Volume 37 (02) March 2025

Several nations of the world are experiencing scarcity of bioenergy so substitute provisions are desired for them. On the other hand, there are numerous riparian countries that need further modernization of river routes. This research is going to address these both issues. The main purpose of the paper is to study the sizing of a photovoltaic (PV) of a hybrid energy system in proper way. And also, an effective design strategy was analysed in this project for of hybrid energy system boat. First, the boat size calculation is studied based on the existing boat design to obtain an efficient solar PV system. Motor used in such boats are 3hp, 5hp, 10hp sizing. Boat can be run directly through sun light or incorporated with battery bank. PV size depends on battery decision. PV size can be 5Kw, 10Kw, 20Kw depending on load demand. Battery backup depends on the duration of the backup time. Optimal boats offer higher PV power and lower battery capacity compared to existing boats. This means the best boats use more solar energy and less reliance on grid energy. Hybrid boat energy calculations and designs of are analysed and efficient one has been established in this research for best utilisation. This paper will be essential, immense help, and strong reference to those who are researching and building boats using hybrid energy.

Keywords: Hybrid energy system; solar boat; sunlight harvesting; Photovoltaic (PV) System Sizing; effective design strategy

Starting powder characteristics can have an impact on the final mechanical properties of a material. This is the same
for a high-strength ceramic such as 3 mol% yttria-stabilized zirconia (3YSZ) in dental applications. Thus,
this study aimed to investigate the impact of 3YSZ nanopowder particle size on its mechanical properties. 30 nm
and 90 nm 3YSZ powder particle sizes were employed. 10 mm-diameter, 5 mm-high samples were prepared by
colloidal processing, followed by cold isostatic pressing (CIP) and the sintering process. Finally, the sintered
samples were characterized. In comparing the 90 nm and 30 nm starting powders, distinct differences emerge in
their respective properties. The grain size of the 90 nm powder measured 303.6 nm, whereas the 30 nm powder
exhibited a slightly larger size at 317.7 nm. Volumetric shrinkage for the 90 nm powder reached 40.3%, while the
30 nm powder had a shrinkage of 34.0%. The hardness of the 90 nm powder was measured at 14.6 GPa, slightly
higher than the 14.4 GPa recorded for the 30 nm powder. Additionally, the fracture toughness of the 90 nm powder
was 5.0 MPa.m^1/2, whereas the 30 nm powder showed a slightly lower value of 4.9 MPa.m^1/2. Both 90 nm and 30
nm 3YSZ powders showcased high mechanical properties, with slightly superior characteristics observed for the
90 nm particles. These findings underscore the nuanced impact of initial particle size on the material’s mechanical
characteristics, emphasizing the importance of precision in powder engineering for optimizing material performance
in various applications.

Keywords: Dental restoration; 3 mol% Yttria-stabilized zirconia; particle size; mechanical properties; characterization.

Human civilization has long depended on fossil fuels as the primary energy source, leading to significant carbon dioxide emissions. One method to reduce these emissions involves converting carbon dioxide into methane. This study developed a simulation model using ASPEN Plus™ software for a commercial-scale plant designed for this purpose, incorporating the Boudouard reaction, the Water-Gas Shift (WGS) reaction, and Fischer-Tropsch (FT) synthesis. A sodium-based catalyst in a fluidized bed reactor facilitated the Boudouard reaction at 900°C and 0.1 MPa, achieving 88% carbon conversion. The WGS reaction, conducted in a packed bed reactor at 400°C and 1.0 MPa with a copper-based catalyst, achieved 95% carbon monoxide conversion. The FT synthesis, also in a packed bed reactor at 240°C and 1.5 MPa with a cobalt-based catalyst, achieved 93% carbon monoxide conversion. The plant model produced 11.53 kg/h of methane from 100 kg/h of carbon dioxide and was validated against literature data. Feasibility studies, focusing on CAPEX, OPEX, ROI, and PBP, examined various carbon dioxide feed flow rates (100–500 kg/h) and feed compositions (0.2–1.0 mass fractions). While CAPEX, OPEX, and ROI values increased with both parameters, OPEX remained unaffected. The breakeven point for the model was determined to be at a carbon dioxide feed rate of 300 kg/h, highlighting the model’s potential scalability and economic viability for larger operations.

Keywords: Process simulation; Boudouard reaction; water-gas shift reaction; Ficher-Tropsch Synthesis; feasibility study

Modular steel constructions (MSCs) are a rapid state-of-the-art construction technique that provides improved quality and cost efficiency. However,their applications have been limited to low-rise buildings in areas with insignificant seismic activities. Therefore, this study needs to investigate the seismic performance of MSC with different stories. Incorporating high-strength bolts into the double-channel beams can enhance its resistance to lateral deformation caused by seismic loads; however, the existing simplified connection model fails to consider this characteristic. The objective of this study is to propose a simplified model that accurately represents the characteristics of beam-to-beam connections suitable for MSC. Based on Chen’s experimental results, a detailed beam-to-beam connection model was developed and the pushover method was used to analyze its mechanical behavior. The obtained numerical simulation results were compared with previous experimental test results to verify their accuracy. Subsequently, this paper utilizes a similar pushover method to investigate the mechanical behavior of the simplified connection model and apply it to full-scale tests. The study investigates the seismic performance of three MSC models (3-story-unbraced, 6-story, and 9-story braced modular constructions). The models were designed to compare their MSC seismic performance with traditional steel constructions using non-linear static and dynamic analysis approaches to capture its capacity curves, story displacement, global damage index and inter-story drift ratio. The results show that the simplified model with high-strength bolts in the double-channel beams

Keywords: Inter-Module Connection; Simplified Connection Model; seismic performance

As the use of drones becomes more widespread, the corresponding rise in drone-related intrusions poses a growing threat to public safety and privacy. Traditional anti-drone systems typically rely on radio-frequency sensors for drone tracking. This paper investigates the fusion of deep learning-based detection algorithms with surveillance cameras within the framework of radio-frequency anti-drone systems. The primary aim is to assess the efficacy of contemporary models and training methodologies in achieving precise and real-time drone detection. One of the central challenges addressed in this paper is the detection of small drones at extended distances, coupled with the demand for real-time performance. To overcome the scarcity of small drone datasets, the research team constructed a real-world dataset for comprehensive evaluations. Various iterations of the YOLO (You Only Look Once) models were compared using this dataset, with specific modifications implemented to enhance small object detection. Additionally, the image sources are diversified for training, incorporating bird images to mitigate false positives and enhance model robustness. Among the YOLO models tested, YOLOv5 exhibited superior precision, recall, and F1 score. The work delves into the impact of additional detection layers on precision, recall, and F1 score, revealing trade-offs between these metrics. The inclusion of bird images in the background training process demonstrated improvements in accuracy and recall, underlining the importance of diverse training data. An intriguing finding was observed when excluding extremely small drones and birds from the analysis, resulting in heightened precision but diminished recall. This highlights the delicate balance required in optimizing detection algorithms for different scenarios. The paper also acknowledges the need for further investigation into the generalizability of the proposed approach across various drone types.

