ORCID Profile
0000-0002-0681-3833
Current Organisation
Universidad Panamericana - Guadalajara
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Publisher: EconJournals
Date: 19-07-2022
DOI: 10.32479/IJEEP.13242
Abstract: This study aims to analyze the influence of foreign direct investment, tourism, exports, and imports on carbon dioxide (CO2) emissions in the High-Income State, Upper-Middle Income, and Lower-Middle-Middle Income in Asia during the period of 2010 to 2019. This study uses the Poisson Pseudo-Maximum Likelihood (PPML) method. The results of this study indicate that Environmental Kuznets Curve Hypothesis (EKC) is valid in the country of High Income and Upper-Middle Income. In addition, there is a non-linear relationship between foreign direct investment (FDI), tourism, Export, and imports on carbon dioxide (CO2) emissions. The interaction variables, which are a foreign direct investment with tourism and foreign direct investment with Export. Each of them is reducing carbon dioxide emissions only in high-income countries. Meanwhile, the interaction variables between foreign direct investment and imports reduce carbon dioxide emissions in high-income countries. However, it increases the carbon dioxide emissions in the upper-middle-income country
Publisher: MDPI AG
Date: 11-03-2022
DOI: 10.3390/MATH10060899
Abstract: In 2005, Guillot published a method for the construction of Boolean functions using linear codes through the Maiorana–McFarland construction of Boolean functions. In this work, we present a construction using Hermitian codes, starting from the classic Maiorana–McFarland construction. This new construction describes how the set of variables is ided into two complementary subspaces, one of these subspaces being a Hermitian Code. The ideal theoretical parameters of the Hermitian code are proposed to reach desirable values of the cryptographic properties of the constructed Boolean functions such as nonlinearity, resiliency order, and order of propagation. An extension of Guillot’s work is also made regarding parameters selection using algebraic geometric tools, including explicit ex les.
Publisher: IOP Publishing
Date: 02-10-2007
Publisher: Springer International Publishing
Date: 2020
Publisher: Elsevier BV
Date: 11-2018
Publisher: MDPI AG
Date: 24-05-2021
DOI: 10.3390/APP11114815
Abstract: The search of bijective n×n S-boxes resilient to power attacks in the space of dimension (2n)! is a controversial topic in the cryptology community nowadays. This paper proposes partitioning the space of (2n)! S-boxes into equivalence classes using the hypothetical power leakage according to the Hamming weights model, which ensures a homogeneous theoretical resistance within the class against power attacks. We developed a fast algorithm to generate these S-boxes by class. It was mathematically demonstrated that the theoretical metric confusion coefficient variance takes constant values within each class. A new search strategy—jumping over the class space—is justified to find S-boxes with high confusion coefficient variance in the space partitioned by Hamming weight classes. In addition, a decision criterion is proposed to move quickly between or within classes. The number of classes and the number of S-boxes within each class are calculated, showing that, as n increases, the class space dimension is an ever-smaller fraction of the space of S-boxes, which significantly reduces the space of search of S-boxes resilient to power attacks, when the search is performed from class to class.
Publisher: Fundacion Universitaria CEIPA
Date: 23-09-2018
DOI: 10.16967/RPE.V5N2A6
Abstract: The aim of this article is to determine the socioeconomic level (SEL) with disaggregation of the Basic Statistical Area (BSA) in the Mexican Republic. The methodology used is the one established by the Mexican Association of Market Research Agencies (AMAI) along with the National Institute of Statistics and Geography (INEGI). The Clustering of the BSAs was carried out according to variables contained in the Population and Housing Census of 2010, through Gaussian mixture models, learning neural networks and finally, by defining the labels corresponding to each SEL. We found the existence of a representative SEL for each BSA. In addition, the definition of each socioeconomic level shows good results with an average of 90.86% of correctly labeled elements.
Publisher: MDPI AG
Date: 04-07-2020
DOI: 10.3390/E22070741
Abstract: The analysis of independence between statistical randomness tests has had great attention in the literature recently. Dependency detection between statistical randomness tests allows one to discriminate statistical randomness tests that measure similar characteristics, and thus minimize the amount of statistical randomness tests that need to be used. In this work, a method for detecting statistical dependency by using mutual information is proposed. The main advantage of using mutual information is its ability to detect nonlinear correlations, which cannot be detected by the linear correlation coefficient used in previous work. This method analyzes the correlation between the battery tests of the National Institute of Standards and Technology, used as a standard in the evaluation of randomness. The results of the experiments show the existence of statistical dependencies between the tests that have not been previously detected.
