• Science of Emotion and Sensibility
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• v.18 no.1
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• pp.79-94
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• 2015

The purpose of this study is to analyze the emotion and sensibility of fashion words in terms of words types, such as loanword and Korean words, Hangul in fashion product label and fashion manufacturing industry. We surveyed 200 persons in their 20s using the questionnaire on the stimulus of product tag label and fashion words with 15 adjectives. Based on daily usage of foreign words in fashion market, we selected 1 item label in 3 forms: 1) Hangul label written in loan words 2) Label written in English and 3) Label written in Hangul and 3 fashion words in 2 forms 1) loanword and 2) Hangul. And the label types and fashion words were analyzed and investigated in terms of consumer's sensibility, preferences and estimated product price. The results are following: consumers preferred loanword label than Hangul label, and they preferred loanword in English than that in Korean. They evaluated loanword more positively, such as refinement, gorgeous and elegant, etc. and estimated the product price of loanword label as higher. But in the sensibility of 'familiar' and 'stability', Hangul label was not significantly different to loanword written in Hangul. That is, label written in English is the highest in all the evaluation, and loanword label written in Hangul is next, and Hangul label showed the lowest result. Consumers showed the evaluation differently between loanwords and Hangul according to their degree in fashion involvement. Consumers of high fashion involvement evaluated the sensibilities of 'refinement', 'elegant', and 'gorgeous' of loanwords as higher, whereas they had tendency to evaluate the sensibilities of 'familiar' and 'stability' of Hangul as higher or similar.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.22 no.2
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• pp.67-73
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• 2011

The purpose of licensing system is to ensure that the medicines are examined for safety, efficacy and quality. Nevertheless, off-label or unlicensed drug usages in pediatric practice is widespread in Korea and worldwide. Psychotropics are one of the most commonly used off-label or unlicensed drugs. The most valid approach to face this dilemma will be to have more evidences from pediatric pharmacological studies. Clinicians, in addition, need to monitor closely their off-label or unlicensed drug prescriptions to minimize the trial and error in practice. Researchers should publish their experiences and provide guidelines. Pharmaceutical companies, regulatory authorities, and consumer organizations should endeavor altogether for the children's right to get safe and efficacious drugs as adults do. Here, the definition as well as the current status of off-label and unlicensed drug prescriptions will be introduced. Critical issues regarding the off label drugs are discussed. In addition, I will describe the present condition as to the off-label and unlicensed drugs in child and adolescent psychiatry and the authorization process of off-label drug prescription in Korea. Lastly, direction we should like to take in this field will be mentioned.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2523-2538
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• 2017

In most of the existing literature, the definition of the class label has the following characteristics. First, the class label of the samples from the same object has an absolutely fixed value. Second, the difference between class labels of the samples from different objects should be maximized. However, the appearance of a face varies greatly due to the variations of the illumination, pose, and expression. Therefore, the previous definition of class label is not quite reasonable. Inspired by discriminative least squares regression algorithm (DLSR), a noisy label based discriminative least squares regression algorithm (NLDLSR) is presented in this paper. In our algorithm, the maximization difference between the class labels of the samples from different objects should be satisfied. Meanwhile, the class label of the different samples from the same object is allowed to have small difference, which is consistent with the fact that the different samples from the same object have some differences. In addition, the proposed NLDLSR is expanded to the kernel space, and we further propose a novel kernel noisy label based discriminative least squares regression algorithm (KNLDLSR). A large number of experiments show that our proposed algorithms can achieve very good performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.5A
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• pp.889-901
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• 2001

본 논문에서 Multiprotocol Label Switching 시스템을 위한 Label Distribution Protocol의 개발과 분석에 관해서 기술한다. 먼저 Gigabit Switched Router를 만들기 위해서, 상용화시 Carrier Class 제품에 적용하기 위한 LDP의 구현시 고려해야 될 사항에 대해 살피고, 상세 설계를 제안한다. IETF 표준에 의거한 LDP의 구현을 위한 상세 설계는 프로토콜 상태기계의 유도 트리와 프로세스 대수를 사용한 형식적 명세를 사용하여 제시한다. 본 논문에서는 제시된 유도트리와 프로세스 대수를 사용한 프로토콜 동작의 분석을 통해, 구현된 LDP의 상호 연동성과 완전성, 생존성, 도달성, 안전성을 검증한다. 또한 이를 사용하여 구현된 LDP가 기존 상용 제품들과의 연동성과 그 동작의 신뢰성을 확보할 것을 기대한다. 결과적으로 구현된 LDP의 프로토콜 동작들의 검증을 제공한다.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.193-203
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• 2019

The issue of health risks from consuming unhealthy product is an important issue that is happening right now. Both developed and developing countries are already aware of the need for attention to the health-risk products. One tool that is believed to be able to change the consumption behavior of the health-risk products is the use of warning label on product packaging. As a persuasive act, both visual and textual warning label are believed to be able to change people's consumption behavior. In addition to the labels that contain health hazards, this research also uses social consequence contents. The main targets of such unhealthy product marketing are children and adolescents. Correspondingly, this study targets the age groups of kids and tweens. The method used in this research is experiment, involving 180 participants from two age groups namely kids and tweens. As a result, the study found that the influence of warning label on the age of tweens is greater in the age of the children. Meanwhile, the use of visual and textual warning label using social consequences contents, proved to be effective at the age of tweens. These results are useful for enrich social marketing subjects, especially within warning label research.

