• Title/Summary/Keyword: Time-series matching

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A Two-Phase Stock Trading System based on Pattern Matching and Automatic Rule Induction (패턴 매칭과 자동 규칙 생성에 기반한 2단계 주식 트레이딩 시스템)

  • Lee, Jong-Woo;Kim, Yu-Seop;Kim, Sung-Dong;Lee, Jae-Won;Chae, Jin-Seok
    • The KIPS Transactions:PartB
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    • v.10B no.3
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    • pp.257-264
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    • 2003
  • In the context of a dynamic trading environment, the ultimate goal of the financial forecasting system is to optimize a specific trading objective. This paper proposes a two-phase (extraction and filtering) stock trading system that aims at maximizing the rates of returns. Extraction of stocks is performed by searching specific time-series patterns described by a combination of values of technical indicators. In the filtering phase, several rules are applied to the extracted sets of stocks to select stocks to be actually traded. The filtering rules are automatically induced from past data. From a large database of daily stock prices, the values of technical indicators are calculated. They are used to make the extraction patterns, and the distributions of the discretization intervals of the values are calculated for both positive and negative data sets. We assumed that the values in the intervals of distinctive distribution may contribute to the prediction of future trend of stocks, so the rules for filtering stocks are automatically induced from the data in those intervals. We show the rates of returns when using our trading system outperform the market average. These results mean rule induction method using distributional differences is useful.

An Index Interpolation-based Subsequence Matching Algorithm supporting Normalization Transform in Time-Series Databases (시계열 데이터베이스에서 인덱스 보간법을 기반으로 정규화 변환을 지원하는 서브시퀀스 매칭 알고리즘)

  • No, Ung-Gi;Kim, Sang-Uk;Hwang, Gyu-Yeong
    • Journal of KIISE:Databases
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    • v.28 no.2
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    • pp.217-232
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    • 2001
  • 본 논문에서는 시계열 데이터베이스에서 정규화 변환을 지원하는 서브시퀀스 매칭 알고리즘을 제안한다. 정규화 변환을 시계열 데이터 간의 절대적인 유클리드 거리에 관계 없이, 구성하는 값들의 상대적인 변화 추이가 유사한 패턴을 갖는 시계열 데이터를 검색하는 데에 유용하다. 기존의 서브시퀀스 매칭 알고리즘을 확장 없이 정규화 변환 서브시퀀스 매칭에 단순히 응용할 경우, 질의 결과로 반환되어야 할 서부시퀀스를 모두 찾아내지 못하는 착오 기각이 발생한다. 또한, 정규화 변환을 지원하는 기존의 전체 매칭 알고리즘의 경우, 모든 가능한 질의 시퀀스 길이 각각에 대하여 하나씩의 인덱스를 생성하여야 하므로, 저장 공간 및 데이터 시퀀스 삽입/삭제의 부담이 매우 심각하다. 본 논문에서는 인덱스 보간법을 이용하여 문제를 해결한다. 인덱스 보간법은 인덱스가 요구되는 모든 경우 중에서 적당한 간격의 일부에 대해서만 생성된 인덱스를 이용하며, 인덱스가 필요한 모든 경우에 대한 탐색을 수행하는 기법이다. 제안된 알고리즘은 몇 개의 질의 시퀀스 길이에 대해서만 각각 인덱스를 생성한 후, 이를 이용하여 모든 가능한 길이의 질의 시퀀스에 대해서 탐색을 수행한다. 이때, 착오 기각이 발생하지 않음을 증명한다. 제안된 알고리즘은 질의 시에 주어진 질의 시퀀스의 길이에 따라 생성되어 있는 인덱스 중에서 가장 적절한 것을 선택하여 탐색을 수행한다. 이때, 생성되어 있는 인덱스의 개수가 많을수록 탐색 성능이 향상된다. 필요에 따라 인덱스의 개수를 변화함으로써 탐색 성능과 저장 공간 간의 비율을 유연하게 조정할 수 있다. 질의 시퀀스의 길이 256 ~ 512중 다섯 개의 길이에 대해 인덱스를 생성하여 실험한 결과, 탐색 결과 선택률이 $10^{-2}$일 때 제안된 알고리즘의 탐색 성능이 순차 검색에 비하여 평균 2.40배, 선택률이 $10^{-5}$일 때 평균 14.6배 개선되었다. 제안된 알고리즘의 탐색 성능은 탐색 결과 선택률이 작아질수록 더욱 향상되므로, 실제 데이터베이스 응용에서의 효용성이 높다고 판단된다.

