• Title/Summary/Keyword: Periodicity

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ANALYSIS OF SAMBOK IN KOREA (한국의 삼복 일자 분석)

  • Mihn, Byeong-Hee;Lee, Ki-Won;Ahn, Young Sook;Ahn, Sang-Hyeon;Lee, Yong Sam
    • Publications of The Korean Astronomical Society
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    • v.29 no.1
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    • pp.1-16
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    • 2014
  • Sambok (三伏, Three Hottest Days) is the common designation of Chobok (初伏, Early Hot Day), Jungbok (中伏, Middle Hot Day), and Malbok (末伏, Late Hot Day), and widely known to be one of the Korean folk customs. Hence, Sambok is notated in Manseryeok (Ten Thousand-Year Almanac) and in the annual astronomical almanac published by Korea Astronomy and Space Science Institute. In this paper, we investigate the changes of Sambok in Korea based on various documents such as Joseonwangjosilok (朝鮮王朝實錄, Annals of the Joseon Dynasty), Jeungbo-Jakryeoksik (增補作曆式, The Supplement of Manual for Calendar Making), astronomical almanacs, and so forth. According to Jeungbo-Jakryeoksik preserved in Kyujanggak Institute for Korean Studies, Chobok and Jungbok are defined as the third and fourth Gyeongil (庚日, The Day Starting with the Seventh Heavenly Stems in Sexagenary Cycles Assigned to Each Day) after the summer solstice, respectively, and Malbok is the first Gyeongil after Ipchu (Enthronement of Autumn). However, if the summer solstice is Gyeongil, then the third Gyeongil counting from the solstice becomes Chobok. Malbok depends on the time of Ipchu. Ipchu itself becomes Malbok if the time of Ipchu is in the morning, or next Gyeongil becomes Malbok if it is the afternoon. On the other hand, Malbok is defined as Ipchu itself regardless of its time according to Chiljeongbobeob (七政步法, Calculating Method for Sun, Moon, and Five Planets), Chubocheobryeo (推步捷例, Quick Examples for Calendrical Calculations), and so on. To verify the methods used to determine Sambok, we examined the record in the extant almanacs during the period of 1392 to 2100 for which the summer solstice or Ipchu is Gyeongil. As a result, we found a periodicity that if the time of Ipchu is in the morning, in general, the time is in the afternoon after two years and then is back into in the morning after nineteen years, i.e., the 2 + 19 years periodicity. However, we found the 2 + 17 years periodicity in some years. We also found that the Chobok method of Jeungbo-Jakryeoksik has been used since 1712, the thirty-eighth reign of King Sukjong (肅宗). In addition, we supposed that Malbok had been determined by the method like Chubocheobryeo since either 1846, the twelfth reign of King Heonjong (憲宗), or 1867, the fourth reign of King Gojong (高宗). At present, these methods of Sambok are customarily used without any legal basis. We, therefore, think that this study will help conventionalize the method defining Sambok in the future.

Forecast of the Daily Inflow with Artificial Neural Network using Wavelet Transform at Chungju Dam (웨이블렛 변환을 적용한 인공신경망에 의한 충주댐 일유입량 예측)

  • Ryu, Yongjun;Shin, Ju-Young;Nam, Woosung;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.45 no.12
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    • pp.1321-1330
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    • 2012
  • In this study, the daily inflow at the basin of Chungju dam is predicted using wavelet-artificial neural network for nonlinear model. Time series generally consists of a linear combination of trend, periodicity and stochastic component. However, when framing time series model through these data, trend and periodicity component have to be removed. Wavelet transform which is denoising technique is applied to remove nonlinear dynamic noise such as trend and periodicity included in hydrometeorological data and simple noise that arises in the measurement process. The wavelet-artificial neural network (WANN) using data applied wavelet transform as input variable and the artificial neural network (ANN) using only raw data are compared. As a results, coefficient of determination and the slope through linear regression show that WANN is higher than ANN by 0.031 and 0.0115 respectively. And RMSE and RRMSE of WANN are smaller than those of ANN by 37.388 and 0.099 respectively. Therefore, WANN model applied in this study shows more accurate results than ANN and application of denoising technique through wavelet transforms is expected that more accurate predictions than the use of raw data with noise.

