• Journal of the Institute of Convergence Signal Processing
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• v.21 no.2
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• pp.55-60
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• 2020

In this paper, we propose a fast block matching algorithm of motion estimation using early detection of optimal candidate with high priority and a threshold. Even though so many fast algorithms for motion estimation have been published to reduce computational reduction full search algorithm, still so many works to improve performance of motion estimation are being reported. The proposed algorithm calculates block matching error for each candidate with high priority from previous partial matching error. The proposed algorithm can be applied additionally to most of conventional fast block matching algorithms for more speed up. By doing that, we can find the minimum error point early and get speed up by reducing unnecessary computations of impossible candidates. The proposed algorithm uses smaller computation than conventional fast full search algorithms with the same prediction quality as the full search algorithm. Experimental results shows that the proposed algorithm reduces 30~70% compared with the computation of the PDE and full search algorithms without any degradation of prediction quality and further reduces it with other fast lossy algorithms.

• KSBB Journal
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• v.21 no.5
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• pp.347-352
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• 2006

This study was carried out to establish the optimum condition for cell disruption with a sonificator in the detection of the gram positive bacteria, Bacillus globigii and Streptococcus epidermidis for the purpose of developing automatic fluorometer. The efficiency of sonificator on the Bacillus globigii and Streptococcus epidermidis disruption differed greatly according to the diameter of sonificator probe tip. The larger sonificator probe diameter showed greater disruption. Bacillus globigii was more disruptive than Streptococcus epidermidis. Sonificator probe of the 13 mm diameter was the most efficient one when sample was sonificated for 20 seconds. The detection limits of Bacillus globigii and Streptococcus epidermidis were $10^5CFU/m{\ell}\;and\;5{\times}10^5CFU/m{\ell}$ respectively when samples were sonificated for 20 seconds with a sonificator probe of 13 mm diameter.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.4
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• pp.369-375
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• 2012

In order to overcome the detection limit by the current nondestructive evaluation technology, a nonlinear resonant ultrasound spectroscopy(NRUS) technique was applied for detection of micro-scale cracks in a material. A down-shift of the resonance frequency and a variation of normalized amplitude of the resonance pattern were suggested as the nonlinear parameter for detection of micro-scale cracks in a materials. A natural-like crack were produced in a standard compact tension(CT) specimen by a low cycle fatigue test and the resonance patterns were acquired in each fatigue step. As the exciting voltage increases, a down-shift of resonance frequency were increases as well as the normalized amplitude decrease. This nonlinear effects were significant and even greater in the cracked specimen, but not observed in a intact specimen.

• Journal of Korea Water Resources Association
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• v.49 no.9
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• pp.749-759
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• 2016

The aim of this study is to apply and to evaluate the radar-based risk prediction algorithm for damage reduction by sudden localized heavy rain in urban areas. The algorithm is combined with three processes such as "detection of cumulonimbus convective cells that can cause a sudden downpour", "automatic tracking of the detected convective cells", and "risk prediction by considering the possibility of sudden downpour". This algorithm was applied to rain events that people were marooned in small urban stream. As the results, the convective cells were detected through this algorithm in advance and it showed that it is possible to determine the risk of the phenomenon of developing into local heavy rain. When use this risk predicted results for flood prevention operation, it is able to secure the evacuation time in small streams and be able to reduce the casualties.

• Journal of Apiculture
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• v.32 no.3
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• pp.191-198
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• 2017

Vespa hornets are notorious predators of honeybees in Korean beekeeping. Detection of vespa hornet attacking on honeybee colony was tried through analysis of wing beat frequency profiling from Vespa mandarinia. Wing beat profiles of V. mandarinia during active flight and resting were distinctively different. From the wing beat profiling, algorithm of automated detection of vespa attack was encoded, and alert system was developed using Teensy 3.2 and Raspberry pi 3. From the laboratory testing, the prototype system successfully detected vespa wing beats and delivered the vespa attack information to the user wirelessly. Further development of the system could help precision alert system of the vespa attack to apiary.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.263-263
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• 2023

