Minimal‐cost route planning via Fibonacci‐heap‐typed data structure by Wangjia Zhan, Haohao Qiu, Bo Min, Lin Lin

“…In particular, the article introduces a Fibonacci‐heap‐typed data structure to the minimal‐cost route planning algorithm, resulting in a remarkable reduction of the time complexity from O(mn) to O(m+nlogn), where m and n represent the cardinalities of the arc set and nodeset, respectively. …”
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Mathematical Modeling of Tuberculosis Transmission Dynamics With Reinfection and Optimal Control by Francis Oketch Ochieng

“…The model was fitted to historical TB incidence data for Kenya from 2000 to 2022 using lsqcurvefit algorithm in MATLAB software. The fitting algorithm yielded a mean absolute error (MAE) of 0.0069, demonstrating a close alignment between simulated and observed data. …”
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The powerless bosses: the working day experience of bicycle messengers and its impact on their identities and wellbeing by Iben Østin Hjelle, Helle Nordrum, Julian-Werner Wentzeck, Ali Teymoori

“…Results We discerned five themes related to the dynamics of autonomy versus algorithmic control, the reduction of workers’ identity to the courier role, lack of collegial bonding among bicycle messengers, physical demands and risks of the job, and the transitory nature of courier work. …”
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Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels by Yi-bing Li, Xue-ying Diao, Qian-hui Dong

“…Simulation results show that rank minimization interference minimization algorithm can provide more interference-free dimensions for desired signals than other rank minimization methods. …”
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Weak fault diagnosis method for rolling bearings under strong background noise based on EEMD-FK-AMCKD by XIE Guizhong, XU Shuaiqiang, DU Wenliao, LUO Shuangqiang, LI Hao, WANG Liangwen, GONG Xiaoyun

“…Next, the fast kurtogram algorithm was employed to determine the carrier frequency, bandwidth, and the layer with the maximum kurtosis value of the reconstructed signal, enabling the design of a bandpass filter for noise reduction. …”
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Species-level classification of urban trees from WorldView-2 imagery in Debrecen, Hungary: An effective tool for planning a comprehensive green network to reduce dust pollution by Vanda Eva MOLNAR, Edina SIMON, Szilárd SZABÓ

“…The best overall accuracy was achieved with the ML algorithm applied to the first four transformed bands (75.1%), and with the SVM algorithm applied to eight bands (71.0%). …”
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New timestamp mark–based energy efficient time synchronization method for wireless sensor networks by Yourui Huang, Gang Zhang, Min Kong, Fugui He

“…The group-wise pair selection algorithm is used to select the network’s pairwise synchronization nodes, and chain-type network topology is thus generated. …”
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Applications of machine learning in decision analysis for dose management for dofetilide. by Andrew E Levy, Minakshi Biswas, Rachel Weber, Khaldoun Tarakji, Mina Chung, Peter A Noseworthy, Christopher Newton-Cheh, Michael A Rosenberg

“…A reinforcement learning algorithm informed by unsupervised learning was able to predict dosing decisions with 96.1% accuracy. …”
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A Bit String Content Aware Chunking Strategy for Reduced CPU Energy on Cloud Storage by Bin Zhou, ShuDao Zhang, Ying Zhang, JiaHao Tan

“…The existing chunking algorithm greatly reduces the system performance when confronted with big data and it wastes a lot of energy. …”
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The Value of Morphologic Study (MRI) of the Median Nerve in Stadialization and Treatment of the Carpal Tunnel Syndrome by Florin Gabriel PANCULESCU, Raluca STEFANESCU, Ion BORDEIANU, Iulian Catalin BRATU

“…The criterion of diameter decrease can be a benchmark in order to establish a therapeutic algorithm in carpal tunnel syndrome.…”
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Optimal design of high‐performance rare‐earth‐free wrought magnesium alloys using machine learning by Shaojie Li, Zaixing Dong, Jianfeng Jin, Hucheng Pan, Zongqing Hu, Rui Hou, Gaowu Qin

“…Abstract In this study, a small dataset of 370 datapoints of Mg alloys are selected for machine learning (ML), in which each datapoint includes five rare‐earth‐free alloying elements (Ca, Zn, Al, Mn and Sn), three extrusion parameters (extrusion speed, temperature and ratio), and three mechanical properties (yield strength [YS], ultimate tensile strength [UTS] and elongation [EL]). The ML algorithms, including support vector machine regression (SVR), artificial neural network, and other three methods, are employed, and the SVR has the best performance in predicting mechanical properties based on the components, and process parameters, with the mean absolute percentage error of YS, UTS, and EL being 6.34%, 4.19%, and 13.64% in the test set, respectively. …”
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A Self-Supervised Feature Point Detection Method for ISAR Images of Space Targets by Shengteng Jiang, Xiaoyuan Ren, Canyu Wang, Libing Jiang, Zhuang Wang

