• Journal of Korean Society for Atmospheric Environment
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• v.13 no.6
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• pp.463-474
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• 1997

Metallic elements in dustfall have been known as notable air pollutants directly or indirectly influencing human health and wealth. The first aim of this study was to obtain precise spatial distribution patterns of 5 elements (Pb, Zn, K, Cr, and Al) in dustfall around Suwon area. To predict isometric lines of metal fluxes deposited on unsupervised random sites, the study has applied both spatial statistics as a receptor model and a GIS (geographic information system). Total of 31 sampling sites were selected in the study area (roughly 3 by 3 km grid basis) and dustfall samples were then collected monthly basis by the British deposit gauges from Dec., 1995 to Nov., 1996. The metallic elements in the dustfall were then analyzed by an atomic absorption spectrometer (AAS). On the other hand, a base map overlapped by 7 layers was constructed by using the AutoCAD R13 and ARC/INFO 3.4D. Four different spatial interpolation and expolation techniques such as IDW (inverse distance weighted averaging), TIN (triangulated irregular network), polynomial regression, and kriging technique were examined to compare spatial distribution patterns. Each pattern obtained by each technique was substantally different as varing pollutant types, land of use types, and topological conditions, etc. Thus, our study focused intensively on uncertainty analysis based on a concept of the jackknife and the sum of error distance. It was found that a kriging technique was the best applicalbe in this study area.

• Journal of Environmental Health Sciences
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• v.38 no.5
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• pp.369-379
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• 2012

Objectives: Spatial analysis is useful for understanding complicated causal relationships. This paper focuses trends and appling methods for spatial analysis associated with environmental asbestos exposure. Methods: Literature review and reflection of experience of authors were conducted to know academic background of spatial analysis, appling methods on epidemiology and asbestos exposure. Results: Spatial analysis based on spatial autocorrelation provides a variety of methods through which to conduct mapping, cluster analysis, diffusion, interpolation, and identification. Cause of disease occurrence can be investigated through spatial analysis. Appropriate methods can be applied according to contagiousness and continuity. Spatial analysis for asbestos exposure source is needed to study asbestos related diseases. Although a great amount of research has used spatial analysis to study exposure assessment and distribution of disease occurrence, these studies tend to focus on the construction of a thematic map without different forms of analysis. Recently, spatial analysis has been advanced by merging with web tools, mobile computing, statistical packages, social network analysis, and big data. Conclusions: Because the trend in spatial analysis has evolved from simple marking into a variety of forms of analyses, environmental researchers including asbestos exposure study are required to be aware of recent trends.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.48-54
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• 2012

The quality of real-time voice communication over Internet Protocol networks based on telematics is affected by network impairments such as delays, jitters, and packet loss. To resolve this issue, this paper proposes a receiver-based enhancing method of VoIP speech quality. The proposed method enables users to deliver high-quality voice using playout control and signal reconstruction, which consists of concealment of lost packets, adaptive playout-buffer scheduling using active jitter estimation, and smooth interpolation between two signals in a transition region. The proposed algorithm achieves higher Perceptual Evaluation of Speech Quality (PESQ) values and low buffering delay than the reference algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.65-71
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• 2011

Face warping techniques have been used for correcting image distortion as well as for creative purposes(e.g., morphing). Smartphone can capture an image from camera and transfer it through network. Thus, warping software which is implemented on the smartphone may be widely used in the fields of game and plastic surgery. This paper describes the design of face warping software using transformation with multiple pairs of lines and bilinear interpolation, and then shows the implementation results on the smartphone. Through many people review, this software showed real-time responsiveness and good transformation quality.

• Journal of Biosystems Engineering
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• v.29 no.1
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• pp.65-70
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• 2004

This study was carried out to verify and predict the soil informations such as the contents of organic matter(OM) and Mg and pH of the soil. The predictability of spacial variation in the paddy field was examined by analyzing the various soil information. The prediction models for the OM pH, and Mg, were developed using inverse distance weighted (IDW), triangulated irregular network(TIN) and Kriging model. The determination of coefficients of linear and spherical Kriging models were 0.756 and 0.578, respectively, and were very low in comparison with other soil information. For IDW and TIN model, the determination of coefficients were 1.000 and hence the performance of the models was found to be excellent. The developed models were validated using unknown soil sample obtained In 2000 and 2001. From the analysis of relationship between the measured pH and predicted 0.9353. For prediction of Mg, the determination of coefficient is more than 0.8. Since the determination of coefficients of developed models for OM were relatively low, it may be difficult to predict the content of OM using the developed models. For further study, the additional works to enhance the performance of the prediction models for soil information are required.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.3
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• pp.74-81
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• 2019

