• Proceedings of the Korean Information Science Society Conference
• /
• 2007.10b
• /
• pp.247-252
• /
• 2007

오늘날 컴퓨팅 환경은 점차 복잡해지고 있으며, 복잡한 환경을 관리하는 이 점차 중요해 지고 있다. 이러한 관리를 위해 어플리케이션의 내부 구조를 드러내지 않은 상태에서 환경에 적응하는 자가치유에 관한 연구가 중요한 이슈가 되고 있다. 우리의 이전 연구에서는 자가 적응 모듈의 성능 향상을 위해 스위치를 사용하여 컴포넌트의 동작 유무를 결정하였다. 그러나 바이러스와 같은 외부 상황에 의해 자가 적응 모듈이 정상적으로 동작하지 않을 수 있으며 다수의 파일을 전송할 때 스위치가 꺼진 컴포넌트들은 메모리와 같은 리소스를 낭비한다. 본 연구에서는 이전 연구인 성능 개선 자가 적응 모듈에서 발생할 수 있는 문제점을 해결하기 위한 방법을 제안한다. 1) 컴포넌트의 동작 여부를 결정하는 스위치를 확인하여 비정상 상태인 컴포넌트를 찾아 치유를 하고, 2) 현재 단계에서 사용하지 않는 컴포넌트를 다른 작업에서 재사용한다. 이러한 제안 방법론을 통해 파일 전송이 않은 상황에서도 전체 컴포넌트의 수를 줄일 수 있으며 자가 적응 제어 모듈을 안정적으로 작동할 수 있도록 한다. 본 논문에서는 명가를 위하여 비디오 회의 시스템 내의 파일 전송 모듈에 제안 방법론을 적용하여 이전 연구의 모듈과 제안 방법론을 적용한 모듈이 미리 정한 상황들에서 정상적으로 적응할 수 있는지를 비교한다. 또한 파일 전송이 많은 상황에서 제안 방법론을 적용하였을 때 이전 연구 방법론과의 컴포넌트 수를 비교한다. 이를 통해 이전 연구의 자가 적응 모듈의 비정상 상태를 찾아낼 수 있었고, 둘 이상의 파일 전송이 이루어 질 때 컴포넌트의 재사용을 통해 리소스의 사용을 줄일 수 있었다.위해 잡음과 그림자 영역을 제거한다. 잡음과 그림자 영역을 제거하면 구멍이 발생하거나 실루엣이 손상되는 문제가 발생한다. 손상된 정보는 근접한 픽셀이 유사하지 않을 때 낮은 비용을 할당하는 에너지 함수의 스무드(smooth) 항에 의해 에지 정보를 기반으로 채워진다. 결론적으로 제안된 방법은 스무드 항과 대략적으로 설정된 데이터 항으로 구성된 에너지 함수를 그래프 컷으로 전역적으로 최소화함으로써 더욱 정확하게 목적이 되는 영역을 추출할 수 있다.능적으로 우수한 기호성, 즉석에서 먹을 수 있는 간편성, 장기저장에 의한 식품 산패, 오염 및 변패 미생물의 생육 등이 발생하지 않는 우수한 생선가공, 저장방법, 저가 생선류의 부가가치 상승 등 여러 유익한 결과를 얻을 수 있는 효과적인 가공방법을 증명하였다.의 평균섭취량에도 미치지 못하는 매우 저조한 영양상태를 보여 경제력, 육체적 활동 및 건강상태 등이 매우 열악한 이들 집단에 대한 질 좋은 영양서비스의 제공이 국가적 차원에서 시급히 재고되어야 할 것이다. 연구대상자 특히 배달급식 대상자의 경우 모집의 어려움으로 인해 적은 수의 연구대상자의 결과를 보고한 것은 본 연구의 제한점이라 할 수 있다 따라서 본 연구결과를 바탕으로 좀 더 많은 대상자를 대상으로 한 조사 연구가 계속 이루어져 가정배달급식 프로그램의 개선을 위한 유용한 자료로 축적되어야 할 것이다.상범주로 회복함을 알수 있었고 실험결과 항암제 투여후 3 일째 피판 형성한 군에서 피판치유가 늦어진 것으로 관찰되어 인체에서 항암 투여후 수술시기는 인체면역계가 회복하는 시기를 3주이상 경과후 적어도 4주째 수술시기를 정하는 것이 유리하리라 생각되

