Body roundness index, visceral adiposity index, and metabolic score for visceral fat in predicting new-onset atrial fibrillation: a UK Biobank cohort study by Yi ZHENG, Lei LIU, Xinyu ZHENG, Tong LIU, Xiaoping LI

“…We further applied the eXtreme Gradient Boosting (XGBoost) algorithm, with the feature importance being measured to evaluate the predictive value of each adiposity index for imaging parameters. …”
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Digital augmentation of aftercare for patients with anorexia nervosa: the TRIANGLE RCT and economic evaluation by Janet Treasure, Katie Rowlands, Valentina Cardi, Suman Ambwani, David McDaid, Jodie Lord, Danielle Clark Bryan, Pamela Macdonald, Eva Bonin, Ulrike Schmidt, Jon Arcelus, Amy Harrison, Sabine Landau

“…We would plan to use similar measures to describe the clinical features and outcomes. This would allow for a meta-synthesis of the results across trials. …”
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Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics by Yuzhen Wei, Siyi Yao, Feiyue Wu, Qiangguo Yu

“…In this research, hyperspectral imaging (380–1030 nm) technology was applied to visually detect the sweetness and acidity of cherry. To improve the imaging performance, two spectral pretreatment methods (wavelet transform, standard normal variable transformation and detrend), three feature selection methods (successive projection algorithm, genetic algorithm, and shuffled frog leaping algorithm), and four regression modeling methods (principal components regression, partial least squares regression, least square-support vector regression, convolutional neural network) were employed and compared. …”
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Application of Variational Mode Decomposition based on the FOA and in Bearing Fault Diagnosis by Chang Liu, Yanxue Wang, Jianwei Yang

“…Finally， the optimal modal component is selected based on the kurtosis maximization criterion for envelope demodulation analysis and extracting the frequency of the fault feature. The effectiveness of the presented method is verified by simulation signal analysis， detecting bearing fault signal and comparing with multi-resolution singular value decomposition （MRSVD） approach based on fruit fly optimization algorithm.…”
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Artificial intelligence analysis in cyber domain: A review by Liguo Zhao, Derong Zhu, Wasswa Shafik, S Mojtaba Matinkhah, Zubair Ahmad, Lule Sharif, Alisa Craig

“…An in-depth learning algorithm is utilized for training a neural network for detecting suspicious user activities. …”
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Machine Learning-Driven Prediction of Vitamin D Deficiency Severity with Hybrid Optimization by Usharani Bhimavarapu, Gopi Battineni, Nalini Chintalapudi

“…The improved whale optimization (IWOA) algorithm was used for feature selection, which optimized weight functions to improve prediction accuracy. …”
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An explainable federated blockchain framework with privacy-preserving AI optimization for securing healthcare data by Tanisha Bhardwaj, K. Sumangali

“…PPFBXAIO employs Secure Hash Algorithm 256 (SHA-256) for blockchain-backed secure model updates, Min-Max normalization for feature scaling, and the Levy Grasshopper Optimization Algorithm (LGOA) for optimal feature selection and federated model tuning. …”
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QuantiFly: Robust Trainable Software for Automated Drosophila Egg Counting. by Dominic Waithe, Peter Rennert, Gabriel Brostow, Matthew D W Piper

“…The accuracy of the baseline algorithm is additionally increased in this study through correction of bias observed in the algorithm output. …”
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Application Of K-Nearest Neighbor Algoritma for Customer Review Sentiment Analysis at Ngeboel Vapestore Shop by Muhammad Aryanda, Ita Arfyanti, Yulindawati Yulindawati

“… This study applies the K-Nearest Neighbor (K-NN) algorithm to classify customer sentiments from online reviews about Ngeboel Vapestore, a local MSME in the vape industry. …”
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CrackNet: A new deep learning-based strategy for automatic classification of road cracks after earthquakes by Fatih Demir, Erkut Yalcin, Mehmet Yilmaz

“…Timely maintenance of highways prevents higher maintenance costs in the future. Especially detecting deterioration on highways due to major earthquakes is of great importance. …”
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Straightness monitoring of scraper conveyor based on CUDA-accelerated dynamic programming and optimized panoramic stitching by LI Bo, SHI Shouyi, ZHANG Jianjun, XIA Rui, WANG Xuewen, CUI Weixiu, NI Qiang

