Fault Identification based on Improved Supervised Orthogonal Neighborhood Preserving Embedding by Ji Yunfeng, Feng Liyuan, Kuang Liang

“…The Orthogonal neighborhood preserving embedding（ ONPE） is an unsupervised feature dimension reduction method and only use global neighborhood parameter,when it is used to high- dimension fault feature for feature dimension reduction,it is incapacity of using sample class label information and adaptive adjust neighborhood parameter while the space distribution of samples changed. …”
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APPLICATION OF SEMI SUPERVISED LAPLACE SCORE IN ROLLING BEARING FAULT DIAGNOSIS (MT) by LIANG Chuang, CHEN ChangZheng, LIU Ye, JIA XinYing

“…SSLS applies the semi supervised idea to the Laplace score feature selection method, uses a small number of labeled samples and a large number of unlabeled samples, and combines KPCA to excavate fault features for a second time. …”
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An LSTM auto-encoder based anomaly detection for industrial system by Xiaojun SHEN, Yanan GE, Zhihao SHEN, Yangdan NI, Mingqi LV, Zhengqiu WENG

“…In the context of the industrial internet,automatic and effective anomaly detection methods are of great significance to the safe and stable production of industrial systems.Traditional anomaly detection methods have the disadvantages of requiring a large number of labeled samples,and not adapting to high-dimensional time series data.Aiming at these limitations,an industrial system anomaly detection method based on LSTM (long short-term memory)auto-encoder was proposed.Firstly,to address the limitation of relying on labeled samples,an encoder used to learn the features and patterns of a large number of normal samples in an unsupervised manner.Then,anomaly detection was performed via reconstructing samples and calculating the reconstruction error.Secondly,to adapt to high-dimensional time series data,a BiLSTM (bidirectional LSTM) was used as an encoder,and then the potential characteristics of multi-dimensional time series data were mined.Experiments based on a real paper industry data set which demonstrate this method has improved the existing unsupervised anomaly detection methods in various indicators,and the overall accuracy of the detection has reached 93.4%.…”
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Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology by Xin Zhang, Pengfei Shao

“…This scheme endorsed computer vision technology for logistics recognition and labelled data detection. In this scheme, the labelled logistics data is verified for its similarity in different migrating locations and to the endpoint. …”
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The interplay between gender-based workplace prejudice and girls’ occupational choice at Bahir Dar polytechnic college by Melaku Mengistu Gebremeskel

“…The analysis and interpretation of data demonstrated that the gender-based workplace labeling has put over its own impact on the professional choice of girls in the college. …”
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The interplay between gender-based workplace prejudice and girls’ occupational choice at Bahir Dar polytechnic college by Melaku Mengistu Gebremeskel

“…The analysis and interpretation of data demonstrated that the gender-based workplace labeling has put over its own impact on the professional choice of girls in the college. …”
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Deformable Models for Segmentation of CLSM Tissue Images and Its Application in FISH Signal Analysis by P. S. Umesh Adiga, B. B. Chaudhuri

“…Three‐dimensional region isolation and labeling technique is used to label and count the FISH signals per cell nucleus. …”
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Catechin-Albumin Conjugates: Enhanced Antioxidant Capacity and Anticancer Effects by Tooru Ooya, Izumi Haraguchi

“…Intracellular incorporation of the CT–HSA was analyzed by fluorescence-activated cell sorting (FACS) and confocal laser scanning microscopy (CLSM) measurements using fluorescein isothiocyanate (FITC)-labelled CT–HSA. The results indicated that the FITC-labelled CT–HSA was incorporated into HeLa cells in a concentration-dependent manner. …”
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Suspension of Mitotic Activity in Dentate Gyrus of the Hibernating Ground Squirrel by Victor I. Popov, Igor V. Kraev, Dmitri A. Ignat'ev, Michael G. Stewart

“…Our data suggest that doublecortin-labelled immature cells exist in a mitotic state and may represent a renewable pool for generation of new neurons within the dentate gyrus.…”
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A comprehensive review of Interferometric Reflectance Imaging Sensor as a sensitive detection platform and its application areas by Monireh Bakhshpour-Yucel, Nese Lortlar Unlu, Elif Seymour, Adil Denizli

