Expert Systems with Applications最新文献

{"title":"A machine learning-incorporated heuristic column generation algorithm for truck grouping and scheduling problem in trailer-swapping transport mode","authors":"Zhaojie Xue ,&nbsp;Haopeng Xu ,&nbsp;Haipeng Cui ,&nbsp;Wenxiang Peng","doi":"10.1016/j.eswa.2025.127327","DOIUrl":"10.1016/j.eswa.2025.127327","url":null,"abstract":"<div><div>The logistics industry is facing significant challenges in both operation costs and practitioner satisfactions, necessitating a higher efficiency and cost control management. In this study, we introduce a novel trailer-swapping transport mode (TSTM) in long-haul road freight scenario based on container/trailer exchanging and study a truck grouping and scheduling problem (TGSP) with TSTM. We formulate the TGSP as a concise mixed-integer programming model (MILP). We propose a machine learning-based heuristic column generation (CGML) algorithm to solve the problem, where the incorporated machine learning technique can effectively improve the decision-making efficiency and accuracy of the column generation (CG) algorithm. We further assess the performance of the MILP, heuristic CG algorithm, and the proposed CGML algorithm for the TGSP based on massive numerical experiments. Results show that the proposed CGML algorithm outperforms other tested approaches in both solution accuracy and efficiency, especially for large-scale instances. Based on sensitivity analysis, several managerial insights are provided.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127327"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longest similar subsequence-modified Hausdorff distance: A new robust approach for measuring distances between linear features","authors":"Dan Liang ,&nbsp;Yongjiu Feng ,&nbsp;Liang Hong ,&nbsp;Xiaohua Tong","doi":"10.1016/j.eswa.2025.127380","DOIUrl":"10.1016/j.eswa.2025.127380","url":null,"abstract":"<div><div>Accurately measuring the distance between linear features is crucial for understanding the similarity between objects. Traditional measures such as the Hausdorff distance (<em>HD</em>) are inadequate in handling length variations and outliers among linear features, and thus reducing the accuracy of similarity assessment. In this paper, we propose a new concept termed Longest Similar Subsequence (<em>LSS</em>), which aims to identify the longest overlapping subsequence of paired linear features. By integrating <em>LSS</em> with a modified Hausdorff Distance (<em>LSS-HD</em>), we propose a matching method that is based on <em>LSS-HD</em> and adaptive threshold-selection. The adaptive threshold-selection method, named the Connected Bin Threshold Selection Algorithm (<em>CBTSA</em>), is based on the distance histogram analysis. Experimental results clearly demonstrate that the <em>LSS</em>-based <em>HD</em> measure is more robust compared to the <em>HD</em> measure without <em>LSS</em> constraints. In the road matching experiments, our matching accuracy, with an F1-score of over 0.96, is significantly higher than that of the matching algorithms (Opt and OILRM), which are also solely based on distance-similarity metrics.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127380"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SA-TPE: An ideal thumbnail-preserving encryption method based on selective area","authors":"Yuexi Peng ,&nbsp;Zeng Huang ,&nbsp;Zhijun Li ,&nbsp;Shaobo He","doi":"10.1016/j.eswa.2025.127275","DOIUrl":"10.1016/j.eswa.2025.127275","url":null,"abstract":"<div><div>Cloud storage platform is widely used to store images due to easy uploading and space-saving. To ensure the security and preview of images in the cloud, an image privacy protection strategy called thumbnail-preserving encryption (TPE) has been proposed, which can effectively balance availability and privacy. However, existing TPE methods have some problems such as low efficiency and high memory expansion rate. To address these issues, this paper proposes a selective area encryption method, which selectively encrypts some areas of the image based on the information entropy of blocks. The algorithm adopts the permutation-diffusion framework and uses pseudo-random sequences generated by a new discrete memristor-based chaotic map. Basic experiments show that the NPCR value of the proposed method is close to the ideal value, and it can recover the original image under the interference of Salt &amp; Pepper noise and data loss. Moreover, several relevant TPE methods are considered for the comparison, and simulation results demonstrate that our method has better performance in time consumption and memory expansion rate.