In middle- and long-distance imaging systems, due to the atmospheric turbulence caused by temperature, wind speed, humidity, and so on, light waves propagating in the air are distorted, resulting in image-quality degradation such as geometric deformation and fuzziness. In remote sensing, astronomical observation, and traffic monitoring, image information loss due to degradation causes huge losses, so effective restoration of degraded images is very important. To restore images degraded by atmospheric turbulence, an image-restoration method based on improved compound multibranch feature fusion (CMFNetPro) was proposed. Based on the CMFNet network, an efficient channel-attention mechanism was used to replace the channel-attention mechanism to improve image quality and network efficiency. In the experiment, two-dimensional random distortion vector fields were used to construct two turbulent datasets with different degrees of distortion, based on the Google Landmarks Dataset v2 dataset. The experimental results showed that compared to the CMFNet, DeblurGAN-v2, and MIMO-UNet models, the proposed CMFNetPro network achieves better performance in both quality and training cost of turbulent-image restoration. In the mixed training, CMFNetPro was 1.2391 dB (weak turbulence), 0.8602 dB (strong turbulence) respectively higher in terms of peak signal-to-noise ratio and 0.0015 (weak turbulence), 0.0136 (strong turbulence) respectively higher in terms of structure similarity compared to CMFNet. CMFNetPro was 14.4 hours faster compared to the CMFNet. This provides a feasible scheme for turbulent-image restoration based on deep learning.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2021.05a
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pp.285-286
/
2021
With the recent development of Internet of Things (IoT) technology, smartization technology is expanding to the fields of agriculture, livestock, and fisheries, and smartization is in progress. In this smart technology, the most important thing is how to measure the data in the field and transmit it to the management system. Currently, the sensors used in the construction of smart farms and other livestock houses and farms are measuring and monitoring smart farms and other environmental conditions through various sensors such as temperature, humidity, CO gas, CO2, hydrogen, and O2. The communication method between these sensors and the HMI (Human Machine Interface) module that controls and manages the smart farm is still mainly using the RS-485-based modbus-RTU method. In this paper, we intend to design the MCU module for HMI so that various sensor modules can be connected to manage data through the RS-485-based Modbus method so that the sensor data required for smart farm construction can be managed by the HMI module.
Byeong-Hun Yu;Sung Do Yun;Chan Woong Na;Ji-Wook Yoon
Journal of the Korean institute of surface engineering
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v.56
no.6
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pp.393-400
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2023
Acetone, a metabolite detected from the exhaled breath of people doing a diet, can be used for non-invasive monitoring of diet efficiency. Thus, gas sensors with rapid response and recovery characteristics to acetone need to be developed. Herein, we report ultrafast acetone sensors using Ce-doped In2O3 nanoparticles prepared by the one-pot microwave-assisted hydrothermal method. The pure In2O3 sensor shows a high response and fast response time (τres = 6 s) upon exposure to 2 ppm acetone at 300 ℃, while exhibiting a relatively sluggish recovery speed (τrecov = 1129 s). When 20 wt% Ce is doped, the τrecov of the sensor significantly decreased to 45 s withholding the fast-responding characteristic (τres = 6 s). In addition, the acetone response (resistance ratio, S) of the sensor is as high as 5.8, sufficiently high to detect breath acetone. Moreover, the sensor shows similar acetone sensing characteristics even under a highly humid condition (relative humidity of 60%) in terms of τres (6 s), τrecov (47 s), and S (4.7), demonstrating its high potential in real applications. The excellent acetone sensing characteristics of Ce-doped In2O3 nanoparticles are discussed in terms of their size, composition, phase, and oxygen adsorption on the sensing surface.
Journal of the Korea institute for structural maintenance and inspection
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v.22
no.1
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pp.208-215
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2018
The causes of column shrinkage and the codes that have been studied up to now are discussed. The documents mentioned in the code deal with the drying shrinkage, creep, compressive strength and elastic modulus of the specimen, and the elastic deformation calculated from the structural analysis. However, the deformation due to the temperature caused by the long term monitoring is less than that caused by the factors generated by the previous studies. In the previous studies, it was found that dehydration shrinkage, creep, and elastic deformation were not considered for temperature-induced deformation, while for the specimen experiments, the temperature-related items were replaced with the humidity-related terms The compensation value by the proposed equation showed error of 4.9 mm in the upper direction and 1.0mm in the lower direction when calculating column shortening, and it was found that its value by the proposed equation almost coincided with the measurement value in Site. Therefore, it is necessary to further study the temperature that can be omitted in calculating the existing column shortening, to consider the influence factors, and to supplement the criteria for the temperature measurement of the structure as well as the specimen tests.
