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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Chenxi Shao Jinfeng Fan Xiaoping Chen Department of Computer Science and Technology University of Science and Technology of China Hefei Anhui China Anhui Province Key Laboratory of Software in Computing and Communication Hefei Anhui China

A novel method combined fuzzy c-means (FCM) and hierarchical agglomerative clustering (HAC) is presented to extract the qualitative states from reconstructed phase space by considering the dynamical relations of underlying nonlinear system. The qualitative state, in which all points have similar properties, is characterized by three measures, linear density, temporal reachability, and stable degree, which are defined as the criteria of merging subclasses. The time series sampled from a classic nonlinear system, Lorenz system, and electroencephalogram (EEG) signals are used to test this method. The results show that the qualitative states can be efficiently distinguished from these time series by the proposed method.

关键词： Space technology Nonlinear systems Clustering methods Fuzzy systems Merging Electroencephalography Chaotic communication Delay Computer science Laboratories

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Research on Ultra-Dependable Embedded Real Time Operating System

Research on Ultra-Dependable Embedded Real Time Operating Sy...

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IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social computing (CPSCom) Green computing and communications (GreenCom)

作者： Hui Chen ShiPing Yang Shanghai Key Laboratory of Trustworthy Computing Software Engineering Institute East China Normal University Shanghai China Guangzhou Haige Communication Industry Group Guangzhou China

In this paper, to research and design ultra-dependable embedded real time operating system supporting security and safety, spatial and temporal isolation safeguard is proposed and used. Temporal isolation mechanism guarantees a subsystem can exclusively use a pre-allocated processing time without any intervention from other subsystem. On the other hand, spatial isolation implies that a subsystem cannot inadvertently access other subsystem's space resources, like memory, buffers, I/O ports, and registers. Thus, a subsystem is the owner of its resources, such as memory, I/O ports, and processor time units. From this, the real time tasks running in different subsystems never interfere with each other. To support the temporal isolation among subsystems, a two-level scheduling model is designed, which consists of a low-level cyclic schedule at the operating system level and high-level fixed priority schedule at subsystem level. Thus, a real time task in a subsystem can only be scheduled and executed during the static time window allocated to the subsystem, and any task overrun cannot cross the time window boundaries of subsystem. It is very easy to restrain a task time-failure within the subsystem with temporal isolation mechanism. In reference to spatial isolation safeguard, a based on hard currency and error holding mechanism is presented, it apply to most embedded modern processors with memory protection unit, such as i386sx, PowerPC. As a result, an ultra-dependable embedded RTOS supporting temporal and spatial isolation safeguard is implemented and verified. It is called ERTOS designed by software Engineering Institute of East China Normal University.

关键词： Servers Operating systems Safety Real time systems Schedules Computer hacking

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Empirical Study of Population-Based Dynamic Constrained Multimodal Optimization Algorithms

Empirical Study of Population-Based Dynamic Constrained Mult...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Xin Lin Wenjian Luo Yingying Qiao Peilan Xu Tao Zhu Anhui Province Key Laboratory of Software Engineering in Computing and Communication School of Computer Science and Technology University of Science and Technology of China Hefei China School of Software Engineering University of South China Hengyang China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

There are many dynamic optimization problems in real-world applications. Although many variants of evolutionary algorithms and swarm intelligence have been proposed to solve such problems, little work has been conducted to address the dynamic constrained multimodal optimization problems (DCMMOPs). In DCMMOPs, there exist multiple optimal solutions corresponding to each environment that the algorithm is required to find. Sometimes, it is also necessary to identify the accepted local optima. Therefore, for each environment, the decision maker can select one from among multiple returned solutions according to his/her domain knowledge and/or preferences. The objective of this paper is to test the performance of various combinations of several population-based dynamic multimodal optimization algorithms and popular constraint handling techniques. First, the typical dynamic constrained optimization problems are slightly modified to be in the form of the dynamic constrained multimodal optimization problems. Second, four different population-based dynamic multimodal optimization algorithms, and five different constraint handling techniques, are pairwise tested in the experiments. Experimental results demonstrate that, among the candidates, DCMM-CSA-SR performs most successfully at all accuracy levels.

关键词： Heuristic algorithms Optimization Vehicle dynamics Sociology Statistics Evolutionary computation Clustering algorithms

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A Novel Method for Semantic Segmentation on Lidar Point Clouds 19th

A Novel Method for Semantic Segmentation on Lidar Point Clou...

