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Forecasting
Special Issues
ITISE 2018: International Conference on Time Series and Forecasting
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ITISE 2018: International Conference on Time Series and Forecasting

A special issue of Forecasting (ISSN 2571-9394).

Deadline for manuscript submissions: closed (15 December 2018) | Viewed by 5636

Special Issue Editor

Prof. Dr. Ignacio Rojas

E-Mail Website
Guest Editor
Information Technology and Telecommunications Engineering, University of Granada, 18010 Granada, Spain
Interests: time series analysis; forecasting; artificial intelligence; biomedical engineering; complex problems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We cordially invite you to contribute to our Special Issue of Forecasting on the theme of "Time Series and Forecasting".

The main goal of this Special Issue, “Special Issue of ITISE 2018”, is to advance new science and methodologies in the fields of time series and forecasting.

ITISE 2018 (International conference on Time Series and Forecasting) seeks to provide a discussion forum for scientists, engineers, educators and students regarding the latest ideas in the foundations, theory, models and applications of Time Series and Forecasting. This is interdisciplinary research, encompassing the disciplines of computer science, mathematics, statistics, forecaster, econometric, etc., in the field of time series and forecasting.

Topics of interest for this Special Issue include, but are not limited to:

  1. Time Series Analysis and Forecasting
  2. Economic and econometric forecasting
  3. Advanced methods and on-line learning in time series
  4. High Dimension and Complex/Big Data forecasting
  5. Hybrid advanced methodologies with evolutionary computation techniques to improve forecasting accuracy.
  6. Forecasting in real problems (finance, transportation, networks, energy, meteorology, e health, environment, etc.)

Prof. Dr. Ignacio Rojas
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forecasting is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Time series
  • Forecasting
  • Econometric
  • Forecasting in real problem

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (1 paper)

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Research

22 pages, 2472 KiB  
Article
Fourier Analysis of Cerebral Metabolism of Glucose: Gender Differences in Mechanisms of Color Processing in the Ventral and Dorsal Streams in Mice
by Philip C. Njemanze, Mathias Kranz and Peter Brust
Forecasting 2019, 1(1), 135-156; https://doi.org/10.3390/forecast1010010 - 30 Sep 2018
Viewed by 4644
Abstract
Conventional imaging methods could not distinguish processes within the ventral and dorsal streams. The application of Fourier time series analysis was helpful to segregate changes in the ventral and dorsal streams of the visual system in male and female mice. The present study [...] Read more.
Conventional imaging methods could not distinguish processes within the ventral and dorsal streams. The application of Fourier time series analysis was helpful to segregate changes in the ventral and dorsal streams of the visual system in male and female mice. The present study measured the accumulation of [18F]fluorodeoxyglucose ([18F]FDG) in the mouse brain using small animal positron emission tomography and magnetic resonance imaging (PET/MRI) during light stimulation with blue and yellow filters, compared to during conditions of darkness. Fourier analysis was performed using mean standardized uptake values (SUV) of [18F]FDG for each stimulus condition to derive spectral density estimates for each condition. In male mice, luminance opponency occurred by S-peak changes in the sub-cortical retino-geniculate pathways in the dorsal stream supplied by ganglionic arteries in the left visual cortex, while chromatic opponency involved C-peak changes in the cortico-subcortical pathways in the ventral stream perfused by cortical arteries in the left visual cortex. In female mice, there was resonance phenomenon at C-peak in the ventral stream perfused by the cortical arteries in the right visual cortex during luminance processing. Conversely, chromatic opponency caused by S-peak changes in the subcortical retino-geniculate pathways in the dorsal stream supplied by the ganglionic arteries in the right visual cortex. In conclusion, Fourier time series analysis uncovered distinct mechanisms of color processing in the ventral stream in males, while in female mice color processing was in the dorsal stream. It demonstrated that computation of colour processing as a conscious experience could have a wide range of applications in neuroscience, artificial intelligence and quantum mechanics. Full article
(This article belongs to the Special Issue ITISE 2018: International Conference on Time Series and Forecasting)
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