Risk assessment of autonomous vehicle based on six-dimensional semantic space by Yanan CHEN, Ang LI, Dan WU

“…To address the problems of inadequate extraction of risk elements and low robustness of risk scenario assessment in autonomous vehicles, a risk assessment framework based on six-dimensional semantic space was proposed, which included risk element extraction based on six-dimensional semantic space and risk scenario assessment based on knowledge graph.Formerly, the semantic space was constructed with RGB and IR data mapped, and rich features were extracted using inter-modal correlations for explicit and potential risk elements.Subsequently, risk elements were distilled into a knowledge graph by semantic role annotation and entity fusion, and an inference method was designed by combining node completion and risk level function for accurate risk assessment.Simulations show that the proposed method surpasses current MSMatch and iSQRT-COV-Net in accuracy, false/missed alarm rate, and processing time.…”
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Dual-Layer Fusion Knowledge Reasoning with Enhanced Multi-modal Features by JING Boxiang, WANG Hairong, WANG Tong, YANG Zhenye

“…The multi-modal feature fusion module adopts a two-layer fusion strategy combining low-rank multi-modal feature fusion and decision fusion to realize the dynamic and complex interaction of multi-modal data between and within modes, and comprehensively considers the contribution degree of each mode in inference to obtain more comprehensive prediction results. …”
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A Spatial-Network Approach to Assessing Transportation Resilience in Disaster-Prone Urban Areas by Francesco Rouhana, Dima Jawad

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A Chinese Few-Shot Named-Entity Recognition Model Based on Multi-Label Prompts and Boundary Information by Cong Zhou, Baohua Huang, Yunjie Ling

“…Activating the relevant parameters in PLM associated with the corresponding entity labels through the prompt information improved the model’s performance in entity recognition under small-sample data. Secondly, by using a Graph Attention Network (GAT) to construct the boundary information extraction module, we integrated boundary information with text features, allowing the model to pay more attention to features near the boundaries when recognizing entities, thereby improving the accuracy of entity boundary recognition. …”
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Investigating surgical risk in coronary artery disease: Utilizing ordinal regression for predictive modeling by Hewir Abdulqadir Khidir, Azhin Mohammed Khudhur, Dler Hussein Kadir, Nozad H. Mahmood, Dlshad Mahmood Saleh

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Advancing Mental Health Care: Intelligent Assessments and Automated Generation of Personalized Advice via M.I.N.I and RoBERTa by Yuezhong Wu, Huan Xie, Lin Gu, Rongrong Chen, Shanshan Chen, Fanglan Wang, Yiwen Liu, Lingjiao Chen, Jinsong Tang

“…As mental health issues become increasingly prominent, we are now facing challenges such as the severe unequal distribution of medical resources and low diagnostic efficiency. This paper integrates finite state machines, retrieval algorithms, semantic-matching models, and medical-knowledge graphs to design an innovative intelligent auxiliary evaluation tool and a personalized medical-advice generation application, aiming to improve the efficiency of mental health assessments and the provision of personalized medical advice. …”
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A Novel Algorithm for a Low-Cost, Curvature-Continuous Smooth Path with Multiple Constraints on a Cost-Assigned Flat Map by Xu Du, Lu Yang

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Enhancing Deep Hashing With GCN-Based Models for Efficient Similarity Search by Sooin Kim, Seonghyun Min, Wongyum Kim, Donghoon Kim, Doosung Hwang

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Node Classification Based on Kolmogorov-Arnold Networks by YUAN Lining, FENG Wengang, LIU Zhao

“…Most graph deep learning methods extract feature information from graph data by using learnable weights and specific activation functions. …”
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The self supervised multimodal semantic transmission mechanism for complex network environments by Jiajun Zou, Zhiping Wan, Feng Wang, Shitong Ye, Shaojiang Liu

“…The sending end employs a self-supervised conditional variational autoencoder and Transformer-DRL-based dynamic semantic compression strategy to intelligently filter and transmit the most core semantic information from video, radar, and LiDAR data. The receiving end combines Transformer and graph neural networks for deep decoding and feature fusion of multimodal data, while also using reinforcement learning self-supervised multi-task optimization engine to collaboratively enhance multiple task scenarios (such as traffic accident detection and vehicle behavior recognition). …”
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Open-World Semi-Supervised Learning for fMRI Analysis to Diagnose Psychiatric Disease by Chang Hu, Yihong Dong, Shoubo Peng, Yuehan Wu

