• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.505-508
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• 2013

스마트폰 응용 프로그램의 메모리 관리는 응용 프로그램의 속도와 안정성 측면에서 중요하게 다루어진다. 응용 프로그램에서 다루는 요소 중 이미지는 메모리 사용량의 많은 부분을 차지하며, 메모리의 여유 공간 내에서 이미지가 사용될 수 있도록 관리되어야 한다. 그러나 이미지의 해상도가 커지거나 다루게 되는 이미지의 개수가 늘어날 수록 이미지 객체의 관리의 어려움도 늘어나게 된다. 이미지 객체가 메모리 공간이 부족한 시점에서 메모리에 적재될 경우 응용 프로그램은 성능이 저하되거나 강제 종료될 수 있어 응용 프로그램의 사용성과 안정성이 낮아지게 된다. 본 논문에서는 안드로이드의 응용 프로그램에서 사용되는 이미지가 메모리의 많은 공간을 차지할 때, 안정적인 응용 프로그램 구동 환경을 제공해주는 동적 메모리 관리 기법을 적용하여 OOM(Out of Memory) 오류가 발생하는 문제를 해결하고자 한다.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.877-885
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• 2009

In this paper, we propose the SINDI-Grid which is a high-performance framework for scientific and technological knowledge discovery using the grid computing. By using the advantages of the grid computing providing data repository of large-volume and high-speed computing power, the SINDI-Grid framework provides a variety of grid services for distributed data analysis and scientific knowledge processing. And the SINDI-Workflow tool exploits these services so that performs the design and execution for scientific and technological knowledge discovery applications which integrate various information processing algorithms.

• Knowledge Management Research
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• v.10 no.1
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• pp.1-15
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• 2009

As pervasive computing technology, which aims to get linked to useful knowledge, information or services anytime, anywhere, using any devices and/or artifacts, is proliferating, desirable impacts on knowledge management systems are now available. The pervasive computing technology will potentially enable the knowledge management systems to realize individualization and socialization and ultimately increase the knowledge processing productivity. However, researchers who apply the pervasive computing methodologies to novel way of knowledge management have been very few. These result in unsatisfactory consideration of establishing pervasive knowledge management systems. Hence, the purpose of this paper is to cast the vision of pervasive knowledge management and search for a couple of possible research issues and possibilities. This paper suggests a framework of ubiDSS, an amended knowledge management system for the next generation deploying pervasive and autonomous knowledge acquisition capabilities of ubiquitous computing technologies. Also the CKAM, context-based knowledge acquisition module, is illustrated as a prototype of future knowledge management systems.

• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.1-9
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• 1996

A key issue in spoken language processing has become the integration of speech understanding and natural language processing(NLP). This paper presents a parallel computational model for the integration of speech and NLP. The model adopts a hierarchically-structured knowledge base and memory-based parsing techniques. Processing is carried out by passing multiple markers in parallel through the knowledge base. Speech-specific problems such as insertion, deletion, and substitution have been analyzed and their parallel solutions are provided. The complete system has been implemented on the Semantic Network Array Processor(SNAP) and is operational. Results show an 80% sentence recognition rate for the Air Traffic Control domain. Moreover, a 15-fold speed-up can be obtained over an identical sequential implementation with an increasing speed advantage as the size of the knowledge base grows.

• The Transactions of the Korea Information Processing Society
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• v.5 no.3
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• pp.662-670
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• 1998

In order to overcome the problems with first generation expert systems at the symbol level, recently various knowledge level development techniques of second generation expert systems have been proposed. But, these techniques are conceptual modelling techniques. This paper modifies and complements these conceptual modelling techniques and proposes a Task Object Modelling (TOM) technique as a practical knowledge level expert system development technique. This paper defines a Task Object(TO) as a knowledge unit consisted of a goal, execution conditions, behaviour knowledge, and so on. And, we define a Task Object Diagram(TOD) to depict structual, dynamic, and functional aspects of TO easily. We also define Inference Types as basic units to describe behaviour knowledge of TOs. In order to utilize the proposed TOM technique as not a simple conceptual modelling technique but a practical second generalion expert system development technique, we implement a TOD editor, a TO editor, and TO processing algorithm based on the state of TOs. Also we implement a Inference Types Library, in which each inference type is corresponded to an IRE(Jntelligent Rules Element) method, to transform the defined inference types into IRE methods automatically.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.68-74
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• 2008