블랙아이스는 눈에 쉽게 구분되지 않아 많은 교통사고를 초래하고 있다. 한국교통연구원 교통사고분석시스템에 따르면, 2017년부터 2021년까지 5년간의 서리/결빙으로 인한 교통사고 사망자는 122명, 적설로 인한 교통사고 사망자는 40명으로, 블랙아이스는 적설에 비해 위험성이 높은 것으로 나타난다. 과거의 다양한 연구에서 블랙아이스 생성조건을 기압과 한기 축적등의 조건에서 예측해왔지만, 이러한 기상학적 모델은 봄철 해빙기의 일교차로 인한 눈의 해동과 재냉각과 같은 다양한 기상 조건에서의 블랙아이스 탐지가 어렵다는 한계가 있어 최근에는 이미지 판별과 딥러닝모델(YOLO 등)을 기반으로 한 센서가 제시되고 있다. 그러나, 이러한 방법은 충분한 컴퓨팅 자원이 뒷받침되어야 하며, 블랙아이스 탐지까지 걸리는 속도가 빠르지 못한 편으로, 블랙아이스 초입 구간에서의 제동에 취약하다는 잠재적인 약점을 가지고 있다. 그러므로 본 연구에서는 블랙아이스의 주 원인인 서리나 어는비가 발생하기 위해서 주변 공기가 이슬점 온도 이하, 노면온도와 이슬점이 어는점보다 낮아야 함을 이용, IoT 센서 모듈을 통해 Magnus 방정식으로 계산한 이슬점 온도와 노면 온도를 사용하는 이동식 블랙아이스 추정 장치를 제시한다. 본 장치는 대기압, 온도, 습도로부터 계산된 이슬점 온도와 노면 온도를 통한 서리발생 가능성과 대기 온도, 노면 온도를 통해 어는비의 발생환경 여부를 계산한다. 본 연구 결과를 통해 블랙아이스 추정과 기상정보 생산을 동시에 가능케 하며, 추정 결과를 통합 수집서버에 전송함으로서 운전자에게 전방 블랙아이스 위험 구간을 조기에 전달하는 시스템과 이를 관리하기 위한 인프라를 구축하여 운전 시 결빙 미끄러짐 사고를 저감하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.246-248
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• 2021

This paper proposes a new general-purpose automatic fire detection system. And it deals with the contents of related research on how to design and develop for this system. The proposed system automatically notifies the user and the nearby fire department when a fire breaks out in a place where a fire alarm is installed. If this is the case, the nearby fire department can quickly confirm this fact and extinguish the fire at an early stage, thereby reducing human and property damage. The main targets of this system are houses and small buildings. The proposed fire alarm functions as a conventional fire alarm, and if a fire occurs, this fact is immediately transmitted to a nearby receiver through wireless data communication. The receiver in this paper communicates data using Korea's firefighting communication frequency band, and establishes one own network by installing it in various places to quickly receive fire alarm data at any time.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.67-77
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• 2023

This study represents an innovative research conducted in the smart farm environment, developing a deep learning-based disease and pest detection model and applying it to the Intelligent Internet of Things (IoT) platform to explore new possibilities in the implementation of digital agricultural environments. The core of the research was the integration of the latest ImageNet models such as Pseudo-Labeling, RegNet, EfficientNet, and preprocessing methods to detect various diseases and pests in complex agricultural environments with high accuracy. To this end, ensemble learning techniques were applied to maximize the accuracy and stability of the model, and the model was evaluated using various performance indicators such as mean Average Precision (mAP), precision, recall, accuracy, and box loss. Additionally, the SHAP framework was utilized to gain a deeper understanding of the model's prediction criteria, making the decision-making process more transparent. This analysis provided significant insights into how the model considers various variables to detect diseases and pests.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.3
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• pp.439-448
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• 2018

Conventional Earthquake Early Warning System (EEWS) detects the propagated P-wave from epicenter which should be achieved within 5 seconds to provide seconds to minutes of warning, allowing people to prepare for protective actions. EEWS in Korea is currently capable of providing a warning within 50 seconds after the primary P-wave detection, however, it is well-known that earthquake warning systems operating around Korean National Parks (KNP) have limited capability to fully monitor earthquake events. This study, therefore, presents a strategy to quantify the potential vulnerability to earthquake hazards by superimposing the distribution of Korea Integrated Seismic System (KISS) and the discretized map of KNP. Total 22 national parks are evaluated, and the results suggest that the improvement of the on-site systems should be necessitated for Gyoengju, Gyeryongsan, Songnisan, Gayasan, and Deogyusan national parks, whereas enhancement of regional systems is required for Bukhansan national park.

• Journal of Korea Water Resources Association
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• v.53 no.4
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• pp.313-322
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• 2020

There is always a risk of water disasters due to sudden storms in mountainous regions in Korea, which is more than 70% of the country's land. In this study, a radar-based risk prediction technique for sudden downpour is applied in the mountainous region and is evaluated for its applicability using Mt. Biseul rain radar. Eight local heavy rain events in mountain regions are selected and the information was calculated such as early detection of cumulonimbus convective cells, automatic detection of convective cells, and risk index of detected convective cells using the three-dimensional radar reflectivity, rainfall intensity, and doppler wind speed. As a result, it was possible to confirm the initial detection timing and location of convective cells that may develop as a localized heavy rain, and the magnitude and location of the risk determined according to whether or not vortices were generated. In particular, it was confirmed that the ground rain gauge network has limitations in detecting heavy rains that develop locally in a narrow area. Besides, it is possible to secure a time of at least 10 minutes to a maximum of 65 minutes until the maximum rainfall intensity occurs at the time of obtaining the risk information. Therefore, it would be useful as information to prevent flash flooding disaster and marooned accidents caused by heavy rain in the mountainous area using this technique.