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.9
• /
• pp.412-419
• /
• 2019

Negative space in the discipline of art defines the space around and between the subject of an image. The use of negative space is an element of artistic composition, since it is occasionally used to artistic effect as the "real" subject of an image. In painting, it is a technique that negatively touches the background of an object to be expressed, so that it gives a feeling of unique texture and silhouette by touching unnecessary parts while leaving necessary parts. As in art, negative space in a design can also be useful to identify an image of infeasible design ranges with a straightforward view. Similarity between two disciplines leads to the introduction of the negative space concept for design space exploration. A rough design space exploration using statistics and visual analytics may support more efficient decision-making, and can provide meaningful insights into the direction of early-phase system design. For this, the approach guarantees dynamic interactions between visualized information and human cognitive systems. Visual analytics is useful to summarize complex and large-scale data. It is useful for identifying feasible design spaces, as well as for avoiding infeasible spaces or highly risky spaces. This paper investigates the possible use of the negative space concept by using an application example.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.12
• /
• pp.186-196
• /
• 2018

Sports has become one way to improve our own health and to enjoy life by changing the lifestyle of modern-day people. Sports athletes not only give pleasure to the public, but also play a role in elevating a nation's reputation through sports. Tennis is popular with the public, and women players receive tennis wear from various sports companies to promote the designs to the public. This study considers the design-related characteristics of women's tennis wear through content analysis of design elements from the tennis wear in four major tournaments over the most recent five years. This is important in order to provide basic data on design directions for tennis wear in the future. The results of this study are as follows. First, the silhouette plays a role in enhancing activity by considering the physical movement of tennis players who are very active. Second, color emphasizes the rules and clarity of traditional tennis tournaments, and reflects a diversified trend in tennis wear by considering smooth game play by players and combining popular colors in the year. Third, patterns and decorations on material are used as a means to emphasize the esthetics of tennis wear, and tape plays an auxiliary role in emphasizing the physical beauty of women or preventing physical movement causing injury. In addition, sponsor logos are generally located at the center of the chest of tennis wear tops by mixing letters and images. This can be interpreted as a part of the marketing strategy to enhance clarity of the sponsor's brand.

• The Journal of the Korea Contents Association
• /
• v.22 no.5
• /
• pp.261-275
• /
• 2022

In this stage when K-Pop and K-Fashion have been drawing global attention, it is required to activate the Korean culture and fashion by developing fashion products which reinterpret various items in the Hanbok fields with modern sense in connection with Korean wave. Thus, this study aims to develop fashion products related to Korean wave with court dance costumes used in court banquets, which may be the origin of K-Pop, as the main theme, and to converge and expand culture and fashion fields. To this end, the original court dance costumes and their modern forms continuing in these days were analyzed and the costumes for Musanhyang, Yeonhwadae, Cheoyongmu, Chundaeokchok and Chunaengjeon differentiated from existing daily Hanbok were selected. The fashion products related to Korean wave reflecting the specific elements of those five costumes were designed. Then, the silhouette and sizes of those costumes were checked using the CLO, the 3D virtual clothing program and total 5 fashion products were created. In conclusion, the results of this paper will contribute on making Korean design popular on the design aspects, expanding the scope of Korean wave contents on the industrial aspects and globalizing the K-Fashion on the global aspects.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.23-45
• /
• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Journal of Fashion Business
• /
• v.3 no.4
• /
• pp.147-160
• /
• 1999

