• Journal of Korea Port Economic Association
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• v.35 no.3
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• pp.19-40
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• 2019

Ports have been facing the adverse impacts of the global recession. In terms of imports, with a vast consumption hinterland, the Incheon Port has developed as the metropolitan's gateway. Additionally, the port's exports to China has been increasing due to a consistent increase in the demand of cold chain foods in the country. Considering the short distance between the Incheon Port and the ports in Northern China, the Incheon Port can serve as a logistics hub and a distribution center for exporting processed foodstuffs to China. The establishment of a cold chain logistics system at the Incheon Port will prove to be a robust strategy. After reviewing studies and interviews from various departments, this study suggested strengths, weaknesses, opportunities, and threats (SWOT) facing the Incheon Port, based on a SWOT analysis; it also recommended competitive strategies for the port. Additionally, the study used the analytic hierarchy process (AHP) to identify important factors such as the infrastructural, operational, cost, and technology factors. This study identified the infrastructural factor to be highly critical to the activation of the Incheon Port's cold chain system. Based on the results, the study proposed policies and strategy directions.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.5
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• pp.401-414
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• 2018

Planing hull type ships are often equipped with interceptor or trim tab to improve the excessive trim angle which leads to poor resistance and sea keeping performances. The purpose of this study is to design a controller to control the attitude of the ship by controllable stern interceptor and validate the effectiveness of the attitude control by the towing tank test. Embedded controller, servo motor and controllable stern interceptor system were equipped with planing hull type model ship. Prior to designing the control algorithm, a model test was performed to identify the system dynamic model of the planing hull type ship including the stern interceptor. The matrix components of model were optimized by Genetic Algorithm. Using the identified model, PID controller which is a classical controller and sliding mode controller which is a nonlinear robust controller were designed. Gain tuning of the controllers and running simulation was conducted before the towing tank test. Inserting the designed control algorithm into the embedded controller of the model ship, the effectiveness of the active control of the stern interceptor was validated by towing tank test. In still water test with small disturbance, the sliding mode controller showed better performance of canceling the disturbance and the steady-state control performance than the PID controller.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.37-48
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• 2012

Image registration is a process to establish the spatial correspondence between the images of same scene, which are acquired at different view points, at different times, or by different sensors. In this paper, we propose an effective registration method for images acquired by multi-sensors, such as EO (electro-optic) and IR (infrared) sensors. Image registration is achieved by extracting features and finding the correspondence between features in each input images. In the recent research, the multi-sensor image registration method that finds corresponding features by exploiting NMI (Normalized Mutual Information) was proposed. Conventional NMI-based image registration methods assume that the statistical correlation between two images should be global, however images from EO and IR sensors often cannot satisfy this assumption. Therefore the registration performance of conventional method may not be sufficient for some practical applications because of the low accuracy of corresponding feature points. The proposed method improves the accuracy of corresponding feature points by combining the gradient orientation as spatial information along with NMI attributes and provides more accurate and robust registration performance. Representative experimental results prove the effectiveness of the proposed method.

• Korean Journal of Optics and Photonics
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• v.16 no.4
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• pp.326-333
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• 2005

Phase-only encryption scheme using exclusive-OR rules in Fourier plane and a single path decryption system are presented. A zero-padded original image, multiplied by a random phase image, is Fourier transformed and its real-valued data is encrypted with key data by using XOR rules. A decryption is simply performed based on 2-1 setup with spatial filter by Fourier transform for multiplying phase-only encrypted data by phase-only key data, which are obtained by phase-encoding process, and spatial filtering for zero-order elimination in inverse-Fourier plane. Since the encryption process is peformed in Fourier plane, proposed encryption scheme is more tolerant to loss of key information by scratching or cutting than previous XOR encryption method in space domain. Compare with previous phase-visualization systems, due to the simple architecture without a reference wave, our system is basically robust to mechanical vibrations and fluctuations. Numerical simulations have confirmed the proposed technique as high-level encryption and simple decryption architecture.

• Korean Journal of Optics and Photonics
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• v.24 no.5
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• pp.213-216
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• 2013

This paper presents a combination of linear Fresnel lenses optimized for ${\times}25$ solar concentration. The combined lens consists of $5{\times}5$ linear Fresnel lenses. Each Fresnel lens is of $10{\times}10$ mm and optimized to tilt the incoming light onto a solar cell of the same size. All of the optimized Fresnel segments have the same pattern height of 35 ${\mu}m$, draft angle of $4^{\circ}$, and edge groove round of 1 ${\mu}m$ but with different facet angles varying from $14.1^{\circ}$ to $31.2^{\circ}$. The solar concentrating efficiency of the combination is shown to be over 80% and more robust than a conventional single ${\times}25$ circular Fresnel lens in terms of pointing misalignment and manufacturing errors. A sensitivity analysis finds that the edge groove round should be kept as small as machining allows since the concentrating efficiency drops ~5% per 1 ${\mu}m$ increase of the edge groove.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.3 s.303
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• pp.39-52
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• 2005