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Efficient Time-Series Subsequence Matching using Duality in Constructing Windows (윈도우를 구성하는 방법의 이원성을 이용한 효율적인 시계열 서부시퀀스 매칭)

  • Mun, Yang-Se;No, Ung-Gi;Hwang, Gyu-Yeong
    • Journal of KIISE:Databases
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    • v.28 no.1
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    • pp.15-30
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    • 2001
  • 서브시퀀스 매칭은 질의 시퀀스와 유사한 서브시퀀스를 가지는 데이터 시퀀스와 해당 서브시퀀스의 위치를 찾는 문제이다. 본 논문에서는 윈도우를 구성하는 방법의 이원성을 이용한 새로운 서부시퀀스 매칭 방법인 Dual-Match는 윈도우를 구성하는 방법에 있어서 Faloutsos 등이 사용한 방법(간단히 FRM 이라한다)의 이원적 접근법이다. 즉, FRM에서는 데이터 시퀀스를 슬라이딩 윈도우로 나누고 질의 시퀀스를 디스조인트 윈도우로 나누는 방법을 사용한 반면, Dual-Match에서는 데이터 시퀀스를 디스조이트 윈도우로 나누고 질의 시퀀스를 슬라이딩 윈도우로 나누는 방법을 사용한다. FRM은 색인에 필요한 저장공간을 줄이기 위하여 개별 점 대신 최소 포함 사각형만을 저장함으로 인하여 많은 착오해답(유사하지 않은 후보 서브시퀀스)을 발생시켰다. Dual-Match는 FRM과 비슷한 크기의 저장공간에 개별 점을 직접 저장함으로써 이 문제를 해결한다. 실험결과, Dual-Match는 많은 경우에 있어서 FRM에 비하여 후보 개수를 크게 줄이고 성능을 향상시켰다. 특히, 선택률이 낮은 경우($10^{-4}$이하)에는 후보 개수를 최대 8800배 까지 줄이고, 페이지 액세스 횟수를 최대 26.9배까지 줄였으며, 성능을 최대 430배까지 향상시켰다. 또한, 동일한 크기의 색인을 생성하는데 있어서 Dual-Match는 FRM보다 4.10~25.6배 빠르게 색인을 구성하였다. 이는 색인 구성시에 CPU 오버헤드의 많은 부분을 차지하는 저차원 변환의 횟수를 FRM에 비해 크게 줄이기 때문이다. 이 같은 결과로 볼 때, Dual-Match는 대용량 데이터베이스에 대한 서부시퀀스 매칭의 성능을 크게 향상시킬 수 있는 획기적인 연구 결과라 믿는다.

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Impact of Road Traffic Characteristics on Environmental Factors Using IoT Urban Big Data (IoT 도시빅데이터를 활용한 도로교통특성과 유해환경요인 간 영향관계 분석)

  • Park, Byeong hun;Yoo, Dayoung;Park, Dongjoo;Hong, Jungyeol
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.5
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    • pp.130-145
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    • 2021
  • As part of the Smart Seoul policy, the importance of using big urban data is being highlighted. Furthermore interest in the impact of transportation-related urban environmental factors such as PM10 and noise on citizen's quality of life is steadily increasing. This study established the integrated DB by matching IoT big data with transportation data, including traffic volume and speed in the microscopic Spatio-temporal scope. This data analyzed the impact of a spatial unit in the road-effect zone on environmental risk level. In addition, spatial units with similar characteristics of road traffic and environmental factors were clustered. The results of this study can provide the basis for systematically establishing environmental risk management of urban spatial units such as PM10 or PM2.5 hot-spot and noise hot-spot.

