In order to improve the discriminative ability of dictionary, a dictionary learning algorithm based on Fisher discriminative criterion constraint of the atoms was proposed, which was called Fisher Discriminative Dictionary Learning of Atoms (AFDDL). Firstly, the specific class dictionary learning algorithm was used to assign a class label to each atom, and the scatter matrices of within-class atoms and between-class atoms were calculated. Then, the difference between within-class scatter matrix and between-class scatter matrix was taken as the Fisher discriminative criterion constraint to maximize the differences of between-class atoms. The difference between the same class atoms was minimized when the autocorrelation was reduced, which made the same class atoms reconstruct one type of samples as much as possible and improved the discriminative ability of dictionary. The experiments were carried out on the AR face database, FERET face database, LFW face database and the USPS handwriting database. The experimental results show that, on the four image databases, the proposed algorithm has higher recognition rate and less training time compared with the Label Consistent K-means-based Singular Value Decomposition (LC-KSVD) algorithm, Locality Constrained and Label Embedding Dictionary Learning (LCLE-DL) algorithm, Support Vector Guided Dictionary Learning (SVGDL) algorithm, and Fisher Discriminative Dictionary Learning (FDDL) algorithm. And on the four image databases, the proposed algorithm has higher recognition rate compared with Sparse Representation based Classification (SRC) and Collaborative Representation based Classification (CRC).

Predicting protein secondary structure is an important issue in structural biology. Aiming at the prediction of eight-class protein secondary structure, a novel deep learning prediction algorithm was proposed by combining recurrent neural network and feed-forward neural network. A bidirectional recurrent neural network was used to model locality and long-range interaction between amino acid residues in protein. In order to predict the eight-class protein secondary structure, the outputs of the hidden layer in the bidirectional recurrent neural network were further fed to the three-layer feed-forward neural network. Experimental results show that the proposed method achieves Q ₈ accuracy of 67.9% on the CB513 dataset, which is significantly better than SSpro8 and SC-GSN (Supervised Convolutional-Generative Stochastic Network).

In Many-objective Optimization Problems (MaOP), the Pareto dominance has exponential increase of non-dominated solutions and the decrease of selection pressure with increasing optimization objectives. To solve these issues, a new type of dominance, namely Linear Weighted Minimal/Maximal dominance (LWM-dominance) was proposed based on the ideas of comparing multi-objective solutions by using linear weighted aggregation and Pareto dominance. It is theoretically proved that LWM non-dominated solution set is a subset of Pareto non-dominated solution set, meanwhile the important corner solutions are reserved. Furthermore, an MaOP algorithm based on LWM dominance was presented. The empirical studies proved the corollaries of the proposed LWM dominance. In detail, the experimental results in random objective space show that the LWM dominance is suitable for the MaOPs with 5-15 objectives; the experiment on comparing the number of LWM non-dominated solutions and Pareto non-dominated solutions with subjects of DTLZ1-DTLZ7 shows that the proportion of non-dominated solutions decreases by about 17% on average when the number of optimization objectives is 10 and 15.

The Ant Colony Optimization (ACO) has slow convergence and is easily trapped in local optimum when solving Multi-Objective Test Case Prioritization (MOTCP). Thus, a pheromone updating strategy based on Epistatic-domain Test case Segment (ETS) was proposed. In the scheme, ETS existed in the test case sequence was selected as a pheromone updating scope, because ETS can determine the fitness value. Then, according to the fitness value increment between test cases and execution time of test cases in ETS, the pheromone on the trail was updated. In order to further improve the efficiency of ACO and reduce time consumption when ants visited test cases one by one, the end of ants' visiting was reset by estimating the length of ETS using optimized ACO. The experimental results show that compared with the original ACO and NSGA-Ⅱ, the optimized ACO has faster convergence and obtains better Pareto optimal solution sets in MOTCP.