Keywords: Drone detection; deep learning; surveillance cameras; anti-drone systems; small object detection; YOLO Models

The classification of histopathological imagery has garnered significant interest among researchers in the last decade due to the valuable outcome that could be obtained from classifying such microscopic fractions. This would significantly contribute to examining biological interactions. To do so, researchers in the literature have employed various machine-learning classification algorithms. However, the key to success for a precise classification task lies in utilizing an appropriate set of features with proper color space channels that can extract important characteristics from the histopathological images. However, the literature shows a limited feature extraction method with limited color space channel utilization. The accuracy of classification is significantly influenced by the color channels. This study aims to extend feature learning by using a wide range of feature extraction methods and different employs distinct color channels to categorize histopathological imagery. It utilizes two benchmark datasets pertinent to the imagery of breast and prostate cancer for the study. Additionally, the study incorporated a series of pre-processing procedures, such as segmenting the images and extracting salient features. Image segmentation in this research was conducted using four distinct methodologies, encompassing Lumen, Nuclei, Cytoplasm, and Stroma. The reason behind selecting such feature extraction methods and color channels is their popularity and differences, which ensure diversity. Finally, the study utilized SVM-RFE to select features and classify images. The assessment employed metrics such as sensitivity, f1-score, and accuracy. The empirical findings demonstrate that the RGB color space yielded superior performance particularly on the sensitivity evaluation metrics across both datasets, underscoring RGB’s efficacy in classifying histopathological images.

Keywords: Histopathology image classification; color space; feature extraction; support vector machine

Spatial Data Infrastructure (SDI) has become important in developing Smart Cities initiatives to incorporates different types of spatial data, sensors, and technologies to optimise services for residents, via leveraging technological advancements across various fields. SDI support the to enable spatial data availability and access. However, integrating SDI into smart city development faces challenges due to a lack of standardized practices, technical interoperability issues, and diverse data governance policies among cities. These challenges hinder policymakers from effectively using spatial data to enhance urban services and sustainability. To address these issues, a comprehensive review is needed to propose strategies for the successful integration of SDIs into smart city initiatives. This study aims to review current developments in SDI integration within Smart City initiatives, identify key areas of focus, and suggest future directions for improvement. This study uses comparative analysis to synthesize the issues, challenges, findings, and future directions in integrating SDI-Smart Cities initiatives. The review identifies issues related to spatial data integration, technology compatibility, data management, metadata analysis, and institutional frameworks. Improvements in integrating SDI-Smart City initiatives can be directed towards spatial data integration, technological advancements, and institutional reforms. This study highlights the importance of SDI integration in Smart City development by providing a robust spatial data foundation, contributing to sustainable urban growth.

Keywords: Spatial Data Infrastructures; SDI; Smart City; SDI integration; SDI and Smart City; spatial data sharing

The discharge of medical institution effluent into a water body can result in eutrophication, primarily due to the presence of ammonia nitrogen in the effluent. Therefore, it is essential to thoroughly treat the effluent to effectively eliminate ammonia nitrogen. This study aimed to to investigate the effectiveness of co-cultures of different bacteria and algae in removing ammonia nitrogen, while also identifying the most effective combination of bacteria and algae. Response surface methodology (RSM) was employed to investigate the interaction effects of “light intensity”, “irradiation time”, and “bacterial inoculation ratio” on the removal efficiency of ammonia nitrogen. The optimal parameter combination was proposed and validated through experiments. The results indicated that among different combinations of bacteria and algae, Chlorella pyrenoidosa and Bacillus licheniformis demonstrated a more effective removal of ammonia nitrogen. Furthermore, the response surface model and variance analysis revealed that light intensity had a significant influence (P = 0.0397< 0.05) as compared to irradiation time and bacterial inoculation ratio. Under optimal conditions, light intensity at 4792lux, irradiation time at 12.8h, and bacterial inoculation ratio at 7.1%, it was predicted that the removal efficiency for ammonia nitrogen reach 88.66%. Subsequent experimental verification under similar conditions – light intensity at 4800lux, irradiation time at 13h, and bacterial inoculation ratio at 7% – yielded an actual value for ammonia nitrogen removal efficiency at 88.15%, consistent with the predicted value. These findings establish a theoretical foundation for the practical implementation of bacteriaalgae symbiosis systems in wastewater treatment processes.

Keywords: Bioremediation; wastewater treatment; bacteria; algae; ammonia nitrogen removal

This study explores the role of museum settings in enhancing visitor engagement and interest at local museums situated near cultural heritage sites. Previous research has shown a lack of studies focusing on the impact of museum settings in such locations, especially compared to renowned sites like Borobudur and Angkor Wat. Initial investigations of four local museums at heritage sites revealed that the surrounding historical sites failed to effectively leverage the museum’s potential. This research delves into how history, ancient monuments, and the natural environment influence visitor attraction and local socio-cultural dynamics. The primary aim of this study is to examine the role of museums located at heritage sites, focusing on their planning, development strategies, and the integration of local history and culture. Four local museums near historic sites were selected as research locations. A qualitative approach, involving an exploratory review of existing literature on museum management, cultural heritage, and heritage tourism, was employed. Findings indicate that, despite their proximity to culturally significant sites, the museums often lack coherent strategies or thoughtful development. Some museums were not initially designed as such, and many suffer from the absence of short- or medium-term strategic plans that incorporate the historical and physical attributes of their surrounding heritage sites. This planning gap hampers the museums’ potential for long-term success and visitor engagement. The research aims to serve as a resource for enhancing the local community’s understanding of cultural and historical heritage, offering insights for future museum development. The findings suggest that the Department of Museums Malaysia can use this study to support the transformation of
local museums into professional, globally recognized institutions that attract a broader international audience.

