Arabian Journal for Science and Engineering最新文献

{"title":"Nucleation of Bioactive Hydroxyapatite on Polydopamine Coating Three-Dimensional Printed Poly (Lactic Acid) Macro-Porous Scaffold for Bone Grafting Application","authors":"Ala Al-Dubai, Mohammed Alhamed, Nurizzati Mohd Daud, Hak Yong Kim, Muhammad Mahadi Abdul Jamil, Syafiqah Saidin","doi":"10.1007/s13369-024-09509-1","DOIUrl":"https://doi.org/10.1007/s13369-024-09509-1","url":null,"abstract":"<p>The integration of poly (lactic acid) (PLA) in 3D printing has revolutionized the biomaterial engineering. This synergy between PLA and 3D printing holds immense potential for advancing tissue engineering and human health. The purpose of this study is to evaluate nucleated hydroxyapatite (HA) on polydopamine (PDA)-coated 3D printed PLA scaffolds, focusing on chemical composition, morphology, crystallinity, wettability, porosity, and biocompatibility via MTT assay. 3D printed PLA scaffolds were designed using computer-aided software (CAD). These scaffolds were immersed in a dopamine salt solution for 24 h to create a thin PDA layer and then placed in Simulated Body Fluid (SBF) for 5 days to stimulate apatite layer formation, observed through FE-SEM. PLA scaffolds had smooth surfaces, while PLA–PDA surfaces were different, and PLA–PDA–HA scaffolds revealed more homogeneous distribution of HA. PLA scaffolds had higher porosity (88%) and hydrophobic, whereas PLA–PDA scaffolds became hydrophilic due to the introduced amine and hydroxyl groups from the PDA coating. PLA–PDA scaffolds were amorphous, indicating reduced crystallinity, while PLA–PDA–HA displayed crystalline structure. The PLA–PDA–HA scaffolds declined most in weight loss (0.7%) due to the hydrolytic degradation of HA. In contrast the PLA–PDA scaffolds were the least degraded, with steady degradation trend lasting up to the 21st day of immersion. The PLA–PDA–HA scaffolds, with HA nucleation, exhibited the highest cell viability (145%) on day 7, emphasizing the crucial role of robust cell viability in tissue engineering. In conclusion, the PLA–PDA–HA scaffold was the most robust option due to its enhanced adhesion, biocompatibility, and potential protection against degradation.</p>","PeriodicalId":8109,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"37 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142194155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical Analysis of the Influence of Trapezoidal Geometry in Phase Change Material Containers on Temperature Distribution in Concentrated Photovoltaic Panel Cooling","authors":"Korhan Ökten, Mehmet Balta, Burak Kurşun","doi":"10.1007/s13369-024-09527-z","DOIUrl":"https://doi.org/10.1007/s13369-024-09527-z","url":null,"abstract":"<p>In concentrated photovoltaic (PV) panels, the amount of waste heat generated increases due to the higher incident radiation on the panel surface, leading to a decrease in PV panel efficiency. Therefore, PV-PCM (Phase Change Material) integration is a widely used passive method to reduce and stabilize PV panel temperature. However, particularly in angled PV panels, the movement of the PCM within its container can cause uneven temperature distributions on the PV panel surface. To address this issue, this study employs a trapezoidal geometry to increase the amount of PCM and the surface area exposed to the environment in the regions where the molten PCM accumulates. Furthermore, the effects of PCM area and heat transfer coefficient to the environment on the temperature distribution of the PV panel for different trapezoidal geometries (different tilt angles and the ratio of side surfaces) were investigated. A numerical model was developed for these investigations, and this model was validated with experimental work found in the literature. The results showed that the surface temperature decreased by 5–21 K and the surface temperature uniformity improved between 10 and 44% depending on the parameter change with the use of trapezoidal geometry.</p>","PeriodicalId":8109,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"62 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142194158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling Efficient Partial Charging Schedules for Wireless Rechargeable Sensor Networks Using Novel Aquila Optimization Approach","authors":"Sk Md Abidar Rahaman, Md Azharuddin, Mohammad Shameem","doi":"10.1007/s13369-024-09473-w","DOIUrl":"https://doi.org/10.1007/s13369-024-09473-w","url":null,"abstract":"<p>There are many potential uses for wireless rechargeable sensor networks (WRSNs), making them an important and exciting field of research. Extending the network’s lifespan is challenging because of the sensors’ short battery life. However, developing appropriate charging schedules for mobile charging vehicles (MCVs) is a difficult problem. These charging schedule designs can have an influence on WRSNs overall consumption of energy and lifetime. We address the challenge of minimizing travel energy for MCVs in WRSNs. Our proposed solution includes a priority-based charging schedule that balances MCV travel time and charging time effectively. Additionally, we offer a method for selecting charging energy levels to conduct partial charges aiming to prolong the network’s lifespan. We have also incorporated the remaining