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127275"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Employment of fuzzy inference system in prediction of optimal solution area for thermal stress generated in the friction stir welding process","authors":"Masoud Seidi ,&nbsp;Saeed Yaghoubi ,&nbsp;Ali Shirazi","doi":"10.1016/j.eswa.2025.127342","DOIUrl":"10.1016/j.eswa.2025.127342","url":null,"abstract":"<div><div>The study of thermal stress in the friction stir welding (FSW) process is of particular importance due to its direct effect on the quality of manufactured part. The present research work is concerned with implementation of novel method to find the best solution area in friction stir welding process. The numerical simulation of FSW has been done using LS-Dyna software. The investigated variables include the rotational speed, transverse speed and shoulder diameter. Due to the necessity of reducing the tensile-thermal stress in FSW operation, the aim of current research work is to minimize this factor. Each variable has five levels and according to Taguchi method, the number of numerical tests was reduced to 25. After performing the simulation of FSW operation, the hierarchical clustering on inputs and output variables has been performed and based on similarity level (more than 80 %), the number of clusters was computed to ten. The extraction rules acquired from the employing of clusters were considered as input of the fuzzy inference system using MATLAB software. According to the surface and heat map plots obtained from the fuzzy inference system, the solution area was determined. Based on the response sensitivity analysis in the range of process variables, the most dependency of the tensile-thermal stress changes was on the rotational speed. In the appropriate feasible solutions set, the rotational speed was gained about 710 rpm and the ranges of the transverse speed and shoulder diameter were computed to, in turn, [70–110] (mm/min) and [19.5–23] (mm).</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127342"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Frequency bounds for edges and paths in optimal Hamiltonian cycle based on frequency Kis","authors":"Yong Wang,&nbsp;Pengbo Liu,&nbsp;Yanlong He","doi":"10.1016/j.eswa.2025.127264","DOIUrl":"10.1016/j.eswa.2025.127264","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Traveling salesman problem (&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;mi&gt;S&lt;/mi&gt;&lt;mi&gt;P&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;) is extensively studied in operations research and computer science. In general, the distances of edges are not helpful for finding edges and paths in optimal Hamiltonian cycle (&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;mi&gt;H&lt;/mi&gt;&lt;mi&gt;C&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;). The frequency bounds for edges and paths in &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;mi&gt;H&lt;/mi&gt;&lt;mi&gt;C&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; are studied based on frequency &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;K&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;s (&lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mn&gt;4&lt;/mn&gt;&lt;mo&gt;≤&lt;/mo&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;mo&gt;≤&lt;/mo&gt;&lt;mi&gt;n&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;) in &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;K&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;n&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;. A frequency &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;K&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; is computed with the optimal &lt;span&gt;&lt;math&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt;-vertex paths with given endpoints (optimal &lt;span&gt;&lt;math&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt;-vertex path for short) in one corresponding &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;K&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; in &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;K&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;n&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;. In this paper, the lower frequency bounds for &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;mi&gt;H&lt;/mi&gt;&lt;mi&gt;C&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; edges and paths in &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;K&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;n&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; are improved under the constrains of optimal &lt;span&gt;&lt;math&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt;-vertex paths in frequency &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;K&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; where &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;i&lt;/mi&gt;&lt;mo&gt;≥&lt;/mo&gt;&lt;mn&gt;5&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;. As the frequency of an edge is computed with frequency &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;K&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;5&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;s under the constraints of optimal 5-vertex paths, the lower frequency bound for &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;mi&gt;H&lt;/mi&gt;&lt;mi&gt;C&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; edges is improved from 5 to &lt;span&gt;&lt;math&gt;&lt;mfrac&gt;&lt;mrow&gt;&lt;mn&gt;131&lt;/mn&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;20&lt;/mn&gt;&lt;/mrow&gt;&lt;/mfrac&gt;&lt;/math&gt;&lt;/span&gt; for small &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;mi&gt;S&lt;/mi&gt;&lt;mi&gt;P&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;. For 3-vertex, 4-vertex, and 5-vertex paths in &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;mi&gt;H&lt;/mi&gt;&lt;mi&gt;C&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;, the lower frequency bounds are derived as &lt;span&gt;&lt;math&gt;&lt;mfrac&gt;&lt;mrow&gt;&lt;mn&gt;187&lt;/mn&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;15&lt;/mn&gt;&lt;/mrow&gt;&lt;/mfrac&gt;&lt;/math&gt;&lt;/span&gt;, &lt;span&gt;&lt;math&gt;&lt;mfrac&gt;&lt;mrow&gt;&lt;mn&gt;187&lt;/mn&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;10&lt;/mn&gt;&lt;/mrow&gt;&lt;/mfrac&gt;&lt;/math&gt;&lt;/span&gt;, and &lt;span&gt;&lt;math&gt;&lt;mfrac&gt;&lt;mrow&gt;&lt;mn&gt;131&lt;/mn&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;5&lt;/mn&gt;&lt;/mrow&gt;&lt;/mfrac&gt;&lt;/math&gt;&lt;/span&gt;, respectively. For a &lt;span&gt;&lt;math&gt;&lt;mi&gt;k&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt;-edge path in &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;O&lt;/mi&gt;&lt;mi&gt;H&lt;/mi&gt;&lt;mi&gt;C&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; if &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;k&lt;/mi&gt;&lt;mo&gt;≥&lt;/mo&gt;&lt;mn&gt;5&lt;/mn&gt;&lt;mi&gt;d&lt;/mi&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; where &lt;span&gt;&lt;math&gt;&lt;mi&gt;d&lt;/mi&gt;&lt;/math&gt;&lt;/span&gt; is a small number, the lower frequency bound is &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mn&gt;7&lt;/mn&gt;&lt;","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127264"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel complex (p,q,r)- spherical fuzzy TOPSIS framework for sustainable urban development assessment","authors":"Muhammad Rahim ,&nbsp;Shah Zeb Khan ,&nbsp;Adel M. Widyan ,&nbsp;A. Almutairi ,&nbsp;Hamiden Abd El-Wahed Khalifa","doi":"10.1016/j.eswa.2025.127288","DOIUrl":"10.1016/j.eswa.2025.127288","url":null,"abstract":"<div><div>Sustainable urban development (SUD) projects aim to enhance infrastructure, services, and facilities in cities to improve residents’ quality of life, promote economic growth, and ensure long-term sustainability. As urbanization accelerates globally, decision-makers face significant challenges in selecting projects that balance environmental, economic, social, and technological factors while aligning with strategic urban planning goals. The complexity of these decisions is further heightened by uncertainties in stakeholder opinions, evolving policy frameworks, and real-world constraints. To address these challenges, this study introduces a multi-criteria group decision-making (MCGDM) framework designed specifically for evaluating SUD projects. The proposed methodology leverages complex <span><math><mrow><mo>(</mo><mi>p</mi><mo>,</mo><mi>q</mi><mo>,</mo><mi>r</mi><mo>)</mo><mo>-</mo></mrow></math></span> spherical fuzzy sets (<span><math><msub><mrow><mi>Com</mi></mrow><mrow><mo>(</mo><mi>p</mi><mo>,</mo><mi>q</mi><mo>,</mo><mi>r</mi><mo>)</mo></mrow></msub></math></span> SFSs) to provide a more flexible and adaptive decision-making structure. These fuzzy sets allow decision-makers to model varying degrees of membership with greater adaptability, ensuring