This was supported by findings which revealed low diversity indices of 1.52, 1.18 and 1.13 for Mzuzu botanic gardens, Mulanje mountain forest reserve and Lilongwe nature sanctuary respectively. To reduce the impact of anthropogenic activities, there is need to intensify day and night patrols to reduce intruders from encroaching the protected areas. Awareness campaigns on the value of the biodiversity would help reduce instances of poaching and smuggling of endangered species but also outreach programs in schools would help to instil a culture of appreciation for nature by students. Re-afforestation programs, establishment of wood-lots and not forgetting community involvement in all activities of biodiversity conservation in the surrounding areas are of paramount importance. These would ease the pressure of over- reliance on natural resources by community members surrounding the protected areas
Extraction, Recovery, and Sintering of Manganese from Spessartine-Pyrolusite-Almandine: A Comprehensive Review
Get PDFManganese, a crucial industrial metal, plays an essential role in steel production, battery manufacturing, and various chemical processes, necessitating efficient and sustainable methods for its extraction and processing. The review explores the sintering of manganese extracted from these minerals, an essential step in producing high-purity manganese products for industrial use. Technological advancements and ecological considerations are emphasized throughout the review, highlighting the need for sustainable practices and green technologies in manganese extraction and processing. Economic analyses of the different extraction and recovery methods are provided, assessing their viability and scalability in global market demand. This underscores the importance of integrated approaches to manganese processing, combining traditional methods with innovative technologies to meet industrial needs while minimizing environmental impact. Future research directions and emerging technologies are identified, offering a roadmap for advancing the field of manganese extraction, recovery, and sintering
Role of Nano Materials in Improving Compressive Strength of Bio-Foamed Concrete Bricks: Towards Green Concrete Production
Get PDFThis study explores the enhancement of compressive strength in bio-foamed concrete through the integration of nanomaterials such as nano rice husk ash (NRHA), nano eggshell powder (NESP), nano coffee grounds (NUCG) as cement replacements, alongside the bacterial agent. By utilizing agricultural and food waste, this research aims to investigate the compressive strength of bio-foamed concrete brick (B-FCB) at 28 days using screening stage method. The nano materials enhanced the compressive strength of the B-FCB. The optimal replacement materials for the maximum compressive strength were 1% NRHA, 1% NUCG, and 5% NESP, combined with Bacillus tequilensis at a concentration of 3×105 cells/ml. The empirical modelling indicated that Bacillus tequilensis and ESP have a significant effect on the compressive strength of B-FCB. Incorporating nanosized agro-industrial wastes into B-FCB improves mechanical performance while reducing the environmental impact of accumulated wastes
Conceptualization of Strategic Ecosystem in an Emerging Market Banking Industry
Get PDFThe interactions between a bank\u27s operating environment and its strategies are often complex and not easily visible, yet they play a significant role in shaping the bank\u27s progress. Hence, this study assessed strategic ecosystem and banking performance in emerging market banking industry. Specifically, the study assessed the revolution, characteristics, dimensions, significance as well as problems and prospect of strategic ecosystem on banking performance in emerging markets. The study adopted conceptualization approach by gathering available and related reviews on the study. The study was also based on Adner Ecosystem Strategy Framework. The study found that through the integration of technology, strategic partnerships, regulatory frameworks, and sustainability considerations, banks in emerging markets are evolving their business models to remain competitive, innovative, and inclusive. However, challenges persist, including technological infrastructure gaps, regulatory barriers, financial constraints, low digital literacy, and cyber security risks, all of which can hinder the full potential of these ecosystems. Conclusively, the concept of a strategic ecosystem in banking is both a transformative opportunity and a multi-faceted challenge that must be approached holistically, especially in the context of emerging markets as it offers a promising opportunities for strong bank performance in these markets. Banks therefore should invest in technological infrastructure to fully leverage the benefits of strategic ecosystems as it is essential to invest in upgrading digital infrastructure. Additionally, banks should promote digital literacy and financial education as it is critical to address the issue of low digital literacy
Application of the Beneish M-Score Model in Detecting Financial Statement Fraud in Transportation and Logistics Sector Companies Listed on the Indonesia Stock Exchange in 2019-2023
