• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1181-1191
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• 2013

This study have implemented finding the optimal water temperature parameter set for Hapcheon dam reservoir using CE-QUAL-W2 model. In particular the sensitivity analysis was carried out for four water temperature parameters of wind sheltering coefficient (WSC), radiation heat coefficient (BETA), light extinction coefficient (EXH2O), heat exchange coefficient at the channel bed (CBHE). Firstly, WSC, BETA, EXH2O shows relatively high sensitivity in common during April to September, and CBHE does during August to November. Secondly, as a result of identifying depth range of parameter influence, BETA and EXH2O show 0~9 m and 8~14 m which is thermocline layer close to water surface, CBHE is deep layer 12 m away from bottom. Finally, applying annual or monthly optimal parameter sets indicates that the bias between two sets does not show much differences for WSC and CBHE parameters, but BETA and EXH2O parameters show $0.20^{\circ}C$ and $0.51^{\circ}C$ of monthly average biases for two parameter sets. In particular the bias reveals to be $0.4^{\circ}C$ and $1.09^{\circ}C$ during May and August that confirms the necessity of use of monthly parameters during that season. It is claimed that the current operational custom use of annual parameters in calibration of reservoir water quality model requires the improvement of using monthly parameters.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.10
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• pp.916-927
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• 2010

In general water treatment process, the disinfection process by chlorine is used to prevent water borne disease and microbial regrowth in water distribution system. Because chlorines were reacted with organic matter, carcinogens such as disinfection by-products (DBPs) were produced in drinking water. Therefore, a suitable injection of chlorine is need to decrease DBPs. Rechlorination in water pipelines or reservoirs are recently increased to secure the residual chlorine in the end of water pipelines. EPANET 2.0 developed by the U.S. Environmental Protection Agency (EPA) is used to compute the optimal chlorine injection in water treatment plant and to predict the dosage of rechlorination into water distribution system. The bulk decay constant ($k_{bulk}$) was drawn by bottle test and the wall decay constant ($k_{wall}$) was derived from using systermatic analysis method for water quality modeling in target region. In order to predict water quality based on hydraulic analysis model, residual chlorine concentration was forecasted in water distribution system. The formation of DBPs such as trihalomethanes (THMs) was verified with chlorine dosage in lab-scale test. The bulk decay constant ($k_{bulk}$) was rapidly decreased with increasing temperature in the early time. In the case of 25 degrees celsius, the bulk decay constant ($k_{bulk}$) decreased over half after 25 hours later. In this study, there were able to calculate about optimal rechlorine dosage and select on profitable sites in the network map.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.25-32
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• 2021

In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.

• 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.

• Proceedings of the Korea Society of Poultry Science Conference
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• 2004.11a
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• pp.80-90
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• 2004

Three experiments were performed to test the assumption that imbalanced dietary amino acid mixtures must lead to increased heat production (HP). The first experiment was based on diets formulated to have a wide range of crude protein (CP) concentrations but a fixed concentration of lysine, formulated to be the first-limiting amino acid. In the second (converse) experiment, lysine concentration was varied over a wide range while CP content was kept constant. To prevent the masking of dietary effects by thermoregulatory demands, the third experiment was performed at 30 $^{\circ}C$ with the diets similar to the diets used in the second experiment. The detailed relationships among amino acid balance, nitrogen (N) metabolism and energy (E) metabolism were investigated in a computer-controlled chamber calorimetry system. The results of experiments were compared with the predictions of a computerised simulation model of E metabolism. In experiment 1. with constant lysine and varying CP, there was a 75 % increase in N intake as CP concentration increased. This led to a 150 % increase in N excretion. with no significant change in HP. Simulated HP agreed with the empirically determined results in not showing a trend with dietary CP. In experiment 2, with varying lysine but constant CP, there was a 3-fold difference in daily weight gain between the lowest and highest lysine diets. HP per bird increased significantly with dietary lysine concentration. There was still an effect when HP was adjusted for body weight differences, but it failed to maintain statistical significance. Simulated HP results agreed in showing little effect of varying lysine concentration and growth rate on HP. Based on the results of these two experiments, the third experiment was designed to test the response of birds to dietary lysine in high ambient temperature. In experiment 3 which performed at high ambient temperature (30 $^{\circ}C$), HP per bird increased significantly with dietary lysine content, whether or not adjusted for body-weight. The trend was greater than in the previous experiment (20 $^{\circ}C$).

