Engineering Science and Technology-An International Journal-Jestech最新文献

{"title":"Communication-constrained multi-UAV task allocation method for non-independent tasks","authors":"Jing Chu,&nbsp;Fei Yan,&nbsp;Zhongxian Xu","doi":"10.1016/j.jestch.2025.102166","DOIUrl":"10.1016/j.jestch.2025.102166","url":null,"abstract":"<div><div>Heterogeneous multi-UAV system can effectively collaborate to execute complex tasks through complementary capabilities. Rational and efficient task allocation strategies can significantly enhance the overall performance of multi-UAV system. This paper addresses the task allocation problem for heterogeneous unmanned aerial vehicles (UAVs) with non-independent tasks and communication constraints. We propose the Non-Independent Task Market-based Task Allocation (NI-MTA) method to tackle this challenge. First, we model the problem by incorporating non-independent tasks, pop up tasks, and communication limitations, reflecting real-world UAV coordination complexities. Second, we develop the NI-MTA method, which integrates a coalition formation algorithm into a market-based framework to enable dynamic task allocation with inconsistent situation awareness under communication constraints. Experimental results demonstrate that NI-MTA improves system performance compared to traditional market-based approaches, effectively handling task dependencies and limited communication. This work advances UAV coordination by providing a scalable and adaptive solution for complex mission scenarios.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102166"},"PeriodicalIF":5.4,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preference-based deep reinforcement learning with automatic curriculum learning for map-free UGV navigation in factory-like environments","authors":"Shunyu Tian ,&nbsp;Changyun Wei ,&nbsp;Shaojie Jian ,&nbsp;Ze Ji","doi":"10.1016/j.jestch.2025.102147","DOIUrl":"10.1016/j.jestch.2025.102147","url":null,"abstract":"<div><div>Autonomous navigation for unmanned ground vehicles in smart factory environments involves satisfying multiple, often conflicting objectives such as safety, efficiency, and motion smoothness. Traditional reinforcement learning approaches typically rely on fixed, manually weighted reward functions to encode these objectives. However, such static formulations struggle to generalize across varying user preferences and dynamic operational contexts common in real-world factory scenarios. Consequently, they require retraining for every new preference configuration, leading to inefficiency and limited practical deployment. To address this challenge, we propose a novel preference-based reinforcement learning framework that enables a single policy to dynamically adapt its behavior according to a user-defined preference vector that encodes trade-offs among multiple objectives. This allows the agent to modify its navigation strategy on-the-fly without additional retraining. To further improve training efficiency and learning stability, we incorporate automatic curriculum learning, which gradually increases the complexity of training tasks based on the agent’s performance, accelerating convergence and robustness. We validate our method in a simulated smart factory environment that reflects realistic navigation constraints. Experimental results demonstrate that our proposed approach ensures faster convergence during training and achieves up to a 93% navigation success rate in challenging factory-like environments compared to recent advances.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102147"},"PeriodicalIF":5.4,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental analysis of a phase change material (PCM) enhanced solar air heater for thermal energy storage","authors":"Ismail Ata ,&nbsp;Yunus Erkam Ozselcuk","doi":"10.1016/j.jestch.2025.102163","DOIUrl":"10.1016/j.jestch.2025.102163","url":null,"abstract":"<div><div>Solar air heaters are widely used heat exchangers that transfer energy from the sun to the working fluid. However, their thermal performance decreases significantly in cloudy weather and at night due to the absence of real-time solar energy. In this experimental study, heat storage was aimed by using phase change material integrated into a storage unit with rectangular fins on the absorber surface. The absorber was made of copper material and commercial Paraffin Wax was used as the phase change material. The thermal energy storage capacities of solar air heaters with and without phase change material were compared under irradiance intensities of 800 W/m² and 1000 W/m², and mass flow rates differing from 0.002 kg/s to 0.003 kg/s, using artificial radiation. As a result of the experiments, the highest heat storage amount of 477.4 kJ was obtained for the solar air heater using paraffin as phase change material in the storage unit, with a flow rate of 0.002 kg/s and an irradiance intensity of 1000 W/m². The lowest heat storage amount of 11.7 kJ was obtained for the solar air heater with no paraffin in the storage unit, a flow rate of 0.003 kg/s, and an irradiance flux of 800 W/m². The findings demonstrate that incorporating paraffin significantly enhances the system’s heat storage capability.