Publisher: Elsevier BV
Date: 09-2022
Publisher: MDPI AG
Date: 08-12-2021
DOI: 10.3390/INFO12120509
Abstract: During the search for S-boxes resistant to Power Attacks, the S-box space has recently been ided into Hamming Weight classes, according to its theoretical resistance to these attacks using the metric variance of the confusion coefficient. This partition allows for reducing the size of the search space. The swap operator is frequently used when searching with a random selection of items to be exchanged. In this work, the theoretical probability of changing Hamming Weight class of the S-box is calculated when the swap operator is applied randomly in a permutation. The precision of these probabilities is confirmed experimentally. Its limit and a recursive formula are theoretically proved. It is shown that this operator changes classes with high probability, which favors the exploration of the Hamming Weight class of S-boxes space but dramatically reduces the exploitation within classes. These results are generalized, showing that the probability of moving within the same class is substantially reduced by applying two swaps. Based on these results, it is proposed to modify/improve the use of the swap operator, replacing its random application with the appropriate selection of the elements to be exchanged, which allows taking control of the balance between exploration and exploitation. The calculated probabilities show that the random application of the swap operator is inappropriate during the search for nonlinear S-boxes resistant to Power Attacks since the exploration may be inappropriate when the class is resistant to Differential Power Attack. It would be more convenient to search for nonlinear S-boxes within the class. This result provides new knowledge about the influence of this operator in the balance exploration–exploitation. It constitutes a valuable tool to improve the design of future algorithms for searching S-boxes with good cryptography properties. In a probabilistic way, our main theoretical result characterizes the influence of the swap operator in the exploration–exploitation balance during the search for S-boxes resistant to Power Attacks in the Hamming Weight class space. The main practical contribution consists of proposing modifications to the swap operator to control this balance better.
Publisher: Informa UK Limited
Date: 20-10-2017
Publisher: Universidad Nacional Autonoma de Mexico
Date: 04-2015
Publisher: MDPI AG
Date: 25-03-2021
Abstract: In 2005, Philippe Guillot presented a new construction of Boolean functions using linear codes as an extension of the Maiorana–McFarland’s (MM) construction of bent functions. In this paper, we study a new family of Boolean functions with cryptographically strong properties, such as non-linearity, propagation criterion, resiliency, and balance. The construction of cryptographically strong Boolean functions is a daunting task, and there is currently a wide range of algebraic techniques and heuristics for constructing such functions however, these methods can be complex, computationally difficult to implement, and not always produce a sufficient variety of functions. We present in this paper a construction of Boolean functions using algebraic codes following Guillot’s work.
Publisher: Inderscience Publishers
Date: 2019
Publisher: European Alliance for Innovation n.o.
Date: 13-07-2018
Publisher: IOP Publishing
Date: 08-04-2011
Publisher: American Society of Civil Engineers (ASCE)
Date: 03-2018
Publisher: MDPI AG
Date: 21-09-2020
DOI: 10.3390/E22091052
Abstract: Generating Boolean Functions (BFs) with high nonlinearity is a complex task that is usually addresses through algebraic constructions. Metaheuristics have also been applied extensively to this task. However, metaheuristics have not been able to attain so good results as the algebraic techniques. This paper proposes a novel ersity-aware metaheuristic that is able to excel. This proposal includes the design of a novel cost function that combines several information from the Walsh Hadamard Transform (WHT) and a replacement strategy that promotes a gradual change from exploration to exploitation as well as the formation of clusters of solutions with the aim of allowing intensification steps at each iteration. The combination of a high entropy in the population and a lower entropy inside clusters allows a proper balance between exploration and exploitation. This is the first memetic algorithm that is able to generate 10-variable BFs of similar quality than algebraic methods. Experimental results and comparisons provide evidence of the high performance of the proposed optimization mechanism for the generation of high quality BFs.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Springer International Publishing
Date: 17-06-2017
Publisher: Hindawi Limited
Date: 08-06-2022
DOI: 10.1155/2022/4821927
Abstract: 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 erse 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.
