• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.117-127
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• 2012

Identifying user requirements efficiently and reflecting them on the existing system is very important in a rapidly changing web and mobile environments. This study proposes the strategies to refining requirements and to prioritizing those refined requirements for changing of web and mobile application based on user requirements (e.g. mobile application comments, Q&A, reported information as discomfort factors). In order to refining the user requirements, those requirements are grouped by using the advancement of the software business of the Forum of standardization and the existing configuration-based programs. Then, we mapped them onto the PIECES framework to identifying whether the refined requirements are correctly reflected to the system in a way of valid and pure. To determine the priority of refined requirements, first, relative weights are given to software structure, requirements and categories of PIECES. Second, integration points on each requirement are counted to obtain the relative value of partial and overall score of a set of software structural requirements. In order to verifying the possibility and proving the effectiveness of proposing technique in this study, survey was conducted on changing requirements of mobile application which have been serviced at S University by targeting 15 people of work-related stakeholders.

• Korean Journal of Cognitive Science
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• v.19 no.4
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• pp.419-441
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• 2008

As the Web and digital libraries have become a commodity, they are used for a variety of purposes and tasks that may require a great deal of cognitive efforts. However, most search engines in the Web and digital libraries support users with only searching and browsing capabilities, leaving all the cognitive burdens of manipulating information objects to the users. We propose a two-level model for human-Web interactions, consisting of knowledge and information spaces, and a tool that provides knowledge space and inter-space operations in addition to searching and browsing at the information level. Knowledge space is an explication of user's conceptual view of the information objects being explored through interactions with the Web or a digital library. Topics are created and related with associations at the knowledge level and connected to information objects in information space. The tool implemented using the Topic Maps framework has been tested for efficacy as an aid to reducing cognitive burden under exploratory search task.

• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.12-26
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• 2004

In the past, geographic data is constructed and serviced through independent formats of its own according to each GIS(Geographic Information System). Recently the provision of interoperability in GIS is important to efficiently apply the various geographic data between conventional GIS's. Whereupon OGC(Open GIS Consortium) proposed GML(Geography Markup Language) to offer the interoperability between heterogeneous GISs in distributed environments. The GML is an XML encoding for the transport and storage of geographic information, including both the spatial and non-spatial properties of geographic features. Also, the GML includes Web Map Server Implementation Specification to service the GML documents. Accordingly the prototype to provide the reciprocal interchange of geographic information between conventional GIS's and GML documents is widely studied. In this paper, we propose a mapping method of geographic in formation between spatial database and GML for the prototype to support the interoperability between heterogeneous geographic information. For this method, firstly the scheme of converting geographic in Formation of the conventional spatial database into the GML document according to the GML specification is explained, and secondly the scheme to transform geographic information of GML documents to geographic data of spatial database is showed. Consequently, the proposed method is applicable to the framework for integrated geographic information services based on Web by making an offer the interoperability between already built geographic information of conventional GIS's using a mapping method of geographic information between spatial database and GML.

• The KIPS Transactions:PartA
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• v.12A no.5 s.95
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• pp.451-460
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• 2005

We present a methodology to design energy-efficient data paths using FPGAs. Our methodology integrates domain specific modeling, coarse-grained performance evaluation, design space exploration, and low-level simulation to understand the tradeoffs between energy, latency, and area. The domain specific modeling technique defines a high-level model by identifying various components and parameters specific to a domain that affect the system-wide energy dissipation. A domain is a family of architectures and corresponding algorithms for a given application kernel. The high-level model also consists of functions for estimating energy, latency, and area that facilitate tradeoff analysis. Design space exploration(DSE) analyzes the design space defined by the domain and selects a set of designs. Low-level simulations are used for accurate performance estimation for the designs selected by the DSE and also for final design selection We illustrate our methodology using a family of architectures and algorithms for matrix multiplication. The designs identified by our methodology demonstrate tradeoffs among energy, latency, and area. We compare our designs with a vendor specified matrix multiplication kernel to demonstrate the effectiveness of our methodology. To illustrate the effectiveness of our methodology, we used average power density(E/AT), energy/(area x latency), as themetric for comparison. For various problem sizes, designs obtained using our methodology are on average $25\%$ superior with respect to the E/AT performance metric, compared with the state-of-the-art designs by Xilinx. We also discuss the implementation of our methodology using the MILAN framework.

