Fuzzy co-clustering algorithm for high-order heterogeneous data by Shao-bin HUANG, Xin-xin YANG, Lin-shan SHEN, Yan-mei LI

“…Finally, experimental results show that HFCC can efficiently mine the overlapped clusters and the qualities of clustering results of HFCC are superior five classical hard high-order co-clustering algorithms. …”
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Evaluation of Drying Characteristics and Quality Attributes for Microwave Vacuum Drying of Pork Skin Crisps by Yuangang Li, Jingming Zhang, Junsheng Wang, Junpeng Ren, Chuanai Cao, Qian Liu, Xinning Huang

“…In this study, microwave vacuum drying (MVD) technology was used to investigate the effects of microwave powers (600, 700, and 800 W) and processing duration on the drying characteristics and quality attributes of pork skin crisps (PSC). Five classical drying models were used to non-linearly fit the experimental data, and the Midilli et al. model was suitable for characterizing the MVD process of PSC. …”
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Zero-shot Image Classification Method Based on Discriminator Feedback by FAN Yufei, DING Bo, HE Yongjun

“…Zero-shot learning (ZSL) strives to classify unseen categories for which no data is available during training.At present, among generative methods, zero-shot learning based on joint generative model VAEGAN is a research hotspot.On this basis, we propose a zero-shot image classification method based on Discriminator Feedback VAEGAN (DF-VAEGAN).This method introduces a feedback module in the discriminator part, which can improve the overall performance of the model in the training stage.In the feature generation stage, it can be combined with the generator to jointly improve the quality of feature generation.Finally, the classifier is trained through high quality synthetic features to improve classification accuracy.The method also reconstructs attribute features through the decoder and uses a cycle consistency loss to ensure semantic consistency of the generated feature.Experiments on ZSL and generalized zero-shot learning (GZSL) show that our method outperforms existing methods on five classical datasets, effectively enhancing the quality of feature synthesis and reducing the goal of between categories in the zero-shot image classification task.…”
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Upadacitinib therapy in refractory inflammatory myositis: a case series of 10 patients by Kun Huang, Jan Dutz, Madelaine Beckett

“…The medical records of these patients were retrospectively reviewed.Results 10 total patients were identified for review, including 5 classic dermatomyositis (DM), 3 amyopathic DM (ADM) and 2 antisynthetase syndrome. …”
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PHILOSOPHY OF PHYSICAL EDUCATION AND SPORTS IN BRAZIL: AN ANALYSIS OF THE PHILOSOPHICAL FOUNDATIONS IN THE WORK OF INEZIL PENNA MARINHO by Dirceu Ribeiro Nogueira da Gama, Lamartine Pereira da Costa, Juliana Brandão Pinto de Castro, Wecisley Ribeiro do Espírito Santo, Rodrigo Gomes de Souza Vale

“…Additionally, Marinho developed dialogues with authors from Aristotelianism, Platonism, Renaissance, Enlightenment, Evolutionism, Empirism, Freudism, Critical Theory, Hedonism, Platonic Theology, Stoicism, Cartesianism, and Bergsonism. Five classical issues appeared in his production: happiness as a transcendental demand; nature of the correspondence between language and reality; duality mind-body; historical conflict between freedom and domination; constitution of the subject. …”
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Estimating QoE from Encrypted Video Conferencing Traffic by Michael Sidorov, Raz Birman, Ofer Hadar, Amit Dvir

“…This paper addresses these challenges by analyzing a large dataset of Zoom sessions and training five classical machine learning (ML) models and two custom deep neural networks (DNNs) to predict three QoE indicators: frames per second (FPS), resolution (R), and the naturalness image quality evaluator (NIQE). …”
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Detection of Some Staphylococcal Enterotoxin Genes in MRSA Strains Using PCR Techniques by Suha M. Abed, Waad M. Raoof, Akeel H. A. Assie, Zeina S. M. Al-Hadeithi, Farooq Ibrahim

“…The extracted DNA yield was observed using the phenol-chloroform method, it ranged from (1.6-1.8) and concentration ranged from 100 to 800 ng/µl. Five classical enterotoxin genes were investigated in 20 isolates using multiplex PCR method after it had been molecularly identified into methicillin resistant using mec A (which is the key genetic component of methicillin resistance) and fem A genes in a duplex PCR technique. …”
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GRL-ITransformer: An Intelligent Method for Multi-Wind-Turbine Wake Analysis Based on Graph Representation Learning With Improved Transformer by Kang Han, Li Xu

“…After that, the data driven method is employed to update the parameters, and the superiority of GRL-ITransformer is highlighted by analyzing and comparing with the existing five classical intelligent algorithms (belongs to four categories). …”
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Software defect prediction based on stacked sparse denoising autoencoders and enhanced extreme learning machine by Nana Zhang, Shi Ying, Kun Zhu, Dandan Zhu

“…The SSDAE is compared with eleven state‐of‐the‐art feature extraction methods in effect and efficiency, and the SSEPG model is compared with multiple baseline models that contain five classic defect predictors and three variants across 24 software defect projects. …”
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Surrogate-assisted global and distributed local collaborative optimization algorithm for expensive constrained optimization problems by Xiangyong Liu, Zan Yang, Jiansheng Liu, Junxing Xiong, Jihui Huang, Shuiyuan Huang, Xuedong Fu

