• International Journal of Costume and Fashion
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• v.13 no.1
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• pp.35-47
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• 2013

We know that humans are able to live comfortably when there is a balance between the living environment that surrounds us and us. Clothing, one of the necessities of life, serves a dual purpose of functioning as protection for the body as well as providing visual satisfaction, and so is the most effective bonding mechanism. A different type of comfort that has been provided through industrialization and advancements in technology has resulted in pollution problems in the environment, and it has reached a point of seriously thinking about its effects. The biggest problems in environmental pollution are air pollution and waste disposal, and something that cannot be ignored is that environmental hormones and harmful heavy metals have been discovered in the synthetic dyes used in the clothing product, and not only are they harmful to the body, but they also have adverse effects on skin allergies such as atopic dermatitis. Its effects on clothing, especially underwear and baby products, can become a serious issue. The use of natural vegetable dye can be considered the basis for the traditional Korean dyeing process, however not all natural dyeing process can be thought of as traditional Korean dyeing. This is because natural dyeing used to be the most common method of dyeing before synthetic dyes came along and became the dye of choice for most clothing. Natural dyes are beneficial to the body, and the nature colors, achieved from the natural materials, relieve eye strains as well as have a healing effect for people who are suffering from psychological instability such as stress. However, the use of mordant in order to increase the fastness and get better color effects can lead to even more damage to the environment, and it cannot be a dyeing method that is good for the body. Traditional natural dyeing is different from regular natural dyeing because it uses colors that the Korean people can identify with and applies specific methods in order to achieve those colors. Even though experimental study with dyestuff and practical use of the dyeing methods for traditional Korean dyeing has been started(Soh, H., 1983) and has been ongoing, it is still not easy for regular people to use the method on their own. At the present time, natural dye materials are getting made and sold more than ever, but there is a lot of confusion among consumers regarding the difference between traditional Korean dyeing and natural dyeing, as companies are using the two terms interchangeably to market their natural dye products. So getting a better understanding of the characteristics of traditional Korean dyeing and traditional colors should be considered first priority at this time. The purpose of this thesis is to study the traditional Korean view of color, which developed the culture of traditional dyeing in Korea, and the characteristics of traditional Korean dyeing, a method that pursued achieving Korea's color through natural dyeing.

• The Research Journal of the Costume Culture
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• v.24 no.3
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• pp.336-348
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• 2016

This study was executed to deduce the factors affecting eco-friendly behaviors and attitudes, to analyse the difference of eco-friendly behaviors and attitudes between countries, and to draw the variables affecting clothing recycling behavior. The sample comprised people from the UK, China, South Korea. The results were as follows. The four factors related to eco-friendly behaviors and the five factors related to eco-friendly attitudes were derived from the results of factor analysis. In the case of eco-friendly behaviors, four eco-friendly behavior factors showed a significant difference all according to gender and country. In the case of eco-friendly attitudes, saving of natural resources for eco-friendly life, recycling for eco-friendly life, and individual preference for eco-friendly life showed a significant according to gender, also recycling for eco-friendly life, individual preference for eco-friendly life, social awareness for eco-friendly life, and company's awareness for eco-friendly life showed a significant difference according to country. All of the variables related to clothing recycling behaviors showed the significant difference according to gender and countries. It was verified that the stronger the behaviors or attitudes for waste recycling and environmental protection, individual preference for eco-friendly life, saving of natural resources, buying eco-friendly products, and separate collection for recycling, the more positive the action to clothing recycling. The results of this study will be helpful to establish a marketing strategy for each country and to deduce a plan to attract clothing recycling form people.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.1
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• pp.95-103
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• 2002

The consumption in the clothing's living has been diversified and rich by the increase in pay, the ostentatious propensity to consume and the diversification of distribution on structure in accordance with the advance of clothing industries, etc. The clothing, however, was not used properly due to the thoughtless purchase, the sudden change of fashion and the difficulty in the use and management of clothing. Most rural communities, furthermore, have the poor market, and the unreasonable management could be often observed, e.g., some people don't follow the care label or burn the clothing to waste. This study was conducted to provide the tool measuring the standardized clothing management behaviors so that the systematic and effective instruction could be achieved to improve the living standards 623 rural and urban housewives to develop the tool measuring the standardized clothing management to compare and measure the effect of before and after the education and guide all the way. And then, we developed the standardized measurement tool consisting of 6 parts of 60 questions after analyzing the validation and reliability of the questions. As a result of analyzing the validation and reliability of the developed tool, each Conbach alpha value of clothing living showed the good reliability; the value of the purchase plan was 0.76, the purchase was 0.83, the wear was 0.80, the management was 0.84, the storage was 0.83, and the disposal was 0.74, which indicated that it was able to use as a standardized tool.

