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Kosmos
Astronomia Astrofizyka
Inne

Kultura
Sztuka dawna i współczesna, muzea i kolekcje

Metoda
Metodologia nauk, Matematyka, Filozofia, Miary i wagi, Pomiary

Materia
Substancje, reakcje, energia
Fizyka, chemia i inżynieria materiałowa

Człowiek
Antropologia kulturowa Socjologia Psychologia Zdrowie i medycyna

Wizje
Przewidywania Kosmologia Religie Ideologia Polityka

Ziemia
Geologia, geofizyka, geochemia, środowisko przyrodnicze

Życie
Biologia, biologia molekularna i genetyka

Cyberprzestrzeń
Technologia cyberprzestrzeni, cyberkultura, media i komunikacja

Działalność
Wiadomości | Gospodarka, biznes, zarządzanie, ekonomia

Technologie
Budownictwo, energetyka, transport, wytwarzanie, technologie informacyjne

Journal of Multimedia

In order to solve network security problem, we need identity authentication protocol to ensure legal user’s authority. Multi-factor identity authentication protocols have more merits than the common identity authentication protocol. This paper analyzes the shortcomings of existing network identity authentication methods, and proposes a new authentication protocol based on SM2 and fingerprint USBkey. The proposed scheme,which Combines the fingerprint USBkey of fingerprint certificate with the National cipher algorithm SM2, constructs the multi-factor authentication model. And the scheme obtains many merits:1) it adopts the challenge response authentication mechanism, and realizes the multi-factor mutual authentication.2) it implements USBkey to verify the user and the remote server authentication by fingerprint features. 3) it can prevent eavesdropping attack, impersonation attack, replay attack and dos attack effectively. 4) it has better calculation and security performance than the existed schemes.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090910691074 2014/09/26 - 06:01

In order to solve network security problem, we need identity authentication protocol to ensure legal user’s authority. Multi-factor identity authentication protocols have more merits than the common identity authentication protocol. This paper analyzes the shortcomings of existing network identity authentication methods, and proposes a new authentication protocol based on SM2 and fingerprint USBkey. The proposed scheme,which Combines the fingerprint USBkey of fingerprint certificate with the National cipher algorithm SM2, constructs the multi-factor authentication model. And the scheme obtains many merits:1) it adopts the challenge response authentication mechanism, and realizes the multi-factor mutual authentication.2) it implements USBkey to verify the user and the remote server authentication by fingerprint features. 3) it can prevent eavesdropping attack, impersonation attack, replay attack and dos attack effectively. 4) it has better calculation and security performance than the existed schemes.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090910691074 2014/09/26 - 06:01

The eye ground texture is disturbed by non ideal imaging factor such as noise, it will affect the clinical diagnosis in practice, an improved multi scale retina eye ground texture recognition algorithm is proposed based on fusion area threshold. The nonlinear sampling multi-scale transform is used to analyze the geometric space coefficient of retinal vessels with multi direction and shift invariant features, the regional threshold filtering is integrated, it is used to suppress the effect of non-uniform blocks for texture recognition. The maximum likelihood local mean standard deviation analysis is used for texture parameters estimation and recognition. The noise reduced greatly, accurate identification of texture feature is obtained. Simulation results show that the algorithm can well characterize the retinal vascular texture, it has good performance in different texture feature recognition, the recognition accuracy is improved, and it has good robustness.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090910751080 2014/09/26 - 06:01

The eye ground texture is disturbed by non ideal imaging factor such as noise, it will affect the clinical diagnosis in practice, an improved multi scale retina eye ground texture recognition algorithm is proposed based on fusion area threshold. The nonlinear sampling multi-scale transform is used to analyze the geometric space coefficient of retinal vessels with multi direction and shift invariant features, the regional threshold filtering is integrated, it is used to suppress the effect of non-uniform blocks for texture recognition. The maximum likelihood local mean standard deviation analysis is used for texture parameters estimation and recognition. The noise reduced greatly, accurate identification of texture feature is obtained. Simulation results show that the algorithm can well characterize the retinal vascular texture, it has good performance in different texture feature recognition, the recognition accuracy is improved, and it has good robustness.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090910751080 2014/09/26 - 06:01

