INTERNATIONAL JOURNAL OF INNOVATION AND INDUSTRIAL REVOLUTION (IJIREV)

THE NUTRITIONAL POTENTIAL OF CHOCOLATE IN CANCER PREVENTION: A SIGNIFICANT LITERATURE REVIEW

2025-06-19T16:56:38+08:00

Chocolate, rich in bioactive compounds such as flavonoids and polyphenols, has attracted growing interest for its potential role in cancer prevention. This Systematic Literature Review (SLR), guided by the PRISMA protocol, evaluates the nutritional potential of chocolate in cancer prevention. Comprehensive searches in Scopus and ScienceDirect identified 33 primary studies that met inclusion criteria. Thematic analysis revealed three key research domains: (1) the role of chocolate and cocoa in functional foods and health promotion, focusing on antioxidant, anti-inflammatory, and chemopreventive properties; (2) agricultural and biotechnological aspects affecting cocoa phytochemical profiles; and (3) dietary behaviors and public health perspectives on chocolate consumption. Findings suggest a strong association between moderate chocolate intake and reduced oxidative stress, inflammation, and cancer risk. However, inconsistencies in processing methods and dosage limit generalizability. This review highlights the need for standardized clinical trials and integrative nutritional frameworks to better utilize chocolate’s chemopreventive potential in public health and oncology.

THE INFLUENCE OF MEANING ON CAREER COMPETENCY AMONG AIRCRAFT LINE MECHANICS IN JAPANESE LCCS: MEDIATING ROLE OF EXPERIENTIAL LEARNING

2025-06-29T16:38:24+08:00

The Japanese aircraft industry faces serious issues with competent aircraft mechanics due to business changes, reduced tacit knowledge learning, increased aircraft reliability, diversity of work values, and an unstructured development system. Therefore, this study examines the influence of meaning on career competency among the aircraft line mechanics in Japanese Low-Cost-Carriers (LCCs), using experiential learning as a mediator. Based on the expertisation and adult learning theories, this study attempts to test 12 hypotheses concerning the relationships of meaning, experiential learning, and career competency, emphasising the mediating effects of experiential learning. Data were collected using an online survey of 284 respondents, and 220 usable responses were obtained (77%). In this regard, validity, reliability, and empirical accuracy were assessed using the Partial Least Squares Structural Equation Modelling (PLS-SEM). eight hypotheses out of 12 were supported. The test result showed that meaning positively influence on experiential learning, some dimensions of experiential learning positively influence on career competency, and some dimensions of experiential learning mediate between meaning and career competency. The findings of this study have significant implications across methodology, theoretical, and practical implications. However, several limitations should be acknowledged, and these form the basis for future research directions.

ENHANCING BREAST CANCER PREDICTION WITH AUTOML TPOT CONFIGURATIONS FOR MAMMOGRAPHIC BREAST CANCER CLASSIFICATION

2025-06-17T15:28:34+08:00

Breast cancer remains a leading cause of death among women worldwide. Early detection using mammographic imaging improves patients’ outcomes; however, its reliability is heavily dependent on radiologist’s expertise, often leading to variability and misdiagnosis. This study explores the potential of Automated Machine Learning (AutoML) on enhancing breast cancer prediction by comparing three configurations Tree-Based Pipeline Optimization Tool (TPOT): Default, Light and Sparse. 244 mammography images were obtained from two database access through The Cancer Imaging Archive (TCIA). Image pre-processing was using MATLAB R2022a, USA, employing Contrast Limited Adaptive Histogram Equalization (CLAHE) for image enhancement and Active Contour Method (ACM) for image segmentation of region of interest (ROI). subsequently enabling the extraction of radiomic features. These extracted features were then used to train and test three TPOT configurations; TPOT Defaults, TPOT Light and TPOT Sparse via Python version 3.9. The classification models later were evaluated for accuracy, sensitivity and specificity to ascertain the model’s efficiency in distinguishing between benign and malignant breast cancer. 37 radiomic features: six First-Order Statistical features, 21Gray-Level Co-occurrence Matrix (GLCM) Texture features and ten Shape-Based Features were extracted from sample images. The TPOT Default configuration achieved the highest accuracy of 0.735 (CI95%: 0.611-0.859), with a sensitivity of 0.760 (CI95%: 0.642- 0.878), and precision of 0.731 (CI95%:0.607-0.855) outperforming both TPOT Light, accuracy: 0.633 (CI95%:0.498 -0.768), sensitivity: 0.667 (CI95%: 0.537- 0.797), precision; 0.615 (CI95%:0.485-0.745) and TPOT Sparse with accuracy: 0.673 (CI95%: 0.543-0.803), sensitivity, 0.653 (CI95%: 0.521-0.785) and precision; 0.708 (CI95%:0.587 -0.829). These results demonstrate that the TPOT Default configuration delivers the most reliable classification, highlighting AutoML’s potential as a clinical decision support tool. By reducing manual feature engineering and improving diagnostic accuracy, AutoML could significantly streamline breast cancer detection and improve outcomes in radiological practice.