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19th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2023

作者： Wang, Fei Wan, Liangtian Zhu, Yan Sun, Lu Zhao, Xiaowei Zheng, Jianbo Wang, Xianpeng Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province School of Software Dalian University of Technology Dalian116620 China Artificial Intelligence Research Institute Shenzhen MSU-BIT University Guangdong Shenzhen518172 China Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Shenzhen MSU-BIT University Guangdong Shenzhen518172 China Department of Communication Engineering Institute of Information Science Technology Dalian Maritime University Dalian116026 China School of Information and Communication Engineering Hainan University Haikou570228 China

ISBN: (纸本)9783031651250

Autonomous driving relies on multiple sensors, such as lidar and cameras, to perceive the surrounding environment and the vehicle’s own position. Among them, lidar point cloud segmentation is a crucial and challenging task for 3D scene understanding. In this paper, we propose a novel deep learning method RPNet for lidar point cloud segmentation that combines range image-based segmentation and point based segmentation. Our method extracts point cloud features from range images and predicts 3D point cloud labels from point clouds. The segmentation results of both branches are fused to improve accuracy. We evaluate our method on the Semantic KITTI dataset and show that it outperforms other fusion algorithms in terms of effectiveness and robustness. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Semantic Segmentation

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Resource allocation for scalable video streaming in highway VANET

Resource allocation for scalable video streaming in highway ...

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International Conference on Wireless communications and Signal Processing (WCSP)

作者： Yang Xu Hao Zhou Xiaoyan Wang Baohua Zhao Province Key Laboratory of Software in Computing and Communication Hefei China School of Science and Technology University of Science and Technology of China Hefei China National Institute of Informatics Tokyo Japan

ISBN: (纸本)9781467376884

In vehicular ad-hoc network (VANET), the popular video transmission service can serve people with live traffic information, real-time news or even high-definition movies, which can assist people to drive on the road and enhance their driving experience. In this paper, we propose a dynamic programming based algorithm for the resource allocation problem of scalable video streaming through long term evolution (LTE) networks in highway VANET. We manage vehicular mobility by using small group of pictures (GOP) sized scalable video coding (SVC) encoder and valid signal-to-interference-and-noise ratio (SINR) estimator. We also adopt adaptive receive window of GOP to enhance the resource utilization efficiency as well as video quality. The simulation results demonstrate the efficiency of the proposed algorithm.

关键词： Streaming media Resource management Vehicular ad hoc networks Signal to noise ratio Interference Road transportation Static VAr compensators

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A Lightweight OS-Level Virtualization Architecture Based on Android

A Lightweight OS-Level Virtualization Architecture Based on ...

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2017 2nd International Conference on Computer, Network Security and communication Engineering(CNSCE2017)

作者： Bo-wen LIU Nai-jie GU De-he GU School of Computer Science and Technology University of Science and Technology of China Institute of Advanced Technology University of Science and Technology of China Anhui Province Key Laboratory of Computing and Communication Software

All kinds of intelligent terminal equipment emerge in endlessly and grow explosively. Typical devices, such as smartphones and tablets, are becoming more and more popular, furthermore, intelligent equipment market share has more than that on PCs. And on mobile devices area, the demand for virtualization technology is gradually increasing. As an important branch of computer technology development, operating system level virtualization is becoming a hot spot of current research due to its low overhead and the advantages of lightweight. In this paper, based on the Android system on mobile devices, implement a prototype which can run multiple virtual system instances on only an Android OS by modifying the namespace mechanism in the Linux kernel to and expand into driver namespace mechanism. In addition, put forward a model called the active-inactive model guaranteeing the process if and only if in the active namespace to operate the device drivers, which was designed and implemented a new scheme of operating system level virtualization.

关键词： Virtualization Android Namespace

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Evolutionary community discovery in dynamic networks based on leader nodes

Evolutionary community discovery in dynamic networks based o...

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International Conference on Big Data and Smart computing (BIGCOMP)

作者： Wenhao Gao Wenjian Luo Chenyang Bu Anhui Province key Laboratory of Software Engineering in Computing and Communication University of Science and Technology of China Hefei Anhui China University of Science and Technology of China Hefei Anhui CN

Evolutionary community discovery is a hot research topic which clusters the dynamic or temporal network. The communities detected in dynamic network should get reasonable partition for the current data while simultaneously not deviate drastically from the previous ones. In this paper, the evolutionary community discovery algorithm based on leader nodes (EvoLeaders) is proposed to cluster the dynamic network. Compared with the static community discovery algorithm based on leader nodes (the Top Leaders algorithm), experimental results over two real-world datasets demonstrate that the EvoLeaders is more suitable for dynamic scenarios.

