Journal of the Institute of Electronics Engineers of Korea TC
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v.48
no.6
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pp.41-50
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2011
This article is concerned with the technology to provide car driver the car's status which are composed of car trouble code in car engine and many sensors. In addition, it installs vehicle diagnostic programs on wireless communication's portable device, for example, Smart phone, PDA, PMP, UMPC. As a result, this is to provide car manager with many information of car sensors when we go to car maintenance. it can monitor relevant information on vehicle by portable device in real time, alert drivers with specific messages and also enable them to address abnormalities immediately. Moreover, the technology could help the drivers who perhaps don't know very well about their vehicles to drive safely and economically as well; the reason is because the whole system is composed of just Vehicle-information collecting device and personal wireless communication's portables and transfers the relating data to server computers through wireless network in order to handle information on vehicles. This technology make us monitor vehicle's running, failure and disorder by using wireless communication's portable device. Finally, this study system is composed of a lot of application to display us the car's status which get car's inner sensor information while driving a car.
Watermelons (Citrulus vulgaris Schrad) are usually sorted manually by weight, appearance, and acoustic impulse, so grading of maturity and internal quality is subject to inaccuracies. It was necessary to develop a nondestructive evaluation technique of internal watermelon quality to reduce human error. Thus, acoustic characteristics related to internal quality factors were analyzed. Among these factors, three (ripeness, presence of an internal cavity, and blood-colored flesh) were selected for evaluation. The number of peaks and the sum of peak amplitudes for watermelons with blood-colored flesh were lower than for normal fruits. The portable evaluation system has an impact mechanism, a microphone sensor, a signal processing board, an LCD panel, and a battery. A performance test was conducted in the field. The internal quality evaluation model showed 87% prediction accuracy. Validation was conducted on 72 samples. The accuracy of quality evaluation was 83%. The quality of samples was evaluated by an inspector using conventional methods (hitting the watermelon and listening to the sounds), and then compared with prototype results. The quality evaluation accuracy of the prototype was better than that of the inspector. This nondestructive quality evaluation system could be useful in the field, warehouse, and supermarket
Kim, Young-Hyuk;Lim, Il-Kwon;Li, Qigui;Park, So-A;Kim, Myung-Jin;Lee, Jae-Kwang
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2010.05a
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pp.463-466
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2010
In this paper, CCTV based fire surveillance system should aim to development. Advantages and Disadvantages analyzed of Existing sensor-based fire surveillance system and video-based fire surveillance system. To national support U-City, U-Home, U-Campus, etc, spread the ubiquitous environment appropriate to fire surveillance system model and a fire judgement technology. For this study, Microsoft LifeCam VX-1000 using through the capturing images and analyzed for apple and tomato, Finally we used H.264. The client uses the Linux OS with ARM9 S3C2440 board was manufactured, the client's role is passed to the server to processed capturing image. Client and the server is basically a 1:1 video communications. So to multiple receive to video multicast support will be a specification. Is fire surveillance system designed for multiple video communication. Video data from the RGB format to YUV format and transfer and fire detection for Y value. Y value is know movement data. The red color of the fire is determined to detect and calculate the value of Y at the fire continues to detect the movement of flame.
The Geostationary Ocean Color Imager (GOCI) on board the Communication Ocean Meteorological Satellite (COMS), the first geostationary ocean color sensor, requires accurate atmospheric correction since its eight bands are also affected by atmospheric constituents such as gases, molecules and atmospheric aerosols. Unlike gases and molecules in the atmosphere, aerosols can interact with sunlight by complex scattering and absorption properties. For the purpose of qualified ocean remote sensing, understanding of aerosol-radiation interactions is needed. In this study, we show micro-physical and optical properties of aerosols using the Optical Property of Aerosol and Cloud (OPAC) aerosol models. Aerosol optical properties, then, were used to analysis the relationship between theoretical satellite measured radiation from radiative transfer calculations and aerosol optical thickness (AOT) under various environments (aerosol type and loadings). It is found that the choice of aerosol type makes little different in AOT retrieval for AOT<0.2. Otherwise AOT differences between true and retrieved increase as AOT increases. Furthermore, the differences between the AOT and angstrom exponent from standard algorithms and this study, and the comparison with ground based sunphotometer observations are investigated. Over the northeast Asian region, these comparisons suggest that spatially averaged mean AOT retrieved from this study is much better than from standard ocean color algorithm. Finally, these results will be useful for aerosol retrieval or atmospheric correction of COMS/GOCI data processing.
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.
In this paper we proposed a new ocean radiation automatic monitoring system. The proposed system has the following characteristics: First, using NaI + PVT mixed detectors, the response speed is fast and precision analysis is possible. Second, the application of temperature compensation algorithm to scintillator-type sensors does not require additional cooling devices and enables stable operation in the changing ocean environment. Third, since cooling system is not needed, electricity consumption is low, and electricity can be supplied reliably by utilizing solar energy, which can be installed at the observation deck of ocean environment. Fourth, using GPS and wireless communications, accurate location information and real-time data transmission function for measurement areas enables immediate warning response in the event of nuclear accidents such as those involving neighboring countries. The results tested by the authorized testing agency to assess the performance of the proposed system were measured in the range of $5{\mu}Sv/h$ to 15mSv/h, which is the highest level in the world, and the accuracy was determined to be ${\pm}8.1%$, making normal operation below the international standard ${\pm}15%$. The internal environmental grade (waterproof) was achieved, and the rate of variation was measured within 5% at operating temperature of $-20^{\circ}C$ to $50^{\circ}C$ and stability was verified. Since the measured value change rate was measured within 10% after the vibration test, it was confirmed that there will be no change in the measured value due to vibration in the ocean environment caused by waves.
