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

{"title":"Critical criteria for sediment suspension derived from suspension probability","authors":"Lixia Sun ,&nbsp;Zhongwu Jin ,&nbsp;Zhilin Sun ,&nbsp;Guiying Shen ,&nbsp;Haolei Zheng ,&nbsp;Chao Guo ,&nbsp;Lingyun Li","doi":"10.1016/j.jestch.2025.102034","DOIUrl":"10.1016/j.jestch.2025.102034","url":null,"abstract":"<div><div>The critical criterion of sediment suspension is<!--> <!-->a key problem in hydraulic engineering, environmental protection and coastal engineering, which plays a significant role in the numerical computations of suspended sediment motion. This study explored the<!--> <!-->critical suspension for nonuniform sediment through theoretical derivation and flume experiments. First, two criteria were proposed based on the suspension probability from the perspectives of dynamics and kinematics, respectively. Then, the flume experiment was conducted with nonuniform dyeing<!--> <!-->sediment and a high-speed camera. Finally, the criteria were verified by the experimental data and compared with several other criteria. It was found that the two criteria of dynamics and kinematics are functions of relative suspension velocity and suspension parameters, respectively. The interaction coefficient of nonuniform sediment is introduced into the two criteria and reflected in the suspension and settling velocities, respectively. The result of this study is a step forward in theory compared with the critical criterion of uniform sediment suspension.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"64 ","pages":"Article 102034"},"PeriodicalIF":5.1,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gas kick and lost circulation risk identification method with multi-parameters based on support vector machine for drilling in deep or ultradeep waters","authors":"Kai Feng ,&nbsp;Shujie Liu ,&nbsp;Zhiming Yin ,&nbsp;Yi-long Xu ,&nbsp;Meipeng Ren ,&nbsp;Deqiang Tian ,&nbsp;Bangtang Yin ,&nbsp;Baojiang Sun","doi":"10.1016/j.jestch.2025.102007","DOIUrl":"10.1016/j.jestch.2025.102007","url":null,"abstract":"<div><div>In deepwater and ultra-deepwater drilling, formation pressures are complex and the drilling fluid density window is narrow, which makes it prone to well control incidents such as kicks and lost circulation. To ensure safe, efficient, and cost-effective drilling operations, real-time monitoring of kick and lost circulation incidents is essential. This paper, based on the classical symbolic aggregate approximation (SAX) method, comprehensively considers the average difference and slope characteristics of time series data for kick and lost circulation monitoring parameters, and proposes an improved SAX method for kick and lost circulation risk identification. Additionally, the paper establishes “kick standards” and “lost circulation standards” models, calculating the similarity measurement distance between the monitoring parameters and the standard models. These similarity measures are used as feature vectors in a support vector machine to develop a multi-parameter collaborative risk identification model for kicks and lost circulation. Verification with data from two wells in the South China Sea demonstrates that the model can accurately identify kick and lost circulation incidents, providing a new approach for real-time risk identification in deepwater drilling.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"64 ","pages":"Article 102007"},"PeriodicalIF":5.1,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grounding DINO and distillation-enhanced model for advanced traffic sign detection and classification in autonomous vehicles","authors":"Hoang Ngoc Tran ,&nbsp;Nam Nhat Ngo Nguyen ,&nbsp;Nhi Quynh Phan Le ,&nbsp;Thu Anh Ngoc Le ,&nbsp;Anh Duy Nguyen","doi":"10.1016/j.jestch.2025.102028","DOIUrl":"10.1016/j.jestch.2025.102028","url":null,"abstract":"<div><div>Accurate traffic sign detection is critical for safe autonomous driving. This paper presents a novel approach that integrates GroundingDINO, known for its semantic grounding capabilities, with a self-distilled ResNet to enhance detection performance and real-time feasibility. While GroundingDINO excels in linking object detection with contextual understanding, it faces challenges when detecting small or occluded signs. To address these limitations, we employ a lightweight LB-scSE (Linear Bottleneck Block with Simultaneous Spatial and Channel Squeeze &amp; Excitation) architecture, thereby improving detection accuracy while significantly reducing computational overhead.</div><div>We evaluate our framework on the custom DINO&amp;GTSRBv1 dataset, where the GroundingDINO Pro model achieves a mAP@50 of 68.52%. The self-distilled network further reduces model size by tenfold compared to baseline models (e.g., MobileNetV2, VGG16, ResNet18), yet maintains competitive accuracy, providing a robust, resource-efficient solution for real-time deployment. Our results indicate that integrating semantic grounding with distillation-based compression not only enhances traffic sign detection performance but also delivers a scalable and efficient approach for complex traffic environments. Additionally, our method outperforms standard architectures such as MobileNetV1-2, VGG16-19, and ResNet34-50, demonstrating higher detection accuracy and lower resource consumption, thus reinforcing its suitability for real-world autonomous driving scenarios.