For the structural characteristics of Chinese NvShu character, this paper proposes an improved two-dimensional (2-D) OTSU segmentation method based on the lateral inhibition network for Nvshu character image. A 2-D histogram with the gray level and the lateral inhibition level of the image was established and the maximum between-cluster variance was chosen as the criterion to select the optimal threshold. Experimental results show that the proposed method not only successfully reduced the effect of background noise, but also improved the accuracy of the character image segmentation, especially for NvShu character images with low contrast, uneven gray level of character strokes and uneven background

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090910811088 2014/09/26 - 06:01

For the structural characteristics of Chinese NvShu character, this paper proposes an improved two-dimensional (2-D) OTSU segmentation method based on the lateral inhibition network for Nvshu character image. A 2-D histogram with the gray level and the lateral inhibition level of the image was established and the maximum between-cluster variance was chosen as the criterion to select the optimal threshold. Experimental results show that the proposed method not only successfully reduced the effect of background noise, but also improved the accuracy of the character image segmentation, especially for NvShu character images with low contrast, uneven gray level of character strokes and uneven background

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090910811088 2014/09/26 - 06:01

According to the problem of low positioning accuracy of the existing line detection algorithm and multiple response problem of the single edge detection, this paper presents an improved Hough transform based on Canny operator object detection algorithm which uses the characters of the line segment object from the commonly used edge detection operator to find the best comprehensive properties of the operator. The algorithm can effectively remove the interference of noise, solved the calculation accuracy and computation speed between the optimal matching problems, and effectively solve the problem of multiple peak detection and false peak problem, improve the line segment detection robustness. Experimental results show the algorithm robustness to image noise has been improved, can get the better results.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090910891096 2014/09/26 - 06:01

According to the problem of low positioning accuracy of the existing line detection algorithm and multiple response problem of the single edge detection, this paper presents an improved Hough transform based on Canny operator object detection algorithm which uses the characters of the line segment object from the commonly used edge detection operator to find the best comprehensive properties of the operator. The algorithm can effectively remove the interference of noise, solved the calculation accuracy and computation speed between the optimal matching problems, and effectively solve the problem of multiple peak detection and false peak problem, improve the line segment detection robustness. Experimental results show the algorithm robustness to image noise has been improved, can get the better results.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090910891096 2014/09/26 - 06:01

To describe the ability of image fractional differential in texture detail enhancement and to study the lateral inhibition principle, multiform masks for digital image fractional differential and their operation rules are discussed. The theoretical basis of fractional differential in modulation and demodulation is also analyzed. Through the derivation on the relation between fractional differential and signal time-frequency analysis, we can acquire the separability of two-dimensional fractional differential under certain conditions. Mach’s phenomenon generated in image texture detail is studied by us from two aspects: optic nerve model and signal processing, to propose novel masks. Then its operating rules for digital image processing based on fractional differential are proposed. The experiments show that our scheme can effectively reserve better information of edge texture detail during the denoising process, especially for weak texture and gray with little change. The total enhancing effect is obviously superior to integer order differential operator

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090910971104 2014/09/26 - 06:01

To describe the ability of image fractional differential in texture detail enhancement and to study the lateral inhibition principle, multiform masks for digital image fractional differential and their operation rules are discussed. The theoretical basis of fractional differential in modulation and demodulation is also analyzed. Through the derivation on the relation between fractional differential and signal time-frequency analysis, we can acquire the separability of two-dimensional fractional differential under certain conditions. Mach’s phenomenon generated in image texture detail is studied by us from two aspects: optic nerve model and signal processing, to propose novel masks. Then its operating rules for digital image processing based on fractional differential are proposed. The experiments show that our scheme can effectively reserve better information of edge texture detail during the denoising process, especially for weak texture and gray with little change. The total enhancing effect is obviously superior to integer order differential operator

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090910971104 2014/09/26 - 06:01

Data mining can uncover previously undetected relationships among data items using automated data analysis techniques. In data mining, association rule mining is a prevalent and well researched method for discovering useful relations between variables in large databases. This paper investigates the principle of traditional rule mining, which will produce more non-essential candidate sets when it reads data into candidate items. Particularly when it deals with massive data, if the minimum support and minimum confidence are relatively small, combinatorial explosion of frequent item sets will occur and computing power and storage space required are likely to exceed the limits of machine. A new ant colony algorithm based on conventional Ant-Miner algorithm is proposed and is used in rules mining. Measurement formula of effectiveness of the rules is improved and pheromone concentration update strategy is also carried out. The experiment results show that execution time of proposed algorithm is lower than traditional algorithm and has better execution time and accuracy

