检索结果-内蒙古大学图书馆

A Transfer Learning-Based Approach for Fatigue Detection Through the Fusion of Physiological Signals

IEEE Sensors Journal 2025年第9期25卷 15750-15760页

作者： Kakhi, Kourosh Asgharnezhad, Hamzeh Khosravi, Abbas Alizadehsani, Roohallah Rajendra Acharya, U. Institute for Intelligent Systems Research and Innovation Deakin University Waurn PondsVIC3216 Australia University of Southern Queensland School of Mathematics Physics and Computing ToowoombaQLD4350 Australia

The improvement of road safety and the reduction of accident occurrences globally necessitates the detection of driver fatigue. This article explores the current research gap in identifying the most effective physiological signals for fatigue detection. Through a comprehensive analysis, physiological signals are converted into images and processed using pretrained deep neural networks (DNNs) to detect patterns indicative of fatigue. This research stands as a pioneering effort in fatigue detection, examining various combinations of physiological signals, pretrained DNNs, and classification methods within a dataset. Our thorough evaluation demonstrates that multiple classifiers using ECG signals can achieve near-perfect performance metrics (accuracy, area under the curve, precision, and recall) on test sets. These highlight the transformative potential of artificial intelligence (AI) technologies in redefining current systems for monitoring driver fatigue, marking a significant leap forward in the application of AI for ensuring driver safety and preventing accidents caused by fatigue. The findings reinforce the critical role of incorporating advanced AI techniques into driver-assistance systems to develop more reliable and efficient fatigue detection solutions. © 2001-2012 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Efficient Algorithms for Minimizing the Kirchhoff Index via Adding Edges

引用

IEEE Transactions on Knowledge and Data Engineering 2025年第6期37卷 3342-3355页

作者： Zhou, Xiaotian Zehmakan, Ahad N. Zhang, Zhongzhi Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China School of Computing Australian National University CanberraACT2601 Australia Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China

The Kirchhoff index, which is the sum of the resistance distance between every pair of nodes in a network, is a key metric for gauging network performance, where lower values signify enhanced performance. In this paper, we study the problem of minimizing the Kirchhoff index by adding edges. We first provide a greedy algorithm for solving this problem and give an analysis of its quality based on the bounds of the submodularity ratio and the curvature. Then, we introduce a gradient-based greedy algorithm as a new paradigm to solve this problem. To accelerate the computation cost, we leverage geometric properties, convex hull approximation, and approximation of the projected coordinate of each point. To further improve this algorithm, we use pre-pruning and fast update techniques, making it particularly suitable for large networks. Our proposed algorithms have nearly-linear time complexity. We provide extensive experiments on ten real networks to evaluate the quality of our algorithms. The results demonstrate that our proposed algorithms outperform the state-of-the-art methods in terms of efficiency and effectiveness. Moreover, our algorithms are scalable to large graphs with over 5 million nodes and 12 million edges. © 2025 IEEE.

关键词： Graph algorithms

来源：评论

学校读者我要写书评

暂无评论

Malware Detection and Analysis in Android Applications with Mobile Security Framework (MobSF) Using a Permission-Based Approach 12th

Malware Detection and Analysis in Android Applications with ...

引用

12th International Conference on Frontiers of intelligent computing: Theory and Applications, FICTA 2024

作者： Kizito, Mark Homayounvala, Elaheh Kazemian, Hassan Araujo, Istteffanny Intelligent Systems Research Group School of Computing and Digital Media London Metropolitan University 166-220 Holloway Rd LondonN7 8DB United Kingdom

