Earticle

In a wireless sensor networks, many topics have been studied in several filed. Most of them are concentrated on efficient use of energy to prolong the network lifetime. In a special environment like as remote battlefield, desert, forest, it is more difficult to recharging the battery of sensor. In this paper, we propose a density control method in a dense wireless sensor. We prolong the lifetime of network by selecting small set of active sensor nodes. Hop-based disjoint wakeup method is used and calculates the hop count with adjustment of communication radius. We analyzed the number of active sensor node and compared with other method with simulation.

Most of social network visualization methods have been only focusing on presentation of social network relationship. However, the methods do not consider an efficient processing speed and computational complexity for increasing at the ratio of arithmetical of a big data regarding social network. This paper proposes a cloud based on visualization method to visualize an inherence relationship of user on social network. The proposed method can intuitionally understand the user's social relationship since the method uses correlation matrix to represent a hierarchical relationship of user nodes of social network. It also can easily identify a key role relationship of users on social network. In addition, the method uses Hadoop based on cloud for distributed parallel processing of visualization algorithm, which it can expedite the big data of social network.

The paper conducted an in-depth research of urban distribution system’s resource integration process; It built the evaluation index system of this issue at the beginning. Later, it studied the normalization methods to these corresponding indicators. Then, it constructed the evaluation model of urban distribution system’s resource integration based on generalized regression neural network. At the end of this paper, it conducted a numerical experiment example and made certain conclusions. The innovation of this paper can be described as that the evaluation model constructed in this paper provides an effective and convenient way to evaluate the urban distribution system’s resource integration process.

Automatic classification of music genre is widely studied topic in music information retrieval (MIR) as it is an efficient method to structure and organize the large numbers of music files available on the Internet. Generally, the genre classification process of music has two main steps: feature extraction and classification. The first step obtains audio signal information, while the second one classifies the music into various genres according to extracted features. In this paper, we present a study on techniques for automatic music genre recognition and classification. We first describe machine learning based chord recognition methods, such as hidden Markov models, neural networks, dynamic Bayesian network and rule-based methods, and template matching methods. We then explain supervised, unsupervised and semi-supervised classification methods classifying music genres. Finally, we briefly describe the proposed method for automatic classification of music genres, which consists of three steps: chord labeling, genre matching and classification.

In this paper, an interaural time difference (ITD) estimation method is proposed for binaural speech separation in reverberant environments. First, the auditory signals are represented in the time-frequency (T-F) domain, and the ITD for each T-F bin is then estimated using generalized cross-correlation (GCC) with a maximum likelihood (ML) weighting function. In particular, the ML weighting function is designed to reduce the reverberation effect. Then, a mask is estimated by comparing the estimated ITD with the ITD corresponding to the location of the pre-defined target speech source. Finally, the target speech is separated by applying the mask to the auditory signals. It is shown that the proposed ITD estimation method outperforms a conventional cross-correlation-based ITD estimation method under reverberant conditions in terms of the signal-to-noise ratio (SNR) and signal-to-distortion ratio (SDR) of the separated speech signals.

In this paper, an improved BP neural network model is proposed. In the model, the momentum factor can improve the training speed and avoid falling into local minimum. Steepness factor and adaptive learning rate can improve the convergence speed. The genetic algorithm is used to solve the problem of low training speed, low accuracy of prediction and easy to fall into local minimum of BP neural network. Then the improved BP neural network model is established to predict GDP of Anhui province. The result shows that it is better than the other models which are presented in this paper on forecasting GDP of Anhui province.

This paper describes an upcoming technology, currently under development, based on packet-optical transport. We present an enhanced packet optical transport system (ePOTS) to cope with the CAPEX/OPEX issues of current networks, and explain the system’s major features, its potential services, and network deployment scenarios. Our results show that ePOTS can provide multimedia services efficiently and reduce the network cost by around one-third that of a multiprotocol label switching network.

ARINC 653 Specification defines a standardized interface of real-time operating systems and an Application Executive (APEX) to develop the reliable applications for avionics based on Integrated Modular Avionics (IMA). The requirements of system platform based on ARINC 653 Standard are defined as configuration data and are integrated to the XML configuration file(s) in the real-time operating system. Unfortunately, existing configuration tools for integrating requirements do not provide checking the syntax errors of XML and verifying the integrity of input data for partitioning. This paper presents a configuration tool for ARINC 653 OS that consist of Wizard module which generates the basic configuration data for IMA based on XML Scheme of ARINC 653 Standard, XML and Partition Editor for the partitioning system of IMA, and Verification module which checks the integrity of input data and XML syntax with its visualization.