• Proceedings of the CALSEC Conference
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• 2003.09a
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• pp.78-83
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• 2003

본 연구에서는 건설CALS/EC 기반의 정보화 추진을 위한 정보시스템을 개발할 때 적용되는 기존의 소프트웨어 개발방법론의 문제점을 분석하고, 표준화되지 않은 개발방법론의 적용으로 시스템 개발에 비효율적인 비용을 투자하는 문제점과 특성상 입찰, 구매, 계약 등 분야별로 상이한 기능의 업무에 따라 구축되는 건설산업 정보화에 있어서 상호간에 데이터 및 프로세스를 원활히 통합하지 못하므로 인하여 발생되는 개발의 중복성, 정보 활용의 비효율성 등의 문제점을 개선하고자 하였다. 이를 위하여 최근 새로이 부각되고 있는 방법론인 컴포넌트 기반 개발방법론(CBD: Component-Based Development)을 사용하여 건선CALS/EC 표준지침 웹서비스를 위한 시스템의 업무프로세스를 모델링하여 사용자가 쉽게 재사용가능하고 타업무분야에 확대 가능한 방향을 제시하였다. 본 연구를 위하여 기존의 소프트웨어 개발 방법론의 적용상 문제점 분석을 통하여 컴포넌트 기반 개발방법론의 필요성을 증명하고 비즈니스 컴포넌트 프레임워크를 사용하여 건설 CALS/EC 표준지침 웹서비스의 업무프로세스에 적용할 기술적인 방법론을 고찰하고 업무에 효과적으로 적용할 수 있는 업무프로세스 컴포넌트를 제시하였다. 본 연구에서 도출된 컴포넌트 모델은 향후 타업무분야의 시스템을 개발할 때 사용자요구분석 단계부터 별도의 재 작업이 없이 사용될 수 있으며 시스템을 구현할 때 개발 모듈의 중복방지와 용이한 비즈니스로직의 변경 등이 가능하며, 추가의 업무 프로세스나 연관된 다른 분야의 업무프로세스의 반영 및 추가 시 컴포넌트의 활동모델을 쉽게 수정하여 정의함으로써 쉽게 시스템의 기능을 확장할 수 있다.LE 산정에 관한 지속적인 실험적 연구가 이루어져야 하겠다. 증가할 것이다. 또한 부분육을 이용한 완전제품, 적색육제품, 유기농이나 별미식 제품과 같은 형태의 다양한 포장육 제품이 도입 될 것으로 생각되어진다.e in vitro SPF test method will be able to be used as an alternative method for in vivo SPF in case of lotion and cream. replica. A statistically significant improvement of Star Fruit Leaf Extract BG30-treated site was seen in decreased wrinkles. Star Fruit Leaf Extract BG30 results in clinically visible improvement in wrinkling when used topically for 5 weeks. 또한 관계마케팅, CRM 등의 이론적 배경이 되고 있는 신뢰와 결속의 중요성이 재확인하는 결과도 의의라고 할 수 있다. 그리고 신뢰는 양사 간의 상호관계에서 조성될 수 있는 특성을 가진 반면, 결속은 계약관계 초기단계에서 성문화하고 규정화 할 수 있는 변수의 성격이 강하다고 할 수가 있다. 본 연구는 복잡한 기업간 관계를 지나치게 협력적 측면에서만 규명했기 때문에 많은 측면을 간과할 가능성이 있다. 또한 방법론적으로 일방향의 시각만을 고려했고, 횡단적 조사를 통하고 국내의 한 서비스제공업체와 관련이 있는 컨텐츠 공급파트너만의 시각을 검증했기 때문에 해석에서 유의할 필요가 있다. 또한 타당성확보 노력을 기하였지만 측정도구

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.2
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• pp.41-56
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• 2019

