• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.392-397
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• 2014

Recently, there are many researches on active safety system of intelligent vehicle. To reduce the probability of collision caused by driver's inattention and mistakes, the active safety system gives warning or controls the vehicle toward avoiding collision. For the purpose, it is necessary to recognize and analyze circumstances around. In this paper, we will treat the problem about collision risk assessment. In general, it is difficult to calculate the collision risk before it happens. To consider the uncertainty of the situation, Monte Carlo simulation can be employed. However it takes long computation time and is not suitable for practice. In this paper, we apply neural networks to solve this problem. It efficiently computes the unseen data by training the results of Monte Carlo simulation. Furthermore, we propose the features affects the performance of the assessment. The proposed algorithm is verified by applications in various crash scenarios.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.4
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• pp.82-92
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• 2006

In the field of image recognition, research on face recognition has recently attracted a lot of attention. The most important step in face recognition is automatic eye detection researched as a prerequisite stage. Existing eye detection methods for focusing on the frontal face can be mainly classified into two categories: active infrared(IR)-based approaches and image-based approaches. This paper proposes an eye region detection method in non-frontal faces. The proposed method is based on the edge--based method that shows the fastest computation time. To extract eye region in non-frontal faces, the method uses edge orientationhistogram of the global region of faces. The problem caused by some noise and unfavorable ambient light is solved by using proportion of width and height for local information and relationship between components for global information in approximately extracted region. In experimental results, the proposed method improved precision rates, as solving 3 problems caused by edge information and achieves a detection accuracy of 83.5% and a computational time of 0.5sec per face image using 300 face images provided by The Weizmann Institute of Science.

• Journal of the Korean Society of Groundwater Environment
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• v.6 no.1
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• pp.23-32
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• 1999

A new numerical method using solution-adaptive grids (SAG) is developed to solve the Richards' equation (RE) for unsaturated flow in porous media. Using a grid generation technique, the SAG method automatically redistributes a fixed number of grid points during the flow process, so that more grid points are clustered in regions of large solution gradients. The method uses the coordinate transformation technique to employ a new transformed RE, which is solved with the standard finite difference method. The movement of grid points is incorporated into the transformed RE, and therefore all computation is performed on fixed grid points of the transformed domain without using any interpolation techniques. Thus, numerical difficulties arising from the movement of the wetting front during the infiltration process have been substantially overcome by the new method. Numerical experiments for an one-dimensional infiltration problem are presented to compare the SAG method to the modified Picard method using a fixed grid. Results show that accuracy of a SAG solution using 41 nodes is comparable with the solution of the fixed grid method using 201 nodes, while it requires only 50% of the CPU time. The global mass balance and the convergence of SAG solutions are strongly affected by the time step size (Δt) and the weighting parameter (${\gamma}$) used for generating solution-adaptive grids. Thus, the method requires automated readjustment of Δt and ${\gamma}$ to yield mass-conservative and convergent solutions, although it may increase computational costs. The method can be effective especially for simulating unsaturated flow and other transport problems involving the propagation of a sharp-front.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.305-313
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• 2019

Recently, spatial information is being constructed actively based on the images obtained by drones. Because occlusion areas occur due to buildings as well as many obstacles, such as trees, pedestrians, and banners in the urban areas, an efficient way to resolve the problem is necessary. Instead of the traditional way, which replaces the occlusion area with other images obtained at different positions, various models based on deep learning were examined and compared. A comparison of a type of feature descriptor, HOG, to the machine learning-based SVM, deep learning-based DNN, CNN, and RNN showed that the CNN is used broadly to detect and classify objects. Until now, many studies have focused on the development and application of models so that it is impossible to select an optimal model. On the other hand, the upgrade of a deep learning-based detection and classification technique is expected because many researchers have attempted to upgrade the accuracy of the model as well as reduce the computation time. In that case, the procedures for generating spatial information will be changed to detect the occlusion area and replace it with simulated images automatically, and the efficiency of time, cost, and workforce will also be improved.

