This study investigates the behavioral characteristic difference of the container volumes of three ports-Gwangyang, Incheon, and Pyeongtaek-Dangjin. All series span the period January 2003 to December 2011. I first test whether the series are stationary or not. I can reject the null hypothesis of a unit root in each of the level variables and of a unit root for the residuals from the cointegration at the 5 percent significance level. I hitherto make use of error-correction model and find that Gwangyang port is the slowest in adjusting the short-run disequilibrium, whereas the adjustment speed of Incheon is much faster than that of Gwangyang. The impulse response functions indicate that container volumes increase only a little to the negative shocks in exchange rate, while they respond positively to the shocks in the business activity in a great magnitude and decay very slowly to its pre-shock level. meaning that the shocks last very long. The accumulative response to the exchange rate increase of 20 won per dollar and the 5 point industrial production increase is the smallest in Gwangyang, no more than a half of that of two ports. The intervention-ARIMA models also forecast that Gwangyang port will have much lower growth rate than Incheon and Pyeongtaek-Dangjin port in trading volumes.
In order to describe runoff characteristics of urban drainage area, outflow from subbasins divided by considering topography and flow path, is analyzed through stormwater system. In doing so, concentration time and time-area curve change significantly according to basin shape, and runoff characteristics are changed greatly by these attributes. Therefore, in this development study of FFC2Q model by MLTM, we aim to improve the accuracy in analyzing runoff by adding a module that considers basin shape, giving it an advantage over popular urban hydrology models, such as SWMM and ILLUDAS, that can not account for geometric shape of a basin due to their assumptions of unit subbasin as having a simple rectangular form. For subbasin shapes, symmetry types (rectangular, ellipse, lozenge), divergent types (triangle, trapezoid), and convergent types (inverted triangle, inverted trapezoid) have been analyzed in application of time-area curve for surface runoff analysis. As a result, we found that runoff characteristic can be quite different depending on basin shape. For example, when Gunja basin was represented by lozenge shape, the best results for peak flow discharge and overall shape of runoff hydrograph were achieved in comparison to observed data. Additionally, in case of considering subbasin shape, the number of division of drainage basin did not affect peak flow magnitude and gave stable results close to observed data. However, in case of representing the shape of subbasins by traditional rectangular approximation, the division number had sensitive effects on the analysis results.
This study was aimed for bettering productivity and technical level of the dental 1 aboratory, and helping the dental technician's benefits and rights, and then endowing them some belonged atmospher and stability on their post by Improving job- satisfaction and maintaining the transferability of one's post at a proper limitation. Therefore, 320 dental technicians extracted randomly from all the technicians working at 494 dental laboratories were subjected for this study. The approach to the study was a way through some postal questionaires executed from March 29, 1988 until May 4, the same year, in which total 254 technicians answered, showing 79% resp"nserate. responserate. The data-analysis was done by a model of the dental technician's transferability from their post, as considering Mobley's(1978)-model of post-transferability, and results through the study are as follows : 1. Satisfaction at a given post showed that the married is better than the unmarried(<0.05), and the experienced is better than the inexperienced(P<0.01). 2. Age, sex, educational experience, and one's service-duration did not affect significantly to the respondent's satisfaction on their post, statistically. 3. Satisfaction at a given post differed in adccordance with given conditions of one's post, i. e.,it stowed high when the monthly payment was good(P<0.05), and when too much duty on their job was given, it was the worst as shown in an example of the next order, too much
The Transactions of The Korean Institute of Electrical Engineers
/
v.60
no.3
/
pp.639-647
/
2011
In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.
