Mauricio A. SanchezUniversidad Autonoma de Baja California, Tijuana, Mexico · Faculty of Chemical Sciences and Engineering
Mauricio A. Sanchez
PhD
About
42
Publications
5,304
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900
Citations
Introduction
Additional affiliations
August 2016 - present
Autonomous University of Baja California
Position
- Professor
March 2016 - July 2016
January 2012 - January 2016
Autonomous University of Baja California, Tijuana, Mexico
Position
- PhD Student
Publications
Publications (42)
Fuzzy Logic Systems have been popular in fields such as control, knowledge representation, and modeling. They involve linguistic information to represent a human perception in the form of Fuzzy Sets. Those systems are advantageous in cases where it is desired to have some interpretability. However, there are some processes, such as optimization, wh...
Interpretable machine learning is trending as it aims to build a human-understandable decision process. There are two main types of machine learning systems: white-box and black-box models. White-box models are inherently interpretable but commonly suffer from under-fitting phenomena; on the other hand, black-box models perform quite well in a wide...
The aim of this work is to present a model for heat transfer, desorbed refrigerant, and pressure of an intermittent solar cooling system’s thermochemical reactor based on backpropagation neural networks and mathematical symmetry groups. In order to achieve this, a reactor was designed and built based on the reaction of BaCl2-NH3. Experimental data...
This study intends to establish the main relations between topographic characteristics of the watershed and the main parameters of the unit hydrograph measured at the outlet. It looks to remove the subjectivity found in traditional synthetic methods and the trial and error setting of the main parameters of the hydrograph. The work was developed thr...
The optimization algorithms based on gradients have a series of hyperparameters that will allow among other things to reach a global minimum of the error function, convergence, and at an adequate velocity, trying to avoid overtraining, divergent solutions and overload of computation to execute an exaggerated number of iterations for its process, he...
The Industrial Internet of Things (IIoT) consists of sensors, networks, and services to connect and control production systems. Its benefits include supply chain monitoring and machine failure detection. However, it has many vulnerabilities, such as industrial espionage and sabotage. Furthermore, many IIoT devices are resource-constrained, which im...
Throughout previous design proposals of Interval Type-2 Fuzzy Logic Systems most of the research work concentrates on optimal design to best fit data behavior and rarely focus on the inner model essence of Type-2 Fuzzy Systems, which is uncertainty. In this way, failing to focus on this key aspect, which is how much uncertainty exists within the mo...
Due to the rapid technological evolution and communications accessibility, data generated from different sources of information show an exponential growth behavior. That is, volume of data samples that need to be analyzed are getting larger, so the methods for its processing have to adapt to this condition, focusing mainly on ensuring the computati...
This work attempts to contribute to shortening the gap between the original conception of ubicomp and the current state of the art. Thus, the original concept has been analyzed to identify one of the main advances required to achieve this. Authors consider that context-awareness is the key element to accomplish this goal and compare the context-awa...
Machine Learning (ML) is a method that aims to learn from data to identify patterns and make predictions. Nowadays ML models have become ubiquitous, there are so many services that people use in their daily life, consequently, those systems affect in very ways to the final users. Recently, there is a special interest on the right of the final user...
As systems evolve into interconnected heterogeneous components, their security threats increase in number and complexity, and static security measures are not capable of confronting all of them. A strategy to address this issue is the use of autonomic software, which adapts the security mechanisms at runtime according to the environmental changes t...
This book gathers a collection of the latest research, applications, and proposals, introducing readers to innovations and concepts from diverse environments and systems. As such, it will provide students and professionals alike with not only cutting-edge information, but also new inspirations and potential research directions.
Each chapter focuse...
The Internet of Things (IoT) paradigm envisions a world where everyday things interchange information between each other in a way that allows users to make smarter decisions in a given context. Even though IoT has many advantages, its characteristics make it very vulnerable to security attacks. Ciphers are a security primitive that can prevent some...
In this paper a new method for the parameterization of general type-2 fuzzy membership functions. The proposed method describes the methodology, equations and pseudo-code for building a set of general type-2 membership functions, which are a combination of two Gaussian-type primary membership functions (Gaussian with uncertain mean, and Gaussian wi...
This book presents a collection of research findings and proposals on computer science and computer engineering, introducing readers to essential concepts, theories, and applications. It also shares perspectives on how cutting-edge and established methodologies and techniques can be used to obtain new and interesting results. Each chapter focuses o...
In an attempt to support efforts to narrow the gap between current Artificial Intelligence and actual intelligent human behavior, this paper addresses Tacit Knowledge. Tacit Knowledge is analyzed and separated into articulable and inarticulable for ease of scrutiny. Concepts and ideas are taken up from knowledge management literature aiming to unde...
The boom of technologies such as social media, mobile devices, internet of things, and so on, has generated enormous amounts of data that represent a tremendous challenge, since they come from different sources, different formats and are being generated in real time at an exponential speed which brings with it new necessities, opportunities, and ma...
