Construction Labor Productivity (CLP) is a critical factor in the construction industry that can significantly influence the success of a project. The lack of comprehensive knowledge and proficiency in CLP and its substantial impact on project outcomes is a significant concern. CLP is a highly effective concept that can significantly improve the overall efficiency of construction projects. While it has received considerable academic attention, it is still relatively underutilized in practice. This academic analysis aims to identify trends within the CLP as revealed by a comprehensive review of existing academic research. A bibliometric analysis, complemented by a descriptive quantitative statistical methodology, was utilized to evaluate the performance metrics and delineate the thematic landscape about the subject matter of CLP. Employing distinct keywords pertinent to the CLP phenomenon and applying specific criteria for metadata exploration facilitated a comprehensive search within the Scopus and Web of Science databases. The PRISMA flowchart was employed as a systematic approach for the identification, screening, and eligibility evaluation of metadata to be incorporated into this study. The study highlights growing CLP research, led by the US and the University of Alberta. Key trends include “improvement” and “construction equipment,” with future focus on “machine learning” and “artificial intelligence.” Despite their potential, data challenges limit their use. More research is needed in developing countries to enhance construction labor productivity.

Keywords : Productivity; construction labor; bibliometric analysis

To produce high strength or rich cement concrete having low water to cement ratio with adequate workability is the biggest challenge for the construction industry. To achieve the necessary workability, the world is now using costly chemical admixtures. Research should be carried out to explore materials having potential to be utilized as costeffective chemical admixtures in concrete. The primary goal of this research is to investigate the combined effect of Cordia Gel (CG) and Waste Engine Oil (WEO) as chemical admixtures on fresh and hardened properties of concrete. Fresh properties of concrete were examined in terms of workability and hardened properties were investigated by compressive strength test and Ultrasonic Pulse Velocity (UPV) test on cubical specimen of dimensions 100mm x 100mm x 100mm after 7, 28 and 90 days of curing in water. Four different percentages of WEO (0.5%, 1%, 1.5% and 2%) were used and percentage of CG kept constant as 0.5% with respect to weight of cement and results were compared with the control mix. Results revealed that workability of fresh concrete increased with increasing amount of CG and WEO. However, a decreasing trend was observed for compressive strength and UPV of hardened concrete when higher values of admixtures were added. The usage of CG and WEO as chemical admixtures in concrete can be a sustainable and cost-effective way to achieve the desired results.

Keywords: Cordia gel; waste engine oil; workability; compressive strength; ultrasonic pulse velocity

In this study, the development of a solar-powered autonomous vehicle prototype with an object detection and avoidance system was implemented and achieved using Raspberry Pi. The advancements in science and technology research have given rise to the robust adoption of smart means of transportation, from steam engines to energyefficient means such as solar, electric, and hybrid-powered vehicles to ease transportation of people, goods, and services with increased human comfortability. Autonomous vehicles (AVs)offer a degree of self-control in driving in which a normal car requires a driver to execute such tasks e.g., braking, acceleration, and steering. An autonomous vehicle, requires sensors, controllers, algorithms, actuators, computers, and advanced software embedded in various locations on the vehicle to perform effectively. The study attempted to proffer solutions to the menace of human errors in decision-making while driving through the use of advances in scientific technology that have given rise to modern approaches to problem-solving. In Nigeria, almost 50% of road accidents were a result of poor decisions leading to the loss of lives and properties. The vehicle uses ultrasonic sensors and a USB webcam to detect and avoid obstacles on its path with the aid of a Raspberry Pie program that effectively executes decision-making changes to manoeuvre the vehicle away from objects on a free path. The study observed that as motor frequency is increased the speed of the AV increases and thus covers distances faster as compared to when the frequency is reduced. However, the increase in frequency also consumes energy faster. Charging rates were compared between the grid and solar photovoltaic, the grid system recorded faster charging rates when the vehicle was stationary while the solar photovoltaic charged the vehicle at stationary and in motion.

Keywords: Autonomous vehicle; sensors; solar vehicles; object detection; Raspberry Pie; smart cars

The national socio-economic development programme prioritises rural development, and the state of Sarawak requires many rural roads to connect existing villages to the main roads. This programme can be achieved by upgrading existing non-standard access roads or constructing new access roads. The current challenges and issues related to the sustainable development of low-volume roads (LVRs) in the Malaysian state of Sarawak were investigated in this study. The key goals of the study were to understand the challenges of sustainable development in Low Volume Roads (LVRs) in Sarawak using expert interviews as well as surveys on experienced engineers. It aimed at clarifying what LVRs are, highlighting challenges to do with designing and planning them, and also discussing pavement design aspects. The data for the research was collected through interviews with experts in state Public Work Department (PWD) and consultants with more than 15 years’ experience in road planning and construction. An online questionnaire was distributed and it targeted government agencies, consultants, contractors, with 52 respondents out of 200 possible. This helped to identify important problems associated with LVR development; it stressed that a proper knowledge of LVR design, planning difficulties and those specific concerning pavement designs is needed among professionals within Sarawak road building industry. Based on the findings, immediate need for actions was required to be taken by road agencies to investigate the development and appropriate design of LVRs also to record and gather historical data on current LVRs for further improvement.

Keywords: Low-volume roads; rural roads; sustainability; sustainable development

Tissue engineering (TE) is a modern approach to improve or restore tissues that has been diseased or damaged by combining the factors in growth signaling and appropriate cells to form compatible biomaterial scaffold. Bone repair has been a major global health challenge in recent decades. Bone transplantation is widely used as an effective clinical treatment for this purpose. However, there are several serious issues with transplantation, including a shortage of autologous bone, immune rejection, the risk of virus transmission with allogeneic bone, and postoperative complications. In recent years, scaffolds for bone tissue engineering have emerged as a promising alternative for bone repair. These scaffolds have porous structures that mimic the extracellular matrix, which can enhance the migration, proliferation, and differentiation of osteoblasts. This process accelerates the repair of bone defects.The usage of bioactive materials has become important tool in tissue engineering and regenerative medicine application as they are to mimic tissues mechanically, chemically, and physically. Polymeric scaffold provides numerous advantageous for tissue engineering since the physicochemical properties such as porosity, pore size, solubility and biocompatibility can be controlled. Therefore, research works were carried out to explore the potential of various materials in producing bone scaffolds in tissue engineering technology. As for both newcomers and experts, this review paper will help them to find information on various types of biomaterials in imparting or enhancing their biological properties such as biocompatibility, bacterial inhibition, tissue regeneration and cell growth, bio inertness, bioactive and resorbability for bone scaffold tissue engineering application.

