• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3071-3080
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• 2015

The increased demand on the transport of both passengers and goods through rail systems implies higher traffic intensity and congestion on the railways, resulting in greater likelihood of accidents and also degraded passenger services. To cope with the issues, development of an integrated communication network for rails has attracted great deal of attention lately. GSM-R is such an example developed in Europe, which seems to have restrictions in providing various communication services due to network speed limit. For the reason, an LTE-based approach is under study in Korea. After the network development, operation management of the network is necessary. Design of operation management systems has been studied little and thus is the objective of this paper. To do so, a conceptual design has been carried out based on model-based approach. Specifically, a context model has first been created using the use case diagram. Then, SysML models of operational scenarios were developed for the management system. The SysML models have alternatively been expressed as EFFBD models to simulate and verify them. Consequently, the result of the conceptual system design for the operation management of the integrated wireless network is expected to be used as a basis for the detailed design later.

• The KIPS Transactions:PartD
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• v.18D no.4
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• pp.261-274
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• 2011

In recent competitive business environment each enterprise has to be agile and flexible. For these purposes run-time monitoring ofservices provided by an enterprise and early decision making through this becomes core competition of the enterprise. In addition, in order to process various innumerable events which are generated on enterprise systems techniques which make filtering of meaningful data are needed. However, the existing study related with this is nothing but discovering of service faults by monitoring depending upon API of BPEL engine or middleware, or is nothing but processing of simple events based on low-level events. Accordingly, there would be limitations to provide useful business information. In this paper, through situation detection an extended complex event model is presented, which is possible to provide more valuable and useful business information. Concretely, first of all an event processing architecture in an enterprise system is proposed, and event meta-model which is suitable to the proposed architecture is going to be defined. Based on the defined meta-model, It is presented that syntax and semantics of constructs in our event processing language including various and progressive event operators, complex event pattern, key, etc. In addition, an event context mechanism is proposed to analyze more delicate events. Finally, through application studies application possibility of this study would be shown and merits of this event model would be present through comparison with other event model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1809-1818
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• 2010

In order to detect the skin color area from input images, many prior researches have divided an image into the pixels having a skin color and the other pixels. In a still image or videos, it is very difficult to exactly extract the skin pixels because lighting condition and makeup generate a various variations of skin color. In this thesis, we propose a method that improves its performance using hierarchical merging of 3D skin color model and context informations for the images having various difficulties. We first make 3D color histogram distributions using skin color pixels from many YCbCr color images and then divide the color space into 3 layers including skin color region(Skin), non-skin color region(Non-skin), skin color candidate region (Skinness). When we segment the skin color region from an image, skin color pixel and non-skin color pixels are determined to skin region and non-skin region respectively. If a pixel is belong to Skinness color region, the pixels are divided into skin region or non-skin region according to the context information of its neighbors. Our proposed method can help to efficiently segment the skin color regions from images having many distorted skin colors and similar skin colors.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.986-998
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• 2006

There has been an increasing necessity of Semantic Web-based metadata that helps computers efficiently understand and manage an information increased with the growth of Internet. However, it seems inevitable to face some semantically ambiguous information when metadata is generated. Therefore, we need a solution to this problem. This paper proposes a new method for automated metadata generation with the help of a concept of class, in which some ambiguous words imbedded in information such as documents are semantically more related to others, by using probability model of consequent words. We considers ambiguities among defined concepts in ontology and uses the Hidden Markov Model to be aware of part of a named entity. First of all, we constrict a Markov Models a better understanding of the named entity of each class defined in ontology. Next, we generate the appropriate context from a text to understand the meaning of a semantically ambiguous word and solve the problem of ambiguities during generating metadata by searching the optimized the Markov Model corresponding to the sequence of words included in the context. We experiment with seven semantically ambiguous words that are extracted from computer science thesis. The experimental result demonstrates successful performance, the accuracy improved by about 18%, compared with SemTag, which has been known as an effective application for assigning a specific meaning to an ambiguous word based on its context.

