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This study aims to develop lesson plans using mixed reality contents in VR experiencing classroom. For the purpose of this study, we analyzed 10 mixed reality contents, VR experiencing classroom environment, and curriculum in C smart model school in KOREA. Moreover, we derived three teaching-learning models and applied them to experience learning activity design using mixed reality contents. Three models included role play model, group investigation model, and task based language teaching model. As the result of this study, we developed specific lesson plans based on three models. For further study, it is needed to apply experience learning activities to elementary class, and to evaluate the effectiveness of these lessons.

Despite the recent massive popularity of smartphones and their impact on our lifestyles, only few objective studies have been conducted on smartphone usage patterns. In this paper, using a comprehensive smartphone usage logging system (a client app and a server), various statistical analysis results from more than 800 man-days usage logs are presented. The anal-ysis shows 1) significant difference in usage frequency and time statistics among the applica-tions, 2) different application category preferences between addicts and non-addicts, and 3) little usage variation between weekdays and weekends, but higher usage in night time for addicts.

In the word of service-oriented architecture and collaboration, it is important to deal with sub-services of cooperating components. In existing research, functions to meet and behavior predictability are two major aspects of Web services composition, but there are some limitations to treatment of behavioral constraints. In this paper, we model a component by an open Petri net, and investigate action patterns as a means to descript and analysis of behavior constraint under the condition that subnets composition are satisfied. This approach can effectively describe the constraint of behaviors, achieve behavior interaction between services and model a component that meets specific behavioral relations. Finally, the theoretical analysis and simulation results show the effectiveness of the method.

A colored overlay has been used as an assistive device for people with visual stress. Recently, a kind of mobile colored overlays has been developed; however, it can’t be applied to all contents of its environment. In this paper, I implemented a mobile overlay application based on the Android operating system and it can be applied to not only all contents in the system but also external contents such as book using camera mode. To achieve this, I measured film overlay colors at transmit mode and reflect mode by using spectrum colorimeter and estimated and implemented color information to apply to virtual overlays. Chromaticity measured in reflect mode was heavier than the one measured in transmit mode. I found I needed to use chromaticity measured in reflect mode in order to keep the film’s overlay effect in virtual colored overlay, which was applied to printed paper. The test results showed that it had the same effect as when existing film overlay was used on white paper, with the exception of color effect on the white screen of mobile devices.

With the rapid expansion of information resources, the amount of image data in the network shows an explosive growth trend. The traditional search engines have not considered users’ different interests; therefore image retrieval efficiency is reduced. To solve the problem, this paper puts forward a research on user-based personalized image retrieval technologies. Firstly, this paper studies the user interest model, and provides its definitions and application strategies; secondly, it studies collaborative filtering algorithm based on K-means clustering, and solves the problem of sparse resources effectively; Finally, explicit tracking, implicit tracking and relevance feedback methods are adopted to learn and update user interest model constantly to meet the users’ needs and improve retrieval accuracy and efficiency. Based on the above studies, this paper presents a kind of user-based personalized recommendation technology, and completes an image retrieval system based on user personalization, proving that this recommendation technology is able to provide users with better personalized recommendation service.

In recent years, the modeling and verifying of Cyber-Physical System (CPS) is now an important aspect of CPS researches. Because of the CPS’ complex architecture, it may suffer from the state-space explosion problem when we verify CPS models by model checking methods. Therefore, we offer a method which models CPS with Component Services. The method treats the CPS components as a service provider, and models component services to further simplify the system’s state-space. We verify the correctness of this model and solve the synchronous/asynchronous communication problems.

High Performance Computer (also called "supercomputer") is a computer which can process the complex and large-scale operation in computational science. In general, High Performance Computer represents the top 500 computers which is based on the computer performance in the world. After the successful commercialization of CDC6600 which has the 9MFLOPS performance in 1964, TFLOPS and PFLOPS High Performance Computer have been developed. High Performance Computer is the public resource which can be developed and provided by government. For the efficient application of High Performance Computer, government has to support the related activities such as research, resource allocation, and professional manpower training. To build a basis of the development of High Performance Computing can improve the quality of life and develop the national economy. For this reason, Korean government preceded the establishment of law for national supercomputing promotion from 2009. As a result of this effort, Korean government enacted the 'National Supercomputing Promotion Act' in 2011. This study provides the domestic and international trend of High Performance Computer, and analyses the major contents of National Supercomputing Promotion Act. This effort will be helpful to propose the strategy in order to provide more efficient service as a momentum of national supercomputing center.

