Digital Filtering Algorithms

Abstract: Despite successful application of constraint programming (CP) to solving many real-life problems there is still an indispensable group or researchers considering (wrongly) CP as a simple evaluation technique only. Even if sophisticated search algorithms play an ...

This paper discusses the usage of sparse sets for integer domain implementation over traditional representations. A first benefit of sparse sets is that they are very cheap to trail and restore. A second key advantage introduced in this work is that sparse sets permit to get delta changes with a very limited cost, allowing efficient incremental propagation. Sparse sets can also be used to represent subset bound domains for set variables.

The problem of automatic tracking and segmentation of the left ventricle (LV) of the heart from ultrasound images can be formulated with an algorithm that computes the expected segmentation value in the current time step given all previous and current observations using a filtering distribution. This filtering distribution depends on the observation and transition models, and since it is hard to compute the expected value using the whole parameter space of segmentations, one has to resort to Monte Carlo sampling techniques to compute the expected segmentation parameters. Generally, it is straightforward to compute probability values using the filtering distribution, but it is hard to sample from it, which indicates the need to use a proposal distribution to provide an easier sampling method. In order to be useful, this proposal distribution must be carefully designed to represent a reasonable approximation for the filtering distribution. In this paper, we introduce a new LV tracking and segmentation algorithm based on the method described above, where our contributions are focused on a new transition and observation models, and a new proposal distribution. Our tracking and segmentation algorithm achieves better overall results on a previously tested dataset used as a benchmark by the current state-of-the-art tracking algorithms of the left ventricle of the heart from ultrasound images.

Social media plays an increasingly important role in people's life. Microblogging is a form of social media which allows people to share and disseminate real-life events. Broadcasting events in microblogging networks can be an effective method of creating awareness, divulging important information, and so on. However, many existing approaches at dissecting the information content primarily discuss the event detection model and ignore the user interest which can be discovered during event evolution. This leads to difficulty in tracking the most important events as they evolve including identifying the influential spreaders. There is further complication given that the influential spreaders interests will also change during event evolution. The influential spreaders play a key role in event evolution and this has been largely ignored in traditional event detection methods. To this end, we propose a user-interest model-based event evolution model, named the hot event evolution model. This model not only considers the user interest distribution but also uses the short text data in the social network to model the posts and the recommend methods to discover the user interests. This can resolve the problem of data sparsity, as exemplified by many existing event detection methods, and improve the accuracy of event detection. A hot event automatic filtering algorithm is initially applied to remove the influence of general events, improving the quality and efficiency of mining the event. Then, an automatic topic clustering algorithm is applied to arrange the short texts into clusters with similar topics. An improved user-interest model is proposed to combine the short texts of each cluster into a long text document simplifying the determination of the overall topic in relation to the interest distribution of each user during the evolution of important events. Finally, a novel cosine measurebased event similarity detection method is used to assess correlation between events, thereby detecting the process of event evolution. The experimental results on a real Twitter data set demonstrate the efficiency and accuracy of our proposed model for both event detection and user interest discovery during the evolution of hot events. INDEX TERMS Microblogging, event evolution, user topic.

Se plantea una solución al problema de reconocer las vocales A-I-U usando un clasificador bayesiano. Este es un problema interesante de abordar debido a que constituye la base para implementar sistemas de transcripción automática de texto. El presente documento se centra en encontrar el subconjunto mínimo de coeficientes MFCC para clasificar las vocales planteadas. Se determinó que sólo tres de los trece coeficientes son necesarios para que un clasificador bayesiano alcance una precisión del 99.2% en las grabaciones empleadas.

La valoración de la calidad vocal mediante el análisis audio-perceptual es parte de la rutina clínica de evaluación de pacientes con trastornos de la voz. La debilidad de este método reside en la subjetividad y en la necesidad de que sea realizada por oyentes experimentados. Este proyecto tiene como objetivo la realización de una clasificación automática de la calidad vocal, valuada en la escala GRBAS, a través de características extraídas del análisis acústico de la señal y técnicas de aprendizaje automático. Particularmente, en este trabajo se muestran los resultados del diseño de las capas de extracción de características de una red neuronal profunda orientada a la clasificación de la calidad vocal.

