In road freight transport, empty return trips by trucks after deliveries are a significant waste for businesses and increase transportation costs. To address this issue, this study proposes an optimization model using Mixed-Integer Linear Programming (MILP) to optimize the allocation of orders to empty return trucks. The research aims to both reduce operating costs and maximize revenue from deliveries, thereby improving the operational efficiency of the transport business. Experimental results from scenario analysis, sensitivity analysis, and analysis of variance show that the proposed model effectively allocates all orders, improving vehicle utilization efficiency and profitability for the business.

Metal Injection Molding (MIM) combines plastic injection molding with powder metallurgy to produce high-strength, complex metal components. While mold design is critical to production quality, conventional 2D cooling channels often cause non-uniform temperature distribution, leading to overheating and structural defects. This study proposes an integrated manufacturing approach involving mold flow analysis, 3D conformal cooling channel design, experiment, and evaluates the effect of the new design. Through experimental injection molding tests, the feasibility of this integrated technology was validated. Results demonstrate that the optimized 3D conformal cooling system significantly enhances cooling efficiency and mold temperature uniformity. Consequently, this approach not only improves product quality and reduces defects but also shortens the molding cycle, substantially increasing overall production productivity.

This study presents an integrated evaluation of the mechanical strength and dynamic characteristics of a leaf spring suspension system for the Toyota Land Cruiser HJ60LG-MZ SUV by combining the Finite Element Method (FEM) and a quarter-car modeling approach. FEM results indicate that the maximum Von Mises stress reaches 437.3 MPa at the spring eye region, while the maximum displacement of 4.39 mm occurs at the center of the leaf spring. The safety factor ranges from 2.7 to 3.9, confirming that the structure operates within the elastic deformation regime. Dynamic simulations showed that the root mean square acceleration (aRMS) varies from 0.73 m/s2 to 0.96 m/s², corresponding to ride comfort levels from “fairly uncomfortable” to “uncomfortable” according to the ISO 2631-1:1997 standard. The study proposes a novel integrated approach that enables a comprehensive assessment of the suspension system from structural durability to operational performance. The findings provide a significant scientific basis for quantifying dynamic behavior and optimizing the design of leaf spring suspension systems in SUVs and light-duty trucks.

The welding experiments were worked on the vertical milling machine MANFORD. The tool rotation speed of 1.875rpm and travel speed of 20mm/min was used in both the welding conditions. Defects associated with friction stir welding (FSW) of two steel grades including Aluminum and Copper were investigated. This study attempts to give an overview of the key factors related to the formation of defects in welding methods commonly used with aluminium and copper alloys by experimental method. Tool rotary speed, target depth and tool traverse speed govern the peak temperature generated during friction stir welding and the time required to weld the material are very important. The investigated model successfully predicted subsurface tunnel defects, surface tunnels, excessive flash formations, and exit hole of pin. And also the strength of the weld joint produced with defect in FSW was superior to that of the Laser weld. The maximum tensile test values of 21.5 MPa and 15.8 MPa are reported at the weld zone for FSW and Laser, respectively.

Can Tho City, the central hub of the Mekong Delta, is characterized by a distinctive “water-based urban identity” shaped by the Hau River, canals, and orchard gardens. Amid rapid urbanization and climate change, Can Tho’s urban landscape experiences multiple pressures, including flooding, riverbank erosion, reduction of green space, and the gradual loss of cultural identity. The study aims to analyze three main dimensions of Can Tho’s landscape: (i) natural – hydrological ecosystems and alluvial soil; (ii) built – urban morphology, infrastructure, and vernacular architecture; (iii) socio-cultural – a lifestyle closely tied to waterways. Grounded in landscape ecology theory and informed by international ecological urban models, the study proposes sustainable ecological orientations including conserving the water-based identity, enhancing blue–green infrastructure, managing flood and erosion risks, applying digital technologies, and fostering community participation, aiming to guide Can Tho towards becoming a resilient, climate-adaptive “water-based ecological city”.