Virtual Desktop Infrastructure (VDI) based on virtual computing laboratories (VCL) model has been implemented in a small or medium scale on cloud computing in universities. Conventional physical computing laboratories with thousands of PCs are still widely used and co-exist with the VCL, however, the conventional PCs are not fully utilized in VCL. The demand of VDI is growing but the numbers of VDIs are bounded by the capacities of host servers. To have scale-up VDI, system feasibility in terms of functionality and performance and scalability of virtual machines should be tested. We propose an extended model of VCL that can scale-up VDIs by running on an integrated virtual and physical lab environment. End-users can build their own workspaces on a host server and migrate to PCs in physical lab. The paper concludes with discussions on the benefits, problems, and performances of the extended model of the VCL.

In this work, we have developed a new bio-inspired neural network algorithms for block-based motion estimation. The main goal is to bridge the gap between algorithmic and biological vision by suggesting a bio-inspired motion estimation model based on neural network. We simplify the matching criterion for the block matching algorithm to reduce the hardware complexity and a number of input ports which maintaining the good quality. This paper implements the optimized algorithm in the reference model of H.264 compiled by VC6.0, and chooses six typical video sequences for simulation. The results show that our algorithm can reduce the average search points up to 82% to the full search black-matching algorithm. The optimized algorithm has reduced the motion estimation by 13.792% compared with UMHexagonS, and it gets better optimization to video testing sequences with low complexity.

Movement information on objects in videos can be used to characterize the content of a scene. This paper proposes a novel shape-based movement-searching algorithm that can effectively search human movements in video streams. Movement information is represented a sequence of boundary shapes of human subjects extracted from input video frames. Information on individual shapes in the sequence is converted into a 1D shape feature by using a shape descriptor. Human movements can be identified in a sequence of shape features extracted from the video, as in the case of searching for words in a long block of text. A comparison of the performance of the proposed algorithm with that of other methods shows that the proposed method can effectively describe human movement information and be useful for movement retrieval applications.

The use of computer has widely used as a tool to help student in learning, one of the computer application to help student in learning is in the form of Intelligent Tutoring System. Intelligent Tutoring System used to diagnose student knowledge state and provide adaptive assistance to student. However, diagnosing student knowledge level is a difficult task due to rife with uncertainty. Student Model is the key component in Intelligent Tutoring System to deal with uncertainty. Bayesian Network and Fuzzy Logic is the most widely used to develop student model. In this paper we will compare the accuracy of student model developed with Bayesian Network and Fuzzy Logic in predicting student knowledge level.

Engineering information in the shipbuilding and marine industry should be inevitably modified owing to frequent changes in, for example, customer's requirements and product specifications. Such a working environment caused by a discrepancy in information between engineering and production departments can have inefficient effects on production tasks. In order to perform efficient production tasks, staff in a production department should have easy access to the latest information in engineering. Furthermore, information should be easy and prompt in sharing and searching when needed. In this paper, we propose a development of collaborative system based on mobile framework. This proposed system facilitates its application to the work environment in the shipbuilding and marine industry. Moreover, it particularly saves resources in shipyards such as energy and costs of labor and materials. Mobile techniques, such as XML, SOAP and Android, which have been used in this paper are useful for implementing functions of sharing and searching for information in a distributed environment. The purpose of the system proposed in this paper is to provide system users with a collaborative environment which is based on an online and paperless mobile framework, when different kinds of tasks are required due to changes in engineering information. This proposed system not only can check information in production tasks in real time but also can implement functions based on mobile framework. By reducing the discrepancy in information between the engineering and production departments, this collaborative system can be implemented effectively.

In this paper, an improved Geometric Active Contour model is presented. This model introduced a window function to research the mean information of each pixel’s neighbor region, and constructed a novel signed pressure force function based on the entropy to drive the contour towers the boundary. In order to improve the efficiency and stability of the algorithm, this paper adopts two valued level set method to realize the segmentation process. The experimental results show that this method can obtain satisfied result even when the images have intensity inhomogeneity and weak edges.

This paper investigates the effect of color channel replacement with histogram equalization. The histogram equalization is broadly employed for contrast intensification in a diverse of consumer electronics applications for its straightforward function. The proposed work is consists of seven steps, original given image, channel separation: color image to three gray scale image, color channel replacement, HEM on individually separated image, histogram modification in each color channel, reconstruct color images, and image display. Simulation results with test images are provided to compare its PSNR and MSE performance.

