A tutorial on reproducing a predefined autocovariance function through AR models: application to stationary homogeneous isotropic turbulence

Sequential methods for synthetic realisation of random processes have a number of advantages compared with spectral methods. In this article, the determination of optimal autoregressive (AR) models for reproducing a predefined target autocovariance function of a random process is addressed. To this end, a novel formulation of the problem is developed. This formulation is linear and generalises the well-known Yule-Walker (Y-W) equations and a recent approach based on restricted AR models (Krenk-Møller approach, K-M). Two main features characterise the introduced formulation: (i) flexibility in the choice for the autocovariance equations employed in the model determination, and (ii) flexibility in the definition of the AR model scheme. Both features were exploited by a genetic algorithm to obtain optimal AR models for the particular case of synthetic generation of homogeneous stationary isotropic turbulence time series. The obtained models improved those obtained with the Y-W and K-M approaches for the same model parsimony in terms of the global fitting of the target autocovariance function. Implications for the reproduced spectra are also discussed. The formulation for the multivariate case is also presented, highlighting the causes behind some computational bottlenecks.

Extraction of Beta-Carotene as Natural Dyes from Cucumis Melo Via Soxhlet Extraction Method

Natural dyes are pronounced as an interesting alternative to fabricated dyes. Accordingly, the attractive demand to develop the extraction techniques of the best ingredients of solid and liquid for natural dyes colorants from fruits materials and their application in human life. Extraction is processed using solvents or using modern techniques like ultrasonication and microwave. In this respect, the extraction of natural colorant from Cucumis melo has been investigated as a model. Determination of the structure of active ingredients was performed conducted by UV spectroscopy and gravimetrical analysis. Through the analysis of the results, it will be confirmed that the dye extracted from Cucumis melo of intense color is beta-carotene, which is considered as one of the most colored dyes. Therefore, we recommend using such dyes in the industrial fields especially for coloring and decorating sweets.

Energy Efficiency Analysis of the Refining Unit in Thermo-Mechanical Pulp Mill

A refining model is developed to analyses the refining process’s energy efficiency based on the refining variables. A simulation model is obtained for longer-term refining energy analysis by further developing the MATLAB Thermo-Mechanical Pulping Simulink toolbox. This model is utilized to predict two essential variables for refining energy efficiency calculation: refining motor-load and generated steam. The conventional variable for presenting refining energy efficiency is refining specific energy consumption (RSEC), which is the ratio of the refining motor load to throughput and does not consider the share of recovered energy from the refining produced steam. In this study, a new variable, corrected refining specific energy consumption (CRSEC), is introduced and practiced for better representation of the refining energy efficiency. In the calculation process of the CRSEC, recovered energy from the refining generated steam is considered useful energy. The developed model results in 160% and 78.75% improvement in simulation model determination coefficient and error, respectively. Utilizing the developed model and hourly district heating demand for CRSEC calculation, results prove a 22% annual average difference between CRSEC and RSEC. Findings confirm that the wintertime refining energy efficiency is 27% higher due to higher recovered energy in the heat recovery unit compared to summertime.

Consequences of COVID-19 on Imports and Exports of China with Forecasted Error and Future Trends

Purpose- The primary motivation behind this paper is to break down results of Coronavirus on imports and fares of China with anticipated mistake and future patterns. Design/methodology/approach - The paper depends on an Auto Backward Coordinated Moving Normal model with explicit suggestion of Box and Jenkins approach each year complete assessment of imports and fares of China as of the year 1950-2016 through supportive quantifiable programming R. It is found that ARIMA (0, 2, 2) and ARIMA (0, 2, 1) model appear to be to be sensible to measure full scale yearly imports and fares of China independently. Findings - After the control of COVID plague Chinese imports and fares will extend a tiny bit at a time and after the skirmish of three years get the figure (153609.6) in 2022, it will get the figure (153096.8) of 2019. After 2022, the advancement movement of Chinese imports and fares will be extended in a reliably close about a comparative rate before the attack of novel COVID. Research limitations/implications - The foremost restriction of the research work it is merely support on secondary data. Practical implications - The scientist can utilize these models for determining yearly imports and fares of China. Any way it ought to be refreshed opportunity to time with a consolidation of current information. It is most significant that the scientist ought to consistently follow the guideline of stinginess and attempt to fit straightforward model rather than model with enormous boundaries. Originality/value - The uniqueness of this article is that it features the select models for gauging import and fare of China. It was discovered that AIC based model determination methods provided ARIMA models with request (0, 2, 2) and request (0, 2, 1) for imports and fares of China separately were proper and helps in advancing money related incorporation with brings about higher monetary development and unfamiliar financial specialists.

V band photometry of asteroids from the All-Sky Automated Survey for Supernovae

<p>The All-Sky Automated Survey for Supernovae (ASAS-SN) currently<br />operates 24 small-aperture telescopes distributed around the globe to<br />automatically survey the entire visible sky every night down to about<br />g~18 mag. Between 2013 and 2018, the survey used a V filter with<br />limiting magnitude V~17. Although primarily hunting for supernovae and<br />other transients, asteroids are common intruders in the ASAS-SN's<br />images. Here we present efforts to analyze the sparsely sampled V-band<br />photometry extracted from the ASAS-SN images for >10,000 asteroids<br />that get brighter than V~17 mag. The data span years 2013-2018 and<br />sample up to 7 consequent apparitions for each asteroid. We provide<span class="im"><br />details about the photometry extraction and calibration, photometry<br />accuracy, and various statistics such as the typical number of data<br />points per asteroid as a function of the brightness. Finally, we<br /></span> analyze the photometric data with the lightcurve inversion method and<br />derive rotation periods, spin axis directions, and shapes for a sample<span class="im"><br />of studied asteroids. We discuss the typical amount of data sufficient<br />for a successful shape model determination. We compare derived<br />physical properties with those available in the literature to<br /></span> illustrate the reliability of the ASAS-SN photometry.</p>