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"64 ","pages":"Article 102028"},"PeriodicalIF":5.1,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Instantaneous time to collision estimation using a constant jerk model and a monocular camera","authors":"Aimad El mourabit ,&nbsp;Omar Bouazizi ,&nbsp;Mustapha Oussouaddi ,&nbsp;Zine El Abidine Alaoui Ismaili ,&nbsp;Yassine Attaoui ,&nbsp;Mohamed Chentouf","doi":"10.1016/j.jestch.2025.102011","DOIUrl":"10.1016/j.jestch.2025.102011","url":null,"abstract":"<div><div>We present the application of a constant-jerk kinematic model to assess collision risk using a monocular camera (MC) for car-following (CF) scenarios. First, we redefined the metric of Instantaneous Time-to-Collision (ITTC). By employing the Kalman filter (KF) and data extracted from the frames, we estimated the equivalent parameters for distance, velocity, acceleration, and jerk on the image plane. These parameters serve as coefficients for the kinematic model on the image plane and allow for the calculation of the ITTC. Deep convolutional neural networks (DCNN) were employed for object detection and tracking in the experimental setup. The results of these experiments confirm the effectiveness of employing a constant-jerk model for evaluating the risk of collision, in contrast to the constant acceleration and constant-speed models. Furthermore, the results underscore the pivotal parameters for optimization to boost the effective utilization of MC data frames in ITTC estimations using uncalibrated MC.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"64 ","pages":"Article 102011"},"PeriodicalIF":5.1,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pedestrian trajectory prediction via physical-guided position association learning","authors":"Yueyun Xu ,&nbsp;Hongmao Qin ,&nbsp;Yougang Bian ,&nbsp;Rongjun Ding","doi":"10.1016/j.jestch.2025.102008","DOIUrl":"10.1016/j.jestch.2025.102008","url":null,"abstract":"<div><div>Pedestrian trajectory prediction possesses huge application value in automatic driving, robots, and video surveillance. Due to the complexity of the environment and the uncertainty of pedestrians, predicting pedestrian trajectories is a challenging task. Previous studies simply employ the LSTM or transformer structure to construct the deep model, which hardly adequately mines the dependency relationship among different pedestrian positions from different views. In addition, directly employing the deep model to output the prediction results is easy to be disturbed by the external factor. To this end, we propose the Physical-guided Position Association Learning (PPAL) method to adequately explore the inter-position dependency relationship with the guidance of the physical motion rule. Specifically, to build the long/short-distance relationship, we develop the position association learning module (PAL) to deeply correlate different position coordinates by utilizing the advantages of the LSTM and transformer structure, which could stimulate the deep model to better perceive the pedestrian intention. In addition, the future motion trajectory has a strong correlation with the previous position and speed. Its physical motion rules provide much prior knowledge and increase the reasonability of trajectory predictions. Hence, we design the physical position modeling (PPM) to utilize the motion rule for trajectory prediction. Finally, we integrate PAL and PPM into a framework to deeply learn the inter-position dependency relationship. Abundant experiments on three mainstream databases demonstrate that the proposed PPAL significantly improves the prediction performance and surpasses other advanced methods. A large number of quantitative analyses show that the predicted trajectory is very close to the real trajectories, indicating that the proposed method has a better forecasting ability.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"64 ","pages":"Article 102008"},"PeriodicalIF":5.1,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermo-hydrodynamic and exergy optimization of a photovoltaic thermal (PV/T) air collector using NSGA-II","authors":"Seyed Morteza Javadpour ,&nbsp;Rasoul Soufi Noughabi ,&nbsp;Ebrahim Kadivar","doi":"10.1016/j.jestch.2025.102030","DOIUrl":"10.1016/j.jestch.2025.102030","url":null,"abstract":"<div><div>This study investigates the hydrodynamic, thermal, and exergy performances of a photovoltaic-thermal (PV/T) air collector by examining four geometric and hydrodynamic variables. The Non-Dominated Sorting Genetic Algorithm (NSGA-II) optimization method, combined with the finite volume method, is employed to identify and analyze the optimal configuration in comparison to the initial design. Unlike prior studies that optimize isolated design parameters, this work presents a comprehensive multi-objective optimization strategy, concurrently minimizing pumping power while maximizing first- and second-law efficiencies. Three distinct single-objective optimizations were also conducted to minimize pumping power, maximize first-law (thermal) efficiency, and enhance second-law (exergy) efficiency, exploring various geometric and operational parameters. Analysis of variance (ANOVA) results reveal that airflow rate and air channel height significantly influence pumping power, while the number of fins and airflow rate have the most substantial impact on thermal and exergy efficiencies. The single-objective optimization results indicate a 28 % enhancement in thermal efficiency and an 18 % improvement in exergy efficiency, while hydrodynamic performance sees a significant 98 % reduction. In comparison, the multi-objective optimized configuration—featuring a channel height of 0.088 m, a width of 0.159 m, six fin rows, and an airflow rate of 0.006 kg/s—demonstrates a 30 % decrease in pumping power.