• Journal of Communications and Networks
• /
• 제17권3호
• /
• pp.286-295
• /
• 2015

Avionic databuses fulfill a critical function in the connection and communication of aircraft components and functions such as flight-control, navigation, and monitoring. Ethernet-based avionic databuses have become the mainstream for large aircraft owning to their advantages of full-duplex communication with high bandwidth, low latency, low packet-loss, and low cost. As a new generation aviation network communication standard, avionics full-duplex switched ethernet (AFDX) adopted concepts from the telecom standard, asynchronous transfer mode (ATM). In this technology, the switches are the key devices influencing the overall performance. This paper reviews the avionic databus with emphasis on the switch architecture classifications. Based on a comparison, analysis, and discussion of the different switch architectures, we propose a new avionic switch design based on a time-division switch fabric for high flexibility and scalability. This also merges the design concept of space-partition switch fabric to achieve reliability and predictability. The new switch architecture, called space partitioned shared memory switch (SPSMS), isolates the memory space for each output port. This can reduce the competition for resources and avoid conflicts, decrease the packet forwarding latency through the switch, and reduce the packet loss rate. A simulation of the architecture with optimized network engineering tools (OPNET) confirms the efficiency and significant performance improvement over a classic shared memory switch, in terms of overall packet latency, queuing delay, and queue size.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.631-634
• /
• 2004

In this paper, the Bayesian recurrent neural network (BRNN) is proposed to predict time series data. Among the various traditional prediction methodologies, a neural network method is considered to be more effective in case of non-linear and non-stationary time series data. A neural network predictor requests proper learning strategy to adjust the network weights, and one need to prepare for non-linear and non-stationary evolution of network weights. The Bayesian neural network in this paper estimates not the single set of weights but the probability distributions of weights. In other words, we sets the weight vector as a state vector of state space method, and estimates its probability distributions in accordance with the Bayesian inference. This approach makes it possible to obtain more exact estimation of the weights. Moreover, in the aspect of network architecture, it is known that the recurrent feedback structure is superior to the feedforward structure for the problem of time series prediction. Therefore, the recurrent network with Bayesian inference, what we call BRNN, is expected to show higher performance than the normal neural network. To verify the performance of the proposed method, the time series data are numerically generated and a neural network predictor is applied on it. As a result, BRNN is proved to show better prediction result than common feedforward Bayesian neural network.

• 한국지역지리학회지
• /
• 제12권2호
• /
• pp.245-264
• /
• 2006

많은 개념적 연구와 담론에 의하면, 정보통신기술의 발달은 일상생활의 시공간적 활동에 지대한 영향을 미치고 있다. 그러나 이에 관한 경험적 연구들은 실제 그 영향이 그렇게 크지 않다는 점을 보이고 있다. 이러한 양 입장을 벗어나기 위해, 이 논문에서는 정보통신기술의 발달과 사회공간에 미치는 영향에 관한 연구는 개별 현상이나 의식에 초점을 두기보다는 사회공간적 관계, 즉 네트워크의 변화에 관심을 주어야 한다는 점을 주장한다. 카스텔(Castells), 어리(Urry) 등이 주장하는 바와 같이, 사실 정보기술의 발달은 새로운 정보네트워크의 창출을 의미하며, 그 공간적 측면을 이해하기 위해 '네트워크 사회공간'이라는 용어를 사용할 수 있고, 라투어(Latour) 등이 주장하는 '행위자-연결망'이론이 원용될 수 있다. 이 논문에서는 특히 새로운 사회공간을 구성하는 네트워크는 즉시적 층위, 기능적 층위, 그리고 물질적 층위를 가지는 것으로 이해한다. 또한 네트워크사회공간은 새로운 사회공간적 관련성으로서 중요성을 가질 뿐만 아니라, 네트워크의 결절을 형성하는 주체들의 참여와 이를 통한 정체성의 재구성이라는 점에서도 중요한 의미를 가진다는 점이 강조된다.

• 한국항공우주학회지
• /
• 제49권3호
• /
• pp.197-204
• /
• 2021

유도탄의 비행 시험 중 고장 또는 비정상적인 기동이 발생하는 경우 비행을 계속하지 않도록 의도적으로 자폭한다. 이때 파편이 발생하며 안전 지역을 벗어났는지 여부를 실시간으로 추정하는 것이 중요하다. 본 논문에서는 Fully-Connected Neural Network(FCNN)를 이용하여 실시간으로 파편의 예상 낙하 영역 및 낙하 시간을 추정하는 방법을 제안한다. 많은 양의 학습 데이터 생성을 위해 Unscented Transform(UT)를 적용하였으며 신뢰도 확보를 위해 Monte-Carlo(MC) 시뮬레이션과 비교하여 파라미터를 선정하였다. 또한 제안한 방법의 추정 결과를 MC와 비교하여 성능을 분석하였다.

• 천문학논총
• /
• 제30권1호
• /
• pp.31-38
• /
• 2015

We develop a real-time data transfer system for the Korea Microlensing Telescope Network (KMTNet) photometry data and test whether it is suitable for Korea Astronomy and Space Science Institute (KASI) and three different observatories, which are Cerro Tololo Inter-Ameriacan Observatory (CTIO) in Chile, Siding Springs Observatory (SSO) in Australia, and South African Astronomical Observatory (SAAO) in South Africa. For this test, we use a high speed global network being dedicated for researches. From the test, we obtain that the elapsed times between KASI and each three observatories, CTIO, SSO, and SAAO to transfer 650 MB of data are 99.0, 9.2, 119.0 seconds, respectively. This means that the system can be used for the real-time data processing of KMTNet.