In this paper, we propose the real time indoor air quality monitoring and controlling platform on cloud using IoT sensor data such as PM10, PM2.5, CO2, VOCs, temperature, and humidity which has direct or indirect impact to indoor air quality. The system is connected to air ventilator to manage and optimize the indoor air quality. The proposed system has three main parts; First, IoT data collection service to measure, and collect indoor air quality in real time from IoT sensor network, Second, Big data processing pipeline to process and store the collected data on cloud platform and Finally, Big data analysis and visualization service to give real time insight of indoor air quality on mobile and web application. For the implication of the proposed system, IoT sensor kits are installed on three different public day care center where the indoor pollution can cause serious impact to the health and education of growing kids. Analyzed results are visualized on mobile and web application. The impact of ventilation system to indoor air quality is tested statistically and the result shows the proper optimization of indoor air quality.
Particulate matter (PM) that has been artificially generated during the recent of rapid industrialization and urbanization moves and disperses according to weather conditions, and adversely affects the human skin and respiratory systems. The purpose of this study is to predict the PM10 concentration in Seoul using meteorological factors as input dataset for multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) models, and compared and evaluated the performance of the models. First, the PM10 concentration data obtained at 39 air quality monitoring sites (AQMS) in Seoul were divided into training and validation dataset (8:2 ratio). The nine meteorological factors (mean, maximum, and minimum temperature, precipitation, average and maximum wind speed, wind direction, yellow dust, and relative humidity), obtained by the automatic weather system (AWS), were composed to input dataset of models. The coefficients of determination (R2) between the observed PM10 concentration and that predicted by the MLR, SVM, and RF models was 0.260, 0.772, and 0.793, respectively, and the RF model best predicted the PM10 concentration. Among the AQMS used for model validation, Gwanak-gu and Gangnam-daero AQMS are relatively close to AWS, and the SVM and RF models were highly accurate according to the model validations. The Jongno-gu AQMS is relatively far from the AWS, but since PM10 concentration for the two adjacent AQMS were used for model training, both models presented high accuracy. By contrast, Yongsan-gu AQMS was relatively far from AQMS and AWS, both models performed poorly.
From April 29 to 30, 2011, under the influence of Asian dust originated from Mongolia, a high concentration of Asian dust was observed nationwide for 4 days in Korea. This study investigated the causes and characteristics of and weather conditions associated with Asian dust at high concentrations at its source in Mongolia. For analysis, Asian dust weather data, Asian dust monitoring tower data, satellite data, backward trajectory data, observation data (PM10 and OPC data), and ECMWF reanalysis data were used. In the synoptic analysis, it was observed that the intervals of isobars were densely distributed in the central region of Mongolia and the pressure gradient force was strong. It could be inferenced that Asian dust occurred due to strong winds. The temperature was relatively high, above 10℃, just before the occurrence of Asian dust, and it decreased sharply at the onset of the dust. The relative humidity had a low value of less than approximately 40%. After the occurrence of Asian dust, it increased sharply to over 50% and then showed a tendency to decrease. In the aerosol index shown by the COMS satellite, a high concentration value of over 25 was detected in Inner Mongolia, and it was consistent with the observations made with naked eyes. In the 72-hour backward trajectory, the northwest airflow streamed into Korea, and on May 2, Heuksando showed the highest PM10 concentration of 1,025 ㎍ m-3(times the average). Especially, in kinematic vertical analysis, it was observed that low pressure on the ground was strengthened by cyclonic relative vorticity developed in the upper layer. Also, the vertical velocity development is considered to have played a major role in the occurrence of high concentration Asian dust.