Keywords: Tissue engineering; biomaterials; bioprinting; bioactivity; biocompatibility; antibiotic infusion

With more functionalities being integrated into a microchip today, higher processing power is drawn. As a result of this, clock and logic power consumption has turned out to be a critical issue to be coped with by chip designers. In this paper, we present various power-saving approaches employed in complementary metal oxide semiconductor (CMOS) circuit designs. The approaches involve restructuring the logic circuits, performing clock gating, and selecting the appropriate circuits for counters and frequency divisions. In order to show their efficacies in power optimization, the approaches were applied to a phase-locked loop (PLL), clock divider (CD), full adder (FA), counter, arithmetic logic unit (ALU), and microprocessor without interlocked pipelined stages (MIPS) circuits and validated using Intel Quartus Prime Lite and Mentor Graphics Modelsim. The following conclusions can be drawn from the results: Firstly, the efficacy of minimizing power dissipation using logic restructuring is found to be in direct proportion with the rate of the switching activity (SA); secondly, a maximum of 3.5% of thermal power dissipation can be saved using clock gating; thirdly, gray counters give the lowest power consumption; and, finally, the thermal power estimation for the phase-locked loop (PLL) is relatively higher than that for the clock divider (CD) when both of them are implemented for dividing frequencies.

Keywords: Power consumption; logic restructuring; clock gating; counter; frequency division

Robust and effective control of brushless dc (BLDC) motors is paramount in modern-day motion control. The BLDC motor is known for its high speed, high torque, small size, low noise, and equally low maintenance requirements compared to the brushed DC motor. Nowadays, it can be found in the areas of robotics, aerospace, military, and industrial machines, among others. In this paper, two inverter topologies, the threephase six-switch driver circuit (TPSSDC) and the three-phase four-switch driver circuit (TPFSDC), are used to drive and control the speed of the BLDC motor. For the control technique, however, a fitting neural network from the deep learning (DL) toolbox is employed to train and improve the speed performance of the motor. Both TPSSDC and TPFSDC are simulated and tested in MATLAB Simulink, and the resultant output is analyzed graphically and analytically. Graphical observation shows that the TPSSDC control approach is superior in terms of reference tracking and has less ripple, and better rise and settling times when compared to the TPFSDC control approach, however, the TPFDC is considered for its low cost and simple circuitry. Numerically, the TPSSDC also outperforms at 1000 rpm with a 1.685 ms rise time and a 1.420 ms settling time compared to the TPFSDC, which rises at 6.526 ms and settles at 5.237 ms. At 3000 rpm motor speed, the TPSSDC is better, having a rise time of 5.815 ms and settling time of 4.048 ms, when compared to the TPFSDC, which rises at 11.277 ms and settles at 10.067 ms.

Keywords: BLDC motor; speed control; inverter topology; deep learning; neural networks

With population growth and rapid urbanisation leading to excessive waste generation in the construction sector and the scarcity of natural resources, such as natural fine aggregates, the demand for recycled alternatives has increased. In exploring the potential of recycled materials for construction materials, the present study investigated the performance of recycled concrete aggregate (RCA) and expanded perlite in mortar as a partial replacement for fine aggregates. Different percentages of RCA and expanded perlite were used. A consistent percentage of perlite was used: 0%, 10%, 15%, 20%, 25%, 30% and 35%. The RCA and expanded perlite were then mixed with other materials such as cement, water and fine aggregate. Flowability, compressive strength and flexural strength tests were carried out. It was found that a 90% replacement of RCA for each increasing percentage of perlite in the mortar mix resulted in a significant reduction in flow diameter. The compressive and flexural strength of the mortar increased with age. However, the flexural strength of the control mortar, which contained neither RCA nor perlite, consistently exceeded that of the mortar with these additives. The results provide valuable insights for the production of new materials in the construction industry, for waste management and for lightweight yet durable construction solutions.

Keywords : Recycled concrete aggregate; expand perlite; flexural strength; flowability; compressive strength

Empty fruit bunch (EFB) is a promising materials to produce activated carbon for electrode materials applications in an energy storage device due to its low cost, high availability and porosity. EFB will require further processing to convert it into activated carbon to enhance its electrochemical performance. In this research, a two-step activation was utilized, in which EFB undergone pyrolysis at 500 °C before being activated via chemical and physical activation methods under various conditions to produce activated carbon. The samples were then characterized using weight loss analysis, Field Emission Scanning Electron Microscopy with Energy Dispersive Xray Spectroscopy (FESEM-EDX) and Raman Spectroscopy to evaluate their physical characteristics. Cyclic voltammetry (CV), galvanostatic charge discharge (GCD) and electrochemical impedance spectroscopy (EIS) were performed to evaluate their electrochemical performance. The specific capacitance measured from CV analysis shows better performance for samples from physical activation which were in the range of 24 to 140 F/g compared to samples from chemical activation that resulted in only 36 to 90 F/g. These results suggested that physical activation has yielded better electrochemical performance of activated carbon which was influenced by the higher activation temperature in comparison with that of the chemical activation that was performed at lower activation temperature.

Keywords: Empty fruit bunch; activated carbon; chemical activation; physical activation; supercapacitor

A Point-of-Sale (POS) is a computerized system of hardware and software utilized by businesses to complete sales transactions. In conventional POS setups, cashiers manually scan individual product barcodes, before processing the totals. This manual procedure is laborious and often leads to long queues and waiting times, especially during peak hours, ultimately affecting customer experience and retention. This work seeks to automate the product scanning procedure with a computer vision approach, thereby expediting the sales process. An efficient YOLOv4 object detection model was trained on a custom dataset of common products found in Malaysian retail stores. 550 images were initially acquired and split 80:20 into training and validation groups; further augmentation tripled the size of the training group to 1,320 images. Training was conducted for 10,000 epochs, at 0.0013 learning rate. During training, the model achieved 99.19% mAP, 87.42% average IoU, and a 0.40 average loss. Subsequently, the model was deployed on a low-power single-board computer running a transaction notification program. To evaluate its performance, 10 instances of shopping carts with random product combinations were processed using the system. The system autonomously identified and quantified all products through its video feed, generating itemized bills in real-time. Fixed with a 0.9 confidence threshold, the system yielded a 98% average accuracy across all object classes. On average, transactions, from product detection to delivering the itemized bill to the system administrator, were processed in just 14 seconds. This POS system holds potential for integration with unmanned stores, offering a seamless shopping experience.

