• KIEAE Journal
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• v.7 no.4
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• pp.147-152
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• 2007

Numerous non-destructive tests(NDT) to assess the safety of real structures have been developed. System identification(SI) techniques using dynamic responses and behaviors of structural systems become an outstanding issue of researchers. However the conventional SI techniques are identified to be non-practical to the complex and tall buildings, due to limitation of the availability of an accurate data that is magnitude or location of external loads. In most SI approaches, the information on input loading and output responses must be known. In many cases, measuring the input information may take most of the resources, and it is very difficult to accurately measure the input information during actual vibrations of practical importance, e.g., earthquakes, winds, micro seismic tremors, and mechanical vibration. However, the desirability and application potential of SI to real structures could be highly improved if an algorithm is available that can estimate structural parameters based on the response data alone without the input information. Thus a technique to estimate structural properties of building without input measurement data and using limited response is essential in structural health monitoring. In this study, shaking table tests on three-story plane frame steel structures were performed. Out-put only model analysis on the measured data was performed, and the dynamic properties were inverse analyzed using least square method in time domain. In results damage detection was performed in each member level, which was performed at story level in conventional SI techniques of frequency domain.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.56-63
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• 2016

We consider a satellite mission scheduling problem, which is a promising problem in recent satellite industry. This problem has various considerations such as customer importance, due date, limited capacity of energy and memory, distance of the location of each mission, etc. Also we consider the objective of each satellite such as general purpose satellite, strategic mission and commercial satellite. And this problem can be modelled as a general knapsack problem, which is famous NP-hard problem, if the objective is defined as to maximize the total mission score performed. To solve this kind of problem, heuristic algorithm such as taboo and genetic algorithm are applied and their performance are acceptable in some extent. To propose more efficient algorithm than previous research, we applied a particle swarm optimization algorithm, which is the most promising method in optimization problem recently in this research. Owing to limitation of current study in obtaining real information and several assumptions, we generated 200 satellite missions with required information for each mission. Based on generated information, we compared the results by our approach algorithm with those of CPLEX. This comparison shows that our proposed approach give us almost accurate results as just less than 3% error rate, and computation time is just a little to be applied to real problem. Also this algorithm has enough scalability by innate characteristic of PSO. We also applied it to mission scheduling problem of various class of satellite. The results are quite reasonable enough to conclude that our proposed algorithm may work in satellite mission scheduling problem.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.113-123
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• 2000

In the navigation for a mobile robot, the collision avoidance with unexpected obstacles is essential for the safe navigation and it is independent of the technique used to control the mobile robot. This paper presents a new collision avoidance algorithm using neural network for the safe navigation of the autonomous mobile robot equipped with CAN and ultrasonic sensors. A tracked wheeled mobile robot has a stability and an efficiency to move on a rough ground. And its mechanism is simple. However it has difficulties to recognize its surroundings. Because the shape of the tracked wheeled mobile robot is a square type, sensor modules are generally located on the each plane surface of 4 sides only. In this paper, the algorithm using neural network is proposed in order to avoid unexpected obstacles. The important character of the proposed algorithm is to be able to detect the distance and the angle of inclination of obstacles. Only using datum of the distance and the angle, informations about the location and shape of obstacles are obtained, and then the driving direction is changed. Consequently, this algorithm is capable of real time processing and available for a mobile robot which has few sensor modules or the limited sensing range such as a tracked wheeled mobile robot. Effectiveness of the proposed algorithm is illustrated through a computer simulation and an experiment using a real robot.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.380-384
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• 2004

