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arXiv 2023年

作者： Lu, Chengjie Ali, Shaukat Yue, Tao The Department of Engineering Complex Software Systems Simula Research Laboratory Oslo0258 Norway Simula Research Laboratory Norway Oslo Metropolitan University Oslo0258 Norway The School of Computer Science and Engineering Beihang University Beijing100191 China

Testing autonomous vehicles (AVs) under various environmental scenarios that lead the vehicles to unsafe situations is known to be challenging. Given the infinite possible environmental scenarios, it is essential to find critical scenarios efficiently. To this end, we propose a novel testing method, named EpiTESTER, by taking inspiration from epigenetics, which enables species to adapt to sudden environmental changes. In particular, EpiTESTER adopts gene silencing as its epigenetic mechanism, which regulates gene expression to prevent the expression of a certain gene, and the probability of gene expression is dynamically computed as the environment changes. Given different data modalities (e.g., images, lidar point clouds) in the context of AV, EpiTESTER benefits from a multi-model fusion transformer to extract high-level feature representations from environmental factors and then calculates probabilities based on these features with the attention mechanism. To assess the cost-effectiveness of EpiTESTER, we compare it with a classical genetic algorithm (GA) (i.e., without any epigenetic mechanism implemented) and EpiTESTER with equal probability for each gene. We evaluate EpiTESTER with four initial environments from CARLA, an open-source simulator for autonomous driving research, and an end-to-end AV controller, Interfuser. Our results show that EpiTESTER achieved a promising performance in identifying critical scenarios compared to the baselines, showing that applying epigenetic mechanisms is a good option for solving practical problems. © 2023, CC BY.

关键词： Autonomous vehicles

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High-Fidelity and High-Efficiency Talking Portrait Synthesis With Detail-Aware Neural Radiance Fields

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IEEE Transactions on Visualization and computer Graphics 2024年 PP卷 PP-PP页

作者： Wang, Muyu Zhao, Sanyuan Dong, Xingping Shen, Jianbing Wuhan University School of Computer Science National Engineering Research Center for Multimedia Software Institute of Artificial Intelligence Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan430072 China Beijing Institute of Technology School of Computer Science Beijing China University of Macau State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science China

In this paper, we propose a novel rendering framework based on neural radiance fields (NeRF) named HH-NeRF that can generate high-resolution audio-driven talking portrait videos with high fidelity and fast rendering. Specifically, our framework includes a detail-aware NeRF module and an efficient conditional super-resolution module. Firstly, a detail-aware NeRF is proposed to efficiently generate a high-fidelity low-resolution talking head, by using the encoded volume density estimation and audio-eye-aware color calculation. This module can capture natural eye blinks and high-frequency details, and maintain a similar rendering time as previous fast methods. Secondly, we present an efficient conditional super-resolution module on the dynamic scene to directly generate the high-resolution portrait with our low-resolution head. Incorporated with the prior information, such as depth map and audio features, our new proposed efficient conditional super resolution module can adopt a lightweight network to efficiently generate realistic and distinct high-resolution videos. Extensive experiments demonstrate that our method can generate more distinct and fidelity talking portraits on high resolution (900 × 900) videos compared to state-of-the-art methods. Our code is available at https://***/muyuWang/HHNeRF. © 1995-2012 IEEE.

关键词： Rendering (computer graphics)

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Towards a Grid of Sensors for Telemedicine

Towards a Grid of Sensors for Telemedicine

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Annual IEEE Symposium on computer-Based Medical systems

作者： C.O. Rolim F.L. Koch M. Assuncao C.B. Westphall Network and Management Laboratory Federal University of Santa Catarina Florianopolis Santa Catarina Brazil Grid Computing and Distributed Systems Laboratory and NICTA Victoria Laboratory Department of Computer Science and Software Engineering University of Melbourne Melbourne VIC Australia

In this article, we describe a grid of sensors to collect patients' vital data and to allow real time monitoring of patients in heath-care centres. We analyse the problem scenario and identify the components involved towards the construction of an integrated and homogeneous management system. Finally, we present a case study to demonstrate the applicability of our approach

关键词： Telemedicine Grid computing Laboratories Real time systems Sensor systems Patient monitoring computerized monitoring Data security Ontologies computer architecture

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Task scheduling for data aggregation in Fault-Tolerant wireless sensor networks

Task scheduling for data aggregation in Fault-Tolerant wirel...