Publisher: IGI Global
Date: 2019
DOI: 10.4018/978-1-5225-8223-6.CH007
Abstract: This chapter presents a case study to organize the sales territories for a company with 11 sales managers to be assigned to 111 sales coverage units in Mexico. The assignment problem is modeled as a mathematical program with two objective functions. One objective minimizes the maximum distance traveled by the manager, and the other objective minimizes the variation of the sales growth goals with respect to the national average. To solve the bi-objective non-linear mixed-integer program, a weights method is selected. Some instances are solved using commercial software with long computational times. Also, a heuristic and a metaheuristic based on simulated annealing were developed. The design of the heuristic generates good solutions for the distance objective. The metaheuristic produces better results than the heuristic, with a better balance between the objectives. The heuristic and the metaheuristic are capable of providing good results with short computational times.
Publisher: Emerald
Date: 16-08-2018
DOI: 10.1108/ARLA-11-2016-0313
Abstract: The purpose of this paper is to analyse the adaptive market efficiency in the price–volume (P–V) relationship of the stocks listed in the Mexican Stock Exchange. The period under study goes from 1982 to 2015. In order to detect causality and, thus, determine adaptive efficiency in the market, one linear and two non-linear tests are applied. There are few papers in the literature that study the P–V relationship in Latin American markets as such, this paper may be of interest and importance to financial academics and practitioners alike. The Diks and Panchenko (DP) non-parametric Granger causality and the Brooks and Hinich (BH) cross-bicorrelation tests are applied. Derived from the DP test, the findings show that there exists bi-directional non-linear Granger causality in 25.71 per cent of the firms studied, compared to 8 per cent when applying the linear Granger causality test. Therefore, there is evidence of weak-form efficiency in the market. From the BH test, evidence is shown of the adaptive market efficiency, since 71.42 per cent of firms exhibited some form of non-linear dependence in certain periods of time. With these results, the information process should be better studied for a greater comprehension of regulatory policies in the market and better decision-making tools for the investors. This paper complements studies on the P–V relationship and efficiency in a Latin American market.
Publisher: Springer International Publishing
Date: 2021
Publisher: Springer International Publishing
Date: 2021
Publisher: MDPI AG
Date: 26-03-2022
DOI: 10.3390/EN15072451
Abstract: The goal of this study was to examine the interlinkage of renewable energy, technology innovation, human capital, and governance on environment quality by using a panel quantile regression in Asian emerging economies over the period of 1990–2019. The results indicated that higher economic growth, population density, technological innovation in renewable energy, and exploitation of natural resources have significantly raised CO2 emissions in emerging Asia. Furthermore, larger capital, more use of renewable energy, green technology, and human capital development can improve environmental sustainability in Asia. As for governances, proxied by corruption rates, no evidence indicated that it has resulted in more damage, unlike earlier studies have suggested. The findings indicated that the three channels exposed in the Kuznets hypothesis can serve as a reference for proposals for environmental policies (scale of consumption, energy composition, and choice of technologies). There are opportunities to reduce CO2 emissions through investments in human development, investing in new technologies to increase efficiency in energy (generation and consumption), increasing working capital (GCF), and migrating to more environmentally friendly energy. The negative link between carbon dioxide emissions and economic growth, increases in population density, and exploitation of natural resources can compromise the achievement of sustainable environmental goals.
Publisher: Emerald
Date: 11-11-2021
DOI: 10.1108/BPMJ-12-2020-0580
Abstract: Small- and medium-sized enterprises (SMEs) mainly rely on their structure and internal networks to achieve their goals and remain competitive. However, their limited internal capabilities and complex environments can hinder their stability. Thus, this study evaluated the relationships among specific factors toward fostering organizational resilience (OR) in tourism SMEs. A multi-methodological approach was adopted to address this research study, including (1) social network analysis (SNA) to formulate the conceptual model and (2) construct validation through partial least squares path modeling (PLS-PM). The six proposed hypotheses were supported. These results suggest that addressing these variables and relationships after considering management style and people development as critical factors can foster OR in tourism SMEs. The ideas that were developed were constrained to the organizational domain. Although the results apply to the Mexican context, this limitation can be offset by extending the proposal to other emergent regions or organizations. This can also increase the generalization of the results and foster improvements in the approaches applied. Academics and managers must rethink resilience as the final state generated by multiple factors. This requires reconfiguring inner organizational interactions, providing more autonomy to operative units, reinforcing business intelligence and improving feedback mechanisms. This research study contrasts previous studies because it proposes that SNA be exploited to avail of the advantages it confers in designing the conceptual model. In this regard, we present new relationships to promote OR and provide new avenues in order to improve the analysis of adaptation processes.
