full-FORCE: A Target-Based Method for Training Recurrent Networks

Trained recurrent networks are powerful tools for modeling dynamic neural computations. We present a target-based method for modifying the full connectivity matrix of a recurrent network to train it to perform tasks involving temporally complex input/output transformations. The method introduces a second network during training to provide suitable "target" dynamics useful for performing the task. Because it exploits the full recurrent connectivity, the method produces networks that perform tasks with fewer neurons and greater noise robustness than traditional least-squares (FORCE) approaches. In addition, we show how introducing additional input signals into the target-generating network, which act as task hints, greatly extends the range of tasks that can be learned and provides control over the complexity and nature of the dynamics of the trained, task-performing network.Comment: 20 pages, 8 figure

Mejoramiento de la capacidad de servicio en el cobro de peaje en la estación Chilca

Esta investigación se presenta con la finalidad de mejorar la capacidad de cobro en la estación de peaje Chilca, ubicada en el km. 66 de la Panamericana Sur y actualmente administrada por la empresa Concesionaria Vial del Perú. En el primer capítulo, se mostrará detalladamente la problematización del estudio, dando a conocer además nuestros objetivos, alcances y limitaciones en esta investigación. En el segundo capítulo, se presentará como base teórica investigaciones acerca de congestionamiento vehicular y teoría de colas. Además se mostrará los conceptos bases de estudio que necesitaremos para esta investigación, que son Teoría de Colas y Simulación. En el tercer y cuarto capítulo, se realizará el análisis de la situación actual del peaje, para lo cual se utilizarán los conceptos de Teoría de Colas y Simulación. Para el desarrollo de simulación se utilizará el software PROMODEL, esto con el fin de definir el modelo actual que presenta la estación de peaje en estudio. Finalmente, se mostrarán las propuestas de mejoras para éste caso, las cuales son presentadas a partir de los resultados mostrados anteriormente. La finalidad es mostrar soluciones con los cuales podemos mejorar los procesos y procedimientos, de tal manera que se incremente la capacidad de cobro sin saturar la estación de peaje.Tesi

BILROST: Handling Actuators of the Internet of Things through Tweets on Twitter using a Domain- Specific Language

In recent years, many investigations have appeared that combine the Internet of Things and Social Networks. Some of them addressed the interconnection of objects as Social Networks interconnect people, and others addressed the connection between objects and people. However, they usually used interfaces created for that purpose instead of using familiar interfaces for users. Why not integrate Smart Objects in traditional Social Networks? Why not control Smart Objects through natural interactions in Social Networks? The goal of this paper is to make easier to create applications that allow non-experts users to control Smart Objects actuators through Social Networks through the proposal of a novel approach to connect objects and people using Social Networks. This proposal will address how to use Twitter so that objects could perform actions based on Twitter users’ posts. Moreover, it will be presented a Domain-Specific language that could help in the task of defining the actions that objects could perform when people publish specific content on Twitter

Towards a Standard-based Domain-specific Platform to Solve Machine Learning-based Problems

Machine learning is one of the most important subfields of computer science and can be used to solve a variety of interesting artificial intelligence problems. There are different languages, framework and tools to define the data needed to solve machine learning-based problems. However, there is a great number of very diverse alternatives which makes it difficult the intercommunication, portability and re-usability of the definitions, designs or algorithms that any developer may create. In this paper, we take the first step towards a language and a development environment independent of the underlying technologies, allowing developers to design solutions to solve machine learning-based problems in a simple and fast way, automatically generating code for other technologies. That can be considered a transparent bridge among current technologies. We rely on Model-Driven Engineering approach, focusing on the creation of models to abstract the definition of artifacts from the underlying technologies

A review about Smart Objects, Sensors, and Actuators

Smart Objects and the Internet of Things are two ideas which describe the future, walk together, and complement each other. Thus, the interconnection among objects can make them more intelligent or expand their intelligence to unsuspected limits. This could be achieved with a new network that interconnects each object around the world. However, to achieve this goal, the objects need a network that supports heterogeneous and ubiquitous objects, a network where exists more traffic among objects than among humans, but supporting for both types. For these reasons, both concepts are very close. Cities, houses, cars, machines, or any another object that can sense, respond, work, or make easier the lives of their owner. This is a part of the future, an immediate future. Notwithstanding, first of all, there are to resolve a series of problems. The most important problem is the heterogeneity of objects. This article is going to show a theoretical frame and the related work about Smart Object. The article will explain what are Smart Objects, doing emphasis in their difference with Not- Smart Objects. After, we will present one of the different object classification system, in our opinion, the most complete

Impact of three co-occurring physical ecosystem engineers on soil Collembola communities

