• Knowledge Management Research
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• v.24 no.3
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• pp.127-148
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• 2023

Traditional Business Intelligence environment is limited to support the rapidly changing businesses and the exponential growth of data in both volume and complexity of data. Companies should shift their business intelligence environment into Self-Service Business Intelligence (SSBI) environment in order to make smarter and faster decisions. However, firms seem to face various challenges in implementing and leveraging the effective business intelligence system, and academics do not provide sufficient studies related including the success factors of SSBI. This study analyzes the three cases of Korean companies in depth, their development process and the assessment of business intelligence, based on the theoretical model on the key success factors of business intelligence systems. The comparative analysis of the three cases including project managers' interviews and performance evaluations provide rich implications for the successful adoption and the use of business intelligence systems of firms. The study is expected to provide useful references for firms to fully leverage the effects of business intelligence systems and upgrade towards self-service business intelligence systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1527-1538
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• 2008

There are growing needs of introducing Next Generation Business Intelligence into firm to strengthen competencies. Recently, Next Generation Business Intelligence appeared in the spotlight because it could support to connect the strategies establishment with enforcing the strategies. In this parer, we analyze the factors and build the theoretical model of influencing the utilization of Next Generation Business Intelligence. The practical implications were also discussed.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.73-86
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• 2012

This paper theoretically derives an algorithm to discover a new type of social networks from workflow models, which is termed workflow-based social network intelligence. In general, workflow intelligence (or business process intelligence) technology consists of four types of techniques that discover, analyze, monitor and control, and predict from workflow models and their execution histories. So, this paper proposes an algorithm, which is termed ICN-based workflow-based social network intelligence discovery algorithm, to be classified into the type of discovery techniques, which are able to discover workflow-based social network intelligence that are formed among workflow performers through a series of workflow models and their executions, In order particularly to prove the correctness and feasibility of the proposed algorithm, this paper tries to apply the algorithm to a specific workflow model and to show that it is able to generate its corresponding workflow-based social network intelligence.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.33-39
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• 2019

As cyber attack methods are becoming more intelligent, incidents such as security breaches and international crimes are increasing. In order to predict and respond to these cyber attacks, the characteristics, methods, and types of attack techniques should be identified. To this end, many security companies are publishing security intelligence reports to quickly identify various attack patterns and prevent further damage. However, the reports that each company distributes are not structured, yet, the number of published intelligence reports are ever-increasing. In this paper, we propose a method to extract structured data from unstructured security intelligence reports. We also propose an automatic intelligence report analysis system that divides a large volume of reports into sub-groups based on their topics, making the report analysis process more effective and efficient.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12B
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• pp.1509-1521
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• 2011

WfMC, which is one of the international standardization organizations leading the business process and workflow technologies, has been officially released the BPAF1.0 that is a standard format to record process instances' event logs according as the business process intelligence mining technologies have recently issued in the business process and workflow literature. The business process mining technologies consist of two groups of algorithms and their analysis techniques; one is to rediscover flow-oriented process-intelligence, such as control-flow, data-flow, role-flow, and actor-flow intelligence, from process instances' event logs, and the other has something to do with rediscovering relation-oriented process-intelligence like process-driven social networks and process-driven affiliation networks from the event logs. The current standardized format of BPAF1.0 aims at only supporting the control-flow oriented process-intelligence mining techniques, and so it is unable to properly support the relation-oriented process-intelligence mining techniques. Therefore, this paper tries to extend the BPAF1.0 so as to reasonably support the relation-oriented process-intelligence mining techniques, and the extended BPAF is termed BPAF2.0. Particularly, we have a plan to standardize the extended BPAF2.0 as not only the national standard specifications through the e-Business project group of TTA, but also the international standard specifications of WfMC.

