• 제어로봇시스템학회논문지
• /
• 제5권1호
• /
• pp.54-61
• /
• 1999

Objective of the research is to put the vast and complex fault tracking knowledge of human experts in semiconductor production line into the knowledge base of computer system. We mined the fault tracking knowledge of domain experts(engineers of production line) for the construction of knowledge base of the expert system. Object oriented fact models which increase the extensibility and reusability have been built. The rules are designed to perform the fault diagnosis of the items in production device. We have exploited the evidence accumulation method to assign check priority in rules. The major contribution is in the overall design and implementation of the nile base and related facts of the expert system in object oriented paradigm for the application of the system in fault diagnosis in semiconductor production line.

• 한국경영과학회지
• /
• 제25권3호
• /
• pp.91-107
• /
• 2000

The linear programming model is a special form of useful knowledge that is embedded in a database. Since formulating models from scratch requires knowledge-intensive efforts, knowledge-based formulation support systems have been proposed in the Decision Support Systems area. However, they rely on the assumption that sufficient domain knowledge should already be captured as a specific knowledge representation form. Hence, the purpose of this paper is to propose a methodology that finds useful knowledge on building linear programming models from a database. The methodology consists of two parts. The first part is to find s first-cut model based on a data dictionary. To do so, we applied the General Problem Solver(GPS) algorithm. The second part is to discover a second-cut model by applying neural network technique. An illustrative example is described to show the feasibility of the proposed methodology.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
• /
• pp.235-240
• /
• 2004

In this paper, we propose a framework for ontological knowledge-based image understanding systems. Ontology composed of concepts can be used as a guide for describing objects from a specific domain of interest and describing relations between objects from different domains The proposed framework consists of four main subparts ⅰ) ontological knowledge bases, ⅱ) primitive feature detectors, ⅲ) concept inference engine, and ⅳ) semantic inference engine. Using ontological knowledge bases on various domains and features extracted from the detectors, concept inference engine infers concepts on regions of interest in an image and semantic inference engine reasons semantic situations between concepts from different domains. We present a outline for ontological knowledge-based image understanding systems and application examples within specific domains such as text recognition and human recognition in order to show the validity of the proposed system.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2001년도 춘계정기학술대회
• /
• pp.215-222
• /
• 2001

The task for chromosome analysis and diagnosis by experienced cytogenetists are being concerned as repetitive, time consuming job and expensive. FOr that reason, chromosome analysis system based on knowledge base for CAI had been established to be able to analyze chromosomes and obtain necessary advises from the knowledge base instead of human experts. That s to say, knowledge base by IF THEN production rule was implemented to a knowledge domain with normal and abnormal chromosomes, and then the inference results by knowledge base could enter the inference data into the database. Experimental data were composed of normal chromosome of 2,736 patients'cases and abnormal chromosomes of 259 patients'cases that have been obtained from GTG-banding metaphase peripheral blood and amniotic fluid samples. The complete system provides variously morphological information by analysis of normal or abnormal chromosomes and it also has the advantage of being able to consult with user on chromosome analysis and diagnosis.

• Journal of Information Processing Systems
• /
• 제9권1호
• /
• pp.1-30
• /
• 2013

The capitalization of know-how, knowledge management, and the control of the constantly growing information mass has become the new strategic challenge for organizations that aim to capture the entire wealth of knowledge (tacit and explicit). Thus, knowledge mapping is a means of (cognitive) navigation to access the resources of the strategic heritage knowledge of an organization. In this paper, we present a new mapping approach based on the Boolean modeling of critical domain knowledge and on the use of different data sources via the data mining technique in order to improve the process of acquiring knowledge explicitly. To evaluate our approach, we have initiated a process of mapping that is guided by machine learning that is artificially operated in the following two stages: data mining and automatic mapping. Data mining is be initially run from an induction of Boolean case studies (explicit). The mapping rules are then used to automatically improve the Boolean model of the mapping of critical knowledge.

• 한국간호교육학회지
• /
• 제19권3호
• /
• pp.307-319
• /
• 2013

Purpose: The purpose of this study was to review nursing studies with regard to simulation- based learning in Korea. Methods: This systematic review examines the literature on simulation in nursing education from 2003 to 2012. The electronic databases reviewed included: RISS, the National Assembly Library, the National Library of Korea, and major nursing journal databases in Korea. The MeSH search terms included nursing, simulation, simulator, and standardized patient. Results: In total, 52 studies were included in the literature review. We included 21 quasi-experimental studies and 25 studies using high-fidelity simulation. They included knowledge and problem-solving ability in the cognitive domain; self efficacy, learning satisfaction, interpersonal relationships and communication, and confidence in the affective domain; and clinical performance ability and learning performance evaluation in the psychomotor domain. This systematic literature review revealed that simulation is useful in nursing education but uncovered a gap in the literature pertaining to the transfer of knowledge to performance and how to learn from cognitive reflection. Conclusions: This result suggests that it is necessary to conduct additional research on the cognitive learning process and transition to performance.

