By research on the privacy disclosure issue in cloud computing, a method for identify privacy disclosure service providers was proposed. Firstly, an optional signature process and a resistant attack method were introd...
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By research on the privacy disclosure issue in cloud computing, a method for identify privacy disclosure service providers was proposed. Firstly, an optional signature process and a resistant attack method were introduced. Then an analysis center with text classification and service classification based analysis algorithm also with testing method was present to identify the privacy disclosure service providers. Analyze and simulation results show the method can identify privacy disclosure service providers well.
With the characteristics of sudden outbreak and inadequate precursors of unconventional emergency, the traditional emergency disposal systems based on data model can hardly reponse to the undefined and unexpected situ...
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With the characteristics of sudden outbreak and inadequate precursors of unconventional emergency, the traditional emergency disposal systems based on data model can hardly reponse to the undefined and unexpected situation quickly. The three layers model of scenario-ontology-data schema mapping was proposed. By using the mapping model, the scenarioe sets can be built agilely to describe the new unconventional emergency type, the scenarioes and factual event data are linked and the unconventional emergencies will be reponsed and disposed effectively. And the method of scenario-based analysis, combined with multi-agent technology, was used to design and implement the multi-agent system of unconventional emergency modeling.
A Relief-F feature weighting based support vector machine (SVM) method for semantic image classification was proposed. Firstly, the feature weight of images in training data set was computed by the Relief-F algorithm;...
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A Relief-F feature weighting based support vector machine (SVM) method for semantic image classification was proposed. Firstly, the feature weight of images in training data set was computed by the Relief-F algorithm;Then, the SVM classifier was trained by taking advantage of the feature vector with different weights;Finally, the automatic classification of images in the test data set was presented by using trained SVM classifier. Experimental results show that the Relief-F feature weighting based SVM classifier is better than the traditional SVM classifier both in classification accuracy and training time-consuming in semantic image classification.
This study constructs a food safety ontology which adopts OWL (Web Ontology Language) to represent food safety knowledge in a structural way in order to help knowledge requesters clearly understand food safety knowled...
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ISBN:
(纸本)9781618399267
This study constructs a food safety ontology which adopts OWL (Web Ontology Language) to represent food safety knowledge in a structural way in order to help knowledge requesters clearly understand food safety knowledge;subsequently designs some ontology reasoning rules for deducing food safety knowledge in order to share and reuse relevant food safety knowledge effectively;finally implement an ontology-based food safety knowledge reasoning mechanism. Results of this study facilitate the food safety knowledge storage, management and sharing to provide knowledge requesters with accurate and comprehensive food safety knowledge for problem solving and decision support.
Robust L_(2) - L_(infinity) consensus control is studied for the second-order multi-agent systems with external disturbances and parameter uncertainties. By defining an appropriate controlled output, the consensus pro...
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ISBN:
(纸本)9781612848006
Robust L_(2) - L_(infinity) consensus control is studied for the second-order multi-agent systems with external disturbances and parameter uncertainties. By defining an appropriate controlled output, the consensus problem of the systems is transformed into a normal L_(2) - L_(infinity) control problem, and distributed state feedback protocols with time-delay are proposed. Sufficient conditions are established for the convergence to consensus of the network under fixed or switching topology. Numerical simulations are provided to demonstrate the effectiveness of our theoretical results.
This paper deals with the active collision avoidance maneuver for the chaser along the specified trajectory, and presents a maneuver approach with constant thrust. Using the 3D stereo vision measurement, The relative ...
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ISBN:
(纸本)9781612848006
This paper deals with the active collision avoidance maneuver for the chaser along the specified trajectory, and presents a maneuver approach with constant thrust. Using the 3D stereo vision measurement, The relative position parameters of the target spacecraft for analyzing the collision possibility are obtained by using the vision measurement and the target maneuver positions are calculated through the equidistance interpolation method. The working times of thrusters in three axes can be respectively computed by the time series analysis method. In particular, the perturbation and fuel consumption are addressed during the computation of working time. Furthermore, the acceleration sequences and the corresponding working time series can be employed to determine a switching control law for the active collision avoidance maneuver. The simulation results show that the switch control law can effectively guarantee the chaser moving along the specified trajectory.
This paper aims to address the robust convergence problem that arises from discrete-time iterative learning control (ILC) systems subject to random disturbances. Two alternative approaches are considered in order to a...
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ISBN:
(纸本)9781612848006
This paper aims to address the robust convergence problem that arises from discrete-time iterative learning control (ILC) systems subject to random disturbances. Two alternative approaches are considered in order to achieve the perfect output tracking of the stochastic discrete-time ILC systems in the sense of both expectation and variance, which use the tracking error and the input error for analysis, respectively. It is shown that the convergence results of two approaches to ILC can be established by developing some statistical expressions in super-vector forms. Moreover, it is demonstrated that the convergence results of two approaches to ILC are not always equal, and they can keep the same only in the case where the controlled plants are square.
This paper is concerned with the column formation control of multi-robot systems that are subject to input constraints. A new leader-follower setup is proposed, under which the Lyapunov method can provide a simple con...
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ISBN:
(纸本)9781612848006
This paper is concerned with the column formation control of multi-robot systems that are subject to input constraints. A new leader-follower setup is proposed, under which the Lyapunov method can provide a simple controller in terms of two feedback parameters. It is shown that using an elliptic approximation to input constraints, the two feedback parameters can be obtained directly with a geometric analysis method. Moreover, a sufficient condition is presented for the leader robot to guarantee that the desired column formation can be achieved, with which a particular controller is designed by selecting two appropriate functions for the feedback parameters. Simulation results are included to verify the effectiveness of the proposed theoretical results.
This paper addresses the problem of tracking multiple maneuvering extended targets in the framework of random finite set theory. An elliptical model is adopted for exploiting sensor measurements of target extent, and ...
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ISBN:
(纸本)9781612848006
This paper addresses the problem of tracking multiple maneuvering extended targets in the framework of random finite set theory. An elliptical model is adopted for exploiting sensor measurements of target extent, and the target dynamics is described by a jump Markov linear system which combines the shape parameters into the kinematic state vector. As each extended target gives rise to unlabeled multiple measurements per time step, all the received measurements are partitioned into a number of subsets so that the measurements in each subset are expected to stem from the same source. In addition, the best-fitting Gaussian approximation approach is employed to circumvent the difficulty of multiple model mixing in the Gaussian mixture probability hypothesis density (GM-PHD) filter. A numerical example is provided to compare the performance of the proposed filter with that of the GM-PHD filter without measurement partition.
FOX is a family of symmetric block ciphers from MediaCrypt AG that helps to secure digital media, communications, and storage. The high-level structure of FOX is the so-called (extended) Lai–Massey scheme. This paper...
FOX is a family of symmetric block ciphers from MediaCrypt AG that helps to secure digital media, communications, and storage. The high-level structure of FOX is the so-called (extended) Lai–Massey scheme. This paper presents a detailed fault analysis of the block cipher FOX64, the 64-bit version of FOX, based on a differential property of two-round Lai–Massey scheme in a fault model. Previous fault attack on FOX64 shows that each round-key (resp. whole round-keys) could be recovered through 11.45 (resp. 183.20) faults on average. Our proposed fault attack, however, can deduce any round-key (except the first one) through 4.25 faults on average (4 in the best case), and retrieve the whole round-keys through 43.31 faults on average (38 in the best case). This implies that the number of needed faults in the fault attack on FOX64 can be significantly reduced. Furthermore, the technique introduced in this paper can be extended to other series of the block cipher family FOX.
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