Taiwan Association of Engineering and Technology Innovation: E-Journals
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A Review of Advances in Bio-Inspired Visual Models Using Event-and Frame-Based Sensors
Full text linkThis paper reviews visual system models using event- and frame-based vision sensors. The event-based sensors mimic the retina by recording data only in response to changes in the visual field, thereby optimizing real-time processing and reducing redundancy. In contrast, frame-based sensors capture duplicate data, requiring more processing resources. This research develops a hybrid model that combines both sensor types to enhance efficiency and reduce latency. Through simulations and experiments, this approach addresses limitations in data integration and speed, offering improvements over existing methods. State-of-the-art systems are highlighted, particularly in sensor fusion and real-time processing, where dynamic vision sensor (DVS) technology demonstrates significant potential. The study also discusses current limitations, such as latency and integration challenges, and explores potential solutions that integrate biological and computer vision approaches to improve scene perception. These findings have important implications for vision systems, especially in robotics and autonomous applications that demand real-time processing
Investigation of Effects of Process Variables on Weld Bead Characteristics in Surface Coating of 309L Stainless Steel by Wire Arc Additive Manufacturing
Full text linkCoating carbon steel surfaces with stainless steel is a crucial technology in various industries to extend the product lifespan. This study focuses on investigating the effects of process parameters on weld bead characteristics in coating SS309L on carbon steel substrates by wire arc additive manufacturing (WAAM) and identifying the optimal parameters. The key parameters are current, travel speed, and voltage, while the weld bead characteristics include height, width, and depth of penetration. Experimental data and analysis of variance (ANOVA) are employed to develop and evaluate predictive models in Minitab software. The results show that the optimal process parameters for coating SS309L on carbon steel substrates by WAAM are voltage = 22 V, current = 132 A, and travel speed = 0.3 m/min, which improve height and width by 56.71% and 25.87%, respectively, while reducing the depth of penetration by 21.74% compared to the worst-case scenario
Uplift Capacity and Displacement of Pre-Bored PC Piles in Undrained Soils
Full text linkThis study aims to present interpretation recommendations to aid in the design of pre-bored PC piles in undrained soils, along with preliminary results for model factors to characterize model uncertainty. Measured capacities are estimated from the load-displacement curves using six interpretation methods, each assessed by employing the L2 method as a normalizing criterion. Predicted capacities are calculated via the α and β methods using analysis parameters for drilled shafts and are compared with measured capacities. Results show mean normalized capacities ranging from 0.45 to 1.60, with 6.4 to >43.9 mm displacements. A comparison of load-displacement behaviors reveals that pre-bored PC piles require greater displacements to mobilize the capacity than drilled shafts, driven piles, and barrette piles. The analysis highlights an overprediction of side resistance. Model factors, defined as the ratio of measured to predicted capacities, can calibrate resistance factors for reliability-based design
Multiclass Plant Leaf Disease Prediction Using Fuzzy Multimodal Feature Extraction
Full text linkDelayed identification of crop diseases, which significantly impact agricultural yields, remains a critical challenge. Crop diseases are a major factor contributing to reducing productivity. Since leaves are the mirrors of crop health, by investigating the leaves, a prediction of crop health can be made. This study aims to predict crop disease in the vegetative growth phase with greater efficiency. The two most prominent features, color and texture of the leaves, are extracted with different techniques, followed by fuzzification of these features. Two machine learning models, the bootstrap model and the multi-class support vector machine (MSVM), are employed for disease prediction. The findings show that for multi-class disease prediction, the bootstrap model with histogram and modified co-occurrence matrix features obtains a superior average accuracy of 98.07%, while the MSVM with fuzzy features delivers an average accuracy of 80.11% in the potato crop with early blight disease
Formulating Seismic Intensity Scale (JMA-SIS) Using Response Spectrum: A New Approach for Structural Engineering Design
Full text linkThis study aims to formulate a calculation for earthquake shaking intensity (rs_mSIS) based on the response spectrum (RS) using the Japan Meteorological Agency-seismic intensity scale. The research investigates the relationship between the response spectrum parameters—period and maximum acceleration—and the earthquake source types, including megathrust, Benioff, and shallow crust/background sources. Artificial ground motions are generated and analyzed using Matlab to calculate shaking intensity values, which are then used to develop the rs_mSIS formula. The formulation is validated against actual response spectrum data from 15 Indonesian cities and demonstrated high accuracy, with the Wariyatno coefficient applicable across all models. This approach provides a standardized method to assess seismic intensity, offering enhanced reliability for building design in earthquake-prone areas and serving as a valuable tool for engineers and urban planners to improve earthquake resilience in diverse seismic environments