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090911051112 2014/09/26 - 06:01

Data mining can uncover previously undetected relationships among data items using automated data analysis techniques. In data mining, association rule mining is a prevalent and well researched method for discovering useful relations between variables in large databases. This paper investigates the principle of traditional rule mining, which will produce more non-essential candidate sets when it reads data into candidate items. Particularly when it deals with massive data, if the minimum support and minimum confidence are relatively small, combinatorial explosion of frequent item sets will occur and computing power and storage space required are likely to exceed the limits of machine. A new ant colony algorithm based on conventional Ant-Miner algorithm is proposed and is used in rules mining. Measurement formula of effectiveness of the rules is improved and pheromone concentration update strategy is also carried out. The experiment results show that execution time of proposed algorithm is lower than traditional algorithm and has better execution time and accuracy

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090911051112 2014/09/26 - 06:01

Automatic target detection is of great importance in high-resolution synthetic aperture radar (SAR) images processing. In this paper, we proposed a hybrid HMM-TSVM model to detect targets in SAR images. Our proposed SAR image target detection system is made up of three steps. In this first step, the testing/training SAR images are pre-processed, and image visual features are extracted through 2DPCA, which is an improved version of principal component analysis. In the second step, we use the HMM model to construct the training sequence from training image dataset. Particularly, the relationships between the image in the azimuth and feature vectors are used to generate the feature sequences and training sequences for hidden Markov model. Furthermore, the feature sequences and training sequences are extracted from feature vectors with similar target images in an azimuth. In the third step, targets are detected from testing SAR images by TSVM classifier based on the training sequence by exchanging the labels of pair of different unlabeled samples to solve an objective function. Experimental results demonstrate the effectiveness of the proposed algorithm

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090911131119 2014/09/26 - 06:01

Automatic target detection is of great importance in high-resolution synthetic aperture radar (SAR) images processing. In this paper, we proposed a hybrid HMM-TSVM model to detect targets in SAR images. Our proposed SAR image target detection system is made up of three steps. In this first step, the testing/training SAR images are pre-processed, and image visual features are extracted through 2DPCA, which is an improved version of principal component analysis. In the second step, we use the HMM model to construct the training sequence from training image dataset. Particularly, the relationships between the image in the azimuth and feature vectors are used to generate the feature sequences and training sequences for hidden Markov model. Furthermore, the feature sequences and training sequences are extracted from feature vectors with similar target images in an azimuth. In the third step, targets are detected from testing SAR images by TSVM classifier based on the training sequence by exchanging the labels of pair of different unlabeled samples to solve an objective function. Experimental results demonstrate the effectiveness of the proposed algorithm

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090911131119 2014/09/26 - 06:01

The paper mainly studies the problem of the forming of group emotion. A new emotion model of crowd based on emotional contagion is proposed. Based on the model, the primary factors of group emotion formation, which are the network structures of interpersonal relationship and the level of emotional dependence between individuals, are analyzed. The evolution process of crowd emotion is simulated under four types of complex network. The simulation results show that the network structure of interpersonal relationship affects the convergence time of group emotion, for example, it takes more time to convergent individuals’ emotions in the regular network than in the other three networks. Not only does the level of emotional dependence on individuals have the significant influence on the intensity of group emotion, but on the formation time of group emotion as well. This study shows that the dynamics of group emotion varies due to the level of emotional dependence and the distinct social network structure of interpersonal relationship.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090911201127 2014/09/26 - 06:01

The paper mainly studies the problem of the forming of group emotion. A new emotion model of crowd based on emotional contagion is proposed. Based on the model, the primary factors of group emotion formation, which are the network structures of interpersonal relationship and the level of emotional dependence between individuals, are analyzed. The evolution process of crowd emotion is simulated under four types of complex network. The simulation results show that the network structure of interpersonal relationship affects the convergence time of group emotion, for example, it takes more time to convergent individuals’ emotions in the regular network than in the other three networks. Not only does the level of emotional dependence on individuals have the significant influence on the intensity of group emotion, but on the formation time of group emotion as well. This study shows that the dynamics of group emotion varies due to the level of emotional dependence and the distinct social network structure of interpersonal relationship.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090911201127 2014/09/26 - 06:01