ISBN: (纸本)9789819601424

This paper examines security concerns in Android applications arising from violations to the principle of least privilege. Using mobile security framework (MobSF), static and dynamic analysis techniques were used in evaluating how non-essential permission groups that are not core to application functions greatly increase risks of unauthorized system access by attackers, data breaches and privacy concerns, enlarged attack surfaces, and hijacking system resources among others. A permission-based approach systematically identifies malware and highlights dangerous permission groups that magnify security risks. The findings of this research study emphasis on meticulous auditing of permissions to prevent security threats in Android applications and to safeguard user-sensitive data. The conducted experiments compared essential core permissions to non-essential ones regarding application functionality and overall system security. It was also noted that background permissions potentially pose a great deal of risk to security when granted without proper rationale as this increases attack surfaces within the application itself. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Android malware

来源：评论

学校读者我要写书评

暂无评论

Seeing through Dense Fog with an intelligent Adaptive Dehazing System

引用

IEEE Sensors Journal 2025年第10期25卷 17696-17705页

作者： Chen, Pengyun Cao, Ning Xu, Ziqin Cui, Shuang Jin, Shaohui Liu, Hao Xu, Mingliang Zhengzhou University School of Computer Science and Artificial Intelligence Zhengzhou450001 China National University of Defense Technology College of Advanced Interdisciplinary Studies Changsha410073 China Ministry of Education Engineering Research Center of Intelligent Swarm Systems Zhengzhou450001 China National Super-computing Center Zhengzhou450001 China

Most existing image dehazing methods are mainly suitable for synthetic datasets and often perform poorly in real-world, complex hazy scenarios. To address this issue, this paper proposes an intelligent adaptive dehazing system that integrates range-gated imaging with deep learning, combining image acquisition and restoration for enhanced dehazing performance. The range-gated imaging system reduces scattered light interference. However, our approach primarily focuses on enhancing image quality through advanced dehazing methods. Specifically, we introduce the MSCENAFormer dehazing network, which achieves high-quality reconstruction of target scenes in dense fog by effectively removing fog and improving visibility. The core modules of MSCENAFormer include the multi-scale enhanced neighborhood attention module (MSENA) and the comprehensive attention refinement module (CARM). MSENA is designed to capture rich local information in harsh environment, improving the dehazing effect and enhancing image details. CARM integrates the local and global information to optimize the visual effect further. In addition, the adaptive feature mixing module (AFM) is used to fuse multi-scale features for better performance. To validate the performance of our method, we utilize our lab-collected non-homogeneous haze real dataset, O-ITDF, along with the public datasets NH-HAZE, NTIRE2021 and NTIRE2023. Experimental results demonstrate that our proposed MSCENAFormer outperforms many methods. We share our code at https://***/NingCao-zzu/MSCENAFormer. © 2001-2012 IEEE.

关键词： Light interference

来源：评论

学校读者我要写书评

暂无评论

Automating Adjudication of Cardiovascular Events Using Large Language Models

arXiv

引用

arXiv 2025年

作者： Sivarajkumar, Sonish Ameri, Kimia Li, Chuqin Wang, Yanshan Jiang, Min Advanced Analytics and Data Sciences Eli Lilly and Company United States Intelligent Systems Program School of Computing and Information University of Pittsburgh United States

Cardiovascular events, such as heart attacks and strokes, remain a leading cause of mortality globally, necessitating meticulous monitoring and adjudication in clinical trials. This process, traditionally performed manually by clinical experts, is time-consuming, resource-intensive, and prone to inter-reviewer variability, potentially introducing bias and hindering trial progress. This study addresses these critical limitations by presenting a novel framework for automating the adjudication of cardiovascular events in clinical trials using Large Language Models (LLMs). We developed a two-stage approach: first, employing an LLM-based pipeline for event information extraction from unstructured clinical data and second, using an LLM-based adjudication process guided by a Tree of Thoughts approach and clinical endpoint committee (CEC) guidelines. Using cardiovascular event-specific clinical trial data, the framework achieved an F1-score of 0.82 for event extraction and an accuracy of 0.68 for adjudication. Furthermore, we introduce the CLEART score, a novel, automated metric specifically designed for evaluating the quality of AI-generated clinical reasoning in adjudicating cardiovascular events. This approach demonstrates significant potential for substantially reducing adjudication time and costs while maintaining high-quality, consistent, and auditable outcomes in clinical trials. The reduced variability and enhanced standardization also allows for faster identification and mitigation of risks associated with cardiovascular therapies. Copyright © 2025, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A NEW HOPE: contextual privacy policies for mobile applications and an approach toward automated generation 24

A NEW HOPE: contextual privacy policies for mobile applicati...