Keywords: Point-of-Sale; YOLO; computer vision; machine learning; object detection

The article “Empowering Digital Entrepreneurship in Technical and Vocational Education and Training (TVET) Education” embarks on a detailed exploration of the integration of digital entrepreneurship within Technical and Vocational Education and Training (TVET). Utilizing advanced searching techniques across Scopus, WoS, ERIC, and Google Scholar databases, the study synthesizes findings from 34 articles, focusing on four main themes: the overview of TVET education, the impact of digital entrepreneurship on TVET, the issue and challenge in integrating digital entrepreneurship into TVET, and the potential pathways for such integration. This study emphasizes how important it is for TVET institutions to include digital entrepreneurship skills in order to prepare a workforce that can successfully navigate the digital economy. It discusses on the precise balance that needs to be achieved between entrepreneurial digital skills and technical vocational training, highlighting how this synergy is essential to developing creativity, flexibility, and competitiveness in the modern workforce. The study also discusses the difficulties in developing curricula, allocating resources, and the importance of industry-academic collaboration, offering thorough solutions for resolving these issues. This paper significantly advances educational policy and practice by providing an in-depth understanding of how digital entrepreneurship can transform Technical and Vocational Education (TVET) and directing industry and educational stakeholders toward the development of a more dynamic, future-focused vocational training ecosystem.

Keywords: Education; digital entrepreneurship; Technical and Vocational Education and Training (TVET)

Emerging contaminants are currently a serious issue primarily because conventional wastewater treatment plants are unable to eliminate them. Environmental pollution caused by various emerging pollutants (particularly pharmaceutical active compounds) in wastewater poses a significant threat to public health and ecological balance. In 21st century, bioremediation is regarded as the most environmental friendly and cost-effective treatment technology. In this study, we investigated the removal efficiency of 19 popular pharmaceutical active compounds (PhACs) from municipal wastewater using Malaysian Ganoderma lucidum fungal strain (G. lucidum). The initial and final concentrations of each compound were determined using liquid chromatography time of flight mass spectrometry (LC-TOF/MS), and the percentage of removal was calculated. In this study, experimental results revealed diverse removal efficiencies for the investigated PhACs in municipal wastewater. The PhACs Azithromycin, doxycycline, clindamycin, ciprofloxacin, sulfamethoxazole, loratadine, and citalopram, showed remarkable removal rates of 90% and above in municipal wastewater, indicating their potential for effective treatment. Conversely, trimethoprim, ketoprofen, diclofenac, venlafaxine, dexamethasone, atenolol, propranolol, losartan, valsartan, metoprolol, fluconazole, and carbamazepine, demonstrated varying removal efficiencies, suggesting the need for further optimization in wastewater treatment processes for these compounds. This study highlights the importance of understanding the biodegradation of different PhACs in municipal wastewater to develop efficient and targeted bioremediation treatment strategies using local fungal strain of G. lucidum. Overall, this study provides promising suggestions for the bioremediation of pharmaceuticals from wastewater.

Keywords: Municipal wastewater; emerging pollutants; pharmaceuticals; bioremediation; Ganoderma lucidum

Nowadays, the construction sector is developing rapidly, and there is an increase in demand for innovative concrete technology. This is because concrete has many advantages over other building materials. Improving the quality of concrete can be done by providing replacement materials or adding several replacement materials, and one of the alternative materials that can be used is styrofoam. The purpose of this research is to evaluate the effect of styrofoam as high-quality concrete and compare the compressive strength between control concrete by using 1%, 2%, and 3% ratios of styrofoam. The experimental method is applied in this research, experiment was conducted and tested in accordance with SNI 03-6468-2000. The results of the study show that the compressive strength of styrofoam mixed concrete using ratios of 1%, 2%, and 3% obtained 23,30 MPa, 17,34 MPa, and 11,64 MPa. The results showed that Styrofoam replacement was used for K.350 high-strength concrete. It is not recommended for building or bridge construction because the compressive strength test results produced are meagre compared to standard concrete without a mixture of styrofoam. After all, the mass of concrete mixed with styrofoam is lighter than normal concrete so that it can be used for construction with low loads.

Keywords: Concrete; high quality; styrofoam

Quay cranes (QCs) are critical equipment in Container Terminals and their performance determines the port operation efficiency in meeting operational Key Performance Indicators (KPIs). Considering 30-year lifespan of QCs and deteriorating reliability of the electrical control system, planning for timely retrofit of the QCs is critical. The paper aims to present a case study on how the performance of a batch of QCs, having more than 50% remaining lifespan, were analyzed and concluded to be retrofitted to address their deteriorating performance, high maintenance cost and obsolescence. The study methodology is based on quantitative data and employed a prospective longitudinal panel research design over sixteen years. eleven years of pre-retrofit and five years of post-retrofit operations, maintenance and financial data were collected. Convenient sampling technique was selected in this study as the QCs identified as samples were having reliability issues. The Correlation Analysis indicates strong positive correlation of more than 90% between Mean Time Between Failure, Mean Move Between Failure and Reliability KPIs. These KPIs have moderate positive correlations of about 50% with Availability KPI. These 4 KPIs have strong negative correlation of between -50% and -85% with Mean Time to Repair, Maintenance and Breakdown Repair Cost indicating performance degradation but increased maintenance and repair costs as shown by Trend Analysis. The 11-year preretrofit data has identified parameters to determine the QC retrofit prediction. The KPIs, obsolescence status, maintenance and breakdown repair cost can be used as the inputs to the future QC Retrofit Prediction Model development.

Keywords: Quay Crane; rtrofit; maintenance; obsolescence; container terminal

Zirconia-based materials have emerged as promising resources for dental restoration applications owing to their excellent strength and aesthetic appearance. In clinical practices, surface treatment on zirconia is essential to ensure enhanced dental bonding. In this study, a novel method was used to produce zirconia block, and the influence of surface treatment on zirconia-dentine microstructure bonding interface was investigated for different particle sizes of zirconia powder. The particle sizes used in this study were 90 and 30 nm on the basis of manufacturer claims. A zirconia block of both particle sizes underwent surface treatment airborne-particle abrasion (50 μm, 0.4 MPa). Dentine specimens were prepared from extracted premolars stored in 0.1% tymol solution before being randomly cemented with the zirconia block sample by using self-adhesive resin cement (RelyX U2000 Clicker, 3M) and then light polymerised. The results after surface treatment showed higher surface roughness values for 90 and 30 nm at 0.17 and 0.18 μm, respectively, than those of the sample without surface treatment at 0.05 and 0.06 μm, respectively, showing no significant difference between particle sizes. Surface treatment improved the bonding of zirconia because the surface roughness allowed for enhanced interlocking of the cement onto the zirconia surface. However, the unbonded dentine and cement was due to the existence of a smear layer on the dentine surface that prevented the selfadhesive resin cement to work well with the dentine surface. Thus, dentine primer must be used to chemically remove the layer and allow for proper bonding between the resin cement and dentine surface.