a more precise and comprehensive evaluation of alternatives. The primary contribution of this study lies in its parametric approach, which enhances the dynamism and adaptability of decision-making in complex urban development scenarios. To achieve this, the study is structured into three phases. First, we introduce the fundamental notations and operational laws of <span><math><msub><mrow><mi>Com</mi></mrow><mrow><mo>(</mo><mi>p</mi><mo>,</mo><mi>q</mi><mo>,</mo><mi>r</mi><mo>)</mo></mrow></msub></math></span> SFSs, followed by the development of aggregation operators to handle uncertainty in expert evaluations. In the second phase, we construct a TOPSIS-based approach utilizing these aggregation operators, enabling systematic ranking of SUD project alternatives. The effectiveness of the proposed approach is demonstrated through a numerical example evaluating five alternatives across seven criteria, capturing key factors influencing sustainable urban planning. Finally, the results are compared with existing decision-making methodologies to validate the robustness, effectiveness, and applicability of the proposed framework. By providing a structured, data-driven, and adaptable approach, this study aims to assist urban planners and policymakers in making more informed, balanced, and sustainable decisions for future urban development.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127288"},"PeriodicalIF":7.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive ensemble learning for efficient keyphrase extraction: Diagnosis, aggregation, and distillation","authors":"Kai Zhang ,&nbsp;Hongbo Gang ,&nbsp;Feng Hu ,&nbsp;Runlong Yu ,&nbsp;Qi Liu","doi":"10.1016/j.eswa.2025.127236","DOIUrl":"10.1016/j.eswa.2025.127236","url":null,"abstract":"<div><div>Keyphrase extraction (KE) refers to the process of identifying words or phrases that signify the primary themes of a document. Although keyphrase extraction is important in many downstream applications, including scientific document indexing, search, and question answering, the challenge lies in executing this extraction both adaptively and effectively. To this end, we propose a novel <em><strong>D</strong>istillation-based <strong>A</strong>daptive <strong>E</strong>nsemble <strong>L</strong>earning (<strong>DAEL</strong>)</em> method specifically designed for efficient keyphrase extraction, encompassing diagnosis, aggregation, and distillation processes. Specifically, we initiate with a <em>Cognitive Diagnosis Module (CDM)</em> to evaluate the diverse capabilities of individual KE models. Following this, an <em>Adaptive Aggregation Module (AAM)</em> is employed to create a weight distribution uniquely suited to each data instance. The process concludes with a <em>Knowledge Distillation Module (KDM)</em> to distill the superior performance of the ensemble model into a single model, thereby refining its efficiency and reducing computational cost. Extensive testing on real-world datasets highlights the superior performance of the proposed model. In comparison with leading-edge methods, our approach notably excels in processing text with complex structures or significant noise, marking a substantial advancement in KE effectiveness.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127236"},"PeriodicalIF":7.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aligning sequence and structure representations leveraging protein domains for function prediction","authors":"Mingqing Wang ,&nbsp;Zhiwei Nie ,&nbsp;Yonghong He ,&nbsp;Athanasios V. Vasilakos ,&nbsp;Zhixiang Ren","doi":"10.1016/j.eswa.2025.127246","DOIUrl":"10.1016/j.eswa.2025.127246","url":null,"abstract":"<div><div>Protein function prediction is traditionally approached through sequence or structural modeling, often neglecting the effective fusion of diverse data sources. Protein domains, as functionally independent building blocks, determine a protein’s biological function, yet their potential has not been fully exploited in function prediction tasks. To address this, we introduce a modality-fused neural network leveraging function-aware domain embeddings as a bridge. We pre-train these embeddings by aligning domain semantics with Gene Ontology (GO) terms and textual descriptions. Additionally, we partition proteins into sub-views based on continuous domain regions for contrastive learning, supervised by a novel triplet InfoNCE loss. Our method outperforms state-of-the-art approaches across various benchmarks, and clearly differentiates proteins carrying distinct functions compared to the competitor.