High resolution remote-sensing images provide abundant color, shape structure and texture information. However, region-based segmentations do not allow to fully exploit the richness of this kind of images. Despite the enormous progress in the analysis of remote sensing imagery over the past three decades, there is a lack of guidance on how to select an image segmentation algorithm suitable for the image type and size. In accordance with the characteristics of color high-resolution remote sensing images, we put forward an improved region filter remote-sensing color-image segmentation algorithm based on traditional JSEG segmentation. In order to well describe the color homogeneity in region, the local homogeneity matrix can be adopted to correct the local value in traditional JSEG segmentation algorithm so as to accurately reflect the boundary region and enhance the accuracy of image segmentation. Simulation experiment results demonstrate that our proposed algorithm can efficiently overcome the inaccurate segmentation of boundary region. In addition, compared with the traditional filter algorithm, our proposed algorithm can extract weak edge more accurately so as to achieve the better segmentation result in high resolution remote-sensing image segmentation

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090911281134 2014/09/26 - 06:01

High resolution remote-sensing images provide abundant color, shape structure and texture information. However, region-based segmentations do not allow to fully exploit the richness of this kind of images. Despite the enormous progress in the analysis of remote sensing imagery over the past three decades, there is a lack of guidance on how to select an image segmentation algorithm suitable for the image type and size. In accordance with the characteristics of color high-resolution remote sensing images, we put forward an improved region filter remote-sensing color-image segmentation algorithm based on traditional JSEG segmentation. In order to well describe the color homogeneity in region, the local homogeneity matrix can be adopted to correct the local value in traditional JSEG segmentation algorithm so as to accurately reflect the boundary region and enhance the accuracy of image segmentation. Simulation experiment results demonstrate that our proposed algorithm can efficiently overcome the inaccurate segmentation of boundary region. In addition, compared with the traditional filter algorithm, our proposed algorithm can extract weak edge more accurately so as to achieve the better segmentation result in high resolution remote-sensing image segmentation

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090911281134 2014/09/26 - 06:01

As different frame lost will lead to different distortion for stereoscopic video sequence, we take into account the temporal and spatial correlation of stereo video, error diffusion characteristics left and of right view frame, as well as recursion theory. Based on the above, we put forward a frame important distinction model of stereoscopic video based on content. The experimental results show that the model can be applied for stereoscopic video sequences with different motion intensity and disparity, accordingly, code ends can accurately estimate the importance of each frame for terminal perception. Finally, the applicability of the model is discussed

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm0908985991 2014/08/23 - 21:55

With the rapid development of computer network and information technology, traditional clothing industry has taken a giant stride forward to computer information and digitization. In this paper, 250 3D point-cloud photos of young females were selected as subjects, and related characteristic points of neck rhizosphere (including front neck point, side neck point and back neck point) were determined. Then the height size, width size, thickness size and girth size of characteristic points were measured by the software named Imageware 12.1. At last, with software called Excel and SPSS, the height rules of characteristic points were analyzed, front and back neck rhizosphere were obtained by width and thickness sizes of characteristic points. The research in this paper has laid the foundation for building female neck rhizosphere line of virtual mannequin which provides datum line and basic sizes for 3D collar patterns

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm0908992997 2014/08/23 - 21:55

Paper similarity detection depends on grammatical and semantic analysis, word segmentation, similarity detection, document summarization and other technologies, involving multiple disciplines. However, there are some problems in the existing main detection models, such as incomplete segmentation preprocessing specification, impact of the semantic orders on detection, near-synonym evaluation, difficulties in paper backtrack and etc. Therefore, this paper presents a two-step segmentation model of special identifier and Sharpley value specific to above problems, which can improve segmentation accuracy. In the aspect of similarity comparison, a distance matrix model with row-column order penalty factor is proposed, which recognizes new words through search engine exponent. This model integrates the characteristics of vector detection, hamming distance and the longest common substring and carries out detection specific to near-synonyms, word deletion and changes in word order by redefining distance matrix and adding ordinal measures, making sentence similarity detection in terms of semantics and backbone word segmentation more effective. Compared with the traditional paper similarity retrieval, the present method has advantages in accuracy of word segmentation, low computation, reliability and high efficiency, which is of great academic significance in word segmentation, similarity detection and document summarization.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm09089981004 2014/08/23 - 21:55

