• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1123-1146
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• 2023

In South Korea, there have been many studies on efficient building-energy management using renewable energy facilities in single zero-energy houses or buildings. However, such management was limited due to spatial and economic problems. To realize a smart zero-energy city, studying efficient energy integration for the entire city, not just for a single house or building, is necessary. Therefore, this study was conducted in the eco-friendly energy town of Chungbuk Innovation City. Chungbuk successfully realized energy independence by converging new and renewable energy facilities for the first time in South Korea. This study analyzes energy data collected from public buildings in that town every minute for a year. We propose a smart city building-energy management model based on the results that combine various renewable energy sources with grid power. Supervised learning can determine when it is best to sell surplus electricity, or unsupervised learning can be used if there is a particular pattern or rule for energy use. However, it is more appropriate to use reinforcement learning to maximize rewards in an environment with numerous variables that change every moment. Therefore, we propose a power distribution algorithm based on reinforcement learning that considers the sales of Energy Storage System power from surplus renewable energy. Finally, we confirm through economic analysis that a 10% saving is possible from this efficiency.

• Steel and Composite Structures
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• v.50 no.3
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• pp.299-318
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• 2024

The main objective of this paper is to compute the far-field acoustic radiation (sound radiation) of functionally graded plates (FGM) loaded by sinusoidally varying point load subjected to the arbitrary boundary condition is carried out. The governing differential equations for thin functionally graded plates (FGM) are derived using classical plate theory (CPT) and Rayleigh integral using the elemental radiator approach. Four cases, segregated on power-law index k=0,1,5,10, are studied. A novel approach is illustrated to compute sound fields of vibrating FGM plates using the physical neutral surface with an elemental radiator approach. The material properties of the FGM plate for all cases are calculated considering the power law indexes. An in-house MATLAB code is written to compute the natural frequencies, normal surface velocities, and sound radiation fields are analytically calculated using semi-analytical formulation. Ansys is used to validate the computed sound power level. The parametric effects of the power law index, modulus ratios, different constituent of FGM plates, boundary conditions, damping loss factor on the sound power level, and radiation efficiency is illustrated. This work is the benchmark approach that clearly explains how to calculate acoustic fields using a solid layered FGM model in ANSYS ACT. It shows that it is possible to asymptotically stabilize the structure by controlling the intermittent layers' stiffness. It is found that sound fields radiated by the elemental radiators approach in MATLAB, ANSYS and literatures are in good agreement. The main novelty of this research is that the FGM plate is analyzed in the low-frequency range, where the stiffness-controlled region governs the whole analysis. It is concluded that a clamped mono-ceramic FGM plate radiates a lesser sound power level and higher radiation efficiency than a mono-metallic or metal-rich FGM plate due to higher stiffness. It is found that change in damping loss factor does not affect the same constituents of FGM plates but has significant effects on the different constituents of FGM plates.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.15 no.1
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• pp.61-74
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• 2004

Objectives：This study was performed to introduce a psychoeducational family therapy model for the families of schizophrenic patient and to investigate the effect of this model on the changes in coping style and depressive symptoms of the family members, and in perception of emotional support by families and depressive symptoms of patients. Methods：Nine preschool children, 3-5 years old, experiencing physical injuries caused by attack from a psychotic patient at kindergarten, were evaluated for psychological assessments；Intelligence test, MSSB(MacArthur Story-Stem Battery), H-T-P test(House-Tree-Person test). And their parents completed rating scale, KPI-C(Korean Personality Inventory for Children about children’s psychological conditions). Results：With respects to the contents and emotional reactions of MSSB, 9 preschool children showed generally high levels of anxiety, depression, avoidance, aggression, probably related to the traumatic experiences. Even though children couldn't verbally report directly about their traumatic experiences, in both MSSB, structured play narrative assessment tool, and HPT, free drawing and association test, they demonstrated psychiatric problems through reenactment plays, regardless of clinical diagnoses. Conclusion：Present study allowed us the chance to see beyond the outer pathological behaviors of PTSD in preschool children, through deeper evaluations of their mental representation. These preliminary data suggest deep understanding of internal representation would be of help for thorough evaluations and treatment plan for preschool children, experiencing severe trauma.

