Accuracy of administrative data for surveillance of healthcare-associated infections: a systematic review by Karel G M Moons, Marc J M Bonten, Maaike S M van Mourik, Pleun Joppe van Duijn, Grace M Lee

“…Administrative data algorithms, including (combinations of) diagnosis codes, are commonly used to determine the occurrence of HAI, either to support within-hospital surveillance programmes or as free-standing quality indicators. …”
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Location Information-Based Routing Protocol for Energy Harvesting Cognitive Radio Wireless Sensor Network by Mohamad-Rida Mortada, Abbass Nasser, Alaaeddine Ramadan, Koffi-Clement Yao, Ali Mansour

“…LIBRO has been recently proposed as an efficient routing algorithm for traditional WSN networks. In this paper, we extend its application to EH-CWSNs, in which the WSN nodes act as Secondary Users (SUs). …”
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Fast 3D Transmission Tower Detection Based on Virtual Views by Liwei Zhou, Jiaying Tan, Jing Fu, Guiwei Shao

“…Finally, by leveraging the projection transformation between the virtual image and the 3D point cloud, combined with a 3D region growing algorithm, the 3D points belonging to the TTs are extracted from the whole 3D point cloud. …”
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A Fluid Model for Mobile Data Offloading Based on Device-to-Device Communications with Time Constraints by Antonio Pinizzotto, Raffaele Bruno

“…Although several analytical models have been developed to derive theoretical performance bounds of D2D-based offloading schemes under different user mobility patterns and routing algorithms used for content dissemination, how to jointly analyse time-limited caching and forwarding policies with both constant and asynchronous timeouts remains still an unsolved problem. …”
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Air Pollution Forecasting Using Artificial and Wavelet Neural Networks with Meteorological Conditions by Qingchun Guo, Zhenfang He, Shanshan Li, Xinzhou Li, Jingjing Meng, Zhanfang Hou, Jiazhen Liu, Yongjin Chen

“…When Bayesian regularization was applied as a training algorithm, the WANN and ANN models accurately reproduced the APIs in both Xi’an and Lanzhou, although the WANN model (R = 0.8846 for Xi’an and R = 0.8906 for Lanzhou) performed better than the ANN (R = 0.8037 for Xi’an and R = 0.7742 for Lanzhou) during the forecasting stage. …”
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Real-Time Physics Simulation Method for XR Application by Nak-Jun Sung, Jun Ma, Kunthroza Hor, Taeheon Kim, Hongly Va, Yoo-Joo Choi, Min Hong

“…The system is deployed within the Unity engine and enhances real-time performance through the use of sophisticated collision detection and response algorithms. Our method employs an AABB-based bounding volume hierarchy (BVH) structure to efficiently detect collisions, and incorporates the Möller–Trumbore algorithm for precise triangle-level interactions. …”
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Multilayer entropy-weighted TOPSIS method and its decision-making in ecological operation during the subsidence period of the Three Gorges Reservoir by Ai Xueshan, Yu Yangxin, Liang Zhiming, Shi Xuanyu, Cao Rui, Zhang Xiaoke

“…A multi-objective optimal reservoir scheduling model was constructed to coordinate the spawning flow demand of " Four Major Chinese Carps"; The model takes the maximum power generation and the maximum membership degree of downstream river ecological water demand as the objective functions, and uses the dynamic programming multi-objective solution algorithm based on penalty factors to solve the problem, and obtains the non-inferior solution set in each scenario. …”
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Optimized ANFIS-Based Robust Nonlinear Control of a Solar Off-Grid Charging Station for Electric Vehicles by Bibi Tabassam Gul, Iftikhar Ahmad, Habibur Rehman, Ammar Hasan

“…The controller gains are optimized using the grey wolf optimization algorithm, and global stability is demonstrated through Lyapunov stability analysis. …”
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A multi-scale rotated ship targets detection network for remote sensing images in complex scenarios by Siyu Li, Fei Yan, Yunqing Liu, Yuzhuo Shen, Lan Liu, Ke Wang

“…The mAP07, mAP12 on the HRSC2016 dataset, as well as the mAP in the ship category of the DOTA dataset, show a significant advantage over other commonly used object detection algorithms, with accuracies of 90.70%, 98.98%, and 89.46%, respectively. …”
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An Estimation Model on Electricity Consumption of New Metro Stations by Zhao Yu, Yun Bai, Qian Fu, Yao Chen, Baohua Mao

