Results 51 to 60 of about 169,559 (249)

EbbRT: Elastic Building Block Runtime - case studies [PDF]

, 2015
We present a new systems runtime, EbbRT, for cloud hosted applications. EbbRT takes a different approach to the role operating systems play in cloud computing.
Appavoo, Jonathan, Cadden, James, Krieger, Orran, Schatzberg, Dan   +3 more
core   +1 more source

Reproducible Experiment Platform

, 2015
Data analysis in fundamental sciences nowadays is an essential process that pushes frontiers of our knowledge and leads to new discoveries. At the same time we can see that complexity of those analyses increases fast due to a)~enormous volumes of ...
Baranov, Alexander, Khairullin, Egor, Likhomanenko, Tatiana, Rogozhnikov, Alex, Ustyuzhanin, Andrey   +4 more
core   +1 more source

Teaching Python with team‐based learning: using cloud‐based notebooks for interactive coding education

FEBS Open Bio, EarlyView.
This study presents a novel approach to teaching Python and bioinformatics using team‐based learning and cloud‐hosted notebooks. By integrating interactive coding into biomedical education, the method improves accessibility, student engagement, and confidence—especially for those without a computing background.
Nuno S. Osório, Leonardo D. Garma
wiley   +1 more source

The MSA Atrophy Index (MSA‐AI): An Imaging Marker for Diagnosis and Clinical Progression in Multiple System Atrophy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Reliable biomarkers are essential for tracking disease progression and advancing treatments for multiple system atrophy (MSA). In this study, we propose the MSA Atrophy Index (MSA‐AI), a novel composite volumetric measure to distinguish MSA from related disorders and monitor disease progression. Methods Seventeen participants with an
Paula Trujillo, Kilian Hett, Amy Cooper, Amy E. Brown, Jessica Iregui, Manus J. Donahue, M. Erik Landman, Italo Biaggioni, Margaret Bradbury, Cynthia Wong, David Stamler, Daniel O. Claassen   +11 more
wiley   +1 more source

Theano: new features and speed improvements [PDF]

, 2012
Theano is a linear algebra compiler that optimizes a user's symbolically-specified mathematical computations to produce efficient low-level implementations.
Bastien, Frédéric, Bengio, Yoshua, Bergeron, Arnaud, Bergstra, James, Bouchard, Nicolas, Goodfellow, Ian, Lamblin, Pascal, Pascanu, Razvan, Warde-Farley, David   +8 more
core  

Pydna: a simulation and documentation tool for DNA assembly strategies using python

BMC Bioinformatics, 2015
Recent advances in synthetic biology have provided tools to efficiently construct complex DNA molecules which are an important part of many molecular biology and biotechnology projects. The planning of such constructs has traditionally been done manually
Filipa Pereira, F. Azevedo, Ângela Carvalho, Gabriela F. Ribeiro, Mark W. Budde, B. Johansson   +5 more
semanticscholar   +1 more source

Detecting Dengue in Flight: Leveraging Machine Learning to Analyze Mosquito Flight Patterns for Infection Detection

Advanced Biology, EarlyView.
Dengue infection alters mosquito flight behavior, enabling detection using machine learning classifiers. This study analyzes 3D flight trajectories and evaluates multiple models, showing that longer sequence lengths improve classification performance.
Nouman Javed, Adam J. López‐Denman, Prasad N. Paradkar, Asim Bhatti   +3 more
wiley   +1 more source

Variable elimination for building interpreters [PDF]

, 2010
In this paper, we build an interpreter by reusing host language functions instead of recoding mechanisms of function application that are already available in the host language (the language which is used to build the interpreter).
Cohen, Julien, Giavitto, Jean-Louis, Michel, Olivier   +2 more
core   +3 more sources

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

Advanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi, Saeed Kamarian, Mahdi Bodaghi, Saeed Saber‐Samandari, Jung‐il Song   +4 more
wiley   +1 more source

Package CovRegpy: Regularized covariance regression and forecasting in Python

Annals of Actuarial Science
This paper will outline the functionality available in the CovRegpy package which was written for actuarial practitioners, wealth managers, fund managers, and portfolio analysts in the language of Python 3.11.
Cole van Jaarsveldt, Gareth W. Peters, M. Ames, Michael Chantler   +3 more
semanticscholar   +1 more source