• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.145-150
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• 1999

A real-time control system, composed of the controlled processor and the controller computer(s), may have a variety of task types, some of which have tight timing-constraints in generating the correct control input. The maximum period of those task failures tolerable by the system is called the hard deadline, which depends on not only fault characteristics but also task characteristics. In the paper, we extend a method deriving the hard deadline in LTI system executing single task. An algorithm to combine the deadlines of all the elementary tasks in the same operation-mode is proposed to derive the hard deadline of the entire system. For the end, we modify the state equation for the task to capture the effects of task failures (delays in producing correct values) and inter-correlation. We also classify the type of executing the tasks according to operation modes associated with relative importance of correlated levels among tasks, into series, parallel, and cascade modes. Some examples are presented to demonstrate the effectiveness of the proposed methods.

• Journal of the Korean Geophysical Society
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• v.9 no.1
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• pp.7-19
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• 2006

Laser scanning is a new technology for obtaining Digital Surface Models(DSM) of the earth surface.It is a fast method for sampling the earth surface with high density and high point accuracy. This paper is for buildings extraction from LiDAR points data. The core part of building construction is based on a parameters filter for distinguishing between terrain and non-terrain laser points. The 3D geometrical properties of the building facades are obtained based on plane fitting using least-squares adjustment. The reconstruction part of the procedure is based on the adjacency among the roof facades. Primitive extraction and facade intersections are used for building reconstruction. For overcome the difficulty just reconstruct of laser points data used with digital camera images. Also, 3D buildings of city area reconstructed using digital map. Finally, In this paper show 3D building Modeling using digital map and LiDAR data.

• Journal of Sensor Science and Technology
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• v.5 no.4
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• pp.57-70
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• 1996

Motion can be estimated continuously from each sensor through the analysis of the instantaneous states of an object. This paper is aimed to introduce a method to estimate the general 3D motion of a planar object from the instantaneous states of an object using multi-sensor data fusion. The instantaneous states of an object is estimated using the linear feedback estimation algorithm. The motion estimated from each sensor is fused to provide more accurate and reliable information about the motion of an unknown planar object. We present a fusion algorithm which combines averaging and deciding. With the assumption that the motion is smooth, the approach can handle the data sequences from multiple sensors with different sampling times. Simulation results show proposed algorithm is advantageous in terms of accuracy, speed, and versatility.

• Journal of Environmental Health Sciences
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• v.42 no.1
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• pp.34-40
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• 2016

Objectives: This study aims to examine the concentration, diversity, and antibiotic characteristics of penicillin G resistant enterobacteria present in pharmaceutical effluent. Methods: Water sampling was performed from a pharmaceutical company in Gyeonggi-do Province, Korea in March 2015. Water samples were plated in triplicate on tryptic soy agar plates with 32 mg/L of penicillin G. Penicillin G resistant enterobacteria were selected from the effluent and were subjected to 16S rRNA analysis for penicillin G resistant species determination. Identified resistant strains were tested for resistance to various antibiotics. Results: Penicillin G resistant enterobacteria were present at 6.2% as to culturable heterotrophic bacteria. Identified penicillin G resistant enterobacteria exhibited resistance to more than 10 of the antibiotics studied. These resistant bacteria are gram negative and are closely related to pathogenic species. Conclusion: Multi-antibiotic resistant bacteria in the effluent suggest a need for disinfection and advanced oxidation processes for pharmaceutical effluents.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2008.04a
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• pp.171-176
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• 2008

Rapid social change affects residential environments and this in turn creates new stimuli to which people have to adapt. These stimuli have been seen to increase stress levels. Therefore, dwellers in these environments try to reduce stress through various methods. The purpose of this paper is to: 1) identify the general trends of coping styles about residential environmental stress, 2) analyze the differences in socio-demographic characteristics and how the physical characteristics of buildings affect stress, find out how personal backgrounds affect stress levels and the ability to get rid of environmental-related stress. The subjects in this study consisted of people living in multi-family housing in Gwang-ju. The city is divided into 5 districts and used quota sampling. 324 housewives were surveyed from the households by self-administered questionnaires. The survey was conducted in December, 2006, after the questionnaire was revised based on the results of preliminary survey. After all the questionnaires were collected, the data was coded and analyzed using the SPSS 12.0 program.

