• Journal of Information Processing Systems
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• 제13권6호
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• pp.1544-1553
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• 2017

The network coding mechanism has attracted much attention because of its advantage of enhanced network throughput which is a desirable characteristic especially in a multi-hop wireless network with limited link capacity such as the device-to-device (D2D) communication network of 5G. COPE proposes to use the XOR-based network coding in the two-hop wireless network topology. For multi-hop wireless networks, the Distributed Coding-Aware Routing (DCAR) mechanism was proposed, in which the coding conditions for two flows intersecting at an intermediate node are defined and the routing metric to improve the coding opportunity by preferring those routes with longer queues is designed. Because the routes with longer queues may increase the delay, DCAR is inefficient in delivering real-time multimedia traffic flows. In this paper, we propose a network coding-aware routing protocol for multi-hop wireless networks that enhances DCAR by considering traffic load distribution and link quality. From this, we can achieve higher network throughput and lower end-to-end delay at the same time for the proper delivery of time-sensitive data flow. The Qualnet-based simulation results show that our proposed scheme outperforms DCAR in terms of throughput and delay.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 봄 학술발표회 논문집
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• pp.357-365
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• 2003

The major problems with the conventional neural network, especially Back Propagation Neural Network, arise from the necessity of many training data for neural network learning and ambiguity in the relation of neural network structure to the convergence of solution. In this paper, the PNN is used as a pattern classifier to detect the damage of structure to avoid those drawbacks of the conventional neural network. In the PNN-based pattern classification problems, the probability density function for patterns is usually assumed by Gaussian distribution. But, in this paper, several probability density functions are investigated in order to select the most approriate one for structural damage assessment.

• 수산해양교육연구
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• 제26권4호
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• pp.760-768
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• 2014

Yet logistics base in China has a refrigerated storage facilities installed areas, the number of those is very limited and is generally insufficient. According to these especial points, a new construction cold chain logistics network design strategy is required from how to use the existing refrigerated warehouses to new issue. For example, however refrigerated storage facility is supplied, can it satisfy all demand of this area? Then does it have optimized location of this area? If future demand expansion, adding that already other refrigerated storage facilities matter? Or, add another refrigerated facilities, optimum cold chain established a network matter? So on. Above problems can be occurred. In order to solve facing many of these issues of distribution network, northeast area in China has been selected as a subject, and we designed a new cold chain distribution network.

• 산업공학
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• 제10권3호
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• pp.179-187
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• 1997

The efficiency of material flow systems in terms of optimal network flow and minimum cost flow has always been an important design and operational goal in material handling and distribution system. In this research, an attempt was made to develop a new algorithm and the model to solve a stochastic material flow network with bidirectional and uncertain flows. A stochastic material flow network with bidirectional flows can be considered from a finite set with unknown demand probabilities of each node. This problem can be formulated as a special case of a two-stage linear programming problem which can be converted into an equivalent linear program. To find the optimal solution of proposed stochastic material flow network, some terminologies and algorithms together with theories are developed based on the partitioning and subgradient techniques. A computer program applying the proposed method was developed and was applied to various problems.

• Journal of Communications and Networks
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• 제11권4호
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• pp.406-415
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• 2009

In this work, we consider performance modeling of a wireless sensor network with a time division multiple access (TDMA) media access protocol with slot reuse. It is assumed that all the nodes are peers of each other and they have two modes of operation, active and sleep modes. We model the sensor network as a Jackson network with unreliable nodes with on and off states. Active and sleep modes of sensor nodes are modeled with on and off states of unreliable nodes. We determine the joint distribution of the sensor node queue lengths in the network. From this result, we derive the probability distribution of the number of active nodes and blocking probability of node activation. Then, we present the mean packet delay, average sleep period of a node and the network throughput. We present numerical results as well as simulation results to verify the analysis. Finally, we discuss how the derived results may be used in the design of sensor networks.

• Journal of information and communication convergence engineering
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• 제19권3호
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• pp.148-154
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• 2021

With the advent of context-aware computing, many attempts were made to understand emotions. Among these various attempts, Speech Emotion Recognition (SER) is a method of recognizing the speaker's emotions through speech information. The SER is successful in selecting distinctive 'features' and 'classifying' them in an appropriate way. In this paper, the performances of SER using neural network models (e.g., fully connected network (FCN), convolutional neural network (CNN)) with Mel-Frequency Cepstral Coefficients (MFCC) are examined in terms of the accuracy and distribution of emotion recognition. For Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) dataset, by tuning model parameters, a two-dimensional Convolutional Neural Network (2D-CNN) model with MFCC showed the best performance with an average accuracy of 88.54% for 5 emotions, anger, happiness, calm, fear, and sadness, of men and women. In addition, by examining the distribution of emotion recognition accuracies for neural network models, the 2D-CNN with MFCC can expect an overall accuracy of 75% or more.