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102163"},"PeriodicalIF":5.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144828056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancements in fiber-reinforced geopolymer along with 3D printed and nano concrete in sustainable construction","authors":"Fatheali A. Shilar ,&nbsp;Sharanabasava V. Ganachari ,&nbsp;N.A. Abu Osman ,&nbsp;S. Ramesh ,&nbsp;Manzoore Elahi M. Soudagar ,&nbsp;T.M. Yunus Khan ,&nbsp;Syed Waheedullah Ghori ,&nbsp;Mohammed Azam Ali","doi":"10.1016/j.jestch.2025.102162","DOIUrl":"10.1016/j.jestch.2025.102162","url":null,"abstract":"<div><div>The mechanical and durability performance of innovative sustainable concrete technologies more especially, fiber-reinforced concrete (FRC), geopolymer reinforced concrete (GRC), 3D printed reinforced concrete (3DRC), and nano-based concrete (NBC) is investigated here. The intention is to assess and contrast these materials in relation to contemporary building requirements and environmental sustainability. Examining more than 100 peer-reviewed papers from Scopus and Web of Science databases using a combined qualitative and quantitative approach, Using kernel density plots, Q-Q graphs, and Weibull analysis, key mechanical parameters including compressive strength, elastic modulus, Poisson’s ratio, and fracture toughness were statistically tested. Achieving compressive strengths of 60–95 MPa, elastic moduli between 30 and 42 GPa, and exceptional crack resistance, the results show that nano-based geopolymer concrete routinely beats others. Between 3 % and 5 % was found to be the ideal fiber content; 25–40 mm fiber lengths enhanced mechanical integrity. Particularly Goal 9 (Industry, Innovation, and Infrastructure) and Goal 13 (Climate Action), these results fit the United Nations Sustainable Development Goals. The work emphasizes the pragmatic benefits of using geopolymers and nano-enhanced materials in the building of sustainable infrastructure.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102162"},"PeriodicalIF":5.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144809414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive review on YOLO versions for object detection","authors":"Ayşe Aybilge Murat ,&nbsp;Mustafa Servet Kiran","doi":"10.1016/j.jestch.2025.102161","DOIUrl":"10.1016/j.jestch.2025.102161","url":null,"abstract":"<div><div>The need for methods used for object detection has gained increasing momentum in recent years. Starting with traditional image processing techniques, this process has been facilitated by the addition of deep learning. Object detection is currently used in areas such as autonomous vehicles, disease diagnosis, robotic vision and industry. The types of systems that are predicted to be needed more and more in the age of developing technology are also increasing. In particular, YOLO (You Only Look Once), which is mostly preferred in real-time object detection, is preferred because it achieves high accuracy in a short time. This paper analyses the main versions of the YOLO algorithm since its first release. The paper systematically analyses the architectural differences between the versions of the YOLO algorithm, the strengths and weaknesses of the models and their contribution to performance. At the same time, in most of the previous studies on YOLO, a comprehensive comparison of the YOLOv9-v11 models is not presented and new architectural features are not evaluated. This review provides an in-depth analysis of the main versions from YOLOv1 to YOLOv11, including recent innovations such as NMS-free, Oriented Bounding Boxes (OBB), GELAN and PGI. This work is intended to be a useful guide for researchers and developers interested in the field.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102161"},"PeriodicalIF":5.4,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144771218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating experimental and theoretical approaches for enhanced machine learning modeling of solar radiation","authors":"Nader Ghareeb ,&nbsp;Abeer Alanazi ,&nbsp;Ahmad Sedaghat ,&nbsp;Mohamad Hussein Farhat ,&nbsp;Arash Mehdizadeh ,&nbsp;Hayder Salem ,&nbsp;Mohammad Nazififard ,&nbsp;Ali Mostafaeipour","doi":"10.1016/j.jestch.2025.102156","DOIUrl":"10.1016/j.jestch.2025.102156","url":null,"abstract":"<div><div>This study presents a novel hybrid framework for estimating solar radiation components—critical for optimizing solar energy systems—by integrating theoretical solar parameters with meteorological data, an approach seldom explored in literature. A one-year