Building intuition of iron evolution during solar cell processing through analysis of different process models

An important aspect of Process Simulators for photovoltaics is prediction of defect evolution during device fabrication. Over the last twenty years, these tools have accelerated process optimization, and several Process Simulators for iron, a ubiquitous and deleterious impurity in silicon, have been developed. The diversity of these tools can make it difficult to build intuition about the physics governing iron behavior during processing. Thus, in one unified software environment and using self-consistent terminology, we combine and describe three of these Simulators. We vary structural defect distribution and iron precipitation equations to create eight distinct Models, which we then use to simulate different stages of processing. We find that the structural defect distribution influences the final interstitial iron concentration ([Fe-i]) more strongly than the iron precipitation equations. We identify two regimes of iron behavior: (1) diffusivity-limited, in which iron evolution is kinetically limited and bulk [Fe-i] predictions can vary by an order of magnitude or more, and (2) solubility-limited, in which iron evolution is near thermodynamic equilibrium and the Models yield similar results. This rigorous analysis provides new intuition that can inform Process Simulation, material, and process development, and it enables scientists and engineers to choose an appropriate level of Model complexity based on wafer type and quality, processing conditions, and available computation time.

Video analysis based vehicle detection and tracking using an MCMC sampling framework

This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments. These methods do not scale well when the dimensionality of the feature space grows, which creates significant limitations when tracking multiple objects. Alternatively, the proposed method is based on a Markov chain Monte Carlo (MCMC) approach, which allows efficient sampling of the feature space. The method involves important contributions in both the motion and the observation models of the tracker. Indeed, as opposed to particle filter-based tracking methods in the literature, which typically resort to observation models based on appearance or template matching, in this study a likelihood model that combines appearance analysis with information from motion parallax is introduced. Regarding the motion model, a new interaction treatment is defined based on Markov random fields (MRF) that allows for the handling of possible inter-dependencies in vehicle trajectories. As for vehicle detection, the method relies on a supervised classification stage using support vector machines (SVM). The contribution in this field is twofold. First, a new descriptor based on the analysis of gradient orientations in concentric rectangles is dened. This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications. Second, a new vehicle image database is generated to train the SVM and made public. The proposed vehicle detection and tracking method is proven to outperform existing methods and to successfully handle challenging situations in the test sequences.

Analysis of frame-compatible subsampling structures for efficient 3DTV broadcast

The evolution of the television market is led by 3DTV technology, and this tendency can accelerate during the next years according to expert forecasts. However, 3DTV delivery by broadcast networks is not currently developed enough, and acts as a bottleneck for the complete deployment of the technology. Thus, increasing interest is dedicated to ste-reo 3DTV formats compatible with current HDTV video equipment and infrastructure, as they may greatly encourage 3D acceptance. In this paper, different subsampling schemes for HDTV compatible transmission of both progressive and interlaced stereo 3DTV are studied and compared. The frequency characteristics and preserved frequency content of each scheme are analyzed, and a simple interpolation filter is specially designed. Finally, the advantages and disadvantages of the different schemes and filters are evaluated through quality testing on several progressive and interlaced video sequences.

Development of Efficient FPGA-Based Multi-Channel Phase Meters for IR-Interferometers

Infrared (IR) interferometry is a method for measuring the line-electron density of fusion plasmas. The significant performance achieved by FPGAs in solving digital signal processing tasks advocates the use of this type of technology in two-color IR interferometers of modern stellarators, such as the TJ-II (Madrid, Spain) and the future W7-X (Greifswald, Germany). In this work the implementation of a line-average electron density measuring system in an FPGA device is described. Several optimizations for multichannel systems are detailed and test results from the TJ-II as well as from a W7-X prototype are presented.

Promising Prospects in Mobile Search: Business As Usual or Techno-Economic Disruptions?

It has taken more than a decade of intense technical and market developments for mobile Internet to take off as a mass phenomenon. And it has arrived with great intensity: an avalanche of mobile content and applications is now overrunning us. Similar to its wired counterpart, wireless Web users will continuously demand access to data and content in an efficient and user-friendly manner.