This paper describes a novel agglutinative language modeling strategy for Uyghur with graphic language model as structure. In graphic modeling language model, sentences are organized by morphemes as a directed graph, which is different from the linear structure in n-gram language models. The graphic language model is verified in two typical natural language processing application scenarios, morphological analysis and machine translation. The experiments show that the graphic language model achieves significant improvement in both morphological analysis and machine translation.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090810051010 2014/08/23 - 21:55

This paper concentrates on how to mine useful information from massive XML documents in cloud computing environment. The structure of the Cloud computing and the corresponding tree data model of a XML document are analyzed in advance. Afterwards, structure of the proposed XML data mining system is illustrated, which is made up of three layers, such as “Application layer”, “Data processing layer”, and “XML Data converting layer”. In the XML Data converting layer, XML data are collected from databases and documents, and then the source data can be converted to XML file effectively. In the data processing layer, the process of data selection, cleaning and standardization for XML data set is implemented, moreover, a XML data set with higher degree of structure and rich semantics are obtained. In the application layer, “the results report module”, “data query module” and “results analysis module” are included. Next, massive XML data mining algorithm is proposed. The main innovations of this algorithm lie in that 1) the structure of a XML document is represented as an unordered tree, 2) the sub-structures of a XML document are modeled as sub-trees, and XML trees are regarded as a forest which is made up of all the sub-trees. Experimental results show that the proposed method can effectively mine useful information from massive XML documents in cloud computing environment with high efficiency.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090810111016 2014/08/23 - 21:55

With the development of information technology, face recognition technology has been continuously developed. This technology has attracted the attention of many researchers, including institutions and production enterprises. Face recognition technology has become a relatively independent application technology area in various social services. This paper presents a face recognition algorithm based on wavelet transform and regional directional weighted local binary pattern. First of all, this algorithm puts forward a new basis for a face recognition, namely the level of detailed components of face images containing valid facial texture details, and the recognition rate is better than that of the vertical component information and diagonal component information. This is called Horizontal Component Prior Principle(HCPP). According to HCPP, the original image is decomposed with wavelet transformation. The algorithm extracts the scale and level of detailed components. To improve the original LBP operator, it presents the regional directional weighted local binary pattern (RDW-LBP). Using the RDW-LBP, it can calculate the histogram of scale components and detailed components decomposed by wavelet. The histogram feature vector of face image can be got with the different weighted sub-regions. The feature vector can be matched with Chi-Square distance. This approach further enhances the ability to extract face direction information effectively

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090810171023 2014/08/23 - 21:55

Contraposing to the features of image data with high sparsity of and the problems on determination of clustering numbers, we try to put forward an color image segmentation algorithm, combined with semi-supervised machine learning technology and spectral graph theory. By the research of related theories and methods of spectral clustering algorithms, we introduce information entropy conception to design a method which can automatically optimize the scale parameter value. So it avoids the unstability in clustering result of the scale parameter input manually. In addition, we try to excavate available priori information existing in large number of non-generic data and apply semi-supervised algorithm to improve the clustering performance for rare class. We also use added tag data to compute similar matrix and perform clustering through FKCM algorithms. By the simulation of standard dataset and image segmentation, the experiments demonstrate our algorithm has overcome the defects of traditional spectral clustering methods, which are sensitive to outliers and easy to fall into local optimum, and also poor in the convergence rate

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090810241031 2014/08/23 - 21:55

As the salient objects extraction is of great importance in computer vision and multimedia information retrieval, this paper concentrates on the problem of salient object recognition using local features. Considering the rotational invariance performance of circular region is much better, we exploit a circular region to replace the rectangular region. To implement the salient object detection, the visual object classes should be constructed from training image dataset through SIFT features clustering. Furthermore, for a test image, the object class which the test image belonged to can be detected by interest points matching. Afterwards, the SIFT features clustering and local features matching process can be implemented through the proposed hybrid SVM-QPSO model. To promote the quality of parameter selection in SVM, we utilize the quantum behaved particle swarm optimization technique to select suitable SVM parameters. Finally, experiments are conducted to make performance evaluation using the MSRC dataset. Experimental results show that compared with other methods, the proposed algorithm can effectively detect salient objects in both object detecting precision and computing efficiency.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090810321039 2014/08/23 - 21:55

