• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.81-91
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• 2019

Although the number of users of urban railways is greatly influenced by the land use plan around the railway station, Korea has been studying this problem in a small scale, so that the entrance width is uniformly calculated irrespective of the land use plan, And there is little deviation. Therefore, this study aims to establish a demand estimation model for the entrance and exit of urban railway stations. For this purpose, the demand, land use area, and socioeconomic indicators for each of the 20 urban railway stations were surveyed at 200m and 500m Regression model. The model is based on the assumption that the dependent variable (response variable) of the model is set to 1 day, peak 1 hour, peak time 5 minutes, Education, and park) and socioeconomic indicators (population, employer, employee, and student) as independent variables (explanatory variables). As a result, it was analyzed that the fit of the model is more statistically significant when the use area of the land use by 500 meters of the center radius of the city rail is used as an independent variable and the demand for the daily use of the railway station is used as a dependent variable. The purpose of this study is to estimate the optimal size of urban railway entrance in order to improve the mobility of the user and the transportation weak in urban railway station.

• Wind and Structures
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• v.10 no.4
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• pp.367-382
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• 2007

A nonlinear numerical method was developed to assess the stability of suspension bridge catwalks under a wind load. A section model wind tunnel test was used to obtain a catwalk's aerostatic coefficients, from which the displacement-dependent wind loads were subsequently derived. The stability of a suspension bridge catwalk was analyzed on the basis of the geometric nonlinear behavior of the structure. In addition, a full model test was conducted on the catwalk, which spanned 960 m. A comparison of the displacement values between the test and the numerical simulation shows that a numerical method based on a section model test can be used to effectively and accurately evaluate the stability of a catwalk. A case study features the stability of the catwalk of the Runyang Yangtze suspension bridge, the main span of which is 1490 m. Wind can generally attack the structure from any direction. Whenever the wind comes at a yaw angle, there are six wind load components that act on the catwalk. If the yaw angle is equal to zero, the wind is normal to the catwalk (called normal wind) and the six load components are reduced to three components. Three aerostatic coefficients of the catwalk can be obtained through a section model test with traditional test equipment. However, six aerostatic coefficients of the catwalk must be acquired with the aid of special section model test equipment. A nonlinear numerical method was used study the stability of a catwalk under a yaw wind, while taking into account the six components of the displacement-dependent wind load and the geometric nonlinearity of the catwalk. The results show that when wind attacks with a slight yaw angle, the critical velocity that induces static instability of the catwalk may be lower than the critical velocity of normal wind. However, as the yaw angle of the wind becomes larger, the critical velocity increases. In the atmospheric boundary layer, the wind is turbulent and the velocity history is a random time history. The effects of turbulent wind on the stability of a catwalk are also assessed. The wind velocity fields are regarded as stationary Gaussian stochastic processes, which can be simulated by a spectral representation method. A nonlinear finite-element model set forepart and the Newmark integration method was used to calculate the wind-induced buffeting responses. The results confirm that the turbulent character of wind has little influence on the stability of the catwalk.

• Journal of Power System Engineering
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• v.17 no.3
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• pp.72-81
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• 2013

Many articles have been published about a 2-degree of freedom model that includes the lateral and yaw motions for controller synthesis in intelligent transport system applications. In this paper, a 3-degree of freedom linear model that includes the roll motion is developed to design a robust steering controller for lane following maneuvers using ${\mu}$-synthesis. This linear perturbed system includes a set of parametric uncertainties in cornering stiffness and unmodelled dynamics in steering actuators. The state-space model with parametric uncertainties is represented in linear fractional transformation form. Design purpose can be obtained by properly choosing the frequency dependent weighting functions. The objective of this study is to keep the tracking error and steering input energy small in the presence of variations of the cornering stiffness coefficients. Furthermore, good ride quality has to be achieved against these uncertainties. Frequency-domain analyses and time-domain numerical simulations are carried out in order to evaluate these performance specifications of a given vehicle system. Finally, the simulation results indicate that the proposed robust controller achieves good performance over a wide range of uncertainty for the given maneuvers.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.2 no.3
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• pp.162-181
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• 1990

The hydrodynamic model is used to analyse the sea surface elevations derived from the SEASAT altimetry over the Yellow Sea and the East China Sea. Periods of significant atmospheric disturbances during the SEASAT mission are selected for this study. These includes periods of July 28-August 2 and August 18-21. Meteoroloeical forcing functions, which are needed for the sea model, are derived by a 2-dimensional grid that is governed by a set of theoretical and empirical meteorological relations over the study area. Ocean tides in this area are known to be significant and introduce a large spatial and time variability in the sea surface elevation. Consequently major tidal constituents of M$_2$, S$_2$, $K_1$ and $O_1$ are included in the computation. With some knowledge of other known sea surface phenomena e.g.(body tide, loading tide), the time-dependent sea surface variation is predicted to com-pare statistically with the satellite altimetric measurements and to achieve the objective of ocean bottom friction study. From a total of 10 SEAST orbit tracks, a friction coefficeint was found ranging from 0.0023 to 0.0027.