• Journal of the Korean Home Economics Association
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• v.41 no.3
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• pp.45-56
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• 2003

The purpose of this study was to compare the pantyhose labels of domestic products which contain fiber content, size spec., care symbol, performance properties with those of foreign-made ones, in order to propose a desirable model of label description for the domestic products. The results were as follows: 1) There were differences in the fiber content and fiber mixture ratio of pantyhose on the label according to the countries. The pantyhoses made in Korea and Japan were described only fiber name on the label, while the pantyhoses made in U.S.A., Taiwan, and England were described fiber name and percent of fiber mixture ratio in detail on the label. 2) Most of the pantyhose size produced and sold in Korea were same Free size, but the products from other countries (U.S.A., England, Japan, Taiwan) were sold in various sizes. 3) There were differences, according to the countries, in the care symbol and related explanation of pantyhose on the label. The pantyhoses made in Korea and Taiwan were described care symbol only on the label, while the pantyhoses made in other countries were described additional explanation for care as well as care symbol on the label. 4) It was known that, unlike Korea, other countries were developing and marketing various types of functional pantyhose. For example, U.S.A. and England were focusing on appearance and comfort aspects of pantyhose, while Japan and Taiwan were focusing to develop functional pantyhose like anti-bacterial and anti-ultraviolet ray pantyhose.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.2
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• pp.77-83
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• 2022

In this paper, the two-stage object detection approach is proposed to implement a deep learning-based label inspection system on edge computing environments. Since the label printed on the products during the production process contains important information related to the product, it is significantly to check the label information is correct. The proposed system uses the lightweight deep learning model that able to employ in the low-performance edge computing devices, and the two-stage object detection approach is applied to compensate for the low accuracy relatively. The proposed Two-Stage object detection approach consists of two object detection networks, Label Area Detection Network and Character Detection Network. Label Area Detection Network finds the label area in the product image, and Character Detection Network detects the words in the label area. Using this approach, we can detect characters precise even with a lightweight deep learning models. The SF-YOLO model applied in the proposed system is the YOLO-based lightweight object detection network designed for edge computing devices. This model showed up to 2 times faster processing time and a considerable improvement in accuracy, compared to other YOLO-based lightweight models such as YOLOv3-tiny and YOLOv4-tiny. Also since the amount of computation is low, it can be easily applied in edge computing environments.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.170-176
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• 2022

Given the critical importance of enhancing the level of ESG practices, the current research examines the impact of credit card users' pro-environmental characteristics (i.e., environmental self-accountability, eco-label involvement) on their satisfaction with credit card benefits related to green life. That is, this research investigates whether consumers' satisfaction with green credit card benefits varies depending on their environmental self-accountability and eco-label involvement. Specifically, we predict that (1) for consumers with high (vs. low) environmental self-accountability, their satisfaction with credit card benefits related to green life will be higher (hypothesis 1); and (2) when consumers have high (vs. low) eco-label involvement, they will be more likely to be satisfied with credit card benefits related to green life (hypothesis 2). An online survey (N = 293) was conducted to test the two hypotheses. In support of the hypotheses, the results indicate that (1) respondents who had high (vs. low) environmental self-accountability were more satisfied with credit card benefits related to green life, and (2) respondents with high eco-label involvement, as compared to those with low eco-label involvement, reported greater satisfaction with credit card benefits related to green life. We suggest an important insight into how credit card companies approaching ESG issues can increase their consumers' satisfaction with green credit card benefits, considering consumers' individual characteristics such as environmental self-accountability and eco-label involvement.

• International Journal of Contents
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• v.10 no.4
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• pp.1-10
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• 2014

In this paper, we propose a method to build an accurate initial trimap for the GrabCut algorithm without the need for human interaction. First, we identify a rough candidate for the label region of a bottle by applying a saliency map to find a salient area from the image. Then, the Hough Transformation method is used to detect the left and right borders of the label region, and the k-means algorithm is used to localize the upper and lower borders of the label of the bottle. These four borders are used to build an initial trimap for the GrabCut method. Finally, GrabCut segments accurate regions for the label. The experimental results for 130 wine bottle images demonstrated that the saliency map extracted a rough label region with an accuracy of 97.69% while also removing the complex background. The Hough transform and projection method accurately drew the outline of the label from the saliency area, and then the outline was used to build an initial trimap for GrabCut. Finally, the GrabCut algorithm successfully segmented the bottle label with an average accuracy of 92.31%. Therefore, we believe that our method is suitable for product label recognition systems that automatically segment product labels. Although our method achieved encouraging results, it has some limitations in that unreliable results are produced under conditions with varying illumination and reflections. Therefore, we are in the process of developing preprocessing algorithms to improve the proposed method to take into account variations in illumination and reflections.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.10 s.340
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• pp.9-16
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• 2005

The growth of the Internet over the last several years has placed a tremendous strain on the high bandwidth Hence, the amount of internet traffic has risen sharply and it has demanded to use the limited resource. MPLS (Multiprotocol Label Switching) is regarded as a core technology for migrating to the next generation Internet. It is important to reduce the number of labels and LSP(Label Switched Path)s for network resource management. In this thesis, we considered an MPLS multicast mechanism in the current Internet. The scalability problem due to lack of labels and multicast property is one of the serious problems in MPLS multicast mechanism, we proposed a Label Aggregation algorithm that the multicast packets on same link in MPLS allocates the same label for the scalability problem. In order to support the proposed algorithm we defined a new LDP(Label Distribution Protocol) multicast field and multicast packet is copied and transmitted for multicast group links of next node in LSR(label Switch Router).