• Journal of Advanced Navigation Technology
• /
• v.16 no.5
• /
• pp.864-870
• /
• 2012

Voice pattern recognition technology to solve the problems of the existing problems and common issues that you may have in language learning content analysis. This is the first problem of language-learning content, online learning posture. Game open another web page through the lesson, but the concentration of the students fell. Have not been able to determine the second issue according Speaking has made the learning process actually reads. Third got a problem with the mechanical process by a learning management system, as well by the teacher in the evaluation of students and students who are learning progress between the difference in the two. Finally, the biggest problem, while maintaining their existing content made to be able to solve the above problem. Speaking learning dedicated learning programs under this background, voice pattern recognition technology learning process for speech recognition and voice recognition capabilities for learning itself has been used in the recognition process the data of the learner's utterance as an audio file of the desired change to a transfer to a specific location of the server or SQL server may be easily inserted into any system or program, any and all applicable content that has already been created without damaging the entire component because the new features were available. Contributed to this paper, active participation in class more interactive teaching methods to change.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.05a
• /
• pp.666-668
• /
• 2013

Recently, the kind and number of malicious code, which operates in Operation System of smart devices, are rapidly increasing along with the fast supplement of smart devices. Especially, smart devices based on Android OS have high potential of danger to expose to malicious code as it has an easy access to system authority. When using intent, the global message system provided from Android, inter approach between applications is available, and possible to access to created data by the device. Intent provides convenience to application development in the aspect of reusability of component however, it could be appointed as a risk element in security-wise. Therefore, if intent is used in malicious purpose, it is easy to lead the condition where is weak on security. That is, it is possible to control as accessing to resources which application is carrying to operate by receiving intents as making smart device uncontrollable or consuming system resources. Especially, in case of system authority is achieved, the risks such as smart device control or personal information exposure become bigger when misusing broadcast intent through malicious code. This paper proposes a corresponding method of security vulnerability of Android intent that monitors the appearance of intent with intent pattern inspection, detects and blocks unidentified pattern intent.

• The KIPS Transactions:PartC
• /
• v.17C no.1
• /
• pp.89-98
• /
• 2010

In current digital broadcasting systems, GEM(Globally Executable MHP)-based middlewares such as MHP(Multimedia Home Platform), OCAP(OpenCable Application Platform), ACAP(Advanced Common Application Platform) are the norm. Despite much of the common characteristics shared, such as MPEG-2 and DSM-CC(Digital Storage Media-Command and Control) protocols, the information and data structures they need are slightly different, which results in incompatibility issues. In this paper, in line with an effort to develop an integrated DTV middleware, we propose a general-purpose, reconfigurable DSM-CC architecture for supporting various standard GEM-based middlewares without code modifications. First, we identify DSM-CC components that are common and thus can be shared by all GEM-based middlewares. Next, the system is provided with middleware-specific information and data structures in the form of XML. Since the XML information can be parsed dynamically at run time, it can be interchanged either statically or dynamically for a specific target middleware. As for the performance issues, the response time and usage frequency of DSM-CC module highly contribute to the performance of STB(Set-Top-Box). In this paper, we also propose an efficient application cache management strategy and evaluate its performance. The performance result has shown that the cache strategy reflecting user preferences greatly helps to reduce response time for executing application.

• Journal of Intelligence and Information Systems
• /
• v.16 no.4
• /
• pp.173-193
• /
• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component-based software development to promote application interaction and integration within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web services repositories not only be well-structured but also provide efficient tools for an environment supporting reusable software components for both service providers and consumers. As the potential of Web services for service-oriented computing is becoming widely recognized, the demand for an integrated framework that facilitates service discovery and publishing is concomitantly growing. In our research, we propose a framework that facilitates Web service discovery and publishing by combining clustering techniques and leveraging the semantics of the XML-based service specification in WSDL files. We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the Web service domain. We have developed a Web service discovery tool based on the proposed approach using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web services repositories. We believe that both service providers and consumers in a service-oriented computing environment can benefit from our Web service discovery approach.

• Journal of Intelligence and Information Systems
• /
• v.16 no.2
• /
• pp.33-54
• /
• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of public Web service repositories have been proposed, but the Web service taxonomy generation has not been satisfactorily addressed. Unfortunately, most existing Web service taxonomies are either too rudimentary to be useful or too hard to be maintained. In this paper, we propose a Web service taxonomy generation framework that combines an artificial neural network based clustering techniques with descriptive label generating and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service repositories. We report on some preliminary results demonstrating the efficacy of the proposed approach.

