Infill patterns significantly affect the mechanical properties, printing time and material consumption of 3-Dimensional (3D) printed Polylactic Acid (PLA) parts. Despite the wide variety of available infill patterns, the effect of combining and arranging multiple infill patterns on strength-to-weight ratio within a single print remains underexplored. This study investigates the effect of infill pattern arrangements on enhancing the strength-to-weight performance for applications requiring strong yet lightweight components. Three infill patterns (Lines, Triangles and Gyroid) were selected and arranged in three different configurations: by-layer, by-horizontal area and by-vertical area. By-layer arrangement exhibited improved tensile strength, Young’s Modulus and strength-to-weight ratio. BL5 with 50% infill density and arranged by-layer, demonstrated the best performance, with a tensile strength of 17.77 MPa and strength-to-weight ratios of 2.85 MPa/g. The infill patterns in this arrangement, delays crack propagation, as the non-continuous geometry created by the varied patterns disrupts the crack path. In contrast, the lowest tensile strength was observed for by-vertical area arrangement, where the tension load was applied perpendicular to the interface between different infill patterns, increasing the likelihood for crack initiation and propagation. Although the by-layer arrangement required a longer printing time, it produced part with a superior strength-to-weight ratio compared to the other arrangements, making it an effective strategy for balancing mechanical strength and material efficiency.

Walking on inclined and declined surfaces introduces distinct biomechanical challenges that alter lower-limb joint loading and stability. This study aimed to investigate the effects of surface inclination on ankle joint reaction forces and to determine the safest walking angle based on the minimum forces exerted. Ten healthy male participants from Universiti Malaysia Perlis walked at self-selected speeds across slope angles of 0°, ±5°, ±7.5°, and ± 10°. Motion capture data were collected using a Qualisys Track Manager system integrated with embedded force plates, and joint reaction forces were analyzed through Visual3D software using inverse dynamics. Data were filtered with a fourth-order Butterworth low-pass filter at 4 Hz to obtain accurate kinematic and kinetic outcomes. The findings revealed that the mean maximum ankle joint reaction force remained nearly constant between level walking and 5° inclination but decreased noticeably at 7.5° and 10° slopes in both uphill and downhill conditions. Statistical analysis showed no significant difference between level and uphill walking, whereas a significant reduction in joint reaction force was observed at −7.5° and − 10° declinations. The ankle joint consistently exhibited the highest load compared to the knee and hip joints across all slope angles. Decline walking demonstrated lower mechanical demands on the ankle, indicating a safer condition compared to incline walking. The study provides valuable insight into joint behavior on sloped terrains and underscores the importance of biomechanical understanding and clinical awareness to minimize joint stress and potential musculoskeletal injury during locomotion on inclined and declined surfaces.

This study investigates the influence of infill patterns and densities on the tensile properties of Fused Deposition Modeling (FDM) 3D-printed Polylactic Acid (PLA) parts, aimingto optimize material efficiency while maintaining structural integrity. Eight infill patterns- Cross 3D, Subdivision Cubic, Octets, Quarter Cubic, Concentric, Grid, Gyroid, and Zigzag-were tested at 45%, 55%, and 65% infill densities, with a solid specimen (100% infill) serving as a benchmark. Tensile testing revealed that the Quarter Cubic pattern at 65% infill density closely matched the mechanical strength and stiffness of the solid specimen while significantly reducing material usage. Statistical analysis using the Taguchi method and ANOVA identified infill percentage as the most influential factor (p = 0.003), while regression modeling (R-2 = 91.88%) demonstrated robust predictive capability. This study contributes novel insights into the interplay between infill design and mechanical performance, guiding sustainable production of high-strength, lightweight PLA components for applications in aerospace, automotive, and consumer products.

