• Proceedings of the Korean Geotechical Society Conference
• /
• 2010.09a
• /
• pp.1190-1200
• /
• 2010

A method was developed to determine resilient modulus for crushed rock-soil mixtures whose usage has been increased recently without engineering specifications. The method is based on the subtle different modulus called nonlinear dynamic modulus and was lately implemented in residual soils and engineered crushed-stones. Hereby. the same method was expanded to crushed rock-soil mixtures containing as large grain diameter as 300mm. The method utilize field direct-arival tests for the determination of maximum Young's modulus, and a large scale free-free resonant column test, which is recently developed to is capable to test as large grain diameter as 25mm, for modulus reduction curves. The prediction model of resilient modulus was evaluated for crushed rock-soil mixtures of a highway construction site at Gimcheon, Korea.

• Journal of Information Processing Systems
• /
• v.19 no.2
• /
• pp.149-163
• /
• 2023

Affected by external factors, errors in time series data collected by sensors are common. Using the traditional method of constraining the speed change rate to clean the errors can get good performance. However, they are only limited to the data of stable changing speed because of fixed constraint rules. Actually, data with uneven changing speed is common in practice. To solve this problem, an online cleaning algorithm for time series data based on dynamic speed change rate constraints is proposed in this paper. Since time series data usually changes periodically, we use the extreme learning machine to learn the law of speed changes from past data and predict the speed ranges that change over time to detect the data. In order to realize online data repair, a dual-window mechanism is proposed to transform the global optimal into the local optimal, and the traditional minimum change principle and median theorem are applied in the selection of the repair strategy. Aiming at the problem that the repair method based on the minimum change principle cannot correct consecutive abnormal points, through quantitative analysis, it is believed that the repair strategy should be the boundary of the repair candidate set. The experimental results obtained on the dataset show that the method proposed in this paper can get a better repair effect.

• Journal of Biosystems Engineering
• /
• v.14 no.2
• /
• pp.67-79
• /
• 1989

This study was conducted to investigate the applicability of true model theory for pull prediction in a powered lugged wheel-soil system and to examine the possibility of using principles of similitude in investigating the dimensions of soil parameters pertinent to a powered lugged wheel-soil system concerning the pull prediction. The following conclusions were derived from the study; 1) The pull of prototype wheels proved to be predicted by those of the model wheels for the range of the dynamic weight tested. The pull curves of models and prototype were respectively very similar in the shape. From this basic knowledge, it was enabled to apply the similitude theory to the performance prediction of the true model. 2) A conditional equation which can be used for the prediction of pull of prototype by model test was derived as follows. $n_f=n_1^{-b}$ where $n_f$ : force scale = $w/w_m$ $n_1$ : length scale = ${\ell}/{\ell}_m$ b : exponent on the length dimension of the soil property ${\alpha}$ The range of the numerical value of b, which was determined by the least square method, was found to be -2.0~-2.6. 3) Considering a relatively wide variation of b values in the pull prediction, b is considered to be a function of many variales. Thus it was concluded that there are several soil properties which are pertinent to the powered lugged-wheel-soil system concerning the pull prediction, and these soil properties may have the different effects on the pull of model and protytype wheels, to give the different dimension on the soil parameters.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1994.10a
• /
• pp.175-182
• /
• 1994

As for the safety evaluation of existing large-scale structures, methods for estimation of the structural and dynamic properties are studied. Sequential prediction error method in time domain and improved FRF estimator in frequency domain are comparatively studied. For this purpose, impact tests of 2 bay 3 floor steel frame structure are performed. Results from both methods are found to be consistent to each others, however those from the finite-element analysis are slightly different from experimental results.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.17 no.3
• /
• pp.12-19
• /
• 1980

A speech recognition system for separately pronounced Korean digits is described. The system is composed of four stages ; parameter extraction, segmentation by voiced-unovied analysis, formant tracking and pattern matching. Digit speech is segmented into an unvoiced segment and/or a voiced one using ZCR and energy measurements, then to estimate the first three formant frequencies a relatively simple formant tracking scheme is applied to the raw formant data extracted from linear prediction spectra. Finally, pattern matching is made using dynamic programmig method. Recognition experiment is carried out for 150 digit utterences spoken by three male speakers, and recgnition rate 94 % is obtained.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2000.11a
• /
• pp.19-22
• /
• 2000

In this paper, we present forecasting ozone concentration with decision support system. Forecasting ozone concentration with decision support system is acquired to information from human knowledge and experiment data. Fuzzy clustering method uses the acquisition and dynamic polynomial neural network gives us a good performance for ozone prediction with ability of superior data approximation and self-organization.

