• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.316-326
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• 2014

Determination of the late marginal heading date (LMHD), which would allow estimation of the late marginal seeding date and the late marginal transplanting date, would help identification of potential double cropping areas and, as a result, establishment of cropping systems. The objective of this study was to determine the LMHD at 51 sites in Korea. For these sites, weather data were obtained from 1971 to 2000 and from 1981 to 2010, which represent past and current normal climate conditions, respectively. To examine crop productivity on the LMHD, climatic yield potential (CYP) was determined to represent the potential yield under a given climate condition. The LMHD was calculated using accumulated temperature for 40 days with threshold values of $760^{\circ}C$, $800^{\circ}C$, $840^{\circ}C$ and $880^{\circ}C$. The value of CYP on a given LMHD was determined using mean temperature and sunshine duration for 40 days from the LMHD. The value of CYP on the LMHD was divided by the maximum value of CYP (CYPmax) in a season to represent the relative yield on the LMHD compared with the potential yield in the season. Our results indicated that the LMHD was delayed at most sites under current normal conditions compared with past conditions. Spatial variation of the LMHD differed by the threshold temperature. Overall, the minimum value of CYP/CYPmax was 81.8% under all of given conditions. In most cases, the value of CYP/CYPmax was >90%, which suggested that yield could be comparable to the potential yield even though heading would have occurred on the LMHD. When the LMHD could be scheduled later without considerable reduction in yield, the late marginal transplanting date could also be delayed accordingly, which would facilitate doublecropping in many areas in Korea. Yield could be affected by sudden change of temperature during a grain filling period. Yet, CYP was calculated using mean temperature and sunshine duration for 40 days after heading. Thus, the value of CYP/CYPmax may not represent actual yield potential due to change of the LMHD, which suggested that further study would be merited to take into account the effect of weather events during grain filling periods on yield using crop growth model and field experiments.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.1
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• pp.73-87
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• 2018

A variety of micro meteorological variables such as air temperature, wind, solar radiation and latent heat at Gwangneung forests (conifer and broadleaved forests) and AWS (Automated Weather Station) of Pocheon urban area were used to quantify the air temperature reduction effect of forests, which is considered to be an eco-friendly solution for reducing the urban heat island intensity during summer. In June, July and August of 2016 and 2017, the average maximum air temperature differences between above and below canopy of forests, and between the forests and urban areas were $-1.9^{\circ}C$ and $-3.4^{\circ}C$ respectively, and they occurred at 17:00. However, there was no difference between conifer and broadleaved forests. The effect of air temperature reduction by the forests was positively correlated with accumulated evapotranspiration and solar radiation from 14:00 to 17:00 and showed a negative correlation with wind speed. We have developed a model to quantify the effect of air temperature reduction by forests using these variables. The nighttime air temperature reduction effect by forests was due to the generation of cold air from radiative cooling and the air temperature inversion phenomenon that occurs when the generated cold air moves down the side of mountain. The model was evaluated in Seoul by using 28 AWSs. The evaluation shows that the air temperature of each district in Seoul was negatively correlated with the area and size of the surrounding tall vegetation that drives vegetation evapotranspiration during the day. During the night, however, the size of the surrounding tall vegetation and the elevations of nearby mountains were the main influencing factors on the air temperature. Our research emphasizes the importance of the establishment and management of urban forests and the composition of wind roads from mountains for urban air temperature reduction.

• Journal of the Korean earth science society
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• v.37 no.7
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• pp.420-433
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• 2016

The purpose of this study is to improve the calibration matrixes of 2-D and 3-D convective rainfall rates (CRR) using the brightness temperature of the infrared $10.8{\mu}m$ channel (IR), the difference of brightness temperatures between infrared $10.8{\mu}m$ and vapor $6.7{\mu}m$ channels (IR-WV), and the normalized reflectance of the visible channel (VIS) from the COMS satellite and rainfall rate from the weather radar for the period of 75 rainy days from April 22, 2011 to October 22, 2011 in Korea. Especially, the rainfall rate data of the weather radar are used to validate the new 2-D and 3-DCRR calibration matrixes suitable for the Korean peninsula for the period of 24 rainy days in 2011. The 2D and 3D calibration matrixes provide the basic and maximum CRR values ($mm\;h^{-1}$) by multiplying the rain probability matrix, which is calculated by using the number of rainy and no-rainy pixels with associated 2-D (IR, IR-WV) and 3-D (IR, IR-WV, VIS) matrixes, by the mean and maximum rainfall rate matrixes, respectively, which is calculated by dividing the accumulated rainfall rate by the number of rainy pixels and by the product of the maximum rain rate for the calibration period by the number of rain occurrences. Finally, new 2-D and 3-D CRR calibration matrixes are obtained experimentally from the regression analysis of both basic and maximum rainfall rate matrixes. As a result, an area of rainfall rate more than 10 mm/h is magnified in the new ones as well as CRR is shown in lower class ranges in matrixes between IR brightness temperature and IR-WV brightness temperature difference than the existing ones. Accuracy and categorical statistics are computed for the data of CRR events occurred during the given period. The mean error (ME), mean absolute error (MAE), and root mean squire error (RMSE) in new 2-D and 3-D CRR calibrations led to smaller than in the existing ones, where false alarm ratio had decreased, probability of detection had increased a bit, and critical success index scores had improved. To take into account the strong rainfall rate in the weather events such as thunderstorms and typhoon, a moisture correction factor is corrected. This factor is defined as the product of the total precipitable waterby the relative humidity (PW RH), a mean value between surface and 500 hPa level, obtained from a numerical model or the COMS retrieval data. In this study, when the IR cloud top brightness temperature is lower than 210 K and the relative humidity is greater than 40%, the moisture correction factor is empirically scaled from 1.0 to 2.0 basing on PW RH values. Consequently, in applying to this factor in new 2D and 2D CRR calibrations, the ME, MAE, and RMSE are smaller than the new ones.

