• 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 Yeungnam Medical Science
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• v.4 no.2
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• pp.65-73
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• 1987

To know the prevalence of the diabetes mellitus and associated diseases, we analysed the data of the 3,088 subjects who were examined with the Computed Automated Medi-Screening Test System which consisted of 65 parameters including blood glucose determination fasting and one hour after 100g of oral glucose load. We grouped the subjects by the modified criteria of National Diabetic Data Group. Followings are the results of the various analysis : 1. The prevalence of diabetes mellitus and impaired glucose tolerance is 2.27% and 18.26% respectively. 2. The prevalence of diabetes mellitus is 2.63% In male and 1.66% in female. There is no statistically significant difference between male and female. 3. There is tendency of increasing prevalence of diabetes mellitus as the age increases. From second to eighth decade, the prevalence of diabetes mellitus Increases as 0.0, 0.45, 0.67, 2.28, 3.47, 5.36, 10.00% respectively. 4. There is no statistically significant difference of prevalence of obesity between normal and diabetes: that is, 18.03%, 22.86% respectively.($P{\geq}0.1$) 5. There is no statistically significant difference of prevalence of impaired glucose tolerance and diabetes between non-obese and obses group. ($P{\geq}0.1$) 6. There is statistically significant increases of frequency of proteinuria, azotemia, hypertension as the glucose tolerance decreases. ($P{\leq}0.05$)

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2551-2562
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• 2013

Since 2006, an Intelligent Excavation Robot which automatically performs the earth-work without operator has been developed in Korea. The technologies for automatically recognizing the terrain of work environment and detecting the objects such as obstacles or dump trucks are essential for its work quality and safety. In several countries, terrestrial 3D laser scanner and stereo vision camera have been used to model the local area around workspace of the automated construction equipment. However, these attempts have some problems that require high cost to make the sensor system or long processing time to eliminate the noise from 3D model outcome. The objectives of this study are to analyze the advantages of the existing 3D modeling sensors and to examine the applicability for practical use by using Analytic Hierarchical Process(AHP). In this study, 3D modeling quality and accuracy of modeling sensors were tested at the real earth-work environment.

• Bulletin of the Korean Chemical Society
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• v.26 no.5
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• pp.729-734
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• 2005

A sensitive and selective method for quantitation of sofalcone and its active metabolite in human plasma has been established using liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI/MS/MS). Plasma samples were transferred into 96-well plate using an automated sample handling system and spiked with 10 $\mu$L of 2 $\mu$g/mL $d_3$-sofalcone and $d_3$-sofalcone metabolite solutions (internal standard), respectively. After adding 0.5 mL of acetonitrile to the 96-well plate, the plasma samples were then vortexed for 30 sec. After centrifugation, the supernatant was transferred into another 96-well plate and completely evaporated at 40 ${^{\circ}C}$ under a stream of nitrogen. Dry residues were reconstituted with mobile phase and were injected into a $C_{18}$ reversed-phase column. The limit of quantitation of sofalcone and its metabolite was 2 ng/mL, using a sample volume of 0.2 mL for analysis. The reproducibility of the method was evaluated by analyzing 10 replicates over the concentration range of 2 ng/mL to 1000 ng/mL. The validation experiments of the method have shown that the assay has good precision and accuracy. Sofalcone and its metabolite produced a protonated precursor ion ([M+H]$^+$) of m/z 451 and 453, and a corresponding product ion of m/z 315 and 317, respectively. Internal standard ($d_3$-sofalcone and $d_3$-sofalcone metabolite) produced a protonated precursor ion ([M+H]$^+$) of m/z 454 and 456 and a corresponding product ion of m/z 315 and 317, respectively. The method has been successfully applied to a pharmacokinetic study of sofalcone and its active metabolite in human plasma.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.4
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• pp.409-415
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• 2020

Low-flow mortar injection method grouting technology was selected and the traffic area was preserved as much as possible in order to secure safety for road traffic when the outflow and subsidence of landfill occurred due to ground-water, and etc. In particular, the current existing method was newly improved since there are risks of damage such as hydraulic fracturing at the lower part of the road, spilling of soil particles on steep slopes, and bumps on the road due to excessive injection pressure during construction. This study was carried out at the site of reinforcement work on the road as a maintenance work for the danger zone for collapse of the steep slope of the 00 hill, which was ordered from the 00 city 00 province. The improved low-flow mortar type grouting method adopted a new automated grouting management system and especially, it composites the method for grouting conditions decision by high-pressure pre-grouting test and injection technology by AGS-controlled and studied about grouting effect analysis by using new technology. By applying the improved low-flow mortar type grouting method, it was possible to lay the groundwork for road maintenance work such as the prevention of subsidence of old roads, uneven subsidence of buildings and civil engineering structures, and of soil leakage of ground-water spills. Furthermore, the possibility of application on future grouting work not only for just construction that prevents subsidence of old roads but also for various buildings and civil engineering structures such as railroads, subways, bridges, underground structures, and boulder stone and limestone areas was confirmed.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.123-133
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• 2019

