• Electronics and Telecommunications Trends
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• v.28 no.6
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• pp.86-98
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• 2013

최근 다양한 형태의 스마트 기기 출현과 대중적 보급으로 고속 데이터 전송에 대한 수요가 나날이 증가하고 있어 소형셀 기술에 대한 이동통신 사업자들의 관심이 높다. 이에 데이터 요구량이 많은 위치에 소형 셀을 다층으로 밀집 배치하고 매크로 기지국 및 소형 셀 기지국의 밀접한 협력을 통해 무선 네트워크의 용량을 증가시키기 위한 기술들에 대한 요구가 높아지고 있다. 매크로 셀과 소형 셀이 다층으로 배치된 구조에서 고려해 볼 수 있는 요소기술들은 단말의 다중 노드 연결, 효율적인 이동성 보장, 효율적인 셀/이동단말 발견, 이종 듀플렉스캐리어 집성, 셀 간 간섭 관리 등이며, 본 논문에서는 이들을 기반으로 최근 3GPP에서 활발히 논의되고 있는 LTE 소형셀 향상 표준화 동향에 대해 기술한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.86-86
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• 2016

본 연구는 가뭄 예측에 대한 오차를 알고리즘과 결합하여 다층 퍼셉트론 (Multi-layer Perceptron, MLP) 네트워크 구조를 인공신경망 모형에 적용하고, 표준강수지수(Standard Precipitation Index, SPI)를 입 력 및 출력 변수로 구성하여 가뭄예측을 시도하였다. 예측모델을 평가하기 위해 기상청 산하의 59개 관측소에 대한 1980년부터 2015년까지의 기상자료를 적용하였으며, 수립된 자료를 활용하여 한반도 전역의 가뭄에 대한 시공간적인 분석을 수행하였다. 단기가뭄 예측성능을 평가하기 위해 2000년에서 2015년까지 16년간의 모의결과를 ROC 분석을 통하여 시공간적 단기가뭄 예측성능을 평가하고 혼동행렬(Conversion Matrix) 구성에 대한 조건적 확률의 다각적 검토를 통해 모델 예측에 대한 정확성(Accuracy), 신뢰성(Precision) 등 다양한 예측성능에 대한 평가를 수행하고 2016년 가뭄전망을 제시하고자 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.292-294
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• 2005

대사증후군은 당뇨병, 고혈압, 복부 비만, 고지혈증 등의 질병이 한 개인에게 동시에 발현하는 것을 말한다. 미국에서는 $25\%$ 이상의 성인이 대사성 증후군인 것으로 알려져 있으며, 경제 여건의 향상 및 식생활 습관의 변화와 함께 최근 우리나라에서도 심각한 문제가 되고 있다. 한편 불확실성의 처리를 위해 많이 사용되고 있는 베이지안 네트워크는 사람이 분석 가능한 확률 기반의 모델로 최근 의학 분야에서 지식 발견, 데이터 마이닝을 위한 도구로 유용하게 사용되고 있다. 본 논문에 서 는 대사증후군을 예측하는 문제를 다루며, 베이지안 네트워크와 의학 지식을 이용한 대사증후군의 예측 모델을 제안한다. 제안하는 모델을 통해 1993년의 데이터를 가지고 1995년의 상태를 예측하는 분류 실험을 수행하였으며, 실험 결과 다층 신경망, k-최근접 이웃 등의 분류기 보다 높은 $81.5\%$의 예측율을 보였다.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.33-39
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• 2020

Interest in 5G communication security has been growing recently amid growing expectations for 5G technology with faster speed and stability than LTE. However, 5G has so far included disparate areas, so it has not yet fully supported the issues of security. This paper proposes a blockchain-based IoT management model in order to efficiently provide the authentication of users using IoT in 5G In order to efficiently fuse the authentication of IoT users with probabilistic theory and physical structure, the proposed model uses two random keys in reverse direction at different layers so that two-way authentication is achieved by the managers of layers and layers. The proposed model applied blockchain between grouped IoT devices by assigning weights to layer information of IoT information after certification of IoT users in 5G environment is stratified on a probabilistic basis. In particular, the proposed model has better functions than the existing blockchain because it divides the IoT network into layered, multi-layered networks.

