4,740 research outputs found
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M2U-net: Effective and efficient retinal vessel segmentation for real-world applications
In this paper, we present a novel neural network architecture for retinal vessel segmentation that improves over the state of the art on two benchmark datasets, is the first to run in real time on high resolution images, and its small memory and processing requirements make it deployable in mobile and embedded systems. The M2U-Net has a new encoder-decoder architecture that is inspired by the U-Net. It adds pretrained components of MobileNetV2 in the encoder part and novel contractive bottleneck blocks in the decoder part that, combined with bilinear upsampling, drastically reduce the parameter count to 0.55M compared to 31.03M in the original U-Net. We have evaluated its performance against a wide body of previously published results on three public datasets. On two of them, the M2U-Net achieves new state-of-the-art performance by a considerable margin. When implemented on a GPU, our method is the first to achieve real-time inference speeds on high-resolution fundus images. We also implemented our proposed network on an ARM-based embedded system where it segments images in between 0.6 and 15 sec, depending on the resolution. Thus, the M2U-Net enables a number of applications of retinal vessel structure extraction, such as early diagnosis of eye diseases, retinal biometric authentication systems, and robot assisted microsurgery
Line shape analysis of the K transition in muonic hydrogen
The K transition in muonic hydrogen was measured with a
high-resolution crystal spectrometer. The spectrum is shown to be sensitive to
the ground-state hyperfine splitting, the corresponding triplet-to-singlet
ratio, and the kinetic energy distribution in the state. The hyperfine
splitting and triplet-to-singlet ratio are found to be consistent with the
values expected from theoretical and experimental investigations and,
therefore, were fixed accordingly in order to reduce the uncertainties in the
further reconstruction of the kinetic energy distribution. The presence of
high-energetic components was established and quantified in both a
phenomenological, i.e. cascade-model-free fit, and in a direct deconvolution of
the Doppler broadening based on the Bayesian approach.Comment: 22 pages, 21 figure
Geosystemics View of Earthquakes
Earthquakes are the most energetic phenomena in the lithosphere: their study
and comprehension are greatly worth doing because of the obvious importance for society.
Geosystemics intends to study the Earth system as a whole, looking at the possible couplings among
the different geo-layers, i.e., from the earth’s interior to the above atmosphere. It uses specific universal
tools to integrate different methods that can be applied to multi-parameter data, often taken on different
platforms (e.g., ground,marine or satellite observations). Itsmain objective is to understand the particular
phenomenon of interest from a holistic point of view. Central is the use of entropy, together with other
physical quantities that will be introduced case by case. In this paper, we will deal with earthquakes,
as final part of a long-term chain of processes involving, not only the interaction between different
components of the Earth’s interior but also the coupling of the solid earth with the above neutral
or ionized atmosphere, and finally culminating with the main rupture along the fault of concern.
Particular emphasis will be given to some Italian seismic sequences.Publishedid 4121A. Geomagnetismo e PaleomagnetismoJCR Journa
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Context-awareness for mobile sensing: a survey and future directions
The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions
Link Scheduling in UAV-Aided Networks
Unmanned Aerial Vehicles (UAVs) or drones are a type of low altitude aerial mobile vehicles. They can be integrated into existing networks; e.g., cellular, Internet of Things (IoT) and satellite networks. Moreover, they can leverage existing cellular or Wi-Fi infrastructures to communicate with one another. A popular application of UAVs is to deploy them as mobile base stations and/or relays to assist terrestrial wireless communications. Another application is data collection, whereby they act as mobile sinks for wireless sensor networks or sensor devices operating in IoT networks. Advantageously, UAVs are cost-effective and they are able to establish line-of-sight links, which help improve data rate. A key concern, however, is that the uplink communications to a UAV may be limited, where it is only able to receive from one device at a time. Further, ground devices, such as those in IoT networks, may have limited energy, which limit their transmit power. To this end, there are three promising approaches to address these concerns, including (i) trajectory optimization, (ii) link scheduling, and (iii) equipping UAVs with a Successive Interference Cancellation (SIC) radio.
Henceforth, this thesis considers data collection in UAV-aided, TDMA and SICequipped wireless networks. Its main aim is to develop novel link schedulers to schedule uplink communications to a SIC-capable UAV. In particular, it considers two types of networks: (i) one-tier UAV communications networks, where a SIC-enabled rotary-wing UAV collects data from multiple ground devices, and (ii) Space-Air-Ground Integrated Networks (SAGINs), where a SIC-enabled rotary-wing UAV offloads collected data from ground devices to a swarm of CubeSats. A CubeSat then downloads its data to a terrestrial gateway. Compared to one-tier UAV communications networks, SAGINs are able to provide wide coverage and seamless connectivity to ground devices in remote and/or sparsely populated areas
OEXP Analysis Tools Workshop
This publication summarizes the software needs and available analysis tools presented at the OEXP Analysis Tools Workshop held at the NASA Langley Research Center, Hampton, Virginia on June 21 to 22, 1988. The objective of the workshop was to identify available spacecraft system (and subsystem) analysis and engineering design tools, and mission planning and analysis software that could be used for various NASA Office of Exploration (code Z) studies, specifically lunar and Mars missions
Research and Education in Computational Science and Engineering
Over the past two decades the field of computational science and engineering
(CSE) has penetrated both basic and applied research in academia, industry, and
laboratories to advance discovery, optimize systems, support decision-makers,
and educate the scientific and engineering workforce. Informed by centuries of
theory and experiment, CSE performs computational experiments to answer
questions that neither theory nor experiment alone is equipped to answer. CSE
provides scientists and engineers of all persuasions with algorithmic
inventions and software systems that transcend disciplines and scales. Carried
on a wave of digital technology, CSE brings the power of parallelism to bear on
troves of data. Mathematics-based advanced computing has become a prevalent
means of discovery and innovation in essentially all areas of science,
engineering, technology, and society; and the CSE community is at the core of
this transformation. However, a combination of disruptive
developments---including the architectural complexity of extreme-scale
computing, the data revolution that engulfs the planet, and the specialization
required to follow the applications to new frontiers---is redefining the scope
and reach of the CSE endeavor. This report describes the rapid expansion of CSE
and the challenges to sustaining its bold advances. The report also presents
strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie
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