Earticle

A new tactic analysis of broadcast sports video is proposed based on player trajectory information. Tactic analysis of sports video aims to recognize and discover tactic modes and match strategies that teams and personal players used in the games. Based on players and ball trajectory. First presents an interactive relationship analysis of temporal and spatial algorithm based on time fragment slice. According to the speed and distance of trajectory shape and the distance measurement and each trajectory in time fragment, to use graphical model was constructed to express tactical video game sports event. Through the analysis of each component fragment of interaction trajectory, the offensive incidents of tactical mode carried out hierarchical recognition of coarse to fine in football game video. In the coarse recognition process, the interaction mode is divided into a coordinated attack and personal attack. In fine recognition further, the coordinated attack mode is divided into interception attack and no interception attack. The personal attack mode is divided into direct attack and the dribbling-attack.

In this paper, we proposed the context-awareness routing algorithm DDV (Dynamic Direction Vector)-hop algorithm at Mobile Ad-hoc Networks. Existing algorithm in MANET, it has a vulnerability that the dynamic network topology and the absence of network expandability of mobility of nodes. This proposed algorithm forms cluster formation using a range of direction and threshold of velocity by base-station, and we calculate exchange cluster head node probability using direction and velocity for maintaining cluster formation. DDV algorithm forms a cluster based on the cluster head node. As a result of simulation, our scheme could maintain the proper number of cluster and cluster members regardless of topology changes. In response to maintain cluster formation, we prove a continuous connection between nodes.

A novel multimodal approach of highlight ranking for sports video summaries in affective context was proposed based on player behavior information and audio keywords of sports game. The mid-level representation trajectory-action-audio is constructed for the video content by fusing the information of player trajectory, action and audio keywords. Based on trajectory-action-audio, the computational affective features are extracted to describe the objective process of highlight ranking of sports video summaries from user subjective perception. A kernel based nonlinear probabilistic ranking model construction method is proposed, which is robust for the noisy data and provided with good expansibility. In addition, a new subjective evaluation criterion is proposed to guide model construction and feature extraction with the assistance of forward search algorithm.

Pointing to the demand of large scale internet websites want to improve users’ loyalty and flows maintaining. A novel conception of analysis engine for massive user behavior is proposed in this paper, which combines static analysis with dynamic monitoring for user behavior. It apply some improved data mining model based on cloud computing to analysis Web log data and contextual information of the page acquired real-time. Meanwhile, using cloud database for efficient processing and storaging. The results show that this system could significantly improve the effect and efficiency of user behavior analysis.

Enormous growth of wireless applications makes the spectrum scarcity problem worse day by day. Moreover, traditional fixed spectrum assignment policy causes serious spectrum underutilization problem. However, Cognitive Radio that enables opportunity based spectrum access for unlicensed users has recently been recognized as a heartening solution for spectrum scarcity and underutilization problem. Medium access control protocol is the key enabler or coordinator for this opportunity based channel access. However, recent studies show that in distributed cognitive radio networks MAC protocol suffers from severe performance degradation due to common control channel selection (CCC) problem, the multichannel hidden terminal problem (MHTP). In this paper, we propose a MAC protocol that eliminates CCC selection problem. Here, unlicensed users use dedicated band owned by them as a common control channel. Every unlicensed user equipped with two transceivers. One is control radio that helps SU’s to get updated control information and other is data radio. This clearly cuts down the number of collisions with other secondary and primary users in data transmission phase. To obtain the accurate sensing result, we propose cooperative sensing for idle channel detection. In this paper, we develop an analytical model to analyze important performance metrics. Simulation results show the effectiveness of our system.

The use of smart mobile devices has grown considerably in recent years. A large variety of digital content has entered the market and, in particular, there has been rapid growth in sales of electronic books (e-books). Consequently, demand for more diverse digital content has increased greatly as has the demand, in particular, for smart digital content for educational purposes, including digital textbooks. This demand has been accelerated through the implementation of an educational environment termed ‘Smart Education’ in Korea. Digital content and digital textbooks can be displayed on smart devices using a content viewer application or an e-book reader. However, existing content viewers only support a limited range of features, most of which are platform-dependent. In addition, most content viewers do not support features that deliver analysis of big data. To address these shortcomings, here we propose a dynamic educational content viewer, which can implement big data analytics and supports multiple device platforms and a wide range of content types.

The characteristics of dynamic, heterogeneity and limited resources of peers result in the existence of selfish behavior in MP2P network, which affect the network performance. To improve the performance of MP2P, a trust management model for peer reputation is established based on multiple-fuzzy theory in this paper. Direct trust, indirect trust, residual energy and active degree of peers are used as the fundamental variables and their weights are determined by using fuzzy theory, and then the reputation of peers is calculated. Peers with high reputation are allowed to participate in the communication and peers with low reputation are not allowed. The experimental simulation results show that the model not only effectively improve the malicious peer detection rate and the query hit rate but also reduce the Cx of the network.

