RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.
It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.
Kim, Ki-Dong;Lee, Tae-Jung;Jung, Won-Seok;Kim, Dong-Sool
Journal of Korean Society for Atmospheric Environment
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v.28
no.3
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pp.233-248
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2012
The national emission from energy sector accounted for 84.7% of all domestic emissions in 2007. Of the energy-use emissions, the emission from mobile source as one of key categories accounted for 19.4% and further the road transport emission occupied the most dominant portion in the category. The road transport emissions can be estimated on the basis of either the fuel consumed (Tier 1) or the distance travelled by the vehicle types and road types (higher Tiers). The latter approach must be suitable for simultaneously estimating $CO_2$, $CH_4$, and $N_2O$ emissions in local administrative districts. The objective of this study was to estimate 31 municipal GHG emissions from road transportation in Gyeonggi Province, Korea. In 2008, the municipalities were consisted of 2,014 towns expressed as Dong and Ri, the smallest administrative district unit. Since mobile sources are moving across other city and province borders, the emission estimated by fuel sold is in fact impossible to ensure consistency between neighbouring cities and provinces. On the other hand, the emission estimated by distance travelled is also impossible to acquire key activity data such as traffic volume, vehicle type and model, and road type in small towns. To solve the problem, we applied a hierarchical cluster analysis to separate town-by-town road patterns (clusters) based on a priori activity information including traffic volume, population, area, and branch road length obtained from small 151 towns. After identifying 10 road patterns, a rule building expert system was developed by visual basic application (VBA) to assort various unknown road patterns into one of 10 known patterns. The expert system was self-verified with original reference information and then objects in each homogeneous pattern were used to regress traffic volume based on the variables of population, area, and branch road length. The program was then applied to assign all the unknown towns into a known pattern and to automatically estimate traffic volumes by regression equations for each town. Further VKT (vehicle kilometer travelled) for each vehicle type in each town was calculated to be mapped by GIS (geological information system) and road transport emission on the corresponding road section was estimated by multiplying emission factors for each vehicle type. Finally all emissions from local branch roads in Gyeonggi Province could be estimated by summing up emissions from 1,902 towns where road information was registered. As a result of the study, the GHG average emission rate by the branch road transport was 6,101 kilotons of $CO_2$ equivalent per year (kt-$CO_2$ Eq/yr) and the total emissions from both main and branch roads was 24,152 kt-$CO_2$ Eq/yr in Gyeonggi Province. The ratio of branch roads emission to the total was 0.28 in 2008.
An area's topography refers to the shape of the earth's surface, described by its elevation, slope, and aspect, among other features. The topographical conditions determine energy flowsthat move water and energy from higher to lower elevations, such as how much solar energy will be received and how much wind or rain will affect it. Another common factor, the topographic wetness index (TWI), is a calculation in digital elevation models of the tendency to accumulate water per slope and unit area, and is one of the most widely referenced hydrologic topographic factors, which helps explain the location of forest vegetation. Analyses of topographical factors can be calculated using a geographic information system (GIS) program based on digital elevation model (DEM) data. Recently, a large number of free open source software (FOSS) GIS programs are available and developed for researchers, industries, and governments. FOSS GIS programs provide opportunitiesfor flexible algorithms customized forspecific user needs. The majority of biodiversity in island areas exists at about 20% higher elevations than in land ecosystems, playing an important role in ecological processes and therefore of high ecological value. However, island areas are vulnerable to disturbances and damage, such as through climate change, environmental pollution, development, and human intervention, and lacks systematic investigation due to geographical limitations (e.g. remoteness; difficulty to access). More than 4,000 of Korea's islands are within a few hours of its coast, and 88% are uninhabited, with 52% of them forested. The forest ecosystems of islands have fewer encounters with human interaction than on land, and therefore most of the topographical conditions are formed naturally and affected more directly by weather conditions or the environment. Therefore, the analysis of forest topography in island areas can be done more precisely than on its land counterparts, and therefore has become a major focus of attention in Korea. This study is focused on calculating the performance of different topographical factors using FOSS GIS programs. The test area is the island forests in Korea's south and the DEM of the target area was processed with GRASS GIS and SAGA GIS. The final slopes and TWI maps were produced as comparisons of the differences between topographic factor calculations of each respective FOSS GIS program. Finally, the merits of each FOSS GIS program used to calculate the topographic factors is discussed.