Corona Virus is a pandemic, and the whole world is affected due to it. Apart from the vaccine, the only cure for this drastic disease is to follow the rules and regulations that avoid further spread. There are different mechanisms like (Social Distancing, Mask Detection, Human occupancy etc.) through which we can able to stop the spread of the coronavirus. In this paper, we proposed hotspot zone detection using the computer vision techniques of deep learning. We have defined the hotspot area as the particular region on which the person touches more than some specified threshold. We further mark that area to some specific color to help the authority take necessary action and disinfect that particular place. To implement this algorithm, we have utilized the human-object interaction concept. We have extracted the dataset of person classes from the publicly available dataset for the person detection and the self-generated dataset to train the algorithm. Different experiments on object detection algorithms (YOLO-v3, Faster RCNN, SSD) for person detection have been performed in this work. We achieved the maximum accuracy in real-time on the YOLO-v3 for person detection. Whereas we have marked the specific area using the template matching algorithm of computer vision techniques. Our proposed algorithm detects the persons and extracts the region of interest points on which the user draws the rectangle. Then we find the intersection over union ratio between the detected person and the region of interest of the marked area to make the decision. We have achieved 88.72% accuracy on person detection in the local environment. Whereas, for the whole system of human-object interaction for detecting the hotspot area zone, we have achieved 86.7% accuracy using the confusion matrix. INDEX TERMS Convolution neural network, object detection, person detection, hotspot zone, fine-tuning.

Data fusion procedure is presented to enhance classical Advanced Driver Assistance Systems (ADAS). The novel vehicle safety approach, combines two classical sensors: computer vision and laser scanner. Laser scanner algorithm performs detection of vehicles and pedestrians based on pattern matching algorithms. Computer vision approach is based on Haar-Like features for vehicles and Histogram of Oriented Gradients (HOG) features for pedestrians. The high level fusion procedure uses Kalman Filter and Joint Probabilistic Data Association (JPDA) algorithm to provide high level detection. Results proved that by means of data fusion, the performance of the system is enhanced.

A time-domain solution of electromagnetic wave propagation in Tellegen materials is presented. The angle tilt between electric and magnetic fields, the phase speed of the wave, and the intrinsic impedance are computed when the medium is excited with a monochromatic source. The results are in good agreement with theoretical predictions.

-Nous proposons de formaliser le problème d'authentification par codes graphiques comme un jeu entre la source légitime et l'adversaire, chaque joueur essayant de sélectionner le meilleur canal d'impression/acquisition pour maximiser/minimiser les performances d'authentification. Il est possible de résoudre ce jeu en utilisant des estimations précises des probabilités de fausse alarme et non détection et en modélisant le canal d'impression-acquisition comme un canal additif Gaussien Généralisé ou Lognomal. L'optimisation s'effectue en considérant deux types de scénarios: la présence d'un adversaire passif (qui possède un canal identique à la source légitime), puis la présence d'un adversaire actif (possédant un canal différent). Elle conduit à une formulation min max. Les résultats de ce cheminement soulignent plusieurs points: (i) les performances d'authentification sont meilleures pour des distributions denses, (ii) les paramètres optimaux de l'adversaire sont proches de ceux de la source légitime, (iii) la source légitime peut trouver une configuration qui maximise les performances d'authentification.

Corona Virus is a pandemic, and the whole world is affected due to it. Apart from the vaccine, the only cure for this drastic disease is to follow the rules and regulations that avoid further spread. There are different mechanisms like (Social Distancing, Mask Detection, Human occupancy etc.) through which we can able to stop the spread of the coronavirus. In this paper, we proposed hotspot zone detection using the computer vision techniques of deep learning. We have defined the hotspot area as the particular region on which the person touches more than some specified threshold. We further mark that area to some specific color to help the authority take necessary action and disinfect that particular place. To implement this algorithm, we have utilized the human-object interaction concept. We have extracted the dataset of person classes from the publicly available dataset for the person detection and the self-generated dataset to train the algorithm. Different experiments on object detection algorithms (YOLO-v3, Faster RCNN, SSD) for person detection have been performed in this work. We achieved the maximum accuracy in real-time on the YOLO-v3 for person detection. Whereas we have marked the specific area using the template matching algorithm of computer vision techniques. Our proposed algorithm detects the persons and extracts the region of interest points on which the user draws the rectangle. Then we find the intersection over union ratio between the detected person and the region of interest of the marked area to make the decision. We have achieved 88.72% accuracy on person detection in the local environment. Whereas, for the whole system of human-object interaction for detecting the hotspot area zone, we have achieved 86.7% accuracy using the confusion matrix. INDEX TERMS Convolution neural network, object detection, person detection, hotspot zone, fine-tuning.

Round-off errors occur each time a program makes use of floating-point computations. They denote the existence of a distance between the actual floating-point computations and the intended computations over the reals. Therefore, analyzing round-off errors is a key issue in the verification of programs with floating-point computations. Most existing tools for round-off error analysis provide an over-approximation of the error. The point is that these approximations are often too coarse to evaluate the effective consequences of the error on the behaviour of a program. Some other tools compute an under-approximation of the maximal error. But these under-approximations are either not rigorous or not reachable. In this paper, we introduce a branch-and-bound algorithm to rigorously enclose the maximal error. Thanks to the use of rational arithmetic, our branch-and-bound algorithm provides a tight upper bound of the maximal error and a lower bound that can be exercised by input values. We outline the advantages and limits of our framework and compare it with state-of-the-art methods. Preliminary experiments on standard benchmarks show promising results.

