• 지식경영연구
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• 제18권3호
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• pp.231-246
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• 2017

As an interest in the efficiency of public sector expenditures has spread across the world, Korea has operated a self-evaluation system for government projects as a part of the performance-based budget system. However, an evaluation system for public information technology project has been criticized for its lack of validity, which stems from the uniformity of performance management. This study draws insight from knowledge management literature in an attempt to address the problems with the extant performance evaluation system in public agencies. To realize benefits from IT investment, an agency needs to develop its own performance management model for information systems projects, with a focus on the interaction of IT and organizational system. The knowledge management-based framework for IT projects was verified through a case study, with which we discussed the applicability of knowledge management to the evaluation of public information systems projects.

• KIEAE Journal
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• 제9권5호
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• pp.13-20
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• 2009

This study suggested practical application of decision aid tool on re-evaluation of current buildings with a focus on a energy and economics evaluation methodology. In Europe, over forty percent of all construction activities are for retrofit. For efficient construction, various tools for re-evaluating existing buildings have been developed and are in use. Legislations of relevant laws and studies are actively initiated. In particular, EPIQR (Energy Performance Indoor environment Quality Retrofit), which was developed through the EU's Third and Fourth Framework Programs laid a foundation on a new concept-based decision aid tool for re-evaluation of existing buildings. As for actual applications, based on this, EPIQR+ was developed to be in line with a building maintenance guideline (SIA 469) and is actively applied to public buildings. This tool quantifies the degree of damages of existing buildings and suggests alternatives to users in energy (SIA 380/1) and economical perspectives. This study examined these preceding tools and suggested some trenchant approaching for more comprehensive and efficient use of re-evaluation tools in building maintenance.

• 정보화연구
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• 제11권2호
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• pp.131-141
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• 2014

Refining the monitoring and evaluation reporting is an important thing in e-Government. Indonesia which has had e-Government roadmap since 2000, has not had the systematic mechanism to monitor and evaluate e-Government in which the report can be easily accessed by the public and used to be the best practice to improve other e-Government implementation. Enterprise architecture (EA) has the major objective to straighten an enterprise to its necessary requirements. It can be used to propose the required system and that was the purpose of this paper. It was started by reviewing the literature about e-Government monitoring and evaluation, using quality of service as the means, and understanding TOGAF as one of EA framework. The second step was comparing EA and the evaluation of e-Government in Korea and Indonesia to get the best practices. And the last step was creating EA for the monitoring and evaluation reporting system based on Korea and the literature reviewed. It is expected that the formulized EA can be a tool to improve e-Government implementation in Indonesia.

• 정보교육학회논문지
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• 제15권1호
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• pp.67-76
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• 2011

본 논문은 스마트 기기의 터치 인터페이스를 활용하여 학습자가 직접 입체 학습 콘텐츠를 제어함으로써 보다 실감적인 교육 환경을 구축하고자 한다. 또한 기존의 입체 학습 콘텐츠는 제작의 어려움으로 인해 콘텐츠 확보와 제공에 한계가 있어 교사 및 학습자가 직접 콘텐츠를 제작하고 공유할 수 있도록 프레임워크를 설계하였다. 프레임워크는 직관적인 XML 언어로 구성되고 안드로이드가 탑재된 기기에서 재생 및 저작이 가능하도록 어플리케이션을 구현하였으며 콘텐츠 공유를 위한 서버 환경도 구축하였다. 제안한 프레임워크는 전문가 평가를 통해 타당성을 검증한 결과 새로운 학습 콘텐츠 활용 가능성 면에서 긍정적으로 분석되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.1909-1928
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• 2020

Predicting human mobility has always been an important task in Location-based Social Network. Previous efforts fail to capture spatial dependence effectively, mainly reflected in weakening the location topology information. In this paper, we propose a neural network-based method which can capture spatial-temporal dependence to predict the next location of a person. Specifically, we involve a graph convolutional network (GCN) based on a seq2seq framework to capture the location topology information and temporal dependence, respectively. The encoder of the seq2seq framework first generates the hidden state and cell state of the historical trajectories. The GCN is then used to generate graph embeddings of the location topology graph. Finally, we predict future trajectories by aggregated temporal dependence and graph embeddings in the decoder. For evaluation, we leverage two real-world datasets, Foursquare and Gowalla. The experimental results demonstrate that our model has a better performance than the compared models.

