• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.595-605
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• 2006

In this thesis, GPS and the electronic mapping were used to realize such a system by recognizing license plate numbers and identifying the location of objects that move at synchronous times with simulated movement in the electronic map. As well, throughout the study, a camera attached to a PDA, one of the mobile devices, automatically recognized and confirmed acquired license plate numbers from the front and back of each car. Using this mobile technique in a wireless network, searches for specific plate numbers and information about the location of the car is transmitted to a remote server. The use of such a GPS-based system allows for the measurement of topography and the effective acquisition of a car's location. The information is then transmitted to a central controlling center and stored as text to be reproduced later in the form of diagrams. Getting positional information through GPS and using image-processing with a PDA makes it possible to estimate the correct information of a car's location and to transmit the specific information of the car to a control center simultaneously, so that the center will get information such as type of the car, possibility of the defects that a car might have, and possibly to offer help with those functions. Such information can establish a mobile system that can recognize and accurately trace the location of cars.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.156-163
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• 2015

In this paper, we propose an active water level and distance measurement algorithm using a light beam pattern. On behalf of conventional water level gauge types of pressure, float-well, ultrasonic, radar, and others, recently, extensive research for video analysis based water level measurement methods is gradually increasing as an importance of accurate measurement, monitoring convenience, and much more has been emphasized. By turning a reference light beam pattern on bridge or embankment actively, we suggest a new approach that analyzes and processes the projected light beam pattern image obtained from camera device, measures automatically water level and distance between a camera and a bridge or a levee. As contrasted with conventional methods that passively have to analyze captured video information for recognition of a watermark attached on a bridge or specific marker, we actively use the reference light beam pattern suited to the installed bridge environment. So, our method offers a robust water level measurement. The reasons are as follows. At first, our algorithm is effective against unfavorable visual field, pollution or damage of watermark, and so on, and in the next, this is possible to monitor in real-time the portable-based local situation by day and night. Furthermore, our method is not need additional floodlight. Tests are simulated under indoor environment conditions from distance measurement over 0.4-1.4m and height measurement over 13.5-32.5cm.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.3
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• pp.48-55
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• 2010

Hearing impairment is one of the most common birth defects among infants. Significant bilateral hearing impairment have profound effects on speech and language development. But it can be prevented, if a hearing impairment is identified and treated in its early stage. ABR (auditory brainstem response) is useful screening tool for new born hearing test. However, the interpretation of conventional ABR should be done by a experienced audiologist and testing takes some time. Therefore, A-ABR(automated ABR) which detect ABR peak automatically have been developed recently. In contrast to A-ABR researches became active in overseas, there has been little study in Korea. In this study, we have developed a portable A-ABR system based on the results of our previous study. For the evaluation of the developed system, the clinical trials were performed on adults and infants. As a results, it showed good sensitivity (94.4%) and specificity (92.2%), and accuracy (93.0%) between clinical diagnosis and the developed A-ABR test.

• Korean Journal of Remote Sensing
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• v.20 no.4
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• pp.261-274
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• 2004

The feature extraction using remotely sensed imagery has been recognized one of the important tasks in remote sensing applications. As the high-resolution imagery are widely used to the engineering purposes, need of more accurate feature information also is increasing. Especially, in case of the automatic extraction of linear feature such as road using mid or low-resolution imagery, several techniques was developed and applied in the mean time. But quantitatively comparative analysis of techniques and case studies for high-resolution imagery is rare. In this study, we implemented a computer program to perform and compare GDPA (Gradient Direction Profile Analysis) algorithm and Hough transformation. Also the results of applying two techniques to some images were compared with road centerline layers and boundary layers of digital map and presented. For quantitative comparison, the ranking method using commission error and omission error was used. As results, Hough transform had high accuracy over 20% on the average. As for execution speed, GDPA shows main advantage over Hough transform. But the accuracy was not remarkable difference between GDPA and Hough transform, when the noise removal was app]ied to the result of GDPA. In conclusion, it is expected that GDPA have more advantage than Hough transform in the application side.