Cloud manufacturing is a new concept of manufacturing process that works like a single factory with connected multiple factories. The cloud manufacturing system is a kind of large-scale CPS that produces products through the collaboration of distributed manufacturing facilities based on technologies such as cloud computing, IoT, and virtualization. It utilizes diverse and distributed facilities based on centralized information systems, which allows flexible composition user-centric and service-oriented large-scale systems. However, the cloud manufacturing system is composed of a large number of highly heterogeneous subsystems. It has difficulties in interconnection, data exchange, information processing, and system verification for system construction. In this paper, we derive the user requirements of various aspects of the cloud manufacturing system, such as functional, human, trustworthiness, timing, data and composition, based on the CPS Framework, which is the analysis methodology for CPS. Next, by analyzing the user requirements we define the system requirements including scalability, composability, interactivity, dependability, timing, interoperability and intelligence. We map the defined CPS system requirements to the requirements of oneM2M, which is the platform standard for IoT, so that the support of the system requirements at the level of the IoT platform is verified through Mobius, which is the implementation of oneM2M standard. Analyzing the verification result, finally, we propose a large-scale cloud manufacturing platform based on oneM2M that can meet the cloud manufacturing requirements to support the overall features of the Cloud Manufacturing CPS with dependability.

• Journal of Korean Society of Archives and Records Management
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• v.21 no.4
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• pp.1-18
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• 2021

Today, record management has become more important in management as records generated from administrative work and data production have increased significantly, and the development of information and communication technology, the working environment, and the size and various functions of the government have expanded. It is explained as an example in connection with the concept of public records with the characteristics of big data and big data characteristics. Social, Technological, Economical, Environmental and Political (STEEP) analysis was conducted to examine such areas according to the big data generation environment. The appropriateness and necessity of applying big data technology in the field of public record management were identified, and the top priority applicable framework for public record management work was schematized, and business implications were presented. First, a new organization, additional research, and attempts are needed to apply big data analysis technology to public record management procedures and standards and to record management experts. Second, it is necessary to train record management specialists with "big data analysis qualifications" related to integrated thinking so that unstructured and hidden patterns can be found in a large amount of data. Third, after self-learning by combining big data technology and artificial intelligence in the field of public records, the context should be analyzed, and the social phenomena and environment of public institutions should be analyzed and predicted.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.29-35
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• 2022

This paper proposes a fuel cell education framework installed on a Metaverse environment, which is to reduce the burden of education costs and improve the effect of education or learning. This Meta-Fuel cell platform utilizes the Unity 3D Web and enables not only theoretical education but also hands-on training. The platform was designed and developed to accommodate a variety of unit education contents, such as ppt documents, videos, etc. The platform, therdore, integrates ppt and video demonstrations for theoretical education, as well as software content "STACK-Up" for hands-on training. Theoretical education section provides specialized liberal arts knowledge on hydrogen, including renewable energy, hydrogen economy, and fuel cells. The software "STACK-Up" provides a hands-on practice on assembling the stack parts. Stack is the very core component of fuel cells. The Meta-Fuelcell platform improves the limitations of face-to-face education. It provides educators with the opportunities of non-face-to-face education without restrictions such as educational place, time, and occupancy. On the other hand, learners can choose educational themes, order, etc. It provides educators and learners with interesting experiences to be active in the metaverse space. This platform is being applied experimentally to a education project which is to develop advanced manpower in the fuel cell industry. Its improvement is in progress.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1115-1124
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• 2022

The impact of climate change on water resources was evaluated for Chungju Dam and Soyang-gang Dam basins by constructing an integrated modeling framework consisting of a dam inflow prediction model based on the Variable Infiltration Capacity (VIC) model, a distributed hydrologic model, and an LSTM based dam outflow prediction model. Considering the uncertainty of future climate data, four models of CMIP6 GCM were used as input data of VIC model for future period (2021-2100). As a result of applying future climate data, the average inflow for period increased as the future progressed, and the inflow in the far future (2070-2100) increased by up to 22% compared to that of the observation period (1986-2020). The minimum value of dam discharge lasting 4~50 days was significantly lower than the observed value. This indicates that droughts may occur over a longer period than observed in the past, meaning that citizens of Seoul metropolitan areas may experience severe water shortages due to future droughts. In addition, compared to the near and middle futures, the change in water storage has occurred rapidly in the far future, suggesting that the difficulties of water resource management may increase.

• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.