• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.339-351
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• 2011

This study investigates the potentials of satellite, ground measurement data, and geo-spatial information within an urban area for the mapping of the Urban Environmental Quality (UEQ) parameters. The UEQ indicates a complex and various parameters resulting from both human and natural factors, which are greenness, climate, air pollution, the urban infrastructure, and etc. Multi-spectral remote sensing data from the Landsat ETM and TM sensors for the mapping of air pollution by the Haze Optimized Transform (HOT) technique, Urban Heat Island (UHO using the emissivity-fusion method in Seoul from 2000 to 2006 in fine resolution (30m) were analyzed for the estimation of UEQ index. Although the UHI values are similar ($8.4^{\circ}C{\sim}9.1^{\circ}C$) during these years, the spatial coverage of "hot" surface temperature (> $24^{\circ}C$) significantly increased from 2000 to 2006 due to the rapid urban development. Furthermore, high correlations between vegetation index and land surface temperature were achieved with a correlation coefficients of 0.85 (2000), 0.81 (2001), 0.84 (2002), and 0.89 (2006), respectively. It was found that the proposed method was successfully analyzed spatial structure of the UEQ and the scenarios of the best and worst areas within the city were also identified. Based on the quantifiable fine resolution satellite image parameters, UEQ can promote the understanding of the complex and dynamic factors controlling urban environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.938-945
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• 2004

On the relationship between the red tide occurrence and the oceanographic factors in the middle coastal area in the South Sea of Korea, the favorable oceanographic conditions for the red tide formation are considered as follows； the calm weather increases sea water temperature in summer and early-fall which the red tide occurs frequently, and the heavy precipitation brings some riverine water to ween: low salinity, high suspended solid, low phosphorus and high nitrogen, respectively. We decided the potential areas in the coastal zones vulnerable to the red tide occurrence based on the limited factors controlling the growth of phytoplankton. By using GIS through the overlap for three subject figures (phosphorus, nitrogen and suspended solids), it was founded that the potential areas are the Yeosu∼Dolsan coast, the Gamak bay, the Namhae coast, the Narodo coast, the Goheung and Deukryang bay. This result has very well coincided to the results of the satellite and in-situ data.

• Journal of Navigation and Port Research
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• v.35 no.5
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• pp.387-392
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• 2011

The value of Photovoltaic as an independent power supply is small, but the city's carbon emissions reduction and for the reduction of fossil fuel use distributed power is the power source to a very high value. However, according to the weather conditions for solar power generation by power fluctuations because of the size distribution to be effective, the big swing for effectively controlling real-time monitoring should be made. But that depends on solar power generation solar radiation forecasts from the National Weather Service does not need to predict it, and this study, the diffuse sky radiation in the history of the solar radiation in the darkness of the clouds, thick and weather forecasts can be inferred from the atmospheric transmittance to announce this value is calculated to represent each weather forecast solar radiation and solar radiation predicted by substituting the expression And the measured solar radiation and CRM (Cloud Cover Radiation Model) technique with an expression of Kasten and Czeplak irradiation when compared to the calculated predictions were verified.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1243-1248
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• 2018

Metal Powder Metallurgy is a manufacturing technology that makes unique model parts or a certain type of product by using a hardening phenomenon when a powder of metal or metal oxide is put it into a mold and compression-molded by a press and then heated and sintered at a high temperature. Powder metallurgical press equipment is mainly used to make the parts of automobile, electronic parts and so on, and most of them are manufactured using precise servo motor. The intelligent precision servo control powder molding press system which is designed and implemented in this paper has advantages of lowering the price and maintaining the precision by using the mechanical camshaft for the upper ram part and precisely controlling the lower ram part using the high precision servo system. In addition, OPC-based monitoring and process data collection systems are designed and implemented to provide scalability that can be applied to smart manufacturing management systems that utilize Big Data in the future.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.381-401
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• 2023

Purpose: The purpose of this study was to understand the perception of medical staff to propose an infected patient transport robot as a means of responding to infectious diseases. Methods: The data collected through the survey was analyzed through AHP analysis. The measurement tools used in this study were derived through the SERVQUAL model and Focus Group Interview(FGI), and consisted of four detailed questions for each of five classes: tangible, reliability, responsiveness, assurance, and empathy. Results: As a result of the study, there are concerns about risk factors that may occur in areas where medical staff intervention is minimized. Above all, we confirmed the consensus that safety should be the top priority during the process of robots to transport patients. In particular, highlighted were the resolution of device errors that may occur during the process for transporting patients and easy provision of the first aid. Additionally, the ability to monitor patients and suppress infection factors turned out to be important, which was directly related to the simplification of the role of medical staff and work efficiency. Conclusion: As one of the means of effectively controlling infectious diseases in a pandemic situation, a robot to transport the infected patient was considered. However, in order to commercialize this, specific verification of the safety of medical staff and patients is needed, and empirical data on providing the first aid, patient monitoring, and infection factor suppression should be presented.

