Martínez Ríos, Félix Orlando
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Martínez Ríos, Félix Orlando
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Martínez Ríos, Félix Orlando
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fmartin
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ORCID
Scopus Author ID
24339038500
Researcher ID
N-7502-2018

Research Output
Now showing 1 - 10 of 34
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Golden Ratio Annealing for Satisfiability Problems Using Dynamically Cooling Schemes

2008 , Frausto-Solís, Juan , Martínez Ríos, Félix Orlando

Abstract Satisfiability (SAT) Problem is an NP-Complete problem which means no deterministic algorithm is able to solve it in a polynomial time. Simulated Annealing (SA) can find very good solutions of SAT instances if its control parameters are correctly tuned. SA can be tuned experimentally or by using a Markov approach; the latter has been shown to be the most efficient one. Moreover Golden Ratio (GR) is an unconventional technique used to solve many problems. In this paper a new algorithm named Golden Ratio for Simulated Annealing (GRSA) is presented; it is tuned for three different cooling schemes. GRSA uses GR to dynamically decrease the SA temperature and a Markov Model to tune its parameters. Two SA tuned versions are compared in this paper: GRSA and a classical SA. Experimentation shows that the former is much more efficient than the latter. © Springer Nature

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New Particle Swarm Optimizer Algorithm with Chaotic Maps for Combinatorial Global Optimization Problems. An Application to the Deconvolution of Mössbauer Spectra

2024-01-01 , Martínez Ríos, Félix Orlando , Jiménez-López, Omar , Alvarez Guillen, Luis Alejandro

In this chapter, we present a novel method for addressing global optimization problems inspired by evolutionary algorithms found in nature. We integrate the Comprehensive Learning Particle Swarm Optimization (CLPSO) algorithm with random value generation based on chaotic maps. The resulting algorithm is applied to the computationally complex task of deconvoluting Mossbauer spectra. We implement ten chaotic maps to generate random values and compare their performance with traditional random number generators. Through experiments, we demonstrate that the developed algorithm excels in exploring the search space and exhibits fast intensification in finding the global minimum. In addition, we perform a comprehensive review of existing solutions to the Mossbauer spectrum deconvolution problem, highlighting the scarce availability of developments in this area. We also present a user-friendly program designed with an intuitive interface to facilitate the deconvolution process by Spector Mossbauer. This program will be freely distributed without operational restrictions. Experimental validation is performed on Mossbauer spectra generated using the developed program and those obtained by experimental means, affirming the efficiency of the new algorithm conceived. ©Springer.

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Optimization Methods, Mobile Networks and Data Analytics: Applications in Engineering and Industry 4.0 : Editorial

2020 , Marmolejo Saucedo, José Antonio , Martínez Ríos, Félix Orlando , Rodríguez Aguilar, Román

The business world is changing and demands the integration of various engineering techniques to make the operation of the system in general more efficient. Optimization, information security and a prospective business vision is essential for companies to be more productive. The application of new technological solutions to manufacturing and management processes is one of the ways through which digital transformation in the supply chain advances, on the road to industry 4.0. To achieve this, optimization techniques, soft-computing, machine learning and Big Data technologies must be combined. With this integration it is possible to work with real-time sensed data to build and simulate Digital Twins with very high precision. © Springer Nature

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Rethinking the applicability domain analysis in QSAR models

2024 , Mora, Jose R. , Marquez, Edgar A. , Pérez-Pérez, Noel , Contreras-Torres, Ernesto , Perez-Castillo, Yunierkis , Agüero-Chapin, Guillermin , Martínez Ríos, Félix Orlando , Marrero-Ponce, Yovani , Barigye, Stephen J.

Notwithstanding the wide adoption of the OECD principles (or best practices) for QSAR modeling, disparities between in silico predictions and experimental results are frequent, suggesting that model predictions are often too optimistic. Of these OECD principles, the applicability domain (AD) estimation has been recognized in several reports in the literature to be one of the most challenging, implying that the actual reliability measures of model predictions are often unreliable. Applying tree-based error analysis workflows on 5 QSAR models reported in the literature and available in the QsarDB repository, i.e., androgen receptor bioactivity (agonists, antagonists, and binders, respectively) and membrane permeability (highest membrane permeability and the intrinsic permeability), we demonstrate that predictions erroneously tagged as reliable (AD prediction errors) overwhelmingly correspond to instances in subspaces (cohorts) with the highest prediction error rates, highlighting the inhomogeneity of the AD space. In this sense, we call for more stringent AD analysis guidelines which require the incorporation of model error analysis schemes, to provide critical insight on the reliability of underlying AD algorithms. Additionally, any selected AD method should be rigorously validated to demonstrate its suitability for the model space over which it is applied. These steps will ultimately contribute to more accurate estimations of the reliability of model predictions. Finally, error analysis may also be useful in “rational” model refinement in that data expansion efforts and model retraining are focused on cohorts with the highest error rates. © 2024 Springer Nature

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An efficient method to compare latencies in order to obtain the best route for SDN

2017 , Elguea, Lorenzo M. , Martínez Ríos, Félix Orlando

Comparing two or more routes on Internet is difficult owing to the variability of the measurements resulting from the different routes or use conditions. With current tools such as SDN[1], it is important to determine with certainty which the best route between a user and an internet service. This will be achieved with fast measurements which do not affect the operation of the network. With trends such as IoT, the best routes can be identified based on latency and not just on the jumps between autonomous systems, fact that optimizes data traffic in a specific way whether it is IPv4 or IPv6. As time elapses, it becomes more important to have a perfect setting for the LAN, which means optimal DNS, LDAP Servers appropriate number, etc. Thats why we propose a precise method that contemplates every possible variation of data, thus making a comparison by means of the use of confidence limits.

