• Journal of Digital Convergence
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• v.10 no.2
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• pp.293-297
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• 2012

In order to provide with personalized recommendation service in context-awareness environment, the collected context data should be analyzed fast and the objective of user should be able to inferred effectively. But, the context collected from the mobile devices is not suitable for applying the existing inference algorithms as they are due to the omission or uncertainty of information and the efficient algorithms are required for mobile environment. In this paper, the behavior pattern was classified using naive bayes classification for minimize the loss caused by the omission or error of information. And pattern matching was used to effectively learn of the users inclination and infer the behavior purpose. The accuracy of the suggested inference model was evaluated by applying to the application recommendation service in the smart phones.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.257-265
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• 2013

Research about business failure was focused on finding the reason of bankruptcy. This research tries to analyze reason and pattern of entrepreneurial failure. Based on 20 entrepreneurial failure cases, we figure out the reason of entrepreneurial failure, utilizing liability of newness and ERIS model. We find that start-up firms in Korea have liability of newness, such as lack of managerial capability, failure of R&D/commercialization, and difficulty of securing marketing channel. Also, we typologize 4 kind of entrepreneurial failure - Lack of preparation of business, failure of resource mobilization, absence of strategy, and failure of marketing.

• Journal of Internet Computing and Services
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• v.18 no.3
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• pp.11-17
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• 2017

To the elderly, sudden falls are one of the most frightening accidents. If an accident occurs, a prompt action has to be taken to deal with the situation. Recently, there have been a number of attempts to detect sudden falls using acceleration sensors embedded in the mobile devices, such as smart phones and wrist-bands. However, using the sensor readings only, the detection rate of the falls is around 65%. Ordinary daily activities such as running or jumping could not be well distinguished from the falls. In this paper, we describe our attempts on improving the fall-detection rate. We implemented a wrist-band fall detection module, using a three-axis acceleration sensor. With the pattern matching on the fall signal-strength frequency spectrum, in addition to the conventional signal strength measurement, we could improve the detection rate by 9% point. Furthermore, by applying two wrist-bands in the experiment, we could further improve the detection rate to 82%.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.4
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• pp.169-179
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• 2002

This paper presents an efficient algorithm for the estimation of damage location and severity in structure using Probabilistic Neural Network (PNN). Artificial neural network has been being used for damage assessment by many researchers, but there are still some barriers that must be overcome to improve its accuracy and efficiency. The major problems with the conventional neural network are the necessity of many training data for neural network learning and ambiguity in the relation of neural network architecture with convergence of solution. In this paper, PNN is used as a pattern classifier to overcome those problems in the conventional neural network. The basic idea of damage assessment algorithm proposed in this paper is that modal characteristics from a damaged structure are compared with the training patterns which represent the damage in specific element to determine how close it is to training patterns in terms of the probability from PNN. The training pattern that gives a maximum probability implies that the element used in producing the training pattern is considered as a damaged one. The proposed damage assessment algorithm using PNN is applied to a 2-span continuous beam model structure to verify the algorithm.

• Journal of Physiology & Pathology in Korean Medicine
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• v.32 no.3
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• pp.171-177
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• 2018

The purpose of this study was to evaluate the reliability and the validity of Deficiency and Excess Pattern Identification Questionnaire. The number of subjects enrolled in this study was 248, from July 2015 to March. 2016. The surveys was conducted two times with 3 month interval. The Cronbach's ${\alpha}$ analysis for internal reliability, Pearson Correlation Coefficient analysis for test-retest reliability were conducted. Factor analysis with varimax rotation for construct validity was used. Kappa analysis for diagnostic reliability were used. The significant p-value was < .05. The Cronbach's ${\alpha}$ was .929 in Deficiency and .932 in Excess questionnaire. The reliabilities between test and retest Intra Correlation Coefficient (ICC) was .71-.762 in the Deficiency, and .58-.786 in Excess questionnaire, respectively. Deficiency was divided by five factors, and Excess four factors. The factor convergence was 72.54% in the Deficiency and 67.5% in Excess questionnaire. The test-retest agreement of four pattern was 68.5% and Kappa was .530. This study reveals that Deficiency and Excess Pattern Identification Questionnaire is a reliable and valid. However, further study to validate the questionnaire is needed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3660-3665
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• 2012

For blind equalization, it is necessary to open an eye pattern quickly in the early stage of equalization, after that it is important to lower an error level of equalizer output signal. This paper discusses coarse error estimation using signal points specifically determined and fine error estimation using original signal constellation, and proposes two suggestions for how to take advantage of the two error estimation methods. The two error estimates, respectively, are effective to quickly open an eye pattern in the state of eye pattern closed, or to lower the level of an error in the steady-state after the eye pattern opening. Two blind equalization algorithms are proposed and their performances are compared, which select one of the two error estimates depending on the state of convergence of the equalizer, or combine two errors weightedly according to the relative reliabilities of the two error estimates, and calculate the new error.

