• Journal of Astronomy and Space Sciences
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• v.33 no.4
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• pp.279-285
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• 2016

The space radiation dose over air routes including polar routes should be carefully considered, especially when space weather shows sudden disturbances such as coronal mass ejections (CMEs), flares, and accompanying solar energetic particle events. We recently established a heliocentric potential (HCP) prediction model for real-time operation of the CARI-6 and CARI-6M programs. Specifically, the HCP value is used as a critical input value in the CARI-6/6M programs, which estimate the aviation route dose based on the effective dose rate. The CARI-6/6M approach is the most widely used technique, and the programs can be obtained from the U.S. Federal Aviation Administration (FAA). However, HCP values are given at a one month delay on the FAA official webpage, which makes it difficult to obtain real-time information on the aviation route dose. In order to overcome this critical limitation regarding the time delay for space weather customers, we developed a HCP prediction model based on sunspot number variations (Hwang et al. 2015). In this paper, we focus on improvements to our HCP prediction model and update it with neutron monitoring data. We found that the most accurate method to derive the HCP value involves (1) real-time daily sunspot assessments, (2) predictions of the daily HCP by our prediction algorithm, and (3) calculations of the resultant daily effective dose rate. Additionally, we also derived the HCP prediction algorithm in this paper by using ground neutron counts. With the compensation stemming from the use of ground neutron count data, the newly developed HCP prediction model was improved.

• Smart Structures and Systems
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• v.4 no.6
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• pp.809-828
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• 2008

Real-time hybrid testing is an attractive method to evaluate the response of structures under earthquake loads. The method is a variation of the pseudodynamic testing technique in which the experiment is executed in real time, thus allowing investigation of structural systems with time-dependent components. Real-time hybrid testing is challenging because it requires performance of all calculations, application of displacements, and acquisition of measured forces, within a very small increment of time. Furthermore, unless appropriate compensation for time delays and actuator time lag is implemented, stability problems are likely to occur during the experiment. This paper presents an approach for real-time hybrid testing in which time delay/lag compensation is implemented using model-based response prediction. The efficacy of the proposed strategy is verified by conducting substructure real-time hybrid testing of a steel frame under earthquake loads. For the initial set of experiments, a specimen with linear-elastic behavior is used. Experimental results agree well with the analytical solution and show that the proposed approach and testing system are capable of achieving a time-scale expansion factor of one (i.e., real time). Additionally, the proposed method allows accurate testing of structures with larger frequencies than when using conventional time delay compensation methods, thus extending the capabilities of the real-time hybrid testing technique. The method is then used to test a structure with a rate-dependent energy dissipation device, a magnetorheological damper. Results show good agreement with the predicted responses, demonstrating the effectiveness of the method to test rate-dependent components.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.2
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• pp.213-218
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• 2008

Prediction models for post-chlorination require complicated information of reaction time, chlorine dosage considering flow rate as well as environmental conditions such as turbidity, temperature and pH. In order to operate post-chlorination process effectively, the correlations between inlet and outlet of clear well were investigated to develop prediction models of chlorine dosages in post-chlorination process. Correlations of environmental conditions including turbidity and chlorine dosage were investigated to predict residual chlorine at the outlet of clear well. A linear regression model and autoregressive model were developed to apply for the post-chlorination which take place time delay due to detention in clear well tank. The results from autoregressive model show the correlationship of 0.915~0.995. Consequently, the autoregressive model developed in this study would be applicable for real time control for post chlorination process. As a result, the autoregressive model for post chlorination which take place time delay and have multi parameters to control system would contribute to water treatment automation system by applying the process control algorithm.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.131-140
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• 1999

Today freeway is experiencing a severe congestion with incoming or outgoing traffic through freeway ramps during the peak periods. Thus, the objectives of this study is to identify the traffic characteristics, analyze the relationships between the traffic characteristics and finally construct the delay predictive models on the ramp junctions of freeway with 70mph speed limit. From the traffic analyses, and model constructions and verifications for delay prediction on the ramp junctions of freeway, the following results were obtained: ⅰ) Traffic flow showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy also showed a big difference depending on the time periods, and the downstream occupancy(Od) was especially shown to have a higher explanatory power for the delay predictive model construction on the ramp junction of freeway. ⅲ) The speed-occupancy curve showed a remarkable shift based on the occupancies observed ; Od < 9% and Od$\geq$9%. Especially, volume and occupancy were shown to be highly explanatory for delay prediction on the ramp junctions of freeway under Od$\geq$9%, but lowly for delay predicion on the ramp junctions of freeway under Od<9%. Rather, the driver characteristics or transportation conditions around the freeway were through to be a little higher explanatory for the delay perdiction under Od<9%. ⅳ) Integrated delay predictive models showed a higher explanatory power in the morning peak period, but a lower explanatory power in the non-peak periods.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.152-155
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• 1991