Keywords: Museums in historic site; historic locations; environmental linkages; museum purpose and function

In this paper, a solar chimney has been investigated to determine its environmental effects and the impact of its components on the volume of air exhausted through the chimney’s outlet under various climate conditions.Simulations were carried out using EnergyPlus software. First, the model was implemented and developed within the software. Second, the influence of climatic factors on the solar chimney’s performance was examined. Finally, the effect of solar chimney components on their performance in Yazd city during the hottest day of the year was assessed. The results highlight the significant influence of the solar chimney’s configuration on its performance. Solar radiation intensity and air temperature directly correlate with the solar chimney’s efficiency, while humidity exhibits an inverse correlation. Additionally, the solar chimney’s performance is affected by its height and the thermal mass behind it. On the hottest day of the year, increasing the chimney’s height from 3 meters to 6 meters leads to a 56% increase in exhaust air volume, and the addition of a thermal insulator during the same period results in a 21% increase. However, the use of single or double-glazed glass and the type of thermal mass do not significantly impact the solar chimney’s performance. Conversely, reducing the cross-sectional area of the solar chimney channel can increase exhaust air volume by increasing airflow velocity and preventing reverse airflow effects.

Keywords: Solar chimney; EnergyPlus; hot-dry climate; natural ventilation

There are numerous forms of earth retaining systems (ERSs). Assessment of the suitable forms of the available ERSs to fit the required application is the first vital stage in the geotechnical design processes. The possible considerations should be adopted to ensure the selected retaining system performs satisfactorily. Before the selection stage, it is necessary to have an idea of the particular forms of the ERSs; also, reviewing the classification bases that affect their final selection is essential. In this review, many ERSs were classified, ranked, and discussed. These systems were presented and described based on various considerations, like the economy and technical feasibility. According to the literature, several bases were named and adopted for this review to help classify and select relevant ERS. These are the cost of ERS, the length of the retaining system and its height, its base width, its alignment and arrangement, the batter of the retaining wall (RW) and the uniformity of its back-face slope, the shape (configuration and the geometry) of ERS, and its flexibility. It was found that the economic factor is the most essential factor affecting decision-making in selecting the ERS. This factor, in turn, is greatly influenced by the flexibility and ductility of RW, the batter face of the RW, and the geometry of RW (using back-face slopes and introducing relief shelves). Finally, the performance of the selected ERS under static and dynamic loading depends on the selected flexibility, height, mass, and geometry of ERS.

Keywords: Earth retaining system economy; seismic load; configuration; geometry flexibility; earthquake load

Driven by environmental sustainability, research in composite materials has seen a surge in interest in biodegradable materials. There is a growing trend among researchers to utilize biodegradable and renewable materials, which enhances the perception of ecological safety. Even though bio-based materials such as poly (lactic) acid (PLA) are biodegradable and completely recyclable, they come up lacking in satisfying certain material requirements such as high thermal stability, mechanical strength, impact resistance, and environmental resistance. Researchers are exploring natural fibers like kenaf to address this challenge and promote sustainability as reinforcements for PLA composites. Despite this, a significant barrier to completion persists in unsatisfactory mechanical performance due to the poor adhesion at the interface between hydrophilic kenaf and hydrophobic PLA. A potential solution to this challenge could involve the incorporation of nano-clay into the natural fiber composites. The enhanced interfacial interaction between the reinforcing material and poly (lactic) acid (PLA) imparts superior properties to composites when the nano-clay is incorporated. This review article examines how incorporating nanoclay into these composites can bridge this gap by enhancing the interfacial bonding between PLA and natural fiber reinforcement. Furthermore, an assessment is conducted on the mechanical properties of natural fiber composites reinforced with nano-clay and kenaf, polymers, and nano-clay. This research is particularly pertinent to the development of automotive applications.

Keywords: Poly(lactic) acid; nano-clay; kenaf; mechanical properties; automotive

The impact of eye health and vision rehabilitation spans several critical areas, including public health, sustainable development, and economic welfare. Currently, a significant number of individuals, families, and communities worldwide are affected by visual impairment and blindness, largely due to limited access to affordable and high-quality eye care services. For socioeconomically disadvantaged populations, the situation is even more dire, highlighting the importance of community outreach programs that focus on the early detection and treatment of ocular diseases. Mobile health technologies, particularly mobile applications, have emerged as promising tools for enhancing accessibility and affordability in eye care. These initiatives promote self-care practices and leverage mobile phone-captured images for real-time ocular disease screening. This paper provides a comprehensive review of the role of mobile applications in ocular disease screening within community outreach programs. The adoption of such technologies can also play a pivotal role in reducing the overall burden on healthcare systems in resourcelimited areas. Additionally, a case study was conducted to evaluate the effectiveness of mobile apps in cataract screening at two old folk homes in Malaysia, showing a high accuracy rate exceeding 90% in both locations. The findings suggest that mobile apps hold significant potential as cost-effective and scalable solutions for ocular screening in underserved communities, particularly in regions where access to high-quality eye care services is limited.

Keywords: Community outreach programs; good health and well-being; mobile apps; ocular diseases

Global warming threatens basic human life, significantly impacting the climate due to human activities and building energy use, increasing carbon footprint. Rapid growth in urban population and urbanisation increases the demand for energy, contributing to continuous Greenhouse gas emissions. It represents a significant threat to climate globally and indoor thermal conditions may fluctuate significantly due to abrupt changes in ambient thermal conditions. This could make the occupants uncomfortable and impact to higher utilisation of cooling system. This paper highlights the idea of the real-time possibility of indoor thermal monitoring, whereas a Digital Twin is a virtual representation of a physical asset that is used in experiments or simulations to forecast behaviour and aid decision-makers. Therefore, the main objective of this bibliometric analysis is to analyse the research on Digital Twins and energy efficiency with a focus on Indoor Thermal Comfort, using the Scopus database. Suitable keywords were chosen to filter the data and then analysed as per different criteria such as the number of articles published by an author, the number of citations, institutions producing a greater number of articles, Journals producing the great number of publications, categorization of scientific documents, and most prolific countries in terms of publications. Results revealed Zhang Yan as the most prolific author, China as the leading country in publications, and “Energies” as the top journal. Despite the growing research interest over the past five years, DTs are expected to be crucial in future industry advancements, especially in construction, as evidenced by their increasing productivity.

