Results 11 to 20 of about 84,677 (290)

Predicting gene expression in the human malaria parasite Plasmodium falciparum using histone modification, nucleosome positioning, and 3D localization features. [PDF]

open access: yes, 2019
Empirical evidence suggests that the malaria parasite Plasmodium falciparum employs a broad range of mechanisms to regulate gene transcription throughout the organism's complex life cycle.
Cook, Kate   +4 more
core   +2 more sources

Routine characterization and interpretation of complex alkali feldspar intergrowths [PDF]

open access: yes, 2015
Almost all alkali feldspar crystals contain a rich inventory of exsolution, twin, and domain microtextures that form subsequent to crystal growth and provide a record of the thermal history of the crystal and often of its involvement in replacement ...
Fitz Gerald, John D.   +2 more
core   +1 more source

A Robust Interpretable Deep Learning Classifier for Heart Anomaly Detection Without Segmentation

open access: yes, 2020
Traditionally, abnormal heart sound classification is framed as a three-stage process. The first stage involves segmenting the phonocardiogram to detect fundamental heart sounds; after which features are extracted and classification is performed.
Denman, Simon   +5 more
core   +1 more source

NATIONAL STATUSES GRANTED FOR PROTECTION REASONS IN IRELAND. ESRI RESEARCH SERIES NUMBER 96 January 2020 [PDF]

open access: yes, 2020
This study examines the national statuses that may be granted for protection reasons in Ireland. The report focuses on national statuses with a sole basis in Irish domestic law and policy and does not examine in detail EU-harmonised statuses.
Brazil, Patricia, Groarke, Sarah
core  

Assessing the Impact of Expert Labelling of Training Data on the Quality of Automatic Classification of Lithological Groups Using Artificial Neural Networks

open access: yesApplied Computer Systems, 2020
Machine learning (ML) methods are nowadays widely used to automate geophysical study. Some of ML algorithms are used to solve lithological classification problems during uranium mining process.
Kuchin Yan   +4 more
doaj   +1 more source

Geochronology (Re–Os and U–Pb) and fluid inclusion studies of molybdenite mineralisation associated with the Shap, Skiddaw and Weardale granites, UK [PDF]

open access: yes, 2008
Late Devonian magmatism in Northern England records key events associated with the Acadian phase of the Caledonian-Appalachian Orogen (C-AO). Zircon U-Pb and molybdenite Re-Os geochronology date emplacement and mineralisation in the Shap (405·2±1·8 Ma ...
Conliffe, J.   +3 more
core   +1 more source

A traceability model for upper corner gas in fully mechanized mining faces based on XGBoost-SHAP

open access: yesGong-kuang zidonghua
To address the weak interpretability caused by the "black-box" structure of current gas concentration prediction models in the upper corner of fully mechanized mining faces, a gas traceability model based on XGBoost-SHAP was proposed for the upper corner
SHENG Wu, WANG Lingzi
doaj   +1 more source

Exploring commuter stress dynamics through machine learning and double optimization

open access: yesMehran University Research Journal of Engineering and Technology
Travel dynamics significantly impact commuter stress, influenced by traffic behavior, road conditions, travel modes, distance, and socio-demographic characteristics.
Ashar Ahmed   +2 more
doaj   +1 more source

Simple high-throughput annotation pipeline (SHAP) [PDF]

open access: yesBioinformatics, 2011
Abstract Summary: SHAP (simple high-throughput annotation pipeline) is a lightweight and scalable sequence annotation pipeline capable of supporting research efforts that generate or utilize large volumes of DNA sequence data. The software provides Grid capable analysis, relational storage and Web-based full-text searching of annotation ...
Matthew Z, DeMaere   +4 more
openaire   +2 more sources

On Network Science and Mutual Information for Explaining Deep Neural Networks

open access: yes, 2020
In this paper, we present a new approach to interpret deep learning models. By coupling mutual information with network science, we explore how information flows through feedforward networks.
Bhardwaj, Kartikeya   +4 more
core   +1 more source

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