30,679 research outputs found
Invitation to the Table Conversation: A Few Diverse Perspectives on Integration
This article represents an invitation to the integration table to several previously underrepresented perspectives within Christian psychology. The Judeo-Christian tradition and current views on scholarship and Christian faith compel us to extend hospitality to minority voices within integration, thereby enriching and challenging existing paradigms in the field. Contributors to this article, spanning areas of cultural, disciplinary, and theological diversity, provide suggestions for how their distinct voices can enhance future integrative efforts
Linking recorded data with emotive and adaptive computing in an eHealth environment
Telecare, and particularly lifestyle monitoring, currently relies on the ability to detect and respond to changes in individual behaviour using data derived from sensors around the home. This means that a significant aspect of behaviour, that of an individuals emotional state, is not accounted for in reaching a conclusion as to the form of response required. The linked concepts of emotive and adaptive computing offer an opportunity to include information about emotional state and the paper considers how current developments in this area have the potential to be integrated within telecare and other areas of eHealth. In doing so, it looks at the development of and current state of the art of both emotive and adaptive computing, including its conceptual background, and places them into an overall eHealth context for application and development
Real-Time Anisotropic Diffusion using Space-Variant Vision
Many computer and robot vision applications require multi-scale image analysis. Classically, this has been accomplished through the use of a linear scale-space, which is constructed by convolution of visual input with Gaussian kernels of varying size (scale). This has been shown to be equivalent to the solution of a linear diffusion equation on an infinite domain, as the Gaussian is the Green's function of such a system (Koenderink, 1984). Recently, much work has been focused on the use of a variable conductance function resulting in anisotropic diffusion described by a nonlinear partial differential equation (PDF). The use of anisotropic diffusion with a conductance coefficient which is a decreasing function of the gradient magnitude has been shown to enhance edges, while decreasing some types of noise (Perona and Malik, 1987). Unfortunately, the solution of the anisotropic diffusion equation requires the numerical integration of a nonlinear PDF which is a costly process when carried out on a fixed mesh such as a typical image. In this paper we show that the complex log transformation, variants of which are universally used in mammalian retino-cortical systems, allows the nonlinear diffusion equation to be integrated at exponentially enhanced rates due to the non-uniform mesh spacing inherent in the log domain. The enhanced integration rates, coupled with the intrinsic compression of the complex log transformation, yields a seed increase of between two and three orders of magnitude, providing a means of performing real-time image enhancement using anisotropic diffusion.Office of Naval Research (N00014-95-I-0409
Understanding synthesis imaging dynamic range
We develop a general framework for quantifying the many different
contributions to the noise budget of an image made with an array of dishes or
aperture array stations. Each noise contribution to the visibility data is
associated with a relevant correlation timescale and frequency bandwidth so
that the net impact on a complete observation can be assessed. All quantities
are parameterised as function of observing frequency and the visibility
baseline length. We apply the resulting noise budget analysis to a wide range
of existing and planned telescope systems that will operate between about 100
MHz and 5 GHz to ascertain the magnitude of the calibration challenges that
they must overcome to achieve thermal noise limited performance. We conclude
that calibration challenges are increased in several respects by small
dimensions of the dishes or aperture array stations. It will be more
challenging to achieve thermal noise limited performance using 15 m class
dishes rather than the 25 m dishes of current arrays. Some of the performance
risks are mitigated by the deployment of phased array feeds and more with the
choice of an (alt,az,pol) mount, although a larger dish diameter offers the
best prospects for risk mitigation. Many improvements to imaging performance
can be anticipated at the expense of greater complexity in calibration
algorithms. However, a fundamental limitation is ultimately imposed by an
insufficient number of data constraints relative to calibration variables. The
upcoming aperture array systems will be operating in a regime that has never
previously been addressed, where a wide range of effects are expected to exceed
the thermal noise by two to three orders of magnitude. Achieving routine
thermal noise limited imaging performance with these systems presents an
extreme challenge. The magnitude of that challenge is inversely related to the
aperture array station diameter.Comment: 27 pages, 24 figures, accepted in A&A, final versio
Prospects for measuring supermassive black hole masses with future extremely large telescopes
The next generation of giant-segmented mirror telescopes ( 20 m) will
enable us to observe galactic nuclei at much higher angular resolution and
sensitivity than ever before. These capabilities will introduce a revolutionary
shift in our understanding of the origin and evolution of supermassive black
holes by enabling more precise black hole mass measurements in a mass range
that is unreachable today. We present simulations and predictions of the
observations of nuclei that will be made with the Thirty Meter Telescope (TMT)