• Korean Chemical Engineering Research
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• v.49 no.2
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• pp.187-194
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• 2011

In compliance with an international law about the ocean dumping of the sludge, the proper sewage treatment process which occurs from the wastewater treatment process has been becoming problem. Generally the sewage and the sludge are controlled from anaerobic condition when the sewage is treated and land filled, where the methane$(CH_{4})$ and the nitrous oxide $(N_{2}O)$ from this process are discharged. Because these gases have been known as one of the responsible gases for global warming, the wastewater treatment process is become known as emission sources of green house gases(GHG). This study is to suggest a new approach of estimate and environmental assessment of greenhouse gas emissions and sludge emissions from wastewater treatment processes. It was carried out by calculating the total amounts of GHG emitted from biological wastewater treatment process and the amount of the sludgegenerated from the processes. Four major biological wastewater treatment processes which are Anaerobic/Anoxic/Oxidation$(A_{2}O)$, Bardenpho, Virginia Initiative Plant(VIP), University of Cape Town(UCT)are used and GPS-X software is used to model four processes. Based on the modeling result of four processes, the amounts of GHG emissions and the sludge produced from each process are calculated by Intergovernmental Panel on Climate Change(IPCC) 2006 guideline report. GHG emissions for water as well as sludge treatment processes are calculated for environmental assessment has been done on the scenario of various sludge treatments, such as composting, incineration and reclamation and each scenario is compared by using a unified index of the economic and environmental assessment. It was found that Bardenpho process among these processes shows a best process that can emit minimum amount of GHG with lowest impact on environment and composting emits the minimum amount of GHG for sludge treatment.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• Journal of the Korean earth science society
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• v.34 no.3
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• pp.209-223
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• 2013

The purpose of this study was to estimate the contributed concentration of each emission source to $CH_4$ by verifying the simulated concentration of $CH_4$ in the Korean peninsula, and then to compare the $CH_4$ emission used to the $CH_4$ simulation with that of a box model. We simulated the Weather Research Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model to estimate the mean concentration of $CH_4$ during the period of April 1 to 22 August 2010 in the Korean peninsula. The $CH_4$ emissions within the model were adopted by the anthropogenic emission inventory of both the EDGAR of the global emissions and the GHG-CAPSS of the green house gases in Korea, and by the global biogenic emission inventory of the MEGAN. These $CH_4$ emission data were validated by comparing the $CH_4$ modeling data with the concentration data measured at two different location, Ulnungdo and Anmyeondo in Korea. The contributed concentration of $CH_4$ estimated from the domestic emission sources in verification of the $CH_4$ modeling at Ulnungdo was represented in about 20%, which originated from $CH_4$ sources such as stock farm products (8%), energy contribution and industrial processes (6%), wastes (5%), and biogenesis and landuse (1%) in the Korean peninsula. In addition, one that transported from China was about 9%, and the background concentration of $CH_4$ was shown in about 70%. Furthermore, the $CH_4$ emission estimated from a box model was similar to that of the WRF-CMAQ model.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.24 no.4
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• pp.436-445
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• 2014

Objectives: Time-activity studies have become an integral part of comprehensive exposure assessment and personal exposure modeling. The aims of this study were to estimate exposure levels to nitrogen dioxide($NO_2$) and volatile organic compounds(VOCs), and to compare estimated exposures by using time-activity patterns and indoor air concentrations. Methods: The major microenvironments for office workers were selected using the Time-Use Survey conducted by the National Statistical Office in Korea in 2009. A total of 9,194 and 6,130 workers were recruited for weekdays and weekends, respectively, from the Time-Use Survey. It appears that workers were spending about 50% of their time in the house and about 30% of their time in other indoor areas during the weekdays. In addition, we analyzed the time-activity patterns of 20 office workers and indoor air concentrations in Daegu using a questionnaire and time-activity diary. Estimated exposures were compared with measured concentrations using the time-weighted average analysis of air pollutants. Conclusions: According to the time-activity pattern for the office workers, time spent in the residence indoors during the summer and winter have been shown as $11.12{\pm}2.20$ hours and $12.48{\pm}1.77$ hours, respectively, which indicates higher hours in the winter. Time spent in the office in the summer has been shown to be 1.5 hours higher than in the winter. The target pollutants demonstrate a positive correlation ($R^2=0.076{\sim}0.553$)in the personal exposure results derived from direct measurement and estimated personal exposure concentrations by applying the time activity pattern, as well as measured concentration of the partial environment to the TWA model. However, these correlations were not statistically significant. This may be explained by the difference being caused by other indoor environments, such as a bar, cafe, or diner.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5350-5355
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• 2012