GREEN HRM IN ASIA: A SYSTEMATIC REVIEW OF TRENDS, GAPS, AND METHODOLOGICAL INSIGHTS

2025-06-29T16:11:52+08:00

Green Human Resource Management (GHRM) has recently become a key strategy for embedding sustainability within organizational routines, promoting employee pro-environmental behavior, and improving corporate environmental performance. Although GHRM has been the centre of attention, little is known regarding the role of leadership styles, organizational strategies and contextual factors in determining the effectiveness of GHRM across sectors and geographical location. In this study, we show that GHRM practices are critical for organizational sustainability as they promote green performance and corporate environmental strategies while engaging employees in sustainability. Our findings show that, especially transformational and environmentally specific leadership, is integral to the development of pro-environmental behaviors. Moreover, GHRM practices lead to sustainability performance through the mediating role of organizational ambidexterity, green training, and psychological climate. These findings highlight the significance of incorporating GHRM into broader corporate sustainability initiatives to realize sustainable environmental and economic advantages. Future research will yield more robust results and more profound conclusions on the long-term effects of GHRM if methodological issues like cross-sectional research designs and self-reported biases (e.g., using the same people to measure both the independent and dependent variable) are considered. AI and big data analytics represent promising frontiers for optimizing GHRM practices.

LTE-BASED PASSIVE FORWARD SCATTERING RADAR FOR HUMAN DETECTION WITH NEMO HANDY SUPPORT

2025-06-22T11:42:01+08:00

A radar used for radar detection includes a setup of a transmitter and a receiver, which may identify any human or animal object that travels between the receiver and the source of illuminator of opportunity via the system. The targets in this study were mainly human, comparable to the situation where intruders enter the country illegally, and by distinguishing between human sizes, the detection can be conducted, which is focused on the body dimension. There have been many cases such as kidnapping at the border in Lahad Datu, Sabah. In order to improve border protection, the passive forward scattering radar system could support the research investigation on the transmitting strength of 4G Long-Term Evolution (LTE) networks that concentrated on Reference Signal Received Quality (RSRQ) and Reference Signal Received Power (RSRP) parameters using Nemo Handy to measure the signal strength and validate the findings of human detection using the setup of this radar system. In addition, this radar system was employed to detect any object that crossed between a commercial transmitter and receiver with a bistatic angle of about 180 ̊ which is forward scatter and produced a Doppler signature. This investigation was carried out utilizing the 1.8 GHz LTE frequency in three separate locations: Batu Laut (Selangor), Port Dickson (Negeri Sembilan), and Taman Suria (UiTM, Selangor). The receiver's data is then extracted and analyzed using MATLAB software. There are four period ranges, namely morning, night, evening and afternoon in this study. Conclusively, Nemo Handy can describe the best time range to support passive forward scattering radar system to provide the best period for human detection. In addition, this system can contribute to many areas such as border or street, to detect human detection and for some reason as protection, security and research.

