• Journal of IKEEE
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• v.13 no.1
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• pp.36-40
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• 2009

In control of time delay systems, if the informations about the system model and the disturbance can be estimated exactly, the ideal response can be achieved by using Smith predictor controller. Therefore, in this paper, an adaptive algorithm is proposed to control time delay systems existing modelling errors and disturbance. An adaptive observer to estimate disturbance and system model is designed and adaptive laws adjusting the observer are proposed. The new Smith predictor controller is designed using the proposed adaptive observer. As a result, the proposed controller can eliminate the effects of the disturbance and the modelling error. The effectiveness and the improved performance of the proposed system are verified by computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.8
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• pp.1587-1594
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• 1994

The pitch predictor is one of the most important part for the robust tree coder. The hybrid backward pitch adapation which is a combination of a block adaptation and a recursive adaptation is used for the pitch predictor. In order to improve the error performance and track the pitch period change of the input speech, it is proposed to smooth the input of the pitch predictor. The smoother with three taps can have fixed coefficients or variable coefficients depending on the estimated autocorrelation function of the output of the pitch synthesizer. The inclusion of a variable smoother can track the pitch period change within a block and reduce the effect of channel errors.

• Journal of the Korean Society of Safety
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• v.18 no.3
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• pp.154-160
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• 2003

Uncertain time delay happens when the process reads the sensor data and sends the control input to the plant located at a remote site in distributed control system. As in the case of data network using TCP/IP, VDN that integrates both device network and data network has uncertain time delay. Uncertain time delay can cause degradation in performance and stability of distributed control system based on VDN. This paper first investigates the transmission characteristic of VDN and suggests a control scheme based on the Smith's predictor to minimize the effect of uncertain varying time delay. The validity of the proposed control scheme is demonstrated with real-time velocity control of DC servo motor located in remote site.

• Mass Spectrometry Letters
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• v.10 no.3
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• pp.93-101
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• 2019

Algorithms and software for predicting tandem mass spectra have been developed in recent years. In this work, we explore how distinct in silico $MS^2$ spectra are predicted for isomers, i.e. compounds having the same formula and similar molecular structures, to differentiate between them. We used the CFM-ID 2.0/3.0 predictor with regard to (a) test compounds, whose experimental mass spectra had been randomly sampled from the MassBank of North America (MoNA) collection, and to (b) the most widespread isomers of test compounds searched in the PubChem database. In the first validation test, in silico mass spectra constitute a reference library, and library searches are performed for test experimental spectra of "unknowns". The searches led to the true positive rate (TPR) of ($46-48{\pm}10$)%. In the second test, in silico and experimental spectra were interchanged and this resulted in a TPR of ($58{\pm}10$)%. There were no significant differences between results obtained with different metrics of spectral similarity and predictor versions. In a comparison of test compounds vs. their isomers, a statistically significant correlation between mass spectral data and structural features was observed. The TPR values obtained should be regarded as reasonable results for predicting tandem mass spectra of related chemical structures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2018-2043
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• 2022

Nowadays, COVID-19 infections are influencing our daily lives which have spread globally. The major symptoms' of COVID-19 are dry cough, sore throat, and fever which in turn to critical complications like multi organs failure, acute respiratory distress syndrome, etc. Therefore, to hinder the spread of COVID-19, a Computerized Doughty Predictor Framework (CDPF) is developed to yield benefits in monitoring the progression of disease from Chest CT images which will reduce the mortality rates significantly. The proposed framework CDPF employs Convolutional Neural Network (CNN) as a feature extractor to extract the features from CT images. Subsequently, the extracted features are fed into the Adaptive Dragonfly Algorithm (ADA) to extract the most significant features which will smoothly drive the diagnosing of the COVID and Non-COVID cases with the support of Doughty Learners (DL). This paper uses the publicly available SARS-CoV-2 and Github COVID CT dataset which contains 2482 and 812 CT images with two class labels COVID⁺ and COVI^-. The performance of CDPF is evaluated against existing state of art approaches, which shows the superiority of CDPF with the diagnosis accuracy of about 99.76%.

