• Korean Medical Education Review
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• v.23 no.3
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• pp.176-184
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• 2021

The aim of this study was to analyze the research trends in articles published in the Korean Journal of Medical Education (KJME) and Korean Medical Education Review (KMER) using keyword network analysis. The analyses included 507 papers from 2010 to 2019 published in KJME and KMER. First, keyword frequency analysis showed that the research topics that appeared in both journals were "medical student," "curriculum," "clinical clerkship," and "undergraduate medical education." Second, centrality analysis of a network map of the keywords identified "curriculum" and "medical student" as highly important research topics in both journals. Third, a cluster analysis of 20 core keywords in KMER identified research clusters related to academic motivation, achievement, educational measurement, medical competence, and clinical practice (centered on "learning," while in KJME, clusters were related to educational method and program evaluation, medical competence, and clinical practice (centered on "teaching"). In conclusion, future medical education research needs to expand to encompass other research areas, such as educational methods, student evaluations, the educational environment, student counseling, and curriculum.

• Korean Journal of Ecology and Environment
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• v.54 no.3
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• pp.221-228
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• 2021

Recently, environmental DNA (eDNA)-based metabarcoding approaches have been proposed to evaluate the status of freshwater ecosystems owing to various advantages, including fast and easy sampling and minimal habitat disruption from sampling. Therefore, as a case study, we applied eDNA metabarcoding techniques to evaluate the effects of an abandoned mine land located near a headwater stream of Nakdonggang River, South Korea, by examining benthic macroinvertebrate diversity and compared the results with those obtained using the traditional Surber-net sampling method. The number of genera was higher in Surber-net sampling (29) than in the eDNA analysis (20). The genus richness tended to decrease from headwater to downstream in eDNA analysis, whereas richness tended to decrease at sites with acid-sulfated sediment areas using Surber-net sampling. Through cluster analysis and non-metric multidimensional scaling, the sampling sites were differentiated into two parts: acid-sulfated and other sites using Surber-net sampling, whereas they were grouped into the two lowest downstream and other sites using eDNA sampling. To evaluate freshwater ecosystems using eDNA analysis in practical applications, it is necessary to constantly upgrade the methodologies and compare the data with field survey methods.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.34-45
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• 2021

On February 18, 2019, the Chinese government officially released the Outline of the Development Plan for the Guangdong-Hong Kong-Macao Greater Bay Area, which will lead the country in a new round of reform and opening-up. The Greater Bay Area will become a dynamic world-class city cluster, an international scientific and technological innovation center with global influence, an important support for the development of the "One Belt And One Road", a demonstration area for in-depth cooperation between the mainland and Hong Kong and Macao, and a high-quality living area for living, working and traveling. Non-Pearl River Delta(Non-PRD) cities in Guangdong Province are adjacent to the Guangdong-Hong Kong-Macao Greater Bay Area, so it is of practical significance to promote the high-quality development of urban tourism from an international perspective. Based on the panel data released in Guangdong Yearbook 2019, this paper uses the envelopment data analysis (DEA) method to explore ways to promote the high-quality tourism development of Non-PRD cities in Guangdong Province based on the perspective of international development.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.213-218
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• 2021

This paper proposes a technique for detecting a significant threat that attempts to get sensitive and confidential information such as usernames, passwords, credit card information, and more to target an individual or organization. By definition, a phishing attack happens when malicious people pose as trusted entities to fraudulently obtain user data. Phishing is classified as a type of social engineering attack. For a phishing attack to happen, a victim must be convinced to open an email or a direct message [1]. The email or direct message will contain a link that the victim will be required to click on. The aim of the attack is usually to install malicious software or to freeze a system. In other instances, the attackers will threaten to reveal sensitive information obtained from the victim. Phishing attacks can have devastating effects on the victim. Sensitive and confidential information can find its way into the hands of malicious people. Another devastating effect of phishing attacks is identity theft [1]. Attackers may impersonate the victim to make unauthorized purchases. Victims also complain of loss of funds when attackers access their credit card information. The proposed method has two major subsystems: (1) Data collection: different websites have been collected as a big data corresponding to normal and phishing dataset, and (2) distributed detection system: different artificial algorithms are used: a neural network algorithm and machine learning. The Amazon cloud was used for running the cluster with different cores of machines. The experiment results of the proposed system achieved very good accuracy and detection rate as well.

• Journal of Industrial Convergence
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• v.1 no.1
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• pp.1-24
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• 2003

The 583 employees as subject for empirical analysis were selected by cluster sampling method in Banwol & Sihwa Industrial complex in Ansan area. This study shows the followings; 1. In the group where the task is unstructured and the subordinate's ability is high, the achievement-oriented and participative leader behavior have positive impact on the subordinate's expectancy. 2. In the group where the task is unstructured and the subordinate's ability is low, the directive leader behavior has positive impact on the subordinate's expectancy. 3. In the group where the task is structured and the subordinate's ability is high, the supportive leader behavior has positive impact on the subordinate's expectancy. 4. In the group where the task is structured and the subordinate's ability is low, only supportive leader behavior has positive impact on the subordinate's expectancy, and the directive leader behavior has no significant impact. 5. The subordinate's need for growth has a strong moderating effect in the relationship between leader behavior and job satisfaction. Finally this study indicates the implication for future theoretical and empirical development.