Keywords: Digital twin; energy efficiency; indoor thermal comfort; bibliometric analysis

In recent years, bamboo’s eco-friendly advantages over synthetic polymers have attracted great attention. This study investigates the effects of mechanical property on G. scortechinii (Buluh Semantan) bamboo fibers, incorporating them at different weight percentages (9, 13 and 18 wt%) are filled in epoxy resin. In this paper, the study of tensile properties and performance of natural bamboo fiber powder reinforced epoxy polymer matrix-based composites were investigated at three distinct curing temperature ranging T26°C, T38°C and T50°C. The treatment of the bamboo fibers improved the mechanical properties of the composites. Mechanical property like tensile strength was evaluated and morphology of the fracture specimens of the composite was studied through SEM (Scanning Electron Microscopy). Results indicate that, at 26°C, tensile strength reached 41.6 MPa and Young’s modulus 2.84 GPa at 13% loading with a 0.52μm particle size. However, at higher temperatures of 38°C and 50°C, tensile strength dropped to 21.2 MPa and 6.15 MPa, correspondingly, with an 18% loading and a 1.5μm particle size. The increase in the tensile strength is due to the excellent fiber matrix interface adhesion. However, it was discovered that the samples with bamboo fiber reinforced- epoxy composites T26°C temperature had greater tensile strength than samples with high temperature T38°C and T50°C bamboo fibers. Scanning Electron Microscope (SEM) analysis at 13% weight loading revealed robust fiber-matrix interfaces without clumping or voids. This study presents a novel approach for creating lightweight, high-strength composites using bamboo fiber and polymer, offering versatility in various applications.

Keywords: Bamboo; fiber-reinforced composite; epoxy resin; mechanical properties

This study describes the protocol of conducting a systematic study on the basis of building defect management theory to increase awareness and education among building occupants and managers. A systematic review shows how previous scholars have applied theories used in managing building defects. Awareness and challenges in defect management for strata title buildings with a focus on the impact of defect management practices. In-depth interviews with occupants and building managers yielded findings about different levels of awareness, challenges in communication and varied experiences of managing building defects. The proposed conceptual framework includes awareness raising, effective communication, consolidation and consolidation of processes and technology integration. This systematic review highlights the considerations that need to be addressed by looking at the variables used in theories involved in managing building defects. The main contribution of this study is to devise appropriate and practical strategies to improve disability management, emphasizing the role of education and technology in improving the overall process.

Keywords: Building defect management; building defects; awareness; education; stratified ownership residential buildings

This study investigates the effect of point distance and time exposure on SLM stainless steel 316 and compare with standard conventional stainless steel 316. Nine specimens (VD2, VD3/VT1, and VT2) were fabricated using the SLM machine Renishaw RenAM 500E with parameters of 240 W laser power, 0.055 mm and 0.06 mm point distance, 80 μs and 90 μs time exposure, 0.11 mm hatch distance, 0.05 mm layer thickness, 67° scanning rotation between subsequent layers, and a stripe with a 5 mm width scanning strategy. The shape of the particle is almost spherical, and the range of particle diameters of metallic powder was 15-45 μm for the fabrication of SLM stainless steel 316. Three specimens of stainless steel 316 from a conventional plate were prepared using a laser cutting machine. Twelve specimens were tested with the Archimedes method using an MDS-300 densimeter for density measurement, surface roughness test using a non-contact profilometer for surface roughness measurement, ultrasonic test using Olympus Epoch 650 to determine sound velocity measurement, and three-point bending test using Instron 5585 to determine Young’s modulus value. In ultrasonic testing, results show that Young’s modulus value of VD3/VT1 (129.152 GPa) is more comparable to the standard Young’s modulus of stainless steel (193 GPa). This is due to a stable molten pool and coarse grain size which leads to an increase in density and sound velocity increase in SLM parts. In three-point bending testing, it is shown that Young’s modulus value of VD3/VT1 (126.825 GPa) is comparable with standard Young’s modulus value of stainless steel 316, due to the internal structure formed during the SLM process. From this study, it is shown that more analysis should be done to explore how point distance and time exposure can be factors that effect on mechanical properties.

Keywords: Selective laser melted; point distance; time exposure; mechanical properties; stainless steel 316

This study aims to explore the potential of thin shell structures as large foundations to improve flood resilience and enhance structural robustness. While thin shell structures have shown promise in resisting various loads, their application as foundations for buildings has not been fully investigated. Thus, this study focuses on designing the necessary reinforcement for a proposed thickness of 304mm. The reinforcement design follows Eurocode 2 guidelines, utilizing T32-300 as the main reinforcement rebar of the thin shell and 5T40 and 4T40 rebars for compression and tension of the ring beam, respectively. R12-150 links are incorporated for added strength and connectivity. This optimized design approach extends the application of thin shell structures beyond lightweight usage, making them viable for withstanding hydrodynamic and seismic loads. This advancement expands possibilities for architects and engineers and improves the resilience of buildings in flood-prone areas. Overall, this study presents a comprehensive design procedure for utilizing thin shell structures as large foundations, contributing to the development of resilient buildings capable of withstanding extreme conditions and safeguarding lives and infrastructure.

Keywords: Thin shell structures; reinforcement design; hydrodynamic load; seismic load; large foundations

Traffic violations like RLR are not only dangerous but are also a leading cause of accidents and injuries worldwide. This research seeks to deepen the understanding of why these behaviours occur, with the ultimate goal of improving road safety and promoting sustainable, safer urban transportation systems. By reviewing existing literature from the Scopus and Web of Science (WoS) databases, this study mapped out three main themes—influence and risk, intention and perception, and intervention and prediction—along with eleven sub-themes related to RLR behaviours. These themes capture the complex factors influencing RLR, such as individual perceptions of risk, societal norms, and the effectiveness of interventions aimed at preventing these dangerous behaviours. This study also highlights the diverse methods researchers use to investigate RLR, from behavioural analysis to predictive modelling, which offering a comprehensive view of the issue. Recognizing the ongoing challenges in this area of research, this study
calls for continued debate and exploration, especially in the context of scoping studies and other literature review methods, to better inform policy and intervention strategies that can make roads safer for all road users. This study contributes to Sustainable Development Goals (SDGs) 3 (Good Health and Well-being) and 11 (Sustainable Cities and Communities) by exploring the critical issue of red-light running (RLR) among riders of two-wheeled vehicles, such as motorcyclists, bicyclists, and e-bikers.

Keywords: Behaviour; riders; red-light running; traffic violation; two-wheeled vehicles

Recent trends indicate a significant rise in artificial intelligence (AI) usage in engineering education, highlighting the need for alignment with the Fourth Industrial Revolution (IR4.0) and 21st-century skills. Traditional assessment methods often fail to promote higher-order thinking skills needed to solve complex real-world problems. This paper presents the 2A2CAI framework, a methodological approach for alternative assessment in culminating courses (2C) within Malaysian engineering programs. The framework addresses specific gaps, such as the lack of personalization and real-time feedback in current assessments, by leveraging AI to enhance precision and efficiency. The development process includes five stages: a comprehensive literature review, qualitative focus group investigations, quantitative pilot studies, the creation of customized assessment tools, and expert validation. By incorporating AI, the framework ensures robust and reliable assessments that evaluate both cognitive and noncognitive skills, transforming educational evaluations to better meet individual student needs and align with desired learning outcomes.

