Journal of Engineering and Sustainable Development (JEASD)

The implementation of e-tenders in the construction industry in the era of globalization faces several challenges in many countries, including Indonesia. Maluku Island, one of Indonesia\'s main islands, is experiencing growth in the construction sector. However, it faces challenges, especially in improving the quality of contractor companies in implementing tenders. This research attempts to examine the issue of tender failure more comprehensively. This study aims to identify and analyze the dominant factors that can affect contractor failure in the tender process. The research methodology includes a literature study developed through relative importance index analysis to determine the dominant factors. The results showed that 36 factors affected contractor failure in the tender process for government construction projects in Maluku province. Factors affecting contractor failure in tendering for government projects are divided into four main categories: administrative document evaluation with an RII value of 0.65, qualification with an RII value of 0.71, technical with an RII value of 0.73, and price with an RII value of 0.73. Technical and price evaluation are the most crucial factors. This research is expected to help contractors prepare better strategies in the tender process, especially in terms of technical and price documents.

Groundwater resources in the semi-arid region south of Chott Hodna (Algeria) are increasingly threatened by depletion and salinization, threatening both human consumption and agriculture. This study assessed groundwater quality by analyzing the physicochemical parameters of 45 well samples. It used arithmetic, entropy-weighted, and fuzzy logic-based water quality indices (WQI, EWQI, and FWQI), integrated with GIS-based spatial analysis, to address data uncertainties and variability. The results revealed WQI values ranging from 59.51 to 233.68, with 64.44% of the wells classified as having poor quality due to high concentrations of sulfate, chloride, calcium, and nitrate. EWQI and FWQI showed consistent contamination patterns, with FWQI demonstrating greater accuracy by reducing extreme classifications. Spatial analysis highlighted poor water quality in the Maadher agricultural area, while better quality was observed at the eastern and western ends. Challenges included managing data variability, managing complex methodologies, and ensuring reliable spatial interpolation. The ordinary kriging technique with a spherical semivariogram model effectively identified key pollutants, including nitrate (NO₃⁻), chloride (Cl⁻), and electrical conductivity (EC), concentrated near wadis and agricultural areas.

Type-A PKW is a type of spillway with inlet and outlet keys connected in a zigzag. The survey shows that previous studies on the flow over PKW mainly focused on establishing empirical equations to calculate Cd. There is no study that meets all research needs. This shows that studies have not taken advantage of data from other studies. Meanwhile, regression Machine Learning (ML) algorithms can solve difficult problems in empirical studies. That is the ability to make maximum use of data sources, and it does not need constraints in predicting Cd values. Therefore, this study was carried out to develop a process to apply ML algorithms to the regression prediction of hydraulic characteristics (including 3 phases). In particular, the application of "Binary tree" algorithms (Decision Tree and Random Forest algorithms) is used to illustrate the study. In addition to determining the advantages of ML algorithms, a comparison was made between applying ML algorithms and using empirical equations to determine Cd values. The study shows that the Random Forest algorithm has better predicting efficiency with statistical indicators very close to the ideal point (R2 = 0.98, RMSE = 0.046, MAPE = 3.1% and MEA = 0.028).

Fear of the increase in global warming, the construction sector seeks to find an alternative to traditional concrete. This paper aims to create high-performance aerated-polystyrene lightweight concrete reinforced by micro-steel fibers and sustainable waste copper fibers that meet sustainable criteria for sound and thermal insulation, and high compressive strength for lightweight concrete that satisfies structural criteria. The methodology was carried out by preparing reference lightweight concrete, in addition to eight aerated-polystyrene lightweight concrete mixtures reinforced by micro-steel fibers and waste copper fibers with ratios of (0.3, 0.6, 0.9, and 1.2) % by concrete volume for each kind. The mechanical characteristics, dry density, thermal conductivity, ultrasonic pulse velocity, scanning electron microscopy, and acoustic impedance were investigated, and compared with the reference concrete without fibers. The final results displayed that the maximum compressive strength of A-EPSC reinforced by micro-steel fibers and waste copper fibers were 56.9 MPa and 55.9 MPa respectively with a maximum density of 1917 Kg/m3. The originality of this research was to adopt waste copper fibers as a sustainable free-cost fiber resulting from the coils of damaged electronic and electrical devices instead of micro-steel fibers to produce aerated-expanded polystyrene lightweight concrete, as an alternative to micro-steel fibers.

The ongoing pollution of water with heavy metals and the costly treatment methods have raised the need to search for an alternative treatment approach. In this work, a batch adsorption experiment using unmodified date palm seeds (UDPS) was conducted to investigate the effects of contact time, pH, adsorbent dose, and initial concentration on the removal rates of cobalt and lead from aqueous solution. Freundlich and Langmuir isotherms, as well as the kinetics of Pseudo-First- and second-order adsorption models, were also assessed. The results showed that equilibrium was reached at a 90-minute contact time, achieving the highest removal efficiencies of Co+2 and Pb+2 at pH 6, an adsorbent dose of 0.5 g, and initial Co+2 and Pb+2 concentrations of 10 mg/L, with maximum uptake potentials of 0.9 and 0.89 mg/g, respectively. Lead adsorption fitted slightly better to the Freundlich isotherm than to the Langmuir isotherm, whereas Co adsorption over the Langmuir isotherm. Regarding the kinetics of adsorption, the Pseudo-second order model better represented Co+2 and Pb+2 than the Pseudo-first-order model. FTIR results illustrate peaks at 3250 cm-1 and 3413 cm-1 for Co and Pb, respectively, corresponding to O=H stretching mode on the adsorbent surfaces.

