A novel neural network design for long range prediction of rainfall pattern

The importance of long-range prediction of rainfall pattern for devising and planning agricultural strategies cannot be overemphasized. However, the prediction of rainfall pattern remains a difficult problem and the desired level of accuracy has not been reached. The conventional methods for prediction of rainfall use either dynamical or statistical modelling. In this article we report the results of a new modelling technique using artificial neural networks. Artificial neural networks are especially useful where the dynamical processes and their interrelations for a given phenomenon are not known with sufficient accuracy. Since conventional neural networks were found to be unsuitable for simulating and predicting rainfall patterns, a generalized structure of a neural network was then explored and found to provide consistent prediction (hindcast) of all-India annual mean rainfall with good accuracy. Performance and consistency of this network are evaluated and compared with those of other (conventional) neural networks. It is shown that the generalized network can make consistently good prediction of annual mean rainfall. Immediate application and potential of such a prediction system are discussed.

Investigations on Reconfigurable Dual Frequency Microstrip Antennas Controlled by PIN Diodes and Varactors

In this work,we investigate novel designs of compact electronically reconfigurable dual frequency microstrip antennas with a single feed,operating mainly in L-band,without using any matching networks and complicated biasing circuitry.These antennas have been designed to operate in very popular frequency range where a great number of wireless communication applications exist.Efforts were carried out to introduce a successful,low cost reconfigurable dual-frequency microstrip antenna design to the wireless and radio frequency design community.

Sistema de selección automática de soluciones tecnológicas de seguridad

Desde la aparición de Internet, hace ya más de 20 años ha existido por parte de diversos sectores de la sociedad, científicos, empresas, usuarios, etc. la inquietud por la aplicación de esta tecnología a lo que se ha dado en llamar “El Internet de las Cosas”, que no es más que el control a distancia de cualquier elemento útil o necesario para la vida cotidiana y la industria. Sin embargo el desarrollo masivo de aplicaciones orientadas a esto, no ha evolucionado hasta que no se han producido avances importantes en dos campos: por un lado, en las Redes Inalámbricas de Sensores (WSN), redes compuestas por un conjunto de pequeños dispositivos capaces de transmitir la información que recogen, haciéndola llegar desde su propia red inalámbrica, a otras de amplia cobertura y por otro con la miniaturización cada vez mayor de dispositivos capaces de tener una autonomía suficiente como para procesar datos e interconectarse entre sí. Al igual que en las redes de ordenadores convencionales, las WSN se pueden ver comprometidas en lo que a seguridad se refiere, ya que la masiva implementación de estas redes hará que millones de Terabytes de datos, muchas veces comprometidos o sometidos a estrictas Leyes de protección de los mismos, circulen en la sociedad de la información, de forma que lo que nace como una ventaja muy interesante para sus usuarios, puede convertirse en una pesadilla debido a la amenaza constante hacia los servicios mínimos de seguridad que las compañías desarrolladoras han de garantizar a los usuarios de sus aplicaciones. Éstas, y con el objetivo de proveer un ámbito de seguridad mínimo, deben de realizar un minucioso estudio de la aplicación en particular que se quiere ofrecer con una WSN y también de las características específicas de la red ya que, al estar formadas por dispositivos prácticamente diminutos, pueden tener ciertas limitaciones en cuanto al tamaño de la batería, capacidad de procesamiento, memoria, etc. El presente proyecto desarrolla una aplicación, única, ya que en la actualidad no existe un software con similares características y que aporta un avance importante en dos campos principalmente: por un lado ayudará a los usuarios que deseen desplegar una aplicación en una red WSN a determinar de forma automática cuales son los mecanismos y servicios específicos de seguridad que se han de implementar en dicha red para esa aplicación concreta y, por otro lado proporcionará un apoyo extra a expertos de seguridad que estén investigando en la materia ya que, servirá de plataforma de pruebas para centralizar la información sobre seguridad que se tengan en ese momento en una base de conocimientos única, proporcionando también un método útil de prueba para posibles escenarios virtuales. ABSTRACT. It has been more than 20 years since the Internet appeared and with it, scientists, companies, users, etc. have been wanted to apply this technology to their environment which means to control remotely devices, which are useful for the industry or aspects of the daily life. However, the huge development of these applications oriented to that use, has not evolve till some important researches has been occurred in two fields: on one hand, the field of the Wireless Sensor Networks (WSN) which are networks composed of little devices that are able to transmit the information that they gather making it to pass through from their wireless network to other wider networks and on the other hand with the increase of the miniaturization of the devices which are able to work in autonomous mode so that to process data and connect to each other. WSN could be compromised in the matter of security as well as the conventional computer networks, due to the massive implementation of this kind of networks will cause that millions of Terabytes of data will be going around in the information society, thus what it is thought at first as an interesting advantage for people, could turn to be a nightmare because of the continuous threat to the minimal security services that developing companies must guarantee their applications users. These companies, and with the aim to provide a minimal security realm, they have to do a strict research about the application that they want to implement in one WSN and the specific characteristics of the network as they are made by tiny devices so that they could have certain limitations related to the battery, throughput, memory, etc. This project develops a unique application since, nowadays, there is not any software with similar characteristics and it will be really helpful in mainly two areas: on one side, it will help users who want to deploy an application in one WSN to determine in an automatically way, which ones security services and mechanisms are those which is necessary to implement in that network for the concrete application and, on the other side, it will provide an extra help for the security experts who are researching in wireless sensor network security so that ti will an exceptional platform in order to centralize information about security in the Wireless Sensor Networks in an exclusive knowledge base, providing at the same time a useful method to test virtual scenarios.