Keywords: Alternative Assessment (AA); artificial intelligence; culminating courses; engineering education; methodological framework

This study focuses on the structural behaviour of cellular stainless-steel beams (CSSBs) with different diameter web holes at elevated temperatures using an experimental-numerical approach. Key parameters such as stiffness, load-bearing capacity, and stress distribution were investigated through three-point bending and fire heating tests in accordance with ISO 7438 and ISO 834 standards, respectively. Using ABAQUS, a two-step Finite Element Analysis (FEA) framework was constructed, with thermal and structural analyses conducted in succession, simulating experimental conditions as closely as possible. Results showed that smaller web hole diameters increased stiffness and load bearing capacity but increased the weight of material. On the other hand, larger holes were more materials efficient but greatly increased stress concentrations, resulting in an overall performance drop of the structure. The parametric studies highlighted the most critical trade-off, between structural integrity and materials efficiency, and the need for careful and optimal web hole design. Although no direct comparison at room temperature was made, qualitative trends agreed with previous studies and confirmed the validity of the numerical model. This study highlights the need for structural design to ensure a balance between web hole size, fire resistance and load-bearing capacity. This approach allows for a more targeted focus on understanding the specific design considerations necessary for enhancing the fire resistance of stainless-steel beams, as the results can be used to support the development of fire-safe design guidelines specifically for this type of beam.

Keyword: Stainless steel beams; cellular structures; fire resistance; Finite Element Analysis (FEA); web hole diameter

Soil stabilization is a widely adopted technique to improve the geotechnical properties of problematic soils, traditionally achieved using calcium-based materials such as cement, lime, and fly ash. However, these conventional additives contribute to carbon emissions, prompting interest in alternative industrial by-products like granite dust. This study explores the effectiveness of granite dust as a stabilizer for enhancing the stress-strain behavior of residual soils. Residual soil samples were collected and mixed with varying percentages of granite dust at 0, 2, 4, 6, 8 and 10% and tested using unconfined compressive strength (UCT). The specimens were tested with curing time of 7 days and compared to without curing time. Results indicate that the addition of granite dust improves soil strength, with 8% of granite dust yielding the highest peak deviator stress of 690 kPa after 7 days of air curing with minimal axial strain (5.2 mm). While higher granite dust content, such as 10%, showed initial strength improvement without curing, it experienced diminishing returns after curing. The study concludes that 8% granite dust is the optimal content for enhancing the mechanical properties of residual soils, providing an eco-friendly and effective alternative to traditional soil stabilization methods.

Keywords: Residual soil; shear strength; granite dust; unconfined compressive strength

The presence of heavy metal in soil poses major threats to the environment and integrity of structures. Rapid industrialization further increases the rate of contamination of heavy metal in soil. The presence of heavy metal contaminants in soil changes the geotechnical properties of soil, which will affect the structure atop the contaminated sites. Changes in mechanical properties of soil could alter the compressibility behaviour of soil. The purpose of this research is to determine the compressibility behaviour of zinc contaminated residual soil with different concentration levels of zinc. A total of thirty samples including a control sample were prepared with ZnSO4.7H20 concentrations of 0 mg/L, 500 mg/L, 1000 mg/L, and 2000 mg/L with curing period of 0 days, 7days, and 28 days. The samples were tested for One- Dimensional Consolidation Oedometer test, pH test, and Electric Conductivity test. The results show a decrease in compression index value, void ratio, and coefficient of consolidation as the concentration of zinc increases. Compression index value decrease to the lowest value of 0.143 under 2000mg/L concentration at 28 days curing period. Void ratio achieves the highest value with 500 mg/L concentration at 7 days curing period while the control sample shows the lowest void ratio value. As for coefficient of consolidation, the highest value is achieved for sample with 500 mg/L at 7 days curing period where the control sample shows the lowest value. The pH value of soil declines to acidic value from 5.82 to 3.84 under concentration of 2000 mg/L at 28 days curing period while electric conductivity increases from 156 μs/cm to 2990 μs/cm at 0 days curing period.

Keywords: Compressibility; residual soil; heavy metal

The Malaysian construction industry has been developing and requires a large workforce. Local laborers are not showing much interest in participating due to their perception that construction site work is often dirty, dangerous, and tough. Employers are compelled to engage foreign immigrants who are willing to work in such conditions and accept low pay due to these issues. Foreign laborers dominate the Malaysian construction industry. These circumstances have led to many problems and adverse effects on the sector. This research objectives are to identify issues with foreign labor participation in Malaysia’s construction sector, investigate its negative impact, and propose solutions to mitigate its adverse effects. These objectives were achieved using a mixed-methods technique that involved an online questionnaire survey and interviews. This study reveals important difficulties related to the participation of foreign workers in the construction business, including their negative effects and potential actions to mitigate these effects. The data was examined using the Relative Important Index (RII) and content analysis. Language barriers had the greatest RII of 0.831, indicating it is a crucial issue in the industry. The interview data indicated that the language barrier primarily affects technical communication on site. The most significant negative consequence was the quality of work, with a RII of 0.837. The interview data indicates that foreign laborers with construction experience are crucial for advancing the project successfully. Ensuring sufficient safety training for foreign workers is widely supported in efforts to address negative consequences, with an RII of 0.857, contingent on aggressive measures by the government and other relevant entities to implement regulations more rigorously. The results can assist industry stakeholders, building firms, and other researchers on these issues

Keywords: Foreign labor; construction industry; negative impact; initiative

Construction projects range from minor repairs to large-scale infrastructure developments and rely heavily on the handling of construction machinery, including excavators, bulldozers, cranes, loaders, and dump trucks. These machines increase efficiency, reduce manual labor, and ensure precise outcomes. However, the risks associated with construction activities necessitate stringent safety measures, underscored by the Occupational Safety and Health Act of 1994, enforced by the Department of Occupational Safety and Health (DOSH) to prioritize worker safety. This paper aims to identify the types of injuries resulting from machinery use, analyze current safety practices, and propose strategies for enhancing worker safety. Key findings reveal that cuts and lacerations are the most frequent injuries, while crushing injuries rank lowest. Furthermore, current safety measures emphasize the importance of providing appropriate personal protective equipment (PPE) for workers. The study highlights the need for clear safety protocols, signage, and designated safety zones to improve machinery handling, with training programs identified as a lower priority for enhancement. Data were gathered through a questionnaire survey distributed to construction personnel which is 28 respondents from G7 contractors in Shah Alam Selangor, including engineers and supervisors, and analyzed using the relative importance index and reliability analysis. The findings are intended to assist construction companies in addressing safety concerns and offer valuable insights for industry personnel and policymakers focused on improving safety practices in construction projects.

