• Journal of Korea Water Resources Association
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• v.45 no.1
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• pp.53-64
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• 2012

In this study (II), the module developed in the previous study (I) has been tested on application and numerical stability. The runoff module was compared the result of analysis with two different models (FFC2Q and $Vflo^{TM}$) considering characteristic of infiltration. To examine the application and stability of developed module, runoff aspect was simulated under the variety case of rainfall intensity, effective soil depth, elapsed time. The development module was presented typical type of infiltration process looking physically, the different of saturation point on soil type, and characteristic of soil type. Also, the module was reflected in the runoff feature about rainfall intensity and time distribution. Finally, this paper drew a conclusion that result of rainfall-runoff analysis as compared with difference models (FFC2Q and $Vflo^{TM}$) has a high accuracy.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.5
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• pp.830-837
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• 2015

A study which is to develop the low-cost urban railway system for low-density line such as Gwang-ju subway Line 2 is in progress, and its TCS(Train Control System) is required as an economic system which is able to train operation suitable in low-density line. We have developed the signaling equipment which is configured with automatic block system between stations, and the control center's equipment in order to meet the requirements of TCS mentioned above. In this paper, we propose the control procedure of ATS to be required for train operation management in the low-density line such as Gwang-ju subway Line 2. The control procedure of ATS considered all features such as the requirements analysis for train operation management, the functions of train control system to be applied and the block type. Also, it considered the station(interlocking, passenger, turn-back) type, station control(stop, route, departure, turn-back departure, turn-back) type, and train operation management for exiting and entering depot. The ATS control procedure proposed in this paper has an advantage in the cost and efficiency through unification and optimization of its function. And in cost of operating and maintenance, the ATS system has a feature that can be significantly reduced.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.4
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• pp.11-23
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• 2011

Mountain streams, which are major components of an entire river network, play an important role as the source of water, sediment, coarse and fine organic matter, and nutrients for lowland rivers. Therefore, dynamics and downstream linkages of each compartment of the mountain stream can be essential for watershed management in catchment scale. The dynamics and downstream linkages are understood as a development of step-pool sequences along a river course. Recently, stream restoration after flooding event often employ the development of step-pool sequences in the world. In this paper, we 1) examined the geomorphic characteristics and the role of step-pool sequences in steep mountain streams by reviewing the results of past studies, and 2) introduced the case studies of stream restoration using step-pool sequences, and finally 3) addressed design methods considering geometry and stability of artificial step-pool sequences for stream restoration. Step-pool sequences play an important role not only as roughness with energy dissipation but also as heterogeneity of stream feature for aquatic habitat. Step-pool sequences, even if they are constructed artificially along a stream, may be effective for small stream restoration considering eco-friendly torrent controls. So far the artificial step-pool sequences were employed for mountainous streams, but those would be applied to urban stream.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.39-39
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• 2012

Data assimilation techniques have received growing attention due to their capability to improve prediction in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modelling software are based on a deterministic approach. In this study, we developed a hydrological modelling framework for sequential data assimilation, namely MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modelling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. In this software framework, sequential data assimilation based on the particle filters is available for any hydrologic models considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and radar rainfall estimates is assessed simultaneously in sequential data assimilation.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.288-296
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• 2021

Automated face recognition in a runtime environment is gaining more and more important in the fields of surveillance and urban security. This is a difficult task keeping in mind the constantly volatile image landscape with varying features and attributes. For a system to be beneficial in industrial settings, it is pertinent that its efficiency isn't compromised when running on roads, intersections, and busy streets. However, recognition in such uncontrolled circumstances is a major problem in real-life applications. In this paper, the main problem of face recognition in which full face is not visible (Occlusion). This is a common occurrence as any person can change his features by wearing a scarf, sunglass or by merely growing a mustache or beard. Such types of discrepancies in facial appearance are frequently stumbled upon in an uncontrolled circumstance and possibly will be a reason to the security systems which are based upon face recognition. These types of variations are very common in a real-life environment. It has been analyzed that it has been studied less in literature but now researchers have a major focus on this type of variation. Existing state-of-the-art techniques suffer from several limitations. Most significant amongst them are low level of usability and poor response time in case of any calamity. In this paper, an improved face recognition system is developed to solve the problem of occlusion known as FRS-OCC. To build the FRS-OCC system, the color and texture features are used and then an incremental learning algorithm (Learn++) to select more informative features. Afterward, the trained stack-based autoencoder (SAE) deep learning algorithm is used to recognize a human face. Overall, the FRS-OCC system is used to introduce such algorithms which enhance the response time to guarantee a benchmark quality of service in any situation. To test and evaluate the performance of the proposed FRS-OCC system, the AR face dataset is utilized. On average, the FRS-OCC system is outperformed and achieved SE of 98.82%, SP of 98.49%, AC of 98.76% and AUC of 0.9995 compared to other state-of-the-art methods. The obtained results indicate that the FRS-OCC system can be used in any surveillance application.

