• 한국심리학회지:학교
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• 제16권3호
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• pp.315-337
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• 2019

이 연구는 PAI-A 증보판 척도가 청소년기 문제행동에 대한 내재화, 외현화 분류를 반영하고 있는지를 알아보는데 목적이 있다. 이를 위해 PAI-A 증보판 하위척도 31개 및 자살관념(Suicidal Ideation, SUI) 척도 점수를 가지고 탐색적, 확인적 요인분석을 실시하였다. 분석 결과, 선행연구와 공통적으로 불안(Anxiety, ANX)과 우울(Depression, DEP)의 하위척도 및 자살관념(SUI) 척도는 내재화에, 반사회적 특징(Antisocial Features, ANT)과 공격성(Aggressive, AGG)의 하위척도는 외현화에 분류되었다. 주목할 만한 특징으로 경계선적 특징(Borderline Features, BOR)의 하위척도에서 정서적 불안정성(Affective Instability, BOR-A), 정체감 문제(Identity Problems, BOR-I), 부정적 관계(Negative Relationships, BOR-N)는 내재화에, 자기손상(Self-Harm, BOR-S)은 외현화에 분리되어 부하되었다. 이후 도출된 내재화 및 외현화 요인구조가 새로운 표본에도 적용될 수 있는지를 확인하기 위해 탐색적 요인분석에 사용된 표본을 제외한 350명의 표본을 무선추출하여 확인적 요인분석을 실시하였다. 분석 결과, 내재화 및 외현화 분류의 적합도가 양호한 수준에 근접한 것으로 나타났다. 따라서 PAI-A의 척도들이 문제행동에 대한 내재화 및 외현화 분류와 이론적 관련성을 가지고 있다고 볼 수 있겠다. 이러한 연구 결과를 근거해서 향후 학교 장면에서 청소년들의 문제행동 평가에 PAI-A 증보판의 활용을 기대할 수 있다. 마지막으로 이 연구의 의의와 제한점을 논의하였다.

• 한국지하수토양환경학회지:지하수토양환경
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• 제20권7호
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• pp.1-12
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• 2015

The purpose of this study is to highlight the National Classification System related to cleanup the soil contaminated sites and to provide some guidance to address the priority management rank system before the remediation for Busan metropolitan city. Based on the previous soil investigation data, the quantitative classification of vulnerable areas for soil pollution was performed to successfully manage the contaminated sites in Busan. Ten evaluation factors indicating the high soil pollution possibility were used for the priority management ranking system and 10 point was assigned for each factor which was evenly divided by 10 class intervals. For 16 Gu/Guns in Busan, the score of each evaluation factor was assigned according to the ratio of the area (or the number) between in each Gu (or Gun) and in Busan. Ten scores for each Gu (or Gun) was summed up to prioritize the vulnerable Gu or Guns for soil pollution in Busan. Results will be available to determine the most urgent area to cleanup in each Gu (or Gun) and also to assist the municipal government to design a successful and cost-effective site management strategy in Busan.

• 농촌계획
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• 제26권1호
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• pp.101-112
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• 2020

Recently, public awareness regarding mountain villages' landscapes is increasing. Thus, this study aimed to provide standards for conservation, management and creation of mountain village landscape by characterizing and classifying those exist. 286 mountain villages' data were collected and 19 variables - extracted from GIS spatial information and statistic data of mountain villages, chosen as right sources according to former studies - were utilized to conduct factor and cluster analysis. As a result of the factor analysis, 7 characteristics of the mountain villages' landscapes were defined - 'Location', 'Cultivation', 'Ecology·Nature', 'Tourism', 'Residence', 'Recreation'. The K-means cluster analysis categorized the mountain villages' landscapes into four types - 'Residential', 'Touristic', 'General', 'Environmentally protected'. The classification was examined to be appropriate by field assessment, and basic guidelines of mountain village landscape management were set. The results of this study are expected to be utilized planning and implementing regarding mountain village landscape in the future.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2008년도 추계학술대회 논문집
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• pp.341-342
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• 2008

• 한국철도학회논문집
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• 제9권4호
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• pp.335-342
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• 2006

Disaster management system should be built for minimizing damage factor that affects to construction facility from natural disaster. It could be classified by three categories such as disaster prevention, damage survey and recovery phases. For an integrated disaster management system, a disaster information classification system(DICS) is necessary for the reasonable disaster information management. This study suggests an integrated DICS that includes disaster type classification, facility type classification and information type classification for disaster management service. The applicability of suggested DICS is verified by railway facility and the research result could be used as a basic information system for national disaster management system.