• Proceedings of the KSRS Conference
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• v.1
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• pp.79-81
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• 2006

Geostationary ocean satellite, unlike other sun-synchronous polar-orbit satellites, will be able to take a picture of a large region several times a day (almost with every one hour interval). For geostationary satellite, the target region is fixed though the location of sun is changed always. Thus, the ocean signal of a given target point is largely dependent on time. In other words, the ocean signal detected by geostationary satellite sensor must translate to the signal of target when both sun and satellite are located in nadir, using another correction model. This correction is performed with a standardization of signal throughout relative geometric relationship among satellite - sun - target points. One signal value of a selected pixel point of the target region of Geostationary Ocean Colour Imager (GOCI) would be set up as a standard, and the ratio of all remained pixel point can be calculated. This relative ratio called bidirectional factor, the result of modelling of spatiotemporal variation of bidirectional factor is shown.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.17 no.4
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• pp.357-368
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• 1988

An application of thermal response coefficient method for obtaining thermal load on stud-frame walls in a typical house is presented. A set of stud-frame walls is two-dimensional heat conduction transients with composite structure. The ambient temperature on the right-hand face of the stud-frame walls is a typical day-cycle input and the room temperature on the left-hand face is a constant input. The desired output is thermal load at the left-hand face. The time-dependent ambient temperature is approximated by a continuous, piecewise-linear function each having one hour interval. The conduction problem is spatially discretized as 8 computer modelings by finite elements to obtain thermal response coefficients. The discretization and round-off errors can be neglected in the range of adequate number of nodes. A 60-node discretization is recommended as the optimum model among 8 computer modelings. Several sets of response coefficients of the stud-frame walls are generated by which the rate of heat transfer through the walls or some temperature in the walls can be calculated for different input histories.

• The Journal of Information Systems
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• v.26 no.3
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• pp.171-185
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• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• The Journal of the Acoustical Society of Korea
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• v.16 no.3
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• pp.64-72
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• 1997

In this paper, study and experiments are performed for finding recognition unit fit which can be used in large vocabulary recognition system. Specifically, a phoneme that is currently used as recognition unit and a syllable in which Korean is well characterized are selected. From comparisons of recognition experiments, the study is performed whether a syllable can be considered as recognition unit of Korean recognition system. For report of an objective result of the comparison experiment, we collected speech data of a male speaker and processed them by hand-segmentation for phoneme boundary and labeling to construct speech database. And for training and recognition based on HMM, we used HTK (HMM Tool Kit) 2.0 of commercial tool from Entropic Co. to experiment in same condition. We applied two HMM model topologies, 3 emitting state of 5 state and 6 emitting state of 8 state, in Continuous HMM on training of each recognition unit. We also used 3 sets of PBW (Phonetically Balanced Words) and 1 set of POW(Phonetically Optimized Words) for training and another 1 set of PBW for recognition, that is "Speaker Dependent Medium Vocabulary Size Recognition." Experiments result reports that recognition rate is 95.65% in phoneme unit, 94.41% in syllable unit and decoding time of recognition in syllable unit is faster by 25% than in phoneme.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.2
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• pp.65-72
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• 2021

Recently, attacks on the network environment have been rapidly escalating and intelligent. Thus, the signature-based network intrusion detection system is becoming clear about its limitations. To solve these problems, research on machine learning-based intrusion detection systems is being conducted in many ways, but two problems are encountered to use machine learning for intrusion detection. The first is to find important features associated with learning for real-time detection, and the second is the imbalance of data used in learning. This problem is fatal because the performance of machine learning algorithms is data-dependent. In this paper, we propose the HSF-DNN, a network intrusion detection model based on a deep neural network to solve the problems presented above. The proposed HFS-DNN was learned through the NSL-KDD data set and performs performance comparisons with existing classification models. Experiments have confirmed that the proposed Hybrid Feature Selection algorithm does not degrade performance, and in an experiment between learning models that solved the imbalance problem, the model proposed in this paper showed the best performance.

• The Journal of the Acoustical Society of Korea
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• v.19 no.3
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• pp.51-56
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• 2000

Is this paper, we studied on the automatic speech control system in real-time windows environment using voice recognition. The applied reference pattern is the variable DMS model which is proposed to fasten execution speed and the one-stage DP algorithm using this model is used for recognition algorithm. The recognition vocabulary set is composed of control command words which are frequently used in windows environment. In this paper, an automatic speech period detection algorithm which is for on-line voice processing in windows environment is implemented. The variable DMS model which applies variable number of section in consideration of duration of the input signal is proposed. Sometimes, unnecessary recognition target word are generated. therefore model is reconstructed in on-line to handle this efficiently. The Perceptual Linear Predictive analysis method which generate feature vector from extracted feature of voice is applied. According to the experiment result, but recognition speech is fastened in the proposed model because of small loud of calculation. The multi-speaker-independent recognition rate and the multi-speaker-dependent recognition rate is 99.08% and 99.39% respectively. In the noisy environment the recognition rate is 96.25%.