“…., passenger volume, air temperature and relative humidity). A genetic algorithm with five-fold cross-validation is used to optimize the hyper-parameters of the SVR model in order to improve its accuracy in estimating the electricity consumption of a metro station (ECMS). …”
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The effects of linear energy density and gas environment on droplet spatter characteristics and dynamics during selective laser melting by Guang Yang, Qi Liu, Da An, Xiangming Wang, Ranliang Wu, Han Xie

“…Utilizing high-speed imaging technology and a novel image processing method, we developed a new spatter feature extraction algorithm to analyze the number, area, angle, and speed of the spatter under different energy densities and protective gas directions. …”
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Traffic Status Prediction of Arterial Roads Based on the Deep Recurrent Q-Learning by Wei Hao, Donglei Rong, Kefu Yi, Qiang Zeng, Zhibo Gao, Wenguang Wu, Chongfeng Wei, Biljana Scepanovic

“…The model is based on the optimized Long Short-Term Memory (LSTM) algorithm to handle the explosive growth of Q-table data, which not only avoids the gradient explosion and disappearance but also has the efficient storage and analysis. …”
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Ensemble Deep Learning Object Detection Fusion for Cell Tracking, Mitosis, and Lineage by Imad Eddine Toubal, Noor Al-Shakarji, D. D. W. Cornelison, Kannappan Palaniappan

“…EDNet detections are used in our M2Track multiobject tracking algorithm for tracking cells, detecting cell mitosis (cell division) events, and cell lineage graphs. …”
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Assessment of crack growth development in main pipeline on the basis of elastoplastic model by К. А. Vansovich, I. P. Aistov, А. А. Nakhlestkin, D. S. Beseliya

“…ANSYS developed an algorithm for modeling crack growth taking into account residual stresses. …”
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Knowledge-driven semantic converting method of multimodal models toward a geospatial perspective by Jianbo Lai, Jun Zhu, Pei Dang, Jianlin Wu, Yukun Guo, Xinyu Yang, Na Li

“…Subsequently, a structural matching template based on knowledge reuse was established, and a knowledge-guided algorithm for multimodal model transformation was designed. …”
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Comparison between Hyperspectral Imaging and Chemical Analysis of Polyphenol Oxidase Activity on Fresh-Cut Apple Slices by Luna Shrestha, Boris Kulig, Roberto Moscetti, Riccardo Massantini, Elke Pawelzik, Oliver Hensel, Barbara Sturm

“…Golden Delicious and Elstar) were used to build a robust detection algorithm, which is independent of cultivars and applied treatments. …”
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Discovering the Graph-Based Flow Patterns of Car Tourists Using License Plate Data: A Case Study in Shenzhen, China by He Bing, Kong Bo, Yin Ling, Wu Qin, Hu Jinxing, Huang Dian, Ma Zhanwu

“…Finally, a frequent subgraph mining algorithm is used to extract the flow patterns of car tourists. …”
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AlgaeClass_Net: Optimizing Few-Shot Marine Microalgae Classification With Multi-Scale Feature Enhancement Network by Dan Liu, Guihong Yuan, Huachao Tan, Yanbo Jiang, Hai Bi, Yuan Cheng

“…Existing few-shot learning classification algorithms that utilize meta-learning for metrics can be a good solution to this problem. …”
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Multi-Disaster Hazard Analysis, The Case of Elazığ Province by Fethi Ahmet Canpolat

“…Various methods, such as the Analytic Hierarchy Process (AHP) and machine learning models, including the Random Forest algorithm, were employed to assess the severity and probability of exposure for each hazard type. …”
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Multistage identification method for real-time abnormal events of streaming data by Hao Luo, Kexin Sun, Junlu Wang, Chengfeng Liu, Linlin Ding, Baoyan Song

“…The identification method proposed in this article first takes advantages of the dynamic time warping algorithm, which is widely applied in the field of audio recognition, to build an anti-aliasing model and identifies whether the perceived data are disaster signal based on the similarity fitting between them and the template waveform of historical disaster data, and second, since the real-time monitoring data are continuous streaming data, it is necessary to identify the start point of the disaster waveform before the identification of the disaster signal. …”
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