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This study proposes a system that applies artificial intelligence tools to reduce the number of vehicular accidents produced by driver drowsiness and distraction. The proposed system, which is suitable for any kind of vehicle, detects the driver’s face, which is fed into a deep neural network that analyzes it. The network output is then fed into a detection stage which determines whether the driver is drowsy or distracted, activating an alarm. The proposed system has a low computational complexity, allowing real time implementation on mobile devices. The experimental results show that the proposed system can detect drowsiness and distraction with an accuracy of 95.8% in high performance computers. It also shows an 84.5% accuracy on mobile devices with limited capacity, keeping an acceptable operational speed for its implementation in real time. It is concluded that the proposed system detects driver drowsiness and distraction with high accuracy. [ABSTRACT FROM AUTHOR]

A Flow Shop is a production system in which a series of jobs must follow a one-directional flow to be processed in several workstations. This article introduces the Permutation Flow Shop Scheduling Problem with Shifts Constraints (PFSSPSC), a variant of the Permutation Flow Shop Scheduling Problem (PFSSP) where it is sought to minimize the time in which all jobs are finished and shift constraints are imposed. These constraints consist of forcing the execution of each job to always end in the same shift in which they begin to avoid interruptions. In addition, this article introduces a hybrid algorithm to find good solutions to the PFSSPSC. This consists of a metaheuristic composed by a Genetic Algorithm and a Variable Neighborhood Search (VNS). The proposed algorithm is tested with 120 instances for the PFSSP available in literature adapted for the PFSSPSC. The obtained solutions are compared with those offered by three heuristic algorithms in terms of execution time and solution quality: a constructive algorithm, a randomized constructive method and a VND. The comparison among the four algorithms shows a superiority of hybrid and VND algorithms in terms of the solution quality, even if constructive and random search are faster. Among the hybrid algorithm and the VND there are not a great difference on solution quality, but the hybrid algorithm is significantly faster than VND. [ABSTRACT FROM AUTHOR]

Introduction: The electrical impedance measurement and characterization of biological tissues allow to distinguish between a healthy and pathological tissues. The use of techniques such as electrical impedance tomography is widely used in clinical testing through various applications. In this work the Linear Back Projection (LBP) method is employed to reconstruct images from electrical impedance measurements in order to obtain the location of carcinoma emulator previously inserted within female-breast-shaped agar-agar models. Method: A ring arrangement of eight electrodes was used for measuring the impedance on the seven female-breast-shaped agar-agar models. A cross section of a healthy female breast (without emulators) corresponding to the measurement plane of the ring electrode arrangement was designed and simulated in the COMSOL software. The sensitivity maps of each pair of electrodes along the impedance measurement were computed using the conductivity distribution data obtained from the simulated model. Finally, the reconstruction of the electrical tomography images was achieved by applying the LBP algorithm to the electrical impedance values measured form the electrode ring arrangement. Results: The sensitivity maps were computed from the electrical impedance measurements for each defined experimental model. As a result, a sensitivity matrix characterizing the electrical potentials distribution within the simulated measurement plane in COMSOL was obtained. The zone locations for all the experimental models with carcinomas emulators inserted outside the center of the electrodes ring arrangement were correctly obtained. Discussion or Conclusion: According to the results obtained from the described project, the proposed methodology allows the generation of images to locate carcinoma emulators with approximate diameters of 1 cm through a non-iterative approach. Therefore, the location does not require a high computational complexity. The localization of a carcinoma emulator inserted on the central zone of the female breast model was not correctly obtained due to the low sensitivity of the electrode ring arrangement in such zone. [ABSTRACT FROM AUTHOR]

The Hammock(2, 2 ,..., 2/k)-Poset Cover Problem is a variation of the Poset Cover Problem with the same input - set {L1, L2, ..., Lm} of linear orders over the set {1, 2, ..., n}, but the solution is restricted to a set of simple hammock(2, 2 ,..., 2/k) posets. The problem is NP-Hard when k = 3 but is in P when k = 1. The computational complexity of the problem when k = 2 is not yet known. In this paper, we determine the approximation complexity of the cases that have been shown to be NP-Hard. We show that the Hammock(2, 2 ,..., 2/k)-Poset Cover Problem is in APX and, in particular, (1 + 1/2K)-approximable, for k = 3. On the other hand, we also explore the computational complexity for the case where k = 2 [Hammock(2,2)-Poset Cover Problem]. We show that it is in P when the transposition graph of the input set of linear orders is rectangular. [ABSTRACT FROM AUTHOR]

