• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.411-417
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• 2021

The field that studies human-computer interaction is called HCI (Human-computer interaction). This field is an academic field that studies how humans and computers communicate with each other and recognize information. This study is a study on hand gesture recognition for human interaction. This study examines the problems of existing recognition methods and proposes an algorithm to improve the recognition rate. The hand region is extracted based on skin color information for the image containing the shape of the human hand, and the center of gravity profile is calculated using principal component analysis. I proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. We proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. The existing center of gravity profile has shown the result of incorrect hand gesture recognition for the deformation of the hand due to rotation, but in this study, the center of gravity profile is used and the point where the distance between the points of all contours and the center of gravity is the longest is the starting point. Thus, a robust algorithm was proposed by re-improving the center of gravity profile. No gloves or special markers attached to the sensor are used for hand gesture recognition, and a separate blue screen is not installed. For this result, find the feature vector at the nearest distance to solve the misrecognition, and obtain an appropriate threshold to distinguish between success and failure.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1697-1707
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• 2021

On 19 February 2020, the 2nd Geostationary Ocean Color Imager (GOCI-II), a maritime sensor of GEO-KOMPSAT-2B, was launched. The GOCI-II instrument expands the scope of aerosol retrieval research with its improved performance compared to the former instrument (GOCI). In particular, the newly included UV band at 380 nm plays a significant role in improving the sensitivity of GOCI-II observations to the absorbing aerosols. In this study, we calculated the aerosol index and detected absorbing aerosols from January to June 2021 using GOCI-II 380 and 412 nm channels. Compared to the TROPOMI aerosol index, the GOCI-II aerosol index showed a positive bias, but the dust pixels still could be clearly distinguished from the cloud and clear pixels. The high GOCI-II aerosol index coincided with ground-based observations indicating dust aerosols were detected. We found that 70.5% of dust and 80% of moderately-absorbing fine aerosols detected from the ground had GOCI-II aerosol indices larger than the 75th percentile through the whole study period.

• Ocean and Polar Research
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• v.43 no.4
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• pp.229-243
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• 2021

Quality control (QC) to process observed time series has become more critical as the types and amount of observed data have increased along with the development of ocean observing sensors and communication technology. International ocean observing institutions have developed and operated automatic QC procedures for these observed time series. In this study, the performance of automated QC procedures proposed by U.S. IOOS (Integrated Ocean Observing System), NDBC (National Data Buy Center), and OOI (Ocean Observatory Initiative) were evaluated for observed time-series particularly from the Yellow and East China Seas by taking advantage of a confusion matrix. We focused on detecting additive outliers (AO) and temporary change outliers (TCO) based on ocean temperature observation from the Ieodo Ocean Research Station (I-ORS) in 2013. Our results present that the IOOS variability check procedure tends to classify normal data as AO or TCO. The NDBC variability check tracks outliers well but also tends to classify a lot of normal data as abnormal, particularly in the case of rapidly fluctuating time-series. The OOI procedure seems to detect the AO and TCO most effectively and the rate of classifying normal data as abnormal is also the lowest among the international checks. However, all three checks need additional scrutiny because they often fail to classify outliers when intermittent observations are performed or as a result of systematic errors, as well as tending to classify normal data as outliers in the case where there is abrupt change in the observed data due to a sensor being located within a sharp boundary between two water masses, which is a common feature in shallow water observations. Therefore, this study underlines the necessity of developing a new QC algorithm for time-series occurring in a shallow sea.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.4
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• pp.28-36
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• 2021

It is known that buried rebars inside concrete structures are protected from corrosion due to passive layer. It is very important to delay the timing of corrosion or evaluate a detection of corrosion initiation for the purpose of cost-beneficiary service life of a structure. In this study, corrosion monitoring was performed on concrete specimens considering 3 levels of cover depth(60 mm, 45 mm, and 30 mm), W/C(water to cement) ratio(40.0%, 50.0%, and 60.0%) and chloride concentration(0.0%, 3.5%, and 7.0%). OCP(Open Circuit Potential) was measured using agar-based socket type sensors. The OCP measurement showed the consistent behavior where the potential was reduced in wet conditions and it was partially recovered in dry conditions. In the case of 30 mm of cover depth for most W/C ratio cases, the lowest OCP value was measured and rapid OCP recovery was evaluated in increasing cover depth from 30 mm to 45 mm, since cover depth was an effective protection against chloride ion ingress. As the chloride concentration increased, the effect on the cover depth tended to be more dominant than the that of W/C ratio. After additional monitoring and physical evaluation of chloride concentration after specimen dismantling, the proposed system can be improved with increasing reliability of the corrosion monitoring.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.764-771
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• 2018

Domestic and foreign agricultural environments nowadays are undergoing various changes such as aging of agricultural population, increase of earned population, rapid climate change, diversification of agricultural product distribution structure, depletion of water resources and limited cultivation area. In order to respond to various environmental changes in recent agriculture, practical use of Smart Greenhouse to easily record, store and manage crop production information such as crop growing information, growth environment and agriculture work log, Interest is growing. In this paper, we propose a system that collects the situation information necessary for growth such as temperature, humidity, solar radiation, CO2 concentration, and monitor the collected data, which can be measured in the rhizosphere of the crop. We have developed a system that collects data such as temperature, humidity, radiation, and growth environment data, which are measured by data obtained from the rhizosphere measuring section of a growing crop and measured by a sensor, and transmitted to a wireless communication gateway of 400 MHz. We developed the integrated SW that can monitor the rhythm environment data and visualize the data by using cloud based data. We can monitor by graph format and data format for visualization of data. The existing smart farm managed crops and facilities using only the data within the farm, and this study suggested the most efficient growth environment by collecting and analyzing the weather and growth environment of the farms nationwide.