Discovery and subsequent effective retrieval of useful user generated content depends on proper meta-data annotation implemented on an object such as a title and Keywords. In this study, a simpler unsupervised non graph-based algorithm for extracting keywords is proposed. A novel key phrases chunking approach was adopted; this utilizes words sequences as they appear in the original document. The simple but effective Term frequency-inverse document frequency (tf-idf) weighting scheme was exploited to rank the novelty created key-phrases. Comparing to a similar algorithm that uses three metrics weighting scheme, the tf-idf yielded a precision of 89%.Thus, the application of tf-idf algorithm on YouTube’s metadata based keywords shows to be useful approach in its objectivity.

For the fact that telecom data size is extremely huge and the management is much complicated, the paper proposes subspace clustering algorithm based on multi-rule constraint, to mine business knowledge information in a more efficient and accurate manner. By relying on K-means clustering algorithm, the method improves selection and mutation operation of genetic algorithms and thus corrects inappropriate choice of K-means initial clustering centers. Meanwhile, with the use of variable weighting strategy, data classification sparseness in the clustering is overcome. A fast and useful mining method is enabled for massive data. Results show its better performance in terms of computing efficiency, accuracy and ability.

An Interactive Documentary is web and multimedia documentary with interactivity and user participatory that present non-linear narratives. These features come from that of new media including hypertext, remediation, modulation and interactivity which is combination of cinema and digital technologies. Focused features of new media and interactive documentary are presented and compared. Variant modes of interactive documentary compared to traditional documentary or media are presented. Interactive Documentary is a New media, mostly affected by user related interactions.

OCR is a complicated process, there are many factors that can influence the recognition rate. Early period people tried to optimize the classifier to obtain high recognition rate, but the premise is that there is only one character no matter print or handwritten. For the performance of classifier has been promoted a lot, recognition rate for single character is high enough for commercial use. With the development of the demand for handwritten text recognition, how to raise the recognition rate of OCR system becomes very important. Unlike OCR system for print which focus on classifier. The research of OCR system for handwritten text is mainly on character segmentation. Statistical analysis showed that the mistake made by missegment is more than the mistake made by classifier. This is decided by the feature of handwritten text. There are more randomness and the lines are not horizontal, besides that, handwritten Chinese characters are more like overlapped and the gaps between characters are smaller. So this is the difficulty of handwritten Chinese characters. In this paper, the mutil-step searching nonlinear line exaction algorithm the paper proposed is easy and the accuracy is high, which can tackle the some weaknesses of direct projection method and indirect projection.

The purpose of this paper is to attempt to discover ways by which a Culture Archetype Portal may be activated. Cultural archetypes are a service which has incurred huge costs over the past ten years with the aim of providing material for the cultural contents industry. As the result of a survey carried out for consumers as to the usefulness of cultural archetype contents, it turns out that there will be a huge demand in the future for such contents. But in actuality, culture archetype contents are not currently being actively used by creators. There are many reasons for this, but above all it's due to the fact that they can't easily find the information they're looking for via these contents. Because of this, in order to activate the service, firstly we need to add necessary metadata for each required field. Secondly, we must reorganize the navigational structure so that contents can be easily understood. And thirdly, we must guarantee the quality of the contents through close relationships with relevant specialist organizations.

Accuracy of designing and producing a micro-force measuring device is 0.1μN, through the device, the maximum supporting force of 5 living water spiders sample were measured, the maximum supporting force of living water striders is 24.8 times its weight. Water spider has large supporting force on water surface, super-hydrophobic structures of water spider legs play important role. designing and producing 5 water strider models, whose legs were made of aluminum wire with 0.45mm diameter, super-hydrophobic processing to surfaces of aluminum wire, its contact angle is 154.5°, experimentally measured that the maximum supporting force of 5 water spider models. Through mechanical analysis, established supporting force mathematical model of the water spider model on water surface, according to the model calculated the maximum supporting force of water spider model. Compare errors between measured values and calculated values of supporting forces, the ratio of the error value is less than 8.39%, verified the correctness the mathematical model of supporting force .

In the mobile ad-hoc network (MANET), mobile nodes can freely move to anywhere whenever they want to. As MANET is no communication infrastructure, the route maintenance for transmitting the data and the volume of being transmitted data are important issues. In this paper, we adopt the content caching scheme to reduce the consumption of network bandwidth and node’s battery power. The proposed caching scheme stores the data being delivered by a neighboring node located in 1 hop away from itself. This has resulted in the increases of the probability that a mobile node stores the data to be used in future request. In evaluation, we examined our proposed scheme in the view of the cache hit ratio as the function of the number of mobile nodes and 4 mobility models: random way point, random direction, boundless simulation area and Gaussian-Markov. From simulation results, we confirm that the proposed scheme offers better performance substantially.