In order to achieve unified management and remote communication of measuring equipment in car body-in-white online visual inspection station, a measurement and control system for the car body-in-white detection was designed to improve the working efficiency. Using STM32F407 as the core, μC/OS-Ⅱ and LwIP were transplanted to build a Web server, and the Web server was set up to realize remote communication. Multithreaded tasks were established to achieve the information interaction between serial port and net port. By analyzing the data security issue in the process of data's routing and discussing the phenomenon of packet loss on transmitting, a solution was proposed. 2D normalized cross-correlation method was used to realize the image 2D positioning, and enhome the processing speed. The experimental results show that the system can provide remote communication function, reduce the cost, and improve the efficiency of equipment management.

As the low ability of triggering the data racing fault of the existing mutation operators for concurrent program in mutation testing, some new mutation strategies based on data racing fault were proposed. From the viewpoint of mutation operator designing, Lock-oriented Mutation Strategy (LMS) and Shared-variable-oriented Mutation Strategy (SMS) were introduced, and two new mutation operators that named Synchronized Lock Resting Operator (SLRO) and Move Shared Variable Operator (MSVO) were designed. From the viewpoint of mutation point selection, also a new mutation point selection strategy named Synchronized relationship pair Mutation Point Selection Strategy (SMPSS) was proposed. SLRO and MSVO mutation operators were used to inject the faults which generated by SMPSS strategy on 12 Java current libraries, and then the ability of mutants to trigger the data racing fault was checked by using Java Path Finder (JPF). The results show that the SLRO and MSVO for 12 Java libs can generate 121 and 122 effective mutants respectively, and effectiveness rates are 95.28% and 99.19% respectively. In summary, the new current mutation operators and mutation strategies can effectively trigger the data racing fault.

Aiming at the problem of low efficiency on generating Thread Scheduling Sequence (TSS) that cover synchronization statements in multi-thread concurrent program, a TSS Generation Based on All synchronization pairs coverage criteria (TGBA) method was proposed. First, according to the synchronization statements in concurrent program, the synchronization pair and All Synchronization Pairs Coverage Criteria (APSC) were defined. Second, a construction method of Synchronization Pair Thread Graph (SPTG) was given. On that basis, TSSs that satisfied APSC were generated. Finally, by using JPF (Java PathFinder) detection tool, TSS generation experiments were conducted on four Java Library concurrent programs, and the comparison analysis of generation efficiency was conducted with general sequence generation methods of Default Scheduling (DS), Preemptive Scheduling (PS) and Cross Scheduling (CS). The experimental results illustrate that TSSs generated by TGBA method can cover all synchronization pairs compared to the DS and CS method. Moreover, when satisfying APSC, TGBA method decreases at least 19889 states and 44352 transitions compared to the PS method, and the average generation efficiency increases by 1.95 times. So TGBA method can reduce cost of state space and improve the efficiency of TSS generation.

Since it's hard to analyze the cryptographic procedure using method of property scan or debugging for the variety and different implementation of cryptographic algorithms, a method was proposed based on library function prototype analysis and their calling-graph building. Library functions prototype analysis is analyzing cryptographic algorithm knowledge and library frame knowledge to form a knowledge base. Calling-graph building is building a calling-graph that reflects the function calling order according to parameter value of the functions. Finally cryptographic algorithm knowledge and library frame knowledge on the calling-graph were extracted. The method discriminated common cryptographic algorithm almost 100%, and it could not only recover cryptographic data, key and cryptographic mode, but also help to analyze the relationship between more than two cryptographic algorithms dealing with the same data. The method could be used to analyze Trojan, worm and test whether the library is used correctly.

To solve the defect of traditional network traffic prediction forecasting, and obtain good forecasting results of network traffic, a network traffic forecasting model based on Gaussian Process Regression (GPR) was proposed. Firstly, the time delay and embedding dimension of network traffic were calculated to construct the learning samples of GPR, and then training samples were input to Gaussian process to learn in which Invasive Weed Optimization (IWO) algorithm was used to optimize the parameters of Gaussian process, and finally, the forecasting model of network traffic was established based on the optimal parameters, and the performance was tested by network traffic data. The results show that the proposed model can improve the forecasting precision of network traffic and it has great practical application value.