Based on natural ventilation design scheme for main transformer room of an indoor substation, different air distribution schemes were obtained by changing height and size of air inlets and outlets. Three-dimensional simulation of air distribution was conducted for the transformer room by using Computational Fluid Dynamics (CFD) method. Ventilation & cooling effect of different indoor ventilation schemes were simulated with software FLUENT. By analyzing velocity fields and temperature fields, influences of different design parameters on safety and reliability of main transformer room of indoor substation were compared and analyzed in details. Additionally, characteristics and change rules of air distribution with different parameter variations were concluded. Considerations of ventilation organization design for main transformer room of indoor substation and recommendation for better air distribution schemes were provided. The research results also offered some guidance for design and renovation of ventilation & cooling projects of transformer room

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090810401047 2014/08/23 - 21:55

Motivated by a wide range of real world applications of hand writing digital recognition, e.g., postal code recognition, the past decades have seen its great progress. The related approaches are generally composed of two components, feature extraction and identification methods. We note that the previous approaches are limited by the following two aspects: (1) the feature is not adaptive enough to cover the great variance within data; (2) the recognition methods are suffered from local minima solution. Inspired by these observations and to overcome these limitations, we in this paper propose an approach HMM-MLR by exploiting hidden Markov model (HMM) and modified logistic regression (MLR). In the proposed approach, HMM is employed to model the trace of handwriting digital, which is able to model the large variance within digitals and can adapt to the data distribution. Then the features are extracted based on HMM and then delivered into MLR for recognition. Benefitting from the global optimum solution of MLR, the proposed approach could reach highly stable results. To verify the effectiveness of the proposed approach, we experimentally compare our proposed approach with other state-of-the-art approaches over Semeion handwritten digit dataset. The experimental results show that, over both recognition accuracy and recall, for different rounds of experiments and different number of training samples, our HMM-MLR exhibits significant improvement over others

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090810481053 2014/08/23 - 21:55

This letter presents a new filtering scheme based on local similarity pattern within the local window for removing random valued impulse noise. A pixel to be considered as an original pixel, it should have ample numbers of similar neighboring pixels in a local window. The neighbors are divided into 2 subtypes: smooth similar neighbors and edge similar neighbors according to the different criterion. Extensive simulations show that the proposed filter provides better performance than many of the existing filters. In particular, the thresholds are adaptive to diverse image types at different noise rate and the computational complexity is very low

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090810541059 2014/08/23 - 21:55

To investigate the rules of a user’s attention allocation and attention shift when they are using a display control terminal, using both methods of information processing, situation awareness theory and eye-movement tracking technology were applied to analyze the influence of different interface element layouts on attention allocation and attention shift. In this study, 26 participants performed an operating task under different display control interfaces, which were divided into two types and used to simulate different situation awareness levels, and the fixation point distribution was recorded as the evaluation index. The participants were asked to perform a daily washing task and a fixed task on the simulation interface of a cylinder washing machine. The experimental results revealed that different situations and different situational awareness levels of the participants influenced the rule of attention allocation and transfer; the information elements on the interface play a key role in the user's cognitive process. The experimental results and users’ subjectivities were generally in agreement; thus, the present study could provide ergonomic evidence with display and control terminal interface design

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm090810601067 2014/08/23 - 21:55

Text similarity calculation is the basic work in the application of Chinese information processing. A high-quality text similarity calculation method must be accurate and efficient, that is, it can be able to compare texts from the level of text natural language meaning, and arrive at the similarity distinction similar to artificial reading based on a full understanding of the author or text source semantic. At the same time, it should also be an efficient algorithm to save the processing time in facing large amount of text information to be processed. Through the research of many domestic and foreign literature, analysis and further research on current situation of similarity calculation, this paper intended to present a new method to improve the performance of similarity calculation, namely a Chinese text similarity algorithm based on word-number difference, which combined the traditional based on statistics and the narrow semantic method that meant the combination of the statistical efficiency and semantic accuracy. Combining the advantages of statistics and semantic category also means the necessity to face and overcome disadvantages of the two kinds of methods. This paper attempted to take the difference in word-number as the breakthrough point, took advantage of the diversity of Chinese word-number, combining with the word frequency, number and meaning, in order to successfully extend the word similarity calculation to the text similarity calculation. Finally, introduced the self built small text set as test object, compared similarity calculation of different methods in the laboratory environment. It shows that the similarity calculation method based on difference in word-number performances better than the traditional methods based on statistical and semantic. Through artificial comparison of the test results of research on this topic in accuracy and speed of segmentation, provide a new approach for Chinese text similarity calculation

