• Journal of Industrial Technology
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• v.15
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• pp.41-50
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• 1995

This paper presents a technique for estimating distribution of data stored in a database. This technique is very useful for accurate selectivity estimation, which is essential in query optimization and physical database design. To maintain data distribution, we employ the directory of the multilevel grid file, a multidimensional dynamic file organization. The major advantage of our technique is that data distribution information is maintained dynamically in the multilevel grid file. In contrast, other static methods such as the histogram method use static date structures, which requires periodic restructuring. Furthermore, we propose a method for keeping the abstract information of data distribution in main memory. This is advantageous in the situation where the size of main memory is not sufficient. Finally, We also suggest formulas for calculating selectivies of various queries based on our data distribution information.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.176-183
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• 2003

Various techniques including histograms, sampling and parametric techniques have been proposed to estimate query result sizes for the query optimization. Histogram-based techniques are the most widely used form for the selectivity estimation in relational database systems. However, in the spatio-temporal databases for the moving objects, the continual changes of the data distribution suffer the direct utilization of the state of the art histogram techniques. Specifically for the future queries, we need another methodology that considers the updated information and keeps the accuracy of the result. In this paper we propose a novel approach based upon the duality and the marginal distribution to construct a histogram with very little time since the spatio-temporal histogram requires the data distribution defined by query predicates. We use data synopsis method in the dual space to construct spatio-temporal histograms. Our method is robust to changing data distributions during a certain period of time while the objects keep the linear movements. An additional feature of our approach supports the dynamic update incrementally and maintains the accuracy of the estimated result.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.544-554
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• 2008

Histograms are popularly used for selectivity estimation in database systems. In conventional histogram methods, buckets return the approximated results based on the assumption that all objects in a bucket are uniformly distributed. However, the objects within the region of a query are not likely to be uniformly distributed. That is, there can be some skews (i.e., clusters) in the buckets, which may significantly degrade the accuracy of the histogram. The aim of this work is to enhance the accuracy of histograms. For this purpose, we propose a new two-dimensional histogram method considering clusters. The proposed method detects dense regions and exploits them for organizing buckets. Since the proposed method effectively reduces accuracy degradation caused by clusters, it can provide improved, robust accuracy against skewed data distributions. Through experiments, we show that the proposed method provides up to 74% improved performance compared with the conventional histogram.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.46-52
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• 2009

In this paper, the timing estimator based on the principle of the best linear unbiased estimator (BLUE) is proposed in OFDMA uplink systems. The proposed timing estimator exploits the phase information of the differential correlation between adjacent subcarriers. The differential correlation can extract the information about timing offset and mitigate the distortion of the signal caused by the frequency selectivity of channel. Compared with conventional methods, the proposed estimator shows more accurate capability in estimation. In addition, the estimator is hardly affected by the distortion caused by the frequency selectivity of channel. Simulation results confirm that the proposed estimator shows a small error mean and a relatively small error variance. In addition, the performance of the estimator is evaluated by means of SNR loss. It is shown by simulations that the SNR loss of the proposed estimator by estimation errors is less than 0.4 dB for the SNR values between 0 and 20 dB. This might indicate that the proposed estimator is suitable for the timing synchronization of multiple users in OFDMA uplink systems.

• Applied Microscopy
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• v.32 no.4
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• pp.311-317
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• 2002

There is great requirement on the TEM specimen preparation method with particle size selectivity as a prerequisite for the quantitative structure analysis on the materials such as gibbsite powder, which generally forms a large agglomerate and shows a variation of transition process depending on their sizes. In this experiment, we made an attempt to give a methodology for the TEM specimen preparation of powder with the size selectivity. After mixing 1 wt% gibbsite powder with ethanol solvent, gibbsite suspension was prepared by application of ball-milling and ultrasonification with addition of 0.25 vol% dispersion agent, Darvan C, which was diluted into distilled water by the ratio 1:19. Appling the static sedimentation method to gibbsite suspension after estimation of the sedimentation time by the measurement of accumulative concentration variation, we acquired TEM specimens with well-dispersed and size selected gibbsite particles in nm scale. Overall picture of each sample was taken by SEM and morphology of each dispersed particle was imaged by TEM. Raw and processed gibbsite powders were also examined by XRD to investigate whether they were suffered from phase change during the process or not.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.22-32
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• 2011