Keywords: Zirconia; surface treatment; bonding; dentine; dental restoration

Solar cooker with different collector like evacuated tubes collector, parabolic trough collector, flat plate collector, and Scheffler reflector collector etc are generally used for the cooking food with SHSMs or PCMs. Present research article, Scheffler reflector with combined heat storage material (one SHSM and one PCM) for late-evening cooking has been experimentally investigated. One material is placed within the inner pot of a solar cooker, while another material is placed outer pot of the solar cooker. Six combinations are formed from various SHSMs (sand, pebbles, and iron pieces) and PCM (acetamide). During the daytime, the solar cooker absorbed and stored heat from the sun, which was transferred to the cooking pot through the heat storage units. The heat required for evening cooking (Rice) has been transferred by the thermal storage system which is kept inside an insulator box. After the experiment, it was observed that food was successfully cooked in pairs of sand-acetamide, acetamide-sand, and acetamide-pebbles and partially cooked in pairs of pebbles-acetamide, iron pieces-acetamide, and acetamide-iron pieces. The water activity test is to be conducted to check the cooking quality of food, and as per the result received from the test, the range of cooking and partially cooking is differentiated between 0.928 and 0.936 and 0.948 and 0.955, respectively. The cooked food’s temperature was determined to be between 60 and 63 oC at 20:00 h. The system’s total cost and payback duration were calculated for the economic analysis resulting in 50750 INR and 9.70 years, respectively.

Keywords: Scheffler reflector; solar energy; solar cooking; combined heat storage unit; thermal performance; SHSMs; PCM

Businesses have benefited tremendously from technological advancements, particularly in production, outsourcing, logistics, and marketing. Although large firms and Multinational Companies (MNCs) are in a better position concerning the use and adoption of technologies, small and medium-sized enterprises (SMEs) have both the agility and potential to leverage their resources, market conditions, globalization’s opportunities, and networks to improve the way they use technology and ultimately enhance their competitiveness. As seen in the literature, most research that has addressed the topic of technology adoption among SMEs has emphasized specific issues such as digitalization, information technology, cloud computing, cybersecurity, and Industry 4.0. This paper has gone beyond such a limited view to touch upon different technological aspects that are important to the functioning and/or survival of SMEs and the conditions surrounding the implementation and use of technologies. Specifically, this study examines the realities of SMEs’ technology adoption and draws lessons for policymakers in developing countries.

Keywords: Technology; SMEs; adoption; use; business; government; support; developing countries

Planned Preventive Maintenance (PPM) is an essential component under facilities management (FM) carried out to ensure the functionality, effectiveness, reliability and safety of the asset and facilities. Poor service quality, lack of monitoring and performance assessment, low level customer satisfaction are among issues arises and has gained a lot of attention, especially among interested parties. In Universiti Teknologi Mara (UiTM) campuses context, FM normally outsourced to third parties namely concessionaires under Private Finance Initiative (PFI) campuses and contractors for conventional campuses. The main objective of this preliminary study was to investigate current practices in terms of service quality aspect of PPM works delivered by concessionaires and contractors in UiTM. A questionnaire was distributed to 27 respondents consist of 12 engineers and 15 assistant engineers from Office of Facilities Management UiTM and analysed using descriptive analysis. Based on the results, current practice to measure PPM work performance is by the number of works completed. Apart from that, there is no defined standard method available to be used as performance measurement in the aspect of service quality of PPM works delivered by concessionaires and contractors in UiTM. In addition, all the respondents agreed that there is indeed a necessity to develop a standard performance measurement in the aspect of service quality of PPM works delivered by concessionaires and contractors. The impact of this finding is to the Office of Facilities Management UiTM, in which they can focus and start to develop standard performance measurement in the aspect of service quality of PPM works delivered by concessionaires and contractors, so the services provided commensurate with the payment made and satisfy customer needs.

Keywords: Facilities management; planned preventive maintenance; service quality

The process of retrieving significant documents based on the search key from a corpus has been a vital research problem in the information retrieval field. This paper proposes an efficient way to retrieve documents related to different personalities extracted from Wikipedia. The proposed method utilizes the Locality Sensitive Hashing Nearest Neighbor algorithm combined with Weighted Jaccard Distance to measure document similarity with enhanced precision. This document retrieval system demonstrates competitive performance compared to existing methods in the Personality Identification domain. The introduction of a document centroid normalization technique significantly improves the effectiveness of information retrieval by enabling better discrimination between documents. The personality document search results were compared for different distance measures using performance metrics like Normalized Discounted Cumulative Gain and Mean Average Precision. The results presented in this paper show that the TF-IDF scheme with Locality Sensitive Hashing Nearest Neighbor Algorithm using the Weighted Jaccard Distance can yield superior retrieval efficiency when contrasted with alternative approaches found in the existing literature.

Keywords: Document Retrieval; locality sensitive hashing nearest neighbor algorithm; weighted jaccard distance; term frequency – inverse document frequency

This work investigates the effects of multi-layered metamaterial design for absorption application at satellite frequency. This is because, the adopted Ka-band frequency is very useful for current technology which can be used in highresolution, close-range targeting radars, military aircraft, space telescopes, commercial, and wireless point-point microwave communication systems. Hence, this work focused on producing a compact design by adopting the optimisation method. Four square-shaped and two circular-shaped metamaterial rings were designed on 0.25 mm substrate material. Furthermore, the properties of the proposed metamaterial were discovered by adopting Computer Simulation Technology. This analytical simulation was performed for a frequency range between 27 and 40 GHz. On the other hand, several design analyses were investigated to gain an optimal metamaterial design structure for the proposed applications. For instance, unit cell selection analysis, reflection coefficient and absorbance analysis of the multi-layer metamaterial. Moreover, the proposed unit cell metamaterial manifests double resonance frequencies for reflection and transmission coefficients approximately at 27.31 GHz, 33.40 GHz and 30.56 GHz, 38.23GHz, respectively. The increment of layers on the proposed unit cell structure revealed unique responses. For example, the double multilayer metamaterial manifests similar dual resonance frequencies as the unit cell design but gains excellent magnitude values of more than -10. Moreover, the absorbance of the three distinct layer metamaterials, likely double, triple and quadruple layers were analysed as well in this work. Overall, the proposed compact metamaterial absorber exhibits unique behaviours for Ka-band satellite frequency applications.