A fuel spiking test was performed to measure the surge margin of the compressor in a gas turbine engine. During the test, fuel spiking signal was superimposed on the engine controller demand and the mixed signals were used to control a fuel line servo-valve. For the superimposition, a subsystem composed of a fuel controller and a function generator was used. During the fuel spiking test, the original scheduled fuel signals and the modified signals were compared to guarantee the consistency excluding the spiking signals. The spiking signals were carefully selected to maintain the engine speed constant. The fuel spiking effects were checked by three dynamic pressure sensors. Sensors were placed before the servo-valve, after the servo-valve, and after the compressor location, respectively. The modulations of the spiking signal duration and fuel flow rate were examined to make the- operating point approach the surge region. The real engine test was performed at the Altitude Engine Test Facility (AETF) in Korea Aerospace Research Institute (KARI). In the real engine test, fuel spiking signals with 25~50 ㎳ of spiking signal time and 17~46 % of base fuel flow rate condition were used. The dithering signal was 5~6 ㎃ at 490 Hz. The test results showed good agreement between the fuel spiking signals and the fuel line pressure signals. Also, the compressor discharge pressure signals showed fuel spiking effects and the changes of the operating point on the compressor characteristic map could be traced.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.545-550
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• 2018

Ministry of Oceans and Fisheries declared action plan for the electric fishing gear using real name in order to prevent overusing the fishing gear and to reduce discarded fishing gear. It is needed for a technique that can efficiently transmit the information including the type and location of the fishing gear and the user's real name to the fishing boat and the control center using IoT-based communication. The marine tracker buoy system, which is placed on the water for a long time, transmit the position data and the state data of the buoys to the control center in the ground by using NB-IoT channels. In this paper, we propose the algorithm for the low-power operation of the marine tracker buoy system is proposed and test results of current consumption in the marine tracker buoy system with the proposed algorithm is investigated.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.3
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• pp.31-41
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• 2010

It is difficult to identify attacker's real location when the attacker spoofs IP address in current IPv4-based Internet environment. If the attacks such as DDoS happen in the Internet, we can hardly expect the protection scheme to respond to these attacks in active or real-time manner. Many traceback techniques have been proposed to protect against these attacks, but most traceback schemes were designed to work with the IPv4-based Internet and found to be lack of verification of whether the traceback related information is forged or not. Few traceback schemes for IPv6-based network environment have been suggested, but it has these disadvantages that needs more study. In this paper, we propose the reliable IP traceback scheme supporting integrity of traceback-related information in IPv6 network environment, simulate it, and compare our proposed scheme with exsisting traceback mechanisms in terms of overhead and functionality.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.47-58
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• 2012

In this paper, we propose a continuous k-nearest neighborhood query processing method for updating the query results in real-time over mobile peer-to-peer environments. The proposed method disseminates a monitoring region to efficiently monitor the k-nearest neighbor peers. The Monitoring Region is created to assure at least k peers as the result of the query within the time range using the vector of neighbor peers. In the propose method, the monitoring region is valid for a long time because it is calculated by the vector of neighbor peers of the query peer. Therefore, the proposed method decreases the cost of re-processing by monitoring region invalidation. In order to show the superiority of the proposed method, we compare it with the previous schemes through performance evaluation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.4
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• pp.344-365
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• 2009

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.23 no.2
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• pp.103-107
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• 2013

Objectives: The principal purpose of this study is to statistically compare dust levels among farmers with and without feeding in a nursery pig building. Methods: Total dust and respirable dust were measured by personal sampling method, and TSP and PM10 were monitored by the direct recording method in the pig building. Results: IIn the personal samples, mean exposure levels of total and respirable dust were higher among the farmers who conducted feeding compared to farmers who did not. A significant difference between farmers with feeding and farmers without feeding was found in total dust concentration(p<0.05), whereas there was no significant difference in respirable dust concentrations. In real-time monitoring of dust based on area sampling, the highest levels of total and respirable dust were detected in the feeding time periods; $4.33{\pm}2.57mg/m^3$ for TSP and $2.53{\pm}1.02mg/m^3$ for PM10, respectively. During time periods without feeding, the levels of total and respirable dust ranged from 1 to $2mg/m^3$ and from 0.5 to $1.5mg/m^3$, respectively. Conclusions: In terms of association of feeding work and air sampling location, the mean concentrations of total and respirable dust were highest in area sampling with feeding and lowest in personal sampling without feeding. However, a significant difference among groups investigated according to air sampling condition was found in total dust.