• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.163-179
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• 2010

Recentlythe concept of fast fashion is drawing attention as customer needs are diversified and supply lead time is getting shorter in fashion industry. It is emphasized as one of the critical success factors in the fashion industry how quickly and efficiently to satisfy the customer needs as the competition has intensified. Because the fast fashion is inherently susceptible to trend, it is very important for fashion retailers to make quick decisions regarding items to launch, quantity based on demand prediction, and the time to respond. Also the planning decisions must be executed through the business processes of procurement, production, and logistics in real time. In order to adapt to this trend, the fashion industry urgently needs supports from intelligent quick response(QR) system. However, the traditional functions of QR systems have not been able to completely satisfy such demands of the fast fashion industry. This paper proposes an intelligent quick response system for the fast fashion(IQRS-FF). Presented are models for QR process, QR principles and execution, and QR quantity and timing computation. IQRS-FF models support the decision makers by providing useful information with automated and rule-based algorithms. If the predefined conditions of a rule are satisfied, the actions defined in the rule are automatically taken or informed to the decision makers. In IQRS-FF, QRdecisions are made in two stages: pre-season and in-season. In pre-season, firstly master demand prediction is performed based on the macro level analysis such as local and global economy, fashion trends and competitors. The prediction proceeds to the master production and procurement planning. Checking availability and delivery of materials for production, decision makers must make reservations or request procurements. For the outsourcing materials, they must check the availability and capacity of partners. By the master plans, the performance of the QR during the in-season is greatly enhanced and the decision to select the QR items is made fully considering the availability of materials in warehouse as well as partners' capacity. During in-season, the decision makers must find the right time to QR as the actual sales occur in stores. Then they are to decide items to QRbased not only on the qualitative criteria such as opinions from sales persons but also on the quantitative criteria such as sales volume, the recent sales trend, inventory level, the remaining period, the forecast for the remaining period, and competitors' performance. To calculate QR quantity in IQRS-FF, two calculation methods are designed: QR Index based calculation and attribute similarity based calculation using demographic cluster. In the early period of a new season, the attribute similarity based QR amount calculation is better used because there are not enough historical sales data. By analyzing sales trends of the categories or items that have similar attributes, QR quantity can be computed. On the other hand, in case of having enough information to analyze the sales trends or forecasting, the QR Index based calculation method can be used. Having defined the models for decision making for QR, we design KPIs(Key Performance Indicators) to test the reliability of the models in critical decision makings: the difference of sales volumebetween QR items and non-QR items; the accuracy rate of QR the lead-time spent on QR decision-making. To verify the effectiveness and practicality of the proposed models, a case study has been performed for a representative fashion company which recently developed and launched the IQRS-FF. The case study shows that the average sales rateof QR items increased by 15%, the differences in sales rate between QR items and non-QR items increased by 10%, the QR accuracy was 70%, the lead time for QR dramatically decreased from 120 hours to 8 hours.

• Journal of Korea Technology Innovation Society
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• v.16 no.4
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• pp.1109-1133
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• 2013

In an effort to discover new technologies and to forecast social changes of technologies, a number of technology life-cycle models have been developed and employed. The hype cycle, a graphical tool developed by a consulting firm, Gartner, is one of the most widely used models for the purpose and it is recognised as a practical one. However, more research is needed on theoretical frames, relations and empirical practices of the model. In this study, hype cycle comparisons in Korean and global search websites were performed by means of web-search traffic which is proposed as an empirical measurement of public expectation, analysed in a specific product or country in previous researches. First, search traffic and market share for new cars were compared in Korea and the U.S. with a view to identifying differences between the hype cycles in the two countries about the same product. The results show the similarity between the two countries with the statistical significance. Next, comparative analysis between search traffic and supply rate for several products in Korea was conducted to check out their patterns. According to the analysis, all the products seem to be at the "Peak of inflated expectations" in the hype cycles and they are similar to one another in the hype cycle. This study is of significance in aspects of expanding the scope of hype cycle analysis with web-search traffic because it introduced domestic web-search traffic analysis from Naver to analyse consumers' expectations in Korea by comparison with that from Google in other countries. In addition, this research can help to explain social phenomina more persuasively with search traffic and to give scientific objectivity to the hype cycle model. Furthermore, it can contribute to developing strategies of companies, such as marketing strategy.