• Korea Journal of Hospital Management
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• v.16 no.2
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• pp.98-116
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• 2011

In this study, we examined the effects of guardians' service quality perception(G-SQP) on patients' service quality perception(P-SQP) leading to patients' behavioral intention(P-BI) and the effects of G-SQP on guardians' behavioral intention(G-BI). To investigate the causalities of the variables, we collected national wide samples of 144 hospitals, 1456 patients and 1455 guardians of the patients and analyzed 1146 guardian-patient coupled cases refined with prerequisites such as missing value, outliers, normality and covariance conditions. Followed were contributions of the present study. First, G-SQP was a predictor of P-SQP. Second, in the first contribution statement, there was no statistically significant difference between inpatient and outpatient group. Third, proven was that G-SQP was a predictor of G-BI. Fourth, verified was that P-SQP was a predictor of P-BI. Fifth, G-SQP was a predictor of P-SQP being led to P-BI that meant P-SQP had a mediating role between G-SQP and P-BI. Since the guardians' perception affected patients' buying decision, the present study implied service managers of hospital settings should pay attention to guardians' perception of service quality as well as patients'. With such strategy, hospitals could improve financial performance in long-term.

• Earthquakes and Structures
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• v.24 no.2
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• pp.81-90
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• 2023

The maximum drifts are important to the seismic evaluation of steel buildings and connections, but the information can hardly be obtained from the post-earthquake field investigation. This research studies the feasibility of using the loss rate of bolt pretension as an earthquake damage predictor. Full-scale tests were made on four steel connections using bolted-web-welded-flange details. One connection was unreinforced (UN), another was reinforced with double shear plates (DS), and the other two used reduced beam sections (RBS). The preinstalled strain gauges were used to control the pretensions and monitor the losses of the high-strength bolts. The results showed that the loss rate of bolt pretension was highly related to the damage of the connections. The pretensions lost up to 10% in all the connections at the yield drifts of 0.5% to 1%. After yielding of the connections, the pretensions lost significantly until fracture occurred. The UN and DS connections failed with a maximum drift of 4 %, and the two RBS connections showed better ductility and failed with a maximum drift of 6%. Under the far-field-type loading protocol, the loss rate grew to 60%. On the contrary, the rate for the specimen under near-fault-type loading protocol was about 40%. The loss rate of bolt pretension is therefore recommended to use as an earthquake damage predictor. Additionally, the 10% and 40% loss rates are recommended to predict the limit states of connection yielding and maximum strength, respectively, and to define the performance levels of serviceability and life-safety for the buildings.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.631-634
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• 2004

In this paper, the Bayesian recurrent neural network (BRNN) is proposed to predict time series data. Among the various traditional prediction methodologies, a neural network method is considered to be more effective in case of non-linear and non-stationary time series data. A neural network predictor requests proper learning strategy to adjust the network weights, and one need to prepare for non-linear and non-stationary evolution of network weights. The Bayesian neural network in this paper estimates not the single set of weights but the probability distributions of weights. In other words, we sets the weight vector as a state vector of state space method, and estimates its probability distributions in accordance with the Bayesian inference. This approach makes it possible to obtain more exact estimation of the weights. Moreover, in the aspect of network architecture, it is known that the recurrent feedback structure is superior to the feedforward structure for the problem of time series prediction. Therefore, the recurrent network with Bayesian inference, what we call BRNN, is expected to show higher performance than the normal neural network. To verify the performance of the proposed method, the time series data are numerically generated and a neural network predictor is applied on it. As a result, BRNN is proved to show better prediction result than common feedforward Bayesian neural network.

• Journal of the Korean Society of Safety
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• v.21 no.4 s.76
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• pp.25-32
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• 2006

LonWorks over IP(LonWorks-IP) virtual device network(VDN) is an integrated form of LonWorks device network and IP data network. In especially real-time distributed servo applications on the factory floor, timely response is essential for predictive and preventive maintenance. The time delay in servo control on LonWorks-IP based VDN has highly stochastic nature. LonWorks-IP based VDN induced transmission delay deteriorates the performance and stability of the real-time distributed control system and can't give an effective preventive and predictive maintenance. In order to guarantee the stability and performance of the system, and give an effective preventive and predictive maintenance, LonWorks-IP based VDN induced time-varying uncertain time delay needs to be predicted and compensated. In this paper new Pill control scheme based on Smith predictor, disturbance observer and band pass filter is proposed and tested through computer simulation about position control of DC servo motor. It is shown that how can the proposed control scheme be designed to minimize the effects of uncertain varying time delay and model uncertainties. The validity of the proposed control scheme is compared and demonstrated with the comparison of internal model controllers(IMC) based on Smith predictor with and without disturbance observer.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.12-18
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• 2001

SAR radar and FLIR images, which are taken from sensors on aircrafts or satellites, are compressed prior to transmission to facilitate rapid transfer through the limited bandwidth channels. In this case, it is important that it achieves compression ratio as high as possible as well as high target detection rate. In this paper a joint ATR-compression system based on the subband coding and VQ is proposed, which utilizes the encoder as a predictor or classifier for target detection. Simulation result shows that the proposed system achieves a relatively high level of target detection performance as well as a high compression ratio over 200:1.