• Korean Journal of Food Science and Technology
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• v.50 no.4
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• pp.420-429
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• 2018

Skin ageing is associated with compromised performance of its fundamental barrier functions, with undesirable changes in appearance. Since this may introduce a detrimental impact on the quality of life, significant effort to discover effective ingredients against ageing is being invested. Recently, collagen hydrolysates containing tripeptides such as GlyPro-Hyp (GPH) have been developed with anticipation of improved effects compared to that of existing collagen hydrolysate-products. To evaluate the cutaneous hydration effect of collagen tripeptides (CTP), meaningful biomarkers in human dermal fibroblasts (HDF) and NC/Nga Tnd mice were analyzed in this study. Increased levels of ceramide kinase, hyaluronic acid, collagen 1A, and hyaluronan synthase-2 (HAS2), and decreased levels of hyaluronidase-1 (HYAL1) and CD44 in HDF cells were demonstrated. Furthermore, significant reduction of transepidermal water loss (TEWL), scratching behavior, HYAL1, $TNF-{\alpha}$ and IL-6 and increased water content and HAS2 were verified by in vivo tests. These results strongly suggest the potential of CTP as a skin hydration agent.

• Journal of the Korea Organic Resources Recycling Association
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• v.24 no.1
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• pp.21-29
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• 2016

We mix food waste leachate and sewage sludge by the proportion of 1:9, 3:7 and 5:5. It turns out that they produced 233, 298 and 344 $CH_4{\cdot}mL/g{\cdot}VS$ of methane gas. The result suggests that as the mixing rate of food waste leachate rises, the methane gas productions increases as well. And more methane gas is made when co-digesting sewage sludge and food waste leachate based on the mixing ratio, rather than digesting only sewage sludge alone. Modified Gompertz and Exponential Model describe the BMP test results that show how methane gas are produced from organic waste. According to the test, higher the mixing rate of food waste leachate is, higher the methane gas productions is. The mixing ratio of food waste leachate that produces the largest volume of methane gas is 3:7. Modified Gompertz model and Exponential model describe the test results very well. The correlation values($R^2$) that show how the results of model prediction and experiment are close is 0.92 to 0.98.

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.228-240
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• 2018

Solar energy is calculated using meteorological (14 station), ceilometer (2 station) and microwave radiometer (MWR, 7 station)) data observed from the Weather Information Service Engine (WISE) on the Seoul metropolitan area. The cloud optical thickness and the cloud fraction are calculated using the back-scattering coefficient (BSC) of the ceilometer and liquid water path of the MWR. The solar energy on the surface is calculated using solar radiation model with cloud fraction from the ceilometer and the MWR. The estimated solar energy is underestimated compared to observations both at Jungnang and Gwanghwamun stations. In linear regression analysis, the slope is less than 0.8 and the bias is negative which is less than $-20W/m^2$. The estimated solar energy using MWR is more improved (i.e., deterministic coefficient (average $R^2=0.8$) and Root Mean Square Error (average $RMSE=110W/m^2$)) than when using ceilometer. The monthly cloud fraction and solar energy calculated by ceilometer is greater than 0.09 and lower than $50W/m^2$ compared to MWR. While there is a difference depending on the locations, RMSE of estimated solar radiation is large over $50W/m^2$ in July and September compared to other months. As a result, the estimation of a daily accumulated solar radiation shows the highest correlation at Gwanghwamun ($R^2=0.80$, RMSE=2.87 MJ/day) station and the lowest correlation at Gooro ($R^2=0.63$, RMSE=4.77 MJ/day) station.

