• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.557-568
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• 2008

An ontology as the core element of Semantic Web is a formal specification of a conceptualization of shared domain knowledge. The use of well-defined ontologies can increase the quality of interoperable information systems in the area of Semantic Web. However, in practice, it is not easy to develop high-quality ontologies which have no errors. Therefore, with methodologies for ontology design, various methods or tools for ontology analysis supporting for error-detection might be very helpful for ontology developers. In this paper, we propose a novel approach for analyzing the core constructs of ontology based on the Formal Concept Analysis and develop a tool that supports error-checking ontologies. Our approach can serve not only as a guidance to modify the existing ontologies, but also as a valuable tool in developing high-quality ontologies.

• Journal of Bio-Environment Control
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• v.12 no.1
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• pp.30-37
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• 2003

An expert system was developed for the stress diagnosis of cucumber and tomato using FoxPro. The principle points in building the system were integration with Korean, effective processing of mass information, and easy access for non-experts such as farmers. The method of inferencing was forward chaining based on pattern matching. Knowledge base was expressed with IF∼THEN rules and was expressed in the form of tree. Also, the expert system was designed so that additions and modifications of all information could easily be performed on windows. The results tested by farmers with the developed system showed that the expert system was reliable for the practical use. It was expected the expert system could be directly applied to the stress diagnosis of other vegetable plants by modifying only data bases.

• The KIPS Transactions:PartD
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• v.14D no.5
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• pp.545-554
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• 2007

The user authentication and authorization in the current home network system almost works at home and home users, sometimes novice, should manage the system directly. This situation can make much of troubles, sometimes cause some suity problems. Moreover, the system costs high to build up, demands special user knowledge to maintain. In this paper, we propose the user authentication and authorization system based on remote management server to solve the problems, designed and implemented the system. To verify the system performance and function, we built a demo system for information appliances. The results of the test, the authentication and authorization function works well and reliably.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.2163-2170
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• 2009

We present an automated, energy minimized-based method for Lung parenchyma segmenting Chest Computed Tomography(CT) datasets. Deformable model is used for energy minimized segmentation. Quantitative knowledge including expected volume, shape of Chest CT provides more feature constrain to diagnosis or surgery operation planning. Segmentation subdivides an lung image into its consistent regions or objects. Depends on energy-minimizing, the level detail image of subdivision is carried. Segmentation should stop when the objects or region of interest in an application have been detected. The deformable model that has attracted the most attention to date is popularly known as snakes. Snakes or deformable contour models represent a special case of the general multidimensional deformable model theory. This is used extensively in computer vision and image processing applications, particularly to locate object boundaries, in the mean time a new type of external force for deformable models, called gradient vector flow(GVF) was introduced by Xu. Our proposed algorithm of deformable model is new external energy of GVF for exact segmentation. In this paper, Clinical material for experiments shows better results of proposal algorithm in Lung parenchyma segmentation on Chest CT.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.571-572
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• 2017

The blockchain technology that implements electronic money uses decentralized computing and all transactions in a blockchain are open to everyone. This technique seems to guarantee anonymity by performing the transaction on the address instead of the user, but by using direction acyclic graph based on the transaction graph, the privacy problem is caused by tracking the addresses. In this paper, we analyze various techniques for centralized processing which makes it difficult to find the relevance on the graph in order to protect the privacy in the block chain technology. We also analyze the techniques of anonymizing in a distributed way to enhance privacy. Using the zero knowledge proof scheme guarantees full distributed anonymity but requires more computation and storage space, and various techniques to make this efficient are proposed. In this paper, we propose a privacy protection scheme of blockchain technology to integrate existing privacy protection techniques into a blockchain technology and perform it more efficiently with a centralized or decentralized technique.