Improving Speech Interaction in Vehicles Using Context-Aware Information through A SCXML Framework

Speech Technologies can provide important benefits for the development of more usable and safe in-vehicle human-machine interactive systems (HMIs). However mainly due robustness issues, the use of spoken interaction can entail important distractions to the driver. In this challenging scenario, while speech technologies are evolving, further research is necessary to explore how they can be complemented with both other modalities (multimodality) and information from the increasing number of available sensors (context-awareness). The perceived quality of speech technologies can significantly be increased by implementing such policies, which simply try to make the best use of all the available resources; and the in vehicle scenario is an excellent test-bed for this kind of initiatives. In this contribution we propose an event-based HMI design framework which combines context modelling and multimodal interaction using a W3C XML language known as SCXML. SCXML provides a general process control mechanism that is being considered by W3C to improve both voice interaction (VoiceXML) and multimodal interaction (MMI). In our approach we try to anticipate and extend these initiatives presenting a flexible SCXML-based approach for the design of a wide range of multimodal context-aware HMI in-vehicle interfaces. The proposed framework for HMI design and specification has been implemented in an automotive OSGi service platform, and it is being used and tested in the Spanish research project MARTA for the development of several in-vehicle interactive applications.

Real Time FPGA Implementation of an Modulation Classifier for Electronic Warfare Applications

This paper presents an automatic modulation classifier for electronic warfare applications. It is a pattern recognition modulation classifier based on statistical features of the phase and instantaneous frequency. This classifier runs in a real time operation mode with sampling rates in excess of 1 Gsample/s. The hardware platform for this application is a Field Programmable Gate Array (FPGA). This AMC is subsidiary of a digital channelised receiver also implemented in the same platform.

Optimized edge appearance probability for cooperative localization based on tree-reweighted nonparametric belief propagation

Nonparametric belief propagation (NBP) is a well-known particle-based method for distributed inference in wireless networks. NBP has a large number of applications, including cooperative localization. However, in loopy networks NBP suffers from similar problems as standard BP, such as over-confident beliefs and possible nonconvergence. Tree-reweighted NBP (TRW-NBP) can mitigate these problems, but does not easily lead to a distributed implementation due to the non-local nature of the required so-called edge appearance probabilities. In this paper, we propose a variation of TRWNBP, suitable for cooperative localization in wireless networks. Our algorithm uses a fixed edge appearance probability for every edge, and can outperform standard NBP in dense wireless networks.

Uniformly reweighted belief propagation for distributed Bayesian hypothesis testing

Belief propagation (BP) is a technique for distributed inference in wireless networks and is often used even when the underlying graphical model contains cycles. In this paper, we propose a uniformly reweighted BP scheme that reduces the impact of cycles by weighting messages by a constant ?edge appearance probability? rho ? 1. We apply this algorithm to distributed binary hypothesis testing problems (e.g., distributed detection) in wireless networks with Markov random field models. We demonstrate that in the considered setting the proposed method outperforms standard BP, while maintaining similar complexity. We then show that the optimal ? can be approximated as a simple function of the average node degree, and can hence be computed in a distributed fashion through a consensus algorithm.

Improvement for detection of microcalcifications through clustering algorithms and artificial neural networks

A new method for detecting microcalcifications in regions of interest (ROIs) extracted from digitized mammograms is proposed. The top-hat transform is a technique based on mathematical morphology operations and, in this paper, is used to perform contrast enhancement of the mi-crocalcifications. To improve microcalcification detection, a novel image sub-segmentation approach based on the possibilistic fuzzy c-means algorithm is used. From the original ROIs, window-based features, such as the mean and standard deviation, were extracted; these features were used as an input vector in a classifier. The classifier is based on an artificial neural network to identify patterns belonging to microcalcifications and healthy tissue. Our results show that the proposed method is a good alternative for automatically detecting microcalcifications, because this stage is an important part of early breast cancer detection

Banco de medidas automático para linealización de amplificadores

This work is focused on building and configuring a measurement test bench for non linear High Power Amplifiers, more precisely those ones based on the Envelope Elimination and Restoration. At first sight the test bench is composed of several arbitrary waveform generators, an oscilloscope, a vector signal generator and a spectrum analyzer all of them controlled remotely. The test bench works automatically, that is why several software control programs have been developed in order to control all this equipment. The control programs have been developed in Matlab/Octave Scripting language and at last chance in a more low level language as C. The signal processing algorithms, taking into account that the time alignment one is the most important, have been developed in Matlab/Octave Scripting too. An improvement of 10dB in the ACPR(Adjacent Channel Power Ratio) has been obtained just by applying the time alignment algorithm developed in this work