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm0907865872 2014/07/31 - 10:31

With the rapid development of the computer and multimedia technology, the video processing technique is applied to the field of sports in order to analyze the sport video. For sports video analysis, how to segment the sports video image has become an important research topic. Nowadays, the algorithms for video image segmentation mainly include neural network, K-means and so on. However, the accuracy and speed of these algorithms for moving objects segmentation are not satisfied, and easily influenced by the irregular movement of the object and illumination, etc. In view of this, this paper proposes an algorithm for object segmentation in sports video image sequence, based on the spectral clustering. This algorithm simultaneously considers the pixel level visual feature and the edge information of the neighboring pixels to make the calculation of similarity is more intuitive and not affected by factors such as image texture. When clustering the image feature, the proposed method: (1) preprocesses video image sequence and extracts the image feature. (2)Using weight function to build and calculate the similar matrix between pixels. (2) Extract feature vector. (3) Perform clustering using spectral clustering algorithm to segment the sports video image. The experimental results indicate that the method proposed in this paper has the advantages, such as lower complexity, high computational effectiveness, low computational amount, and so on. It can get better extraction effects on video image

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm0907873878 2014/07/31 - 10:31

With the large-scale construction and rapid development of underground engineering, a large number of underground engineering construction, such as tunnel and subway emerged. The geological structure of the tunnel is complex and the roc is fragmented. Tunnel seismic image is a new geophysical technique. This method has advantages such as high resolution, high reliability and obvious image characteristics. Therefore, to insure the safety of the construction and to eliminate geological disasters, the advanced prediction technology of seismic image in tunnel detection is applied. In the paper, the seismic image was used to detect the Huangzhuang tunnel geological condition. The reflected waves, the refraction wave and the surface waves can reflect the same geological conditions, and the result is in accordance with the drilling. Tunnel seismic image can effectively and safely guide the excavation of the tunnel section working surface in combination with reconstructed images and excavation technology.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm0907879886 2014/07/31 - 10:31

With the widespread use of mobile devices and fast development of wireless network, m-learning has become another hot topic except e-learning. Considering the less utilization of traditional learning resources and the poor-directed users, this paper puts forward an improved method of m-learning. Due to oceans of m-learning resources, this paper suggests an integration platform of information resources based on granular in order to improve learning efficiency. Meanwhile, personalized concept is introduced into the system. This paper studies personalized problems of hierarchical retrieval model and the methods of how to dynamically obtain users’ interest. According to the hierarchical features of website structure, the system can actively obtain users’ interest as well as output retrieval results based on different users’ backgrounds under the help of ant colony algorithm. This method is easy to realize and can effectively trace users’ short-term and long-term interest changes. It is suitable for the complicated and changeable network environment.

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm0907887894 2014/07/31 - 10:31

The traditional wireless sensor network localization algorithm can be divided into the positioning algorithm based on distance and has nothing to do with the distance algorithm, due to the positioning algorithm based on distance is not suitable for the application of low power consumption and low cost areas and distance has nothing to do with poor precision problems of algorithm, this paper proposes a node self-localization algorithm based on received signal strength. Based on node location database in the grid topology analysis of the known conditions, and from the Angle of practical evaluates the localization algorithm scalability and fault tolerance. Finally with the traditional wireless network positioning algorithm do the experiment comparisons. The experimental results show that the proposed algorithm is less than the traditional algorithm in the interference in the environment of high precision, low cost, less energy consumption

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm0907895901 2014/07/31 - 10:31

In order to design a reasonable pedestrian evacuation and exclude the security risks in large stadiums, this thesis proposes the research of security model of evacuation in stadiums combined with multi-agent and cellular automata. The research is based on cellular automata model and the process makes extended analysis to the cell’s behavior of autologous, and then it makes simulation experiments of the process of simulating the evacuation in large stadiums. Simulation results finally show that cell Agent combines the advantages of multi-agent and cellular automata, which fully considers the individual internal factors. Compared to traditional cell cellular automata, it is more close evacuation situation of the realistic major sports stadium, and it shortens the evacuation time and improves the safety