This work is developed around Computational Complexity, very different from the Theory of Complexity as such, a transdisciplinary current of research poorly defined and that involves works in areas such as complex dynamic systems, chaos theory, artificial life and many others. The confusion between these fields arises from the fact that the word complexity is often used in different ways. Besides, a system or object could be reasonably described as complex under multiple conditions: if it consists of many interacting parts, if it is disordered or shows high entropy, if it exhibits diversity based on a hierarchical structure, or if it exhibits details on many different scales, as fractal sets. Some of these meanings of complexity are related to the Theory of Computational Complexity, but others only tangentially, as analyzed in this article. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical programing model that supports the design of timetables of classes in primary and secondary educational institutions, allowing the decision maker to take into account the constraints and variables that are commonly associated to this problem. Our model differs from most of those in the literature as the objective function aims at maximizing the number of blocks, two consecutive hours of lecture devoted to the same subject, which favors the learning process, optimizes teachers' agendas by reducing idle times and reduces cost and contractual difficulties. The model is validated using a real instance of a middle size institution for which the current timetable is considerably improved. Additionally, computational experiments with larger instances were carried on in order to test the capacity of the model for which promising results were obtained. [ABSTRACT FROM AUTHOR]

This paper considers the Location-Routing Problem with Heterogeneous Fleet (LRPH), in which the aim is to determine the depots to be opened, the customers to be assigned to each open depot, and the routes to be performed to fulfill the demand of the customers by considering a heterogeneous fleet with different capacities and associated costs. The objective is to minimize the sum of the cost of the open depots, of the used vehicle costs, and of the variable costs related with the distance traveled by the performed routes. In this paper, it is proposed a metaheuristic algorithm based on a granular tabu search to solve the LRPH. Computational experiments on adapted benchmark instances from the literature show that the proposed approach is able to obtain, within short computing times, high quality solutions illustrating its effectiveness. [ABSTRACT FROM AUTHOR]

The present work aims to design and implement a linear and integer programming model that allows partitioning a region into a given number of territories, according to certain measures of activity. Specifically, the proposed optimization model seeks to divide geographically certain provinces of Ecuador in a fixed number of electoral districts and satisfying the requirements established in the Elections Law of Ecuador, where the territories must be balanced in accordance with populational, and political measures. Moreover, it is required that the dispersion between the basic units within constituted districts is minimized. The computational complexity of the model has been determined and a heuristic method in two phases is exposed. Finally, computational experiments based on real data are reported, where the method obtains results close to the optimum in relatively short times. [ABSTRACT FROM AUTHOR]

This paper shows an overview of the problem, "School Timetabling", it treats first a definition of this problem, their classification, their computational complexity, and then it makes a review the different techniques which can be solved and the last one review one of these techniques such as genetic algorithms (GA), which was chosen to solution it. [ABSTRACT FROM AUTHOR]

Development of efficient and accurate heuristic algorithms of polynomial order, which achieve good solutions to complex problems in class NP-C, remains a great challenge. A strategy is proposed to improve heuristic algorithms, specifically for the euclidean traveling salesman problem, known as E-TSP. A defined set of indicators informs the extent to which programmed heuristics is reflected in the algorithm. The feedback obtained through indicators facilitates the process of refining the initial algorithm, in order to achieve better solutions. [ABSTRACT FROM AUTHOR]

In this paper, we present four models of uncertainty in the MRP closed systems in the production components, such as: manufacturing capacity of each product, delivery time and inventory availability. These parameters are processed by the fuzzy logic by modeling an MRP closed system deterministic. Therefore, three models are initially MRP closed system, where each independently consider uncertainty in capacity, delivery time and inventory availability. Also, we present a fourth model of MRP closed system jointly analyzes the uncertainty in the three parameters mentioned above. Each of these models is corroborated with information from a company in the Colombian electricity area, evaluating the total cost of the production plan, inventory levels, service level and computational complexity. [ABSTRACT FROM AUTHOR]

The EU rules on state aids, primarily contained in articles 107, 108 and 109 of the TFEU is, with the Principle of Non-Fiscal Discrimination, one of the fundamental pillars of the common market and the EU taxation, preventing States members to give aids to companies, including under this term the fiscal measures, that allow them to be placed at an advantage over its competitors. However, the State aid regime is complex and, in addition, the jurisprudence of the ECJ has refined and clarified the provisions of the Treaty. For these reasons, this paper provides a definition of the concept of State aid extensive and accurate for, later, study in detail each of the requirements that a national measure must meet to be qualified as State aid. In addition, it also discusses the implications of the fact that a national measure is considered as such. Finally, a brief reflection is offered on the relationship between the concept of State aid and the Principle of Non-Fiscal Discrimination, as a result of the relatively recent JCJEU 17.11.2009, Presidente del Consiglio dei Ministri, Case C-169/08. [ABSTRACT FROM AUTHOR]