dataset, recorded at 15-minute intervals, was collected from a weather station at The Australian University, Kuwait. The theoretical global solar radiation values were validated against 8,784 hourly averaged experimental data points, incorporating key solar parameters such as local time, solar declination, the Equation of Time (EoT), hour angle, and solar zenith angle. These theoretical inputs, combined with meteorological parameters (temperature, humidity, wind speed, and wind direction), were used to train multiple machine learning (ML) models. To improve model accuracy, a four-scenario data treatment strategy was applied, including Gaussian fitting and zero-removal techniques. In total, 28 ML models were evaluated, encompassing linear regression, support vector machines, Gaussian process regression, and neural networks. The Exponential GPR model emerged as the most accurate, achieving R² values &gt; 0.99 and RMSE as low as 0.13 W/m². These results represent a significant performance improvement over existing models in the literature, many of which report RMSE values in the range of 20–60 W/m² and R² values between 0.85 and 0.98. The findings demonstrate substantial improvements over existing methods and offer a scalable solution for a more precise solar forecasting in various environments.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102156"},"PeriodicalIF":5.4,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144771219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance evaluation of deep learning algorithms for channel estimation in OFDM-IM","authors":"Omer Adiguzel ,&nbsp;Ibrahim Develi","doi":"10.1016/j.jestch.2025.102160","DOIUrl":"10.1016/j.jestch.2025.102160","url":null,"abstract":"<div><div>This paper presents a detailed performance evaluation on the use of various deep neural networks for channel estimation in orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems. The channel estimation performances of the models previously employed for OFDM in the literature are analysed in OFDM-IM. In the context of OFDM systems, the placement of pilot symbols within the process of channel estimation demonstrates a degree of flexibility. Conversely, within the framework of OFDM-IM, the placement of pilot symbols is constrained to the position subsequent to each sub-block, given that not all sub-carriers are active. Consequently, the process of channel estimation in OFDM-IM can be more arduous than in OFDM. In this work, a new channel estimation model is also introduced, which combines Long Short Term Memory (LSTM) and residual network (ReEsNet) for OFDM-IM systems, and which is termed LSTM-ReEsNet. A comparative analysis is conducted between available models and the introduced LSTM-ReEsNet model, in terms of training time, computation time, computational complexity, mean squared error (MSE) and bit error rate (BER). Furthermore, the paper presents BER analyses for different power delay profiles (PDP) in order to measure the generalisation capabilities of the employed models. The findings demonstrate that the proposed LSTM-ReEsNet model exhibits improved in performance when compared to traditional methods and comparable performance with other deep learning (DL) models. Notably, training time is significantly reduced with the proposed LSTM-ReEsNet model.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102160"},"PeriodicalIF":5.4,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144781818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A low cost compact network TAP device with Raspberry Pi 4","authors":"Murat Varol ,&nbsp;Murat İskefiyeli","doi":"10.1016/j.jestch.2025.102118","DOIUrl":"10.1016/j.jestch.2025.102118","url":null,"abstract":"<div><div>The communication of multiple networks in different locations is an open problem since the networks include various devices and applications. There is a necessarity to monitor the network to detect any kind of attacks or problems. Determining which device is the source of the problem and vulnerability is also a problem. Network TAP devices are positioned between network devices, allowing for device-based monitoring of communications across the entire network. With this feature Network TAP devices play a main role in network security, network visibility, network monitoring, forensics, etc. Typically, Network TAP devices copy all packets transmitted between two network devices and allow the network authority to monitor the packets through the monitoring port. However, TAP devices available in the market are high cost devices. At this point, we propose a low-cost network TAP device using Raspberry Pi 4. This article provides theoretical and practical contributions into the network TAP literature and includes a method that can be easily implemented for end users. The proposed TAP device has a cost between 1/8 to 1/30 compared to the prices in the market. The device, with its flexible