Redes VSAT con el estándar DVB-S

Actualmente las redes VSAT (Very Small Aperture Terminal) están adquiriendo una mayor importancia en las comunicaciones por satélite debido a las nuevas aplicaciones que se están desarrollando tanto a nivel empresarial como a nivel de usuario final. El presente proyecto pretende hacer un estudio de este tipo de red para presentarla como una solución al problema de querer conectar estaciones dispersas, que por el perfil del terreno hace difícil la conexión de las mismas a través de las redes terrestres convencionales. Los nuevos estándares están haciendo que este tipo de redes proliferen muy deprisa ya que se consigue una mayor flexibilidad que con los estándares precedentes para este tipo de red. En concreto, en este proyecto se ha estudiado el estándar abierto DVB-S desarrollado por el grupo de trabajo DVB por ser uno de los más aceptado internacionalmente. Para comprender este sistema de comunicaciones, el proyecto está estructurado en dos partes. En la primera parte se hace una revisión de cómo han evolucionado las comunicaciones satelitales VSAT, indicando las ventajas y desventajas de su implementación y sobre todo la orientación que éstas muestran a la utilización de los estándares DVB. Posteriormente se realiza un estudio de los estándares DVB-S y DVBRCS en donde se profundiza en conceptos claves tales como el Multiplexado de Transporte MPEG-2, los mecanismos de envío de mensajes de señalización, etc. En la segunda parte del proyecto se presta atención a la seguridad de la red, analizando los mecanismos propios que presenta el estándar DVB así como los diferentes protocolos de seguridad existentes en las capas superiores para una protección adicional. Para concluir el proyecto se han creado dos aplicaciones, la primera como método didáctico para comprender mejor el comportamiento de las redes VSAT con el estándar DVB-S, y una segunda aplicación con carácter comercial para la transferencia de ficheros de manera segura con características específicas, enfocada particularmente en redes VSAT, aunque siendo posible su uso en otras redes. ABSTRACT. Nowadays VSAT networks (Very Small Aperture Terminal) are becoming more important in satellite communications, due to several new applications that are being developed both at company level and end user level. This project aims to make a study of this type of network to present it as a solution to the problem of wanting to connect scattered stations, because the terrain profile makes difficult to connect them via conventional terrestrial networks. New standards are making that such networks proliferate very quickly for the reason that a more flexibility than the previous standards for this type of network is achieved. Specifically, this project has studied the open standard DVB-S developed by the DVB workgroup as one of the most internationally accepted. To understand this communication system, this project is structured in two different parts: On one hand, in the first part a review about how VSAT satellite communications have evolved, indicating the advantages and disadvantages of its implementation and above all, the guidance that they show to the use of the DVB standards. Subsequently, a study of the DVB-S and DVB-RCS standards is developed, where delves into key concepts such as MPEG-2 Multiplexed Transport, mechanisms of transmission of signaling messages, etc. On the other hand, in the second part of the project, we focus on network security, analyzing the mechanisms presented by the DVB standard and various existing security protocols in the upper layers for an extra protection. To complete the project two different applications have been developed: the first one as a teaching method to better understand the behavior of VSAT networks in DVB-S standard, and the second one with a commercial basis for transferring files securely with specific features applications focused particularly in VSAT networks, although with a possible use on other networks.