This study compares Checkerboard and ChArUco for camera calibration in laser vision systems for industrial welding robots, to evaluate their performance and potential for fast recalibration toward real-time use. A unified evaluation framework was developed based on the pinhole camera model with Brown–Conrady distortion, using the same camera–lens setup, board poses, and image acquisition conditions, including three noisy scenarios (glare and partial occlusion). The evaluation metrics include RMS reprojection error, detection speed, and detection success rate. The results show that the estimated intrinsic matrix and distortion coefficients are equivalent, with RMS errors below 0.2 px for both methods. ChArUco outperforms Checkerboard in detection robustness under noisy conditions, whereas Checkerboard achieves faster detection (» 9.5 ms/image versus » 19.5 ms/image) but fails in noisy images. These results indicated that ChArUco is more suitable for fast recalibration scenarios requiring high detection robustness in noisy industrial environments.

This paper presents a case study on the improvement of soft ground using prefabricated vertical drains (PVD) combined with vacuum preloading and surcharge loading at Long Thanh Industrial Park, Dong Nai, Vietnam. The effectiveness of the treatment was evaluated using field monitoring data, analytical analysis, and numerical simulation. The results indicated that the geotechnical properties were significantly improved after treatment. Specifically, the natural water content decreased by 25.5%, and the void ratio decreased by 29.2%. In comparison, the undrained shear strength and preconsolidation pressure increased by 20.1% and 26.0%, respectively, indicating that the soil became denser and its bearing capacity was significantly enhanced. Field monitoring data show that the ground reached approximately 90% degree of consolidation after about 70 days when applying a surcharge load with an overload ratio of about 1.2 times the design service load. The results also showed that when the overload ratio is increased to about 1.4 times, the time required to reach the target degree of consolidation can be reduced by approximately 15%, while the total settlement changes insignificantly.

This study evaluates the feasibility of using a C11708MA mini-spectrometer for the non-destructive prediction of melon sweetness (°Brix). The spectrometer was integrated with an STM32 microcontroller to acquire and transmit spectral data to a computer for machine-learning-based prediction. Spectra in the range of 640–1050 nm were collected from 50 melons using a multi-point sampling strategy. Preprocessing techniques, including Savitzky–Golay filtering, standard normal variate, multiplicative scatter correction, and their combinations, were applied before developing partial least squares regression (PLS) and support vector regression (SVR) models. SVR generally outperformed PLS, achieving RPD values of about 1.7–1.8, indicating acceptable prediction capability for rapid screening. These results are comparable to previous studies using mini-spectrometers and highlight the potential for developing low-cost handheld spectroscopic devices for rapid fruit quality assessment.

Electron Channeling Contrast Imaging (ECCI) was applied to elucidate the mechanism of discontinuous crack propagation in a single-crystalline Fe–3 wt%Si alloy subjected to tensile loading in air. Subsurface observations revealed symmetrically activated slip systems and regularly spaced slip bands emitted from the crack tip. Intersecting slip bands and dislocation cell structures were identified ahead of the crack tip, forming low-energy dislocation structures that locally hinder crack advance. The spacing of these dislocation features was found to coincide with the striation spacing observed on the fracture surface, indicating that crack growth increments are governed by intrinsic dislocation arrangements rather than global crack length. A microstructure-controlled mechanism involving cyclic dislocation emission, work hardening, crack advance, and arrest is proposed.

This study focuses on analyzing the effects of process parameters, including laser power (P), scanning speed (v), and pulse frequency (f) on the surface roughness of 6061 aluminum alloy during pulsed Nd:YAG laser polishing. A full experimental design was conducted with 27 combinations, evaluating surface roughness in two directions (Rax and Ray). Analysis of variance (ANOVA) indicates that Rax is predominantly influenced by scanning speed, while Ray depends primarily on laser power. Notably, the P–v interaction effect also showed statistical significance regarding surface roughness. Furthermore, two separate Multilayer Perceptron (MLP) models were developed to predict Rax and Ray. The testing results demonstrate high prediction accuracy, with R² values of 0.964 for Rax and 0.961 for Ray. These findings provide a scientific foundation for optimizing laser polishing parameters on 6061 aluminum alloy.