The interplay between organisms with their abiotic environment may have profound effects within ecological networks, but are still poorly understood. Soil physical ecosystem engineers (EEs) modify the abiotic environment, thereby potentially affecting the distribution of other species, such as microarthropods. We focus on three co-occurring physical EEs (i.e. cattle, vegetation, macrodetritivore) known for their profound effect on soil properties (e.g. pore volume, microclimate, litter thickness). We determined their effects on Collembola community composition and life-form strategy (a proxy for vertical distribution in soil) in a European salt marsh. Soil cores were collected in grazed (compacted soil, under short and tall vegetation) and non-grazed areas (decompacted soil, under short and tall vegetation), their pore structure analysed using X-ray computed tomography, after which Collembola were extracted. Collembola species richness was lower in grazed sites, but abundances were not affected by soil compaction or vegetation height. Community composition differed between ungrazed sites with short vegetation and the other treatments, due to a greater dominance of epigeic Collembola and lower abundance of euedaphic species in this treatment. We found that the three co-occurring EEs and their interactions modify the physical environment of soil fauna, particularly through changes in soil porosity and availability of litter. This alters the relative abundance of Collembola life-forms, and thus the community composition within the soil. As Collembola are known to play a crucial role in decomposition processes, these compositional changes in litter and soil layers are expected to affect ecosystem processes and functioning

Swift vs. Objective-C: A New Programming Language

The appearance of a new programming language gives the necessity to contrast its contribution with the existing programming languages to evaluate the novelties and improvements that the new programming language offers for developers. These kind of studies can show us the efficiency, improvements and useful or uselessness of the new programming languages. Also these studies can show us the good or bad properties of the existing programming languages. For these reasons, these studies allow us to know if the new programming language is offering improvements or relapses. In this article, we compare the new programming language of Apple, Swift, with the main programming language of Apple before Swift, Objective-C. We are going to show the differences, characteristics and novelties to verify the words of Apple about Swift. With that we want to answer the next question: Is Swift a new programming language easier, more secure and quicker to develop than Objective-C

A Comparison of Cybersecurity Risk Analysis Tools

This paper presents the ongoing work of a decision aiding software intended to support cyber risk and cyber threats analysis of an information and communications technology infrastructure. The work focuses on the evaluation of the different tools in relation to risk assessment and decision making to incorporate some of the characteristics, metrics and strategies that will help cybersecurity risk analysis, decision-making, prevention measures and risk strategies for infrastructure and the protection of an organization's information assets

Optical Trapping of Single Nanostructures in a Weakly Focused Beam. Application to Magnetic Nanoparticles

"This document is the Accepted Manuscript version of a Published Work that appeared in final form in The Journal of Physical Chemistry C, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see [insert ACS Articles on Request author-directed link to Published Work, see https://pubs.acs.org/doi/10.1021/acs.jpcc.8b04676."[EN] Optical trapping of individual particles is believed to be only effective under highly focused beams because these conditions strengthen the gradient forces. This is especially critical in the beam propagating direction, where the scattering and absorption forces must be counterbalanced. Here, we demonstrate that optical trapping of nanostructures is also possible in a weakly focused beam. We study the theoretical conditions for effective three-dimensional optical confinement and verify them experimentally on iron-oxide-based nanoparticles with and without a silica coating, for which scattering, absorption, and gradient forces exist. This chemical approach to their all-optical control is, in turn, convenient for making magnetic nanostructures biocompatible. Weakly focused beams reduce the irradiance in the focal region and therefore the photon damage to the samples, which is further important to delay quantum dot quenching in the trap or to prevent artifacts in the study of biomolecular motor dynamics.We are grateful to Dr. Maria Acebron and Dr. Beatriz H. Juarez for their support in the silica encapsulation of the nano particles. This work was supported by the Spanish Ministry of Economy and Competitiveness (MINECO, Grant MAT2015-71806-R). IMDEA Nanociencia acknowledges support from the "Severo Ochoa" Programme for Centers of Excellence in R&D (MINECO, Grant SEV-2016-0686). H.R.-R. is supported by an FPI-UAM fellowship.Rodríguez-Rodríguez, H.; De Lorenzo, S.; De La Cueva, L.; Salas, G.; Arias-Gonzalez, JR. (2018). Optical Trapping of Single Nanostructures in a Weakly Focused Beam. Application to Magnetic Nanoparticles. The Journal of Physical Chemistry C. 122(31):18094-18101. https://doi.org/10.1021/acs.jpcc.8b04676S18094181011223

A Review of Artificial Intelligence in the Internet of Things

Humankind has the ability of learning new things automatically due to the capacities with which we were born. We simply need to have experiences, read, study… live. For these processes, we are capable of acquiring new abilities or modifying those we already have. Another ability we possess is the faculty of thinking, imagine, create our own ideas, and dream. Nevertheless, what occurs when we extrapolate this to machines? Machines can learn. We can teach them. In the last years, considerable advances have been done and we have seen cars that can recognise pedestrians or other cars, systems that distinguish animals, and even, how some artificial intelligences have been able to dream, paint, and compose music by themselves. Despite this, the doubt is the following: Can machines think? Or, in other words, could a machine which is talking to a person and is situated in another room make them believe they are talking with another human? This is a doubt that has been present since Alan Mathison Turing contemplated it and it has not been resolved yet. In this article, we will show the beginnings of what is known as Artificial Intelligence and some branches of it such as Machine Learning, Computer Vision, Fuzzy Logic, and Natural Language Processing. We will talk about each of them, their concepts, how they work, and the related work on the Internet of Things fields