28,997 research outputs found

    Image classification over unknown and anomalous domains

    Get PDF
    A longstanding goal in computer vision research is to develop methods that are simultaneously applicable to a broad range of prediction problems. In contrast to this, models often perform best when they are specialized to some task or data type. This thesis investigates the challenges of learning models that generalize well over multiple unknown or anomalous modes and domains in data, and presents new solutions for learning robustly in this setting. Initial investigations focus on normalization for distributions that contain multiple sources (e.g. images in different styles like cartoons or photos). Experiments demonstrate the extent to which existing modules, batch normalization in particular, struggle with such heterogeneous data, and a new solution is proposed that can better handle data from multiple visual modes, using differing sample statistics for each. While ideas to counter the overspecialization of models have been formulated in sub-disciplines of transfer learning, e.g. multi-domain and multi-task learning, these usually rely on the existence of meta information, such as task or domain labels. Relaxing this assumption gives rise to a new transfer learning setting, called latent domain learning in this thesis, in which training and inference are carried out over data from multiple visual domains, without domain-level annotations. Customized solutions are required for this, as the performance of standard models degrades: a new data augmentation technique that interpolates between latent domains in an unsupervised way is presented, alongside a dedicated module that sparsely accounts for hidden domains in data, without requiring domain labels to do so. In addition, the thesis studies the problem of classifying previously unseen or anomalous modes in data, a fundamental problem in one-class learning, and anomaly detection in particular. While recent ideas have been focused on developing self-supervised solutions for the one-class setting, in this thesis new methods based on transfer learning are formulated. Extensive experimental evidence demonstrates that a transfer-based perspective benefits new problems that have recently been proposed in anomaly detection literature, in particular challenging semantic detection tasks

    Embodying entrepreneurship: everyday practices, processes and routines in a technology incubator

    Get PDF
    The growing interest in the processes and practices of entrepreneurship has been dominated by a consideration of temporality. Through a thirty-six-month ethnography of a technology incubator, this thesis contributes to extant understanding by exploring the effect of space. The first paper explores how class structures from the surrounding city have appropriated entrepreneurship within the incubator. The second paper adopts a more explicitly spatial analysis to reveal how the use of space influences a common understanding of entrepreneurship. The final paper looks more closely at the entrepreneurs within the incubator and how they use visual symbols to develop their identity. Taken together, the three papers reject the notion of entrepreneurship as a primarily economic endeavour as articulated through commonly understood language and propose entrepreneuring as an enigmatic attractor that is accessed through the ambiguity of the non-verbal to develop the ‘new’. The thesis therefore contributes to the understanding of entrepreneurship and proposes a distinct role for the non-verbal in that understanding

    Underwater optical wireless communications in turbulent conditions: from simulation to experimentation

    Get PDF
    Underwater optical wireless communication (UOWC) is a technology that aims to apply high speed optical wireless communication (OWC) techniques to the underwater channel. UOWC has the potential to provide high speed links over relatively short distances as part of a hybrid underwater network, along with radio frequency (RF) and underwater acoustic communications (UAC) technologies. However, there are some difficulties involved in developing a reliable UOWC link, namely, the complexity of the channel. The main focus throughout this thesis is to develop a greater understanding of the effects of the UOWC channel, especially underwater turbulence. This understanding is developed from basic theory through to simulation and experimental studies in order to gain a holistic understanding of turbulence in the UOWC channel. This thesis first presents a method of modelling optical underwater turbulence through simulation that allows it to be examined in conjunction with absorption and scattering. In a stationary channel, this turbulence induced scattering is shown to cause and increase both spatial and temporal spreading at the receiver plane. It is also demonstrated using the technique presented that the relative impact of turbulence on a received signal is lower in a highly scattering channel, showing an in-built resilience of these channels. Received intensity distributions are presented confirming that fluctuations in received power from this method follow the commonly used Log-Normal fading model. The impact of turbulence - as measured using this new modelling framework - on link performance, in terms of maximum achievable data rate and bit error rate is equally investigated. Following that, experimental studies comparing both the relative impact of turbulence induced scattering on coherent and non-coherent light propagating through water and the relative impact of turbulence in different water conditions are presented. It is shown that the scintillation index increases with increasing temperature inhomogeneity in the underwater channel. These results indicate that a light beam from a non-coherent source has a greater resilience to temperature inhomogeneity induced turbulence effect in an underwater channel. These results will help researchers in simulating realistic channel conditions when modelling a light emitting diode (LED) based intensity modulation with direct detection (IM/DD) UOWC link. Finally, a comparison of different modulation schemes in still and turbulent water conditions is presented. Using an underwater channel emulator, it is shown that pulse position modulation (PPM) and subcarrier intensity modulation (SIM) have an inherent resilience to turbulence induced fading with SIM achieving higher data rates under all conditions. The signal processing technique termed pair-wise coding (PWC) is applied to SIM in underwater optical wireless communications for the first time. The performance of PWC is compared with the, state-of-the-art, bit and power loading optimisation algorithm. Using PWC, a maximum data rate of 5.2 Gbps is achieved in still water conditions

    Machine learning based adaptive soft sensor for flash point inference in a refinery realtime process