</div><div>Additionally, it improves first- and second-law efficiencies by 25 % and 11 %, respectively. Furthermore, the average panel surface temperature decreases by 7 °C in this optimized scenario. By systematically optimizing air channel parameters and integrating exergy-based analysis, this study establishes a novel performance enhancement framework for PV/T systems, providing valuable insights for next-generation solar energy applications.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"64 ","pages":"Article 102030"},"PeriodicalIF":5.1,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Swarm intelligence driven inverse design of slot patterns for sub-6 GHz 5G MIMO antennas in virtual reality applications","authors":"Shadman Fuad Bin Faruquee,&nbsp;Himel Bhuiyan,&nbsp;Md. Shafiul Alam,&nbsp;Sharnali Islam,&nbsp;Khaleda Ali","doi":"10.1016/j.jestch.2025.102026","DOIUrl":"10.1016/j.jestch.2025.102026","url":null,"abstract":"<div><div>This paper presents an efficient approach for developing miniature sub-6 GHz 5G MIMO antennas with enhanced bandwidth and high isolation. Utilizing the capabilities of particle swarm optimization (PSO) on a pixelated surface, an objective function is formulated to minimize the reciprocal of the bandwidth while ensuring that the reflection coefficient (<span><math><mrow><mo>|</mo><msub><mrow><mi>S</mi></mrow><mrow><mn>11</mn></mrow></msub><mo>|</mo></mrow></math></span>) remains below -10 dB and the transmission coefficient (<span><math><mrow><mo>|</mo><msub><mrow><mi>S</mi></mrow><mrow><mn>21</mn></mrow></msub><mo>|</mo></mrow></math></span>) is below -20 dB. This methodology effectively eliminates the necessity for incorporating complex decoupling networks to enhance isolation. The inverse design concept is independently implemented in the slot arrangements of two different configurations of 2-element MIMO antennas: one in which the individual antenna components are placed in an antiparallel orientation, and the other in which they are arranged orthogonally. The optimized designs, measuring 24 × 48 (0.4<span><math><msub><mrow><mi>λ</mi></mrow><mrow><mi>o</mi></mrow></msub></math></span> <span><math><mrow><mo>×</mo><mn>0</mn><mo>.</mo><mn>8</mn><msub><mrow><mi>λ</mi></mrow><mrow><mi>o</mi></mrow></msub></mrow></math></span>) <span><math><mrow><mi>m</mi><msup><mrow><mi>m</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></math></span> in size, yield operating spectra spanning from 4.53 GHz to 7.01 GHz for the orthogonal scenario and 3.95 GHz to 5.15 GHz for the antiparallel orientation in free space. An ECC <span><math><mo>&lt;</mo></math></span>0.0173 and MEG <span><math><mo>&lt;</mo></math></span>-6 dB, observed in the operating bandwidth, supports satisfactory MIMO antenna diversity performance. Having negligible current coupling between ports, these MIMO antennas, with a diversity gain of close to 10 dB are well-suited for integration into virtual reality (VR) headsets. In situ path loss measurement campaign was executed by integrating the antenna into participants’ virtual reality headsets. The performance of the proposed MIMO antenna has been tested through numerical analysis, equivalent circuit modeling, and measurement campaigns using fabricated prototypes. Experimental results from testing the prototypes closely align with the simulations, confirming the effectiveness of the proposed designs both in free space and in proximity to the human body.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"64 ","pages":"Article 102026"},"PeriodicalIF":5.1,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discovering temporal, spatial, and contextual anomalous social activities from streaming social media datasets","authors":"Mete Celik ,&nbsp;Ahmet Sakir Dokuz ,&nbsp;Alper Ecemis ,&nbsp;Emre Erdogmus","doi":"10.1016/j.jestch.2025.102006","DOIUrl":"10.1016/j.jestch.2025.102006","url":null,"abstract":"<div><div>Social media data refers to data collected from social media platforms, including user interactions, posts, comments, likes, etc., while streaming social media data is a specific type of social media data that is continuously and sequentially collected from these platforms. Processing of streaming social media data is crucial for providing quick responses and reacting promptly to issues. Therefore, it requires more specialized solutions compared to traditional social media data processing algorithms. Temporal, spatial, and contextual anomalous social activity of a social media user can be defined as activities of sending a frequent and abnormal number of posts that are contextually similar to other posts in a time frame and at specific locations. However, detecting anomalies in streaming social media datasets has many difficulties due to the size, continuous increase, different characteristics (e.g., temporal, spatial, and contextual) of the data, and shortcomings of existing algorithms to handle streaming social media datasets. In the literature, many studies are conducted on detecting anomalies in social media data or