• Journal of Astronomy and Space Sciences
• /
• v.11 no.1
• /
• pp.1-12
• /
• 1994

The structure of the magnetic funnel element in the intermediate polar is considered in terms of an important site for the X-ray absorption and the reemission of the X-ray as the optical light. In this paper the column density and the optical depth vary with the filling factor, which is introduced to characterize the structure of matter in the magnetic funnel element. The results of the energy dependence of the X-ray spectrum and the modulation depth of the X-ray light curve are discussed.

• Journal of KIISE:Databases
• /
• v.34 no.5
• /
• pp.420-436
• /
• 2007

The choice of an effective indexing method is crucial to guarantee the performance of the spatial join operator which is heavily used in geographical information systems. The $R^*$-tree based method is renowned as one of the most representative indexing methods. In this paper, we propose an efficient spatial join technique based on the DOT(Double Transformation) index, and compare it with the spatial Join technique based on the $R^*$-tree index. The DOT index transforms the MBR of an spatial object into a single numeric value using a space filling curve, and builds the $B^+$-tree from a set of numeric values transformed as such. The DOT index is possible to be employed as a primary index for spatial objects. The proposed spatial join technique exploits the regularities in the moving patterns of space filling curves to divide a query region into a set of maximal sub-regions within which space filling curves traverse without interruption. Such division reduces the number of spatial transformations required to perform the spatial join and thus improves the performance of join processing. The experiments with the data sets of various distributions and sizes revealed that the proposed join technique is up to three times faster than the spatial join method based on the $R^*$-tree index.

• Journal of Astronomy and Space Sciences
• /
• v.15 no.1
• /
• pp.1-26
• /
• 1998

The structure of the magnetic funnel element in the intermediate polar is con-sidered in terms of an important site for the X-ray absorption and the reemis-sion of the X-ray as the optical light. In this paper the column density and the optiacl depth vary with the filling factor, which is introduced to characterize the structure of matter in the magnetic funnel element. The results of the en-ergy dopendence of the X-ray spectrum and the modulation depth of the X-ray light curve are discussed.

• Bulletin of the Korean Mathematical Society
• /
• v.51 no.1
• /
• pp.29-41
• /
• 2014

In this paper, we prove that infinite-dimensional vector spaces of -dense curves are generated by means of the functional equations f(x)+f(2x)+${\cdots}$+f(nx) = 0, with $n{\geq}2$, which are related to the partial sums of the Riemann zeta function. These curves ${\alpha}$-densify a large class of compact sets of the plane for arbitrary small ${\alpha}$, extending the known result that this holds for the cases n = 2, 3. Finally, we prove the existence of a family of solutions of such functional equation which has the property of quadrature in the compact that densifies, that is, the product of the length of the curve by the $n^{th}$ power of the density approaches the Jordan content of the compact set which the curve densifies.

• Journal of Information Technology and Architecture
• /
• v.10 no.1
• /
• pp.79-91
• /
• 2013

This paper proposes a systematic methodology that could be used to decide which one shows the best performance among space filling curves (SFCs) in applying lower-dimensional transformations to histogram sequences. A histogram sequence represents a time-series converted from an image by the given SFC. Due to the high-dimensionality nature, histogram sequences are very difficult to be stored and searched in their original form. To solve this problem, we generally use lower-dimensional transformations, which produce lower bounds among high dimensional sequences, but the tightness of those lower-bounds is highly affected by the types of SFC. In this paper, we attack a challenging problem of evaluating which SFC shows the better performance when we apply the lower-dimensional transformation to histogram sequences. For this, we first present a concept of spatial locality, which comes from an intuition of "if the entries are adjacent in a histogram sequence, their corresponding cells should also be adjacent in its original image." We also propose spatial locality preservation metric (slpm in short) that quantitatively evaluates spatial locality and present its formal computation method. We then evaluate five SFCs from the perspective of slpm and verify that this evaluation result concurs with the performance evaluation of lower-dimensional transformations in real image matching. Finally, we perform k-NN (k-nearest neighbors) search based on lower-dimensional transformations and validate accuracy of the proposed slpm by providing that the Hilbert-order with the highest slpm also shows the best performance in k-NN search.