Publisher: MDPI AG
Date: 30-04-2021
DOI: 10.3390/SYM13050777
Abstract: This work demonstrates the ineffectiveness of the Ripley’s K function tests, the distance to the nearest neighbor, and the empty space function in the Graphical Authentication scenario with Passpoint for the detection of non-random graphical passwords. The results obtained show that none of these tests effectively detect non-random graphical passwords the reason for their failure is attributed to the small s le of the spatial pattern in question, where only the five points of the graphical password are analyzed. Consequently, a test based on mean distances is proposed, whose experiments show that it detects with good efficiency non-random graphical passwords in Passpoint. The test was designed to be included in the Graphical Authentication systems with Passpoint to warn the user about a possibly weak password during the registration phase, and in this way, the security of the system is increased.
Publisher: MDPI AG
Date: 17-11-2019
DOI: 10.3390/SU11226469
Abstract: This article explores and validates the integrated use of the viable system model (VSM) and the partial least squares path modeling (PLS-PM) approach to assess the sustainable management of RAMSAR sites carrying out economic activities. This work adopts a systems-thinking approach integrating systemic methodologies in three phases: (1) the VSM was first used to develop a conceptual model of the organisational problem (2) PLS-PM was used to propose a construct to outline a solution, as well as to statistically validate the relationships proposed in the conceptual model finally, (3) through the VSM, the relationships between actors were rethought in order to promote sustainable performance. The results obtained suggest that the joint use of VSM and PLS-PM is an effective approach that aids in the identification of relational and structural pathologies affecting the observed RAMSAR systems. It also proved useful to suggest that relationships can lead to the sustainable performance of the sites under study. It should be noted that the framework of systemic tools is constrained in its application to the organisational domain: assessing two RAMSAR areas in Mexico. Methodologically, this is the first application of the integrated use of VSM and PLS-PM to analyse the management and viability/sustainability of RAMSAR areas from an organisational perspective, opening a new avenue for the analysis and optimisation of management of such areas. This study provides tools to support actors and academics related to RAMSAR sites and opens up a discussion on how to rethink the organisational interactions in order to improve RAMSAR sites’ adaptive capabilities.
Publisher: Informa UK Limited
Date: 11-09-2017
Publisher: American Society of Civil Engineers (ASCE)
Date: 09-2017
Publisher: IGI Global
Date: 2019
DOI: 10.4018/978-1-5225-8223-6.CH011
Abstract: A MILP and genetic algorithm optimization model for the sequencing of jobs in a medium-sized factory, dedicated to the manufacturing of home furniture, where different categories and types of articles are produced and whose routes and manufacturing processing times vary widely, are proposed. Different scenarios are considered for the objective function based on minimizing makespan and tardiness. The results of the optimization for an instance of 24 jobs on five machines, chosen as a representative instance of the order sizes that are handled by the company, show important reductions in the productive system's usage times, oscillating between 10% and 20% with respect to a random initial sequence in the production plan. Improvements were similar in both techniques, the main difference being the solution time of each one.
Publisher: EconJournals
Date: 10-08-2020
DOI: 10.32479/IJEEP.9599
Publisher: Wiley
Date: 06-02-2023
DOI: 10.1002/IJFE.2534
Abstract: This paper analyzes the time‐varying causality between government bond and oil returns of the United States over the monthly period of 1859:10 to 2019:03, that is, the longest possible span of historical data, starting from the beginning of the modern era of the petroleum industry. While the standard constant parameter causality test fails to pick up any evidence of causality, the time‐varying framework shows evidence of bi‐directional spillovers over the entire s le period. The results are robust to the inclusion of stock returns as a control variable in the model. We also detect evidence of time‐varying causality‐in‐volatility between sovereign bond and oil markets, as well as spillovers in returns and volatility from the oil market to corporate bonds.
