Arabian Journal for Science and Engineering最新文献

In view of the perishable nature and complex storage requirements of certain blood products, the delivery of blood groups from blood banks to hospitals is a key aspect of the healthcare system. The centralization of blood supply facilities for economic reasons and an increase in traffic volume have led to significant delays in the use of traditional emergency vehicles. The aim of the proposed mathematical model is to minimize logistics costs by strategically positioning launch and refueling stations and assigning requests to these stations. The proposed approach employs integer binary linear programming to offer four possible scenarios that consider the flight range and supply node capacity of the drone. The study conducted a scenario-based analysis to examine the primary decision-making process for transporting blood groups and identified the optimal configuration for launching and refueling stations based on 50 group requests. The study uncovered two essential factors, NL and NR, which signify the ideal number of launching stations and the number of refueling stations situated away from the optimal launching sites. The findings offer decision-makers the precise number of stations necessary for an ideal outcome, whereas information on refueling station locations assists in resource distribution planning. Introducing refueling stations for blood supply can extend the mission range and improve coverage in nonemergency situations. Gradual implementation can prevent operational disruptions, such as station closures. This approach can also reduce delivery times and minimize delays, potentially saving lives, as refueling stations have a significant impact on the management of blood supply and logistics.

The brewing industry plays a crucial place in the global economy during manufacturing enormous amounts of wastewater generated containing excessive organic pollutants. The release of untreated brewery wastewater into water bodies causes severe consequences for the environment and human health. The primary objective of this work is to treat brewery wastewater effectively by synthesizing a novel composite material consisting of biochar, cerium oxide and titanium oxide. Biochar was synthesized from malt bagasse by pyrolysis at 360 °C for 1 h using nitrogen gas. Biochar, cerium oxide and titanium oxide were mixed with 10 M nitric acid solution maintained at 140 °C for 4 h, and the resultant mixture was cooled, filtered and dried. The D-optimal experimental design was used to identify the optimum composition of the composite. The impact of component fractions on individual factors was analysed using statistical analysis, and the empirical model was developed. At optimum condition (13.32% by weight of cerium oxide, 13.33% by weight of titanium oxide and 73.33% by weight of biochar) by the process of adsorption and photocatalysis, 66.38 ± 1.88% of chemical oxygen demand and 53.58 ± 1.45% of total dissolved solid were removed after 320 min. The desirability scores for chemical oxygen demand removal (%) and total dissolved solids removal (%) were found to be 0.9654 and 0.9488, respectively, indicating its effectiveness. Further, the kinetic investigation was performed using the Langmuir–Hinshelwood model. Thus, the optimized cerium oxide/titanium oxide/biochar composite is an efficient photocatalyst for brewery wastewater treatment.

Identifying offensive and discriminatory content, commonly referred to as hate speech, within textual data is a critical task. This study addresses the task of identifying hate speech in textual data, focusing on the challenge of selecting optimal word embedding methods and classifiers. Leveraging the Google Jigsaw dataset, the research employs explainable artificial intelligence (XAI) for hate speech detection. Following preprocessing, which includes converting text to lowercase, removing punctuation, extra whitespace, numbers, and non-ASCII characters, a thorough analysis reveals high-frequency words. The research extensively compares three-word embedding techniques—CountVectorizer, GloVe, and bidirectional encoder representations from transformers (BERT)—in combination with two machine learning models (support vector classifier and logistic regression) and four deep learning models [artificial neural network (ANN), recurrent neural network (RNN), bidirectional gated recurrent unit (Bi-GRU), bidirectional long-short term memory (Bi-LSTM)] for hate speech detection. The fusion of BERT with a bidirectional gated recurrent unit (Bi-GRU) achieved an impressive accuracy of 92%, and an ensemble of the top-performing models further improves accuracy by nearly 2%. To enhance result interpretability, the study employs XAI techniques such as local interpretable model agnostic explanations (LIME) and Shapley additive explanations (SHAP) on the top-performing ensembled model to provide insights into its predictions. The paper concludes by suggesting potential future research directions, including exploring additional embedding techniques and models, addressing dataset generalizability, improving interpretability methods, and considering computational resource constraints.

