• Korean Journal of Construction Engineering and Management
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• v.19 no.6
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• pp.46-54
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• 2018

In the 21st century, the Earth has continued its efforts to reduce carbon emissions to overcome the crisis caused by climate change. The construction industry, which is a representative industry that produces large amounts of the environmental load during construction, should actively reduce the amount of the environmental load. From the planning stage of the construction facility, it is necessary to consider the environmental load such as route selection and structure type selection to reduce the environmental load. However, the environmental load can be estimated based on the input resource amount. However, in the planning stage, it is difficult to accurately calculate the environmental load due to lack of information on the construction amount. The purpose of this study is to select the environmental load factors for IPC girder bridges to be used in the environmental load estimation model in the planning stage. Specific information related to the environmental load was selected from a list of information available in the planning stage, reflecting the Life Cycle Assessment(LCA), correlation, principal components analysis and expert opinion. The list of selected planning stage information is 10 such as span length and bridge extension, and it is expected to be used as a basic data for the future development of environmental load estimation model.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.531-540
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• 2007

In this research, we proposed a two-phase hybrid stock price forecasting model with cointegration tests and artificial neural networks. Using not only the related stocks to the target stock but also the past information as input features in neural networks, the new model showed an improved performance in forecasting than that of the usual neural networks. Firstly in order to extract stocks which have long run relationships with the target stock, we made use of Johansen's cointegration test. In stock market, some stocks are apt to vary similarly and these phenomenon can be very informative to forecast the target stock. Johansen's cointegration test provides whether variables are related and whether the relationship is statistically significant. Secondly, we learned the model which includes lagged variables of the target and related stocks in addition to other characteristics of them. Although former research usually did not incorporate those variables, it is well known that most economic time series data are depend on its past value. Also, it is common in econometric literatures to consider lagged values as dependent variables. We implemented a price direction forecasting system for KOSPI index to examine the performance of the proposed model. As the result, our model had 11.29% higher forecasting accuracy on average than the model learned without cointegration test and also showed 10.59% higher on average than the model which randomly selected stocks to make the size of the feature set same as that of the proposed model.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.653-662
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• 2016

This paper describes a test case generation algorithm for Simulink/Stateflow models based on the Rapidly exploring Random Tree (RRT) algorithm that has been successfully applied to path finding. An important factor influencing the performance of the RRT algorithm is the metric used for calculating the distance between the nodes in the RRT space. Since a test case for a Simulink/Stateflow (SL/SF) model is an input sequence to check a specific condition (called a test target in this paper) at a specific status of the model, it is necessary to drive the model to the status before checking the condition. A status maps to a node of the RRT. It is usually necessary to check various conditions at a specific status. For example, when the specific status represents an SL/SF model state from which multiple transitions are made, we must check multiple conditions to measure the transition coverage. We propose a unique distance calculation metric, based on the observation that the test targets are gathered around some specific status such as an SL/SF state, named key nodes in this paper. The proposed metric increases the probability that an RRT is extended from key nodes by imposing penalties to non-key nodes. A test case generation algorithm utilizing the proposed metric is proposed. Three models of Electrical Control Units (ECUs) embedded in a commercial vehicle are used for the performance evaluation. The performances are evaluated in terms of penalties and compared with those of the algorithm using a typical RRT algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.315-320
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• 2017

Estimating the correct pose of augmented objects on the real camera view efficiently is one of the most important questions in image tracking area. In computer vision, Homography is used for camera pose estimation in augmented reality system with markerless. To estimating Homography, several algorithm like SURF features which extracted from images are used. Based on extracted features, Homography is estimated. For this purpose, RANSAC algorithm is well used to estimate homography and DCS-RANSAC algorithm is researched which apply constraints dynamically based on Constraint Satisfaction Problem to improve performance. In DCS-RANSAC, however, the dataset is based on pattern of feature distribution of images manually, so this algorithm cannot classify the input image, pattern of feature distribution is not recognized in DCS-RANSAC algorithm, which lead to reduce it's performance. To improve this problem, we suggest the KCS-RANSAC algorithm using K-means clustering in CS-RANSAC to cluster the images automatically based on pattern of feature distribution and apply constraints to each image groups. The suggested algorithm cluster the images automatically and apply the constraints to each clustered image groups. The experiment result shows that our KCS-RANSAC algorithm outperformed the DCS-RANSAC algorithm in terms of speed, accuracy, and inlier rate.