Keywords: Machinery; safety; construction; workers; strategies

The increasing demand for sustainable and eco-friendly materials has driven the development of biodegradable biocomposites with improved mechanical and thermal properties. However, the mechanical performance of hydrophilic starch fillers and hydrophobic polymer matrices is limited due to their low compatibility, which makes the development of durable bioplastics for real-world applications challenging. This study investigated the effects of acetylation and ultraviolet/ozone (UV/O₃) surface modification on the performance of polylactic acid (PLA) reinforced with tapioca starch (TS) as a biodegradable filler. The modified and unmodified composites were characterized by using Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and Field Emission scanning electron microscopy (FESEM) to evaluate chemical, thermal, and morphological changes. The acetylation process introduced ester linkages, while UV/O₃ treatment enhanced surface hydroxyl groups, leading to improved compatibility and adhesion between the PLA matrix and tapioca filler. Thermogravimetric analysis revealed enhanced thermal stability, with both modifications delaying the onset of degradation. Mechanical testing showed that UV/O₃-treated PLA/TS achieved a tensile strength of 48 MPa, showing a 45.4% increase over untreated composites, while acetylated PLA/TS demonstrated superior elongation at break, reaching 1.81 mm. These findings highlight that targeted surface modification significantly enhances the mechanical properties of hard bioplastics, making them suitable for applications in sustainable food packaging such as plates, cutlery, and lunch boxes. This study provided a foundation for developing high-performance biodegradable composites by leveraging surface engineering strategies, contributing to the broader goals of environmental sustainability and reduced reliance on petrochemical-based materials.

Keywords: Surface modification; acetylation; UV/ozone treatment; biocomposites; tapioca starch

Excessive use of food additives such as benzoic acid negatively affects human health, leading to serious conditions such as liver failure, kidney failure and cancer. To detect benzoic acid in food, this project proposes the development of a surface plasmon resonance polymer optical fiber (SPR-POF) sensor. The sensor is fabricated by removing portion of the POF’s cladding and core, followed by coating it with a 5nm thick layer of gold (Au) film. The D-shaped POF structure after polishing was analyzed and examined using Field Emission Scanning Electron Microscopy (FESEM). A detectable change in the response of the sensor that occurs when it encounters different concentrations of benzoic acid, enabling the identification of its presence SPR-POF detects power loss with a discrete peak generated by a 650nm diode laser and a power meter is used to show the chemical fingerprint of benzoic acid. This allows quantitative and qualitative measurement of peak wavelength intensity, which in turn allows the detection of benzoic acid concentration. The main results show that the gold-coated and polished D-shaped optical fiber sensor has the lowest power loss of -7.6 dB at a concentration of 0.4 g/ml, with the lowest limit of detection (LoD) of 5.6 ng/mL indicating high sensitivity.

Keywords: Polymer optical fiber; surface plasmon resonance; D-shaped; benzoic acid

This study compiles comprehensive data on significant flooding incidents throughout the historical narrative of Malaysia and presents the official estimates of flood-related losses for the chosen major flood occurrences spanning from 1970 to 2024. Additionally, it offers details regarding the underlying factors and consequences of floods, as well as an explanation of the flood prevention strategies implemented in this area. In addition, it provides information on the distribution of financial resources for flood mitigation initiatives by the Malaysian government as part of the Malaysia Plan (1971 to 2020). Past flood experiences have shown that a significant danger leading to potential loss of life or severe harm to individuals arises from the scale and strength of the floods, encompassing factors such as water levels, flow rates, and the speed at which the flood occurs. Intense floods characterised by elevated water levels and sudden occurrence, such as flash floods, have the potential to overwhelm flood defences and escape routes, hence increasing the risk of drowning and injuries. Nevertheless, it is recommended that Integrated Smart Alarm System will be deployed in flood-prone regions to decrease fatalities.

Keywords: Flood; disaster; Malaysia; rainfall; monsoon

This study investigates the enhancement of PMMA’s dielectric properties through the incorporation of three distinct conductive fillers-carbon black (CB), carbon nanotubes (CNT), and silver nanoparticles (AgNPs), at various weight percentages. The composites were characterized for their real permittivity and dielectric constant across the S, C, and X frequency bands (2–12 GHz) using a Vector Network Analyzer. The results reveal that CB significantly outperformed CNT and AgNPs, achieving a 311% improvement in dielectric constant at 6 GHz with 5.0 wt.% loading. CNT demonstrated moderate enhancements, while AgNPs showed the least improvement, attributed to larger interparticle distances and weaker interfacial polarization. FESEM analysis confirmed the morphological differences between fillers and highlighted the critical role of dispersion and interfacial interactions in determining dielectric performance. This study not only identifies CB as a superior filler for dielectric enhancement but also provides critical insights into the filler-matrix interaction mechanisms. These findings open new avenues for the development of advanced polymer composites tailored for high-performance applications such as energy-efficient capacitors, electromagnetic shielding, and next-generation electronic components.

Keywords: PMMA; Real permittivity; dielectric constant, Maxwell-Wagner-Sillars (MWS) interfacial polarization

The rapid advancement of fuel cell systems, driven by technological progress, has led to increased global adoption. However, in Malaysia, exposure to renewable energy technologies among children remains inadequate, resulting in limited awareness of their importance. This study addresses this gap by leveraging augmented reality (AR) through a mobile application, SmartSelFuel, to enhance students’ interest in fuel cell education. Using the ADDIE instructional design model, the study began with an analysis of children’s understanding and challenges in grasping fuel cell concepts. The SmartSelFuel application was tested on 77 nine-year-old children using a quantitative research approach to evaluate improvements in knowledge acquisition and awareness of renewable energy. Results showed a remarkable 96.2% increase in students’ understanding and knowledge after interacting with the application. Statistical analysis confirmed a significant impact, with a p-value < 0.05. This study introduces SmartSelFuel as an innovative learning model that integrates AR to create an engaging and interactive educational experience. The application not only improved children’s cognitive performance but also significantly increased their interest in renewable energy innovations and heightened awareness of its critical role in sustainable development. These findings underscore the transformative potential of AR-based mobile applications in fostering renewable energy education and inspiring future generations to embrace sustainable practices.

