A real-time video quality estimator for emerging wireless multimedia systems

Wireless Mesh Networks (WMNs) are increasingly deployed to enable thousands of users to share, create, and access live video streaming with different characteristics and content, such as video surveillance and football matches. In this context, there is a need for new mechanisms for assessing the quality level of videos because operators are seeking to control their delivery process and optimize their network resources, while increasing the user’s satisfaction. However, the development of in-service and non-intrusive Quality of Experience assessment schemes for real-time Internet videos with different complexity and motion levels, Group of Picture lengths, and characteristics, remains a significant challenge. To address this issue, this article proposes a non-intrusive parametric real-time video quality estimator, called MultiQoE that correlates wireless networks’ impairments, videos’ characteristics, and users’ perception into a predicted Mean Opinion Score. An instance of MultiQoE was implemented in WMNs and performance evaluation results demonstrate the efficiency and accuracy of MultiQoE in predicting the user’s perception of live video streaming services when compared to subjective, objective, and well-known parametric solutions.

Quantitative 3D strain analysis in analogue experiments: Integration of X-ray computed tomography and digital volume correlation techniques

The combination of scaled analogue experiments, material mechanics, X-ray computed tomography (XRCT) and Digital Volume Correlation techniques (DVC) is a powerful new tool not only to examine the 3 dimensional structure and kinematic evolution of complex deformation structures in scaled analogue experiments, but also to fully quantify their spatial strain distribution and complete strain history. Digital image correlation (DIC) is an important advance in quantitative physical modelling and helps to understand non-linear deformation processes. Optical non-intrusive (DIC) techniques enable the quantification of localised and distributed deformation in analogue experiments based either on images taken through transparent sidewalls (2D DIC) or on surface views (3D DIC). X-ray computed tomography (XRCT) analysis permits the non-destructive visualisation of the internal structure and kinematic evolution of scaled analogue experiments simulating tectonic evolution of complex geological structures. The combination of XRCT sectional image data of analogue experiments with 2D DIC only allows quantification of 2D displacement and strain components in section direction. This completely omits the potential of CT experiments for full 3D strain analysis of complex, non-cylindrical deformation structures. In this study, we apply digital volume correlation (DVC) techniques on XRCT scan data of “solid” analogue experiments to fully quantify the internal displacement and strain in 3 dimensions over time. Our first results indicate that the application of DVC techniques on XRCT volume data can successfully be used to quantify the 3D spatial and temporal strain patterns inside analogue experiments. We demonstrate the potential of combining DVC techniques and XRCT volume imaging for 3D strain analysis of a contractional experiment simulating the development of a non-cylindrical pop-up structure. Furthermore, we discuss various options for optimisation of granular materials, pattern generation, and data acquisition for increased resolution and accuracy of the strain results. Three-dimensional strain analysis of analogue models is of particular interest for geological and seismic interpretations of complex, non-cylindrical geological structures. The volume strain data enable the analysis of the large-scale and small-scale strain history of geological structures.

Recognition of activities of daily living in healthy subjects using two ad-hoc classifiers

Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionnaires due to self-reporting biases. Various sensor-based (wearable, in-home, intrusive) systems have been proposed to successfully recognize and quantify ADL without relying on self-reporting. New classifiers required to classify sensor data are on the rise. We propose two ad-hoc classifiers that are based only on non-intrusive sensor data. METHODS: A wireless sensor system with ten sensor boxes was installed in the home of ten healthy subjects to collect ambient data over a duration of 20 consecutive days. A handheld protocol device and a paper logbook were also provided to the subjects. Eight ADL were selected for recognition. We developed two ad-hoc ADL classifiers, namely the rule based forward chaining inference engine (RBI) classifier and the circadian activity rhythm (CAR) classifier. The RBI classifier finds facts in data and matches them against the rules. The CAR classifier works within a framework to automatically rate routine activities to detect regular repeating patterns of behavior. For comparison, two state-of-the-art [Naïves Bayes (NB), Random Forest (RF)] classifiers have also been used. All classifiers were validated with the collected data sets for classification and recognition of the eight specific ADL. RESULTS: Out of a total of 1,373 ADL, the RBI classifier correctly determined 1,264, while missing 109 and the CAR determined 1,305 while missing 68 ADL. The RBI and CAR classifier recognized activities with an average sensitivity of 91.27 and 94.36%, respectively, outperforming both RF and NB. CONCLUSIONS: The performance of the classifiers varied significantly and shows that the classifier plays an important role in ADL recognition. Both RBI and CAR classifier performed better than existing state-of-the-art (NB, RF) on all ADL. Of the two ad-hoc classifiers, the CAR classifier was more accurate and is likely to be better suited than the RBI for distinguishing and recognizing complex ADL.