and the adaptive optics assisted integral-field spectrograph IRIS, which is
capable of diffraction-limited spectroscopy from band (0.9 m) to
band (2.2 m). These simulations, for the first time, use realistic values
for the sky, telescope, adaptive optics system, and instrument, to determine
the expected signal-to-noise ratio of a range of possible targets spanning
intermediate mass black holes of \msun to the most massive black
holes known today of . We find that IRIS will be able to
observe Milky Way-mass black holes out the distance of the Virgo cluster, and
will allow us to observe many more brightest cluster galaxies where the most
massive black holes are thought to reside. We also evaluate how well the
kinematic moments of the velocity distributions can be constrained at the
different spectral resolutions and plate scales designed for IRIS. We find that
a spectral resolution of will be necessary to measure the masses of
intermediate mass black holes. By simulating the observations of galaxies found
in SDSS DR7, we find that over massive black holes will be observable at
distances between with the estimated sensitivity and angular
resolution provided by access to -band (0.9 m) spectroscopy from IRIS
and the TMT adaptive optics system. (Abridged)Comment: 19 pages, 20 figures, accepted to A
Depth Fields: Extending Light Field Techniques to Time-of-Flight Imaging
A variety of techniques such as light field, structured illumination, and
time-of-flight (TOF) are commonly used for depth acquisition in consumer
imaging, robotics and many other applications. Unfortunately, each technique
suffers from its individual limitations preventing robust depth sensing. In
this paper, we explore the strengths and weaknesses of combining light field
and time-of-flight imaging, particularly the feasibility of an on-chip
implementation as a single hybrid depth sensor. We refer to this combination as
depth field imaging. Depth fields combine light field advantages such as
synthetic aperture refocusing with TOF imaging advantages such as high depth
resolution and coded signal processing to resolve multipath interference. We
show applications including synthesizing virtual apertures for TOF imaging,
improved depth mapping through partial and scattering occluders, and single
frequency TOF phase unwrapping. Utilizing space, angle, and temporal coding,
depth fields can improve depth sensing in the wild and generate new insights
into the dimensions of light's plenoptic function.Comment: 9 pages, 8 figures, Accepted to 3DV 201
Hybrid integration methods for on-chip quantum photonics
The goal of integrated quantum photonics is to combine components for the generation, manipulation, and detection of nonclassical light in a phase-stable and efficient platform. Solid-state quantum emitters have recently reached outstanding performance as single-photon sources. In parallel, photonic integrated circuits have been advanced to the point that thousands of components can be controlled on a chip with high efficiency and phase stability. Consequently, researchers are now beginning to combine these leading quantum emitters and photonic integrated circuit platforms to realize the best properties of each technology. In this paper, we review recent advances in integrated quantum photonics based on such hybrid systems. Although hybrid integration solves many limitations of individual platforms, it also introduces new challenges that arise from interfacing different materials. We review various issues in solid-state quantum emitters and photonic integrated circuits, the hybrid integration techniques that bridge these two systems, and methods for chip-based manipulation of photons and emitters. Finally, we discuss the remaining challenges and future prospects of on-chip quantum photonics with integrated quantum emitters. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreemen
Robust Detection of Moving Human Target in Foliage-Penetration Environment Based on Hough Transform
Attention has been focused on the robust moving human target detection in foliage-penetration environment, which presents a formidable task in a radar system because foliage is a rich scattering environment with complex multipath propagation and time-varying clutter. Generally, multiple-bounce returns and clutter are additionally superposed to direct-scatter echoes. They obscure true target echo and lead to poor visual quality time-range image, making target detection particular difficult. Consequently, an innovative approach is proposed to suppress clutter and mitigate multipath effects. In particular, a clutter suppression technique based on range alignment is firstly applied to suppress the time-varying clutter and the instable antenna coupling. Then entropy weighted coherent integration (EWCI) algorithm is adopted to mitigate the multipath effects. In consequence, the proposed method effectively reduces the clutter and ghosting artifacts considerably. Based on the high visual quality image, the target trajectory is detected robustly and the radial velocity is estimated accurately with the Hough transform (HT). Real data used in the experimental results are provided to verify the proposed method
Conceptual spatial representations for indoor mobile robots
We present an approach for creating conceptual representations of human-made indoor environments using mobile
robots. The concepts refer to spatial and functional properties of typical indoor environments. Following ļ¬ndings
in cognitive psychology, our model is composed of layers representing maps at diļ¬erent levels of abstraction. The
complete system is integrated in a mobile robot endowed with laser and vision sensors for place and object recognition.
The system also incorporates a linguistic framework that actively supports the map acquisition process, and which
is used for situated dialogue. Finally, we discuss the capabilities of the integrated system
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