We describe a fast multi-level layout for visualizing social networks, which can visualize social networks high quality and rapidly. There are two innovations in our fast multi-level layout. Firstly, we proposed a new graph multi-layered compression method based on random walk. The multi-layered compression process groups vertices to form “planet” systems and then abstract these “planet” systems as new vertices to define a new graph and is repeated until the graph size falls below some threshold. And we also proposed a new single level force-directed layout based on sampling. The multi-level layout process can be accelerated based on these two innovations. Finally, we have evaluated our layout on several well-known data sets. The experimental results show that our layout outperforms the state-of-the-art method.

The widely spread exergames advertise in providing health benefits through entertainment. However the effectiveness of those in essence is questionable. This paper aims to observe muscular strength amongst others, which if proven effective, or otherwise, it will set out to identify factors associated with it, and to design more effective exergames for muscular strength in the extent to which basic criteria and factors must be met and considered. Lastly, it aims to develop exergames based on the design considered.

In order to solve the two-sided matching problem based on uncertain score information, a new method is presented. Firstly, the description of the two-sided matching problem with uncertain scores is given. Secondly, the satisfaction degrees of each agent towards the agents on the other side are calculated. A multi-objective optimization model to maximize the satisfaction degrees of agents is set up. Considering the important degree of each agent in each side, the multi-objective optimization model is transformed into a bi-objective optimization model. Furthermore, the bi-objective optimization model is transformed into a single-objective model by using the linear weighted method. The matching alternative can be determined by solving the single-objective model. Lastly, an example is given to illustrate the validity of the proposed method.

It is the important that Support Vector Machine (SVM) is the powerful learning machines and has been applied to varying task with generally acceptable performance. The SVM success for classification tasks in one domain is affected by features that it represents the instance of specific class. The representative and discriminative features that they are given, SVM learning is going to provide better generalization and consequently that we are able to obtain good classifier. In this paper, we define the problem of feature choices for tasks of human detections and measure the performance of each feature. And also we consider HOG-family feature to study an effective feature selection method. Finally we proposed the multi-scale HOG as a NEW family member in this feature group. In addition we also combine SVM with Principal Component Analysis (PCA) to reduce dimension of features and enhance the evaluation speed while retaining most of discriminative feature vectors.

Enhanced Distributed Channel Access (EDCA) mechanism is used in WLAN to support QoS for various multimedia service flows. IEEE 802.11e EDCA introduces some new QoS parameters based on DCF. How to adjust these parameters is a significant problem. In the paper, we present a novel saturated throughput analysis of the IEEE 802.11e EDCA. This approach involves a novel analytical model that is an extension to previous works, which provide Markov chain analysis to IEEE 802.11e EDCA. Throughput analysis of our model is evaluated by comparison with NS2 simulations. We found the model is correct and suitable for both basic access and request-to-send/clear-to-send (RTS/CTS) access mechanisms.

The purpose of this paper is to analyze and to design knowledge management systems in the School of Information Systems at XYZ University, which will improve organization’s performance and deliver innovation to organization as well as provide solutions when it’s needed. Analytical method that used in this study consist of two methods namely data & information collection method and analysis & design information systems method. Data & information collection method was obtained based on literature review study, while analysis & design information systems method was obtained by using object based information systems with the unified processes. The conclusion from this research is knowledge management systems provide solutions to address the problem of managing knowledge in academic and operation area in the School of Information Systems, by designing web based information systems which can make the process of production and distribution knowledge more effective and more efficient.

In order to improve the global searching ability of differential evolution algorithm in solving complex optimization problem, an improved differential evolution (SMDE) algorithm based on the self-adaptive method and multi-population is proposed in this paper. In the proposed SMDE algorithm, the population is divided into multi-populations in order to keep the diversity, then the self-adaptive method is used to control the parameters of differential evolution algorithm in order to balance the local search and global search ability. Finally, several complex benchmark functions are selected to validate the efficiency of the SMDE algorithm. The experiment results show that the proposed SMDE algorithm is better at the global convergence ability and the searching precision.

An efficient single-image super-resolution based on the discrete wavelet transform is proposed. The low-resolution image to be enhanced is assumed to be the low-frequency subband of the high-resolution image to be reconstructed. A support vector machine that synthesizes the high-frequency subband based on the inter-subband correlation of the directional edges is designed. Subband coefficients are classified into one of homogeneous region, edge region, and textured region. The support vector machine is adaptively trained for each region. Experimental results of sample images show that the proposed system offers improvements in terms of both measured distortion and subjective appearance.

