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