Abstract visual reasoning based on algebraic methods by Mingyang Zheng, Weibing Wan, Zhijun Fang

“…Through a gating fusion module, the model incrementally integrates explicit representations of objects and abstract relationships. …”
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Improving Automatic Coronary Stenosis Classification Using a Hybrid Metaheuristic with Diversity Control by Miguel-Angel Gil-Rios, Ivan Cruz-Aceves, Arturo Hernandez-Aguirre, Martha-Alicia Hernandez-Gonzalez, Sergio-Eduardo Solorio-Meza

“…<b>Conclusions</b>: The Hybrid Metaheuristic with explicit diversity control improved the classification performance of coronary stenosis cases compared to previous literature. …”
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Smoothing the Subjective Financial Risk Tolerance: Volatility and Market Implications by Wookjae Heo, Eunchan Kim

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Research on the Academic Impact of Sports in the Multidimensional Matrix Evaluation Framework by Ruiqing Zhang, Yifan Liu

“…In order to objectively assess the impact of sports scholarship on China and provide evidence to support future changes in sports academic cooperation, this study takes 269,647 academic papers produced by sports alone from 2010–2018 as the research object and integrates explicit, implicit, and performance information contained in the paper output to construct a multidimensional matrix assessment framework. …”
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LightMFF: A Simple and Efficient Ultra-Lightweight Multi-Focus Image Fusion Network by Xinzhe Xie, Zijian Lin, Buyu Guo, Shuangyan He, Yanzhen Gu, Yefei Bai, Peiliang Li

“…To address this, we propose LightMFF, an ultra-lightweight fusion network that achieves superior performance with minimal computational overhead. Our core insight is to reformulate the multi-focus fusion problem from a classification perspective to a refinement perspective, where coarse initial decision maps and explicit edge information are leveraged to guide the final decision map generation. …”
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TableBorderNet: A Table Border Extraction Network Considering Topological Regularity by Jing Yang, Shengqiang Zhou, Xialing Li, Yuchun Huang, Honglin Jiang

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SAM for Road Object Segmentation: Promising but Challenging by Alaa Atallah Almazroey, Salma kammoun Jarraya, Reem Alnanih

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Learning to solving vehicle routing problems via local–global feature fusion transformer by Wei Li, Bing Tian Dai, Xueming Yan, Junying Zou, Zhijie Liang, Jingwen Li

“…Specifically, we introduce a Distance-Assisted Multi-Head Attention (DA-MHA) mechanism that incorporates explicit spatial distance information into the attention computation, thereby preserving spatial consistency and facilitating more robust global representation learning. …”
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Document-Level Neural Machine Translation With Document Embeddings by Linxing Zhu, Shu Jiang, Hai Zhao, Zuchao Li, Jiashuang Huang, Weiping Ding, Bao-Liang Lu

“…Standard neural machine translation (NMT) assumes that document-level context information is irrespective. Most existing document-level NMT methods are satisfied with a smattering sense of shallow document-level information, such as using a few context sentences surrounding the source sentence as document-level information. …”
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Self-Organizing TDMA: A Distributed Contention-Resolution MAC Protocol by Mahsa Derakhshani, Yahya Khan, Duc Tuong Nguyen, Saeedeh Parsaeefard, Atoosa Dalili Shoaei, Tho Le-Ngoc

“…These are achieved by adapting the transmission-opportunity duration to the common idle/busy channel state information acquired by each node, without any explicit message passing among nodes. …”
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Learning Distributed Parameters of Land Surface Hydrologic Models Using a Generative Adversarial Network by Ruochen Sun, Baoxiang Pan, Qingyun Duan

“…Notably, due to the discriminator's explicit identification of model spatial biases, GAN‐PO excels in maintaining spatial consistency, outperforming the state‐of‐the‐art differentiable parameter learning (dPL) method in terms of model spatial performance.…”
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Energy Management Strategy for Fuel Cell Vehicles Based on Online Driving Condition Recognition Using Dual-Model Predictive Control by Fuxiang Li, Xiaolin Wang, Xucong Bao, Ziyu Wang, Ruixuan Li

“…Secondly, to enhance the real-time performance and control effectiveness of the EMS, model predictive control (MPC) and explicit model predictive control (eMPC) are established based on a unified optimization objective and constraints. …”
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A simple interpolation-based data augmentation method for implicit sentiment identification by Yuxia Zhao, Mahpirat Mamat, Alimjan Aysa, Kurban Ubul

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A Lightweight Transformer-Based Spatiotemporal Analysis Prediction Algorithm for High-Dimensional Meteorological Data by Yinghao Tan, Junfeng Wu, Yihang Liu, Shiyu Shen, Xia Xu, Bin Pan

“…SA-Fit introduces a lightweight Transformer-based spatiotemporal analysis network to encode spatiotemporal information, which can integrate the interaction information between different coordinates in the data. …”
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Anomaly Detection and Business Process Orchestration for Low-Code Platform in Power System Based on Deep-Cross Model With Data Balancing by Jin Huang, Ming Sheng Xu, Chang Ming Zhu, Guo An Wang

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A Knowledge-Driven Approach to Automate Job Hazard Analysis Process by Sonali Pandithawatta, Raufdeen Rameezdeen, Seungjun Ahn, Christopher W. K. Chow, Nima Gorjian

“…The validation of the JHAKG was conducted in two stages: the first stage validated the information extraction process by calculating performance metrics, while the second stage validated the data population process and the JHAKG's reasoning capability. …”
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The impact of task simplification in skill acquisition for young children from a simplexity approach by Jia Yi Chow, Wan Ting Loh, Karen Lai Fong Low, Ludovic Seifert

“…It was found that participants provided with simplified informational constraints (Nonlinear Pedagogy condition) learnt the badminton serving task as well as participants provided with explicit information constraints and with a focus on repeating consistent outcome (Linear Pedagogy condition). …”
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LLM-DSK: A Domain-Specific Semantic Knowledge-Guided Ocean Environment Prediction Method Based on Large Language Models by Ning Song, Caichao Lv, Jie Nie, Min Ye, Enyuan Zhao, Jun Ma, Xiong Liu, Zhiqiang Wei

“…LLM-DSK comprises three core modules: 1) a spatiotemporal feature extraction module that utilizes geographic data (e.g., latitude, longitude, wind fields, and land&#x2013;sea boundaries) to extract key domain-relevant spatiotemporal features; 2) a semantic encoding module that employs an attention mechanism to align these features with the vocabulary of LLMs, enabling cross-modal alignment between oceanic and natural language domains to enrich semantic representations; and 3) an LLM-based prediction module driven by domain-specific prompts that integrate geographic information and statistical indicators. We validated LLM-DSK using remote sensing data (sea surface temperature) and reanalysis data (significant wave height), and the results demonstrate that LLM-DSK achieves superior predictive performance compared to state-of-the-art (SOTA) models.…”
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The function of “looking-at-nothing” for sequential sensorimotor tasks: Eye movements to remembered action-target locations by Rebecca Martina Foerster

“…When performing manual actions, eye movements precede hand movements to target locations: Before we grasp an object, we look at it. …”
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Comparative study of feedback linearization control for IM taking into account magnetic saturation effects by Mustapha Es-Semyhy, Abdellfattah Ba-Razzouk, Mustapha El haroussi, Abdelilah Hilali

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