This study was conducted to find ways to control environment with the difference between body temperature and background temperature based on swine activity, and to apply to the environment control system of swine barns based on the findings. Following are the results. 1. Swine activity related to background temperature was achieved as color images and swine activity status was categorized into cold, comfortable, and hot periods with visualization system (thermal image system). 2. Thermal image system consisted of an infrared CCD camera, an image processing board - DIF (TH3100), an main computer (400Hz, 128M, 586 Pentium model) with C++ program installed. 3. Thermal image system categorizing temperatures into cold, comfortable, and hot was applicable to the environment control system of swine barns 4. Feed intake was higher in cold temperature, and finishing weight and weight gain per day in cold temperature were lower than others (p<0.05).
Journal of the Korea Academia-Industrial cooperation Society
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v.17
no.9
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pp.745-752
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2016
In the era of the Internet of Things, where all physical objects are connected to the Internet, we suggest a remote control system using a Raspberry Pi single-board computer with ZigBee, which can turn an indoor light-emitting diode (LED) and a multiple-tap on and off, and with a smart phone can control the brightness of the LED as well as an electronic door lock. By connecting an infrared (IR) transmitter module to the Raspberry Pi, we can control home appliances, such as an air conditioner, and we can also monitor indoor images, indoor temperatures, and illumination by using a smart phone app. We developed a method of finding out IR transmission codes required for remote-controllable appliances with an AVR micro-controller. We suggest a method to remotely open and shut an office door by novating the door lock. The brightness level of an LED (between 0 and 10) can be controlled through a PWM signal generated by an ATmega88 microcontroller. A mutiple-tap is controlled using an ATmega32, a photo-coupler, and a TRIAC. The signals for measured temperature and illumination are converted from analog to digital by using the ATtiny44A microcontroller transmitting to a Raspberry Pi through SPI communication. Then, we connect a camera to the CSI head of the Raspberry Pi. We can turn on the smart multiple-tap for a certain period of time, or we can schedule the multi-tap to turn on at a specific time. To reduce standby power, people usually pull out a power code from multiple-taps or turn off a switch. Our method helps people do the same thing with a smart phone, if they are away from home.
The objectives of this investigation are : 1. To analyze spectral signature and the associated vegetation index for geometric illumination conditions inf1uenced by low solar elevation and high slope orientations in mountainous forest. 2. To assess the accuracy of the spectral angle mapper classification for the a winter land cover in comparison with the maximum likelihood classification. 3. To produce the image of water quality and water properties that could be used to estimate the water pollution sources and the tide-included by turbid water in estuarine and coastal areas. These objectives are to characterize environmental and ecological monitoring applications of the Nak-Dong River Basin by using Fuyo-1 OPS VNIR data acquired on December 26, 1992. The results of this paper are as follows : 1. The spectral digital numbers and vegetation indexes (NDVI and TVI) of mountainous forest are higher on the slope facing the sun than on the slope hidden the sun under low sun elevation condition. 2. The spectral angle mapper algorithm produces a more accurate land cover classification of areas with steep slope, various aspects and low solar elevation than the maximum likelihood classifier. 3. The maximum likelihood classification images can be used for identifying the location and movement of both freshwater and salt water, regardless of geometric illumination conditions. 4. The color-coded density sliced image of selected water bodies by using the near-infrared band 3 can provide distribution of the water quality of the Lower Nak-Dong River. 5. The color-coded normalized difference vegetation index image of the selected mountain forest is suitable to classify winter vegetation cover types, i.e., forest canopy densities for slope orientations.
