• Journal of Environmental Impact Assessment
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• v.27 no.5
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• pp.447-474
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• 2018

The purpose of this study is to build a new dataset of spatially interpolated climate data of South Korea by performing various geo-statistical interpolation techniques for comparison with the LDAPS grid data of KMA. Among 595 observation data in 2017, 80 % of the total points and remaining 117 points were used for spatial mapping and quantification,respectively. IDW, cokriging, and kriging were performed via the ArcGIS10.3.1 software and Python3.6.4, and each result was then divided into three clusters and four watersheds for statistical verification. As a result, cokriging produced the most suitable grid climate data for instantaneous temperature. For 1-hr accumulated precipitation, IDW was most suitable for expressing local rainfall effects.

• Journal of Korean Tunnelling and Underground Space Association
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• v.15 no.3
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• pp.253-270
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• 2013

This paper concerns the effect of orientation and geometric characteristics of a fracture zone on the tunnel behavior using a numerical investigation. A parametric study was executed on a number of drill and blast tunnelling cases representing different fracture and tunnelling conditions using two and three dimensional finite element analyses. The variables considered include the strike and dip angle of fracture zone relative to the longitudinal tunnel axis, the width and the clearance of the fracture zone, the tunnel depth, and the initial lateral stress coefficient. The results of the analyses were examined in terms of the tunnel deformation including crown settlement, convergence, and invert heave as well as shotcrete lining stresses. The results indicate that the tunnel deformation as well as the shotcrete lining stress are strongly influenced by the orientation of the fracture zone, and that such a trend becomes more pronounced for tunnels with greater depths.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.609-617
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• 2017

Railways are one of the safest and most important transportation systems in the world. On the other hand, due to the increasing complexity of the railway system and the running distance of rail vehicles, railway accidents occur continuously every year. In particular, in the case of high-speed trains and freight trains, if the function of the axle bearing is lost due to abnormal overheating of the axle box bearing, the load on the axle becomes uneven. Therefore, abnormal overheating in the train axle box bearings can cause serious accidents or derailments. For this purpose, a Hot Box Detector (HBD) was installed in the track side of a high speed line to detect abnormal overheating. This paper proposes an EWMA technique-based axle temperature monitoring method to detect abnormal overheating quickly and efficiently. A statistical design of the proposed method was also performed. The proposed method has better performance compared to the current method in the case of abnormal overheating and the performance is improved by approximately 170% at the maximum.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.558-567
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• 2017

In this research, we developed an efficient real-time human exercise pose estimation system using multiple Kinects. The main objective of this system is to measure and recognize the user's posture (such as knee curl or lunge) more accurately by employing Kinects on the front and the sides. Especially it is designed as an extensible and modular method which enables to support various additional postures in the future. This system is configured as multiple clients and the Unity3D server. The client processes Kinect skeleton data and send to the server. The server performs the multiple-Kinect calibration process and then applies the pose estimation algorithm based on the Kinect-based posture recognition model using feature extractions and the weighted averaging of feature values for different Kinects. This paper presents the design and implementation of the human exercise pose estimation system using multiple Kinects and also describes how to build and execute an interactive Unity3D exergame.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.75-84
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• 2003

Current techniques for road-traffic monitoring rely on sensors which have limited capabilities, are costly and disruptive to install. The use of video cameras coupled with computer vision techniques offers an attractive alternative to current sensors. Video based traffic monitoring systems are now being considered key points of advanced traffic management systems. In this paper, we propose the new method which extract the traffic information using video camera. The proposed method uses an adaptive updating scheme for background in order to reduce the false alarm rate due to various noises in images. also, the proposed extraction method of traffic information calculates the traffic volume ratio of vehicles passing through predefined detection area, which is defined by the length of profile occupied by cars over that of overall detection area. Then the ratio is used to define 8 different states of traffic and to interpret the state of vehicle flows. The proposed method is verified by an experiment using CCTV traffic data from urban area.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.7
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• pp.703-714
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• 2010

This paper describes the design optimization of a rotating rectangular channel with staggered arrays of pin-fins by Kriging metamodeling technique. Two non-dimensional variables, the ratio of the height to the diameter of the pin-fins and the ratio of the spacing between the pin-fins to the diameter of the pin-fins are chosen as the design variables. The objective function that is a linear combination of heat transfer and friction loss related terms with a weighting factor is selected for the optimization. To construct the Kriging model, objective function values at 20 training points generated by Latin hypercube sampling are evaluated by a three-dimensional Reynolds-averaged Navier-Stokes (RANS) analysis method with the SST turbulence model. The Kriging model predicts the objective function value that agrees well with the value calculated by the RANS analysis at the optimum point. The objective function is reduced by 11% by the optimization of the channel.