• 디자인학연구
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• 제13권2호
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• pp.73-80
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• 2000

본 연구는 제품디자인의 환경 및 관련 정보가 급격하게 변화함에 따라, 이에 대응하기 위하여 디자인 프로세스를 다변화하는 것을 그 목표로 한다. 이를 위하여 먼저, 제품에 대한 일반적인 정보로부터 디자인 정보를 구분하여 정의하고, 이로부터 제품디자인에 반영될 인자를 그 가치와 역할에 근거해 다음과 같이 다섯 가지 디자인 인자로 분류하여 규명하였다. .혁신인자(innovation factor)- 이전에는 존재하지 않았던 요소나 뚜렷한 개선에 관계된 요인 .개방인자(open factor)- 사용유형의 현황과 새로운 가능성의 파악을 통해 현재의 기능에 대한 개선 뿐 아니라 새로운 기능을 유도하는 적극적 요인 .선행인자(anterior factor)- 공유시스템, CIPD, 디자인 전략 등과 관계되어 조건설정에 미리 관여함으로써, 기획 및 초기 요구조건을 지속, 발전시키는 요인 .자명인자(self-evidence factor)- 형태와 기능을 합일시키는 것으로, 제품구조를 통한 기능의 시각화와 관련된 요인 .절대인자(rigid factor)- 인간공학을 기초로 사용자의 효율성, 특히 안전성에 관계된 요인 이와 같은 디자인 인자는 목표고객이나 시장의 특성과 관련되어 제품의 개발 초기 단계부터 제품의 주요 성격을 규정하면서 해석되어진 분류이다. 이 해석 과정에서 중요도가 더 높은 인자를 지배인자로 합성하여 차별화된 결과물을 효과적으로 도출케 하는 인자 구조화 프로세스를 제안하였다. 디자인 인자 구조화 프로세스는 제품의 개념 개발과정에서 제품과 관련된 디자인 지배인자를 목적에 따라 조합하여, 제품에 각각의 특징을 부여하여 제품을 합리적으로 차별화b할 수 있으며, 다양하고 구체적인 소비자의 요구에 능동적으로 대응하는 접근방법으로 활용할 수 있다.

• 한국측량학회지
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• 제35권5호
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• pp.415-422
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• 2017

Finding influential factors from given clustering result is a typical data science problem. Genetic Algorithm based method is proposed to derive influential factors and its performance is compared with two conventional methods, Classification and Regression Tree (CART) and Chi-Squared Automatic Interaction Detection (CHAID), by using Dunn's index measure. To extract the influential factors of preference towards political parties in South Korea, the vote result of $18^{th}$ presidential election and 'Demographic', 'Health and Welfare', 'Economic' and 'Business' related data were used. Based on the analysis, reverse engineering was implemented. Implementation of reverse engineering based approach for influential factor analysis can provide new set of influential variables which can present new insight towards the data mining field.

• 한국의류학회지
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• 제20권2호
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• pp.373-389
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• 1996

The purpose of this study was to classify the somatotype based on the side view and to analyze the characteristics of each somatotype. The subjects were 201 middle-aged women aged from 35 to 54. Data were collected through anthropometry and photometry and analyzed by factor analysis, cluster analysis, analysis of variance, and discriminant analysis. As the result of factor analysis for the classification of somatotypes, 6 factors which explain 80.8% of variance were extracted from 35 photometric measurement. Using factor scores cluster analysis was carried out and the subjects were classified into 4 cluster Each cluster was classified as straight type, turning over type, bending type and swayback according to its position to the relative plumb line and their side view contour. And 4 somatotypes were analyzed by theirs direct anthropometric and indirect Photometric measurment to represent physical characteristics of each group.

• 한국의류학회지
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• 제21권7호
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• pp.1227-1235
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• 1997

The purpose of this study was to classify the somatotype based on the side view and to analyze the characteristics of each somatotype. In order to reduce the burden of stocks and increase clothing fitness, systematic information on typical body sizes and somatotypes is essential. The subjects were 206 unmarried women aged from 19-29. Data were collected through anthropometry and photometry and analyzed by factor analysis, cluster analysis and analysis of variance. As the result of factor analysis for the classification of somatotypes, 8 factors which explain 74.7% of variance were extracted from 35 photometric and 17 anthrometric data. Using factor scores cluster analysis was carried out and the subjects were classified into 4 cluster.Each cluster was classified as bending type, swayback, turning over type and straight type accordding to its position to the relativeplumb line and their side view contour.

• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.265-271
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• 2022

Social media is a form of communication based on the internet to share information through content and images. Their choice of profile images and type of image they post can be closely connected to their personality. The user posted images are designated as personality traits. The objective of this study is to predict five factor model personality dimensions from profile images by using deep learning and neural networks. Developed a deep learning framework-based neural network for personality prediction. The personality types of the Big Five Factor model can be quantified from user profile images. To measure the effectiveness, proposed two models using convolution Neural Networks to classify each personality of the user. Done performance analysis among two different models for efficiently predict personality traits from profile image. It was found that VGG-69 CNN models are best performing models for producing the classification accuracy of 91% to predict user personality traits.