7,203 research outputs found
Neural Networks for Modeling and Control of Particle Accelerators
We describe some of the challenges of particle accelerator control, highlight
recent advances in neural network techniques, discuss some promising avenues
for incorporating neural networks into particle accelerator control systems,
and describe a neural network-based control system that is being developed for
resonance control of an RF electron gun at the Fermilab Accelerator Science and
Technology (FAST) facility, including initial experimental results from a
benchmark controller.Comment: 21 p
Assessing Human Error Against a Benchmark of Perfection
An increasing number of domains are providing us with detailed trace data on
human decisions in settings where we can evaluate the quality of these
decisions via an algorithm. Motivated by this development, an emerging line of
work has begun to consider whether we can characterize and predict the kinds of
decisions where people are likely to make errors.
To investigate what a general framework for human error prediction might look
like, we focus on a model system with a rich history in the behavioral
sciences: the decisions made by chess players as they select moves in a game.
We carry out our analysis at a large scale, employing datasets with several
million recorded games, and using chess tablebases to acquire a form of ground
truth for a subset of chess positions that have been completely solved by
computers but remain challenging even for the best players in the world.
We organize our analysis around three categories of features that we argue
are present in most settings where the analysis of human error is applicable:
the skill of the decision-maker, the time available to make the decision, and
the inherent difficulty of the decision. We identify rich structure in all
three of these categories of features, and find strong evidence that in our
domain, features describing the inherent difficulty of an instance are
significantly more powerful than features based on skill or time.Comment: KDD 2016; 10 page
Global communication part 1: the use of apparel CAD technology
Trends needed for improved communication systems, through the development of future computer-aided design technology (CAD) applications, is a theme that has received attention due to its perceived benefits in improving global supply chain efficiencies. This article discusses the developments of both 2D and 3D computer-aided design capabilities, found within global fashion supply chain relationships and environments. Major characteristics identified within the data suggest that CAD/CAM technology appears to be improving; however, evidence also suggest a plateau effect, which is accrediting forced profits towards information technology manufactures, and arguably compromising the industry's competitive advantage. Nevertheless, 2D CAD increases communication speed; whereas 3D human interaction technology is seen to be evolving slowly and questionably with limited success. The article discusses the findings and also presents the issues regarding human interaction; technology education; and individual communication enhancements using technology processes. These are still prevalent topics for the future developments of global strategy and cultural communication amalgamation
Randomly Broken Nuclei and Disordered Systems
Similarities between models of fragmenting nuclei and disordered systems in
condensed matter suggest corresponding methods. Several theoretical models of
fragmentation investigated in this fashion show marked differences, indicating
possible new methods for distinguishing models using yield data. Applying
nuclear methods to disordered systems also yields interesting results.Comment: 10 pages, 4 figure
Pseudocraters on Mars
The morphology and origin of the Martian volcanic-dome like structures are compared to the terrestial pseudocraters
1863-11-25 Chaplain B.A. Chase informs Governor Coburn that a petition on behalf of Captain Robert Gray may have been maliciously withheld
https://digitalmaine.com/cw_me_4th_regiment_corr/1447/thumbnail.jp
1864-05-03 Chaplain B.A. Chase will provide a photograph for General Hodsdon\u27s Illustrated Roster of Officers when he returns home
https://digitalmaine.com/cw_me_4th_regiment_corr/1503/thumbnail.jp
Attribute-Based Encryption Optimized for Cloud Computing
Abstract. In this work, we aim to make attribute-based encryption (ABE) more suitable for access control to data stored in the cloud. For this purpose, we concentrate on giving to the encryptor full control over the access rights, providing feasible key management even in case of multiple independent authorities, and enabling viable user revocation, which is essential in practice. Our main result is an extension of the decentralized CP-ABE scheme of Lewko and Waters [LW11] with identity-based user revocation. Our revocation system is made feasible by removing the computational burden of a revocation event from the cloud service provider, at the expense of some permanent, yet acceptable overhead of the encryption and decryption algorithms run by the users. Thus, the computation overhead is distributed over a potentially large number of users, instead of putting it on a single party (e.g., a proxy server), which would easily lead to a performance bottleneck. Besides describing our scheme, we also give a formal proof of its security in the generic bilinear group and random oracle models.
Cognitive processes that indirectly affect olfactory dysfunction in Parkinson\u27s disease
Introduction Accurate early diagnosis of Parkinson\u27s disease is hampered by its long prodromal period and the variable manifestations of its motor symptoms. While olfactory dysfunction can occur before motor-symptom onset and serve as a non-disease-specific diagnostic aid, its underlying causes are incompletely understood.
Methods Correlation analyses, univariate density estimates, ANOVA and regression evaluated relationships between scores on the Montreal Cognitive Assessment and Hopkins Verbal Learning Test and those on the University of Pennsylvania Smell Identification Test in 1280 Parkinson\u27s Progression Markers Initiative subjects placed into five diagnostic categories. Structural equation modeling identified cognitive measures having significant indirect effects on olfactory-function-test scores.
Results Global cognition, verbal learning and memory, attention, delayed-recall, and visuospatial/executive function scores show weak-to-moderate, significant associations with olfactory-function-test scores. Associations are stronger in symptomatic than asymptomatic subjects having mutations in LRRK2, GBA or SNCA. Score distributions are nonuniform across diagnostic categories. Linear regression found that all cognitive measures except attention predicted olfactory-function-test scores. Three structural equation models assessing indirect effects of verbal learning/memory with either global cognition, visuospatial/executive function, or delayed-recall had a good statistical fit to the data. Only verbal learning/memory scores significantly help explain olfactory-function-test scores in all symptomatic diagnostic categories (−0.56 \u3c b \u3c −0.23, 0.001 \u3c P \u3c .005). Visuospatial/executive-function test scores help explain olfactory-function-test scores in both genetic Parkinson\u27s disease diagnostic categories (−0.25 \u3c b \u3c −0.17, 0.032 \u3c P \u3c .033).
Conclusion Impaired verbal learning/memory and visuospatial/executive function contributes to lower performance on olfactory function tests in Parkinson\u27s disease. As both of these domains impact decision-making, decision-making in turn may impact olfactory assessment in Parkinson\u27s disease
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