• Tunnel and Underground Space
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• v.28 no.4
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• pp.325-342
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• 2018

The ${\bigcirc}{\bigcirc}$ mines have been tried in various ways to perform secondary and tertiary mining in fragile rock properties. For such mining, the panels should be maintained while the mining compartments are divided and paneled. In this study, the mining gate between the panels was maintained by a steel beam and the panel life time was probabilistic evaluated. We used Taylor's formula for panel life time and modified the Pert distribution conceptually. The main input data were determined by the Pert distribution, and Monte Carlo simulation was performed to evaluate the panel life time for the probability distribution. As a result, it was analyzed that the panels could be stand-up time from a minimum of 6.5 days to a maximum of 20.6 days when the panel width was 18 to 25 m. At the confidence level of 90%, the panel life time was analyzed as 8.2-15.6 days. The short panel life time is not possible with the panel mining. Therefore, it was planned to construct a steel beam for panel maintenance. As result, it was analyzed that steel beam for panel maintenance with mining plan of less than 3 years according to mine could maintain panel within 90% confidence level.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.415-421
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• 2013

A new approach to retrieve the single-scattering albedo (SSA) of Asian dust plume, mixed with pollution particles, using multi-wavelength Raman lidar system was suggested in this study. Asian dust plume was separated as dust and non-dust particle (i.e. spherical particle) by the particle depolarization ratio at 532 nm. The vertical profiles of optical properties (the particle extinction coefficient at 355 and 532 nm and backscatter coefficient at 355, 532 and 1064 nm) for non-dust particle were used as input parameter for the inversion algorithm. The inversion algorithm provides the vertical distribution of microphysical properties of non-dust particle only so that the estimation of the SSA for the Asian dust in mixing state was suggested in this study. In order to estimate the SSA for the mixed Asian dust, we combined the SSA of non-dust particles retrieved by the inversion algorithms with assumed the SSA of 0.96 at 532 nm for dust. The retrieved SSA of Asian dust plume by lidar data was compared with the Aerosol Robotics Network (AERONET) retrieved values and showed good agreement.

• Korean Journal of Applied Biomechanics
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• v.16 no.3
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• pp.137-148
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• 2006

The purpose of this study was to compare muscle activity in the lower extremity during walking wearing jogging and roller shoes. Twelve male middle school students (age: 15.0 yrs, height 173.7 cm, weight 587.7 N) who have no known musculoskeletal disorders were recruited as the subjects. Seven pairs of surface electrodes (QEMG8, Laxtha Korea, gain = 1,000, input impedance >$1012{\Omega}$, CMMR >100 dB) were attached to the right-hand side of the body to monitor the rectus femoris (RF), vastus medialis (VM), vastus lateralis (VL), biceps femoris (BF), tibialis anterior (TA), and medial (GM) and lateral gastrocnemius (GL) while subjects walked wearing roller and jogging shoes in random order at a speed of 1.1 m/s. An event sync unit with a bright LED light was used to synchronize the video and EMG recordings. EMG data were filtered using a 10 Hz to 350 Hz Butterworth band-passdigital filter and further normalized to the respective maximum voluntary isometric contraction EMG levels. For each trial being analyzed, five critical instants and four phases were identified from the recording. Averaged IEMG and peak IEMG were determined for each trial. For each dependent variable, paired t-test was performed to test if significant difference existed between shoe conditions (p<.05). The VM, TA, BF, and GM activities during the initial double limb stance and the initial single limb stance reduced significantly when going from jogging shoe to roller shoe condition. The decrease in EMG levels in those muscles indicated that the subjects locked the ankle and knee joints in an awkward fashion to compensate for the imbalance. Muscle activity in the GM for the roller shoe condition was significantly greater than the corresponding value for the jogging shoe condition during the terminal double limb stance and the terminal single limb stance. Because the subjects tried to keep their upper body weight in front of the hip to prevent falling backward, the GM activity for the roller shoe condition increased. It seems that there are differences in muscle activity between roller shoe and jogging shoe conditions. The differences in EMG pattern may be caused primarily by the altered position of ankle, knee, and center of mass throughout the walking cycle. Future studies should examine joint kinematics during walking with roller shoes.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.255-268
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• 2012