software-based solutions, extensible storage options with any portable disk, can be adapted into various test cases. In addition, the proposed TAP device offers the opportunity to monitor the captured packets via a monitor or remote connection without a computer. Unlike traditional TAP devices, it captures and records packets independently without the necessary of an external computer connection, while enabling real-time monitoring through connected monitor. Experimental studies are carried out at CENTER SAU testbed center with our proposed TAP device and ET2000 device from Beckhoff. When the pcap files obtained from the experimental studies were examined, it was observed that the same packets were captured, therefore the proposed TAP device captured all packets lossless. The results show that the device is a cost-effective alternative for corporate and individual users.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102118"},"PeriodicalIF":5.4,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards efficient multi-legal document summarization: An ensemble approach for Turkish law","authors":"Maha Ahmed Abdullah Albayati,&nbsp;Kürşat Mustafa Karaoğlan,&nbsp;Oğuz Findik","doi":"10.1016/j.jestch.2025.102138","DOIUrl":"10.1016/j.jestch.2025.102138","url":null,"abstract":"<div><div>Legal document summarization is a critical yet challenging task due to the structural complexity, terminological density, and contextual depth of legal texts, especially in low-resource languages like Turkish. Building on our previous research in hybrid summarization (Albayati and Findik, 2025), this study proposes an advanced ensemble-based framework tailored to Turkish legal documents. The framework integrates four transformer models, LED, Long-T5, BART-Large, and GPT-3.5 Turbo, and employs three complementary techniques: the Consecutive-Aware Semantic Voting Mechanism (CASVM), the Weighted Hybrid Sentence Ranking Framework (WHSRF), and a T5-Based Meta-Model (T5-Meta). Together, these components leverage both extractive precision and abstractive fluency. Experimental results over a dataset of 2,000 Turkish court decisions show significant improvements in summary quality and consistency. The proposed ensemble achieved ROUGE-1, ROUGE-2, ROUGE-L, and ROUGE-Sum scores of 0.90, 0.78, 0.88, and 0.85 respectively, reflecting relative gains of 63.64%, 122.86%, 109.52%, and 93.18% compared to the best-performing individual models. In parallel, BERTScore evaluations confirmed a high level of semantic fidelity, validating the model’s ability to preserve legal meaning even in paraphrased output. This research sets a new benchmark in Turkish legal summarization, showcasing the power of ensemble learning for multilingual legal NLP and paving the way for its integration into intelligent legal assistants that support faster, more accurate information access for legal professionals.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102138"},"PeriodicalIF":5.4,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retrofitting of seismically deficient RC bridge pier using HSP concrete jacket and FRP rebars","authors":"Muhammad Waleed Ahmad,&nbsp;Muhammad Rizwan,&nbsp;Muhammad Fiaz Tahir","doi":"10.1016/j.jestch.2025.102146","DOIUrl":"10.1016/j.jestch.2025.102146","url":null,"abstract":"<div><div>Bridges in high seismic zones are prone to failure due to inadequate seismic design or cumulative damage from repeated earthquakes, compromising structural integrity and functionality This study investigates the effectiveness of retrofitting seismically deficient reinforced concrete (RC) bridge piers using high-performance strength concrete (HPSC) jackets and Fiber-reinforced polymer (FRP) rebars applied at the plastic hinge zone. Two 1:4 scaled RC pier specimens with different transverse reinforcement arrangements were tested under constant axial load and quasi-static cyclic lateral loading to induce damage. The damaged piers were then retrofitted and retested to assess seismic performance improvements. Key parameters such as load-carrying capacity, hysteresis behaviour, energy dissipation, and stiffness degradation were evaluated. The retrofitted specimens showed substantial restoration of strength and stiffness and exhibited enhanced energy dissipation compared to both the original and CFRP-wrapped specimens. Additionally, a finite element model was developed in SeismoStruct (2024), showing good agreement with experimental results and validating the proposed retrofitting approach. The study concludes that the HPSC-FRP retrofit method significantly enhances the seismic resilience of damaged bridge piers and presents a viable solution for extending the service life of aging bridge infrastructure.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102146"},"PeriodicalIF":5.4,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144723025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}