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The Boolean functions are cryptographic functions that have been widely used in the fields of cryptography, error correction coding, and spread spectrum communication. Finding good performance Boolean functions has always been one of the important issues in the field of cryptography. Based on the gravitational search algorithm, this paper designed a new algorithm for searching Boolean functions. This algorithm imitated the law of universal gravitation, used the mass points in n-dimensional space to represent the Boolean function, and used the cryptographic characteristics of the Boolean function as the target fitness function for searching. The experimental results show that by changing the newly designed target fitness function, a balanced Boolean can be directly generated that meets a variety of cryptographic indicators such as 1-order resilient, 1-order propagation, or high non-linearity, high algebraic number, and low auto correlation index function. Further more, this paper implemented a computer search algorithm that directly generated a 2-output balanced Boolean function. [ABSTRACT FROM AUTHOR]

To solve the problem of clustering of platform resources in C2 organization, this paper firstly defined each element in process of decision-making entity configuration, then defined the workload by two aspects as inside workload and outside workload. It took the root mean square(RMS) of workload as the objective function to establish the decision-making entity configuration model, and took the platform scheduling scheme as the input information, and applied ant colony algorithm based on global updating rule to solve this problem. Finally, this paper verified and analyzed the method by simulation example. Results show that this method obtains a greater clustering scheme, and it has advantages over traditional methods in terms of clustering results and convergence speed. [ABSTRACT FROM AUTHOR]

For the problem that the ICI self-cancellation algorithm leads to the underutilization of the UFMC system frequency band, this paper proposed an improved scheme that combines partial self-cancellation and raised cosine windows. This scheme specifically inserted the self-eliminating sub-carriers into the UFMC system' s transmitting terminal band boundary, and performed windowing in the time domain at the receiving end of the UFMC system to achieve the purpose of suppressing UFMC system interference and improving system band utilization. This paper conducted simulation experiments of the algorithm on MATLAB platform. There were four self-cancelled sub-carriers on both sides of the sub-band, the system carrier-to-interference ratio increased compared with the self-cancellation algorithm, and the spectrum utilization of the system also increased by 10%. The simulation results show that the proposed algorithm can effectively suppress ICI, improve the system' s anti-jamming performance, and improve the system bandwidth utilization. [ABSTRACT FROM AUTHOR]

As for the tme-efficient A* algorithm significantly reduces the algorithm time, lead to the problem of increase path planning length and path sawtooth. This paper proposed an improved bidirectional time-efficient A* algorithm, which ran the A*algorithm from the start and the end point to find the path and applied the multiple neighbor grid distance computation scheme. At the same time, according to different environment map, this paper compared and analyzed the A* algorithm, time-efficient A*algorithm and bidirectional time-efficient A*algorithm. Finally, it chose the index of algorithm time and path length as two indicators to evaluate the merits and demerits of the algorithm. Experimental results show that compared with traditional A*algorithm, the bidirectional time-efficient A*decreases the time of the algorithm by 76. 8% at the maximum, and reduces the maximum time by 55. 4% compared with time-efficient A*algorithm. It also solves the problem that the path distance of the time-efficient A*algorithm is augmented and the path is not smooth enough. [ABSTRACT FROM AUTHOR]

In order to overcome AES key expansion's safety problem, this paper proposed a new key expansion method and used the simplest MixColumn and inverse MixColumn operation on GF(28) to replace the former. In aspect of RSA,this paper suggested a four prime RSA with Chinese remainder theorem and Montgomery algorithm to improve the computing efficiency. Then it proposed a mixed encryption system and created a high security communicating model. Experiments show that advanced algorithm is faster than the original and mixed system has higher practicability. [ABSTRACT FROM AUTHOR]

To solve the privacy security problem of the recommendation algorithm between systems,this paper developed a secure computation model based on the theory of secure multi-party computation. The model used LBlock,a lightweight block cipher algorithm,to encrypt the provided data by the third part,and used RSA public key cryptosystem to manage keys of LBlock. Applying this model to the collaborative filtering between systems with randomized perturbation techniques,the paper developed a new algorithm whose calculation method of similarity could protect the system from the attack of artificial users. It used secure vector to prevent the untrusted third party from colluding. Experiments show that algorithm not only has stronger ability to protect the user’s privacy disclosing to the system which is cooperated,but also has better quality of recommendation. [ABSTRACT FROM AUTHOR]