“…Experimental studies on five classical test suites demonstrate that the SGDLCO provides excellent performance in solving expensive constrained optimization problems.…”
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A HYBRID APPROACH FOR MALARIA CLASSIFICATION USING CNN-BASED FEATURE EXTRACTION AND TRADITIONAL MACHINE LEARNING CLASSIFIERS by omar Mohammed Alzakholi, Walat A. Ahmed, Bafreen N. Mohammed, Asaad Kh. Ibrahim

“…For our study, we utilize VGG16 CNN with a weight pre-trained on ImageNet to extract the features from non-infected and infected blood cell images from malaria. Five classical machine learning algorithms, such as Random Forest, Logistic Regression, K-Nearest Neighbours (KNN), Support Vector Machine (SVM), & Gradient Boosting, are used to classify the extracted features. …”
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Rapid detection of wheel tread defects for YOLO-v5 trains based on residual attention by ZHANG Changfan, XU Yifu, HE Jing, YANG Haonan

“…Finally, hundreds of real defect images of wheel treads were collected and contrasted with five classic detection models to verify the superiority of the algorithm. …”
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DFCNformer: A Transformer Framework for Non-Stationary Time-Series Forecasting Based on De-Stationary Fourier and Coefficient Network by Yuxin Jin, Yuhan Mao, Genlang Chen

“…Experimental findings reveal that when the proposed model is tested on six public datasets, in comparison with five classic models it reduces the MSE by an average of 9.67%, with a maximum improvement of 40.23%.…”
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Identification of nitric oxide-mediated necroptosis as the predominant death route in Parkinson’s disease by Ting Zhang, Wenjing Rui, Yue Sun, Yunyun Tian, Qiaoyan Li, Qian Zhang, Yanchun Zhao, Zongzhi Liu, Tiepeng Wang

“…Using the Scaden deep learning algorithm, we predicted neurocyte subtypes and modelled dynamic interactions for five classic cell death pathways to identify the predominant routes of neuronal death during PD progression. …”
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Enterotoxin gene profile of Staphylococcus aureus isolates recovered from bovine milk produced in central Ethiopia by Eyasu Tigabu Seyoum, Tesfu Kassa Mekonene, Daniel Asrat Woldetsadik, Bayleyegn Molla Zewudie, Wondwossen Abebe Gebreyes

“…Two sets of multiplex polymerase chain reaction (PCR) assays were used to detect the five classical enterotoxin-coding genes and the toxic shock syndrome toxin gene. …”
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Prevalence and genetic diversity of porcine reproduction and respiration syndrome viruses in Sichuan Province from 2023–2024 by MingXiang Li, MingXiang Li, Min Wang, Hao Li, KeLei Zhou, ZhiQiang Hu, ZhiQiang Hu, WenXing Bai, GuiYing Hao, GuiYing Hao, GuangWen Yan, GuangWen Yan

“…Further analysis of the complete ORF5 gene sequences of 56 PRRSV strains revealed that they could be classified into six lineages: PRRSV-1, lineage 8 (HP-PRRSV), lineage 5 (Classical PRRSV), lineage 1.8 (NADC30-like strain), lineage 1.5 (NADC34-like strain), and lineage 3.5 (QYYZ-like strain). …”
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DeLA: An extremely faster network with decoupled local aggregation for large scale point cloud learning by Weikang Yang, Xinghao Lu, Binjie Chen, Chenlu Lin, Xueye Bao, Weiquan Liu, Yu Zang, Junyu Xu, Cheng Wang

“…Experimental results on five classic benchmarks show that DeLA achieves state-of-the-art performance with reduced or equivalent latency. …”
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Causes of watershed drought analyzed using explainable deep learning: a case study of the Fenhe River Basin by Zixuan Chen, Zixuan Chen, Zixuan Chen, Xikun Wei, Guojie Wang, Yifan Hu, Haonan Liu, Jinman Zhang, Jinman Zhang, Jinman Zhang, Shuang Zhou, Shuang Zhou, Shuang Zhou, Zengbao Zhao, Zengbao Zhao, Zengbao Zhao, Yushan Liu, Yushan Liu, Yushan Liu

“…The standardized antecedent precipitation evapotranspiration index (SAPEI) was selected as an index for evaluating drought conditions. Five classical deep learning prediction models, namely, long short-term memory (LSTM), gated recurrent unit (GRU), bidirectional long short-term memory (biLSTM) networks, transformer (TFR), and informer (IFR), were applied in the experiment, and the performance of each model was comprehensively evaluated. …”
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Are ROC-improved logistic regressions beneficial to statistical models of land change? A counter example by Mingyang Qin, Yiru Xie, Shi Hua, Zhanhong Liu, Peichao Gao

“…To address this gap, we compared the basic LR model with five classic improved models using Lhasa as a case study, comparing the receiver-operating characteristic (ROC) values of each model and further evaluating the performance of the land change models generated by coupling each LR model with the CLUE-s model using six evaluation metrics (Kno, Klocation, Kquantity and the divergence indices (D, A and Q)). …”
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Mechanistic insights into the anti-depressant effect of quercetin: an integrated bibliometrics, bioinformatics, and animal experimentation by Zhujin Song, Zhujin Song, Yuhua Wu, Liping Luo, Qingqing Hu, Saiwei Wu, Miaolian Wu, Guoqing Zhang

“…This research focuses on quercetin, a principal bioactive constituent shared among five classical TCM antidepressant formulations, to systematically decode its multi-target mechanisms via an integrative framework combining neuroinflammatory modulation and synaptic plasticity regulation.MethodsA tripartite experimental design was implemented. …”
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