Predicting Clinical Outcomes at the Toronto General Hospital Transitional Pain Service via the Manage My Pain App: Machine Learning Approach by James Skoric, Anna M Lomanowska, Tahir Janmohamed, Heather Lumsden-Ruegg, Joel Katz, Hance Clarke, Quazi Abidur Rahman

“…MethodsInformation entered into the MMP app by 160 Transitional Pain Service patients over a 1-month period, including profile information, pain records, daily reflections, and clinical questionnaire responses, was used to extract 245 relevant variables, referred to as features, for use in a machine learning model. The machine learning model was developed using logistic regression with recursive feature elimination to predict clinically significant improvements in pain-related pain interference, assessed by the PROMIS Pain Interference 8a v1.0 questionnaire. …”
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Deep Learning-Based Active Jamming Suppression for Radar Main Lobe by Yilin Jiang, Yaozu Yang, Wei Zhang, Limin Guo

“…By first filtering out interference-related features and then reconstructing the signal, we can achieve better jamming suppression performance. …”
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Tenuta del registro formale nella comunicazione accademica scritta in italiano L1 e L2 by Francesca Pagliara

“…The results show that there are common features in the ability to manage the formal register in the written production of L1 and L2 students, although significant differences emerge in the use of punctuation and polite pronouns, mostly due to interlinguistic interference. …”
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Intelligent Dynamic Trajectory Planning of UAVs: Addressing Unknown Environments and Intermittent Target Loss by Zhengpeng Yang, Suyu Yan, Chao Ming, Xiaoming Wang

“…Precise trajectory planning is crucial in terms of enabling unmanned aerial vehicles (UAVs) to execute interference avoidance and target capture actions in unknown environments and when facing intermittent target loss. …”
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Recognition Algorithm of AE Signal of Rock Fracture Based on Multiscale 1DCNN-BLSTM by Weihua Wang

“…In response to the interference characteristics of acoustic emission signal data, a multiscale one-dimensional convolutional neural network embedded with efficient channel attention (ECA) module was incorporated into the model, and multiscale convolutional kernels were used to extract features of different levels of precision. …”
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Subject-object asymmetries in the processing of European Portuguese cleft structures by Xinyi Li, Maria Lobo, Joana Teixeira

“…It is thus plausible that different theoretical perspectives on intervention effects (featural Relativized Minimality and similarity-based interference models) complement each other, predicting that morphosyntactic features trigger stronger effects than semantic features. …”
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Low illumination image enhancement algorithm of CycleGAN coal mine based on attention mechanism and Dilated convolution by Yuanbin WANG, Yaru GUO, Jia LIU, Xu WANG, Bingchao WU, Meng LIU

“…In order to improve the detail feature extraction ability of the generator network, the image enhancement network was constructed by using the Parameter-Free Attention Mechanism (simAM) and the Dual-Channel Attention Mechanism (CBAM) to improve the anti-interference ability of the model in complex background, so that the model could recover the image detail features better, which improved the anti-interference ability of the model under complex background and made the model recover the detail features better. …”
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Hong–Ou–Mandel interferometry and quantum metrology with multimode frequency-bin entangled photons by Xu Jing, Linjie Fan, Xiaodong Zheng, Tangsheng Chen, Yuechan Kong, Bin Niu, Liangliang Lu

“…Building on the Fisher information analysis, we explore the relationship between the features in multimode entangled state interference traces and the precision of interferometric measurements even in the presence of experimental nonidealities. …”
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Pattern Design of Ethnic Clothing Based on Stretchable Nanofiber Fabrics by Xueqing Lu, Jing Wen, Xiaohua Shao

“…Through the influence of image rotation, scale change, noise interference, and other factors, a method for extracting features of ethnic clothing patterns based on image rotation, scale change, and noise interference is proposed. …”
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Prediction of cancer cell line-specific synergistic drug combinations based on multi-omics data by Jiaqi Chen, Huirui Han, Lingxu Li, Zhengxin Chen, Xinying Liu, Tianyi Li, Xuefeng Wang, Qibin Wang, Ruijie Zhang, Dehua Feng, Lei Yu, Xia Li, Limei Wang, Bing Li, Jin Li

“…In XDDC, drug chemical structures, adverse drug reactions, and target information were selected as drug features; gene expression, methylation, mutations, copy number variations, and RNA interference data were used as cell line features; and pathway information was incorporated to link drug features and cell line features. …”
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Technical note: Spectral correction for cavity ring-down isotope analysis of plant and soil waters by G. J. Bowen, S. Banerjee, S. Chakraborty

