• Korean Journal of Cognitive Science
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• v.26 no.2
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• pp.147-165
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• 2015

Through short-answer questions, we can reflect the depth of students' understanding and higher-order thinking skills. Scoring for short-answer questions may take long time and may be an issue on consistency of grading. To alleviate such the suffering, automated scoring systems are widely used in Europe and America, but are in the initial stage in research in Korea. In this paper, we propose a semi-automatic scoring system for short Korean free-text responses using semi-supervised learning. First of all, based on the similarity score between students' answers and model answers, the proposed system grades students' answers and the scored answers with high reliability have been included in the model answers through the thorough test. This process repeats until all answers are scored. The proposed system is used experimentally in Korean and social studies in Nationwide Scholastic Achievement Test. We have confirmed that the processing time and the consistency of grades are promisingly improved. Using the system, various assessment methods have got to be developed and comparative studies need to be performed before applying to school fields.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.117-125
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• 2023

In the development of clothing design through virtual simulation, it is essential to minimize the differences between the virtual and the real world as much as possible. The most critical task to enhance the similarity between virtual and real garments is to find simulation parameters that can closely emulate the physical properties of the actual fabric in use. The simulation parameter optimization process requires manual tuning by experts, demanding high expertise and a significant amount of time. Especially, considerable time is consumed in repeatedly running simulations to check the results of applying the tuned simulation parameters. Recently, to tackle this issue, artificial neural network learning models have been proposed that swiftly estimate the results of drape test simulations, which are predominantly used for parameter tuning. In these earlier studies, relatively simple linear stiffness models were used, and instead of estimating the entirety of the drape mesh, they estimated only a portion of the mesh and interpolated the rest. However, there is still a scarcity of research on non-linear stiffness models, which are commonly used in actual garment design. In this paper, we propose a learning model for estimating the results of drape simulations for non-linear stiffness models. Our learning model estimates the full high-resolution mesh model of drape. To validate the performance of the proposed method, experiments were conducted using three different drape test methods, demonstrating high accuracy in estimation.

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.4
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• pp.195-203
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• 2006

An antagonistic strain, Burkholderia MP-1, showed antimicrobial activity against various filamentous plant pathogenic fungi, yeasts and food borne bacteria (Gram-positive and Gram-negative). The nucleotide sequence of the 16S rRNA gene (1491 pb) of strain MP-1 exhibited close similarity (99-100%) with other Burkholderia 16S rRNA genes. Isolation of the antibiotic substances from culture broth was fractionated by ethyl acetate (EtOAc) solvent and EtOAc-soluble acidic fraction. The antibiotic substances were purified through a silica gel, Sephadex LH-20, ODS column chromatography, and high performance liquid chromatography, respectively. Four active substances were identified as phenylacetic acid, hydrocinnamic acid, 4-hydroxyphenylacetic acid and 4-hydroxyphenylacetate methyl ester by gas chromatographic-mass spectrum analysis. The minimum inhibition of concentration (MIC) of each active compound inhibited the growth of the microorganisms tested at 250 to $2500{\mu}g\;ml^{-1}$. The antimicrobial activity of crude acidic fraction at 1 mg of dry weight per 6 mm paper disc was more effective than authentic standard mixture (four active substances were mixed with the same ratio as acidic fraction) over a wide range of bacterial test.

• 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 Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.115-123
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• 2016

The road name address system has been in effect in Korea since 2012. However, the existing address system is still being used in many fields because of the difference between the spatial awareness of people and the road name address system. For the spatial awareness based on the road name address system, various spatial datasets in daily life should be referenced by the road names. The goal of this paper is to link the road name address system with the wayfinding process, which is closely related to the spatial awareness. To achieve our goal, we designed and implemented a geometric matching method for spatial data sets. This method generates network neighborhoods from road objects in the 'road name address map' and the 'pedestrian network data'. Then it computes the geometric similarities between the neighborhoods to identify corresponding road name for each object in the network data. The performance by F0.5 was assessed at 0.936 and it was improved to 0.978 by the manual check for 10% of the test data selected by the similarity. By help of our method, the road name address system can be utilized in the wayfinding services, and further in the spatial awareness of people.

• The Korean Journal of Mycology
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• v.41 no.1
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• pp.14-20
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• 2013

We already reported four groups which contains some similar strains based on URP-PCR in the previous paper. The objective of this study was to confirm those strains by the amplified fragment length polymorphism (AFLP) and vegetative compatibility group (VCG). AFLP analysis showed no difference among these strains except ASI 2595 and 2183 in Weonhyeong group and ASI 2829 in Suhan group. They showed specific DNA bands only in the result of P + AG/M + AAG and P + GT/M + ATG primer combinations out of eight different combinations. The AFLP primers produced a total of 330 fragments between 80 and 1000 bp in length for 31 Pleurotus ostreatus strains. At a genetic similarity of 0.96, the UPGMA analysis separated the isolates into four distinct clusters. Each group was classified by similar strains. Confrontation test by vegetative compatibility groups (VCGs) also showed distinct line between strains from different groups, but no line between similar strains within the cluster. Our results indicate that most of similar strains was not distinctness. Thus, similar strains are considered to be very close on the genealogy of their parent or same strain with different name.

