• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1163-1170
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• 2010

In this paper, in order to develop a remote progress management system through the Internet, we show a design method to make easy maintenance by developing the system with both the JAVA language and GoF Design Patterns. For the system implementation, we added the RS232C and RS422/RS485 communication modules to PLC(Programmable Logic Controller) in the control box which provide the real time status data of machines. Also we set up the RS232C to Ethernet converter based on wireless environment to communicate the PLC control data. We use JAVA Swing components to implement the multi-tier architecture system supported the GUI of the Applet and Frame at the same time so that the manager grasps the progress of work easily at the remote machines through the Internet. The key objective of the multi-tier architecture is to share resources among clients, this proposed system can help to develop the software to control the remote machine, and also it has the advantage that developer who wants to make a similar software can make easy to add new function reusing the existing codes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.29-38
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• 2010

The airborne LiDAR which was introduced in the early 2000's provides the point data. The new methods for the verification of LiDAR materials with high accuracy which is different from the existing airborne survey are needed. In accordance with the rules of airborne laser survey which were enacted in 2009, the verifications by three methods of Unmeasured Rate and point accuracy, point density have been executed, and Unmeasured Rate is to evaluate the rate for the presence of points within uniform grids except non-reflective areas such as watershed areas. For the calculation of Unmeasured Rate, non-reflective areas should be removed by all means, and in case of normal LiDAR materials, as there are scant points for watershed areas, watershed areas should be divided by additional spatial information. So, in this study, the watershed areas were extracted using domain extension technique from the high resolution CIR images of 0.3m grade. In addition, in order to compare the accuracy of Unmeasured Rate calculated, the comparative analysis of the Unmeasured Rate calculated by digital maps has been done. In conclusion, we found that 1I1e accuracy of Unmeasured Rate extracted by domain extension technique is similar to the value extracted by digitizing technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.592-597
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• 2020

Currently, river survey data is mainly performed by acquiring longitudinal and cross-sectional data of rivers using total stations or the GNSS(Global Navigation Satellite System). There is not much research that addresses the use of LiDAR(Light Detection and Ranging)systems for surveying rivers. This study evaluates the applicability of using LiDAR data for surveying rivers The Ministry of Land, Infrastructure and Transport recently launched a drone-based river fluctuation survey. Pilot survey projects were conducted in major rivers nationwide. Studies related to river surveying were performed using the ground LiDAR(Light Detection And Ranging)system.Accuracy was ensured by extracting the linearity of the object and comparing it with the total station survey performance. Data on trees and other features were extracted to generate three-dimensional geospatial information for the point-cloud data on the ground.Deviations were 0.008~0.048m. and compared with the results of surveying GNSS and the use of drone LiDAR data. Drone LiDAR provided accurate three-dimensional spatial information on the entire target area. It was able to reduce the shaded area caused by the lack of surveying results of the target area. Analyses such as those of area and slope of the target sites are possible. Uses of drones may therefore be anticipated for terrain analyses in the future.

• Korean journal of applied entomology
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• v.42 no.4
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• pp.353-360
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• 2003

Immunodepression can be required for entomopathogenic bacteria to induce their potent pathogenicities to the target insects. Here, we raise a hypothesis that the capacity of a pathogenic bacterium to induce the target insect immunodepression has positive relationship with the degree of pathogenicity. X. nematophilus had 1,200 times as potent as another entomopathogenic bacterium, Staphylococcus gallinarum against the fifth instar larvae of silkworm, Bombyx mori, when they were Injected into the hemocoel. Although both bacteria had significant cytotokic effect on the hemocytes of B. mori, X. nematophilus gave faster and greater cytotoxicity than did S. gallinarum. In cellular immune reactions, B. mori could form 20 hemocyte nodules against the bacterial injection with 5${\times}$10$\^$5/ cells. The number of the hemocyte nodules was significantly depressed when live X. nematophilus was inject-ed, but not in S. gallinarum. Activation of prophenoloxidase (proPO) was depressed in the bacterial injection. The depression of PO activation was significantly greater in X. nematophilus infection than in S. gallinarum injection. Lysozyme activity was induced by the injection of S. gallinarum at 4 h after the treatment, but not induced in X. nematophilus at all the time. These results showed that X. nemato-philus induced greater immunodepression against B. mori and resulted in higher pathogenicity than did S. gallinarum. Therefore, this study suggests that the immunodepression induced by entomopathogenic bacteria has positive relationship with their pathogenicity.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.99-105
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• 2013

In rapidly developing urban areas that include high-rise, large, and complex buildings, indoor and outdoor maps in GIS become a basis for utilizing and sharing information pertaining to various aspects of the real world. Although an indoor mapping has gained much attentions, research efforts are mostly in 2D and 3D modeling of terrain and buildings. Therefore, to facilitate fast and accurate construction of indoor GIS, this paper proposes a semi-automatic method consisting of preprocessing, 2D mapping, and 3D mapping stages. The preprocessing is designed to estimate heights of building interiors and to identify noise data from point clouds. In the 2D mapping, a floor map is extracted with a tracing grid and a refinement method. In the 3D mapping, a 3D wireframe model is created with heights from the preprocessing stage. 3D mesh data converted from noise data is combined with the 3D wireframe model for detail modeling. The proposed method was applied to point clouds depicting a hallway in a building. Experiment results indicate that the proposed method can be utilized to construct 2D and 3D maps for indoor GIS.

