• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2003년도 추계 학술대회 학술발표 논문집
• /
• pp.122-125
• /
• 2003

By advent of NNC(Neural Network Chip), it is possible that process in parallel and discern the importance of signal with learning oneself by experience in external signal. So, the design of general purpose operation unit using VHDL(VHSIC Hardware Description Language) on the existing FPGA(Field Programmable Gate Array) can replaced EN(Expert Network) and learning algorithm. Also, neural network operation unit is possible various operation using learning of NN(Neural Network). This paper present general purpose operation unit using hierarchical structure of EN EN of presented structure learn from logical gate which constitute a operation unit, it relocated several layer The overall structure is hierarchical using a module, it has generality more than FPGA operation unit.

• 경영과학
• /
• 제26권1호
• /
• pp.113-126
• /
• 2009

By the newly emerging network access technology, we face the new heterogeneous network environment. Focusing on the co-existence of multiple access network technology and the complex service needs of users, the wireless service operators should present the stable service quality for every user. For this, the service operators should build the new operation framework which combine the pre-established network and newly adopted one. Our problem is finding the optimal heterogeneous network operation framework. We suggest market-based marginal cost function for evaluating the relative value of resource of each network and develop the whole new heterogeneous network operation framework. To test the applicability of developed operation framework, we build large-scale JAVA simulator. By this development, we can easily test the new network environment in practical engineering field.

• 전기학회논문지
• /
• 제62권10호
• /
• pp.1451-1457
• /
• 2013

Recently, new concept of energy systems such as microgrid, smart grid, supergrid, and energy network has been introducing. In this paper, the concept of the centralized micro-energy network, which is an energy community of a building group without district heating system, is introduced. In addition, a mathematical model for optimal operation of the micro-energy network as a main function of an energy management system (EMS) for the micro-energy network is proposed. In order to show the validation, the proposed model is tested through the simulation and analyzed.

• 대한전자공학회논문지
• /
• 제13권6호
• /
• pp.20-23
• /
• 1976

본논문에서는 통신회로망의 신뢰도를 계산하는데 부울대수를 이용하는 방법을 제시하였다. 한 회로의 두 접합점사이의 모든 단순통로가 주어지면 병렬연산이라고 명명되는 부울대수산법에 의하여 두 단점사이의 신뢰도가 기호적으로 계산된다. 이 방법은 회로가 방향성이거나 비방향성이거나 다 효과적이다. A boolean algebra method for computing the reliability in a communication network is prosented. Given the set of all simple paths between two nodes in a network, the terminal reliability can be symbolically computed by the Boolean operation which is named parallel operation. The method seems to be promising for both oriented and nonoriented network.

• 한국콘텐츠학회논문지
• /
• 제3권4호
• /
• pp.63-68
• /
• 2003

본 논문은 통신 네트워크 운용관련 민감도 측정에 관한 연구를 위해 네트워크 운용 적정비용 산출 및 효율화 방안을 제안하였다. 통신 네트워크 운용효율화를 위해 네트워크 운용 효율성 측정을 위한 모형을 개발하였다. 전반적/포괄적 관점에서 산출된 네트워크 운용의 적정비용에 대해 품질수준 개선을 위한 요소, 고객만족도 관련 요소 등과의 연계성을 중심으로 재평가하고 개선하는 것이 본 논문의 가장 핵심적인 연구이다. 이러한 과정은 네트워크 운용의 가장 큰 부분을 차지하는 것이 품질관련 활동이고 품질관련 활동은 결국 고객만족도로 나타나게 되는 것이기 때문에, 각 요소별 개별적인 변화가 상호간에 미치는 영향을 중심으로 상관관계를 정립하여 민감도 측정을 바탕으로 네트워크운용비용을 산출하는 것이 진정한 의미의 적정수준 분석이라 할 수 있다. 따라서, 본 논문에서는 네트워크 운용에 대한 체계적인 모형의 구축 및 효율성 측정을 위한 다양한 시나리오에 따른 민감도 측정을 위한 시스템을 개발하였다.