• Journal of Navigation and Port Research
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• v.35 no.1
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• pp.83-91
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• 2011

The accuracy of forecasting is remarkably important to reduce total cost or to increase customer services, so it has been studied by many researchers. In this paper, the artificial neural network (ANN), one of the most popular nonlinear forecasting methods, is compared with autoregressive integrated moving average(ARIMA) model through performing a prediction of container traffic. It uses a hybrid methodology that combines both the linear ARIAM and the nonlinear ANN model to improve forecasting performance. Also, it compares the methodology with other models in performance for prediction. In designing network structure, this work specially applies the genetic algorithm which is known as the effectively optimal algorithm in the huge and complex sample space. It includes the time delayed neural network (TDNN) as well as multi-layer perceptron (MLP) which is the most popular neural network model. Experimental results indicate that both ANN and Hybrid models outperform ARIMA model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.628-631
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• 2014

Recently, the proliferation of new applications, e.g., mobile TV, Internet gaming, large file transfer, and the various of user terminals, e.g., smart phones and notebooks, has dramatically increased user traffic and network load. In order to meet this traffic growth, vendors and cellular operators are working on the development of new technologies and cellular standards. Within them, small cell deployment has been heralded as one of most promising way to increase both coverage and capacity of future cellular network. Small cell technology enables to improve capacity of cellular radio network by tight cooperation between small cell and macro cell in multi-tier network where small cells are densely deployed within macro cell coverage. In this paper, we describe the deployment scenarios for cooperation between macro cell and small cells and state-of-the-art technologies related to dense small cell deployment. Then, we also provide design principles and standardization trends for small cell enhancement in 3GPP.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.99-105
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• 2011

Typically, quick and easily deployed communication for a clear disaster management is required in a disaster situation. But it is not easy because lack of backbone network and poor conditions of disaster site. it is possible to obtain a wide service coverage and low power with portable wireless mesh network technology. In this paper, we developed portable wireless mesh network gateway with a network processor and evaluate it's performance including throughput, latency delay, packet loss, etc. The experiments show our wireless mesh network gateway has basic performance and can be used in various environments like disaster site.

• Journal of the Korean association of regional geographers
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• v.21 no.4
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• pp.704-715
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• 2015

Provincial boundary regions need differentiated strategies from non-provincial boundary regions because they form multilayered regional networks with boundary cites and provinces. This paper aims to analyze the attributions of provincial boundary regions' regional networks in the dimensions of commuters, companies, and government and to explore their political strategies. At commuters level, Okcheon, a case study area, forms the strongest regional networks with Daejeon and does not have any regional network with Honam region. At companies level, it forms the regional network with Daejeon, Gyeonggi, and Chungbuk, and with Daejeon(Donggu, Daedukgu), and Gyeonggi(Bucheon) at government level. This paper suggests the following conclusive policies. First, provincial boundary regions should be postulated as the new policy targets. Second, Population and Housing Census should be constructed pan-regionally as the base data of regional network studies. Lastly, cooperation system among local government of the provincial boundary regions should be constructed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2843-2852
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• 2013

In the nested mobile network environment, the mobile node selects one of multiple mobile routers. The MR(Mobile Router) by existing top-down or bottom-up methods may not be the optimal MR if the numbers of mobile nodes and routers are substantially increased, and the scale of the network is increased drastically. Since an inappropriate MR decision causes handover or binding renewal to mobile nodes, determining of the optimal MR is important for efficiency. In this paper, we propose an algorithm that decides on the optimal MR using MR QoS(Quality of Service) information, and we describe how to understand the various structured MLP(Multi-Layered Perceptron) based on the algorithm. In conclusion, we prove the ability of the suggested neural network for a nesting mobile network through the performance analysis of each learned MLP.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3C
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• pp.115-125
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• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by insitu test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network (NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. It was already found that NN model can come over the site dependency and prediction accuracy is greatly improved when compared with present theoretical and empirical models. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network (CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. Prediction results of CNN model are compared with those of conventional empirical and theoretical models and multi-layered neural network model, which has the optimized structure. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.