This paper addresses the analytical modeling of multiport flyback converters, which are governed by linear differential–algebraic equations. The modeling of these converters poses a challenge due to the switching between multiple such equations that govern the circuit’s behavior. The study emphasizes the importance of robust control strategies for addressing the non-idealities in flyback converters. Using MATLAB/Simulink, a dynamic model of the converter is developed. A comparison is made between a Lyapunov function-based controller, a linear proportional integrator controller, and an integral sliding mode controller. The controller consists of two main parts: a duty-ratio feedforward control unit for steady-state parameters and a Lyapunov function-based feedback control unit to handle disturbances. The feedforward control signal helps reduce the workload on the Lyapunov feedback controller. This control system ensures global exponential stability of the closed-loop system, enabling a swift transient response even under line and load disturbances. Mathematical simulations demonstrate its superior performance and stability, while experimental validations are conducted considering equivalent series resistances of each component. The proposed model and control scheme are further validated through a hardware prototype tested under various load and line disturbances. This research highlights the necessity of stress testing and performance evaluation for ensuring smooth and efficient operation of controlled multiport flyback converters across diverse conditions.

Mobile wireless sensor networks (MWSNs) have revolutionized observing and tracking. Accurately locating mobile sensor nodes remains a challenging task. The precisely identifying event source location is very important. To locate mobile sensor nodes there is a need of developing an efficient localization method. Most of the researcher have used multiple anchor nodes for localization. Therefore, in resource constraint networks reducing number of anchor nodes is an open research issue. The main idea of this work is to propose a localization method using single anchor node. To achieve this, a novel coordinated auto-localization algorithm with particle swarm optimization (PSO) is introduced to enhance localization and tracking of mobile sensor nodes. A mathematical framework has been developed which uses parallel coordinate system to identify location and PSO to track movement pattern of sensor nodes. PSO minimized localization error by refining position accuracy through iterative convergence. It achieves 10% reduction in localization error and a 25% increase in correctly localized nodes, with an overall tracking precision of 80%. Comparative analysis with different techniques like mobile anchor positioning with mobile anchor & neighbor, fish swarm optimization algorithm, DV-hop localization, and autonomous groups particle swarm optimization shows that this method reduces the average localization error to 10% and improves localization efficiency by reducing the required time by 16% compared to other techniques. A pairwise Wilcoxon rank test with a 95% confidence interval shows the proposed method’s superior performance, with a mean of 2.6321E-18 and standard deviation of 3.2705E-19, compared to other metaheuristic algorithms.

Bifacial solar PV power generation is one of the most promising and popular power generation technologies for overcoming environmental pollution and energy shortages. The phenomenon of dust deposition on bifacial PV modules greatly weakens the power generation performance and threatens safe operation. In this work, the dust deposition laws of bifacial PV modules are studied using the DEM. Besides, the influence of dust deposition and installation conditions on the power generation gain of bifacial PV modules is investigated. The results indicate that the dust concentration on windward surfaces is greater than that on leeward sides during nonfree deposition but smaller than that on upper surfaces during free deposition. The particle morphological distribution and motion behaviour differ among the left, right and top inlets under the coupled effects of deposition and separation forces. The power generation gain increases when the inclination angle, PV installation height and ground reflectivity increase. The power generation gain under overcast weather conditions is the greatest among the three kinds of typical weather conditions. When the dust deposition density varies from 0 to 0.95 g/m², the power generation gain greatly decreases by 41–65%. The research findings can be of great theoretical guidance and commercial value for cleaning technologies of bifacial PV modules.

An 8-elements dual band multiple-input multiple-output (MIMO) antenna is proposed in this article. The single element antenna consists of a defected ground structure (DGS) to obtain the first resonance at 2.4 GHz (Wi-Fi) and inset fed patch is responsible for second resonance at 3.6 GHz (Wi-MAX). As the single antenna is extended for 8-elements MIMO arrangement in a compact layout, the |S11| deteriorates which improved by engraving additional I-shaped DGS slots that enhances the impedance matching at the antenna ports. Due to closely placed antenna elements the mutual coupling at the resonant bands is poor. Hence, T- shaped stubs are introduced to achieve reduced mutual coupling between the antennas which effectively improves isolation characteristics of individual antenna elements beyond − 20 dB. A dual band Artificial Magnetic Conductor (AMC) is designed and placed below the MIMO antenna at a certain distance to enhance the gain at both the bands without perturbing the scattering parameters. The gain is improved from − 2.7 to 3.5 dB at the first resonance and from 1.7 to 3.85 dB at the second resonance. The diversity performances of MIMO are calculated in terms of Envelop Correlation Coefficient, Diversity Gain, Mean Effective Gain, Channel Capacity Loss, Total Active Reflection Coefficient, and Multiplexing Efficiency which confirm that the proposed MIMO antenna is a very potential candidate for multifunctional high speed wireless communication systems. The composite MIMO antenna with AMC is fabricated, and the antenna characteristics are measured which comply with the simulated results.