Keywords: Ka-ban; metamaterial absorber; multi-layer; satellite frequency

This paper presents a dual circular polarized C-band patch antenna for a small satellite communication system The antenna consists of two different annular patch structure with three split ring resonators. The antenna is designed considering space environment and the smallest form of satellite structure. The antenna is fabricated space qualified substrate material Rogers 5880 with overall dimension of 85.22× 48.59 × 1.575 mm3. The antenna achieves circular polarization at 5.1 GHz and 5.2 GHz frequency for port 2 and port 1, respectively. The split ring resonator structures contribute to enhance antenna gain and axial beamwidth. Realized gain of 7.29 dB and 7.33 dB are achieved at 5.1 GHz and 5.2 GHz operating frequency with 3dB axial beamwidth of 170 ̊ and 153 ̊ , respectively. Antenna size and performance show that the antenna can be a potential candidate for smooth operation of small satellite communication system.

Keywords: Circular polarization; C-band; dual CP; small satellite; high gain

Gait analysis is a vital field in biomechanics, focusing on studying human walking patterns and movement. Traditional methods relied on visual observation, lacking accuracy and objectivity. Instrumented gait analysis improved measurements using specialized equipment like motion capture systems and wearable sensors, but had limitations due to cost, and markers or sensors interfering with natural movement. The field underwent a significant transformation with the advent of markerless pose estimation-based gait analysis, which harnessed computer vision methodologies to monitor human movement without the requirement for specialized equipment, delivering a cost-effective and easily accessible analysis in real-world environments. However, it still faces challenges, including limitations in the sagittal plane and reliance on computationally demanding models like OpenPose. This study introduced a novel frontal plane gait analysis approach using the lightweight MediaPipe Pose model and a single camera setup. The objective is to evaluate the feasibility, and accuracy of MediaPipe Pose by comparing it to the established 3D Vicon motion capture system. The proposed approach tracked body keypoints during gait, detected gait events based on ankle depth changes and vertical difference between left and right ankles, and calculated gait parameters. The findings demonstrated that MediaPipe Pose-based gait analysis showed promise for accurately analyzing gait parameters in the frontal plane with low mean absolute error (0.00–0.30). Combining this method with satellite technology enhances e-health by facilitating teleconsultations, remote diagnostics, and extending healthcare services to disaster-stricken or remote areas.

Keywords: Markerless pose estimation; gait analysis; frontal plane; MediaPipe Pose

Polyamide is one of the materials in 3D printing that can produce valuable products to meet the needs of the industry. Previous studies have proven that the layer thickness of the 3D printed material and the increase in temperature affect the mechanical and physical properties. However, only a few studies involve polyamide material as a test material, especially in analyzing the influence of the layer thickness of the printed material and the increase in temperature on the mechanical and physical properties of polyamide. Therefore, the bending properties of polyamide with different layer thicknesses at 0.1 mm, 0.2 mm and 0.3 mm and the tensile properties of the material at different temperatures at room temperature, 75˚C and 110˚C will be studied. This study will involve polyamide (PA) materials printed at three different layer heights using the Fused Deposition Modelling (FDM) process. Bending and tensile tests at different temperatures from 27˚C to 110˚C are conducted using the Instron Universal Testing Machine. The study results show that the layer height of 0.3 mm exhibits the highest flexural strength at an average rate of 11.05 MPa compared to 0.1 mm (6.7 MPa) and 0.2 mm (9.6 MPa). The tensile strength decreases when the temperature elevates, making the temperature of 110˚C have the lowest tensile value (1.591 MPa) compared to the temperature of 75˚C (1.6MPa) and 27˚C (2.1MPa). Several material characterizations such as SEM, TGA, DMA, DSC and density have been performed to study the microstructure and influence of tensile test temperature on the mechanical properties of polyamide.

Keywords: Polyamide; 3D printing; layer height; mechanical strength; temperature

Effective Raw Material Inventory Management is crucial for overall company performance, demanding significant improvements. In the current technologically advanced landscape, the imperative adoption of the Internet of Things (IoT) is crucial for propelling inventory management forward and amplifying the visibility of raw materials. This case study is dedicated to developing an IoT Kaizen System, meticulously aligned with the Smart Lean Factory Inventory Control Framework, tailored to enhance Raw Material Inventory Management within an SME factory in Seremban, Negeri Sembilan. With a focal point on Loft Layer materials, the study encompasses Raw Material Ordering, Receiving, and Charging Out Log operations. Leveraging web-based tools such as Google Sheets, AppSheet, and Looker Studio, the system adeptly digitizes manual processes, tracking real-time data and integrating data visualization tools for informed decision-making. Implemented within a genuine industrial context, the project is intricately tailored to meet the unique preferences and requirements of the company, ensuring a customized solution that aligns with industry standards and reflects specific operational nuances. The resulting digital system introduces a structured, simplified, and efficient approach to Raw Material Inventory Management, injecting enhanced operational control and adaptability into the company’s workflow. Through the system implementation, warehouse space was reduced by 15%, order processing was done fully digitally that achieve zero case of ordering error and achieved zero case of material stock out. This system can adjust to what’s needed in modern manufacturing. It proves that using innovation and technology can make a business better by making things run more smoothly and helping with decision-making.

Keywords: Order processing system; Mobile Apps; Google Sheet; Google Appsheet; Looker Studio; Operational Dashboard; IoT warehouse.

The bio-retted kenaf (Hibiscus cannabinus L.) bast fibres offer significant advantages over synthetic fibre regarding their being lightweight, environmentally friendly, and cheap. During the characterization procedure, the chemical composition as well as the physical, thermal, mechanical, crystallinity, and morphological properties of bio-retted kenaf (Hibiscus cannabinus L.) bast fibre were assessed. The chemical composition analysis of the bioretted bast fibre of kenaf (H. cannabinus L.) revealed that it contained a significantly high proportion of cellulose (58.72%). While, in the tensile test, the bast fibre of bio-retted kenaf (Hibiscus cannabinus L.) exhibited an average tensile strength of 3876 ± 1122 MPa and modulus of elasticity of 577 ± 177 GPa. X-ray diffraction (XRD) analysis of the bio-retted kenaf (Hibiscus cannabinus L.) bast fibre revealed its crystalline size to be 19.65 nm and crystallinity index to be 68.62%. The thermogravimetric analysis (TGA) performed on the bast fibre of kenaf (Hibiscus cannabinus L.) revealed that it maintains a thermal stability of 240°C. The scanning electron microscope (SEM) was employed to examine the fibre’s morphology. The fibre exhibited flaws and a smoothed surface, as determined by the morphological evaluation. The utilisation of bio-retted bast fibre derived from kenaf (Hibiscus cannabinus L.) as a reinforcing agent in applications involving elevated temperatures exhibited encouraging outcomes.