Publisher: MDPI AG
Date: 14-07-2021
DOI: 10.3390/E23070896
Abstract: This paper presents a criterion, based on information theory, to measure the amount of average information provided by the sequences of outputs of the RC4 on the internal state. The test statistic used is the sum of the maximum plausible estimates of the entropies H(jt|zt), corresponding to the probability distributions P(jt|zt) of the sequences of random variables (jt)t∈T and (zt)t∈T, independent, but not identically distributed, where zt are the known values of the outputs, while jt is one of the unknown elements of the internal state of the RC4. It is experimentally demonstrated that the test statistic allows for determining the most vulnerable RC4 outputs, and it is proposed to be used as a vulnerability metric for each RC4 output sequence concerning the iterative probabilistic attack.
Publisher: Universidad de Guadalajara
Date: 06-04-2016
Abstract: Models that apply to negotiation are based on different perspectives that range from the relationship between the actors, game theory or the steps in a procedure. This research proposes a model of negotiation scenarios that considers three factors (time, relevance and control), which are displayed as the most important in a negotiation. These factors interact with each other and create different scenarios for each of the actors involved in a negotiation. The proposed model not only facilitates the creation of a negotiation strategy but also an ideal choice of effective tactics.
Publisher: International Association for Energy Economics (IAEE)
Date: 09-2018
Publisher: MDPI AG
Date: 29-10-2020
DOI: 10.3390/APP10217668
Abstract: The bit independence criterion was proposed to evaluate the security of the S-boxes used in block ciphers. This paper proposes an algorithm that extends this criterion to evaluate the degree of independence between the bits of inputs and outputs of the stream ciphers. The effectiveness of the algorithm is experimentally confirmed in two scenarios: random outputs independent of the input, in which it does not detect dependence, and in the RC4 ciphers, where it detects significant dependencies related to some known weaknesses. The complexity of the algorithm is estimated based on the number of inputs l, and the dimensions, n and m, of the inputs and outputs, respectively.
Publisher: MDPI AG
Date: 31-01-2023
DOI: 10.3390/E25020261
Abstract: There are many algorithms used with different purposes in the area of cryptography. Amongst these, Genetic Algorithms have been used, particularly in the cryptanalysis of block ciphers. Interest in the use of and research on such algorithms has increased lately, with a special focus on the analysis and improvement of the properties and characteristics of these algorithms. In this way, the present work focuses on studying the fitness functions involved in Genetic Algorithms. First, a methodology was proposed to verify that the closeness to 1 of some fitness functions’ values that use decimal distance implies decimal closeness to the key. On the other hand, the foundation of a theory is developed in order to characterize such fitness functions and determine, a priori, if one method is more effective than another in the attack to block ciphers using Genetic Algorithms.
Publisher: Hindawi Limited
Date: 21-09-2022
DOI: 10.1155/2022/3624587
Abstract: PassPoint is a graphical authentication technique that is based on the selection of five points in an image. A detected vulnerability lies in the possible existence of a pattern in the points that make up the password. The objective of this work is to detect nonrandom graphical passwords in the PassPoint scenario. A spatial randomness test based on the average of Delaunay triangles’ perimeter is proposed, given the ineffectiveness of the classic tests in this scenario, which only consists of five points. A state-of-the-art of various applications of Voronoi polygons and Delaunay triangulations are presented to detect clustered and regular patterns. The distributions of the averages of the triangles’ perimeters in the PassPoint scenario for various sizes of images are disclosed, which were unknown. The test’s decision criterion was constructed from one of the best distributions to which the data were adjusted. Type I and type II errors were estimated, and it was concluded that the proposed test could detect clustered and regular graphical passwords in PassPoint, therefore being more effective in detecting clustering than regularity.
Publisher: MDPI AG
Date: 05-05-2021
DOI: 10.3390/SYM13050806
Abstract: In recent years, the use of Genetic Algorithms (GAs) in symmetric cryptography, in particular in the cryptanalysis of block ciphers, has increased. In this work, the study of certain parameters that intervene in GAs was carried out, such as the time it takes to execute a certain number of iterations, so that a number of generations to be carried out in an available time can be estimated. Accordingly, the size of the set of in iduals that constitute admissible solutions for GAs can be chosen. On the other hand, several fitness functions were introduced, and which ones led to better results was analyzed. The experiments were performed with the block ciphers AES(t), for t∈{3,4,7}.
