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


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Editorial Advisory Board's Chair
William Lesso

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

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Behavior of Cell in Uniform Shear Flow Field between Rotating Cone and Stationary Plate
Shigehiro Hashimoto, Hiromi Sugimoto, Haruka Hino
(pages: 1-7)

Teachers Continuing Professional Development: Trends in European Countries. Towards Teachers' Professionalism
Liliana Budkowska, Pawel Poszytek
(pages: 8-12)

Play, Connect and Learn: Using Mobile Phones to Improve Early Grade Reading Skills at Home
Ira Joshi
(pages: 13-16)

May Parental Reading Behavior Explain the Gender Differences in Subteeners’ Reading Attitude?
Aniko Joó, Erzsébet Dani
(pages: 17-22)

Leadership and Literacy Processes in School Improvement Creating and Supporting a Community of Success: A Case Study Examining the Principal’s Role in the Reconstitution of a Campus to Transform Literacy and Learning
W. Todd Duncan, Lisa E. Colvin
(pages: 23-28)

Rwandan Collaborative Model for Educator Capacity Building
Andrew Moore, Vincentie Nyangoma, Jaco Du Toit, Peter Wallet, Pascal Rukundo
(pages: 29-35)

Do You Know Where Your Students Are? Digital Supervision and Digital Privacy in Schools
Lorayne Robertson, Laurie Corrigan
(pages: 36-42)

A General Case Study of Complexity Science: Analytical and Logical Interconnection Between Soft and Hard Sciences (Invited Paper)
Jack Jia-Sheng Huang, Yu-Heng Jan
(pages: 43-48)

Novel Application of Immobilized Bacillus Cells for Biotreatment of Furfural-Laden Wastewater
Haneen A. Khudhair, Zainab Z. Ismail
(pages: 49-54)

Reliable Sub-Nanosecond Switching of a Perpendicular SOT-MRAM Cell without External Magnetic Field
Viktor Sverdlov, Alexander Makarov, Siegfried Selberherr
(pages: 55-59)

The Methodology and Implementation of Unique Technology Focused Entrepreneurship/Intrepreneurship Programs
Stephen A. Szygenda, Diana M. Easton
(pages: 60-66)

Intelligent Fault Pattern Recognition of Aerial Photovoltaic Module Images Based on Deep Learning Technique
Xiaoxia Li, Qiang Yang, Wenjun Yan, Zhebo Chen
(pages: 67-71)

Real-Time Implementation of Model Predictive Control in a Low-Cost Embedded Device
John Espinoza, Jorge Buele, Esteban X. Castellanos, Marco Pilatásig, Paulina Ayala, Marcelo V. García
(pages: 72-77)

Real-Time Sentimental Polarity Classification on Live Social-Media
Khalid N. Alhayyan, Imran Ahmad
(pages: 78-84)

Information Modeling and Information Retrieval for the Internet of things (IoT) in Buildings
Renata Baracho, Izabella Cunha, Mário Lúcio Pereira Junior
(pages: 85-91)


 

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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