This study analyzed the surface temperature mitigation effect of wetlands during cold waves (below -12℃ from January to February) and heat waves (above 33℃ from July to August) in 2018. We used Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Daytime and Nighttime Land Surface Temperature (LST) product, and the maximum and minimum air temperature observed at 86 stations of Korea Meteorological Administration (KMA). For the cold wave analysis, the LST of Terra MODIS nighttime was the highest at forest area with -12.7℃, followed by upland crop and wetland areas of -12.9℃ and -13.0℃ respectively. The urban area showed the lowest value of -14.4℃. During the heat wave, the urban area was the highest with + 34.6℃ in Aqua MODIS LST daytime. The wetland area was + 33.0℃ showing - 1.6℃ decrease comparing with urban area.

• Journal of the Korea Computer Graphics Society
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• v.12 no.4
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• pp.23-32
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• 2006

In recent years, since the digital camera has been popularized, so users can easily collect hundreds of photos in a single usage. Thus the managing of hundreds of digital photos is not a simple job comparing to the keeping paper photos. We know that managing and classifying a number of digital photo files are burdensome and annoying sometimes. So people hope to use an automated system for managing digital photos especially for their own purposes. The previous studies, e.g. content-based image retrieval, were focused on the clustering of general images, which it is not to be applied on digital photo clustering and classification. Recently, some specialized clustering algorithms for images clustering digital camera images were proposed. These algorithms exploit mainly the statistics of time gap between sequent photos. Though they showed a quite good result in image clustering for digital cameras, still lots of improvements are remained and unsolved. For example the current tools ignore completely the image transformation with the different focal lengths. In this paper, we present a photo considering focal length information recorded in EXIF. We propose an algorithms based on MVA(Matching Vector Analysis) for classification of digital images taken in the every day activity. Our experiment shows that our algorithm gives more than 95% success rates, which is competitive among all available methods in terms of sensitivity, specificity and flexibility.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.101-109
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• 2014

It is an essential element for the establishment of image processing related systems to find the exact contour from the image of an arbitrary object. In particular, if a vision system is established to inspect the products in the automated production process, it is very important to detect the contours for standardized shapes such lines and curves. In this paper, we propose a prototype adaptive dynamic contour model, p-Snake with improved contour extraction algorithms by adding the prototype energy. The proposed method is to find the initial contour by applying the existing Snake algorithm after Sobel operation is performed for prototype analysis. Next, the final contour of the object is detected by analyzing prototypes such as lines and circles, defining prototype energy and using it as an additional energy item in the existing Snake function on the basis of information on initial contour. We performed experiments on 340 images obtained by using an environment that duplicated the background of an industrial site. It was found that even if objects are not clearly distinguished from the background due to noise and lighting or the edges being insufficiently visible in the images, the contour can be extracted. In addition, in the case of similarity which is the measure representing how much it matches the prototype, the prototype similarity of contour extracted from the proposed p-ACM is superior to that of ACM by 9.85%.

• Journal of the Korea Convergence Society
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• v.7 no.5
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• pp.29-34
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• 2016

Recently, with the development of high-tech industry, the use of the drones in various aspects of daily life is rapidly advancing. With technical and functional advancements, drones have an advantage of being easy to be utilized in the areas of use according to various lifestyles. In addition, through the diversification of the drone service converged with image processing medium such as camera and CCTV, an automated security system that can replace humans is expected to be introduced. By designing these unmanned security technology, a new convergence security drone service techniques that can strengthen the previous drone application technology will be proposed. In the proposed techniques, a biometric authentication technology will be designed as additional authentication methods that can determine the safety incorporated with security by selecting the search and areas of an object focusing on the objects in the initial windows and search windows through OpenCV technology and CAM-Shift algorithm which are an object tracking algorithm. Through such, a highly efficient security drone convergence service model will be proposed for performing unmanned security by using the drones that can continuously increase the analysis of technology on the mobility and real-time image processing.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.83-96
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• 2018

Extracting keywords representing documents is very important because it can be used for automated services such as document search, classification, recommendation system as well as quickly transmitting document information. However, when extracting keywords based on the frequency of words appearing in a web site documents and graph algorithms based on the co-occurrence of words, the problem of containing various words that are not related to the topic potentially in the web page structure, There is a difficulty in extracting the semantic keyword due to the limit of the performance of the Korean tokenizer. In this paper, we propose a method to select candidate keywords based on semantic similarity, and solve the problem that semantic keyword can not be extracted and the accuracy of Korean tokenizer analysis is poor. Finally, we use the technique of extracting final semantic keywords through filtering process to remove inconsistent keywords. Experimental results through real web pages of small business show that the performance of the proposed method is improved by 34.52% over the statistical similarity based keyword selection technique. Therefore, it is confirmed that the performance of extracting keywords from documents is improved by considering semantic similarity between words and removing inconsistent keywords.