Embedded system is vulnerable to buffer overflow attack. In order to solve this problem, a block based protection scheme was proposed after analyzing the memory management of μC/OS-Ⅱ. By making a combination of all the memory blocks which belong to one task and managing it through the established block_table, the introduced scheme protected the safety through creating isolation between task memories, checking and controlling the access of memory blocks. Then, an effective analysis about this scheme was given. In addition, a buffer overflow attack experiment was operated on Nios Ⅱ with the improved uC/OS-Ⅱ, and the results show that the proposed scheme is feasible.

In this paper, the author put forward a Least Significant Bit (LSB) matching steganalytic algorithm. Through calculating the second-order differential of the image pixels on horizontal and vertical directions, the differential matrix was obtained and it was used as sensitive feature extracting source and the second-order Markov transformation matrix of the differential matrix was extracted as the features, according to the LSB matching steganography with high security. According to the experimental result shows that the algorithm proposed in the paper speedups the detection process in a large extent and enhances the performance and practicability of the steganalytic algorithm while maintaining high detection accuracy, compared with the algorithms based on first-order differential Markov transition probability matrix.

The Scale Invariant Feature Transform (SIFT) algorithm is robust to the feature extraction of face image. However, the feature data derived by SIFT is of high dimension, and is difficult to be handled. Therefore, a Direct Locality Preserving Projections-SIFT (DLPP-SIFT) algorithm was proposed. In the algorithm, SIFT was used to extract feature, and the subspace method with Locality Preserving Projections (LPP) was utilized for dimension reduction. This algorithm solved locality preserving problem via simultaneous diagonalization; therefore, the singularity of the matrix was avoided. The experiments on ORL and FERET face databases show that the proposed algorithm reduces the computation complexity and matching time of features successfully, and is more robust than SIFT, Principal Component Analysis (PCA)-SIFT and LPP-SIFT methods.

As the new generation communication system, LTE/LTE-A requires reliable communication of higher standard for its high-throughput characteristic. Among those decoding algorithms of Turbo, Log-MAP algorithm, as a simplified algorithm, has a good performance, but its high complexity and delay is still a big problem; Max-Log-MAP algorithm with low complexity could not achieve a good performance as the Log-MAP algorithm. This paper proposed an improved Turbo decoding algorithm based on a linear approximation of the correction function. The improved algorithm adopted different correction fitting parameters for different regions. The simulation results demonstrate that, compared with the existing algorithms, this improved algorithm can achieve the same Bit Error Rate (BER) performance as the Log-MAP algorithm and effectively reduce the decoding delay. More importantly, the proposed algorithm is better for implementation.

In multi-user MIMO (Multiple Input Multiple Output) system, the users transmit the Channel State Information (CSI) to the base station through feedback. Then the system could achieve the multiplexing gain through precoding or user scheduling with the received CSI at the base station. Concerning that the traditional way of feedback takes up too many uplink resources, a limited feedback MIMO precoding algorithm was proposed based on Grassmannian codebook. Only a few bits were required to be the feedback to the base station because the new approach quantized the channel matrix and transmitted the sequence number of the quantized channel matrix according to the codebook, which reduced the feedback load considerably. The simulation results of the Bit Error Rate (BER) and throughput rate show that the new approach maintains the performance of the system. Furthermore, the system throughput is illustrated on the condition that the estimated error and quantized error of the channel matrix exist. The analytic expression with the throughput, variance of error and transmitted power will benefit the channel estimation process.