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IEEE International Conference on systems, Man and Cybernetics

作者： Hang Qin Lin Qiu Software Engineering State Key Laboratory Wuhan University of China Wuhan China Computer School Yangtze University Jingzhou China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University of China Wuhan China

This paper attempts to identify the reliability assessment in terms of data aggregation in wireless sensor networks. With the sensor nodes' Bayesian lifetime model, the fault ratio of sensing data among a pair of nodes in the worst case is derived. Leveraging the property of exponential aggregation latency distribution, the optimizing strategy, namely fault-tolerant scheduling for aggregation (FTSA) is proposed. Quantitative analysis of the task scheduling is also presented, which is used for reducing the latency of data aggregation. Moreover, the sensor fault probability and aggregation latency are initially introduced into the data collection scheduling process, and it mathematically shows that the fused local estimate can obtain a global estimation with the reliable data acquisition framework. Performance evaluations of the proposed approach with both sensor node faults and scheduling policy are carried out. These results show that the proposed approach outperforms the earlier algorithms in terms of latency designed without regard to sensor faults.

关键词： Fault tolerance Wireless sensor networks Delay Intelligent sensors Sensor phenomena and characterization Biosensors computer networks Laboratories Bayesian methods Military computing

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Detection of Detonators in Baggage Using Deep CNN Architecture: A Comparative Study of Contrast Enhancement and Feature Extraction Methods 8

Detection of Detonators in Baggage Using Deep CNN Architectu...

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8th IEEE International Conference on Image and Signal Processing and their Applications, ISPA 2024

作者： Lynda, Oulhissane Mostefa, Merah Moldovanu, Simona Moraru, Luminita LSS Faculty of Science and Technology Abdelhamid Ibn Badis University Laboratory of Signals and Systems Mostaganem Algeria Faculty of Automation Computers Electrical Engineering and Electronics Dunarea de Jos University of Galati Modelling & Simulation Laboratory MSlab Department of Computer Science and Information Technology Galati Romania Faculty of Sciences and Environment Modelling & Simulation Laboratory Dunarea de Jos University of Galati MSlab Department of Chemistry Physics & Environment Galati Romania

ISBN: (纸本)9798350309249

Visual inspection of dual-energy X-ray radiographic images of cabin baggage requires high performance, but is hindered by various challenges such as low target prevalence, variability in target visibility, possible presence of multiple targets, and security personnel fatigue and inattention. Artificial intelligence (AI) techniques, particularly deep convolutional neural networks (CNNs), have shown promise in improving the automatic detection of explosives, even with low-resolution radiographic images, especially in high baggage throughput scenarios. In this paper, we focus on the detection of detonators as components of improvised explosive devices. The proposed approach involves comparing two experiments implemented in a deep CNN architecture using TensorFlow and Keras libraries. In the first experiment, raw dual-energy radiographic images without any enhancement were used. The second experiment includes three methods for contrast enhancement and feature extraction: the Contrast Limited Adaptive Histogram Equalization (CLAHE) method, the wavelet transform-based method, and the mixed CLAHE RGB-Wavelet method. In the latter two methods, Haar, Db2, Coif2, and Sym2 mother wavelet functions at two levels (HH and HL) were employed. The analysis of results focuses on a comparative study of performance measures such as accuracy, precision, recall, and F1 score. It was found that the preprocessing methods used in experiment 2, for the two evaluated classes (detonator and no detonator), achieved higher accuracy compared to the raw radiographic images used in experiment 1 (98.08%). The highest accuracies in experiment 2, with a value of 100%, were obtained with the CLAHE method (green channel in grayscale, blue channel in grayscale, and RGB channels) and the wavelet transform method with Haar mother wavelet at two levels HL © 2024 IEEE.

关键词： Feature extraction

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Distributed circle formation control over directed networks with communication constraints ⁎

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IFAC-PapersOnLine 2019年第3期52卷 108-113页

作者： Peng Xu Jiayan Wen Chen Wang Guangming Xie College of Electrical and Information Engineering Guangxi University of Science and Technology Liuzhou 545006 China National Engineering Research Center for Software Engineering Peking University Beijing 100871 China The State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing100871 China

This paper investigates distributed circle formation problems of multi-agent systems (MAS) subject to limited information communication under a class of weight-unbalanced directed graphs, in which the communication topology contains a directed spanning tree and each agent can only perceive the distances from itself to the nearest neighbor in counterclockwise direction as well as the counterpart in the clockwise direction. Towards this end, a novel algorithm combined with an encoder-decoder framework has been proposed. We show that, under the proposed policy, the resulting network executions can drive the states of all mobile agents to converge to some expected equilibrium point. Numerical simulation results have been given to demonstrate the effectiveness of the proposed algorithm.

关键词： Multi-agent systems Communication Bandwidth Directed Network Circle Formation Control

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A Design of Firewall Based on Feedback of Intrusion Detection System in Cloud Environment

A Design of Firewall Based on Feedback of Intrusion Detectio...