In the search of modeling methodologies for complex systems various attempts have been made, and so far, all have been inadequate in one thing or another leading the pathway open for the next better tool. Fuzzy cognitive maps have been one of such tools, although mainly used for decision making in what-if scenarios, they can also be used to represe...
As Granular Computing has gained interest, more research has lead into using different representations for Information Granules, i.e., rough sets, intervals, quotient space, fuzzy sets; where each representation offers different approaches to information granulation. These different representations have given more flexibility to what information gr...
This work is focused on creating fuzzy granular classification models based on general type-2 fuzzy logic systems when consequents are represented by interval type-2 TSK linear functions. Due to the complexity of general type-2 TSK fuzzy logic systems, a hybrid learning approach is proposed, where the principle of justifiable granularity is heurist...
This paper presents a literature review of applications using type-2 fuzzy systems in the area of image processing. Over the last years, there has been a significant increase in research on higher-order forms of fuzzy logic; in particular, the use of interval type-2 fuzzy sets and general type-2 fuzzy sets. The idea of making use of higher orders,...
This paper proposes a new method for the formation of fuzzy higher type granular models. This is accomplished by directly discovering uncertainty from a sample of numerical information. In this case the coefficient of variation is proposed as a heuristic for measuring uncertainty, where a direct relation between this measure and the footprint of un...
All experimentation is focused on the previously shown approaches to fuzzy information granulation. Most experiments were done with benchmark datasets
which will be described in the following paragraph. Two benchmark dataset types were used: classification, and identification.
The focus of this book emphasizes the field of Granular Computing
, where by nature is a vast area still under development. This section summarizes this matter as well as derived topics which aid Granular Computing, such as Fuzzy Sets and clustering algorithms.
This book is a research compendium in the area of Fuzzy Granular Computing
. Two main branches are handled, a proposed fuzzy granulating algorithm, and higher-type information granuleHigher-type information granule
formation, although more work was performed on the latter.
In this book, a series of granular algorithms are proposed. A nature inspired granular algorithm based on Newtonian gravitational forces is proposed. A series of methods for the formation of higher-type information granules represented by Interval Type-2 Fuzzy Sets are also shown, via multiple approaches, such as Coefficient of Variation, principle...
This paper proposes a new method for directly discovering the uncertainty from a sample of discrete data, which is then used in the formation of an Interval Type-2 Fuzzy Inference System. A Coefficient of Variation is used to measure the uncertainty on a finite sample of discrete data. Based on the maximum possible coverage area of the Footprint of...
Mobile ad-hoc networks (MANETs) are dynamic by nature; this dynamism comes from node mobility, traffic congestion, and other transmission conditions. Metrics to evaluate the effects of those conditions shine a light on node’s behavior in an ad-hoc network, helping to identify the node or nodes with better conditions of connection. In this paper, we...
Simulation data results.
Data from Omnet++ simulations used in results section.
(XLSX)
A method for Higher Order polynomial Sugeno Fuzzy Inference Systems formation is presented. Compared to other existing Higher Order Sugeno implementations, it uses fewer parameters; and compared to Zero and 1st Order Sugeno Fuzzy Systems it has overall improved model performance. While best models are not always obtained via a Higher Order represen...
In this paper a granular approach for intelligent control using generalized type-2 fuzzy logic is presented. Granularity is used to divide the design of the global controller into several individual simpler controllers. The theory of alpha planes is used to implement the generalized type-2 fuzzy systems. The proposed method for control is applied t...
This paper proposes a new method for directly discovering the uncertainty from a sample of discrete data, which is then used in the formation of an Interval Type-2 Fuzzy Inference System. A Coefficient of Variation is used to measure the uncertainty on a finite sample of discrete data. Based on the maximum possible coverage area of the Footprint of...
The aim of this paper is to show that a Generalized Type-2 Fuzzy Control System can outperform Type-1 and Interval Type-2 Fuzzy Control Systems when external perturbations are present. A Generalized Type-2 Fuzzy System can handle better uncertainty because of the nature of its membership functions, and as such, they are better tailored for situatio...
A technique for forming information granules is shown in this paper. Based on the theory of uncertainty-based information, an approach toward a general base is given which forms information granules. Two implementations are proposed which form Interval Type-2 Fuzzy information granules, both with Takagi–Sugeno–Kang consequents optimized with Cuckoo...
A new method for finding fuzzy information granules from multivariate data through a gravitational inspired clustering algorithm is proposed in this paper. The proposed algorithm incorporates the theory of granular computing, which adapts the cluster size with respect to the context of the given data. Via an inspiration in Newton's law of universal...
A new technique for forming information granules is shown in this chapter. Based on the theory of uncertainty-based information, an approach is proposed which forms Interval Type-2 Fuzzy information granules. This approach captures multiple evaluations of uncertainty from taken samples and uses these models to measure the uncertainty from the diffe...
In this paper, a new hybrid method for forming interval type 2 fuzzy inference systems (IT2 FIS) is shown. This methodology builds upon an existing type 1 fuzzy inference system (T1 FIS) or from the output centers from any clustering algorithm, calculating the footprint of uncertainty (FOU) based on the implementation of the principle of justifiabl...