Phase space reconstruction is an important part in recognizing chaos during ship's sailing, it directly influences the result of chaotic analyzing and the effect of chaos controlling. In order to choose a proper method, this paper reconstructed the ship's sailing data series by two methods, and compared the performances of reconstructions. It is proved that the C-C method does well on processing ship's sailing data series, while the autocorrelation &G-P method does a little bad. Different methods were used to conduct qualitative analysis and quantitative analysis based on the phase space reconstruction, the results of the analysis show the existence of chaotic characteristic in the ship's sailing data series, which provides the following research on ship's chaos control with essential basic data and comparison foundation.

In order to get rid of the noise of flight data more effectively, based on discussing the principle of Stationary Wavelet Transform (SWT), a new denoising method was proposed, which combined correlation of wavelet coefficient with wavelet shrinkage. Firstly, signals were decomposed by using SWT; secondly, wavelet coefficient was dealt with by using methods of coefficient correlation and wavelet shrinkage in sequence; at last, denoised signal was reconstructed through inverse wavelet transform. The results of experiments show that the proposed method can raise Signal-to-Noise Ratio (SNR), decrease Mean Squared Error (MSE) and preserve the shape of signal; and it can be applied to flight data effectively.

Test case generation of EFSM (Extended Finite State Machine Models) includes test path generation and test data generation. However, nowadays most research into EFSM testing focuses on test path generation. In order to explore the automatic test generation, a test data generation method oriented to the path of EFSM models was proposed. A Tabu Search (TS) strategy was adopted to automatically generate test data, and the key factors that affect the performance of test data generation in EFSM models were analyzed. Moreover, the test generation efficiency was compared with that of Genetic Algorithm (GA). The experimental results show that the proposed method is promising and effective, and it is obviously superior to the GA in the test generation for EFSM models.

The application of traffic smoothing algorithms(mainly WTS) in the context of developing a high-performance streaming server was studied.Two practical problems were analyzed and solved: one was to prevent the application of smoothing algorithm from bringing impacts on synchronization of audio and video streams on the client ends,and the other was to modify the sending plans produced by smoothing algorithms in order to make them applicable in RTP transferring.These two problems were studied and analyzed,and corresponding solutions and algorithms were presented and validated by experiments.

According to the traits and requirements of protocol conformance testing, especially the characteristic of OSPF protocol, the design of a conformance testing system for OSPFv3 protocol was introduced. In our design, the environment of multiple virtual testers with controlling channel was used and Tcl language was choosed as test case describing language. This conformance testing system gets both good testing ability and flexibility. Testing of several different implementations of OSPFv3 protocol was accomplished. An example was shown, and the future work was also discussed.

The modified coding algorithm based on listless zerotree wavelet was proposed by studying SPIHT and LZC. The zerotree coding process was improved, and the complexity of the encoding procedure was reduced. The novel algorithm was easy to be realized by hardware. The top bits of transformed coefficients were used to store flag maps, and the memory requirements of coding process were further reduced. Experiment results show that PSNR(Peak Signal Noise Ratio) values of the novel algorithm are obviously better than those of LZC, and less than those of SPIHT appreciably at the same compression ratio.

The document images scanned may be skew somehow. Severe image skew makes image segmentation difficult and lowers character recognition accuracy. A new approach of skew detection based on Hough transform was presented. In order to overcome the heavy computing burdens of Hough transform,the method selected the subfield with part representation and extracted the horizontal edge from images in the first place, then performed two-stage Hough transform on the edge extracted. Experiment results show that it corrects the skew document images more rapidly and accurately than general Hough method and cross relation method.

 In this paper such a general architecture was presented based on Rejaie’s work on the architecture of media streaming servers, which took into consideration the functions and characteristics of live streaming servers, and incorporated the impacts of fluctuant network environment on them. In this architecture, four function modules, namely Rate Control Module, Error Control Module, Video Quality Adaptation Module and Buffer Control Module, comprise the whole server. These modules respectively perform specific tasks, and collaborate to enable the whole server systems to provide adaptive video streaming services as a whole. How they can interplay and cooperate was discussed thoroughly in this paper. This architecture presented in the paper can be flexibly configured according to specific needs of particular applications, and can be helpful to development of live streaming server systems.