Objectives: The purpose of this study is to analyse the domestic trends of Traditional Korean Medicine on Hot flush in menopausal women. Methods: We searched six databases and selected relevant papers according to the criteria. Results: 12 papers included case report, literature review, randomized controlled clinical trials (RCTs), Non-RCTs, and retrospective chart analysis study design. 1. The daily diary, Kupperman's Index, Menopause Rating Scale, Menopause-specific Quality of Life Questionnaire, Digital Infrared Thermographic Imaging were used as a measure of the symptoms of hot flush. 2. There were significant correlations between Thermographic images, Pulse energy, Lifestyle Habits, Low frequency power/High frequency power (LF/HF) ratio and certain items of Menopausal Symptoms Measurement. 3. The case report using Er-Xian decoction and Hwangryunhaedoktang-Gamibang showed significant effect. 4. Domestic RCT studies using herbal or acupuncture treatments showed a significant value of 3.4 on average in the quality assessment conducted in the study. However, the number of domestic studies included was five, which is not enough compared to foreign countries. Conclusions: This study examined domestic research trends on hot flushes of menopausal women and found that various evaluation tools and diagnostic methods were applied. It is necessary to conduct various RCT studies in Korea, where the number of studies is insufficient compared to overseas.
Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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v.9
no.6
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pp.701-709
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2019
Recently, heart rate signal, which is one of biological signals, have been used in various fields related to healthcare. Conventionally, most of the proposed heart rate signal detection methods are contact type methods, but there is a problem of discomfort that the subject have to contact with the device. In order to solve the problem, detection study by non-contact method has been progressed recently. The detected heart rate signal can be used for finger vein liveness detection and various application using heart rate. In this paper, we propose a method to obtain heart rate signal by using finger vein imaging system. The proposed method detected the signal from the changes of the brightness value in the time domain of the infrared finger vein images and converted it into the frequency domain using the image processing algorithm. After the conversion, we removed the noise not related to the heart rate signal through band-pass filtering. In order to evaluate the accuracy of the signal, we analyzed the correlation with the signal obtained simultaneously with the finger vein acquisition device and contact type PPG sensor approved by KFDA. As a result, it was possible to confirm that the heart rate signal detected in non-contact method through the finger vein image coincides with the waveform of actual heart rate signal.
Journal of the Korean Association of Geographic Information Studies
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v.24
no.2
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pp.52-63
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2021
In previous research, the coastal wetlands were detected by using the vegetation indices or land cover classification maps derived from the multispectral bands of the satellite or aerial imagery, and this approach caused the various limitations for detecting the coastal wetlands with high accuracy due to the difficulty of acquiring both land cover and topographic information by using the single remote sensing data. This research suggested the efficient methodology for detecting the coastal wetlands using the sentinel-2 satellite image and SRTM(Shuttle Radar Topography Mission) DEM (Digital Elevation Model) acquired in Gomsoman Bay, west coasts of South Korea through the following steps. First, the NDWI(Normalized Difference Water Index) image was generated using the green and near-infrared bands of the given Sentinel-2 satellite image. Then, the binary image that separating lands and waters was generated from the NDWI image based on the pixel intensity value 0.2 as the threshold and the other binary image that separating the upper sea level areas and the under sea level areas was generated from the SRTM DEM based on the pixel intensity value 0 as the threshold. Finally, the coastal wetland map was generated by overlaying analysis of these binary images. The generated coastal wetland map had the 94% overall accuracy. In addition, the other types of wetlands such as inland wetlands or mountain wetlands were not detected in the generated coastal wetland map, which means that the generated coastal wetland map can be used for the coastal wetland management tasks.
The impacts of ice clouds on the energy budget of the Earth and their representation in climate models have been identified as important and unsolved problems. Ice clouds consist almost exclusively of non-spherical ice crystals with various shapes and sizes. To determine the influences of ice clouds on solar and infrared radiation as required for remote sensing retrievals and numerical models, knowledge of scattering and microphysical properties of ice crystals is required. A conventional method for representing the radiative properties of ice clouds in satellite retrieval algorithms and numerical models is to combine measured microphysical properties of ice crystals from field campaigns and pre-calculated single-scattering libraries of different shapes and sizes of ice crystals, which depend heavily on microphysical and scattering properties of ice crystals. However, large discrepancies between theoretical calculations and observations of the radiative properties of ice clouds have been reported. Electron microscopy images of ice crystals grown in laboratories and captured by balloons show varying degrees of complex morphologies in sub-micron (e.g., surface roughness) and super-micron (e.g., inhomogeneous internal and external structures) scales that may cause these discrepancies. In this study, the current idealized models representing morphologies of ice crystals and the corresponding numerical methods (e.g., geometric optics, discrete dipole approximation, T-matrix, etc.) to calculate the single-scattering properties of ice crystals are reviewed. Current problems and difficulties in the calculations of the single-scattering properties of atmospheric ice crystals are addressed in terms of cloud microphysics. Future directions to develop physically consistent ice-crystal models are also discussed.