Get PDFThe high rate of fraud in Indonesia, especially in financial reports, is a serious concern because it causes large losses. This study aims to analyse the percentage level of transportation and logistics sector companies listed on the Indonesia Stock Exchange during the 2019- 2023 period which are classified into three categories, namely manipulators, grey companies and non-manipulators. This study uses a quantitative descriptive method with purposive sampling technique resulting in 20 companies as samples. The data used is secondary data obtained from annual financial reports and analyzed using eight Beneish M-Score ratios. The results showed fluctuations in the manipulator category with the highest percentage in 2020 at 35%. The grey company category was found at 5% in 2019 and 2021, and 10% in 2022, but not found in 2020 and 2023. Meanwhile, the non-manipulator category dominates with the highest proportion of 95% in 2023. The level of integrity of financial statements in the transport and logistics sector has not been consistent. Investors and creditors should be more aware of the potential manipulation of financial statements in order to avoid the risk of loss. Companies are expected to increase transparency and compliance with financial reporting standards to maintain stakeholder trust
Success Factors of Malaysian eBay Entrepreneurs: Skills, Attitudes and Strategies for Digital Growth
Get PDFThe focus is on digital entrepreneurship in Malaysia with specific reference to eBay site, the purpose of the study being to precise the skills, attitudes and strategies that enhance the success of those involved in the business. Even though the Malaysian DKN 2030 (full) and MyDIGITAL projects recognize digital entrepreneurship as a hope for the country’s economy growth, only some of the eBay entrepreneurs in Malaysia may be recognized as ‘Top Rated Sellers’. This research uses qualitative research technique and conducts a series of semi-structured interviews with 10 Malaysian eBay successes. The research evidence suggests that ability to manage stock control, integrated tools in the internet and social networks like SEO (full), and the employees’ favorable personality attributes like perseverance and lobbying. Also, proper use of e-marketing techniques and strong brand image are some of the critical success factors that yielded demonstrated positive outcomes. The result of this research opens the way into theory, practice, and policy, it does open pathways where entrepreneurs require adequate programs and training programs for getting better results. As for the suggestions for the future studies, they include the investigation of social networks, the impact of AI and blockchain on them, as well as the quantitative methods to enhance the understanding of this subject
Transforming TVET: The Impact of Staff Training on Digitization Success
Get PDFIn today’s fast-paced technological era, digitizing records has become a crucial step for organizations to improve efficiency, streamline data access, and ensure information security. As digitization continues to advance, incorporating digital tools and technologies into TVET (Technical and Vocational Education and Training) programs has become increasingly vital. Digitization improves the accessibility, delivery, and relevance of education and training, enabling learners to acquire skills that are crucial in an ever-changing job market. On top of that, TVET (Technical and Vocational Education and Training) is crucial for driving economic growth and decreasing unemployment by equipping individuals with the practical skills and knowledge required across various industries. It helps connect education with employment, ensuring that learners gain competencies that meet the needs of the job market. Despite the tremendous benefits of digitization, many organizations struggle with its implementation due to a lack of adequate training for their staff. Without the proper skills and knowledge, employees find it challenging to adapt to new systems, ultimately delaying or hindering the effectiveness of the digitization process. The absence of structured and continuous training not only slows down the transition but also poses risks such as data errors, information leakage, and decreased productivity. Besides, with the rapid advancement of technology, organizations are increasingly turning to digitization to enhance efficiency and streamline their record-keeping systems. This article will explore how the lack of staff training impacts the success of record digitization and suggest strategies to overcome these challenges
Simulation of Absorption Cross Section: A Preliminary Study of Infrared Absorption Spectroscopy for Sulfur Dioxide Gas Measurement
Get PDFSulfur dioxide (SO2), an unpleasant-smelling toxic gas, is among the six common air pollutants. These gases, particularly Sulfur Dioxide, are released through the combustion of fossil fuels or other materials containing sulfur. This gas can react with other substances in the atmosphere, forming tiny particles that may enter the lungs and lead to similar adverse health effects. Previously, it has been reported that the development of sulfur dioxide gas sensor such as semiconductor, electrochemical, and others show a long response time compared to absorption spectroscopy-based sensor. Thus, the aim of this project is detection of sulfur dioxide using absorption spectroscopy technique in the infrared region. Initially, the infrared region\u27s absorption cross-section of sulfur dioxide was simulated using the Spectralcalc.com® simulator. The validity of the simulation results was established by comparing them to previous research. The deviation of less than 1% was obtained for the value of absorption cross section. Thus, it indicates the suitability of the Spectralcalc.com® simulator for obtaining the value of absorption cross section in the infrared region. Then, simulations were conducted to analyze the effects of pressure on the absorption cross-section, ranging from 800 mbar to 1200 mbar. According to the simulation, the wavelength at 1412 cm-1 exhibited minimal pressure effect, making it conducive for accurate sulfur dioxide concentration calculation