• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.7
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• pp.653-660
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• 2004

This paper presents monopole antenna with electromagnetically coupled feed and its equivalent circuit model. The proposed structure is consists of a rectangular disk-loaded monopole and a probe with rectangular spiral strip line feed. The rectangular disk-loaded monopole is represented by parallel RLC resonant circuit and the probe with rectangular spiral strip line feed is represented by series RLC resonant circuit. Therefore broad bandwidth can be achieved through electromagnetic coupling between these structures that generate two resonances within close frequency range. The antenna with electrical dimensions of only 0.075λ$\sub$0/${\times}$0.075λ$\sub$0/${\times}$0.075λ$\sub$0/ has 16.5 % fractional bandwidth for VSWR$\leq$2 at a center frequency of 2.038GHz.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.18 no.1
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• pp.8-14
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• 1985

A circulation water channel with observational section of $4m{\times}2.4m{\times}1m(length{\times}breadth{\times}depth)$ and the maximum channel flow speed of 2 m/sec was designed for model tests of fishing gears. It consists of 6 sections evenly divided for easy connection. Two observational acryl windows of $1.2m{\times}1.5m$ and 2cm thick are provided. Steel deflection plates, equally spaced in 20-40cm, are fixed at corners of the channel to reduce the loss of water pressure head through the channel. The flow in the channel is controlled by D.C. motor control system with 50 H.P. driving propeller system. A series of model testing capabilities for fishing gear have been examined and the results are as follows. 1) The speed of water flow was in the range from zero to 2.3 m/sec. 2) The difference between the velocity of channel flow along the center line and that along both sides in the channel was less than 0.2 m/sec.

• Smart Media Journal
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• v.13 no.6
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• pp.24-34
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• 2024

If the future can be predicted from network traffic data, which is a time series, it can achieve effects such as efficient resource allocation, prevention of malicious attacks, and energy saving. Many models based on statistical and deep learning techniques have been proposed, and most of these studies have focused on improving model structures and learning algorithms. Another approach to improving the prediction performance of the model is to obtain a good-quality data. With the aim of obtaining a good-quality data, this paper applies a dense sampling technique that augments time series data to the application of network traffic prediction and analyzes the performance improvement. As a dataset, UNSW-NB15, which is widely used for network traffic analysis, is used. Performance is analyzed using RMSE, MAE, and MAPE. To increase the objectivity of performance measurement, experiment is performed independently 10 times and the performance of existing sparse sampling and dense sampling is compared as a box plot. As a result of comparing the performance by changing the window size and the horizon factor, dense sampling consistently showed a better performance.

• 한국방재학회:학술대회논문집
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• 2009.02b
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• pp.36-42
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• 2009

A series of heavy rainfall, typhoon and earthquake disasters caused a proportionately large number of deaths among the elderly in the year 2004 in Japan. In response to these tragedies, the national government set up committees to reduce damage within the disaster vulnerable population for the next three years. The discussions in the committee led to a new conceptualization that disaster vulnerability was caused by a lack of interaction between a person's special needs and the environment's capacity and resources to meet them. This person-in-environment model of hazard vulnerability was applied to those who resided in the Nankai-Tonankai tsunami hazard-prone area. 123 home care service users were interviewed in terms of their self-evacuation ability, degree of social isolation, and building weakness as well as tsunami exposure risks. Results were quantified and scores of person-in-environmentmodel hazard vulnerability were obtained. These scores were then used to visualize socially created vulnerability by means of weighted kernel density mapping of both persons with special needs (PSN's) and persons with special needs at times of disaster (PSND's).

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.1166-1171
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• 2008

Despite of the increasing number of the application of drilled shaft piles in construction site, most studies on pile capacity have been focused on the side shear resistance. But it is common that the drilled shaft is socketed on the rock so as to use its bearing resistance. The prediction of the end movement and characteristics of the bearing capacity of the pile is great important as well. Therefore, a series of scaled model tests were carried out in order to study the characteristics of the bearing capacity on rock mass. The material of the test block was cement mortar which was mixed with sand, cement and water, and the size of a test block size was $240{\times}240{\times}240mm$. The axial load was applied by a miniaturized pile of 45mm in diameter and flat jacks and steel plate were used for confinement to simulate the real underground loading conditions. The relation of load-displacement was measured in various different conditions of rock mass such as strength, discontinuity of the rock mass and in-situ stress, so q-w curves of the end of the pile were presented for each condition.

