• Title/Summary/Keyword: Complex Data

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Truncated Complex Moment Problem with Data in a Circle

  • Lee, Sang-Hun;Sim, Jung-Hui
    • Kyungpook Mathematical Journal
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    • v.45 no.2
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    • pp.241-247
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    • 2005
  • Let ${\gamma}{\equiv}\left{{\gamma}_{ij}\right}(0{\leq}i+j{\leq}2n)$ be a collection of complex numbers with ${\gamma}_{00}>0$ and ${\gamma}_{ji}={\bar{\gamma}}_{ij}$. The truncated complex moment problem for ${\gamma}$ entails finding a positive Borel measure ${\mu}$ supported in the complex plane ${\mathbb{C}}$ such that ${\gamma}_{ij}={\int}{\bar{z}}^{i}z^jd{\mu}(z)(0{\leq}i+j{\leq}2n)$. We solve this truncated moment problem with data in a circle and discuss the behavior of data in an extended moment matrix.

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High-Volume Data Processing using Complex Event Processing Engine in the Web of Next Generation (차세대 웹 환경에서 Complex Event Processing 엔진을 이용한 대용량데이터 처리)

  • Kang, Man-Mo;Koo, Ra-Rok;Lee, Dong-Hyung
    • Journal of KIISE:Databases
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    • v.37 no.6
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    • pp.300-307
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    • 2010
  • According to growth of web, data processing technology is developing. In the Web of next generation, high-speed or high-volume data processing technologies for various wire-wireless users, USN and RFID are developing too. In this paper, we propose a high-volume data processing technology using Complex Event Processing(CEP) engine. CEP is the technology to process complex events. CEP Engine is the following characteristics. First it collects a high-volume event(data). Secondly it analyses events. Finally it lets event connect to new actions. In other words, CEP engine collects, analyses, filters high-volume events. Also it extracts events using pattern-matching for registered events and new events. As the results extracted. We use it by an input event of other work, real-time response for demanded event and can trigger to database for only valid data.

Pseudo Complex Correlation Coefficient: with Application to Correlated Information Sources for NOMA in 5G systems

  • Chung, Kyuhyuk
    • International journal of advanced smart convergence
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    • v.9 no.4
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    • pp.42-51
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    • 2020
  • In this paper, the authors propose the pseudo complex correlation coefficient (PCCC) of the two complex random variables (RV), because the four real correlation coefficients (RCC) of the corresponding four real RVs cannot be obtained only from the complex correlation coefficient (CCC) of given two complex RV. Such observation is motivated by the general statement; "The complex jointly-Gaussian random M-vector cannot be completely described by the complex covariance matrix, even though the real Gaussian random 2M-vector can be completely descried by the real covariance matrix. Therefore, in order to describe completely the complex jointly-Gaussian random M-vector, we need an additional matrix, namely the complex pseudo-covariance matrix, along with the complex covariance matrix." Then, we apply PCCC to correlated information sources (CIS) for non-orthogonal multiple access (NOMA) in 5G system, and investigate impact of the proposed PCCC on the achievable data rate of the stronger channel user in the conventional successive interference cancellation (SIC) NOMA with CIS. It is shown that for the given same CCC, the achievable data rates with the different PCCC are different, because the corresponding RCC are different. We also show that as the absolute value of the same CCC increases, the impact of the different PCCC becomes more significant.

Improvement in the Simulation of Wind Fields Over the Complex Coastal Area, Korea (한반도 복잡 해안지역의 바람장 모의 개선)

  • Kim, Yoo-Keun;Bae, Joo-Hyun;Jeong, Ju-Hee;Kweon, Ji-Hye;Seo, Jang-Won;Kim, Yong-Sang
    • Journal of Environmental Science International
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    • v.15 no.5
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    • pp.417-430
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    • 2006
  • We focused on improvement in simulation of wind fields for the complex coastal area. Local Analysis and Prediction System(LAPS) was used as a data assimilation method to improve initial conditions. Case studies of different LAPS inputs were performed to compare improvement of wind fields. Five cases have been employed : I) non data assimilation, II) all available data, III) AWS, buoy, QuikSCAT, IV) AWS, buoy, wind profiler, V) AWS, buoy, AMEDAS. Data assimilation can supplement insufficiency of the mesoscale model which does not represent detailed terrain effect and small scale atmospheric flow fields. Result assimilated all available data showed a good agreement to the observations rather than other cases and estimated veil the local meteorological characteristics including sea breeze and up-slope winds. Result using wind profiler data was the next best thing. This implies that data assimilation with many high-resolution sounding data could contribute to the improvements of good initial condition in the complex coastal area. As a result, these indicated that effective data assimilation process and application of the selective LAPS inputs played an important role in simulating wind fields accurately in a complex area.