This paper is intended to compare and analyze the fashion trends that were introduced in the recent shows, held abroad and in Korea, so as to investigate how well the designers in Taegu and Kyungbuk (TK) area are keeping up with the international vogue. The research has done, analyzing Pret-a-Porter in Paris and the three events held in the TK area in 1997 -The Taegu Collection, Kyungbuk Fashion Festival and Textile & Apparel Fair and using reference pictures and documentary records. In order to investigate the trends the research is divided by four groups which are the silhouette, the detail, the color and the Fashion image and has done with the help of three postgraduate students. The results are as follows. 1. The Silhouette The slim-line has the greatest importance in the silhouette analysis of the recent collections. Like Elongated and Fit & Flare, tight-fitting and female-line were also appeared quite a lot. Compared with foreign collection, Korean collections put the bigger importance on the slim-line. 2. The Detail The printings, using paintings and plant-logos had the large portion of the accessories in both foreign and Korean collections. Draw string and wrap style were also presented a lot. Especially, at the Korean collections, layerd, corsage, and craft accent were emphasized, too. As for the necklines the similarity was found over the four events considering. Camisole neckline and halter neck were presented the most, and bared top, Vneckline, boat and low-neck which can highlight the feminity were often appeared as well. Considering collars, tailored and peaked collars which are frequently used for the jackets, were usually shown at the collections. Like convertable, shirts, wing and Italian collar, the collars that can be applied for the sports wears were presented a lot. Virtually no variation of design was found in the sleeve analysis. While set-in-sleeve and sleeveless were found commonly, not so many ornaments were added to the sleeves. The ankle and knee length for the pants and skirts were common. Furthermore, including the micro-mini, showing extremely feminine style the mini-style had the 20% portion of the skirt-length. Unbalanced lengths, using bias-cut were presented quite a lot on the runways. Deep slit skirts, wide pants and irregular hem skirts were in vogue. On the runways of Paris, more than 21% of the design was the burmuda pants. 3. The Color Red and Blue were in vogue in the four collections considering. Sometimes, yellowish was combined in Korean collections. Black and pale tone were appeared to be in fashion also with light grayish, moderate and deep tone. 4. The Fashion image As for the fashion image, feminine-decorative trend amounted to the large percentage in korean collections. At the foreign collection feminine-decorative trend and feminine trend were predominant, then mannish trend and simple trend were apeared equally. The research shows that TK area and foreign collections are fairy similar, which means that the designers in TK area have been making their efforts to satisfy the clients who have the international minds. However, compared with foreign collections, TK collections were apprered to be strongly inclined to only a few trends. Consequently the season trends are not as diverse as the foreign trends, which cannot satisfy the fashion taste of the clients in TK area. The local designers should know the tendency and the taste of the clients and make the more efforts to read local clients' mind.

• The Journal of the Acoustical Society of Korea
• /
• v.42 no.6
• /
• pp.603-616
• /
• 2023

In this study, machine learning-based clustering and classification of residential noise in apartment buildings was conducted using frequency and temporal characteristics. First, a residential noise source dataset was constructed . The residential noise source dataset was consisted of floor impact, airborne, plumbing and equipment noise, environmental, and construction noise. The clustering of residential noise was performed by K-Means clustering method. For frequency characteristics, L_eq and L_max values were derived for 1/1 and 1/3 octave band for each sound source. For temporal characteristics, Leq values were derived at every 6 ms through sound pressure level analysis for 5 s. The number of k in K-Means clustering method was determined through the silhouette coefficient and elbow method. The clustering of residential noise source by frequency characteristic resulted in three clusters for both L_eq and L_max analysis. Temporal characteristic clustered residential noise source into 9 clusters for L_eq and 11 clusters for L_max. Clustering by frequency characteristic clustered according to the proportion of low frequency band. Then, to utilize the clustering results, the residential noise source was classified using three kinds of machine learning. The results of the residential noise classification showed the highest accuracy and f1-score for data labeled with L_eq values in 1/3 octave bands, and the highest accuracy and f1-score for classifying residential noise sources with an Artificial Neural Network (ANN) model using both frequency and temporal features, with 93 % accuracy and 92 % f1-score.