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Testing different supervised machine learning architectures for the classification of liquid crystals

• Authors : Dierking, Ingo; Dominguez, Jason; Harbon, James

• Source: Dierking , I , Dominguez , J , Harbon , J & Heaton , J 2023 , ' Testing different supervised machine

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Wind Turbine Generator Controller Signals Supervised Machine Learning for Shaft Misalignment Fault Detection: A Doubly Fed Induction Generator Practical Case Study

• Authors : Durovic, Sinisa; Wang, Yingzhao

• Source: Durovic , S & Wang , Y 2021 , ' Wind Turbine Generator Controller Signals Supervised Machine Learning for

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Semi-Supervised Machine Learning for Automated Species Identification by Collagen Peptide Mass Fingerprinting

• Authors : Gu, Muxin; Buckley, Michael

Subjects: ResearchInstitutes_Networks_Beacons/manchester_institute_of_biotechnology; Manchester Institute of Biotechnology

• Source: Gu , M & Buckley , M 2018 , ' Semi-Supervised Machine Learning for Automated Species Identification by

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Detection of Airborne Biological Particles in Indoor Air Using a Real-Time Advanced Morphological Parameter UV-LIF Spectrometer and Gradient Boosting Ensemble Decision Tree Classifiers

• Authors : Crawford, Ian; Topping, David; Gallagher, Martin

Subjects: Bioaerosol; Biological aerosol; Building mycology

• Source: Crawford , I , Topping , D , Gallagher , M , Forde , E , Lloyd , J R , Foot , V , Stopford , C & Kaye , P 2020 , ' Detection of Airborne Biological Particles in Indoor Air Using a Real-Time Advanced

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Identifying mouse developmental essential genes using machine learning

• Authors : Tian, David; Wenlock, Stephanie; Kabir, Mitra

Subjects: essential genes; supervised machine learning; mouse knockout

• Source: Tian , D , Wenlock , S , Kabir , M , Tzotzos , G , Doig , A & Hentges , K 2018 , ' Identifying mouse developmental essential genes using machine

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Automatic Keyphrase Extraction from Scientific Chinese Medical Abstracts Based on Character-Level Sequence Labeling

• Authors : Ding, Liangping; Zhang, Zhixiong; Liu, Huan

Subjects: Automatic keyphrase extraction; Character-level sequence labeling; Pretrained language model

• Source: Ding , L , Zhang , Z , Liu , H , Li , J & Yu , G 2021 , ' Automatic Keyphrase Extraction from Scientific Chinese Medical Abstracts Based on Character-Level Sequence Labeling ' , Journal of Data and

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Predicting congenital renal tract malformation genes using machine learning

• Authors : Kabir, Mitra; Stuart, Helen; Lopes, Filipa

• Source: Kabir , M , Stuart , H , Lopes , F , Fotiou , E , Keavney , B , Doig , A , Woolf , A S & Hentges , K 2023 , ' Predicting congenital renal tract malformation genes using

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Arabic Sentiment Analysis Based on Word Embeddings and Deep Learning

• Authors : Elhassan, Nasrin; Varone, Giuseppe; Ahmed, Rami

Subjects: Arabic Sentiment Analysis; FastText; Word2Vec

• Source: Elhassan , N , Varone , G , Ahmed , R , Gogate , M , Dashtipour , K , Almoamari , H , El-Affendi , M A , Al-Tamimi , B N , Albalwy , F & Hussain , A 2023 , ' Arabic Sentiment Analysis Based on Word

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AI-based dimensional neuroimaging system for characterizing heterogeneity in brain structure and function in major depressive disorder:COORDINATE-MDD consortium design and rationale

• Authors : Fu, Cynthia H.Y.; Erus, Guray; Fan, Yong

Subjects: Biomarkers; Classification; Deep learning

• Source: Fu , C H Y , Erus , G , Fan , Y , Antoniades , M , Arnone , D , Arnott , S R , Chen , T , Choi , K S , Fatt , C C , Frey , B N , Frokjaer , V G , Ganz , M , Garcia , J , Godlewska , B R , Hassel , S ,

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Machine learning classification of polar sub-phases in liquid crystal MHPOBC

• Authors : Betts, Rebecca; Dierking, Ingo

• Source: Betts , R & Dierking , I 2023 , ' Machine learning classification of polar sub-phases in liquid crystal MHPOBC ' , Soft Matter .

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