• 전자공학회논문지B
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• 제28B권5호
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• pp.394-403
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• 1991

This paper described the development of input driven multilayer perceptron(IDMLP) neural network and it's application to the Korean spoken digit recognition. The IDMPLP neural network used here and the learning algorithm for this network was proposed newly. In this model, weight value is integer and transfer function in the neuron is hard limit function. According to the result of the network learning for the some kinds of input data, the number of network layers is one or more by the difficulties of classifying the inputs. We tested the recognition of binaried data for the spoken digit 0 to 9 by means of the proposed network. The experimental results are 100% and 96% for the learning data and test data, respectively.

• 한국정보통신학회논문지
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• 제25권7호
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• pp.940-945
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• 2021

NDN (Named Data Networking)과 같은 미래 네트워크 아키텍처는 현재 호스트 중심 네트워크 기술에서 정보 중심 네트워크 기술로 데이터를 전송할 수 있는 방식을 변경하기 위해 탄생하였다. 최근 Vehicular NDN을 커넥티드 차량을 포함한 스마트 차량의 통신 네트워크 기술에 접목하기 위한 많은 연구가 진행되고 있다. Vehicular NDN 환경에서 Interest/Data 패킷 브로드 캐스팅으로 인한 데이터 트래픽 폭증은 VNDN 기반 데이터 통신을 실현하기 위해 해결해야 할 매우 중요한 문제이다. 본 논문에서는 데이터 브로드캐스트 폭풍 현상이 얼마나 심각하게 발생하는지를 보여주기 위해 VNDN 네트워크에서 네트워크 사이즈, 차량 스피드, 인터레스트 패킷 발생 빈도수의 증가에 따른 데이터 패킷 사본 발생을 ndnSIM을 이용하여 실험하고 평가한다. VNDN 안에 커넥티드 차량 수 및 Interest 패킷 발생 빈도수의 증가에 따라 중복된 데이터 패킷 처리량도 증가함을 확인하였다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (3)
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• pp.142-144
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• 2004

To provide more qualified data service on the HFC(Hybrid-Fiber Coaxial) access network, the channel characteristics of upstream transmission band should be carefully investigated and analysed. It will be easier to do network management if the monitoring system for noise measurement in the network is available, In this paper, noise analysis method and the frequency selection method in the upstream band for duplex transmission are suggested. And, Data aquisition device for the signal measurement Is implemented. With this network monitoring system, field test and the result from the collected data are described.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.230-235
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• 1992

We propose a method of generating data to train a neural network controller. The data can be prepared directly by an iterative learning technique which repeatedly adjusts the control input to improve the tracking quality of the desired trajectory. Instead of storing control input data in memory as in iterative learning control, the neural network stores the mapping between the control input and the desired output. We apply this concept to the trajectory control of a two link robot manipulator with a feedforward neural network controller and a feedback linear controller. Simulation results show good generalization of the neural network controller.

• Journal of Information Processing Systems
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• 제4권4호
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• pp.133-144
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• 2008

Clusters have become a popular alternative for building high-performance parallel computing systems. Today's high-performance system area network (SAN) protocols such as VIA and IBA significantly reduce user-to-user communication latency by implementing protocol stacks outside of operating system kernel. However, emerging parallel applications require a significant improvement in communication latency. Since the time required for transferring data between host memory and network interface (NI) make up a large portion of overall communication latency, the reduction of data transfer time is crucial for achieving low-latency communication. In this paper, Eager Data Transfer (EDT) mechanism is proposed to reduce the time for data transfers between the host and network interface. The EDT employs cache coherence interface hardware to directly transfer data between the host and NI. An EDT-based network interface was modeled and simulated on the Linux-based, complete system simulation environment, Linux/SimOS. Our simulation results show that the EDT approach significantly reduces the data transfer time compared to DMA-based approaches. The EDTbased NI attains 17% to 38% reduction in user-to-user message time compared to the cache-coherent DMA-based NIs for a range of message sizes (64 bytes${\sim}$4 Kbytes) in a SAN environment.

