• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.362-369
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• 2014

This study aimed to propose an accurate diagnostic method for osteoporosis by realizing a computer-aided diagnosis system with the application of the statistical analysis of texture features using digital images of lateral lumbar spine of patients with osteoporosis and providing reliable supplementary diagnostic information by model experimental research for early diagnosis of diseases. For these purposes, digital images of lateral lumbar spine of normal individuals and patients with osteoporosis were used in the experiments, and the values of statistical texture features on the set ROI were expressed in six parameters. Among the texture feature values of the six parameters of osteoporosis, the highest and lowest recognition rates of 95 and 80% were shown in average gray level and uniformity, respectively. Moreover, all the six parameters showed recognition rates of over 80% for osteoporosis: 82.5% in average contrast, 90% in smoothness, 87.5% in skewness, and 87.5% in entropy. Therefore, if a program developing into a computer-aided diagnosis system for medical images is coded based on the results of this study, it is considered possible to be applied to preliminary diagnostic data for automatic detection of lesions and disease diagnosis using medical images, to provide information for definite diagnosis of diseases, to diagnose by limited device, and to be used to shorten the time to analyze medical images.

• The KIPS Transactions:PartD
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• v.12D no.4 s.100
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• pp.583-588
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• 2005

Being able to resolve huge problems deriving from integration of information systems in-house or business to business, the web service that uses the XML standard technology has recently taken a quick dominance the next generation e-business bases. It's one constant concern how to integrate, change, and maintain such systems as based on certain technologies according to the changes to information technology, which is on the ongoing process of evolution. To help solve those problems, OMG suggested a new software architecture called MDA(Model Driven Architecture). MDA runs a process that establishes a platform independent model(PIM), which is an analysis model used as part of the existing development procedures, and automatically converts it into a platform specific model(PSM), a design model, based on the established PIM. Such automatic conversion has lots of benefits including easy support for diverse platforms, reducing the coding time that usually consume a great deal of the developer's effort, and facilitating quality control in the aspect of development processes. By applying the MDA development process to a new web service development, you can choose web service as the target platform at the PIM of MDA and express PSM with a web service model, WSDL. This study set out to classify the web service development or integration processes by the provider md requester to identify the types of web service development processes, and to apply the MDA development process to web service development, thus suggesting a new kind of web service development process that can be referred to by both the web service provider and requester.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.461-470
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• 2023

While speech animation generation employing deep learning has been actively researched for English, there has been no prior work for Korean. Given the fact, this paper for the very first time employs supervised deep learning to generate Korean speech animation. By doing so, we find out the significant effect of deep learning being able to make speech animation research come down to speech recognition research which is the predominating technique. Also, we study the way to make best use of the effect for Korean speech animation generation. The effect can contribute to efficiently and efficaciously revitalizing the recently inactive Korean speech animation research, by clarifying the top priority research target. This paper performs this process: (i) it chooses blendshape animation technique, (ii) implements the deep-learning model in the master-servant pipeline of the automatic speech recognition (ASR) module and the facial action coding (FAC) module, (iii) makes Korean speech facial motion capture dataset, (iv) prepares two comparison deep learning models (one model adopts the English ASR module, the other model adopts the Korean ASR module, however both models adopt the same basic structure for their FAC modules), and (v) train the FAC modules of both models dependently on their ASR modules. The user study demonstrates that the model which adopts the Korean ASR module and dependently trains its FAC module (getting 4.2/5.0 points) generates decisively much more natural Korean speech animations than the model which adopts the English ASR module and dependently trains its FAC module (getting 2.7/5.0 points). The result confirms the aforementioned effect showing that the quality of the Korean speech animation comes down to the accuracy of Korean ASR.