978 resultados para Color vision.


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Regenerative sustainability is emerging as an alternative discourse around the transition from a ‘mechanistic’ to an ‘ecological’ or living systems worldview. This view helps us to re-conceptualize relationships among humans’ technological, ecological, economic, social and political systems. Through exploration of ‘net positive’ or ‘regenerative’ development lenses and the traditional sustainability literature, the conceptualization and approaches to achieve sustainable development and ecological modernization are expanded to articulate and to explore the evolving sustainability discourse, ‘regenerative sustainability’. This Special Volume of Journal of Cleaner Production (SV) is focused upon various dimensions of regenerative sustainability (e.g. regenerative design, regenerative development, and positive development) applied to the urban built environment at scales, which range from individual buildings, neighborhoods, and urban developments to integrated regional sustainable development. The main focus is on how these approaches and developments are evolving, how they can help us to prevent or adapt to climate change and how these approaches are likely to evolve in the next two to three decades. These approaches are addressed in four themes: (1) reviewing the theoretical development of the discourse of regenerative sustainability, its emerging principles and practices, (2) explaining how it can be measured and monitored, (3) providing encouraging practical pathways and examples of its implementation in multiple cultural and climatic contexts, and (4) mapping obstacles and enablers that must be addressed to help to ensure that more rapid progress is made in implementing the transitions towards an urban built environment that supports genuinely sustainable societies.

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In recent years more and more complex humanoid robots have been developed. On the other hand programming these systems has become more difficult. There is a clear need for such robots to be able to adapt and perform certain tasks autonomously, or even learn by themselves how to act. An important issue to tackle is the closing of the sensorimotor loop. Especially when talking about humanoids the tight integration of perception with actions will allow for improved behaviours, embedding adaptation on the lower-level of the system.

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Monopoles which are sources of non-Abelian magnetic flux are predicted by many models of grand unification. It has been argued elsewhere that a generic transformation of the "unbroken" symmetry group H cannot be globally implemented on such monopoles for reasons of topology. In this paper, we show that similar topological obstructions are encountered in the mechanics of a test particle in the field of these monopoles and that the transformations of H cannot all be globally implemented as canonical transformations. For the SU(5) model, if H is SU(3)C×U(1)em, a consequence is that color multiplets are not globally defined, while if H is SU(3)C×SU(2)WS×U(1)Y, the same is the case for both color and electroweak multiplets. There are, however, several subgroups KT, KT′,… of H which can be globally implemented, with the transformation laws of the observables differing from group to group in a novel way. For H=SU(3)C×U(1)em, a choice for KT is SU(2)C×U(1)em, while for H=SU(3)C×SU(2)WS×U(1)Y, a choice is SU(2)C×U(1)×U(1)×U(1). The paper also develops the differential geometry of monopoles in a form convenient for computations.

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Many grand unified theories (GUT's) predict non-Abelian monopoles which are sources of non-Abelian (and Abelian) magnetic flux. In the preceding paper, we discussed in detail the topological obstructions to the global implementation of the action of the "unbroken symmetry group" H on a classical test particle in the field of such a monopole. In this paper, the existence of similar topological obstructions to the definition of H action on the fields in such a monopole sector, as well as on the states of a quantum-mechanical test particle in the presence of such fields, are shown in detail. Some subgroups of H which can be globally realized as groups of automorphisms are identified. We also discuss the application of our analysis to the SU(5) GUT and show in particular that the non-Abelian monopoles of that theory break color and electroweak symmetries.

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There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.

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This paper introduces a machine learning based system for controlling a robotic manipulator with visual perception only. The capability to autonomously learn robot controllers solely from raw-pixel images and without any prior knowledge of configuration is shown for the first time. We build upon the success of recent deep reinforcement learning and develop a system for learning target reaching with a three-joint robot manipulator using external visual observation. A Deep Q Network (DQN) was demonstrated to perform target reaching after training in simulation. Transferring the network to real hardware and real observation in a naive approach failed, but experiments show that the network works when replacing camera images with synthetic images.

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Recent interest in affect and the body have mobilised a contemporary review of aesthetics and phenomenology within architecture to unpack how environments affect spatial experience. Emerging spatial studies within the neurosciences, and their implications for architectural research as raised by architectural theorists has been well supported by a raft of scientists and institutions. Although there has been some headway in spatial studies of the vision impaired (Cattaneo et al., 2011) to understand the role of their non-visual systems in assisting navigation and location, little is discussed in terms of their other abilities in sensing particular qualities of space which impinge upon emotion and wellbeing. This research explores, through published studies and constructed spatial interviews, the affective perception of the vision impaired and how further interplay between this research and the architectural field can contribute new knowledge regarding space and affect. The research aims to provide background of current and potential cross disciplinary research and highlight the role wearable technologies can play in enhancing knowledge of affective spatial experience.

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To develop and test a custom-built instrument to simultaneously assess tear film surface quality (TFSQ) and subjective vision score (SVS).