Herein, we performed a comparative study on approximate multi-objective design optimization, to realize a structural design to improve the weight and vibration performances of the knuckle - a car suspension component - considering various load conditions and vibration characteristics. In the approximate multi-objective optimization process, a regression meta-model was generated using the response surfaces method (RSM), while Kriging and back-propagation neural network (BPN) methods were applied for interpolation meta-modeling. The Pareto solutions, multi-objective optimal solutions, were derived using the non-dominated sorting genetic algorithm (NSGA-II). In terms of the knuckle design considered in this study, the characteristics and influence of the meta-model on multi-objective optimization were reviewed through a comparison of the approximate optimization results with the meta-models and the actual optimization.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.1
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• pp.55-66
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• 2021

In this paper, we propose a signal propagation modeling technique for generating a positioning fingerprint DB based on Long Term Evolution (LTE) signals. When a DB is created based on the location-based signal information collected in an urban area, gaps in the DB due to uncollected areas occur. The spatial interpolation method for filling the gaps has limitations. In addition, the existing gap filling technique through signal propagation modeling does not reflect the signal attenuation characteristics according to directions occurring in urban areas by considering only the signal attenuation characteristics according to distance. To solve this problem, this paper proposes a Deep Neural Network (DNN)-based signal propagation functionalization technique that considers distance and direction together. To verify the performance of this technique, an experiment was conducted in Seocho-gu, Seoul. Based on the acquired signals, signal propagation characteristics were modeled for each method, and Root Mean Squared Errors (RMSE) was calculated using the verification data to perform comparative analysis. As a result, it was shown that the proposed technique is improved by about 4.284 dBm compared to the existing signal propagation model. Through this, it can be confirmed that the DNN-based signal propagation model proposed in this paper is excellent in performance, and it is expected that the positioning performance will be improved based on the fingerprint DB generated through it.

• Wind and Structures
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• v.38 no.2
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• pp.147-160
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• 2024

The aerodynamic force is a significant component that influences the stability and safety of structures. It has unstable properties and depends on computer precision, making its long-term prediction challenging. Accurately estimating the aerodynamic traits of structures is critical for structural design and vibration control. This paper establishes an unsteady aerodynamic time series prediction model using Long Short-Term Memory (LSTM) network. The unsteady aerodynamic force under varied Reynolds number and angles of attack is predicted by the LSTM model. The input of the model is the aerodynamic coefficients of the 1 to n sample points and output is the aerodynamic coefficients of the n+1 sample point. The model is predicted by interpolation and extrapolation utilizing Unsteady Reynolds-average Navier-Stokes (URANS) simulation data of flow around a circular cylinder, square cylinder and airfoil. The results illustrate that the trajectories of the LSTM prediction results and URANS outcomes are largely consistent with time. The mean relative error between the forecast results and the original results is less than 6%. Therefore, our technique has a prospective application in unsteady aerodynamic force prediction of structures and can give technical assistance for engineering applications.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.64-74
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• 2019

Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.

• Spatial Information Research
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• v.7 no.1
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• pp.1-12
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• 1999

The DTM(Digital Terrain Model) in GIS(Geographical Information System) shows the elevation from interpolation using data points surveyed. In panoramic flat landform, pixel size, resolution of source data may not be the problem in using DTM However, in mountainous landform like Korea, appropriate resolution accuracy of source data are important factors to represent the topography concerned. In this study, the difference in contour interval of source data, the resolution after interpolation, and different data structures were compared to figure out the accuracy of slope calculation using DTM from the topographic maps of Togyusan National Park Two types of GIS softwares, Idrisi(grid) ver. 2.0 using the altitude matrices and ArcView(TIN) ver. 3.0a using TIN were used for this purpose. After the analysis the conclusions are as follows: 1) The coarser resolution, the more smoothing effect inrepresenting the topography. 2) The coarser resolution the more difference between the grid-based Idrisi and the TIN-based ArcView. 3) Based on the comparison analysis of error for 30 points from clustering, there is not much difference among 10, 20, 30 m resolution in TIM-based Airview ranging from 4.9 to 6.2n However, the coarser resolution the more error for elevation and slope in the grid-based Idrisi. ranging from 6.3 to 10.9m. 4) Both Idrisi and ArcView could net consider breaklines of lanform like hilltops, valley bottoms.