• Journal of the Korea Computer Industry Society
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• v.7 no.4
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• pp.309-320
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• 2006

The imprecise real-time system provides flexibility in scheduling time-critical tasks. Most scheduling problems of satisfying both 0/1 constraint and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. Liu suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on uniprocessors for minimizing the total error. Song et al suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on multiprocessors for minimizing the total error. But, these algorithms are all off-line algorithms. In the online scheduling, NORA algorithm can find a schedule with the minimum total error for the imprecise online task system. In the NORA algorithm, the EDF strategy is adopted in the optional scheduling.<중략> The algorithm, proposed in this paper, can be applied to some applications efficiently such as radar tracking, image processing, missile control and so on.

• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.277-282
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• 2006

The purpose in having a control surface on a ship is to control the motion of the ship. The control surface may be composed entirely of a single movable surface or of a combination of fixed and movable portion A control surface has one sole function to perform in meeting its purpose, and that is to develop a control force in consequence of its orientation and movement relative to the water. The forces and moments generated as a result of this rotation and angle of attack then determine the maneuvering characteristics of the ship. In this paper the study of flapped rudder's 2-dimensional section was accomplished. Model tests had been carried out with different angles of attack of a main foil and flap's deflection angles to predict the performance of the flapped rudder and the 2 frame particle tracking method had been used to obtain the velocity distribution in the flow field $Re=2.8\times10^4$ had been used during the whole experiments and measured results had been compared with each other.

• Smart Structures and Systems
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• v.24 no.5
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• pp.567-585
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• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

• Journal of the Korea Convergence Society
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• v.7 no.5
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• pp.29-34
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• 2016

Recently, with the development of high-tech industry, the use of the drones in various aspects of daily life is rapidly advancing. With technical and functional advancements, drones have an advantage of being easy to be utilized in the areas of use according to various lifestyles. In addition, through the diversification of the drone service converged with image processing medium such as camera and CCTV, an automated security system that can replace humans is expected to be introduced. By designing these unmanned security technology, a new convergence security drone service techniques that can strengthen the previous drone application technology will be proposed. In the proposed techniques, a biometric authentication technology will be designed as additional authentication methods that can determine the safety incorporated with security by selecting the search and areas of an object focusing on the objects in the initial windows and search windows through OpenCV technology and CAM-Shift algorithm which are an object tracking algorithm. Through such, a highly efficient security drone convergence service model will be proposed for performing unmanned security by using the drones that can continuously increase the analysis of technology on the mobility and real-time image processing.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1463-1478
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• 2022

Maritime transport accounts for 99.7% of the exports and imports of the Republic of Korea; therefore, developing a vessel monitoring system for efficient operation is of significant interest. Several studies have focused on tracking and monitoring vessel movements based on automatic identification system (AIS) data; however, ships without AIS have limited monitoring and tracking ability. High-resolution optical satellite images can provide the missing layer of information in AIS-based monitoring systems because they can identify non-AIS vessels and small ships over a wide range. Therefore, it is necessary to investigate vessel monitoring and small vessel classification systems using high-resolution optical satellite images. This study examined the possibility of developing ship monitoring systems using Compact Advanced Satellite 500-1 (CAS500-1) satellite images by first training a deep learning model using satellite image data and then performing detection in other images. To determine the effectiveness of the proposed method, the learning data was acquired from ships in the Yellow Sea and its major ports, and the detection model was established using the You Only Look Once (YOLO) algorithm. The ship detection performance was evaluated for a domestic and an international port. The results obtained using the detection model in ships in the anchorage and berth areas were compared with the ship classification information obtained using AIS, and an accuracy of 85.5% and 70% was achieved using domestic and international classification models, respectively. The results indicate that high-resolution satellite images can be used in mooring ships for vessel monitoring. The developed approach can potentially be used in vessel tracking and monitoring systems at major ports around the world if the accuracy of the detection model is improved through continuous learning data construction.

• Journal of the Korean Society for Marine Environment & Energy
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• v.17 no.3
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• pp.247-256
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• 2014

Recently, camera and RADAR are used for more effective and accurate observation of the bird migration. In recent years, many researches on the bird migration using RADAR are undertaking and in active, thus causes the advent of "RADAR ornithology" as a new academic field. Due to the lack of accessibility, economic feasibility and mobility of weather RADAR, airport searching RADAR and tracking RADAR, Nowadays, a marine RADAR is widely used for a bird observation. In this paper, we deals with a study on development of a remote bird observation system using marine FMCW RADAR, which monitors, records and analyzes bird movement by RADAR image processing and target recognition technology. Also, we conduct first test and second test for availability of the developed system, and verify the system to apply in bird observation domain. Consequently, we figured problems out, and correct the problems to improve the system. The developed system can apply in other domains such as environment evaluation. In the future, the system needs to improve accuracy of statistics and to track migration route of bird.