• Journal of the Society of Disaster Information
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• v.9 no.4
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• pp.449-461
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• 2013

As the hydrofluoric acid leak in Gumi-si, Gyeongsangbuk-do or hydrochloric acid leak in Ulsan, Gyeongsangnam-do demonstrated, chemical related accidents are mostly caused by large amounts of volatile toxic substances leaking due to the damages of storage tank or pipe lines of transporter. Safety assessment is the most important concern because such toxic material accidents cause human and material damages to the environment and atmosphere of the surrounding area. Therefore, in this study, a hydrofluoric acid leaked from a storage tank was selected as the study example to simulate the leaked substance diffusing into the atmosphere and result analysis was performed through the numerical Analysis and diffusion simulation of ALOHA(Areal Location of Hazardous Atmospheres). the results of a qualitative evaluation of HAZOP (Hazard Operability)was looked at to find that the flange leak, operation delay due to leakage of the valve and the hose, and toxic gas leak were danger factors. Possibility of fire from temperature, pressure and corrosion, nitrogen supply overpressure and toxic leak from internal corrosion of tank or pipe joints were also found to be high. ALOHA resulting effects were a little different depending on the input data of Dense Gas Model, however, the wind direction and speed, rather than atmospheric stability, played bigger role. Higher wind speed affected the diffusion of contaminant. In term of the diffusion concentration, both liquid and gas leaks resulted in almost the same $LC_{50}$ and ALOHA AEGL-3(Acute Exposure Guidline Level) values. Each scenarios showed almost identical results in ALOHA model. Therefore, a buffer distance of toxic gas can be determined by comparing the numerical analysis and the diffusion concentration to the IDLH(Immediately Dangerous to Life and Health). Such study will help perform the risk assessment of toxic leak more efficiently and be utilized in establishing community emergency response system properly.

• Korean journal of applied entomology
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• v.59 no.2
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• pp.93-107
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• 2020

Adults of seven noctuid potential pests (Spodoptera frugiperda, S. litura, S. exigua, Ctenoplusia agnata, Mythimna loreyi, Athetis dissimilis, and A. lepigone) of soybean and maize in Suwon, Korea were identified by their morphological characteristics in the wing pattern and male genitalia and partial mitochondrial DNA sequences of cytochrome c oxidase subunit 1 gene. The generation number of adults that emerge annually in six species (except A. lepigone) was estimated from the data on density fluctuations of adults caught in sex pheromone traps in 2019 and the forecasted data using temperature-associated development and reproduction models for those species. S. frugiperda adults were caught from July 27th to October 31st in 2019, and hence were initially estimated to emerge three times per year. But, it was finally expected that S. frugiperda adults could possibly emerge a total of four times per year in Suwon, considering larval emergence observed during mid- and late June in other areas. Adult emergence of S. litura, S. exigua, C. agnata, and M. loreyi in 2019 was observed from May 29th to November 6th, from May 14th to November 6th, from May 26th to October 25th, and from May 31st to November 23rd, respectively. Annual adult emergence of these four species was estimated as at least four times. Adults of A. dissimilis were caught from May 26th to September 11th in 2019, and adult emergence was estimated at only twice per annum. It was postulated that the first adult populations of five species except the two Athetis species were probably migrated from other areas.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.57-67
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• 2020