• Journal of Wind Energy
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• v.13 no.2
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• pp.13-22
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• 2022

In this study, the resonant motion of a floating offshore wind system due to negative damping was mitigated by peak shaving algorithms of the NREL ROSCO controller, and the decreased gains of the blade pitch controller by the gain detuning method for the floating system was increased to the gains of onshore baseline controller to improve the power performance of the turbine. To check the performance of the controller, the dynamic responses between the existing gain-detuned pitch controller and the ROSCO controller with peak shaving control for an OC4 floating offshore wind system were compared. As a result of DLC1.1 at near-rated wind speed, when peak shaving was applied, the average generator power decreased by 1.9%, but it was confirmed that the standard deviation was reduced and stability was improved with fast pitch regulation. In addition, since peak shaving reduces the maximum thrust of the rotor, was confirmed that not only are the loads of the blades and tower reduced, but the surge motion of the floater is also reduced, and the tension of the mooring lines is reduced.

• Review of KIISC
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• v.31 no.5
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• pp.13-19
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• 2021

사이버 공격이 점점 복잡해지고 빠르게 진화하면서, 기존에 알려졌거나 향후 예견되는 위협에 대한 근거를 바탕으로 한 지식인 사이버 위협 인텔리전스(CTI)를 구축하고 공유하려는 노력이 최근 주목을 받고 있다. 특히, Transport Layer Security(TLS)와 같은 암호화 프로토콜을 활용해 암호화된 인터넷 트래픽이 증가하면서 패킷 페이로드(payload)의 분석이 어려워짐에 따라, 암호화된 네트워크 트래픽을 핑거프린팅(fingerprinting)하고 이 정보를 공유해 위협의 근거로 활용하고자 하는 시도들이 등장하고 있다. 본 논문에서는 최근에 제안된 주요 TLS 핑거프린팅 기법 및 이를 사이버 위협 인텔리전스 구축을 위해 데이터베이스화 하는 사례를 소개한다.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.584-586
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• 2018

사이버 공격 기법이 다양해지고 지능화됨에 따라 침해사고 발생이 증가하고 있으며, 그에 따른 피해도 확산되고 있다. 이에 따라 보안 기업들은 다양한 침해사고를 파악하고 빠르게 대처하기 위하여 위협정보를 정리한 인텔리전스 리포트를 배포하고 있다. 하지만 인텔리전스 리포트의 형식이 정형화되어 있지 않고 점점 증가하고 있어, 인텔리전스 리포트를 수작업을 통해 분류하기 힘들다는 문제점이 있다. 이와 같은 문제를 해결하기 위해 본 논문에서는 개체명 인식 시스템을 활용하여 비정형 인텔리전스 리포트에서 위협정보를 자동으로 탐지하고 추출할 수 있는 모델을 제안한다.

• Information Systems Review
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• v.6 no.2
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• pp.65-77
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• 2004

Business intelligence assumes an integrated and inter-connected information resources. To manage an integrated database, we need to trace data transformation processes from its outset. For this purpose, this study proposes an extended Information Structure Graph that models data transformation steps in addition to data transformation structures. Using the graph, we can identify relationship among data entities and assign data quality measures to each nodes or arcs of a graph, thus eases management of data and enhancing their quality.

• International Commerce and Information Review
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• v.19 no.1
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• pp.127-152
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• 2017

One of the biggest challenges in export activities of SME is the increasingly cultural diversity that requires especially export managers to adapt their doing business in many different kinds of cross-cultural situations effectively. A relative newly developed concept 'Cultural Intelligence' has been evaluated as a key element for the success in international business activities. This study aims to investigate empirically the role of Cultural Intelligence(CQ), one component of cultural competence, on export marketing adaptation. The statistical method used to test the hypotheses was Structural Equation Modeling using PLS. The results of this study are follows. The moderating role of Cultural Intelligence between information seeking and information using abilities is more stronger in marketing rather than relationship adaptation. Cultural Intelligence moderates between them. Critical factors affecting Cultural Intelligence are also discussed; foreign language fluency, business travels in abroad, characteristics of the business travels, multi-lingual ability, pre-education related cultural subjects, and visit experience in foreign countries. Especially, export managers' foreign language ability leads to much stronger influence on cultural intelligence. The result of the empirical study provides important implications for export SME and export supporting organizations. Export firms and supporting organizations must expand programs widely in multi cultural training and education to help managers gain a better understanding in a various export environment.