• Journal of the Korean Society of Hazard Mitigation
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• v.2 no.4 s.7
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• pp.87-95
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• 2002

Because of the gravitation of population toward large cities, a number of buildings have been constructed since 1970's. They have been rapidly deteriorated as time passed by. Therefore the purpose of this paper is to present basic data on private buildings managed by the Seoul Metropolitan Government and to analyse deterioration factors of them as well as interrelation. And then, the results of this paper can be used to establish the policy of managing timeworn buildings. Through this study timeworn masonry buildings occupy the major part of timeworn buildings, which have almost structural instability, especially individual residence. Both structure type and building type have an interrelation with the deterioration grade. The structure grade have an interrelation with occupancy class more than structure type.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.4
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• pp.181-189
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• 2003

Because of the gravitation of population toward large cities, a number of masonry buildings have been constructed since 1960. They have been rapidly deteriorated as time passed by. Therefore the purpose of this paper is to present basic data on timeworn masonry buildings which have been managed by metropolitan government and to analyse their deterioration factors. And then, the results of this paper can be used to establish the policy of managing timeworn masonry buildings. According to this study, the crack of masonry wall is the most effective deterioration factor and timeworn masonry buildings have a problem with foundation. The structure grade have an interrelation with occupancy type more than building age. Also, the longer building age becomes, the sooner deterioration speeds. A timeworn masonry building is in urgent need of reinforcement on a thirty-year period of building age.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.14-19
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• 2021

This paper presents LiDAR static obstacle map based vehicle dynamic state estimation algorithm for urban autonomous driving. In an autonomous driving, state estimation of host vehicle is important for accurate prediction of ego motion and perceived object. Therefore, in a situation in which noise exists in the control input of the vehicle, state estimation using sensor such as LiDAR and vision is required. However, it is difficult to obtain a measurement for the vehicle state because the recognition sensor of autonomous vehicle perceives including a dynamic object. The proposed algorithm consists of two parts. First, a Bayesian rule-based static obstacle map is constructed using continuous LiDAR point cloud input. Second, vehicle odometry during the time interval is calculated by matching the static obstacle map using Normal Distribution Transformation (NDT) method. And the velocity and yaw rate of vehicle are estimated based on the Extended Kalman Filter (EKF) using vehicle odometry as measurement. The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment, and is verified with data obtained from actual driving on urban roads. The test results show a more robust and accurate dynamic state estimation result when there is a bias in the chassis IMU sensor.

• Earthquakes and Structures
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• v.22 no.6
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• pp.561-570
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• 2022

It is of great importance to be able to evaluate different structural systems not only based on their seismic performance but also considering their lifetime service costs. Many structural systems exist that can meet the engineering requirements for different performance levels; therefore, these systems shall be selected based on their economic costs over time. In this paper, two structural systems, including special steel moment-resisting and the ordinary concentric braced frames, are considered, which are designed to meet the three performance levels: Immediate Occupancy (IO), Life Safety (LS), Collapse Prevention (CP). The seismic behavior of these two systems is studied under three strong ground motions (i.e., Tabas, Bam, Kajour earthquake records) using the Perform3D package, and the incurred damages to the studied systems are examined at two hazard levels. Economic analyses were performed to determine the most economical structural system to meet the specified performance level requirements, considering the initial cost and costs associated with damages of an earthquake that occurred during their lifetime. In essence, the economic lifetime study results show that the special moment-resisting frames at IO and LS performance levels are at least 20% more economical than braced frames. The result of the study for these building systems with different heights designed for different performance levels also shows it is more economical from the perspective of long-term ownership of the property to design for higher performance levels even though the initial construction cost is higher.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.39-44
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• 2022

This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is commonly used in highway automated vehicle systems. For urban automated vehicle systems, RTK GPS have some trouble in shaded area. Therefore, this paper represents a method to estimate the position of the host vehicle using AVM camera, front camera, LiDAR and low-cost GPS based on Extended Kalman Filter (EKF). Static obstacle map (STOM) is constructed only with static object based on Bayesian rule. To run the algorithm, HD map and Static obstacle reference map (STORM) must be prepared in advance. STORM is constructed by accumulating and voxelizing the static obstacle map (STOM). The algorithm consists of three main process. The first process is to acquire sensor data from low-cost GPS, AVM camera, front camera, and LiDAR. Second, low-cost GPS data is used to define initial point. Third, AVM camera, front camera, LiDAR point cloud matching to HD map and STORM is conducted using Normal Distribution Transformation (NDT) method. Third, position of the host vehicle position is corrected based on the Extended Kalman Filter (EKF).The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment and showed better performance than only lane-detection algorithm. It is expected to be more robust and accurate than raw lidar point cloud matching algorithm in autonomous driving.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1339-1355
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• 2023