• Journal of Korea Multimedia Society
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• v.7 no.9
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• pp.1282-1293
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• 2004

This paper proposes an asymmetric watermarking system using Public Key Infrastructure. The distinguishing characteristic of the proposed method connects between the two different techniques, cryptography technique and watermarking technique, by using the authentication technique. The connection between the two techniques are established based on the special qualities of each technique. Watermarks that are inserted into the digital contents consist of a digital signature described as an encrypted copyright information with the private key of a distributor or a copyright holder, and an authentication code. In the situation where the ownership of the digital contents has to be decided, authentication technique examines the data integrity of the digital contents based on an authentication and decides the ownership of the digital contents by examining whether it satisfies or not satisfies the integrity test. The formal case uses decryption method which compares the user defined copyright information, and the decrypted copyright information extracted from the watermark in the digital contents that are decrypted by distributors' public key The latter case determines the ownership by comparing the similarity between encrypted copyright information separated from the watermark that are extracted from the digital contents, and the user defined encrypted copyright information that are separated from the watermark The proposed method provides protection from the assault which attempts to identify or erase the encoding key.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1418-1432
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• 1997

Most general content_based image retrieval techniques use color and texture as retrieval indices. In color techniques, color histogram and color pair based color retrieval techniques suffer from a lack of spatial information and text. And This paper describes the design and implementation of content_based image retrieval system using color space and keywords. The preprocessor for image retrieval has used the coordinate system of the existing HSI(Hue, Saturation, Intensity) and preformed to split One image into chromatic region and achromatic region respectively, It is necessary to normalize the size of image for 200*N or N*200 and to convert true colors into 256 color. Two color histograms for background and object are used in order to decide on color selection in the color space. Spatial information is obtained using a maximum entropy discretization. It is possible to choose the class, color, shape, location and size of image by using keyword. An input color is limited by 15 kinds keyword of chromatic and achromatic colors of the Korea Industrial Standards. Image retrieval method is used as the key of retrieval properties in the similarity. The weight values of color space ${\alpha}(%)and\;keyword\;{\beta}(%)$ can be chosen by the user in inputting the query words, controlling the values according to the properties of image_contents. The result of retrieval in the test using extracted feature such as color space and keyword to the query image are lower that those of weight value. In the case of weight value, the average of te measuring parameters shows approximate Precision(0.858), Recall(0.936), RT(1), MT(0). The above results have proved higher retrieval effects than the content_based image retrieval by using color space of keywords.

• Journal of Broadcast Engineering
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• v.14 no.6
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• pp.661-675
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• 2009

The carelessly and illegally copied contents are raising serious social problem as internet and multimedia technologies are advancing. Therefore, development of video copy detection system must be settled without delay. In this paper, we propose the hierarchical video copy detection method that estimates similarity using statistical characteristics between original video and manipulated(transformed) copy video. We rank according to luminance value of video to be robust to spacial transformation, and choose similar videos categorized as candidate segments in huge amount of database to reduce processing time and complexity. The copy videos generally insert black area in the edge of the image, so we remove rig black area and decide copy or not by using statistical characteristics of original video and copied video with center part of frame that contains important information of video. Experiment results show that the proposed method has similar keyframe accuracy to reference method, but we use less memory to save feature information than reference's, because the number of keyframes is less 61% than that of reference's. Also, the proposed method detects if the video is copied or not efficiently despite expansive spatial transformations such as blurring, contrast change, zoom in, zoom out, aspect ratio change, and caption insertion.

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.396-404
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• 2014

The field of searching clothing, which is very difficult due to the nature of the informal sector, has been in an effort to reduce the recognition error and computational complexity. However, there is no concrete examples of the whole progress of learning and recognizing for cloth, and the related technologies are still showing many limitations. In this paper, the whole process including identifying both the person and cloth in an image and analyzing both its color and texture pattern is specifically shown for classification. Especially, deformable search descriptor, LBPROT_35 is proposed for identifying the pattern of clothing. The proposed method is scale and rotation invariant, so we can obtain even higher detection rate even though the scale and angle of the image changes. In addition, the color classifier with the color space quantization is proposed not to loose color similarity. In simulation, we build database by training a total of 810 images from the clothing images on the internet, and test some of them. As a result, the proposed method shows a good performance as it has 94.4% matching rate while the former Dense-SIFT method has 63.9%.