Real-time wireless sensor networks in the industrial settings usually consist of tens of nodes. Seldom do we see a network of over 100 wireless nodes. The smaller size is usually sufficient as a typical plane unit is ...
A novel metric for full-reference image quality assessment (IQA) is proposed in this paper. Based on the sparse representation in independent component analysis (ICA) domain, the image basis is generated from natural ...
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A novel metric for full-reference image quality assessment (IQA) is proposed in this paper. Based on the sparse representation in independent component analysis (ICA) domain, the image basis is generated from natural images adaptively, which coincides with the characteristics of human vision system (HVS). In order to extract the feature vector, a hybrid norm optimization strategy is introduced for achieving more stable computational performances. The proposed IQA metric is calculated as a correlation coefficient between the two feature vectors from reference and distorted images, respectively. Experimental results on the LIVE Database Release 2 demonstrate that the proposed metric can achieve competitive performances as compared to the well-known structural similarity (SSIM) metric.
Web services composition (WSC) is the key techniques in its application. Dynamically selecting reliable Web services (WSs) becomes crucial to users. In fact, most works regard a Web service (WS) as the basic unit and ...
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With the explosive growth of Internet information, it is more and more important to fetch real-time and related information. And it puts forward higher requirement on the speed of webpage classification which is one o...
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Spatial-temporal modeling considering the particularity of traffic data is a crucial part of traffic forecasting. Many methods take efforts into relatively independent time series modeling and spatial mining and then ...
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In high frequency radar, we should avoid noise disturbances in the radar's working-frequency segment. Moreover, the sidelobes of strong targets interfere with the detection of weak targets. A new method based on a...
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In high frequency radar, we should avoid noise disturbances in the radar's working-frequency segment. Moreover, the sidelobes of strong targets interfere with the detection of weak targets. A new method based on an adaptive selecting working-frequency is proposed. Frequency spectrum monitor is designed for selecting quiet frequency segment for the radar. Frequency spectrum monitor and the receiver of the radar are arranged to work according to special time periods respectively. So the radar can work in the frequency segments with lower noise disturbances. Moreover, there is no correlation between the noise and the useful echo signal, though the correlation between noises over very short time periods is strong, the noise data produced by frequency spectrum monitor can be exploited effectively Adjusting system parameters in real-time by adaptive methods can be utilized to reduce noise disturbances. Algorithm based on the properties of crosscorrelation between noise and target is exploited for suppressing sidelobe disturbances of strong targets. Lastly, the feasibility of the methods is verified by processing actual radar data.
Compared with wheeled mobile robots, legged robots can easily step over obstacles and walk through rugged ground. They have more flexible bodies and therefore, can deal with complex environment. Nevertheless, some oth...
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Compared with wheeled mobile robots, legged robots can easily step over obstacles and walk through rugged ground. They have more flexible bodies and therefore, can deal with complex environment. Nevertheless, some other issues make the locomotion control of legged robots a much complicated task, such as the redundant degree of freedoms and balance keeping. From literatures, locomotion control has been solved mainly based on programming mechanism. To use this method, walking trajectories for each leg and the gaits have to be designed, and the adaptability to an unknown environment cannot be guaranteed. From another aspect, studying and simulating animals' walking mechanism for engineering application is an efficient way to break the bottleneck of locomotion control for legged robots. This has attracted more and more attentions. Inspired by central pattern generator (CPG), a control method has been proved to be a successful attempt within this scope. In this paper, we will review the biological mechanism, the existence evidences, and the network properties of CPG. From the en- gineering perspective, we will introduce the engineering simulation of CPG, the property analysis, and the research progress of CPG inspired control method in locomotion control of legged robots. Then, in our research, we will further discuss on existing problems, hot issues, and future research directions in this field.
Person search aims to locate target individuals in large image databases captured by multiple non-overlapping cameras. Existing models primarily rely on spatial feature extraction to capture fine-grained local details...
Person search aims to locate target individuals in large image databases captured by multiple non-overlapping cameras. Existing models primarily rely on spatial feature extraction to capture fine-grained local details, which is vulnerable to background clutter and occlusions and leads to unstable feature representations. To address the issues, we propose a Dynamic Frequency Selection and Spatial Interaction Fusion Network (PS-DFSI), marking the first attempt to introduce frequency decoupling and selection into person search. By integrating frequency and spatial features, PS-DFSI enhances feature expressiveness and robustness. Specifically, it comprises two core modules: the Dynamic Frequency Selection Module (DFSM) and the Spatial Frequency Interaction Module (SFIM). DFSM decouples feature maps into low-frequency and high-frequency components using learnable low-pass and high-pass filters, and a frequency selection modulator emphasizes key frequency components via channel attention. SFIM refines local details by fusing frequency-enhanced features with high-level semantic representations, leveraging multi-scale receptive fields and cross-feature attention for efficient spatial-frequency integration. Extensive experiments on CUHK-SYSU and PRW demonstrate that PS-DFSI significantly improves person search performance, validating its effectiveness and robustness.
A vehicle tracking mode based on dynamic roles is proposed in the smart camera networks. The tracking for a specific vehicle is organized collaboratively and automatically in smart camera network. The tracking is comp...
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Modern datacenter servers hosting popular Internet services face significant and multi-facet challenges in performance and power control. The user-perceived performance is the result of a complex interaction of comple...
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Modern datacenter servers hosting popular Internet services face significant and multi-facet challenges in performance and power control. The user-perceived performance is the result of a complex interaction of complex workloads in a very complex underlying system. Highly dynamic and bursty workloads of Internet services fluctuate over multiple time scales, which has a significant impact on processing and power demands of datacenter servers. High-density servers apply virtualization technology for capacity planning and system manageability. Such virtuMized computer systems are increasingly large and complex. This paper surveys representative approaches to autonomic performance and power control on virtualized servers, which control the quality of service provided by virtualized resources, improve the energy efficiency of the underlying system, and reduce the burden of complex system management from human operators. It then presents three designed self-adaptive resource management techniques based on machine learning and control for percentile-based response time assurance, non-intrusive energy-efficient performance isolation, and joint performance and power guarantee on virtualized servers. The techniques were implemented and evaluated in a testbed of virtualized servers hosting benchmark applications. Finally, two research trends are identified and discussed for sustainable cloud computing in green datacenters.
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