A comparative study on unconstrained hand biometrics

Biometrics applied to mobile devices are of great interest for security applications. Daily scenarios can benefit of a combination of both the most secure systems and most simple and extended devices. This document presents a hand biometric system oriented to mobile devices, proposing a non-intrusive, contact-less acquisition process where final users should take a picture of their hand in free-space with a mobile device without removals of rings, bracelets or watches. The main contribution of this paper is threefold: firstly, a feature extraction method is proposed, providing invariant hand measurements to previous changes; second contribution consists of providing a template creation based on hand geometric distances, requiring information from only one individual, without considering data from the rest of individuals within the database; finally, a proposal for template matching is proposed, minimizing the intra-class similarity and maximizing the inter-class likeliness. The proposed method is evaluated using three publicly available contact-less, platform-free databases. In addition, the results obtained with these databases will be compared to the results provided by two competitive pattern recognition techniques, namely Support Vector Machines (SVM) and k-Nearest Neighbour, often employed within the literature. Therefore, this approach provides an appropriate solution to adapt hand biometrics to mobile devices, with an accurate results and a non-intrusive acquisition procedure which increases the overall acceptance from the final user.

Estudio de Análogos Naturales de Captura y Almacenamiento de CO2: Relación Radón (222Rn) - Torón (220Rn)

La Fundación Ciudad de la Energía (CIUDEN) está desarrollando un proyecto de almacenamiento geológico de CO2. El área seleccionada para la colocación de la planta piloto de desarrollo tecnológico se encuentra en las proximidades de la localidad de Hontomín (Burgos, España). Dentro de los objetivos de este proyecto se encuentra el desarrollo y puesta a punto de una metodología no intrusiva/invasiva que permita mejorar el conocimiento de formaciones geológicas a partir del registro en superficie de la emisión de gases de origen natural. Para cumplir con parte de este objetivo, se ha realizado un estudio de los flujos y de la relación entre las actividades de radón (222Rn) y torón (220Rn) asociados a flujos altos de CO2. El área de estudio se encuentra en la zona volcánica de Campo de Calatrava de la provincia de Ciudad Real en España. Dado que los flujos muy altos (566 a 2011 g/m2•dia) de CO2 son puntuales en el emplazamiento de estudio, éstos podrían equipararse a escapes puntuales en zonas de debilidad de un almacenamiento comercial de CO2. Los resultados obtenidos indican que los flujos altos de CO2 conllevan actividades muy altas de 222Rn (118398 Bq/m3), y altas relaciones radón-torón, ya que se observa una disminución de las concentraciones de torón. Abstract The Fundación Ciudad de la Energía (CIUDEN) is presently developing a project of geological storage of CO2. The selected area is close to Hontomín town (Burgos, Spain). One of the aim objectives of this project is the development and testing of a non-intrusive/invasive methodology to improve our knowledge of geological formations from the surface record of the emission of soil gas. To meet part of this goal, a survey of 222Rn and 220Rn measurements has been performed at a site called La Sima, located in volcanic area of Campo de Calatrava (Ciudad Real, Spain) which is characterized by high fluxes of CO2 (566 a 2011 g/m2•dia). These high, point-source fluxes can be considered as analogues of potential leakages in commercial storages. The obtained results show a clear correlation between high flux of CO2 and very high activities of 222Rn (118398 Bq/m3). In contrast, activity of 220Rn is significantly low and consequently high ratios of radon-thoron are measured.