• Journal of Soil and Groundwater Environment
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• v.11 no.5
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• pp.1-8
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• 2006

The objective of this study is to assess impacts of sorption heterogeneity on the transport of leachate leaked from unlined landfill sites and is accomplished by examining the results from a series of Monte-Carlo simulations. For random distribution coefficient ($K_{d}$) fields with four different levels of heterogeneity ranging from homogeneous to highly heterogeneous, the transport of leachate was investigated by linking a saturated flow model with a contaminant transport model. Impacts of a chemical heterogeneity were evaluated using point statistics values such as mean, standard deviation, and coefficient of variation of the concentration obtained at monitoring wells from 100 Monte-Carlo trials. Inspection of point statistics shows that the distribution of distribution coefficient in the landfill site proves to be an important parameter in controlling leachate concentrations. In comparison to homogeneous sorption, heterogeneous $K_{d^-}$ fields produce the variability in the leachate concentration for different realizations. The variability increases significantly as the variance in the $K_{d^-}$ field and the travel time between source and monitoring well increase. These outcomes indicate that use of a constant homogeneous $K_{d}$ value for predicting the transport of leachate can result in significant error, especially when variability in $K_{d}$ is high.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.229-235
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• 2013

This paper proposed the method to reduce and manage the amount of using power by using the Self-Learning of inference engine that evolves through learning increasingly smart ways for each spaces with in the Space-Based Energy Management System (SEMS, Space-based Energy Management System) that is defined as smallest unit space with constant size and similar characteristics by using the collectible Big Data from the various information networks and the informations of various sensors from the existing Energy Management System(EMS), mostly including such as the Energy Management Systems for the Factory (FEMS, Factory Energy Management System), the Energy Management Systems for Buildings (BEMS, Building Energy Management System), and Energy Management Systems for Residential (HEMS, Home Energy Management System), that is monitoring and controlling the power of systems through various sensors and administrators by measuring the temperature and illumination.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.184-191
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• 2010

In the environment of 450mm wafers production known as the next-generation semiconductor production process, one of the most significant features is the full automation over the whole manufacturing processes involved. The full automation system for 450mm wafer production will minimize the human workers' involvement in the manufacturing process as much as possible. In addition, since the importance of an individual wafer processing increases noticeably, it is necessary to develop more robust scheduling systems in the whole manufacturing process than so ever. The scheduling systems for the next-generation semiconductor production processes also should be capable of monitoring individual wafers and collecting useful data on them in real time. Based on the information gathered from these processes, the system should finally have a real-time scheduling functions controlling whole the semiconductor manufacturing processes. In this study, preliminary investigations on the requirements and needed functions for constructing the real time scheduling system and transforming manufacturing environments for 300mm wafers to those of 400mm are conducted and through which the next generation semiconductor processes for efficient scheduling in a clustered production system architecture of the scheduler is proposed. Our scheduling architecture is composed of the modules for real-time scheduling, the clustered production type supporting, the optimal scheduling and so on. The specifications of modules to define the major required functions, capabilities, and the relationship between them are presented.

• Journal of Korean Society on Water Environment
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• v.32 no.6
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• pp.528-536
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• 2016

The purpose of Total Pollution Load Control at Tributary is to obtain maximum improvement effect of water quality through finding the most impaired section of water-body and establishing the proper control measure of pollutant load. This study was implemented to determine the optimal management of reach, period, condition, watershed, and pollution source and propose appropriate reduction practices using the Load duration curve (LDC) and field monitoring data. With the data of measurement, LDC analysis shows that the most impaired condition is reach V (G4~G5), E group (flow exceedance percentile 90~100%) and winter season. For this reason, winter season and low flow condition should be preferentially considered to restore water quality. The result of pollution analysis for the priority reach and period shows that agricultural nonpoint source loads from onion and garlic culture are most polluting. Therefore, it is concluded that agricultural reuse of surface effluent (storm-water runoff with non-point sources) and low impact farming that includes reducing fertilization and controlling the height of drainage outlet are efficient water quality management for this study watershed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.373-379
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• 2019

Smart-farm has been spreading across Korea to improve the labor efficiency and productivity of greenhouse crops. Although notable improvements have been made in the monitoring technologies and environmental-controlling systems in greenhouses, only a few simple decision-support systems are available for predicting the optimum environmental conditions for crop growth. In this study, a tomato growth model (GreenTom), which was developed by Seoul National University in 1997, was calibrated and validated to examine if the model can be used as a decision-supporting system. The original GreenTom model was not able to simulate artificial defoliation, which resulted in overestimation of the leaf area index in the late growth. Thus, an algorithm for simulating the artificial defoliation was developed and added to the original model. The node development, leaf growth, stem growth, fruit growth, and leaf area index were generally well simulated by the modified model indicating that the model could be used effectively in the decision-making of smart greenhouse.