• Science of Emotion and Sensibility
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• v.6 no.4
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• pp.15-23
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• 2003

Recently, there have been many attempts to develop BCI (brain computer interface) based on EEG (electroencephalogram). Measurement and analysis of EEG evoked by particular stimulation is important for the design of brain wave pattern and interface of BCI. The purpose of this study is to develop a general-purpose system that measures subject's reaction time after audio-visual stimulation which can work together with any other biosignal measurement systems. The entire system is divided into four modules, which are stimulation signal generation, reaction time measurement, evoked potential measurement and synchronization. Stimulation signal generation module was implemented by means of Flash. Measurement of the reaction time (the period between the answer request and the subject reaction) was achieved by self-made microcontroller system. EEG measurement was performed using the ready-made hardware and software without any modification. Synchronization of all modules was achieved by, first, the black-and-white signals on the stimulation screen synchronized with the problem presentation and the answer request, second, the photodetectors sensing the signals. The proposed method offers easy design of purpose-specific system only by adding simple modules (reaction time measurement, synchronization) to the ready-made stimulation and EEG system, and therefore, it is expected to accelerate the researches requiring the measurement of evoked response and reaction time.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.2
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• pp.151-159
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• 2004

The diversity, expansion of human activity and rapid urbanization make modem society to faced with problems like damage of nature and drain of natural resources. Under these circumstances rapid and accurate change detection techniques, which can detect wide range utilization changes, are needed for efficient management and utilization plan of national territory. In this study to perform change detection from remote sensing images, space analysis technique contained in Geographic Information System is applied. And from this technique, the software. that can execute new change detection algorithm, query, inquiry and analysis, is produced. This software is on the basis of graphic user interface and has many functions such as format conversion, grid calculation, statistical processing, display and reference. In this study, simultaneously change detection for multi-temporal satellite images can be performed and integrated one change image about four different periods was produced. Further more software user can acquire land cover change information for an specific area through querying and questioning about yearly changes. Finally making of every application module for change detection into one window based visual basic program, can be produced user convenience and automatic performances.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.5
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• pp.267-274
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• 2018

For successful BIM settlement, it is a key technic for engineer to design structures in the 3-dimensional digital space and to work out related design documents directly. Lately many BIM tool has been released and each supports their 3-dimensional object libraries. But it is not easy to apply those libraries to design transportation infra structures that were placed along the route(3-dimensional line). Moreover, in case of design changes, it is so difficult to reflect those changes with the integrated model that was assembled by them. Because of they were developed without consideration for redundancy of parameters between objects that were placed nearby or were related each other. In this paper, a method to develop module for modeling and placing 3-dimensional object for transportation infra structures is presented. The modules are employed by a parametric method and can deal with design changes. Also, for a railroad bridge, through developing user interface of the integrated 3-dimensional model that was assembled by those modules the applicability of them was reviewed.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.116-123
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• 2007

Despite the number of backlight manufacturer is increased as the market of flat panel display equipments and related development devices is enlarged, the inspection based on the human eye is still used in many backlight production lines. The defects such as particle, spot and scratch on the light emitting surface of the backlight prevent the LCD device from displaying the colors correctly. From that manual inspection it is difficult to maintain the quality of backlight consistently because the accuracy and the speed of the inspection may change with the physical condition of the operater. In this paper we studied on the development of automatic backlight surface defect inspection system. For this, we made up of the computer vision system and we developed the main program with various user interfaces to operate the inspection system effectively. And we developed the image processing module to extract the defect information. Furthermore, we presented the labeling process to reconstruct defect regions using the labeling table and the defect index. From the experimental results, we found that our system can detect all defect regions identified from human eye and it is sufficient to substitute for the conventional surface inspection.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.623-629
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• 2018

Smart Factory is a concept of automatic production system of machines by the fusion of ICT and manufacturing. As a base technology for realizing such a smart factory, there is an increasing interest in a low-power environmentally friendly LED lighting system, and researches on so-called optical ID related application technologies such as communication using a LED and position recognition are actively underway. In this paper, We have proposed a system that can reliably identify logistics location and additional information without being affected by electromagnetic interference such as high voltage, high current, and generator in the plant. Through the basic experiment, we confirmed the applicability of the color ID recognition rate from 98.8% to 93.8% according to the eight color variations in the short distance.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.177-183
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• 2002

Current state-of-the-art of VMS control is based upon simple knowledge-based inference engine with message set and each message's priority. And R&Ds of the VMS control are focused on the accurate detection and estimation of traffic condition of the subject roadways. However VMS display itself cannot achieve a desirable traffic allocation among alternative routes in the network In this context, VMS display strategy is the most crucial part in the VMS control. VMS itself has several limitations in its nature. It is generally known that VMS causes overreaction and concentration problems, which may be more serious in urban network than highway network because diversion should be more easily made in urban network. A feedback control algorithm is proposed in this paper to address the above-mentioned issues. It is generally true that feedback control approach requires low computational effort and is less sensitive to models inaccuracy and disturbance uncertainties. Major features of the proposed algorithm are as follows: Firstly, a regulator is designed to attain system optimal traffic allocation among alternative routes for each VMS in the network. Secondly, strategic messages should be prepared to realize the desirable traffic allocation, that is, output of the above regulator. VMS display strategy module is designed in this context. To evaluate Probable control benefit and to detect logical errors of the Proposed feedback algorithm, a offline simulation test is performed using real network in Daejon, Korea.