Estudio y desarrollo de sensores de fibra óptica para detección de vibraciones en ductos ascendentes submarinos

En esta tesis doctoral se describe el trabajo de investigación enfocado al estudio y desarrollo de sensores de fibra óptica para la detección de presión, flujo y vibraciones en ductos ascendentes submarinos utilizados en la extracción y transporte de hidrocarburos, con el objetivo de aplicarlos en los campos de explotación de aguas profundas en el Golfo de México pertenecientes a la Industria Petrolera Mexicana. El trabajo se ha enfocado al estudio y desarrollo de sensores ópticos cuasi distribuidos y distribuidos. En especial se ha profundizado en el uso y aplicación de las redes de Bragg (FBG) y de reflectómetros ópticos en el dominio del tiempo sensible a la fase (φ-OTDR). Los sensores de fibra óptica son especialmente interesantes para estas aplicaciones por sus ventajosas características como su inmunidad a interferencias electromagnéticas, capacidad de multiplexado, fiabilidad para trabajar en ambientes hostiles, altas temperaturas, altas presiones, ambientes salino-corrosivos, etc. Además, la fibra óptica no solo es un medio sensor sino que puede usarse como medio de transmisión. Se ha realizado un estudio del estado del arte y las ventajas que presentan los sensores ópticos puntuales, cuasi-distribuidos y distribuidos con respecto a los sensores convencionales. Se han estudiado y descrito los interrogadores de redes de Bragg y se ha desarrollado un método de calibración útil para los interrogadores existentes en el mercado, consiguiendo incertidumbres en la medida de la longitud de onda menores de ± 88 nm e incertidumbres relativas (la mas interesante en el campo de los sensores) menores de ±3 pm. Centrándose en la aplicación de las redes de Bragg en la industria del petróleo, se ha realizado un estudio en detalle del comportamiento que presentan las FBGs en un amplio rango de temperaturas de -40 ºC a 500 oC. Como resultado de este estudio se han evaluado las diferencias en los coeficientes de temperatura en diversos tramos de mas mismas, así como para diferentes recubrimientos protectores. En especial se ha encontrado y evaluado las diferencias de los diferentes recubrimientos en el intervalo de temperaturas entre -40 ºC y 60 ºC. En el caso del intervalo de altas temperaturas, entre 100 ºC y 500 ºC, se ha medido y comprobado el cambio uniforme del coeficiente de temperatura en 1pm/ºC por cada 100 ºC de aumento de temperatura, en redes independientemente del fabricante de las mismas. Se ha aplicado las FBG a la medición de manera no intrusiva de la presión interna en una tubería y a la medición del caudal de un fluido en una tubería, por la medida de diferencia de presión entre dos puntos de la misma. Además se ha realizado un estudio de detección de vibraciones en tuberías con fluidos. Finalmente, se ha implementado un sistema de detección distribuida de vibraciones aplicable a la detección de intrusos en las proximidades de los ductos, mediante un φ-OTDR. En este sistema se ha estudiado el efecto negativo de la inestabilidad de modulación que limita la detección de vibraciones distribuidas, su sensibilidad y su alcance. ABSTRACT This thesis describes the research work focused for the study and development of on optical fiber sensors for detecting pressure, flow and vibration in subsea pipes used in the extraction and transportation of hydrocarbons, in order to apply them in deepwater fields in the Gulf of Mexico belonging to the Mexican oil industry. The work has focused on the study and development of optical sensors distributed and quasi distributed. Especially was done on the use and application of fiber Bragg grating (FBG) and optical reflectometers time domain phase sensitive (φ-OTDR). The optical fiber sensors especially are interesting for these applications for their advantageous characteristics such as immunity to electromagnetic interference, multiplexing capability, reliability to work in harsh environments, high temperatures, high pressures, corrosive saline environments, etc. Furthermore, the optical fiber is not only a sensor means it can be used as transmission medium. We have performed a study of the state of the art and the advantages offered by optical sensors point, quasi-distributed and distributed over conventional sensors. Have studied and described interrogators Bragg grating and has developed a calibration method for interrogators useful for the existing interrogators in the market, resulting uncertainty in the measurement of the wavelength of less than ± 0.17 nm and uncertainties (the more interesting in the field of sensors) less than ± 3 pm. Focusing on the application of the Bragg gratings in the oil industry, has been studied in detail the behavior of the FBGs in a wide range of temperatures from -40 °C to 500 oC. As a result of this study we have evaluated the difference in temperature coefficients over various sections of the same, as well as different protective coatings. In particular evaluated and found the differences coatings in the range of temperatures between -40 º C and 60 º C. For the high temperature range between 20 ° C and 500 ° C, has been measured and verified the uniform change of the temperature coefficient at 1pm / ° C for each 100 ° C increase in temperature, in networks regardless of manufacturer thereof. FBG is applied to the non-intrusive measurement of internal pressure in a pipeline and measuring flow of a fluid in a pipe, by measuring the pressure difference between two points thereof. Therefore, has also made a study of detecting vibrations in pipes with fluids. Finally, we have implemented a distributed sensing system vibration applied to intrusion detection in the vicinity of the pipelines, by φ-OTDR. In this system we have studied the negative effect of modulation instability limits the distributed vibration detection, sensitivity and scope.