• Korean Journal of Construction Engineering and Management
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• v.19 no.2
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• pp.15-24
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• 2018

Despite the recognition of the need for productivity information and its importance, the feedback of productivity information is not well-established in the construction industry. Effective use of productivity information is required to improve the reliability of construction planning. However, in many cases, on-site productivity information is hardly management effectively, but rather it relies on the experience and/or intuition of project participants. Based on the literature review and expert interviews, the authors recognized that one of the possible solutions is to develop a systematic approach in dealing with productivity information of the construction job-sites. It is required that the new system should not be burdensome to users, purpose-oriented information management, easy-to follow information structure, real-time information feedback, and productivity-related factor recognition. Based on the preliminary investigations, this study proposed a framework for a novel system that facilitate the effective management of construction productivity information. This system has utilized Sketchup software which has good user accessibility by minimizing additional data input and related workload. The proposed system has been designed to input, process, and output the pertinent information through a four-stage process: preparation, input, processing, and output. The inputted construction information is classified into Task Breakdown Structure (TBS) and Material Breakdown Structure (MBS), which are constructed by referring to the contents of the standard specification of building construction, and converted into productivity information. In addition, the converted information is also graphically visualized on the screen, allowing the users to use the productivity information from the job-site. The productivity information management system proposed in this study has been pilot-tested in terms of practical applicability and information availability in the real construction project. Very positive results have been obtained from the usability and the applicability of the system and benefits are expected from the validity test of the system. If the proposed system is used in the planning stage in the construction, the productivity information and the continuous information is accumulated, the expected effectiveness of this study would be conceivably further enhanced.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.20 no.3
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• pp.131-140
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• 2015

To set up unicellular cyanobacterial strains with photo-biological $H_2$ production potential, live samples were repeatedly collected from 68 stations in the coastal zone of Korea for the four years since 2005. Among 77 cyanobacterial strains established six (KNU strains, CB-MAL002, 026, 031, 054, 055 and 058) were finally chosen as the excellent strains for $H_2$ production with $H_2$ accumulation over 0.15 mL $H_2\;mL^{-1}$ under general basic $H_2$ production conditions as well as positive $H_2$ production for more than 60 hr. To explore optimum procedures for higher $H_2$ production efficiency of the six cyanobacterial strains, the inter-strain differences in the growth rate under the gradients of water temperature and salinity were investigated. The maximum daily growth rates of the six strains ranged from 1.78 to 2.08, and all of them exhibited $N_2-fixation$ ability. Based on the similarity of the 16S rRNA sequences, all the test strains were quite close to Cyanothece sp. ATCC51142 (99%). The six strains, however, were grouped into separate clades from strain ATCC51142 in the molecular phylogeny diagram. Chlorophyll- a content was 3.4~7.8% of the total dried weight, and the phycoerythrin and phycocyanin contents were half of those in the Atlantic strain, Synechococcus sp. Miami BG03511. The growth of the six strains was significantly suppressed at temperatures above the optimal range, $30{\sim}35^{\circ}C$, to be nearly stopped at $40^{\circ}C$. The growth was not inhibited by high salinities of 30 psu salinity in all the strains while strain CB055 maintained its high growth rate at low salinities down to 15 psu. The euryhaline strains like CB055 might support massive biotechnological cultivation systems using natural basal seawater in temperate latitudes. base seawater. The biological and ecophysiological characteristics of the test strains may contribute to designing the optimal procedures for photo-biological $H_2$ production by unicellular cyanobacteria.

• Korean journal of applied entomology
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• v.53 no.4
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• pp.375-380
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• 2014

The sweetpotato whitefly (SPW), Bemisia tabaci Gennadius, is a major pest in tomato greenhouses on Jeju Island because they transmit viral diseases. To develop practical sampling methods for adult SPWs, yellow-color sticky traps were used in commercial tomato greenhouses throughout the western part of Jeju Island in 2011 and 2012. On the basis of the size and growing conditions in the tomato greenhouses, 20 to 30 traps were installed in each greenhouse for developing a sampling plan. Adult SPWs were more attracted to horizontal traps placed 60 cm above the ground than to vertical trap placed 10 cm above the plant canopy. The spatial patterns of the adult SPWs were evaluated using Taylor's power law (TPL) and Iwao's patchiness regression (IPR). The results showed that adult SPWs were aggregated in each surveyed greenhouse. In this study, TPL showed better performance because of the coefficient of determination ($r^2$). On the basis of the fixed-precision level sampling plan using TPL parameters, more traps were required for higher precision in lower SPW densities per trap. A sequential sampling stop line was constructed using TPL parameters. If the treatment threshold was greater than 10 maximum adult SPWs on a trap, the required traps numbered 15 at a fixed-precision level of 0.25. In estimating the mean density per trap, the proportion of traps with two or more adult SPWs was more efficient than whole counting: ${\ln}(m)=1.19+0.90{\ln}(-{\ln}(1-p_T))$. The results of this study could be used to prevent the dissemination of SPW as a viral disease vector by using accurate control decision in SPW management programs.