• Title/Summary/Keyword: time dominated data

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Statistical study of phase reversal locations on the SC-associated preliminary impulse

  • Sung, Suk-Kyung;Kim, Khan-Hyuk;Cho, Kyung-Suk
    • Bulletin of the Korean Space Science Society
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    • 2008.10a
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    • pp.30.3-30.3
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    • 2008
  • In this study, we investigate the magnetic latitude of phase reversal on the sudden commencement (SC)-associated preliminary impulse with 267 SC events using the ground magnetometer data of the IMAGE from 1997 to 2005. During SC event, geomagnetic fields are affected by various currents flowing in the magnetosphere and/or ionosphere. In particular, high-latitude geomagnetic field variations are significantly dominated by the change of SC-associated field aligned current (FAC). Until now, however, there are few studies to examine where the location of the FAC in the ionosphere is and what determines the location of the FAC. The location of the SC-associated FAC can be examined by using magnetometer data obtained from high-latitude stations distributed along the same magnetic meridian. The phase reversal locations are concentrated two regions, ~62 deg (L~4.5) and ~70 deg (L~8.5) in magnetic latitude. If FAC is a result of a mode conversion from fast mode to Alfven mode, then the FAC location could be determine by the duration time of the input energy. When we use the rise time, dT, as the input energy, there is no relationship between dT and the location where the first pulse of SC is reversed. We consider other factors such as local time and solar wind condition.

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An Analysis of Wedding Outfits through Families's Wedding Photographs (결혼사진에 나타난 남녀 결혼예복의 형태 분석)

  • 김재숙;송경자;이혜숙
    • The Research Journal of the Costume Culture
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    • v.11 no.2
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    • pp.253-262
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    • 2003
  • The purposes of the study were (1) to analysis Korean traditional wedding costumes through families's wedding photographs from 1940 to 2000, and (2) to categorize bride and groom's costumes according to the wedding time by means of a time series analysis. (3) to find out functional relationship among changes in garment types, garment details, embellishments and colors. The study was a documentary research and data were collected from 390 family wedding photographs by a convenient sampling. The data were analyzed by qualitative and quantitative method and the statistic used were frequency, content analysis, and cross-tab analysis. The results were as follows; First, the garments of wedding couples were categorized into 5 period according to garment's characteristics. 1. The period between 1940~1959 : Korean traditional wedding costumes and western style wedding costumes were existed together in Korean wedding culture. 2. The period between 1960~early 1970's western wedding costumes were dominated. 3. The period of late 1970's : wedding couple's costumes became more formal and decorative. 4. The period of 1980's : introducing see-through materials for brides and tuxedo suit for grooms. 5. The period of 1990's : extravagance in shapes and exposure. Second, there were significant relationships among brides's dress types and neckline, glove length, embellishments and transparency of materials and among groom's garment types and necktie types, types and color of shirts, vests. Third, the time series analysis of bride and groom's outfit produced 5 schematic expressions of wedding outfits according to the period.

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A scheduling algorithm for ASIC design (ASIC 설계를 위한 스케쥴링 알고리듬)

  • 김기현;정정화
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.32A no.7
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    • pp.104-114
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    • 1995
  • In this paper, an intermediate representation HSFG(Hanyang Sequential Flow GRaph) and a new scheduling algorithm for the control-dominated ASIC design is presented. The HSFG represents control flow, data dependency and such constraints as resource constraints and timing constraints. The scheduling algorithm minimizes the total operating time by reducing the number of the constraints as maximal as possible, searching a few paths among all the paths produced by conditional branches. The constraints are substitute by subgraphs, and then the number of subgraphs (that is the number kof the constraints) is minimized by using the inclusion and overlap relation among subgraphs. The proposed algorithm has achieved the better results than the previous ones on the benchmark data.