Keywords: Bio-retted kenaf (hibiscus cannabinus l.); mechanical properties; crystallinity index; thermogravimetric analysis; morphological

Veneering technique is discussed as one of the reasons for chipping of porcelain veneered zirconia (PVZ) restorations, which impacts their longevity and success. This study aims to evaluate the effect of veneering technique; heat-pressed, and hand-layered, on the shear bond strength of PVZ ceramics through finite element analysis. Six cylindrical bilayer material model configurations were analysed; two types of zirconia, IPS e.max® ZirCad (Z) and Luxen Zr (L) and each veneered with three porcelain types, Shofu Vintage ZR (V), IPS e.max® Ceram (C), IPS e.max® Zirpress (P), with dimensions of (10 mm x 1.2 mm) and (5 mm x 3 mm), respectively. The force for threedimensional model configurations were fixed at 5 kN. The results show that heat-pressed groups (ZP and LP) have slightly higher bond strength value 49.12 MPa and 49.03 MPa, compared to hand-layered groups (ZC, LC, ZV, and LV), measuring 48.87 MPa with 0.5% difference at maximum. Bond strength in MPa underwent variance analysis, revealing a significant influence of ceramic material on mean values (p = 0.0017). Thus, the highest stress concentrations occur at the edges of the load application points, gradually decreasing as the distance from the point of load application increases. Results indicate that heat-pressed technique is better than hand-layered veneering technique due to its effectiveness in strong adhering veneer to the zirconia core.

Keywords: Zirconia; veneer porcelain; shear bond strength; finite element analysis

Lean sustainability is often perceived to only be possible to be maintained via small group application of lean culture that carry out improvement activities. The purpose of this case study is thus to examine the success factors of inculcating lean culture framework by lean practitioners in Malaysian Manufacturing and Engineering (ME) companies that faced inconsistencies in implementing and sustaining lean. The impact of lean culture framework practiced by Small Group Improvement Activities (SGIA) was analysed via productivity improvement methodologies comprises of semi-structured interviews and analysis of 633 Small Group Improvement Activities (SGIA) project reports in establishing a final lean culture framework that can contribute to the longevity of a lean company. The improved lean culture framework that had been extended to other strategic business units (SBU) in ME companies are found to be the positive factor contributing to the sustainability of lean culture and achieving tangible and intangible benefits via small group improvement activities, enhancement standard which include companies’ policy, as well as providing a guideline in problem solving methodology. The findings revealed that enhancement of inculcating lean framework is crucially in need especially in expanding the initiatives across ME companies via a systematic and standardised problem-solving methodology. This study intends to aid organisations, practitioners, academicians, and respective industries in benchmarking the best practises and at the same time further reduce the gap and continually improve the lean culture framework in other compass industries.

Keywords: Lean Culture; continual improvement; small group improvement activity; problem-solving; lean manufacturing

A circular economy is an alternative to the traditional linear economy. The concept reduces waste by recovering resources at the end of a product’s life cycle and repurposing them to reduce environmental impact. The repurposing of machines is a model of production and consumption that involves re-pairing, refurbishing, and recycling to reduce waste. This project aims to improvise and repurpose existing mangosteen peeling machines into another suitable manufacturing process. The designed potato-cutting machine uses the existing conveyor system of a customised mangosteen peeling machine. The cutting mechanism incorporates safety and automation systems using through-beam infrared and capacitive proximity sensors. For the safety system, detecting objects within a range of 2.0 cm to the conveyor region indicates that the machine is unsafe to operate. The system will stop the machine and send audio and visual warnings to notify the users. Based on the trial runs the machine cuts the potato with approximately 1-tenth of the time needed in manual labour. The most significant benefit, however, is the overall savings in production costs, which are more than 85%. This is achieved as the machine re-purposes more than 50% of the components from the existing mangosteen peeling machine, such as sensors, control panel boxes, and PLC system. Consequently, this has helped minimise the overall cost of new equipment while encouraging a circular economy approach to engineering practices.

Keywords: Circular economy; sensor; safety system; automation system; cutting mechanism

The escalating concerns over climate change and the urgent demand for sustainable development have propelled significant efforts to mitigate carbon footprints by sequestering carbon dioxide (CO₂) into cementitious materials. One promising approach involves the incorporation of calcium-rich materials along with super-saturated aqueous solutions in cement, a method demonstrated to be effective in various studies. However, further research is necessary to address technical challenges and optimize the process. This paper presents a comprehensive review of the existing knowledge on the impact of different calcium-rich materials and curing conditions on the workability and compressive strength of concrete, with a particular focus on aqueous CO₂. Utilizing the Systematic Literature Review (SLR) method, this study identifies the problem, selects the subject of investigation, and gathers pertinent information from suitable databases. The selected documents were analyzed, evaluated, and synthesized to combine the findings. Additionally, the parameters of carbonated concrete utilized in recent studies were analyzed and discussed, providing a thorough understanding of the current advancements and areas requiring further investigation.

Keywords: Carbonic acid; compressive strength; hydration; calcium rich materials; dolomite

Globally, current research has developed new cement-based materials to meet increased demands for performance, energy efficiency, and environmental protection. Geopolymer, cost-effective, and high-early strength concrete binder alternative, has grown in popularity. Geopolymer reduces emissions by 80% during production while maintaining strength levels comparable to Ordinary Portland Cement (OPC). In their natural state, geopolymer binders have a microstructure that is cross-linked and significantly more brittle than OPC. To improve the properties of geopolymer, several approaches were adopted. However, recent study suggests that incorporating nanomaterials such as graphene oxide (GO) to geopolymer has shown an improvement in physical and mechanical properties. Graphene oxide is an inorganic nanomaterial that improves the mechanical characteristics of various composite materials by showing substantial filling effects on composite materials that significantly improve composite material integrity. The investigation into the potential of GO to improve the efficacy of geopolymer composite materials in various engineering applications has garnered considerable attention in recent years. The simplified hummer’s method was employed to synthesise the GO. Various characterization techniques involving SEM, XRD, and FTIR were utilized to understand the crystalline structure and microstructure of GO nanoparticles. GO powder were used as 0.05%, 0.10%, 0.15%, 0.20%, and 0.25% by weight of binder that includes fly ash class F and steel slag with an optimum binder modification of 40% fly ash and 60% steel slag. The influence of GO on Bulk density, microstructure, and mechanical strength were determined. The compressive strength results indicated an improvement of compressive strength by 21.48% in geopolymer paste with 0.15% GO after 28 days of curing.

