• Journal of Fashion Business
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• v.14 no.5
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• pp.49-65
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• 2010

The purpose of this paper is to derive the categories of negative e-WOM (electronic word of mouth) via consumer review. Disclosing the details of negative e-WOM based consumer reviews has never been done before. For this reason, a content analysis was adopted to provide knowledge and understanding of the phenomenon. This paper analyzes the content of 630 consumer reviews posted on the open market internet site, www.auction.co.kr. The analysis was conducted from October 20th, 2008 to March 10th, 2009. The results indicated that the negative e-WOM based consumer reviews can be divided into two categories: the cognitive evaluation and the expression of consumer's emotion. The category of cognitive evaluation is consisted of negative e-WOM of product, negative e-WOM of service, and warning about the risk of purchasing products. The category of expressing consumers' emotion are composed of venting customers' dissatisfaction and passive response of dissatisfaction. Investigating the details of negative e-WOM has a number of implications. Most importantly, the results revealed multidimensional structure of negative e-WOM. This understanding of negative e-WOM communication allows marketers to improve products and services that better meet customers' current and future needs.

• Journal of Korea Technology Innovation Society
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• v.16 no.4
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• pp.1006-1031
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• 2013

This study investigates the extent to which product innovation is associated with firm performance, and how this effect is moderated by other type of innovation efforts. Empirical analysis is conducted (1) to determine the effect of product innovation on firm performance; (2) to explore the moderating effect that process innovation, organizational innovation and marketing innovation activities each has on the relationship between product innovation and firm performance. The analytical sample comprises a total of 816 Korean manufacturing firms from the 2010 KIS (Korean Innovation Survey) data and merged with financial data from KIS Info for acquiring the objectivity. The results show that product innovation is positively associated with a firm performance. Product innovation when combined with higher levels of process, organizational and marketing innovation activities resulted in higher firm performance. The results suggest that product innovation is a decisive factor of firm performance. More importantly, process, organizational and marketing innovation activities support product innovation and thus impact firm performance indirectly. In addition, this study examines the effect of innovation activities on firm performance by different firm size and R&D intensity, thereby further improving the details of this study.

• Fashion & Textile Research Journal
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• v.22 no.3
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• pp.271-286
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• 2020

This study evaluated designs via the consumers' function and design preferences survey for using product design images, virtual avatar wearing images and product explanations that identified consumers' function and design preferences for knee protection pads as well as to develop movement assistive knee pad designs. We developed Design A for men and Design B for women. For Design A, the front of the knee supports muscles and alleviates pain with a hole. Mesh material with good ventilation was applied to enhance wearing comfort. The color was achromatic for a modern style, and the hook fastener and loops enabled easy wear and removal of the pad while controlling size and pressure strength. For Design B, taping details seamlessly support muscles in the knee area with fabrics less than 0.1 cm thick and with long sleeves in the diverse sizes. The design's satisfaction assessment showed that potential consumers were satisfied with Design A and Design B for overall design and functional features. Over 77% wanted to use/wear and purchase designs; in addition, over 78% expected it would help with walking and relieve knee pain. The results can be helpful for designers when deciding designs for manufacturing and commercializing kneepad products.

• Journal of Society of Preventive Korean Medicine
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• v.18 no.1
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• pp.23-41
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• 2014

Objective : The purpose of this study was to lay the groundwork for understanding the details and scope of the legal definition of medicinal products, following the changes in the relevant laws and regulations. This will let readers properly understand the origins of the ongoing conflicts on herbal drugs and new drugs from natural products that are present in the medical field and the medical industry. Possible solutions are proposed in the end. Method : I analyzed the changes in definition of medicinal products since 1945 that have been used in relevant laws and regulations(i.e. Pharmaceutical Affairs Act) and drug approval process(i.e. New Drug Application and Investigational New Drug Application). Results : Legal definition of medicinal products has changed in accordance with the changes in the pharmaceutical industry, such as the establishment of dualistic medical and pharmaceutical System and the introduction of the substance patent. Due to those changes, boundaries of Western medicinal products and health food expanded, while those of herbal medicine products relatively downscaled. Conclusion : Legal definition of medicinal products-i.e. Herbal Drugs, Crude Drugs, and New Drugs from Natural Products-should be reestablished according to academic legitimacy and dualistic medical and pharmaceutical System.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1787-1795
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• 2009