• Journal of KIISE
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• v.44 no.2
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• pp.148-162
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• 2017

Recently, the accomplishment of a system's quality attributes requires the negotiation of increasingly complex requirements, and this is because the contextual and developmental environments in which software is used has undergone broad changes. Nevertheless, with regard to most architectural designs, many of the proportions depend on the architect's intuition. Moreover, even if reusable architectural patterns are adapted to an architectural design, common schemas for the description of their use are nonexistent, and it is difficult to make a comparison for the selection of an appropriate systemic pattern because the focus of the schemas is not the user's perspective. To achieve a fast initial-design decision, this paper suggests new schemas that reduce the distance between the quality attribute requirements and the design by reinterpreting architectural patterns from the user's perspective. Also, based on the reconstructed pattern model that is derived from the use of the new schemas, an architectural-pattern recommendation method (APOQATo) for which the trade-off and the constraints that are due to the design decision are considered is provided as well as the advantages of the architectural pattern for which the quality attributes are satisfied.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2167-2175
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• 2017

In recent years, an IoT is dramatically developing according to the enhancement of AI, the increase of connected devices, and the high-performance cloud systems. Huge data produced by many devices and sensors is expanding the scope of services, such as an intelligent diagnostics, a recommendation service, as well as a smart monitoring service. The studies of edge computing are limited as a role of small server system with high quality HW resources. However, there are specialized requirements in a smart factory domain needed edge computing. The edges are needed to pre-process containing tiny filtering, pre-formatting, as well as merging of group contexts and manage the regional rules. So, in this paper, we extract the features and requirements in a scope of efficiency and robustness. Our edge offers to decrease a network resource consumption and update rules and learning models. Moreover, we propose architecture of edge computing based on learning factors sharing with a cloud system in a smart factory.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.441-450
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• 2008

Recently, access control on form-based web information systems has become one of the useful methods for implementing client systems in a service-oriented architecture. In particular, XForms language is being adopted in many systems as a description language for XML-based user interfaces and server interactions. In this paper, we propose an efficient algorithm for the evaluation of XPath-based access rules for XForms pages. In this model, an XForms page is a sequence of queries and the client system performs user interface realization along with XPath rule evaluations. XPath rules have instance-dependent predicates, which for the most part are shared between rules. For the efficient evaluation of shared predicate expressions in access control rules, we proposed a predicate graph model that reuses the previously evaluated results for the same context node. This approach guarantees that each predicate expression is evaluated for the relevant xml node only once.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.12
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• pp.455-462
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• 2014

In recent years, various services in mobile environments due to the growth of mobile devices and related techniques like wireless networks. Furthermore, as the increasing communication traffic in cellular networks has become a new significant issue, many studies for device-to-device(D2D) communication and D2D-based cooperative services have been performed recently. In this paper, we design a smart agent system for D2D-based cooperative services and propose a dynamic service binding method based on service ontology. We classify roles of mobile devices for cooperative services by defining three types of smart agents, and construct a knowledge base in order to describe properties of 'service' unit. The proposed knowledge model, D2D cooperative service ontology, can enable a autonomous cooperative services between mobile devices by binding a requested service to the appropriate member device according to the real-time context in mobile environments.

• Design Convergence Study
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• v.15 no.1
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• pp.233-246
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• 2016

Mobile health industry has been combined with IT technology and is attracting attention. The health application has been developed to provide users a healthy life style. First of all, 5 mobile health applications were selected and reviewed in terms of their service trend. It turned out that none of those applications had any emotional data but physical one. Secondly, to extract users' emotion, technological researches were sorted into different categories. And the result implied that text-based emotion recognition technology is the most suitable for the mobile health service. To implement the service, the application was designed and developed the process of emotion recognition system based on the contents of the research. One-dimension emotion model, which is the standard of classifying emotional data and social network service, was set up as a source. In last, to suggest the usage of health application has been combined with persuasive technology. As a result, this paper prospered a overall service process, concrete service scheme and a guidelines containing 15 services in accordance with the five emotions and time. It is expected to become a direction for indicators considering a psychological individual context.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.2
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• pp.35-48
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• 2017

There are many and various devices like sensors, displays, smart phone, etc. in smart environment. And contents can be provided by using these devices. Vast amounts of contents are provided to users, but in most environments, there are no regard for user or some simple elements like location and time are regarded. So there's a limit to provide meaningful contents to users. In this paper, I suggest the contents recommendation system that can recommend contents to users by reasoning context of users, devices and contents. The contents recommendation system suggested in this paper recommend the contents by calculating the user preferences using the situation reasoned with the contextual data acquired from various devices and the user profile received from the user directly. To organize this process, the method on how to model ontology with domain knowledge and how to design and develop the contents recommendation system are discussed in this paper. And an application of the contents recommendation system in Centum City, Busan is introduced. Then, the evaluation methods how the contents recommendation system is evaluated are explained. The evaluation result shows that the mean absolute error is 0.8730, which shows the excellent performance of the proposed contents recommendation system.