• Journal of KIISE
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• v.43 no.8
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• pp.910-918
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• 2016

A tensor is a multi-dimensional array that represents many data such as (user, user, time) in the social network system. A tensor generator is an important tool for multi-dimensional data mining research with various applications including simulation, multi-dimensional data modeling/understanding, and sampling/extrapolation. However, existing tensor generators cannot generate sparse tensors like real-world tensors that obey power law. In addition, they have limitations such as tensor sizes that can be processed and additional time required to upload generated tensor to distributed systems for further analysis. In this study, we propose TeT, a distributed tera-scale tensor generator to solve these problems. TeT generates sparse random tensor as well as sparse R-MAT and Kronecker tensor without any limitation on tensor sizes. In addition, a TeT-generated tensor is immediately ready for further tensor analysis on the same distributed system. The careful design of TeT facilitates nearly linear scalability on the number of machines.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.301-307
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• 2018

The most of the IR focus on the method for searching the document, so the keyword-based IR system is not able to reflect the feature information of the image. In order to overcome these limitations, we have developed a system that can search similar images based on the vector information of images, and it can search for similar images based on sketches. The proposed system uses the GAN to up sample the sketch to the image level, convert the image to the vector through the CNN, and then retrieve the similar image using the vector space model. The model was learned using fashion image and the image retrieval system was developed. As a result, the result is showed meaningful performance.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.280-280
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• 2023

강수의 정확한 시·공간적 추정은 홍수 대응, 가뭄 관리, 수자원 계획 등 수문학적 모델링의 핵심 기술이다. 우주 기술의 발전으로 전지구 강수량 측정 프로젝트(Global Precipitation Measurement, GPM)가 시작됨에 따라 위성의 여러 센서를 이용하여 다양한 고해상도 강수량 자료가 생산되고 있으며, 기후변화로 인한 수재해의 빈도가 증가함에 따라 준실시간(Near-Real-Time) 위성 강수 자료의 활용성 및 중요성이 높아지고 있다. 하지만 준실시간 위성 강수 자료의 경우 빠른 지연시간(latency) 확보를 위해 관측 이후 최소한의 보정을 거쳐 제공되므로 상대적으로 강수 추정치의 불확실성이 높다. 이에 따라 본 연구에서는 앙상블 머신러닝 기반 수집된 위성 강수 자료들을 관측 자료와 병합하여 보정된 준실시간 강수량 자료를 생성하고자 한다. 모형의 입력에는 시단위 3가지 준실시간 위성 강수 자료(GSMaP_NRT, IMERG_Early, PERSIANN_CCS)와 방재기상관측 (AWS)의 온도, 습도, 강수량 지점 자료를 활용하였다. 지점 강수 자료의 경우 결측치를 고려하여 475개 관측소를 선정하였으며, 공간성을 고려한 랜덤 샘플링으로 375개소(약 80%)는 훈련 자료, 나머지 100개소(약 20%)는 검증 자료로 분리하였다. 모형의 정량적 평가 지표로는 KGE, MAE, RMSE이 사용되었으며, 정성적 평가 지표로 강수 분할표에 따라 POD, SR, BS 그리고 CSI를 사용하였다. 머신러닝 모형은 개별 원시 위성 강수 자료 및 IDW 기법보다 높은 정확도로 강수량을 추정하였으며 공간적으로 안정적인 결과를 나타내었다. 다만, 최대 강수량에서는 다소 과소추정되므로 이는 강수와 관련된 입력 변수의 개수 업데이트로 해결할 수 있을 것으로 판단된다. 따라서 불확실성이 높은 개별 준실시간 위성 자료들을 관측 자료와 병합하여 보정된 최적 강수 자료를 생성하는 머신러닝 기법은 돌발성 수재해에 실시간으로 대응 가능하며 홍수 예보에 신뢰도 높은 정량적인 강수량 추정치를 제공할 수 있다.

• Proceedings of the Korea Concrete Institute Conference
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• 2009.05a
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• pp.275-276
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• 2009

This paper provides a new approach for predicting the corrosion resistivity of reinforced concrete structures exposed to carbonation. In this method, the prediction can be updated successively by a Bayesian theory when additional data are available. The stochastic properties of model parameters are explicitly taken into account into the model. To simplify the procedure of the model, the probability of the durability limit is determined from the samples obtained from the Latin hypercube sampling technique. The new method may be very useful in designing important concrete structures and help to predict the remaining service life of existing concrete structures which have been monitored.