New generation of human machine interfaces for controlling UAV through depth based gesture recognition

New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.

A cyber-physical approach to combined HW-SW monitoring for improving energy efficiency in data centers

High-Performance Computing, Cloud computing and next-generation applications such e-Health or Smart Cities have dramatically increased the computational demand of Data Centers. The huge energy consumption, increasing levels of CO2 and the economic costs of these facilities represent a challenge for industry and researchers alike. Recent research trends propose the usage of holistic optimization techniques to jointly minimize Data Center computational and cooling costs from a multilevel perspective. This paper presents an analysis on the parameters needed to integrate the Data Center in a holistic optimization framework and leverages the usage of Cyber-Physical systems to gather workload, server and environmental data via software techniques and by deploying a non-intrusive Wireless Sensor Net- work (WSN). This solution tackles data sampling, retrieval and storage from a reconfigurable perspective, reducing the amount of data generated for optimization by a 68% without information loss, doubling the lifetime of the WSN nodes and allowing runtime energy minimization techniques in a real scenario.

Caracterización de la agitación local y la respuesta oscilatoria de un buque mediante el uso de técnicas de visión artificial : aplicación al análisis de los umbrales operativos en líneas de atraque y amarre

El desarrollo de actividades de carga y descarga son parte de la esencia de la naturaleza funcional de un puerto, de las cuales derivan en gran medida los ingresos del mismo y la eficiencia de la cadena logística en su conjunto. Las oscilaciones en el interior de una dársena y en un línea de atraque disminuyen la calidad de la estancia de las embarcaciones en puerto, reducen el rendimiento de la estiba de los buques y solicitan y fatigan las estructuras y los cuerpos flotantes amarrados. Si los parámetros que definen la agitación local se aproximan a regiones de fallo 0 parada, el subsistema pierde rendimiento, fiabilidad y finalmente se paralizan las operaciones, produciéndose de este modo tiempos de inactividad. Estas paradas operativas conllevan pérdidas económicas para la terminal y, consecuentemente, para el puerto. Hoy día se dispone vastas redes de monitorización destinadas a la caracterización del medio físico en el entorno de los puertos. Paralelamente, las operaciones de manipulación de cargas en las terminales se están dirigiendo hacia modelos de automatización o semi automatización, que permiten no sólo la sistematización de procesos, sino también un profundo conocimiento del flujo de tareas. En este contexto hay un déficit de información sobre cómo afectan los diferentes forzadores del medio físico al rendimiento, la seguridad funcionalidad del proceso de manipulación de carga y descarga. Esto se debe en gran medida a la falta de registros dilatados en el tiempo que permitan correlacionar todos los aspectos mencionados de un modo particularizado para cada línea de atraque y amarre de un puerto. En esta tesis se desarrolla una metodología de vídeo monitorización no intrusiva y de bajo coste basada en la aplicación de técnicas "pixel tool' y la obtención de los parámetros extrínsecos de una observación monofocal. Con ello pretende poner en valor las infraestructuras de vídeo vigilancia de los puertos y de los laboratorios de experimentación a escala reducida, con el objeto de facilitar el estudio los umbrales operativos de las áreas de atraque y amarre. The development of loading and unloading activities is an essential part of he functional nature of a port, which derive largely from he same income and the efficiency of he supply chain as a whole. The oscillations inside a dock and a mooring line diminish he quality of the stay of vessels in port reducing the performance of the stowage of ship and asking and fatigued structures and moored floating bodies. If the parameters defining the local al agitation regions are close to areas of failure or shutdown, he subsystem looses performance, reliability and eventually paralyzes the operations, thereby producing downtime. These operational stops entail economic 1osses to the terminal and, consequently for the port. Today vast networks of monitoring, aimed at he characterization of the physical environment in the vicinity of he ports, are available. In parallel, the cargo handling operations at terminals are moving towards automation or semi-automation models that allow not only the systematization of processes, but also a deep understanding of he workflow. In this context, there is a lack of information about how the different forcing agents of the physical environment affect the performance and he functional safety of the loading and unloading process. This is due largely to the lack of spread-over-time records which would allow to correlate all aspects mentioned, specifically, for each berthing and mooring of a port. This thesis develops a methodology for non-intrusive and low cost monitoring video based on the application of "pixel tool" techniques and on obtaining the extrinsic parameters of a monofocal observation. It seeks an enhancement of the video monitoring infrastructure at ports and at experimental laboratories of reduced scale, in order to facilitate the study of operational thresholds berthing and mooring areas.