• 한국인터넷방송통신학회논문지
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• 제14권5호
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• pp.145-151
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• 2014

RCS-e 사용자와 SMS 사용자간 메시지를 주고받기 위해서는 RCS-e 사용자가 메시지를 보내기 전 SMS 사용자의 프레즌스 정보를 알 수 있어야 한다. 그러나 RCS-e 표준 규격 상으로는 SMS 사용자의 프레즌스 정보를 조회할 수 없는 한계가 있다. 본 논문은 RCS-e 관련 서버 기능을 일부 수정하여 기존 RCS-e 클라이언트 기능의 수정 없이 SMS 사용자의 프레즌스 정보를 RCS-e 사용자가 클라이언트를 통해 조회할 수 있는 소프트웨어 프레임워크를 제안한다. 이를 위해 각 장비 간 호 처리 흐름을 정의하였으며 SMS 가입자에 대한 RCS-e 서비스 별 Tag 및 서비스 튜플을 정의하였다. 또한 성능 평가를 통해 제안하는 방법이 네트워크에 추가적인 부하를 주지 않는다는 것을 증명하였다.

• 한국산학기술학회논문지
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• 제12권10호
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• pp.4600-4605
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• 2011

본 논문은 스프링 프레임워크 2.5의 동일한 플랫폼 환경에서 하이버네이트 3.2와 아이바티스 2.3에 대하여 기능별 수행 속도를 비교하여 프로젝트 규모별 장단점을 분석해 보는데 그 목적이 있다. 현재까지 경량 컨테이너 구조로 많이 사용되고 잘 알려진 구조로 스프링 프레임워크이 있다. 또한 데이터베이스의 생산성을 높여주기 위한 기법으로 ORM이 있다. 현재 많이 사용되는 ORM 도구로 하이버네이트와 아이바티스가 있다. 따라서 본 연구에서는 동일한 스프링 프레임워크 2.5 환경을 기반으로 하이버네이트 3.2와 아이바티스 2.3에서 파일럿 시스템을 설계하고 구현하여 CRUD별 수행 속도를 비교함으로써 프로젝트의 적용에 평가 지표를 제공하고자 한다.

• Journal of Information Processing Systems
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• 제16권5호
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• pp.1214-1222
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• 2020

Pervasive augmented reality (AR) technology can be used to efficiently search for the required information regarding products in stores through text augmentation in an Internet of Things (IoT) environment. The evolution of context awareness and image processing technologies are the main driving forces that realize this type of AR service. One of the problems to be addressed in the service is that augmented objects are fixed and cannot be replaced efficiently in real time. To address this problem, a real-time mobile AR framework is proposed. In this framework, an optimal object to be augmented is selected based on object similarity comparison, and the augmented objects are efficiently managed using distributed metadata servers to adapt to the user requirements, in a given situation. To evaluate the feasibility of the proposed framework, a prototype system was implemented, and a qualitative evaluation based on questionnaires was conducted. The experimental results show that the proposed framework provides a better user experience than existing features in smartphones, and through fast AR service, the users are able to conveniently obtain additional information on products or objects.

• 한국농공학회논문집
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• 제63권4호
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• pp.65-86
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• 2021

This study aims at testing a hypothesis that the resilience of agricultural water systems is characterized by trade-offs and synergies of effects from climate and socioeconomic change. To achieve this, an Agricultural Water System Climate Resilience Assessment (ACRA) framework is established to evaluate comprehensive resilience of an agricultural water system to the combined impacts of the climate and socioeconomic changes with a case study in South Korea. Understanding dynamic behaviors of the agricultural water systems under climate and socioeconomic drivers is not straightforward because the system structure includes complex interactions with multiple feedbacks across components in water and agriculture sectors and climate and socioeconomic factors, which has not been well addressed in the existing decision support models. No consideration of the complex interactions with feedbacks in a decision making process may lead to counterintuitive and untoward evaluation of the coupled impacts of the climate and socioeconomic changes on the system performance. In this regard, the ACRA framework employs a System Dynamics (SD) approach that has been widely used to understand dynamics of the complex systems with the feedback interactions. In the ACRA framework applied to the case study in South Korea, the SD model works along with HOMWRS simulation. The ACRA framework will help to explore resilience-based strategies with infrastructure investment and management options for agricultural water systems.

• 청정기술
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• 제28권2호
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• pp.138-146
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• 2022

Electricity has become a factor that dramatically affects the market economy. The day-ahead system marginal price determines electricity prices, and system marginal price forecasting is critical in maintaining energy management systems. There have been several studies using mathematics and machine learning models to forecast the system marginal price, but few studies have been conducted to develop, compare, and analyze various machine learning and deep learning models based on a data-driven framework. Therefore, in this study, different machine learning algorithms (i.e., autoregressive-based models such as the autoregressive integrated moving average model) and deep learning networks (i.e., recurrent neural network-based models such as the long short-term memory and gated recurrent unit model) are considered and integrated evaluation metrics including a forecasting test and information criteria are proposed to discern the optimal forecasting model. A case study of South Korea using long-term time-series system marginal price data from 2016 to 2021 was applied to the developed framework. The results of the study indicate that the autoregressive integrated moving average model (R-squared score: 0.97) and the gated recurrent unit model (R-squared score: 0.94) are appropriate for system marginal price forecasting. This study is expected to contribute significantly to energy management systems and the suggested framework can be explicitly applied for renewable energy networks.