Sensitivity analysis for active matched antennas with non-foster elements

During the last years many researchers have been working on the active matching or on non-Foster matching networks for one- and two-port electrically small antennas (ESAs). A new parameter on the sensitivity of the two-port electrically small antenna when loaded with a non-F oster network is presented. This sensitivity analysis will allow us to choose what kind of antennas can be properly matched with non-Foster networks and their position in order to optimi ze the performance of the design. Then, a typical high Q two-port antenna will be harder to match over a broad bandwidth, since |S21| is very small and only agrees with |S11| over very small frequency bands, yielding very large sensitivity values. However, for these two-port antennas, if high levels of coupling can be engineered for a high Q multiple-port antenna, the return and insertion losses can be similar over larger bandwidths and, hence, the sensitivity can be kept low over larger bandwidths, enabling broader impedance matched bandwidths to be achieved, even for highly resonant antennas.

Uma abordagem paramétrica do impacto da geração distribuída sobre as correntes de curto-circuito e na proteção de redes de distribuição.

Esta dissertação tem por propósito analisar os impactos da geração distribuída sobre as correntes de curto-circuito e sobre a proteção das redes de média tensão das concessionárias de distribuição de energia elétrica usando uma abordagem paramétrica. A principal motivação deste trabalho são os recentes incentivos regulatórios que estão fomentando a geração distribuída no Brasil. Contudo, as redes de distribuição convencionais foram projetadas para serem passivas e a introdução da geração poderá causar problemas de ordem técnica que ainda precisam ser resolvidos. Tais problemas foram pesquisados e aqueles relacionados com os impactos sobre as correntes de curto-circuito foram enfatizados. As normas técnicas das concessionárias também foram investigadas porque seus requisitos, como a ligação dos transformadores de acoplamento, influem nas correntes de curto-circuito. Para se calcular as correntes de curto-circuito, desenvolveu-se uma planilha eletrônica cujos resultados foram validados com programas comerciais de análise de redes elétricas. Esta ferramenta foi utilizada para demonstrar, através de exemplos, o impacto causado pela geração distribuída sobre as correntes de curto-circuito e, posteriormente, para realizar as análises paramétricas nas quais a influência de cada variável foi avaliada. A aplicação do método paramétrico permitiu o estudo de possíveis limites para a potência de um gerador distribuído em função dos impactos admissíveis, de seu ponto de conexão, de seus parâmetros elétricos e dos parâmetros elétricos da rede.

On Logical Correction of Neural Network Algorithms for Pattern Recognition

The paper is devoted to the description of hybrid pattern recognition method developed by research groups from Russia, Armenia and Spain. The method is based upon logical correction over the set of conventional neural networks. Output matrices of neural networks are processed according to the potentiality principle which allows increasing of recognition reliability.

The Cascade Neo-Fuzzy Architecture and its Online Learning Algorithm

In the paper learning algorithm for adjusting weight coefficients of the Cascade Neo-Fuzzy Neural Network (CNFNN) in sequential mode is introduced. Concerned architecture has the similar structure with the Cascade-Correlation Learning Architecture proposed by S.E. Fahlman and C. Lebiere, but differs from it in type of artificial neurons. CNFNN consists of neo-fuzzy neurons, which can be adjusted using high-speed linear learning procedures. Proposed CNFNN is characterized by high learning rate, low size of learning sample and its operations can be described by fuzzy linguistic “if-then” rules providing “transparency” of received results, as compared with conventional neural networks. Using of online learning algorithm allows to process input data sequentially in real time mode.

Digital surveillance based on video CODEC System-on-a-Chip (SoC) platforms

Today, most conventional surveillance networks are based on analog system, which has a lot of constraints like manpower and high-bandwidth requirements. It becomes the barrier for today's surveillance network development. This dissertation describes a digital surveillance network architecture based on the H.264 coding/decoding (CODEC) System-on-a-Chip (SoC) platform. The proposed digital surveillance network architecture includes three major layers: software layer, hardware layer, and the network layer. The following outlines the contributions to the proposed digital surveillance network architecture. (1) We implement an object recognition system and an object categorization system on the software layer by applying several Digital Image Processing (DIP) algorithms. (2) For better compression ratio and higher video quality transfer, we implement two new modules on the hardware layer of the H.264 CODEC core, i.e., the background elimination module and the Directional Discrete Cosine Transform (DDCT) module. (3) Furthermore, we introduce a Digital Signal Processor (DSP) sub-system on the main bus of H.264 SoC platforms as the major hardware support system for our software architecture. Thus we combine the software and hardware platforms to be an intelligent surveillance node. Lab results show that the proposed surveillance node can dramatically save the network resources like bandwidth and storage capacity.