• Journal of the Korean Institute of Landscape Architecture
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• v.35 no.1 s.120
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• pp.1-8
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• 2007

The purpose of this study is to suggest the minimum distance needed between landscape trees and apartment buildings. in order for the trees to grow soundly and maintain constant growth. Therefore, this study investigated and analyzed the present conditions of the green-spaces contiguous to apartment buildings and the trees inside the apartment complex. The following general problems were identified : (1) the tree growth conditions, (2) the planting intervals, and (3) the planting methods in the apartment complexes. The method of this study was to survey areas, measure the trees and analyze the results. Ten apartment complexes located in Seoul were randomly selected for this study. To analyze the greens contiguous to the building of each apartment complex, the greens were divided into three types, including the front greens, the side greens, and the rear greens. The study surveyed the width of all contiguous greens and the distance from trees to my given building. Four representative sites were specifically investigated to measure the crown widths, heights, and diameters of the trees. These investigations were carried out over 3 months from August to December 2006. According to the results of the study, it was found that the greens are narrower in width and the more closer to a building. The study identified a correlation between the tree and the passage of time after the completion of construction of an apartment complex, showing that the malformation of the trees worsened as time passed. As a result of measuring the right crown and left crown width with the tree trunk as the center, a broad difference was found between coniform trees and trees that tend to branch out more. For example, the ratio of the width of the Acer palmatum is 1:6. However, the ratio of the Metasequoia glyptostroboide is 1:1.7. Based on the overall analysis, it was concluded that the maintained minimum width must be greater than one meter over the green space according to the 'Landscape Standard 2000'. However, that is only applicable to cases such as apartment buildings that present no obstacles. In conclusion having greens placed within one meter of width to a building is not an appropriate environment for the healthy growth of trees. To create sound green spaces, sustainable, long-term growth rate and size should be considered. It is necessary to prepare new standards for the computation of planting trees and the measurement of square landscapes. Wall greenery and shrubberies could be an alternative in the case of a narrow-width green space.

• The KIPS Transactions:PartC
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• v.14C no.4
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• pp.331-340
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• 2007

Mobile network environments are the environments where mobile devices are distributed invisible in our daily lives so that we can conventionally use mobile services at my time and place. The fact that we can work with mobile devices regardless of time and place, however, means that we are also in security threat of leaking or forging the information. In particular, without solving privacy concern, the mobile network environments which serve convenience to use, harmonized without daily lives, on the contrary, will cause a serious malfunction of establishing mobile network surveillance infrastructure. On the other hand, as the mobile devices with various sizes and figures, public key cryptography techniques requiring heavy computation are difficult to be applied to the computational constrained mobile devices. In this paper, we propose efficient PKI-based user authentication and java-based cryptography module for the privacy-preserving in mobile network environments. Proposed system is support a authentication and digital signature to minimize encrypting and decrypting operation by compounding session key and public key based on Korean standard cryptography algorithm(SEED, KCDSA, HAS160) and certificate in mobile network environment. Also, it has been found that session key distribution and user authentication is safety done on PDA.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.99-104
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• 2012

The United States will proceed with the effort to modernize the GPS system, and one of its main content is to provide L5 signal. L5 will be transmitted in a radio band reserved exclusively for aviation safety services. And, L5, in combination with L1, will improve the position accuracy via ionospheric correction and robustness via signal redundancy. However, The acquisition processing time of L5 takes longer than that of L1 as the code length of L5 is 10 times longer than that of L1. To reduce this acquisition processing time, a higher number of correlators in the aquisition module should be used. However, there is a problem that this causes increase in the complexity of the correlator configuration and the computation power. So, in this paper, we propose L5 signal tracking scheme using tracking results in the GPS L1/L5 receiver. The proposed scheme could reduce the hardware complexity as the GPS L5 signal acquisition module is not needed, and provide fast and stable tracking of L5 signal by aiding L1 tracking results such as PRN, the code phase synchronization, and the Doppler frequency. The feasibility of the proposed scheme is demonstrated through simulation results.

