• Journal of the Korea Society of Computer and Information
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• v.6 no.3
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• pp.78-83
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• 2001

In this paper, we are considered Nakagami-m fading, which can model variable multipath mobile radio communication channel, in DS-CDMA system. System modeling using nakagami -m fading is suited for urban mobile communication channel with multipath. We used adaptive serial search PN code acquisition scheme and derived the detection probability($P_D$) and false alarm probability($P_FA$) which have influence on code acquisition time, over Nakagami-m fading. Detection probability($P_D$) and false alarm probability($P_FA$) are detection variable to decide PN code acquisition time and should use to calculate mean and variance. of acquisition time. From computer simulation, we analyzed mean and variance about PN code acquisition of fading channel. Then we can apply it to the H/W design of mobile communication.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.2
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• pp.9-13
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• 2011

The Performance-based fire protection design required to construct super high-rise building is the active measure for the evaluation of fire risks and the establishment of fire protection systems on the basis of engineering analysis, which is more efficient and proper than existing prescriptive-based design. This study applied time-line analysis of RSET is required safe egress time and ASET is available safe egress time with the fire and evacuation simulation to analyze. The result of this study showed the sprinkler system increased ASET and fire detection and alarm system reduced RSET efficiently. Reduced evacuation time influences to secure the life safety. Also it is essential to maintain the fire suppression system and fire detection & alarm system properly. Database of fire movement and evacuation action program are useful for the performance-based design.

• Land and Housing Review
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• v.12 no.2
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• pp.99-108
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• 2021

With increasing interest in living in hanoks, there's a growing need for more quantitative data on the thermal comfort performance of modern hanoks. With that in mind, this research project studied a modern hanok located in Jamjeong-Haetsal Village in Hwasun, Jeollanam Province as a case study to evaluate the Predicted Mean Vote (PMV) of modernized hanoks. Based on environmental data collected at the hanok and computer simulation both Life-Cycle PMV (L.C.PMV) and Normal PMV (N.PMV) were calculated for the hanok. Study results showed that during the summer and winter seasons the PMV and heat index at major heat and major cold weather points significantly deviated from the comfort zone. The rate of change in PMV was also greater in the winter than in the summer. The study found that the modern hanok lacks proper thermal insulation for maintaining thermal comfort.

• Wind and Structures
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• v.28 no.2
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• pp.129-140
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• 2019

Accurately simulating the wind field of large-scale region, for instant urban areas, the locations of large span bridges, wind farms and so on, is very difficult, due to the complicated terrains or land surfaces. Currently, the regional wind field can be simulated through the combination of observation data and numerical model using observation-nudging in the Weather Research and Forecasting model (WRF). However, the main drawback of original observation-nudging method in WRF is the effects of observation on the surrounding field is fully mathematical express in terms of temporal and spatial, and it ignores the effects of terrain, wind direction and atmospheric circulation, while these are physically unreasonable for the turbulence. For these reasons, a spatial correlation-based observation-nudging method, which can take account the influence of complicated terrain, is proposed in the paper. The validation and comparation results show that proposed method can obtain more reasonable and accurate result than original observation-nudging method. Finally, the discussion of wind field along bridge span obtained from the simulation with spatial correlation-based observation-nudging method was carried out.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.3
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• pp.179-187
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• 2021

To estimate the location of the train, we consider an integrated navigation system that combines Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS). This system provides accurate navigation results in open sky by combining only the advantages of both systems. However, since measurement update cannot be performed in GNSS signal blocked areas such as tunnels, mountain, and urban areas, pure INS is used. The error of navigation information increases in this area. In order to reduce this problem, the train's Non-Holonomic Constraints (NHC) information can be used. Therefore, we deal with the INS/GNSS/NHC integrated navigation system in this paper. However, in the process of installing the navigation system on the train, a Mounting Misalignment Error of the IMU (MMEI) inevitably occurs. In this case, if the NHC is used without correcting the error, the navigation error becomes even larger. To solve this problem, a method of easily estimating the MMEI without an external device is introduced. The navigation filter is designed using the Extended Kalman Filter (EKF) by considering the MMEI. It is assumed that there is no vertical misalignment error, so only the horizontal misalignment error is considered. The performance of the integrated navigation system according to the presence or absence of the MMEI and the estimation performance of the MMEI according to the method of using NHC information are analyzed based on simulation. As a result, it is confirmed that the MMEI is accurately estimated by using the NHC information together with the GNSS information, and the performance and reliability of the integrated navigation system are improved.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.77-87
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• 2021

Environment is an important factor in city life. Environmental elements are a subject that must be discussed in the smart city plan, but there is still a lack of information and data sharing in the urban environment, so improvements are needed. As part of the intelligent of Nanjing, this research has made in-depth investigation into the construction and service demand of environmental information, and has carried out the research on the design and construction of intelligent information platform that conforms to Nanjing intelligent city planning, improves environmental quality and provides environmental information service. The visualization of information is also studied. The result is an important module in the construction of intelligent city in Nanjing.

• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.670-679
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• 2011

Chlorophyll-a is a major water quality indicator for an algal bloom in streams and lakes. The purpose of the study is to estimate chlorophyll-a concentration in tributaries of the Seonakdonggang by an artificial neural network (ANN). As the tributaries are ungauged streams, a watershed runoff and quality model was used to simulate water quality parameters. The tributary watersheds include urban area and thus Storm Water Management Model (SWMM) was used to simulate TN, TP, BOD, COD, and SS. SWMM, however, can not simulate chlorophyll-a. The chlorophyll-a series data from the tributaries were estimated by the ANN and the simulation results of water quality parameters using SWMM. An assumption used is as follows: the relation between water quality parameters and chlorophyll-a in the tributaries of the Seonakdonggang would be similar to that in the mainstream of the Seonakdonggang. On the assumption, the measurement data of water quality and chlorophyll-a in the mainstream of the Seonakdonggang were used as the learning data of the ANN. Through the sensitivity analysis, the learning data combination of water quality parameters was determined. Finally, chlorophyll-a series were estimated for tributaries of the Seonakdonggang by the ANN and TN, TP, BOD, COD, and temperature data from those streams. The relative errors between the estimated and measured chlorophyll-a were approximately 40 ~ 50%. Though the errors are somewhat large, the estimation process for chlorophyll-a may be useful in ungauged streams.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.16-41
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• 2020

Geospatial input setting to represent the reality of spatial distribution or quantitative property within model has become a major interest in earth system simulation. Many studies showed the variation of grid resolution could lead to drastic changes of spatial model results because of insufficient surface property estimations. Hence, in this paper, the authors proposed Monte Carlo Integration (MCI) to apply spatial probability (SP) in a spatial-sampling framework using a three-dimensional point cloud (3DPC) to keep the optimized spatial distribution and area/volume property of buildings in urban area. Three different decision rule based building identification results were compared : SP threshold, cell size, and 3DPC density. Results shows the identified building area property tend to increase according to the spatial sampling grid area enlargement. Hence, areal building property manipulation in the sampling frameworks by using decision rules is strongly recommended to increase reliability of geospatial modeling and analysis results. Proposed method will support the modeling needs to keep quantitative building properties in both finer and coarser grids.

• Atmosphere
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• v.30 no.4
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• pp.361-376
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• 2020

This study evaluates multiple Regional Climate Models (RCMs) in simulating temperature and precipitation over the Far East Asia (FEA) and estimates the portions of the total uncertainty originating in the RCMs and the driving Global Climate Models (GCMs) using nine present-day (1981~2000) climate data obtained from combinations of three GCMs and three RCMs in the CORDEX-EA phase2. Downscaling using the RCMs generally improves the present temperature and precipitation simulated in the GCMs. The mean temperature climate in the RCM simulations is similar to that in the GCMs; however, RCMs yield notably better spatial variability than the GCMs. In particular, the RCMs generally yield positive added values to the variability of the summer temperature and the winter precipitation. Evaluating the uncertainties by the GCMs (VARGCM) and the RCMs (VARRCM) on the basis of two-way ANOVA shows that VARRCM is greater than VARGCM in contrast to previous studies which showed VARGCM is larger. In particular, in the winter temperature, the ocean has a very large VARRCM of up to 30%. Precipitation shows that VARRCM is greater than VARGCM in all seasons, but the difference is insignificant. In the following study, we will analyze how the uncertainty of the climate model in the present-day period affects future climate change prospects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.619-627
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• 2021

Recent advance in low cost and light-weight drones has extended their application areas in both military and private sectors. Accordingly surveillance program against unfriendly drones has become an important issue. Drone detection and classification technique has long been emphasized in order to prevent attacks or accidents by commercial drones in urban areas. Most commercial drones have small sizes and low reflection and hence typical sensors that use acoustic, infrared, or radar signals exhibit limited performances. Recently, artificial intelligence algorithm has been actively exploited to enhance radar image identification performance. In this paper, we adopt machined learning algorithm for high resolution radar imaging in drone detection and classification applications. For this purpose, simulation is carried out against commercial drone models and compared with experimental data obtained through high resolution radar field test.