Machine learning is the core of artificial intelligence. It is a fundamental way to the computer intelligence. Support vector machine is one of the important methods in the field of machine learning. It has the advantages of global optimization and strong generalization ability. It has been successfully applied to face recognition, fault diagnosis, financial forecasting and other fields. In this paper, a novel SVR model is proposed to forecast GDP. In the model, The neighborhood rough set (NRS) is used to reduce the index set and the chaotic genetic algorithm (CGA) is adopted to parameters searching in SVR model. Then the novel model NRS-CGA-SVR is established to predict GDP of Anhui province. The results show that the proposed model is better than the other models presented in this paper on forecasting GDP.

Ordinal Pattern analysis has been used recently for extracting qualitative information from non-linear time series and it has been applied to usefully track brain dynamics. In this paper, we proposed a novel P300-based BCI system which depends on ordinal time series analysis as a feature extraction method. We have shown that this method can efficiently revel P300 feature, and therefore good classification accuracies and bitrates have been achieved for healthy and disabled subjects.

The PS algorithm divides the tags within the reader’s identification range into smaller groups by increasing the transmission power incrementally and identifies them. This algorithm uses the fixed frame size at every scan. Therefore, it has problems that the performance can be variously shown according to the number of tags, frame size, and power level increase. In this paper, we propose an EPS algorithm that allocates the optimal frame size by estimating the number of tags at each scan. The simulation results showed that the identification delay of EPS algorithm could be improved 70% compared with PS algorithm. It also provided a stable identification delay regardless of power level increase.

In this paper, a two-step approach for vehicles detection is proposed. The first step of approach is to approximate vehicles’ potential locations through searching for shadow area of vehicle low-part. In order to find these shadows, Haar-like feature with Adaboost was used to train a Haar detector offline and the relearning process with hard training samples is applied to increase detection rate. Based on the previous processing, ROI (Region of interest) + HOG + SVM algorithm is used for vehicle verification. At last, K-means approach is used to combine the similar detection results. The experimental results proved that our system could be used for real-time preceding vehicle detection robustly and accurately.

New learning method and the need for e-learning technology of the constructivist paradigm which consist the individual experience-centered learning experience, knowledge increased by escaping from the videos and flash-based simple one-side education contents.In this paper, the augmented reality English learning contents for the students to learn through the role and mission in the virtual space as the contents of new forms for the experiential learning through the augmented reality and TOLED(Transparent, Organic Light Emitting Diodes) system by using the vibrating Bluetooth maker cube for themulti maker configuration was designed and the system was designed to service it.

Online Social Networks (OSNs) accumulate a large amount of user-generated data and Social Recommender Systems (SRSs) can help users discover information they are interested. However, most of the existing SRSs do not have good scalabilities to process huge volumes of data. Aiming to this problem we design a social recommender system named SRSH, which is based on Hadoop parallel computing platform. SRSH provides second-degree friends, similar users, user community and content recommendation modules, which can meet user needs of finding potential friends and attractive content. Especially, every core methods existing in these modules above can be implemented using MapReduce parallel programming framework and run in Hadoop cluster. We have conducted extensive related experiments on the realistic dataset and the experimental results show that SRSH scales well and has the ability of dealing with the problem of recommendation in the large-scale OSN.

Cloud Computing is a paradigm to provide the services like Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). Virtualization technology plays an important role to provide these services. Due to lack of finance as well as requirement, data center providers are unable to establish data centers all over the world. To provide better Quality of Service (QoS) and maintain Service Level Agreement (SLA), data center providers collaborate with other data center which is named as a Federated Cloud. Load balancing process distributes the load or service request among the data centers by implementing distribution policies. Depending on the policies, the central manager chooses the location to deploy the virtual machine. This paper proposes the data center selection algorithm in a federated cloud to optimize the cost as well to improve the performance.

Human Computer Interaction (HCI) is a discipline dealing with the study, planning, and design of interactions between humans and computers. The prevalent use of digital devices is increasing the need for research and education on HCI. Paying a close attention to HCI is important as poorly designed user interfaces can lead to unexpected problems. This work is focused on a new education method geared towards reducing errors and exceptions while developing a program, incorporating role-changing brainstorming techniques during HCI design process. According to the proposed approach, two evaluation elements, including the ability to find errors and exceptions and the ability to present alternative solutions when faced with these errors, are considered. Through a role-changing brainstorming based design exploration, a low-fi prototype was developed to set up an assessment method incorporating quantitative and qualitative factors for a team-based HCI project.