• Journal of KIISE:Databases
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• v.34 no.6
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• pp.503-517
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• 2007

In this paper we address the MBR-safe property of Piecewise Aggregation Approximation(PAA), and propose an of efficient subsequence matching method based on the MBR-safe PAA. A transformation is said to be MBR-safe if a low-dimensional MBR to which a high- dimensional MBR is transformed by the transformation contains every individual low-dimensional sequence to which a high-dimensional sequence is transformed. Using an MBR-safe transformation we can reduce the number of lower-dimensional transformations required in similar sequence matching, since it transforms a high-dimensional MBR itself to a low-dimensional MBR directly. Furthermore, PAA is known as an excellent lower-dimensional transformation single its computation is very simple, and its performance is superior to other transformations. Thus, to integrate these advantages of PAA and MBR-safeness, we first formally confirm the MBR-safe property of PAA, and then improve subsequence matching performance using the MBR-safe PAA. Contributions of the paper can be summarized as follows. First, we propose a PAA-based MBR-safe transformation, called mbrPAA, and formally prove the MBR-safeness of mbrPAA. Second, we propose an mbrPAA-based subsequence matching method, and formally prove its correctness of the proposed method. Third, we present the notion of entry reuse property, and by using the property, we propose an efficient method of constructing high-dimensional MBRs in subsequence matching. Fourth, we show the superiority of mbrPAA through extensive experiments. Experimental results show that, compared with the previous approach, our mbrPAA is 24.2 times faster in the low-dimensional MBR construction and improves subsequence matching performance by up to 65.9%.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1367-1383
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• 2007

A sensor network consists of a network of sensors that can perform computation and also communicate with each other through wireless communication. Some important characteristics of sensor networks are that the network should be self administered and the power efficiency should be greatly considered due to the fact that it uses battery power. In sensor networks, when large amounts of various stream data is produced and multiple queries need to be processed simultaneously, the power efficiency should be maximized. This work proposes a technique to create an index on multiple monitoring queries so that the multi-query processing performance could be increased and the memory and power could be efficiently used. The proposed SMILE tree modifies and combines the ideas of spatial indexing techniques such as k-d trees and R+-trees. The k-d tree can divide the dimensions at each level, while the R+-tree improves the R-tree by dividing the space into a hierarchical manner and reduces the overlapping areas. By applying the SMILE tree on multiple queries and using it on stream data in sensor networks, the response time for finding an indexed query takes in some cases 50% of the time taken for a linear search to find the query.

• Journal of Navigation and Port Research
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• v.41 no.3
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• pp.137-148
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• 2017

Port service level is a metric of competitiveness among ports for the operating/managing bodies such as the terminal operation company (TOC), Port Authority, or the government, and is used as an important indicator for shipping companies and freight haulers when selecting a port. Considering the importance of metrics, we developed software to objectively define and manage six important service indicators exclusive to container and bulk terminals including: berth occupancy rate, ship's waiting ratio, berth throughput, number of berths, average number of vessels waiting, and average waiting time. We computed the six service indicators utilizing berth 1 through berth 5 in the container terminals and berth 1 through berth 4 in the bulk terminals. The software model allows easy computation of expected ship's waiting ratio over berth occupancy rate, berth throughput, counts of berth, average number of vessels waiting and average waiting time. Further, the software allows prediction of yearly throughput by utilizing a ship's waiting ratio and other productivity indicators and making calculations based on arrival patterns of ship traffic. As a result, a TOC is able to make strategic decisions on the trade-offs in the optimal operating level of the facility with better predictors of the service factors (ship's waiting ratio) and productivity factors (yearly throughput). Successful implementation of the software would attract more shipping companies and shippers and maximize TOC profits.