• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.97-104
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• 2017

In semantic information retrieval, we first need to build domain ontology and second, we need to convert the users' search keywords into a standard query such as SPARQL. In this paper, we propose a method that can automatically convert the users' search keywords into the SPARQL queries. Furthermore, our method can ensure effective performance in a specific domain such as law. Our method constructs the keyword history ontology by associating each keyword with a series of information when there are multiple keywords. The constructed ontology will convert keyword history ontology into SPARQL query. The automatic transformation method of SPARQL query proposed in the paper is converted into the query statement that is deemed the most appropriate by the user's intended keywords. Our study is based on the existing legal ontology constructions that supplement and reconstruct schema and use it as experiment. In addition, design and implementation of a semantic search tool based on legal domain and conduct experiments. Based on the method proposed in this paper, the semantic information retrieval based on the keyword is made possible in a legal domain. And, such a method can be applied to the other domains.

• Journal of Power Electronics
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• v.9 no.2
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• pp.224-231
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• 2009

The induction motor rotor fault diagnosis system using current signals, which are measured using an axis-transformation method, is presented in this paper. In inverter-fed motor drives, unlike line-driven motor drives, the stator currents are rich in harmonics; therefore fault diagnosis using stator current is not trivial. The current signals for rotor fault diagnosis need precise and high resolution information, which means the diagnosis system demands additional hardware such as a low pass filter, high resolution ADC, and encoder, etc. The proposed axis-transformation method with encoder and without encoder is expected to contribute to a low cost fault diagnosis system in inverter-fed motor drives without the need for any additional hardware. In order to confirm the validity of the developed algorithms, various experiments for rotor faults are tested and the line current spectrum of each faulty situation using Park transformation is compared with the results obtained from fast Fourier transforms.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.225-230
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• 2009

We propose a template matching method for component inspection of SMD assembly system. To discriminate wrong assembled components, the input image of component is matched with its standard image by template matching algorithm. For a fast inspection system, the calculation time of matching algorithm should be reduced. Since the standard images of all components located in a PCB are stored in computer, it is desirable to reduce the memory size of standard image. We apply the discrete wavelet transformation to reduce the image size as well as the calculation time. Only 7% memory of the BMP image is used to discriminate goodness or badness of components assembly. Comparative results are presented to verify the usefulness of the proposed method.

• MALSORI
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• no.58
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• pp.45-66
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• 2006

In this paper, a rule-based (transformation-based) NE recognition system is proposed. This system uses Brill's rule inference approach. The performance of the rule-based system and IdentiFinder, one of most successful stochastic systems, are compared. In the baseline case (no punctuation and no capitalisation), both systems show almost equal performance. They also have similar performance in the case of additional information such as punctuation, capitalisation and name lists. The performances of both systems degrade linearly with the number of speech recognition errors, and their rates of degradation are almost equal. These results show that automatic rule inference is a viable alternative to the HMM-based approach to NE recognition, but it retains the advantages of a rule-based approach.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.442-445
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• 2002

We present an algorithm for automatic anatomically adaptive image enhancement of digital chest radiographs. Chest images were exposed using digital radiography system with a 0.143 mm pixel pitch, l4-bit gray levels, and 3121 ${\times}$ 3121 matrix size. A chest radiograph was automatically divided into two classes (lung field and mediastinum) by using a maximum likelihood method. Each pixel in an image was processed using fuzzy domain transformation and enhancement of both the dynamic range and local gray level variations. The lung fields were enhanced appropriately to visualize effectively vascular tissue, the bronchus, and lung tissue, etc as well as pneumothorax and other lung diseases at the same time with the desired mediastinum enhancement. A prototype implementation of the algorithm is undergoing trials in the clinical routine of radiology department of major Korean hospital.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3121-3144
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• 2023

As interest in the metaverse has grown, there has been a demand for avatars that can represent individual users. Consequently, research has been conducted to reduce the time and cost required for the current 3D human modeling process. However, the recent automatic generation of 3D humans has been focused on creating avatars with a realistic human form. Furthermore, the existing methods have limitations in generating avatars with imbalanced or unrealistic body shapes, and their utilization is limited due to the absence of datasets. Therefore, this paper proposes a new framework for automatically transforming and creating stylized 3D avatars. Our research presents a definitional approach and methodology for creating non-realistic character avatars, in contrast to previous studies that focused on creating realistic humans. We define a new shape representation parameter and use a deep learning-based method to extract character body information and perform automatic template mesh transformation, thereby obtaining non-realistic or unbalanced human meshes. We present the resulting outputs visually, conducting user evaluations to demonstrate the effectiveness of our proposed method. Our approach provides an automatic mesh transformation method tailored to the growing demand for avatars of various body types and extends the existing method to the 3D cartoon stylized avatar domain.

• Journal of Korea Multimedia Society
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• v.11 no.9
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• pp.1286-1295
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• 2008

Colors of 2D animation characters are generally assigned by art directors' subjective color sense. Even same characters should be colored differently according to the mood of animation scenes. In this study, we introduce the model for automatic color transformation of characters by using neural network. It can not only create automatically colors of characters which are good matched with 2D animation scenes but also reproduce art directors' subjective color sense. Specifically, this neural network model is initially made to learn the patterns of color change between basic colors of characters and colors of characters in various scene. Then if you know basic colors of some characters, you can derive colors of characters under other light source environments using the learned neural network. Subjective ratings(which is adopted to verify the proposed model) by color experts on the automatically transformed colors showed that the colors created by the model tended to be evaluated natural.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.228-234
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• 2023

As the increasing demand for high-quality software, there is huge requiring for quality certification of international standards, industrial functional safety (IEC 61508), automotive (ISO 26262), embedded software guidelines for weapon systems, etc., in the industry. Software companies are very difficult to systematically acquire the quality certification in terms of cost and manpower of Startup, venture small-sized companies. For their companies one test case automatic generation is considered as a core technique to evaluate or improve software quality. This paper proposes a test case automatic generation method based on the design decision table for system and software design verification. We apply the proposed method with OMG's standard techniques of metamodel and model transformation for automatically generating test cases. To do this, we design the metamodels of design decision table (Model) and test case document (Text) and define model transformation to automatically generate test cases, which will expect to easily work MC/DC coverage.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.12
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• pp.84-91
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• 2004

A CCD camera with a laser stripe was applied to realize the automatic weld seam tracking in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noises such as spatter and arc tight. For this reason, it was complemented with adaptive Hough transformation to have an on-line processing ability for scanning specific weld points. The adaptive Hough transformation was used to extract laser stripes and to obtain specific weld points. The 3-dimensional information obtained from the vision system made it possible to generate the weld torch path and to obtain the information such as width and depth of weld line. In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• Journal of Welding and Joining
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• v.19 no.6
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• pp.600-607
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• 2001

A CCD camera with a laser stripe was applied to realize the automatic weld seam tracking in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noises such as spatter and arc light. For this reason. it was complemented with adaptive Hough transformation to have an on-line processing ability for scanning specific weld points. The adaptive Hough transformation was used to extract laser stripes and to obtain specific weld points. The 3-dimensional information obtained from the vision system made it possible to generate the weld torch path and to obtain the information such as width and depth of weld line. We controled the wire feeding rate using informations of weld line.