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The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

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Robotic vision is limited by line of sight and onboard camera capabilities. Robots can acquire video or images from remote cameras, but processing additional data has a computational burden. This paper applies the Distributed Robotic Vision Service, DRVS, to robot path planning using data outside line-of-sight of the robot. DRVS implements a distributed visual object detection service to distributes the computation to remote camera nodes with processing capabilities. Robots request task-specific object detection from DRVS by specifying a geographic region of interest and object type. The remote camera nodes perform the visual processing and send the high-level object information to the robot. Additionally, DRVS relieves robots of sensor discovery by dynamically distributing object detection requests to remote camera nodes. Tested over two different indoor path planning tasks DRVS showed dramatic reduction in mobile robot compute load and wireless network utilization.

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One of the main aims of evolutionary biology is to explain why organisms vary phenotypically as they do. Proximately, this variation arises from genetic differences and from environmental influences, the latter of which is referred to as phenotypic plasticity. Phenotypic plasticity is thus a central concept in evolutionary biology, and understanding its relative importance in causing the phenotypic variation and differentiation is important, for instance in anticipating the consequences of human induced environmental changes. The aim of this thesis was to study geographic variation and local adaptation, as well as sex ratios and environmental sex reversal, in the common frog (Rana temporaria). These themes cover three different aspects of phenotypic plasticity, which emerges as the central concept for the thesis. The first two chapters address geographic variation and local adaptation in two potentially thermally adaptive traits, namely the degree of melanism and the relative leg length. The results show that although there is an increasing latitudinal trend in the degree of melanism in wild populations across Scandinavian Peninsula, this cline has no direct genetic basis and is thus environmentally induced. The second chapter demonstrates that although there is no linear, latitudinally ordered phenotypic trend in relative leg length that would be expected under Allen s rule an ecogeographical rule linking extremity length to climatic conditions there seems to be such a trend at the genetic level, hidden under environmental effects. The first two chapters thus view phenotypic plasticity through its ecological role and evolution, and demonstrate that it can both give rise to phenotypic variation and hide evolutionary patterns in studies that focus solely on phenotypes. The last three chapters relate to phenotypic plasticity through its ecological and evolutionary role in sex determination, and consequent effects on population sex ratio, genetic recombination and the evolution of sex chromosomes. The results show that while sex ratios are strongly female biased and there is evidence of environmental sex reversals, these reversals are unlikely to have caused the sex ratio skew, at least directly. The results demonstrate that environmental sex reversal can have an effect on the evolution of sex chromosomes, as the recombination patterns between them seem to be controlled by phenotypic, rather than genetic, sex. This potentially allows Y chromosomes to recombine, lending support for the recent hypothesis suggesting that sex-reversal may play an important role on the rejuvenation of Y chromosomes.

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Visual information processing in brain proceeds in both serial and parallel fashion throughout various functionally distinct hierarchically organised cortical areas. Feedforward signals from retina and hierarchically lower cortical levels are the major activators of visual neurons, but top-down and feedback signals from higher level cortical areas have a modulating effect on neural processing. My work concentrates on visual encoding in hierarchically low level cortical visual areas in human brain and examines neural processing especially in cortical representation of visual field periphery. I use magnetoencephalography and functional magnetic resonance imaging to measure neuromagnetic and hemodynamic responses during visual stimulation and oculomotor and cognitive tasks from healthy volunteers. My thesis comprises six publications. Visual cortex forms a great challenge for modeling of neuromagnetic sources. My work shows that a priori information of source locations are needed for modeling of neuromagnetic sources in visual cortex. In addition, my work examines other potential confounding factors in vision studies such as light scatter inside the eye which may result in erroneous responses in cortex outside the representation of stimulated region, and eye movements and attention. I mapped cortical representations of peripheral visual field and identified a putative human homologue of functional area V6 of the macaque in the posterior bank of parieto-occipital sulcus. My work shows that human V6 activates during eye-movements and that it responds to visual motion at short latencies. These findings suggest that human V6, like its monkey homologue, is related to fast processing of visual stimuli and visually guided movements. I demonstrate that peripheral vision is functionally related to eye-movements and connected to rapid stream of functional areas that process visual motion. In addition, my work shows two different forms of top-down modulation of neural processing in the hierachically lowest cortical levels; one that is related to dorsal stream activation and may reflect motor processing or resetting signals that prepare visual cortex for change in the environment and another local signal enhancement at the attended region that reflects local feed-back signal and may perceptionally increase the stimulus saliency.

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Detect and Avoid (DAA) technology is widely acknowledged as a critical enabler for unsegregated Remote Piloted Aircraft (RPA) operations, particularly Beyond Visual Line of Sight (BVLOS). Image-based DAA, in the visible spectrum, is a promising technological option for addressing the challenges DAA presents. Two impediments to progress for this approach are the scarcity of available video footage to train and test algorithms, in conjunction with testing regimes and specifications which facilitate repeatable, statistically valid, performance assessment. This paper includes three key contributions undertaken to address these impediments. In the first instance, we detail our progress towards the creation of a large hybrid collision and near-collision encounter database. Second, we explore the suitability of techniques employed by the biometric research community (Speaker Verification and Language Identification), for DAA performance optimisation and assessment. These techniques include Detection Error Trade-off (DET) curves, Equal Error Rates (EER), and the Detection Cost Function (DCF). Finally, the hybrid database and the speech-based techniques are combined and employed in the assessment of a contemporary, image based DAA system. This system includes stabilisation, morphological filtering and a Hidden Markov Model (HMM) temporal filter.