• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.683-690
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• 2004

MND(Ministry of National Defense) has developed .nm AF(Ministry of National Defense Architecture Framework) to guarantee interoperability among defense information systems. Users can easily and consistently develop architecture products through MND AF. There is necessity for development if CADM(Core Architecture Data Model), which facilitate exchange, integration, and comparison for architecture data, to store architecture data from architecture products and reuse them. We developed CADM from defining entities and relationships that satisfy data requirement of each architecture product from MND AF. After we developed architecture products about MIMS(Military Intelligence Management System), and inserted these architecture data to CADM repository. we verified CADM entities and relationships through query. Through CABM which provides common data model for the whole my architectures, interoperability and integration among defense information systems ran be improved, and integrated defense information resources efficiently can be managed.

• Journal of Society of Preventive Korean Medicine
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• v.6 no.2
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• pp.36-47
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• 2002

Over thousands of years oriental traditional medicine has developed a theoretical and practical approach to treat and prevent diseases and to promote people's health in China and Korea. In China, the integration of traditional Chinese medicine into the national healthcare system began in the late 1950s. This was in response to national planning needs to provide comprehensive healthcare services. On contrary to China, South Korea established the parallel operation of two independent medical systems in 1952. Hence there has been a political conflict between oriental and modern medicine over issues of fee, the ability to sell and prescribe herbal medicines, and the licensing of practitioners in traditional medicines. Given this background. This study is to compare peoples' attitudes and opinions for oriental traditional medicine by ethnicity (Chinese, Korean-Chinese and Korean). Chinese and Korean-Chinese were more used and satisfied with traditional medicine treatment and traditional practitioners compared with Koreans. The proportion of Koreans who reported the cost of traditional treatments was expensive was higher than those of Chinese and Korean Chinese. Most of Chinese, Korean-Chinese, and Koreans reported that they would use traditional medicine: 1) when they would have some disease to be treated best through traditional medicine; and 2) when traditional practitioner had a reputation and lots of experiences for those diseases. Most Korean people reported that oriental and western practitioners should cooperate each other to improve the quality of care. Therefore, policy framework including integration of traditional and western medicine, regulation, etc. is needed. In addition, research is needed to determine which diseases is treated best through traditional medicine.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.79-88
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• 2007

Demand for the technology for access to device control network in industry and for access to building automation system via internet is on the increase. In such technology integration of a device control network with a data network such as internet and organizing wide-ranging DCS(distributed control system) is needed, and it can be realized in the framework of VDN(virtual device network)[1,2]. Specifications for device control network and data network are quite different because of the differences in application. So a router that translates the communication protocol between device control network and data network and efficiently transmits information to destination is needed for implementation of the VDN, This paper proposes the concept of NCS(networked control system) based on VDN(virtual device network) and suggests the routing algorithm that uses embedded system.[3]

• The KIPS Transactions:PartA
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• v.14A no.2
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• pp.117-124
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• 2007

In this paper we present a translation lookaside buffer (TLB) system with low power consumption for embedded processors. The proposed TLB is constructed as multiple banks, each with an associated block buffer and a corresponding comparator. Either the block buffer or the main bank is selectively accessed on the basis of two bits in the block buffer (tag buffer). Dynamic power savings are achieved by reducing the number of entries accessed in parallel, as a result of using the tag buffer as a filtering mechanism. The performance overhead of the proposed TLB is negligible compared with other hierarchical TLB structures. For example, the two-cycle overhead of the proposed TLB is only about 1%, as compared with 5% overhead for a filter (micro) TLB and 14% overhead for a same structure without continuos accessing distinction algorithm. We show that the average hit ratios of the block buffers and the main banks of the proposed TLB are 95% and 5% respectively. Dynamic power is reduced by about 95% with respect to with a fully associative TLB, 90% with respect to a filter TLB, and 40% relative to a same structure without continuos accessing distinction algorithm.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.235-246
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• 2011

We are living in the era of globalization, convergence of multi technologies and dual service system especially in the cultural, social, political, economical and technical aspects. These waves are making us go beyond Information Society and urge to enter the Smart Society. In the past, we have focused only on creating, proceeding and accumulating vast amount of information. Where as today, we are hoping to be provided with more intellectual, cheep, and converged form with the help of stored information without any space and time constraints. In this thesis, with consideration of the knowledge based society service integration paradigm, we will first look at the concept of Smart Service with various case studies, proposition strategy implementation on Smart Platform by analysing the service the implementing aspect, looking at the roles of each related divisions, and measuring the secure elements etc.

