• 한국정보시스템학회지:정보시스템연구
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• 제19권3호
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• pp.181-208
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• 2010

As knowledge-based society comes to the fore, sharing knowledge becomes a hot issue. Among various types of knowledge, a significance of software(applications) and contents is a huge in a current society. Moreover, along with appearance of smartphone, for instance iPhone, Application Store(also known as AppStore) utilized as a common gateway for sharing software and contents, brings a big interest for many users and developers. However, prior research to understand users' behavior on AppStore has been a scant. Therefore, the main purpose of this study is to investigate the impact of key smart service environmental factors on AppStore in order to empirically explain users' psychological feelings of intention to use AppStore. Based on a well-known technology adoption model, TAM, the study incorporates three main characteristics(user, society, and service) with six constructs(Innovation, Enjoyment, Subjective Norm, Information Level, Content variety, and Cost), influencing perceived usefulness, which then affects users' intention to use AppStore. Results provide evidence that support the tested hypotheses. The implications of the findings suggest a new theoretical work for future AppStore research and offers suggestions that the researchers and practitioners of AppStore should consider regarding the development of application and contents.

• 한국지능시스템학회논문지
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• 제8권6호
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• pp.27-36
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• 1998

본 논문은 대규모 데이터베이스에서 유용한 지식을 발견하기 위해 라프셋을 중심으로 한 통합적 방법을 제시한다. 본 방업에서는 데이터베이스에 있는 실제 데이터에서 일반화된 데이터를 추출하기 위해 속성중심의 개념계층 상승기법을 사용하고, 획득 정보량을 측정하기 위해 결정 트리에 의한 귀납법을 사용한다. 그리고 불필요한 속성 및 속성값을 제거하기 위해 라프셋 이론의 지식감축 방법을 적용한다. 통합 알고리즘은 먼저, 개념의 일반화에 의해 데이터베이스의 크기를 줄이고, 다음으로 결정속성에 영향을 적게 미치는 조건속성을 제거함으로써 속성의 수를 줄인다. 마지막으로 속성간의 종속관계를 분석함으로써 불필요한 속성값을 제거하여 간략화된 결정규칙을 유도한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권4호
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• pp.1972-1986
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• 2017

With the advent of the knowledge economy, science and technology resources have played an important role in economic competition, and their optimal allocation has been regarded as very important across the world. Thus, allocation optimization research for regional science and technology resources is significant for accelerating the reform of regional science and technology systems. Regional science and technology resource allocation optimization is modeled as a double-layer optimization model: the entire system is characterized by top-layer optimization, whereas the subsystems are characterized by bottom-layer optimization. To efficaciously solve this optimization problem, we propose a mixed search method based on the orthogonal genetic algorithm and sensitivity analysis. This novel method adopts the integrated modeling concept with a combination of the knowledge model and heuristic search model, on the basis of the heuristic search model, and simultaneously highlights the effect of the knowledge model. To compare the performance of different methods, five methods and two channels were used to address an application example. Both the optimized results and simulation time of the proposed method outperformed those of the other methods. The application of the proposed method to solve the problem of entire system optimization is feasible, correct, and effective.

• 한국지능시스템학회논문지
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• 제19권6호
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• pp.760-765
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• 2009

객체 영상에서 색, 모양과 같은 특징은 객체의 특성을 명확하게 표현하지 못한다. 따라서 제한된 특징 정보는 객체 영상인식의 애매성을 야기한다. 최근에는 객체 인식에서의 애매성을 줄이기 위해 지식베이스에 기반한 영상의 인식에 관한 연구가 진행되고 있다. 그러나 영상은 수치적 정보로 표현되고 지식베이스는 개념적 정보로 표현되어 영상과 지식 베이스의 결합이 쉽지 않다. 본 논문에서는 영상과 지식베이스의 정보 표현의 차이를 줄이기 위해 온톨로지를 이용하여 지식베이스를 구성한다. 그리고 내부 객체 정보를 이용하여 객체 영상 인식 과정에서의 애매성을 줄이는 객체 영상 인식 방법을 제안한다. 또한, 과일 영역에서의 객체 영상 인식 실험을 통해 제안한 방법의 효용성을 확인한다.

• 산업공학
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• 제12권2호
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• pp.319-328
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• 1999

Today, offshore design field is concerned with system integration such as CIM(Computer Integrated Manufacturing), PDMS(Product Data Management System) and EDMS(Engineering Data Management System) in order to cope with the change of engineering specification as owner's requirements during construction stage of the project. This paper deals with the case study that describes about the efficient interface between material control system and 3D CAD system to support the design process in offshore industry using design rules involved the designer's knowledge. In this paper, we constructed an information system, called knowledge-based CAD interface systems, which is composed material code management system and 3D specification generator which automatically creates 3D catalogue anti specification by linking the material code, called short code, and the specification components of the 3D CAD system. As a result of the construction, it is possible to maintain consistency of the design process, and through reduction of the design processing time and improvement of the design process, competitiveness is improved.

