• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12B
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• pp.1063-1069
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• 2004

There are some problems with the methods of paging and routing cache(PRC) and quasi soft handoff that are proposed to improve the performance for the transmission of real time data. This paper proposed a reasonable solution of these problems by proposing a new method using a combined cache(CC) and applying a different handoff procedure according to each type of data. The combined cache dose not maintain the handoff state but the idlle/active state. The simulation results in a better performance than the above methods in terms of the control packet traffic load, initial recevied data packet traffic load and arrival tune of real time packet at the epoch of handoff.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.256-258
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• 2021

최근 전세계 각 연구기관에서 CPS, 클라우드 컴퓨팅, 5G, 빅데이터, IIOT, Milk-run AI 알고리즘 등을 활용한 CIPs(Connected Industrial parks) 아키텍쳐가 다양하게 제안되고 있다. 평균적으로 한국의 중소기업은 기술력과 가격 경쟁력 문제로 많은 어려움을 겪고 있다. 미국, 일본, 유럽 등의 해외 선진국들에 비하여 기술력이 확실한 우위를 보이지 못하고 있으며, 중국, 베트남 등의 국가에 비하여는 제조 가격 경쟁력을 보이지 못하고 있다. 이러한 상황에서 한국의 중소 기업들은 지속 가능한 성장 방안을 찾기 위하여 많은 노력을 하고 있다. 재무적으로 한국의 중소기업들이 수익성을 향상시키기 위해서는 매출을 증대시키는 것 보다 비용을 절감하는 것이 효과적이다. 이러한 문제 의식 속에서 한국 CIPs에 위치한 중소 기업들의 비용 절감을 위한 방안으로서 VJP(Vehicle Junction Problem)를 주목하였다. 중소 기업의 최소 물류 비용 달성을 위한 방법으로 CIPs 결제 한국형 시스템을 연구하였다. 새로운 한국형 CIPs결제 시스템의 세부 항목을 크게 4가지 "데이터(Data)", "업무(Business)", "자금(Finance)", "기술(Technique)"로 구분하여 정리하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.7-18
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• 2021

Recently, various connected industrial parks (CIPs) architectures using new technologies such as cloud computing, CPS, big data, fifth-generation mobile communication 5G, IIoT, VR-AR, and ventilation transportation AI algorithms have been proposed in Korea. Korea's small and medium-sized enterprises do not have the upper hand in technological competitiveness than overseas advanced countries such as the United States, Europe and Japan. For this reason, Korea's small and medium-sized enterprises have to invest a lot of money in technology research and development. As a latecomer, Korean SMEs need to improve their profitability in order to find sustainable growth potential. Financially, it is most efficient for small and medium-sized Korean companies to cut costs to increase their profitability. This paper made profitability improvement by reducing costs for small and medium-sized enterprises located in CIPs in Korea a major task. VJP (Vehicle Action Program) was noted as a way to reduce costs for small and medium-sized enterprises located in CIPs in Korea. The method of achieving minimum logistics costs for small businesses through the Korean CIPs payment system was analyzed. The details of the new Korean CIPs payment system were largely divided into four types: "Business", "Data", "Technique", and "Finance". Cost Benefit Analysis (CBA) was used as a performance analysis method for CIPs payment systems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.362-370
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• 2001

In this paper, we proposed multispectral image compression method using CIP (classified inter-channel prediction) and SVQ (selective vector quantization) in wavelet domain. First, multispectral image is wavelet transformed and classified into one of three classes considering reflection characteristics of the subband with the lowest resolution. Then, for a reference channel which has the highest correlation and the same resolution with other channels, the variable VQ is performed in the classified intra-channel to remove spatial redundancy. For other channels, the CIP is performed to remove spectral redundancy. Finally, the prediction error is reduced by performing SVQ. Experiments are carried out on a multispectral image. The results show that the proposed method reduce the bit rate at higher reconstructed image quality and improve the compression efficiency compared to conventional methods. Index Terms-Multispectral image compression, wavelet transform, classfied inter-channel prediction, selective vetor quantization, subband with lowest resolution.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.520-523
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• 2022

일본 우주항공연구개발기구(Japan Aerospace Exploration Agency, JAXA)는 2007년부터 2017년까지 달 탐사선 셀레네(Selenological and Engineering Explorer, SelEnE)가 관측한 데이터를 수집하고, 연구했다. JAXA는 지구 상층 대기에 존재하는 산소가 자기장의 꼬리 부분에 실려 달로 이동한다는 사실을 발견했다. 하지만 이 연구는 아직 진행 중이며 달의 산화 과정 규명에 추가 연구가 필요하다. 본 논문에서는 생성적 적대 신경망(Generative Adversarial Networks, GAN)으로 달 분화구의 영구 그림자 영역을 제거하고, 물과 얼음을 발견하여 선행 연구의 완성도를 향상하고자 한다. 실험에 사용할 모델은 CIPS(Conditionally Independent Pixel Synthesis)다. CIPS는 실제 같은 영상을 고해상도로 합성한다. 합성할 데이터의 최적인 가중치 초기화 및 파라미터 갱신 방법, 활성 함수 조합은 실험을 통해 확인한다. 필요에 따라 앙상블 학습을 할 수도 있다. 성능평가는 FID(Frechet Inception Distance), 정밀도, 재현율을 사용한다. 제안한 방법은 진행 중인 연구의 시간과 비용을 절약하고, 인과관계를 더욱 명확히 밝히는 데 도움 될 수 있다고 사료된다.

• Journal of the Korean Geotechnical Society
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• v.39 no.9
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• pp.13-24
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• 2023

To investigate the stability of temporary retaining walls during excavation, it is essential to develop reverse analysis technologies capable of precisely evaluating the properties of the ground and a learning model that can assess stability by analyzing real-time data. In this study, we targeted excavation sites where the C.I.P method was applied. We developed a Deep Neural Network (DNN) model capable of evaluating the stability of the retaining wall, and estimated the physical properties of the ground being excavated using a Differential Evolution Algorithm. We performed reverse analysis on a model composed of a two-layer ground for the applicability analysis of the Differential Evolution Algorithm. The results from this analysis allowed us to predict the properties of the ground, such as the elastic modulus, cohesion, and internal friction angle, with an accuracy of 97%. We analyzed 30,000 cases to construct the training data for the DNN model. We proposed stability evaluation grades for each assessment factor, including anchor axial force, uneven subsidence, wall displacement, and structural stability of the wall, and trained the data based on these factors. The application analysis of the trained DNN model showed that the model could predict the stability of the retaining wall with an average accuracy of over 94%, considering factors such as the axial force of the anchor, uneven subsidence, displacement of the wall, and structural stability of the wall.