“…Due to the incomplete nature of cognitive testing data and human subjective biases, accurately diagnosing mental disease using functional magnetic resonance imaging (fMRI) data poses a challenging task. …”
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Exploring Gait Recognition in Wild Nighttime Scenes by Haotian Li, Wenjuan Gong, Yutong Li, Yikai Wu, Kechen Li, Jordi Gonzàlez

“…Notably, many gait recognition tasks occur under low-light conditions at night. At present, research on gait recognition in nocturnal environments is relatively limited, and effective methods for nighttime gait recognition are lacking. …”
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Stillbirth rates, trend and distribution in the Volta region, Ghana: findings from institutional data analysis, 2018–2022 by Chrysantus Kubio, Williams Azumah Abanga, Ignatius Aklikpe, Dzidefo Kofi Agbavor, Victor Zeng, Samuel Adolf Bosoka, Desmond Klu, Senanu Kwesi Djokoto

“…Microsoft Excel 2016 and ArcGIS 10.4 were used for the data analysis. Descriptive statistics were performed with results presented in a table, graph, and map. …”
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A Caputo–Fabrizio fractional-order model with MCMC estimation for rabies transmission dynamics in a multi-host population by Jufren Zakayo Ndendya, Joshua A. Mwasunda, Stephen Edward, Nyimvua Shaban

“…The effective reproduction number is derived through a graph-theoretic approach. Parameter estimation is performed using Markov Chain Monte Carlo methods applied to real and synthetic data. …”
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Task Mapping and Scheduling With Uneven Data Partition on Homogeneous and Single-ISA Heterogeneous CPUs in Model-Based Parallelization by Shanwen Wu, Satoshi Kumano, Kei Marume, Masato Edahiro

“…Existing methods that rely on even data partitioning may result in suboptimal performance. …”
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Hyperspectral Band Selection with Unique Pixel Extraction and Adaptive Neighbor Clustering by Bing Han, Mingqing Liu, Zhenyu Ma, Ke Zhang, Yanke Xu, Jingyu Wang, Qi Wang

“…First, in consideration of the characteristics of HSI data and tasks, unique pixels are obtained with a low-rank representation, where the importance of bands is analyzed from both spectral and spatial perspectives. …”
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Prevalence and associated factors of active trachoma among children of 1 to 9 years in low-income countries of Africa: a systematic review and meta-analysis by Leykun Berhanu, Gete Berihun, Belay Desye, Abebe Kassa Geto, Chala Daba

“…The data was extracted using an Excel sheet and exported to STATA version 17 software. …”
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Accelerometer based independent and combined associations of physical activity and sedentary time on physical fitness in preschool children: a cross-sectional study by Chunyi Fang, Longkai Li, Zhenhua Jin, Changshuang He, Feng Liang, Xiangming Ye, Yaofei Lu, Minghui Quan

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Effect of depressive symptoms on treatment response in patients with axSpA: data from the RABBIT-SpA register by Xenofon Baraliakos, Denis Poddubnyy, Anja Strangfeld, Anja Weiß, Anne Constanze Regierer, Jacqueline Detert, Silke Zinke, Andreas Reich, Lisa Lindner, Carsten Stille

“…Objectives This analysis aimed to evaluate the effect of depressive symptoms on treatment outcomes in patients with axial spondyloarthritis (axSpA), focusing on low disease activity (LDA) and inactive disease (ID) at 3 and 6 months after the start of a new systemic therapy.Methods This analysis used data from the longitudinal, observational RABBIT-SpA register. …”
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Research and Construction of Knowledge Map of Golden Pomfret Based on LA-CANER Model by Xiaohong Peng, Hongbin Jiang, Jing Chen, Mingxin Liu, Xiao Chen

“…First, by integrating and standardizing multi-source information, the knowledge graph offers comprehensive and accurate data, supporting decision-making for aquaculture management. …”
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