Development and validation of an explainable machine learning model for mortality prediction among patients with infected pancreatic necrosisResearch in context by Caihong Ning, Hui Ouyang, Jie Xiao, Di Wu, Zefang Sun, Baiqi Liu, Dingcheng Shen, Xiaoyue Hong, Chiayan Lin, Jiarong Li, Lu Chen, Shuai Zhu, Xinying Li, Fada Xia, Gengwen Huang

“…Multiple organ failure, Acute Physiology and Chronic Health Examination II (APACHE II) score ≥20, duration of organ failure ≥21 days, bloodstream infection, time from onset to first intervention <30 days, Bedside Index of Severity in Acute Pancreatitis score ≥3, critical acute pancreatitis, age ≥ 50 years, and hemorrhage were 9 most important features associated with mortality. Furthermore, SHAP algorithm revealed insightful nonlinear interactive associations between important predictors and mortality, identifying 9 features pairs with high interaction SHAP value and clinical significance. …”
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Efficient Solutions of Multidimensional Sixth-Order Boundary Value Problems Using Symmetric Generalized Jacobi-Galerkin Method by E. H. Doha, W. M. Abd-Elhameed

“…The proposed algorithms are extended to solve the two-dimensional sixth-order differential equations. …”
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Reframing the filter bubble through diverse scale effects in online music consumption by Dougal Shakespeare, Victor Chareyron, Camille Roth

“…Abstract The impact of platforms’ algorithmic curation devices on users’ consumption diversity has long since been the subject of debate in popular culture and academia alike. …”
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DRAV: Detection and repair of data availability violations in Internet of Things by Jinlin Wang, Haining Yu, Xing Wang, Hongli Zhang, Binxing Fang, Yuchen Yang, Xiaozhou Zhu

“…In this work, the detection and repair of data availability violations (DRAV) framework is proposed to detect and repair data violations in Internet of Things with a distributed parallel computing environment. DRAV uses algorithms in the MapReduce programming framework, and these include detection and repair algorithms based on enhanced conditional function dependency for data consistency violation, MapJoin, and ReduceJoin algorithms based on master data for k -nearest neighbor–based integrity violation detection, and repair algorithms. …”
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Online Coregularization for Multiview Semisupervised Learning by Boliang Sun, Guohui Li, Li Jia, Kuihua Huang

“…Experiments show that our derived online coregularization algorithms achieve risk and accuracy comparable to offline algorithms while consuming less time and memory. …”
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Online Parameter Estimation in Digital Twins for Real-Time Condition Monitoring by Agus Hasan

“…This paper introduces innovative online parameter estimation algorithms that employ both deterministic and stochastic methodologies in digital twins for real-time condition monitoring. …”
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Comparative evaluation of SNVs, indels, and structural variations detected with short- and long-read sequencing data by Shunichi Kosugi, Chikashi Terao

“…The recall of SV detection with short-read-based algorithms was significantly lower in repetitive regions, especially for small- to intermediate-sized SVs, than that detected with long-read-based algorithms. …”
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Joint User Detection and Channel Estimation in Grant-Free Random Access for Massive MIMO Systems by Yang Yang, Guanghua Song, Hui Liu

“…As a result, these algorithms generate highly precise estimations of user channels. …”
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A Survey of Efficient Lightweight Cryptography for Power-Constrained Microcontrollers by Jesús Soto-Cruz, Erica Ruiz-Ibarra, Javier Vázquez-Castillo, Adolfo Espinoza-Ruiz, Alejandro Castillo-Atoche, Joaquin Mass-Sanchez

“…Therefore, lightweight and efficient security algorithms are essential. This review paper assesses the implementation of lightweight cryptographic algorithms for power-constrained microcontrollers in IoT systems using symmetric cryptography. …”
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Pedestrian navigation: how can inertial measurment units assist smartphones? by I. A. Chistyakov, I. V. Grishov, A. A. Nikulin, M. V. Pikhletsky, I. B. Gartseev

“…This paper is devoted to construction of reference walking trajectories for developing pedestrian navigation algorithms for smartphones. Such trajectories can be used both for verification of classical algorithms of navigation or for application of machine learning technics. …”
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Autonomous Planning of Multigravity-Assist Trajectories with Deep Space Maneuvers Using a Differential Evolution Approach by Ossama Abdelkhalik

“…The biologically inspired concept of hidden genes has been recently introduced in genetic algorithms to solve optimization problems where the number of design variables is variable. …”
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Heterogeneous Breast Phantom Development for Microwave Imaging Using Regression Models by Camerin Hahn, Sima Noghanian

“…As new algorithms for microwave imaging emerge, it is important to have standard accurate benchmarking tests. …”
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Copy-Move Forgery Verification in Images Using Local Feature Extractors and Optimized Classifiers by S. B. G. Tilak Babu, Ch Srinivasa Rao

“…CoMoFoD, CASIA, and MICC datasets and a combination of CoMoFoD and CASIA datasets images are used to quantify the performance of the proposed algorithms. The proposed algorithms are more efficient than state-of-the-art algorithms even though the suspected image is post-processed.…”
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Discrete resource allocation problems and military applications by Vytautas Tiešis

“…The non-linear models of multiple target prioritisation are presented in the case of multiple different weapons. The fast greedy algorithms are presented and investigated. In the case of homogeneous resources (weapons) the algorithms give optimal solutions. …”
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Rule-Based Classification Based on Ant Colony Optimization: A Comprehensive Review by Sayed Kaes Maruf Hossain, Sajia Afrin Ema, Hansuk Sohn

“…The Ant Colony Optimization (ACO) algorithms have been well-studied by the Operations Research community for solving combinatorial optimization problems. …”
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Mining Conditional Functional Dependency Rules on Big Data by Mingda Li, Hongzhi Wang, Jianzhong Li

“…Current Conditional Functional Dependency (CFD) discovery algorithms always need a well-prepared training dataset. …”
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Second-Order Model Reduction Based on Gramians by Cong Teng

“…Some new and simple Gramian-based model order reduction algorithms are presented on second-order linear dynamical systems, namely, SVD methods. …”
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Aircraft Detection for Remote Sensing Images Based on Deep Convolutional Neural Networks by Liming Zhou, Haoxin Yan, Yingzi Shan, Chang Zheng, Yang Liu, Xianyu Zuo, Baojun Qiao

“…However, the proposed algorithms still have a series of problems; for instance, the algorithms will miss some small-scale aircrafts when applied to the remote sensing image. …”
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From Integer Programming to Machine Learning: A Technical Review on Solving University Timetabling Problems by Xin Gu, Muralee Krish, Shaleeza Sohail, Sweta Thakur, Fariza Sabrina, Zongwen Fan

“…We explored the uses of machine learning algorithms and the hybrid solutions of combining the integer programming and machine learning algorithms in higher education timetabling solutions. …”
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Revisiting Sum of Residues Modular Multiplication by Yinan Kong, Braden Phillips

“…As the field matured, sum of residues modular multiplication lost favor to the extent that all recent surveys have either overlooked it or incorporated it within a larger class of reduction algorithms. In this paper, we present a new taxonomy of modular multiplication algorithms. …”
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