Firstly, this paper analyzed the characteristics of the micro-blog text and designed a filtering algorithm of garbage micro-blog. Then, in order to solve the problem of data sparsity, taking full advantage of the feature of community tightness, this paper proposed the concept of micro-blog comments tree and an evaluation model of hot topic. Finally, based on the two points above, it proposed a hot topic detection method on micro-blog community. Experiments on real data sets show that the necessity of the filtering algorithm and the validity of hot topic evaluation model and hot topic detection method. [ABSTRACT FROM AUTHOR]

This paper compared and analyzed statistical parameters of partial Hadamard matrices and Gauss matrices in order to optimize Gauss matrices. It determined the main influencing factors that led to partial Hadamard matrices' excellent behavior. Moreover, this paper proposed the optimization algorithm of Gauss matrices. It verified the validation and generality of optimization algorithm by Gauss matrices of different size, and determined optimal matrices' applicability to different sparse signal reconstruction algorithms. At last, it conducted preliminary theory experiment analysis of optimal matrices' performance. Optimal matrices were as much as partial Hadamard matrices more in the signal recovery ability. The research results provide a new idea and method for the analysis, design and optimization of measurement matrices. [ABSTRACT FROM AUTHOR]

In order to do further research on enigmatical knapsack problems, this paper proposed an economic model based on dynamic expectation efficiency, and established a new optimization algorithm of 0-1 knapsack problem after analysis and research with the traditional theory of solving knapsack problem. And this paper gave the individual experiment and comparison experiment with artificial glowworm swam algorithm. The results of experiment show that the algorithm is better than greedy algorithm, backtracking algorithm, dynamic programming algorithm and bound algorithm in the same 0-1 knapsack problem. In comparison with artificial glowworm swam algorithm, this algorithm improves convergence speed largely and saves the storage space, and the convergence speed is ten times as the artificial glowworm swam algorithm. Finally, this paper gave 20 0-1 knapsack problems, proved the feasibility of the algorithm, and determined an adaptive scope of the algorithm. [ABSTRACT FROM AUTHOR]

Current Internet security architecture is fixed and exhibits low efficiency. Based on the thinking of "supporting diverse security applications with the variable limited node resources and providing multilevel security guarantee by inherent security architecture", avoiding limitations of traditional model aiming at pursuing high security quality of service and ensuring security by providing more flexibility and scalability, this paper first presented a network reconfiguration-oriented security business-services-components model, and gave a preliminary conception of reconfigurable network security architecture as well. Then this paper proposed a novel security structure which was named reconfigurable security carrying network (RSCN for short) to provide multilevel security guarantee. At last, it gave the construction algorithm and reconstruction algorithm of RSCN. The simulation results show that the algorithms are effective. [ABSTRACT FROM AUTHOR]

Aimed at the problem that the noise data influence on the anomaly detection results for time series, this paper put forward a kind of uncertain continuous time series Top-K anomaly detection algorithm. Based on the typical time series anomaly detection method, it dealed with time series discord as interval, and structured density functions of uniform distribution. Then it combined with the uncertain scores Top-K technology to implement Top-K ranking on uncertain time series data with noise and unknown distribution. Experiment tests on simulated data and real data, this proposed algorithm has increased significantly in anomaly detection accuracy than traditional time series detection method. Although the method has increased in computing time, this paper put forward the corresponding optimization strategy and improved on computing time obviously when the K value was large. It verifies the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

This paper designed a new algorithm for vertex-distinguishing edge coloring of graphs. This new algorithm had combined probability thought and graph coloring, established objective function according to the constraint rules of vertex-distinguishing edge coloring, used exchange rules to optimize the results gradually, accomplished coloring when the value of objective function met the requirements. The paper also described the algorithm steps in detail, tested and analyzed it. And the experimental results show that the edge chromatic number that the algorithm got conforms the conjecture of vertex-distinguishing edge coloring of graphs. [ABSTRACT FROM AUTHOR]