• Journal of Positioning, Navigation, and Timing
• /
• 제11권4호
• /
• pp.263-268
• /
• 2022

Precise Point Positioning-Real Time Kinematic (PPP-RTK) is a high accuracy positioning method that combines RTK and PPP to overcome the limitations on service coverage of RTK and convergence time of PPP. PPP-RTK provides correction data in the form of State Space Representation (SSR), unlike RTK, which provides measurement-based Observation Space Representation (OSR). Due to this, PPP-RTK has an advantage that it can transmit less data than RTK. So, recently, several techniques for PPP-RTK have been proposed. However, in order to utilize PPP-RTK techniques, performance analysis of these in a real environment is essential. In this paper, we implement the local network PPP-RTK and analyze the positioning performance according to the distance within 100 km from the reference station in Korea. As results of experiment, the horizontal and vertical 95% errors of local network PPP-RTK were 6.25 cm and 5.86 cm or less, respectively.

• 한국정보통신학회논문지
• /
• 제24권3호
• /
• pp.349-354
• /
• 2020

녹지 영역의 확충을 위한 사전 조사에는 많은 비용과 시간이 필요하다는 문제가 발생한다. 본 논문에서는 구글 어스를 이용한 합성곱 신경망 기반의 녹지 분류를 통해 특정 지역의 녹지 비율을 측정함으로써 문제를 해결한다. 먼저 제안하는 방법은 구글 어스에서 여러 지역 영상을 수집하고 합성곱 신경망을 이용하여 학습한다. 제안하는 방법은 특정 지역의 녹지 비율을 측정하기 위해서 영상을 재귀적으로 분할하고 학습된 모델을 이용하여 녹지 여부를 판단한 뒤, 녹지로 판단된 영역 면적을 이용하여 녹지 비율을 계산한다. 실험 결과 제안하는 방법은 다양한 지역의 녹지 비율 측정에 높은 성능을 보여주는 것을 확인할 수 있었다.

• Journal of Astronomy and Space Sciences
• /
• 제34권1호
• /
• pp.7-17
• /
• 2017

In South Korea, there are about 80 Global Positioning System (GPS) monitoring stations providing total electron content (TEC) every 10 min, which can be accessed through Korea Astronomy and Space Science Institute (KASI) for scientific use. We applied the computerized ionospheric tomography (CIT) algorithm to the TEC dataset from this GPS network for monitoring the regional ionosphere over South Korea. The algorithm utilizes multiplicative algebraic reconstruction technique (MART) with an initial condition of the latest International Reference Ionosphere-2016 model (IRI-2016). In order to reduce the number of unknown variables, the vertical profiles of electron density are expressed with a linear combination of empirical orthonormal functions (EOFs) that were derived from the IRI empirical profiles. Although the number of receiver sites is much smaller than that of Japan, the CIT algorithm yielded reasonable structure of the ionosphere over South Korea. We verified the CIT results with NmF2 from ionosondes in Icheon and Jeju and also with GPS TEC at the center of South Korea. In addition, the total time required for CIT calculation was only about 5 min, enabling the exploration of the vertical ionospheric structure in near real time.

• 천문학회보
• /
• 제37권2호
• /
• pp.239.1-239.1
• /
• 2012

This paper presents the results of one of early sciences with Korean VLBI Network (KVN): a large fringe survey of compact radio sources at 43GHz. We established the catalog of correlated flux densities in three ranges of baseline projection lengths of 637 sources from a 43 GHz (Q-band) survey observed with the Korean VLBI Network. Of them, 623 sources have not been observed before at Q-band with VLBI. The goal of this work in the early science phase of the new VLBI array is twofold: to evaluate the performance of the new instrument that operates in a frequency range of 22--129 GHz and to build a list of objects that can be used as targets and as calibrators. We have observed the list of 799 target sources with declinations down to $-40{\circ}$. Among them, 724 were observed before with VLBI at 22 GHz and had correlated flux densities greater than 200 mJy. The overall detection rate is 78%. The detection limit, defined as the minimum flux density for a source to be detected with 90% probability in a single observation, was in a range of 115--180 mJy depending on declination. However, some sources as weak as 70 mJy have been detected. Of 623 detected sources, 33 objects are detected for the first time in VLBI mode. We determined their coordinates with the median formal uncertainty 20 mas. The results of this work set the basis for future efforts to build the complete flux-limited sample of extragalactic sources at frequencies 22 GHz and higher at 3/4 of the celestial sphere.

• Nuclear Engineering and Technology
• /
• 제32권5호
• /
• pp.485-494
• /
• 2000

In this work, a fuzzy neural network is used to estimate the relevant sensor signal using other sensor signals. Noise components in input signals into the fuzzy neural network are removed through the wavelet denoising technique . Principal component analysis (PCA) is used to reduce the dimension of an input space without losing a significant amount of information. A lower dimensional input space will also usually reduce the time necessary to train a fuzzy-neural network. Also, the principal component analysis makes easy the selection of the input signals into the fuzzy neural network. The fuzzy neural network parameters are optimized by two learning methods. A genetic algorithm is used to optimize the antecedent parameters of the fuzzy neural network and a least-squares algorithm is used to solve the consequent parameters. The proposed algorithm was verified through the application to the pressurizer water level and the hot-leg flowrate measurements in pressurized water reactors.