Short-Term Traffic Prediction considering Spatial-Temporal Characteristics of Freeway Flow by Jiaqi Wang, Yingying Ma, Xianling Yang, Teng Li, Haoxi Wei

“…Second, the hybrid model constructed by long short-term memory and K-nearest neighbor (LSTM-KNN) algorithm using transformed grey wolf optimization is discussed. …”
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On the enhancement of estimator efficiency of population variance through stratification, transformation, and formulation with application to COVID-19 data by Hameed Ali, Zafar Mahmood, T.H. AlAbdulaal

“…This work introduces a novel data-driven machine learning algorithm aiming stratification problem, formally based on subjective approach. …”
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Precision Imaging for Early Detection of Esophageal Cancer by Po-Chun Yang, Chien-Wei Huang, Riya Karmakar, Arvind Mukundan, Tsung-Hsien Chen, Chu-Kuang Chou, Kai-Yao Yang, Hsiang-Chen Wang

“…We employed the Yolov5 model, a state-of-the-art object detection algorithm, to predict early ECA based on the provided images. …”
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Modelling COVID-19 in the North American region with a metapopulation network and Kalman filter by Matteo Perini, Teresa K. Yamana, Marta Galanti, Jiyeon Suh, Roselyn Kaondera-Shava, Jeffrey Shaman

“…The model is informed by COVID-19 case data, which are assimilated using the Ensemble Adjustment Kalman filter (EAKF), a Bayesian inference algorithm. Additionally, commuting and mobility data are used to build and adjust the network and movement across locations on a daily basis. …”
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A New Asymmetric Fully Homomorphic Encryption Scheme for Cloud Banking Data by Zana Thalage Omar, Fadhil Salman Abed, Shaimaa Khamees Ahmed

“…Our current research provides a new algorithm for a publicly-keyed encryption system to keep bank data from tampering and theft when stored on the cloud computing platform, and our new system achieves fully Homomorphic Encryption, which allows mathematical operations to be performed on the encrypted text without the need for the original text. …”
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An Ultrafast Image Simulation Technique with Spatially Variable Point-spread Functions by Zeyu Bai, Peng Jia, Jiameng Lv, Xiang Zhang, Wennan Xiang, Lin Nie

“…Simulated images are essential in algorithm development and instrument testing for optical telescopes. …”
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Weakly-Supervised Deep Shape-From-Template by Sara Luengo-Sanchez, David Fuentes-Jimenez, Cristina Losada-Gutierrez, Daniel Pizarro, Adrien Bartoli

“…WS-DeepSfT addresses the limitations of existing SfT techniques by combining a weakly-supervised deep neural network (DNN) for registration and a classical As-Rigid-As-Possible (ARAP) algorithm for 3D reconstruction. Unlike previous deep learning-based SfT methods, which require extensive synthetic data and depth sensors for training, WS-DeepSfT only requires regular RGB video of the deforming object and a segmentation mask to discriminate the object from the background. …”
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On the Effect of the Patient Table on Attenuation in Myocardial Perfusion Imaging SPECT by Tamino Huxohl, Gopesh Patel, Wolfgang Burchert

“…Methods Jaszczak phantom scans are acquired according to quality control and MPI procedures. An algorithm is developed to automatically remove the patient table from the CT for attenuation correction. …”
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AI based predictive acceptability model for effective vaccine delivery in healthcare systems by Muhammad Shuaib Qureshi, Muhammad Bilal Qureshi, Urooj Iqrar, Ali Raza, Yazeed Yasin Ghadi, Nisreen Innab, Masoud Alajmi, Ayman Qahmash

“…A sample dataset containing 7150 data records with 31 demographic and socioeconomic attributes from PDHS (2017–2018) is used in this paper. Using the LightGBM algorithm, the proposed model constructed on the basis of different machine-learning procedures achieved 98% accuracy to accurately predict the acceptability of vaccines included in the immunization program. …”
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Unbiased Feature Selection in Learning Random Forests for High-Dimensional Data by Thanh-Tung Nguyen, Joshua Zhexue Huang, Thuy Thi Nguyen

“…Aiming at debiasing feature selection in RFs, we propose a new RF algorithm, called xRF, to select good features in learning RFs for high-dimensional data. …”
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A Deformation Reconstruction Strategy for Integrated Truss Structures Subjected to Thermal–Mechanical Load by Zexing Yu, Xiaofei Ma, Jialong Zhu, Dayu Zhang, Yonggang Xue, Pengfei Huang, Yichen Li, Hao Li