Keywords: Augmented reality; fuel cell; education; smartphone; application

It has been found that there is still a lack of awareness and knowledge about sustainability and circular economy concepts among graduates, potentially putting them at a disadvantage in an increasingly competitive job market. This study aims to investigate students’ levels of knowledge and perceptions of the importance of the circular economy and the extent to which circular economy concepts are integrated into their academic programs. Using a purposive sampling method, an online survey was completed by 195 respondents out of 380 students enrolled in engineering and built environment programs at a local university. The findings revealed that 93.3% of students consider sustainability personally important, 94.4% relate it to their field of study, but only 78.4% feel that sustainability topics are sufficiently addressed in their academic programs, indicating a gap in integrating sustainability into the curriculum. The study also found that students have a better understanding of 3R principles such as Reuse (90%), Recycle (80%), and Reduce (70%), but are less exposed to other circular economy principles like Refurbish (30%) and Remanufacture (30%). Additionally, the majority are unfamiliar with concepts such as Extended Product Lifetime (72.8%), Closing the Loop (73.8%), and Dematerialization (62.1%), but are more familiar with the concept of Regeneration (68.7%). ANOVA analysis showed no significant differences between departments in terms of the importance of sustainability and knowledge of circular economy concepts such as Extended Product Lifetime and Closing the Loop. However, significant differences were found in knowledge of the concepts of Products as Services (p= .012, η² = 0.065) and Regeneration (p=.001, η² = 0.097), with respondents from the Chemical Engineering Department demonstrating higher levels of knowledge compared to those in Mechanical Engineering and Electrical, Electronics & Computer Systems Engineering. The findings of this study can serve as a basis for further research to evaluate the effectiveness of educational interventions and training programs in enhancing knowledge and practices related to circular economy concepts within engineering and built environment academic programs.

Keywords: Sustainability; circular economy; sustainability education; circular economy education; engineering education

A coupled mechanical and thermal analysis of powder during the warm compaction process has been investigated. This paper presents the development of the numerical model to generate a green compact through uniaxial die compaction using the finite element analysis software LS-Dyna. The objective of this simulation is to study the stress and the pressure apply on Stainless-Steel 316L metal powder during compaction. The results show that increasing the compaction force within a certain range can increase the density of the bulk pellets, and that the lubrication conditions need to be improved to further increase the relative density. Numerical simulations are used to obtain the maximum compaction forces for different materials and to provide guidance for improving and optimizing the process parameters in practical production. As a result, the powder deforms without break and show Stainless-Steel 316L is ductile material since it can sustain until 169MPa in Von Mises stress. However, the pressure is increase simultaneously with time which is it can reach until 7.66GPa and the value is higher than tensile strength of Stainless steel 316L. The analysis of particle stress reveals that during the compaction process, stress concentrates occur on the Stainless steel 316L particles. The Stainless steel 316L particles fill the pores in the compacted billet through plastic deformation, leading to stress concentration on the harder Stainless steel 316L particles.

Keywords: Stainless-Steel 316L; powder press; simulation; LS-Dyna; Von Mises stress

In the 21st-century digital economy, the demand for skilled Science, Technology, Engineering and Mathematics (STEM) professionals, including engineering talent, is at an all-time high. However, Malaysian STEM education has witnessed a significant decline in enrolment, reflecting a global trend of waning interest in STEM subjects among students since their early schooling. One of the key determinants impacting the enrolment of upper-secondary students in STEM is mathematics achievement, particularly in Additional Mathematics, which plays a vital role in preparing students for tertiary mathematically oriented engineering programs. Alarming statistics from the Pahang State Education Department reveal a sharp drop in enrolment for Additional Mathematics. This study’s primary objective is to identify the significant determinants impacting the enrolment of urban upper-secondary students in Additional Mathematics in the Kuantan District, especially among the first cohort to experience the revised Kurikulum Standard Sekolah Menengah (KSSM) since 2017. Utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) data science methodology, empirical findings underscore the importance of educational discipline, gender, PT3 mathematics achievements, mathematics self-efficacy, peer influence, and teacher influence as key determinants shaping enrolment decisions among urban secondary students in Additional Mathematics. These insights offered valuable guidance for policymakers, highlighting the urgency of STEM education initiatives. Furthermore, they could emphasize the need to empower teachers and counselors in guiding students toward STEM careers in the digital economy and promote gender equality in STEM fields through curriculum enhancements, adjusted teacher expectations, improved educational tracking, and supportive peer interactions.

Keywords: STEM professionals; enrollment; additional mathematics; tertiary engineering; educational policy

Concrete plays an important role in the field of construction and cement is main component of it. In this paper the experimental study of partial replacement of cement with dolomite and fly ash is done. The research presented here explores the use of dolomite and fly ash as cement substitutes to improve sustainable self-compacting concrete (SCC). Dolomite is an anhydrous material and is composed of calcium magnesium carbonate. Experimental phases involve fresh concrete properties, including workability, and mechanical properties like compressive and splitting tensile strengths. In design mixes cement is replaced with dolomite and fly ash in varying percentages. The replacement percentages of cement by dolomite powder and fly ash is 15%, 20%, 25%,30%,35%,40%,45% and 50%. The concrete achieved the required strength levels in early time indicating good performance. Dolomite emerges as a key contributor to early and enhanced strength in SCC, promoting sustainability in construction. With the addition of dolomite powder microstructure of concrete filled up and its internal pores refined due to which it contributes to increase its compressive strength. Furthermore, substituting cement with dolomite fostered the creation of CSH gel. In 7 days, 14 days, and 28 days for concrete, the test specimens were cured and tested for compressive strength and split tensile strength.

Keywords: Self-compacting concrete; fly ash; dolomite; mechanical properties; microstructural analysis

In recent decade, due to the rapid development of nanotechnology and nanomaterials, carbon quantum dot (CQD) is recognized as a new rising zero-dimensional carbon-based nanomaterial as green substitute of heavy-metal-based nanomaterials with a particle size of less than 10 nm, strong photoluminescence (PL), and similar electrochemical properties as semiconductors. CQD has attracted widespread attention from scientists and researchers due to its excellent and tuneable PL characteristic. This review presents an overview of synthesis approaches, and parameters considered during CQD synthesis and its applications. Photoluminescent CQD can be synthesized through two main approaches, which are top-down (laser ablation, electrochemical etching, ultrasonic treatment and arc discharge) and bottom-up (hydrothermal/solvothermal and microwave-assisted pyrolysis) approaches. The PL characteristic of CQD, which are excitation and emission wavelengths, could be tuned through manipulation of the particle size of CQD, reaction temperature, reaction time, and use of doping agents and solvent during the synthesis of CQD. The tuneable PL property of CQD has widened their applications in the fields of biosensors, biomedical, energy, food engineering, and photosynthesis due to the factors of safety, sustainability, and non-toxicity of photoluminescent CQD. It is believed that the photoluminescent CQD could be further applied into the biomedical, electrochemical applications and lightdependent processes.

