• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.60-67
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• 2022

An Electro-Optical Tracking System (EOTS) is an electric optical system with EO/IR cameras, laser sensors, and an IMU. The EOTS calculates coordinates of targets, using attitude and acceleration measured by the IMU. In particular for an armed aircraft, the performance of the weapon system depends on how quickly and accurately it acquires the target coordinates. The IMU should be operated after alignment is complete, to meet the coordinate accuracy required by the weapon system so the initial stabilization time of the IMU should be reduced, by quickly measuring the attitude and acceleration. Alignment is the process of determining the initial attitude by resolving the attitude error of the IMU, and the IMU of mission equipment such as an airborne EOTS, uses velocity matching based on the velocity from GPS/INS for aircraft navigation. In this paper, a method is presented to improve the transfer alignment performance of the airborne EOTS, by maneuvering aircraft and the mission equipment. First, the performance factor of the alignment was identified, as a heading error through the velocity matching model and simulation results. Then acceleration maneuvers and attitude changes were necessary, to correct the error. As a result of flight tests applied to an EOTS on a OOO aircraft system, the transfer alignment performance was improved as the duration time was decreased, by more than five times when the aircraft accelerated by more than 0.2g and the EOTS was moving until 6.7deg/s.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.82-92
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• 2022

This study aims to investigate the effect of total electrochemical cell resistance (TECR) on electrochemical impedance (EI) measurements of reinforced concrete (RC) by electrochemical impedance spectroscopy (EIS) using a three-electrode system. A series of experimental study is performed to measure electrochemical behavior of a steel bar embedded in a concrete cube specimen, with a side length of 200 mm, in various experimental conditions. Main variables include concrete dry conditions, coupling resistance between sensing electrodes and concrete surface, and area of the counter electrode. It is demonstrated that EI values remains stable when the compliant voltage of a measuring device is sufficiently great compared to the potential drop caused by TECR of concrete specimens. It is confirmed that the effect of the coupling resistance of TECR is far more influential than other two factors (concrete dry conditions and area of the counter electrode). The results in this study can be used as a fundamental basis for development of a surface-mount sensor for corrosion monitoring of reinforced concrete structures exposed to wet-and-dry cycles under marine environment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.687-693
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• 2006

Image co-registration is the process of overlaying two images of the same scene, one of which represents a reference image, while the other is geometrically transformed to the one. In order to improve efficiency and effectiveness of the co-registration approach, the author proposed a pre-qualified area matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with cross correlation coefficient. For refining matching points, outlier detection using studentized residual was used and iteratively removes outliers at the level of three standard deviation. Throughout the pre-qualification and the refining processes, the computation time was significantly improved and the registration accuracy is enhanced. A prototype of the proposed algorithm was implemented and the performance test of 3 Landsat images of Korea. showed: (1) average RMSE error of the approach was 0.435 pixel; (2) the average number of matching points was over 25,573; (3) the average processing time was 4.2 min per image with a regular workstation equipped with a 3 GHz Intel Pentium 4 CPU and 1 Gbytes Ram. The proposed approach achieved robustness, full automation, and time efficiency.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.63-73
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• 2024

Autonomous vehicles at Levels 3 to 5, currently under global research and development, seek to replace the driver's perception, judgment, and control processes with various sensors integrated into the vehicle. This integration enables artificial intelligence to autonomously perform the majority of driving tasks. However, autonomous vehicles currently obtain temporary driving permits, allowing them to operate on roads if they meet minimum criteria for autonomous judgment abilities set by individual countries. When autonomous vehicles become more widespread in the future, it is anticipated that buyers may not have high confidence in the ability of these vehicles to avoid hazardous situations due to the limitations of temporary driving permits. In this study, we propose a method for grading the judgment abilities of autonomous vehicles based on a driving simulator experiment comparing and evaluating drivers' abilities to avoid hazardous situations. The goal is to derive evaluation criteria that allow for grading based on specific scenarios and to propose a framework for grading autonomous vehicles. Thirty adults (25 males and 5 females) participated in the driving simulator experiment. The analysis of the experimental results involved K-means cluster analysis and independent sample t-tests, confirming the possibility of classifying the judgment abilities of autonomous vehicles and the statistical significance of such classifications. Enhancing confidence in the risk-avoidance capabilities of autonomous vehicles in future hazardous situations could be a significant contribution of this research.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.115-123
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• 2024

In this paper, we propose a vibration notification system that combines navigation information and wearable bands to ensure safe driving for the transportation vulnerable. This system transmits navigation driving information to a linked application, converts it into a vibration signal, and provides notifications through a wearable band. Existing navigation systems focus on providing route guidance and location information, so the driver's concentration is dispersed, and safety and convenience are deteriorated, especially for those with mobility impairments, due to standard vision and delayed recognition of stimuli, resulting in an increasingly high traffic accident rate. To solve this problem, navigation driving information is converted into vibration signals through a linked application, and vibration notifications for events, left turns, right turns, and speeding are provided through a wearable band to ensure driver safety and convenience. In the future, we will use cameras and vehicle sensors to increase awareness of safety inside and outside the vehicle by adding a function that provides notifications with vibration and LED when the vehicle approaches or recognizes an object, and we will continue to conduct research to build a safer driving environment. plan.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.11 s.353
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• pp.48-57
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• 2006