This paper proposed an adaptive similarity mapping algorithm for high-speed Ethernet based on the special nature of user behavior and characteristics of the flow quintuple. It fully considered the random distribution of the quintuple in this algorithm and designed an improved XOR-SHIFT algorithm for flows classification. This paper raised concepts of similar database and heterogeneous database and designed similarity comparison functions for this two databases. With this method, similar eigenvalues can be mapped to data files precisely and matching efficiency is improved. It carried out some simulation tests in the campus network and proved that this mapping algorithm has higher precision and applicability than other methods. It is appropriate to search similarity flows in large data networks. [ABSTRACT FROM AUTHOR]

In view of that the rational exchange protocol was a dynamic game model, under complete imperfect information dynamic game, this paper introduced the maximum entropy principle to solve the problem of strategy behavior inference of rational party. Based on information entropy, this paper extended a rational exchange protocols model in which a new fairness description was given combined with a desired payoff function and an expected equilibrium. In addition, it constructed a new rational exchange protocol based on the maximum entropy principle, which was proved secure and fair. Meanwhile, made analysis of the exchange process by game tree. Results show that the proposed protocol can achieve expected equilibrium. Without the participation of the trusted third party, the protocol can achieve rational fairness and be beautifully adapted to the real environment. [ABSTRACT FROM AUTHOR]

According to the virtualization technology of cloud computing, it can solve the problems that the electronic cash systems exist leakage of privacy, non-standard transactions and high cost in the traditional network. In the existing work, considering merchants and customers used the same bank to restrict the widespread use of electronic cash in a certain degree, the paper presented an multi-bank electronic cash payment scheme for trusted cloud platform based on TPM. Considering the efficiency and security from the electronic cash payment of the scheme, the scheme used the group signature and elliptic curve algorithm ECC to improve the execution efficiency of the protocol, and used the privacy protection and remote attestation function of TPM to achieve security. Finally, the paper analyzed the safety and efficiency of the scheme. [ABSTRACT FROM AUTHOR]

In order to realize intelligence management of guide sign system, this paper proposed an algorithm for deploying guide signs using guide sign data model from the perspective of road guiding levels. The algorithm took road intersection as research object, and guide sign information was classified into two categories, namely, connection signs and direction signs according to the relationship of guide signs information and road network topology. Moreover, the paper illustrated the selection principles of directional signs based on road guiding levels, and constructed deployment algorithm model for directional signs. Finally, a case study was conducted: the deployment model was tested in Guangzhou Higher Education Mega Center. The result revealed that the data model could support the automatic deployment, analysis and evaluation for guide signs. [ABSTRACT FROM AUTHOR]

Aim at the problem for how to analyze the propensity to spread of shortage of supplies in emergency logistics decision support system, this paper proposed a new model to study the propensity to spread of shortage of supplies for emergency logistics network. This paper, by the mechanism of viral spreading and introducing the parameter of time "t", it constructed SI-SIRS ( susceptible infective and susceptible infective recover susceptible) model to analyze the scale-free network which included 61 nodes. Case analysis shows that SIRS effectively depicts the spread behavior of shortage of supplies in emergency logistics network. Propensities to spread of shortage of supplies are effected by node self-spread ability, network topology, individual nodes differences and responding mechanism of emergency logistics. [ABSTRACT FROM AUTHOR]

Direction is a key factor of accessibility research. Therefore, this paper proposed a calculation method on space-time accessibility considering the direction of travel. First, it constructed an experiential hierarchy of road network using experiential taxi routes. Second, it used the Dijkstra algorithm based on hierarchical road network to compute the travel time between each OD, and then used a grid method and inverse distance weighting method to render the isochrones maps of Guangzhou CBD. Finally, the paper analyzed the accessibility of it in different direction of travel and different time periods. The experimental results prove that accessibility in different direction, especially in peak time, is quite different. [ABSTRACT FROM AUTHOR]

Community structure is one of the most important and basic topologic properties of complex network. The rational division of community structure in complex network is the main purpose of the complex network's community division research. This paper mainly researched the division of community structure in complex network based on the theory of supernetwork and standardized degree centrality. Based on the lack of GN algorithm, this paper proposed a new comprehensive algorithm to divide community structure from the perspective of supernetwork. Finally, the new comprehensive algorithm is illustrated through examples. [ABSTRACT FROM AUTHOR]