Controlling water levels in main channels by constructing side weirs can be influenced by geometric modification. Therefore, proposed geometric changes to the crest of the traditional sharp-crested weir are tested to study the hydrodynamic performance of these weirs. Triangular labyrinth side weir with and without a ramp, curved wing crest and 3 different diameters of circular crest were investigated experimentally and numerically. All the tested shapes have three inclusion angles (θ = 30, 45, and 60°), and three heights (0.1, 0.15, 0.2 m). The fluid volume (VOF) and the turbulence renormalization (RNG k-ϵ) method were selected for simulation and verifying the free surface flow along the center line and beside the weir in the main channel and measuring the velocity at certain cross sectionssections. The smaller inclusion angle between the walls (θ = 30°) performs better in discharging side flow and has a higher discharge coefficient than others. Upon comparison with a traditional labyrinth side weir, a modified side weir with a curved wing and a smaller circular crest diameter increases discharge coefficient (Cd) by about 20.7% and 6.43%, respectively, while its value reduced with the increase of crest diameter and its performance decreased about 17% by increasing the weir crest diameter from 2.5 to 5 cm. However, no improvements have been visualized for adding an upstream ramp. Moreover, in a smaller inclusion angle, the diverting streamline width of flow was obtained to be 0.81 and 0.65 times the main channel width for the modified weir with a curved wing and triangular labyrinth side weir, respectively. In addition, the highest separation zone width downstream of the parent channel for inclusion angle (30°) was observed to be about 2.5 and 1.8 times its width of angle (60°) for curved wing and traditional labyrinth weir, respectively. The discharge coefficient of the curved wing was 3 times the normal rectangular side weir coefficient.

Extended-spectrum β-lactamase (ESBL)-producing bacteria are responsible for a considerable burden of difficult to treat infections in different regions of the world. This study was conducted to assess the prevalence, characterize the isolates, and assess the antibiotic susceptibility profiles of ESBL-producing bacteria in fecal samples of outpatients in Nablus, Palestine. The design of this study was a retrospective cross-sectional design, during which 161 Gram-negative bacterial isolates were obtained from the fecal samples of 268 outpatients et al.-Rahma Center, Rafidia Surgical Hospital, and Al-Watani Hospital. These bacterial isolates were identified previously as potential ESBL-producers and then were stored at − 8 0 °C. Out of these isolates 112 (41.7%) were phenotypically confirmed to be ESBL producers and their antibiotic-resistance profile were examined using the disk diffusion method. Female patients were 2.21-times more likely to test positive for ESBL-producing bacteria compared to male patients (95% CI 1.08–4.52) among the tested isolates. Escherichia coli, Klebsiella pneumoniae, and Klebsiella oxytoca were the most prevalent ESBL-producing bacteria.

This study explores the potential of rice straw. The durability and effectiveness of polyvinyl alcohol (PVA)-treated rice straw in reinforcing silty clay were evaluated by measuring its adhesive absorption, tensile strength, and water absorption. The study found that the compressive strength of the reinforced soil first increased and then decreased with the addition of straw, with an optimal mix of 0.3%. The water stability of the reinforced soil improved significantly, with reduced disintegration rates and extended disintegration times. The germination rate, growth height, and coverage of plants in the reinforced soil also increased significantly. As the curing time increased, the compressive strength of the reinforced soil peaked at 7 days before declining. The soil reinforced with PVA-treated straw showed better compressive strength and water stability than untreated straw. The PVA treatment did not negatively affect plant germination or growth, only slightly affecting early plant promotion. The test results provide a scientific basis for the implementation of more sustainable and environmentally friendly civil engineering practices.