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Building-integrated photovoltaics forecasting: Machine learning models for irradiance and power, feasibility, and recommended directions
Full text linkBuilding-integrated photovoltaics (BIPV) are central to energy-efficient buildings, yet forecasting irradiance and power with operational practicality remains challenging. This review analyzes 70 studies on machine learning approaches for BIPV forecasting and organizes the literature by task and deployment needs. For irradiance forecasting, the survey catalogs common contexts (façade/roof, sky/season, urban geometry), input modalities (telemetry, weather, imagery), model families, and frequently reported error metrics. For power forecasting, horizons from intra-hour to seasonal are compared, distinguishing direct power modeling from approaches that incorporate irradiance estimates. Beyond accuracy, the review examines feasibility and robustness, which determine field viability—namely, latency and memory budgets for edge versus cloud execution, sensitivity to outdoor variability, and risks to generalization across sites and seasons. The review concludes with recommended directions focused on implementable next steps, including shared data/metadata conventions for comparability, methods that can be transferred across buildings and seasons, interpretable operations for building-level decision workflows, and pipelines designed for edge execution. The resulting map of models, inputs, and constraints enables readers to match techniques to forecasting tasks and operational contexts
Wear behaviour of nickel coatings reinforced by recycled quarry dust: Influence of current density
Full text linkNickel coatings incorporated with quarry dust were synthesized through direct current electrodeposition from a nickel Watt’s bath. The study explored the effects of varying current densities on the surface morphology and wear behaviour of the nickel-quarrydust (Ni-QD) composite coatings deposited on a high-speed steel (HSS) substrate. Quarry dust was chosen as a reinforcement material due to its high silica and alumina content, which enhance the properties of the coating. To achieve finer particle size, the quarry dust was subjected to ball milling before electrodeposition. The study tested a range of current densities from 2 to 8 A/dm², as different current densities produce different results. The composite coatings were characterized using a Scanning Electron Microscope (SEM) and their wear resistance was evaluated through pin-on-disk test. The results indicated that increasing the current density enhanced the wear resistance of the coatings. Coatings produced at high current densities displayed a colony-like structure, demonstrating the impact of deposition conditions on colony size relative to current density. Ni-QD composite coatings created at 6 and 8 A/dm² resulted in smoother and narrower wear scars with minimal scratching, attributed to the low surface roughness of the coatings
A fabric-based double rectangular complementary split ring resonator for wideband applications
Full text linkThis paper introduces a novel wideband antenna composed of fabric materials suitable for wearable and flexible applications and a straightforward single-unit Metamaterial (MTM). The antenna design employs ShieldIT Super as the conductive fabric and felt as the dielectric substrate, creating a lightweight and adaptable solution with dimensions of 58 mm × 34 mm × 2 mm. Operating over a frequency range of 1.88 to 6.88 GHz, the proposed antenna achieves a peak gain of 4.72 dBi and a radiation efficiency of 94%. The antenna has a wide measured bandwidth from 1.2 to 3.5 GHz (97%) and 4.0 to 5.9 GHz (38%), with an average measured gain of 3 dBi in
the lower band and 4.6 dBi in the upper band. The MTM-inspired design features a double rectangular complementary split-ring resonator at the center of the radiating patch, which enhances bandwidth. The MTM structure exhibits Epsilon-Near-Zero (ENZ) and Mu-Negative
(MNG) properties. This novel design illustrates significant advancements in wideband antenna performance and is suitable for wearable fabric-based S band, C band, 5G, Wireless Body Area Network (WBAN), and microwave imaging applications
Application of the trait-Factor theory-Based vocational preference inventory on the government school counsellors in Malaysia
No full textThe study aimed to develop a reliable module of career counselling based on the trait-factor theory for government school counsellors in Malaysia. Known as the Modul Kaunseling Kerjaya Tret dan Faktor (MKKKTF), this module was adapted from the Model Pembinaan Modul Sidek (MPMS) and integrated with the trait-factor theorem guidelines. To determine the module’s validity, the content and the module’s appropriateness and significance were evaluated and reviewed by a group of panel experts who were selected using a specific list of criteria. Using the Fuzzy Delphi Technique, the experts’ responses and evaluation of MKKKTF were analysed, and the findings revealed that the MKKKTF was significantly variable to be used as a guideline for government school counsellors, including those who are not registered with the Kaunselor Berdaftar Perakuan Amalan (KBPA) in Malaysia