• Journal of the Korean Society for Precision Engineering
• /
• v.23 no.7 s.184
• /
• pp.152-158
• /
• 2006

The objective of this work is to develop the knee joint model for representing various pendulum motions and quantifying the spasticity. Knee joint model included the extension and flexion muscles. The joint moment consists of both the active moment from the stretch reflex and the passive moment from the viscoelastic joint properties. The stretch reflex was modeled as nonlinear feedback of muscle length and the muscle lengthening velocity, which is Physiologically-feasible. Moreover, we modeled the spastic reflex as having dynamic threshold to account far the various pendulum trajectories of spastic patients. We determined the model parameters of three patients who showed different pendulum trajectories through minimization of error between experimental and simulated trajectories. The simulated joint trajectories closely matched with the experimental ones, which show the proposed model can predict pendulum motions of patients with different spastic severities. The predicted muscle force from spastic reflex appeared more frequently in the severe spastic patient, which indicates the dynamic threshold relaxes slowly in this patient as is manifested by the variation coefficient of dynamic threshold. The proposed method provides prediction of muscle force and intuitive and objective evaluation of spasticity and it is expected to be useful in quantitative assessment of spasticity.

• Journal of the Korean GEO-environmental Society
• /
• v.6 no.3
• /
• pp.55-61
• /
• 2005

Dynamic compaction is a ground improvement technique which is particularly effective for loose granular soils. It has also been used successfully to the cohesive soils with high void ratio, and wastes and fills. For the design of dynamic compaction method, prediction of depth of improvement is very important. The depth of improvement is influenced not only by compaction energy but also by many parameters such as grid spacing, soil property, degree of saturation and site conditions. Based on the test results, the depth of improvement were evaluated with considering compaction energy, soil type and ground water level.

• Journal of Ship and Ocean Technology
• /
• v.4 no.2
• /
• pp.13-23
• /
• 2000

A low-order potential based boundary element method is applied to the prediction of the flow around the cavitating propeller in steady or in unsteady inflow. For given cavitation number, the cavity shape is determined in an iterative manner until the kinematic and the dynamic boundary conditions are both satisfied on the approximate cavity boundary. In order to improve the solution behavior near the tip region, a hyperboloidal panel geometry and a modified split panel method are applied. The method is then extended to include the analysis of time-varying cavitating flows around the propeller blades via a time-step algorithm in time domain. In the method, the steady state oscillatory solution is obtained by incremental stepping in the itme domain. Finally, the present method is validated through comparison with other numerical results and experimental data.

• Smart Structures and Systems
• /
• v.11 no.1
• /
• pp.53-67
• /
• 2013

In this paper we apply Monte Carlo Filter to identifying dynamic parameters of structural systems and improve the efficiency of this algorithm. The algorithms using Monte Carlo Filter so far has not been practical to apply to structural identification for large scale structural systems because computation time increases exponentially as the degrees of freedom of the system increase. To overcome this problem, we developed a method being able to reduce number of particles which express possible structural response state vector. In MCF there are two steps which are the prediction and filtering processes. The idea is very simple. The prediction process remains intact but the filtering process is conducted at each node of structural system in the proposed method. We named this algorithm as relaxation Monte Carlo Filter (RMCF) and demonstrate its efficiency to identify large degree of freedom systems. Moreover to increase searching field and speed up convergence time of structural parameters we proposed an algorithm combining the Genetic Algorithm with RMCF and named GARMCF. Using shaking table test data of a model structure we also demonstrate the efficiency of proposed algorithm.