• The KIPS Transactions:PartC
• /
• v.13C no.4 s.107
• /
• pp.501-510
• /
• 2006

Software streaming allows the execution of stream-enabled software on desktop or portable computing devices like PC, PDA, laptop, cellular phone, etc., even while the transmission/streaming from the server may still be in progress. In this paper, we present an efficient streaming system called Software On-Demand(SOD) streaming system to transmit stream-enabled applications in addition to automatic installation of program registry, environment variables, configuration files, and related components. In particular, we design and implement a SOD system in Linux to provide the user with the instant look-and-click software execution environment such that software download and installation are internally proceeded in a completely user-transparent way. Therefore, the SOD system relieves the user from the tricky, failure-prone installation business. In addition, the software developer now obtains a new, powerful means to advertise and propagate their software products since the user can use software packages via user-friendly UI window or web browser by look-and-click interactive operation. In the paper, we also make a couple of SOD streaming experiments using a spectrum of popular softwares. Based on the analysis of the experiment results, we also propose two performance improvement schemes.

• The KIPS Transactions:PartD
• /
• v.15D no.2
• /
• pp.271-284
• /
• 2008

Self-healing is an approach to evaluating constraints defined in target system and to applying an appropriate strategy when violating he constrains. Today, the computing environment is very complex, so researches that endow a system with the self-healing's ability that recognizes problem arising in a target system are being an important issues. However, most of the existing researches are that self-healing developers need much effort and time to analyze and model constraints. Thus, this paper proposes an automated approach to determine problem arising in external and internal system environment. The approach proposes: 1) Specifying the target system through the models created in design phase of target system. 2) Automatically creating constraints for external and internal system environment, by using the specified contents. 3) Deriving a dependency model of a component based on the created internal state rule. 4) Translating the constraints and dependency model into code evaluating behaviors of the target system, and determinating problem level. 5) Monitoring an internal and external status of system based on the level of problem determination, and applying self-healing strategy when detecting abnormal state caused in the target system. Through these, we can reduce the efforts of self-healing developers to analyze target system, and heal rapidly not only abnormal behavior of target system regarding external and internal problem, but also failure such as system break down into normal state. To evaluate the proposed approach, through video conference system, we verify an effectiveness of our approach by comparing proposed approach's self-healing activities with those of the existing approach.

• Journal of vocational education research
• /
• v.35 no.6
• /
• pp.85-112
• /
• 2016

This study aims to identify the cooperative relations among researchers and their network structures based on the academic papers published in the field of lifelong vocational education and training from 2000 to 2015. Authors in three representative journals, 'Journal of Lifelong Education', 'Journal of Vocational Education Research', and 'Korea Research Institute for Vocational Education & Training,' during the periods, were selected and co-authorship network analysis was applied using NetMiner 4.0 in order to find the social relation among researchers and their academic influences. The results showed that the research productivity in the field of lifelong vocational education and training forms a shape of the power function where there exist components called, 'detailed research groups.' This network structure represents characteristics of a small world. In addition, the centrality analysis suggest authors with high centrality serve as co-authors who play as a central role on the network and exchange information with other researchers, while those with high betweenness centrality serve as a channel where they transfer knowledge and information among research groups. Increasing member of co-authorship has positively contributed to the opportunity and development of cooperative research among researchers in the field of lifelong vocational education and training. However it is recommended co-authorship be formed more heterogeneously instead of a few researches centrally dominate co-authorship. Various researchers should continually conduct research for good research performances.

• Journal of Korea Society of Industrial Information Systems
• /
• v.23 no.5
• /
• pp.119-134
• /
• 2018

Today, many firms face the environment of high uncertainty and severe competition due to the rapid technology development and the diverse needs of customers. In the business environment, one of the most important ways to gain sustainable competitive advantage and future growth engine is related to NPD (New Product Development), which is a very important issue for practice and academia. Thus, this study intends to provide new values to practitioners and researchers related to NPD by analyzing current research trends and future trends in NPD field. For this, we bibliometrically analyzed keyword networks which consist of keywords that were already published in the eminent journals from Scopus database to generate insights that have not been captured in the previous reviews on the topic. As a result, we could understand the extant research streams in NPD field, and suggest the changes of specific research topics based on the connected relationships among keywords over the time. In addition, we also foresaw the general future research trends in NPD field based on the keywords according to preferential attachment processes. Through this study, it was confirmed that NPD keyword network is a small world network that follows the distribution of power law and the growth of network is formed by link formation by keyword preferential attachment. In addition, through component analysis and centrality analysis, keywords such as Innovation, New product innovation, Risk management, Concurrent engineering, Research and development, and Product life cycle management are highly centralized in NPD keyword network. On the other hand, as a result of examining the change of preferential attachment of keywords over the time, we suggested the required new research direction including i) NPD collaboration with suppliers, ii) NPD considering market uncertainty, iii) NPD considering convergence with the other academic areas like technology management and knowledge management, iv) NPD from SME(Small and medium enterprises) perspective. The results of this study can be used to determine the research trends of NPD and the new research themes for interdisciplinary studies with other disciplines.

• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.101-123
• /
• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.