Applied Mechanics and Materials Vols. 644-650

Abstract: For the recovery of an plaintext with different levels of values encrypted by permutation-only multimedia ciphers, a L-ary based chosen text construction method is first proposed in this paper. And plaintexts are created to reach the lower bound of the plaintext number required for chosen plaintext attacks which is given by Li et al. Then based on the created plaintexts, two attacks are proposed on permutation-only image/video ciphers. Finally the validity of the two attacks is proved by Proposition 2 and Proposition 3 respectively.

Abstract: Because of the powerful capability of global searching and robustness of genetic algorithm, so it can be well applied in the automated generation of test data.Establish a module to generate test cases automatically by genetic algorithms.We can find that genetic algorithm guide the generation of the test data by the evaluation function according to the constraints of the path.It will not only avoid the blindness of the data searching process with higher efficiency,but also need not to consider the matching problem of the generated test data and test sequences.It can even run effectively relying only on the fitness of the point in the searching space supplied by the evaluation function.This advantage makes it a powerful searching algorithm on the type of random searching.

Abstract: The Basic Principles of Data mining Decision-tree ID3 is opened out. The main deficiencies are analysed. An improved algorithm based on the ID3 is calculated. For fault diagnosis of engine exemple, traditional ID3 algorithm and the improved algorithm are applied to estimate the fault diagnosis of engine separately. Decision Trees of traditional ID3 algorithm and the improved algorithm are construct. Experiment result display the accuracy of improved algorithm is better than traditional ID3. The improved algorithm is more fit to applied to the equipment fault diagnosis.

Abstract: Aiming at the limitation of the application of principal component analysis model for fault diagnosis in nonlinear time-varying process, kernel transformation theory is introduced into the data feature extraction of nonlinear space, on the basis of the periodic characteristics of the batch process, putting forward a kind of improved multi-way kernel principal component analysis fault diagnosis model, which effectively solves the nonlinear problem of process data and ensures integrity of data and information extraction. By comparing with other methods in experiment, the results show that the proposed method has good real-timing and accuracy to slow time-varying of batch process.

Abstract: Due to the advancement of technology, modern networks such as social networks, citation networks, Web networks have been extremely large, reaching millions of nodes in a network. But most of the existing graph clustering algorithms can only tackle with small or medium-size networks. In this paper, we introduce a new method which can achieve high graph clustering quality for large scale networks by optimizing the modularity function. It is based on the iterative idea and takes good advantage of the exsiting multilevel local search heuristics. After introducing this modularity-based method, we evaluate its performance by applying it to several well-known network datasets. With a cost of more but acceptable time, it outperforms the best algorithms in the literature in the case of modularity optimization quality.

Abstract: This paper introduces the service-oriented architecture technology, and proposes the architecture model of Out-trajectory Data Processing in distributed environment. According to the demand and features of Ship-borne Out-trajectory Data Processing flow, it describes how to carry out cross-platform service integration by using the Service Bus Middleware, and provides a kind of typical distributed deployment strategy.

Abstract: A support vector machine (SVM) model combined Laplacian Eigenmaps (LE) with Cross Validation (CV) is proposed for intrusion detection. In the proposed model, a classifier is adopted to estimate whether an action is an attack or not. Maximum Likelihood Estimation (MLE) is used to estimate the intrinsic dimensions, and LE is used as a preprocessor of SVM to reduce the dimensions of feature vectors then training time is shortened. In order to improve the performance of SVM, CV is used to optimize the parameters of SVM in RBF kernel function. Compared with other detection algorithms, the experimental results show that the proposed model has the advantages: shorter training time, higher accuracy rate and lower false positive rate.

Abstract: In the case that a single fault occurs on a power feeder in the one-source distribution system, the directional layered model of the network which reflects the layered topological characteristic of the network was built up. Then a new algorithm for fault detection in power distribution network was proposed to locate the faulty sections in distribution feeder network. The algorithm itself as well as its program design is simple. It can be applied to complex distribution systems with multi-sources. It is proved correct by an example.

Abstract: In this paper, we propose a method for model based diagnosis using case based reasoning. This method can effectively use results from previous diagnosis, other than do everything from scratch. According to our analysis, this method has lower time complexity than other methods. People have attempted to use case based reasoning to do abductive diagnosis. We propose a better mechanism for case based reasoning and model based diagnosis to interact with each other so that it can be used for diagnosis.

Abstract: To meet the scheduling demands of dispatching the agricultural machinery to the reasonable farmlands, time-windows based temporal and spatial scheduling model for agricultural machinery resources was built,which serialized decision-making processes and got optimal solutions for each process.The experiment results showed that the model could perform well in practice,which improved the management and working efficiency of the agricultural association.