In order to promote the feasibility of the construction of cubic splines, this paper presented a novel pseudoinverse-based construction method (PCM) to construct the cubic spline function effectively. Without using endpoint-constraint conditions, this method obtained the solution of the second-order derivatives of the cubic spline that was closest to the origin, namely the minimum norm solution. Theoretical analysis and numerical experiments highlight the efficacy of the PCM. For better understanding, it further studied and investigated the characteristics of various construction methods. In this way, it provided guidelines for choosing suitable methods to construct cubic splines in practical applications of engineering calculation. [ABSTRACT FROM AUTHOR]

This paper presented an efficient hierarchical group signature scheme which could meet the high performance needs of modern e-commerce and e-government. First, the scheme improved the elliptic curve digital signature scheme, which avoided time-consuming modular inverse, the modular multiplication and reduced once point multiplication. Thus it improved the efficiency of the signature and verification algorithms. Then the scheme constructed an efficient group signature scheme based on the improved ECDSA. Finally, the program combined with message level table and put forward an efficient hierarchical group signature scheme based on elliptic curve. The analysis shows that the scheme greatly shortens the hierarchical group signature and verification time. Compared with existing schemes, the new scheme has high efficiency and greater safety. It also has strong practicability and the advantages of the elliptic curve cryptosystem. What's more, it is applicable to intelligent systems. [ABSTRACT FROM AUTHOR]

In order to improve the efficiency of such vulnerabilities discovery, this paper presented a method which used data correlation analysis auxiliary vulnerabilities discovery. Firstly, the method decompiled target files and constructed the abstract syntax tree (AST), designed algorithm to extract the inversely correlation information of key variables. Then, it applied the extracted information to detect of buffer overflow. This method has obvious advantages in non-source code vulnerability discovery, can discover buffer overflow in the software effectively, and improve the efficiency and automation of vulnerability discovery. [ABSTRACT FROM AUTHOR]

To solve the problem that nodes can easily suffer from various attacks during the process of coverage optimization, this paper discussed reliable coverage technology on the basis of the trust management system framework, and proposed a reliable coverage algorithm based on grid trust value. The algorithm performed the reliability screening and rotation scheduling on nodes, and the coverage based on the credibility of grid point by the way of parallel coverage. After discussing the value of the trust threshold, the paper found that it had a significant influence on the security of whole coverage area and the coverage quality. By comparing the new algorithm with traditional single coverage algorithms, the algorithm can improve the security and network lifetime effectively. Simulation experiments show the effectiveness of this algorithm and reflect the correctness of the analysis. [ABSTRACT FROM AUTHOR]

This paper did a research regarding the immune intrusion detection system and the IP traceback. By deploying distributed immune intrusion detection and data packet mark, this paper utilized immune intrusion detection system to analysis network packet's characteristic in real time to instruct path marking technique dynamically, making path marking method adaptable to different characteristics of network data, rapidly recognized attack path, and provided the path information to the immune intrusion detection system with the regard to develop characteristics checker for attack path. Experiments show that this method can reconstruct the information of attack path very fast, and is better than the-state-of-art probabilistic packet marking algorithm in terms of the convergence efficiency and false alarm rate, can provide the information of attack path to immune intrusion detection system. [ABSTRACT FROM AUTHOR]

Image quality assessment is of fundamental importance to numerous image processing applications. Objective image quality metrics can be classified into three categories: full reference, semi-reference and no-reference. Currently, full reference metrics can achieve satisfied performance, while semi-reference and no-reference metrics are in their preliminary stage. This paper gave an overview of the full reference image quality assessment. Firstly, it introduced these methods briefly. Secondly, it described several important full reference image quality assessment algorithms in detail, such as PSNR, SSIM, MSSIM, IFC, VIF and FSIM. Then it compared the performance of these methods in the LIVE database and TID2008 database. Finally, this paper summarized the trends of future research on image quality assessment. [ABSTRACT FROM AUTHOR]

In order to improve the performance of the object localization technology, this paper researched the approach of fusing image classification into object localization. According to the object localization task in the large-scaled image set containing multi-class objects, this paper proposed an effective scheme that a fast image classification was carried out before a precise object localization. The MIMLSVM + algorithm predicted which images contained the objects, then the ESS method localized the objects just in those images. And aiming at a higher precision in the object localization task, the paper proposed a new scoring mechanism of the optimal box which included the global classified information in the multi-label classification task. The corresponding experimental results on the PASCAL 2006 data set show that the former method shortens the processing time while obtaing a good average positioning accuracy; the latter method brings an improvement in the localization performance on many categories as it make the scoring mechanism of the optimal box better. The experimental results prove that fusing image classification into object localization can really improve the performance of object localization. [ABSTRACT FROM AUTHOR]