Journal of the Korean Society of Environmental Restoration Technology
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v.7
no.2
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pp.75-86
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2004
This study aims to figure out ecological characteristic of natural forests focusing on vegetation as a way of ecological renovation for the restoration of naturalness for golf courses that were constructed in the Country and to present vegetation models and appropriate tree species for the purpose. The study site is P golf club, which is located in Gapyong-gun, Kyeonggi Province. The site is within a forest where the grade from the natural ecology map is the first one and the level from the green index accounts for the eight, thus showing a typical environment for a golf course in terms of location. The location of the site explains a reason for restoration. The major substance of the study is to conduct ecological evaluation of vegetation structures around and inside the golf course and to present a vegetation model. In order to evaluate the ecological characteristics of the vegetation structures, the analysis of the study covered succession stages, multi-layer vegetation structures and species diversity. Plant communities that have high species diversity were selected for the vegetation model and proper density and species were proposed considering the number of species and individuals and distances between trees. The vegetation restoration model targets succession into an oak forest. Within a unit of 100 $m^2$, the recommended model include a tall-tree layer with 11 trees such as Quercus serrata and Quercus mongolica, a sub-tall-tree layer with 12 trees including Quercus mongolica, Quercus serrata, Prunus sargentii, Fraxinus rhynchophylla and Acer pseudo sieboldianum, a shrub layer with 32 trees from 16 species, and a grass layer with a cover rate of 45 %. The proposed vegetation restoration model needs to apply to : 1) damaged natural forests by the construction of golf courses; 2) boundaries between golf courses and surrounding forests; 3) buffer zones; 4) open spaces in between courses; and 5) areas between greens and tees where open spaces are available in a mass. In conclusion, one of the most important factors in presenting a vegetation model for the restoration of naturalness in the golf course and other damaged forests is to provide multi-layer vegetation structures that are composed of native species. As for the specific application for the site, it is recommended to manage the vegetation in such a way that the environment of the site can have a similar environment to the surrounding forest which is expected to succeed into an oaks-dominant one.
Kim, Ji-Min;Kim, Chang-Hoon;Kim, Do-Sam;Hur, Dong-Soo
Journal of Korean Society of Coastal and Ocean Engineers
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v.19
no.1
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pp.57-65
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2007
Shallow water waves are hindcasted from sea wind fields, which include wave transformations such as shoaling, refraction, diffraction, reflection and wave breaking. In case of estimating sea wind field in shallow water, the sea wind revised from free wind obtained by the typhoon model is widely used. However, this method is not able to consider the effect of land topography on the wind field, which will be important factor for shallow water wave forecasting and hindcasting. In this study, therefore, the effect of land topography on sea wind field in shallow water is investigated for shallow water wave forecasting and hindcasting with high accuracy. The 3-D MASCON model is introduced to consider the influence of land topography on the wind field. And, for two areas divided by the topographical characteristics, i.e. shielded and opened coastal areas, sea wind field is examined by comparison between initial wind field by typhoon model and modified wind field by 3-D MASCON model. Finally, applying these sea wind fields to SWAN model, the results of shallow water wave calculated in shielded and opened coastal areas are compared, and, also, the effect of MASCON model on shallow water wave forecasting and hindcasting is discussed.
Air drying was carried out on 15 Korean red pine logs to provide a prediction model of the moisture content (MC) change in the wood during drying. The final MC was 17.4% after 880 days since the beginning of air drying in the summer for 6 Korean red pine logs with 68.7% initial MC. The final MC was 16.0% after 760 days since the beginning of air drying in the winter for 9 Korean red pine logs with 35.8% initial MC. A regression model with R-squared of 0.925 was obtained as a result of multiple regression analyses with initial MC, top diameter, temperature, relative humidity, and wind speed as independent variable and and MC change during air drying as dependent variable. The initial MC and top diameter, which is the characteristic of Korean red pine, have greater effect on the MC decrease during air drying compared to meteorological factors such as the temperature, relative humidity, and wind speed. Two-dimensional mass transfer analysis was performed to predict the MC distribution of Korean red pine logs during air drying. Two prediction models with different air drying days and different meteorological factors for the determination of the diffusion coefficient and surface emission coefficient were presented. The error between the different two methods ranged from 0.1 to 0.8% and the difference from the measured value ranged from 2.2 to 3.6%. By measuring the internal MC during air drying of Korean pine logs with various initial MC and diameter, and calculating the moisture transfer coefficient in wood for each meteorological condition, the error of the prediction model can be reduced.