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm0907902909 2014/07/31 - 10:31

Recognition rate of mainstream fingerprint recognition algorithm is very low for occluded fingerprint image. In order to solve this problem, based on multi association matching features this thesis proposes the recognition algorithm (RA-MAMF). Firstly, image is pre-processing, the fingerprint image’s Gabor filter is enhanced, and bi-narized and thinning pretreated are involved; secondly, the image is divided into multi homogeneous subsets, in which statistical association features and the bifurcation points of each subset are respectively extracted; finally on the basis of fingerprint, images are to be recognized, they are compared and match with the subset. Complete and occluded fingerprints data sets are used to make tested; the recognition algorithm based on multi association matching features has achieved excellent recognition accuracy; the RA-MAMF algorithm does not significantly increase the operating time, and this method effectively solves the low accuracy of traditional identifying the Occluded fingerprint image

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm0907910917 2014/07/31 - 10:31

To investigate the allocation scheme of the multi-view distributed video coding (DVC), the corresponding improvements are proposed correspondingly for traditional multi-view DVC. Traditional multi-view DVC (Wyner-Ziv DVC) encodes for all areas of Wyner-Ziv frame indiscriminately based on Turbo or LDPC. In this kind of encoding process, with regard to violent motor area, decoder can’t decode violent motor area accurately and also send more solicited message to feedback channel, which lowers the code efficiency and decodes inaccurately for violent motor area, it causes a part of area distortion in the image. In this paper, a distributed video encryption algorithm is proposed which based on discrete cosine transform (DCT). The algorithm combines decision criteria of ROI to get violent motor area and non-violent motor area. For violent motor area, to extract low frequency coefficient of DCT as DCT-R algorithm to assist decoder end to decode, decoder utilizes low frequency coefficient of DCT which has already been decoded to carry on bi-directional movement evaluation. Simulation experiment tests and verifies the improved algorithm effectiveness of proposed multi-view DVC in this paper

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm0907918925 2014/07/31 - 10:31

Chip Multiprocessors (CMPs) are adopted by industry to deal with the speed limit of the single-processor. But memory access has become the bottleneck of the performance, especially in multimedia applications. In this paper, a set of management policies is proposed to improve the cache performance for a SoC platform of video application. By analyzing the behavior of Vedio Engine, the memory-friendly writeback and efficient prefetch policies are adopted. The experiment platform is simulated by System C with ARM Cotex-A9 processor model. Experimental study shows that the performance can be improved by the proposed mechanism in contrast to the general cache without Last Level Cache (LLC): up to 18.87% Hit Rate increased, 10.62% MM Latency and 46.43% CPU Read Latency decreased for VENC/16way/64bytes; up to 52.1% Hit Rate increased, 11.43% MM Latency and 47.48% CPU Read Latency decreased for VDEC/16way/64bytes, but with only 8.62% and 4.23% Bandwidth increased respectively

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm0907926933 2014/07/31 - 10:31

The technology of three-dimensional reconstruction based on visual sensor has become an important research aspect. Based on Newton iteration algorithm, the improved 3D normal distribution transformation algorithm” (NI-3DNDT) is put forward, aiming to fix the problem of discrete point cloud registration algorithm in poor astringency and being open to local optimum. The discrete 3d point cloud adopts one order and two order derivative of piecewise smooth functions on surface, divides the point cloud space into Cubic grids, and calculate corresponding value of the mean and covariance matrix. To downgrade algorithm complexity, the Gauss function approximation of the log likelihood function is introduced, the probability density function parameters of 3D normal distribution transformation algorithm is simplified, and the Hessian matrix and gradient vector is solved through translation, rotation relation and Jacobean matrix; to make sure algorithm is converged to one certain point after a small number of iterations, it proposes that Newton iterative algorithm step be improved by employing better line search. Finally, the algorithm is put on simulation experiment and compared with other ways, the result of which proves that the suggested algorithm is able to achieve better registration effect, and Improve accuracy and efficiency

http://ojs.academypublisher.com/index.php/jmm/article/view/jmm0907934940 2014/07/31 - 10:31