In order to produce crop information using remote sensing, we use classification and growth monitoring based on crop phenology. Therefore, time-series satellite images with a short period are required. However, there are limitations to acquiring time-series satellite data, so it is necessary to use fusion with other earth observation satellites. Before fusion of various satellite image data, it is necessary to overcome the inherent difference in radiometric characteristics of satellites. This study performed Korea Multi-Purpose Satellite-3 (KOMPSAT-3) cross calibration with Landsat-8 as the first step for fusion. Top of Atmosphere (TOA) Reflectance was compared by applying Spectral Band Adjustment Factor (SBAF) to each satellite using hyperspectral sensor band aggregation. As a result of cross calibration, KOMPSAT-3 and Landsat-8 satellites showed a difference in reflectance of less than 4% in Blue, Green, and Red bands, and 6% in NIR bands. KOMPSAT-3, without on-board calibrator, idicate lower radiometric stability compared to ladnsat-8. In the future, efforts are needed to produce normalized reflectance data through BRDF (Bidirectional reflectance distribution function) correction and SBAF application for spectral characteristics of agricultural land.
KIPS Transactions on Software and Data Engineering
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v.11
no.3
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pp.141-148
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2022
Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.
Lee, Sang Gyu;Choi, Chang Sun;Lee, Hee Ju;Jang, Yoon Ah;Lee, Jun Gu
Horticultural Science & Technology
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v.33
no.3
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pp.303-308
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2015
The consumption of leaf vegetables has been steadily increasing in Korea. Leaf vegetables are used for "Ssam (vegetable wrap-up), eaf vegetables has been steadily increasing in Korea. Leaf vegetables are used for asoned condiments inside several layers of young vegetable leaves. This study investigated the effect of air temperature on the growth and phytochemical contents of beet (Beta vulgaris L.) and Ssamchoo (Brassica lee L. ssp. namai) grown in a closed-type plant factory system where fluorescent lamps were used as an artificial light source. Seeds of beet and Ssamchoo were sown in a peat-lite germination mix. The roots of 20-day-old seedlings were washed, and the seedlings were planted on a styrofoam board and grown in hydroponic beds for 25 days under fluorescent light. Plants were exposed to one of three different air temperature regimes (20, 25 and $30^{\circ}C$ during the day combined with $18^{\circ}C$ during the night), which were monitored with a sensor at 30 cm above the plant canopy. Increased plant height and leaf area were observed in beet at $25^{\circ}C$ and $30^{\circ}C$ compared to $20^{\circ}C$. For Ssamchoo, the greatest plant height, leaf area, fresh weight and dry weight were obtained at $20^{\circ}C$. Ascorbic acid content of beet and Ssamchoo leaves were highest at $30^{\circ}C$. In beet, total polyphenol and flavonoid contents were higher at $20^{\circ}C$ (42.4, $197.0mg{\cdot}g^{-1}DW$) and $25^{\circ}C$ (46.9, $217.0mg{\cdot}g^{-1}DW$) than $30^{\circ}C$ (22.4, $88.0mg{\cdot}g^{-1}DW$). In Ssamchoo, total polyphenol and flavonoid contents were also higher at $20^{\circ}C$ (79.2, $268.2mg{\cdot}g^{-1}DW$) and $25^{\circ}C$ (66.3, $258.3mg{\cdot}g^{-1}DW$), respectively, than $30^{\circ}C$ (53.7, $134.7mg{\cdot}g^{-1}DW$). Hence, the optimum temperature appears to be $20^{\circ}C$ for growing both beet and Ssamchoo in a closed-type plant factory system with fluorescent light.
In this study, a method to assess and monitor hydrological drought using remote sensing was investigated for use in regions with limited observation data, and was applied to the Upper Namhangang basin in South Korea, which was seriously affected by the 2008-2009 drought. Drought information may be obtained more easily from meteorological data based on water balance than hydrological data that are hard to estimate. Air temperature data at 2 m above ground level (AGL) were estimated using remotely sensed data, evapotranspiration was estimated from the air temperature, and the correlations between precipitation minus evapotranspiration (P-PET) and streamflow percentiles were examined. Land Surface Temperature data with $1{\times}1km$ spatial resolution as well as Atmospheric Profile data with $5{\times}5km$ spatial resolution from MODIS sensor on board Aqua satellite were used to estimate monthly maximum and minimum air temperature in South Korea. Evapotranspiration was estimated from the maximum and minimum air temperature using the Hargreaves method and the estimates were compared to existing data of the University of Montana based on Penman-Monteith method showing smaller coefficient of determination values but smaller error values. Precipitation was obtained from TRMM monthly rainfall data, and the correlations of 1-, 3-, 6-, and 12-month P-PET percentiles with streamflow percentiles were analyzed for the Upper Namhan-gang basin in South Korea. The 1-month P-PET percentile during JJA (r = 0.89, tau = 0.71) and SON (r = 0.63, tau = 0.47) in the Upper Namhan-gang basin are highly correlated with the streamflow percentile with 95% confidence level. Since the effect of precipitation in the basin is especially high, the correlation between evapotranspiration percentile and streamflow percentile is positive. These results indicate that remote sensing-based P-PET estimates can be used for the assessment and monitoring of hydrological drought. The high spatial resolution estimates can be used in the decision-making process to minimize the adverse impacts of hydrological drought and to establish differentiated measures coping with drought.
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