“…Then, the oriented FAST and rotated BRIEF (ORB) algorithm was used to detect and calculate feature points and descriptors from the two video frames. …”
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Decoding Anomalous Diffusion Using Higher-Order Spectral Analysis and Multiple Signal Classification by Miguel E. Iglesias Martínez, Òscar Garibo-i-Orts, J. Alberto Conejero

“…Recent advances using statistical methods and recurrent neural networks have made it possible to detect such phenomena, even in noisy conditions. In this work, we explore feature extraction through parametric and non-parametric spectral analysis methods to decode anomalously diffusing trajectories, achieving reduced computational costs compared with other approaches that require additional data or prior training. …”
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An Approach for Predicting the Shape and Size of a Buried Basic Object on Surface Ground Penetrating Radar System by Nana Rachmana Syambas

“…The pattern of object under test will be known by comparing its data with the training data using a decision tree method. A simple powerful algorithm to extract feature parameters of object which is based on linear extrapolation is proposed. …”
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Multiple-Image Encryption Mechanism Based on Ghost Imaging and Public Key Cryptography by Leihong Zhang, Xiao Yuan, Kaimin Wang, Dawei Zhang

“…In the encryption system, a plurality of light paths are set, and the Hadamard basis patterns are used for illumination, so that each light path is concentrated in a bucket detector to obtain intensity values of all images. Then, all the detected intensity values are encrypted by using public key cryptography algorithm to obtain the final ciphertext. …”
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Fault Diagnosis of Industrial Process Based on FDKICA-PCA by ZHANG Jing, ZHU Fei-fei, LIU Jia-xing, WANG Jiang-tao

“…Because the dynamic characteristics of autocorrelation and lag correlation in production process are neglected in fault diagnosis,Kernel Independent Component AnalysisPrincipal Component Analysis (KICAPCA) is very poor in detecting small and gradual faults because of lacking available variable contribution analysis.In this paper, a dynamic kernel independent component analysis (KICAPCA) fault diagnosis method based on wavelet packet filtering is proposed.This method integrates wavelet packet filtering theory and AR model prediction data characteristics into KICAPCA to extract the feature information of process variable autocorrelation and lagrelated .In this paper, KICAPCA algorithm is used to extract the independent components and principal components of process variables to determine the control limits of three monitoring indicators T2, SPE,I2.Nonlinear contribution graph is used for fault diagnosis, and the advantage of FDKICAPCA method is verified by simulation results of Tennessee process.…”
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Reversible Spectral Speech Watermarking with Variable Embedding Locations Against Spectrum-Based Attacks by Xuping Huang, Akinori Ito

“…Due to the integrity of the original data with probative importance, the algorithm requires reversibility, imperceptibility, and reliability. …”
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A Resilient Deep Learning Approach for State Estimation in Distribution Grids With Distributed Generation by Ronald Kfouri, Harag Margossian

“…We then subject the neural network to multiple test scenarios featuring noisier measurements and bad data to evaluate the robustness of our algorithm. …”
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Research on Soft-Sensing Methods for Measuring Diene Yields Using Deep Belief Networks by Xiangwu Deng, Zhiping Peng, Delong Cui

“…A diene yield prediction method based on a deep belief network algorithm network is proposed, and the regularity of historical diene yield data is fully explored by the method. …”
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Predicting Protein Interactions Using a Deep Learning Method-Stacked Sparse Autoencoder Combined with a Probabilistic Classification Vector Machine by Yanbin Wang, Zhuhong You, Liping Li, Li Cheng, Xi Zhou, Libo Zhang, Xiao Li, Tonghai Jiang

“…This method was developed based on a deep learning algorithm-stacked sparse autoencoder (SSAE) combined with a Legendre moment (LM) feature extraction technique. …”
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Soft-sensor modeling of silicon content in hot metal based on sparse robust LS-SVR and multi-objective optimization by GUO Dong-wei, ZHOU Ping

“…Based on those, an on-line soft sensor model of hot metal[Si] with the optimal parameters was obtained by using the multi-objective genetic algorithm (NSGA-Ⅱ) with the non-dominated sort and elitist strategy. …”
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