• Journal of Ocean Engineering and Technology
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• v.33 no.2
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• pp.168-177
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• 2019

KRISO (Korea Research Institute of Ship & Ocean Engineering) started a project to develop the core algorithms for autonomous intervention using an underwater robot in 2017. This paper introduces the development of the robot platform for the core algorithms, which is an ROV (Remotely Operated Vehicle) type with one 7-function manipulator. Before the detailed design of the robot platform, the 7E-MINI arm of the ECA Group was selected as the manipulator. It is an electrical type, with a weight of 51 kg in air (30 kg in water) and a full reach of 1.4 m. To design a platform with a small size and light weight to fit in a water tank, the medium-size manipulator was placed on the center of platform, and the structural analysis of the body frame was conducted by ABAQUS. The robot had an IMU (Inertial Measurement Unit), a DVL (Doppler Velocity Log), and a depth sensor for measuring the underwater position and attitude. To control the robot motion, eight thrusters were installed, four for vertical and the rest for horizontal motion. The operation system was composed of an on-board control station and operation S/W. The former included devices such as a 300 VDC power supplier, Fiber-Optic (F/O) to Ethernet communication converter, and main control PC. The latter was developed using an ROS (Robot Operation System) based on Linux. The basic performance of the manufactured robot platform was verified through a water tank test, where the robot was manually operated using a joystick, and the robot motion and attitude variation that resulted from the manipulator movement were closely observed.

• Journal of Sensor Science and Technology
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• v.28 no.1
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• pp.41-46
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• 2019

In order to develop novel thermal imaging materials for microbolometer applications, $[(Ni_{0.3}Mn_{0.7})_{1-x}Cu_x]_3O_4$ ($0.18{\leq}x{\leq}0.26$) thin films were fabricated using metal-organic decomposition. Effects of Cu content on the electrical properties of the annealed films were investigated. Spinel thin films with a thickness of approximately 100 nm were obtained from the $[(Ni_{0.3}Mn_{0.7})_{1-x}Cu_x]_3O_4$ films annealed at $380^{\circ}C$ for five hours. The resistivity (${\rho}$) of the annealed films was analyzed with respect to the small polaron hopping model. Based on the $Mn^{3+}/Mn^{4+}$ ratio values obtained through x-ray photoelectron spectroscopy analysis, the hopping mechanism between $Mn^{3+}$ and $Mn^{4+}$ cations discussed in the proposed study. The effects of $Cu^+$ and $Cu^{2+}$ cations on the hopping mechanism is also discussed. Obtained results indicate that $[(Ni_{0.3}Mn_{0.7})_{1-x}Cu_x]_3O_4$ thin films with low temperature annealing and superior electrical properties (${\rho}{\leq}54.83{\Omega}{\cdot}cm$, temperature coefficient of resistance > -2.62%/K) can be effectively employed in applications involving complementary metal-oxide semiconductor (CMOS) integrated microbolometer devices.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• Design & Manufacturing
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• v.13 no.2
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• pp.17-21
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• 2019

In this study, selective laser sintered 3D printing mold core and metal core were used to investigate the difference of the thickness shrinkage from the gate of the injection molded part at a constant interval. SLS 3D printing mold core was made of nylon-based PA2200 powder and the metal core was manufactured by conventional machining method. As the PA2200 powder material has low strength, thermal conductivity and high specific heat characteristics compared with metal, molding conditions were set with the consideration of molten temperature and injection pressure. Crystalline resin(PP) and amorphous resin(PS) with low melting temperature and viscosity were selected for the injection molding experiment. Cooling time for processing condition was selected by checking the temperature change of the cores with a cavity temperature sensor. The cooling time of the 3D printing core was required a longer time than that of the metal core. The thickness shrinkage of the molded part compared to the core depth was measured from the gate by a constant interval. It was shown that the thickness shrinkage of the 3D printing core was 2.02 ~ 4.34% larger than that of metal core. In additions, in the case of metal core, thickness shrinkage was increased with distance from the gate, on the contrary, in the case of polymer core showed reversed aspect.

• Science of Emotion and Sensibility
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• v.21 no.4
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• pp.43-54
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• 2018

The aim of this study is to determine the effect of motion sickness on pupil rhythm. Sixteen volunteers of both genders (8 male, 8 female, mean age $25.67{\pm}2.43$ years) experienced VR contents in both 2D and HMD versions for 15 minutes, and their pupillary rhythms were compared. The irregular pattern of the pupillary rhythms, as demonstrated by increasing mean pupil diameter (mPD) and standard deviation of the pupil diameter (sPD), revealed motion sickness after experiencing HMD condition. The pupillary response is strongly related to the cognitive load, and the motion sickness can be interpreted as a change in the cognitive load caused by the increasing volume of visual information that must be processed and the conflict or inconsistency between different sensory modalities. The method proposed in this study could be a non-contact measurement method for the monitoring of motion sickness using a web-camera rather than previous sensor-based methods.