“…The Interferometric Reflectance Imaging Sensor (IRIS) technology represents a significant advancement in biosensing, providing a label-free, selective, sensitive, and high-throughput platform for detecting molecular interactions. …”
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Robust Framework to Combine Diverse Classifiers Assigning Distributed Confidence to Individual Classifiers at Class Level by Shehzad Khalid, Sannia Arshad, Sohail Jabbar, Seungmin Rho

“…We have presented a classification framework that combines multiple heterogeneous classifiers in the presence of class label noise. An extension of m-Mediods based modeling is presented that generates model of various classes whilst identifying and filtering noisy training data. …”
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Pretraining Convolutional Neural Networks for Image-Based Vehicle Classification by Yunfei Han, Tonghai Jiang, Yupeng Ma, Chunxiang Xu

“…Through the data enhancement on manual labeled images, we got 2000 labeled images in each category of motorcycle, transporter, passenger, and others, with 1400 samples for training and 600 samples for testing. …”
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Protocol for profiling RNA m5C methylation at base resolution using m5C-TAC-seq by Xiaoting Zhang, Liang Lu, Chengqi Yi, Xiaoyu Li

“…Here, we present a protocol for transcriptome-wide m5C methylome profiling at base resolution using bisulfite-free m5C detection strategy enabled by ten-eleven translocation (TET)-assisted chemical labeling sequencing (m5C-TAC-seq). We detail steps for TET-assisted chemical labeling, library construction, and data analysis. m5C-TAC-seq enables accurate and robust m5C detection in various RNA species.For complete details on the use and execution of this protocol, please refer to Lu et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.…”
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Hypergraph Regularized Discriminative Nonnegative Matrix Factorization on Sample Classification and Co-Differentially Expressed Gene Selection by Yong-Jing Hao, Ying-Lian Gao, Mi-Xiao Hou, Ling-Yun Dai, Jin-Xing Liu

“…Both the hypergraph Laplace and the discriminative label information are utilized together to learn the projection matrix in the standard method. …”
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Emotion Recognition Using PPG Signals of Smartwatch on Purpose of Threat Detection by Gyuwon Hwang, Sohee Yoo, Jaehyun Yoo

“…In this paper, Gaussian Mixture Models are learned to remove ambiguously labeled training, and those models are also used to remove ambiguous test data. …”
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Honey-Induced Protein Stabilization as Studied by Fluorescein Isothiocyanate Fluorescence by Yin How Wong, Habsah Abdul Kadir, Saad Tayyab

“…Protein stabilizing potential of honey was studied on a model protein, bovine serum albumin (BSA), using extrinsic fluorescence of fluorescein isothiocyanate (FITC) as the probe. BSA was labelled with FITC using chemical coupling, and urea and thermal denaturation studies were performed on FITC-labelled BSA (FITC-BSA) both in the absence and presence of 10% and 20% (w/v) honey using FITC fluorescence at 522 nm upon excitation at 495 nm. …”
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SSL-MBC: Self-Supervised Learning With Multibranch Consistency for Few-Shot PolSAR Image Classification by Wenmei Li, Hao Xia, Bin Xi, Yu Wang, Jing Lu, Yuhong He

“…However, supervised training relying on massive labeled samples is one of its major limitations, especially for PolSAR images that are hard to manually annotate. …”
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Anomaly Detection in High Mobility MDT Traces Through Self-Supervised Learning by J. M. Sanchez-Martin, C. Gijon, M. Toril, S. Luna-Ramirez, V. Wille

“…Supervised Learning (SL) allows to train automatic systems for detecting abnormal MDT measurements by using a labeled dataset. Unfortunately, labeling MDT data is a labor-intensive task, that can be alleviated by using Self-Supervised Learning (SSL). …”
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Adaptive Diagnosis Method Based on Gearbox Unbalanced Fault Data by Tian Juan, Xie Gang, Zhang Shun, Wang Yufei

“…Firstly, a gated local connection network was utilized to reduce the reliance on the labeled data and extract intrinsic features directly from the original data. …”
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