Human tyrosinase (hTyr) catalyzes the first and rate limiting step in the biosynthesis of a skin color determinant, melanin. Although a number of cosmetic companies have tried to develop hTyr inhibitors for several decades, absence of 3D structure of hTyr make it impossible to design or screen inhibitors by structure-based approach. Therefore, we built a 3D structure by comparative modeling technique based on the crystal structure of tyrosinase from Bacillus megaterium to provide structural information and to search new hit compounds from database. Our model revealed that two copper atoms of active site located deep inside and were coordinated with six strictly conserved histidine residues coming from four-helix-bundle. Substrate binding site had narrow funnel like shape and its entrance was wide and exposed to solvent. In addition, hTyr-tyrosine and hTyr-kojic acid, a well-known inhibitor, complexes were modeled with the guide of solvent accessible surface generated by in-house software. Our model demonstrated that only phenol group or its analogs could fill the binding site near the nuclear copper center, because inside of binding site had narrow shape relatively. In conclusion, the results of this study may provide helpful information for designing and screening new anti-melanogenic agents.

• Investigative Magnetic Resonance Imaging
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• v.21 no.2
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• pp.65-70
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• 2017

Purpose: To optimize the saturation time and maximizing the pH-weighted difference between the normal and ischemic brain regions, on 3-tesla amide proton transfer (APT) imaging using an in vivo rat model. Materials and Methods: Three male Wistar rats underwent middle cerebral artery occlusion, and were examined in a 3-tesla magnetic resonance imaging (MRI) scanner. APT imaging acquisition was performed with 3-dimensional turbo spin-echo imaging, using a 32-channel head coil and 2-channel parallel radiofrequency transmission. An off-resonance radiofrequency pulse was applied with a Sinc-Gauss pulse at a $B_{1,rms}$ amplitude of $1.2{\mu}T$ using a 2-channel parallel transmission. Saturation times of 3, 4, or 5 s were tested. The APT effect was quantified using the magnetization-transfer-ratio asymmetry at 3.5 ppm with respect to the water resonance (APT-weighted signal), and compared with the normal and ischemic regions. The result was then applied to an acute stroke patient to evaluate feasibility. Results: Visual detection of ischemic regions was achieved with the 3-, 4-, and 5-s protocols. Among the different saturation times at $1.2{\mu}T$ power, 4 s showed the maximum difference between the ischemic and normal regions (-0.95%, P = 0.029). The APTw signal difference for 3 and 5 s was -0.9% and -0.7%, respectively. The 4-s saturation time protocol also successfully depicted the pH-weighted differences in an acute stroke patient. Conclusion: For 3-tesla turbo spin-echo APT imaging, the maximal pH-weighted difference achieved when using the $1.2{\mu}T$ power, was with the 4 s saturation time. This protocol will be helpful to depict pH-weighted difference in stroke patients in clinical settings.

• Journal of Energy Engineering
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• v.8 no.2
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• pp.224-232
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• 1999

Latent heat storage system using micro-encapsuled phase change material is effective method for floor heating of house and building. The temperature profile in capsule block and flow rate of hot water are important parameters for the development of heat storage system. In the present study, a mathematical model based on 3-D, non-steady state, Navier-Stokes equations, scalar conservation equations and turbulence model ($\kappa$-$\varepsilon$), is used to predict the temperature profiles in capsule and the velocity vectors in hot water pipe. The multi-block grids and fine grids embedding are used to join the circle in hot water pipe and square in capsule block. The phase change process of the capsule is quite complex not only because the size of phase change material is very small, but also because phase change material is mixed with the cement to form thermal storage block. In calculation, it's assumed that the phenomena of phase change is limited only the thermal properties of phase change material and the change of boundary is not happened in capsule. The purpose of this study is to calculate the temperature profiles in capsule block and velocity vectors in hot water pipe using the numerical calculation. Two kinds of thermal boundary condition were considered, the first (case 1) is the adiabatic condition for the both outside surfaces of the wall, the second (case 2) is the case in which one surface is natural convection with atmosphere and another surface is adaibatic. Calculation results are shown that the temperature profile in capsule block for case 1 is higher than that for case 2 due to less heat loss in adaibatic surface. Specially, in the domain of near Y=0, the difference of temperature is greater in case 1 than in case 2. The detailed experimental data of capsule block on the temperature profile and the thermal properties such as specific heat and coefficient of heat transfer with the various temperature are required to predict more exact phenomena of heat transfer.