A delta is a depositional landform that is formed when sediment transported by a river is deposited in a relatively low-energy environment, such as a lake, sea, or a main channel. Among these, a delta formed at the confluence of rivers has a great importance in river management and research because it has a significant impact on the hydraulic and sedimentological characteristics of the river. Recently, the equilibrium state of the confluence area has been disrupted by large-scale dredging and construction of levees in the Nakdong River. However, due to the natural recovery of the river, the confluence area is returning to its pre-dredging natural state through ongoing sedimentation. The time-series data show that the confluence delta has been steadily growing since the dredging, but once it reaches a certain size, it repeats growth and retreat, and the overall size does not change significantly. In this study, we developed a model to explain the sedimentation-erosion processes in the confluence area based on the assumption that the confluence delta reaches a dynamic equilibrium. The model is based on two fundamental principles: sedimentation due to supply from the tributary and erosion due to the main channel. The erosion coefficient that represents the Nakdong River confluence areas, was obtained using data from the tributaries of the Nakdong River. Sensitivity analyses were conducted using the developed model to understand how the confluence delta responds to changes in the sediment and water discharges of the tributary and the main channel, respectively. We then used annual average discharge of the Nakdong River's tributaries to predict the dynamic equilibrium positions of the confluence deltas. Finally, we conducted a simulation experiment on the development of the Gamcheon-Nakdong River delta using recorded daily discharge. The results showed that even though it is a simple model, it accurately predicted the dynamic equilibrium positions of the confluence deltas in the Nakdong River, including the areas where the delta had not formed, and those where the delta had already formed and predicted the trend of the response of the Gamcheon-Nakdong River delta. However, the actual retreat in the Gamcheon-Nakdong River delta was not captured fully due to errors and limitations in the simplification process. The insights through this study provide basic information on the sediment supply of the Nakdong River through the confluence areas, which can be implemented as a basic model for river maintenance and management.
KIPS Transactions on Computer and Communication Systems
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v.1
no.3
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pp.143-150
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2012
A simulation methodology and corresponding program based on it is to be discussed for analyzing the effects of the networking operation of existing DHC system in connection with CHP system on-site. The practical simulation for arbitrary areas with various building compositions is carried out for the analysis of operational features in both systems, and the various aspects of thermal energy grids with connecting operation are highlighted through the detailed assessment of predicted results. The intrinsic operational features of CHP prime movers, gas engine, gas turbine etc., are effectively implemented by realizing the performance data, i.e. actual operation efficiency in the full and part loads range. For the sake of simplicity, a simple mathematical correlation model is proposed for simulating various aspects of change effectively on the existing DHC system side due to the connecting operation, instead of performing cycle simulations separately. The empirical correlations are developed using the hourly based annual operation data for a branch of the Korean District Heating Corporation (KDHC) and are implicit in relation between main operation parameters such as fuel consumption by use, heat and power production. In the simulation, a variety of system configurations are able to be considered according to any combination of the probable CHP prime-movers, absorption or turbo type cooling chillers of every kind and capacity. From the analysis of the thermal network operation simulations, it is found that the newly proposed methodology of mathematical correlation for modelling of the existing DHC system functions effectively in reflecting the operational variations due to thermal energy grids with connecting operation. The effects of intrinsic features of CHP prime-movers, e.g. the different ratio of heat and power production, various combinations of different types of chillers (i.e. absorption and turbo types) on the overall system operation are discussed in detail with the consideration of operation schemes and corresponding simulation algorithms.