As a crucial step in the process of teaching and training, examination, especially oral examination, is characterized with such defects as excessive subjectivity, difficult organization, low efficiency and heavy pressure. Thus, network technology and computer technology are employed to further promote the informationization of traditional oral examination. Through analyzing the existing problems of traditional oral examination and the feasibility of oral examination under network environment, this paper puts forward a universal framework and management model for oral examination under network environment and designed an oral examination system based on digital voice technology, artificial intelligence and software engineering. The research findings have been applied to mandarin Chinese test. So far Over 10 organization users have adopted the system and more than 300,000 examinees have been tested. Viewed from the practice, expected effects have been achieved.

Under today’s big data environment, with the rapid development of computer network technology and information technology, data mining is becoming more and more important in computer science. Classification is one of the most important aspects in data mining research Field. Recently, representation methods, such as sparse representation and low rank representation, have been much concerned. They both have wide applications in scientific and engineering fields. However, sparse representation and low rank representation include many methods, although these methods have their own characteristics, they are all effective for handling classification problems. This paper focuses on the performance comparison of different representation methods currently used in handling classification problems and views other conventional methods that can be applied in this field.

Recently, play learning becomes important and is emphasized as a useful tool. Thus, interest in edutainment contents is growing. Digitalstorytelling is considered first as a method that improves the transmission of information and draws a learner’s interest when planning edutainment contents. In this study, we designed and implemented edutainment contents in the form of an adventure game that applies a digital storytelling method on both smart device and PC. The edutainment contents also provide questions and items to be constituted dynamically and the adaptive learning contents through analysis of the evaluation results. It allows learners to solve various questions through an effective iterative learning. We analyzed our edutainment contents implemented. As a result, we showed that the learners can reach a mastery learning on computer operating principle using our adaptive edutainment system.

The interoperation of various applications will need a representation that goes beyond the traditional geometry-based one, which is inadequate for capturing semantic information. This paper proposes an approach to annotate the CAD models based on ontology with the aim of making the design intent understood by computer and applied in engineering analysis, such as FEA. The paper presents the design domain ontology and FEA domain ontology, and applies feature technologies and the semantic Web to complete annotation. Semantic markup can embed the engineering semantic information such as product function, and design principle into the CAD geometry data through annotating, it makes the analyzers reuse design ideas quickly and conveniently to increase efficiency. The semantic file is proposed to support an exchange of product data semantics between CAD and CAE. The main idea of the approach is presented and key technologies are elaborated, including the creation of the FEA solution template, and the matching algorithm between semantic markup file and FEA template file. Finally, the feasibility and effectiveness of the approach is empirically validated by a case study.

Audio identification technologies are becoming of increasing interest for copyright protection and digital forensic. In this paper, we propose an audio fragment identification system for efficient audio identifying applications in practice. To identify an audio file fragment, we have to decode it according to its format. Thus, we precede format classification of audio fragment using Support Vector Machine in advance. After identify the format, fragment recovery is implemented by adding a maximum similar frame header in front of the fragment. Then we extract a chroma feature from the decoded audio data to achieve audio identification. The experimental results show the evaluations of the format classification, fragment recovery and audio identification.

T As development of computer network technology and multimedia technology accelerates the education reform, a new kind of education system ---multimedia teaching, which injects new technology into traditional teaching, has come into being. Consequently, traditional English teaching with injection of multimedia technology is reformed to a large extent. Evaluation of the multimedia English teaching system is used as a criterion to examine whether the teaching system is perfect or not and is of great importance to the integration of multimedia. This paper studies the multimedia English teaching system and concludes one first class index and five second class indexes and twenty one third class indexes by using the multilevel analysis method. It also assesses thirty teaching systems by using grey analysis method and Matlab software and classifies the results by the degree of grey. This paper aims to provide a theoretical basis to the algorithm of the multimedia English teaching system by studying its assessment theory and provide a rational analytical method for the teaching system to serve students more efficiently.

CRInSAR is a newly developed technique to monitor ground deformation. In CRInSAR algorithm, the identification of Corner Reflectors in SAR images is necessary. Due to the uncertainty of traditional identification method, a new method based on the intensity and correlation coefficient of each CR candidates in SAR images is presented. The method has been successfully used to determine the locations of 11 CRs installed along a highway in six SAR images over the study area. The results show that the identification accuracy of the new method is about 1 pixel. It is effective and reliable especially in the area with lots of lightspots around the CR points. The method proposed can play important role in the highway deformation monitoring within CRInSAR algorithm.