引用

Proceedings of the 33rd USENIX Conference on Security Symposium

作者： Shidong Pan Zhen Tao Thong Hoang Dawen Zhang Tianshi Li Zhenchang Xing Xiwei Xu Mark Staples Thierry Rakotoarivelo David Lo School of Computing Australian National University and Software and Computational Systems Research Program CSIRO's Data61 Software and Computational Systems Research Program CSIRO's Data61 Khoury College of Computer Sciences Northeastern University School of Computing and Information Systems Singapore Management University

ISBN: (纸本)9781939133441

Privacy policies have emerged as the predominant approach to conveying privacy notices to mobile application users. In an effort to enhance both readability and user engagement, the concept of contextual privacy policies (CPPs) has been proposed by researchers. The aim of CPPs is to fragment privacy policies into concise snippets, displaying them only within the corresponding contexts within the application's graphical user interfaces (GUIs). In this paper, we first formulate CPP in mobile application scenario, and then present a novel multimodal framework, named SEEPRIVACY, specifically designed to automatically generate CPPs for mobile applications. This method uniquely integrates vision-based GUI understanding with privacy policy analysis, achieving 0.88 precision and 0.90 recall to detect contexts, as well as 0.98 precision and 0.96 recall in extracting corresponding policy segments. A human evaluation shows that 77% of the extracted privacy policy segments were perceived as well-aligned with the detected contexts. These findings suggest that SEEPRIVACY could serve as a significant tool for bolstering user interaction with, and understanding of, privacy policies. Furthermore, our solution has the potential to make privacy notices more accessible and inclusive, thus appealing to a broader demographic. A demonstration of our work can be accessed at https://***/SeePrivacy/

关键词：

来源：评论

学校读者我要写书评

暂无评论

Learning to Design Transceiver for Integrated Sensing and Communications: A Satellite Communications Perspective

引用

IEEE Transactions on Wireless Communications 2025年

作者： Lukito, William D. Xiang, Wei Liu, Chang Lai, Phu Cheng, Peng Mao, Guoqiang La Trobe University School of Computing Engineering and Mathematical Sciences MelbourneVIC3086 Australia Southeast University Research Laboratory of Smart Driving and Intelligent Transportation Systems Jiangsu Nanjing211102 China

With its dual-functional advantages, integrated sensing and communications (ISAC) technologies can be further extended to satellite communications, enhancing global coverage services. However, achieving vast coverage would result in significant delays and considerable path losses. Motivated by this, in this paper, we focus on satellite-based ISAC (S-ISAC) systems and propose a general transceiver design framework incorporating both transmit waveform and receive filter. Unlike existing approaches, our approach uses a predictive joint transmit waveform and receive filter design that eliminates the need of channel estimation, thereby reducing time overhead. Additionally, a versatile weighting mechanism is designed to allow flexible prioritization between communications and sensing. To tackle the intractability of the ISAC transceiver design problem, we adopt a data-driven deep learning-based approach, where the model learns to design the transmit waveform and receive filter from historical channel data. Specifically, we propose a predictive optimization network (PONet), leveraging convolutional layers and a Transformer encoder to capture long-term spatial-temporal features and facilitate the learning capability. Numerical results demonstrate the effectiveness of the proposed PONet in terms of communications and sensing rates in S-ISAC networks in various system settings. © 2002-2012 IEEE.