• Fashion & Textile Research Journal
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• v.21 no.3
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• pp.267-276
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• 2019

This study develops 3D-printed-garment collections for a fashion show presentation. A design concept using traditional patterns that consisted of garments regarding the limitation of the printing technology was investigated in order to develop the collection. The structures of the connecting joints of the textile parts which could be easily and sturdily interconnected were invented. Wearability as garments that could be naturally worn on the human body were sought. As a result, four 3D-printed-garments were developed. The 1st garment composed of objects based on a 'Yeon-Dang-Cho'-pattern was constructed as a geometric robe style using a FDM 3D printer and transparent TPU filaments. The 2nd and 3rd 3D-printed-garments composed of an object based on a 'Boe-Sang-Hwa'-pattern was constructed as a distorted one-piece exaggerating the silhouettes of shoulders and waist parts as well as a straight asymmetric tunic style that used the same printer and material as the 1st garment. The last garment composed of an object based on a 'Boe-Sang-Hwa'-pattern printed using a SLA 3D printer and flexible-liquid-resin was constructed attaching the objects on the fabric material by the hot-press machine. The four developed garments were presented in the opening fashion show of 'the 6th International 3D-printing Korea Expo'. This study provides a basic case for related studies to adapt 3D-printing technology in textile pattern development of garment construction.

• The Journal of Economics, Marketing and Management
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• v.12 no.5
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• pp.21-30
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• 2024

Purpose: As competition in the online platform market heats up due to the growing online presence, there is a growing interest in consumer protection legislation to protect consumers. The current online platform law has been criticized for its limitations in regulating the rapidly evolving platform economy. In particular, there is an ongoing need to regulate 'dark patterns' that deceive and mislead consumers. Research Design and Methods: This trend has been recognized not only in Korea, but also in Europe and the United States, which have enacted related regulatory bills, making some types of dark patterns illegal. It is necessary to protect consumers from dark patterns. However, there are some opinions that legal regulations do not protect consumers, but reduce consumer choice, as there is no specific definition of 'dark patterns' or analysis of the damage status. It has also been argued that extensive regulations could shrink the online platform market. Results: Therefore, it is necessary to clarify the areas that can resolve consumers' complaints about dark patterns before the revised law is implemented. In addition, it should be a rational and efficient system so that the continuously growing online platform market does not shrink due to excessive regulations and can develop healthily through the prevention of dark patterns. Conclusions: Here, it is also extremely important to specifically present the scope and standards of regulations and reduce the scope for unnecessary legal interpretation. It can also be a good idea to strengthen the education of consumers and businesses on dark pattern problems and their solutions, and to create a foundation that allows them to solve problems autonomously.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06d
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• pp.151-153
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• 2006

웹을 이용하는 사용자들은 통상적으로 짧은 시간 내에 포탈의 여러 페이지를 방문하는 현상이 있는데, 이 때 방문하는 각 페이지 상에 위치 정보를 필요로 하는 콘텐츠(위치 기반 광고 배너, 위치 기반 날씨 등)가 존재한다면 웹의 특성상 짧은 시간 내에 동일 IP에 대한 위치 정보 검색을 반복하게 된다. 본 논문에서는 이러한 웹 사용 패턴을 캐시를 통해 반영한 고성능 인터넷 위치 검색을 제안, 구현하고 그 성능을 검증한 것이다. 이는 초당 2-3천 건 이상의 대용량 위치 정보를 검색을 수행하데 특히 적합한 방법으로, 적은 비용으로 위치 검색 성능을 획기적으로 높일 수 있었다.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.1
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• pp.27-34
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• 2001

Refining of powder particles and their dissolution into the Al matrix during mechanical alloying(MA) were investigated by using X-ray diffraction(XRD) transmission electron microscopy (TEM) functions of alloy composition, milling time and ball to powder ratio(BPR). It is found that Ti particles less than 20nm are observed in a dark field image of mechanically alloyed Al-10wt%Ti whose XHD pattern exhibits no Ti peak. The observed change of lattice constant of AI indicates that about 1 wt%Ti can he solved in Al after MA for a long time, independent of alloy composition, milling time and BPR, suggesting that most of Ti particles arc retained in the Al matrix. It is concluded that the disappearance of XRD peaks in mechanically alloyed Al-10wt%Ti is not simply attributable to the dissolution of Ti into Al, but associated mainly with extreme refining and/or heavy straining of Ti Particles.