DCT Type-III for Multicarrier Modulation

In this paper we propose the use of Discrete Cosine Transform Type-III (DCT3) for multicarrier modulation. There are two DCT3 (even and odd) and, for each of them, we derive the expressions for both prefix and suffix to be appended into each data symbol to be transmitted. Moreover, DCT3 are closely related to the corresponding inverse DCT Type-II even and odd. Furthermore, we give explicit expressions for the 1-tap per subcarrier equalizers that must be implemented at the receiver to perform the channel equalization in the frequency-domain. As a result, the proposed DCT3-based multicarrier modulator can be used as an alternative to DFT-based systems to perform Orthogonal Frequency-Division Multiplexing or Discrete Multitone Modulation

A region based approach to background modeling in a wavelet multi-resolution framework

In the field of detection and monitoring of dynamic objects in quasi-static scenes, background subtraction techniques where background is modeled at pixel-level, although showing very significant limitations, are extensively used. In this work we propose a novel approach to background modeling that operates at region-level in a wavelet based multi-resolution framework. Based on a segmentation of the background, characterization is made for each region independently as a mixture of K Gaussian modes, considering the model of the approximation and detail coefficients at the different wavelet decomposition levels. Background region characterization is updated along time, and the detection of elements of interest is carried out computing the distance between background region models and those of each incoming image in the sequence. The inclusion of the context in the modeling scheme through each region characterization makes the model robust, being able to support not only gradual illumination and long-term changes, but also sudden illumination changes and the presence of strong shadows in the scene

Hand Image Segmentation by means of Gaussian Multiscale Aggregation for biometric applications

Applying biometrics to daily scenarios involves demanding requirements in terms of software and hardware. On the contrary, current biometric techniques are also being adapted to present-day devices, like mobile phones, laptops and the like, which are far from meeting the previous stated requirements. In fact, achieving a combination of both necessities is one of the most difficult problems at present in biometrics. Therefore, this paper presents a segmentation algorithm able to provide suitable solutions in terms of precision for hand biometric recognition, considering a wide range of backgrounds like carpets, glass, grass, mud, pavement, plastic, tiles or wood. Results highlight that segmentation accuracy is carried out with high rates of precision (F-measure 88%)), presenting competitive time results when compared to state-of-the-art segmentation algorithms time performance

Implementación de Algoritmos de Procesado de Señal sobre FPGA: Especificación, Reutilización y Exploración del Espacio de Diseño

