• The Journal of the Petrological Society of Korea
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• v.23 no.2
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• pp.145-152
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• 2014

Geological heritages can be defined conveniently as geological records worthy of conservation, and are represented in most cases by geological outcrops. So survey and evaluation of geologic outcrops are necessary for better conservation of geological heritages. As a measure to prevent potential destruction of geological heritages from various development projects, I propose construction of database based on survey and evaluation forms of geological outcrop, which can also be used for environmental impact assessment. The geological survey form consists of survey area, category, subcategory, location, dimension, geologic features, photo, description, and investigator. The evaluation form consists of evaluation category, detailed evaluation, comprehensive evaluation, and evaluation grade. The evaluation category is divided into academic aspect, education effect and landscape. The detailed evaluation items for academic aspects and education effect are representativeness, rarity, diversity and typicality, while those for geomorphology and landscape are peculiarity, aesthetics and naturalness. The evaluation grades are divided into five, where the first grade means a must of conservation.

• Journal of Fashion Business
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• v.27 no.4
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• pp.88-100
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• 2023

This study analyzed the compositional characteristics of fashion videos and the characteristics of fashion design spreading as trends through Subversive Basics. Literature research and case studies were conducted concurrently. Based on the literature review, an analysis method was designed, focusing on the concept of online video content, Subversive Basics, and the video content type. For the case analysis, videos were collected and classified using Subversive Basics as the keyword. The content was observed, and design features were analyzed. Based on the results, the collected videos were classified into tutorial, curation, and creative content types according to their compositional characteristics. Tutorial content emphasizes practical actions that demonstrate how to make or modify clothing, thereby promoting user-generated content for dissemination. Curation contents provide users with style ideas and information about clothing and purchases to encourage clothing purchases and influence purchase decisions that lead to dissemination through clothing consumption and wear. Creative content showcases the process of modifying and creating clothes to enhance understanding and value of creative design. The characteristics of fashion design utilized in these contents include bold designs with high visual effects as the first category, designs that can be easily and quickly modified due to intentional incompleteness as the second category, and prominently featured body-positive, individualistic designs as the third category. The results of this study can be associated with balanced development between basic design elements and personalized unique designs, catering to consumer needs.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.6
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• pp.28-39
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• 2010

The study aims at offering a solution to the problems of transmission delay and data throughput decrease as the number of contending On-Board Units (OBU) increases by applying CSMA medium access control protocol based upon IEEE 802.11p. In a competition-based medium, contention probability becomes high as OBU increases. In order to improve the performance of this medium access layer, the author proposes EDCA which a adaptive adjustment of the Contention Windows (CW) considering traffic density and data type. EDCA applies fixed values of Minimum Contention Window (CWmin) and Maximum Contention Window (CWmax) for each of four kinds of Access Categories (AC) for channel-specific service differentiation. EDCA does not guarantee the channel-specific features and network state whereas it guarantees inter-AC differentiation by classifying into traffic features. Thus it is not possible to actively respond to a contention caused by network congestion occurring in a short moment in channel. As a solution, CWminAS(CWmin Adaptation Scheme) and ACATICT(Adaptive Contention window Adjustment Technique based on Individual Class Traffic) are proposed as active CW control techniques. In previous researches, the contention probabilities for each value of AC were not examined or a single channel based AC value was considered. And the channel-specific demands of IEEE 802.11p and the corresponding contention probabilities were not reflected in the studies. The study considers the collision number of a previous service section and the current network congestion proposes a dynamic control technique ACCW(Adaptive Control of Contention windows in considering the WAVE situation) for CW of the next channel.

• Journal of the Korean Society for Library and Information Science
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• v.39 no.1
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• pp.45-58
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• 2005

This Paper is a comparative study of feature selection methods for Korean web documents clustering. First, we focused on how the term feature and the co-link of web documents affect clustering performance. We clustered web documents by native term feature, co-link and both, and compared the output results with the originally allocated category. And we selected term features for each category using $X^2$, Information Gain (IG), and Mutual Information (MI) from training documents, and applied these features to other experimental documents. In addition we suggested a new method named Max Feature Selection, which selects terms that have the maximum count for a category in each experimental document, and applied $X^2$ (or MI or IG) values to each term instead of term frequency of documents, and clustered them. In the results, $X^2$ shows a better performance than IG or MI, but the difference appears to be slight. But when we applied the Max Feature Selection Method, the clustering Performance improved notably. Max Feature Selection is a simple but effective means of feature space reduction and shows powerful performance for Korean web document clustering.