Keywords: Graphene oxide; nanoparticles; geopolymer concrete; sustainable construction materials

Plain concrete beam repair and strengthening are increasingly important in structural strengthening and retrofitting. This study examines the glass fibre-reinforced polymer (GFRP) sheets in plain concrete beams under flexural behaviour by using its patching sheets. Through the implementation of a symmetrical four-point static loading technique, a series of tests were conducted on plain concrete beams that had been externally joined with GFRP sheets. These beams were subjected to rigorous testing until they reached their ultimate failure point. The experimental test consists of casting nine plain concrete beams with identical specifications. Three beams are utilised as control beams; three are reinforced with GFRP sheets measuring 50 mm × 100 mm, and another three are reinforced with GFRP sheets measuring 100 mm × 200 mm. The flexural test is designed to determine the tensile strength of concrete under bending. Compared to the control beams, the specimens strengthened with GFRP sheets demonstrated a significantly enhanced ultimate load capacity. The beams with larger GFRP sheets exhibited a higher ultimate load of 14.84 kN, while those with smaller sheets showed an ultimate load of 8.54 kN, marking an appreciable improvement in performance. Moreover, the smaller area GFRP-reinforced beams failed at a 45% higher shear stress compared to those with a larger area GFRP, indicating a differential impact based on the size of the reinforcement used. This study highlights the effectiveness of GFRP sheets in enhancing the structural performance of plain concrete beams, providing crucial insights into the benefits of different sizes of reinforcement.

Keywords: Glass fiber reinforced polymer (GFRP) sheet; Concrete beam; Strengthening; Ultimate load; Energy absorption.

Activated Carbon (AC) has been a great alternative to reduce the cost of the process in wastewater treatment plants (WWTP) but they also have several hidden impacts on the environment. The impact assessment on the waste materials from coconut shells and wood will be identified using the Life Cycle Assessment (LCA) software approach. Through the “Cradle-to-gate” approach, activated carbon made from waste materials is produced and consumed, and its eighteen environmental effects which are fine particulate matter formation, fossil resource scarcity, freshwater ecotoxicity, freshwater eutrophication, global warming, human carcinogenic toxicity, human non-carcinogenic toxicity, ionizing radiation, land use, marine ecotoxicity, marine eutrophication, mineral resource scarcity, human health, terrestrial ecosystem, stratospheric ozone depletion, terrestrial acidification, terrestrial ecotoxicity and water consumption are assessed using the LCA software. This study aims to discover whether the choice of waste material precursors from the Activated Carbon (AC) can help to minimise environmental impacts. The study evaluates the potential benefits of using waste-derived activated carbon in wastewater treatment by comparing the environmental performance of activated carbon obtained from coconut, wood, and coal. This study is based on past studies all around the world. In thirteen of the eighteen impact categories, wood has the greatest environmental impact. Coconut shells on the other hand, has the lowest total environmental impacts, ranking first or second in fifteen among the eighteen environmental categories. The findings help in making choices for environmentally friendly wastewater treatment methods by illuminating the effects of employing waste products as an alternative source of adsorbents.

Keywords: Waste materials; activated carbon; adsorbent; OpenLCA software

Food waste has an influence throughout the whole food supply chain, from production to consumption. Composting effectively and affordably reduces the need for synthetic fertilizers, water, soil erosion, pesticides, and soil carbon storage. Composting may also improve crop yields and soil fertility, leading to more sustainable farming practices. The potential of efficient microorganisms (EM) for dehydrated food waste decomposition was investigated in this study. The research assessed the temperature and pH profiles during composting, whereas nitrogen, phosphorus, potassium, organic content, and E. coli were measured in mature composts. Therefore, the study revealed that EM greatly hastened the composting process by boosting critical factors such as temperature, pH, nitrogen content (TN : 1.17±0.6%, TP: 0.059±1.92%, K: 0.12±5.3%) organic enrichment (85%), and E-coli (<1 MPN/g). The germination index (GI) of kale seed was then analysed with the study’s findings indicating an 80% soil-compost ratio was the best. This research investigates the use of effective microorganisms (EM) to transform food waste into beneficial agricultural resources, with favourable results for soil health and kale seed germination. Researchers and circular economy officials may use the results to promote sustainable agriculture. The research helps to minimize landfill food waste, methane emissions, and synthetic fertilizer consumption, all of which benefit the environment. Farmers and gardeners may use the findings to boost soil fertility and crop yields on a budget. This research indicates that food waste may be transformed into useful resources, encouraging sustainable and eco-friendly agricultural.

Keywords: Food waste; compost; effective microorganisms; germination index

Alzheimer’s disease, acknowledged for its intricate and degenerative characteristics, presents considerable challenges, particularly among the elderly population. The relentless nature of Alzheimer’s, marked by the gradual deterioration of cognitive function, underscores the urgency to develop effective strategies for early diagnosis and intervention. Artificial intelligence has played a significant role in terms of disease diagnosis and treatments. However, it has got limited acceptance in the medical community due to its lack of transparency. This study aims to advance the understanding and prediction of Alzheimer’s disease progression through the integration of time-aware modeling and Explainable AI techniques. It makes significant contributions by addressing two key objectives in the context of Alzheimer’s disease. First, by including temporal aspects, it accurately depicts the pace at which relevant predictors change over time, thereby capturing the dynamic nature of Alzheimer’s disease. Second, by giving interpretable insights into the algorithm’s decision-making process, the study hopes to empower researchers and physicians. This approach not only enhances transparency but also builds trust in the model’s outcomes. The ADNI dataset, comprising 2980 observations, was employed for developing a prediction model using various machine learning classifiers. Among these classifiers, the Random Forest model emerged as the top performer, exhibiting superior accuracy, a high Coefficient of Determination (R2), and an impressive F1 score. To enhance interpretability, subsequent analyses utilized LIME and SHAP techniques. By combining time-aware modeling with Explainable AI methods, we seek to unravel the dynamic relationships within the dataset, providing transparent insights into the temporal evolution of Alzheimer’s disease. Thus, this paper contributes to the creation of a clinically relevant and practical model for monitoring Alzheimer’s disease progression that holds the potential for a deeper understanding of the evolving nature of the disease and paving the way for personalized and timely interventions.

Keywords: Alzheimer’s disease; explainable AI; time-aware modeling; machine learning; LIME; SHAP

In recent years, there has been a noticeable rise in the need for wireless network connection in healthcare facilities. This is a result of the requirement for immediate access to patient data as well as the growing number of medical devices that are internet-connected. To guarantee dependable and secure communication as well as support for diverse healthcare applications and services, it is essential to choose the right wireless network type. However, the selection procedure can be difficult because it includes a number of variables that are frequently arbitrary and subjective. The difficulties of choosing the best wireless network type to be used in healthcare facilities are addressed in this research by the introduction of a new fuzzy model for multi-criteria decision-making (MCDM). The approach considers several evaluation factors, including patient cost, patient privacy, patient safety, and patient comfort and convenience. The model uses a fuzzy analytic hierarchy process (FAHP) to compute the weights of these criteria. In addition, the model uses fuzzy methods like fuzzy ARAS, fuzzy EDAS, and fuzzy TOPSIS to rank the different kinds of wireless networks according to their performance. It is clear from the results that the suggested model can effectively and dependably assess different alternatives. Additionally, it provides useful and practical advice on how to choose the right wireless network types for medical facilities. The best feature is that this approach is easily adaptable to other healthcare industry decision-making procedures.

