CryoProtect: A Web Server for Classifying Antifreeze Proteins from Nonantifreeze Proteins by Reny Pratiwi, Aijaz Ahmad Malik, Nalini Schaduangrat, Virapong Prachayasittikul, Jarl E. S. Wikberg, Chanin Nantasenamat, Watshara Shoombuatong

“…The predictive model is provided as a free publicly available web server called CryoProtect for classifying query protein sequence as being either AFP or non-AFP. …”
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Fault Identification of Rotor System Based on Classifying Time-Frequency Image Feature Tensor by Hui Li, Xiaofeng Liu, Lin Bo

“…In the field of rotor fault pattern recognition, most of classical pattern recognition methods generally operate in feature vector spaces where different feature values are stacked into one-dimensional (1D) vector and then processed by the classifiers. …”
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Clinical validation of an artificial intelligence algorithm for classifying tuberculosis and pulmonary findings in chest radiographs by Thiago Fellipe Ortiz de Camargo, Thiago Fellipe Ortiz de Camargo, Guilherme Alberto Sousa Ribeiro, Guilherme Alberto Sousa Ribeiro, Maria Carolina Bueno da Silva, Luan Oliveira da Silva, Pedro Paulo Teixeira e Silva Torres, Denise do Socorro Rodrigues da Silva, Mayler Olombrada Nunes de Santos, William Salibe Filho, Marcela Emer Egypto Rosa, Magdala de Araujo Novaes, Thiago Augusto Massarutto, Osvaldo Landi Junior, Elaine Yanata, Marcio Rodrigues da Cunha Reis, Gilberto Szarf, Pedro Vieira Santana Netto, Joselisa Peres Queiroz de Paiva

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Application of Data Clustering Embedded in Fuzzy Classifier Expert System for Water Quality Recognition by JC Obi, AA Imianvan

“…@JASEM Keywords: Fuzzy classifier, fuzzy logic, fuzzy set, Water J. Appl. …”
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Classifying, Predicting, and Reducing Strategies of the Mesh Excitations of Gear Whine Noise: A Survey by Menglei Sun, Chihua Lu, Zhien Liu, Yi Sun, Hao Chen, Cunrui Shen

“…The excitations of gear whine noise are classified into three groups: transmission error along the line of action direction, frictional excitations along the off-line of action direction, and shuttling excitation along the axial direction. …”
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Performance Assessment of Multiple Classifiers Based on Ensemble Feature Selection Scheme for Sentiment Analysis by Monalisa Ghosh, Goutam Sanyal

“…These methods offer a ranking to the features depending on their score; thus a prominent feature vector (CompIG, CompGI, and CompCHI) can be generated easily for classification. Finally, the machine learning classifiers SVM, MNB, KNN, and ME used prominent feature vector for classifying the review document into either positive or negative. …”
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Mitigating GNSS Multipath Effects Using XGBoost Integrated Classifier Based on Consistency Checks by Dengao Li, Xiaoli Ma, Jumin Zhao, Fanming Wu

“…The results show that the performance of the model is significantly improved after applying the CC method, in which the average classification accuracy of the multipath signals in the target feature set can reach 91.6%. …”
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Concordance of Australian state and territory government guidelines for classifying the healthiness of foods in public settings by Bettina Backman, Meg Adam, Jasmine Chan, Josephine Marshall, Emalie Rosewarne, Gary Sacks, Adrian J Cameron, Miranda R Blake

“…Design: Commonly available products in Australian food service settings across 8 food categories were classified according to each of the 17 Australian state and territory food classification guidelines applying to public schools, workplaces, and healthcare settings. …”
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Attention-Based Hybrid Deep Learning Models for Classifying COVID-19 Genome Sequences by A. M. Mutawa

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EEG Transformer for Classifying Students’ Epistemic Cognition States in Educational Contexts by Rosanna Yuen-Yan Chan

“…This study addresses this limitation by employing transformers and publicly available electroencephalography (EEG) datasets to classify students’ epistemic cognition states. …”
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Addendum to: Classifying 5d SCFTs via 6d SCFTs: rank one by Lakshya Bhardwaj, Patrick Jefferson

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Gradient method for designing cascaded DOEs and its application in the problem of classifying handwritten digits by D.V. Soshnikov, L.L. Doskolovich, E.V. Byzov

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Detection of mite infested saffron plants using aerial imaging and machine learning classifier by Hossein Sahabi, Jalal Baradaran-Motie

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Beyond DNA: An Integrated and Functional Approach for Classifying Germline Variants in Breast Cancer Genes by T. Pesaran, R. Karam, R. Huether, S. Li, S. Farber-Katz, A. Chamberlin, H. Chong, H. LaDuca, A. Elliott

“…The accuracy of an assay is reliant on not only the technology and bioinformatics analysis utilized but also the experience and infrastructure required to correctly classify genetic variants as disease-causing. Interpreting the clinical significance of germline variants identified by hereditary cancer testing is complex and has a significant impact on the management of patients who are at increased cancer risk. …”
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Classifying the Involvement of Men and Women in Climate Smart Agricultural Practices in Kayonza Sub-county by Turyasingura, Benson, Ayiga, Natal

“…The purpose of this study was therefore classifying the involvement of men and women in climate smart agricultural practices in Kayonza sub-county, Kanungu district, Uganda. …”
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Critical Optical Depth Hypothesis for Phytoplankton Growth and Bloom. A New Graphical Approach to the Classic Sverdrup Critical Depth Model by Wojciech Szeligiewicz

“…This model shows not only the direction of the growth for a given column, such as the classic Sverdrup model, but also the magnitude of that growth. …”
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LSD and psilocybin for chronic nociplastic pain: A narrative review of the literature supporting the use of classic psychedelic agents in chronic pain by J Van Der Walt, R Parker

“…Novel ways of treating people who suffer from chronic nociplastic pain with classic psychedelic agents may offer a new lens through which to approach their pain. …”
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«SCHOOL OF COMPETENCIES» AS A TECHNOLOGY FOR THE DEVELOPMENT OF STUDENTS’ ADDITIONAL COMPETENCIES AT CLASSICAL UNIVERSITY by V. Y. Stromov, Р. V. Sysoyev, V. V. Zavyalov

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Exploring Effects of Mental Stress with Data Augmentation and Classification Using fNIRS by M. N. Afzal Khan, Nada Zahour, Usman Tariq, Ghinwa Masri, Ismat F. Almadani, Hasan Al-Nashah

“…Linear discriminant analysis (LDA) showed a maximum accuracy of 60%, whereas non-augmented data classified by a convolutional neural network (CNN) provided the highest classification accuracy of 73%. …”
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