This paper shows the result of an analysis pertaining to the applicability of RESTful web services (RESTful WS) in solving various software and data integration scenarios in control centers for the electric power syst...
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This paper shows the result of an analysis pertaining to the applicability of RESTful web services (RESTful WS) in solving various software and data integration scenarios in control centers for the electric power system domain. There are many possible ways to enhance power system software/data integration by combining RESTful WS and the IEC 61970 set of standards. The goal of this paper is to highlight those lines of integration in control centers, where the benefits of leveraging RESTful WS are most noticeable. The importance of selecting the most prominent integration scenarios from the viewpoint of RESTful WS stems from the fact, that not all integration problems are naturally fitted for RESTful WS. Assuming a type of RESTful WS, which wraps the resource oriented power system data model defined in the IEC 61970-301 Common Information Model (CIM) and the generic query interface defined in IEC 61970-403 Generic Data Access (GDA), the paper demonstrates that such a RESTful WS may be successfully utilized in many concrete integration situations. As an added advantage, a RESTful WS atop of existing IEC 61970 standards can significantly loose the couplings between different software packages used in power system control centers. We have realized several pilot projects using real life power system data models (some used in CIM interoperability tests) to assert the outcome of our feasibility study. This study clearly shows that RESTful web services are a powerful tool for solving numerous power system software and data integration problems in control centers.
A new tool has been developed for comparison and evaluation of medical images based on image registration and edge detection algorithms. The tool performance has been demonstrated on the processing of the ortopantomog...
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A new tool has been developed for comparison and evaluation of medical images based on image registration and edge detection algorithms. The tool performance has been demonstrated on the processing of the ortopantomograms taken before and after treatment. The accuracy of the performance has been discussed and the possible origins of tool performance errors have been explained. The results obtained using presented tool have been discussed by an expert. The expert has confirmed that the tool is well suited for comparison and evaluation of ortopantomograms. The expert has come to the conclusion that our tool can be useful in other specializations of dentistry, not only in orthodontics.
A new tool has been developed for comparison and evaluation of medical images based on image registration and edge detection algorithms. The tool performance has been demonstrated on the processing of the ortopantomog...
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A new tool has been developed for comparison and evaluation of medical images based on image registration and edge detection algorithms. The tool performance has been demonstrated on the processing of the ortopantomograms taken before and after treatment. The accuracy of the performance has been discussed and the possible origins of tool performance errors have been explained. The results obtained using presented tool have been discussed by an expert. The expert has confirmed that the tool is well suited for comparison and evaluation of ortopantomograms. The expert has come to the conclusion that our tool can be useful in other specializations of dentistry, not only in orthodontics.
In remote sensing researches, the curse of dimensionality is one greatly difficult classification problem. Many studies have demonstrated that multiple classifier systems, such as the random subspace method (RSM), can...
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In remote sensing researches, the curse of dimensionality is one greatly difficult classification problem. Many studies have demonstrated that multiple classifier systems, such as the random subspace method (RSM), can alleviate small sample size and high dimensionality concern and obtain more outstanding and robust results than a single classifier on extensive pattern recognition issues. A dynamic subspace method (DSM) was proposed for constructing component classifiers with adaptive subspaces to adjust the shortcomings of RSM based on re substitution accuracy by applying each classifier. However, the performances of SVMs are based on choosing the proper kernel functions or proper parameters of a kernel function. The objective of this research is to develop a novel ensemble technique based on support vector machines (SVMs) via the optimal kernel method, and propose a novel subspace selection mechanism, named the kernel-based dynamic subspace method (KDSM), to improve DSM on automatically determining dimensionality and selecting component dimensions for diverse subspaces. Experimental results show a sound performance of classification on the famous hyperspectral images, Washington DC Mall.
Physically-based methods are often used to simulate cloth animation. For generating realistic cloth animation, stability and effectiveness are two most important aspects which need to be considered. In cloth animation...
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Physically-based methods are often used to simulate cloth animation. For generating realistic cloth animation, stability and effectiveness are two most important aspects which need to be considered. In cloth animation, the users often need to attach a vertex to make sure the vertex is free collision or reduce the excessive elongation of some edges. Some existing methods directly adjust the particle position or use stiff spring model for the simulation regarding these facts. However, these methods can cause energy loss or system performance degradation. In this paper, we propose a novel method to simulate cloth based on physically-model with constraints. Cloth deformation is solved using a physically-based model, and then constraints are iteratively imposed to avoid over-elongation and penetration. The experiments show that our method is stable and effective, and can generate realistic cloth animations.
Accurate description and analysis of liver vascular system is critical in diagnosis and treatment of liver diseases. Even though there are plenty of researches put their efforts on the acquisition of optimal visual in...
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This paper is devoted to noise suppression in systems for double station observation of meteors, nowadays known as MAIA (Meteor Automatic Imager and Analyzer). The noise analysis based on acquisition of testing video ...
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This paper is devoted to noise suppression in systems for double station observation of meteors, nowadays known as MAIA (Meteor Automatic Imager and Analyzer). The noise analysis based on acquisition of testing video sequences at different lighting conditions and their statistical evaluation were described in our previous paper. The measurement showed that the type of noise generated by the system is signal-independent in a certain illumination range. The noise and image models in the wavelet domain are based on the Generalized Laplacian Model (GLM) and it is the most convenient to estimate the model parameters using the moment method. Furthermore, the noise component may be modeled by the GLM also in the space domain. Overall, we verified that the GLM allows for modeling various types of probability density functions. In the final section of this paper, the performance of the proposed advanced de-noising algorithm is verified on the real data, which were acquired in the Astronomical Institute.
In this paper, a new linear delayed delta operator switched system model is proposed to describe networked control systems with packets dropout and network-induced delays. The plant is a continuous-time system, which ...
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作者:
G. LiW.P. HeathG. HerrmannSchool of Engineering
Computing and Mathematics University of Exeter North Park Road Exeter UK EX4 4QF Control Systems Centre
School of Electrical and Electronic Engineering University of Manchester Sackville Street Building Manchester M13 9PL UK ACTLab
Department of Mechanical Engineering University of Bristol Queens Building University Walk Bristol BS8 1TR UK
Abstract We develop an anti-windup (AW) compensator synthesis approach using Integral Quadratic Constraints (IQC). The synthesis finds the AW compensator that achieves a specified robustness against additive or input ...
Abstract We develop an anti-windup (AW) compensator synthesis approach using Integral Quadratic Constraints (IQC). The synthesis finds the AW compensator that achieves a specified robustness against additive or input multiplicative uncertainty, provided there exists a feasible solution. We also incorporate a performance criterion into the AW compensator synthesis to achieve an appropriate trade-off between the performance and robustness. The efficacy of this approach is demonstrated by a numerical example.
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