• Journal of Korean Medical classics
• /
• v.23 no.1
• /
• pp.59-79
• /
• 2010

Objective : We did a comparative study about characteristics of oriental medical books. As a result, we took notice of classification in the nominal terms by semantic type of UMLS(Unified Medical Language System). By using classified nominal terms, comparative study can be more effectively. So, we selected another oriental medical book and classified nominal terms in it by semantic type of UMLS. By result of classification, we have attempted to study about comparison between oriental medical books and development of medical theories. Method :We have made a comparative study on classification in the nominal terms between "Biwiron(脾胃論)" and "Soayakjeungjikgyeol(小兒藥證直訣)" according to the below the procedure. (1) Making a nominal terms list of "Soayakjeungjikgyeol(小兒藥證直訣)" and grasping contextual meaning of nominal terms of it. (2) Modification and supplementation about semantic type of UMLS for "Soayakjeungjikgyeol(小兒藥證直訣)". Using the modified classification system, we classified nominal terms. After this process, we arranged classified nominal terms by Haansoft Hangul 2007. (3) Comparing classified nominal terms between "Biwiron(脾胃論)" and "Soayakjeungjikgyeol(小兒藥證直訣)". Result : In the "Soayakjeungjikgyeol(小兒藥證直訣)", there are more than 2,519's nominal terms and different categories of semantic type of UMLS classification from "Biwiron(脾胃論)". Through comparison between their classification of nominal terms, we can understand the characteristics of the two and their development of medical theories.

• Journal of Korean Library and Information Science Society
• /
• v.23
• /
• pp.439-469
• /
• 1995

The purpose of this study is to develop a new domestic (national) law classification scheme with universality. An underlying reason for the development of this scheme reset upon the fact that Civil law system, Common law system, Socialistic law system have had difficulties each other and that current classification scheme covering three law systems have not been still in existence. From the comparative discussion of classification schemes that are the representative of each law system, a new national law classification scheme with universality was designed. If law classification scheme have been completeness, this new scheme must be combined with jurisprudence and international law classification scheme which was developed already.

• Journal of Korean Library and Information Science Society
• /
• v.39 no.3
• /
• pp.345-368
• /
• 2008

This study investigated the general problems concerning the subject Computer Science in the KDC(Korean Decimal Classification) 4th edition based on the comparative analysis with DDC, NDC, Disciplinary Classification System of Korean Research Foundation and National Standard Science and Technology Classification and Science and Technology Classification of Korea Science and Engineering Foundation, and suggested some ideas for the improvements of them. The subject of Computer science in the KDC 4th edition will be helpful to be improved to integrate in classes 004-005 now separated into two main classes of 000(004-005) and 500(566) in KDC4, to systematize subdivisions, to add new subjects, to delete and relocate some inappropriate subjects and to add notes.

• Journal of the Korean Society for Library and Information Science
• /
• v.58 no.2
• /
• pp.269-288
• /
• 2024

To structure the KOS registry, it is necessary to select a classification system that suits the characteristics of the collected KOS. This study aimed to classify domestic KOS collected through various classification schems, and based on these results, provide insights for selecting a classification system when structuring the KOS registry. A total of 313 KOS data collected via web searches were categorized using five types of classification systems and a thesaurus, and the results were analyzed. The analysis indicated that for international linkage of the KOS registry, foreign classification systems should be applied, and for optimization with domestic knowledge resources or to cater to domestic researchers, domestic classification systems need to be applied. Additionally, depending on the field-specific characteristics of the KOS, research area KOS should apply classification systems based on academic disciplines, while public sector KOS should consider classification systems based on government functions. Lastly, it is necessary to strengthen the linkage between domestic and international KOS, which also requires the application of multiple classification systems.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.3
• /
• pp.221-227
• /
• 2024

