• Journal of the Society of Naval Architects of Korea
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• v.28 no.2
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• pp.241-250
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• 1991

The reliability analysis for web frame of tanker is carried out by the probabilistic finite element method combined with the classical reliability method such as MVFOSM and AFOSM which can be used for calculating the probability of failure for the complicated structures in which the limit state equation is implicitly expressed. As random variables external load, elastic modulus, sectional moment of inertia and field stress are chosen and Parkinson's iteration algorithm in AFOSM is used for reliability analysis. By adding only the covariance data of the random variables to the input data set required for conventional finite element method, the present method can easily calculate the probability of failure at every element end as well as the covariances of structural reponses such as displacements at every element end and member forces at every element, even for the complicated ship structure.

• The Journal of Natural Sciences
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• v.5 no.1
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• pp.87-93
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• 1992

A robotically assisted field material handling system designed for loading and unloading of a planar pallet with a forklift in unstructured field environment is presented. The system uses combined acoustic/visual sensing data to define the position/orientation of the pallet and to determine the specific locations of the two slots of the pallet, so that the forklift can move close to the slot and engage it for transport. In order to reduce the complexity of the material handling operation, we have developed a method based on the integration of 2-D range data of Poraloid ultrasonic sensor along with 2-D visual data of an optical camera. Data obtained from the two separate sources complements each other and is used in an efficient algorithm to control this robotically assisted field material handling system . Range data obtained from two linear scannings is used to determine the pan and tilt angles of a pallet using least mean square method. Then 2-D visual data is used to determine the swing angle and engagement location of a pallet by using edge detection and Hough transform techniques. The limitations of the pan and tilt orientation to be determined arc discussed. The system developed is evaluated through the hardware and software implementation. The experimental results are presented.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.1-10
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• 2000

In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modify rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verify the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.6
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• pp.375-381
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• 2019

Structural health monitoring to determine structural conditions at an early stage and to efficiently manage the energy requirements of buildings using systems that collects relevant data, is under active investigation. Structural monitoring requires cutting-edge technology in which construction, sensing, and ICT technologies are combined. However, the scope of application is limited because expensive sensors and specialized technical skills are often required. In this study, a Raspberry Pi module, one of the most widely used single board computers, a Lora module that is capable of long-distance communication at low power, and a high-performance accelerometer are used to construct a wireless edge computing system that can monitor building response over an extended time period. In addition, the Raspberry Pi module utilizes an edge computing algorithm, and only meaningful data is obtained from the vast amount of acceleration data acquired in real-time. The raw data acquired using Wi-Fi communication are compared to the Laura data to evaluate the accuracy of the data obtained using the system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8B
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• pp.1141-1149
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• 2010

Next Generation Networks (NGN) is defined as IP-based networks with multi-services and with multi-access networks. A variety of services and access technologies are co-existed within NGN. Therefore there are numerous transport technologies such as Differentiated Services (DiffServ), Multi-protocol Label Switching (MPLS), and the combined transport technologies. In such an environment, flows are aggregated and de-aggregated multiple times in their end-to-end paths. In this research, a method for calculating end-to-end delay bound for such a flow, provided that the information exchanged among networks regarding flow aggregates, especially the maximum burst size of a flow aggregate entering a network. We suggest an admission control mechanism that can decide whether the requested performance for a flow can be met. We further verify the suggested calculation and admission algorithm with a few realistic scenarios.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.10
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• pp.1062-1068
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• 2014

In this paper, a novel approach estimating target's rotation velocity(RV) is proposed for inverse synthetic aperture radar(ISAR) cross-range scaling(CRS). Scale invariant feature transform(SIFT) is applied to two sequently generated ISAR images for extracting non-fluctuating scatterers. Considering the fact that the distance between target's rotation center(RC) and SIFT features is same, we can set a criterion for estimating RV. Then, the criterion is optimized through the proposed method based on particle swarm optimization(PSO) combined with exhaustive search method. Simulation results show that the proposed algorithm can precisely estimate RV of a scenario based maneuvering target without RC information. With the use of the estimated RV, ISAR image can be correctly re-scaled along the cross-range direction.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.307-312
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• 2015

ARPA(Automatic Radar Plotting Aid) is a device to calculate CPA(closest point of approach)/TCPA(time of CPA), true course and speed of targets by vector operation of relative courses and speeds. The purpose of this study is to develop target acquisition and tracking technology for ARPA Radar implementation. After examining the previous studies, applicable algorithms and technologies were developed to be combined and basic ARPA functions were developed as a result. As for main research contents, the sequential image processing technology such as combination of grayscale conversion, gaussian smoothing, binary image conversion and labeling was deviced to achieve a proper target acquisition, and the NNS(Nearest Neighbor Search) algorithm was appllied to identify which target came from the previous image and finally Kalman Filter was used to calculate true course and speed of targets as an analysis of target behavior. Also all technologies stated above were implemented as a SW program and installed onboard, and verified the basic ARPA functions to be operable in practical use through onboard test.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.859-869
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• 2012

In this paper, a new method to efficiently generate the 3-D(three-dimensional) video holograms for 3-D moving scenes, which is called here the TSR-N-LUT method, is proposed by the combined use of temporal-spatial redundancy(TSR) of 3-D video images and novel look-up table(N-LUT) technique. That is, in the proposed scheme, with the differential pulse code modulation (DPCM) algorithm, temporally redundancy redundant data in the inter-frame of a 3-D video images are removed between the frames, and then inter-line redundant data in the inter-frame of 3-D video images are also removed by using the DPCM method between the lines. Experimental results show that the proposed method could reduced the number of calculated object points and the calculation time of one object point by 23.72% and 19.55%, respectively on the average compared to the conventional method. Good experimental results with 3-D test moving pictures finally confirmed the feasibility of the proposed method to the fast generation of CGH patterns of the 3-D video images.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.1
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• pp.81-90
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• 2002

This paper presents an Implementation of digital high-performance position sensorless control system of Reluctance Synchronous Motor(RSM) drives with Direct Torque Control(DTC). The system consists of stator flux observer, speed and torque estimator, two digital hysteresis controllers, an optimal switching look-up table, Insulated Gate Bipolar Transistor(IGBT) voltage source inverter, and TMS320C31 DSP board. The stator flux observer Is based on the combined voltage and current model with stator flux feedback adaptive control of which inputs are current and voltage sensed on motor terminal for wide speed range. In order to prove the suggested sensorless control algorithm for industrial field application, we have some simulation and actual experiment at low and high speed range. The developed high-performance speed control by fully digital system are shown a good response characteristic of control results and high performance features using 1.0[kW] RSM having 2.57 reluctance ratio of $L_d/L_q$.

• Journal of Broadcast Engineering
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• v.15 no.1
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• pp.3-13
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• 2010

In this paper, we propose a method for filling out the occlusions in generating multi-view images from one source image and its ground-truth depth image. The method is based on image inpainting and layered interpolation. The source image is first divided into several layers using depth information. The occlusions are interpolated separately in every layered image using the image inpainting algorithm. Finally, the interpolated layered images are combined to obtain different viewpoint images. Interpolating occlusions with depth-correlated texture information that is contained to each layer makes it possible to obtain more detailed and accurate results than previous methods. The effectiveness of the proposed method is shown through experimental results.