Development of Shape-Optimization Tools for the Aerodynamic Design of Turbomachinery Blades

The aim of this work is to develop an automated tool for the optimization of turbomachinery blades founded on an evolutionary strategy. This optimization scheme will serve to deal with supersonic blades cascades for application to Organic Rankine Cycle (ORC) turbines. The blade geometry is defined using parameterization techniques based on B-Splines curves, that allow to have a local control of the shape. The location in space of the control points of the B-Spline curve define the design variables of the optimization problem. In the present work, the performance of the blade shape is assessed by means of fully-turbulent flow simulations performed with a CFD package, in which a look-up table method is applied to ensure an accurate thermodynamic treatment. The solver is set along with the optimization tool to determine the optimal shape of the blade. As only blade-to-blade effects are of interest in this study, quasi-3D calculations are performed, and a single-objective evolutionary strategy is applied to the optimization. As a result, a non-intrusive tool, with no need for gradients definition, is developed. The computational cost is reduced by the use of surrogate models. A Gaussian interpolation scheme (Kriging model) is applied for the estimated n-dimensional function, and a surrogate-based local optimization strategy is proved to yield an accurate way for optimization. In particular, the present optimization scheme has been applied to the re-design of a supersonic stator cascade of an axial-flow turbine. In this design exercise very strong shock waves are generated in the rear blade suction side and shock-boundary layer interaction mechanisms occur. A significant efficiency improvement as a consequence of a more uniform flow at the blade outlet section of the stator is achieved. This is also expected to provide beneficial effects on the design of a subsequent downstream rotor. The method provides an improvement to gradient-based methods and an optimized blade geometry is easily achieved using the genetic algorithm.

Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

Web-based screening and brief intervention for hazardous drinking: a double-blind randomized controlled trial

Background Strong evidence exists for the efficacy of screening and brief intervention for reducing hazardous drinking. However, problems have been highlighted with respect to its implementation in health-care systems, not least of which is a reluctance of some doctors to discuss alcohol proactively with their patients. Aims To determine the efficacy of a novel web-based screening and brief intervention (e-SBI) to reduce hazardous drinking. Design A double-blind randomized controlled trial. Setting A university student health service. Participants A total of 16 7 students (17-26 years) were recruited in the reception area and completed a 3-minute web-based screen including the Alcohol Use Disorder Identifiation Test (AUDIT) questionnaire. Of these, 112 tested positive, and 104 (52 females) who consented to follow-up were included in the trial. Measurements Drinking frequency, typical occasion quantity, total volume, heavy episode frequency (females > 80 g ethanol, males > 120 g ethanol), number of personal problems, an academic problems score. Intervention Participants were randomized to 10-15 minutes of web-based assessment and personalized feedback on their drinking (intervention, n = 5 1) or to a leaflet-only control group (n = 5 3). Findings Mean baseline AUDIT scores for control and intervention groups were 16.6 (SD = 6.0) and 16.6 (SD = 5.7). At 6 weeks, participants receiving e-SBI reported significantly lower total consumption (geometric mean ratio = 0.74; 9 5 % confidence interval: 0.56-0.96), lower heavy episode frequency (0.63; 0.42-0.92) and fewer personal problems (0.70; 0.54-0.91). At 6 months personal problems remained lower (0.76; 0.60-0.97), although consumption did not differ significantly. At 6 months, academic problems were lower in the intervention group relative to controls (0.72; 0.51-1.02). Conclusions e-SBI reduced hazardous drinking among university students, to an extent similar to that found for practitioner-delivered brief interventions in the general population. e-SBI offers promise as a strategy to reduce alcohol-related harm in a way that is non-intrusive, appealing to the target group, and capable of being incorporated into primary care. Research is required to replicate the findings, to determine the duration of intervention effects, and to investigate the mechanisms by which the intervention operates.

