Grammars and cellular automata for evolving neural networks architectures

IEEE International Conference on Systems, Man, and Cybernetics. Nashville, TN, 8-11 October 2000The class of feedforward neural networks trained with back-propagation admits a large variety of specific architectures applicable to approximation pattern tasks. Unfortunately, the architecture design is still a human expert job. In recent years, the interest to develop automatic methods to determine the architecture of the feedforward neural network has increased, most of them based on the evolutionary computation paradigm. From this approach, some perspectives can be considered: at one extreme, every connection and node of architecture can be specified in the chromosome representation using binary bits. This kind of representation scheme is called the direct encoding scheme. In order to reduce the length of the genotype and the search space, and to make the problem more scalable, indirect encoding schemes have been introduced. An indirect scheme under a constructive algorithm, on the other hand, starts with a minimal architecture and new levels, neurons and connections are added, step by step, via some sets of rules. The rules and/or some initial conditions are codified into a chromosome of a genetic algorithm. In this work, two indirect constructive encoding schemes based on grammars and cellular automata, respectively, are proposed to find the optimal architecture of a feedforward neural network

Neural Network architectures design by Cellular Automata evolution

4th Conference of Systemics Cybernetics and Informatics. Orlando, 23-26 July 2000The design of the architecture is a crucial step in the successful application of a neural network. However, the architecture design is basically, in most cases, a human experts job. The design depends heavily on both, the expert experience and on a tedious trial-and-error process. Therefore, the development of automatic methods to determine the architecture of feedforward neural networks is a field of interest in the neural network community. These methods are generally based on search techniques, as genetic algorithms, simulated annealing or evolutionary strategies. Most of the designed methods are based on direct representation of the parameters of the network. This representation does not allow scalability, so to represent large architectures very large structures are required. In this work, an indirect constructive encoding scheme is proposed to find optimal architectures of feed-forward neural networks. This scheme is based on cellular automata representations in order to increase the scalability of the method.Publicad

Education on Sustainable Development Goals: Geographical Perspectives for Gender Equality in Sustainable Cities and Communities

Because of its interdisciplinary approach as a social science directly related to the natural sciences, geography is the academic discipline and school subject that equips students well with knowledge, skills, and values related to education on sustainable development goals. This study is part of the results of MyGEO, a project funded by the European Commission, and it is based on a collaborative mapping of streets named after women in a medium-sized city (Zaragoza, Spain), in connection with the international initiative GeoChicas (GeoGirls) on OpenStreetMap. Its main objective is to obtain evidence to emphasize, through public and digital space, gender equality and the empowerment of women in teacher education by means of their achievements. The learning methodology consists of (i) standardization and correction of alphanumeric information referring to street names contained in the OpenStreetMap spatial database that identify gender and (ii) linking and creating thematic information through Wikipedia editing. The results show that Zaragoza is at the top of the ranking of Spanish and Latin American cities mapped to date in the “Women’s Streets” viewer, with 18% of the streets named after women, compared to the average 15% in the rest of the 30 cities involved in GeoChicas. The direct participation of trainee primary and secondary schoolteachers in this project makes it possible to consolidate a narrative as well as a specific instructional design on education for sustainable development, particularly on SDG number 5 (gender balance) and SDG number 11 (sustainable cities and communities). © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Mobile learning for sustainable development and environmental teacher education

Outdoor learning has, for a long time, been an important instructional resource in school education, usually embedded in the natural sciences and social sciences curricula. Teaching geography, geology, or biology beyond the traditional classroom allows students to interact with physical and social environments for meaningful learning. Mobile devices that are based on geospatial technologies have provided more accurate data, but also a combined instructional design with other WebGIS, map viewers, or geographic information system (GIS) layers, which are useful to foster education for sustainable development. This paper analyzes the applications of mobile learning based on citizen science and volunteer geographic information, but also on the growing awareness that citizens and educators need a set of digital competencies to enhance and innovate lifelong learning and active citizenship. The empirical research aims to measure teacher–training experience, highlighting the potential of mobile devices and their applications in environmental education. Data collected from the research and results prove the positive impact of mobile learning in environmental education. Finally, a discussion about mobile learning and education for sustainable development is provided

Generative capacities of cellular automata codification for evolution of NN codification

Proceeding of: International Conference on Artificial Neural Networks. ICANN 2002, Madrid, Spain, August 28-30, 2002Automatic methods for designing artificial neural nets are desired to avoid the laborious and erratically human expert’s job. Evolutionary computation has been used as a search technique to find appropriate NN architectures. Direct and indirect encoding methods are used to codify the net architecture into the chromosome. A reformulation of an indirect encoding method, based on two bi-dimensional cellular automata, and its generative capacity are presented.Publicad

Evolutionary cellular configurations for designing feed-forward neural networks architectures