    Get PDF
    In industrial control processes, certain characteristics are sometimes difficult to measure by a physical sensor due to technical and/or economic limitations. This fact is especially true in the petrochemical industry. Some of those quantities are especially crucial for operators and process safety. This is the case for the automotive diesel Flash Point Temperature (FT). Traditional methods for FT estimation are based on the study of the empirical inference between flammability properties and the denoted target magnitude. The necessary measures are taken indirectly by samples from the process and analyzing them in the laboratory, this process implies time (can take hours from collection to flash temperature measurement) and thus make it very difficult for real-time monitorization, which in fact results in security and economical losses. This study defines a procedure based on Machine Learning modules that demonstrate the power of real-time monitorization over real data from an important international refinery. As input, easily measured values provided in real-time, such as temperature, pressure, and hydraulic flow are used and a benchmark of different regressive algorithms for FT estimation is presented. The study highlights the importance of sequencing preprocessing techniques for the correct inference of values. The implementation of adaptive learning strategies achieves considerable economic benefits in the productization of this soft sensor. The validity of the method is tested in the reality of a refinery. In addition, real-world industrial data sets tend to be unstable and volatile, and the data is often affected by noise, outliers, irrelevant or unnecessary features, and missing data. This contribution demonstrates with the inclusion of a new concept, called an adaptive soft sensor, the importance of the dynamic adaptation of the conformed schemes based on Machine Learning through their combination with feature selection, dimensional reduction, and signal processing techniques. The economic benefits of applying this soft sensor in the refinery's production plant and presented as potential semi-annual savings.This work has received funding support from the SPRI-Basque Gov- ernment through the ELKARTEK program (OILTWIN project, ref. KK- 2020/00052)

    Interactive Sonic Environments: Sonic artwork via gameplay experience

    Get PDF
    The purpose of this study is to investigate the use of video-game technology in the design and implementation of interactive sonic centric artworks, the purpose of which is to create and contribute to the discourse and understanding of its effectiveness in electro-acoustic composition highlighting the creative process. Key research questions include: How can the language of electro-acoustic music be placed in a new framework derived from videogame aesthetics and technology? What new creative processes need to be considered when using this medium? Moreover, what aspects of 'play' should be considered when designing the systems? The findings of this study assert that composers and sonic art practitioners need little or no coding knowledge to create exciting applications and the myriad of options available to the composer when using video-game technology is limited only by imagination. Through a cyclic process of planning, building, testing and playing these applications the project revealed advantages and unique sonic opportunities in comparison to other sonic art installations. A portfolio of selected original compositions, both fixed and open are presented by the author to complement this study. The commentary serves to place the work in context with other practitioners in the field and to provide compositional approaches that have been taken

    Diseño de un sistema de control y planeamiento de trayectoria coordinado en el tiempo para múltiples robots móviles no holonómicos en presencia de obstáculos

    Get PDF
    La presente tesis tiene como objetivo diseñar un sistema de control y planeamiento de trayectoria coordinado para múltiples robots móviles no holonómicos en mapas con presencia de obstáculos variados. En esta se simula el control y planeamiento en modelos matemáticos de tipo bicicleta. El sistema implementado consiste de tres partes, las cuales son el planeamiento de caminos, el generador de trayectorias y el control de seguimiento de trayectorias. El planeamiento de caminos se dividió en tres partes. En la primera parte se desarrolló el planeador local para un robot no holonómico, modificando el algoritmo Hybrid A*, de manera que utilice las ecuaciones movimiento circular del móvil en vez de las cinemáticas. Este algoritmo permite al robot encontrar los caminos que lo llevan de una configuración de posición y orientación inicial a una final en mapas con obstáculos variados. En la segunda parte se agregó al planeador local el planeamiento en el tiempo, combinando a este con el algoritmo de planeamiento de caminos en intervalos seguros (SIPP), el cual permite al robot evadir obstáculos en el tiempo. Finalmente, en la tercera parte se desarrolló el planeador global usando el algoritmo de búsqueda basada en conflictos (CBS), el cual resuelve los conflictos que se presentan entre los caminos de los móviles, imponiendo restricciones en el tiempo en el movimiento de cada uno de ellos. Por otro lado, el generador de trayectorias es desarrollado en una única parte, en la cual, se plantea la función de costo a optimizar, se calcula todos los gradientes y se plantea utilizar el algoritmo de descenso de gradiente de forma desacoplada para la optimización de trayectoria de cada móvil. Mientras que el desarrollo del sistema de control de seguimiento de trayectoria se dividió en dos partes. En la primera se linealiza el modelo matemático por extensión dinámica para sistemas flatness diferencial y en la segunda parte se desarrolla el controlador LQR de cada móvil que permite seguir las trayectorias de referencia deseadas. Al término de la tesis se logra el planeamiento, generación de trayectoria y el control de seguimiento de trayectoria de hasta 10 móviles no holonómicos en mapas con obstáculos variados, evitando la colisión con los obstáculos del entorno y la colisión con otros móviles durante el planeamiento y la optimización de trayectoria. Así mismo, se verifica que el planeador es capaz de resolver conflictos en entornos propensos al atasco como mapas tipo T o H
    • …
    corecore