• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.189-199
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• 2019

The purpose of this study is to derive spatial area(preventive zone) where the movement of livestock vehicles occurs frequently. For this purpose, this study used 6 periods facility entrance data provided by KAHIS. This data was converted into vehicle movement data between livestock facilities and aggregated into administrative district units. The R-mode factor analysis was performed on the constructed OD data, and the region extracted by the same factor was judged as one region. The results of the analysis are summarized as follows. First, the factor analysis of 6 periods data showed 16 ~ 18 factors, and the derived factors explained 63 ~ 68% of the total variance. Second, based on the factors that were derived, Jeonam coastal area, Jeonnam area, Jeonbuk area, Chungnam coastal area, Gyeongnam area, northern Gyeongbuk area, Yeongnam costal area were found to be stable, with little change over time. On the other hand, Chungbuk area, Gangwon area, Seoul metropolitan area are relatively volatile areas. Third, 13 areas were derived by combining data from six periods.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.97-110
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• 2021

This study estimated the delay factor, which is the ratio of travel time at the speed limit and travel time at the actual speed using real-time traffic information in Seoul. The actual travel speed on the road was lower than the maximum speed of the road and the travel speed was the slowest during the rush hour. As a result of accessibility analysis based on travel speed during the rush hour, the travel time at the actual speed was 37.49 minutes on average. However, the travel time at the speed limit was 15.70 minutes on average. This result indicated that the travel time at the actual speed is 2.4 times longer than that at the speed limit. In addition, this study proposedly defined the delay factor as the ratio of accessibility by the speed limit and accessibility to actual travel speed. As a result of delay factor analysis, the delay factor of Seoul was 2.44. The results by the administrative district showed that the delay factor in the north part areas of the Han River is higher than her south part areas. Analysis results after applying the relationship between road density and traffic volume showed that as the traffic volume with road density increased, the delay factor decreased. These results indicated that it could not be said that heavy traffic caused longer travel time. Therefore, follow-up research is needed based on more detailed information such as road system shape, road width, and signal system for finding the exact cause of increased travel time.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.1-7
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• 2023

An artificial intelligence (AI) method based on image deep learning is proposed to predict the entire displacement shape of a structure using the feature of partial displacements. The performance of the method was investigated through a structural test of a steel frame. An image-to-image regression (I2IR) training method was developed based on the U-Net layer for image recognition. In the I2IR method, the U-Net is modified to generate images of entire displacement shapes when images of partial displacement shapes of structures are input to the AI network. Furthermore, the training of displacements combined with the location feature was developed so that nodal displacement values with corresponding nodal coordinates could be used in AI training. The proposed training methods can consider correlations between nodal displacements in 3D space, and the accuracy of displacement predictions is improved compared with artificial neural network training methods. Displacements of the steel frame were predicted during the structural tests using the proposed methods and compared with 3D scanning data of displacement shapes. The results show that the proposed AI prediction properly follows the measured displacements using 3D scanning.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.183-192
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• 2023

The remotely sensed data, such as satellite imagery and aerial photos, can be used to extract and detect some objects in the image through image interpretation and processing techniques. Significantly, the possibility for utilizing digital map updating and land monitoring has been increased through automatic object detection since spatial resolution of remotely sensed data has improved and technologies about deep learning have been developed. In this paper, we tried to extract plastic greenhouses into aerial orthophotos by using fully convolutional densely connected convolutional network (FC-DenseNet), one of the representative deep learning models for semantic segmentation. Then, a quantitative analysis of extraction results had performed. Using the farm map of the Ministry of Agriculture, Food and Rural Affairsin Korea, training data was generated by labeling plastic greenhouses into Damyang and Miryang areas. And then, FC-DenseNet was trained through a training dataset. To apply the deep learning model in the remotely sensed imagery, instance norm, which can maintain the spectral characteristics of bands, was used as normalization. In addition, optimal weights for each band were determined by adding attention modules in the deep learning model. In the experiments, it was found that a deep learning model can extract plastic greenhouses. These results can be applied to digital map updating of Farm-map and landcover maps.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.61-67
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• 2006