Twitter Issue Tracking System by Topic Modeling Techniques (토픽 모델링을 이용한 트위터 이슈 트래킹 시스템)

  • Bae, Jung-Hwan;Han, Nam-Gi;Song, Min
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.109-122
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    • 2014
  • People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

Tracking Moving Object using Hierarchical Search Method (계층적 탐색기법을 이용한 이동물체 추적)

  • 방만식;김태식;김영일
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.3
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    • pp.568-576
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    • 2003
  • This paper proposes a moving object tracking algorithm by using hierarchical search method in dynamic scenes. Proposed algorithm is based on two main steps: generation step of initial model from different pictures, and tracking step of moving object under the time-yawing scenes. With a series of this procedure, tracking process is not only stable under far distance circumstance with respect to the previous frame but also reliable under shape variation from the 3-dimensional(3D) motion and camera sway, and consequently, by correcting position of moving object, tracking time is relatively reduced. Partial Hausdorff distance is also utilized as an estimation function to determine the similarity between model and moving object. In order to testify the performance of proposed method, the extraction and tracking performance have tested using some kinds of moving car in dynamic scenes. Experimental results showed that the proposed algorithm provides higher performance. Namely, matching order is 28.21 times on average, and considering the processing time per frame, it is 53.21ms/frame. Computation result between the tracking position and that of currently real with respect to the root-mean-square(rms) is 1.148. In the occasion of different vehicle in terms of size, color and shape, tracking performance is 98.66%. In such case as background-dependence due to the analogy to road is 95.33%, and total average is 97%.

Correction of Lunar Irradiation Effect and Change Detection Using Suomi-NPP Data (VIIRS DNB 영상의 달빛 영향 보정 및 변화 탐지)

  • Lee, Boram;Lee, Yoon-Kyung;Kim, Donghan;Kim, Sang-Wan
    • Korean Journal of Remote Sensing
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    • v.35 no.2
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    • pp.265-278
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    • 2019
  • Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) data help to enable rapid emergency responses through detection of the artificial and natural disasters occurring at night. The DNB data without correction of lunar irradiance effect distributed by Korea Ocean Science Center (KOSC) has advantage for rapid change detection because of direct receiving. In this study, radiance differences according to the phase of the moon was analyzed for urban and mountain areas in Korean Peninsula using the DNB data directly receiving to KOSC. Lunar irradiance correction algorithm was proposed for the change detection. Relative correction was performed by regression analysis between the selected pixels considering the land cover classification in the reference DNB image during the new moon and the input DNB image. As a result of daily difference image analysis, the brightness value change in urban area and mountain area was ${\pm}30$ radiance and below ${\pm}1$ radiance respectively. The object based change detection was performed after the extraction of the main object of interest based on the average image of time series data in order to reduce the matching and geometric error between DNB images. The changes in brightness occurring in mountainous areas were effectively detected after the calibration of lunar irradiance effect, and it showed that the developed technology could be used for real time change detection.

A Review of Acupuncture and Moxibustion for the Treatment of Parkinson's Disease (파킨슨병의 침구치료 동향에 대한 고찰)

  • Lee, Eun;Kang, Ki-Wan;Kim, Lak-Hyung;Kang, Sei-Young;Sun, Seung-Ho;Han, Chang-Ho;Jang, In-Soo
    • The Journal of Internal Korean Medicine
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    • v.35 no.1
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    • pp.12-23
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    • 2014
  • Objectives : The purpose of this study was to report possibility of acupuncture or moxibustion for the treatment of Parkinson's disease (PD) by reviewing literature about its effectiveness. Methods : In this review, PubMed, SCOPUS, Science Direct and CINAHL of EBSCOhost were used to search medical journals, using keywords "Parkinson's disease and acupuncture" and "Parkinson's disease and moxibustion". The search range included randomized controlled trials (RCT) about Parkinson's disease combined with another disease and other treatments with acupuncture or moxibustion. Non-randomized controlled trial (nRCT), case study, animal experiment, human experiment, review, survey, essay, letter, and protocol for review were excluded. Results : From 311 studies, 111 were selected during the title and the screening. Finally, 16 RCTs (15 for acupuncture research and one for moxibustion) were included in this review, after scanning and matching the inclusion and exclusion criteria. The number of patients varied between 5 and 88. A total of 12 studies using electroacupuncture (EA) were classified into acupuncture studies. The body acupuncture studies numbered 4, scalp acupuncture 4, body and scarp acupuncture mixed studies 4, and bee venom, ear and abdomen acupuncture were each one study. In evaluation methods, total effective rate method was used in 9 studies, the Unified Parkinson's Disease Rating Scale (UPDRS) was used in 8, and the Webster score in 2. In addition, the Berg balance scale (BBS), 30 m walking time, steps to walk 30 m, PD motor function score, and Motor Performance Series by Schoppe (MLS) method were used for evaluation. In 15 of the 16 studies, the verum acupuncture group showed significant improvement compared with the control. In 9 studies using total effective rate method, the effective rate was reported as 80.0-97.3% in verum acupuncture groups and 52.6-86.4% in controls. Conclusions : Acupuncture may be a plausible alternative method to care for the long term symptoms and treat movement impairment of Parkinson's disease. However, to confirm this result, high quality studies including randomized, placebo-controlled double-blind trials are warranted.