Pinus densiflora is the most widely distributed tree species in South Korea. Its ecological and socio-cultural attributes makes it one of the most important tree species in S. Korea. In recent times however, the distribution of P. densiflora has been affected by dieback. This phenomenon has largely been attributed to climate change. This study was conducted to investigate the responses of growth and physiology of P. densiflora to drought and nitrogen fertiliz ation according to the RCP 8.5 scenario. A Temperature Gradient Chamber (TGC) and CO₂. Temperature Gradient Chamber (CTGC) were used to simulate climate change conditions. The treatments were established with temperature (control versus +3 and +5℃; aCeT) and CO₂ (control: aCaT versus x1.6 and x2.2; eCeT), watering(control versus drought), fertilization(control versus fertilized). Net photosynthesis (P_n), stomatal conductance (g_s), biomass and relative soil volumetric water content (VWC) were measured to examine physiological responses and growth. Relative soil VWC in aCeT significantly decreased after the onset of drought. P_n and g_s in both aCeT and eCeT with fertiliz ation were high before drought but decreased rapidly after 7 days under drought because nitrogen fertilization effect did not last long. The fastest mortality was 46 days in aCeT and the longest survival was 56 days in eCeT after the onset of drought. Total and partial biomass (leaf, stem and root) in both aCeT and eCeT with fertiliz ation were significantly high, but significantly low in aCeT. The results of the study are helpful in addressing P. densiflora vulnerability to climate change by highlighting physiological responses related to carbon allocation under differing simulated environmental stressors.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.55-64
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• 2019

The flowering seasons can be advanced due to climate change that would cause an abnormally warm winter. Such warm winter would increase the frequency of crop damages resulted from sudden occurrences of low temperature before and after the vegetative growth stages, e.g., the period from germination to flowering. The degree and pattern of freezing damage would differ by the development stage of each individual fruit tree even in an orchard. A critical temperature, e.g., killing temperature, has been used to predict freeze damage by low-temperature conditions under the assumption that such damage would be associated with the development stage of a fruit flower bud. However, it would be challenging to apply the critical temperature to a region where spatial variation in temperature would be considerably high. In the present study, a phenological model was used to estimate major bud development stages, which would be useful for prediction of regional risks for the freeze damages. We also derived a linear function to calculate a probabilistic freeze risk in spring, which can quantitatively evaluate the risk level based solely on forecasted weather data. We calculated the dates of freeze damage occurrences and spatial risk distribution according to main production areas by applying the spring freeze risk function to apple, peach, and pear crops in 2018. It was predicted that the most extensive low-temperature associated freeze damage could have occurred on April 8. It was also found that the risk function was useful to identify the main production areas where the greatest damage to a given crop could occur. These results suggest that the freezing damage associated with the occurrence of low-temperature events could decrease providing early warning for growers to respond abnormal weather conditions for their farm.

• Korean Chemical Engineering Research
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• v.60 no.4
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• pp.535-543
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• 2022

A CPFD (Computational particle fluid dynamics) model of solar fluidized bed receiver of silicon carbide (SiC: average d_p=123 ㎛) particles was established, and the model was verified by comparing the simulation and experimental results to analyze the effect of particle behavior on the performance of the receiver. The relationship between the heat-absorbing performance and the particles behavior in the receiver was analyzed by simulating their behavior near bed surface, which is difficult to access experimentally. The CPFD simulation results showed good agreement with the experimental values on the solids holdup and its standard deviation under experimental condition in bed and freeboard regions. The local solid holdups near the bed surface, where particles primarily absorb solar heat energy and transfer it to the inside of the bed, showed a non-uniform distribution with a relatively low value at the center related with the bubble behavior in the bed. The local solid holdup increased the axial and radial non-uniformity in the freeboard region with the gas velocity, which explains well that the increase in the RSD (Relative standard deviation) of pressure drop across the freeboard region is responsible for the loss of solar energy reflected by the entrained particles in the particle receiver. The simulation results of local gas and particle velocities with gas velocity confirmed that the local particle behavior in the fluidized bed are closely related to the bubble behavior characterized by the properties of the Geldart B particles. The temperature difference of the fluidizing gas passing through the receiver per irradiance (∆T/I_DNI) was highly correlated with the RSD of the pressure drop across the bed surface and the freeboard regions. The CPFD simulation results can be used to improve the performance of the particle receiver through local particle behavior analysis.