• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2162-2166
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• 2016

This paper describes the implementation of AUSV system for sonar image acquisition to survey the seabed. The system is controlled by Feed Forward PID algorithm on the vessel for bearing of the thrusters composed of motion sensor and DGPS which calculates the differences between the current location and the destination location for longitude and latitude based on GPS coordinates. As experimental results, the bearing control performance is good that the error distance from the destination positions are under 6m in total survey track of 1km. And the sonar image deviation of a object is under 12 pixels from the manned survey method, which the comparison with the total image quality is almost the same as the manned survey one. Thus the proposed AUSV system is a new method of system can be utilized at the limited survey areas as the surveyor should not be able to approach on sea surface by onboard vessel.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.6_spc
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• pp.644-650
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• 2016

Track maintenance works based on track geometry recordings are essential to enhance the safety and comfort of railway transportation. Usually, the track irregularity has been measured by a special inspection trains which all were imported from abroad. Because the inspection train speed is limited under 160 km/h, it takes a long time to inspect railways and there is difficulty in daytime operation. To solve this problem, we started to develop a track geometry measuring system (TGMS) with measurement speed up to 300 km/h which can be installed in commercial vehicles such as HEMU-430X. In this paper, we introduce a newly developed inertial TGMS and propose two inertial navigation system (INS) algorithms (method A, B) for measuring track geometry. In order to investigate advantage and disadvantage of each algorithm, we performed vibration test of the TGMS, which was simulated by 6-axis shaking table. Through the vibration test, we analyzed the influence of vehicle vibration on the TGMS which will be installed on bogie frame. To the vibration test, two methods satisfied the required accuracy of track geometry measurement under the level of the actual vehicle vibration of HEMU-430X train. Theoretically, method A is sensitive to vehicle vibration than method B. However, HEMU-430X's bogie vibration frequency range is out of interest range of measurement system. Therefore, method A can also apply the HEMU-430X train.

• Korean Journal of Remote Sensing
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• v.17 no.3
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• pp.275-284
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• 2001

This study was carried out to evaluate high resolution satellite imagery of IKONOS for classifying the land cover, especially forest type. The IKONOS imagery of 11km$\times$11km size was taken on April 24, 2000 in Bong-pyoung Myun Pyungchang-Gun, Kangwon Province. Land cover classes were water, coniferous evergreen, Larix leptolepis, broad-leaved tree, bare land, farm land, grassland, sandy soil and asphalted area. Supervised classification method with algorithm of maximum likelihood was applied for classification. The terrestrial survey was also carried out to collect the reference data in this area. The accuracy of the classification was analyzed with the items of overall accuracy, producer's accuracy, user's accuracy and k for test area through the error matrix. In the accuracy analysis of the test area, overall accuracy was 94.3%, producer's accuracy was 77.0-99.9%, user's accuracy was 71.9-100% and k and 0.93. Classes of bare land, sandy soil and farm land were less clear than other classes, whereas classification result of IKONOS in forest area showed higher performance than that of other resolution(5-30m) satellite data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.293-296
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• 2016

In case of an emergency on a busy road of a city, drivers should make way for special vehicles such as police cars, fire engines, or ambulance as soon as possible. If road infrastructures recognize the movements of special vehicles, and transfer alert message to traffic signal controllers and normal cars through wireless network such as WAVE or TPEG, normal cars can prepare to make way in advance. As a result, it help special vehicles move faster. In this paper, we install a roof mark on the roof of a special vehicle, detect the mark through a mark recognition algorithm which includes perspective transformation, and get the inner information by decoding the digital pattern on it. The experiment results show that mark can be recognized 100% and 93.3% of inner digital data of the mark can be recognized, when the size of a mark is larger than $88cm{\times}88cm$ and the mark moves at a speed of 50km/s.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.440-449
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• 2018

Purpose: This study aims to design and verify an onsite EEWS that extracts the P-wave from a single seismic station and deduce the PGV. Method: The P-wave properties of Pd, Pv, and Pa were calculated by using 12 seismic waveform data extracted from historic seismic records in Korea, and the PGVs were computed using empirical equation on the P properties - PGV relationship and compared with the observed values. Results: Comparison of the observed and estimated PGVs within the alarm level shows the error rate of 86.7% as minimum. By reducing the PTW to 2 seconds, the alarm time can be shortened by 1 second and the seismic blind zone near the epicenter can be shortened by 6 Km. Conclusion: Through this study, we confirmed the availability of the on-site EEWS in Korea. For practical use, it is necessary to develop regression formula and algorithm reflect local effect in Korea by increasing the number of seismic waveform data through continuous observation, and to eliminate the noise from the site.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.70-85
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• 2021

Deep learning methodology, which has been actively studied in recent years, has improved the performance of artificial intelligence. Accordingly, systems utilizing deep learning have been proposed in various industries. In traffic systems, spatio-temporal graph modeling using GNN was found to be effective in predicting traffic speed. Still, it has a disadvantage that the model is trained inefficiently due to the memory bottleneck. Therefore, in this study, the road network is clustered through the graph clustering algorithm to reduce memory bottlenecks and simultaneously achieve superior performance. In order to verify the proposed method, the similarity of road speed distribution was measured using Jensen-Shannon divergence based on the analysis result of Incheon UTIC data. Then, the road network was clustered by spectrum clustering based on the measured similarity. As a result of the experiments, it was found that when the road network was divided into seven networks, the memory bottleneck was alleviated while recording the best performance compared to the baselines with MAE of 5.52km/h.