Keywords: Applications; carbon quantum dot; parameters; photoluminescence; synthesis approaches

Work fatigue in heavy equipment operators can reduce productivity and increase the risk of work accidents. This study aims to design an Internet of Things (IoT)-based work fatigue monitoring system with an ergonomic approach to monitor the physical condition of operators in real-time in CV. Wana Indoraya Lumajang. This system measures working pulse, oxygen saturation, temperature, humidity, and calorie expenditure using a smartwatch whose data is processed through a cloud server. The research method involved the physiological measurement of the operator over six working days, with two daily measurement sessions. The results showed that the average operator’s pulse rate was 149.5 pulses/minute and calorie expenditure reached 598 kcal/min, indicating a heavy workload. In addition, a decrease in oxygen saturation as well as a rise in temperature and a decrease in air humidity in the workspace worsen fatigue conditions. 149IoT monitoring systems are effective in monitoring operator fatigue conditions in real-time, and can help supervisors in taking preventive measures to reduce the risk of accidents due to work fatigue.

Keywords: Work fatigue; internet of things; ergonomics; heavy equipment operator; pulse

Photopolymerization-based additive manufacturing has become a key technology due to its advantages, such as low energy consumption and rapid processing. However, optimizing the mechanical properties of composite materials produced through this process remains a challenge. The impact of filler geometry on the mechanical performance of photopolymerized composites has not been fully explored. Shrinkage stresses during polymerization, especially in acrylate-based materials, can lead to brittleness and cracking, limiting their structural integrity and industrial application. This study aims to investigate the influence of different filler shapes and densities on the tensile strength, strain, and stress distribution of composite materials fabricated through photopolymerization. A Finite Element Representative Volume Element (FE-RVE) approach was employed, integrating ABAQUS scripting with Random Sequential Adsorption (RSA) for filler modelling. Non-linear dynamic tensile simulations were conducted to analyse the mechanical behaviour of composites with three filler shapes: sphere, prism, and polyhedron. Experimental validation was performed using ASTM D-638 tensile tests to ensure the accuracy of the simulations. The study anticipates that filler geometry significantly influences the mechanical performance of composites. Polyhedron-shaped fillers are expected to exhibit the highest tensile stress due to their superior stress distribution capabilities, while prism fillers may demonstrate enhanced flexibility. These findings aim to provide valuable insights into designing optimized composites for industrial applications, such as automotive and high-performance engineering.

Keywords: Photopolymerization; FE-RVE; RSA-RVE; ABAQUS; additive manufacturing

Artificial intelligence (AI) has long been applied in agriculture and has become especially prevalent in recent years. AI especially deep learning technique have progressed to have much stronger learning ability to learn more useful features to handle even more complicated task in the field of precision agriculture. Challenges in agriculture such as disease, infestation, inadequate irrigation and soil treatment, and poor crop management have brought about crop losses and adverse effects on the environment. Not to mention, the ever-increasing demand of agricultural product due to the increasing global population and the limited amount of arable land. To be overcome, those challenges need innovative approaches, ones that could benefit from AI’s flexibility, accuracy, cost-effectiveness, and generally superior efficiency. AI technology whose aim is to mimic the ability of humans to solve problems especially in decision making enables agricultural activities to be done more efficiently while reducing human interference. The use of AI in agriculture has evolved from the application of fuzzy logic, then into machine learning and deep learning. Some deep learning methods that have been applied in precision agriculture are convolutional neural network, transformer learning, meta deep learning, and lightweight deep learning. This paper presents a review of 100 research papers addressing the application of AI in overcoming challenges in agriculture from the year 2000 to 2023. The paper selection for this review paper is done by using the SALSA method to effectively identify relevant research papers. In the near future, AI will be ubiquitous in the global agricultural sector and will bring about new technologies, new knowledge, and endless possibilities.

Keywords: Fuzzy logic; artificial neural network; deep learning

Hydrogen is an alternative fuel that offers a more sustainable solution with less environmental impact. Hydrogen combustion in internal combustion engines is currently considered as an option because the operation of internal combustion engines is more affordable, simple, and durable. This study aims to identify injection strategies for optimal efficiency and evaluate the performance of a spark-ignition engine at different engine speeds. Computational Fluid Dynamics (CFD) simulations were used to examine the effects of direct injection of hydrogen in a spark ignition hydrogen engine. The study describes the properties of hydrogen, analyzes combustion strategies in spark-ignition engines, and sets objectives to understand the causes of abnormal combustion. The research approach involves simulation methods using Converge CFD software based on a direct hydrogen injection engine parameter. The study focuses on fuel injection pressure and engine speed as manipulated variables to achieve optimal engine combustion. The results are analyzed along with previous studies to validate the model. The findings indicate that an injection pressure of 10 MPa and an engine speed of 1200 RPM achieve optimal hydrogen combustion for the four-stroke engine model. These findings provide a deep understanding of the development and advancements in using this strategy.

Keywords: Hydrogen combustion, Direct injection, Spark-ignition engine, Engine speed, Injection pressure

Fatigue is recognized as a threat for drivers, potentially resulting in road collisions. Designing technical systems can enhance safety by alerting drivers to prevent drowsiness. This study seeks to identify the criteria for the vibrator system from the driver’s viewpoint. It has four main phases that integrate three approaches; systematic reviews, survey questionnaires, and experimental studies. A systematic review was conducted to compile previous research on vibrotactile aspects, while a survey was employed to gather drivers’ perceptions regarding the appropriateness of the vibrator system from their perspectives. A set of experiments utilized a car simulator to determine the optimal location and threshold for drowsiness detection. The device system was designed with an Arduino Uno and incorporates vibrators, ultrasonic sensors, and driver’s seat backrests to deliver vibrations as a warning to drivers who doze off while operating a vehicle. Postural assessment and subjective metrics were employed to validate the onset of drowsiness. This study revealed head nodding as an indicator of drowsiness. The questionnaire results indicated that a majority of participants (87.8%) perceived the product positioning the vibrator on the lower back and thighs as more effective in delivering vibrations to the driver. In reaction to the driving experiment, most participants nodded their heads after driving for over 30 minutes at a challenging period, specifically at 2:00 p.m. Upon detection of head movement by the ultrasonic sensor positioned 45 cm from the driver, the vibrator will be engaged to notify the driver. This study is expected to diminish the incidence of accidents attributable to fatigued drivers. This research corresponds with the third and eleventh Sustainable Development Goals.

Keywords: Microsleep; drowsy; nodding; vibration; driver seat