This study evaluates the performance and emissions of the D229-4 engine fueled with Biodiesel derived from waste coffee grounds. Fuel blends were formulated by mixing Diesel and Biodiesel at 0%, 20%, 40%, and 100%. Simulation results at 1,200 – 2,400 rpm show that increasing the Biodiesel ratio slightly reduces engine efficiency, with power and torque decreasing by 2 – 5% for B20 and B40, and 15 – 20% for B100; while brake specific fuel consumption rises by 2 – 4% for B20 and B40, and 20 – 25% for B100. Regarding emissions, B20, B40, and B100 reduce Particulates Matter (PM), , and  by approximately 70 – 79%, 65 – 85%, and 12 – 40%, respectively. NOₓ increases by 3 – 10% for B20 and B40, but decreases by 45 – 65% for B100. These results demonstrated that coffee-ground Biodiesel is a promising renewable fuel that does not compete with food resources and can substantially mitigate environmental pollution.

This paper presents a nonlinear model predictive control (NMPC) scheme for differential-drive mobile robots to achieve trajectory tracking and dynamic obstacle avoidance. The nonlinear predictive framework effectively addresses robot model nonlinearities, enhancing trajectory accuracy and navigation stability. By integrating input constraints on linear velocity and angular velocity, the method ensures smoother and more reliable motion. Safety distance constraints are embedded into the NMPC optimization to guarantee collision-free navigation in dynamic environments. Simulations on a 3D robot model in Gazebo under ROS, combined with experiments on a real two-wheeled robot, are conducted and compared with the Dynamic Window Approach (DWA). Results confirm that NMPC outperforms DWA in trajectory tracking accuracy, motion smoothness, and obstacle avoidance effectiveness.

This study presents the design and feasibility evaluation of an automated NIR interactance spectral acquisition module for mandarin sweetness assessment. The system integrates a clamping–rotation mechanism, a translational probe with a ring light source, and a dark chamber to enable automated measurements at multiple fruit regions. Compared with manual acquisition, the average measurement time was reduced from ~40 s to 17.7 s per fruit, corresponding to a 55.75% reduction, while spectral stability was improved. Sweetness prediction models developed from 300 averaged spectra of 75 mandarins achieved a maximum RPD of 1.65, indicating the system’s potential for rapid and non-destructive fruit quality evaluation.

This study develops and simulates a dynamic model of an electric vehicle equipped with an electronic differential system (EDS) that independently controls two DC motors on the rear axle, replacing the conventional mechanical differential. The model is derived from the Newton-Euler equations, coupled with a nonlinear Pacejka tire model and a DC motor model. A PI controller is integrated into the EDS to compute and distribute traction forces between the driven wheels. MATLAB/Simulink simulations under various operating conditions demonstrate that the longitudinal velocity closely tracks the reference; torque is dynamically and appropriately distributed to each wheel during steering maneuvers; and both the vehicle sideslip angle and trajectory tracking error are consistently maintained at low levels, ensuring stable and safe operation. These results demonstrate the feasibility and effectiveness of the proposed electronic differential structure, providing a solid foundation for developing more advanced control algorithms.

This study aims to evaluate the influence of cutting parameters, including cutting speed (V), feed rate (S), and depth of cut (t), on the surface roughness of concave parts when milling SKD11 steel with a ball-end mill on a 3-axis CNC machine. Using a full experimental design and regression analysis in Minitab, an experimental regression model describing the relationship between surface roughness and cutting parameters was developed. The surface roughness values for concave parts, after machining, were determined from 0.468 µm to 3.054 µm, corresponding to cutting speeds from 75 ÷ 85 m/min, feed rates from 800 ÷ 1000 mm/min, and depths of cut from 0.1 ÷ 0.3 mm. The resulting regression model showed that depth of cut and feed rate were two factors that significantly influence surface roughness of the workpiece after machining. The model can be used to predict surface roughness during machining and to select appropriate cutting parameters for machining concave surfaces on SKD11 steel.