Le présent travail porte sur l'optimisation du simulateur d'évanouissement de Suzuki basé sur le filtrage du bruit blanc gaussien (FWGN), qui est un modèle stochastique plus approprié et plus adéquat pour le canal radio mobile terrestre non sélectif en fréquence, car cette distribution composite de type Rayleigh-Lognormal représente le pire des cas d'évanouissement. Dans un travail précédent, le simulateur de Young et Beaulieu basé sur le modèle Clarke & Gans a été identifié comme étant un meilleur compromis de modélisation et de simulation du canal de Rayleigh. Le générateur d'évanouissements log normaux est optimisé grâce à l'étude de différents filtres passe-bas numériques permettant le choix du meilleur compromis en fonction de l'environnement, des statistiques d'ordre supérieur d'évanouissement requis et de la sévérité d'évanouissement ou du niveau de masque souhaité. Les filtres à réponse impulsionnelle finie (FIR) et à réponse impulsionnelle infinie (IIR) sont évalués. Les critères de discrimination des filtres sont la réponse fréquentielle en amplitude et de phase, l'ordre de filtre minimum requis et donc le coût de mise en oeuvre du matériel de filtrage, la probabilité de coupure et l'autocorrélation, ainsi que la divergence statistique entre les distributions des évanouissements lents simulé et théorique dans un environnement LTE typique. En tant que métrique de divergence, la distance de Bhattacharyya est calculée à l'aide d'une méthode de Monte Carlo. Le simulateur d'évanouissement Suzuki proposé, son signal de sortie et ses paramètres statistiques d'ordre divers sont enfin présentés.

Abstract: Despite successful application of constraint programming (CP) to solving many real-life problems there is still an indispensable group or researchers considering (wrongly) CP as a simple evaluation technique only. Even if sophisticated search algorithms play an ...

Solving NP-complete problems can be tough because of the combinatorics. Constraint Programming and Approximation algorithms can be used to solve these problems. In this paper, we explore how to automatically derive filtering algorithms from a dedicated algorithm solving the Bin Packing problem. To this end, we automatically derive a filtering algorithm from the Best-Fit algorithm. We empirically show that our filtering algorithm BF-Prop is experimentally strictly more efficient in terms of filtering than Shaw’s state-of-the-art global constraint.

En este documento se aplica la DFT para obtener las frecuencias que componen el sonido fonético de la letra "A", se obtienen sus frecuencias y sus amplitudes, posteriormente se reconstruye el sonido fonético de la letra "A" con las 11 frecuencias de mayor magnitud y se convierte a archivo de audio para poder comparar con el audio original y el audio generado por síntesis aditiva. Con el fin de que el alumno comprenda mejor los usos que le puede dar al espectro de Fourier.

En este trabajo se presentan los resultados del diseño y desarrollo de una red neuronal de tipo feed-forward en un sistema embebido, para identificar patrones asociados con la pronunciación de fonemas vocálicos del idioma español. Para el entrenamiento de la red fueron utilizados los coeficientes cepstrales de las frecuencias de Mel (MFCC), extraídos a partir de señales de audio provenientes de la pronunciación de las vocales abiertas (/a/, /e/ y /o/). La captura de nuevas muestras se realizó a través de un computador y un sistema embebido para la evaluación, comprobación y comparación del desempeño de la red neuronal. Se obtuvo un porcentaje de identificación correcta por encima del 98%. Esto indica que el error en la separación de clases fue inferior al 2% en la red neuronal al momento de evaluar patrones asociados a alguna de las tres vocales. Basado en los resultados obtenidos se concluye que la implementación de algoritmos de inteligencia artificial para tareas de clasificación en sistemas embebidos es factible, y presenta resultados similares a los que tendría el mismo sistema operando con los recursos de un computador.

In this work, a new analytical matrix formulation approach for the characterization of a microwave planar structure printed on a complex medium is detailed. The approach is based on the Generalized Exponential Matrix Technique (GEMT) combined with the Method of Moments (MoM)and Galerkin's procedure. The mathematical calculation development is a robust approach that exclusively uses matrix formulations starting from Maxwell's equations until the derivation of a compact form of the Green's tensor of the studied structure. Reduced complexity and calculation simplicity foundation of the applied approach have actually incited the authors to consider the case study of a complex bianisotropic lossy chiral substrate medium. The complexity of the medium is expressed by full tensors form of all four constitutive parameters: permittivity, permeability and magnetoelectric parameters, each is represented by a nine-element tensor. To investigate the electromagnetic behavior of complex media, results of particular bianisotropy cases are presented and discussed. Original results of the biaxial chiral anisotropy case are carried out, discussed and compared with data available in literature.