关键词： Heuristic algorithms Clustering algorithms Current measurement Partitioning algorithms Social network services History Merging

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ECG signal feature selection for emotion recognition

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Telkomnika - Indonesian Journal of Electrical Engineering 2013年第3期11卷 1363-1370页

作者： Xun, Lichen Zheng, Gang Key Laboratory of Tianjin Intelligent Computing and Software Technologies Tianjin University of Technology Tianjin China Department of Computer and Communication Engineering Tianjin University of Technology Tianjin 300384 China

This paper aims to study the selection of features based on ECG in emotion recognition. In the process of features selection, we start from existing feature selection algorithm, and pay special attention to some of the intuitive value on ECG waveform as well. Through the use of ANOVA and heuristic search, we picked out the different features to distinguish joy and pleasure these two emotions, then we combine this with pathological analysis of ECG signals by the view of the medical experts to discuss the logic corresponding relation between ECG waveform and emotion distinguish. Through experiment, using the method in this paper we only picked out five features and reached 92% of accuracy rate in the recognition of joy and pleasure. © 2013 Universitas Ahmad Dahlan.

关键词： Electrocardiography

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Combining multipopulation evolutionary algorithms with memory for dynamic optimization problems

Combining multipopulation evolutionary algorithms with memor...

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Congress on Evolutionary Computation

作者： Tao Zhu Wenjian Luo Lihua Yue Anhui Province Key Laboratory of Software Engineering in Computing and Communication Hefei Anhui China School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China

ISBN: (纸本)9781479914869

Both multipopulation and memory are widely used approaches in the field of evolutionary dynamic optimization. It would be interesting to examine the effect of the combinations of multipopulation algorithms (MPAs) and memory schemes. However, since most of the existing memory schemes are proposed with single population algorithms, straightforwardly applying them to MPAs may cause problems. By addressing the possible problems, a new memory scheme is proposed for MPAs in this paper. In the experiments, several existing memory schemes and the newly proposed scheme are combined with a MPA, i.e. the Species-based Particle Swarm Optimizer (SPSO), and these combinations are tested on cyclic and acyclic problems. The experimental results indicate that 1) straightforwardly using the existing memory schemes sometimes degrades the performance of SPSO even on cyclic problems; 2) the newly proposed memory scheme is very competitive.

关键词： Sociology Statistics Memory management Optimization Heuristic algorithms Benchmark testing Particle swarm optimization

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SvdNPD: a negative data publication method based on the sensitive value distribution

SvdNPD: a negative data publication method based on the sens...

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International Workshop on Artificial Immune Systems (AIS)

作者： Linli Wu Wenjian Luo Dongdong Zhao University of Science and Technology of China Hefei Anhui CN Anhui Province Key Laboratory of Software Engineering in Computing and Communication University of Science and Technology of China Hefei Anhui China

Existing data publication methods retain the relationship between the quasi-identifier attributes and sensitive attributes of published data. We call them "positive data publication". However, it will lead to potential risk that attackers could deduce the privacy of the corresponding individuals from the published data. Recently, by combining the negative representation with k-anonymity and l-diversity, (k, m)- anonNPD and (l, m)-divNPD algorithms have been proposed, which improve the degree of privacy because the sensitive value of each individual is transformed into a negative value randomly. However, to reduce the average error of the reconstructed distribution, the data published by (k, m)-anonNPD and (l, m)-divNPD are often much larger than the original data. In this paper, we take the Sensitive Value Distribution into consideration, and propose a novel Negative Data Publication approach (i.e. SvdNPD), which is based on l-diversity. According to the sensitive value distribution, the negative selection probability of the sensitive attribute in each record can be calculated. Then the data could be published by transforming the sensitive value to a negative one with this probability. Experimental results show that the effective usage of the individual sensitive value distribution could enhance the utility of published data. Meanwhile, compared with (l, 1)-divNPD, SvdNPD just sacrifices a tiny privacy degree which is acceptable.

关键词： Data privacy Privacy Diseases Aggregates Databases Lungs Organizations

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