Journal of Korean Society of Environmental Engineers
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v.32
no.7
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pp.690-698
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2010
Contamination of groundwater resources by organic chemicals has become an issue of increasing environmental concern. Surfactant-enhanced aquifer remediation (SEAR) is widely recognized as one of the most promising techniques to remediate organic contaminations in-situ. Solutions of surfactant or surfactant with polymer are used to dramatically expedite the process, which in turn, may reduce the treatment time of a site compared to use of water alone. In the design of surfactant-based technologies for remediation of organic contaminated aquifers, it is very important to have a considerable analysis using extensive numerical simulations prior to full-scale implementation. This study investigated the formation and flow of microemulsions during SEAR of organic-contaminated aquifer using the finite difference model UTCHEM, a three-dimensional, multicomponent, multiphase, compositional model. The remediation process variables considered in this study were the sequence of injection fluids, the injection and extraction rate, the concentrations of polymer in surfactant slug and chase water, and the duration of surfactant injection. For each variable, temporal changes in injection and production wells and spatial distributions of relative saturations in the organic phase were compared. Cleanup time and cumulative organic recovery were also quantified. The study would provide useful information to design strategies for the remediation of nonaqueous phase liquid-contaminated aquifers.
Lignite of low rank coal and petroleum coke of high sulfur content can be high potential energy sources for coal gasification process because of their plentiful supply. The kinetic study of steam gasification has been performed in an atmospheric thermobalance with wood chip, lignite, bituminous, anthracite, pet-coke. The effects of gasification temperature($600{\sim}850^{\circ}C$) and partial pressure of steam(30~90 kPa) on the gasification rate have been investigated. The modified volumetric reaction model was applied to the experimental data to describe the behavior of carbon conversion and to evaluate the needed kinetic parameters. Lignite and wood chip with high volatile content showed high average gasification rates comparing to other fuel and thus they might be proper fuel for gasification processes. The activation energies for wood chip, lignite, bituminous, anthracite, and pet-coke through Arrhenius plot were found to be 260.3, 167.9, 134.6, 82.2, 168.9 kJ/mol, respectively. The expression of apparent reaction rates for steam gasification of various chars have been proposed as basic information for the design of coal gasification processes.
Journal of the Korean Society for Advanced Composite Structures
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v.2
no.4
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pp.1-10
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2011
This study investigates the performance of composite (steel-concrete) frame structures through numerical experiments on individual connections. The innovative aspects of this research are in the use of connections between steel beams and concrete-filled tube (CFT)columns that utilize a combination of low-carbon steel and shape memory alloy (SMA) components. In these new connections, the intent is to utilize the recentering provided by super-elastic shape memory alloy tension bars to reduce building damage and residual drift after a major earthquake. The low-carbon steel components provide excellent energy dissipation. The analysis and design of these structures is complicated because the connections cannot be modeled as being simply pins or full fixity ones they are partial restraint (PR). A refined finite element (FE) model with sophisticated three dimensional (3D) solid elements was developed to conduct numerical experiments on PR-CFT joints to obtain the global behavior of the connection. Based on behavioral information obtained from these FE tests, simplified connection models were formulated by using joint elements with spring components. The behavior of entire frames under cyclic loads was conducted and compared with the monotonic behavior obtained from the 3D FE simulations. Good agreement was found between the simple and sophisticated models, verifying the robustness of the approach.
The shape of land surface work as a cradle for various environmental processes and human activities. As spatially distributed process modelings become increasing important in current research communities, a classification system that delineates land surface into characteristic geomorphological units is a pre-requisite for sustainable land use planning and management. Existing classification systems are either morphometric or generic, which have limitations to characterize continuous ecological processes over the landscape. A new classification system was developed to delineate the land surface into different geomorphological units from Digital Elevation Models(DEMs). This model assumes that there are pedo-geomorphological units in which distinct sets of hydrological, pedological, and consequent ecological processes occur. The classification system first divides the whole landsurface into eight soil-landscape units. Possible energy and material nows over the land surface were interpreted using a continuity equation of mass flow along the hillslope, and subsequently implemented in terrain analysis procedures. The developed models were tested at a 12$\textrm{km}^2$ area in Yangpyeong-gun, Kyeongi-do, Korea. The method proposed effectively delineates land surface into distinct pedo-geomorphological units, which identify the geomorphological characteristics over a large area at a low cost. The delineated landscape units mal provide a basic information for natural resource survey and environmental modeling practices.
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