Publisher: Academic Publications
Date: 21-04-2017
Publisher: MDPI AG
Date: 30-04-2021
DOI: 10.3390/E23050561
Abstract: 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 s les 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 s les of bytes and bits.
Publisher: European Alliance for Innovation n.o.
Date: 05-05-2020
Publisher: Inderscience Publishers
Date: 2020
Publisher: MDPI AG
Date: 06-01-2022
DOI: 10.3390/APP12020531
Abstract: Conventional electronic voting systems use a centralized scheme. A central administration of these systems manages the entire voting process and has partial or total control over the database and the system itself. This creates some problems, accidental or intentional, such as possible manipulation of the database and double voting. Many of these problems have been solved thanks to permissionless blockchain technologies in new voting systems however, the classic consensus method of such blockchains requires specific computing power during each voting operation. This has a significant impact on power consumption, compromises the efficiency and increases the system latency. However, using a permissioned blockchain improves efficiency and reduces system energy consumption, mainly due to the elimination of the typical consensus protocols used by public blockchains. The use of smart contracts provides a secure mechanism to guarantee the accuracy of the voting result and make the counting procedure public and protected against fraudulent actions, and contributes to preserving the anonymity of the votes. Its adoption in electronic voting systems can help mitigate part of these problems. Therefore, this paper proposes a system that ensures high reliability by applying enterprise blockchain technology to electronic voting, securing the secret ballot. In addition, a flexible network configuration is presented, discussing how the solution addresses some of the security and reliability issues commonly faced by electronic voting system solutions.
Publisher: MDPI AG
Date: 05-10-2022
DOI: 10.3390/E24101420
Abstract: The relationship between three different groups of COVID-19 news series and stock market volatility for several Latin American countries and the U.S. are analyzed. To confirm the relationship between these series, a maximal overlap discrete wavelet transform (MODWT) was applied to determine the specific periods wherein each pair of series is significantly correlated. To determine if the news series cause Latin American stock markets’ volatility, a one-sided Granger causality test based on transfer entropy (GC-TE) was applied. The results confirm that the U.S. and Latin American stock markets react differently to COVID-19 news. Some of the most statistically significant results were obtained from the reporting case index (RCI), A-COVID index, and uncertainty index, in that order, which are statistically significant for the majority of Latin American stock markets. Altogether, the results suggest these COVID-19 news indices could be used to forecast stock market volatility in the U.S. and Latin America.
Publisher: MDPI AG
Date: 12-01-2023
DOI: 10.3390/MATH11020394
Abstract: This study uses daily COVID-19 news series to determine their impact on financial market volatility. This paper assesses whether U.S. financial markets react differently to COVID-19 news than emerging markets and if such markets are impacted differently by country-specific and global news. To detect the spillover effects from news on market volatility, a time-varying DCC-GARCH model was applied. The results suggest that the U.S. and emerging markets are affected differently by pandemic news, global series have a stronger impact on emerging markets than country-specific ones, and misleading information plays a significant role in financial market volatility, especially for the U.S.
Publisher: EconJournals
Date: 15-03-2020
DOI: 10.32479/IJEEP.9002
Publisher: MDPI AG
Date: 03-03-2022
DOI: 10.3390/S22051987
Abstract: An alternative authentication method to traditional alphanumeric passwords is graphical password authentication, also known as graphical authentication, for which one of the most valuable cued-recall techniques is PassPoints. This technique stands out for its security and usability. However, it can be violated if the user follows a predefined pattern when selecting the five points in an image as their passwords, such as the DIAG and LINE patterns. Dictionary attacks can be built using these two patterns to compromise graphical passwords. So far, no reports have been found in the state of the art about any test capable of detecting graphical passwords with DIAG or LINE patterns in PassPoints. Studies carried out in other scenarios have shown the effectiveness of the characteristics of Delaunay triangulations in extracting information about the dependence between the points. In this work, graphical passwords formed by five randomly selected points on an image are compared with passwords whose points contain patterns of the DIAG or LINE type. The comparison is based on building for each password its Delaunay triangulation and calculating the mean value of the maximum angles of the triangles obtained such a mean value is denoted by amadt. It is experimentally shown that in passwords containing DIAG and LINE patterns, the value of amadt is higher than the one obtained in passwords formed by random dots. From this result, it is proposed to use this amadt value as a statistic to build a test of means. This result constitutes the work’s main contribution: The proposal of a spatial randomness test to detect weak graphic passwords that contain DIAG and LINE type patterns. The importance and novelty of this result become evident when two aspects are taken into account: First, these weak passwords can be exploited by attackers to improve the effectiveness of their attacks second, there are no prior criteria to detect this type of weak password. The practical application of said test contributes to increasing PassPoints security without substantially affecting its efficiency.