“…The proposed approach utilizes Ko displacement theory as the core algorithm, while the least squares optimization method is employed to determine the integration with unknown initial values during the reconstruction process. …”
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An Ensemble Learning Based Framework for Traditional Chinese Medicine Data Analysis with ICD-10 Labels by Gang Zhang, Yonghui Huang, Ling Zhong, Shanxing Ou, Yi Zhang, Ziping Li

“…The base learners are sorted by accuracy and diversity through nondominated sort (NDS) algorithm and combined through a deep ensemble learning strategy. …”
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Fast, super‐resolution sparse inverse synthetic aperture radar imaging via continuous compressive sensing by Lv Mingjiu, Ma Lei, Ma Jianchao, Chen Wenfeng, Yang Jun, Ma Xiaoyan, Cheng Qi

“…Second, to improve the resolution and reduce the computational burden significantly, a locally convergent iterative algorithm based on the alternating direction method of multipliers, which iteratively performs ANM with a sound reweighting strategy, is implemented. …”
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Nondestructive Testing on Ancient Wooden Components Based on Shapley Value by Li-hong Chang, Xiao-hong Chang, Hao Chang, Wei Qian, Li-ting Cheng, Xiao-li Han

“…By distributing the errors from the two nondestructive testing methods on the basis of a Shapley value algorithm, we determined the weights of stress wave and impedance meter data in the forecasting models and established combined forecasting models that showed greater accuracy with a mean relative error of less than 6%. …”
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Developing an Intelligent System for Efficient Botnet Detection in IoT Environment by Ramesh Singh Rawat, Manoj Diwakar, Umang Garg, Prakash Srivastava

“…This paper focused on analyzing botnet traffic in an IoT environment using machine learning and deep learning classifiers: Decision tree classifier, Naïve Bayes, K nearest neighbor, Convolution neural network, Recurrent neural network, and Random Forest. We calculated each algorithm's Accuracy, True Positive, False Positive, False Negative, True Negative, Precision, and Recall. …”
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A Driver Behavior Detection Model for Human-Machine Co-Driving Systems Based on an Improved Swin Transformer by Junhua Cui, Yunxing Chen, Zhao Wu, Huawei Wu, Wanghao Wu

“…The results show that the proposed model algorithm has a better performance in 10 classifications of driver behavior detection, with an accuracy of 99.42%, which is improved by 3.8% and 1.68% compared to Vgg16 and MobileNetV2, respectively. …”
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Loss shaping enhances exact gradient learning with Eventprop in spiking neural networks by Thomas Nowotny, James P Turner, James C Knight

“…Here, we investigate how the recently discovered Eventprop algorithm for gradient descent on exact gradients in spiking neural networks (SNNs) can be scaled up to challenging keyword recognition benchmarks. …”
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Machine learning-driven benchmarking of China's wastewater treatment plant electricity consumption by Minjian Li, Chongqiao Tang, Junhan Gu, Nianchu Li, Ahemaide Zhou, Kunlin Wu, Zhibo Zhang, Hui Huang, Hongqiang Ren

“…To overcome the complexity of wastewater compositions, an unsupervised machine learning algorithm, spectral clustering, is introduced to analyze 2,576 WWTPs across China, effectively characterizing influent quality as a single variable and contributing to robust benchmarks with 75 % of the fittings achieving coefficients of determination (R2) >0.85. …”
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Analysis and Dynamic Prediction of Bus Dwell Time Under Rainfall Conditions by Baoyun SUN, Yaping YANG, Lei DONG, Honglin LU, Zimin WANG

“…Support vector machine, k-nearest neighbour and backpropagation (BP) prediction models were established, and the BP neural network model, having the best prediction effect, was optimised using a genetic algorithm (GA). The constructed GA-BP prediction model was more realistic than the BP prediction model and can be used to predict bus dwell times under rainfall conditions. …”
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Cross-Modality 2D-3D Face Recognition via Multiview Smooth Discriminant Analysis Based on ELM by Yi Jin, Jiuwen Cao, Qiuqi Ruan, Xueqiao Wang

“…To speed up the learning phase of the classifier, the recent popular algorithm named Extreme Learning Machine (ELM) is adopted to train the single hidden layer feedforward neural networks (SLFNs). …”
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