• Journal of KIISE
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• v.43 no.1
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• pp.71-79
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• 2016

Disambiguation of homographs is an important job in Korean semantic processing and has been researched for long time. Recently, machine learning approaches have demonstrated good results in accuracy and speed. Other knowledge-based approaches are being researched for untrained words. This paper proposes a hybrid method based on the machine learning approach that uses a lexical semantic network. The use of a hybrid approach creates an additional corpus from subcategorization information and trains this additional corpus. A homograph tagging phase uses the hypernym of the homograph and an additional corpus. Experimentation with the Sejong Corpus and UWordMap demonstrates the hybrid method is to be effective with an increase in accuracy from 96.51% to 96.52%.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.11
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• pp.339-344
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• 2020

During COVID-19, education industry is organizing the concept of 'Edutech', which has evolved one step further from the existing e-Learning, by introducing various intelligent information technologues based on the core technology of the 4th industrial revolution and spreading it through diverse contents. Meanwhile, each industries are creating new industries by applying new technology to existing businesses and ask for needs of cultivating human resources who understand the existing traditional ICT technology and industrial business which can solve a newly rising problems. However, it is difficult to build contents for cultivating such human resources with the existing e-learning of transferring knowledge by one-way or some two-way commnication system which has established some interactive conversational system. Accordingly, this study conducted a research on a cooperative e-learning system that enables educators to communicate with learners in real time and allows problem-solving education based on the existing two-way communication system. As a result, frame for contents and prototype was developedp and artially applied to the actual class and conducted an efficiency analysis, which resulted in the validation of being applied to the actual class as a simulation-based cooperative content.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.1059-1062
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• 2009

As the electronic processing of music gradually is developed, there has been growing interest in automatical input of music. As a result, various researches which input music in the computer has been studied. However, previous studies have drawbacks that only the experts can do it. In other words, if beginners would like to use traditional production program of music scores than prior knowledge is required. To resolve this, we propose system painting music scores automatically using a bandwidth of soundsource, after extracting the voice sounds created by amateurs. The System provides amateurs with convenience so that they can compose. As well as, the System provides the ability to play music that produced by the computer. By using the system, amateurs can compose using voice and simple system handling. And, they can make a music that plays desired instruments.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.247-253
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• 2008

Web 2.0 and Semantic Web technology will be merged to be a next generation Web that leads presentation-oriented Web to data-centric Web. In the next generation Web. semantic processing. Web Platform, and data fusion are most important technology factors. Resolving the Link Rot is the one of the essential technologies to enable these features. The Link Rot causes not only simple annoyances to users but also more serious problems including data integrity. loss of knowledge. breach of service. and so forth. We have suggested a new XRI-based persistent Web link architecture to cure the Link Rot that has been considered as a deep-seated Problem of the Web. The Proposed architecture is based on the XRI suggested by OASIS and it is designed to support a persistent link by using URL rewriting. Since the architecture is designed as a server-side technology, it is superior to existing research especially in Interoperability. Transparency and Adoptability. In addition to this, the architecture provides a metadata identification to be used fer context-aware link resolution.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.374-376
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• 2021

For the diagnosis of cancer-related diseases in clinical practice, pathological examination using biopsy is essential after basic diagnosis using imaging equipment. In order to proceed with such a biopsy, the assistance of an oncologist, clinical pathologist, etc. with specialized knowledge and the minimum required time are essential for confirmation. In recent years, research related to the establishment of a system capable of automatic classification of cancer cells using artificial intelligence is being actively conducted. However, previous studies show limitations in the type and accuracy of cells based on a limited algorithm. In this study, we propose a method to identify a total of 4 cancer cells through a convolutional neural network, a kind of deep learning. The optical images obtained through cell culture were learned through EfficientNet after performing pre-processing such as identification of the location of cells and image segmentation using OpenCV. The model used various hyper parameters based on EfficientNet, and trained InceptionV3 to compare and analyze the performance. As a result, cells were classified with a high accuracy of 96.8%, and this analysis method is expected to be helpful in confirming cancer.