lifetime of sensor nodes (SNs) as a crucial factor in mitigating the occurrence of dead SNs in the network. In this article, we partition the requested SNs into several partitions and assign an MCV to each region using the Aquila Optimization meta-heuristic approach. A heuristic-based partial charging method is proposed. We compare the outcome of our proposed technique with several other existing algorithms. The outcomes of the simulation indicate that our suggested method performs better than the others. Additionally, an analysis of variance and a post hoc analysis are carried out. We demonstrate, through comprehensive simulations and hypothesis testing, that the proposed scheme increases the number of replenished sensor nodes up to 36.36% and the charging utility up to 97.82% while decreasing the charging time and the number of dead sensor nodes up to 54.16% and 85.86%, respectively.</p>","PeriodicalId":8109,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"13 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142194157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Online Dynamic Point Separation and Removal SLAM Frameworks for Dynamic Environments","authors":"Hongwei Zhu, Guobao Zhang, Yongming Huang","doi":"10.1007/s13369-024-09422-7","DOIUrl":"https://doi.org/10.1007/s13369-024-09422-7","url":null,"abstract":"<p>Dynamic objects in the environment can compromise map quality and, in severe cases, lead to robot localization failures. To address this issue, this paper proposes a simultaneous localization and mapping (SLAM) framework with dynamic point removal capabilities, which incrementally filters out dynamic points during the mapping process to enhance map accuracy and localization reliability. The framework consists of two main modules: the SLAM module and the dynamic point removal module. The SLAM module, based on Fast-LIO, incorporates novel loop detection and filtering algorithms to improve long-term mapping accuracy, while the dynamic point removal module optimizes the map by eliminating dynamic points. The dynamic point removal module employs three key methods. Firstly, to enhance dynamic point identification accuracy and minimize misclassification, a novel multi-resolution height map method is introduced. This method effectively segments static ground points and directly preserves them as static points. Secondly, a visibility-based approach is employed to maximize the removal of suspected dynamic points by comparing range differences between the local map and the current frame. Finally, K-nearest neighbors and principal component analysis methods are utilized to compare feature vectors between clusters, facilitating the recovery of static points that may have been erroneously removed. The proposed method is validated via public datasets and real-world scenarios, demonstrating significant improvements in dynamic point recognition as well as in localization and mapping accuracy compared to other state-of-the-art methods.</p>","PeriodicalId":8109,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"85 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142194152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging large language models through natural language processing to provide interpretable machine learning predictions of mental deterioration in real time","authors":"Francisco de Arriba-Pérez, Silvia García-Méndez","doi":"10.1007/s13369-024-09508-2","DOIUrl":"https://doi.org/10.1007/s13369-024-09508-2","url":null,"abstract":"<p>Based on official estimates, 50 million people worldwide are affected by dementia, and this number increases by 10 million new patients every year. Without a cure, clinical prognostication and early intervention represent the most effective ways to delay its progression. To this end, artificial intelligence and computational linguistics can be exploited for natural language analysis, personalized assessment, monitoring, and treatment. However, traditional approaches need more semantic knowledge management and explicability capabilities. Moreover, using large language models (<span>llm</span>s) for cognitive decline diagnosis is still scarce, even though these models represent the most advanced way for clinical–patient communication using intelligent systems. Consequently, we leverage an <span>llm</span> using the latest natural language processing (<span>nlp</span>) techniques in a chatbot solution to provide interpretable machine learning prediction of cognitive decline in real-time. Linguistic-conceptual features are exploited for appropriate natural language analysis. Through explainability, we aim to fight potential biases of the models and improve their potential to help clinical workers in their diagnosis decisions. More in detail, the proposed pipeline is composed of (i) data extraction employing <span>nlp</span>-based prompt engineering; (ii) stream-based data processing including feature engineering, analysis, and selection; (iii) real-time classification; and (iv) the explainability dashboard to provide visual and natural language descriptions of the prediction outcome. Classification results exceed 80% in all evaluation metrics, with a recall value for the mental deterioration class about 85%. To sum up, we contribute with an affordable, flexible, non-invasive, personalized diagnostic system to this work.