• Cartoon and Animation Studies
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• s.43
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• pp.343-362
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• 2016

The purpose of this study is to analyze the 'depth of the film image' and to discuss its aesthetic implications in the Wes Anderson's films. In this study, I have analysed his two recent representative films, (2014) and (2012). As a result, it is found that Wes Anderson created a symmetrical composition with the depth by placing symmetrically things on the Z axis or using one-point perspective. In general, symmetrical composition is a two-dimensional form. The symmetrical composition in these two films, however, has the depth perception. It gives a sense of the fantastic world, not the real world. Thus, it is the unique way of Wes Anderson's expressing the world of the fairy tale on his films. It is also found that he used the camera work, emphasizing the depth of the image. Through these devices, Wes Anderson has created his own sensational mise-en-scene for a storyline like a fairy tale.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.283-295
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• 2021

This paper proposes a method for generating dense depth map using information of color images and depth map generated based on lidar based on self-organizing map. The proposed depth map upsampling method consists of an initial depth prediction step for an area that has not been acquired from LiDAR and an initial depth filtering step. In the initial depth prediction step, stereo matching is performed on two color images to predict an initial depth value. In the depth map filtering step, in order to reduce the error of the predicted initial depth value, a self-organizing map technique is performed on the predicted depth pixel by using the measured depth pixel around the predicted depth pixel. In the process of self-organization map, a weight is determined according to a difference between a distance between a predicted depth pixel and an measured depth pixel and a color value corresponding to each pixel. In this paper, we compared the proposed method with the bilateral filter and k-nearest neighbor widely used as a depth map upsampling method for performance comparison. Compared to the bilateral filter and the k-nearest neighbor, the proposed method reduced by about 6.4% and 8.6% in terms of MAE, and about 10.8% and 14.3% in terms of RMSE.

• Korean Journal of Optics and Photonics
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• v.34 no.4
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• pp.139-150
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• 2023

Despite various light detection and ranging (LiDAR) architectures, it is very difficult to achieve long-range detection and high resolution in both vertical and horizontal directions with a wide field of view (FOV). The scanning architecture is advantageous for high-performance LiDAR that can attain long-range detection and high resolution for vertical and horizontal directions. However, a large-area photodetector (PD), which is disadvantageous for detection speed, is essentially required to secure the wide FOV. Thus we propose a PD based on the static unitary detector (STUD) technique that can operate multiple small-area PDs as a single large-area PD at a high speed. The InP/InGaAs STUD PIN-PD proposed in this paper is fabricated in various types, ranging from 1,256 ㎛×949 ㎛ using 32 small-area PDs of 1,256 ㎛×19 ㎛. In addition, we measure and analyze the noise and signal characteristics of the LiDAR receiving board, as well as the performance and sensitivity of various types of STUD PDs. Finally, the LiDAR receiving board utilizing the STUD PD is applied to a 3D scanning LiDAR prototype that uses a 1.5-㎛ master oscillator power amplifier laser. This LiDAR precisely detects long-range objects over 50 m away, and acquires high-resolution 3D images of 320 pixels×240 pixels with a diagonal FOV of 32.6 degrees simultaneously.

• The Journal of Bigdata
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• v.9 no.1
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• pp.101-113
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• 2024

Federated learning has garnered attention as an efficient method for training machine learning models in a distributed environment while maintaining data privacy and security. This study proposes a novel FedRFBagging algorithm to optimize the performance of random forest models in such federated learning environments. By dynamically adjusting the trees of local random forest models based on client-specific data characteristics, the proposed approach reduces communication costs and achieves high prediction accuracy even in environments with numerous clients. This method adapts to various data conditions, significantly enhancing model stability and training speed. While random forest models consist of multiple decision trees, transmitting all trees to the server in a federated learning environment results in exponentially increasing communication overhead, making their use impractical. Additionally, differences in data distribution among clients can lead to quality imbalances in the trees. To address this, the FedRFBagging algorithm selects only the highest-performing trees from each client for transmission to the server, which then reselects trees based on impurity values to construct the optimal global model. This reduces communication overhead and maintains high prediction performance across diverse data distributions. Although the global model reflects data from various clients, the data characteristics of each client may differ. To compensate for this, clients further train additional trees on the global model to perform local optimizations tailored to their data. This improves the overall model's prediction accuracy and adapts to changing data distributions. Our study demonstrates that the FedRFBagging algorithm effectively addresses the communication cost and performance issues associated with random forest models in federated learning environments, suggesting its applicability in such settings.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.133-138
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• 2016

This paper describes the track initiation and target-tracking filter for ship tracking in a marine environment by using Light Detection And Ranging (LiDAR). LiDAR with three-dimensional scanning capability is more useful for target tracking in the short to medium range compared to RADAR. LiDAR has rotating multi-beams that return point clouds reflected from targets. Through preprocessing the cluster of the point cloud, the center point can be obtained from the cloud. Target tracking is carried out by using the center points of targets. The track of the target is initiated by investigating the normalized distance between the center points and connecting the points. The regular track obtained from the track initiation can be maintained by the target-tracking filter, which is commonly used in radar target tracking. The target-tracking filter is constructed to track a maneuvering target in a cluttered environment. The target-tracking algorithm including track initiation is experimentally evaluated in a sea-trial test with several boats.