“…We develop multivariate statistical models that use analyzer-reported spectral features to correct for interference. These models account for 57 % of the observed <span class="inline-formula"><i>δ</i>²H</span> bias and 99 % of the <span class="inline-formula"><i>δ</i>¹⁸O</span> bias, and after correction the standard deviation of the CRDS <span class="inline-formula">−</span> IRMS differences for plant samples (4.1 ‰ for <span class="inline-formula"><i>δ</i>²H</span> and 0.4 ‰ for <span class="inline-formula"><i>δ</i>¹⁸O</span>) was similar to that for soil samples. …”
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NONLINEAR ANALYSIS OF BEARING SIGNAL BASED ON IMPROVED VARIATIONAL MODAL DECOMPOSITION AND MUTI FRACTAL by JIN JiangTao, XU ZiFei, LI Chun, MIAO WeiPao, ZHANG WanFu, LI Gen

“…Some characteristics of bearing initial signals are considered including unobvious features, susceptibility to noise interference and strong nonlinearity when a bearing was damaged. …”
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Fault Diagnosis of Rolling Element Bearing based on Angular Domain Empirical Wavelet Transform by Yang Changzheng

“…The rolling element bearing experimental signal analysis results show that the proposed method can effectively inhibit the influence of noise,other interference factors and extract the order ratio fault features accurately,it provides an effective method for rollering bearing fault diagnosis under variable speed.…”
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CBSNet: An Effective Method for Potato Leaf Disease Classification by Yongdong Chen, Wenfu Liu

“…Firstly, a convolution module called Channel Reconstruction Multi-Scale Convolution (CRMC) is designed to extract the upper and lower features by separating the channel features and applying a more optimized convolution to the upper and lower features, followed by a multi-scale convolution operation to capture the key changes more effectively. …”
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GLAD: Global–Local Approach; Disentanglement Learning for Financial Market Prediction by Humam M. Abdulsahib, Foad Ghaderi

“…Inspired by recent advancements in disentanglement representation learning, in this paper, we present a promising model for predicting financial markets that learn disentangled representations of features and eliminate those features that cause interference. …”
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EBBA-detector: An effective detector for defect detection in solar panel EL images with unbalanced data. by Yixing Zhang, Ziyan Mo, Zhuan Xin, Xianyu Chen, Yuqin Deng, Xuan Dong

“…The EBFPN captures defect features of different sizes, significantly improving the recognition ability for small defects, while the B-A Module suppresses background interference, guiding the model to focus more on defect locations. …”
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Multipath Effects Mitigation in Offshore Construction Platform GNSS-RTK Displacement Monitoring Using Parametric Temporal Convolution Network by Yiyang Jiang, Cheng Guo, Jinfeng Wang, Rongqiao Xu

“…Through time domain and frequency domain analysis, it has been demonstrated that the trained network can capture the main features of multipath models and suppress those components in both the data distribution and frequency band, effectively mitigating the interference of multipath errors in observations.…”
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Automatic LPI radar waveform recognition of overlapping signals based on vision language model by Pengkun Yang, Guangyi Li, Hui Tang, Yingjie Zhao, Hua Yan

“…By utilizing two distinct encoders for text and image, the model effectively aligns radar image and context prompt embeddings into a unified feature space. This alignment enables the model to more deeply learn and capture the intrinsic characteristics of radar waveforms, enhancing its ability to discern subtle modulation features. …”
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DESIGN AND SIMULATION PLASMONIC 2X1 MULTIPLEXER BASED ON ELLIPTICAL RING RESONATOR by Mohammed Sabah Talib, Faris al-Jaafiry

“…Constructed with silver and oxide zinc materials, proposed design operates by precisely guiding light waves to either negate each other through destructive interference or enhance each other through constructive interference. …”
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Contrastive learning of cross-modal information enhancement for multimodal fake news detection by Weijie Chen, Fei Cai, Yupu Guo, Zhiqiang Pan, Wanyu Chen, Yijia Zhang

“…Thus, we construct an information enhancement and contrast learning framework by introducing Improved Low-rank Multimodal Fusion approach for Fake News Detection (ILMF-FND), which aims to reduce the noise interference and achieve efficient fusion of multimodal feature vectors with fewer parameters. …”
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