Data fusion procedure is presented to enhance classical Advanced Driver Assistance Systems (ADAS). The novel vehicle safety approach, combines two classical sensors: computer vision and laser scanner. Laser scanner algorithm performs detection of vehicles and pedestrians based on pattern matching algorithms. Computer vision approach is based on Haar-Like features for vehicles and Histogram of Oriented Gradients (HOG) features for pedestrians. The high level fusion procedure uses Kalman Filter and Joint Probabilistic Data Association (JPDA) algorithm to provide high level detection. Results proved that by means of data fusion, the performance of the system is enhanced.

Data fusion procedure is presented to enhance classical Advanced Driver Assistance Systems (ADAS). The novel vehicle safety approach, combines two classical sensors: computer vision and laser scanner. Laser scanner algorithm performs detection of vehicles and pedestrians based on pattern matching algorithms. Computer vision approach is based on Haar-Like features for vehicles and Histogram of Oriented Gradients (HOG) features for pedestrians. The high level fusion procedure uses Kalman Filter and Joint Probabilistic Data Association (JPDA) algorithm to provide high level detection. Results proved that by means of data fusion, the performance of the system is enhanced.

With the prevalence of location-based services and geo-functioned devices, the trend of spatial data outsourcing is rising. In the data outsourcing scenario, result integrity must be ensured by means of a query authentication scheme. However, most of the existing studies are confined to a centralized environment. In this paper, we investigate the query authentication problem in distributed environments and focus on the k nearest neighbor (kNN) query, which is widely used in spatial data analytics. We design a new distributed spatial authenticated data structure (ADS), distributed MR-tree, to facilitate efficient kNN processing. Furthermore, we propose a basic algorithm to process authenticated kNN queries based on the new ADS. Apart from the results, some verification objects are generated to guarantee the results' integrity. We also design two optimized algorithms to reduce the size of verification objects as well as the verification cost. Our experiments validate the good performance of the proposed techniques in terms of query cost, communication overhead, and verification time.

In this work, a new analytical matrix formulation approach for the characterization of a microwave planar structure printed on a complex medium is detailed. The approach is based on the Generalized Exponential Matrix Technique (GEMT) combined with the Method of Moments (MoM)and Galerkin's procedure. The mathematical calculation development is a robust approach that exclusively uses matrix formulations starting from Maxwell's equations until the derivation of a compact form of the Green's tensor of the studied structure. Reduced complexity and calculation simplicity foundation of the applied approach have actually incited the authors to consider the case study of a complex bianisotropic lossy chiral substrate medium. The complexity of the medium is expressed by full tensors form of all four constitutive parameters: permittivity, permeability and magnetoelectric parameters, each is represented by a nine-element tensor. To investigate the electromagnetic behavior of complex media, results of particular bianisotropy cases are presented and discussed. Original results of the biaxial chiral anisotropy case are carried out, discussed and compared with data available in literature.

In these modern times there are several methods of communication between ourselves and even our machines, these allow us to create ties between people contact or via an interface for human-machine interaction. These techniques have been developed over time by the constant evolution of technology, triggered by a futuristic world and wants to be globalized. One of these techniques has been developed, is the recognition of Subvocal also known speech or silent speech, which allows us to analyze the signals from the vocal apparatus without the need for sound waves or pronounce words.

SUMMARY Our aim was determinate the ef- fect of noise presence at time to eva- luate the pitch, and the study of possi- ble improvements. Several algorithms (Terhard, Duifhuis, Cepstrum, simple FFT and visual determination), were studied and implementated. These al- gorithms were applicated to different vowels with a progresive augment of noise level; conclusions were that Ter- hardt method is very similar to the ear, Duifhuis implementation of Godsteins model is too much sensible to the pre- sence of noise and cepstrum and visual detection are very insensible to the presence of noise. In general, the noise presence involve a loss of accurancy because spurious components appear in the spectrum. At this point the multi- resolution analysis (MRA) become a useful tool to eliminate the effect of elevate noise level. MRA were used to smooth the vowels analyzed. Then the algorithms were applicated to the news files obtained with the 10-Daudechies coefficients at differents levels of con- ...

El desarrollo de tecnología de asistencia para personas en condición de discapacidad permite dar solución a necesidades que, aunque no son consideradas prioridad en las entidades de salud, tienen una gran influencia en la calidad de vida de los afectados. En este caso de estudio se consideran dos personas de 17 y 20 años con trauma raquimedular a nivel de C3 y C4 con clasificación ASIA A, quienes expresaron la necesidad de recuperar la independencia en actividades de entretenimiento, tales como el manejo del celular y el control del televisor. Por consiguiente, se decidió desarrollar dos dispositivos que funcionen como control remoto para el último. Para el diseño y desarrollo de la tecnología se implementó la metodología de diseño de Hans Gugelot, obteniendo como resultado dos dispositivos electrónicos que funcionan mediante pulsadores y comandos de voz que cumplieron satisfactoriamente con su objetivo y que se consideran de bajo costo debido a que no superan los 75 USD.

