• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

• Tuberculosis and Respiratory Diseases
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• v.45 no.5
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• pp.984-991
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• 1998

Background: The 3p deletions has been shown to be the most frequent alteration in lung cancers, strongly suggesting the presence of at least one tumor suppressor gene in this chromosomal region. However, no solid candidate for the tumor suppressor gene(s) on 3p has as yet been identified. Recent attention has focused on a candidate 3p14.2 tumor suppressor gene, FHIT, which is located in a region that is homozygously deleted in multiple tumor cell lines and disrupted by the hereditary renal cell carcinoma t(3;8) chromosomal translocation breakpoint FHIT also spans FRA3B, the most common fragile sites in the human genome. In the present study, we have analyzed expression of the FHIT gene in lung cancer cell lines. Methods: RNA from 21 lung cancer cell lines (16 NSCLC, 5 SCLC) were extracted using standard procedures. Random-primed. first strand cDNAs were synthesized from total RNA and PCR amplication of coding exons 5 to 9 was performed. The RT-PCR products were electrophoresed in 1.5% ethidium bromide-stained agarose gels. Results: 12 of 21(57%) lung cancer cell lines exhibited absent or aberrant FHIT expression [7 of 16(44%) of non-small cell lung cancer and 5 of 5(100%) of small cell lung cancer cell lines]. Conclusion: The result shows that abnormal transcription of the FHIT gene is common in human lung cancer cell lines, especially in small cell lung cancer.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.11
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• pp.140-149
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• 1996

Cursive characters are written on an economical principle to reduce the motion of a pen in the limit of distinction between characters. That is, the pen is not lifted up to move for writing a next stroke, the pen is not moved at all, or connected two strokes chance their shapes to a similar and simple shape which is easy to be written. For these reasons, strokes and korean alphabets are not only easy to be changed, but also difficult to be splitted. In this paper, we propose a curvature stroke modeling method for splitting and matching by using a structural primitive. A curvature stroke is defined as a substroke which does not change its curvanture. Input strokes handwritten in a cursive style are splitted into a sequence of curvature strokes by segmenting the points which change the direction of rotation, which occur a sudden change of direction, and which occur an excessive rotation Each reference of korean alphabets is handwritten in a printed style and is saved as a sequence of curvature strikes which is generated by splitting process. And merging process is used to generate various sequences of curvature strikes for matching. Here, it is also considered that imaginary strokes can be written or omitted. By using a curvature stroke as a unit of recognition, redundant splitting points in input characters are effectively reduced and exact matching is possible by generating a reference curvature stroke, which consists of the parts of adjacent two korean alphasbets, even when the connecting points between korean alphabets are not splitted. The results showed 83.6% as recognition rate of the first candidate and 0.99sec./character (CPU clock:66MHz) as processing time.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.79-79
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• 2010

다른 물질에 비해 많은 우수한 특성을 가지고 있는 CuInSe2(CIS)박막 태양전지는 많은 연구자들에 의해 개발되어 오고 있다. CIS의 대표적인 장점으로는 직접천이형 밴드갭, 높은 흡수계수, 열 안정화상태 및 p형으로의 전도성물질의 가능성 등 다양하다. 또한 간단한 구조를 이용하여 유리같은 싼 기판을 이용하기 때문에 저가형 태양전지로서 많은 각광을 받고 있다. CIGS태양전지는 CIS의 In 사이트에 Ga을 도핑함으로서 만들어지는데 밴드갭은 약 1.4eV이다. CIS박막을 만드는 많은 방법이 존재하나 구성원소로부터 최적화된 조성을 찾을수 있는 방법이 가장 중요한 요소 중의 하나로 인식되고 있으며, 이런점에서 증발법 및 스퍼터링법 등 같은 진공방식이 비진공방식에 비해 훨씬 간편하게 조성비를 맞출수 있다. 그 중에 스퍼터링법은 대면적 박막태양전지로의 가능성으로 비출어 볼때 산업화를 위한 좋은 후보군이 될 수 있다. Selenization을 하기전에 Cu-In-Se의 전구체 조합은 여러개의 타겟으로부터 동시 스퍼터링법이나 다층 전구체법을 사용하여 준비되는데 어떤 방법이 되던지 Se의 부가적인 공급은 불가피하다. 지금까지 많은 관련 연구의 대부분인 구조적, 조성비적 그리고 광학적인 특성평가에 집중되어 오고 있는데, 전기적특성평가의 경우는 면저항, 비저항 같은 간단한 결과 위주로 보고되어 오고 있다. 또한 캐리어농도와 이동도에 대한 보고가 있음에도 불구하고 이해되기에는 충분치 못한 면이 많다.본 발표에서는 태양전지 제조 전단계로서 소다라임유리기판(SLG)위에 Mo의 유무에 따라 CIS박막의 전기적인 특성 변화에 대한 내용을 담고 있다. 소다라임유리($2cm{\times}2cm$)를 기판으로 사용하여 아세톤-에탄올 용액에 초음파세척을 수행하고, Mo 후면전극을 DC 스퍼터링방식을 이용하여 증착을 한다. SLG와 Mo이 코팅된 SLG를 각각 RF 스퍼터 챔버에 이송한 후 수증기 제거를 위해 약 10분간 예열을 한다. 샘플에 대한 전기적특성은 Hall효과 측정장치에 의해 측정이 되며 전기전도도, 캐리어농도, 이동도 및 전도형에 대한 정보가 각각의 변수에 따라 조사된돠. 부가적으로 구조적, 조성비적인 특성을 SEM,XRD 및 EDX를 통해 조사를 하여 전기적 특성에 따른 관계성을 검토한다. SLG와 Mo가 코팅된 SLG위의 CIS박막은 전기적으로 약간 다른 특성을 보일 것으로 예측되며, 이러한 기대를 바탕으로 조성비가 이상적인 화학양론에 근접할 때 p형으로서 제시될 수 있다는 것을 보여줄 것이다.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.181-194
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• 2017