Thermoplastic filaments used in fused deposition modelling (FDM) are increasingly adopted for functional components, yet their durability under thermal and moisture-related service conditions remains incompletely characterised. This study presents a multi-modal investigation of the mechanical degradation of three commercial FDM filaments, namely polylactic acid (PLA), polyethene terephthalate glycol (PETG), and wood-filled PLA (PLA-Wood), subjected to two independent degradation pathways: accelerated isothermal thermal ageing at material-relevant glass-transition temperatures for four and eight days, and immersion in distilled water for 24–720 h. Specimens were fabricated according to American Society for Testing and Materials (ASTM) D638, ASTM D790, and ASTM D695 standards using 70% concentric infill, then evaluated through tensile, flexural, and compressive testing, gravimetric mass and moisture analysis, and scanning electron microscopy (SEM). Under thermal ageing, PETG exhibited the highest tensile strength retention, maintaining 40.87 ± 1.18 MPa after eight days, with the smallest proportional tensile modulus reduction of ≤ 5.1%. PLA-Wood sustained the greatest compressive modulus loss of 15.6%, attributed to combined PLA matrix chain scission and hygroscopic wood-filler desorption. Under moisture exposure, PETG maintained stable wet-state tensile strengths of 24.38–25.60 MPa after initial conditioning, whereas PLA-Wood absorbed approximately 50% apparent moisture in compression specimens and suffered a 57% flexural strength reduction. PLA showed transient increases in stiffness associated with secondary crystallisation before degradation. SEM confirmed distinct material–stressor degradation pathways. These results establish the first integrated dual-stressor degradation profile for this filament triad, providing quantitative selection criteria for FDM applications involving thermal or humid service environments.

This study examines the biomechanical responses of the ankle, knee, and hip joints during walking on varying slopes to understand how different inclinations affect joint loading and movement mechanics. While previous research has explored slope walking, many studies lack detailed multi-plane analyses of joint moments and accelerations, limiting their applicability in rehabilitation and injury prevention. To address these gaps, we employed advanced motion capture and force plate measurements to quantify joint moments and accelerations at inclinations of 0 degrees, 5 degrees, 7.5 degrees, and 10 degrees. Our results indicate that steeper slopes significantly increase joint moments and accelerations, particularly in the knee and hip during incline walking and in the ankle during decline walking. These findings highlight the increased biomechanical demands on lower limb joints, emphasizing the need for tailored rehabilitation programs, training strategies, and ergonomic interventions. By providing a more comprehensive understanding of slope-related mechanical stresses, this study contributes valuable insights for injury prevention, rehabilitation, and performance optimization in both clinical and athletic settings. The findings suggest that to decrease the risk of falling and manage the demands of inclined walking, appropriate walking strategies and improved safety measures should be implemented, especially during decline and anterior-posterior orientations. This study also offers additional understanding of optimal incline walking techniques for secure and practical locomotion.

3D printing and 3D scanning technologies have become pivotal tools in the medical field, especially for the design and fabrication of customized medical devices. This study focuses on the development and testing of a novel composite 3D-printed pneumatic artificial muscle exoskeleton robot designed to assist the human hand in heavy weight lifting. We fabricate the load-bearing frame using 3D printing technology and carbon fiber-reinforced plastic materials. This frame aims to assist individuals with mobility impairments, workers in industrial environments, and patients requiring rehabilitation after injury. The product, fully personalized through 3D scanning technology, ensures high precision and comfort for the user. This paper provides an overview of the research's significance, the design and fabrication methods, as well as the results from product testing. The load-bearing frame is not only lighter than traditional alternatives but also offers enhanced strength and load-bearing capacity with the support of pneumatic artificial muscles. Furthermore, the study explores the economic advantages, potential practical applications, and the opportunity to replace costly imported products with locally produced solutions at more affordable costs. The findings from this research contribute to improving treatment outcomes and quality of life for patients while also opening new avenues for the application of 3D printing and scanning technologies in healthcare sector.

An improved and modified Probabilistic Roadmap (PRM) algorithm for non-circular holonomic mobile robot is proposed based on the consideration the shape and its kinematic constraint of non-circular holonomic mobile robot while moving from the initial point to the target point, especially to pass through the narrow passage. The path planning algorithm is also being modified to generate a shorter path distance in the shortest duration of time with the least number of turning points. The comparison of the conventional path planning algorithm will be carried out to determine the most optimal algorithm for modification to achieve the objectives. Then, the chosen path planning algorithm is PRM are improved by obstacle expansion and automatic selection for region of interest (AutoROI). Software simulation and analysis are performed on three different environment maps by a single holonomic mobile robot. The analysis of simulation revealed the performance of the modified path planning algorithm able to reduce elapsed time of PRM and increase the percentage of success path planning.