Decomposition of sounds into their sinusoidal, transient, and noise components is an active research topic and a widely-used tool in audio processing. Multiple solutions have been proposed in recent years, using time-frequency representations to identify either horizontal and vertical structures or orientations and anisotropy in the spectrogram of the sound. In this paper, we present SiTraNo: an easy-to-use MATLAB application with a graphic user interface for audio decomposition that enables visualization and access to the sinusoidal, transient, and noise classes, individually. This application allows the user to choose between different well-known separation methods to analyze an input sound file, to instantaneously control and remix its spectral components, and to visually check the quality of the separation, before producing the desired output file. The visualization of common artifacts, such as birdies and dropouts, is demonstrated. This application promotes experimenting with the sound decomposition process by observing the effect of variations for each spectral component on the original sound and by comparing different methods against each other, evaluating the separation quality both audibly and visually. SiTraNo and its source code are available on a companion website and repository.

In these modern times there are several methods of communication between ourselves and even our machines, these allow us to create ties between people contact or via an interface for human-machine interaction. These techniques have been developed over time by the constant evolution of technology, triggered by a futuristic world and wants to be globalized. One of these techniques has been developed, is the recognition of Subvocal also known speech or silent speech, which allows us to analyze the signals from the vocal apparatus without the need for sound waves or pronounce words.

Location-based services have been widely adopted in many systems. Existing works employ a pull model or user-initiated model, where a user issues a query to a server which replies with location-aware answers. To provide users with instant replies, a push model or server-initiated model is becoming an inevitable computing model in the next-generation location-based services. In the push model, subscribers register spatio-textual subscriptions to capture their interests, and publishers post spatio-textual messages. This calls for a high-performance location-aware publish/subscribe system to deliver publishers' messages to relevant subscribers. In this paper, we address the research challenges that arise in designing a location-aware publish/subscribe system. We propose an R-tree based index by integrating textual descriptions into R-tree nodes. We devise efficient filtering algorithms and effective pruning techniques to achieve high performance. Our method can support both conjunctive queries and ranking queries. We discuss how to support dynamic updates efficiently. Experimental results show our method achieves high performance which can filter 500 messages in a second for 10 million subscriptions on a commodity computer Ç

In this paper, an auxiliary differential equation (ADE) transmission line method (TLM) is proposed for broadband modeling of electromagnetic (EM) wave propagation in biological tissues with the Cole-Cole dispersion Model. The fractional derivative problem is surmounted by assuming a linear behavior of the polarization current when the time discretization is short enough. The polarization current density is approached using Lagrange extrapolation polynomial, and the fractional derivation is obtained according to Riemann definition of a fractional α-order derivative. Reflection coefficients at an air/muscle and air/fat tissues interfaces simulated in a 1-D domain are found in good agreement with those obtained from the analytic model over a broad frequency range, demonstrating the validity of the proposed approach.

A new 2D convolution-based filter is presented specifically designed to improve Visual Search applications. It exploits a new radix-3 partitioning method of integer numbers, derived from the weight partition theory, which allows substituting multipliers with simplified floating-point adders, working on 32 bits floating point filter coefficients. The memory organization allows elaborating the incoming data in raster scan order, as those directly provided by an acquisition source, without frame buffers and additional aligning circuitry. Compared to the existent literature, build around conventional arithmetic circuitry, the proposed design achieves state-of-the-art performances in the reduction of the mapped physical resources and elaboration velocity, achieving a critical path delay of about 4.5 ns both with a Xilinx Virtex 7 FPGA and CMOS 90nm std_cells.

Artificial neural networks (ANNs) were used to classify EMG signals from an arm. Using an amplifier card from the Smart Hand project or prosthetic hand, 16-channel EMG signals were collected from the patients arm and Filtered. After time-domain feature extraction, simple back-propagation training was used to train the networks. During the training, the patient moved his Fingers according to a predefined pattern. After the training, the patient could move an artificial hand by duplicating the movements made during training. Artificial hands are nothing new. One of the earliest mentions is of a Roman general that fought with an iron arm back around the year 50 AD and many of researchers have done on this project. Hopefully, this work will show that this approach to the problem of controlling hand prosthesis is viable and that it has benefits over other methods previously used.

In this paper, an auxiliary differential equation (ADE) transmission line method (TLM) is proposed for broadband modeling of electromagnetic (EM) wave propagation in biological tissues with the Cole-Cole dispersion Model. The fractional derivative problem is surmounted by assuming a linear behavior of the polarization current when the time discretization is short enough. The polarization current density is approached using Lagrange extrapolation polynomial, and the fractional derivation is obtained according to Riemann definition of a fractional α-order derivative. Reflection coefficients at an air/muscle and air/fat tissues interfaces simulated in a 1-D domain are found in good agreement with those obtained from the analytic model over a broad frequency range, demonstrating the validity of the proposed approach.