• Proceedings of the Safety Management and Science Conference
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• 2013.11a
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• pp.9-23
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• 2013

건설공사는 인력의존도가 가장 높으며 타 산업에 대비하여 자동화가 매우 낮고 외기에 노출된 작업 환경으로 추락 등의 중대재해 위험이 가장 높은 산업이다. e-나라지표에 의하면 2006년부터 2012년까지 전체 산업의 약 21.9%를 차지하는 건설 근로자가 생산 활동에 종사하고 있으며, 이직 및 인력의 이동이 매우 잦은 특성을 갖고 있다. 2006년~2012년까지의 재해발생 통계에 따르면 전체적으로 타 산업은 매년 다소간의 증감은 있으나 재해가 감소하는 추세이지만, 건설공사의 경우는 지속적으로 증가하고 있다. 특히, 사고성 사망재해의 경우는 7년간 전체 산업에서 발생하는 사고성 사망재해의 평균 40.9%를 건설업이 차지하고 있어 가장 높아 매우 심각한 수준이다. 또한 건설현장과 건설회사의 안전보건경영의 운영방법 및 제도가 매우 단순하고 정성적인 수준으로 타 산업에 비하여 안전경영의 정량화에 대한 노력이 매우 미약하다. 과거 재해사례 및 통계를 분석하여 앞으로의 재해 위험 요소를 제거하거나 안전한 상태로 형성하여야 하나, 발표되는 재해사례나 통계를 구호 또는 슬로건으로 전파, 교육하는 수준에 머물고 있다. 본 연구에서는 아파트공사를 대상으로 2006년~2011년의 과거 재해통계(8,687건)를 분석하여 데이터베이스화하고, 실제 공사한 아파트공사 샘플현장의 자료(89,375명)를 데이터베이스화하여 현 실정에 부합한 정량적 직종별 위험도를 산정하는 연구를 진행하였다. 따라서 아파트공사의 직종별 위험도를 정량적인 데이터로 산출하고, 과학적인 방법으로 현장 위험수준을 실시간 모니터링 함으로써 건설현장의 주된 생산력인 근로자의 생명과 건강을 보호할 수 있는 효과적인 재해예방이 이루어 질 것으로 기대된다.

• Culinary science and hospitality research
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• v.18 no.5
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• pp.63-79
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• 2012

The purpose of this study is to empirically determine the structural relationship between employee constructs such as internal service quality, employee satisfaction, and organization commitment and customer constructs such as perceived value, customer satisfaction, and loyalty to suggest an effective business strategy for restaurant business. To do this, the study consulted with the Korea Restaurant Association, the representative of Korean food service and got the intention of participating in the research from the Daegu branch. As a result, 51 restaurants registered in the Daegu branch who showed their intention to participate were selected as an initial sample. Also, other restaurants were introduced through snow-ball sampling method by the owners of restaurants who finished responding to the survey, and total 100 restaurants were examined. A survey was conducted to external customers who visited restaurants and internal customers working there. For final analysis, 741 questionnaires of internal customers and 970 questionnaires of external customers were used. The result of analysis showed that team-work & communication in internal service quality has a significant effect on employee satisfaction, employee satisfaction on organization commitment, and organization commitment on value perceived by customers. Also, perceived value has a significant effect on customer satisfaction and loyalty, and customer satisfaction on loyalty.

• Journal of the Korea Concrete Institute
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• v.20 no.1
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• pp.77-88
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• 2008

This paper provides a new approach for predicting the corrosion resistivity of reinforced concrete structures exposed to chloride attack. In this method, the prediction can be updated successively by a Bayesian theory when additional data are available. The stochastic properties of model parameters are explicitly taken into account into the model. To simplify the procedure of the model, the probability of the durability limit is determined from the samples obtained from the Latin hypercube sampling technique. The new method may be very useful in designing important concrete structures and help to predict the remaining service life of existing concrete structures which have been monitored.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.401-410
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• 2019

In this paper, we propose a reference picture generation method for Inter-layer prediction based deep learning to improve the SHVC coding performance. A description will be given of a structure for performing filtering using a VDSR network on a DCT-IF based upsampled picture to generate a new reference picture and a training method for generating a reference picture between SHVC Inter-layer. The proposed method is implemented based on SHM 12.0. In order to evaluate the performance, we compare the method of generating Inter-layer predictor by applying dictionary learning. As a result, the coding performance of the enhancement layer showed a bitrate reduction of up to 13.14% compared to the method using dictionary learning, a bitrate reduction of up to 15.39% compared to SHM, and a bitrate reduction of 6.46% on average.

• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.10-20
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• 2013

Nowadays, video technology has been successfully improved creating tremendous results. As video technology improve, multimedia devices and demands from users are diversified. Therefore, a video codec used in these devices should support various displays with different resolutions. The technology to generate a higher resolution image from the associated low-resolution image is called interpolation. Interpolation is generally performed in either the spatial domain or the DCT domain. To use the advantages of both domains, we have proposed the new adaptive interpolation algorithm based on edge direction, which adaptively exploits the advantages of both domains. The experimental results demonstrate that our algorithm performs well in terms of PSNR and reduces the blocking artifacts.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.965-972
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• 2020

Depth maps have distance information of objects. They play an important role in organizing 3D information. Color and depth images are often simultaneously obtained. However, depth images have lower resolution than color images due to limitation in hardware technology. Therefore, it is useful to upsample depth maps to have the same resolution as color images. In this paper, we propose a novel method to upsample depth map by shifting the pixel position instead of compensating pixel value. This approach moves the position of the pixel around the edge to the center of the edge, and this process is carried out in several steps to restore blurred depth map. The experimental results show that the proposed method improves both quantitative and visual quality compared to the existing methods.