• Nuclear Engineering and Technology
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• 제46권1호
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• pp.11-26
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• 2014

The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk assessment is typically limited, so that the analysis must strongly rely on expert judgments. In this paper, a Dempster-Shafer Theory (DST) framework for handling uncertainties in NPP SPRAs is proposed and applied to an example case study. The main contributions of this paper are two: (i) applying the complete DST framework to SPRA models, showing how to build the Dempster-Shafer structures of the uncertainty parameters based on industry generic data, and (ii) embedding Bayesian updating based on plant specific data into the framework. The results of the application to a case study show that the approach is feasible and effective in (i) describing and jointly propagating aleatory and epistemic uncertainties in SPRA models and (ii) providing 'conservative' bounds on the safety quantities of interest (i.e. Core Damage Frequency, CDF) that reflect the (limited) state of knowledge of the experts about the system of interest.

• Soft Computing and Machine Intelligence
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• 제1권1호
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• pp.1-10
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• 2021

Analysis and Tracking of bug reports is a challenging field in software repositories mining. It is one of the fundamental ways to explores a large amount of data acquired from defect tracking systems to discover patterns and valuable knowledge about the process of bug triaging. Furthermore, bug data is publically accessible and available of the following systems, such as Bugzilla and JIRA. Moreover, with robust machine learning (ML) techniques, it is quite possible to process and analyze a massive amount of data for extracting underlying patterns, knowledge, and insights. Therefore, it is an interesting area to propose innovative and robust solutions to analyze and track bug reports originating from different open source projects, including Mozilla and Eclipse. This research study presents an ML-based classification model to analyze and track bug defects for enhancing software engineering management (SEM) processes. In this work, Artificial Neural Network (ANN) and Naive Bayesian (NB) classifiers are implemented using open-source bug datasets, such as Mozilla and Eclipse. Furthermore, different evaluation measures are employed to analyze and evaluate the experimental results. Moreover, a comparative analysis is given to compare the experimental results of ANN with NB. The experimental results indicate that the ANN achieved high accuracy compared to the NB. The proposed research study will enhance SEM processes and contribute to the body of knowledge of the data mining field.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권1호
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• pp.261-279
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• 2023

In this article, the uplink achievable rate is investigated for massive multiple-input multiple-output (MIMO) under correlated Ricean fading channel, where each base station (BS) and user are both deployed multiple antennas. Considering the availability of prior knowledge at BS, two different channel estimation approaches are adopted with and without prior knowledge. Based on these channel estimations, a two-layer decoding scheme is adopted with maximum ratio precoding as the first layer decoder and optimal second layer precoding in the second layer. Based on two aforementioned channel estimations and two-layer decoding scheme, the exact closed form expressions for uplink achievable rates are computed with and without prior knowledge, respectively. These derived expressions enable us to analyze the impacts of line-of-sight (LoS) component, two-layer decoding, data transmit power, pilot contamination, and spatially correlated Ricean fading. Then, numerical results illustrate that the system with spatially correlated Ricean fading channel is superior in terms of uplink achievable rate. Besides, it reveals that compared with the single-layer decoding, the two-layer decoding scheme can significantly improve the uplink achievable rate performance.

• 정보관리학회지
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• 제23권4호
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• pp.295-315
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• 2006

본 연구에서는 캠퍼스 지식경영의 관점에서 대학 내 지식 중에서도 대학 교수들 간의 강의자원 공유의 필요성과 그에 영향을 미치는 영향요인들에 대해 분석하였다. 분석결과 강의자원 공유 영향요인으로 설정된 6개의 요인 즉, 인지도, '신뢰성', '의사소통의 개방성', '협력도', '평가와보상', 'IT 인프라기반 의사소통채널'중 관계적 요인의 '인지도'와 구조적요인의 '평가와 보상' 두 요인만이 종속변수인 '대학 내 강의자원공유'에 유의한 영향을 미치는 것으로 나타났다. 개별 독립변수들의 상대적 중요도를 비교해보면 특히 관계적 요인인 '인지도' 가 '대학 내 강의자원 공유'에 탁월한 영향력을 미치고 있는 것으로 나타났다.

• The Journal of Asian Finance, Economics and Business
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• 제8권5호
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• pp.1079-1089
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• 2021

The current study aims to examine the effect of Hofstede's dimensions of culture on the intention of sharing knowledge in higher education institutions (HEIs) in Jordan. In the literature, researchers have given limited attention to such an effect. Therefore, by adopting Hofstede's framework, the current study attempts to investigate how Jordan's cultural context impacts on the intentions to share knowledge in HEIs. This study applied quantitative research methods to investigate the effect of Hofstede's cultural dimensions on knowledge-sharing intentions. In total, 307 questionnaires were collected from employees in Jordanian universities and, then, tested using descriptive and regression analytical methods. The study results show that culture dimensions influence knowledge-sharing intention and that each dimension plays a different role in enhancing this knowledge-sharing intention. More specifically, it was found that long-term orientation, collectivism and high uncertainty avoidance had a positive effect on knowledge-sharing intention, while cultural masculinity and power distance had no negative effect. Based on these results, the study makes several recommendations, the most important of which is the promotion of cultural values that encourage intention to share knowledge. Also, more qualitative research is needed to explore in depth the effective means that encourage intentions to share different types of knowledge.