• Annual Conference of KIPS
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• 2004.05a
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• pp.673-676
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• 2004

Fast and high-quality document clustering algorithms play an important role in providing data exploration by organizing large amounts of information into a small number of meaningful clusters. In particular, hierarchical clustering provide a view of the data at different levels, making the large document collections are adapted to people's instinctive and interested requires. Many papers have shown that the hierarchical clustering method takes good-performance, but is limited because of its quadratic time complexity. In contrast, K-means has a time complexity that is linear in the number of documents, but is thought to produce inferior clusters. Think of the factor of simpleness, high-quality and high-efficiency, we combine the two approaches providing a new system named CONDOR system [10] with hierarchical structure based on document clustering using K-means algorithm to "get the best of both worlds". The performance of CONDOR system is compared with the VIVISIMO hierarchical clustering system [9], and performance is analyzed on feature words selection of specific topics and the optimum hierarchy depth.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.1-4
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• 2019

Edge Computing 환경에서는 데이터 처리와 시스템 제어를 위한 별도의 서버가 존재하지 않는다. 서버를 통한 중앙통제 방식이 아닌 Edge computing에 사용된 IoT기기들이 연동되어 데이터 분산 처리와 연산을 통해 전체 시스템이 동작된다. 이러한 Edge computing 시스템 구조 특성상 전체 시스템이 과부하를 피하기 위해 각 IoT 기기에서 동시다발적으로 감지되는 실시간 상황 정보를 효율적으로 처리 하여야한다. 이에 따라 실시간 상황 정보를 효율적으로 처리하거나, 다양한 데이터 분석처리 알고리즘들이 연구 개발되어 데이터 처리에 적용되어 왔다. 하지만 데이터의 정보 흐름과 타입에 초점을 맞춘 것이 아니라 예상분석 및 획일화된 알고리즘을 통해서 분석되기 때문에 해당 플랫폼이 주로 지향하는 데이터 형식에 맞지 않으면 성능저하를 수반하며 사용에 제약이 많은 문제점이 있다. 따라서 본 논문에서는 IoT 환경에서 실시간 반응성 향상을 목표로 오픈소스 기반 스트림 데이터 처리 방법에 대한 비교 분석과 Fast-reaction을 위한 데이터 처리 도구 비교 분석을 연구를 진행한다.

• Wind and Structures
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• v.29 no.2
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• pp.139-147
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• 2019

One of the most important factors in tall buildings design in urban spaces is wind. The present study aims to investigate the aerodynamic behavior in the square and triangular footprint forms through aerodynamic modifications including rounded corners, chamfered corners and recessed corners in order to reduce the length of tall buildings wake region. The method used was similar to wind tunnel numerical simulation conducted on 16 building models through Autodesk Flow Design 2014 software. The findings revealed that in order to design tall 50 story buildings with a height of about 150 meters, the model in triangular footprint with aerodynamic modification of chamfered corner facing wind direction came out to have the best aerodynamic behavior comparing the other models. In comparison to the related reference model (i.e., the triangular footprint with sharp corners and no aerodynamic modification), it could reduce the length of the wake region about 50% in general. Also, the model with square footprint and aerodynamic modification of chamfered corner with the corner facing the wind could present favorable aerodynamic behavior comparing the other models of the same cluster. In comparison to the related reference model (i.e., the square footprint with sharp corners and no aerodynamic modification), it could decrease the wake region up to 30% lengthwise.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.3
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• pp.427-439
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• 2019

This study investigated the semantic network based on the focus of the fashion image and SNS text utilized by global SPA brands on the last seven years in terms of the quantity and quality of data generated by the fast-changing fashion trends and fashion content-based media environment. The research method relocated frequency, density and repetitive key words as well as visualized algorithms using the UCINET 6.347 program and the overall classification of the text related to fashion images on social networks used by global SPA brands. The conclusions of the study are as follows. A common aspect of global SPA brands is that by looking at the basis of text extraction on SNS, exposure through image of products is considered important for sales. The following is a discriminatory aspect of global SPA brands. First, ZARA consistently exposes marketing using a variety of professions and nationalities to SNS. Second, UNIQLO's correlation exposes its collaboration promotion to SNS while steadily exposing basic items. Third, in the case of H&M, some discriminatory results were found with other brands in connectivity with each cluster category that showed remarkably independent results.

• Development and Reproduction
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• v.23 no.3
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• pp.297-304
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• 2019

The higher fragment sizes (>2,100 bp) are not observed in the two C. spp. populations. The six oligonucleotides primers OPA-11, OPB-09, OPB-14, OPB-20, OPC-14, and OPC-18 were used to generate the unique shared loci to each tonguesole population and shared loci by the two tonguesole populations. The hierarchical polar dendrogram indicates two main clusters: Gunsan (GUNSAN 01-GUNSAN 11) and the Atlantic (ATLANTIC 12-ATLANTIC 22) from two geographic populations of tonguesoles. The shortest genetic distance displaying significant molecular difference was between individuals' GUNSAN no. 02-GUNSAN no. 01 (genetic distance=0.038). In the long run, individual no. 02 of the ATLANTIC tonguesole was most distantly related to GUNSAN no. 06 (genetic distance=0.958). These results demonstrate that the Gunsan tonguesole population is genetically different from the Atlantic tonguesole population. The potential of PCR analysis to identify diagnostic markers for the identification of two tonguesole populations has been demonstrated. As a rule, using various oligonucleotides primers, this PCR method has been applied to identify polymorphic/specific markers particular to species and geographical population, as well as genetic diversity/polymorphism in diverse species of organisms.