Intonation expressiveness of the text at program sounding

As the amount of media content increases, there is a need for its automated sounding with the most accessible built-in and mobile means. The factors influencing the formation of different intonations were analyzed in the article, the dependences of the change of sound characteristics in accordance with the intonations were mathematically described. In the course of the study, the numerical analysis of sentences was improved using the moving average method for smoothing audio recording, approximation lines for approximate generalization of emotions as mathematical functions, and Fourier transform for volume control. The obtained dependences allow to synthesize the necessary intonations according to the punctuation of the sentence, the presence of emotionally colored vocabulary and psycho-emotional mood of the speaker when reading such a text. As a result of our study, software for emotional sounding of texts was developed, which provides the perception of audio information easier, clearer and more comfortable based on the use of built-in processors of mobile devices.

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Moving average method based air pollution monitoring system using IoT platform

Journal of Physics Conference Series ◽

10.1088/1742-6596/1706/1/012078 ◽

2020 ◽

Vol 1706 ◽

pp. 012078

Author(s):

Anumandla Kiran Kumar ◽

A Sri Lakshmi ◽

P Janaki Nivas Rao

Keyword(s):

Air Pollution ◽

Monitoring System ◽

Average Method ◽

Moving Average ◽

Pollution Monitoring ◽

Air Pollution Monitoring ◽

Iot Platform

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Effect of a multi-lead PCA approach on modified moving average method for T-wave alternans detection

Journal of Medical Engineering & Technology ◽

10.3109/03091902.2014.960605 ◽

2014 ◽

Vol 38 (8) ◽

pp. 396-401

Author(s):

Aruna Deogire ◽

Satish Hamde

Keyword(s):

Average Method ◽

Moving Average ◽

T Wave ◽

T Wave Alternans

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Pemisahan Anomali Regional-Residual pada Metode Gravitasi Menggunakan Metode Moving Average, Polynomial dan Inversion

INDONESIAN JOURNAL OF APPLIED PHYSICS ◽

10.13057/ijap.v3i01.1208 ◽

2016 ◽

Vol 3 (01) ◽

pp. 10 ◽

Cited By ~ 3

Author(s):

Jarot Purnomo ◽

Sorja Koesuma ◽

Mohtar Yunianto

Keyword(s):

Average Method ◽

Moving Average ◽

Continuation Method ◽

Inversion Method ◽

Polynomial Method ◽

Minimum Error ◽

Gravity Method ◽

Upward Continuation ◽

And Inversion ◽

Separation Results

It has been done a research about separation of regional-residual anomaly in Gravity method. This research compares the result of three methods i.e. moving average method, polynomial method, and inversion method. The computer program is created using a computer programming Matlab 7. From three methods that have been made, the separation results are compared with results of separation by using Upward Continuation method. From the results of these comparisons will be available an excellent program of regional-residual anomali separation. The results show that in polynomial method of the order 4 obtained similar contour to the separation by Upward Continuation Software. So that the output of this separation will be treated again with Grav2DC software. The output of this software is the density of rock Grav2DC of the study area. Processing results obtained the minimum error of 1.85% for the separation by polynomial method, while for the method of Upward Continuation obtained minimum error of 2.22%. The results obtained show that the separation of regional-residual anomali by polynomial method is similar to separation by Upward Continuation method.

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Impulse Parameters Determination using the Moving Average Method for Digitally Measured Lightning Impulse Voltage Record

IEEJ Transactions on Fundamentals and Materials ◽

10.1541/ieejfms.123.55 ◽

2003 ◽

Vol 123 (1) ◽

pp. 55-61 ◽

Cited By ~ 1

Author(s):

Shuji Sato ◽

Tatsuya Harada ◽

Kohei Kaneko ◽

Yoshifumi Tsubouchi

Keyword(s):

Average Method ◽

Moving Average ◽

Impulse Voltage ◽

Lightning Impulse

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MODIFIED MOVING-AVERAGE METHOD IN PROBLEMS OF SHORT-TERM FORECASTING OF TECHNICAL AND ECONOMIC INDICATORS IN HIGH-TECHNOLOGY ENTERPRISES

Bulletin of NTU KhPI Series Strategic Management Portfolio Program and Project Management ◽

10.20998/2413-3000.2016.1174.13 ◽

2016 ◽

Vol 6 (2(1174)) ◽

pp. 58

Author(s):

Igor I. KOVALENKO ◽

Lyubava S. CHERNOVA

Keyword(s):

Average Method ◽

Moving Average ◽

High Technology ◽

Economic Indicators ◽

Short Term ◽

Short Term Forecasting ◽

Technical And Economic Indicators

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Planning Production Capacity Using Time Series Forecasting Method and Linier Programming

Engineering Management Research ◽

10.5539/emr.v7n2p20 ◽

2018 ◽

Vol 7 (2) ◽

pp. 20

Author(s):

M. Tirtana Siregar ◽

S. Pandiangan ◽

Dian Anwar

Keyword(s):

Average Method ◽

Moving Average ◽

Demand Forecasting ◽

Production Capacity ◽

Mean Absolute Percentage Error ◽

Programming Method ◽

Percentage Error ◽

Absolute Percentage Error ◽

Forecasting Method ◽

Planning Production

The objectives of this research is to determine the amount of production planning capacity sow talc products in the future utilizing previous data from january to december in year 2017. This researched considered three forecasting method, there are Weight Moving Average (WMA), Moving Average (MA), and Exponential Smoothing (ES). After calculating the methods, then measuring the error value using a control chart of 3 (three) of these methods. After find the best forecasting method, then do linear programming method to obtain the exact amount of production in further. Based on the data calculated, the method of Average Moving has a size of error value of Mean Absolute Percentage Error of 0.09 or 9%, Weight Moving Average has a size error of Mean Absolute Percentage Error of 0.09 or 9% and with Exponential Method Smoothing has an error value of Mean Absolute Percentage Error of 0.12 or 12%. Moving Average and Weight Moving Average have the same MAPE amount but Weight Moving Average has the smallest amount Mean Absolute Deviation compared to other method which is 262.497 kg. Based on the result, The Weight Moving Average method is the best method as reference for utilizing in demand forecasting next year, because it has the smallest error size and has a Tracking Signal  not exceed the maximum or minimum control limit is ≤ 4. Moreover, after obtained Weight Moving Average method is the best method, then is determine value of planning production capacity in next year using linier programming method. Based on the linier programming calculation, the maximum amount of production in next year by considering the forecasting of raw materials, production volume, material composition, and production time obtained in one (1) working day is 11,217,379 pcs / year, or 934,781 pcs / month of finished product. This paper recommends the company to evaluate the demand forecasting in order to achieve higher business growth.

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