The College Reputation System using Public Data and Sentiment Analysis (공공데이터와 감성분석을 이용한 대학평판시스템)

  • Kim, Eun-Ah;Lee, Yon-Sik
    • Convergence Security Journal
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    • v.18 no.1
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    • pp.103-110
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    • 2018
  • Modern society is increasingly demanding in many areas of big data processing technology to collect, aggregate, and analyze large amounts of data over the Internet and SNS. A typical application is to evaluate the reputation of a company or college. To measure and quantify a reputation, fair and precise data and efficient data processing are very important. For this purpose, a quantitative quotient was obtained using public data, a qualitative quotient was obtained through sentiment analysis using news articles, and a complex college reputation quotient was calculated. In this paper, a complex college reputation quotient was calculated based on the quantitative index, reflecting the sentimental reputation, and based on the proposed mixed university system. In this paper, the Complex College Reputation System(CCRS) was proposed, which produced the Complex College Reputation Quotient with an objective quantitative quotient and qualitative quotient reflecting the sentimental reputation to measure the college reputation.

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Use of Graph Database for the Integration of Heterogeneous Biological Data

  • Yoon, Byoung-Ha;Kim, Seon-Kyu;Kim, Seon-Young
    • Genomics & Informatics
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    • v.15 no.1
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    • pp.19-27
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    • 2017
  • Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

Review of Data-Driven Multivariate and Multiscale Methods

  • Park, Cheolsoo
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.2
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    • pp.89-96
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    • 2015
  • In this paper, time-frequency analysis algorithms, empirical mode decomposition and local mean decomposition, are reviewed and their applications to nonlinear and nonstationary real-world data are discussed. In addition, their generic extensions to complex domain are addressed for the analysis of multichannel data. Simulations of these algorithms on synthetic data illustrate the fundamental structure of the algorithms and how they are designed for the analysis of nonlinear and nonstationary data. Applications of the complex version of the algorithms to the synthetic data also demonstrate the benefit of the algorithms for the accurate frequency decomposition of multichannel data.

Numerical Simulation of Atmospheric Flow Fields Using Surface Observational Data in the Complex Coastal Regions (복잡한 해안지역에서의 지상 관측 자료를 이용한 대기 유동장 수치모의)

  • Lee, Hwa-Woon;Won, Hye-Young;Choi, Hyun-Jung
    • Journal of Korean Society for Atmospheric Environment
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    • v.20 no.5
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    • pp.633-645
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    • 2004
  • A critical component of air pollution modeling is the representation of meteorological fields within a model domain, since an accurate air quality simulation requires an accurate portrayal of the three-dimensional wind fields. The present study investigated data assimilation using surface observational data in the complex coastal regions to simulate an accurate meteorological fields. Surface observational data were categorized into three groups(Near coastal region, Far coastal regiln 1, Far costal region 2) by the locations where the data are. Experiments were designed and MM5 was used in each case of regions. Case 1 is an experiment without data assimilation, Case N is executed with data assimilation using observational data by meteorological stations and AWS data located in the near coastal region, within 1 km. Case F1 is also an experiment with data assimilation using observational data by meteorological stations and AWS data located in the far coastal regiln 1, more than 1km and less than 5km from the coastal lines. Case F2 is appled to data assimilation using observational data by meteorological stations and AWS data located in the far coastal region 2, beyond 5km from the coastal lines. The result of this study indicated that data assimilation using data in the far coastal region 1 and 2 provided an attractive method for generating accurate meteorological fields, especially in the complex coastal regions.

Complex Analyses for Gas Hydrate Seismic Reflection Data (가스하이드레이트 탄성파 자료의 복소분석)

  • Hien, D.H.;Jang, Seong-Hyung;Kim, Young-Wan;Suh, Sang-Yong
    • 한국신재생에너지학회:학술대회논문집
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    • 2008.10a
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    • pp.208-212
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    • 2008
  • Gas hydrate has been paid attention to study for because: 1) it can be considered as a new energy resources; 2) one of reasons causing the instability of sea floor slope and 3) a factor to the climate change. Bottom simulating reflector (BSR) defined as seismic boundary between the gas hydrate and free gas zone has been considered as the most common evidence in the seismic reflection data for the gas hydrate exploration. BSR has several characteristics such as parallel to the sea bottom, high amplitude, reducing interval velocity between above and below BSR and reversing phase to the sea bottom. Moreover, instantaneous attribute properties such as amplitude envelop, instantaneous frequency, phase and first derivative of amplitude of seismic data from the complex analysis could be used to analyze properties of BSR those would be added to the certain properties of BSR in order to effectively find out the existence of BSR of the gas hydrate stability zone. The output of conventional seismic data processing for gas hydrate data set in Ulleung basin in the East sea of Korea will be used for complex analyses to indicate better BSR in the seismic reflection data. This result of this analysis implies that the BSR of the analyzed seismic profile is clearly located at the two ways time (TWT) of around 3.1 seconds.

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