• Korean Journal of Exercise Nutrition
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• v.25 no.1
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• pp.23-29
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• 2021

[Purpose] This preliminary study aimed to develop a regression model to estimate the non-exercise activity thermogenesis (NEAT) of Korean adults using various easy-to-measure dependent variables. [Methods] NEAT was measured in 71 healthy adults (male n = 29; female n = 42). Statistical analysis was performed to develop a NEAT estimation regression model using the stepwise regression method. [Results] We confirmed that age^A, weight^B, heart rate (HR)_average^C, weight × HR_average^D, weight × HR_sum^E, systolic blood pressure (SBP) × HR_rest^F, fat mass ÷ height^2G, gender × HR_average^H, and gender × weight × HR_sum^I were important variables in various NEAT activity regression models. There was no significant difference between the measured NEAT values obtained using a metabolic gas analyzer and the predicted NEAT. [Conclusion] This preliminary study developed a regression model to estimate the NEAT in healthy Korean adults. The regression model was as follows: sitting = 1.431 - 0.013 × (A) + 0.00014 × (D) - 0.00005 × (F) + 0.006 × (H); leg jiggling = 1.102 - 0.011 × (A) + 0.013 × (B) + 0.005 × (H); standing = 1.713 - 0.013 × (A) + 0.0000017 × (I); 4.5 km/h walking = 0.864 + 0.035 × (B) + 0.0000041 × (E); 6.0 km/h walking = 4.029 - 0.024 × (C) + 0.00071 × (D); climbing up 1 stair = 1.308 - 0.016 × (A) + 0.00035 × (D) - 0.000085 × (F) - 0.098 × (G); and climbing up 2 stairs = 1.442 - 0.023 × (A) - 0.000093 × (F) - 0.121 × (G) + 0.0000624 × (E).

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.2
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• pp.83-92
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• 2024

Currently, various countries are enhancing accessibility by providing bicycle rental services for convenient usage within daily life. This paper introduces the Nubija public bicycle service in Changwon, South Korea, aiming to address the imbalance between demand and supply of Nubija bicycles. We propose a Highest Priority Reallocation Scheme to prevent this disparity. Comparing this scheme with others that randomly visit terminals for redistribution and those that prioritize terminals closest to current locations, we illustrate its superior efficiency. Our proposed Highest Priority Reallocation Scheme prioritizes terminals with the highest demand and shortest distances nearby. Through experiments, our proposed scheme demonstrates superior performance, with the lowest average of 817.44km distance and an average of 6437.45 times, i.e., 88.14% successful rental occurrences. This highlights its superiority over the other two algorithms.

• Journal of Radiation Protection and Research
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• v.45 no.3
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• pp.117-129
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• 2020

Background: Radiation portal monitors (RPMs) involving plastic scintillators installed at the border inspection sites can detect illicit trafficking of radioactive sources in cargo containers within seconds. However, RPMs may generate false alarms because of the naturally occurring radioactive materials. To manage these false alarms, we previously suggested an energy-weighted algorithm that emphasizes the Compton-edge area as an outstanding peak. This study intends to evaluate the identification of radioactive sources using an improved energy-weighted algorithm. Materials and Methods: The algorithm was modified by increasing the energy weighting factor, and different peak combinations of the energy-weighted spectra were tested for source identification. A commercialized RPM system was used to measure the energy-weighted spectra. The RPM comprised two large plastic scintillators with dimensions of 174 × 29 × 7 ㎤ facing each other at a distance of 4.6 m. In addition, the in-house-fabricated signal processing boards were connected to collect the signal converted into a spectrum. Further, the spectra from eight radioactive sources, including special nuclear materials (SNMs), which were set in motion using a linear motion system (LMS) and a cargo truck, were estimated to identify the source identification rate. Results and Discussion: Each energy-weighted spectrum exhibited a specific peak location, although high statistical fluctuation errors could be observed in the spectrum with the increasing source speed. In particular, ¹³⁷Cs and ⁶⁰Co in motion were identified completely (100%) at speeds of 5 and 10 km/hr. Further, SNMs, which trigger the RPM alarm, were identified approximately 80% of the time at both the aforementioned speeds. Conclusion: Using the modified energy-weighted algorithm, several characteristics of the energy weighted spectra could be observed when the used sources were in motion and when the geometric efficiency was low. In particular, the discrimination between ⁶⁰Co and ⁴⁰K, which triggers false alarms at the primary inspection sites, can be improved using the proposed algorithm.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.26-41
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• 2012

It is necessary to manage, forecast and prepare agricultural production based on accurate and up-to-date information in order to cope with the climate change and its impacts such as global warming, floods and droughts. This study examined the applicability as well as challenges of the object-based image analysis method for developing a land cover image classification algorithm, which can support the fast thematic mapping of wide agricultural areas on a regional scale. In order to test the applicability of RapidEye's multi-temporal spectral information for differentiating agricultural land cover types, the integration of other GIS data was minimized. Under this circumstance, the land cover classification accuracy at the study area of Kimje ($1300km^2$) was 80.3%. The geometric resolution of RapidEye, 6.5m showed the possibility to derive the spatial features of agricultural land use generally cultivated on a small scale in Korea. The object-based image analysis method can realize the expert knowledge in various ways during the classification process, so that the application of spectral image information can be optimized. An additional advantage is that the already developed classification algorithm can be stored, edited with variables in detail with regard to analytical purpose, and may be applied to other images as well as other regions. However, the segmentation process, which is fundamental for the object-based image classification, often cannot be explained quantitatively. Therefore, it is necessary to draw the best results based on expert's empirical and scientific knowledge.