In this paper, an auxiliary differential equation (ADE) transmission line method (TLM) is proposed for broadband modeling of electromagnetic (EM) wave propagation in biological tissues with the Cole-Cole dispersion Model. The fractional derivative problem is surmounted by assuming a linear behavior of the polarization current when the time discretization is short enough. The polarization current density is approached using Lagrange extrapolation polynomial, and the fractional derivation is obtained according to Riemann definition of a fractional α-order derivative. Reflection coefficients at an air/muscle and air/fat tissues interfaces simulated in a 1-D domain are found in good agreement with those obtained from the analytic model over a broad frequency range, demonstrating the validity of the proposed approach.

Los algoritmos de reconocimiento de voz son utilizados en aplicaciones de control inteligente especialmente en el área de la medicina. Una de las aplicaciones es el control de equipos de asistencia motora como las sillas de ruedas para pacientes con discapacidad motora total de sus extremidades inferiores y superiores. Las personas en esta condición tienen dificultad para trasladarse de un lugar a otro, dependiendo siempre de ayuda externa. El presente artículo describe el desarrollo de un algoritmo de reconocimiento de comandos de voz aplicando técnicas no lineales para la identificación de instrucciones de control en el desplazamiento de equipos de asistencia motora, con el fin de proporcionar un desplazamiento autónomo a personas con discapacidad motora total que pueden oír, ver y hablar. Las muestras de voz fueron recolectadas en un ambiente sin ruido y con ruido, aplicando un filtro digital para la eliminación del mismo. El procesamiento de la información filtrada se realizó me...

Resumen.-El presente documento propone realizar la evaluación de sistemas de reconocimiento de locutor basados en los algoritmos LPC (Coeficientes de Predicción Lineal), CC (Coeficientes Cepstrales) y MFCC (Coeficientes Cepstrales en Frecuencias Mel), empleados en la extracción de parámetros de voz. La evaluación, siguiendo una metodología cuantitativa experimental, consiste en determinar el cambio de desempeño cuando la señal de entrada es expuesta a diferentes condiciones de ruido (bullicio y gaussiano), es decir, a distintos niveles de SNR, comparando los resultados de verificación para 2 locutores. Aunque todos los sistemas disminuyen su desempeño en ambientes ruidosos, cada uno posee de forma intrínseca cierto nivel de robustez. Esta evaluación servirá de referencia en la construcción de sistemas de reconocimiento de locutor, los cuales incluyan sistemas de mejora de voz para disminución del ruido. Palabras clave: Reconocimiento de locutor, ruido de bullicio, algoritmo MFCC, algoritmo CC, algoritmo LPC. Summary.-This document proposes the evaluation of speaker recognition systems based on the LPC (Linear Predicting Coding), CC (Cepstral Coefficients) and MFCC (Mel Frequency Cepstral Coefficients) algorithms, used in the extraction of voice parameters. The evaluation, following an experimental quantitative methodology, consists of determining the change in performance when the input signal is exposed to different noise conditions (crowd and Gaussian noise), namely, at different levels of SNR, comparing the verification results for 2 speakers. Although all the systems decrease their performance in noisy environments, each one possesses intrinsically a certain level of robustness. This evaluation will serve as a reference in the construction of speaker recognition systems, which include voice enhancement systems to reduce noise.

Preprocessing text data sets for use in Natural Language Processing tasks is usually a time-consuming and expensive effort. Text data, normally obtained from sources such as, but not limited to, web scraping, scanned documents or PDF files, is typically unstructured and prone to artifacts and other types of noise. The goal of the TextCL package is to simplify this process by providing multiple methods suited for text data preprocessing. It includes functionality for splitting texts into sentences, filtering sentences by language, perplexity filtering, and removing duplicate sentences. Another functionality offered by the TextCL package is the outlier detection module, which allows to identify and filter out texts that are different from the main topic distribution of the data set. This method allows selecting one of several unsupervised outlier detection algorithms, such as TONMF (block coordinate descent framework), RPCA (robust principal component analysis), or SVD (singular value decomposition) and apply it to the text data.

Structural health monitoring (SHM), an emerging technique developed from Non Destructive Testing(NDT), combines advanced sensor technology with intelligent algorithms to interrogate the structural ‘health’ conditions. SHM performs the real-time and on-line damage detection with the help of in-situ sensors. The potential benefits of implementing SHM in automotive sector includes improving reliability, reducing life-cycle costs and high safety factor to improve the design of automotive components. For these purposes, a car has been fitted with measuring equipment’s: strain gauge and
accelerometer to record the measuring drives in the present work.