</p>","PeriodicalId":8109,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"11 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142194131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimized Design of Floating Stone Columns for Enhanced Long-term Settlement Performance of Soft Soils","authors":"Khaoula Chenche, Meriem Fakhreddine Bouali, Jorge Castro","doi":"10.1007/s13369-024-09443-2","DOIUrl":"https://doi.org/10.1007/s13369-024-09443-2","url":null,"abstract":"<p>In two-dimensional axial symmetry finite element analyses, compressible clayey deposits improved by a large group of floating stone columns were performed using the unit cell idealization. The primary focus of this study is to assess the efficiency of floating stone columns in enhancing the consolidation rate of low-permeable soils. Additionally, it aims to evaluate the long-term stability of constructions built along marine coastal areas. To this end, two real case studies were investigated; the Béjaïa and Algiers Mediterranean harbors. Various geometric variables, pertaining to the design of floating stone columns, have been considered to analyze their effect in impacting the consolidation process and the long-term behavior emphasizing their fundamental importance in the design. Besides, a thorough comparison between the design in both short-term and long-term conditions, satisfying the admissible settlement, has been made, ultimately resulting in the optimized design selected. The results also indicate that increasing both the area improvement ratio and the floating column length leads to a speeding up of the consolidation rate. However, in contrast to the area substitution ratio, the column length has comparatively lesser importance in terms of reducing the settlement. Importantly, it is demonstrated that the design of floating stone columns for long-term conditions is significantly distinct from that for short-term conditions, requiring an approximate 40% increase in the area improvement ratio as designs based on the immediate settlement may not align with improved soft soil long-term behavior. Finally, the study reveals that the applied load ultimately governs the design of floating stone columns.</p>","PeriodicalId":8109,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"8 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142194161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Complex Scenes Fire Object Detection Based on Feature Fusion and Channel Attention","authors":"Xinrong Cao, Jincai Wu, Jian Chen, Zuoyong Li","doi":"10.1007/s13369-024-09471-y","DOIUrl":"https://doi.org/10.1007/s13369-024-09471-y","url":null,"abstract":"<p>For recognizing small targets, fire-like objects in fire images, and detecting fires across various scenes, we propose a fire detection method based on feature fusion and channel attention. Most existing fire detection methods have specific application scenarios with poor speed or accuracy. To address the issues of poor accuracy when directly applying existing object detection models and the reduced detection speed when improving models for fire targets, our approach aims to balance accurate fire localization with real-time processing. In the backbone of the model, deformable convolution is used to capture rich image information, and channel attention is employed to enhance features. The feature fusion in the neck achieves better localization of small fire targets. The visualized heatmap results indicate the effectiveness of our improved measures. By simultaneously employing multiple improvement measures, our method achieved satisfactory fire detection performance. Experimental results on a self-annotated dataset demonstrate that the best AP@50 of the model can reach 63.9%, the fastest detection speed can reach 114 FPS, and the F1-score is stable at around 63%. Our method strikes a good balance between detection speed and accuracy.\u0000</p>","PeriodicalId":8109,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"76 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142194163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic Risk Forecasting Based on Deep Learning and Collapse Risk Comprehensive Evaluation of Mountain Tunnel Portal Construction","authors":"Kun Lin, Yazhen Sun, Jinchang Wang, Fengbin Zhu, Longyan Wang","doi":"10.1007/s13369-024-09470-z","DOIUrl":"https://doi.org/10.1007/s13369-024-09470-z","url":null,"abstract":"<p>In this paper, a comprehensive risk assessment system is proposed to evaluate the risk of collapse in mountain tunnels. This system integrates risk source identification, dynamic and static risk classification, deep learning prediction, and engineering risk evaluation. Firstly, risk events and sources are identified, and a risk evaluation method combines the fuzzy analytic hierarchy process (FAHP) and interval technique for order preference by similarity to ideal solution (TOPSIS). FAHP is used to calculate weights, and a risk classification table based on five classical values is derived using traditional TOPSIS. The actual project’s risk value is then calculated using Interval TOPSIS to determine the risk level. Secondly, six models (BP, SVM, CNN, LSTM, PSO-SLTM, and EPL) are trained and tested to predict surface settlement at the tunnel