• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.368-373
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• 2002

The inverse z-transform of a z-domain expression of a sequence can be Performed in many different methods among which the recursive computational method is based on the difference equation. In applying this method, a few initial values of the sequence should be obtained separately. Although the existing method generates the right initial values of the sequence, its derivation and justification are not theoretically in view of the definition of z-transform and its shift theorems. In this paper a general approach for formulating a difference equation and for obtaining required initial values of a sequence is proposed, which completely complies to the definition of the z-transform and an interpretation of the validity of the existing method which is theoretically incorrect.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.416-426
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• 2003

In this paper we propose a new method for choosing the initial values of Expectation-Maximization(EM) algorithm that has been used in various applications for clustering. Conventionally, the initial values were chosen randomly, which sometimes yields undesired local convergence. Later, K-means clustering method was employed to choose better initial values, which is currently widely used. However the method using K-means still has the same problem of converging to local points. In order to resolve this problem, a new method of initializing values for the EM process. The proposed method not only strengthens the characteristics of EM such that the number of iteration is reduced in great amount but also removes the possibility of falling into local convergence.

• The Journal of Advanced Prosthodontics
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• v.16 no.3
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• pp.174-188
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• 2024

PURPOSE. The purpose of this study was to investigate the effects of surface treatments, liquids, and aging on color, translucency, and surface properties of monolithic ceramics. MATERIALS AND METHODS. Lithium disilicate (LDS) and zirconia-reinforced lithium silicate (ZLS) ceramics (n = 135 each) were cut and divided into three groups [crystallization+glaze (single stage), crystallization-glaze (two stages), and crystallization-polish (two stages)]. One sample from each group was examined using scanning electron microscopy (SEM). Remaining samples were divided into four subgroups (distilled water, coffee, grape juice, and smoothie) (n = 11 each), stored for 12 d in the respective liquids, and thermally aged. One sample from each subgroup was analyzed using SEM. The color, gloss, and roughness values of the samples were analyzed after surface treatment (initial) and storage under different liquids+aging conditions. The initial data and both the aged data and data change values were analyzed using robust two- and three-way analyses of variance. RESULTS. The glazed groups exhibited smoother surfaces. Ceramic type and ceramic-surface treatment interactions affected the initial translucency parameter (TP) (P < .001) and the initial and aged roughness values (P ≤ .001). Surface treatment type affected the color change (P < .001), and ceramic type affected the aged TP values (P < .001). Type of ceramic, surface treatment, and their interactions affected both the initial and aged gloss (P ≤ .001) and TP change values (P ≤ .015). Surface treatment type and ceramic-surface treatment interactions affected the gloss change values (P ≤ .001). CONCLUSION. Although both ceramics and all surface treatments are clinically applicable, crystallization-glaze is recommended. When gloss and smoothness are important or when translucency is important, ZLS or LDS may be preferred, respectively.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.13-16
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• 2001

In reinforcement teaming, Q-learning converges quite slowly to a good policy. Its because searching for the goal state takes very long time in a large stochastic domain. So I propose the speedup method using the Q-value initialization for model-free reinforcement learning. In the speedup method, it learns a naive model of a domain and makes boundaries around the goal state. By using these boundaries, it assigns the initial Q-values to the state-action pairs and does Q-learning with the initial Q-values. The initial Q-values guide the agent to the goal state in the early states of learning, so that Q-teaming updates Q-values efficiently. Therefore it saves exploration time to search for the goal state and has better performance than Q-learning. 1 present Speedup Q-learning algorithm to implement the speedup method. This algorithm is evaluated. in a grid-world domain and compared to Q-teaming.

• Proceedings of the KSME Conference
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• 2000.11b
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• pp.532-537
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• 2000

The purpose of this study is to determine the performance of a commercial air cleaner in removing tobacco smoke indoors. Following injection of tobacco smoke in a room, decay rates for particle concentrations were obtained far mass concentration at each point. The size distribution of the tobacco smoke particles was approximately $1.266{\mu}m$ in mass median diameter with a geometric standard deviation of 1.313. The air cleaner consisted of an electrostatic filtration unit and a fan operated at a flow rate of 5.98 CMM. The collection efficiency for $>1\;{\mu}m$ was more than 99%. Without air cleaner operation, tobacco smoke concentration ratio in room decreased to 30% of initial values within 30 minutes and with air cleaner operation, decreased to 90% of initial values in the test chamber, volume $51.27\;m^3$. Without air cleaner operation, tobacco smoke concentration ratio in room decreased to 10% of initial values within 30 minutes and with air cleaner operation, decreased to 30-70% of initial values in the test chamber, volume $149.2\;m^3$.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.476-481
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• 1988