Proceeding of: 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13–15, 2001In the recent years, the interest to develop automatic methods to determine appropriate architectures of feed-forward neural networks has increased. Most of the methods are based on evolutionary computation paradigms. Some of the designed methods are based on direct representations of the parameters of the network. These representations do not allow scalability, so to represent large architectures, very large structures are required. An alternative more interesting are the indirect schemes. They codify a compact representation of the neural network. In this work, an indirect constructive encoding scheme is presented. This scheme is based on cellular automata representations in order to increase the scalability of the method

Non-Direct Encoding Method Based on Cellular Automata to Design Neural Network Architectures

Architecture design is a fundamental step in the successful application of Feed forward Neural Networks. In most cases a large number of neural networks architectures suitable to solve a problem exist and the architecture design is, unfortunately, still a human expert’s job. It depends heavily on the expert and on a tedious trial-and-error process. In the last years, many works have been focused on automatic resolution of the design of neural network architectures. Most of the methods are based on evolutionary computation paradigms. Some of the designed methods are based on direct representations of the parameters of the network. These representations do not allow scalability; thus, for representing large architectures very large structures are required. More interesting alternatives are represented by indirect schemes. They codify a compact representation of the neural network. In this work, an indirect constructive encoding scheme is proposed. This scheme is based on cellular automata representations and is inspired by the idea that only a few seeds for the initial configuration of a cellular automaton can produce a wide variety of feed forward neural networks architectures. The cellular approach is experimentally validated in different domains and compared with a direct codification scheme.Publicad

Synthesis, Photochemical, and Redox Properties of Gold(I) and Gold(III) Pincer Complexes Incorporating a 2,2′:6′,2″-Terpyridine Ligand Framework

Reaction of [Au(C6F5)(tht)] (tht = tetrahydrothiophene) with 2,2′:6′,2″-terpyridine (terpy) leads to complex [Au(C6F5)(η1-terpy)] (1). The chemical oxidation of complex (1) with 2 equiv of [N(C6H4Br-4)3](PF6) or using electrosynthetic techniques affords the Au(III) complex [Au(C6F5)(η3-terpy)](PF6)2 (2). The X-ray diffraction study of complex 2 reveals that the terpyridine acts as tridentate chelate ligand, which leads to a slightly distorted square-planar geometry. Complex 1 displays fluorescence in the solid state at 77 K due to a metal (gold) to ligand (terpy) charge transfer transition, whereas complex 2 displays fluorescence in acetonitrile due to excimer or exciplex formation. Time-dependent density functional theory calculations match the experimental absorption spectra of the synthesized complexes. In order to further probe the frontier orbitals of both complexes and study their redox behavior, each compound was separately characterized using cyclic voltammetry. The bulk electrolysis of a solution of complex 1 was analyzed by spectroscopic methods confirming the electrochemical synthesis of complex 2

Sex Differences in COVID-19 Hospitalization and Hospital Mortality among Patients with COPD in Spain: A Retrospective Cohort Study

We aimed to assess the effect of COPD in the incidence of hospital admissions for COVID-19 and on the in-hospital mortality (IHM) according to sex. (2) Methods: We used national hospital discharge data to select persons aged ≥40 years admitted to a hospital with a diagnosis of COVID-19 in 2020 in Spain. (3) Results: The study population included 218,301 patients. Age-adjusted incidence rates of COVID-19 hospitalizations for men with and without COPD were 10.66 and 9.27 per 1000 persons, respectively (IRR 1.14; 95% CI 1.08–1.20; p < 0.001). The IHM was higher in men than in women regardless of the history of COPD. The COPD was associated with higher IHM among women (OR 1.09; 95% CI 1.01–1.22) but not among men. The COPD men had a 25% higher risk of dying in the hospital with COVID-19 than women with COPD (OR 1.25, 95% CI 1.1–1.42). (4) Conclusions: Sex differences seem to exist in the effect of COPD among patients suffering COVID-19. The history of COPD increased the risk of hospitalization among men but not among women, and COPD was only identified as a risk factor for IHM among women. In any case, we observed that COPD men had a higher mortality than COPD women. Understanding the mechanisms underlying these sex differences could help predict the patient outcomes and inform clinical decision making to facilitate early treatment and disposition decisions.Fac. de Enfermería, Fisioterapia y PodologíaTRUEComunidad de MadridUniversidad Complutense de Madridpu

Positioning Axes of Sustainable Tourist Destinations: The Case of Aragón

The purpose of this research is to determine the optimal positioning strategies of Aragón as a sustainable tourist destination. An exploratory research is carried out based on the analysis of statistical information sources, the identification of global and multisectoral macro-trends with direct impact on the evolution of the tourist sector, and the use of the qualitative technique of the focus group. The main and secondary axes to provide a basis for the positioning strategy of the autonomous community are presented as a resul