portal and using RMSE, MAE, and maximum (minimum and average) error values for comparison; the best model is determined. The study concludes that a two-stage model, which uses ensemble empirical mode decomposition to process raw data and particle swarm optimization to optimize long short-term memory hyperparameters, provides the best predictive results. Finally, static and dynamic risks are combined for a comprehensive risk evaluation. The Aktepe Tunnel Project in Xinjiang, China, serves as a case study to successfully and accurately forecast surface settlement and evaluate the safety of the tunnel portal. This assessment confirms that this section of the tunnel is at average risk and that the current building conditions ensure the safety of the tunnel, the case study validates the rationality of the comprehensive evaluation system, offering a reference for tunnel portal risk evaluation.</p>","PeriodicalId":8109,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"22 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142194164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tailoring Novel SnO2/α-MnO2 Composites for Photocatalytic Performance Under Visible-Light","authors":"Aiman Jabeen, Shams ur Rahman, A. Shah, Sibghat Ullah Khan, Nasir Ali Siddiqui, Rabia Maryam, Afzal Hussain, Zainab Tariq, Rafaqat Hussain","doi":"10.1007/s13369-024-09406-7","DOIUrl":"https://doi.org/10.1007/s13369-024-09406-7","url":null,"abstract":"<p>Efficient removal of industrial effluents from wastewater is critical for a clean and sustainable water supply. In this study, novel nanosized SnO₂/MnO₂ photocatalysts with crystallite size between 34–40 nm were synthesized and evaluated for methylene blue (MB) degradation under visible light. The optimal percentage of MnO₂ nanowires was explored for superior photocatalytic efficiency by varying its amount in the composites. The findings suggested that the SnO₂/MnO₂ composites exhibited enhanced photocatalytic performance compared to their individual components, which was attributed to the synergistic interaction between SnO₂ and MnO₂. Preliminary analysis by X-ray diffraction, Raman spectra, and EDX confirmed the crystalline structure and chemical composition of SnO₂, MnO₂ and their composites. Additionally, the morphology of MnO₂ was observed to be of nanowires; while SnO₂ was found to be comprised of agglomerated particles. Notably, the photocatalysts demonstrated a systematic reduction in the bandgap of the composites with increasing MnO₂ content, leading to improved visible light utilization. Among all the prepared photocatalysts, the optimized SnO₂/MnO₂ composite with 75 wt. % MnO₂ (denote as SM-3) revealed exceptional photocatalytic activity by degrading 93% of MB in 150 min of light exposure. Moreover, the catalytic process followed pseudo-first-order kinetics, highlighting the efficiency of the composites. The scavenger studies suggested that holes, hydroxyl and superoxide radicals are primarily responsible for the MB degradation. The composite SM-3 also exhibited impressive stability and reusability. This study demonstrates the potential of SnO₂/MnO₂ composites as effective photocatalysts for wastewater treatment under visible light.</p>","PeriodicalId":8109,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"50 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141932735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"One-Dimensional Rock and Soil Characteristic Parameters Prediction Method Based on SRR","authors":"Zeliang Wang, Rui Gao, Xiuren Hu","doi":"10.1007/s13369-024-09393-9","DOIUrl":"https://doi.org/10.1007/s13369-024-09393-9","url":null,"abstract":"<p>Acquiring precise geologic parameters for obstructed or complex geologic regions poses a difficult task in practical engineering. Current predictions depend on the expertise of engineers, leading to inadequate levels of precision. Therefore, in this study, geotechnical stratigraphic data were transformed into visualization images containing only red information corresponding to <i>R</i> values in RGB images. The generated visualization images were analyzed using a super-resolution convolutional neural network (SRCNN) for prediction and compared with linear interpolation-based prediction methods. Subsequently, a dataset containing 430,000 patches was generated using real geologic data from a specific project, and this dataset was used for SRCNN training to validate its prediction. The results showed that SRCNN yields a peak signal-to-noise ratio (PSNR) of 40.22 dB, exceeding the linear interpolation on the geologic map (39.93 dB). The SRCNN training was successful and outperformed the linear interpolation. The PSNR values of the SRCNN were higher (34.69 dB, 37.68 dB, 38.79 dB, 37.56 dB, and 44.99 dB) compared to linear interpolation (34.53 dB, 37.43 dB, 38.38 dB, 37.29 dB, and 44.31 dB). These findings confirmed the significant potential of the application of super-resolution reconstruction for predicting soil distribution, and this method is expected to yield more precise soil prediction results as the dataset grows.</p>","PeriodicalId":8109,"journal":{"name":"Arabian Journal for Science and Engineering","volume":"26 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141932736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}