This study aims to develop a regression model for forest volume estimation using field-collected forest inventory information and airborne LiDAR data. The response variable of the model is forest stem volume, was measured by random sampling from each individual plot of the 30 circular sample plots collected in Bonghwa-gun, Gyeong sangbuk-do, while the predictor variables for the model are Height Percentiles(HP) and Height Bin(HB), which are metrics extracted from raw LiDAR data. In order to find the most appropriate model, the candidate models are constructed from simple linear regression, quadratic polynomial regression and multiple regression analysis and the cross-validation tests were conducted for verification purposes. As a result, $R^2$ of the multiple regression models of $HB_{5-10}$, $HB_{15-20}$, $HB_{20-25}$, and $HBgt_{25}$ among the estimated models was the highest at 0.509, and the PRESS statistic of the simple linear regression model of $HP_{25}$ was the lowest at 122.352. $HB_{5-10}$, $HB_{15-20}$, $HB_{20-25}$, and $HBgt_{25}-based$ models, thus, are comparatively considered more appropriate for Korean forests with complicated vertical structures.

• Communications of Mathematical Education
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• v.30 no.1
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• pp.67-83
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• 2016

Correcting an imbalance between cognitive and affective aspects of mathematics in schools is recognized as a crucial issue with regards to mathematics education in Korea. Therefore, research and studies about affective aspects have been increasing and themes relating to affective aspects were diverse. Their theme included the improvement of affective aspect, investigation of factors of affective aspect, and development of measurement tools for affective aspect. The purpose of this study is to analyze and organize the research that has been done with respect to affective aspect and drive trend, implication, and their instruction to mathematics education. This study has investigated 103 studies released from 2005 to 2015 on KCI, Korea Citation Index. The results of this study are as follow. First, since released research of affective aspects in mathematics has not increased in number in the last 11 years, academic interest in the affective aspects seems lower than recent interest arousing in Korea. Second, most studies utilized quantitative research as a tool to analyze phenomena and the cause and effect of affective aspects. Third, middle school students were the most common subjects of the studies, followed by elementary school students. Fourth, the studies had various themes such as analyzing the cause and effect of affective aspect, recognizing changes of affective aspects, and measuring affective aspects. The studies, especially, focused most on analyzing how to improve affective aspects by applying it to programs such as mathematic activities and solving mathematic problems. It is necessary for future research to have a long-term perspective and to provide a space for communication. Research should not only focus on how recognize affective aspects differently, which is based on its cultural background, but also to draw affective solutions from them.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.6
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• pp.623-629
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• 2002

In transmitting compressed video bit-stream over Internet, packet losses cause error propagations in both spatial and temporal domains, which in turn leads to severe degradation I image quality. In this paper, a new error concealment algorithm, called EBMA(Edge Detection based Boundary Matching Algorithm), is proposed to repair damaged portions of the video frames in the receiver. Conventional BMA(Boundary Matching Algorithm) assumes that the pixels on the boundary of the missing block and its neighboring blocks are very similar, but has no consideration of edges across the boundary. In our approach, the edges are detected across the boundary of the lost or erroneous block. Once the orientation of each edge is found, only the pixel difference along the expected edges across the boundary is measured instead of the calculation of difference along the expected edges across the boundary is measured instead of the calculation of differences between all adjacent pixels on the boundary Therefore, the proposed approach needs very few computations and the experiment shows and improvement of the performance over the conventional BMA in terms of both subjective and objective quality of video sequences.

• KSBB Journal
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• v.16 no.1
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• pp.41-47
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• 2001

H. pylori is known to be a key pathogen of chronic gastric and duodenal ulcers. Bacterial adhesion to hosts is an essential step for bacterial infection and the inhibition of this adhesion provides a possible method for the treatment of the infection. The inhibitory effect of antibody lgY, produced from immunized hens with H. pylori antigen, was studied in vitro. The inhibition of H. pylori adhesion to AGS was as high as 90% using 0.5mg/ml of lgY, and almost 80% of the detachmentwas also achieved. The inhibitory effect of adhesion-inhibition candidates was investigated. Additives in combination with lgY increased the adhesion-inhibiting effect by about 30-50%. However, the adhesion molecules of H. pylori were varied and complex, therefore the further studies are necessary to develop an adhesion inhibitor and effective enough to be employed for the treatment of H.pylori, in vivo.

• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.671-678
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• 2005

In this paper, we suggest an algorithm that allows us to extract the important obbject from motion pictures and then replace the background with arbitrary images. The suggested technique can be used not only for protecting privacy and reducing the size of data to be transferred by removing the background of each frame, but also for replacing the background with user-selected image in video communication systems including mobile phones. Because of the relatively large size of image data, digital image processing usually takes much of the resources like memory and CPU. This can cause trouble especially for mobile video phones which typically have restricted resources. In our experiments, we could reduce the requirements of time and memory for processing the images by restricting the search area to the vicinity of major object's contour found in the previous frame based on the fact that the movement of major object is not wide or rapid in general. Specifically, we detected edges and used the edge image of the initial frame to locate candidate-object areas. Then, on the located areas, we computed the difference image between adjacent frames and used it to determine and trace the major object that might be moving. And then we computed the contour of the major object and used it to separate major object from the background. We could successfully separate major object from the background and replate the background with arbitrary images.