For the predator-prey model, most conventional researches have focused on the food chain. In recent computer game and movies, simulation of natural phenomena has been increased. Realistic simulation is a key to the simulation of natural phenomena. It also comes in as an important role when simulating predator-prey chasing. Various factors must be put into consideration - such as physical condition, emotion of the predator, and the environment of the pursuit - when creating a realistic simulation of predator-prey chasing. It is not easy to simulate by reflecting all factors independently. Thus, this paper assumes that these independent variables are converted in terms of energy for the pursuit. It will simulate the situation of a predator chasing a prey using the “energy for the pursuit”. To do this, we proposed the consumed energy by using steering force based on Newton's law and the needed energy based on physics theory for a predator to move a distance as maximum velocity. A number of experiments were conducted in order to show the correctness of the proposed energies. Through experiments, this paper illustrates that the proposed energy models are well suited for natural pursuit.

With the development of the Internet of Things (IoT) and indoor positioning technologies, how to manage the rapidly increasing indoor moving object data is a research topic. The fundamental issue is to consider the representation of complicated indoor space as well as the moving object. In this paper, we aim to propose a complete indoor space model that can sup-port various indoor applications. The proposed model divides each indoor element into multi-granularity grids and introduces grids as indoor primitive geometry for the representation of connectivity between indoor elements and location of moving objects. The advantage of this approach is that it can simultaneously represent the connective relationship and geometric information of indoor elements, and give more accurate description of indoor distance and direction information. Several queries of indoor applications under the shopping mall scenar-io are employed to illustrate the completeness and robustness of our model.

Maritime wireless communication is different from terrestrial wireless communication, due to difference of environments. Nevertheless technologies based on WiMAX (IEEE 802.16j) for ship to ship maritime communication promised to deliver high data rates over large distances and deliver multimedia services and are expected to use e-Navigation system. This paper focuses to simulate on IEEE 802.16j for ship to ship maritime communication under various sea states. We describe BER level according to sea states under Rician fading channel model. BER patterns are designed using MATLAB.

Domestic hog raising industry has been continuously advancing both quantitatively and qualitatively along with economic advancement. However, the current circumstance is that system on domestic sow specification management is insufficient with severe individual differences, and the number of MSY remains to be low compared to that of advanced countries. To solve this issue, systematic specification management technology is needed to decrease the replacement rate of sow and improve the parturition and productivity. Through the proposed QR code based sow specification management system in this paper, it increased the weekly management cycle of sow and designed a system for systematic specification management of sow. When pregnancy succeeded through sow weekly management, 16 weeks of pregnancy period stored in database and current date are added to provide expected delivery date to user. When pregnancy failed, it is added with rut cycle 22 days to display expected date of rut. Through this, it can increase the number of MSY and provide convenience of user.

Today, as the developing of hardware of mobile is getting better, the performance index is much higher than the actual requirements of the software configuration. Phone's features more depend on software. As the Android operating system is getting more popular, the application based on Android SDK attracts much more attention. But now, some of the Android application interface is too cumbersome, pop-up ads is overmuch and the function is too single, these cause some inconvenience to the users. This article presents the application by eliminating the redundancy. Three kinds of applications are developed base on Java and Android SDK --- Weibo client, video player and audio player. The audio player uses the ContentResolver and Curor to obtain music files and plays the music by using the Service Components to call the Media Player class in the background. The video player uses the Media Player class provided by Android SDK. This class loads the file through URL, realize the multimedia file parsing by calling the OpenCore Library, which is at the bottom of Android, through JNI and by calling the SurfaceFlinger interface to realize the video files’ playback. The users’ data is collected through the Sina open platform called by Sina client and the data will be returned under the format of JSON by the Sina server. The system uses the OAuth authentication method for user authorization to complete the login process. The specific functions of this system are developed based on Android Weibo SDK. The interfaces of these Android apps are pretty and the operation is smooth. What’s more, the cumbersome interface and excessive advertising are eliminated, so that users are able to manipulate these apps more conveniently and smoothly.

Data races are the hardest defect to handle in multithreaded programs due to the non-deterministic interleaving of concurrent threads. It incurs the expensive costs of dynamic data race detection to monitor all of memory operations to shared memory locations. This paper presents a hierarchical filtering method that removes unnecessary monitoring memory operations from three levels of binary image, and evaluates empirically the effectiveness of the filtering method for dynamic data race detection. The empirical results using a set of benchmarks show that our filtering method reduces the average runtime overhead to over 50% of dynamic data race detection.

This paper makes research on the form of electronic learning products based on Ergonomics. The design idea of “people-oriented” is fully reflected through the design of electronic learning products on product semantics, modeling, touching texture and interactive interface, etc. And under the function principle of products in use, pleasantness is added to products on operating mode, physiology, psychology and product semantics, which makes electronic information products more pleasant, and reflects the development direction of electronic information products’ external form.