This work describes a 12b 200KHz 0.52mA $0.47mm^2$ algorithmic ADC for sensor applications such as motor controls, 3-phase power controls, and CMOS image sensors simultaneously requiring ultra-low power and small size. The proposed ADC is based on the conventional algorithmic architecture with recycling techniques to optimize sampling rate, resolution, chip area, and power consumption. The input SHA with eight input channels for high integration employs a folded-cascode architecture to achieve a required DC gain and a sufficient phase margin. A signal insensitive 3-D fully symmetrical layout with critical signal lines shielded reduces the capacitor and device mismatch of the MDAC. The improved switched bias power-reduction techniques reduce the power consumption of analog amplifiers. Current and voltage references are integrated on the chip with optional off-chip voltage references for low glitch noise. The employed down-sampling clock signal selects the sampling rate of 200KS/s or 10KS/s with a reduced power depending on applications. The prototype ADC in a 0.18um n-well 1P6M CMOS technology demonstrates the measured DNL and INL within 0.76LSB and 2.47LSB. The ADC shows a maximum SNDR and SFDR of 55dB and 70dB at all sampling frequencies up to 200KS/s, respectively. The active die area is $0.47mm^2$ and the chip consumes 0.94mW at 200KS/s and 0.63mW at 10KS/s at a 1.8V supply.

• Journal of Bio-Environment Control
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• v.25 no.4
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• pp.277-282
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• 2016

This study was aimed to investigate the effect of air-circulation fans on air temperature and relative humidity in a single-span tomato greenhouse (W: 7m, L: 25m, H: 3.2m). According to standard of fan layout by ASAE (1997), a total of 10 fans were bilaterally arranged in 2 rows in the experimental greenhouse. The distributions of air temperature and relative humidity were measured from 6 pm to 8 am under different conditions, with and without fans. The measurement heights were 0.7m, 1.7m and 2.7m. Under the condition of "fans off", the spatial differences of air temperature and relative humidity between upper and lower sides were $1.7^{\circ}C$ and 10.8%, respectively. The operation of 10 fans showed their differences to $0.1^{\circ}C$ and 3.2%. The number of fans and installation direction were evaluated their performance on reducing the spatial variation of air temperature and relative humidity. The experimental layouts were 5 and fans in 2 rows (bilaterally) and 10 fans in the one (same) direction. Under the condition of "6 fans on" and "5 fans on", the spatial differences of air temperature and relative humidity between upper and lower side were $0.3^{\circ}C$, 3.4% and $0.3^{\circ}C$ and 4.0%. The operation of 10 fans in the one direction reduced their differences to $0.5^{\circ}C$ and 4.9%. The overall findings of this study showed that there was no significant differences under each condition. Therefore, this study suggested that it is more economic and effective to install five fans in 2 rows (bilaterally) in the greenhouse (W: 7m, L: 25m, H: 3.2m).

• Research in Plant Disease
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• v.28 no.4
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• pp.221-230
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• 2022

The fire blight caused by Erwinia amylovora (Ea) was first reported in 2015 in Korea, and the disease has rapidly spread to 22 regions until 2021. In Korea, all host plants in the apple and pear orchards where fire blight occurred should be eliminated and buried by the Plant Protection Act. To prevent the spread of the disease, all burial sites were prohibited from planting the new host plants for the next three years. To confirm the eradication efficiency of Ea and the reoccurrence of fire blight, the surveillance facilities were established on three burial sites from 2019 to 2020 in Anseong-si, Gyeonggi-do, and Chungju-si, Chungcheongbuk-do. As host plants, five apple trees of fire blight-susceptible cultivar 'Fuji', were planted in each facility. All facilities were enclosed with fences and nets and equipped with two CCTVs, motion sensors, and several other sensors for recording weather conditions to monitor the environment of the sentinel plants in real-time. The sentinel plants were checked for the reoccurrence of fire blight routinely. Suspicious plant parts were collected and analyzed for Ea detection by loop-mediated isothermal amplification polymerase chain reaction and conventional polymerase chain reaction. Until November 2022, Ea has not been detected in all sentinel plants. These results might support that the burial control of infected plants in soil works efficiently to remove Ea and support the possibility to shorten the prohibition period of host plant establishment in the burial sites.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• Journal of Korea Water Resources Association
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• v.48 no.7
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• pp.553-566
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• 2015

Acoustic Doppler Current Profilers(ADCPs) have capability to concurrently capitalize three-dimensional velocity vector and bathymetry with highly efficient and rapid manner, and thereby enabling ADCPs to document the hydrodynamic and morphologic data in very high spatial and temporal resolution better than other contemporary instruments. However, ADCPs are also limited in terms of the inevitable unmeasured regions near bottom, surface, and edges of a given cross-section. The velocity in those unmeasured regions are usually extrapolated or assumed for calculating flow discharge, which definitely affects the accuracy in the discharge assessment. This study aimed at scrutinizing a conventional extrapolation method(i.e., the 1/6 power law) for estimating the unmeasured regions to figure out the accuracy in ADCP discharge measurements. For the comparative analysis, we collected spatially dense velocity data using ADV as well as stationary ADCP in a real-scale straight river channel, and applied the 1/6 power law for testing its applicability in conjunction with the logarithmic law which is another representative velocity law. As results, the logarithmic law fitted better with actual velocity measurement than the 1/6 power law. In particular, the 1/6 power law showed a tendency to underestimate the velocity in the near surface region and overestimate in the near bottom region. This finding indicated that the 1/6 power law could be unsatisfactory to follow actual flow regime, thus that resulted discharge estimates in both unmeasured top and bottom region can give rise to discharge bias. Therefore, the logarithmic law should be considered as an alternative especially for the stationary ADCP discharge measurement. In addition, it was found that ADCP should be operated in at least more than 0.6 m of water depth in the left and right edges for better estimate edge discharges. In the future, similar comparative analysis might be required for the moving boat ADCP discharge measurement method, which has been more widely used in the field.