The rapid digital transformation of transportation systems has elevated Extended Reality (XR) technologies—including Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR)—as critical tools. XR improves safety, optimizes mobility, and enhances human-machine interaction.This study presents a bibliometric analysis and thematic review of XR research in transportation. We analyzed 283 Scopus-indexed publications from 2014 to 2024 using Bibliometrix, VOSviewer, and Python-based libraries. The results show an annual publication growth rate of 18.15%. Cornell University, the University of Glasgow, and Delft University of Technology emerged as leading institutional contributors. National leadership was dominated by the United States, Germany, and China.Thematic mapping identified key areas such as autonomous vehicle validation, pedestrian-AV interaction, AI-driven traffic simulation, immersive driver training, and AR navigation for rail and maritime transport. Keyword analysis emphasized research focuses including Virtual Reality, Augmented Reality, Autonomous Vehicles, Pedestrian Safety, Mixed Reality, Traffic Simulation, and Human Factors.Despite this progress, significant challenges persist. Studies often lack ecological validity, demographic diversity, scalability, cybersecurity resilience, and ethical transparency. Most XR applications remain confined to laboratory settings with limited real-world validation or cross-cultural generalizability.To address these gaps, we propose integrated frameworks and a strategic research agenda. We emphasize ecological realism, cognitive-adaptive XR designs, interdisciplinary collaboration, and ethical governance.This study consolidates existing knowledge and outlines future research directions. XR is positioned as a transformative and human-centered technology, crucial for advancing safer, smarter, and more inclusive transportation ecosystems.

This study aims to assess the performance of an Additive Manufacturing (AM) machine, specifically a Selective Laser Sintering (SLS) machine, through the design and evaluation of a benchmarking artifact. Drawing from insights gained in previous research, the artifact is meticulously crafted with two distinct materials to explore potential variations in geometric accuracy. The artifact comprises two types: one featuring straight geometries and another incorporating curved elements. The research methodology involves printing both artifact types at default machine settings, followed by precise measurements using a 3D scanner. The inclusion of straight and curved features facilitates a comprehensive examination of the machine's ability to reproduce diverse geometries. The amalgamation of these features into a combined artifact provides a holistic assessment of the machine's overall performance. To validate the benchmarking artifact, the final design is reproduced, and its output is compared not only with the original design but also with real-life parts. The results show that flexible polymers offer higher accuracy but lower resolution, while rigid polymers provide better resolution but with a greater number of defects. This comparative analysis serves to highlight the accuracy and reliability of the benchmarking artifact in reflecting the machine's performance in practical scenarios. In conclusion, this study endeavours to advance the understanding of an SLS machine's capabilities by leveraging a carefully designed benchmarking artifact.

The growth of 3D printer inks is in line with the growth of 3D printing technology. Finding a suitable formulation of 3D printer ink is crucial for fulfilling the demands of construction fields, bio-printing, and consumer products. Soft materials, such as silicone paste, have become one of the requested inks owing to their natural characteristics, cost effectiveness, and substantial environmental friendliness. However, because of the thixotropic behavior of silicone, the development of silicone paste as a 3D printer ink is challenging. This study aimed to develop a new soft material formulation ink made from silicone for extrusion-based 3D printing. A common silicone polymer was added with 0.2

