Sosa-Gómez, Guillermo
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Preferred name
Sosa-Gómez, Guillermo
Official Name
Sosa Gómez, Guillermo
Alternative Name
gsosag
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ORCID
Scopus Author ID
57202400202
Researcher ID
ABA-2857-2020

Research Output
Now showing 1 - 10 of 33
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Matheuristics for the Design of a Multi-Step, Multi-Product Supply Chain with Multimodal Transport

2021 , Ruvalcaba-Sandoval, David A. , Olivares-Benitez, Elias , Rojas, Omar , Sosa-Gómez, Guillermo

Supply-chain network design is a complex task because there are many decisions involved, and presently, global networks involve many actors and variables, for example, in the automotive, pharmaceutical, and electronics industries. This research addresses a supply-chain network design problem with four levels: suppliers, factories, warehouses, and customers. The problem considered decides on the number, locations, and capacities of factories and warehouses and the transportation between levels in the supply chain. The problem is modeled as a mixed-integer linear program. The main contribution of this work is the proposal of two matheuristic algorithms to solve the problem. Matheuristics are algorithms that combine exact methods and heuristics, attracting interest in the literature because of their fast execution and high-quality solutions. The matheuristics proposed to select the warehouses and their capacities following heuristic rules. Once the warehouses and their capacities are fixed, the algorithms solve reduced models using commercial optimization software. Medium and large instances were generated based on a procedure described in the literature. A comparison is made between the algorithms and the results obtained, solving the model with a time limit. The algorithms proposed are successful in obtaining better results for the largest instances in shorter execution times.

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Automating the avocado supply chain with Blockchain and Off-chain

2020 , López-Pimentel, Juan Carlos , Rojas, Omar , Alcaraz Rivera, Miguel , Sosa-Gómez, Guillermo , Verteramo-Chiu, L.

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Conscious Exploration of Alpha-Cuts in the Parametric Solution of the School Bus Routing Problem with Fuzzy Walking Distance

2022 , Eduardo Sánchez-Ansola , Ana C. Pérez-Pérez , Alejandro Rosete , Isis Torres-Pérez , Rojas, Omar , Sosa-Gómez, Guillermo , Diego Oliva

Combinatorial optimization problems allow for modeling multiple situations in which proper allocation of resources is needed. For some real-world problems, the use of fuzzy elements in the models allows for incorporating certain levels of uncertainty to better approximate such real-world situations. One way to solve combinatorial optimization problems with fuzzy elements is the parametric approach, where it is necessary to define how to explore different relaxation levels using alpha-cuts. Researchers tend to select such alpha-cuts uniformly. The current investigation proposes a novel strategy for selecting alpha-cuts in the School Bus Routing Problem with fuzzy students’ maximum walking distance. This proposal bases its foundations on the number of student-bus stop pairs available according to the different levels of relaxations allowed. Results demonstrate how the proposed strategy gives attractive solutions with more diverse trade-offs, contrasted with other methods in the literature. Furthermore, it decreases the computational cost for those instances where the maximum relaxation does not provide new pairs of students-bus stops.

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Practical Improvement in the Implementation of Two Avalanche Tests to Measure Statistical Independence in Stream Ciphers

2024 , Evaristo José Madarro-Capó , Eziel Christians Ramos Piñón , Sosa-Gómez, Guillermo , Rojas, Omar

This study describes the implementation of two algorithms in a parallel environment. These algorithms correspond to two statistical tests based on the bit’s independence criterion and the strict avalanche criterion. They are utilized to measure avalanche properties in stream ciphers. These criteria allow for the statistical independence between the outputs and the internal state of a bit-level cipher to be determined. Both tests require extensive input parameters to assess the performance of current stream ciphers, leading to longer execution times. The presented implementation significantly reduces the execution time of both tests, making them suitable for evaluating ciphers in practical applications. The evaluation results compare the performance of the RC4 and HC256 stream ciphers in both sequential and parallel environments.

