• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.22 no.12
• /
• pp.1726-1734
• /
• 1998

This paper focuses on the unsteady close-contact melting phenomenon occurring between a phase change material kept at its melting temperature and a flat surface on which constant heat flux is imposed. Based on the same simplifications and framework of analysis as the case of constant surface temperature, an approximate analytical solution which depends only on the liquid-to-solid density ratio is successfully derived. In order to keep consistency with the known solution procedure, both the dimensionless wall heat flux and the Stefan number are properly redefined. The obtained solution proves to agree quite well with the published numerical data and to be capable of resolving the fundamental features of unsteady close-contact melting, especially in the presence of the solid-liquid density difference. The density ratio directly affects the film growth rate and the initial value of solid descending velocity, thereby controlling the duration of unsteady process. The effects of other parameters can be evaluated readily from the steady solution which is implied in the normalized result. Since the dimensionless surface temperature for the present boundary condition increases from zero to unity along the evolution path of the liquid film thickness, the unsteady process lasts longer than that for the case of isothermal heating.

• Journal of Korea Multimedia Society
• /
• v.6 no.5
• /
• pp.753-768
• /
• 2003

In this paper, we propose a multi-dimensional index structure, tailed a VA(Vector Approximate)-tree that is constructed with vector approximates of multi-dimensional feature vectors. To save storage space for index structures, the VA-tree employs vector approximation concepts of VA-file that presents feature vectors with much smaller number of bits than original value. Since the VA-tree is a tree structure, it does not suffer from performance degradation owing to the increase of data. Also, even though the VA-tree is MBR(Minimum Bounding Region) based tree structure like a R-tree, its split algorithm never allows overlap between MBRs. We show through various experiments that our proposed VA-tree is a suitable index structure for large amount of multi-dimensional data.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.11 no.4
• /
• pp.565-574
• /
• 2000

A new ground penetrating radar imaging method for the estimation of buried artificial structures location and their approximate shapes in dispersive lossy ground is investigated. Fundamental idea is based on estimating delayed time and amplitude retrieval coefficients from scattered signals by buried scatterers. Using absolute value integration of each scanning site not only improve the accuracy of measured scattered signal, but also offers convenient ways to extract the image of buried structures. Multi-term Debye model was employed to describe a dispersive and lossy ground medium. We used the finite difference time domain method to discretize the wave equation in continuous form into the machine suitable form. This imaging method uses a new wave path tracing technique in time domain, which is helpful to identify the exact position of buried structures against the ground surface fluctuations.

• Proceedings of the KSME Conference
• /
• 2001.06b
• /
• pp.48-52
• /
• 2001

In this paper presents an accurate AFM used that is free from the Z-directional distortion of a servo actuator is described. Two mathematical correction methods by the in-situ self-calibrationare employed in this AFM. One is the method by the integration, and the other is the method by inverse function of the calibration curve. The in situ self-calibration method by the integration, the derivative of the calibration curve function of the PZT actuator is calculated from the profile measurement data sets which are obtained by repeating measurements after a small Z-directional shift. Input displacement at each sampling point is approximately estimated first by using a straight calibration line. The derivative is integrated with reference to the approximate input to obtain the approximate calibration curve. Then the approximation of the input value of each sampling point is improved using the obtained calibration curve. Next the integral of the derivative is improved using the newly estimated input values. As a result of repeating these improving process, the calibration curve converges to the correct one, and the distortion of the AFM image can be corrected. In the in situ self-calibration through evaluating the inverse function of the calibration curve, the profile measurement data sets were used during the data processing technique. Principles and experimental results of the two methods are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.9
• /
• pp.3087-3103
• /
• 2022

Nearest neighbor query in location-based services has become a popular application. Aiming at the shortcomings of the privacy protection algorithms of traditional ciphertext nearest neighbor query having the high system overhead because of the usage of the double Hilbert curves and having the inaccurate query results in some special circumstances, a privacy protection algorithm of ciphertext nearest neighbor query which is based on the single Hilbert curve has been proposed. This algorithm uses a single Hilbert curve to transform the two-dimensional coordinates of the points of interest into Hilbert values, and then encrypts them by the order preserving encryption scheme to obtain the one-dimensional ciphertext data which can be compared in numerical size. Then stores the points of interest as elements composed of index value and the ciphertext of the other information about the points of interest on the server-side database. When the user needs to use the nearest neighbor query, firstly calls the approximate nearest neighbor query algorithm proposed in this paper to query on the server-side database, and then obtains the approximate nearest neighbor query results. After that, the accurate nearest neighbor query result can be obtained by calling the precision processing algorithm proposed in this paper. The experimental results show that this privacy protection algorithm of ciphertext nearest neighbor query which is based on the single Hilbert curve is not only feasible, but also optimizes the system overhead and the accuracy of ciphertext nearest neighbor query result.