The Internet of Things (IoT) is a paradigm-shifting technology that represents the future communication and computing. The implementation of IoT is widespread and can be used in any industry including the agricultural sector. Mango farming is becoming an increasingly important sector in Malaysia as the country's population grows. Harumanis mango is the main agriculture in Perlis, Malaysia and is a source of income for the state and local residents. The quality of the fruit produced is inconsistent due to the manual process of fruit and tree monitoring. In addition, incorrect fertilisation and tree care is the main cause of poor fruit quality. Therefore, this project was produced as a system based on the Internet of Things (IoT) to monitor soil parameters of Harumanis trees. IoT systems can reduce labour costs while improving farm management, costs efficiency, crop monitoring, crop quantity, and quality. This system uses a pH level sensor, a temperature, and humidity sensor and a soil moisture sensor to monitor soil conditions of Harumanis farm. The system is a simple IoT architecture where sensors will collect data and transmit it to the cloud database via Wi-Fi. Every data collected during the test is stored in a cloud database using the Blynk IoT platform, which the farmer can use to track the daily growth of the tree from their smartphone or laptop. This system can help farmers in monitoring the growth of Harumanis trees and produce Harumanis mangoes of the best possible quality, and farmers will also be able to react immediately if abnormal data is obtained through the Blynk Application warning system.

Surgeons face a significant challenge due to the heat generated during drilling, as excessive temperatures at the bone–tool interface can lead to irreversible damage to the regenerative soft tissue and result in thermal osteonecrosis. While previous studies have explored the use of machine learning to predict the temperature rise during bone drilling, this in vitro study introduces a comprehensive approach by combining the Response Surface Methodology (RSM) with advanced machine learning techniques. The main objective lies in the comprehensive evaluation and comparison of support vector machine (SVM) and random forest (RF) models specifically for the optimization of the bone drilling parameters to prevent thermal bone necrosis. A total of 27 experiments were conducted using a multi-level factorial method, with analysis performed via the Minitab software version 19.1. Performance metrics such as the mean squared error (MSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) were used to assess model accuracy. The RF model emerged as the most effective, with R2 values of 94.2% for testing and 97.3% for training data, significantly outperforming other models in predicting temperature fluctuations. This study demonstrates the superior predictive capabilities of the RF model and offers a robust framework for the optimization of surgical procedures to mitigate the risk of thermal damage.

This research paper explores the influence of infill patterns on the tension and compression strength of 3D printed parts using polylactic acid (PLA) material. The study utilized an ASTM D638 and 50 × 50 × 50 mm cube as investigated models with three different infill patterns in each case. The infill patterns that were investigated included line lattice (0/0), grid (0/90), grid (−45/45), and triangle (−30,30). The ASTM D638 models will be tested by tension force whereas the cubic models will be tested by compression force. The results of the study showed that the infill pattern, line (0/0) in case of ASTM D638 and triangle (−30/30) in case of the cube, provided higher tension and compression strength compared to other patterns. It was revealed that each pattern’s microstructure is a crucial factor determining the mechanical properties of the printed parts. The findings of this study suggest that selecting the appropriate infill pattern could enhance the mechanical performance of 3D printed parts made from PLA material. Additionally, this research provides valuable insights into how selecting different infill patterns could influence the tension and compression strength of 3D printed parts produced from PLA material. Moreover, combining continuous carbon fiber (CCF) reinforcement with PLA resin can greatly enhance the strength of the models. It is the first step to expand the application of 3D printed parts with CCF.

Diabetic retinopathy (DR) is a common diabetic complication that affects the retina of the eye. The severity of DR is determined by the number and type of lesions, such as microaneurysms, haemorrhages, and exudates that appear on the surface of the retina. However, DR is hard to be detected in the initial stages and may vary from expert to expert. This may lead to a serious side effect in giving the patient a suitable treatment, which can cause a significant impact commonly among high-risk patients. Thus, the demand for advanced DR diagnosis and treatment has drawn the attention of researchers. The main contribution of this work is to develop an automated grading system using deep learning architecture in the urge to help experts in identifying the severity level of DR. The process that has been addressed in this work begins with the pre-processing step, followed by the segmentation of features using local entropy thresholding. In the classification stage, three different deep learning classifier architectures, namely CNN, ResNet152v2, and Inception-v3 convolution neural networks were used to differentiate the category between the normal, mild non-proliferative diabetic retinopathy (NPDR), moderate NPDR, and severe NPDR. Overall, the classification performance results show that the ResNet152v2 model is a better classifier than the other two models with a testing accuracy of 90

