• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.95-103
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• 1996

This paper describes a computer aided design system for spur and helical gears. To establish the appropriate program, an integrate approach based on a rule-base system was adopted. This system is implemented on the personal computer and its environment is a commercial CAD package called AutoCAD. This system includes a main program and five sub-modules such as data input module, tooth profile drawing module, strength calculation module, and drawing edit module. In the main program, all the sub-modules are loaded and the type of gear and tooth profile are selected. In the data input module, the variables which are necessary to the design of gear are selected from the database. In the drawing module, from the calculated results, the required gear tooth is produced on the screen. The developed system that aids gear designer provides powerful capabilities for gear design.

• Journal of Physiology & Pathology in Korean Medicine
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• v.24 no.5
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• pp.758-769
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• 2010

This is a preliminary study for examining the identity issue of the current Traditional Korean Medicine(TKM). In order to examine the identity issue, it is necessary to understand "what" current TKM is. The current TKM has been formed in the complicated historical settings and the newly formed academic geography of modern times, completely different from those of the traditional era. This paper took diachronic and synchronic approaches in order to understand the current TKM. In the process of modernization and scientization of the TKM-which had begun in the early twentieth century-the western medical knowledge merged into the TKM. Also, as the College education of the TKM began after the Liberation from the Japanese colonial rule, the TKM scholars accepted the western medical department system to develop the TKM into professional knowledge. Meanwhile, since the late 1970s, the TKM has been influenced by the modern Traditional Chinese Medicine (TCM), and the TCM knowledge also merged into the TKM. And recently, the research methodology of the complementary and alternative medicine (CAM), and the clinical research technique of the western medicine-like Evidence based Medicine (EBM)-are affecting the scientization and clinical study of the TKM. The current TKM has been formed as a result of the hybridization of these different knowledges. These changes in the TKM were inevitable for the survival of it in the fast changing world. But these changes brought with them problems. Among those, the identity issue is the most important and crucial.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.56-64
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• 2018

In recent years, imbalanced data is one of the most important and frequent issue for quality control in industrial field. As an example, defect rate has been drastically reduced thanks to highly developed technology and quality management, so that only few defective data can be obtained from production process. Therefore, quality classification should be performed under the condition that one class (defective dataset) is even smaller than the other class (good dataset). However, traditional multi-class classification methods are not appropriate to deal with such an imbalanced dataset, since they classify data from the difference between one class and the others that can hardly be found in imbalanced datasets. Thus, one-class classification that thoroughly learns patterns of target class is more suitable for imbalanced dataset since it only focuses on data in a target class. So far, several one-class classification methods such as one-class support vector machine, neural network and decision tree there have been suggested. One-class support vector machine and neural network can guarantee good classification rate, and decision tree can provide a set of rules that can be clearly interpreted. However, the classifiers obtained from the former two methods consist of complex mathematical functions and cannot be easily understood by users. In case of decision tree, the criterion for rule generation is ambiguous. Therefore, as an alternative, a new one-class classifier using hyper-rectangles was proposed, which performs precise classification compared to other methods and generates rules clearly understood by users as well. In this paper, we suggest an approach for improving the limitations of those previous one-class classification algorithms. Specifically, the suggested approach produces more improved one-class classifier using hyper-rectangles generated by using Gaussian function. The performance of the suggested algorithm is verified by a numerical experiment, which uses several datasets in UCI machine learning repository.

• The Journal of the Acoustical Society of Korea
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• v.29 no.6
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• pp.402-409
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• 2010

In this paper, we propose an efficient integrated suppression algorithm based on combined power of acoustic echo and background noise. The proposed method combines the acoustic echo and noise power by the weighting parameter derived from the decision rule based on the estimated echo to noise power ratio. Therefore, in the proposed approach, the acoustic echo and noise signal are able to be reduced through only one suppression filter based on the estimated combined power. The proposed unified structure improves the problems of the residual echo and noise resulted from the conventional unified structure where the noise suppression (NS) operation is placed after the acoustic echo suppression (AES) algorithm or vice versa. The performance of the proposed algorithm is evaluated by the objective test under various environments and yields better results compared with the conventional scheme.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.202-214
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• 2005

The semantic web is the web paradigm that represents not general link of documents but semantics and relation of document. In addition it enables software agents to understand semantics of documents. We propose a semantic search based on inference with ontologies, which has the following characteristics. First, our search engine enables retrieval using explicit ontologies to reason though a search keyword is different from that of documents. Second, although the concept of two ontologies does not match exactly, can be found out similar results from a rule based translator and ontological reasoning. Third, our approach enables search engine to increase accuracy and precision by using explicit ontologies to reason about meanings of documents rather than guessing meanings of documents just by keyword. Fourth, domain ontology enables users to use more detailed queries based on ontology-based automated query generator that has search area and accuracy similar to NLP. Fifth, it enables agents to do automated search not only documents with keyword but also user-preferable information and knowledge from ontologies. It can perform search more accurately than current retrieval systems which use query to databases or keyword matching. We demonstrate our system, which use ontologies and inference based on explicit ontologies, can perform better than keyword matching approach .