• Journal of Korean Society of Environmental Engineers
• /
• v.31 no.6
• /
• pp.428-433
• /
• 2009

Dissolved oxygen is considered as one of the important water-quality constituents in streams from one century ago and fishes perish in low dissolved oxygen concentration. Environmental scientists and engineers have introduced the deterministic model to estimate dissolved oxygen concentration of streams and recommended the use of the Delta Method (DM), Approximate Delta Method (ADM), Extreme Value Method (EVM) and Optimization Method (OPT) which can be applied in no spatial variation of dissolved oxygen. The diurnal or annual variation of dissolved oxygen is mainly determined from the parameters such as reaeration rate, 1st production rate and respiration rate which are related to dissolved oxygen. Each method was briefly introduced and applied to two sampling sites of Anseong Stream watershed in this paper. The limitation, advantages and disadvantages of each method were reviewed and analyzed after running the each method. From these analyses, the benefit-cost approach to estimate dissolved oxygen effectively in streams was recommended.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.29 no.8 s.145
• /
• pp.1102-1113
• /
• 2005

The propose of this study is to develop the optimal sizing system of ready-to-wear f3r elementary school girls using a newly invented statistical technique. The body measurements was classified by the method that equalizes the distribution of the subjects using the probability density function, to theoretically systemize a method to determine a size range of ready-to-wear for elementary school girls between 6 to 12 years old. The statistical method were 1) The total of 11 height groups, which size interval from one another is 6 cm that is an average height gap between each age. 2) In order to determine an approximate figure (m ${\times}$ n) to establish the appropriate sizes far each height group that fit to the combinations of bust and hip girth, which based on their means and standard deviations on the probability density curve to produce the standard normal distribution. 3) m and n were aligned by 4cm -the grading increments used for patterns making- and determined the size ranges by confirming the approximate figures of m and n. 4) The representative values were determined by an area ratio calculated by dividing the area determined from the range of bust and hip girth with the representative value. Considering the characteristics of subjects' distribution, the area ratios was used. 5) Weight was calculated by seeking a growth exponent for each age and multiplying it by the number of girls that fit to each size range. As sections that show the highest weight are more likely sought by the consumers, these sections were determined as the optimal size standards. 6) This optimal sizing system consists of sizes determined by the optimal size standards and its sizes are marked with height, bust and hip girth.

• The KIPS Transactions:PartD
• /
• v.8D no.3
• /
• pp.203-210
• /
• 2001

These days data is being collected and accumulated in a wide variety of fields. Stored data itself is to be an information system which helps us to make decisions. An information system includes many kinds of necessary and unnecessary attribute. So many algorithms have been developed for finding useful patterns from the data and reasoning approximately new objects. We are interested in the simple and understandable rules that can represent useful patterns. In this paper we propose an algorithm which can reduce the information in the system to a minimum, based on a probabilistic rough set theory. The proposed algorithm uses a value that tolerates accuracy of classification. The tolerant value helps minimizing the necessary attribute which is needed to reason a new object by reducing conditional attributes. It has the advantage that it reduces the time of generalizing rules. We experiment a proposed algorithm with the IRIS data and Wisconsin Breast Cancer data. The experiment results show that this algorithm retrieves a small reduct, and minimizes the size of the rule under the tolerant classification rate.

• Geophysics and Geophysical Exploration
• /
• v.10 no.2
• /
• pp.124-130
• /
• 2007

Least squares ($l^2$ norm) solutions of seismic inversion tend to be very sensitive to data points with large errors. The $l^1$ norm minimization gives more robust solutions, but usually with higher computational cost. Iteratively reweighted least squares (IRLS) method gives efficient approximate solutions of these $l^1$ norm problems. I propose an efficient implementation of the IRLS method for a hybrid $l^1/l^2$ minimization problem that behaves as $l^2$ norm fit for small residual and $l^1$ norm fit for large residuals. The proposed algorithm shows more robust characteristics to the decision of the threshold value than the l1 norm IRLS inversion does with respect to the threshold value to avoid singularity.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.5
• /
• pp.231-241
• /
• 2013

In this paper, we propose an average approximation filter which can effectively remove the noises of the images. The noises include impulse noises, gaussian noises and mixed noises. The algorithm is as follows. First, as a step of noise detection, we find whether the difference between the pixel value and the average value is greater than the threshold value or not after getting the average value that removed the minimum and maximum values in the applied mask. If the pixel value is greater than the threshold value, the pixel value is processed as noise. If it is less than or equal to the threshold value, it is processed as non-noise. Next, as the noise reduction step, we output the approximate value in mask as the pixel value and the average value except the minimum and maximum values of the pixel including the noise. As the result of applying this average approximation filter to the mixed noise images, the approximation filter can reduce the noises effectively more than 0.4[dB] as compared with applying the median filter and the average filter, respectively.