3,781 research outputs found
Sound Source Localization in a Multipath Environment Using Convolutional Neural Networks
The propagation of sound in a shallow water environment is characterized by
boundary reflections from the sea surface and sea floor. These reflections
result in multiple (indirect) sound propagation paths, which can degrade the
performance of passive sound source localization methods. This paper proposes
the use of convolutional neural networks (CNNs) for the localization of sources
of broadband acoustic radiated noise (such as motor vessels) in shallow water
multipath environments. It is shown that CNNs operating on cepstrogram and
generalized cross-correlogram inputs are able to more reliably estimate the
instantaneous range and bearing of transiting motor vessels when the source
localization performance of conventional passive ranging methods is degraded.
The ensuing improvement in source localization performance is demonstrated
using real data collected during an at-sea experiment.Comment: 5 pages, 5 figures, Final draft of paper submitted to 2018 IEEE
International Conference on Acoustics, Speech and Signal Processing (ICASSP)
15-20 April 2018 in Calgary, Alberta, Canada. arXiv admin note: text overlap
with arXiv:1612.0350
Cryptographically Secure Information Flow Control on Key-Value Stores
We present Clio, an information flow control (IFC) system that transparently
incorporates cryptography to enforce confidentiality and integrity policies on
untrusted storage. Clio insulates developers from explicitly manipulating keys
and cryptographic primitives by leveraging the policy language of the IFC
system to automatically use the appropriate keys and correct cryptographic
operations. We prove that Clio is secure with a novel proof technique that is
based on a proof style from cryptography together with standard programming
languages results. We present a prototype Clio implementation and a case study
that demonstrates Clio's practicality.Comment: Full version of conference paper appearing in CCS 201
Leveraging HPC Profiling & Tracing Tools to Understand the Performance of Particle-in-Cell Monte Carlo Simulations
Large-scale plasma simulations are critical for designing and developing
next-generation fusion energy devices and modeling industrial plasmas. BIT1 is
a massively parallel Particle-in-Cell code designed for specifically studying
plasma material interaction in fusion devices. Its most salient characteristic
is the inclusion of collision Monte Carlo models for different plasma species.
In this work, we characterize single node, multiple nodes, and I/O performances
of the BIT1 code in two realistic cases by using several HPC profilers, such as
perf, IPM, Extrae/Paraver, and Darshan tools. We find that the BIT1 sorting
function on-node performance is the main performance bottleneck. Strong scaling
tests show a parallel performance of 77% and 96% on 2,560 MPI ranks for the two
test cases. We demonstrate that communication, load imbalance and
self-synchronization are important factors impacting the performance of the
BIT1 on large-scale runs.Comment: Accepted by the Euro-Par 2023 workshops (TDLPP 2023), prepared in the
standardized Springer LNCS format and consists of 12 pages, which includes
the main text, references, and figure
The TRiC/CCT chaperone is implicated in Alzheimer's disease based on patient GWAS and an RNAi screen in Aβ-expressing Caenorhabditis elegans.
The human Aβ peptide causes progressive paralysis when expressed in the muscles of the nematode worm, C. elegans. We have exploited this model of Aβ toxicity by carrying out an RNAi screen to identify genes whose reduced expression modifies the severity of this locomotor phenotype. Our initial finding was that none of the human orthologues of these worm genes is identical with the genome-wide significant GWAS genes reported to date (the "white zone"); moreover there was no identity between worm screen hits and the longer list of GWAS genes which included those with borderline levels of significance (the "grey zone"). This indicates that Aβ toxicity should not be considered as equivalent to sporadic AD. To increase the sensitivity of our analysis, we then considered the physical interactors (+1 interactome) of the products of the genes in both the worm and the white+grey zone lists. When we consider these worm and GWAS gene lists we find that 4 of the 60 worm genes have a +1 interactome overlap that is larger than expected by chance. Two of these genes form a chaperonin complex, the third is closely associated with this complex and the fourth gene codes for actin, the major substrate of the same chaperonin
Light field image denoising using a linear 4D frequency-hyperfan all-in-focus filter
Imaging in low light is problematic as sensor noise can dominate imagery, and increasing illumination or aperture size is not always effective or practical. Computational photography offers a promising solution in the form of the light field camera, which by capturing redundant information offers an opportunity for elegant noise rejection. We show that the light field of a Lambertian scene has a 4D hyperfan-shaped frequency-domain region of support at the intersection of a dual-fan and a hypercone. By designing and implementing a filter with appropriately shaped passband we accomplish denoising with a single all-in-focus linear filter. Drawing examples from the Stanford Light Field Archive and images captured using a commercially available lenselet-based plenoptic camera, we demonstrate that the hyperfan outperforms competing methods including synthetic focus, fan-shaped antialiasing filters, and a range of modern nonlinear image and video denoising techniques. We show the hyperfan preserves depth of field, making it a single-step all-in-focus denoising filter suitable for general-purpose light field rendering. We include results for different noise types and levels, over a variety of metrics, and in real-world scenarios. Finally, we show that the hyperfan’s performance scales with aperture count. 1