In order to use computer to get high quality hillshading map automatically, the paper analysised the HSV color model and used elevation data to calculate the H and S components of the HSV color space. It introduced the Hillshade algorithm to calculate hillshade value and used the hillshade value to instead of the reflected light intensity of the earth's surface point. Then it used the reflected light intensity to calculate the V component of the HSV color space, consequently constructed a set of mapping model from elevation and reflected light intensity to all the components of HSV color space. Experiments was programmed with visual C ++. NET. Practices prove that the shaded image with the method described in the paper has the characteristics of natural color transition, clear topography distinguish and strong stereo sense. Compared with ENVI 4. 5 software to create hill shade image with suitable color table, the color transition is more natural and the details are better. [ABSTRACT FROM AUTHOR]

This paper introduced the development of 3D virtual robot kinematics simulation system. And this paper elaborated an effective method of building 3D virtual robot kinematics simulation system based on a physics engine. According to the characteristic of the virtual robot parts and the functions, it described the robot graphical modeling method, sensor functions and the kinematics simulation procession. The experimental results demonstrate that the kinematics simulation system works well based on the physics rule, and it is better than LEGO software. [ABSTRACT FROM AUTHOR]

In the process of encoder grating assembly, the center of rotation and grating encoder main shaft is difficult to coincidence which will affect the accuracy of output signal from the encoder. In order to solve the eccentric problem of the encoder grating, this paper put forward a grating eccentric automatic adjustment system based on machine vision to analyse and process the image of the surface of grating. It studied boundary tracking algorithm and arc detection algorithm based on Hough transform. At first, it built the hardware system of eccentric computational system according to the requirement of the grating assembly. Then it made the grating image preprocessing and morphological operations. On the basis of the analysis and the extraction of part of the grating base circle's arc boundary, it restored the base circle of the grating and demarcated the center of circle with the principle of arc detection based on Hough transform. At last, this paper introduced the system which fitting turning circle by the centre of grating base circles and determined the grating eccentric position. The experimental results show that the computational method of eccentricity based on machine vision encoder grating calculates the eccentric position of the grating and the main spindle successfully, lays the foundation for grating eccentric adjustment. The grating eccentric computational system has a very good feasibility in the encoder grating assembly operations. [ABSTRACT FROM AUTHOR]

In order to solve the problems of background interference in the Mean-Shift tracking algorithm, this paper proposed an improved algorithm based on color and texture blending characteristics and background weighted update approach. The original RGB image was converted into the HSV color space, then color feature was extracted in the H, S channel and texture feature was extracted based on the LBP descriptor in the V channel. Base on this, this paper established the color-texture histogram of the object region and background. During object tracking, it updated the background region using weighted update approach according to the Bhattacharyya coefficient. The extensive experimental results show that, compared with the algorithm adopting the full background update approach with color or color-texture features, the improved algorithm makes full use of color and texture features and adopts weighted updated background region, and has a higher level of reliability and robustness and better execution efficiency. [ABSTRACT FROM AUTHOR]

In order to accurately forecast pollutant emission volume nationwhide, this paper constructed an improved gray Markov chain model by combining gray prediction with Markov chain, given the fact that pollutant emission was under the influence of multiple gray factors and the acquired pollution data was characteristic of high stochastic volatility. This gray system model was used for predicting general trend of pollutant emission volume, while the Markov chain was used as a sensor for detecting the system's stochastic volatility. Moreover, this model improved through real-time correction for more accurate prediction. On that basis, this paper applied an improved model to forecast pollutants' emission reduction based on gray Markov chain. Finally, it carried out a case study to forecast SO2 emission volume nationwhide, which analysed the forecast accuracy and validity of this model. The results demonstrate that, compared with traditional ones, this newly-combined gray Markov model has improved the prediction accuracy obviously and is an effective algorithm for the prediction of pollutant emission volume. [ABSTRACT FROM AUTHOR]

