Neuromorphic Detection of Vowel Representation Spaces

In this paper a layered architecture to spot and characterize vowel segments in running speech is presented. The detection process is based on neuromorphic principles, as is the use of Hebbian units in layers to implement lateral inhibition, band probability estimation and mutual exclusion. Results are presented showing how the association between the acoustic set of patterns and the phonologic set of symbols may be created. Possible applications of this methodology are to be found in speech event spotting, in the study of pathological voice and in speaker biometric characterization, among others.

Transient acoustic response in car cabins with localization of reflections

Due to its small size and the restrictions on source and listener positions, the design of sound reproduction systems for car cabins is particularly cumbersome. In the present project the measurement of the impulse response between a single loudspeaker and a listener position, with special emphasis on the directional characteristics, will be examined. The propagation paths inside a car are very short, meaning that it is very difficult for the existing commercial measurement systems to resolve the different reflections arriving to the listener. This paper propose a first approach of an algorithm based on time difference of arrival along a measurement technique aiming at finding the reflections and their direction of arrival to the listener. To this end a circular microphone array at a known position is employed, along with Maximum-Length Sequences (MLS) measurement technique. The results are processed so as to extract the directional properties, demonstrate the physical limitations that can influence or prevent this detection in practice. Measurements were carried out in a free-field environment (anechoic chamber) making use of different panels closer around the microphone array. RESUMEN. El diseño de sistemas de reproducción de audio para cabinas de coche es especialmente complicado debido al reducido tamaño del espacio y las restricciones de los altavoces y posiciones de escucha de los ocupantes. En el presente proyecto, se examinan mediciones de la respuesta al impulso entre un altavoz y una posición de escucha con especial énfasis en las características direccionales. Los caminos de propagación de las ondas sonoras dentro de un coche son muy cortos, lo que hace difícil para los instrumentos de medida existentes en el mercado determinar las direcciones de llegada de las diferentes reflexiones que llegan a una posición de escucha. Este trabajo propone una primera aproximación de un algoritmo, basado en las diferencias temporales de llegada de una onda a diferentes puntos de medida, y una particular técnica de medida de la respuesta al impulso para obtener las direcciones de llegada de reflexiones a una posición de escucha. Para ello, se emplea una matriz circular de micrófonos en una posición conocida junto con la técnica de medida MLS (Maximum Length Sequence). Los resultados obtenidos son procesados para extraer la dirección de llegada de las reflexiones acústicas y encontrar las limitaciones que influyan en la detección de dichas reflexiones. Las mediciones se llevan a cabo en un entorno de campo libre y utilizando diferentes superficies reflectantes alrededor de la matriz de micrófonos.

Neuroanatomic-based detection algorithm for automatic labeling of brain structures in brain injury

The number and grade of injured neuroanatomic structures and the type of injury determine the degree of impairment after a brain injury event and the recovery options of the patient. However, the body of knowledge and clinical intervention guides are basically focused on functional disorder and they still do not take into account the location of injuries. The prognostic value of location information is not known in detail either. This paper proposes a feature-based detection algorithm, named Neuroanatomic-Based Detection Algorithm (NBDA), based on SURF (Speeded Up Robust Feature) to label anatomical brain structures on cortical and sub-cortical areas. Themain goal is to register injured neuroanatomic structures to generate a database containing patient?s structural impairment profile. This kind of information permits to establish a relation with functional disorders and the prognostic evolution during neurorehabilitation procedures.

A generalized method for flat plates impact detection and location

In the last years, many analyses from acoustic signal processing have been used for different applications. In most cases, these sensor systems are based on the determination of times of flight for signals from every transducer. This paper presents a flat plate generalization method for impact detection and location over linear links or bars-based structures. The use of three piezoelectric sensors allow to achieve the position and impact time while the use of additional sensors lets cover a larger area of detection and avoid wrong timing difference measurements. An experimental setup and some experimental results are briefly presented.

Sistema de adquisición de datos para una aplicación de detección del ruido de reversa en tiempo real