streaming data. Nonetheless, anomaly detection studies on streaming social media datasets are very limited. The focus of this study is the detection of temporal, spatial, and contextual anomalous social activities from streaming social media datasets. In particular, streaming Twitter/X dataset is analyzed in terms of three different aspects, such as temporal, spatial, and contextual anomalous social activity detection. The proposed Temporal, Spatial, and Contextual Anomalous Social Activity Miner (TSCASA-Miner) algorithm is experimentally evaluated with a naive alternative and related studies. Evaluations are conducted using a real-life streaming Twitter/X dataset from New York, USA. The results demonstrate that the proposed TSCASA-Miner algorithm outperforms the other algorithms, with a recall of 0.93, a precision of 0.95, and an accuracy of 0.9323, marking an improvement of 0.018 in accuracy.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"64 ","pages":"Article 102006"},"PeriodicalIF":5.1,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New blockchain consensus algorithm applied on healthcare industry: Proof of Visit- (POV)","authors":"Çetin Şahin,&nbsp;Muhammed Ali Aydin,&nbsp;Ahmet Sertbaş","doi":"10.1016/j.jestch.2025.102014","DOIUrl":"10.1016/j.jestch.2025.102014","url":null,"abstract":"<div><div>The increase in the world’s population, technological advancements, genetic research, digital health services, and medical devices are among the reasons that lead to the rapid growth of Electronic Health Record (EHR). Health services, clinical studies, public health studies, health insurance data, health research, and similar sources generate a large amount of EHR. One of today’s important issues is the storage of data in centralized database systems and the fact that data accuracy and security are only ensured through these centers. Due to communication and integration issues between these centers, vital data such as examinations and laboratory tests can be repeated due to difficulty accessing the EHR. As citizens do not have full control over sharing their own EHR, this situation can cause deficiencies and disruptions in the healthcare process. Sharing personal EHR without the citizen’s consent can lead to data privacy issues. In systems where patient data is centrally stored, software changes can cause problems such as loss of patient data. The fact that the patient’s potentially valuable EHR is secondary causes irregular maintenance of the data. With its decentralized architecture and verification mechanisms, blockchain technology can work more efficiently than centralized structures without data loss or security problems. In this study, it is proposed to share EHR using blockchain infrastructure and to prepare a consensus algorithm specifically for health data on the blockchain. This way, personal EHR is stored in the patient’s own control and their own health wallet.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"64 ","pages":"Article 102014"},"PeriodicalIF":5.1,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Designing green and safe micro mobility routes: An advanced geo-analytic decision system based approach to sustainable urban infrastructure","authors":"Ömer Kaya","doi":"10.1016/j.jestch.2025.102027","DOIUrl":"10.1016/j.jestch.2025.102027","url":null,"abstract":"<div><div>Urban mobility faces increasing challenges due to congestion, environmental concerns, and inefficiencies in transport infrastructure. Micro-mobility solutions have gained significant attention as a sustainable alternative, yet their integration into urban transport networks remains a complex task. To this end, this study introduces a geo-analytic decision-making framework for optimizing micro-mobility route planning. The methodology consists of five key steps: (i) identification and spatial analysis of 33 critical factors influencing micro-mobility adoption in a Geographic Information Systems (GIS) environment; (ii) a suitability map for the routes was generated using the state-of-the-art Fuzzy Logarithm Methodology of Additive Weights (FLMAW) and Fuzzy Simple Weight Calculation (fuzzy SIWEC) weighting methods. It was determined that criteria such as cyclist lanes, public transportation routes, terrain inclination, and recreational areas have a high impact on micro mobility use; (iii) based on this analysis, 21 optimized routes were developed, and their relationships with the main criteria were validated through Spearman’s rank correlation analysis, revealing a significant and strong positive correlation; (iv) additionally, Random Forest classification was applied to categorize routes into nine different usage classes. Route classes with different nicknames such as GreenLink and UrbanHealth Path have been created; and (v) DOmbi Bonferroni (DOBI) performance evaluation method was used to determine the preferred priority order for route construction in the study area. The results indicate that the construction priority of routes R9 and R10 is higher than that of other routes. The proposed framework offers a scalable, adaptable, data-driven, and evidence-based approach, providing valuable insights for urban planners and policymakers aiming to integrate micro-mobility into sustainable transportation strategies.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"64 ","pages":"Article 102027"},"PeriodicalIF":5.1,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}