This paper shows a new technique for forming fuzzy Gaussian membership functions based on the numerical evidence which is found in its information granule. Inspired by the principle of justifiable granularity, and by obtaining a meaningful granule of information, general type-2 Gaussian membership functions are created which better represent a piec...
The initial process for the granulation of information is the clustering of
data, once the relationships between this data have been found these become
clusters, each cluster represents a coarse granule, whereas each data point
represents a fine granule. All clustering algorithms find these relationships by
different means, yet the notion of the pr...
The initial process for the granulation of information is the clustering of data, once the relationships between this data have been found these become clusters, each cluster represents a coarse granule, whereas each data point represents a fine granule. All clustering algorithms find these relationships by different means, yet the notion of the pr...
The initial process for the granulation of information is the clustering of data, once the relationships between this data have been found these become clusters, each cluster represents a coarse granule, whereas each data point represents a fine granule. All clustering algorithms find these relationships by different means, yet the notion of the pr...
Given the nature of clustering algorithms of finding automatically, or semi-automatically, an unspecified number of clusters, much work has been done in this area. This paper will introduce a proposed gravitational model for finding clusters, the algorithm is based on the gravitational forces from Newton's law of universal gravitation and the outpu...
Projects
Projects (3)
After prodigious success of seven annual conferences, we are now proudly announcing the 8th Congreso Internacional de Investigacion Tijuana (CI2T) and would like to continue our success journey further.
The Conference Organizing Committee remains vigilant in monitoring the COVID-19 pandemic and our decision was to plan this event in a webinar allowing many more people to participate without risk due to the current health contingency.
Organizing Committee cordially invites participants from all over the world to attend 8th Congreso Internacional de Investigación Tijuana, scheduled during April 25-28, 2022 at Webinar.
The CI2T will take place completely in virtual form, organized by the Faculty of Chemical Sciences and Engineering of the Autonomous University of Baja California, Tijuana campus, as a bilingual dissemination platform (English/Spanish) for professors, researchers, students, graduates, and professionals , where theoretical and / or practical works will be presented. VIRTUAL CI2T 2022 provides an ideal platform and opportunity to network with scientific and academic communities as well as directors, presidents, plant engineers, regulatory specialists, industry experts, manufacturers, brand marketers, advertising agencies executives and business intelligence experts.
Our group promotes the strategic link between the industrial, academic, scientific, environmental and social sectors for the technological development and innovation that allow addressing priority problems worldwide.
Conferences
The CI2T 2022 is composed of the following tracks:
SASSSI 3nd Symposium on Applied Sciences for Solving Society's Issues
CST 5th Conference on Chemical Sciences and Technology
CoCSCE 5th Conference on Computer Science and Computer Engineering
CoEE 5th Conference on Electronics Engineering
ICIP 5th International Conference on Industrial Projects
Important dates
Abstract and paper submission deadline: January 30, 2022
Notification of acceptance: February 28, 2022
Camera ready deadline: March 15, 2022
Payment registration March 31, 2022
Conference April 25-28, 2022
http://ci2t.tij.uabc.mx/index.php
After prodigious success of six annual conferences, we are now proudly announcing the 7th Congreso Internacional de Investigacion Tijuana (CI2T) and would like to continue our success journey further.
The Conference Organizing Committee remains vigilant in monitoring the COVID-19 pandemic and our decision was to plan this event in a webinar allowing many more people to participate without risk due to the current health contingency.
Organizing Committee cordially invites participants from all over the world to attend 7th Congreso Internacional de Investigacion Tijuana, scheduled during May 12-13, 2021 at Webinar.
The CI2T will take place completely in virtual form, organized by the Faculty of Chemical Sciences and Engineering of the Autonomous University of Baja California, Tijuana campus, as a bilingual dissemination platform (English / Spanish) for professors, researchers, students, graduates, and professionals , where theoretical and / or practical works will be presented. VIRTUAL CI2T 2021 provides an ideal platform and opportunity to network with scientific and academic communities as well as directors, presidents, plant engineers, regulatory specialists, industry experts, manufacturers, brand marketers, advertising agencies executives and business intelligence experts.
Our group promotes the strategic link between the industrial, academic, scientific, environmental and social sectors for the technological development and innovation that allow addressing priority problems worldwide.
The CI2T 2021 is composed of the following tracks:
CoCSCE 4th Conference on Computer Science and Computer Engineering
CoEE 4th Conference on Electronics Engineering
ICIP 4th International Conference on Industrial Projects
CST 4th Conference on Chemical Sciences and Technology
SASSSI 2nd Symposium on Applied Sciences for Solving Society's Issues
http://ci2t.tij.uabc.mx/
Paper submission deadline: March 29, 2021
Notification of acceptance: April 16, 2021
Camera ready deadline: April 30, 2021
Payment registration: May 1-7,2021
Conference: May 12-13, 2021
To build a university-wide system to predict when a student might dropout based on their current academic trayectory.