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A Novel Network Science and Similarity-Searching-Based Approach for Discovering Potential Tumor-Homing Peptides from Antimicrobials

2022 , Romero, Maylin , Marrero-Ponce, Yovani , Rodríguez, Hortensia , Agüero-Chapin, Guillermin , Antunes, Agostinho , Aguilera-Mendoza, Longendri , Martínez Ríos, Félix Orlando

Peptide-based drugs are promising anticancer candidates due to their biocompatibility and low toxicity. In particular, tumor-homing peptides (THPs) have the ability to bind specifically to cancer cell receptors and tumor vasculature. Despite their potential to develop antitumor drugs, there are few available prediction tools to assist the discovery of new THPs. Two webservers based on machine learning models are currently active, the TumorHPD and the THPep, and more recently the SCMTHP. Herein, a novel method based on network science and similarity searching implemented in the starPep toolbox is presented for THP discovery. The approach leverages from exploring the structural space of THPs with Chemical Space Networks (CSNs) and from applying centrality measures to identify the most relevant and non-redundant THP sequences within the CSN. Such THPs were considered as queries (Qs) for multi-query similarity searches that apply a group fusion (MAX-SIM rule) model. The resulting multi-query similarity searching models (SSMs) were validated with three benchmarking datasets of THPs/non-THPs. The predictions achieved accuracies that ranged from 92.64 to 99.18% and Matthews Correlation Coefficients between 0.894–0.98, outperforming state-of-the-art predictors. The best model was applied to repurpose AMPs from the starPep database as THPs, which were subsequently optimized for the TH activity. Finally, 54 promising THP leads were discovered, and their sequences were analyzed to encounter novel motifs. These results demonstrate the potential of CSNs and multi-query similarity searching for the rapid and accurate identification of THPs.

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A new approach of the rain-fall optimization algorithm using parallelization

2020 , Guerrero-Valadez, Juan Manuel , Martínez Ríos, Félix Orlando

This chapter introduces a new implementation of the Rain-Fall Optimization Algorithm (RFO) proposed by Kaboli, Sevbaraj, and Rahim in “Rain-Fall Optimization Algorithm. A Population-Based Algorithm for Solving Constrained Optimization Problems” by Kaboli et al. (J Comput Sci 19:31–42, 2017). RFO is a nature-inspired algorithm, which is based on the behavior of the water drops produced by a rainfall going down through a mountain to find the minimum values of specific functions. The algorithm was tested on four multidimensional benchmark functions: Ackley, Griewank, Rosenbrock, and Sphere functions. It was also tested in a four-dimensional function, the Kowalik function. The first step was to match the results of the rewritten algorithm with the results obtained by the original authors. Then the algorithm had to be modified to make some efficiency improvements and to get better results. The main modifications were a new equation to modify the step size for a function called explosion process and a parallel execution of the algorithm with two different restarting techniques: restart to the best and genetic restart to the best. © Springer Nature Switzerland AG 2020.

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A first-year design experience based on SAE Aero Design contest to support ABET learning outcomes and engineering vocation in freshmen student

2017 , Martínez Ríos, Félix Orlando

The a-k outcomes established by Accreditation Board for Engineering and Technology (ABET) for Engineering students in their self-assessment framework, should be reflected in the different subjects that taught to the students of the first two years of the various engineering programs. On the other hand, in those first semesters, the vocation of the students about the different Engineering is not very well defined. This experiment shows a proposal that links the results of ABET with an international student competition such as Society of Automotive Engineers (SAE) Aero Design, to reinforce and guide the new students in their future choice of specialization in the School of Engineering. We also show the relationship between the challenges and problems in the SAE Aero Design competition for new students and ABET's a-k outcomes. We show the results obtained with nineteen students over three years. It is important to mention that none of the students involved in this experiment comes from Aeronautical Engineering (or similar to it).

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New metrics to modify BGP routes based on SDN

2019 , Elguea, Lorenzo M. , Martínez Ríos, Félix Orlando

Through Software Defined Network, routes obtained through Border Gateway Protocol can be modified to improve latency or select a shorter path. With the same tool that perform the above actions, you can modify routes, for example, to avoid autonomous systems in certain countries or some other policy that may help, for example, security. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

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A new heuristic algorithm to solve Circle Packing problem inspired by nanoscale electromagnetic fields and gravitational effects

2018 , Martínez Ríos, Félix Orlando , Marmolejo Saucedo, José Antonio , Murillo-Suarez, Alfonso

In this paper, we present a new algorithm for the fast and efficient solution of the Packing problem in two dimensions. The packing problem consists in finding the best arrangement of objects (many geometrical forms) in a specific space called container.This new algorithm is inspired by the observations of nanometric scale electromagnetic fields. We use the electromagnetic theory of the electric field to calculate the best position to place a circular object in a configuration of other circular objects previously packing. Also, in this new algorithm we simulate two processes called »gravity» and »shaken» that compact the distribution of the objects placed in the container and allow to minimize the unoccupied space. © 2018 IEEE.

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