A solution to the problem of robot manipulator tracking of a smoothly moving object is given. It is shown that fuzzy prediction rule, fuzzy control can compensate the adverse effects of noise, time delay, unknown object trajectory, and robot modeling uncertainty. Simulations show that the fuzzy logic control results in acceptable precision,

• Convergence Security Journal
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• v.6 no.1
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• pp.55-63
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• 2006

In this paper, an algorithm that provisions absolute differentiation of packet delays is proposed with an objective for enhancing quality of service (QoS) in future packet networks. It features an adaptive scheme that compensates the deviation for prediction on the traffic to be arrived continuously. It predicts the traffic to be arrived at the beginning of a time slot and measures the actual arrived traffic at the end of the time slot, and derives the deviation between the two quantity. The deviation is utilized to the delay control operation for the next time slot to offset it. As it compensates the prediction error continuously, it shows superior adaptability to the bursty traffic as well as the constant rate traffic. It is demonstrated through simulation that the algorithm meets the quantitative delay bounds and shows superiority to the traffic fluctuation in comparison with the conventional mechanism.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.112-118
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• 2010

This paper describes a noise suppression system based on a normalization method using a time-delay neural network and line spectrum pair having a parameter of frequency domain. First, a time-delay neural network is trained using line spectrum pair values of noisy speech signals obtained by linear prediction analysis. After trained the time-delay neural network, the proposed system enhances speech signals that are degraded by a background noise. Accordingly, the proposed time-delay neural network restores from the line spectrum pair values of noisy speech signals to the line spectrum pair values of clean speech signals. It is confirmed that this system is effective for speech signals degraded by a background noise, judging from spectral distortion measurement.

• Explosives and Blasting
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• v.32 no.3
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• pp.18-25
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• 2014

Ground vibration and noise from blasting operation are known to be the most representative constituents which can cause human and material damage. In this study, the effect of delay time on ground vibration is investigated by adopting seven different delay times in bench blasting. For each delay time, three blasting operations were performed. The prediction equations for blasting vibration are derived from 50 sets of measurement and the time theory of Langefors is evoked in the analysis of the blasting vibrations and frequencies. For the delay times of 8 ms and 28 ms, the average values of ground vibration are 5.76 cm/sec and 5.75 cm/sec, respectively, which are considerably low. Also the cyclic variation in the vibration measurements with the delay time confirms the interference effect. From the application of the measurements of blasting vibration and frequency to the time theory of Langefors, it is concluded that the optimum delay times are 8 ms and 24 ms for the test site.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.125-134
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• 2010

It is occurred bus arrival time errors when a bus arrives at a bus stop because of a variety of traffic condition such as traffic signal cycle, the time to get on and off a bus, a bus-only lane and so on. In this paper, bus delay time which is occurred as the result of traffic condition was estimated with Markov Chain process and bus arrival time at each bus stop was predicted with it. As the result of the study, it is confirmed to improve accuracy than the method of bus arrival time prediction with existing method (weighed moving average method) in case predicting bus arrival time using 7 by 7 and 9 by 9 matrixes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.113-115
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• 2015

In this paper, we proposed an algorithm based on movement prediction using rate of change of the attribute information of nodes what is called WRC(Weighted Rate Control) in delay tolerant networks(DTNs). Existing DTN routing algorithms based on movement prediction communicate by selecting relay nodes increasing connectivity with destination node. Thus, because the mobile nodes are in flux, the prediction algorithms that do not reflect the newest attribute information of node decrease reliability. In this paper, proposed algorithm approximate speed and direction of attribute information of node and analysis rate of change of attribute information of node. Then, it predict movement path of node using proposed weight. As the result, proposed algorithm show that network overhead and transmission delay time decreased by predicting movement path of node.