To solve the lack of real-time traffic information source, visual sensoring and interaction ability, this paper proposed a novel model of traveler information system--MMTIS, based on mutual interaction between cloud scheduling and intelligent terminal sensoring. It mainly focused on the research of cloud scheduling algorithm, combined with simulation and model machine testing. This paper presented a traveler information system based on MMTIS, along with the industrialization case study. [ABSTRACT FROM AUTHOR]

This paper studied the capacity of resisting rotational attack of Luffa hash function. Through analyzing characteristics of Luffa permutation, it defined the rotational pair of Luffa permutation, gave the influence of basic word transformations to rotational relation, proved that the AND operation and the OR operation had the same influence on rotational relation, and presented the distinguisher algorithm between round-reduced Luffa permutation and a random permutation. Theoretical analysis and experiment results show that 3 round Luffa permutation can't resist rotational attack and the attack complexity is only 216. [ABSTRACT FROM AUTHOR]

In order to improve 2D thresholding algorithm's processing speed, this paper presented a fast implementation method of 2D Otsu. Based on marginal probability distribution of bivariate discrete random variable, it calculated two ID optimal threshold, s* and t*, and then kept (s*, t* ) as the optimal 2D Otsu threshold. Furthermore, in order to improve the segmentation of the original algorithm, this paper introduced the definition of intra-class variance and proposed a new discriminant. The experimental results show that the proposed algorithm outperforms original algorithm. Without losing the robustness to noise, its time complexity is reduced from O (L) to O (L), space complexity is reduced from S (L) to S(L), and the misclassification rate is lower. The method is suitable for handling the fast threshold segmentation of Gaussian noise images. [ABSTRACT FROM AUTHOR]

This paper proposed a parallel video coding scheme based on MapReduce. It divided the input video sequence into segments and mapped to multiple computers in the form of tasks. After that, it encoded all these tasks in parallel at different computer nodes to achieve better encoding speed. In order to minimize the makespan of a given tasks set and balance the system load, this paper proposed a LBMM algorithm according to the computing capacity and the coding charactertics. The simulated results show the proposed parallel video coding system greatly improves the big volumn video sequence coding efficiency, reduces the average job response time. The LBMM algorithm outperforms Min-Min (minimal-minimal complete time) algorithm and RR (round robin) algorithm using in CloudSim. [ABSTRACT FROM AUTHOR]

Traditional measurement method of skull and craniofacial similarity has some disadvantages, such as discrete point correspondence, the errors caused by curve fitting and the problem of manual intervention and so on. In order to overcome those problems, this paper proposed the measure method based on resampling and DFT (discrete Fourier transform) of contour pixel. This paper first used Canny operator and sliding window method for edge detection and boundary tracking. Secondly, it took resampling on a pair of contour extracted from the edge of mandibular of skull and craniofacial image. Then it employed normalizing and discrete Fourier transform, measured the similarity of this pair of Fourier descriptor. Finally, it got a measurement value of determining similarity. Experimental results show that the method achieves a precise effect, has lower algorithm complexity, realizes automatical evaluation process and lays a foundation for skull-photo superimposition of identity authentication. [ABSTRACT FROM AUTHOR]

Aiming at the reasonable placement of different business contents in content centric networking (CCN), this paper proposed a hybrid caching scheme based on service classification and node partition (SCNP). For streaming media-on-de-mand services, this scheme used push-pull cache strategy based on popularity to achieve its sequential storage in the edge network. For non-streaming contents, this scheme used hash-based explicit cache strategy to implement its placement of single copy in the core network. Simulation results show that compared with the classic cache algorithms, this scheme can improve the cache hit ratio and the hop reduction ratio, and reduce the average request delay. [ABSTRACT FROM AUTHOR]

In order to further excavate the hidden information between data, under the framework of multilayer concept factorization algorithm, this paper proposed a novel algorithm called dual-graph regularized multilayer concept factorization algorithm, which encoded the geometric structure information of data and feature spaces by constructing two Laplacian regularize term in each layer factorization, respectively. By this way, the proposed method could learn features in a hierarchical manner, and thus provided a better chance for learning meaningful features from the complex data. Moreover, it developed the iterative updating optimization scheme for DHCF, and also provided the convergence proof of the optimization scheme. Experimental results on TDT2 document datasets, PIE and COIL20 image datasets demonstrate the effectiveness of this proposed method. [ABSTRACT FROM AUTHOR]