关键词： Satellite communication systems

来源：评论

学校读者我要写书评

暂无评论

Trajectory tracking of a SCARA robot using intelligent active force control

引用

Neural computing and Applications 2025年 1-26页

作者： Huang, Hanyi Arogbonlo, Adetokunbo Yu, Samson Kwek, Lee Chung Lim, Chee Peng Institute for Intelligent Systems Research and Innovation Deakin University 75 Pigdons Rd Waurn PondsVIC3216 Australia Swinburne Research Office Swinburne University of Technology John Street HawthornVIC3122 Australia School of Engineering Deakin University 75 Pigdons Rd Waurn PondsVIC3216 Australia Faculty of Engineering and Technology Multimedia University 75450 Ayer Keroh Melaka Bukit Beruang75450 Malaysia Department of Computing Technologies Swinburne University of Technology John Street HawthornVIC3122 Australia

Trajectory tracking with disturbance rejection is a challenging problem in robotics, particularly in applications involving selective compliance articulated robot arms (SCARA). In this paper, we address the trajectory tracking problem with the presence of disturbances in applying SCARA, by designing controllers with active force control (AFC)-based control methods. AFC has shown potential in disturbance rejection, and its per efficiency of the designed controllers, we integrated different machine learning techniques into the AFC controller, including iterative learning (IL), adaptive neuro-fuzzy inference system (ANFIS) and reinforcement learning (RL). Two case studies were conducted and compared with two different benchmark controllers to validate intelligent AFC-based controllers: a port-controlled Hamiltonian (PCH) control and a hybrid proportional-integral-derivative (PID) control. The results demonstrate that the AFC-based controllers consistently outperform the benchmark methods. Specifically, in Case 1, the AFC-RL controller achieves a 99.99% improvement in root mean square error for joint 1 compared to the hybrid PID control. In Case 2, the AFC-RL controller outperforms the AFC-IL controller in trajectory tracking accuracy by 98.71%. Also, disturbance rejection ability was tested on the AFC-based controllers with various types of disturbances. Among the three AFC-based controllers, AFC-RL shows the best performance. The findings highlight the potential of integrating machine learning into AFC for more accurate and efficient robotic control. © The Author(s) 2025.

关键词： Disturbance rejection

来源：评论

学校读者我要写书评

暂无评论

Efficient Algorithms for Minimizing the Kirchhoff Index via Adding Edges

arXiv

引用

arXiv 2025年

作者： Zhou, Xiaotian Zehmakan, Ahad N. Zhang, Zhongzhi Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China School of Computing Australian National University Canberra Australia

关键词： Consensus algorithm

来源：评论

学校读者我要写书评

暂无评论

Quantum-Chiplet: A Novel Python-Based Efficient and Scalable Design Methodology for Quantum Circuit Verification and Implementation

arXiv

引用

arXiv 2025年

作者： Kao, Yu-Ting Lu, Hao-Yu Chang, Yeong-Jar Lu, Darsen Industrial Technology Research Institute Taiwan Intelligent Computing Industrial Doctorate Program Miin Wu School of Computing National Cheng Kung University Taiwan Institute of Microelectronics Department of Electrical Engineering National Cheng Kung University Taiwan

Analysis and verification of quantum circuits are highly challenging, given the exponential dependence of the number of states on the number of qubits. For analytical derivation, we propose a new quantum polynomial representation (QPR) to facilitate the analysis of massively parallel quantum computation and detect subtle errors. For the verification of quantum circuits, we introduce Quantum-Chiplet, a hierarchical quantum behavior modeling methodology that facilitates rapid integration and simulation. Each chiplet is systematically transformed into quantum gates. For circuits involving n qubits and k quantum gates, the design complexity is reduced from "greater than O(2n)" to O(k). This approach provides an open-source solution, enabling a highly customized solution for quantum circuit simulation within the native Python environment, thereby reducing reliance on traditional simulation packages. A quantum amplitude estimation example demonstrates that this method significantly improves the design process, with more than 10x speed-up compared to IBM Qiskit at 14 qubits. Copyright © 2025, The Authors. All rights reserved.

关键词： Qubits

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：