• Journal of the Korean Society for information Management
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• v.29 no.2
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• pp.155-171
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• 2012

In text categorization, core terms of an input document are hardly selected as classification features if they do not occur in a training document set. Besides, synonymous terms with the same concept are usually treated as different features. This study aims to improve text categorization performance by integrating synonyms into a single feature and by replacing input terms not in the training document set with the most similar term occurring in training documents using Wikipedia. For the selection of classification features, experiments were performed in various settings composed of three different conditions: the use of category information of non-training terms, the part of Wikipedia used for measuring term-term similarity, and the type of similarity measures. The categorization performance of a kNN classifier was improved by 0.35~1.85% in $F_1$ value in all the experimental settings when non-learning terms were replaced by the learning term with the highest similarity above the threshold value. Although the improvement ratio is not as high as expected, several semantic as well as structural devices of Wikipedia could be used for selecting more effective classification features.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.93-105
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• 2016

Among 28 land Categories, 'road' is that most frequently established or transformed. Like that of other 27 land categories, the boundary of road should be defined by boundary making principles and then fixed by cadastral laws. But, some criteria to determine the land boundary, especially in boundary making rule which can be used by geographical features, is confused partly in Land Use Planning stages. Because the purpose of making any rules in fixing road boundary may be misinterpreted, the gap between law and real land boundary can be occurred. Those related rules in determining the land boundary must be improved urgently. Cut surface' or 'slope' should be conformed as a legal term and I suggest that 'Structures' must be changed to 'geographical features'.

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.329-347
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• 2017

Early research into category-based feature inference reported various phenomena in human thinking including typicality, diversity, similarity effects, etc. Later research discovered that participants' prior knowledge has an extensive influence on these sorts of reasoning. The current research tested the effects of causal knowledge on feature inference and conducted modeling on the results. Participants performed feature inference for categories consisted of four features where the features were connected either in common cause or common effect structure. The results showed typicality effects along with violations of causal Markov condition in common cause structure and causal discounting in common effect structure. To model the results, it was assumed that participants perform feature inference based on the difference between the probabilities of an exemplar with the target feature and an exemplar without the target feature (that is, $p(E_{F(X)}{\mid}Cat)-p(E_{F({\sim}X)}{\mid}Cat)$). Exemplar probabilities were computed based on causal model theory (Rehder, 2003) and applied to inference for target features. The results showed that the model predicts not only typicality effects but also violations of causal Markov condition and causal discounting observed in participants' data.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.39-48
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• 2022

Today the regulation of socio-economic development has been the subject of active scientific debate. The modern paradigm of regulatory policy in foreign countries involves a change in the role and strategy of the state, which determines the relevance of this topic. The aim of the article is to study the current state of regulatory policy research. The article is based on a bibliographic analysis of the study of regulatory policy. The study is based on the data search functions of the Scopus platform. It uses a set of VOSviewer program, online visualization of keywords in the titles of scientific journals and citations of publications. The study led to the conclusion that the number of publications that directly study the nature and features of regulatory policy is insignificant, but constantly growing. In our opinion, further research should determine the essence of regulatory policy as a separate category, a description of its features and factors of formation. It is also necessary to develop a common concept that governments should be actively involved in ensuring the quality of regulation, rather than responding to the shortcomings of regulation, which is evolving into regulatory governance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6009-6027
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• 2019

Support vector machine (SVM) classifiers have been widely used for object detection. These methods usually locate the object by finding the region with maximal score in an image. With bag-of-features representation, the SVM score of an image region can be written as the sum of its inside feature-weights. As a result, the searching process can be executed efficiently by using strategies such as branch-and-bound. However, the feature-weight derived by optimizing region classification cannot really reveal the category knowledge of a feature-point, which could cause bad localization. In this paper, we represent a region in an image by a collection of local feature-points and determine the object by the region with the maximum posterior probability of belonging to the object class. Based on the Bayes' theorem and Naive-Bayes assumptions, the posterior probability is reformulated as the sum of feature-scores. The feature-score is manifested in the form of the logarithm of a probability ratio. Instead of estimating the numerator and denominator probabilities separately, we readily employ the density ratio estimation techniques directly, and overcome the above limitation. Experiments on a car dataset and PASCAL VOC 2007 dataset validated the effectiveness of our method compared to the baselines. In addition, the performance can be further improved by taking advantage of the recently developed deep convolutional neural network features.

• International Journal of Safety
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• v.3 no.1
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• pp.53-58
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• 2004

SMART-P is a promising advanced small and medium category nuclear power reactor. It is an integral type reactor with a sensible mixture of new innovative design features and proven technologies aimed at achieving a highly enhanced safety and improved economics. The enhancement of the safety and reliability is realized by incorporating inherent safety improving features and reliable passive safety systems. The improvement in the economics is achieved through a system simplification, and component modularization. Preliminary safety analyses on selected limiting accidents confirm that the inherent safety improving design characteristics and the safety system of SMART-P ensure the reactor's safety. SMART-P is an advanced integral pressurized water reactor. The purpose of this study is for the safety analysis of the steam generator module pipe break for the SMART-P. The integrity of the fuel rod is the major criteria of this analysis. As a result of this analysis, the safety of the RCS and the secondary system is guaranteed against the module pipe break of a steam generator of the SMART-P.