• 한국수학교육학회지시리즈A:수학교육
• /
• 제41권3호
• /
• pp.233-256
• /
• 2002

This study investigated school mathematics curriculum of England, newly revised in 1998, focused on the 'number and algebra' domain among three major domains of the English curriculum. On the basis of its understanding, this domain was compared and analyzed with school mathematics curriculum of Korea. In doing so, this study explored its plans and procedures and established a frame of comparison for the curriculums between the two countries. The structure of the National Curriculum in England is composed of programmes of study and attainment targets. The former sets out what should be taught in mathematics at key stages 1, 2, 3, and 4 and provides the basis for planning schemes of work, and the latter sets out the knowledge, skills, and understanding that pupils of different abilities and matures are expected to have by the end of each key stage. Attainment targets are composed of eight levels and an additional level of increasing difficulty. According to the results of the present study, Korea focuses on the formal and systematic mathematical knowledge on the basis of sound understanding of certain mathematical terms or concepts. On the other hand, England tends to deal with numbers more flexibly and naturally through the aquisition of mental methods, calculator use methods, etc, and emphasizes that mathematics be realistic and useful in solving a diverse number of problems confronted in everyday life.

• 한국생물정보학회:학술대회논문집
• /
• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
• /
• pp.86-94
• /
• 2003

Electronically available biological literature has been accumulated exponentially in the course of time. So, researches on automatically acquiring knowledge from these tremendous data by text mining technology become more and more prosperous. However, most of the previous researches are technology oriented and are not well focused in practical extraction target, hence result in low performance and inconvenience for the bio-researchers to actually use. In this paper, we propose a more biology oriented target domain specific text mining system, that is, POSTECH bio-text mining system (POSBIOTM), for signal transduction pathway extraction, especially for G protein-coupled receptor (GPCR) pathway. To reflect more domain knowledge, we specify the concrete target for pathway extraction and define the minimal pathway domain ontology. Under this conceptual model, POSBIOTM extracts interactions and entities of pathways from the full biological articles using a machine learning oriented extraction method and visualizes the pathways using JDesigner module provided in the system biology workbench (SBW) [14]

• 한국산학기술학회:학술대회논문집
• /
• 한국산학기술학회 2003년도 Proceeding
• /
• pp.57-64
• /
• 2003

Achieving the beneficiary goal of recent discovery in human genome project still needs a way to retrieve and analyze the exponentially expanding bio-related information. Research on bio-related fields naturally applies knowledge discovered to the current problem and make inferences to extract new information where shared concepts and data containing information need to be defined and used in a coherent way. In such a professional domain, while the need to help users reduce their work and to improve search results has been emerged. methods for systematic retrieval and adequate exchange of relevant information are still in their infancy. The design of our system aims at improving the quality of information retrieval in a professional domain by utilizing both corpus-based and concept-based ontology. Meta-rules of helping users to make an adequate query are formed into an ontology in the domain. The integration of those knowledge permits the system to retrieve relevant information in a more semantic and systematic fashion. This work mainly describes the query models with details of GUI and a secondary query generation of the system.

• ETRI Journal
• /
• 제43권6호
• /
• pp.966-977
• /
• 2021

Filterbank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) is an attractive alternative to the orthogonal frequency division multiplexing (OFDM) modulation technique. In comparison with OFDM, the FBMC-OQAM signal has better spectral confinement and higher spectral efficiency and tolerance to synchronization errors, primarily due to per-subcarrier filtering using a frequency-time localized prototype filter. However, the filtering process introduces intrinsic interference among the symbols and complicates channel estimation (CE). An efficient way to improve the CE in FBMC-OQAM is using a technique known as windowed frequency domain averaging (FDA); however, it requires a priori knowledge of the window length parameter which is set based on the channel's frequency selectivity (FS). As the channel's FS is not fixed and not a priori known, we propose a k-nearest neighbor-based machine learning algorithm to classify the FS and decide on the FDA's window length. A comparative theoretical analysis of the mean-squared error (MSE) is performed to prove the proposed CE scheme's effectiveness, validated through extensive simulations. The adaptive CE scheme is shown to yield a reduction in CE-MSE and improved bit error rates compared with the popular preamble-based CE schemes for FBMC-OQAM, without a priori knowledge of channel's frequency selectivity.