• Fire Science and Engineering
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• v.32 no.6
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• pp.34-39
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• 2018

In this paper, the architecture of a safe stove with an automatic fire suppression function using a sound wave fire extinguisher has been proposed and developed for the first time. A microcontroller connected to a fire sensor detects and suppresses a fire by driving a fire extinguisher. The sound wave fire extinguisher is composed of a speaker and collimator, and is driven by a driver module including an audio amplifier. The attenuation of the sound wave is reduced by preventing the sound diffusion with an enclosure surrounding a stove. The frequency of the sound wave is set to 50 Hz, and the sound pressure of 93 dBA is measured at the distance of 0.5 m. It takes maximum 8 and 15 seconds to suppress the flame from 7-cc and 14-cc flammable liquid, respectively, which corresponds to 24% and 42% of the natural extinguishing time. Since the proposed safe stove is non-toxic and leaves no residues over the conventional ones, it would combine with various home appliances to suppress early-stage fires and prevent fire expansion.

• Journal of Information Technology Applications and Management
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• v.28 no.3
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• pp.59-75
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• 2021

This study aims to establish a foundation for autonomous driving on campus and communication of abundant university information in the HCI environment in a VR environment where college freshmen can freely travel around campus facilities. The purpose of this study is to develop a three-dimensional VR-style campus tour system to establish a media environment to provide abundant university information guidance services to freshmen in non-face-to-face situations. This study designed a three-dimensional virtual reality campus tour system to solve the problem of discontinuity in which VR360 filming space does not lead to space like reality, and to solve many problems of expertise in VR technology by constructing an integrated production environment of tour system. We aim to solve the problem of inefficiency, which requires a large amount of momentum in virtual space, by constructing a GUI that utilizes the motion of the field of view focus. The campus environment was designed as a three-dimensional virtual reality using a three-dimensional graphic design. In non-face-to-face situations, college freshmen freely transformed the HMD VR device, smartphone, FPS operation mode of the gyroscope sensor. The design elements of the three-dimensional virtual reality campus tour system were classified as ①Visualization of factual experiences, ②Continuity of space movement, ③Operation, automatic operation mode, ④Natural landscape animation, ⑤Animation according to wind direction, ⑥Actual space movement mode, ⑦Informatization of spatial understanding, ⑧GUI by experience environment, ⑨Text GUI by building, ⑩VR360, 3D360 Studio Environment, ⑪Three-dimensional virtual space coupling block module, ⑫3D360-3D Virtual Space Transmedia Zone, ⑬Transformable GUI(VR Device Dual Viewer-Gyro Sensor Full Viewer-FPS Operation Viewer) and an integrated production environment was established with each element. It is launched online (http://vautu.com/u1) by constructing a GUI for free driving mode and college information screens to adapt to college life for freshmen, and designing an environment that can be used simultaneously by current media such as PCs, Android, and iPads. Therefore, it conducted user research, held a development presentation, a forum on excellence in university innovation support projects, and applied it as a system on the website of a particular university. College freshmen will be able to experience university information directly from the web and app to the virtual reality campus environment.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.228-239
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• 2022

In this paper, we propose an unmanned vehicle scratch detection deep learning model for car sharing services. Conventional scratch detection models consist of two steps: 1) a deep learning module for scratch detection of images before and after rental, 2) a manual matching process for finding newly generated scratches. In order to build a fully automatic scratch detection model, we propose a one-step unmanned scratch detection deep learning model. The proposed model is implemented by applying transfer learning and fine-tuning to the deep learning model that detects changes in satellite images. In the proposed car sharing service, specular reflection greatly affects the scratch detection performance since the brightness of the gloss-treated automobile surface is anisotropic and a non-expert user takes a picture with a general camera. In order to reduce detection errors caused by specular reflected light, we propose a preprocessing process for removing specular reflection components. For data taken by mobile phone cameras, the proposed system can provide high matching performance subjectively and objectively. The scores for change detection metrics such as precision, recall, F1, and kappa are 67.90%, 74.56%, 71.08%, and 70.18%, respectively.

• 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.