The aim of the work is to investigate the measured strain signals, suggestions for improvement and optimization identified based on the theories of signal conditioning and signal analysis and computationally implemented for a SHM system. The thesis work majorly deals with signal monitoring, damage monitoring and fatigue life monitoring in a SHM system. The measured strain signal is generated from hardware embedded platform and it deals with several practical issues. The measured signal has a disturbance superimposed on the good data. This disturbance can mask some important fatigue features of the stress or strain signals. One of the goal in this study includes an implementation and evaluation methods for noise suppression and drift removal of the signal. Hence several digital filters are designed and applied for the signals. Filter efficiency was checked, compared and recommended with a focus on setting-up a processed signal for next signal analysis step with amplitude based methods.

A car is subjected to a large number of highly variable loads, but fatigue life prediction is typically based on constant amplitude fatigue behaviour. Therefore counting method was used for describing variable amplitude signals as a collection of constant amplitude cycles with predominantly using Rainflow analysis. The rainflow matrix and load spectrum are obtained for vehicle structure signals. An assessment of the remaining service life of a car structure is carried out by a simplified version of the linear damage accumulation hypothesis according to Palmgren-Miner rules and derivation of S-N curve which relates the stresses to the number of cycles to failure.

Z-TLM based compact modeling approach for dispersive media exhibiting magnetoelectric coupling is presented in this paper. Scattering parameters based representation of considered medium is created in a form of compact model by extracting effective electromagnetic parameters using a retrieval method, and implementing them into a non-uniform TLM grid. Proposed approach is illustrated here on the example of dispersive isotropic chiral medium modeling.

El labio y/o paladar hendido (LPH) es una malformación, que tiene orígenes de tipo genético y ambiental. En Colombia, 6 de ca-da 10000 niños nacen con esta malformación, mientras en el resto del mundo la proporción se encuentra en 1 de cada 10000. El LPH trae consigo patologías en el habla tales como: hipernasalidad, hi-ponasalidad, golpe glótico, entre otras. De todas estas patologías, la hipernasalidad es la más recurrente en pacientes con LPH, apa-reciendo aproximadamente en el 90% de los casos. En este trabajo se hace un análisis, basado en resultados experimentales, del desempeño del Operador de Energía de Teager (TEO, por las siglas en inglés de Teager Energy Operator), para la detección de hiper-nasalidad en pacientes con LPH. Se analiza una versión generali-zada del TEO con el fin de validar su capacidad discriminante en la detección de hipernasalidad, aplicándolo sobre una base de da-tos con registros de voz reales, de niños con LPH y niños control. Los resultados obtenidos...

Los algoritmos de reconocimiento de voz son utilizados en aplicaciones de control inteligente especialmente en el área de la medicina. Una de las aplicaciones es el control de equipos de asistencia motora como las sillas de ruedas para pacientes con discapacidad motora total de sus extremidades inferiores y superiores. Las personas en esta condición tienen dificultad para trasladarse de un lugar a otro, dependiendo siempre de ayuda externa. El presente artículo describe el desarrollo de un algoritmo de reconocimiento de comandos de voz aplicando técnicas no lineales para la identificación de instrucciones de control en el desplazamiento de equipos de asistencia motora, con el fin de proporcionar un desplazamiento autónomo a personas con discapacidad motora total que pueden oír, ver y hablar. Las muestras de voz fueron recolectadas en un ambiente sin ruido y con ruido, aplicando un filtro digital para la eliminación del mismo. El procesamiento de la información filtrada se realizó me...

One-dimensional (1D) Transmission Line Matrix (TLM) method with Z-transforms, is applied in the paper to allow for an efficient time-domain simulation of thin anisotropic conductive panel of dispersive behavior. It uses a digital filter model to incorporate the scattering coefficients of the panel at two TLM cells interface in order to avoid a fine meshing of panel thickness. Model validation is done for a panel made of carbon-fibre material whose electric conductivity is anisotropic and assumed to be frequency dependent according to the Drude model. Fine TLM mesh results are used to verify the model accuracy.

La idea basica de la cancelacion de ecos es bloquear la senal desde la sala remota para que no se realimente. Para ello se coloca un sistema adaptativo en medio que genere “idealmente” la misma senal que proviene de la sala local y se envia de vuelta a la sala remota la diferencia entre la senal estimada y la que retorna de la sala local, en lugar de esta ultima. La introduccion de multiples canales permite capturar la espacialidad de los locutores pero introduce una alta correlacion entre las senales que afecta el comportamiento del cancelador adaptativo. Este inconveniente de mal condicionamiento del sistema, conocido como problema de la no?unicidad, puede hacer incluso que el sistema adaptativo converja a una solucion no unica. En la cancelacion de ecos multicanal estas soluciones no solo dependen de las respuestas al impulso de la sala local, sino tambien de las respuestas al impulso de la sala remota. Las respuestas al impulso de las salas tipicas en aplicaciones manos libres, ...