In daily routine movement, the ankle joint plays a crucial role in stability and mobility, especially when different types of terrain are involved. However, the simple task of standing can become a biomechanical difficulty when performed on a slope since demands that have to be accommodated are made on the complex structure of the ankle joint. The purpose of this study is to develop finite element (FE) models of the ankle joint with different inclined foot postures and to analyse the stress distributions on the ankle joint while standing on an inclined or declined surface. In this study, the FE model of the foot was developed, and von Mises stress distribution at the ankle joint was explored. The results show that the bone, cartilage, and ligament of the ankle experienced a different von Mises stress distribution pattern during flat standing in comparison with slope standing. In addition, this study found that the maximum von Mises stress distribution at the component of the ankle joint is higher during slope standing than flat standing. Taken together, these results suggest that slope standing, both inclined and declined, with more than 10° inclination, might contribute to a higher risk of injury as a higher maximum stress was observed. Therefore, to maintain proper body posture, it is suggested that weight be evenly distributed at both feet, since this can reduce stress at the ankle.

Drilling is a widely employed technique in machining processes, crucial for efficient material removal. However, when applied to living tissues, its invasiveness must be carefully considered. This study investigates drilling processes on polyurethane foam blocks mimicking human bone mechanical properties. Various drill bit types (118 degrees twist, 135 degrees twist, spherical, and conical), drilling speeds (1000-1600 rpm), and feed rates (20-80 mm/min) were examined to assess temperature elevation during drilling. The Taguchi method facilitated systematic experiment design and optimization. Signal-to-noise (S/N) ratio and analysis of variance (ANOVA) identified significant drilling parameters affecting temperature rise. Validation was conducted through confirmation testing. Results indicate that standard twist drill bits with smaller point angles, lower drilling speeds, and higher feed rates effectively minimize temperature elevation during drilling.

This project explores EasyOCR’s performance with Latin characters under image degradation. Variables like character-background intensity difference, Gaussian blur, and relative character size were tested. EasyOCR excels in distinguishing unique lowercase and uppercase characters but tends to favor uppercase for similar shapes like C, S, U, or Z. Results showed that high character-background intensity differences affected OCR output, with confidence scores ranging from 3 % to 80%. Higher differences caused confusion between characters like o and 0, or i and 1. Increased Gaussian blur hindered recognition but improved it for certain letters like v. Image size had a significant impact, with character detection failing as sizes decreased to 40% to 30% of the original. These findings provide insights into EasyOCR’s capabilities and limitations with Latin characters under image degradation.

Postural stability may be affected during slope walking, as there are different body kinetics and kinematic responses compared with level walking. Understanding body adaptations toward different inclinations is essential to prevent the risk of injury from falls or slips. This study was conducted to determine the correlations between stability parameters and loading response in terms of joint reaction force at the lower-extremity joints during inclined and declined walking. Twenty male subjects walked in the level, incline, and decline directions on a custom-built platform at three different slope angles (i.e., 5°, 7.5°, and 10°). To determine the ground reaction force (GRF), joint reaction force (JRF), center of pressure (COP), and center of mass (COM), a motion capture system was used to read the data of the ten reflective markers and transfer them to visual three-dimensional (3D) software. Pearson’s correlation test was performed with statistical significance set at p < 0.05 to evaluate the correlation of the required coefficient of friction (RCOF), postural stability index (PSI), and COP-COM distance with the JRF. This study has identified that the JRF changes in opposition to the changes in the RCOF during the initial strike during incline and decline walking, as JRF increases, the RCOF decreases with different strengths of correlation. There is also a strong positive correlation between the PSI and JRF in the proximal–distal direction, where the JRFs change in accordance with the change in the PSI, and the JRF increases with the increment of PSI. In addition, the JRF of the lower extremity also changed in a manner similar to the COP-COM distance in the medial–lateral direction. Overall, each stability parameter was correlated with the JRF of the lower-extremity joints in different directions and strengths. This study demonstrated that slope walking is particularly affected by surface inclination in terms of stability and loading. Therefore, this research can serve as a basis for future studies on slopes, as there is no specific basis for a maximum degree of inclination that is safe and suitable for all applications.