• Journal of Astronomy and Space Sciences
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• v.34 no.4
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• pp.303-314
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• 2017

With increased human activity in space, the risk of re-entry and collision between space objects is constantly increasing. Hence, the need for space situational awareness (SSA) programs has been acknowledged by many experienced space agencies. Optical and radar sensors, which enable the surveillance and tracking of space objects, are the most important technical components of SSA systems. In particular, combinations of radar systems and optical sensor networks play an outstanding role in SSA programs. At present, Korea operates the optical wide field patrol network (OWL-Net), the only optical system for tracking space objects. However, due to their dependence on weather conditions and observation time, it is not reasonable to use optical systems alone for SSA initiatives, as they have limited operational availability. Therefore, the strategies for developing radar systems should be considered for an efficient SSA system using currently available technology. The purpose of this paper is to analyze the performance of a radar system in detecting and tracking space objects. With the radar system investigated, the minimum sensitivity is defined as detection of a $1-m^2$ radar cross section (RCS) at an altitude of 2,000 km, with operating frequencies in the L, S, C, X or Ku-band. The results of power budget analysis showed that the maximum detection range of 2,000 km, which includes the low earth orbit (LEO) environment, can be achieved with a transmission power of 900 kW, transmit and receive antenna gains of 40 dB and 43 dB, respectively, a pulse width of 2 ms, and a signal processing gain of 13.3 dB, at a frequency of 1.3 GHz. We defined the key parameters of the radar following a performance analysis of the system. This research can thus provide guidelines for the conceptual design of radar systems for national SSA initiatives.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.81-89
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• 1996

A design method of fuzzy modeling is presented for the model identification of route choice of traffic problems.The proposed fuzzy modeling implements system structure and parameter identification in the eficient form of""IF..., THEN-.."", using the theories of optimization theory, linguistic fuzzy implication rules. Three kinds ofmethod for fuzzy modeling presented in this paper include simplified inference (type I), linear inference (type 21,and proposed modified-linear inference (type 3). The fuzzy inference method are utilized to develop the routechoice model in terms of accurate estimation and precise description of human travel behavior. In order to identifypremise structure and parameter of fuzzy implication rules, improved complex method is used and the least squaremethod is utilized for the identification of optimum consequence parameters. Data for route choice of trafficproblems are used to evaluate the performance of the proposed fuzzy modeling. The results show that the proposedmethod can produce the fuzzy model with higher accuracy than previous other studies -BL(binary logic) model,B(production system) model, FL(fuzzy logic) model, NN(neura1 network) model, and FNNs (fuzzy-neuralnetworks) model -.fuzzy-neural networks) model -.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1387-1399
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• 2016

In a hyper-connected society realized through IoT-enabled technology, a large amount of data is collected by various devices and is processed to provide new services to users. While communicating through a network, it is essential for devices to execute mutual authentication since users' privacy can be infringed by malicious attackers. ID-based signature enables authentication and key exchange with a unique ID of a device. However, most of the previous ID-based signature schemes based on RSA require an additional step to share parameters for key exchange so that they are not suitable for resource-constrained devices in terms of efficiency. In this paper, we design an efficient ID-based signature and thereby propose an efficient ID-based authentication and key exchange protocol in which sessions for both an authentication and a key exchange are executed simultaneously. In addition, we prove the security of our scheme under the RSA onewayness problem and analyze the efficiency by comparing with the previous schemes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.184-192
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• 2011

In this study, we introduce a identification methodology for FCM-based fuzzy model. The two underlying design mechanisms of such networks involve Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on FCM clustering method for efficient processing of data and the optimization of model was carried out using PSO. The premise part of fuzzy rules does not construct as any fixed membership functions such as triangular, gaussian, ellipsoidal because we build up the premise part of fuzzy rules using FCM. As a result, the proposed model can lead to the compact architecture of network. In this study, as the consequence part of fuzzy rules, we are able to use four types of polynomials such as simplified, linear, quadratic, modified quadratic. In addition, a Weighted Least Square Estimation to estimate the coefficients of polynomials, which are the consequent parts of fuzzy model, can decouple each fuzzy rule from the other fuzzy rules. Therefore, a local learning capability and an interpretability of the proposed fuzzy model are improved. Also, the parameters of the proposed fuzzy model such as a fuzzification coefficient of FCM clustering, the number of clusters of FCM clustering, and the polynomial type of the consequent part of fuzzy rules are adjusted using PSO. The proposed model is illustrated with the use of Automobile Miles per Gallon(MPG) and Boston housing called Machine Learning dataset. A comparative analysis reveals that the proposed FCM-based fuzzy model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• ETRI Journal
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• v.40 no.1
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• pp.39-50
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• 2018