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IEEE Global Communications Conference

作者： Xiaoyu Ma Xiao Fu Bin Luo Xiaojiang Du Mohsen Guizani State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Dept. of Computer and Information Sciences Temple University Philadelphia USA Dept. of Computer Science and Engineering Qatar University Qatar

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Security is critical to cloud services, this paper introduces a design of firewall, which based on IDS's feedback t change rules in order to detect attack flexible. It combines firewall and Intrusion Detection systems (IDS) by using Intrusion Detection systems, which detects ICMP, TCP, UDP attacks. Usually, a cloud service is a service built on a virtual machine. The virtual device is virtualized to achieve the purpose of multiplexing. Therefore, if you want to implement cloud security detection, you can listen to the physical device's network card. There are two types of Intrusion Detection System, one is host-based intrusion detection system (HIDS) and another is network intrusion detection system (NIDS). What's more, in order to highlight the importance of the firewall, the IDS monitoring data is analyzed and added to the firewall's defense strategy automatically. Finally, we measure the effectiveness of the system by False Negative (FN) and False Positive (FP), and verify that feedback plays a crucial role in improving the effectiveness of the system, improving the efficiency of the entire system filtering attacks.

关键词： Monitoring Cloud computing Firewalls (computing) Filtering Intrusion detection Virtual machining

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Management towards reducing cloud usage costs

Management towards reducing cloud usage costs

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Latin American Network Operations and Management Symposium, (LANOMS)

作者： Vladimir Tosic Hiroshi Wada Adnene Guabtni Kevin Lee Anna Liu Software Systems Research Group NICTA Sydney Australia School of Computer Science and Engineering University of New South Wales Sydney Australia School of Information Technologies University of Sydney Sydney Australia

Summary form only given. Many organizations are attracted to cloud computing as an ICT (information and communications technology) sourcing model that can improve flexibility and total cost of ICT systems. However, it can be difficult for a prospective cloud customer to determine and manage cloud usage costs. We present an overview of several NICTA research projects that aim at providing information that can help ICT professionals determine various cloud usage costs and make decisions that are appropriate from the business viewpoint. Before migrating an application into a cloud, it is necessary to choose to which cloud to migrate, because there is a huge variety of cloud offerings, with significantly different pricing models. To accurately capture projected operating costs of an application in a particular cloud and enable side-by-side comparison of cloud offerings from different providers, NICTA developed a cost estimation tool that calculates the costs based on usage patterns and other characteristics of the application. This tool can also be used during runtime as an input into making adaptation/control decisions. To collect various runtime metrics (e.g., about the amount of transferred data or received quality of service - QoS) that are necessary for operational management and assessment of cloud usage costs, NICTA developed an innovative tool for flexible and integrated monitoring of applications in clouds and (in case of hybrid clouds) related local data centers. To help determine which runtime adaptation/control decisions are best from the business viewpoint (e.g., incur lowest cost), we extended the WS-Policy4MASC language and MiniZnMASC middleware for autonomic business-driven IT management with events and adaptation actions relevant for cloud management. The tools from the presented projects can be used separately or as parts of a powerful integrated cloud management system (which contains several additional tools).

关键词： Educational institutions Runtime Business Australia software systems Estimation Cloud computing

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PMC-CNN: Trajectory Prediction Method Fusing Pedestrian Motion Features

PMC-CNN: Trajectory Prediction Method Fusing Pedestrian Moti...

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IEEE International Symposium on information (IT) in Medicine and Education, ITME

作者： Xiling Cao Yan Li Hong Liu School of Information Science and Engineering Shandong Normal University Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan China Inspur (Shandong) Computer Technology Co Ltd. Jinan China

ISBN: (数字)9798350356670

ISBN: (纸本)9798350356687

Predicting how pedestrians will move is a valuable and challenging task. It can be applied to various domains, such as crowd evacuation and autonomous driving. However, in practice, scene information and pedestrian interaction make it difficult to accurately predict pedestrian trajectories. Therefore, more effective processing of information affecting pedestrian trajectories is particularly important. Extraction of pedestrian motion features is insufficient in current research in this area. To address this problem, a neural network trajectory prediction method, PMC-CNN, is proposed. This method incorporates pedestrian motion features and stores the heterogeneous information required for prediction within a knowledge graph. Furthermore, it combines this information with the proposed IN-EX pedestrian motion model, resulting in an improvement in prediction accuracy. In addition, this research applies the prediction framework to a crowd evacuation scenario to improve the efficiency of crowd evacuation. This verifies the effectiveness and practicality of our proposed model.

关键词： Pedestrians Accuracy Urban planning Neural networks Safety management Knowledge graphs Predictive models Feature extraction Real-time systems Trajectory

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Joint Asynchronous Congestion Control and Distributed Scheduling for Multi-Hop Wireless Networks

Joint Asynchronous Congestion Control and Distributed Schedu...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： L. Bui A. Eryilmaz R. Srikant X. Wu Department of Electrical and Computer Engineering and Coordinated Science Laboratory University of Illinois Urbana-Champaign USA Laboratory for Information and Decision Systems Massachusetts Institute of Technology USA Flarion Technologies NJ USA

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