Publisher: MDPI AG
Date: 15-10-2021
DOI: 10.3390/APP11209646
Abstract: In the last three decades, the RC4 has been the most cited stream cipher, due to a large amount of research carried out on its operation. In this sense, dissimilar works have been presented on its performance, security, and usability. One of the distinguishing features that stand out the most is the sheer number of RC4 variants proposed. Recently, a weakness has been reported regarding the existence of statistical dependence between the inputs and outputs of the RC4, based on the use of the strict avalanche criterion and the bit independence criterion. This work analyzes the influence of this weakness in some of its variants concerning RC4. The five best-known variants of RC4 were compared experimentally and classified into two groups according to the presence or absence of such a weakness.
Publisher: MDPI AG
Date: 11-2021
DOI: 10.3390/APP112110251
Abstract: Supply-chain network design is a complex task because there are many decisions involved, and presently, global networks involve many actors and variables, for ex le, 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.
Publisher: Springer International Publishing
Date: 2020
Publisher: Informa UK Limited
Date: 25-09-2022
Publisher: Universidad Nacional Autonoma de Mexico
Date: 11-02-2019
DOI: 10.22201/FCA.24488410E.2020.2358
Abstract: This paper is aimed at studying a MS-GARCH model applied to Bitcoin. The Bayesian estimation of the model shows that Bitcoin’s volatility can be modelled using two states of volatility, high and low. The modelled volatility is not stable over time. Twenty eight periods of high volatility were found, the largest period of volatility occurred during 2013. The findings help explain what happened during these high volatility periods. strong /strong
Publisher: Asia University
Date: 2020
Publisher: MDPI AG
Date: 19-10-2020
DOI: 10.3390/SU12208657
Abstract: Small and medium-sized tourism companies (SMEs) strongly depend on their collaborators to achieve competitiveness and sustainability. In this sense, these organizations need to identify those factors that help them to use their resources and efforts to achieve the aforementioned goals. This article proposes a model oriented to organizational sustainability in the tourism sector. A systemic approach was adopted to articulate this research therefore, the soft systems methodology was applied to structure the problem and express a conceptual model that suggests relationships as an alternative solution to the expressed problem. Partial least squares path modeling was applied to statistically validate the relationships expressed in the construct. Results suggest that the relationships proposed in the construct are valid and may promote organizational sustainability. The ideas developed are restricted to the organizational domain and although the results apply in a Mexican context, this potential limitation can be offset by the multi-methodological approach proposed, extending the model’s application to other types of organizations. This study may enable scholars and managers to improve communication and inter-organizational relationships, allowing organizations to focus their strategies and efforts using systems thinking to increase responsiveness and adaptation.
Publisher: Springer International Publishing
Date: 2018
Publisher: Universidad Nacional de Colombia
Date: 20-04-2016
DOI: 10.15446/DYNA.V83N196.49737
Abstract: This work applies a test that detects dependence between pairs of variables. The kind of dependence is a non-linear one, and the test is known as cross-bicorrelation, which is associated with Brooks and Hinich [1]. We study dependence periods between U.S. Standard and Poor's 500 (SP500), used as a benchmark, and six Latin American stock market indexes: Mexico (BMV), Brazil (BOVESPA), Chile (IPSA), Colombia (COLCAP), Peru (IGBVL) and Argentina (MERVAL). We have found windows of nonlinear dependence and comovement between the SP500 and the Latin American stock markets, some of which coincide with periods of crisis, leading to an interpretation of a possible contagion or interdependence.
Publisher: Springer Science and Business Media LLC
Date: 28-04-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Elsevier BV
Date: 2022
No related grants have been discovered for Omar Rojas.