As a common delivery model in cloud computing, SaaS applications are becoming increasingly popular. Multi-tenancy is a key characteristics of SaaS applications. Service composition plays a main role in SaaS applications because of frequent composability and reusability of software services. With the development of cloud computing, one side, there are an increasing number of available services, other side, tenant’ individual and diverse requirement become more intense, which makes service composition tend to be more complex. This paper proposes an effective infrastructure for service composition, MultiGranular, which provides a semantic basis for multi-tenant service composition. The MultiGranular supports the characteristic of hierarchy, uncertain correlation, inheritance and versioning, effectively responding to the requirements of complexity of service composition for cloud computing SaaS applications. The computing process of MultiGranular includes three steps: basic service clustering, correlation mining and hierarchy building. MultiGranular makes it possible to change disorder services into the hierarchy and ordered clustering services, and makes it easy to develop multi-tenant SaaS applications. The experimental results demonstrate that by utilizing the proposed method, complexity of multi-tenant service composition are solved and the efficiency of service composition has been improved greatly.

With the increasing number of vehicles equipped with GPS enabled wireless communication devices, locations and trajectories of vehicles can be collected every time. Finding similar trajectories in massive trajectory data can benefit emerging novel mobile applications, such as carpooling, friend recommendation and traffic analysis. This paper proposes a novel spatio-temporal based trajectory similarity evaluation method. In this method, the significance of each point on the query trajectory can be assigned according to personal preference. Speed factor is also considered in the evaluation approach. Furthermore, most of existing trajectory similarity evaluation methods hold the precondition that the compared trajectories should have the same space and time length. This is not a compulsive condition in our method.

We present an improved sketch-based image search framework through which users can search their target images from the images in database. Our basic approach is to search the database by comparing the user-created sketch with the graph extracted from the images in the database and estimating the similarity. The images of high similarities are suggested as the candidates that match the target image. To improve the accuracy of the matching process, we substitute the graph-based representation of images with vectorized coherent lines, which are known as one of the most precise schemes in extracting and describing important features in an image. By the experiments on 820 images of 32 categories, we prove that our scheme shows higher matching accuracy than the existing schemes.

This paper researched relationship between Power of adapter and total harmonic distortion of the open-type earphone. In the power of adapter, even harmonic component is extremeley less and only the odd harmonics component is found. When analysed THD of leaking sound open-type earphone far from 1m, as a result, even harmonic component was 2% and odd harmonic component was 35.5%. THD of the diaphragm was affected by THD of electric signal.

Current English-Chinese translation machine can’t understand the source sentence fully. The theory of hierarchical network of concepts is proposed for resolving the problem through methods including function, translator, effect, relation and state. English semantic feature plays an important role in analysis of sentence comprehension. In our study, we discuss the core structure of English semantic respectively and put forward the corresponding of source sentence compared with online machine translation machines .The experimental results can provide technical support for English -Chinese machine translation. Effect chain and judge is called generalized function effect chain, it is not only the basis of element concept classification, but also the foundation of sentence semantic classification.

Infectious video watermarking (IVW) is to embed the first watermark in encoder/decoder for the protection of video contents and to infect the watermark in different codecs whenever video contents are copied or edited. This paper presents an infectious reversible video watermarking for fast infection in the infectious watermarking model (IWM). Our method is designed by following main features. The first is that the watermark for the available period of video contents is combined with the control code for content-based video watermarking. This makes the video quality and strength be adaptively controlled in the infectious process. The second is the low complexity for fast infection. The third is to embed the infectious watermark as a unit of macro block (MB) for avoiding the delay time for extracting and recovering. Experiment results verified that the reversible watermark can be detected or recovered without loss in different codecs and the quality of recovered content has maintained in the same bit-rate.

In order to solve the problems of product innovation design, an innovation model is developed. the five layers innovation design model integrates the creative methods (cluster analysis, brainstorm, TRIZ, QFD and reliable testing) and the process management method (design for the six sigma). The model take the step as following: taking advantage of the S curve of TRIZ evolution theory and design study to indentify the lifecycle stage, using the cluster analysis to study the customers' requirements, using brainstorm to define the most important requirement and the possible solution, utilizing the TRIZ to further explore the creative solutions, utilizing reliable testing to verify the reliable of the final solutions. The five layers model is proved highly effective by the case of lighting design.

Smoke simulation is an interesting topic in simulation fluid dynamics and graphics area. Main research area is simulation Backdraft physical unity 4.2.1f4 version. The Unity 3D game engine 4.2 versions have been start support PhysX. From Game Smoking part using Fluvio 2.1.0 Multiphasic Simulation smoke effect, Smoke Coordinate based on FDS Simulation. When firefighters discover and search a building fire survivor pulling air into itself, they generally evacuate immediately, because this is a strong indication that a backdraft is imminent. Due to pressure differences, puffs of smoke are sometimes drawn back into the enclosed space from which they emanated, which is how the term backdraft originated. Backdrafts are very dangerous, often surprising even experienced firefighters. The most common tactic used by firefighters to defuse a potential backdraft is to ventilate a room from its highest point, allowing the heat and smoke to escape without igniting explosively. The paper main goal is focus on simulation naturally fire model of backdraft. Use the Simulation data in Unity 3D game Engine. After computing the coordinates and explosion of Unity 3D simple particle system of Fluvio 2.1.0 and PhysX discuss moving location boundary and physically effects, make them flow like simulation’s real world smoke fluid and physically support fire effect backdraft model.