In this paper, a registration method is presented to register partial 3D point clouds, acquired from a multi-view camera, for 3D reconstruction of an indoor environment. In general, conventional registration methods require a high computational complexity and much time for registration. Moreover, these methods are not robust for 3D point cloud which has comparatively low precision. To overcome these drawbacks, a projection-based registration method is proposed. First, depth images are refined based on temporal property by excluding 3D points with a large variation, and spatial property by filling up holes referring neighboring 3D points. Second, 3D point clouds acquired from two views are projected onto the same image plane, and two-step integer mapping is applied to enable modified KLT (Kanade-Lucas-Tomasi) to find correspondences. Then, fine registration is carried out through minimizing distance errors based on adaptive search range. Finally, we calculate a final color referring colors of corresponding points and reconstruct an indoor environment by applying the above procedure to consecutive scenes. The proposed method not only reduces computational complexity by searching for correspondences on a 2D image plane, but also enables effective registration even for 3D points which have low precision. Furthermore, only a few color and depth images are needed to reconstruct an indoor environment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.1
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• pp.19-29
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• 2003

This paper presents a novel hybrid classifier for face recognition with artificially generated virtual training samples. We utilize both the nearest neighbor approach in feature angle space and a connectionist model to obtain a synergy effect by combining the results of two heterogeneous classifiers. First, a classifier called the nearest feature angle (NFA), based on angular information, finds the most similar feature to the query from a given training set. Second, a classifier has been developed based on the recall of stored frontal projection of the query feature. It uses a frontal recall network (FRN) that finds the most similar frontal one among the stored frontal feature set. For FRN, we used an ensemble neural network consisting of multiple multiplayer perceptrons (MLPs), each of which is trained independently to enhance generalization capability. Further, both classifiers used the virtual training set generated adaptively, according to the spatial distribution of each person's training samples. Finally, the results of the two classifiers are combined to comprise the best matching class, and a corresponding similarit measure is used to make the final decision. The proposed classifier achieved an average classification rate of 96.33% against a large group of different test sets of images, and its average error rate is 61.5% that of the nearest feature line (NFL) method, and achieves a more robust classification performance.

• Journal of Digital Convergence
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• v.13 no.1
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• pp.297-304
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• 2015

Recently, the demand for a PRT(Personal Rapid Transit) system based on autonomous navigation is increasing. Accordingly, the applicability investigations of the PRT system on rail tracks or roadways have been widely studied. In the case of unmanned vehicle operations without physical guideways on roadways, to monitor the position of the vehicle in real time is very important for stable, robust and reliable guidance of an autonomous vehicle. The Global Positioning System (GPS) has been commercially used for vehicle positioning. However, it cannot be applied in environments as tunnels or interiors of buildings. The PRT navigation system based on magnetic markers reference sensing that can overcome these environmental restrictions and the vehicle dynamics model for its H/W configuration are presented in this study. In addition, the design of a control S/W dedicated for unmanned operation of a PRT vehicle and its prototype implementation for experimental validation on a pilot network were successfully achieved.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.4
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• pp.11-17
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• 2001

In this paper, we propose a polarity decision carrier recovery algorithm for high order QAM(Quadrature Amplitude Modulation), which has robust and large frequency acquisition performance in the high order QAM modem. The proposed polarity decision PD(Phase Detector) output and its variance characteristic are mathematically derived and the simulation results are compared with conventional DD(Decision-Directed) method. While the conventional DD algorithm has linear range of $3.5^{\circ}{\sim}3.5^{\circ}$, the proposed polarity decision PD algorithm has linear range as large as $-36^{\circ}{\sim}36^{\circ}$ at ${\gamma}-17.9$. The conventional DD algorithm can only acquire offsets less than ${\pm}10\;KHz$ in the case of the 256 QAM while an analog front-end circuit generally can reduce the carrier-frequency offset down to only ${\pm}100\;KHz$. Thus, in this case additional AFC or phase detection circuit for carrier recovery is required. But by adopting the proposed polarity decision algorithm, we can find the system can acquire up to ${\pm}300\;KHz$at SNR = 30dB without aided circuit.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.209-220
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• 2014

In this paper, we analyze the discriminability of features for the classification of transient signals with an ambient noise in a shallow water. For the classification of the transient signals, robust features for the variance of a noise are required due to a low SNR under a marine environment. In the modelling the ambient noise in shallow water, theoretical noise model, Wenz's observation data from the shallow water, and Yule-walker filter are used. Discrimination of each feature of the transient signals with an additive ambient noise is analyzed by utilizing a Fisher score. As the analysis of a classification accuracy about the transient signals of 24 classes using the selected features with a high discriminability, the features selected in the environment without a noise relatively have a good classification accuracy. From the analyzed results, we finally select a total 16 features out of 28 features. The recognition using the selected features results in the classification accuracy of 92% in SNR 20dB using Multi-class SVM.