Finding and matching communities in social networks using data mining

The rapid growth in the number of users using social networks and the information that a social network requires about their users make the traditional matching systems insufficiently adept at matching users within social networks. This paper introduces the use of clustering to form communities of users and, then, uses these communities to generate matches. Forming communities within a social network helps to reduce the number of users that the matching system needs to consider, and helps to overcome other problems from which social networks suffer, such as the absence of user activities' information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased using the community information.

Face recogniton based on the optimal combination of neural networks, eigenfaces and least squares matching methods

Report of a research project of the Fachhochschule Hannover, University of Applied Sciences and Arts, Department of Information Technologies. Automatic face recognition increases the security standards at public places and border checkpoints. The picture inside the identification documents could widely differ from the face, that is scanned under random lighting conditions and for unknown poses. The paper describes an optimal combination of three key algorithms of object recognition, that are able to perform in real time. The camera scan is processed by a recurrent neural network, by a Eigenfaces (PCA) method and by a least squares matching algorithm. Several examples demonstrate the achieved robustness and high recognition rate.

Extensive Comparisons of Optical Fast-OFDM and Conventional Optical OFDM for Local and Access Networks

A performance comparison between a recently proposed novel technique known as fast orthogonal frequency-division multiplexing (FOFDM) and conventional orthogonal frequency-division multiplexing (OFDM) is undertaken over unamplified, intensity-modulated, and direct-detected directly modulated laser-based optical signals. Key transceiver parameters, such as the maximum achievable transmission capacity and the digital-to-analog/analog-to-digital converter (DAC/ADC) effects are explored thoroughly. It is shown that, similarly to conventional OFDM, the least complex and bandwidth efficient FOFDM can support up to similar to 20 Gb/s over 500 m worst-case multimode fiber (MMF) links having 3 dB effective bandwidths of similar to 200 MHz X km. For compensation of the DAC/ADC roll-off, a power-loading (PL) algorithm is adopted, leading to an FOFDM system improvement of similar to 4 dB. FOFDM and conventional OFDM give similar optimum DAC/ADC parameters over 500 m worst-case MMF, while over 50 km single-mode fiber a maximum deviation of only similar to 1 dB in clipping ratio is observed due to the imperfect chromatic dispersion compensation caused by one-tap equalizers.

Assimilation of data from conventional and non conventional networks through a LETKF scheme in the COSMO model

The present work studies a km-scale data assimilation scheme based on a LETKF developed for the COSMO model. The aim is to evaluate the impact of the assimilation of two different types of data: temperature, humidity, pressure and wind data from conventional networks (SYNOP, TEMP, AIREP reports) and 3d reflectivity from radar volume. A 3-hourly continuous assimilation cycle has been implemented over an Italian domain, based on a 20 member ensemble, with boundary conditions provided from ECMWF ENS. Three different experiments have been run for evaluating the performance of the assimilation on one week in October 2014 during which Genova flood and Parma flood took place: a control run of the data assimilation cycle with assimilation of data from conventional networks only, a second run in which the SPPT scheme is activated into the COSMO model, a third run in which also reflectivity volumes from meteorological radar are assimilated. Objective evaluation of the experiments has been carried out both on case studies and on the entire week: check of the analysis increments, computing the Desroziers statistics for SYNOP, TEMP, AIREP and RADAR, over the Italian domain, verification of the analyses against data not assimilated (temperature at the lowest model level objectively verified against SYNOP data), and objective verification of the deterministic forecasts initialised with the KENDA analyses for each of the three experiments.

Matching Recall and Storage in Sequence Learning with Spiking Neural Networks

Storing and recalling spiking sequences is a general problem the brain needs to solve. It is, however, unclear what type of biologically plausible learning rule is suited to learn a wide class of spatiotemporal activity patterns in a robust way. Here we consider a recurrent network of stochastic spiking neurons composed of both visible and hidden neurons. We derive a generic learning rule that is matched to the neural dynamics by minimizing an upper bound on the Kullback–Leibler divergence from the target distribution to the model distribution. The derived learning rule is consistent with spike-timing dependent plasticity in that a presynaptic spike preceding a postsynaptic spike elicits potentiation while otherwise depression emerges. Furthermore, the learning rule for synapses that target visible neurons can be matched to the recently proposed voltage-triplet rule. The learning rule for synapses that target hidden neurons is modulated by a global factor, which shares properties with astrocytes and gives rise to testable predictions.