Although mobile phones currently are taking Geographic Information Systems (GIS) out of the office and into the field, human-computer interaction (HCI) as a field is not yet theoretically equipped to match this reality. Consequently, human-GIS interface provided by mobile phones makes the growing influence on residents, they obtain related services through submit their request like search routes. However, the information offered by users is limited. To get more hidden information can make the command of users accurately; therefore, context-aware is advocated. In this article, we proposed a method which considering the existing context to concern users' ability and combining with the user feedback to provide a more effective way of human-GIS interface on mobile phones. Through a design case, we develop the methodological approach and illustrate how the model can be applied to analyze the context of users.

Safety navigation of vessels is always the most important issue in maritime field. Recently, according to increasing the use of electronic equipment onboard, the requests for safety related information services have been growing up. To support this, International Hydrographic Organization suggests the concept of common maritime data structure. Since 2010, S-100 standard and relative product specifications have been defined as a part of that concept, covering the electronic navigational chart data and safe navigation related data. In this paper, we introduce an empirical application of S-100 standard, applied to marine casualty information. We analyze marine casualty cases reported in Korea for recent four years, make XML documents with schema design and then implement an application to present the marine casualty information on google map.

As the development of the internet, there are increasingly online shoppers in the world engaging in e-commerce activities. As the biggest developing country, China has the highest online population growth rates in terms of online shopping. For companies to take full advantage of the potential offered by the Web, it is essential that their electronic commerce (e-commerce) websites be prepared and organized in highly usable manner. This paper is an attempt to investigate the main factors affecting the performance of the top 10 B2C e-commerce companied in retail market in China. GRA (Grey Relational Analysis) and Fisher’s exact test is applied to identify the main affecting factors of online performance of the selected e-commerce companied. The results could be the guideline for the e-commerce companies in terms of improving their online popularity. The managerial implications and suggestions for future research are also discussed.

In this paper, the works on time synchronization in wireless sensor networks are investigated step by step. In particular, the diffusion-based algorithms for global synchronization in large-scale distributed sensor network are intensively focused. We thus propose a fast-converged asynchronous diffusion synchronization scheme in order to improve the performance of the asynchronous averaging diffusion method, and then prove its convergence mathematically. The evaluation results and discussions for the proposed scheme are also presented with simulation study. We eventually show that the proposed scheme converges a little faster than the asynchronous averaging diffusion method.

The rapid development of computer network technology and electronic commerce bring a series of convenience to the people but also brings a lot of problems. At the same time, these new computer technologies have forced many enterprises to reconstruct their distribution channels by adding the electronic channel. In the real life, the conflict between the network channel and traditional channel is an important problem. Supply chain has formed a network in real life and cyber work. In this paper, we consider the problem of optimal decision of supply chain and discuss the pricing strategy of manufacturers in the Stackelberg leader follower strategy and the Bertrand strategy respectively. Finally, we analyze the equilibrium price and profit of two strategies. The result shows that a fixed pricing strategy for retailers and manufacturers is not always advantageous with the changing of product price of manufacturer. The first part is the research status and related problems. The second part is the establishment of the model and the analysis of and pricing strategy. The last part is the experimental analysis and conclusion.

Recently, people pay more and more attention to the healthy lifestyles. And there is an increasing demand for the green agricultural products in real life. With the rapid development of the computer network technology and the electronic commerce, the emergence of e-business provides a new idea to promote the service of agricultural products. A huge supply chain network is established by the new idea and the technology. More and more agricultural products firms establish the electronic sale channel and get great profits. Firstly, we analyze the status of the agricultural products logistics distribution in both traditional sale channel and electronic sale channel in this paper. Then, we summarize the problems appeared in e- commerce channel. To solve these problems, we build an optimization model of the agricultural products distribution in e- commerce channel.

The worldwide trend of aging is highlighting the importance of the silver generation as a major consumer group for various industries. In particular, the necessity of mobile services for the silver generation in the IT industry is increasing. The purpose of this research is to develop a smart phone utilization plan by analyzing the needs of developing mobile services applying the characteristics of the silver generation on smart phones and by studying the smart phone acceptance factors.