• Microbiology and Biotechnology Letters
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• v.48 no.1
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• pp.57-63
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• 2020

Over the past 20 years, global warming has transformed the marine ecosystem of the Jeju Island into a subtropical zone making it conducive to the production of tropical fishes. Recently, the balloon fish (Diodon holoanthus) has been found off the coast of the Jeju Island. In this study, we analyzed the diversity of its intestinal microorganisms as a representative for the surrounding environment. In addition, the isolates were evaluated for their antibacterial activity. A total of 161 strains of various species were identified and isolated using 16S ribosomal RNA gene sequence analysis. They were separated into three groups, of which Phylum Proteobacteria was found to be the most dominant with 91% sequence similarity. This includes the class γ-proteobacteria that is made up of twelve genera and twenty-four hundred species. The second group comprised strains of the genus Vibrio, made up of 35% Photobacteria, 32% Shewanella, and 6% Psychrobacter. It was also determined that 4% of the isolates were Acinetobacter, 3% were Enterovibrio, while Moraxella_g2 accounted for 1% of the total isolates. Class α-proteobactera includes five genera and five species; Brevundimonas, Allorhizobium, Pseudoceanicola and Erythrobcter, each accounting for 1% of the total isolates. The Firmicute strains belonged to six genera and ten species. 5% of the strains were Terribacillus, while Paenibacillus, Salinicoccus, Staphylococcus and Streptococcus accounted for 1% each of the total isolates. Actinobacteria accounted for the final phylum with strains belonging to three genera and ten species with Janibacter, Micrococcus and Isoptericola each accounting for 1% of the total isolates.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.12
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• pp.1939-1949
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• 2008

The purpose of this study was to identify differences or similarities across the ensembles of 2006 F/W fashion trends in the big fashion centers such as Paris, London, New York, and Seoul, by street fashion research. The study focuses on understanding of localized fashion trend in the marketplace. We used photograph observation and analyzed data by SPSS program. We found there is a significant difference in winter outfits at these different global fashion mega cities. Most Korean women were wearing light colored outer jackets and blue jeans were dominant style for pants. The majority of Paris/London, New York and Seoul people on the street were wearing wool/wool like coat. Padded coats were worn more by New Yorkers than by people in Seoul. For the bottom, there is a similarity between Paris/London, and New York City, in that skinny pants were popular. Koreans were wearing skinny pants mostly, but the percentage of mini skirts/shorts was also higher than any other cities. We found that the cross-cultural fashion mega trend is similar in clusters, but there is a slight difference of trend in clothing color, style and design details, and accessories by localized fashion cities. Not only direct observation but also identification of cultural characteristics and consumer behavior through the years will bring much more contributions to apparel industries.

• The Korean Journal of Mycology
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• v.29 no.1
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• pp.34-40
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• 2001

RAPD test and the observation of morphological, cultural characteristics of fourteen selected entomogenous fungi were conducted to investigate the analysis of their internal relationships. Paecilomyces tenuipes showed snow flower form attached to numerous white conidiophores, produced globular and semi-egg types on the club types of phialides. Cordyceps militaris formed globosely conidiophores, dark yellow fruiting body on pupa. The phialide as on Acremonium-type in global conidiophores. Beauveria bassiana covered with conidia was not formed fruiting body and adhered conidia on conidiophore of zigzag type. The PDA and SDAY medium were confirmed as an optimum growth of them. P. tenuipes showed to velvet and plane types in several media whereas C. militaris was belong to centrally raised and floccose in the morphological type. In contrast, B. bassiana covered with conidia on velvet shape. The size of amplified products were analyzed by RAPD using URP primer and were from 100 bp to 2.0 kb with $10{\sim}14$ geuomic DNA. Total similarities of two groups were by dendrogram of UPGMA analysis. The homology of P. tenuipes groups was 94.8 to 100%. It also showed 70.1 to 96.6% in C. militaris group and B. bassiana was higher similarity than any other. The internal change of C. militaris, produced telemorph fruiting body, was higher seperated in species than P. tenuipes and B. bassiana in the RAPD.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.473-481
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• 2005

In this paper, we propose an image segmentation method preserving object's boundaries by using the number of quantized colors and merging regions using adaptive threshold values. First of all, the proposed method quantizes an original image by a vector quantization and the number of quantized colors is determined differently using PSNR each image. We obtain initial regions from the quantized image, merge initial regions in CIE Lab color space and RGB color space step by step and segment the image into semantic regions. In each merging step, we use color distance between adjacent regions as similarity-measure. Threshold values for region-merging are determined adaptively according to the global mean of the color difference between the original image and its split-regions and the mean of those variations. Also, if the segmented image of RGB color space doesn't split into semantic objects, we merge the image again in the CIE Lab color space as post-processing. Whether the post-processing is done is determined by using the color distance between initial regions of the image and the segmented image of RGB color space. Experiment results show that the proposed method splits an original image into main objects and boundaries of the segmented image are preserved. Also, the proposed method provides better results for objective measure than the conventional method.