• Journal of the Korean Institute of Educational Facilities
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• v.28 no.4
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• pp.11-17
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• 2021

This study is aimed at presenting an efficient management plan of user participatory design in a situation where the School Space Innovation Project is in progress. 2 schools that were the targets of the Incheon School Space Innovation Project in 2019 were selected for this, and features such as the physical environment of that classroom, classroom usage plan, and the stepwise outcome of the user participatory design workshop were contemplated. Especially the workshop outcome was compared and analyzed quantitatively, focusing on the actual master plan and zoning plan, in order to identify the feature that opinions of various users are reflected on the actual plan. As a result, the following conclusion could be reached. Firstly, it was confirmed that the expression about the user preferential space influences the classroom usage plan of that classroom. Vague expressions about the whole space held a large majority of the objects for the linguistic expression of the preferential space. The expression mode as limited as the expression of the actions that users want to carry out in the space. On the other hand, when the usage purpose of the classroom was definite, it was confirmed that the demand for furniture·facility is relatively high. Secondly, according to the analysis of zoning for each function, it seems that the stereotype, which is arranged on the basis of the chalkboard at the front of existing classrooms, was applied in the case of the learning zone. However, in cases of other functions, a tendency was identified that the user carries out an image description that reflects the physical features of the space. Sufficient preparation will need to precede for the efficient management of the user participatory design workshop and the acceptance of various opinions. It seems that especially the classroom usage plan, number of workshops, consultation of each step, and the education about the space expression mode affect the master plan.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.2
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• pp.203-218
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• 2022

The global value chain, as a major feature of the contemporary global economic system, has been mainly led by developed countries. Whereas developing countries have taken the relatively low value-added activities and this made geographical imbalances in value distribution. This imbalance in value distribution, however, began to gradually alleviated. Related to this phenomenon, the purpose of this research is to analyze the factors affecting factors. Focused on the method of upgrading the industry in the global value chain, the impact on the acquisition of value-added in developing countries was analyzed among the various factors to achieve the research purpose. Panel analysis was conducted on all industries, food and tobacco industries, textile and clothing industries, computer and electornics industries, and automobile industries of the OECD Value-Added Trade Data (TiVA). As a result of the analysis, it was confirmed that in all industries, value-added acquisition in developing countries was improved by increased total production, high value-added product production and participation in early stage. The analysis results by detailed industry showed slightly different patterns depending on the characteristics of each industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.45-52
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• 2023

Recently, as the importance of walking in daily life has been emphasized, projects to guarantee walking rights and create a pedestrian environment are being promoted throughout the region. In previous studies, a pedestrian environment assessment was conducted using Jeonju-si road images, and an image comparison pair data set was constructed. However, data sets expressed in numbers have difficulty in generalizing the judgment criteria of pedestrian environment assessors or visually identifying the pedestrian environment preferred by pedestrians. Therefore, this study proposes a method to interpret the results of the pedestrian environment assessment through data visualization by building a web application. According to the semantic segmentation result of analyzing the walking environment components that affect pedestrian environment assessors, it was confirmed that pedestrians did not prefer environments with a lot of "earth" and "grass," and preferred environments with "signboards" and "sidewalks." The proposed study is expected to identify and analyze the results randomly selected by participants in the future pedestrian environment evaluation, and believed that more improved accuracy can be obtained by pre-processing the data purification process.

• Journal of the Korean Institute of Rural Architecture
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• v.26 no.2
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• pp.35-40
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• 2024

This study examines the classification and typical characteristics of 148 owner shop houses existing in the historical city center of Cheongju. First, they can be classified into single-story, middle-story, and divided types according to the distribution of residential and commercial functions. The single-story(36) has 'ㅡ', 'ㄱ', and 'narrow and deep'-shaped arrangement, with stores on the front and houses on the rear. The middle-story second floor(89) is divided into a first-story store and a second-story house, and the third floor(23) has different functions for each floor, but more than half of them have houses on the second and third floors. Among the total, there are also 16 cases in which the division type is taken with different construction times and structures. Second, in the position of the stairs connected to the upper floor among the middle-floor types(112), the outer stair type(52) to separate from the living space while making the most of the stores on the first floor accounts for 47%, but the biggest feature is that the inner staircase type(34) with privacy reaches 30%. The rear stair room type(26) entering through alleyways or private yards is also 23%. Third, the front pillar spacing varies from 1bay to 4bay in appearance, but the 2bay type on the 2nd floor and the 1bay type on the 3rd floor occupy the largest proportion. This exterior type is a characteristic of a owner shop house that can measure the range of personal ownership. Despite the conflicting functions of stores and houses, 35~40% of the cases are in which the opening positions of the upper and lower floors are unified.