Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Artificial Neural Networks still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning ANN parameters. In recent years the use of hybrid technologies, combining Artificial Neural Networks and Genetic Algorithms, has been utilized to. In this work, several ANN topologies were trained and tested using Artificial Neural Networks and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out.

Redes para la promoción del desarrollo territorial en el cinturón hortícola platense : Reflexiones y aportes

En el cinturón hortícola platense áun conjunto de instituciones del sector público y privado, establecen redes de diálogo, en la que los sujetos interaccionan, en el marco de procesos de desarrollo regional. El trabajo tiene como objetivo, conocer yá analizar las redes de diálogo que contribuyen al desarrollo regional. Se utilizó una metodología de tipo cualitativa. Los resultados muestran la mayor densidad en las relaciones que se establecen desde distintas instituciones del sector público, para la ejecución de políticas. Asimismo, se visualiza el protagonismo e influencia que desde el sector privado, tienen los vendedores de insumos.

Redes para la promoción del desarrollo territorial en el cinturón hortícola platense : Reflexiones y aportes

En el cinturón hortícola platense áun conjunto de instituciones del sector público y privado, establecen redes de diálogo, en la que los sujetos interaccionan, en el marco de procesos de desarrollo regional. El trabajo tiene como objetivo, conocer yá analizar las redes de diálogo que contribuyen al desarrollo regional. Se utilizó una metodología de tipo cualitativa. Los resultados muestran la mayor densidad en las relaciones que se establecen desde distintas instituciones del sector público, para la ejecución de políticas. Asimismo, se visualiza el protagonismo e influencia que desde el sector privado, tienen los vendedores de insumos.

Redes para la promoción del desarrollo territorial en el cinturón hortícola platense : Reflexiones y aportes

En el cinturón hortícola platense áun conjunto de instituciones del sector público y privado, establecen redes de diálogo, en la que los sujetos interaccionan, en el marco de procesos de desarrollo regional. El trabajo tiene como objetivo, conocer yá analizar las redes de diálogo que contribuyen al desarrollo regional. Se utilizó una metodología de tipo cualitativa. Los resultados muestran la mayor densidad en las relaciones que se establecen desde distintas instituciones del sector público, para la ejecución de políticas. Asimismo, se visualiza el protagonismo e influencia que desde el sector privado, tienen los vendedores de insumos.

Predicting corticospinal excitability from pre-TMS EEG using convolutional neural networks

The amplitude of motor evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS) of the primary motor cortex (M1) shows a large variability from trial to trial, although MEPs are evoked by the same repeated stimulus. A multitude of factors is believed to influence MEP amplitudes, such as cortical, spinal and motor excitability state. The goal of this work is to explore to which degree the variation in MEP amplitudes can be explained by the cortical state right before the stimulation. Specifically, we analyzed a dataset acquired on eleven healthy subjects comprising, for each subject, 840 single TMS pulses applied to the left M1 during acquisition of electroencephalography (EEG) and electromyography (EMG). An interpretable convolutional neural network, named SincEEGNet, was utilized to discriminate between low- and high-corticospinal excitability trials, defined according to the MEP amplitude, using in input the pre-TMS EEG. This data-driven approach enabled considering multiple brain locations and frequency bands without any a priori selection. Post-hoc interpretation techniques were adopted to enhance interpretation by identifying the more relevant EEG features for the classification. Results show that individualized classifiers successfully discriminated between low and high M1 excitability states in all participants. Outcomes of the interpretation methods suggest the importance of the electrodes situated over the TMS stimulation site, as well as the relevance of the temporal samples of the input EEG closer to the stimulation time. This novel decoding method allows causal investigation of the cortical excitability state, which may be relevant for personalizing and increasing the efficacy of therapeutic brain-state dependent brain stimulation (for example in patients affected by Parkinson’s disease).

Paikkatiedon kerääminen ja hyödyntäminen WLAN-verkossa

Työn teoriaosuudessa tutustutaan ensin yleisimpiin paikannusmenetelmiin. Käsiteltävänä ovat GPS-satelliittipaikannus sekä radiosoluverkkojen paikannusmenetelmät solupaikannuksesta monimutkaisempiin signaalin ominaisuuksia tutkiviin menetelmiin. Teoriaosuudessa käsitellään myös IEEE 802.11 –standardin PHY- ja MAC-kerrosten toimintaa sekä WLAN-verkon siirtotien ominaisuuksia paikannuksen kannalta. Ennen paikannusjärjestelmän toteuttamista työssä esitellään menetelmiä ja tuloksia muista tutkimuksista samalta tutkimusalueelta. Työssä toteutetaan paikannusjärjestelmä sekä solupaikannusta että signaalitasopaikannusta hyödyntäen. Solupaikannusjärjestelmälle määritellään palvelurajapinta, jonka kautta paikannuspalvelua voidaan hyödyntää muissa palveluissa. Kaksi paikannuspalvelun päälle luotua palvelua esitellään lyhyesti malliesimerkkeinä. Signaalitasopaikannuksen osalta kuvataan kaksi menetelmään kuuluvaa vaihetta ja yksittäisten komponenttien toiminta näissä vaiheissa. Paikannusmenetelmien tarkkuutta tutkitaan mittausten avulla ja testituloksista muodostetaan paikannustarkkuutta kuvaavat tilastot. Solupaikannuksen keskimääräinen virhe on ±50 metriä. Vastaavasti signaalitasopaikannuksen virhe on ±4 metriä ja parannettua algoritmia käyttäen ±3 metriä.