In this work, a physical model and a Computational Fluid Dynamics simulation model in COMSOL software version 6.4 were used to simulate the two-stage transport of pollutants through porous Media. As for the physical model, it was manufactured in a laboratory to conduct practical experiments to verify two-phase flow through sandy soil. Kerosene (as a pollutant in this work) was pumped through the porous medium in different experiments at mixing ratios (100%, 85% oil to water), such that this stage represents the pollution stage. At the end of each pollution stage, the soil is washed by pumping clear water to represent the washing process. Based on standard statistical indicators, it was found that the Computational Fluid Dynamics simulation model consistently yields water-saturated ratio S1 and oil-saturated ratio S2 that are close to reality, with an acceptable error rate. This indicates the ability of Computational Fluid Dynamics models to simulate the complex two-stage pollutant transport process through porous media with high accuracy and in a short time, at lower cost and effort.

Server security is the most important thing for administrators. The server has service access via port 22, which is the most crucial point to secure because illegal access to the system is common. To overcome this problem, a firewall is implemented to act as a barrier. However, firewall users themselves are still less effective because of how it works, which closes all access without caring about anyone connected to the network. To address these issues, the port-knocking method is used in server security. The technique works by opening and closing Port 22 blocks using a firewall that detects knock attempts on network devices. Tests were conducted using port scanning, a DDoS attack, and brute-force attacks to evaluate the port-knocking method's performance in securing the server. With many tests —30, 15, and 26 times—success percentages of 0%, 90%, and 100%, the port knocking method can secure the server against unauthorized access and overcome problems caused by firewalls.

In this work, an inter-change capacitor design is developed using the particle swarm optimization technique. The PSO improves the inter-digital capacitor filter characteristics by varying capacitance geometry parameters. The capacitance value will vary greatly depending on the intended scale (in mm) for physical characteristics such as the number of fingers, finger width, and finger length. After executing the PSO algorithm for a predetermined number of iterations, the maximum capacitance value closest to the intended value is obtained. The optimization process was implemented in MATLAB and validated via full-wave simulations in HFSS at 1 GHz. The PSO algorithm achieved convergence within 50 iterations and produced capacitance values ranging from 0.48 pF to 0.92 pF, closely matching the desired targets with an average error of less than 2%. Results demonstrated that increasing the number and length of the fingers while reducing the gap between them significantly improved capacitance density. Compared with traditional trial-and-error and ANN-based approaches, the proposed PSO method reduced the design time by approximately 40% while maintaining high computational efficiency. The developed algorithm offers a simple mathematical formulation, fast convergence, and practical accuracy, making it a reliable optimization tool for high-frequency and RF/microwave circuit applications.

The most important factor in making a suitable decision in video-based AI systems is the ability to forecast future outputs from computer vision data. Deep-learning (DL) architectures are considered a promising new direction in many fields of computer vision. The researchers have recently introduced several novel video prediction (VP) models that achieve high performance. However, before building any prediction model, the basic principles of VP architectures and theories must be understood to determine the appropriate datasets and evaluation metrics. This study reviews 51 peer-reviewed papers published that cover the major VP architectures, including CNN, RNN, Autoencoder, VAE, and GAN models. The comparative analysis shows that 3D-CNN and GAN-based architectures achieve superior performance, with SSIM = 0.97 and PSNR = 40.2 dB across standard datasets such as UCF101 and KITTI. The novelty of this work lies in providing a comprehensive quantitative comparison of architectures, metrics, and datasets, and in proposing a unified taxonomy that integrates spatial-temporal deep learning models, their evolution from 2D to 3D, and probabilistic approaches. The paper's main contribution is offering a structured classification of VP architectures and datasets, serving as a reference framework for researchers to evaluate and design novel video prediction systems.

TThis study presents the modeling and simulation of a Buck-Boost converter designed for photovoltaic applications. The converter is controlled by a sliding mode control (SMC) technique, which has several advantages when utilized in DC-DC power converters. The design was simulated using MATLAB R2023a. To obtain more realistic results, the study used local solar irradiation during the summer months as the radiation incident on solar panels. The battery maintains voltage stability even during periods without solar irradiation. The results emphasized the advantages of the control method for producing a stable, long-lasting output voltage despite fluctuations in solar irradiation and uncertainty in system parameter values. Additionally, the control method reduces the tracking error to zero and speeds up the connection to the reference voltage. This work employs a second-order sliding-mode control strategy, specifically the super-twisting algorithm, to mitigate the chattering phenomenon commonly associated with first-order sliding mode. The effectiveness of the second-order sliding mode control (SOSMC) was confirmed by Fast Fourier Transform (FFT) analysis, which revealed a 75% reduction in total harmonic distortion (THD).