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.137-146
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• 2008

Fault localization plays a significant role in enormous distributed system because it can identify root cause of observed faults automatically, supporting self-managing which remains an open topic in managing and controlling complex distributed systems to improve system reliability. Although many Artificial Intelligent techniques have been introduced in support of fault localization in recent research especially in increasing complex ubiquitous environment, the provided functions such as diagnosis and prediction are limited. In this paper, we propose fault localization for self-managing in performance evaluation in order to improve system reliability via learning and analyzing real-time streams of system performance events. We use probabilistic reasoning functions based on the basic Bayes' rule to provide effective mechanism for managing and evaluating system performance parameters automatically, and hence the system reliability is improved. Moreover, due to large number of considered factors in diverse and complex fault reasoning domains, we develop an efficient method which extracts relevant parameters having high relationships with observing problems and ranks them orderly. The selected node ordering lists will be used in network modeling, and hence improving learning efficiency. Using the approach enables us to diagnose the most probable causal factor with responsibility for the underlying performance problems and predict system situation to avoid potential abnormities via posting treatments or pretreatments respectively. The experimental application of system performance analysis by using the proposed approach and various estimations on efficiency and accuracy show that the availability of the proposed approach in performance evaluation domain is optimistic.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.122-131
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• 2010

This paper introduces the concept of a virtual ecosystem and reports the following three mathematical approaches that could be widely used to construct such an ecosystem, along with examples: (1) a molecular dynamics simulation approach for animal flocking behavior, (2) a stochastic lattice model approach for termite colony behavior, and (3) a rule-based cellular automata approach for biofilm growth. The ecosystem considered in this study consists of artificial organisms and their environment. Each organism in the ecosystem is an agent that interacts autonomously with the dynamic environment, including the other organisms within it. The three types of model were successful to account for each corresponding ecosystem. In order to accurately mimic a natural ecosystem, a virtual ecosystem needs to take many ecological variables into account. However, doing so is likely to introduce excess complexity and nonlinearity in the analysis of the virtual ecosystem's dynamics. Nonetheless, the development of a virtual ecosystem is important, because it can provide possible explanations for various phenomena such as environmental disturbances and disasters, and can also give insights into ecological functions from an individual to a community level from a synthetic viewpoint. As an example of how lower and higher levels in an ecosystem can be connected, this paper also briefly discusses the application of the second model to the simulation of a termite ecosystem and the influence of climate change on the termite ecosystem.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.113-130
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• 2002

In this paper, we developed DNL(Dynamic Network Loading) model based on Moving cell theory to analyze the dynamic characteristics of traffic flow in congested network. In this paper vehicles entered into link at same interval would construct one cell, and the cells moved according to Cell following rule. In the past researches relating to DNL model a continuous single link is separated into two sections such as running section and queuing section to describe physical queue so that various dynamic states generated in real link are only simplified by running and queuing state. However, the approach has some difficulties in simulating various dynamic flow characteristics. To overcome these problems, we present Moving cell theory which is developed by combining Car following theory and Lagrangian method mainly using for the analysis of air pollutants dispersion. In Moving cell theory platoons are represented by cells and each cell is processed by Cell following theory. This type of simulation model is firstly presented by Cremer et al(1999). However they did not develop merging and diverging model because their model was applied to basic freeway section. Moreover they set the number of vehicles which can be included in one cell in one interval so this formulation cant apply to signalized intersection in urban network. To solve these difficulties we develop new approach using Moving cell theory and simulate traffic flow dynamics continuously by movement and state transition of the cells. The developed model are played on simple network including merging and diverging section and it shows improved abilities to describe flow dynamics comparing past DNL models.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1652-1660
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• 2009

The main objective of this research is to build a behavior prediction model of gameplay for MMO (Massively Multiplayer Online) game using the GOMS analysis method. GOMS analysis is an observational approach to HCI(Human Computer Interaction) to model and predict behaviors of a human operator in a highly interactive task. In this research, a pilot experiment was previously conducted with three skilled gamers. The gamers were provided with the goals and operators through the user's guide book, and they found methods and selection rules while being observed. Based on the results obtained from the pilot study, this research was expanded and the model was further tested with 30 subjects (game experts). The new outcomes revealed that the relevance of GOMS analysis for predicting selection rules is 96.25% according to the degree of abstraction and 77.35% based on the degree of complexity. This research will provide game designers with a new testing mechanism in the early development stages, in order to improve the quality of the game product.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.347-357
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• 2003

The web is an important source of information and most of Web applications are based on form documents in HTML-based form documents only play a role as user interfaces, and they do not involve the procedures or rules if business process which form document designers assume. However, from documents imply methods for treating documents, and these embedded procedural knowledge can be utilized.actively in automation of business process. In this respect, we Investigate the activeness of documents with cognitive science to automate business processes based on from documents. Through this, we have a new concept and applicability of active documents. Our active documents include business rules and declarative knowledge to support the automation of document processing. Also, we propose a processing framework for the active documents. The framework has two phases: build-time and run-time. in order to demonstrate the usefulness of the proposed framework, a prototype called ActiveForm is designed and implemented for requisition processing them in an inference engine can enhance the intelligence of Internet applications.