Esta Tesis aborda el diseño e implementación de aplicaciones en el campo de procesado de señal, utilizando como plataforma los dispositivos reconfigurables FPGA. Esta plataforma muestra una alta capacidad de lógica, e incorpora elementos orientados al procesado de señal, que unido a su relativamente bajo coste, la hacen ideal para el desarrollo de aplicaciones de procesado de señal cuando se requiere realizar un procesado intensivo y se buscan unas altas prestaciones. Sin embargo, el coste asociado al desarrollo en estas plataformas es elevado. Mientras que el aumento en la capacidad lógica de los dispositivos FPGA permite el desarrollo de sistemas completos, los requisitos de altas prestaciones obligan a que en muchas ocasiones se deban optimizar operadores a muy bajo nivel. Además de las restricciones temporales que imponen este tipo de aplicaciones, también tienen asociadas restricciones de área asociadas al dispositivo, lo que obliga a evaluar y verificar entre diferentes alternativas de implementación. El ciclo de diseño e implementación para estas aplicaciones se puede prolongar tanto, que es normal que aparezcan nuevos modelos de FPGA, con mayor capacidad y mayor velocidad, antes de completar el sistema, y que hagan a las restricciones utilizadas para el diseño del sistema inútiles. Para mejorar la productividad en el desarrollo de estas aplicaciones, y con ello acortar su ciclo de diseño, se pueden encontrar diferentes métodos. Esta Tesis se centra en la reutilización de componentes hardware previamente diseñados y verificados. Aunque los lenguajes HDL convencionales permiten reutilizar componentes ya definidos, se pueden realizar mejoras en la especificación que simplifiquen el proceso de incorporar componentes a nuevos diseños. Así, una primera parte de la Tesis se orientará a la especificación de diseños basada en componentes predefinidos. Esta especificación no sólo busca mejorar y simplificar el proceso de añadir componentes a una descripción, sino que también busca mejorar la calidad del diseño especificado, ofreciendo una mayor posibilidad de configuración e incluso la posibilidad de informar de características de la propia descripción. Reutilizar una componente ya descrito depende en gran medida de la información que se ofrezca para su integración en un sistema. En este sentido los HDLs convencionales únicamente proporcionan junto con la descripción del componente la interfaz de entrada/ salida y un conjunto de parámetros para su configuración, mientras que el resto de información requerida normalmente se acompaña mediante documentación externa. En la segunda parte de la Tesis se propondrán un conjunto de encapsulados cuya finalidad es incorporar junto con la propia descripción del componente, información que puede resultar útil para su integración en otros diseños. Incluyendo información de la implementación, ayuda a la configuración del componente, e incluso información de cómo configurar y conectar al componente para realizar una función. Finalmente se elegirá una aplicación clásica en el campo de procesado de señal, la transformada rápida de Fourier (FFT), y se utilizará como ejemplo de uso y aplicación, tanto de las posibilidades de especificación como de los encapsulados descritos. El objetivo del diseño realizado no sólo mostrará ejemplos de la especificación propuesta, sino que también se buscará obtener una implementación de calidad comparable con resultados de la literatura. Para ello, el diseño realizado se orientará a su implementación en FPGA, aprovechando tanto los elementos lógicos generalistas como elementos específicos de bajo nivel disponibles en estos dispositivos. Finalmente, la especificación de la FFT obtenida se utilizará para mostrar cómo incorporar en su interfaz información que ayude para su selección y configuración desde fases tempranas del ciclo de diseño. Abstract This PhD. thesis addresses the design and implementation of signal processing applications using reconfigurable FPGA platforms. This kind of platform exhibits high logic capability, incorporates dedicated signal processing elements and provides a low cost solution, which makes it ideal for the development of signal processing applications, where intensive data processing is required in order to obtain high performance. However, the cost associated to the hardware development on these platforms is high. While the increase in logic capacity of FPGA devices allows the development of complete systems, high-performance constraints require the optimization of operators at very low level. In addition to time constraints imposed by these applications, Area constraints are also applied related to the particular device, which force to evaluate and verify a design among different implementation alternatives. The design and implementation cycle for these applications can be tedious and long, being therefore normal that new FPGA models with a greater capacity and higher speed appear before completing the system implementation. Thus, the original constraints which guided the design of the system become useless. Different methods can be used to improve the productivity when developing these applications, and consequently shorten their design cycle. This PhD. Thesis focuses on the reuse of hardware components previously designed and verified. Although conventional HDLs allow the reuse of components already defined, their specification can be improved in order to simplify the process of incorporating new design components. Thus, a first part of the PhD. Thesis will focus on the specification of designs based on predefined components. This specification improves and simplifies the process of adding components to a description, but it also seeks to improve the quality of the design specified with better configuration options and even offering to report on features of the description. Hardware reuse of a component for its integration into a system largely depends on the information it offers. In this sense the conventional HDLs only provide together with the component description, the input/output interface and a set of parameters for its configuration, while other information is usually provided by external documentation. In the second part of the Thesis we will propose a formal way of encapsulation which aims to incorporate with the component description information that can be useful for its integration into other designs. This information will include features of the own implementation, but it will also support component configuration, and even information on how to configure and connect the component to carry out a function. Finally, the fast Fourier transform (FFT) will be chosen as a well-known signal processing application. It will be used as case study to illustrate the possibilities of proposed specification and encapsulation formalisms. The objective of the FFT design is not only to show practical examples of the proposed specification, but also to obtain an implementation of a quality comparable to scientific literature results. The design will focus its implementation on FPGA platforms, using general logic elements as base of the implementation, but also taking advantage of low-level specific elements available on these devices. Last, the specification of the obtained FFT will be used to show how to incorporate in its interface information to assist in the selection and configuration process early in the design cycle.