• Journal of the Korean Data and Information Science Society
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• 제15권2호
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• pp.331-337
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• 2004

In the analysis of massive volume data, a neural network model is a useful tool. To implement the Neural network model, it is important to select initial value. Since the initial values are generally used as random value in the neural network, the convergent performance and the prediction rate of model are not stable. To overcome the drawback a possible method use samples randomly selected from the whole data set. That is, coefficients estimated by logistic regression based on the samples are the initial values.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.177-178
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• 2005

Wireless 1394 over IEEE802.15.3 must allow a data reserved for delivery over a wired 1394 network to be delivered over an IEEE802.15.3 wireless network through bridging IEEE 1394 to IEEE802.15.3. Isochronous transfers on the 1394 bus guarantee timely delivery of data. Specifically, isochronous transfers are scheduled by the bus so that they occur once every $125\;{\mu}s$ and require clock time synchronization to complete the real-time data transfer. IEEE1394.1 and Protocol Adaptation Layer for IEEE1394 over IEEE802.15.3 specify clock time synchronization for a wired 1394 bus network to a wired 1394 bus network and wireless 1394 nodes, which are IEEE802.15.3 nodes handling 1394 applications, over IEEE802.15.3. Thus, the clock time synchronizations are just defined within a homogeneous network environment like IEEE1394 or IEEE802.15.3 until now. This paper proposes new clock time synchronization method for wireless 1394 heterogeneous networks between 1394 and 802.15.3. If new method is adopted for various wireless 1394 products, consumer electronics devices such as DTV and Set-top Box or PC devices on a 1394 bus network can transmit real time data to the AV devices on the other 1394 bus in a different place via IEEE 802.15.3.

• 한국산업정보학회논문지
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• 제15권3호
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• pp.67-75
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• 2010

네트워크 리프로그래밍은 센서 필드에 배치된 센서 노드들의 효율적인 유지 보수를 위해 코드 업데이트와 오류 수정을 원격으로 수행할 수 있도록 하는 기술이다. 센서 노드들 간에 소량의 데이터를 전달하는 일반적인 무선 센서 네트워크 통신과는 달리 네트워크 리프로그래밍에서는 대용량 데이터의 신뢰성 있는 전달이 요구된다. 기존의 네트워크 리프로그래밍 기법은 신뢰성 있는 데이터 전달을 위해 데이터 손실 발생 시 복구를 위한 비용이 많이 들며 이로 인한 에너지 소모가 급증하는 문제점을 안고 있다. 본 논문에서는 센서 네트워크에 적합한 클러스터 기반의 리프로그래밍 기법을 제안한다. 센서 필드를 클러스터로 나누고 각 클러스터에 대표 노드를 선정하여 중복 전송과 불필요한 경쟁을 최소화함으로써 에너지 소모를 줄인다. 또한 테이블을 이용하여 노드들의 상태 정보를 통해 정확한 오류 복구를 수행함으로써 신뢰성을 높이고 있다.

• International Journal of Quality Innovation
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• 제7권3호
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• pp.58-69
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• 2006

This paper presents neural network-based recognition system for automatic light emitting diode (LED) inspection. The back-propagation neural network (BPNN) is proposed and tested. The current-voltage (I-V) characteristic data of LED from the inspection process is used for the network training and testing. This study selects 300 random samples as network training and employs 100 samples as network testing. The experimental results show that if the classification work is done well, the accuracy of recognition is 100%, and the testing speed of the proposed recognition system is almost one half faster than the traditional inspection system does. The proposed neural-network approach is successfully demonstrated by real data sets and can be effectively developed as a recognition system for a practical application purpose.

• 대한산업공학회지
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• 제24권2호
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• pp.241-249
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• 1998

In this paper, we seek to find an optimal allocation of link capacity in a data communication network. The architecture of the data communication network considered in the study is an online-service network based on public switched telephone network(PSTN) and packet switched data network(PSDN). In designing the architecture of the network, we need to deal with various measures of quality of service(QoS). Two important service measures are the call blocking probability in PSTN and the data transfer delay time in PSDN. Considering the tradeoff between the call blocking probability and the data transfer delay time in the network, we have developed the optimal link capacity allocation model that minimizes the total link cost, while guarantees the call blocking probability and the data transfer delay time within an acceptable level of QoS. This problem can be formulated as a non-linear integer programming model. We have solved the problem with tabu search and simulated annealing methods. In addition, we have analyzed the sensitivity of the model and provided the insight of the model along with computational results.