Location-based services have been widely adopted in many systems. Existing works employ a pull model or user-initiated model, where a user issues a query to a server which replies with location-aware answers. To provide users with instant replies, a push model or server-initiated model is becoming an inevitable computing model in the next-generation location-based services. In the push model, subscribers register spatio-textual subscriptions to capture their interests, and publishers post spatio-textual messages. This calls for a high-performance location-aware publish/subscribe system to deliver publishers' messages to relevant subscribers. In this paper, we address the research challenges that arise in designing a location-aware publish/subscribe system. We propose an R-tree based index by integrating textual descriptions into R-tree nodes. We devise efficient filtering algorithms and effective pruning techniques to achieve high performance. Our method can support both conjunctive queries and ranking queries. We discuss how to support dynamic updates efficiently. Experimental results show our method achieves high performance which can filter 500 messages in a second for 10 million subscriptions on a commodity computer Ç

In this paper, an auxiliary differential equation (ADE) transmission line method (TLM) is proposed for broadband modeling of electromagnetic (EM) wave propagation in biological tissues with the Cole-Cole dispersion Model. The fractional derivative problem is surmounted by assuming a linear behavior of the polarization current when the time discretization is short enough. The polarization current density is approached using Lagrange extrapolation polynomial, and the fractional derivation is obtained according to Riemann definition of a fractional α-order derivative. Reflection coefficients at an air/muscle and air/fat tissues interfaces simulated in a 1-D domain are found in good agreement with those obtained from the analytic model over a broad frequency range, demonstrating the validity of the proposed approach.

Se presenta una revisión conceptual generalizada de los conformadores de entrada de sistemas de control como herramientas para eliminar vibraciones en la salida de los sistemas. Se desarrollan los diferentes tipos de conformadores como versiones mejoradas de Posicast, el conformador original. Luego se presentan las aplicaciones de Posicast en el desarrollo de sistemas electrónicos, específicamente, en circuitos de potencia y en circuitos microelectrónicos.

The computerized world we are living in has a ton of information and data that is utilized by an assortment of clients, for example, videos, books and articles. Different users like different content. Getting what each user likes can be irritating. Each online services provider always aims in having many clients. Recommender systems importance’s arises in such situations. The recommender framework proposes to a client some substance for example e.g. movies and books depending on what the user likes. In this research, a new movie recommender system is proposed, that will be able to improve the existing recommender systems. With this new recommender framework, the client will receive an improved forecast contrasted with different frameworks that as of now exist for example content-based filtering and collaborative-filtering. In order to overcome the disadvantages of the both methods (collaborative filtering algorithm (unsupervised learning) and content-based filtering algorithm (supervised learning)), the new system combines both methods. This will bring up a more stable system compared to the existing ones.

Currently, Field Programmable Gate Array (FPGA) goes beyond the low-level line-by-line hardware description language programming in implementing parallel multidimensional image filtering algorithms. High-level abstract hardware-oriented parallel programming method can structurally bridge this gap. This paper proposes a first step toward such a method to efficiently implement Parallel 2-D MRI image filtering algorithms using the Xilinx system generator. The implementation method consists of five simple steps that provide fast FPGA prototyping for high performance computation to obtain excellent quality of results. The results are obtained for nine 2-D image filtering algorithms. Behaviourally, two Virtex-6 FPGA boards, namely, xc6vlX240Tl-1lff1759 and xc6vlX130Tl-1lff1156 are targeted to achieve; lower power consumption of (1.57 W) and down to (0.97 W) respectively at maximum sampling frequency of up to (230 MHZ). Then, one of the nine MRI image filtering algorithms, has empirically improved to generate an enhanced MRI image filtering with moderate lower power consumption at higher maximum frequency. I. INTRODUCTION FPGAs are increasingly used in modern parallel algorithm applications such as medical imaging [1], DSP [2], image filtering [3], power consumption in portable image processing [4], MPEG-4 motion estimation in mobile applications [5], satellite data processing [6], new Mersenne Number Transform [7][8], high speed wavelet-based image compress [9] and even the global communication link [10]. However, most of the above FPGA-based solutions are typically programmed with low-level hardware description languages (HDL) inherited from ASIC design methodologies [11]. On the other hand, parallel multidimensional image filtering algorithms[12], for aerospace, defence, digital communications, multimedia, video and imaging industries, demand insatiable computationally complex operations [13] [14] at maximum sampling frequency. Traditional DSP processor arrays, with fixed architectures and relatively short life, can be costly programmed line-by-line with thousands of code's lines [15] [16]. Alternatively, this paper presents a high-level abstract implementation method to fill the present programming gap between parallel algorithms coding and final FPGA implementation. The proposed FPGA implementation method is architecturally based on the Xilinx system generator development tool [17] within the ISE 11.3 development