A review of the state-of-the-art of wireless SHM systems and an experimental set-up towards an improved design

2004 ◽

Cited By ~ 11

Author(s):

Mehernosh Irani ◽

Lyle Finn

Keyword(s):

Gulf Of Mexico ◽

Model Test ◽

State Of The Art ◽

Model Testing ◽

Model Tests ◽

The State ◽

Test Results ◽

Test Set ◽

Vortex Induced Vibrations ◽

Set Up

The state-of-the art in model testing for Vortex Induced Vibrations (VIV) of Spars is presented. Important issues related to Spar VIV model testing are highlighted. The parameters that need to be modeled including hull geometry, strake configuration, mass and mooring properties and, considerations of test set-up and instrumentation are discussed. Results are presented from model tests of an as-built Spar deployed in the Gulf of Mexico. It is shown that the model test results compare well with the VIV responses measured in the field.

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Seeking for the Maximum Symmetric Rank

Mathematics ◽

10.3390/math6110247 ◽

2018 ◽

Vol 6 (11) ◽

pp. 247 ◽

Cited By ~ 1

Author(s):

Alessandro De Paris

Keyword(s):

State Of The Art ◽

Symmetric Tensor ◽

Upper Bounds ◽

The State ◽

Tensor Rank ◽

Symmetric Tensors ◽

Lower And Upper Bounds ◽

Symmetric Tensor Rank ◽

Set Up ◽

Divided Powers

We present the state-of-the-art on maximum symmetric tensor rank, for each given dimension and order. After a general discussion on the interplay between symmetric tensors, polynomials and divided powers, we introduce the technical environment and the methods that have been set up in recent times to find new lower and upper bounds.

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Automated and Formal Synthesis of Neural Barrier Certificates for Dynamical Models

Tools and Algorithms for the Construction and Analysis of Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-030-72016-2_20 ◽

2021 ◽

pp. 370-388

Author(s):

Andrea Peruffo ◽

Daniele Ahmed ◽

Alessandro Abate

Keyword(s):

Neural Network ◽

State Of The Art ◽

The State ◽

Dynamical Models ◽

Safety Verification ◽

Data Set ◽

New Approach ◽

Formal Synthesis ◽

Numerical Robustness ◽

Set Up

AbstractWe introduce an automated, formal, counterexample-based approach to synthesise Barrier Certificates (BC) for the safety verification of continuous and hybrid dynamical models. The approach is underpinned by an inductive framework: this is structured as a sequential loop between a learner, which manipulates a candidate BC structured as a neural network, and a sound verifier, which either certifies the candidate’s validity or generates counter-examples to further guide the learner. We compare the approach against state-of-the-art techniques, over polynomial and non-polynomial dynamical models: the outcomes show that we can synthesise sound BCs up to two orders of magnitude faster, with in particular a stark speedup on the verification engine (up to three orders less), whilst needing a far smaller data set (up to three orders less) for the learning part. Beyond improvements over the state of the art, we further challenge the new approach on a hybrid dynamical model and on larger-dimensional models, and showcase the numerical robustness of our algorithms and codebase.

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OpenClinicalAI: enabling AI to diagnose diseases in real-world clinical settings

10.1101/2021.09.08.21263249 ◽

2021 ◽

Author(s):

Yunyou Huang ◽

Nana Wang ◽

Suqin Tang ◽

Li Ma ◽

Tianshu Hao ◽

...

Keyword(s):

Real World ◽

State Of The Art ◽

The State ◽

Clinical Settings ◽

Medical Systems ◽

Learning Framework ◽

Personalized Diagnosis ◽

Set Up ◽

Art And State ◽

Unnecessary Testing

This paper quantitatively reveals the state-of-the-art and state-of-the-practice AI systems only achieve acceptable performance on the stringent conditions that all categories of subjects are known, which we call closed clinical settings, but fail to work in real-world clinical settings. Compared to the diagnosis task in the closed setting, real-world clinical settings pose severe challenges, and we must treat them differently. We build a clinical AI benchmark named Clinical AIBench to set up real-world clinical settings to facilitate researches. We propose an open, dynamic machine learning framework and develop an AI system named OpenClinicalAI to diagnose diseases in real-world clinical settings. The first versions of Clinical AIBench and OpenClinicalAI target Alzheimer's disease. In the real-world clinical setting, OpenClinicalAI significantly outperforms the state-of-the-art AI system. In addition, OpenClinicalAI develops personalized diagnosis strategies to avoid unnecessary testing and seamlessly collaborates with clinicians. It is promising to be embedded in the current medical systems to improve medical services.

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Practical Picture Processing

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100051700 ◽

1974 ◽

Vol 32 ◽

pp. 338-339

Author(s):

T. A. Welton

Keyword(s):

Radiation Damage ◽

Coherence Length ◽

Spatial Information ◽

State Of The Art ◽

Coherent Radiation ◽

The State ◽

Energy Spread ◽

Electron Micrograph ◽

Picture Processing ◽

Molecular Skeleton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.

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