• Journal of Positioning, Navigation, and Timing
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• v.13 no.3
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• pp.221-235
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• 2024

Errors included in Global Navigation Satellite System (GNSS) measurements degrade the performance of user position estimation but can be mitigated by spatial correlation properties. Augmentation systems providing correction data can be broadly categorized into State Space Representation (SSR) and Observation Space Representation (OSR) methods. The satellite-based cm-level augmentation service based on the SSR broadcasts correction data via satellite signals, unlike the traditional Real-Time Kinematic (RTK) and Network RTK methods, which use OSR. To provide a large amount of correction data via the limited bandwidth of the satellite communication, efficient message structure design considering service area, correction generation, and broadcast intervals is necessary. For systematic message design, it is necessary to analyze the influence of error components included in GNSS measurements. In this study, errors in satellite orbits, satellite clocks for GPS, Galileo, BeiDou, and QZSS satellite constellations ionospheric and tropospheric delays over one year were analyzed, and their spatial decorrelations and linear modeling characteristics were examined.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.5
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• pp.451-457
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• 2011

The main objective of this study is to investigate the variation in the ignition characteristics of coals as a function of moisture content in a laminar flow reactor (LFR) equipped with a fuel moisture micro-supplier designed by the Pusan Clean Coal Center. The volatile ignition position and time were observed experimentally when a pulverized coal with moisture was fed into the LFR under burning conditions similar to those at the exit of the pulverizer and real boiler. The reaction-zone temperature along the centerline of the reactor was measured with a $70-{\mu}m$, R-type thermocouple. For different moisture contents, the volatile ignition position was determined based on an average of 15 to 20 images captured by a CCD camera using a proprietary image-processing technique. The reaction zone decreased proportionally as a function of the moisture content. As the moisture content increased, the volatile ignition positions were 2.92, 3.36, 3.96, and 4.65 mm corresponding to ignition times of 1.46, 1.68, 2.00, and 2.33 ms, respectively. These results indicate that the ignition position and time increased exponentially. We also calculated the ignition-delay time derived from the adiabatic thermal explosion. It showed a trend that was similar to that of the experimental data.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.453-461
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• 2017

The video image in the movie has become more spectacular than ever, and the expression area and the subject have been infinitely expanded, but it can not be said that the range of imagination has expanded. Instead, the 60s and 70s, which were the epochs of popular culture, The film that implements the artististic visual style and expression style of the artist. Stanley Kubrick's "Clockwork Orange", which has been pursuing technological perfection and experimental style, was created using traditional video grammar and gained a great repercussion with outstanding material and high artistic expression technique at that time. These techniques have led audiences to rational observation through irony, rather than emotional sympathy for the situation, for extreme violence and sensational films. This is because the purpose of the director was not to be in technological perfection but to reveal the contradictions of the real society and to reflect on the meaning of the existence of society itself. These creative traditional visual grammar and expression methods are a good visual style that enables the intentionally transmitted message to be transmitted more intensely and effectively, and the artistic depth can be created at the same time by unconsciously perceiving the meaning present on the back to the audience.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.582-587
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• 2020

Recently, disasters caused by extreme weather and the damage caused by them are increasing worldwide. The interest in disasters, such as earthquakes, typhoons, and ground subsidence, is increasing in Korea. Korea has enacted a special law based on disaster management, and has built monitoring systems for individual facility units by building precision sensors and related systems to measure the displacement status of long bridges and high-rise composite buildings. On the other hand, the application of a real-time monitoring system is insufficient for slopes, open-pit mines, small and medium structures due to weather, measurement methods, cost, and constant monitoring difficulties. In this study, the displacement monitoring method using the total station was studied and the applicability was suggested through the experiment. Through the research, the concept and operation flow of a monitoring system that can measure the displacement of the terrain or the structure using the total station was presented. The monitoring system allows the user to select the location and operation method of the equipment so that the equipment can be installed according to the site situation, and set the number of observations, the period, and the observation range of the object. Using the experiment on the monitoring system, the station was monitored with precision within 5mm, and it was suggested that the displacement of the object can be monitored using the total station. Further research will be needed to assess the applicability of monitoring to real slopes and structures.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1779-1790
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• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.4
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• pp.225-242
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• 2012