Recent embedded processors become to be multi-cored, due to the increased power consumption by higher operating frequencies. Multi-core processors stimulate applications to be parallelized. Since general purpose CPU has small number of core, which is optimized for serial processing, it has a limitation of parallel processing. To overcome this limitation, GPU is used for the parallel processing. In this paper, we implement GP-GPU of SIMT architecture for parallel processing in the embedded environment. The performance of the implemented GP-GPU is compared with the existing multi-core CPU of the embedded environment. The comparison results show the performance of parallel processing with the implemented GP-GPU is improved significantly.

This study proposes a new pallet recognition system using Kinect camera. Depth image of Kinect camera is produced from the infrared ray data of random dot type. This system was applied to an automated guided vehicle(AGV) to recognize the pallet in various conditions. A modularized hardware and software of the pallet recognition system was developed. The performance of the developed pallet recognition system was tested through experiments under various environment, and it show good performance.

This paper mainly analyzes the core contents of IA, which contain Organization System, Navigation System, Labeling System, and Search System. on the basis of former researches, the article puts forward a set of evaluation system with observation principles of second index for B-C e-commerce website IA, and endows different power to indexes with analytic hierarchy process, defines three different levels of IA, which are information dissemination, information- improvement and information exchange. According to those, choosing some sample websites to research on their level of IA, and acquires website IA situation in China. Additionally, it points out the strengths and weaknesses of China’s website IA, and gives suggestions to the three different levels of IA.

HTML5 is the next generation of web standards, and needs to be used to improve Web accessibility. To do this, Korea has taken various activities, such as laying down laws and standards related to web accessibility and investigating the realities of web accessibility. Recently, the market for web accessibility has been growing. This study compared the rates of building up HTML5, focusing on the top 100 most visited websites in Korea and abroad. Also, this study assessed the web accessibility of websites built in HTML5, and compared the web accessibility of Korea to those of foreign countries, verifying any efforts made to decrease any information gap. The results of this study show that Korea has built fewer HTML5 web sites than foreign countries. However, the web accessibility in Korea has steadily increased, and there is not much difference in web accessibility between Korea and foreign countries.

Video streaming has become one of the most essential ways in online communication. While video streaming is widely used in most of the Mobile Multimedia applications, it is not only necessarily required to maintain the high video quality but also minimized the video processing time to ensure the Quality of Service (QoS) as well as Quality of Experience (QoE) of the system in live broadcasting. This paper introduces the different way to evaluate the transmission errors in video applications by measuring the error with un-uniform distribution of information importance factor in pixels to achieve a suitable order in error correction. By changing the QoS evaluating method by considering Regions of Interest, especially fundamental rules in art study such Rule of Thirds, QoE should be improved to get closer to the viewer concerns and increase the system efficiency. Error detection as well as correction should be significantly corrected in priority orders.

Zigbee is a kind of wireless network susceptible to interferences. Network reliability is one of the key elements for the entire network. Zigbee networks have been widely used in many fields such as agriculture, medicine, traffic and environmental protection. The larger the net-work is, the more complex the environment of network will be, and the more problems will be caused. There are some typical problems, such as the network disconnection caused by inter-ferences, route errors in communication, the irrationality of network topology, data conges-tion appears in the central node of a mesh network. These problems are all caused by the instability of network topology eventually. This paper proposes a Zigbee network model used to large-scale networking. The network model maintains a relatively stable network topology, plans the data flow on network links reasonably, and offers protection for reliable network communication.

This paper proposes an interactive Web 3D based virtual educational system using O3D- WebGL. The proposed system is capable of providing flexible services without being confined to a specific platform. A virtual educational content was implemented with an educational goal of "saving the earth from global warming." The developed virtual educational content of global warming consists of two subjects: Amazon and Arctic. The effectiveness of the proposed virtual education system was verified based on implementation of user interaction. A storytelling approach was employed to maximize the interactive experience, and the 3D environment was implemented using O3D of WebGL to provide a user-oriented interface, as well as low-capacity, high-quality data services.

Along with internet broadcasting technology, cloud broadcasting is gradually becoming the development tendency to audience view. But the problems which existed in cloud environment also may affect in cloud based multimedia streaming service area. In this paper, we proposes an approach of risk management for multimedia streaming service in cloud computing. Through previous study, we recommended a leveraged BMIS model for cloud risk management. To apply this model into cloud broadcasting environment, considerate with the new feature required in multimedia streaming service, we found the significance of performance in cloud based streaming service. Then we integrate and leverage the new feature to the remodeled BMIS model, and finally develop a performance targeted leveraged BMIS model for cloud multimedia streaming risk management.