Use of regression equation of peripheral pulse timing characteristics to predict hypertension in children

Studies have shown that an increase in arterial stiffening can indicate the presence of cardiovascular diseases like hypertension. Current gold standard in clinical practice is by measuring the blood pressure of patients using a mercury sphygmomanometer. However, the nature of this technique is not suitable for prolonged monitoring. It has been established that pulse wave velocity is a direct measure of arterial stiffening. However, its usefulness is hampered by the absence of techniques to estimate it non-invasively. Pulse transit time (PTT) is a simple and non-intrusive method derived from pulse wave velocity. It has shown its capability in childhood respiratory sleep studies. Recently, regression equations that can predict PTT values for healthy Caucasian children were formulated. However, its usefulness to identify hypertensive children based on mean PTT values has not been investigated. This was a continual study where 3 more Caucasian male children with known clinical hypertension were recruited. Results indicated that the PTT predictive equations are able to identify hypertensive children from their normal counterparts in a significant manner (p < 0.05). Hence, PTT can be a useful diagnostic tool in identifying hypertension in children and shows potential to be a non-invasive continual monitor for arterial stiffening.

The human factors of automatic speech recognition in control room systems

This thesis addresses the viability of automatic speech recognition for control room systems; with careful system design, automatic speech recognition (ASR) devices can be useful means for human computer interaction in specific types of task. These tasks can be defined as complex verbal activities, such as command and control, and can be paired with spatial tasks, such as monitoring, without detriment. It is suggested that ASR use be confined to routine plant operation, as opposed the critical incidents, due to possible problems of stress on the operators' speech.  It is proposed that using ASR will require operators to adapt a commonly used skill to cater for a novel use of speech. Before using the ASR device, new operators will require some form of training. It is shown that a demonstration by an experienced user of the device can lead to superior performance than instructions. Thus, a relatively cheap and very efficient form of operator training can be supplied by demonstration by experienced ASR operators. From a series of studies into speech based interaction with computers, it is concluded that the interaction be designed to capitalise upon the tendency of operators to use short, succinct, task specific styles of speech. From studies comparing different types of feedback, it is concluded that operators be given screen based feedback, rather than auditory feedback, for control room operation. Feedback will take two forms: the use of the ASR device will require recognition feedback, which will be best supplied using text; the performance of a process control task will require task feedback integrated into the mimic display. This latter feedback can be either textual or symbolic, but it is suggested that symbolic feedback will be more beneficial. Related to both interaction style and feedback is the issue of handling recognition errors. These should be corrected by simple command repetition practices, rather than use error handling dialogues. This method of error correction is held to be non intrusive to primary command and control operations. This thesis also addresses some of the problems of user error in ASR use, and provides a number of recommendations for its reduction.

Aerodynamic load characteristics evaluation and tri-axial performance testing on fiber reinforced polymer connections and metal fasteners to promote hurricane damage mitigation

Damages during extreme wind events highlight the weaknesses of mechanical fasteners at the roof-to-wall connections in residential timber frame buildings. The allowable capacity of the metal fasteners is based on results of unidirectional component testing that do not simulate realistic tri-axial aerodynamic loading effects. The first objective of this research was to simulate hurricane effects and study hurricane-structure interaction at full-scale, facilitating better understanding of the combined impacts of wind, rain, and debris on inter-component connections at spatial and temporal scales. The second objective was to evaluate the performance of a non-intrusive roof-to-wall connection system using fiber reinforced polymer (FRP) materials and compare its load capacity to the capacity of an existing metal fastener under simulated aerodynamic loads. ^ The Wall of Wind (WoW) testing performed using FRP connections on a one-story gable-roof timber structure instrumented with a variety of sensors, was used to create a database on aerodynamic and aero-hydrodynamic loading on roof-to-wall connections tested under several parameters: angles of attack, wind-turbulence content, internal pressure conditions, with and without effects of rain. Based on the aerodynamic loading results obtained from WoW tests, sets of three force components (tri-axial mean loads) were combined into a series of resultant mean forces, which were used to test the FRP and metal connections in the structures laboratory up to failure. A new component testing system and test protocol were developed for testing fasteners under simulated triaxial loading as opposed to uni-axial loading. The tri-axial and uni-axial test results were compared for hurricane clips. Also, comparison was made between tri-axial load capacity of FRP and metal connections. ^ The research findings demonstrate that the FRP connection is a viable option for use in timber roof-to-wall connection system. Findings also confirm that current testing methods of mechanical fasteners tend to overestimate the actual load capacities of a connector. Additionally, the research also contributes to the development a new testing protocol for fasteners using tri-axial simultaneous loads based on the aerodynamic database obtained from the WoW testing. ^