In this paper a pH process of a weak acid with a strong base is modeled into a bilinear form, and a self-tuning pH control algorithm which is robust against initial values of solution and disturbances is presented. The control algorithm employs the recursive least square method for the parameter estimation and the generalised minimum variance criterion as the objective function. The computer simulation shows that the tracking of desired pH values is obtained in satisfactory manner regardless of the initial values chosen for the process.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.214-220
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• 2019

The calibration method of the initial value error obtained in the weight measurement through anchor bolt type strain gauge sensor is proposed. The strain gauge sensor is developed for preventing the overturning of forklift, which is the most frequent type of safety-accident in industry. It was confirmed that the initial value error is caused from the physical and mechanical error of anchor bolt, and the environmental problem. Since the elimination of these causes falls outside the realm of this research, we find out the calibrated values based on all the causes, and we adjust the initial values of analog-to-digital convertor (ADC) module consisted of strain gauge sensor block using the calibrated values. We use the linear interpolation method for our calibration. We confirm that four sensor modules have the different under 5% between the real weight and the measured value in the experiment applied with the calibration of initial values. The low correlation between the real weights and ADC values is also improved through the proposed calibration.

• KSBB Journal
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• v.6 no.3
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• pp.255-261
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• 1991

The effect of concentration of yeast extract and NH4Cl in the mediun of alcohol fermentation of S. cerevisiae ATCC 24858 on the fermentation characteristics, specific growth rate, sugar conversion, alcohol productivity was experimentally investigated. Regardless of initial sugar concentrations, the values of the above three characteristics increased with augument of concentration of yeast extract. However, the increasing tendency ceased above a certain concentration. The concentration of NH4Cl had little effect on the change of the three characteristics. The functional relationships between the concentration of yeast extract and the characteristics were different according to the initial sugar concentrations, but those between the ratio of yeast extract concentration to initial sugar concentration and the characteristics could be expressed as same forms respectively regardless of initial sugar concentrations. Also the values of the three characteristics approached to the maximum values around 0.085 of the ratio, but did not increase any more above 0.1 of the ratio. We have come to conclusion that the optimum ratio of the yeast extract concentration to the initial sugar concentration was about 0.085 and the ratio should not be decided as greater than 0.1 in the medium of alcohol fermentation of S. cerevisiae ATCC 24858.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1394-1400
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• 1999

This paper presents and efficient improvement of the iterative eigenvalue calculation method and the selection of initial values in AESOPS algorithm. To determine the initial eigenvalues of the system, system state matrix is constructed with the two-axis generator model. From the submatrices including synchronous and damping coefficients, the initial eigenvalues are calculated by the QR method. Participation factors are also calculated from the above submatrices in order to determine the generators which have a important effect to the specific oscillation mode. Also, the heuristically approximated eigenvalue calculation method in the AESOPS algorithm is transformed to the Newton Raphson Method which is largely used in the nonlinear numerical analysis. The new methods are developed from the AESOPS algorithm and thus only a few calculation steps are added to practice the proposed algorithm.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1302-1306
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• 2005

This study has Performed to develop rehabilitation model for determination of optimal rehabilitation time on the Cast Iron Pipes (CIP) with diameter less than 300 mm in water pipeline network and to analysis the sensitivity on the rehabilitation times of developed model. In the result from the application of the field, the renovation time was faster about 10 years than the replacement time. Especially, as the difference between rehabilitation and replacement time on E-CIP was about from 3 to 5 years, and it was thought that the replacement was effective on E-CIP. To sensitivity analysis, the discount rate of coefficient was fixed at 0.08, and the values of initial year break rate(N($t_o$) and growth rate coefficient(A) were adjusted in values of 0.0009, 0.0018, 0.0027, and 0.05, 0.10, 0.15 respectively. When the values of N($t_o$) and A was increased, the results from the time of rehabilitation and replacement was faster It was thought that N($t_o$), 0.018 was reliable values on the applied pipeline through the result of the study. In case of A, the values of A above 0.1 was thought to be Proper.