Localization is a hot research spot for many areas, especially in the mobile robot field. Due to the weak signal of the global positioning system (GPS), the alternative schemes in an indoor environment include wireless signal transmitting and receiving solutions, laser rangefinder to build a map followed by a re-localization stage and visual positioning methods, etc. Among all wireless signal positioning techniques, Wi-Fi is the most common one. Wi-Fi access points are installed in most indoor areas of human activities, and smart devices equipped with Wi-Fi modules can be seen everywhere. However, the localization of a mobile robot using a Wi-Fi scheme usually lacks orientation information. Besides, the distance error is large because of indoor signal interference. Another research direction that mainly refers to laser sensors is to actively detect the environment and achieve positioning. An occupancy grid map is built by using the simultaneous localization and mapping (SLAM) method when the mobile robot enters the indoor environment for the first time. When the robot enters the environment again, it can localize itself according to the known map. Nevertheless, this scheme only works effectively based on the prerequisite that those areas have salient geometrical features. If the areas have similar scanning structures, such as a long corridor or similar rooms, the traditional methods always fail. To address the weakness of the above two methods, this work proposes a coarse-to-fine paradigm and an improved localization algorithm that utilizes Wi-Fi to assist the robot localization in a geometrically similar environment. Firstly, a grid map is built by using laser SLAM. Secondly, a fingerprint database is built in the offline phase. Then, the RSSI values are achieved in the localization stage to get a coarse localization. Finally, an improved particle filter method based on the Wi-Fi signal values is proposed to realize a fine localization. Experimental results show that our approach is effective and robust for both global localization and the kidnapped robot problem. The localization success rate reaches 97.33%, while the traditional method always fails.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.120-122
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• 2021

Currently, as demand for cars at home and abroad increases, the number of vehicles is decreasing and the number of vehicles is increasing. This is the main cause of the traffic jam. To solve this problem, it operates a high-ocompancy vehicle (HOV) lane, a multi-passenger vehicle, but many people ignore the conditions of use and use it illegally. Since the police visually judge and crack down on such illegal activities, the accuracy of the crackdown is low and inefficient. In this paper, we propose a system design that enables more efficient detection using imaging techniques using computer vision to solve such problems. By improving the existing vehicle detection method that was studied, the trigger was set in the image so that the detection object can be selected and the image analysis can be conducted intensively on the target. Using the YOLO model, a deep learning object recognition model, we propose a method to utilize the shift amount of the center point rather than judging by the bounding box in the image to obtain real-time object detection and accurate signals.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.353-359
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• 2006

Image frame analysis is a conventional way of evaluating loop detector's performance. In image frame analysis, the time to evaluate performance is linearly proportional to the number of evaluated subjects, and the results can be subjective, depending on operator's personal evaluation standards and physical condition. Also, this method is often inferior in accuracy to that provided by the evaluated devices. Therefore, it is critical to develop a portable standard system which has better accuracy and more objectivity in evaluating vehicle detectors. This paper discusses function and reliability of tape-switch detector, which can be a replacement for image frame analysis, for effectively measuring traffic volume, speed, and occupancy.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.1-8
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• 2024

In the API gateway, API composition is an essential function that can reduce the number of client calls and prevent over-fetching and under-fetching. API composition that operate with IMJ (In-Memory Join) consume a lot of resources, putting a burden on the performance of the API gateway. In this paper, to improve the problem of IMJ-style API composition, we propose SAPIC (Stream-based API Composition), which delivers the data to be composed to the client by streaming. SAPIC calls each MSA API that makes up the client response data and immediately streams the received response data to the client, reducing the resource consumption of the API gateway and providing faster response time compared to IMJ. As a result of a comparison experiment with GraphQL, a representative API combination technology, SAPIC recorded a maximum CPU occupancy rate of approximately 21 to 70 % lower, a maximum heap usage rate of approximately 16 to 74 % lower, and a throughput rate that was 1 to 2.3 times higher than GraphQL.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.3
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• pp.179-196
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• 1986

In this paper, the peformance of a statistical packet voice/data multiplexer is studied. In ths study we assume that in the packet voice/data multiplexer two separate finite queues are used for voice and data traffics, and that voice traffic gets priority over data. For the performance analysis we divide the output link of the multiplexer into a sequence of time slots. The voice signal is modeled as an (M+1) - state Markov process, M being the packet generation period in slots. As for the data traffic, it is modeled by a simple Poisson process. In our discrete time domain analysis, the queueing behavior of voice traffic is little affected by the data traffic since voice signal has priority over data. Therefore, we first analyze the queueing behavior of voice traffic, and then using the result, we study the queueing behavior of data traffic. For the packet voice multiplexer, both inpur state and voice buffer occupancy are formulated by a two-dimensional Markov chain. For the integrated voice/data multiplexer we use a three-dimensional Markov chain that represents the input voice state and the buffer occupancies of voice and data. With these models, the numerical results for the performance have been obtained by the Gauss-Seidel iteration method. The analytical results have been verified by computer simylation. From the results we have found that there exist tradeoffs among the number of voice users, output link capacity, voic queue size and overflow probability for the voice traffic, and also exist tradeoffs among traffic load, data queue size and oveflow probability for the data traffic. Also, there exists a tradeoff between the performance of voice and data traffics for given inpur traffics and link capacity. In addition, it has been found that the average queueing delay of data traffic is longer than the maximum buffer size, when the gain of time assignment speech interpolation(TASI) is more than two and the number of voice users is small.