Changing the Face of Traditional Education

At large, research universities, a common approach for teaching hundreds of undergraduate students at one time is the traditional, large, lecture-based course. Trends indicate that over the next decade there will be an increase in the number of large, campus courses being offered as well as larger enrollments in courses currently offered. As universities investigate alternative means to accommodate more students and their learning needs, Web-based instruction provides an attractive delivery mode for teaching large, on-campus courses. This article explores a theoretical approach regarding how Web-based instruction can be designed and developed to provide quality education for traditional, on-campus, undergraduate students. The academic debate over the merit of Web-based instruction for traditional, on-campus students has not been resolved. This study identifies and discusses instructional design theory for adapting a large, lecture-based course to the Web.

Mathe-Üben in Studium und Abitur

Fehlende Grundkenntnisse in der Mathematik zählen zu den größten Hindernissen für einen erfolgreichen Start in ein Hochschulstudium. Studienanfänger in einem MINT-Studium bringen inzwischen deutlich unterschiedliche Vorrausetzungen mit: „Mathe-Angst“ gilt als typisches Phänomen und der Übergang in ein selbstbestimmtes Lernverhalten stellt eine große Herausforderung dar. Diese Fall-Studie beschreibt, wie mit Hilfe einer Mathe-App bereits zu Beginn des Studiums aktives Lernen unterstützt und selbstbestimmtes Lernen eingeübt werden kann. Das neue Kurskonzept mit App-Unterstützung stößt an der Hochschule Offenburg auf breite Akzeptanz. Der mobile BYOD-Ansatz ermöglicht Lern-Szenarien, die über PC- bzw.- Laptop-gebundene eLearning-Lösungen nicht realisierbar sind. Der Inhalt des MassMatics-Vorbereitungskurs orientiert sich am Mindestanforderungskatalog des cosh-Arbeitskreises für den Übergang Schule-Hochschule. In der Zwischenzeit wurde der App-gestützte Kurs mit seinen über 500 Aufgaben von mehr als 1000 Studierenden besucht.

Aplicaciones de los modelos de predicción bio-inspirados en la administración

Las organizaciones y sus entornos son sistemas complejos. Tales sistemas son difíciles de comprender y predecir. Pese a ello, la predicción es una tarea fundamental para la gestión empresarial y para la toma de decisiones que implica siempre un riesgo. Los métodos clásicos de predicción (entre los cuales están: la regresión lineal, la Autoregresive Moving Average y el exponential smoothing) establecen supuestos como la linealidad, la estabilidad para ser matemática y computacionalmente tratables. Por diferentes medios, sin embargo, se han demostrado las limitaciones de tales métodos. Pues bien, en las últimas décadas nuevos métodos de predicción han surgido con el fin de abarcar la complejidad de los sistemas organizacionales y sus entornos, antes que evitarla. Entre ellos, los más promisorios son los métodos de predicción bio-inspirados (ej. redes neuronales, algoritmos genéticos /evolutivos y sistemas inmunes artificiales). Este artículo pretende establecer un estado situacional de las aplicaciones actuales y potenciales de los métodos bio-inspirados de predicción en la administración.

Review of Robust Cooperative Spectrum Sensing Techniques for Cognitive Radio Networks

Cognitive radio networks sense spectrum occupancy and manage themselvesto operate in unused bands without disturbing licensed users. The detection capability of aradio system can be enhanced if the sensing process is performed jointly by a group of nodesso that the effects of wireless fading and shadowing can be minimized. However, taking acollaborative approach poses new security threats to the system as nodes can report falsesensing data to reach a wrong decision. This paper makes a review of secure cooperativespectrum sensing in cognitive radio networks. The main objective of these protocols is toprovide an accurate resolution about the availability of some spectrum channels, ensuring thecontribution from incapable users as well as malicious ones is discarded. Issues, advantagesand disadvantages of such protocols are investigated and summarized.

Comparison Study of Pattern Synthesis Techniques Using Neural Networks

In this paper, a comparison study among three neuralnetwork algorithms for the synthesis of array patterns is presented. The neural networks are used to estimate the array elements' excitations for an arbitrary pattern. The architecture of the neural networks is discussed and simulation results are presented. Two new neural networks, based on radial basis functions (RBFs) and wavelet neural networks (WNNs), are introduced. The proposed networks offer a more efficient synthesis procedure, as compared to other available techniques

Cooperative caching techniques for mobile ad hoc networks

Data caching can remarkably improve the efficiency of information access in a wireless ad hoc network by reducing the access latency and bandwidth usage. The cache placement problem minimizes total data access cost in ad hoc networks with multiple data items. The ad hoc networks are multi hop networks without a central base station and are resource constrained in terms of channel bandwidth and battery power. By data caching the communication cost can be reduced in terms of bandwidth as well as battery energy. As the network node has limited memory the problem of cache placement is a vital issue. This paper attempts to study the existing cooperative caching techniques and their suitability in mobile ad hoc networks.

Artificial neural networks and clustering techniques applied in the reconfiguration of distribution systems

One objective of the feeder reconfiguration problem in distribution systems is to minimize the power losses for a specific load. For this problem, mathematical modeling is a nonlinear mixed integer problem that is generally hard to solve. This paper proposes an algorithm based on artificial neural network theory. In this context, clustering techniques to determine the best training set for a single neural network with generalization ability are also presented. The proposed methodology was employed for solving two electrical systems and presented good results. Moreover, the methodology can be employed for large-scale systems in real-time environment.

An approach to implement data fusion techniques in wireless sensor networks using genetic machine learning algorithms

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks. © 2013 Elsevier B.V. All rights reserved.

Geographical variation in mutualistic networks: similarity, turnover and partner fidelity

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)