In this paper, we first analyze the differences of underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) systems and conventional terrestrial OFDM system, and give a simple introduction of the backgrounds. By considering the real UWA channel environments, the measured channel data is used to generate the UWA channel model and calculate the relative parameters for underwater OFDM systems. Practical least square (LS) based channel estimation with linear interpolation are adopted to obtain the channel state information (CSI) at receiver side. As multi-input multi-output (MIMO) processing techniques, Alamouti code is implemented and evaluated to perform for space time block coding (STBC) and space frequency block coding (SFBC) for UWA OFDM systems with the MIMO configuration of $2{\times}1$, at the same time, $1{\times}2$ maximum ratio combining (MRC) is performed for the purpose of comparison. The simulation results show that, with perfect channel estimation, SFBC failed to work duo to the serious frequency selectivity of UWA channel environments. When the practical channel estimation is applied, in the case of STBC, the proposed 4-column pilot pattern gives better performance about 7dB than SISO system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.10
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• pp.802-809
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• 2017

This paper presents a novel apnea detection and respiration rate estimation method using impulse-radio ultra-wideband (IR-UWB) radar. The proposed method utilizes amplitude, time of arrival, and power in the selected band. The experimental results show that respiration rate can be estimated accurately using proposed method. And, it is shown that the selectivity between apnea and respiration can be improved more than 50 dB using the proposed method.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.13-15
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• 2004

최근에 공간 정보들의 이력 정보를 효과적으로 다를 수 있는 기술에 대한 연구가 활발하게 이루어지고 있다. 이러한 기술은 토지 관리 시스템이나 시간에 따라 변하는 지리 정보들을 처리하는 시스템에서 유용하게 사용되어질 수 있다. 본 논문에서는 시간의 흐름에 따라 변화하는 공간정보 질의들의 최적화를 위한 선택도 추정 기법을 제시한다. 기본 개념은 Minskew 히스토그램을 이용하여 공간 히스토그램을 구축하고, 이를 timestamp에 따라 재구축 한 뒤 유지하는데 기반하고 있다. 또한, 정확한 선택도 추정률을 유지하고 히스토그램 재구축 횟수를 줄이기 위해 히스토그램 변경 내용이 최적의 임계치를 넘어 섰을 때만 시공간 데이터베이스에 현존하는 엔트리를 기반으로 히스토그램을 새로 구축하는 기법을 제시한다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2006.05a
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• pp.78-83
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• 2006

선택율 추정은 질의 최적화를 위한 기법중의 하나이다. 이동객체에 대한 기존 선택율 추정 기법은 시간에 따른 빈번한 이동객체의 위치 변화를 요약 정보에 반영하지 못함으로써 선택 율 추정시 많은 에러를 발생시키고 있다. 따라서 이 논문에서는 이동객체의 질의에 대한 선택율 추정을 위한 색인 기반의 히스토그램 기법을 제안하였다. 또한 제안된 기법의 구현과 평가를 통 해 제안된 기법의 성능을 분석하였다. 이 논문에서 제안된 기법은 차량 추적 시스템, 위치 기반 서비스, 응급 구조 서비스, 그리고 텔레매틱스 서비스 통과 같은 연속적으로 위치를 변경하는 이동객체의 정보를 실시간으로 관리하고 검색하는 응용분야에 활용 가능할 것이다.

• Journal of Computing Science and Engineering
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• v.5 no.1
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• pp.85-110
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• 2011

Achieving situation awareness is especially challenging for real-time data stream applications because they i) operate on continuous unbounded streams of data, and ii) have inherent realtime requirements. In this paper we showed how formal data stream modeling and analysis can be used to better understand stream behavior, evaluate query costs, and improve application performance. We used MEDAL, a formal specification language based on Petri nets, to model the data stream queries and the quality-of-service management mechanisms of RT-STREAM, a prototype system for data stream management. MEDAL's ability to combine query logic and data admission control in one model allows us to design a single comprehensive model of the system. This model can be used to perform a large set of analyses to help improve the application's performance and quality of service.