THE EFFECTS OF ARTIFICIAL INTELLIGENCE (AI) ON EMPLOYEE EFFICIENCY IN ABU DHABI’S INSURANCE COMPANIES

2025-06-19T17:00:27+08:00

The purpose of this research was to determine the effect of ease of use of AI (EU-AI); usefulness of AI tools (U-AI) and actual use of AI (AU-AI) on employee efficiency in insurance companies Abu Dhabi. This study employed a quantitative method. Data were collected from a sample of 370 employees who are working in insurance companies “Abu Dhabi National Insurance Company (ADNIC), Daman Insurance Company, and THIQA Insurance Company using face-to-face questionnaire. To analyses the data, descriptive analysis and partial least squares structural equation modeling (PLS-SEM) were used. The results indicated that AU-AI, U-AI and EU-AI have a significant impact on Employee Efficiency (EE). Specifically, AU-AI has (β = 0.266, t-value = 3.108, p = 0.000), while EU-AI has (β = 0.578, t-value = 6.754, p-value = 0.000). Additionally, EU-AI acts as a mediator in the relationships between AU-AI and EE (β = 0.458, t-value = 6.398, p-value= 0.000) and between U-AI and EE (β = 0.085, t-value = 2.529, p-value = 0.000). Furthermore, the AU-AI has a significant favourable effect on EU-AI (β=0.791, t-value = 23.552, p-value=0.000), and U-AI has an effect on EU-AI (β=0.147, t-value = 2.903, p-value=0.000). This finding indicating that employees who find AI tools easy to use tend to be more efficient in their work. In conclusion, these findings highlight the importance of artificial intelligence in enhancing employees' efficiency within the organization.

DEVELOPING AN INTEGRATED MODEL FOR THE BACKYARD ECONOMY TO SUSTAIN FOOD SECURITY IN MALAYSIA: A SYSTEMATIC LITERATURE REVIEW

2025-06-29T16:46:34+08:00

The backyard economy is an important but little-studied aspect of sustainable food systems, especially in fast-urbanizing countries like Malaysia. This study reviews the literature to determine how an integrated model of the backyard economy can be developed to support Malaysia's food security agenda. The results show that although backyard farming increases household food self-sufficiency, current practices are fragmented because of regulatory barriers, knowledge gaps, resource constraints, and economic disincentives. The study identifies enabling factors like technological innovation, policy integration, community mobilisation, financial support mechanisms, and ecological sustainability as crucial elements of an integrated model. Finally, it suggests a conceptual framework that connects these aspects holistically to position backyard farming as a strategic pillar of national food security. Policy recommendations include mainstreaming backyard farming into urban planning, investing in capacity-building, promoting inclusive technological adoption, developing innovative financing structures, embedding ecological practices, and culturally revalorizing backyard agriculture. This research contributes to advancing sustainable food systems discourse by offering a context-specific blueprint for Malaysia’s backyard economy transformation.

FORMULATION STRATEGIES FOR CHOCOLATE COUVERTURE UTILIZING COCOA BUTTER ALTERNATIVES: A SYSTEMATIC REVIEW

2025-06-19T16:52:04+08:00

This Systematic Literature Review (SLR) investigates formulation strategies for chocolate couverture utilizing Cocoa Butter Alternatives (CBA), addressing the growing demand for innovative chocolate formulations that cater to health and sustainability concerns. The problem centers on the challenges posed by the rising costs and ethical implications related to Cocoa Butter (CB) usage. Employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, we systematically searched two databases, Scopus and ScienceDirect, identifying 27 primary studies relevant to our research focus. Our findings are organized into three key themes: (1) CBAs and Fat Modification, exploring various substitutes and their impact on sensory properties; (2) Nutritional and Functional Enhancement of Chocolate, assessing the implications of alternative ingredients on health benefits; and (3) Processing, Crystallization, and Analytical Techniques in Chocolate Formulation, highlighting the technological advancements that facilitate effective incorporation of CBAs. The review reveals significant opportunities for optimizing chocolate formulations while potentially improving nutritional profiles. Ultimately, the evidence suggests that although CBAs show promise, careful consideration of their effects on texture, stability, and consumer acceptance is critical for successful product development. This study provides valuable insights for researchers and manufacturers aiming to create innovative chocolate products that align with current market trends and consumer preferences.

A SYSTEMATIC REVIEW ON POROUS GALLIUM NITRIDE UTILIZED PHOTOELECTROCHEMICAL ETCHING TECHNIQUE

2025-06-29T16:28:38+08:00

Wide band gap semiconductor gallium nitride (GaN) has been extensively study in the past few decades due to its great potential for many applications, including optoelectronics, solar cells, and power electronics. Porous GaN is one of the most promising nanostructure improvements to enhance the optical properties as well as the sensing and detection capabilities of a device. One low-cost and harmless method to create nanostructured GaN is photoelectrochemical (PEC) etching. This paper presents a systematic literature review of the PEC etching technique's performance and process. There are 15 selected papers chosen from five electronic databases, including Web of Science, IEEE Xplore, Science Direct, ACS, and Emerald Insight. This paper refers to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. The results conclude the specification of the GaN material as well as the growth technique. The pre, during, and post process of PEC has also been discussed in this paper. As a way to find out the performance of PEC etching, the morphological, structural, and optical properties of porous GaN have been analyzed in this study. This paper can be used as a reference for PEC etching of GaN in the future.