• 한국산업정보학회논문지
• /
• 제19권3호
• /
• pp.9-15
• /
• 2014

In the ubiquitous computing environment, a ubiquitous vehicle will be a communication node in the vehicular network as well as the means of ground transportation. It will make humans and vehicles seamlessly and remotely connected. Especially, one of the prominent services in the ubiquitous vehicle is the vehicle remote operation. However, mutual-collaboration with the in-vehicle communication network, the vehicle-to-vehicle communication network and the vehicle-to-roadside communication network is required to provide vehicle remote operation services. In this paper, an Internet-based human-vehicle interfaces and a network architecture is presented to provide remote vehicle control and diagnosis services. The performance of the proposed system is evaluated through a design and implementation in terms of the round trip time taken to get a vehicle remote operation service.

• 한국통신학회논문지
• /
• 제32권10A호
• /
• pp.941-949
• /
• 2007

신규 무선 네트워크 기술의 발전은 현재의 단일 네트워크 위주의 구성을 가진 무선 서비스 사업자에 새로운 다중 네트워크 (Heterogeneous Network) 환경을 맞이하게 하였다. 또한 무선 통신 사용자 수는 계속적인 증가추세에 있고 사용자들이 원하는 서비스의 종류 또한 계속적으로 다양해지고 있으며 사용자가 기대하는 서비스의 질과 수준 역시 높아지고 있다. 이에 무선 서비스 사업자들은 사용자들의 높아진 서비스 품질을 만족시키고 새로운 형태의 서비스를 안정적으로 공급하며, 현재의 네트워크와 신규 네트워크의 조화로운 운용을 위해 새로운 형태의 운용 구조 (Operation Framework)를 필요로 한다. 본 논문에서는 네트워크간의 비용/효용에 대한 한계 비용 (Marginal Cost) 산정 기법을 도입하여 서비스에 따른 최적 네트워크 운용 기법에 대해 논술한다.

• 대한전기학회논문지:전력기술부문A
• /
• 제50권11호
• /
• pp.506-513
• /
• 2001

The islanding detection for distributed resources (DR) becomes an important and emerging issue in power system protection since the distributed generator installations are rapidly increasing and most of the installed systems are interconnected with distribution network. In order to avoid the negative impacts from islanding operations of DR on protection, operation and management of distribution system, it is necessary to effectively detect the islanding operations of DR and rapidly disconnect it from distribution network. Generally, it is difficult to detect islanding operation by monitoring only one system parameter This paper presents a new logic based islanding detection method for distributed resources(DR) which are interconnected with distribution network. The proposed method detects the islanding operation by monitoring four system parameter: voltage variation, phase displacement, frequency variation, and the variation of total harmonic distortion(THD) of current; therefore, it effectively detects island operation of DR unit operating in parallel with the distribution network. We also verified the efficiency of the proposed algorithm using the radial distribution network of IEEE 34 bus model.

• KIEE International Transactions on Power Engineering
• /
• 제2A권3호
• /
• pp.102-108
• /
• 2002

Due to the many attractive aspects of DG in the future power distribution system, distribution automation will be a center hub of integration of the distribution system and resources to satisfy the various needs of customers in a competitive and deregulated environment. In this paper, operation strategies are presented which use network reconfiguration of the automated distribution systems with DG as a real-time operation tool for loss reduction and service restoration from the view of distribution operation. The algorithms and operation strategies of an automated distribution system with DG are introduced to achieve the positive effects of DG in distribution systems. A simple case study shows the effectiveness of the proposed operation strategies.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권1호
• /
• pp.413-435
• /
• 2018

Although the accuracy of handwritten character recognition based on deep networks has been shown to be superior to that of the traditional method, the use of an overly deep network significantly increases time consumption during parameter training. For this reason, this paper took the training time and recognition accuracy into consideration and proposed a novel handwritten character recognition algorithm with newly designed network structure, which is based on an extended nonlinear kernel residual network. This network is a non-extremely deep network, and its main design is as follows:(1) Design of an unsupervised apriori algorithm for intra-class clustering, making the subsequent network training more pertinent; (2) presentation of an intermediate convolution model with a pre-processed width level of 2;(3) presentation of a composite residual structure that designs a multi-level quick link; and (4) addition of a Dropout layer after the parameter optimization. The algorithm shows superior results on MNIST and SVHN dataset, which are two character benchmark recognition datasets, and achieves better recognition accuracy and higher recognition efficiency than other deep structures with the same number of layers.