Keywords: FMCDM; wireless network; ARAS; EDAS; TOPSIS; healthcare

Personalised e-learning aims at providing a personalisation effect based on the learner’s characteristics such as knowledge level, preferences, and learning style. The support derived from using social collaboration tools like social media reflects the discovery of these characteristics from content generated during collaboration. The collaboration process is guided using different annotations equipped with the collaboration tool. This type of system needs to be evaluated in terms of usability factors including usefulness, ease of use, and System Usability Scale (SUS). These evaluation factors reflect the objectives of the system based on the different functionalities provided. Thus, the correlation between these factors and how they are related to the system objectives is needed to be validated. This validation is performed using Principal Component Analysis (PCA) utilising PerLCol framework as discussed in this paper. PerLCol is a framework that aims at providing personalisation effects by utilising the generated information during social collaboration and interaction. The result reveals the strength items as indicated by the selected components (PC1, PC2, and PC3). These components are related to three evaluated factors which are personalisation, social collaboration, and seamless design which ultimately reflect the objectives of the framework.

Keywords: Personalisation; e-learning, social collaboration; Principal Component Analysis; System Usability Scale

Refractive error is a visual impairment that arises when the ocular anatomy hinders the proper focusing of light onto the retina, the light-sensitive tissue layer located at the posterior region of the eye. This condition poses difficulties in achieving clear vision. Refractive error stands as the prevailing kind of visual impairment. The objective of this study is to classify two surgical approaches utilized in the treatment of refractive defects. Two commonly performed refractive surgeries are Photo-Refractive Keratectomy (PRK) and Laser-Assisted In-Situ Keratomileusis (LASIK). Artificial Intelligence (AI) encompasses a specific branch known as Machine Learning (ML), which is the focal point of this investigation. ML is dedicated to the advancement and use of algorithms that possess the capacity to acquire knowledge from data and enhance their predictive capabilities without explicit programming. The present study employs sophisticated ML methods to classify different types of refractive defect surgeries using a dataset of 124 samples obtained from Al-Rabee Hospital in Iraq, specifically focusing on corneal topography data. Two ML approaches, namely K-Nearest Neighbor (KNN) and Artificial Neural Network (ANN), are employed to predict the kind of refractive defect surgery. The findings produced from the experiment demonstrated an accuracy rate of 90.32% for the KNN algorithm and a perfect accuracy rate of 100% for the ANN algorithm. Additionally, the KNN algorithm exhibited a sensitivity of 90% and a specificity of 90.54%. The study’s findings indicate that the ANN classifier outperforms the KNN classifier.

Keywords: Refractive error; classification; k-nearest neighbor; artificial neural network

Stroke is a potentially fatal illness that requires emergency care. There is a greater chance that the patient will recover and resume their regular life when they receive treatment and diagnosis as soon as feasible. Artificial Intelligence has the potential to significantly impact stroke diagnosis and facilitate prompt patient treatment for physicians. Machine learning can be utilized in stroke prediction by evaluating huge volumes of patient data and detecting patterns and risk variables that may contribute to the likelihood of a stroke. In this study, we explored a stacked ensemble model that uses four base models—Decision Tree, XGBoost, RandomForest, and ExtraTree classifiers to predict the stroke. We discovered that the accuracy of the stacked ensemble model was 96.35%, higher than that of the traditional machine-learning models, other ensemble models, and ANN model.

Keywords: Ensemble Model, Bagging, Voting, Stacked ensemble, Boosting

Wireless communication systems require electrical energy to operate and function. Whereas standalone applications require reliable power sources which can be realised by photovoltaic technology. Typically, photovoltaic cells and antennas are two separate devices. These devices compete for space in mobile or standalone systems, where available space is generally very limited. To address this issue, a combination of an antenna and a solar cell into a single device is needed. Integrating an antenna with a solar cell is challenging due to the importance of maintaining a compact, simple design while achieving optimal efficiency for both elements. This study focuses on designing a transparent grid array antenna integrated with Dye-Sensitized Solar Cells (DSSC) for Ku-band applications. The grid array design aims to improve antenna performance and is chosen for its suitability with the design and structure of the solar antenna device. The integrated antenna and solar cell were simulated using Computer Simulation Technology (CST) software at a frequency of 14 GHz for Ku-band applications. A prototype of the antenna and solar cell was fabricated, then tested and measured for the efficiency of both the antenna and solar elements. For the solar element, performance measurements were conducted using a halide lamp to mimic sunlight, with results presented in the form of current-voltage curves. In summary, by the end of this study, a transparent solar antenna for Ku-band applications was successfully designed with a gain exceeding 10 dBi. The solar cell’s performance showed an open-circuit voltage (V_OC) of 0.6733 V, a short-circuit current density (J_SC) of 2.06 mA/cm², a fill factor (f_F) of 29.31%, and a power conversion efficiency (η) of 0.407%.

Keywords: Solar antenna; transparent antenna; transparent solar antenna; Dye Sensitised Solar Cell (DSSC); grid array

Renewable energy (RE) is getting more attention in solving the escalating global warming issue. However, the community has not been sufficiently educated about this fact. Exposure to renewable energy technology in Malaysia, especially for children, is still lacking, leading to a lack of awareness on the importance of renewable energy. Besides, children’s lack of knowledge about renewable energy and lack of interest in the field of science became problems in this study. Therefore, this study on effect of usefulness, user friendly, quality and user acceptance toward mobile application approach in introducing knowledge of renewable energy. The main software in developing the RE application consist of five components, i.e. introduction, video, game, quiz and news. Testing was carried out on selected children to evaluate children’s satisfaction in terms of using the application in learning RE. A pilot study was conducted on 30 children and the application model was validated by three experts and evaluated for its effectiveness through quantitative studies. Then, the mobile apps were tested on 77 9-year-old children with a quantitative research method to assess the level of knowledge acceptance and awareness of renewable energy. Results indicate that the children’s knowledge of RE increased with the use of this RE mobile application because RE information is delivered in the form of images, audios, and videos. More than 98% of the respondents agree that the application helps in understanding RE. The mobile application also successfully attracted the children’s interest in RE innovation and increased their awareness on the importance of RE.

Keywords: Android application; mobile apps; renewable energy; awareness