Learning Method for Regression Model by Analysis of Relationship Between Input and Output Data with Periodicity (주기성을 갖는 입출력 데이터의 연관성 분석을 통한 회귀 모델 학습 방법)

  • Kim, Hye-Jin;Park, Ye-Seul;Lee, Jung-Won
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.7
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    • pp.299-306
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    • 2022
  • In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

ON POSITIVE SOLUTIONS OF A RECIPROCAL DIFFERENCE EQUATION WITH MINIMUM

  • QINAR CENGIZ;STEVIC STEVO;YALQINKAYA IBRAHIM
    • Journal of applied mathematics & informatics
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    • v.17 no.1_2_3
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    • pp.307-314
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    • 2005
  • In this paper we consider positive solutions of the following difference equation $$x_{n+l}\;=\;min[{\frac{A}{x_{n}},{\frac{B}{x_{n-2}}}],\;A,B\;>\;0$$. We prove that every positive solution is eventually periodic. Also, we present here some results concerning positive solutions of the difference equation $$x_{n+l}\;=\;min[{\frac{A}{x_{n}x_{n-1}{\cdots}x_{n-k}},{\frac{B}{x_{n-(k+2)}{\cdots}x_{n-(2k+2)}}],\;A,B\;>\;0$$.

Development of the equipment for detecting the poor power facilities by receiving electric noises (전자파 잡음을 이용한 전기설비 불량 검출장치 개발)

  • 이복규;강성철
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1356-1359
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    • 1997
  • There are various methods to detect the faulty electric facilities(esp, insulator) indirectly on power distribution lines at a certain distance apart. This paper describes the proto type equipment to detect a faulty insulator by receiving a electric discharge noises, which are generated with a periodicity of 120Hz.

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A Dynamic-Stochastic Model for Air Pollutant Concentration (大氣汚染濃度에 관한 動的確率모델)

  • 김해경
    • Journal of Korean Society for Atmospheric Environment
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    • v.7 no.3
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    • pp.156-168
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    • 1991
  • The purpose of this paper is to develop a stochastic model for daily sulphur dioxide $(SO_2)$ concentrations prediction in urban area (Seoul). For this, the influence of the meteorological parameters on the $SO_2$ concentrations is investigated by a statistical analysis of the 24-hr averaged $SO_2$ levels of Seoul area during 1989 $\sim$ 1990. The annual fluctuations of the regression trend, periodicity and dependence of the daily concentration are also analyzed. Based on these, a nonlinear regression transfer function model for the prediction of daily $SO_2$ concentrations is derived. A statistical procedure for using the model to predict the concentration level is also proposed.

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Detection of Laryngeal Pathology in Speech Using Multilayer Perceptron Neural Networks (다층 퍼셉트론 신경회로망을 이용한 후두 질환 음성 식별)

  • Kang Hyun Min;Kim Yoo Shin;Kim Hyung Soon
    • Proceedings of the KSPS conference
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    • 2002.11a
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    • pp.115-118
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    • 2002
  • Neural networks have been known to have great discriminative power in pattern classification problems. In this paper, the multilayer perceptron neural networks are employed to automatically detect laryngeal pathology in speech. Also new feature parameters are introduced which can reflect the periodicity of speech and its perturbation. These parameters and cepstral coefficients are used as input of the multilayer perceptron neural networks. According to the experiment using Korean disordered speech database, incorporation of new parameters with cepstral coefficients outperforms the case with only cepstral coefficients.

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ON PARTIAL VALUE SHARING RESULTS OF MEROMORPHIC FUNCTIONS WITH THEIR SHIFTS AND ITS APPLICATIONS

  • Noulorvang, Vangty;Pham, Duc Thoan
    • Bulletin of the Korean Mathematical Society
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    • v.57 no.5
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    • pp.1083-1094
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    • 2020
  • In this paper, we give some uniqueness theorems of nonconstant meromorphic functions of hyper-order less than one sharing partially three or four small periodic functions with their shifts. As an application, some sufficient conditions for periodicity of meromorphic functions are given. Our results improve and extend previous results of W. Lin, X. Lin and A. Wu [11].