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Analysis of the Number of Sides of Voronoi Polygons in PassPoint

2021 , Lisset Suárez-Plasencia , Joaquín A. Herrera-Macías , Carlos M. Legón-Pérez , Raisa Socorro-LLanes , Rojas, Omar , Sosa-Gómez, Guillermo

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Selecting an Effective Entropy Estimator for Short Sequences of Bits and Bytes with Maximum Entropy

2021 , Lianet Contreras Rodríguez , Evaristo José Madarro-Capó , Carlos Miguel Legón-Pérez , Rojas, Omar , Sosa-Gómez, Guillermo

Entropy makes it possible to measure the uncertainty about an information source from the distribution of its output symbols. It is known that the maximum Shannon’s entropy of a discrete source of information is reached when its symbols follow a Uniform distribution. In cryptography, these sources have great applications since they allow for the highest security standards to be reached. In this work, the most effective estimator is selected to estimate entropy in short samples of bytes and bits with maximum entropy. For this, 18 estimators were compared. Results concerning the comparisons published in the literature between these estimators are discussed. The most suitable estimator is determined experimentally, based on its bias, the mean square error short samples of bytes and bits.

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Optimization models and techniques applied to transportation problems

2024-04-01 , Eduardo Sánchez-ansola , Suarez, Alejandro Rosete , Luis Angel Suarez Gonzalez , Perez, Ana Camila Pérez , Humberto Díaz-pando , Cynthia Porras Nodarse , Sosa-Gómez, Guillermo , Rojas, Omar , Peres, Isis Torres

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Using hadamard transform for cryptanalysis of pseudo-random generators in stream ciphers

2020 , Sosa-Gómez, Guillermo , Rojas, Omar , Páez-Osuna, O.

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New Test to Detect Clustered Graphical Passwords in Passpoints Based on the Perimeter of the Convex Hull

2024 , Joaquín Alberto Herrera-Macías , Lisset Suárez-Plasencia , Carlos Miguel Legón-Pérez , Sosa-Gómez, Guillermo , Rojas, Omar

This research paper presents a new test based on a novel approach for identifying clustered graphical passwords within the Passpoints scenario. Clustered graphical passwords are considered a weakness of graphical authentication systems, introduced by users during the registration phase, and thus it is necessary to have methods for the detection and prevention of such weaknesses. Graphical authentication methods serve as a viable alternative to the conventional alphanumeric password-based authentication method, which is susceptible to known weaknesses arising from user-generated passwords of this nature. The test proposed in this study is based on estimating the distributions of the perimeter of the convex hull, based on the hypothesis that the perimeter of the convex hull of a set of five clustered points is smaller than the one formed by random points. This convex hull is computed based on the points that users select as passwords within an image measuring 1920 × 1080 pixels, using the built-in function convhull in Matlab R2018a relying on the Qhull algorithm. The test was formulated by choosing the optimal distribution that fits the data from a total of 54 distributions, evaluated using the Kolmogorov–Smirnov, Anderson–Darling, and Chi-squared tests, thus achieving the highest reliability. Evaluating the effectiveness of the proposed test involves estimating type I and II errors, for five levels of significance α∈{0.01,0.02,0.05,0.1,0.2}, by simulating datasets of random and clustered graphical passwords with different levels of clustering. In this study, we compare the effectiveness and efficiency of the proposed test with existing tests from the literature that can detect this type of pattern in Passpoints graphical passwords. Our findings indicate that the new test demonstrates a significant improvement in effectiveness compared to previously published tests. Furthermore, the joint application of the two tests also shows improvement. Depending on the significance level determined by the user or system, the enhancement results in a higher detection rate of clustered passwords, ranging from 0.1% to 8% compared to the most effective previous methods. This improvement leads to a decrease in the estimated probability of committing a type II error. In terms of efficiency, the proposed test outperforms several previous tests; however, it falls short of being the most efficient, using computation time measured in seconds as a metric. It can be concluded that the newly developed test demonstrates the highest effectiveness and the second-highest efficiency level compared to the other tests available in the existing literature for the same purpose. The test was designed to be implemented in graphical authentication systems to prevent users from selecting weak graphical passwords, enhance password strength, and improve system security.

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Publication

Generation of the symmetric group Sn2

2021 , Carlos Zequeira Sánchez , Evaristo José Madarro Capó , Sosa-Gómez, Guillermo

In various scenarios today, the generation of random permutations has become an indispensable tool. Since random permutation of dimension [Formula: see text] is a random element of the symmetric group [Formula: see text], it is necessary to have algorithms capable of generating any permutation. This work demonstrates that it is possible to generate the symmetric group [Formula: see text] by shifting the components of a particular matrix representation of each permutation.

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