This is the first attempt to produce simultaneous surface current field from satellite altimeter data for the entire East Sea and to provide surface current information to users with formal description. It is possible to estimate surface geostrophic current field in near real-time because satellite altimeters and coastal tide gauges supply sea level data for the whole East Sea. Strength and location of the major currents and meso-scale eddies can be identified from the estimated surface geostrophic current field. The mean locations of major surface currents were explicated relative to topographic, ocean-surface and undersea features with schematic representation of surface circulation. In order to demonstrate the practical use of this surface current information, exemplary descriptions of annual, seasonal and monthly mean surface geostrophic current distributions were presented. In order to objectively classify surface circulation patterns in the East Sea, empirical orthogonal function (EOF) analysis was performed on the estimated 16-year (1993-2008) surface current data. The first mode was associated with intensification or weakening of the East Korea Warm Current (EKWC) flowing northward along the east coast of Korea and of the anti-cyclonic circulation southwest of Yamato Basin. The second mode was associated with meandering paths of the EKWC in the southern East Sea with wavelength of 300 km. The first and second modes had inter-annual variations. The East Sea surface circulation was classified as inertial boundary current pattern, Tsushima Warm Current pattern, meandering pattern, and Offshore Branch pattern by the time coefficient of the first two EOF modes.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.171-181
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• 2013

Recently, ground penetrating radar(GPR) has been widely used in detecting metallic and nonmetallic buried landmines and a number of related researches have been reported. A novel preprocessing method is proposed in this paper to flag potential locations of buried mine-like objects from GPR array measurements. GPR operates by measuring the reflection of an electromagnetic pulse from discontinuities in subsurface dielectric properties. As the GPR pulse propagates in the geologic medium, it suffers nonlinear attenuation as the result of absorption and dispersion, besides spherical divergence. In the proposed algorithm, a logarithmic transformed regression model which successfully represents the time-varying signal amplitude of the GPR data is estimated at first. Then, background signals may be densely distributed near the regression model and candidate signals of targets may be far away from the regression model in the time-amplitude space. Based on the observation, GPR signals are decomposed into candidate signals of targets and background signals using residuals computed from the estimated value by regression and the measurement of GPR. Candidate signals which may contain target signals and noise signals need to be refined. Finally, targets are detected through the refinement of candidate signals based on geometric signatures of mine-like objects. Our algorithm is evaluated using real GPR data obtained from indoor controlled environment and the experimental results demonstrate remarkable performance of our mine-like object detection method.

• Korean Journal of Cognitive Science
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• v.24 no.3
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• pp.237-270
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• 2013

Determinism and compatibilism have thought that libertarianism contradicts the scientific view. This paper demonstrates that the hypothesis that free will exists does not cause any problems and contradictions, while maintaining pro-scientific view. Rather, determinism lacks scientific and demonstrative bases. At first, I reject dualistic self by assuming identity theory of the self and physical body & brain. Free will is a functional concept or property that can have multiple realization. Therefore we can recognize whether aliens or robots have free will through observation on their acts. 'Free will' is a functional kinds term like 'digestion'. As we know we have digestive function, we can know that we have free will even before knowing the necessity of its existence by understanding micro structure of human free will. The judgement that an individual has free will function depends on whether it has particular actions. Those actions are controlling and restraining actions in context, predicting future, making elaborate conditional sentences, etc. Real being of free will is the physical occupant of the function that makes those actions. Determinism is based on various kinds of misconceptions and misunderstandings. Determinists often confuse necessity of physical law and determinism. Another decisive misunderstanding is that free will postulates same conditions and different results from the same point of time. However, free will postulates that the two points of time are different. Because determinism is unnecessary redundant hypothesis influenced by religions, according to Ockham's Razor, determinism should be eliminated.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.52-67
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• 2008

Recently, frequent occurrence of flash floods caused by climactic change has necessitated prompt and quantitative prediction of precipitation. In particular, the usability of rainfall radar that can carry out real-time observation and prediction of precipitation behavior has increased. Moreover, the use of distributed hydrological model that enables grid level analysis has increased for an efficient use of rainfall radar that provides grid data at 1km resolution. The use of distributed hydrologic model necessitates grid-type spatial data about target basins; to enhance reliability of flood runoff simulation, the use of visible and precise data is necessary. In this paper, physically based $Vflo^{TM}$ model and ModClark, a quasi-distributed hydrological model, were used to carry out flood runoff simulation and comparison of simulation results with data from Imjin River Basin, two-third of which is ungauged. The spatial scope of this study was divided into the whole Imjin River basin area, which includes ungauged area, and Imjin River basin area in South Korea for which relatively accurate and visible data are available. Peak flow and lag time outputs from the two simulations of each region were compared to analyze the impact of uncertainty in topographical parameters and soil parameters on flood runoff simulation and to propose effective methods for flood runoff simulation in ungauged regions.