• 대한방사선치료학회:학술대회논문집
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• 2005.06a
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• pp.13-17
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• 2005

Introduction : For stereotactic radiosurgery (SRS) of a tumor in the region whose movement due to respiration is significant, like Lung lower lobe, the gated therapy, which delivers radiation dose to the selected respiratory phases when tumor motion is small, was peformed using the Respiratory gating system and its clinical effectiveness was evaluated. Methode and Materials : For two SRS patients with a tumor in Lung lower lobe, a marker block (infrared reflector) was attached on the abdomen. While patient' respiratory cycle was monitored with Real-time Position Management (RPM, Varian, USA), 4D CT was performed (10 phases per a cycle). Phases in which tumor motion did not change rapidly were decided as treatment phases. The treatment volume was contoured on the CT images for selected treatment phases using maximum intensity projection (MIP) method. In order to verify setup reproducibility and positional variation, 4D CT was repeated. Result : Gross tumor volume (GTV) showed maximum movement in superior-inferior direction. For patient $\#$1, motion of GTV was reduced to 2.6 mm in treatment phases ($30\%\~60\%$), while that was 9.4 mm in full phases ($0\%\~90\%$) and for patient $\#$2, it was reduced to 2.3 mm in treatment phases ($30\%\~70\%$), while it was 11.7 mm in full phases ($0\%\~90\%$). When comparing two sets of CT images, setup errors in all the directions were within 3 mm. Conclusion : Since tumor motion was reduced less than 5 mm, the Respiratory gating system for SRS of Lung lower lobe is useful.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.55-64
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• 2013

In this paper, the HILS (Hardware In-the-Loop Simulation) system to analyze and to verify the performance of the targeting pod is addressed. The main functions of the targeting pod is acquiring and tracking targets to guide a LGB (Laser Guided Bomb) to the targets. For the analysis of targeting pod, the real time simulate images generation of IR and daylight cameras, sever control technology, and the analysis of laser transfer characteristics are necessary. For the real time image generation and the laser transfer characteristics analysis, off-the-shelf SDK(Software Development Kit) OKTAL-SE is used. For the servo controller, well-proven mechanism in the previous program is applied to increase servo control accuracy. To analyze the performance of a targeting pod in a realistic environment, 1553B, ARINK818 interface and etc. which are actually implemented in real combat aircrafts are applied in the system. By using the developed HILS system, the performance of currently operating targeting pods in real combat aircrafts can be analyzed and predicted. Additionally, the relationship between overall system performance and each module performance can be analyzed, the currently developed HILS system is expected to be a very useful tool to generate system development requirements of targeting pods and to reduce any possible future development risks.

• Korean Association of Arts Management
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• no.53
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• pp.207-247
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• 2020

is a project for the senior generation with humanistic knowledge to become a mentor and communicate with them to present the wisdom and direction of life to the new generations of mentees based on various life experiences. has been expanding since 2015, starting with the pilot operation in 2014. In general, projects such as these are assessed to establish effectiveness indicators to verify effectiveness and to establish project management and development strategies. However, most of the evaluations have been conducted quantitatively and qualitatively based on the short-term duration of the project. Therefore, in the case of continuous projects such as , especially in the field of culture and arts where long-term effectiveness verification is required, the short-term evaluation is difficult to predict and judge the actual meaningful effects. In this regard, tried to examine the qualitative change of key participants in this project through the 2017 and 2018 image tracking survey. For this purpose, we adopted qualitative research methodology through interview video shooting, field shooting, and value coding as a research method suitable for the research subject. To analyze the results, first, the interview images were transcribed, keywords were extracted, value encoding works were matched with human psychological values, and the theoretical method was used to identify changes and to derive the meaning. In fact, despite the fact that the study conducted in this study was a follow-up survey, it remained a limitation that it analyzed the changed pattern in a rather short time of 2 years. However, this study systemized the specific methodology that researchers should conduct for follow-up and provided the flow of research at the present time when there is hardly a model for follow-up in the field of culture and arts education business in Korea as well as abroad. Significance can be derived from this point. In addition, it can be said that it has great significance in preparing the detailed system and case of comparative analysis methodology through value coding.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.623-634
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• 2022

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.