More people prefer using rail traffic for travel or for commuting owing to its convenience and flexibility. The railway scenario has become an important communication scenario in the fifth generation era. The communication system should be designed to support high-data-rate demands with seamless connectivity at a high mobility. In this paper, the channel characteristics are studied and modeled for the railway tunnel scenario with straight and curved route shapes. On the basis of measurements using the "Mobile Hotspot Network" system, a three-dimensional ray tracer (RT) is calibrated and validated for the target scenarios. More channel characteristics are explored via RT simulations at 25.25 GHz with a 500-MHz bandwidth. The key channel parameters are extracted, provided, and incorporated into a 3rd-Generation-Partnership-Project-like stochastic channel generator. The necessary channel information can be practically realized, which can support the link-level and system-level design of the communication system in similar scenarios.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.10
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• pp.1-6
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• 2007

Wireless Self-Powered Temperature Sensor for UHF Sensor Tags which are basic device for construction of ubiquitous sensor network is proposed. The key parameters of the target specification are resolution of $0.1\;^{\circ}C$ per output bit, below 1.5 V of operating voltage and below 5 uW of power consumption during sensing operation. Temperature sensor circuit consists of PTAT current generator, band gap reference circuit generating both reference voltage and current, Sigma-Delta Converter, and Digital Counter. Simulated maximum resolution was $0.23\;^{\circ}C/bit$ in 11-bit output. The proposed temperature sensor was fabricated by using a 0.25 m CMOS process. The chip area is $0.32\;{\times}\;0.22\;mm$ and the operating frequency is 2 MHz. Measured resolution from fabricated temperature sensor was $4\;^{\circ}C/bit$ in 8-bit output for the temperature range from $10^{\circ}C$ to $80^{\circ}C$.

• Journal of Korea Water Resources Association
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• v.40 no.11
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• pp.841-849
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• 2007

This study evaluated the effect of combined rainfall observation of using rain gauge and rain radar. The effect of combined observations is to be evaluated by considering the decrease of measurement error due to combined use of design orthogonal observation methods. As an example, this study evaluated the rain gauge network of the Keum river basin, and showed how the density of rain gauges could be decreased by combining the radar observation. This study applied the researches on sampling error by North and Nakamoto(1989), Yoo et al. (1996) and Yoo (1997), also the simple NFD model for representing the rainfall field. The model parameters were decided using the rainfall characteristics (correlation time and length) estimated using the data collected in the Keum River Basin by 28 rain gauges and the operation rule of radar was assumed arbitrarily. This study considered the rain gauge density criteria provided by WMO(1994) and the rain gauge density installed in the Keum river basin to decrease the rain gauge density under the condition of introducing the radar.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.408-411
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• 2009

In this paper, conventional PI, fuzzy neural network(FNN) and adaptive teaming mechanism(ALM)-FNN for rotor field oriented controlled(RFOC) induction motor are studied comparatively. The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. Comparative study of PI, FNN and ALM-FNN are carried out from various aspects which is dynamic performance, steady-state accuracy, parameter robustness and complementation etc. To have a clear view of the three techniques, a RFOC system based on a three level neutral point clamped inverter-fed induction motor drive is established in this paper. Each of the three control technique: PI, FNN and ALM-FNN, are used in the outer loops for rotor speed. The merit and drawbacks of each method are summarized in the conclusion part, which may a guideline for industry application.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.5
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• pp.86-94
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• 2008

In this paper proposed the solar tracking system to use a fuzzy based on PC in of order to increase an output of the PV(Photovoltaic) array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. Recently, artificial intelligent control of the fuzzy control, neural-network and genetic algorithm etc. have been studies. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. Hence the fuzzy control was used to perform the tracking system after comparing with error values of setting-up, nonlinear altitude and azimuth. In this paper designed a fuzzy controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.

• Journal of the Korean Society for Railway
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• v.19 no.4
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• pp.436-444
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• 2016

The primary windings of the main transformer for rolling stock have several natural frequencies that can occur internal resonance with transient voltages induced on a high voltage feeding line. Factory testing is limited in its ability to determine whether or not transient voltage with various shape and duration can be excitable. This study presents the design of a high voltage windings model and simulation and analysis of the internal resonant characteristics in terms of the initial voltage distribution and voltage-frequency relationship using the electromagnetic transients program (EMTP). Turn-based lumped-parameters are calculated using the geometry data of the transformer. And, sub-models, being grouped into the total number of layers, are composed using a ladder-network model and implemented by the library function of EMTP. Case studies are used to show the layer-based voltage-frequency relationship characteristics according to the frequency sweep and the voltage escalation and distribution aspects in time-domain simulation.