• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.217-222
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• 2009

Priority queues can be used in applications such as scheduling, sorting, retrival based on a priority like gene searching, shortest paths computation. This paper proposes a data structure using array representation for double-ended priority queue in which insertion and deletion takes O(1) amortized time and O(logn) time, respectively. To the author's knowledge, all the published array-based data structures for double ended priority queue support O(logn) time insertion and deletion operations.

• Journal of the Korean Society of Safety
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• v.11 no.3
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• pp.104-111
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• 1996

A system was developed that could predict hazardous states for safe operation of chemical plants. This system aimed to prevent hazards of chemical processes from misoperation before real operation. In this study, a data base was organized which consisted of all hazards in the chemical processes. The structure of process was represented by signed direct graph(SDG) of NODEs and ARCs. Each NODE and ARC have property variables ; connected structure and state of processes etc. The hazards that could be occurred in processes were divided into two classes ; one is by operation of unit and the other is by hazardous materials. Using Hazardous States Transition Network, we could recognize transition progress of process states.

• Journal of Korean Library and Information Science Society
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• v.39 no.4
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• pp.283-304
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• 2008

This is to develop Intelligent Retrieval System which can automatically present early query's category terms(association terms connected with knowledge structure of relevant terminology) through learning function and it changes searching form automatically and runs it with association terms. For the reason, this theoretical study of Intelligent Automatic Indexing System abstracts expert's index term through learning and clustering algorism about automatic classification, text mining(categorization), and document category representation. It also demonstrates a good capacity in the aspects of expense, time, recall ratio, and precision ratio.

• Journal of The Korean Association For Science Education
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• v.25 no.6
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• pp.698-709
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• 2005

When modeling students' conceptual understanding, there are several different frameworks, among which are the alternative conception framework and the mental model framework, which converge to suggest a form of knowledge representation. However, little research has explained how they are different from each other and from memory. The purpose of this study was to develop a new mental model theory that integrates the different terminologies and their background theories, which refer to students' ideas not only in science education, but also in other research areas. For this purpose, at first, we compared different terminologies including alternative conception, p-prim, and mental models, and the underlying theories used for representing students' ideas in learning science. Through such comparison, we tried to find the relationship among them. We reviewed related literature and synthesized the results from both cognitive science (related research areas) and science education approaches, especially, Vosniadou's mental model theory. Based on reviewing previous studies, we have developed a preliminary mental model theory 'an integrated theoretical structure of mental models'. We applied the new mental model theory to interpret data on students' ideas about circular motion from our previous research. We expect our new mental model theory will help us understand how students form their own ideas in science from an integrated perspective.

• The Mathematical Education
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• v.46 no.4
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• pp.371-388
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• 2007

This is a case study trying to understand from the view of affordance which certain three middle school students perceive an activation of previous knowledge in the course of problem solving when they solve algebra word problems with a previous knowledge. The results of this study showed that at first, every subjects perceived the text as affordance which explaining superficial similarities, that is, a working(painting)situation rather than problem structure and then activated the related solution knowledge on the ground of the experience of previous problem solving which is similar to current situation. The subject's applying process for solving knowledge could be arranged largely into two types. The first type is a numeral information connected with the described problem situation or a symbolic representation of mathematical meaning which are the transformed solution applied process with a suitable solution formula to the current problem. This process achieved by constructing a virtual mental model that indicating mathematical situation about the problem when the solver read the problem integrating symbolized information from the described text. The second type is a case that those subjects symbolizing a formal mathematical concept which is not connected with the problem situation about the described numeral information from the applied problem or the text of mathematical meaning, which process is the case to perceive superficial phrases or words that described from the problem as affordance and then applied previously used algorithmatical formula as it was. In conclusion, on the ground of the results of this case study, it is guessed that many students put only algorithmatical knowledge in their memories through previous experiences of problem solving, and the memories are connected with the particular phrases described from the problems. And it is also recognizable when the reflection process which is the last step of problem solving carried out in the process of understanding the problem and making a plan showed the most successful in problem solving.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.43-61
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• 2011

In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker's state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker's personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker's context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker's personal case-base. We convince that the selected case should be the best case depending on context related to decision maker's current status as well as decision maker's requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn't satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker's requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.115-125
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• 2006

A concept hierarchy represents the knowledge with multi-level form, which is very useful to categorize, store and retrieve the data. Traditionally, a concept hierarchy has been built manually by domain experts. However, the manual construction of a concept hierarchy has caused many problems such as enormous development and maintenance costs and human errors such as inconsistency. This paper proposes the automatic creation of concept hierarchies using the predefined hypernym relation. To create the hierarchy automatically, we first eliminate the ambiguity of the senses of data values, and construct the hierarchy by grouping and leveling of the remaining senses. We use the WordNet explanations for multi-meaning word to eliminate the ambiguity and use the WordNet hypernym relations to create multi-level hierarchy structure.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.159-169
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• 1994

In this paper, we develop a prototype of ITS(Intelligent Tutoring Systems) system: UNIX TUTOR. It is designed for the purpose of teaching the UNIX beginners the principal concepts of UNIX and the shell commands using the communication between the student and the system. UNIX TUTOR engages the student in a two-way conversation that is mixed-initiative dialogue and attempts to teach the student UNIX via the Socratic method of guided discovery and the Coaching method interchangeably. And the student model is based on both the overlay model and the buggy model together. Thus TUTOR aims at teaching the students effectively whose levels of learning are different using various explanations which are determined by the student model. Because the knowledge representation for UNIX-TUTOR is based on the frame structure and the production rules it is easy to represent the complicated constructs. UNIX TUTOR is implemented on the SPARC station using X/Motif and C for cp command among 10 ones which were selected.

• Korean Institute of Interior Design Journal
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• v.14 no.2 s.49
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• pp.197-205
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• 2005

In estimating designed architectural buildings, many factors in various design domains such as function, structure, form, environment may be considered and then a building design might be selected or modified as final design from many possible design results. This paper proposed a method to obtain complexity values from two dimensional drawings which are floor plans or elevations. The Complexity values could be turned into esthetic values. The method has been developed based on information theory, shape pattern representation and cognitive theory. Results of measuring complexity value can make the computer evaluate and select final results produced from automatic design processes by the computer That is to say, aesthetic values based on order and chaos can be measured using complexity values and then some results having superior values can be selected as final result. Also some cognitive processes as perception of two dimensional drawings are discussed using shape representations. Aesthetic values could be varied in terms of shape properties such as size, individualities and knowledge as well as order and chaos.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.09a
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• pp.300-324
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• 1995

This research investigates the automatic identification of typical embedded structures in the Integer Programming(IP) models and automatic transformation of the problem to an adequate Lagrangian problem which can provide tight bounds within the acceptable run time. For this purpose, the structural distinctiveness of variables, constants, blocks of terms, and constraint chunks is identified to describe the structure of the IP model. To assist the identification of the structural distinctiveness, the representation by the knowledge based IP model formulator UNIK-IP is adopted. For the reasoning for the structural identification, the bottom-up, top-down, and case-based approaches are proposed. A prototype system UNIK-RELAX is developed to implement the approaches proposed in this research.