Integrating family business values into cultural heritage stewardship at Malacca Heritage World Site, Malaysia
Full text linkThis research investigates the intersection of family business practices and cultural heritage management in Malaysia, a country rich in cultural diversity and history. The study was motivated by the need to understand how family-run businesses contribute to preserving and promoting cultural heritage in Malaysia. Through a comprehensive qualitative approach, researchers examined the business strategies, cultural values, and operational models of family businesses engaged in cultural heritage sectors. The findings revealed a
unique blend of traditional values and modern business understanding, highlighting how these businesses play a crucial role in sustaining cultural heritage. Family businesses in Malaysia have developed distinctive approaches to cultural heritage management, blending traditional values with innovative strategies to navigate the challenges of modernisation and globalisation. This has implications for
business practices and cultural preservation, offering insights into sustainable cultural heritage management in a rapidly evolving global landscape. The study underscores the importance of family business-based culture in the stewardship of cultural heritage. It argues for greater recognition of these businesses in policy formulation and heritage management strategies. The “take home” message is clear: Malaysia's symbiotic relationship between family businesses and cultural heritage presents a unique model that balances economic viability with cultural preservation, offering valuable lessons for the business world and cultural heritage sectors globally
A review of technologies and techniques for indoor positioning systems
Full text linkLocation-based services are among important applications in current telecommunication networks which causes an increasing demand in the advancements of indoor positioning
systems (IPS). This paper presents a comprehensive review of the technologies and techniques employed in recent works related to IPS and discusses the challenges in IPS implementations. This study widely categorizes indoor positioning technologies into five types which are computer vision, short-range communication, acoustic-based, magnetic
methods, and radio frequency (RF) technologies. The strengths and limitations of each technology is discussed based on its accuracy, coverage, infrastructure, implementation cost and signal characteristics. The literature study shows that range-based and fingerprinting are two main techniques employed in IPS. In addition, the study indicates that fingerprinting methods utilizing Wi-Fi and cellular networks are prevalent due to their widespread
availability. However, these technologies face some challenges such as multipath fading, signal instability, device heterogeneity, infrastructure and cost implications, computational complexity, and privacy and security concerns. This paper emphasizesthe need for innovative approaches to enhance positioning accuracy and reduce infrastructure costs, thereby fostering broader adoption of IPS across diverse applications
Evaluation of mandibular advancement surgery efficacy in treating obstructive sleep apnea: A study on turbulence kinetic energy
No full textBackground and Objective: Obstructive sleep apnoea (OSA) is a prevalent sleep disease characterised by recurrent airway obstruction during sleep, resulting in diminished oxygen intake and disrupted sleep patterns. This study investigates the effectiveness of mandibular advancement surgery as a surgical intervention for obstructive sleep apnoea by analysing the postoperative alterations in turbulence kinetic energy (TKE). Methodology: The research involved five subjects receiving mandibular advancement surgery (MAS). The quantification of TKE was performed both before and throughout the method using a combination of computational fluid dynamics (CFD) models and empirical measurements. A suitable grid size of 2.6 million cells for CFD simulations was determined by grid sensitivity analysis and corroborated with physical measurements. Results: The findings indicated a significant increase in TKE for each individual post-procedure, with increments varying from 23 % to 460 %. The elevated TKE indicates a more rapid airflow in the upper airway post-surgery. This is probably attributable to alterations in the airway's morphology resulting from the surgery. The observed rise in speed and turbulence is theoretically supported by Bernoulli's principle, which elucidates the relationship between air flow velocity and the pressure it generates. Conclusions: This study demonstrates that mandibular advancement surgery efficiently alleviates OSA by markedly enhancing airflow and diminishing turbulence in the upper airway post-treatment. The use of physical validation and grid sensitivity analysis in computational fluid dynamics simulations underscores the meticulous technique utilised, offering a comprehensive assessment of the efficacy of the surgical interventions for OSA
