1,203 research outputs found
Snap-n-Snack: a Food Image Recognition Application
Many people desire to be informed about the nutritional specifics of the food they consume. Current popular dietary tracking methods are too slow and tedious for a lot of consumers due to requiring manual data entry for everything eaten. We propose a system that will take advantage of image recognition and the internal camera of Android phones to identify food based off of a picture of a user’s plate. Over the course the last year, we trained an object detection model with images of different types of food, built a mobile application around it, and tested their integration and performance. We believe that our program meets the requirements we set out for it at its conception and delivers a simple, fast, and efficient way of tracking one’s diet
Noise and disturbance in quantum measurements: an information-theoretic approach
We introduce information-theoretic definitions for noise and disturbance in
quantum measurements and prove a state-independent noise-disturbance tradeoff
relation that these quantities have to satisfy in any conceivable setup.
Contrary to previous approaches, the information-theoretic quantities we define
are invariant under relabelling of outcomes, and allow for the possibility of
using quantum or classical operations to `correct' for the disturbance. We also
show how our bound implies strong tradeoff relations for mean square
deviations.Comment: v3: to appear on PRL (some issues fixed, supplemental material
expanded). v2: replaced with submitted version; 5 two-column pages + 6
one-column pages + 3 figures; one issue corrected and few references added.
v1: 17 pages, 3 figure
On the Confidence in Bit-Alias Measurement of Physical Unclonable Functions
Physical Unclonable Functions (PUFs) are modern solutions for cheap and
secure key storage. The security level strongly depends on a PUF's
unpredictability, which is impaired if certain bits of the PUF response tend
towards the same value on all devices. The expectation for the probability of 1
at some position in the response, the Bit-Alias, is a state-of-the-art metric
in this regard. However, the confidence interval of the Bit-Alias is never
considered, which can lead to an overestimation of a PUF's unpredictability.
Moreover, no tool is available to verify if the Bit-Alias is within given
limits. This work adapts a method for the calculation of confidence intervals
to Bit-Alias. It further proposes a statistical hypothesis test to verify if a
PUF design meets given specifications on Bit-Alias or bit-wise entropy.
Application to several published PUF designs demonstrates the methods'
capabilities. The results prove the need for a high number of samples when the
unpredictability of PUFs is tested. The proposed methods are publicly available
and should improve the design and evaluation of PUFs in the future.Comment: Original publication at 2019 17th IEEE International New Circuits and
Systems Conference (NEWCAS
Design and Evaluation of a Collective IO Model for Loosely Coupled Petascale Programming
Loosely coupled programming is a powerful paradigm for rapidly creating
higher-level applications from scientific programs on petascale systems,
typically using scripting languages. This paradigm is a form of many-task
computing (MTC) which focuses on the passing of data between programs as
ordinary files rather than messages. While it has the significant benefits of
decoupling producer and consumer and allowing existing application programs to
be executed in parallel with no recoding, its typical implementation using
shared file systems places a high performance burden on the overall system and
on the user who will analyze and consume the downstream data. Previous efforts
have achieved great speedups with loosely coupled programs, but have done so
with careful manual tuning of all shared file system access. In this work, we
evaluate a prototype collective IO model for file-based MTC. The model enables
efficient and easy distribution of input data files to computing nodes and
gathering of output results from them. It eliminates the need for such manual
tuning and makes the programming of large-scale clusters using a loosely
coupled model easier. Our approach, inspired by in-memory approaches to
collective operations for parallel programming, builds on fast local file
systems to provide high-speed local file caches for parallel scripts, uses a
broadcast approach to handle distribution of common input data, and uses
efficient scatter/gather and caching techniques for input and output. We
describe the design of the prototype model, its implementation on the Blue
Gene/P supercomputer, and present preliminary measurements of its performance
on synthetic benchmarks and on a large-scale molecular dynamics application.Comment: IEEE Many-Task Computing on Grids and Supercomputers (MTAGS08) 200
Many-Task Computing and Blue Waters
This report discusses many-task computing (MTC) generically and in the
context of the proposed Blue Waters systems, which is planned to be the largest
NSF-funded supercomputer when it begins production use in 2012. The aim of this
report is to inform the BW project about MTC, including understanding aspects
of MTC applications that can be used to characterize the domain and
understanding the implications of these aspects to middleware and policies.
Many MTC applications do not neatly fit the stereotypes of high-performance
computing (HPC) or high-throughput computing (HTC) applications. Like HTC
applications, by definition MTC applications are structured as graphs of
discrete tasks, with explicit input and output dependencies forming the graph
edges. However, MTC applications have significant features that distinguish
them from typical HTC applications. In particular, different engineering
constraints for hardware and software must be met in order to support these
applications. HTC applications have traditionally run on platforms such as
grids and clusters, through either workflow systems or parallel programming
systems. MTC applications, in contrast, will often demand a short time to
solution, may be communication intensive or data intensive, and may comprise
very short tasks. Therefore, hardware and software for MTC must be engineered
to support the additional communication and I/O and must minimize task dispatch
overheads. The hardware of large-scale HPC systems, with its high degree of
parallelism and support for intensive communication, is well suited for MTC
applications. However, HPC systems often lack a dynamic resource-provisioning
feature, are not ideal for task communication via the file system, and have an
I/O system that is not optimized for MTC-style applications. Hence, additional
software support is likely to be required to gain full benefit from the HPC
hardware
The Economics of Tax Compliance: Fact and Fantasy
This paper reviews the current state of theoretical and empirical knowledge regarding compliance with the federal income tax laws. We focus on the validity of certain myths that have come to dominate tax compliance discussions. Toward that end, we discuss three general categories--empirical work, theoretical methodology and fiscal policy recommendations--that seem to require more careful assessment and formulation
Searchaton: a gamified, team-based on-site teaching format for literature searching for medical students
The Medical Faculty and the University Medical Library of the University of Basel jointly developed a new learning unit called Searchaton. This learning unit aimed at providing knowledge for the point-of-care literature search in everyday clinical practice. To make this as practical and customer-oriented as possible, the faculty and library interacted closely with medical experts. During the Searchaton, the task was to translate a patient case into a clinical question and to find an answer to that question. The format combined collaborative working and gamification with an aspect of time pressure to better reflect everyday clinical situations. The participants benefited greatly from the intensive support and were able to assess their searching skills in the context of evidence-based clinical decision-making
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