• Journal of the Korean Society of Costume
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• v.60 no.6
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• pp.1-10
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• 2010

The cultures and traditions of Asia has the roots so deep and it is the origin of inspiration. Therefore, it is easy to find a different inspiration when designing, expecially for Western designers who are seeking European tradition and its comparison. The most distinctive feature of the Asian look is non-structural and has no clear form close to the structure of the body or mathematical ratio, but is steric with 2-Dimensional planed textiles, and has a flexible, non-structural formative characteristic related to the movable body. This is base on the vision of the universe that regards the parts as the whole. From this research, generally studying about the Asian look and its non-structural formative characteristics. The study looked closely into the aesthetic value of non-structural formative characteristics formation, with basis on the large dress regulation system of the western reasoning and rationalism and mechanism. At first, my study pointed on the dressing functionalism or Neo-classism considering emotions, Anti-Western aspect observing surrealism dressing and expressionism dressing. Second, with men and women showing similar outer shape without the equivalent element such from wearing a corset, the sexism is abolished. Finally, the designers’ inner intention of art is being delivered, from the aspect that the expression of art, size and no waste of fabric shows effort of communicating with the world, giving value to the possibility of continuance.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1126-1126
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• 2001

The paper presented here is the initial part of a larger study, in which it was determined which quality parameters in cheese powder could already be predicted by NIR at an early stage in the process and which could only be predicted at the final stages of the process. This initial study was performed in order to establish the levels and nature of variation within and between batches such that the subsequent data collection could be tackled optimally. The perspectives evolved into more than was originally planned and revealed some interesting uses of NIR-technology. Cheese powder production starts as a batch process, where waste cheese from other dairies is melted down in a vat. The process then turns into a continual process as the vat is emptied and the melted cheese is then filtered, homogenized, pasteurized and finally spray dried. Between each batch the powder is to a greater or lesser degree a mixture of 2 batches. This paper is divided into 2 aspects, one regarding the optimization of sampling time and the other is a study of process dynamics. Optimizing sampling time This initial study included 9 powder samples from 9 different batches produced during one day. The raw materials for the batches were chosen with the aim of creating a relatively high level of variation in the data. The total of 81 samples were taken out at regular intervals and spectra were collected on a NIR-systems 6500 instrument. The subsequent reduction of the data by PCA to score values shows the power of NIR as a tool to determine not only when samples are representative of a certain batch, but also which batches are stable enough to include in a further study. Studying process dynamics To take this experiment a step further 1 of the 81 samples were sent to the laboratory for further analyses. The samples were chosen on the criteria that they covered the spectral variation in the dataset. These samples were analysed for 4 chemical components and 5 physical attributes, which are essential for describing the quality of the product. The latent structure of the 7 samples, using the chemical and physical variables, is totally comparable to the latent structure of the NIR spectra. This outcome makes it possible to describe the dynamics of one day's production both chemically and physically with relatively little resources. Additionally it raises the question as to whether reference values are needed, as the latent structure of the NIR-spectra appears to be sufficient in providing information on the quality of the product. To be able to use NIR in this way would require defining quality limits in the principal component space as opposed to each of the reference values. The potential of NIR applied in an explorative fashion with batch processes opens a whole new gateway for the use of this technology. This study explains yet again after so many years in the field “why I'm crazy about NIR!”.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.7 no.2
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• pp.209-222
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• 1997

Authors surveyed the ground water near the waste disposed from a fiberglass production factory to confirm the presence of glassfiber in the water and to determine the effect of sampling conditions and storage on the recovery of fibrous materials in the ground water. Sample was collected at every 4 hours for 48 hours consecutively. After finishing the 48 hours sample, water sampling was done from each tap after repeated turning on and off the water for 30 seconds at each time. Sample was collected in the two 1.5 liter polyethylene bottle after vigorously shaking the bottle with the same water several times with the flowing tap water. At each paired sample, one bottle was stored stand still at room temperature, and the other sample was filtered immediately after sampling. Water was filtered on the Mixed Cellulose Ester filter with negative pressure. Each sample was divided into upper and lower layer. The other bottle was stored at room temperature standstill for 7 days and filtered in the same fashion as the other pair of sample did. Each MCE filter was divided into 4 pieces and one piece was treated with acetone to make it transparent. Each prepared sample was observed by two researchers under the light and polarizing microscopy, scanning electron microscopy and energy dispersive X-ra microanalysis. Fibers were classified by the morphology and polarizing pattern under the polarizing microscope, and count was done. 1. There was a significant fluctuation in number of the fibers, but there was no specific demonstrable pattern. 2. Non-polarizing fibers frequently disappeared after 7 days's storage. But cluster of fibers were found at the wall of the same container by scratching technique. 3. Polarizing fibers were usually found in between the filter and the manicure pasted area. Possible explanations for this phenomenon will be that either these fibers are very light or have electronic polarity. Hence, these fibers are not able to be attached on the surface of slide glass. 4. Under the scanning electron microscopic examination, the fibers which are not refractive under the light microscopy were identified as glassfiber. Other fibers which is refractive under the polarizing microscopy were identified as magnesium silicate fibers. It is strongly suggested that development of standardized method of sample collection and measurement of fibrous material in the water is needed.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.