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127246"},"PeriodicalIF":7.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Constraint augmented differential dynamic programming for humanoid robot automatic falling recovery","authors":"Mingyue Jin ,&nbsp;Junyao Gao ,&nbsp;Xiaokun Jin ,&nbsp;Leilei Xie ,&nbsp;Weilong Zuo ,&nbsp;Taiping Wu ,&nbsp;Jiongnan Liu ,&nbsp;Jiahang Huang","doi":"10.1016/j.eswa.2025.127286","DOIUrl":"10.1016/j.eswa.2025.127286","url":null,"abstract":"<div><div>The complex mechanical structure and multiple degrees of freedom (DoF) make the humanoid robot system unstable and nonlinear. The humanoid robot may fall accidentally while performing tasks due to these inherent properties. For this reason, research on the automatic falling recovery of humanoid robots is a very useful project. Fall recovery motion planning for humanoid robots is a complex, whole-body, multiple-contact and nonlinear optimization problem. To address this challenge, the constraint augmented differential dynamic programming (CA-DDP) algorithm is proposed in our work to enable the humanoid robot to recover from arbitrary fall posture. Firstly, the collision dynamics constraint based on the Karush–Kuhn–Tucker (KKT) condition is formulated to satisfy the robot’s dynamics constraint and absolute static stability requirement of contact points. Then, an improved derivation process is developed to modify the action-value function and its gradient and Hessian matrices during the backward pass of CA-DDP algorithm. Through CA-DDP iterations, the optimal control torque and joint trajectories are obtained with a faster convergence speed. Finally, the effectiveness of the proposed CA-DDP is verified through simulation and real-world experiments on a BHR-FCR humanoid robot automatically falling recovery. With various arbitrary initial falling postures and CA-DDP iterations, the optimal solutions enable the BHR-FCR robot to achieve the desired recovery state with over 95% recovery accuracy and computation time under 50 s. Moreover, the BHR-FCR robot successfully achieves state recovery on a flat floor, grass ground and soft cushion in real-world experiments.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127286"},"PeriodicalIF":7.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An intelligent design methodology for multi-stage loading paths of variable parameters during large-scale electric upsetting process","authors":"Yan-ze Yu ,&nbsp;Guo-zheng Quan ,&nbsp;Yu-qing Zhang ,&nbsp;Ying-ying Liu ,&nbsp;Li-he Jiang ,&nbsp;Wei Xiong ,&nbsp;Jiang Zhao","doi":"10.1016/j.eswa.2025.127316","DOIUrl":"10.1016/j.eswa.2025.127316","url":null,"abstract":"<div><div>It is a great challenge to design the multi-stage loading path of variable parameters to obtain the component with smooth shape and fine-grained microstructures during the electric upsetting process of large-scale valves. To achieve this, an intelligent design methodology was developed and applied in an electric upsetting process of Ni80A alloy. The methodology integrates backpropagation neural network (BP neural network), case-based reasoning (CBR), and parameter self-feedback adjustment coupling with finite element (FE). Firstly, a BP neural network model was developed based on the basic database to predict the initial processing parameters of components (upsetting force, current, and pre-heating time). Secondly, utilizing the CBR method, the suitable design schemes were identified by retrieving similar components, and then the multi-stages loading paths for upsetting force and current were devised. Thirdly, a subroutine of self-feedback adjustment to fine-tune the loading paths was developed and implanted into the multi-field and multi-scale coupling FE model. Finally, the optimal loading paths was obtained using the FE model until the deformed component meets the requirements of shape and grain size. The results indicated that the surface contour of component was smoother and without macroscopic defects under the optimal loading paths, with the maximum grain size refined to 103.9 μm. To further improve the automation level of the parameters design process, an expert system was developed based on the designed methodology. This work contributes to the intelligent design of processing parameters for the electric upsetting process, which provides a design framework of processing parameter in other manufacturing technologies.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127316"},"PeriodicalIF":7.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}