In autonomous navigation systems, the need for fast and accurate image processing using deep learning and advanced sensor technologies is paramount. These systems rely heavily on the ability to process and interpret visual data swiftly and precisely to ensure safe and efficient navigation. Despite the critical importance of such capabilities, there has been a noticeable lack of research specifically focused on ship image classification for maritime applications. This gap highlights the necessity for more in-depth studies in this domain. In this paper, we aim to address this gap by presenting a comprehensive comparative study of ship image classification using two distinct neural network models: the Feedforward Neural Network (FNN) and the Convolutional Neural Network (CNN). Our study involves the application of both models to the task of classifying ship images, utilizing a dataset specifically prepared for this purpose. Through our analysis, we found that the Convolutional Neural Network demonstrates significantly more effective performance in accurately classifying ship images compared to the Feedforward Neural Network. The findings from this research are significant as they can contribute to the advancement of core source technologies for maritime autonomous navigation systems. By leveraging the superior image classification capabilities of convolutional neural networks, we can enhance the accuracy and reliability of these systems. This improvement is crucial for the development of more efficient and safer autonomous maritime operations, ultimately contributing to the broader field of autonomous transportation technology.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.27 no.1
• /
• pp.26-33
• /
• 2019

It is necessary to establish a UAV pilot license and training system because the number of UAV-related accidents has rapidly risen. Most of accidents are caused by the human factors such as the lack of control skill and aviation knowledge. In this paper, we investigate licensing policy of small UAV pilots and examine the level of UAV licensing system and classification criteria based on comparative analysis of national cases such as USA, UK and China. Recently, the Ministry of Land, Infrastructure and Transport Affairs is planning to improve the safety regulation by taking into account the risk level of the licensing system, which has been classified according to the existing weight and commercial purpose. From the comparative analysis, we suggested a improvement policy for UAV licensing system in the view of pilot license segmentation, beyond Visual Line-of-sight flight and high risk UAV for non-commercial.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.3
• /
• pp.27-32
• /
• 2024

Reliable and fine-grained musical metadata are required for efficient search of rapidly increasing music files. In particular, since the primary motive for listening to music is its emotional effect, diversion, and the memories it awakens, emotion classification along with genre classification of music is crucial. In this paper, as an initial approach towards a "ground-truth" dataset for music emotion and genre classification, we elaborately generated a music corpus through labeling of a large number of ordinary people. In order to verify the suitability of the dataset through the classification results, we extracted features according to MPEG-7 audio standard and applied different machine learning models based on statistics and deep neural network to automatically classify the dataset. By using standard hyperparameter setting, we reached an accuracy of 93% for genre classification and 80% for emotion classification, and believe that our dataset can be used as a meaningful comparative dataset in this research field.

• Journal of KIISE:Software and Applications
• /
• v.37 no.2
• /
• pp.155-160
• /
• 2010

This paper proposes a method for Korean comparative sentence classification which is a part of comparison mining. Comparison mining, one area of text mining, analyzes comparative relations from the enormous amount of text documents. Three-step process is needed for comparison mining - 1) identifying comparative sentences in the text documents, 2) classifying those sentences into several classes, 3) analyzing comparative relations per each comparative class. This paper aims at the second task. In this paper, we use transformation-based learning (TBL) technique which is a well-known learning method in the natural language processing. In our experiment, we classify comparative sentences into seven classes using TBL and achieve an accuracy of 80.01%.

• Journal of the Semiconductor & Display Technology
• /
• v.20 no.2
• /
• pp.109-114
• /
• 2021

When we inspect scaffold defect using sight, inspecting performance is decrease and inspecting time is increase. We need for automatically scaffold defect detection method to increase detection accuracy and reduce detection times. In this paper. We produced scaffold defect classification models using densenet, alexnet, vggnet algorithms based on CNN. We photographed scaffold using multi dimension camera. We learned scaffold defect classification model using photographed scaffold images. We evaluated the scaffold defect classification accuracy of each models. As result of evaluation, the defect classification performance using densenet algorithm was at 99.1%. The defect classification performance using VGGnet algorithm was at 98.3%. The defect classification performance using Alexnet algorithm was at 96.8%. We were able to quantitatively compare defect classification performance of three type algorithms based on CNN.

• Communications for Statistical Applications and Methods
• /
• v.18 no.1
• /
• pp.89-102
• /
• 2011

The discretization process that converts continuous attributes into discrete ones is a preprocessing step in data mining such as classification. Some classification algorithms can handle only discrete attributes. The purpose of discretization is to obtain discretized data without losing the information for the original data and to obtain a high predictive accuracy when discretized data are used in classification. Many discretization algorithms have been developed. This paper presents the results of our comparative study on recently proposed representative discretization algorithms from the view point of splitting versus merging and supervised versus unsupervised. We implemented R codes for discretization algorithms and made them available for public users.