In recent years, lotus seed products have yielded high economic efficiency, promoted sustainable agriculture, and contributed to improving life in the Mekong Delta. Equipment and machinery for processing fresh lotus seeds have become essential to increase productivity. Classifying fresh lotus seeds is one of the steps in the processing process, supporting the separation of the fresh lotus seeds into groups of similar sizes. This can support the process of cutting and peeling the green shell of lotus seeds, as different sizes of lotus seeds are cut with various depths, significantly reducing the risk of lotus seeds turning brown due to the lotus flesh being deeply cut. In this study, a fresh lotus seed classifying device that applied the principle of a rotating cage with a capacity of 20 kg/hr was researched, designed, and manufactured to classify the fresh lotus seeds of different sizes. As a result, the fresh lotus seeds can be classified into 4 various types based on their diameter with an accuracy of over 95%.

In this study, Al(III), Ni(II), and Mg(II) from the HCl synthetic solution of spent steam reforming catalysts were recovered by selective precipitation. The influence of factors on metal recovery efficiency was also investigated. The results showed that > 99.0% of Al(III) was precipitated as γ-Al₂O₃ with a purity of 95.5% using Na₂CO₃ under the following conditions: pH 6.8, 80 °C, 30 min, followed by calcination at 500 °C for 2 hour. Subsequently, >99.9% of Ni(II) from the filtrate containing Mg(II) was precipitated to Ni(OH)2·NiOOH by NaClO at pH 8, a Ni(II):NaClO molar ratio of 1:2, 30 minutes, 30°C, and the purity of the precipitate was 98.5%. Meanwhile, the precipitation efficiency of NiS was low, reaching

This paper presents a contact force control approach for a three-degree-of-freedom robotic manipulator based on impedance control. The proposed method combines a PID-based position controller to achieve accurate end-effector motion with a force control strategy that uses force sensor feedback to regulate contact forces during interaction. The resulting control structure improves interaction stability and is well suited for surface processing applications such as grinding and polishing. The effectiveness of the proposed approach is evaluated through MATLAB/Simulink simulations using a three-dimensional model implemented in the Simscape environment, as well as experimental tests conducted on a physical robotic manipulator. The force control performance is assessed using the root mean square error (RMSE) between the desired and measured contact forces. Simulation results show that the RMSE is below 0.25 N, while the experimental results range from approximately 1.0 N to 1.25 N, indicating stable operation and reliable force tracking under real operating conditions.

In the context of increasing competition in the mechanical and automotive industry, optimizing production processes and minimizing waste is essential for the sustainable development of enterprises. This study analyzes production waste and proposes improvement solutions using Value Stream Mapping (VSM), a key tool of Lean Manufacturing. The research was conducted at a truck body manufacturing company. The results indicate that several types of waste still exist in the production process, including waiting time, unnecessary transportation, work-in-process inventory, and imbalance among production stages. After implementing improvement solutions, the lead time decreased from 9.900 minutes to 7.782 minutes (a reduction of 21,4%), while the maximum cycle time decreased from 1.124 minutes to 565 minutes (a reduction of 49,7%), thereby significantly improving production efficiency. This study provides practical evidence for the application of Lean Manufacturing in mechanical enterprises in the Mekong Delta region.

This study experimentally compares the starting characteristics and power generation performance of four small-scale vertical axis wind turbine configurations, including an improved Aeroleaf rotor, a twisted Savonius rotor, a Darrieus rotor, and SH-200R rotor under low wind speed conditions. All models were designed with an identical swept area (approximately 0.305 m²) and were coupled to the same generator system to ensure objective evaluation. Experiments were conducted at three low wind levels, and the parameters, including cut-in wind speed, rotational speed, and output voltage, were averaged from four repeated measurements. The results show that the improved Aeroleaf rotor exhibits the lowest average cut-in wind speed (2.54 m/s) and achieves the highest rotational speed (164.75 RPM) and output voltage (16.1 V). These differences are attributed to the hybrid aerodynamic characteristics of the Aeroleaf blade, which combine drag and lift effects, thereby enhancing self-starting capability and power generation performance in low wind conditions.

In the soft soil conditions of Vinh Long Province, precast prestressed spun concrete piles are widely used for the foundations of heavy-load structures. However, significant discrepancies among pile bearing capacity values obtained from analytical methods, static load tests, and current design standards have made it difficult to select appropriate design capacities. This study focuses on evaluating the ultimate bearing capacity of prestressed spun concrete piles with a diameter of 0,5 m and a length of 47 m under the geological conditions of Long Chau Ward, Vinh Long Province. The applied approaches include analytical calculations in accordance with TCVN 10304:2025, interpretation of in-situ static pile load test results, and numerical simulations using PLAXIS 3D with staged construction procedures. The results enable a comprehensive comparison and assessment of the applicability of each method in estimating the ultimate pile bearing capacity. Based on the findings, a suitable approach for determining the ultimate bearing capacity of pileBs under local geological conditions is proposed, thereby improving safety and economic efficiency in pile foundation design.

