Standardized test

Summary

A standardized test is a test that is administered and scored in a consistent, or "standard", manner. Standardized tests are designed in such a way that the questions and interpretations are consistent and are administered and scored in a predetermined, standard manner. Any test in which the same test is given in the same manner to all test takers, and graded in the same manner for everyone, is a standardized test. Standardized tests do not need to be high-stakes tests, time-limited tests, or multiple-choice tests. A standardized test may be any type of test: a written test, an oral test, or a practical skills performance test. The questions can be simple or complex. The subject matter among school-age students is frequently academic skills, but a standardized test can be given on nearly any topic, including driving tests, creativity, athleticism, personality, professional ethics, or other attributes. The opposite of standardized testing is non-standardized testing, in which eith

Official source

https://en.wikipedia.org/wiki/Standardized_test

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Open Source Brain: A Collaborative Resource for Visualizing, Analyzing, Simulating, and Developing Standardized Models of Neurons and Circuits

Matteo Cantarelli, András Ecker, Michael Lee Hines, Sergio Solinas, Werner Alfons Hilda Van Geit

Computational models are powerful tools for exploring the properties of complex biological systems. In neuroscience, data-driven models of neural circuits that span multiple scales are increasingly being used to understand brain function in health and disease. But their adoption and reuse has been limited by the specialist knowledge required to evaluate and use them. To address this, we have developed Open Source Brain, a platform for sharing, viewing, analyzing, and simulating standardized models from different brain regions and species. Model structure and parameters can be automatically visualized and their dynamical properties explored through browser-based simulations. Infrastructure and tools for collaborative interaction, development, and testing are also provided. We demonstrate how existing components can be reused by constructing new models of inhibition-stabilized cortical networks that match recent experimental results. These features of Open Source Brain improve the accessibility, transparency, and repro-ducibility of models and facilitate their reuse by the wider community.

CELL PRESS2019

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A primary aim of RILEM TC 267-TRM: Tests for Reactivity of Supplementary Cementitious Materials (SCMs) is to compare and evaluate the performance of conventional and novel SCM reactivity test methods across a wide range of SCMs. To this purpose, a round robin campaign was organized to investigate 10 different tests for reactivity and 11 SCMs covering the main classes of materials in use, such as granulated blast furnace slag, fly ash, natural pozzolan and calcined clays. The methods were evaluated based on the correlation to the 28days relative compressive strength of standard mortar bars containing 30% of SCM as cement replacement and the interlaboratory reproducibility of the test results. It was found that only a few test methods showed acceptable correlation to the 28days relative strength over the whole range of SCMs. The methods that showed the best reproducibility and gave good correlations used the R-3 model system of the SCM and Ca(OH)(2), supplemented with alkali sulfate/carbonate. The use of this simplified model system isolates the reaction of the SCM and the reactivity can be easily quantified from the heat release or bound water content. Later age (90days) strength results also correlated well with the results of the IS 1727 (Indian standard) reactivity test, an accelerated strength test using an SCM/Ca(OH)(2)-based model system. The current standardized tests did not show acceptable correlations across all SCMs, although they performed better when latently hydraulic materials (blast furnace slag) were excluded. However, the Frattini test, Chapelle and modified Chapelle test showed poor interlaboratory reproducibility, demonstrating experimental difficulties. The TC 267-TRM will pursue the development of test protocols based on the R-3 model systems. Acceleration and improvement of the reproducibility of the IS 1727 test will be attempted as well.

SPRINGER2018

Probabilistic Atlases to Enforce Topological Constraints

Pascal Fua, Graham Knott, Pamuditha Udaranga Wickramasinghe

Probabilistic atlases (PAs) have long been used in standard segmentation approaches and, more recently, in conjunction with Convolutional Neural Networks (CNNs). However, their use has been restricted to relatively standardized structures such as the brain or heart which have limited or predictable range of deformations. Here we propose an encoding-decoding CNN architecture that can exploit rough atlases that encode only the topology of the target structures that can appear in any pose and have arbitrarily complex shapes to improve the segmentation results. It relies on the output of the encoder to compute both the pose parameters used to deform the atlas and the segmentation mask itself, which makes it effective and end-to-end trainable.

2019