• Smart Media Journal
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• v.10 no.3
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• pp.31-38
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• 2021

It is hard to predict when and where a fall accident will happen. Also, if rapid follow-up measures on it are not performed, a fall accident leads to a threat of life, so studies that can automatically detect a fall accident have become necessary. Among automatic fall-accident detection techniques, a fall detection scheme using an IMU (inertial measurement unit) sensor attached to a wrist is difficult to detect a fall accident due to its movement, but it is recognized as a technique that is easy to wear and has excellent accessibility. To overcome the difficulty in obtaining fall data, this study proposes an algorithm that efficiently learns less data through machine learning such as KNN (k-nearest neighbors) and SVM (support vector machine). In addition, to improve the performance of these mathematical classifiers, this study utilized feature data aquired in the frequency space. The proposed algorithm analyzed the effect by diversifying the parameters of the model and the parameters of the frequency feature extractor through experiments using standard datasets. The proposed algorithm could adequately cope with a realistic problem that fall data are difficult to obtain. Because it is lighter than other classifiers, this algorithm was also easy to implement in small embedded systems where SIMD (single instruction multiple data) processing devices were difficult to mount.

• Journal of Wetlands Research
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• v.20 no.4
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• pp.304-313
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• 2018

Agricultural land reclamation in Saemangeum tidal land project is mostly planned to be completed by 2020. Irrigation water for the land is required to be prepared by that time. However, water quality for the irrigation sources is barely meet the target concentration. This paper described the reduction effect of and policy consideration for best management practices (BMPs) which were fertilizer prescription by soil test (SO#1), mixed application of SO#1 and 3 (SO#2), drainage gate control (SO#3), time-release fertilizer application (SO#4), and control (CT). Reduction of paddy runoff was relatively higher in SO#3 (25%) and SO#1 (27%) while lower in SO#4 (9%) and SO#2 (7%) than that in CT. In addition, farmers promised to follow the BMP guidelines but they didn't because of the several problems caused for the BMPs implementation. Thus, it recommended developing an automated control of irrigation gate and paddy water depth and supporing farmers for NPS pollution control and irrigation water reduction.

• 재활복지
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• v.17 no.4
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• pp.291-309
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• 2013

Web usability is utilized as a standard for constructing and managing website to be useful by people of all abilities and disabilities. Link integrity is one of main criteria for web usability evaluation. Links that are found to be broken or pointing to irrelevant information lead gradual degradation of link integrity over time. This study has conducted investigation for link integrity of Korean public institution website. Among 49 website that are accessible by an automatic link checker software, 91.8% of the website has more than one broken links. Also average number of broken links is 50.5 that is 0.33% of the number of links. 29 websites consist of internal broken links. And 22 website do not provide any information on the missing page. Broken links enlower website confidence by reducing web usability as well as they prohibit web search engine not to provide information on the website. Therefore, web developers and managers need to be aware of importance of link integrity and prohibit web usability degradation by performing link validation as a web management task or periodically.

• 재활복지
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• v.21 no.3
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• pp.129-146
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• 2017

In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.663-670
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• 2020

In the present study, we assessed the accuracy of aerial triangulation using a UAV (Unmanned Aerial Vehicle) capable of network RTK (Real-Time Kinematic) survey in a disaster situation that may occur in a semi-urban area mixed with buildings. For a reliable survey of check points, they were installed on the roofs of buildings, and static GNSS (Global Navigation Satellite System) survey was conducted for more than four hours. For objective accuracy assessment, coded aerial targets were installed on the check points to be automatically recognized by software. At the instance of image acquisition, the 3D coordinates of the UAV camera were measured using VRS (Virtual Reference Station) method, as a kind of network RTK survey, and the 3-axial angles were achieved using IMU (Inertial Measurement Unit) and gimbal rotation measurement. As a result of estimation and update of the interior and exterior orientation parameters using Agisoft Metashape, the 3D RMSE (Root Mean Square Error) of aerial triangulation ranged from 0.153 m to 0.102 m according to the combination of the image overlap and the angle of the image acquisition. To get higher aerial triangulation accuracy, it was proved to be effective to incorporate oblique images, though it is common to increase the overlap of vertical images. Therefore, to conduct a UAV mapping in an urgent disaster site, it is necessary to acquire oblique images together rather than improving image overlap.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.654-661
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• 2021

Air pollution caused by industrial development has become a level that can seriously threaten human health. In general, indoor air pollution is considered to be lower than outdoors, but modern people live indoors most of the time, thus it is essential to keep the indoor air quality comfortable in order to take care of one's own health and improve the quality of life. Therefore, the development of an indoor environment management platform using Internet of Things and data processing technology, which is currently drawing attention, is considered a very meaningful study. In this paper, we designed an IoT-based management platform that can remotely monitor and control indoor environments. In addition, the functions of the IoT terminal, gateway, and data server constituting the platform were implemented using open source and open libraries, and all functional operations were also verified. In particular, the IoT terminal and the gateway in this paper exchange data using BLE communication, so they can operate with relatively low power and since the gateway uses the BLE Advertising mode, it has the advantage of automatically recognizing IoT terminals that have not been previously configured.