In this study, bimetallic CuZn-ZIFs material was synthesized via a solvothermal method and evaluated for its ability to remove malachite green from aqueous solutions. The structural, morphological, and physicochemical properties of CuZn-ZIFs were characterized using PXRD, FT-IR, SEM, TGA, BET, and EDX analyses. CuZn-ZIFs exhibited a characteristic polyhedral morphology, high thermal stability up to approximately 350°C, and a specific surface area of 1286 m2/g. The removal efficiency of malachite green reached 98.7% when 0.3 g/L CuZn-ZIFs and 0.1 g/L potassium peroxydisulfate were applied within 20 minutes at room temperature. After four consecutive reuse cycles, the material maintained a removal efficiency above 85%, indicating effective recovery and reuse potential.

Decree 64/2010/ND-CP of the Government on urban tree management creates a general legal framework and initial decentralization of management, but still has some limitations such as: Lack of specific procedures and technical standards leading to lack of synchronization in management,... and lack of a mechanism to mobilize social resources to develop the urban tree system. Circular 12/2024/TT-BXD of the Ministry of Construction stipulates the principles of determining and managing costs of public services for urban lighting and urban trees, but there are still some shortcomings such as: Reference norms causing difficulties in practical application, lack of synchronization and transparency causing waste of resources, not fully reflecting the practical development of these services. This paper limits the research on solutions to determine highly applicable standards, consistent in calculation methods, towards a reasonable system of standards for green tree planting costs, to improve the efficiency of urban green tree cost management in Can Tho.

Okra is a highly nutritious vegetable rich in vitamins, minerals, and bioactive compounds that are beneficial to human health. However, due to its high moisture content and high respiration rate, okra is highly perishable after harvest, resulting in rapid deterioration of sensory quality and nutritional value. The application of appropriate preservation methods, particularly edible coatings, is essential to extend shelf life and maintain product quality. Accordingly, this study was conducted to evaluate the effects of different edible coatings (control, 1% CMC, and 2% sodium alginate) on the quality of fresh okra during storage. The results indicated that the application of a 1% CMC coating effectively preserved color and minimized nutrient loss, with vitamin C (15.34 ± 6.03 mg/100 g DW) and chlorophyll (15.60 ± 2.35 mg/g DW) contents remaining at relatively high levels after 14 days of storage at 13 ± 1 °C.

Welded joints are among the most failure-prone regions in mechanical structures, particularly as the weld surface is directly exposed to environmental conditions. Manual inspection of large volumes of welds is prone to human error. This study proposes an approach for anomaly detection and localization on weld surface images within regions of interest (ROI) using two deep learning models: FastFlow and PatchCore-Lite. A total of 5,451 images were standardized to a resolution of 512×512 pixels. Each image includes a weld mask, while anomalous samples are additionally annotated with defect masks serving as ground truth. Experimental results indicate that PatchCore-Lite achieves superior performance in anomaly detection at the image level, with an AUROC of 0.8978. In contrast, FastFlow demonstrates better localization performance within the ROI, achieving an FPR of 0.01875, a Dice score of 0.04175, and an IoU of 0.02161.These findings provide a foundation for developing automated weld surface defect inspection systems under conditions of limited defect data, which is a common constraint in industrial applications.

Maintenance of mobile telecommunication towers is essential for ensuring the continuity and quality of telecommunication infrastructure. This paper presents a systematic review of maintenance methods for telecommunication towers, conducted in accordance with the PRISMA 2020 guidelines. Relevant literature was retrieved from IEEE Xplore, ScienceDirect, SpringerLink, and Google Scholar, covering the period 2015–2025. Following a structured screening process, [N=42] studies were selected and classified into four categories: manual inspection, structural health monitoring, unmanned aerial vehicle (UAV)-based inspection, and deep learning-based defect detection. The findings indicate that conventional methods remain limited in efficiency and scalability, whereas the integration of UAVs with artificial intelligence demonstrates clear potential for automated detection of corrosion, coating degradation, and structural deformation. The review also identifies key research gaps concerning domain-specific datasets, the regulatory framework for UAV operations in Vietnam, and real-world deployment, thereby outlining directions for future research.