Science is an ever-changing discipline. Modern medical knowledge is based on science. Current medical paradigm is both linear and reductionist. There is a new general theory validated by computer's calculations named chaos and complexity theory. This new paradigm will probably have an impact on medical practice. Cardiovascular physiology may display fractal and/ or chaotic behavior. Computerized heart rhythm analyses enhanced our understanding of complex diseases otherwise not explainable by current linear-reductionist paradigms. Cases in point are diverse dysautonomia including orthostatic intolerance, cardiac X syndrome and fibromyalgia. Derived from this, new knowledge is a different diagnostic and therapeutic stance: scientific holism. [ABSTRACT FROM AUTHOR]

The problem considered is that of scheduling the production of several different items over the same machine with restricted capacity and on a repetitive basis. The problem is NP-hard and there exist several methods for the problem. In this research we worked with Bomberger's basic cycle approach, for which there are reported several solution proposals, among which are found so far only genetic algorithms in regard to the implementation of metaheuristic techniques to solve the problem. We solved Bomberger's classical example problem, applying simulated annealing metaheuristic. The contributions of this research consist on how to obtain bounds for search space of the variables, and a strategy to control the search along the solution space performed by the algorithm. Because this is a first implementation, we tested several values of the parameters. The algorithm achieves the same cost in almost all tests and the algorithm performs better where the ratio [Multiple line equation(s) cannot be represented in ASCII text] is high, improving some of the results reported in the literature. [ABSTRACT FROM AUTHOR]

This article presents a methodology based on metaheuristic optimization techniques for the solution of the two- dimensional rectangular guillotineable bin packing problem, with and without 90 degrees items rotation. This one belongs to the family of cutting and packing problems, considered classic problems in the operations research, due to its big spectrum of application in the industry and its highly mathematical and computational complexity. An appropriate encoding called slicing tree was developed to work this problem. In the results analysis a computational study was presented using 3 algorithms based on the particle swarm technique. In order to check the efficiency of the presented methodology in terms of the computational time and the quality of the answers, different cases of study from the specialized literature were taken to make a benchmark, that finally corroborated the performance of the proposed methodology. [ABSTRACT FROM AUTHOR]

Cutting and packing problems are common in operations research, due to their big spectrum of application in the industry and its highly mathematical and computational complexity for the academy. In this study we present the unconstrained two-dimensional cutting stock problem of rectangular items, with and without weights associated to the items, bearing in mind the possibility to rotate items at 90°, and with guillotine cuts (also known as unconstrained two-dimensional guillotineable single knapsack problem). For this problem, we describe the mathematical model recognized by the academic community. We develop an appropriate encoding of the problem so it is possible to work on it using metaheuristic hybrid algorithm particle swarm optimization and simulated annealing. To check the efficiency of this methodology, case studies were taken from specialized literature, where the presented solution method could be analyzed and compared with current problems. The results obtained had an excellent quality and had never been reported. [ABSTRACT FROM AUTHOR]

The development of new algorithms that turn out to be convergent and efficient, is a required step for a fruitful use of grammatical inference in the solution of real-world and greater-size problems. In this work, we present two algorithms known as DeLeTe2 and MRIA, which do grammatical inference by means of non-deterministic automata, in contrast to the algorithms more commonly used, which make use of deterministic automata. We consider the advantages and disadvantages of such a change of representation model by means of a detailed description and comparison of the two inference algorithms with regard to the approach used for their implementation, their computational complexity, their termination criteria, and their performance on a corpus of synthetic data. [ABSTRACT FROM AUTHOR]

El artículo discute las aplicaciones de la economía computacional y la teoría de la complejidad. Se discuten los resultados de un estudio sobre las simulaciones computacionales, la modelación y su relación con los modelos económicos. El autor sigue discutiendo las herramientas necesarias para el estudio de sistemas sociales complejos.

El artículo presenta una reflexión del autor acerca del aprovechamiento del comportamiento caótico en las ingenierías. El autor discurre sobre la complejidad no-lineal en los fenómenos naturales y hace referencia al empleo de modelos matemáticos para representar comportamientos dinámicos con componentes aleatorios. Explora su aplicación mediante la convergencia de un sistema caótico en un punto de equilibro y su conversión en un sistema con periodicidad oscilatoria.