Currently, due to lack of effective iterative stopping criterion(ISC), most of the ID algorithms are usually implemented with fixed iteration steps, leading to the low efficiency and poor deblurring results. Therefore, this paper proposed a deblurring measure(DM) based on the residual image(the difference between the intermediate estimated image convoluted with blur kernel and blur image during each iterative step). Based on the proposed DM metric, it designed and applied an adaptive iterative stopping criterion(AISC) to the classic nonlocally centralized sparse representation(NCSR). Extensive experiments on uniform blur, Gaussian blur and motion blur show that, compared with the original NCSR algorithm using fixed iteration steps, the NCSR algorithm adopting AISC has an obvious advantages in terms of efficiency and the reconstructed images have a similar image quality in terms of peak signal-to-noise ratio(PSNR), structural similarity(SSIM) and feature similarity(FSIM). [ABSTRACT FROM AUTHOR]

Due to the impact of the surrounding environment, the stability of Wi-Fi fingerprint positioning was very poor. And the PDR couldn’t independently give positioning result without the initial position of the target and had serious cumulative error. To address this issue, the paper presented a Wi-Fi indoor positioning algorithm based on PDR feedback. The scheme consisted of three processes. The first was to get the initial position based on relevance vector regression (RVR) methods, and the second was the feedback correction process which based on PDR. The third was the fingerprint positioning process based on Knearest neighbor (KNN) algorithm. Experimental results show that the proposed algorithm can well improve the accuracy and stability of the final positioning result. And the proposed method can greatly reduce the time complexity which improves real time performance. [ABSTRACT FROM AUTHOR]

In order to improve the classification accuracy of the minority samples, this paper proposed a novel resampling algorithm based on the improved density peaks clustering method, named IDP-SMOTE. First, it improved density peaks clustering algorithm by utilizing Box-Cox transformation and σ-rule for finding the clustering centers and outliers automatically. Second, it combined the improved density peaks clustering algorithm with SMOTE method. With removing the noisy data, the synthetic samples could be generated in the sub-class regions on the basis of the values of local density and nearest distance of the minority samples. The presented algorithm avoids the boundary ambiguity caused by over-sampling, improves the imbalance problem with-in class and reduces the learning difficulty of the boundary data. Meanwhile, it realizes automatic clustering and resampling, and avoids the interference of subjective factors. Through the contrast experiment, the proposed algorithm is effective and adaptive. [ABSTRACT FROM AUTHOR]

In order to construct a good topology, reduce nodes energy consumption and extend the lifetime of the network, this paper improved the traditional GAF algorithm. Considering the problem of connectivity and the optimal number of cluster heads, this paper proposed a new method of dividing the virtual cells. Not only considering the residual energy of nodes and the distances from base station, but also taking into account the node throughput in the cluster head selection stage. Besides, by defining the cluster-head selection function to find the cluster head. Simulation results show that, the improved GAF algorithm has effect on reducing the node's energy consumption and extending the network lifetime. The performance of the algorithm is better than the traditional GAF algorithm. [ABSTRACT FROM AUTHOR]

This paper concerned with the non-differentiable equations and the absolute value equations. Based on maximum entropy and a new interval opeator, this paper proposed a interval maximum entropy algorithm which could solve the absolute value equations and estimate error between real solution and approximate solution. It proved the convergence and linear convergent rate when the singular values of A exceeded the singular value of |B|. Theoretic analysis and numerical results show the method is effective. [ABSTRACT FROM AUTHOR]

In order to improve anti-multipath interference debility of linear frequency modulation (Chirp) binary orthogonal keying (BOK), this paper proposed an algorithm emploied square law detection and equalization. Square law detection could resist the influence on pulse compression caused by frequency offset and phase offset, to low complexity and enhance robust, its performance reduction was less than 0. 2 dB in the condition of high frequency offset and doppler frequency shift extension. This paper analyzed the equalization model of BOK square law detection, demonstrated the feasibility of the equalization and corroborated the performance of equalization and detection in multipath channel with high frequency offset and doppler frequency shift extension. The simulation results indicate that introducing square law detection and equalization can efficiently improve system performance. [ABSTRACT FROM AUTHOR]