Purpose: The purpose is to establish a safe facility environment from abnormal voltages such as lightning by developing a smart land resistance measuring device that can acquire real-time land resistance data using Arduino. Method: This paper studied design models and application cases by developing a land resistance acquisition and analysis system with Arduino and a power line communication (PLC) system. Some sites in the wind power generation complex in Gyeongsangnam-do were selected as test beds, and real-time land resistance data applied with new technologies were obtained. The electrode arrangement adopted a smart electrode arrangement using a combination of a Wenner four electrode arrangement and a Schlumberger electrode arrangement. Result: First, the characteristic of this technology is that the depth of smart multi-electrodes is organized differently to reduce the error range of the acquired data even in the stratigraphic structure with specificity between floors. Second, IT convergence technology was applied to enable real-time transmission and reception of information on land resistance data acquired from smart ground electrodes through the Internet of Things. Finally, it is possible to establish a regular management system and analyze big data accumulated in the server to check the trend of changes in various elements, and to model the optimal ground algorithm and ground system design for the IT convergence environment. Conclusion: This technology will reduce surge damage caused by lightning on urban infrastructure underlying the 4th industrial era and design an optimized ground system model to protect the safety and life of users. It is also expected to secure intellectual property rights of pure domestic technology to create jobs and revitalize our industry, which has been stagnant as a pandemic in the post-COVID-19 era.
Journal of Korean Society of Disaster and Security
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v.14
no.2
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pp.1-11
/
2021
Recently, in Korea, the risk of meteorological disasters is increasing due to climate change, and the damage caused by rainfall is being emphasized continuously. Although the current weather forecast provides quantitative rainfall, there are several difficulties in predicting the extent of damage. Therefore, in order to understand the impact of damage, the threshold rainfall for each watershed is required. The damage caused by rainfall occurs differently by region, and there are limitations in the analysis considering the characteristic factors of each watershed. In addition, whenever rainfall comes, the analysis of rainfall-runoff through the hydrological model consumes a lot of time and is often analyzed using only simple rainfall data. This study used GIS data and calculated the threshold rainfall from the threshold runoff causing flooding by coupling two hydrologic models. The calculation result was verified by comparing it with the actual case, and it was analyzed that damage occurred in the dangerous area in general. In the future, through this study, it will be possible to prepare for flood risk areas in advance, and it is expected that the accuracy will increase if machine learning analysis methods are added.
Pruritus (itching) is classically defined as an unpleasant cutaneous sensation that leads to scratching behavior. Although the scientific criteria of classification for pruritic diseases are not clear, it can be divided as acute or chronic by duration of symptoms. In this study, we investigated whether skin injury caused by chemical (contact hypersensitivity, CHS) or physical (skin-scratching stimulation, SSS) stimuli causes initial pruritus and analyzed gene expression profiles systemically to determine how changes in skin gene expression in the affected area are related to itching. In both CHS and SSS, we ranked the Gene Ontology Biological Process terms that are generally associated with changes. The factors associated with upregulation were keratinization, inflammatory response and neutrophil chemotaxis. The Kyoto Encyclopedia of Genes and Genomes pathway shows the difference of immune system, cell growth and death, signaling molecules and interactions, and signal transduction pathways. Il1a, Il1b and Il22 were upregulated in the CHS, and Tnf, Tnfrsf1b, Il1b, Il1r1 and Il6 were upregulated in the SSS. Trpc1 channel genes were observed in representative itching-related candidate genes. By comparing and analyzing RNA-sequencing data obtained from the skin tissue of each animal model in these characteristic stages, it is possible to find useful diagnostic markers for the treatment of itching, to diagnose itching causes and to apply customized treatment.
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