This paper presents a sliding mode control design for a three-dimensional container crane system considering wheel–rail friction effects. A nonlinear dynamic model of the underactuated crane is derived using the Lagrange formulation, capturing the coupling between translational motions and payload swing dynamics. To represent practical operating conditions, the friction force is described by a modified Coulomb–viscous model, which provides a continuous friction characteristic in the low-velocity region and accounts for parameter uncertainties within ±10%. Based on the reduced-order model, a sliding mode control law is developed to directly compensate bounded friction uncertainties and equivalent disturbances. To alleviate the chattering phenomenon inherent in conventional sliding mode control, the discontinuous sign function is replaced by a hyperbolic tangent function, resulting in smoother control signals suitable for implementation and yielding practical stability in a small neighborhood of the sliding surface. Lyapunov-based analysis is provided to establish closed-loop stability and robustness. MATLAB/Simulink simulations demonstrate that the proposed method achieves a convergence time of approximately 10–13 s, limits the payload swing angles to below 3°, and maintains robust trajectory tracking under ±5% parameter disturbances. The results confirm the effectiveness and practical potential of the proposed controller for three-dimensional crane systems operating under friction and model uncertainties.

To meet the demand for precise micro-hole drilling on thin steel in microelectronics and biomedicine. This study investigates the effects of laser power (P), pulse frequency (f), and scanning speed (v) on the quality of 400 μm micro-holes drilled in 0,1 mm thick AISI 304 stainless steel. Based on 27 experimental sets, results indicate that the taper angle fluctuated between 5,2o and 13,7o, while the diameter deviation from the design specifications ranged from 1 to 15 μm. ANOVA analysis revealed a distinctly non-linear relationship between the drilling parameters (power, frequency, and speed) and the quality indicators (diameter deviation and taper). Each parameter exhibited a unique contribution and mechanism of action on the individual geometric characteristics of the laser-drilled holes. These findings not only provide a scientific foundation for process optimization but also demonstrate the potential to replace specialized, high-cost methods in the manufacturing of micro-components for electronics and biomedical applications.

This study proposes an intelligent security system designed to overcome the limitations of traditional frameworks while enhancing threat detection and early warning capabilities. The proposed architecture integrates key components, including Internet of Things (IoT) modules, surveillance cameras, object recognition algorithms, RFID technology for multi-zone access control, and management software to streamline security operations and monitoring. Experimental results demonstrate that the system significantly improves the comprehensiveness of security protocols of real-time environments, offering enhanced access control efficiency and timely alerts upon incident occurrence. This confirms the transformative potential of IoT and Artificial Intelligence (AI) in the security sector, providing a foundation for the development of more progressive security solutions in the future.

In this study, biochar derived from Thai jackfruit peel was prepared through pyrolysis and subsequently modified to evaluate its adsorption performance toward Indigo Carmine (IC) in simulated wastewater. The structural characteristics of the modified biochar (Bio-P500) were analyzed using advanced techniques, including FT-IR, SEM, EDX, and nitrogen adsorption measurements. The results revealed that Bio-P500 exhibits a high specific surface area (1113.8 m2.g-1), a large pore volume (1,2 cm3.g-1). Bio-P500 achieved a maximum IC removal efficiency of 99.1%, with an adsorption capacity of 39.7 mg.g-1 after 60 minutes at room temperature. The Langmuir isotherm adsorption model best described the adsorption equilibrium with R2 = 0.994. Furthermore, the adsorption kinetic results showed that the adsorption process was beneficial for IC removal controlled by the pseudo-first-order (PFO) model. In addition, the material is also reusable with an adsorption efficiency of over 90% after three cycles, showing high potential in the application of dye treatment in industrial wastewater, contributing to environmental protection as well as industrial development associated with green chemistry.