Assessing the Effectiveness of Exclusive Truck Lanes: A Korean Expressways Case Study
Full text linkThis study investigates the operational and safety impacts of introducing exclusive truck lanes on the Gyeongbu Expressway in South Korea, addressing the necessity of such lanes due to the disparities in vehicle weight and performance between trucks and passenger cars. The study focused on the 33.2 km, one-way, four-lane Chilgok-Mulryu to Gimcheon segment, adhering to international installation criteria. Using the micro-simulation tool VISSIM, the rightmost lane was modeled as exclusive for trucks, and traffic operations and safety were analyzed under varying conditions of Level of Service (LOS). Under LOS C, the exclusive truck lane reduced the speed standard deviation (a surrogate safety measure) with minimal travel speed reduction. Conversely, under LOS A with low traffic, average travel speed declined, and speed standard deviation increased due to limited truck usage. These findings highlight the need for flexible truck lane management tailored to traffic and road conditions
An Abductive Reasoning Approach for Energy Saving in Robotic Systems
Full text linkThe velocity and acceleration commands of industrial robots are set to their maximum values to shorten the cycle time of products. However, the excessively high speed and acceleration for movements can cause unnecessary mechanical energy and electricity consumption. This paper proposes an energy-saving approach for robotic systems based on abductive reasoning. Results for different combinations of speed commands and acceleration commands are evaluated based on energy consumption and cycle time. Moreover, a well-designed abduction rule formula is used to achieve a good balance between cycle time and mechanical energy consumption of industrial robots. Simulation results of a Franka robot by ROS, Gazebo, and Moveit verify the effectiveness of the proposed approach
Quantifying the Influence of Surface Roughness on Concrete Overlay Bonding in Sulfuric Acid Environments
Full text linkThis study examines the impact of sulfuric acid on the concrete bond interface, emphasizing surface roughness variation. Three surface treatments: control surface (CS) defined as as-cast without surface preparation, drilled holes (DS), and grooved surfaces (GS). Specimens are immersed in a 5% sulfuric acid solution for 15 and 30 days. Bond performance is assessed through slant shear tests, splitting tensile tests, ultrasonic pulse velocity (UPV) measurements, mass loss evaluation, X-ray diffraction (XRD) analysis, and visual inspections of the degraded specimens. The results show that DS and GS significantly enhance shear and splitting tensile strength compared to CS. Among the treatments, GS specimens exhibited the highest shear strength and superior resistance to debonding under sulfuric acid exposure. While sulfuric acid exposure had minimal impact on UPV, roughened surfaces maintained higher UPV due to improved contact area. Visually, the GS specimens retained structural integrity after 30 days in 5% sulfuric acid, outperforming DS and CS specimens, as corroborated by XRD analysis
Optimization Method for Cross-Regional Scheduling of Retired Charging Pile Component Reuse
Full text linkWith the increasing number of decommissioned charging piles, efficient reuse of their components is essential for sustainable resource utilization and intelligent grid management. To address the challenges in recycling and scheduling retired charging pile components, this study proposes a cost-optimization approach for delivery planning in smart grid logistics. An Electric Vehicle Routing Problem with Time Windows (EDVRP-TW) model is formulated that considers vehicle capacity and time constraints. To solve it, an Improved Chicken Swarm Optimization Algorithm (ICOOT) is developed, integrating Circle chaotic mapping, spiral search strategy, and normal cloud mutation to enhance convergence speed and solution quality. Simulation experiments using real-world datasets demonstrate that the proposed method significantly reduces operation and maintenance costs, achieving up to an 11.77% cost reduction. The results validate the effectiveness and applicability of the model and algorithm in intelligent recycling and scheduling of grid materials
Study of Industrial Accident Based on In-Depth Investigation
Full text linkIndustrial accidents caused by static electricity were common for years. Beyond grounding and other static mitigation devices, plants often control environmental humidity and optimize production processes to reduce static hazards. This study aims to determine the causes and mechanism of an industrial accident and well-known unusual event related to static electricity, volatile organic compounds (VOC), and minimum ignition energy (MIE). Through instrument measurements and analysis methodology such as Hartmann tube, static electricity meter and fault tree, the cross factors are analyzed to complete the study systematically. Results reveal that anti-rust paint on the inner surfaces of machinery created insulating conditions, allowing static electricity to accumulate and discharge during material feeding. The induced static electricity subsequently releases a high discharge energy exceeding the MIE of the particle. When combined with VOC generation from an unexpected process interruption, it can lead to fire or explosion