Journal of the Korea Society of Computer and Information
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v.27
no.2
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pp.33-42
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2022
In this paper, we proposed a deep learning model based on multi-scale dilated convolution feature fusion for the segmentation of black ice region in road image to send black ice warning to drivers in real time. In the proposed multi-scale dilated convolution feature fusion network, different dilated ratio convolutions are connected in parallel in the encoder blocks, and different dilated ratios are used in different resolution feature maps, and multi-layer feature information are fused together. The multi-scale dilated convolution feature fusion improves the performance by diversifying and expending the receptive field of the network and by preserving detailed space information and enhancing the effectiveness of diated convolutions. The performance of the proposed network model was gradually improved with the increase of the number of dilated convolution branch. The mIoU value of the proposed method is 96.46%, which was higher than the existing networks such as U-Net, FCN, PSPNet, ENet, LinkNet. The parameter was 1,858K, which was 6 times smaller than the existing LinkNet model. From the experimental results of Jetson Nano, the FPS of the proposed method was 3.63, which can realize segmentation of black ice field in real time.
The utilization of multispectral imaging systems (MIS) in remote sensing has become crucial for large-scale agricultural operations, particularly for diagnosing plant health, monitoring crop growth, and estimating plant phenotypic traits through vegetation indices (VIs). However, environmental factors can significantly affect the accuracy of multispectral reflectance data, leading to potential errors in VIs and crop status assessments. This paper reviewed the complex interactions between environmental conditions and multispectral sensors emphasizing the importance of accounting for these factors to enhance the reliability of reflectance data in agricultural applications.An overview of the fundamentals of multispectral sensors and the operational principles behind vegetation index (VI) computation was reviewed. The review highlights the impact of environmental conditions, particularly solar zenith angle (SZA), on reflectance data quality. Higher SZA values increase cloud optical thickness and droplet concentration by 40-70%, affecting reflectance in the red (-0.01 to 0.02) and near-infrared (NIR) bands (-0.03 to 0.06), crucial for VI accuracy. An SZA of 45° is optimal for data collection, while atmospheric conditions, such as water vapor and aerosols, greatly influence reflectance data, affecting forest biomass estimates and agricultural assessments. During the COVID-19 lockdown,reduced atmospheric interference improved the accuracy of satellite image reflectance consistency. The NIR/Red edge ratio and water index emerged as the most stable indices, providing consistent measurements across different lighting conditions. Additionally, a simulated environment demonstrated that MIS surface reflectance can vary 10-20% with changes in aerosol optical thickness, 15-30% with water vapor levels, and up to 25% in NIR reflectance due to high wind speeds. Seasonal factors like temperature and humidity can cause up to a 15% change, highlighting the complexity of environmental impacts on remote sensing data. This review indicated the importance of precisely managing environmental factors to maintain the integrity of VIs calculations. Explaining the relationship between environmental variables and multispectral sensors offers valuable insights for optimizing the accuracy and reliability of remote sensing data in various agricultural applications.
Song Heung-Kwon;Kwon Kyung-Tae;Park Cheol-Su;Yang Oh-Nam;Kim Min-Su;Kim Jeong-Man
The Journal of Korean Society for Radiation Therapy
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v.17
no.2
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pp.125-131
/
2005
Purpose : 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 performed using the Respiratory gating system and its clinical effectiveness was evaluated. Materials and Methods : 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. Results : 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 ($30{\sim}60%$), while that was 9.4 mm in full phases ($0{\sim}90%$) and for patient #2, it was reduced to 2.3 mm in treatment phases ($30{\sim}70%$), while it was 11.7 mm in full phases ($0{\sim}90%$). 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.
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