• Journal of Information Science Theory and Practice
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• 제10권spc호
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• pp.123-134
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• 2022

Existing network cryptography systems are threatened by recent developments in quantum computing. For example, the Shor algorithm, which can be run on a quantum computer, is capable of overriding public key-based network cryptography systems in a short time. Therefore, research on new cryptography systems is actively being conducted. The most powerful cryptography systems are quantum key distribution (QKD) and post quantum cryptograph (PQC) systems; in this study, a network based on both QKD and PQC is proposed, along with a quantum key management system (QKMS) and a Q-controller to efficiently operate the network. The proposed quantum cryptography communication network uses QKD as its backbone, and replaces QKD with PQC at the user end to overcome the shortcomings of QKD. This paper presents the functional requirements of QKMS and Q-Controller, which can be utilized to perform efficient network resource management.

• 상하수도학회지
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• 제20권6호
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• pp.799-811
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• 2006

As an alternative measure to replace reactive stance with proactive one, a risk based management scheme has been commonly applied to enhance public satisfaction on water service by providing a higher creditable solution to handle a rehabilitation problem of pipe having high potential risk of leaks. This study intended to examine the feasibility of a simulation model to predict a recurrence probability of pipe leaks. As a branch of the data mining technique, probabilistic neural network (PNN) algorithm was applied to infer the extent of leaking recurrence probability of water network. PNN model could classify the leaking level of each unit segment of the pipe network. Pipe material, diameter, C value, road width, pressure, installation age as input variable and 5 classes by pipe leaking probability as output variable were built in PNN model. The study results indicated that it is important to pay higher attention to the pipe segment with the leak record. By increase the hydraulic pipe pressure to meet the required water demand from each node, simulation results indicated that about 6.9% of total number of pipe would additionally be classified into higher class of recurrence risk than present as the reference year. Consequently, it was convinced that the application of PNN model incorporated with a data base management system of pipe network to manage municipal water distribution network could make a promise to enhance the management efficiency by providing the essential knowledge for decision making rehabilitation of network.

• KEPCO Journal on Electric Power and Energy
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• 제5권4호
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• pp.275-286
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• 2019

본 논문은 DC (Direct Current) 배전망 혹은 DC 마이크로그리드 운영을 위한 실시간 DC 계통해석 응용프로그램의 개발에 대한 내용을 다룬다. 응용프로그램은 중앙 에너지 관리시스템(EMS: Energy Management System)에 탑재되어 운영자에게 실시간으로 운영 솔루션을 제공한다. DC 배전계통을 해석하기 위한 프로그램의 구성 및 시퀀스를 제안한다. 각 프로그램의 알고리즘과 AC 계통 프로세스와의 차이점을 분석한다. 한국전력공사 고창전력시험센터 내 DC 배전망 실증사이트를 소개하고, EMS 구축 내용을 기술한다. 개발된 DC 계통해석 응용프로그램을 실증 사이트 EMS에 탑재하여, 검증 시험을 수행한다. DC 배전망 전압 제어를 위한 시험 시나리오를 구성에 대해 논한다. 마지막으로 실증시험 결과 측정 데이터, 응용프로그램 결과 데이터를 PSCAD/EMTDC를 이용한 오프라인 시뮬레이션 결과값과 비교 분석하여 정합성을 검증한다.

• 정보처리학회논문지D
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• 제10D권7호
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• pp.1207-1212
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• 2003

전자상거래의 발전과 함께 물류유통을 위한 분배망의 구성은 점차 복잡해지고 있으며, 이에 따라 분배계획이 점차 중요해지고 있다. 분배계획에 있어서 분배망의 관리는 중요하다. 분배망은 분배센터(DC)와 그 상호작용으로 나타낼 수 있다. DC 내부요인 및 DC의 상호작용으로 인한 외부요인은 분배망에 많은 영향을 미친다. 따라서 효율적인 분배망 관리계획의 수립을 위해서는 DC와 DC의 상호작용을 고려한 분배망의 분석이 필요하다. 지금까지 자원할당 같은 공급망 관리 관점의 연구가 이루어졌지만 공급망을 구성하는 분배망의 분석에 대한 연구가 이루어지지 않았다. 본 논문은 DC와 DC의 상호작용을 고려한 분배망 분석 기법을 제안한다. 제안 기법은 크게 두 가지 단계로 이루어진다. 먼저, 분배망은 DC와 DC의 상호작용을 포함한 그래프 형태로 모델링된다. 두 번째, 그래프로 모델링된 분배망은 도달성 트리를 이용하여 분석된다. 또한 예제모델을 제시하고, 이것의 분석을 통해 제안기법의 효용성을 보였다.