• The Journal of the Acoustical Society of Korea
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• v.19 no.8
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• pp.68-77
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• 2000

Line special frequency (LSF) parameters have been widely used in low bit-rate speech coding due to their efficiency for representing the short-time speech spectrum. In this paper, a new distance measure based on the masking properties of human ear is proposed for quantizing LSF parameters whereas most conventional quantization methods are based on the weighted Euclidean distance measure. The proposed method derives the perceptual distance measure from the definition of noise-to-mask ratio (NMR) which has high correspondence with the actual distortion received in the human ear and uses it for quantizing LSF parameters. In addition, we propose an adaptive bit allocation scheme, which allocates minimal bits to LSF parameters maintaining the perceptual transparency of given speech frame for reducing the average bit-rates. For the performance evaluation, we has shown the ratio of perceptually transparent frames and the corresponding average bit-rates for the conventional and proposed methods. By jointly combining the proposed distance measure and adaptive bit allocation scheme, the proposed system requires only 770 bps for obtaining 95.5% perceptually transparent frames, while the conventional systems produce 89.9% at even 1800 bps.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.162-170
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• 2013

In recent years, the interests and needs of the Pedestrian Protection System (PPS), which is mounted on the vehicle for the purpose of traffic safety improvement is increasing. In this paper, we propose a pedestrian candidate window extraction and unit cell histogram based HOG descriptor calculation methods. At pedestrian detection candidate windows extraction stage, the bright ratio of pedestrian and its circumference region, vertical edge projection, edge factor, and PCA reconstruction image are used. Dalal's HOG requires pixel based histogram calculation by Gaussian weights and trilinear interpolation on overlapping blocks, But our method performs Gaussian down-weight and computes histogram on a per-cell basis, and then the histogram is combined with the adjacent cell, so our method can be calculated faster than Dalal's method. Our PCA reconstruction error based pedestrian detection candidate window extraction method efficiently classifies background based on the difference between pedestrian's head and shoulder area. The proposed method improves detection speed compared to the conventional HOG just using image without any prior information from camera calibration or depth map obtained from stereo cameras.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.11-21
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• 2011

An embedded sensor is significantly influenced by its spatial environment, such as barriers or distance, through low power and signal strength. Due to these causes, noise data frequently occur in an embedded sensor. Because the information acquired from the embedded sensor exists in a time series, it is hard to detect an error which continuously takes place in the time series information on a realtime basis. In this paper, we proposes an error detection method based on time-series prediction that detects error signals of embedded sensors in real time in consideration of the physical characteristics of embedded devices. The error detection method based on time-series prediction proposed in this paper determines errors in generated embedded device signals using a stable distance function. When detecting errors by monitoring signals from an embedded device, the stable distance function can detect error signals effectively by applying error weight to the latest signals. When detecting errors by monitoring signals from an embedded device, the stable distance function can detect error signals effectively by applying error weight to the latest signals.

• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.129-139
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• 2010

This study proposes a model for measuring the connectivity of nodes in road networks. The connectivity index between two nodes is characterized by the number of routes, degree of circuitousness, design speed, and route capacity between the nodes. The connectivity index of a node is then defined as the weighted average of the connectivity indexes between the node and other nodes under consideration. The weighting factor between two nodes is determined by the travel demand and distance between them. The application of the model to a toy network shows that it reasonably well quantifies the level of connectivity of nodes in the network. If flow of rail networks can be measured in the same scale as that of road networks and the capacity of rail links can be estimated, the model proposed in this paper could be applied to intermodal transportation networks as well.