Various methods have been applied for the research to model the relationship between rainfall-runoff, which shows a strong nonlinearity. In particular, most researches to model the relationship between rainfall-runoff using artificial neural networks have used back propagation algorithm (BPA), Levenberg Marquardt (LV) and radial basis function (RBF). and They have been proved to be superior in representing the relationship between input and output showing strong nonlinearity and to be highly adaptable to rapid or significant changes in data. The theory of artificial neural networks is utilized not only for prediction but also for classifying the patterns of data and analyzing the characteristics of the patterns. Thus, the present study applied self?organizing map (SOM) based on Kohonen's network theory in order to classify the patterns of rainfall-runoff process and analyze the patterns. The results from the method proposed in the present study revealed that the method could classify the patterns of rainfall in consideration of irregular changes of temporal and spatial distribution of rainfall. In addition, according to the results from the analysis the patterns between rainfall-runoff, seven patterns of rainfall-runoff relationship with strong nonlinearity were identified by SOM.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.1
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• pp.45-51
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• 2003

Stereo bird's-eyes-view was prepared for 3-dimensional view of various forms of Jecheon city, and 3-dimensional simulation was applied to it so as to show it in moving pictures in spatial. In manufacturing stereo bird's-eyes-view, perspective technology was used in image-making technology, and the basic material images are prepared as fellows: used EOC Images from Arirang-1 satellite, created DEM whose error was optionally geometric corrected after drawn from the contour line of the map on a scale of l/5,000 manufactured by national geography institute as a national standard map, and classified road lines which were manufactured as a road layer vector file of a map on a scale of l/l,000 and then overlay it over the three dimensional image of target area. Especially for the connectivity with address system to be used in new address, an arterial road map on a scale of l/l,000 that had been manufactured to grant new address was used in maximum in road network structure data of city area in this study.

• The Korean Journal of Rheology
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• v.11 no.2
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• pp.159-167
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• 1999

Sandwich injection molding is one of the remarkable polymer processes recently developed from conventional injection molding. But it is almost impossible to do theoretical investigation that we've researched it through numerical simulation. In this paper, numerical simulation on the study of sandwich injection molding is based on Finite Element Method and FAN/Control Volume method. In addition to conventional filling parameter that can confirm skin polymer melt front, new filling parameters have been introduced to confirm core polymer melt front advancement. These filling parameters are defined in each layer which is divided to solve temperature field along the thickness direction. One can notice different filling patterns resulted from the variation of material properties such as viscosities and power-law indexes, and processing conditions such as switch-over times and wall temperatures. It gives us a better understanding of the sandwich injection molding process. And we can recognize that it's the core polymer spatial distribution after the completion of filling that is the most important key point to use this process for industrial molding process.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2797-2808
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• 1998

Multimedia scenario database system is a read-only multimedia-on-demand system which transfers scenarios representing the display ordering of multimedia objects. A scenario is a graph of multimedia objects and it contains spatial, temporal and contextual information of multimedia data. By structuring multimedia objects as a scenario, it is possible to enforce their display order based on their context. Furthermore, it can provide multiple display paths as well as the sharing of objects between different scenarios. As a result, the multimedia scenario database system can perform the pre-scheduling of multimedia objects, which makes it possible to reorder the transmission order of objects in a scenario. Consequently, the overall system resource such as data buffer and network bandwidth can be highly utilized. In this paper, we discuss the requirements of structuring a scenario to design a scenario database that stores and manages multimedia scenario. Furthermore, we devise and analyze several scheduling policies based on the reordering mechanism for the objects in a scenario.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2480-2487
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• 2011

As sensor technology grows up in fields such as environmental hazards detecting system, ubiquitous sensor network, intelligent robot, the sensing and detecting system for sensor is increasing. The sensor data is measured by change of chemical and physical status. Because of decrepit sensor or various sensing environment, it is problem that sensor data is inaccurate result. So the reliability of sensor data is essential. In this paper, we proposes a reliable sensor signal processing platform for various sensor. To improve reliability, we use same sensors in multiple array structure. As sensor data is corrected by spatial and temporal relation signal processing algorithm for measured sensor data, reliability of sensor data can be improved. The exclusive protocol between platform components is designed in order to verify sensor data and sensor state in various environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1A
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• pp.8-18
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• 2011

Visible light communication (VLC) using optical sources which can be simultaneously utilized for illumination and communication is currently an attractive option for wireless personal area network. Improving the data rate in optical wireless communication system is challenging due to the limited bandwidth of the optical sources. In this paper, we design the singular value decomposition (SVD)-based multiplexing multi-input multi-output (MIMO) system to support two data streams in optical wireless channels. In order to improve the spectral efficiency, the rate adaptation using multi-level pulse amplitude modulation (PAM) is applied according to the channel condition and we propose the method to allocate the optical power, the offset and the size of modulation scheme theoretically under the constraints of the nonnegativity of the modulated signals, the aggregate optical power and the bit error rate (BER) requirement. The simulation results show that the proposed allocation method gives the better performance than the method to allocate the optical power equally for each data stream.