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Magnetic Parameters as Indicators of Late-Quaternary Environments on Fort Riley Kansas (암석 자기 변수들을 이용한 제4기 고환경 복원-Fort Riley 캔사스)

  • Park, kyeong
    • The Korean Journal of Quaternary Research
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    • v.11 no.1
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    • pp.57-68
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    • 1997
  • Climatic change of the late-Quaternary period has been record-ed in the loess deposits of the central Great plains and the record of such change is extractable using a number of approaches and parameters. The stratigraphy of loess deposits which have been investigated on Fort Riley exhibits the same sequence of loess units and intercalated buried soils as is found elsewhere in the re-gion but adds detail unique to the reservation Upland late-Qua-ternary composite stratigraphy preserved on the reservation con-sists of the basal Sangamon soil of the Last interglacial(c. 120-110ka), Gilman Canyon Formation(c. >40 -20ka), Peoria loess(c. 20 -10ka) Brady soil(c. 11 -10ka) Bignell loess(c. 9-\ulcornerka). and mod-ern surface soil. Application of magnetic analyses has provided proxy data sets that represent a time series of climatically regulated pedogenesis/weathering and botanical composition. magetic data have yielded an impression of the variation in climate from Sangamon time to the late Holocene through a reconstruction of the history of pedogenesis/weathering. Sangamon soil formation dominated the reservation durin the Last interglacial as indicated by magnetic parameters. During Gil-man Canyon time loess influx was usually sufficiently slow as to permit pedogenesis which appears to have been at a maximum twice during that time. Warm season grasses were important dur-ing soil formation but diminished in importance during the peri-ods of more rapid loess fall which were cooler and perhaps wet-ter. Peoria loess fall a function of the deterioration of climate during the last Glacial Maximum thinly blanketed the reservation with thickest accumulations occurring to the north-west(Bala Cemetery site)proximal to the source region. Long-term surface stability did not apparently occur within Peoria time but short-term stability may be indicaed by the presence of thin weathering zones(incipient soils) in the Peoria loess. Re-gional landscape stability prevailed during the environmental shift at the Pleistocene/Holocene transition resulting in forma-tion of the well expressed Brady soil. One or more weak soils developed in the Bignell loess as it ac-cumulated. A notable feature of the Bignell loess is the appear-ance of the Altithermal dry period: the loess experienced little weathering and was dominated by warm season grasses until the latter of the Holocene.

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Skyline Query Algorithm in the Categoric Data (범주형 데이터에 대한 스카이라인 질의 알고리즘)

  • Lee, Woo-Key;Choi, Jung-Ho;Song, Jong-Su
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.7
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    • pp.819-823
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    • 2010
  • The skyline query is one of the effective methods to deal with the large amounts and multi-dimensional data set. By utilizing the concept of 'dominate' the skyline query can pinpoint the target data so that the dominated ones, about 95% of them, can efficiently be excluded as an unnecessary data. Most of the skyline query algorithms, however, have been developed in terms of the numerical data set. This paper pioneers an entirely new domain, the categorical data, on which the corresponding ranking measures for the skyline queries are suggested. In the experiment, the ACM Computing Classification System has been exploited to which our methods are significantly represented with respect to performance thresholds such as the processing time and precision ratio, etc.

Designing a Vehicles for Open-Pit Mining with Optimized Scheduling Based on 5G and IoT

  • Alaboudi, Abdulellah A.
    • International Journal of Computer Science & Network Security
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    • v.21 no.3
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    • pp.145-152
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    • 2021
  • In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancement coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multi-objective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).

A Low Power-Driven Data Path Optimization based on Minimizing Switching Activity (스위칭 동작 최소화를 통한 저전력 데이터 경로 최적화)

  • 임세진;조준동
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.36C no.4
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    • pp.17-29
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    • 1999
  • This paper presents a high level synthesis method targeting low power consumption for data-dominated CMOS circuits (e.g., DSP). The high level synthesis is divided into three basic tasks: scheduling, resource and register allocation. For lower power scheduling, we increase the possibility of reusing an input operand of functional units. For a scheduled data flow graph, a compatibility graph for register and resource allocation is formed, and then a special weighted network is then constructed from the compatibility graph and the minimum cost flow algorithm is performed on the network to obtain the minimum power consumption data path assignment. The formulated problem is then solved optimally in polynomial time. This method reduces both the switching activity and the capacitance in synthesized data path. Experimental results show 15% power reduction in benchmark circuits.

