Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.

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Published by
The International Institute of Informatics and Cybernetics


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Academia.edu
(A Community of about 40.000.000 Academics)


Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Quality Assurance

Editors

Journal's Reviewers
Call for Special Articles
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Transfer Learning for Facial Emotion Recognition on Small Datasets
Paolo Barile, Clara Bassano, Paolo Piciocchi
(pages: 1-5)

How to Link Educational Purposes and Immersive Video Games Development? An Ontological Approach Proposal
Nathan Aky
(pages: 6-13)

Application of Building Information Modeling (BIM) in the Planning and Construction of a Building
Renata Maria Abrantes Baracho, Luiz Gustavo da Silva Santiago, Antonio Tagore Assumpção Mendoza e Silva, Marcelo Franco Porto
(pages: 14-19)

Transformative, Transdisciplinary, Transcendent Digital Education: Synergy, Sustainability and Calamity
Rusudan Makhachashvili, Ivan Semenist
(pages: 20-27)

New Online Tools for the Data Visualization of Bivalve Molluscs' Production Areas of Veneto Region
Eleonora Franzago, Claudia Casarotto, Matteo Trolese, Marica Toson, Mirko Ruzza, Manuela Dalla Pozza, Grazia Manca, Giuseppe Arcangeli, Nicola Ferrè, Laura Bille
(pages: 28-32)

Geodata Processing Methodology on GIS Platforms When Creating Spatial Development Plans of Territorial Communities: Case of Ukraine
Olena Kopishynska, Yurii Utkin, Ihor Sliusar, Leonid Flehantov, Mykola Somych, Oksana Yakovlieva, Olena Scryl
(pages: 33-40)

D-CIDE: An Interactive Code Learning Program
Lukas Grant, Matthew F. Tennyson, Jason Owen
(pages: 41-46)

Interdisciplinary Digital Skills Development for Educational Communication: Emergency and Ai-Enhanced Digitization
Rusudan Makhachashvili, Ivan Semenist, Ganna Prihodko, Irina Kolegaeva, Olexandra Prykhodchenko, Olena Tupakhina
(pages: 47-51)

Interdisciplinarity in Smart Systems Applied to Rural School Transport in Brazil
Renata Maria Abrantes Baracho, Mozart Joaquim Magalhães Vidigal, Marcelo Franco Porto, Beatriz Couto
(pages: 52-59)

Peculiarities of the Realization of IT Projects for the Implementation of ERP Systems on the Path of Digitalization of Territorial Communities Activities
Olena Kopishynska, Yurii Utkin, Ihor Sliusar, Khanlar Makhmudov, Olena Kalashnyk, Svitlana Moroz, Olena Kyrychenko
(pages: 60-67)


 

Abstracts

 


ABSTRACT


The Kernel Estimation in Biosystems Engineering

Esperanza Ayuga Téllez, Mª Angeles Grande Ortiz, Concepción González García, Angel Julián Martín Fernández, Ana Isabel García García


In many fields of biosystems engineering, it is common to find works in which statistical information is analysed that violates the basic hypotheses necessary for the conventional forecasting methods. For those situations, it is necessary to find alternative methods that allow the statistical analysis considering those infringements. Non-parametric function estimation includes methods that fit a target function locally, using data from a small neighbourhood of the point. Weak assumptions, such as continuity and differentiability of the target function, are rather used than “a priori” assumption of the global target function shape (e.g., linear or quadratic). In this paper a few basic rules of decision are enunciated, for the application of the non-parametric estimation method. These statistical rules set up the first step to build an interface usermethod for the consistent application of kernel estimation for not expert users. To reach this aim, univariate and multivariate estimation methods and density function were analysed, as well as regression estimators. In some cases the models to be applied in different situations, based on simulations, were defined. Different biosystems engineering applications of the kernel estimation are also analysed in this review.

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