Entre todas las fuentes de ruido, la activación de la propulsión en reversa de un avión después de aterrizar es conocida por las autoridades del aeropuerto como una causa importante de impacto acústico, molestias y quejas en las proximidades vecinas de los aeropuertos. Por ello, muchos de los aeropuertos de todo el mundo han establecido restricciones en el uso de la reversa, especialmente en las horas de la noche. Una forma de reducir el impacto acústico en las actividades aeroportuarias es implementar herramientas eficaces para la detección de ruido en reversa en los aeropuertos. Para este proyecto de fin de carrera, aplicando la metodología TREND (Thrust Reverser Noise Detection), se pretende desarrollar un sistema software capaz de determinar que una aeronave que aterrice en la pista active el frenado en reversa en tiempo real. Para el diseño de la aplicación se plantea un modelo software, que se compone de dos módulos:  El módulo de adquisición de señales acústicas, simula un sistema de captación por señales de audio. Éste módulo obtiene muestra de señales estéreo de ficheros de audio de formato “.WAV” o del sistema de captación, para acondicionar las muestras de audio y enviarlas al siguiente módulo. El sistema de captación (array de micrófonos), se encuentra situado en una localización cercana a la pista de aterrizaje.  El módulo de procesado busca los eventos de detección aplicando la metodología TREND con las muestras acústicas que recibe del módulo de adquisición. La metodología TREND describe la búsqueda de dos eventos sonoros llamados evento 1 (EV1) y evento 2 (EV2); el primero de ellos, es el evento que se activa cuando una aeronave aterriza discriminando otros eventos sonoros como despegues de aviones y otros sonidos de fondo, mientras que el segundo, se producirá después del evento 1, sólo cuando la aeronave utilice la reversa para frenar. Para determinar la detección del evento 1, es necesario discriminar las señales ajenas al aterrizaje aplicando un filtrado en la señal capturada, después, se aplicará un detector de umbral del nivel de presión sonora y por último, se determina la procedencia de la fuente de sonido con respecto al sistema de captación. En el caso de la detección del evento 2, está basada en la implementación de umbrales en la evolución temporal del nivel de potencia acústica aplicando el modelo de propagación inversa, con ayuda del cálculo de la estimación de la distancia en cada instante de tiempo mientras el avión recorre la pista de aterrizaje. Con cada aterrizaje detectado se realiza una grabación que se archiva en una carpeta específica y todos los datos adquiridos, son registrados por la aplicación software en un fichero de texto. ABSTRACT. Among all noise sources, the activation of reverse thrust to slow the aircraft after landing is considered as an important cause of noise pollution by the airport authorities, as well as complaints and annoyance in the airport´s nearby locations. Therefore, many airports around the globe have restricted the use of reverse thrust, especially during the evening hours. One way to reduce noise impact on airport activities is the implementation of effective tools that deal with reverse noise detection. This Final Project aims to the development of a software system capable of detecting if an aircraft landing on the runway activates reverse thrust on real time, using the TREND (Thrust Reverser Noise Detection) methodology. To design this application, a two modules model is proposed: • The acoustic signals obtainment module, which simulates an audio waves based catchment system. This module obtains stereo signal samples from “.WAV” audio files or the catchment system in order to prepare these audio samples and send them to the next module. The catchment system (a microphone array) is located on a place near the landing runway. • The processing module, which looks for detection events among the acoustic samples received from the other module, using the TREND methodology. The TREND methodology describes the search of two sounds events named event 1 (EV1) and event 2 (EV2). The first is the event activated by a landing plane, discriminating other sound events such as background noises or taking off planes; the second one will occur after event one only when the aircraft uses reverse to slow down. To determine event 1 detection, signals outside the landing must be discriminated using a filter on the catched signal. A pressure level´s threshold detector will be used on the signal afterwards. Finally, the origin of the sound source is determined regarding the catchment system. The detection of event 2 is based on threshold implementations in the temporal evolution of the acoustic power´s level by using the inverse propagation model and calculating the distance estimation at each time step while the plane goes on the landing runway. A recording is made every time a landing is detected, which is stored in a folder. All acquired data are registered by the software application on a text file.

Islanding detection in Microgrids using Harmonic Signature

In recent years, there has been a growing interest in incorporating microgrids in electrical power networks. This is due to various advantages they present, particularly the possibility of working in either autonomous mode or grid connected, which makes them highly versatile structures for incorporating intermittent generation and energy storage. However, they pose safety issues in being able to support a local island in case of utility disconnection. Thus, in the event of an unintentional island situation, they should be able to detect the loss of mains and disconnect for self-protection and safety reasons. Most of the anti-islanding schemes are implemented within control of single generation devices, such as dc-ac inverters used with solar electric systems being incompatible with the concept of microgrids due to the variety and multiplicity of sources within the microgrid. In this paper, a passive islanding detection method based on the change of the 5th harmonic voltage magnitude at the point of common coupling between grid-connected and islanded modes of operation is presented. Hardware test results from the application of this approach to a laboratory scale microgrid are shown. The experimental results demonstrate the validity of the proposed method, in meeting the requirements of IEEE 1547 standards.

Tuning of modulation spectrum parameters for voice pathology detection

Acoustic parameters are frequently used to assess the presence of pathologies in human voice. Many of them have demonstrated to be useful but in some cases its results could be optimized by selecting appropriate working margins. In this study two indices, CIL and RALA, obtained from Modulation Spectra are described and tuned using different frame lengths and frequency ranges to maximize AUC in normal to pathological voice detection. After the tuning process, AUC reaches 0.96 and 0.95 values for CIL and RALA respectively representing an improvement of 16 % and 12 % at each case respect to the typical tuning based only on frame length selection.

A Survey on Underwater Acoustic Sensor Network Routing Protocols

Underwater acoustic sensor networks (UASNs) have become more and more important in ocean exploration applications, such as ocean monitoring, pollution detection, ocean resource management, underwater device maintenance, etc. In underwater acoustic sensor networks, since the routing protocol guarantees reliable and effective data transmission from the source node to the destination node, routing protocol design is an attractive topic for researchers. There are many routing algorithms have been proposed in recent years. To present the current state of development of UASN routing protocols, we review herein the UASN routing protocol designs reported in recent years. In this paper, all the routing protocols have been classified into different groups according to their characteristics and routing algorithms, such as the non-cross-layer design routing protocol, the traditional cross-layer design routing protocol, and the intelligent algorithm based routing protocol. This is also the first paper that introduces intelligent algorithm-based UASN routing protocols. In addition, in this paper, we investigate the development trends of UASN routing protocols, which can provide researchers with clear and direct insights for further research.