This paper describes an automation of architectural design processes and the direction between this automation and robotic system in building construction using the concept of the object-oriented design in architecture. The research starts from the premise that many computer-aided design systems are mostly aimed at serving as drawing tools which are used only after a design formal solution has already been established by the architect. If the computer is well applied to the architectural design process, many positive things such as standardization of design detail, increasing productivity and collaboration, minimizing construction costs etc. can be done. To support an early design solution in the computer-based environment, the proposed automation was developed and tested in a real building project, using the object-oriented design concept such as product model. This design automation gives various design alternatives from the early design phase to the final stage of design details, according to musical harmony. This paper shows how architectural design process can be automated and how the data of the applied architectural design can be integrated into product model environment, in relation to robotic system in building construction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3923-3942
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• 2022

Environment, price, regulation, and other factors influence the price of agricultural products, which is a social signal of product supply and demand. The price of many agricultural products fluctuates greatly due to the asymmetry between production and marketing details. Horticultural goods are particularly price sensitive because they cannot be stored for long periods of time. It is very important and helpful to forecast the price of horticultural products which is crucial in designing a cropping plan. The proposed method guides the farmers in agricultural product production and harvesting plans. Farmers can benefit from long-term forecasting since it helps them plan their planting and harvesting schedules. Customers can also profit from daily average price estimates for the short term. This paper study the time series models such as ARIMA, SARIMA, and neural network models such as BPN, LSTM and are used for wheat cost prediction in India. A large scale available data set is collected and tested. The results shows that since ARIMA and SARIMA models are well suited for small-scale, continuous, and periodic data, the BPN and LSTM provide more accurate and faster results for predicting well weekly and monthly trends of price fluctuation.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• Natural Product Sciences
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• v.6 no.4
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• pp.189-192
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• 2000

A new isoflavone, $(+)-4'-O-methyl-8-C-{\beta}-D-glucopyranosylgenistein$, was isolated from the aerial parts of Spartidium saharae together with the known isoflavone, $(+)-8-C-{\beta}-D-glucopyranosylgenistein$ as well as dipiperidine alkaloids, (+)-ammodendrine and (+)-N-acetyl hystrine. Details of their structure elucidation are based on chemical and spectroscopic methods. N-formyl ammodendrine was detected by GC-MS. The potential chemotaxonomic value of the alkaloid content is explored. Cytotoxic activity has been determined for both alcoholic extract and isolated compounds.

• Korean Journal of Computational Design and Engineering
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• v.15 no.2
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• pp.144-156
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• 2010

When existing parts are re-used for the development of a new product or business-to-business transactions, a method for searching parts from a part database that meets user's requirements is necessary. To this end, it is important to develop a part search method which is able to measure similarity between parts and user's input data with generality as well as robustness. In this paper, the authors suggest a method for measuring part similarity using ontology and multi-criteria decision making method and address its technical details. The proposed method ensures the interoperability with existing engineering information management systems, represents part specifications systematically, and has generality in the procedure for comparing part specifications. The case study for ejector pins having been conducted to demonstrate the proposed method is also discussed.

• Proceedings of the Korean Society of Toxicology Conference
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• 2002.05a
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• pp.84-84
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• 2002

Abstract To study the status of oxidative DNA damage in Helicobacter pylori infection in more details, gene-specific oxidative DNA damage was investigated by examining oxidative DNA damage to individual genes. This was done by determining the loss of PCR product of a targeted gene before and after gastric mucosal DNA was treated with 8-hydroxyguanine glycosylase, which cleaves DNA at the 8-hydroxyguanine residues.(omitted)