• Journal of KIISE:Databases
• /
• v.32 no.4
• /
• pp.345-361
• /
• 2005

A transform-space index indexes objects represented as points in the transform space An advantage of a transform-space index is that optimization of join algorithms using these indexes becomes relatively simple. However, the disadvantage is that these algorithms cannot be applied to original-space indexes such as the R-tree. As a way of overcoming this disadvantages, the authors earlier proposed the transform-space view join algorithm that joins two original- space indexes in the transform space through the notion of the transform-space view. A transform-space view is a virtual transform-space index that allows us to perform join in the transform space using original-space indexes. In a transform-space view join algorithm, the order of accessing disk pages -for which various space filling curves could be used -makes a significant impact on the performance of joins. In this paper, we Propose a new space filling curve called the adaptive row major order (ARM order). The ARM order adaptively controls the order of accessing pages and significantly reduces the one-pass buffer size (the minimum buffer size required for guaranteeing one disk access per page) and the number of disk accesses for a given buffer size. Through analysis and experiments, we verify the excellence of the ARM order when used with the transform-space view join. The transform-space view join with the ARM order always outperforms existing ones in terms of both measures used: the one-pass buffer size and the number of disk accesses for a given buffer size. Compared to other conventional space filling curves used with the transform-space view join, it reduces the one-pass buffer size by up to 21.3 times and the number of disk accesses by up to $74.6\%$. In addition, compared to existing spatial join algorithms that use R-trees in the original space, it reduces the one-pass buffer size by up to 15.7 times and the number of disk accesses by up to $65.3\%$.

• Journal of KIISE:Databases
• /
• v.33 no.1
• /
• pp.32-41
• /
• 2006

In data-centric networks, various data items, such as temperature, humidity, etc. are sensed and stored in sensor nodes. As these attributes are mostly scalar values and inter-related, multi-dimensional range queries are useful. To process multi-dimensional range queries efficiently in data-centric storage, data addressing is essential. The Previous work focused on efficient query processing without considering overall network lifetime. To prolong network lifetime and support multi-dimensional range queries, we propose a dynamic data distribution method for multi-dimensional data, where data space is divided into equal-sized regions and linearized by using Hilbert space filling curve.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.9
• /
• pp.2294-2304
• /
• 1999

Our research purpose in this paper is to improve the performance of query processing in GIS(Geographic Information System) by enhancing the I/O performance exploiting parallel I/O and efficient disk access. By packing adjacent spatial data, which are very likely to be referenced concurrently, into one block or continuous disk blocks, the number of disk accesses and the disk access overhead for query processing can be decreased, and this eventually leads to the I/O time decrease. So, in this paper, we proposes EPR(Enhanced Parallel R-tree) indexing method which integrates the parallel I/O method of the previous Parallel R-tree method and a packing-based clustering method. The major characteristics of EPR method are as follows. First, EPR method arranges spatial data in the increasing order of proximity by using Hilbert space filling curve, and builds a packed R-tree by bottom-up manner. Second, with packing-based clustering in which arranged spatial data are clustered into continuous disk blocks, EPR method generates spatial data clusters. Third, EPR method distributes EPR index nodes and spatial data clusters on multiple disks through round-robin striping. Experimental results show that EPR method achieves up to 30% or more gains over PR method in query processing speed. In particular, the larger the size of disk blocks is and the smaller the size of spatial data objects is, the better the performance of query processing by EPR method is.

• The KIPS Transactions:PartD
• /
• v.18D no.5
• /
• pp.323-328
• /
• 2011

For content-based image retrieval, the earth mover's distance and the optimal color composition distance are proposed to measure the dissimilarity. Although providing good retrieval results, both methods are too time-consuming to be used in a large image database. To solve the problem, we propose a new distance function that calculates an approximate earth mover's distance in linear time. To calculate the dissimilarity in linear time, the proposed approach employs the space-filling curve. We have performed extensive experiments to show the effectiveness and efficiency of the proposed approach. The results reveal that our approach achieves almost the same results with the EMD in linear time.

• The Bulletin of The Korean Astronomical Society
• /
• v.41 no.1
• /
• pp.41.1-41.1
• /
• 2016

We present the physical properties of KIC 6220497 exhibiting multiperiodic pulsations from the Kepler photometry. The light curve synthesis represents that the eclipsing system is a semi-detached Algol with a mass ratio of q=0.243, an orbital inclination of i=77.3 deg, and a temperature difference of ${\Delta}T=3,372K$, in which the detached primary component fills its Roche lobe by ~87% and is about 1.6 times larger than the lobe-filling secondary. To detect reliable pulsation frequencies, we analyzed separately the Kepler light curve at the interval of an orbital period. Multiple frequency analyses of the eclipse-subtracted light residuals reveal 32 frequencies in the range of $0.75-20.22d^{-1}$ with semi-amplitudes between 0.27 and 4.55 mmag. Among these, four frequencies ($f_1$, $f_2$, $f_5$, $f_7$) may be attributed to pulsation modes, while the other frequencies can be harmonic and combination terms. The pulsation constants of 0.16-0.33 d and the period ratios of $P_{pul}/P_{orb}=0.042-0.089$ indicate that the primary component is a ${\delta}$ Sct pulsating star in p modes and, thus, KIC 6220497 is an oscillating eclipsing Algol (oEA) star. The dominant pulsation period of about 0.1174 d is considerably longer than the values given by the empirical relations between the pulsational and orbital periods. The surface gravity of log $g_1=3.78$ is significantly smaller than those of the other oEA stars with similar orbital periods. The pulsation period and the surface gravity of the pulsating primary demonstrate that KIC 6220497 would be the more evolved EB, compared with normal oEA stars.