To Compare and Analyze Costumes in the Film "The Great Gatsby" and Y&Kei Collection (영화 "The Great Gatsby" 의상과 Y&Kei 컬렉션 비교 분석)

  • O, Ji-Hye;Lee, In-Seong
    • The Research Journal of the Costume Culture
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    • v.16 no.6
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    • pp.1050-1063
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    • 2008
  • A movie is a fiction made on a basis of an author's and a writer's imagination, but all sorts of properties mixed with each other and most realistically expresses the era which becomes the background of a movie and acts as a carrier that connects designers with consumers. Thus, this study was carried out to review how the fashion products that designer's intention and commercial value added are expressed in collections by comparing and analysing the costumes in the movie "The Great Gatsby" that described the life of America's upper-class in 1920s and the 04 S/S Y&Kei collection which were proceeding after getting inspiration from this movie. For this, literature materials were inspected in order to make a theoretical review on social and cultural background and costumes history background in 1920s and the photo materials on movie costume were collected and analysed using DVD video captures, as well as the photo materials on 04 S/S Y&Kei were collected and analyzed through the institute providing domestic fashion information. The following conclusion was deduced through this study. First, in 1920s which becomes the background of this study, the slim shape of Flapper which looks like a young and boy became an ideal figure condition and the straight silhouette with low waist line and the short skirt that rose to knee was popular. Second, as a result of analysing movie costume by classifying it in silhouette, colors, and materials, straight silhouette of low waistline with a near colored - tone seen in the pastel series, including white, beige, pink, and gray was mainly constituted and the metal colors like silver and gold were used. As a material, chiffon, satin, velvet, flower patterned prints, and beads were used, which represented luxurious life of women in the upper classes. Third, as a result of comparing and analysing, it turned out that there was a similarity. However, in dress collection for a heroine, some dissimilarity differentiated from a movie costumes was found out in that the dresses in collection expressed moderate beauty and modernism and elegant beauty at the same time by matching a variety of materials and using black color.

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AUTOMATED STREAK DETECTION FOR HIGH VELOCITY OBJECTS: TEST WITH YSTAR-NEOPAT IMAGES (고속이동천체 검출을 위한 궤적탐지 알고리즘 및 YSTAR-NEOPAT 영상 분석 결과)

  • Kim, Dae-Won;Byun, Yong-Ik;Kim, Su-Yong;Kang, Yong-Woo;Han, Won-Yong;Moon, Hong-Kyu;Yim, Hong-Suh
    • Journal of Astronomy and Space Sciences
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    • v.22 no.4
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    • pp.385-392
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    • 2005
  • We developed an algorithm to efficiently detect streaks in survey images and made a performance test with YSTAR-NEOPAT images obtained by the 0.5m telescope stationed in South Africa. Fast moving objects whose apparent speeds exceed 10 arcsec/min are the main target of our algorithm; these include artificial satellites, space debris, and very fast Near-Earth Objects. Our algorithm, based on the outline shape of elongated sources employs a step of image subtraction in order to reduce the confusion caused by dense distribution of faint stars. It takes less than a second to find and characterize streaks present in normal astronomical images of 2K format. Comparison with visual inspection proves the efficiency and completeness of our automated detection algorithm. When applied to about 7,000 time-series images from YSTAR telescope, nearly 700 incidents of streaks are detected. Fast moving objects are identified by the presence of matching streaks in adjoining frames. Nearly all of confirmed fast moving objects turn out to be artificial satellites or space debris. Majority of streaks are however meteors and cosmic ray hits, whose identity is often difficult to classify.