The Korea Forest Service(KFS) has been initiating restoration activities of ridgeline in damaged and fragmented areas of Baekdudaegan since 2011. Completed project in Ihwaryeong, Yuksimnyeong & Beoljae(2012; 2013) were selected as sites for this study. The changes in microclimate condition, vegetation composition and soil properties between project sites and adjacent stands were compared to evaluate the effect of restoration at early stage(after 2years). Pinus densiflora was planted mainly for these restoration sites, however Robinia pseudoacacia and Alnus sibirica invaded the area two years after the restoration activities. Ihwaryeong showed the most changes in understory vegetation among the study sites. Exotic species, such as Ambrosia artemisiifolia, Oenothera odorata, Erigeron annuus, and Coreopsis tinctoria invaded Ihwaryeong, and the dominance have invaded currently. It resulted from the poor survival rate of trees and high difference in microclimate wherein there's an increased temperature and decreased humidity in both restored sites and adjacent stands. In addition, it is also caused by poor soil chemical property, especially pH and organic matter content due to lack of humus layer and its accumulation, compared to adjacent forest soil in restored sites. Significant difference on chemical soil property was observed between restored sites and adjacent forest but no significant difference was observed after two years of restoration. Ecological monitoring is needed to understand the ecological changes after restoration and to establish a long-term management strategy.
Journal of the Korean Association of Geographic Information Studies
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v.18
no.3
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pp.63-75
/
2015
As forest therapy is getting more attention than ever, it is important to organize time for activity and location based on spatio-temporal distribution of weather condition in forest. This study aimed to analyze precise spatio-temporal distribution of weather condition by installing long-term weather monitoring device in Yonghyun national natural recreation forest and using acquired weather data in order to support forest recreation and therapy activity. First, we statistically compared 4 models of semi-variogram and the results were all similar. We selected and analyzed the circular model for this study because it was presumed to be the best model for this case. We derived 128 results from the circular model and through semi-variogram, we identified seasonal and temporal distributions of temperature and humidity. Then, we used boxplot, made of partial sill level, to identify significant differences in seasonal and temporal distributions. As a result, in spring and early morning, both temperature and humidity showed equalized result. On the other hand, in summer and early afternoon, both temperature and humidity showed uneven result. In spring and early morning, changes in weather condition are shown little from spatial shifting, it is ideal to perform recreational activities and forest therapy but in summer and early afternoon, it is unadvisable to do so as the changes in weather condition could be harmful unless any other means of preparations are made. This study proposes its significance by analyzing seasonal micro-weather of single recreation forest and presenting seasonal and temporal outcomes.
In this study, after analyzing several local climate characteristics of South Korea, I validated distribution, invasion, foraging, underground activities, attack season as ecological characteristics and also temperature, relative humidity, and tree species as preference characteristics of Korean termites (Reticulitermes speratus kyushuensis Morimoto). Especially, southern part of the Korean peninsula is a suitable area for inhabitation and motion of termites holding same ecological characteristic like R. speratus kyushuensis. Busan is a neighboring district at field distribution north limiting temperature of Coptotermes formosanus Shiraki and Chuncheon is a passing area through the Korean Peninsula of field distribution north limiting temperature of Reticulitermes speratus Kolbe. The termite attack of wood devices was about 34.5% for 3 years in the forest of Jongmyo. Although the attack rate of termite increased each year, the detection rate decreased and the missing rate was high by degrees. I confirmed a foraging habits which is a part of termite colony was a role of continuous decomposition and another was a role of new food hunt as experimental results. The foraging termites were found under ground at Jongmyo in Seoul from April to November in the 2001 and the most active period was on July and August. The termite invasion rate of bait station increased in every monitoring. Through the increasing attack rate of bait station during 2nd monitoring (November, 2000) and 3rd monitoring(March, 2001), I confirmed that termites moved into the deep underground in winter, and were working continuously to forage. R. speratus kyushuensis inhabiting at the Korean Peninsula is a species which has food consumption rate with higher temperature. The termite revealed the greatest amount of food(filter paper) at $30^{\circ}C$(90% RH), but showed increasing death rate at over $32^{\circ}C$. Also, survival rate of this termite was 97% at 84% RH($30^{\circ}C$), but killed 100% at 52% RH($30^{\circ}C$) and 70% RH($30^{\circ}C$). For wood feeding, this was observed the preference in a pine tree(Pinus densiflora) above all others. Survival of termites was high(87%) at a pine tree, but low(13.5%) at a paulownia tree(Paulownia coreana). In this study, I presented the biological characteristic of termite(R. speratus kyushuensis Morimoto) and confirmed the deterioration degree of termite on wooden cultural heritage in Korea. Depending on climate and soil temperature, each area in the southern part of the Korea Peninsula, has some different active period and different distribution of R. speratus kyushensis. With these results, I expect that this report helps to prepare the integrated pest management(IPM) of the termite on wooden cultural heritage in Korea, and it may help to reduce the economical loss from termite damage in Korea.
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