• IE interfaces
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• v.16 no.spc
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• pp.28-32
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• 2003

In this paper, the fuzzy group method data handling-type(GMDH) neural networks and their application to the forecasting of mobile communication system are described. At present, GMDH family of modeling algorithms discovers the structure of empirical models and it gives only the way to get the most accurate identification and demand forecasts in case of noised and short input sampling. In distinction to neural networks, the results are explicit mathematical models, obtained in a relative short time. In this paper, an adaptive learning network is proposed as a kind of neuro-fuzzy GMDH. The proposed method can be reinterpreted as a multi-stage fuzzy decision rule which is called as the neuro-fuzzy GMDH. The GMDH-type neural networks have several advantages compared with conventional multi-layered GMDH models. Therefore, many types of nonlinear systems can be automatically modeled by using the neuro-fuzzy GMDH. The computer program is developed and successful applications are shown in the field of estimating problem of mobile communication with the number of factors considered.

• Earthquakes and Structures
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• v.5 no.3
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• pp.359-378
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• 2013

The problem of identification of multi-component and (or) spatially varying earthquake support motions based on measured responses in instrumented structures is considered. The governing equations of motion are cast in the state space form and a time domain solution to the input identification problem is developed based on the Kalman and particle filtering methods. The method allows for noise in measured responses, imperfections in mathematical model for the structure, and possible nonlinear behavior of the structure. The unknown support motions are treated as hypothetical additional system states and a prior model for these motions are taken to be given in terms of white noise processes. For linear systems, the solution is developed within the Kalman filtering framework while, for nonlinear systems, the Monte Carlo simulation based particle filtering tools are employed. In the latter case, the question of controlling sampling variance based on the idea of Rao-Blackwellization is also explored. Illustrative examples include identification of multi-component and spatially varying support motions in linear/nonlinear structures.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1650-1657
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• 2017

In this study, the distributed secondary voltage control of islanded microgrids with multi-agent consensus algorithm is investigated. As an alternative to a time-triggered approach, an event-triggered scheme is proposed to reduce the communication load among inverter-based distributed generators (DGs). The proposed aperiodic control scheme reduced unnecessary utilization of limited network bandwidth without degrading control performance. By properly establishing a distributed triggering condition in DG local controller, each inverter is only required to send voltage information when its own event occurs. The compensation of voltage amplitude deviation can be realized, and redundant data exchange related to fixed high sampling rate can be avoided. Therefore, an efficient use of communication infrastructure can be realized, particularly when the system is operating in steady state. The effectiveness of the proposed scheme is verified by simulations on a microgrid test system.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.721-730
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• 2010

In satellite remote sensing, irregular temporal sampling is a common feature of geophysical and biological process on the earth's surface. Lee (2008) proposed a feed-back system using a harmonic model of single period to adaptively reconstruct observation image series contaminated by noises resulted from mechanical problems or environmental conditions. However, the simple sinusoidal model of single period may not be appropriate for temporal physical processes of land surface. A complex model of multiple periods would be more proper to represent inter-annual and inner-annual variations of surface parameters. This study extended to use a multi-periodic harmonic model, which is expressed as the sum of a series of sine waves, for the adaptive system. For the system assessment, simulation data were generated from a model of negative errors, based on the fact that the observation is mainly suppressed by bad weather. The experimental results of this simulation study show the potentiality of the proposed system for real-time monitoring on the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.2
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• pp.196-200
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• 1987

The following methods are proposed for implementing digital dual tone multi-frequency (DTMF) receiver: using infinite impulse response(IIR) digital filters, period-counting algorithm, discrete Fourier transform(DFT), and fast Fourier transform(FFT)[2]. The PARCOR(Partical Correlation) analysis method which has been widly used in the speech signal processing area is applied to the dual tone multi-frequency(DTMF) signal detection. This method is easy to implement digitally and stronger to digit simulation of speech than any other methods proposed up to date. Since sampling rate of 4KHz is used in the DTMF receiver for the detection of input DTMF signal originally sampled at 8KHz, it effects two times higher multiplexing efficiency.