Low-cost integrated circuit packaging defect classification system using edge impulse and ESP32CAM
Full text linkDefects in integrated circuit (IC) packaging are inevitable. Several factors can cause defects in IC packaging such as material quality, errors in machine and human handling operations, and non-optimized processes. An automated optical inspection (AOI) is a typical method to find defects in the IC manufacturing field. Nevertheless, AOI requires human assistance in the event of uncertain defect classification. Human inspection often misses very tiny defects and is inconsistent throughout the inspection. Therefore, this study proposed a low-cost IC packaging defect classification system using edge impulse and ESP32-CAM. The method involves training a deep learning model (i.e., convolutional neural network (CNN)) using a dataset of non-defective and defective ICs on Edge Impulse. For defective ICs, the top surface of the ICs is deliberately scratched to imitate the cosmetic defects. ICs with scratch-free on their top surfaces are considered non-defective ICs. A successfully trained model using Edge Impulse is subsequently deployed on ESP32-CAM. The model is optimized to fit the limited resources of the ESP32-CAM. By using the built-in camera in ESP32-CAM, the trained model can perform a real-time image classification of non-defective/defective ICs. The proposed system achieves 86.1% prediction accuracy by using a 1,571 image dataset of defective and non-defective ICs
Leveraging CQT-VMD and pre-trained AlexNet architecture for accurate pulmonary disease classification from lung sound signals
No full textThis study presents a novel algorithm for classifying pulmonary diseases using lung sound signals by integrating Variational Mode Decomposition (VMD) and the Constant-Q Transform (CQT) within a pre-trained AlexNet convolutional neural network. Breathing sounds from the ICBHI and KAUHS databases are analyzed, where three key intrinsic mode functions (IMFs) are extracted using VMD and subsequently converted into CQT-based time-frequency representations. These images are then processed by the AlexNet model, achieving an impressive classification accuracy of 93.30%. This approach not only demonstrates the innovative synergy of CQT-VMD for lung sound analysis but also underscores its potential to enhance computerized decision support systems (CDSS) for pulmonary disease diagnosis. The results, showing high accuracy, a sensitivity of 91.21%, and a specificity of 94.9%, highlight the robustness and effectiveness of the proposed method, paving the way for its clinical adoption and the development of lightweight deep-learning algorithms for portable diagnostic tools
Strengthening e-waste governance: A decision framework for sustainable transboundary movements under the Swiss-Ghana Amendments
Full text linkThe Swiss-Ghana Amendments to the Basel Convention mark a significant milestone in global e-waste (electronic waste) management, requiring Prior Informed Consent (PIC) for all transboundary movements of Waste Electrical and Electronic Equipment (WEEE), regardless of their hazard classification. However, developing nations encounter substantial challenges in adhering to these amendments due to regulatory gaps, limited infra‐ structure, and an increasing influx of illicit e-waste imports. This study uses Malaysia as a case study to evaluate the readiness of developing nations to implement amendments, highlighting transferable solutions and recommendations. This study employs a mixed-methods approach that combines qualitative thematic analysis
and bibliometric mapping to analyze academic literature, official reports, and international case studies. The findings reveal that while Malaysia has foundational policies in place, significant challenges remain in addressing informal recycling practices, improving enforcement mechanisms, and building the institutional capacity to implement PIC procedures effectively. This study identifies key areas for improvement, including regulatory reforms, infrastructure development, and enhanced monitoring systems. To address these issues, this study proposes a six-key Integrated Decision Framework that emphasizes legislative and regulatory updates, infrastructure development, international cooperation, capacity building and training, public awareness and engagement, and robust monitoring and enforcement mechanisms. Although tailored to Malaysia, the framework offers transferable solutions to align e-waste management systems with the Swiss-Ghana Amendments, providing a pathway for developing nations to strengthen regulatory readiness, mitigate environmental risks, and contribute to global sustainability