• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.4
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• pp.51-63
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• 2002

This paper presents a hybrid control strategy for seismic protection of a benchmark cable-stayed bridge, which is provided as a testbed structure for the development of strategies for the control of cable-stayed bridges. This benchmark problem considers the cable-stayed bridge that is scheduled for completion in Cape Girardeau, Missouri, USA in 2003. Seismic considerations were strongly considered in the design of this bridge due to the location of the bridge in the New Madrid seismic zone and its critical role as a principal crossing of the Mississippi river. Based on detailed drawings of this cable-stayed bridge, a three-dimensional linearlized evaluation model has been developed to represent the complex behavior of the bridge. A set of eighteen evaluation criteria has been developed to evaluate the capabilities of each control strategy. In this study, a hybrid control system is composed of a passive control system to reduce the earthquake-induced forces in the structure and an active control system to further reduce the bridge responses, especially deck displacements. Conventional base isolation devices such as lead rubber bearings are used for the passive control design and Bouc-Wen model is used to simulate the nonlinear behavior of these devices For the active control design, ideal hydraulic actuators are used and on $H_2$/LQG control algorithm is adopted. Numerical simulation results show that the performance of the proposed hybrid control strategy is quite effective compared to that of the passive control strategy and slightly better than that of the active control strategy. The hybrid control method is also more reliable than the fully active control method due to the passive control part. Therefore, the proposed hybrid control strategy can effectively be used to seismically excited cable-stayed bridges.

• Korea Real Estate Review
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• v.27 no.4
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• pp.7-20
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• 2017

This study attempts to diagnose and categorize the characteristics of old industrial parks, and eventually link the results to the regeneration of industrial complexes. For this reason, we performed a factor analysis by utilizing 15 indices of 89 industrial parks, excluding 5 large equipment industry sites. The 15 indices were classified into 5 factors. Factor 1 can be described as a category of 'urbanization possibility' for the indices of building age, plot ratio of less than $1,650m^2$, and urbanization ratio of the surrounding area. Factor 2 can be described as a category of 'productive efficiency' for the indices of land productivity, amount of exports by land, employment productivity, and repair costs of industrial areas. Factor 3 can be described as a category of 'infrastructure amenity' for the indices of road ratio, plot ratio attached to the road, and parks and recreation ratio. Factor 4 can be described as a category of 'location potentiality' for the indices of land price, infrastructure age, and distance to the highway, while factor 5 can be described as a category of 'availability of supporting facilities' for the indices of parking lot ratio and supporting facility land ratio. By using these 5 factor scores, we were able to extract industrial parks included in the lower 25% of the factor score and searched for what kind of factor problem they have for each industrial park. Based on these results, this research will provide sufficient information on the decline of industrial parks with respect to their demerits. The results of this study show significant implications and contribute to the establishment of policies for regional competitiveness, as well as job creation, in the process of industrial regeneration.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.483-494
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• 2022

Owing to the saturation of ground spaces in downtown areas, underground spaces are being developed increasingly. Underground spaces are utilized for transportation, water supply and sewerage, communication zones, electric power zones, and various cultural complexes. In Korea, for excavating underground spaces, blasting methods using gunpowder such as the New Austrian Tunneling Method (NATM) are mainly used. However, the blasting method causes vibration and noise during tunnel excavation, generating many complaints from residents in the vicinity of the excavation site. To address this problem, various methods have been developed, and recently, vibration and noise have been reduced using deep excavation. This study predicts blast vibration changes according to the depth, under the same blasting and tunnel conditions, using numerical analysis based on the blast vibration measurement data of the GTX-A route, the tunnel cross-section drawings, and ground investigation reports. Furthermore, the necessary separation distance from densely populated areas such as residential areas is suggested by analyzing the trend of decreasing blast vibration according to the distance from ground surface directly above the blasting location.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.315-322
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• 2021

This study analyzes the Required Safe Egress Time (RSET), in the event of a fire at a welfare center for the disabled, using the emergency passage according to the floor arrangement of users to evaluate the safety and the difference in RSET for each emergency passage using the Pathfinder simulation program to suggest an efficient evacuation method. As a result of RSET, it was found that there is no problem in evacuation safety for the current state of the facility's personnel allocation by satisfying the standard RSET in case of fire, and evacuation can be completed safely by evacuating through stairs rather than using elevators if possible. It is necessary for employees to be provided sufficient education and training in advance so that they can evacuate effectively with the disabled in case of fire. This study gives significance in saving many precious lives and safely evacuate in case of fire as evacuation routes were secured through the design, construction and operation of facilities for the disabled and the RSET was shortened through regular evacuation practices. It is necessary to discuss the further RSET studies based on the automatic fire shutters open or not when a fire occurs at a specific location following the installation of automatic fire shutter at the entrance of each floor of the facilities.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.279-286
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• 2021

Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.425-433
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• 2019

In this paper, the RCS analysis of the 10m unmanned surface vehicles was performed, and the factors of RCS increase were analyzed. Modeling techniques by transforming a geometric shape can reduce the RCS area, which can be used to develop stealth unmanned surface vehicles. In order to reduce the RCS, the existing Top Mast part was moved 1m to the tail part, the 5 degree tilt angle was moved below 0.5 m, and additional guided walls were installed to minimize the influence on the center and surrounding corner reflecting structures. As a result of comparing and analyzing the RCS analysis value with the existing model, it can be seen that the reduced countermeasure model is -3.79 dB lower than the existing model for all elevations. In particular, it can be seen that the strong scattering phenomenon is substantially removed in the region except the sacrificial angle region. In addition, it can be seen that in the case of -5m to 2m where the guide wall is added, the reflected signal is improved up to 20 to 40 dB or more, so that it does not appear on the 2D ISAR image. RCS analysis of unmanned surface vehicles explained the process of analyzing and identifying problem location through distance profile analysis and ISAR image analysis.

• Journal of the Korean Institute of Gas
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• v.23 no.1
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• pp.27-35
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• 2019

In order to solve the global warming and reduce greenhouse gas emissions, $CO_2$ capture technology was developed by applying oxy-fuel combustion. But there has been such a problem that its economic efficiency is low due to the high price of oxygen gases. ASU is known to be most suitable method to produce large quantity of oxygen, to reduce the oxygen production cost, the efficiency of ASU need to be improved. To improve the efficiency of ASU, exergy analysis can be used. The exergy analysis provides the information of used energy in the process, the location and size of exergy destruction. In this study, the exergy analysis was used for process developing and optimization of large scale ASU. The process simulation of ASU was conducted, the results were used to calculate the exergy. As a result, to reduce the exergy loss in the cold box of ASU, a lower operating pressure process was suggested. It was confirmed the importance of heat leak and heat loss reduction of cold box. Also, the unit process of ASU which requires thermal integration was confirmed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.3
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• pp.167-174
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• 2021

Recent investigation into the integrity of nuclear containment buildings has highlighted the importance of developing an elaborate diagnostic method to evaluate the distribution and size of cavities inside concrete walls. As part of developing such a method, this paper presents a finite element approach to modeling elastic waves propagating in the containment building walls of a nuclear power plant. We introduce a perfectly matched layer (PML) wave-absorbing boundary to limit the large-scale nuclear containment wall to the region of interest. The formulation results in a semi-discrete form with symmetric damping and stiffness matrices. The transient elastic wave equations for a mixed unsplit-field PML were solved for displacement and stresses in the time domain. Numerical results show that the sensitivity of displacement, velocity, acceleration, and stresses is large depending on the size and location of the cavity. The dynamic response of the wall slightly differs depending on the existence of the containment liner plate. The results of this study can be applied to a full-waveform inversion approach for characterizing cavities inside a containment wall.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.5
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• pp.71-82
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• 2011

The RFID system provides undeniable advantages so that it is used for various application. However recent RFID system is vulnerable to some attacks as eavesdropping, replay attack, message hijacking, and tag tampering, because the messages are transmitted through the wireless channel and the tags are cheap. Above attacks cause the tag and reader impersonation, denial of service by invalidating tag, and the location tracking concerning bearer of tags, A lot of RFID authentication protocol bas been proposed to solve the vulnerability. Since Weis, Sanna, Rivest, and Engel, proposed the bash-based RFID authentication protocol, many researchers have improved hash-based authentication protocol and recent bash-based authentication protocols provide security and desirable privacy. However, it remains open problem to reduce the tag identification time as long as privacy and security are still guaranteed. Here we propose a new protocol in which the tags generate the message depending on the state of previous communitions between tag and reader. In consequence, our protocol allows a server to identify a tag in a reasonable amount of time while ensuring security and privacy, To be specific, we reduced the time for the server to identify a tag when the last session finished abnormally by at least 50% compared with other bash-based schemes that ensure levels of security and privacy similar to ours.