Application areas of Knowledge Discovery in Database(KDD) have been expanded to many R&D management processes including technology trends analysis, forecasting and evaluation etc. Established research field such as informetrics (or scientometrics) has utilized techniques or methods of KDD. Various systems have been developed to support works of analyzing large-scale R&D related databases such as patent DB or bibliographic DB by a few researchers or institutions. But extant systems have some problems for korean users to use. Their prices is not moderate, korean language processing is impossible, and user's demands not reflected. To solve these problems, Korea Institute of Science and Technology Information(KISTI) developed stand-alone type information analysis system named as KnowledgeMatrix. KnowledgeMatrix system offer various functions to analyze retrieved data set from databases. KnowledgeMatrix's main operation unit is composed of user-defined lists and matrix generation, cluster analysis, visualization, data pre-processing. Matrix generation unit help extract information items which will be analyzed, and calculate occurrence, co-occurrence, proximity of the items. Cluster analysis unit enable matrix data to be clustered by hierarchical or non-hierarchical clustering methods and present tree-type structure of clustered data. Visualization unit offer various methods such as chart, FDP, strategic diagram and PFNet. Data pre-processing unit consists of data import editor, string editor, thesaurus editor, grouping method, field-refining methods and sub-dataset generation methods. KnowledgeMatrix show better performances and offer more various functions than extant systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.160-163
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• 2014

IP 네트워크를 통해 전송되는 실시간 스트라밍은 네트워크 상태에 따라 데이터 손실 및 전송 지연의 문제가 발생 할 수 있다. 이에 멀티미디어 네트워킹 애플리케이션은 RTP(Realtime Transport Protocol)와 RTCP(RTP Control Protocol)를 지원하는 RTSP(Realtime Streaming Protocol)를 사용한다. RTSP를 사용하는 송신단은 패킷 손실과 전송지연이 발생할 경우 끊김 없는 멀티미디어 스티리밍을 제공하기 위해 네트워크 상태에 따라 전송률을 변경한다. 하지만 전송률이 낮아지면 멀티미디어 품질이 떨어지게 된다. 만약 짧은 시간 동안 전송률이 빈번하게 변경된다면 일관성 있는 품질의 서비스를 제공하기 어렵다. 본 논문에서는 SDN 환경에서 실시간 스트리밍을 효과적으로 제어하기 위해 중앙 컨트롤러가 RTCP를 수신하고 송신단의 전송률과 현재 링크의 가용 전송율을 추정한다. 추정된 가용 전송율이 송신단의 전송률보다 낮다며 각 스위치의 활성화된 플로우 엔트리가 낮은 스위치로 라우팅 경로를 선택하는 메커니즘을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.151-154
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• 2011

유비쿼터스 협업 (Ubiquitous Collaboration)은 유비쿼터스 환경에서 다양한 이기종 디바이스 (PC, Tablet PC, Smart Phone, etc)들이 유무선망을 통해 언제 어디서나 원하는 서비스를 주고 받을 수 있는 시스템으로 시간과 장소에 상관없이 다양한 데이터를 주고 받을 수 있다. 스마트폰의 보편화, 하드웨어 / 소프트웨어 그리고 무선망의 진화로 협업의 중요성은 점점 증가하고 있다. 본 연구에서는 스마트폰 환경에서 이미지, 도형, 텍스트 등의 도구를 사용 협업하는 인터랙티브 화이트보드 어플리케이션(Interactive Whiteboard Application on Smart Phone)을 사용하여 다양한 환경의 사용자들이 서로 다른 이기종 디바이스와 함께 통신하는 방법을 보인다. 또한 서로 다른 이기종 디바이스 간 그룹 통신에서 오는 동기화(Synchronization), 비동기화(Asynchronization), 또한 다른 화면 크기로 부터 발생되는 서로 다른 이미지 크기 표현문제를 극복하기 위한 사용성 평가실험(Usability Test)을 통하여 연구의 타당성 및 우수성을 증명해 보이고자 한다.

• IE interfaces
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• v.14 no.2
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• pp.164-171
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• 2001

We suggest a Business Performance Information System with Knowledge Discovery in Databases(KDD) as a key component of integrated information and knowledge management system. The proposed system measures business performance by considering both VA(Value-Added), which represents stakeholder's point of view and EVA(Economic Value-Added), which represents shareholder's point of view. In modeling of Business Performance Information System, we apply the following KDD processes : Data Warehouse for consistent management of a performance data, On-Line Analytic Processing(OLAP) for multidimensional analysis, Genetic Algorithms for exploring and finding dominant managing factors and Analytic Hierarchy Process(AHP) for applying expert's knowledge and experience. To demonstrate the performance of the system, we conducted a case study using financial data of Korean automobile industry over 16 years from 1981 to 1996, which is taken from database of KISFAS(Korea Investors Services Financial Analysis System).

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.5
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• pp.93-102
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• 1997

Conventional expert systems have difficulties in the inference on time-varing situations because they don't have the structure for processing time related informations and rule representation method to describe time explicitely. Some expert systems capable of temporal reasoning are not applicable to the domain in which state changes happen by unpredictble events that cannot be represented by periodic changes of data. In this paper, an event based temporal reasoning method is proposed. It is capable of processing te unpredictable events, representing the knowledge related to event and time, and infering by that knowledge as well as infering by periodically time-varing data. The NEO/temporal, an temporal inference engine, is implemented by applying the proposed temporal reasoning situation assessment and decision supporting system is implemented to show the benefits of the proposed temporal information processing model.