• Geomechanics and Engineering
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• v.5 no.3
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• pp.263-281
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• 2013

Geotextiles and geogrids have been in use for several decades in variety of geo-structure applications including foundation of embankments, retaining walls, pavements. Geocells is one such variant in geosynthetic reinforcement of recent years, which provides a three dimensional confinement to the infill material. Although extensive research has been carried on geocell reinforced sand, clay and layered soil subgrades, limited research has been reported on the aggregates/ballast reinforced with geocells. This paper presents the behavior of a railway sleeper subjected to monotonic loading on geocell reinforced aggregates, of size ranging from 20 to 75 mm, overlying soft clay subgrades. Series of tests were conducted in a steel test tank of dimensions $700mm{\times}300mm{\times}700mm$. In addition to the laboratory model tests, numerical simulations were performed using a finite difference code to predict the behavior of geocell reinforced ballast. The results from numerical simulations were compared with the experimental data. The numerical and experimental results manifested the importance that the geocell reinforcement has a significant effect on the ballast behaviour. The results depicted that the stiffness of underlying soft clay subgrade has a significant influence on the behavior of the geocell-aggregate composite material in redistributing the loading system.

• Geotechnical Engineering
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• v.10 no.2
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• pp.57-68
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• 1994

To find out the most efficient arrangement of root piles reinforcing sandy soil under a strip footing, a series of model tests for the patten A of by R.H. Bassett and N.C. Last are carried out. In the model test, the variables adopted are a pile length, longitudinal spacing, and the number of rows of piles. According to the results, the most efficient longitudinal spacing of piles is six times of a pile diameter. When the pile length exceeds five times of footing width, no further increase of reinforcing effect is observed. In the pattern A, piles of second row exhibit the largest reinforcing effect and the fifth row show no significant reinforcing effect on the soil.

• Journal of the Korean Society of Safety
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• v.20 no.3 s.71
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• pp.152-157
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• 2005

This experimental study was devoted to investigate skin friction of H group piles with uplift loading conditions in granite soil under laboratory test. Model piles made of steel embedded in weathered granite soil were used in this study. Pile arrangements($2{\times}2,\;3{\times}3$), pile space(2D, 4D, 6D), and soil density($D_r=40%,\;80%$) were tested. The main results obtained from the model tests can be summarized as follows. The series of tests found that ultimate uplift load and displacement for group piles were increased as piles space ratio increases to $D_r=40%$ of soil density. In the relative density of $D_r=80%$, bearing capacity for group piles was greater than for single pile. In the relative density of $D_r=40%$, the theoretical value of skin friction for group piles was greater than practical value. In the relative density of $D_r=80%$, both theoretical and practical value of skin friction for group piles were increased as piles space ratio increases.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.279-289
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• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.268-268
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• 2021

Groundwater resource is mostly used in Abomey-calavi (southern region of Benin) as main source of water for domestic, industrial, and agricultural activities. Groundwater intake across the region is not perfectly controlled by a network due to the presence of many private boreholes and traditional wells used by the population. After some decades, this important resource is becoming more and more vulnerable and needs more attention. For a better groundwater management in the region of Abomey-calavi, the present study attempts to predict a future probable groundwater drought using Recurrent Neural Network (RNN) for future groundwater level prediction. The RNN model was created in python using jupyter library. Six years monthly groundwater level data was used for the model calibration, two years data for the model test and the model was finaly used to predict two years future groundwater level (years 2020 and 2021). GRI was calculated for 9 wells across the area from 2012 to 2021. The GRI value in dry season (by the end of March) showed groundwater drought for the first time during the study period in 2014 as severe and moderate; from 2015 to 2021 it shows only moderate drought. The rainy season in years 2020 and 2021 is relatively wet and near normal. GRI showed no drought in rainy season during the study period but an important diminution of groundwater level between 2012 and 2021. The Pearson's correlation coefficient calculated between GRI and rainfall from 2005 to 2020 (using only three wells with times series long period data) proved that the groundwater drought mostly observed in dry season is not mainly caused by rainfall scarcity (correlation values between -0.113 and -0.083), but this could be the consequence of an overexploitation of the resource which caused the important spatial and temporal diminution observed from 2012 to 2021.