POTENTIAL OF COBIA (Rachycentron Canadum) IN MALAYSIA: A REVIEW

2025-06-26T18:13:53+08:00

The Rachycentron canadum, more often referred to as the Cobia, is a pelagic fish that migrates and is found in tropical and subtropical oceans. This species, belonging to the Perciformes order, has been commercially farmed since the late 1990s due to its fast growth rate, high-quality meat, and tolerance to temperature and salinity fluctuations. The majority of commercial manufacturing takes place in China and Taiwan, with China being the primary location. R. canadum is a highly migratory species, often associated with structures like buoys, oil rigs, and shipwrecks for shelter and prey. Its high nutritional value, including 18% to 21% protein content, omega-3 fatty acids, and essential vitamins and minerals like vitamin D, vitamin B12, selenium, and phosphorus, contributes to its ecological role as both predator and prey in marine ecosystems. Commercialization opportunities for R. canadum include rapid development and high-quality white flesh, with operations in the Americas, Vietnam, Thailand, the USA, Australia, and other regions. The International Union for Conservation of Nature (IUCN) does not categorize the R. canadum as vulnerable or endangered, but it is classified as a species of least concern.

POROUS GAN FABRICATION: A BIBLIOMETRIC EXPLORATION OF ELECTROLESS, ELECTROCHEMICAL AND PHOTOELECTROCHEMICAL ETCHING

2025-06-19T17:06:46+08:00

The bibliometric analysis on the topic of porous gallium nitride (GaN) was sourced from the Web of Science (WoS) Core Collection database to provide insight regarding the progression of the topic. A performance analysis and science mapping were performed using Microsoft Excel, WoS analytical tool and VOSviewer to analyze the publication of porous GaN until the year 2023. The result revealed a fluctuating trend of published documents and citations impact of porous GaN research over the past 26 years. The highest publication output of porous GaN was in the year 2016 with 20 documents while the highest yearly publication impact was in 2012 with 309 citations. Although the publication performance is fluctuating, the recent publication of porous GaN in the year 2023 is at 11 documents with four citations and is expected to rise. China ranked as the most productive country contributing to 53 documents on the topic while the USA is the most impactful country in producing quality research with 1331 overall citations. The study also included the most influential and prolific in terms of organizations and authors relating to the porous GaN topic. Furthermore, keyword analysis illustrated through the science mapping suggests the future trend of porous GaN involves a multidisciplinary approach concerning the fabrication of GaN through optical engineering and material characterization. Limitations of the studies included the dataset received only from the Web of Science database and not from any other source, such as Scopus or Google Scholar. The value of the study lies in providing a bibliometric understanding of the evolution, popularity, and advancement of these etching methods.

BIBLIOMETRIC ANALYSIS OF DIGITAL TRANSFORMATION IN THE OIL AND GAS INDUSTRY: A COMPARATIVE STUDY OF MALAYSIA, NORWAY, AND THE UNITED KINGDOM USING LENS.ORG AND VOSVIEWER

2025-06-29T17:01:26+08:00

This study addresses the uneven adoption of digital transformation in the oil and gas industry by benchmarking Malaysia against advanced economies such as Norway and the United Kingdom (UK). Specifically, this research aims to identify key trends, influential sources, and thematic differences in digital transformation research across these three countries. Using a bibliometric methodology, 258 publications from 2010 to 2024 were retrieved from Lens.org and analysed with VOSviewer software. The main analyses included co-occurrence analysis, examination of publication trends, and citation mapping. Results revealed distinct national priorities: Malaysia focuses on workforce readiness and infrastructure development, Norway emphasizes sustainability and renewable energy integration, and the UK leads in innovation and process optimization. The co-occurrence analysis further delineated thematic clusters such as engineering practices, digital technology adoption, and sustainability policies, each shaped by the specific regulatory, industrial, and technological contexts of the nations studied. These findings provide valuable insights for policymakers and industry stakeholders aiming to enhance innovation, sustainability, and competitiveness. Future research should investigate practical strategies for cross-border collaboration and implementing best practices in digital transformation to accelerate sustainable development in the oil and gas industry.