Fractal geometries have emerged as a promising approach for designing compact, tunable electronic components, particularly in microwave and radio-frequency circuits. This article presents a tunable filter for mobile communications that exploits a miniaturized open Ring Resonator, fabricated using the Minkowski fractal method. The fractal resulted in a 25.1% reduction in size, with an overall filter surface area of 51.84 mm2. The proposed filter was constructed on a Roger RO4003 substrate with a center frequency of 2.69 GHz, a bandwidth of 0.14 GHz, and a compact size of 0.137λg × 0.13λg. This frequency will shift according to a variable capacitor added to the resonator with a range of 2.22-2.56GHz. The insertion loss of the tuning states ranged from 0.38 to 0.58 dB, the return loss was 20.7-28.4 dB, and the fractional bandwidth was 2.25-4.6%. This proposed design shows promising performance with 7.7 GHz band rejection, high selectivity, and a compact size.

Mobile robots are now crucial elements in manufacturing sectors. A five-link robot leg is fundamental for understanding robotic leg principles, modelled by a nonlinear differential equation. Numerical solutions are used when closed-form solutions become difficult for systems with higher degrees of freedom. This study focused on controlling the robot leg to reach the desired position by combining computed torque control with a PID (Proportional Integral Derivative) controller based on the motion equation derivation. The numerical solution implemented using MATLAB includes simulation and modelling, where Simulink tools are used for simulating dynamic systems and then evaluated against the computed torque control approach. Position errors for motor 1 and motor 4 were observed for 1 second and 10 seconds. Stability was achieved in the first motor after approximately 0.75 seconds. The second motor's movement stabilized after around 0.9 seconds, with the error value between input and output for 10 seconds starting at 0.06 and 6.1, stabilizing at zero within 1 second at motors 1 and 4, respectively. The system reached stability after approximately 0.3 seconds using computed torque with PID control, with gains (Kp, Kd, and Ki) set to (9500:10:20). Numerical simulation outcomes validate the controller's effectiveness in accurately tracking diverse trajectories.

Corrosion is one of the main problems materials face, leading to degradation and loss of mechanical properties. Welding also deforms the heat-affected zone (HAZ), altering metal properties and requiring improved connections through heat treatment. Two plates from (DIN 17100 St 60-2) measuring 42×20×6 mm with a V-groove shape at a 74-degree angle were welded using shielded metal arc welding (SMAW), exposure to the heat treatment process (annealing and tempering) with different holding times of 0.5, 1, 1.5, and 2 hours subsequently, the samples were immersed in 5M HCL acidic and brine solutions. Vickers microhardness was assessed before and after immersion of the samples in the two solutions; the results were analyzed using SPSS. The results indicate that the heat treatment technique enhances hardness after corrosion has occurred. The most effective treatment for the acidic and brine solutions with the least decrease in hardness was 2-hour annealing, followed by oven cooling, resulting in corrosion rates of 1.249 for the acidic solution and 0.598 for the brine solution. Due to the importance of corrosion in the industry, this research aims to improve the corrosion resistance and hardness of welded low-carbon steel.

Crash prediction is a suitable alternative to an unreliable accident record for the purpose of conducting traffic safety studies. This paper's goal is to find the impact of relative delay rate on the rate of crashes at arterial roads in the city of Karbala. The study area is Fatima Al-Zahraa Street, which is an urban arterial with a length of 1.40 km. The traffic volume data had been calculated manually using video camera recordings for five days (Jan 25th to 29th, 2023) with an average of 16 hours per day. A simulation model was run using PTV VISSIM software for the purpose of calculating the relative delay rate and service level. The crash rate was predicted using the Highway Safety Manual (HSM). Through the use of linear regression analysis, it was possible to determine a linear link between the relative delay rate and the rate of crashes that occurred during peak hours, and this relationship is consistent with previous literature and research.

Monitoring water quality is essential for identifying current issues and changes in water sources over time. Conventional water quality monitoring methods still rely on collecting on-site samples for later examination in environmental labs. The development of open-source, inexpensive hardware based on the Arduino platform has enabled the creation of low-cost, portable, and site-specific measurement platforms. As a result, the project's objective is to develop a biosensor device (BSD) using an Arduino Uno and sensors. Turbidity, pH, temperature, and electrical conductivity are the sensors that have been interfaced with it. They are all electrically linked to the mother Arduino drum, and each sensor has been programmed to display its measured values. Following the individual calibration of each sensor, we ensured that the sensor data were consistent with one another. Water contaminated with Escherichia coli was diluted to ensure the device's precision. Furthermore, tap water, distilled water, and Aquafina water were compared to the standard records for each type. The correlation between the results suggests that the device measurements were precise.