Nonpoint source pollution has become a concern for water quality in the Han River system, especially during the high runoff events during the monsoon season. The patterns in nonpoint source runoff the relationships with land use, rainfall intensity, and stream nutrients concentrations were surveyed in 19 streams in the Han River watershed. The results show that the magnitude of NPS inputs of nutrients and sediment in the Han River watershed are of a serious concern. In the South Han River watershed, event mean concentrations (EMC) for biochemical oxygen demand (BOD), suspended sediment (SS), dissolved organic carbon (DOC), dissolved total phosphorus (DTP), total nitrogen (TN) Nitrate ($NO_3$-N) and total phosphorus (TP) were $1.94mg{\cdot}L^{-1},\;251mg{\cdot}L^{-1},\;2.75mg{\cdot}L^{-1},\;0.076mg{\cdot}L^{-1},\;2.82mg{\cdot}L^{-1},\;2.40mg{\cdot}L^{-1}$ and $0.232mg{\cdot}L^{-1}$, respectively. In the North Han River watershed, EMCs for BOD, SS, DOC, DTP, TN, $NO_3$-N and TP were $1.34mg{\cdot}L^{-1},\;172mg{\cdot}L^{-1},\;2.63mg{\cdot}L^{-1},\;0.032mg{\cdot}L^{-1},\;1.97mg{\cdot}L^{-1},\;1.55mg{\cdot}L^{-1}$ and $0.148mg{\cdot}L^{-1}$, respectively. The specific export coefficients of nutrient and sediments were much higher than those of other reports. Our study also found that the proportion of agricultural field area was significantly correlated with the EMCs for nutrients. Therefore, efforts to reduce NPS loading must focus on agricultural practices in the watershed. The relationships between land use and nutrient and sediment export found in this study can be used to derive estimates of runoff coefficients for agricultural field and as input data for modeling works and to develop total maximum daily load and best management practices in the Han River watershed.

• Journal of Korea Water Resources Association
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• v.43 no.10
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• pp.865-881
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• 2010

To evaluate influence of the future climate change on water environment, it is necessary to use a rainfall-runoff model, or a basin model allowing us to simultaneously simulate water quality factors such as sediment and nutrient material. Thus, SWAT is selected as a watershed-based model and Nakdong river basin is chosen as a target basin for this study. To apply climate change scenarios as input data to SWAT, Australian model (CSIRO: Mk3.0, CSMK) and Canadian models (CCCma: CGCM3-T47, CT47) of GCMs are used. Each GCMs which have A2, B1, and A1B scenarios effectively represent the climate characteristics of the Korean peninsula. For detecting climate change in Nakdong river basin, precipitation and temperature, increasing rate of these were analyzed in each scenarios. By simulation results, flow and increasing rate of these were analyzed at particular points which are important in the object basin. Flow and variation of flow in the scenarios for present and future climate changes were compared and analyzed by years, seasons, divided into mid terms. In most of the points temperature and flow rate are increased, because climate change is expected to have a significant effect on rising water temperature and flow rate of river and lake, further on the basis of this study result should set enhancing up water control project of hydraulic structures caused by increasing outer discharge of the Nakdong River Basin due to climate change.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.386-395
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• 2006

Multi-view video coding technology demands the very high efficient coding technologies, because it has to encode a number of video sequences which are achieved from a number of video cameras. For this purpose, multi-view video coding introduces the inter-view prediction scheme between different views, but it shows a limitation of coding performance enhancement by adopting only new prediction method. Accordingly, we are going to achieve the more coding performance by enhancing dequantizer perfermance. Multi-view video coding is implemented basically based on H.264/AVC and uses the same quantization/de-quantization method as H.264/AVC does. The conventional quantizer and dequantizer is designed with the assumption that input residual signal follows the Laplacian PDF. However, it doesn't follow the fixed PDF type always. This mismatch between assumption and real data causes degradation of coding performance. To solve this problem, we propose the efficient de-quantization method based on quantized coefficients distribution at decoder without extra information. The extensive simulation results show that the proposed algorithm produces maximum $1.5\;dB{\sim}0.6\;dB$ at high bitrate compared with that of conventional method.