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Long-term deflection prediction in steel-concrete composite beams

  • Lou, Tiejiong;Wu, Sishun;Karavasilis, Theodore L.;Chen, Bo
    • Steel and Composite Structures
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    • v.39 no.1
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    • pp.21-33
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    • 2021
  • This paper aims to improve the current state-of-the-art in long-term deflection prediction in steel-concrete composite beams. The efficiency of a time-dependent finite element model based on linear creep theory is verified with available experimental data. A parametric numerical study is then carried out, which focuses on the effects of concrete creep and/or shrinkage, ultimate shrinkage strain and reinforcing bars in the slab. The study shows that the long-term deformations in composite beams are dominated by concrete shrinkage and that a higher area of reinforcing bars leads to lower long-term deformations and steel stresses. The AISC model appears to overestimate the shrinkage-induced deflection. A modified ACI equation is proposed to quantify time-dependent deflections in composite beams. In particular, a modified reduction factor reflecting the influence of reinforcing bars and a coefficient reflecting the influence of ultimate shrinkage are introduced in the proposed equation. The long-term deflections predicted by this equation and the results of extensive numerical analyses are found to be in good agreement.

A Study on the Research Trends of Archival Preservation Papers in Korea from 2000 to 2021 (국내 기록보존 연구동향 분석: 2000~2021년 학술논문을 중심으로)

  • Yonwhee, Na;Heejin, Park
    • Journal of Korean Society of Archives and Records Management
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    • v.22 no.4
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    • pp.175-196
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    • 2022
  • This study aims to determine the research trends in archival preservation through keyword analysis, understand the current research status, and identify the research topics' changes over time. The degree and betweenness centrality analyses were conducted and visualized on 463 "archival preservation studies" articles published from 2000 to 2021 in various academic journals, using NetMiner 4.0. The collected research papers were divided into three time periods according to when they were published: the first period (2000-2007), the second period (2008-2014), and the third period (2015-2021). The subject keywords for the research papers on archival preservation in Korea that have influence and expandability are as follows. Across all periods, these were "electronic records" and "long-term preservation." In addition, if taken separately per period, the "OAIS reference model" and "electronic records" dominated the first and second periods, respectively, while the "records management standard table" and "long-term preservation" both dominated the third period. A conceptual framework and theory-oriented study for archival preservation, such as "digital preservation," "digitalization," and the "OAIS reference model," dominated the first period. During the second period, more research focused on procedures and practical applications related to conservation activities, such as "electronic record," "appraisal," and "DRAMBORA." In contrast, the majority of the research in the third period was on technical implementation according to the changes in the records management environment, such as "data set," "administrative information system," and "social media."

Oil Price Forecasting Based on Machine Learning Techniques (기계학습기법에 기반한 국제 유가 예측 모델)

  • Park, Kang-Hee;Hou, Tianya;Shin, Hyun-Jung
    • Journal of Korean Institute of Industrial Engineers
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    • v.37 no.1
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    • pp.64-73
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    • 2011
  • Oil price prediction is an important issue for the regulators of the government and the related industries. When employing the time series techniques for prediction, however, it becomes difficult and challenging since the behavior of the series of oil prices is dominated by quantitatively unexplained irregular external factors, e.g., supply- or demand-side shocks, political conflicts specific to events in the Middle East, and direct or indirect influences from other global economical indices, etc. Identifying and quantifying the relationship between oil price and those external factors may provide more relevant prediction than attempting to unclose the underlying structure of the series itself. Technically, this implies the prediction is to be based on the vectoral data on the degrees of the relationship rather than the series data. This paper proposes a novel method for time series prediction of using Semi-Supervised Learning that was originally designed only for the vector types of data. First, several time series of oil prices and other economical indices are transformed into the multiple dimensional vectors by the various types of technical indicators and the diverse combination of the indicator-specific hyper-parameters. Then, to avoid the curse of dimensionality and redundancy among the dimensions, the wellknown feature extraction techniques, PCA and NLPCA, are employed. With the extracted features, a timepointspecific similarity matrix of oil prices and other economical indices is built and finally, Semi-Supervised Learning generates one-timepoint-ahead prediction. The series of crude oil prices of West Texas Intermediate (WTI) was used to verify the proposed method, and the experiments showed promising results : 0.86 of the average AUC.