Organic acidurias: Major gaps, new challenges, and a yet unfulfilled promise
Organic acidurias (OADs) comprise a biochemically defined group of inherited metabolic diseases. Increasing awareness, reliable diagnostic work-up, newborn screening programs for some OADs, optimized neonatal and intensive care, and the development of evidence-based recommendations have improved neonatal survival and short-term outcome of affected individuals. However, chronic progression of organ dysfunction in an aging patient population cannot be reliably prevented with traditional therapeutic measures. Evidence is increasing that disease progression might be best explained by mitochondrial dysfunction. Previous studies have demonstrated that some toxic metabolites target mitochondrial proteins inducing synergistic bioenergetic impairment. Although these potentially reversible mechanisms help to understand the development of acute metabolic decompensations during catabolic state, they currently cannot completely explain disease progression with age. Recent studies identified unbalanced autophagy as a novel mechanism in the renal pathology of methylmalonic aciduria, resulting in impaired quality control of organelles, mitochondrial aging and, subsequently, progressive organ dysfunction. In addition, the discovery of post-translational short-chain lysine acylation of histones and mitochondrial enzymes helps to understand how intracellular key metabolites modulate gene expression and enzyme function. While acylation is considered an important mechanism for metabolic adaptation, the chronic accumulation of potential substrates of short-chain lysine acylation in inherited metabolic diseases might exert the opposite effect, in the long run. Recently, changed glutarylation patterns of mitochondrial proteins have been demonstrated in glutaric aciduria type 1. These new insights might bridge the gap between natural history and pathophysiology in OADs, and their exploitation for the development of targeted therapies seems promising
Mid-water current aided localization for autonomous underwater vehicles
Author Posting. © The Author(s), 2015. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Autonomous Robots 40 (2016): 1207–1227, doi:10.1007/s10514-016-9547-3.Survey-class Autonomous Underwater Vehi-
cles (AUVs) typically rely on Doppler Velocity Logs
(DVL) for precision localization near the seafloor. In
cases where the seafloor depth is greater than the DVL
bottom-lock range, localizing between the surface and
the seafloor presents a localization problem since both
GPS and DVL observations are unavailable in the mid-
water column. This work proposes a solution to this
problem that exploits the fact that current profile layers
of the water column are near constant over short time
scales (in the scale of minutes). Using observations of
these currents obtained with the Acoustic Doppler Cur-
rent Profiler (ADCP) mode of the DVL during descent,
along with data from other sensors, the method dis-
cussed herein constrains position error. The method is
validated using field data from the Sirius AUV coupled
with view-based Simultaneous Localization and Map-
ping (SLAM) and on descents up to 3km deep with the
Sentry AUV.This work is supported in part by NCRIS IMOS, the
Australian Research Council (ARC), the New South
Wales Government and the Woods Hole Oceanographic
Institution.2017-02-1
Biometric assessment of deep-sea vent megabenthic communities using multi-resolution 3D image reconstructions
This paper describes a method to survey the distribution of megabenthos over multi-hectare regions of the seafloor. Quantitative biomass estimates are made by combining high-resolution 3D image reconstructions, used to model spatial relationships between representative taxa, with lower-resolution reconstructions taken over a wider area in which the distribution of larger predatory animals can be observed. The method is applied to a region of the Iheya North field that was the target of scientific drilling during the IODP Expedition 331 in 2010. An area of 2.5 ha was surveyed 3 years and 4 months after the site was drilled. More than 100,000 organisms from 6 taxa were identified. The visible effects of drilling on the distribution of megabenthos were confined to a 20 m radius of the artificially created hydrothermal discharges, with the associated densities of biomass lower than observed in nearby naturally discharging areas
Towards a macroscope : leveraging technology to transform the breadth, scale and resolution of macroecological data
M.D. is grateful for support from the Templeton Foundation (grant #60501, “Putting the Extended Evolutionary Synthesis to the Test”) and from a Leverhulme Trust Fellowship.The problem Earth‐based observations of the biosphere are spatially biased in ways that can limit our ability to detect macroecological patterns and changes in biodiversity. To resolve this problem, we need to supplement the ad hoc data currently collected with planned biodiversity monitoring, in order to approximate global stratified random sampling of the planet. We call this all‐encompassing observational system ‘the macroscope’. The solution With a focus on the marine realm, we identify seven main biosphere observation tools that compose the macroscope: satellites, drones, camera traps, passive acoustic samplers, biologgers, environmental DNA and human observations. By deploying a nested array of these tools that fills current gaps in monitoring, we can achieve a macroscope fit for purpose and turn these existing powerful tools into more than the sum of their parts. An appeal Building a macroscope requires commitment from many fields, together with coordinated actions to attract the level of funding required for such a venture. We call on macroecologists to become advocates for the macroscope and to engage with existing global observation networks.PostprintPeer reviewe
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