• Journal of Information Science Theory and Practice
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• v.9 no.2
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• pp.66-82
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• 2021

Recommender Systems have gained immense popularity due to their capability of dealing with a massive amount of information in various domains. They are considered information filtering systems that make predictions or recommendations to users based on their interests and preferences. The more recent technology, Linked Open Data (LOD), has been introduced, and a vast amount of Resource Description Framework data have been published in freely accessible datasets. These datasets are connected to form the so-called LOD cloud. The need for semantic data representation has been identified as one of the next challenges in Recommender Systems. In a LOD-enabled recommendation framework where domain awareness plays a key role, the semantic information provided in the LOD can be exploited. However, dealing with a big chunk of the data from the LOD cloud and its integration with any domain datasets remains a challenge due to various issues, such as resource constraints and broken links. This paper presents the challenges of interconnecting and extracting the DBpedia data with the MovieLens 1 Million dataset. This study demonstrates how LOD can be a vital yet rich source of content knowledge that helps recommender systems address the issues of data sparsity and insufficient content analysis. Based on the challenges, we proposed a few alternatives and solutions to some of the challenges.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.37-43
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• 2023

In today's business landscape, collaboration and interoperability are crucial for organizational success and profitability. However, integrating operations across multiple organizations is challenging due to differing roles and policies in Identity and Access Management (IAM). User-centric identity (UCI) adopts a personalized approach to digital identity management, centering on the end-user for authentication and access control. It provides a decentralized system that ensures secure and customized access for each user. UCI aims to address complex security challenges by aligning access privileges with individual user requirements. This research delves into UCI's ability to streamline resource access amidst conflicting IAM roles and protocols across various organizations. The study presents a UCI-based multi-domain access control (MDAC) framework, which encompasses an ontology, a unified method for articulating access roles and policies across domains, and software services melding with UCI infrastructure. The goal is to enhance organizational resource management and decision-making by offering clear guidelines on access roles and policy management across diverse domains, ultimately boosting companies' return on investment.

• Journal of KIISE
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• v.45 no.2
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• pp.113-125
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• 2018

Recently, with the advent of the Big Data era, we have gained the capability of acquiring vast amounts of knowledge from various fields. The collected knowledge is expressed by well-formed formula and in particular, OWL, a standard language of ontology, is a typical form of well-formed formula. The symbolic reasoning is actively being studied using large amounts of ontology data for extracting intrinsic information. However, most studies of this reasoning support the restricted rule expression based on Description Logic and they have limited applicability to the real world. Moreover, knowledge management for inaccurate information is required, since knowledge inferred from the wrong information will also generate more incorrect information based on the dependencies between the inference rules. Therefore, this paper suggests that the SWAT, knowledge management system should be combined with the SWRL (Semantic Web Rule Language) reasoning based on ATMS (Assumption-based Truth Maintenance System). Moreover, this system was constructed by combining with SWRL reasoning and ATMS for managing large ontology data based on the distributed In-memory framework. Based on this, the ATMS monitoring system allows users to easily detect and correct wrong knowledge. We used the LUBM (Lehigh University Benchmark) dataset for evaluating the suggested method which is managing the knowledge through the retraction of the wrong SWRL inference data on large data.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.195-209
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• 2009

The embedded software has been become more important than the hardware in mobile systems in ubiquitous society. The improvement models such as CMMI(Capability Maturity Model Integration) and SPICE(Software Process Improvement and Capability dEtermination) are used to improve the quality of software in general systems. Software process improvement is also necessary for mobile embedded software development to improve its quality. It is not easy to apply the general software improvement model to the mobile embedded software development due to the high cost effectiveness and heavy process. On the other hand, XP has the characteristics on focused communications with customers and iteration development. It is specially suitable for mobile embedded software development as depending on customer's frequent requirement changes and hardware attributes. In this paper, we propose a framework for development small process improvement based XP(eXtreme Programming)'s practice in order to accomplish CMMI level 2 or 3 in mobile embedded software development at the small organizations. We design and implement the Mobile Embedded Software Process Improvement System(MESPIS) to support process improvement. We also suggest the evaluation method for the mobile embedded software development process improvement framework with CMMI coverage check by comparing other process improvement model. In the future, we need to apply this proposed framework to real project for practical effectiveness and the real cases quantitative. It also include the enhance the functionality of MESPIS.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.785-794
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• 2002

Automatic stock trading systems should be able to solve various kinds of optimization problems such as market trend prediction, stock selection, and trading strategies, in a unified framework. But most of the previous trading systems based on supervised learning have a limit in the ultimate performance, because they are not mainly concerned in the integration of those subproblems. This paper proposes a stock trading system, called R-Trader, based on reinforcement teaming, regarding the process of stock price changes as Markov decision process (MDP). Reinforcement learning is suitable for Joint optimization of predictions and trading strategies. R-Trader adopts two popular reinforcement learning algorithms, temporal-difference (TD) and Q, for selecting stocks and optimizing other trading parameters respectively. Technical analysis is also adopted to devise the input features of the system and value functions are approximated by feedforward neural networks. Experimental results on the Korea stock market show that the proposed system outperforms the market average and also a simple trading system trained by supervised learning both in profit and risk management.