To solve the problem of detecting faces with large variances on pose and illumination under complex background,this paper presented a robust and fast algorithm which combined selective search strategy with Gabor optimizing convolutional neural network. Selective search strategy selected the candidate regions. Image warping computed a fixed-size convolutional neural network input from each region proposal. After a series of convolution and pooling operations,convolutional neural network extracted features of candidate regions to confirm whether candidate regions contained faces or not. Experiments on LFW database show that Gabor optimizing convolutional neural network can avoid the uncertainty of traditional feature extraction and has better generalization and robustness. [ABSTRACT FROM AUTHOR]

In order to overcome the traditional mutual information-based multimodality medical image registration algorithm is easy to drop into local optimal problem, this paper presented an improved multi-resolution three-dimensional medical image registration method. In this method, original images were decomposed into multi-scale image pyramid by Gaussian filter, and Mattes mutual information was used as the similarity measure of the registration framework. It used the particle swarm optimization algorithm to search global transformation parameters in lower resolution layer of image pyramid, then took the global transformation parameters as the initial parameters of high resolution layer registration optimized by Powell optimization algorithm. The experimental results show that the improved registration method not only makes the spatial position of images align, but also is higher precision, better robustness than traditional mutual information method. And it can efficiently solve the possibility of registration algorithm based on mutual information dropping into a local optimal solution. [ABSTRACT FROM AUTHOR]

In order to overcome the shortages of the traditional wavelet transform, this paper presented new image denoising algorithm based on the combination of symmetrical normal inverse Gaussian model in nonsubsampled quaternion contourlet transform (NSQCT) domain and non-local means filter (NLMF) in spatial domain. It constructed NSQCT by combining the quaternion wavelet transform (QWT) and nonsubsampled directional filter banks (NSDFB), which had highly directional selectivity, multi-direction and approximate shift invariant. Simulation experiment shows that the algorithm can obtain better performances than those classical denoising algorithms in terms of peak signal-to-noise ratio (PSNR), mean structural similarity (MSSIM) as well as visual quality. [ABSTRACT FROM AUTHOR]

For the disturbance such as shadows, lights, cracks and other factors, current road marking segmentation methods could not achieve accurate segmentation. This paper proposed the road marking segmentation method based on splitting and merging algorithm. By analyzing the features of gray, edge, texture of road marking lines, it used the bresenham algorithm to judge whether there were road marking lines in the detected images. Road images were divided into road marking areas and non-road marking areas by road marking lines. Secondly, it used two methods which were the region merging method based on the center of gravity lines of gray value and the region merging method based on the gray and edge feature of road marking areas to complete the mergence of road marking areas. The experimental results show that the proposed method, which has a higher accuracy of segmentation and good robustness, can well meet the needs of the real-time processing of images acquired by road detection vehicles. [ABSTRACT FROM AUTHOR]

Aiming at the problem that isotropic algorithm can easily blur the feature of image information and that tensor-based algorithm will produce pseudo striations at noisy points within homogeneous regions, this paper proposed a feature parameter that was local variance of image, this parameter could effectively reflect local structural features of image, based on this parameter, it proposed a novel algorithm that combined the above two algorithms. The proposed algorithm could adaptively adjust to the diffusion rate of the above two diffusion algorithms according to local statistics of image when de-noising on different regions of the image in order to preserve the advantages and cancel the drawbacks existed in the two algorithms mentioned above. The experimental results show that the proposed algorithm compared with others classical algorithm can remove the noise effectively and preserve, enhance the image edges better. [ABSTRACT FROM AUTHOR]

Aiming at the poor generalization of the ISOMAP algorithm when applied on new samples, this paper proposed MRC-ISOMAP (manifold reconstruction-ISOMAP) algorithm to reduce sample characteristics' dimension on the basis of having an in-depth understanding of LLE algorithm's local reconstruction idea. For training samples, MRC-ISOMAP adopted ISOMAP algorithm's global nonlinear structure theory to calculate training samples' low-dimensional representations, and for added samples, the algorithm adopted the theory of local linear to maintain local linear relationships which could conduct the new samples' low-dimensional representation reconstructed by low-dimensional training samples more quickly and accurately. Comparing with the original ISOMAP algorithm, experiments on USTB3 ear image library show that MRC-ISOMAP algorithm can get a higher recognition rate, and achieve a higher efficiency when dealing with added samples. [ABSTRACT FROM AUTHOR]