• Journal of Microbiology and Biotechnology
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• v.12 no.1
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• pp.114-120
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• 2002

A 1,989-bp genomic region encoding nickel resistance genes was isolated from Legionella pneumophila, a pathogen for legionellosis. From a sequencing and computer analysis, the region was found to harbor two structural genes, a nreB-like protein gene (1,149 bp) and a nreA-like protein gene (270 bp), in a row. Both genes exhibited a significant degree of similarity to the corresponding genes from Synechocystis sp. PCC6803 ($54\%$ amino acid sequence identity) and Achromobacter xylosoxidans 31A ($76\%$). The gene was successfully expressed in E. coli MG1655 and conferred a nickel resistance of up to 5 mM in an LB medium and 3 mM in a TMS medium including gluconate as the sole carbon source. E. coli harboring the nickel resistance gene also exhibited a substantial resistance to cobalt, yet no resistance to cadmium or zinc. Since the extracellular concentration of nickel remained constant during the whole period of cultivation, it was confirmed that the nickel resistance was provided by an efflux system like the $Ni^2＋$permease (nrsD) of Synechocystis sp. strain PCC6803. Since polyphosphate (poly-P) is known as a global regulator for gene expression as well as a potential virulence factor in E. coli, the nickel resistance of a ppk mutant of E. coli MG 1655 harboring the nickel resistance gene from L. pneumophila was compared with that of its parental strain. The nickel resistance was significantly attenuated by ppk inactivation, which was more pronounced in an LB medium than in a TMS medium.

• Journal of KIISE:Software and Applications
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• v.35 no.11
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• pp.671-680
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• 2008

Motion capture devices have been utilized in producing several contents, such as movies and video games. However, since motion capture devices are expensive and inconvenient to use, motions segmented from captured data was recycled and synthesized to utilize it in another contents, but the motions were generally segmented by contents producers in manual. Therefore, automatic motion segmentation is recently getting a lot of attentions. Previous approaches are divided into on-line and off-line, where ow line approaches segment motions based on similarities between neighboring frames and off-line approaches segment motions by capturing the global characteristics in feature space. In this paper, we propose a graph-based high-level motion segmentation method. Since high-level motions consist of repeated frames within temporal distances, we consider similarities between neighboring frames as well as all similarities among all frames within the temporal distance. This is achieved by constructing a graph, where each vertex represents a frame and the edges between the frames are weighted by their similarity. Then, normalized cuts algorithm is used to partition the constructed graph into several sub-graphs by globally finding minimum cuts. In the experiments, the results using the proposed method showed better performance than PCA-based method in on-line and GMM-based method in off-line, as the proposed method globally segment motions from the graph constructed based similarities between neighboring frames as well as similarities among all frames within temporal distances.

• KIISE Transactions on Computing Practices
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• v.22 no.12
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• pp.646-653
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• 2016

Outbound market is a rapidly growing global industry, and has evolved into a 11 trillion won trade. A lot of recommender systems, which are based on collaborative and content filtering, target the existing purchase log or rely on studies based on similarity of products. These researches are not highly efficient as data was not obtained in advance, and acquiring the overwhelming amount of data has been relatively slow. The characteristics of an outbound product are that it should be purchased at least twice in a year, and its pricing should be in the higher category. Since the repetitive purchase of a product is rare for the outbound market, the old recommender system which profiles the existing customers is lacking, and has some limitations. Therefore, due to the scarcity of data, we suggest an improved customer-profiling method using web usage mining, algorithm of association rule, and rule-based algorithm, for faster recommender system of outbound product.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.125-134
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• 2012

In this paper, we propose a method to analyze M:N corresponding relations in semantic matching, especially focusing on feature class matching. Similarities between any class pairs are measured by spatial objects which coexist in the class pairs, and corresponding classes are obtained by clustering with these pairwise similarities. We applied a graph embedding method, which constructs a global configuration of each class in a low-dimensional Euclidean space while preserving the above pairwise similarities, so that the distances between the embedded classes are proportional to the overall degree of similarity on the edge paths in the graph. Thus, the clustering problem could be solved by employing a general clustering algorithm with the embedded coordinates. We applied the proposed method to polygon object layers in a topographic map and land parcel categories in a cadastral map of Suwon area and evaluated the results. F-measures of the detected class pairs were analyzed to validate the results. And some class pairs which would not detected by analysis on nominal class names were detected by the proposed method.