“…The experiments demonstrate that SFPD has better performance in feature point detection and feature point matching than usual algorithms.…”
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An FPGA-accelerated multi-level AI-integrated simulation framework for multi-time domain power systems with high penetration of power converters by Chen Liu, Peng Su, Hao Bai, Xizheng Guo, Alber Filbà Martínez, Jose Luis Dominguez Garcia

“…The framework structures systems hierarchically using energy transmission functions and unified energy information flow-based surrogate models with defined ports, ensuring compatibility with artificial intelligence algorithms. By integrating AI techniques, such as back propagation neural networks, the framework predicts variables with high computational complexity, improving accuracy and simulation efficiency. …”
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TPE-LCE-SHAP: A Hybrid Framework for Assessing Vehicle-Related PM2.5 Concentrations by Hamad Almujibah, Abdulrazak H. Almaliki, Caroline Mongina Matara, Adil Abdallah Mohammed Elhassan, Khalaf Alla Adam Mohamed, Mudthir Bakri, Afaq Khattak

“…This hybrid framework delivers robust predictive accuracy and actionable insights, making it a valuable tool for effective environmental management and policy making.…”
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Synthesis and characterization of machine learning designed TADF molecules by Weimei Shi, Yan Li, Ziying Zhang, Zheng Tan, Shiqing Yang

“…In this study, we present a novel approach to the development of thermally activated delayed fluorescence (TADF) molecules with potentials for organic light-emitting diode (OLED) applications, leveraging machine learning (ML) algorithms to guide the materials design process. Recognizing the imperative for high-efficiency, low-cost emissive materials, we integrated ML driven models with experimental characterization to expedite the discovery of TADF compounds. …”
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Artificial intelligence as a transforming factor in motility disorders–automatic detection of motility patterns in high-resolution anorectal manometry by Miguel Mascarenhas, Francisco Mendes, Joana Mota, Tiago Ribeiro, Pedro Cardoso, Miguel Martins, Maria João Almeida, João Rala Cordeiro, João Ferreira, Guilherme Macedo, Cecilio Santander

“…The testing dataset was used for models’ evaluation through its accuracy, sensitivity, specificity, positive and negative predictive values and area under the receiving-operating characteristic curve. …”
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Does the hepatologist still need to rely on aminotransferases in clinical practice? A reappraisal of the role of a classic biomarker in the diagnosis and clinical management of chr... by Patrizia Burra, Calogero Cammà, Pietro Invernizzi, Fabio Marra, Maurizio Pompili

“…ALT, a sensitive and cost-effective marker of liver injury, remains pivotal in predicting clinical outcomes and guiding interventions in several chronic liver diseases including metabolic dysfunction-associated steatotic liver disease, and chronic viral hepatitis. …”
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Topological Optimization of Dynamic Stiffness in Continuum Structure Based on Bidirectional Evolutionary Structural Optimization by JIANG Xudong, LIU Zheng, TENG Xiaoyan

“…By minimizing structural dynamic compliance, the programming scheme of optimal stiffness for continuum structure under dynamic load is proposed, by combination of Equivalent Static Loads with Bidirectional Evolutionary Structural Optimization To effectively decrease calculation scale for dynamic optimization in structural topology, the Equivalent Static Loads Method is applied to transforming dynamic optimization to static one that is solved by Bidirectional Evolutionary Structural Optimization in structural topology To enhance the optimal efficiency of the original BESO method to optimization of dynamic stiffness in continuum structure, a design domain reduction method is developed to establish a new volume control and a stop criterion in this study Numerical results show that the dynamic compliance is asymptotically convergent to optimal solution with volume constraint precisely 〖JP3〗satisfied, and optimal configuration can effectively inhibit the vibration induced by dynamic load Whereby the presented optimization algorithm is verified to be robust and adapt Consequently it is provided with theoretical significance to extend the original Evolutionary Structural Optimization Method to dynamic optimization in structural design…”
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Intelligent Energy Management in an Isolated DC Microgrid using Fuzzy Logic by Youssfi Abdelaziz, El Kadi Youssef Ait

“…The PV system is controlled by a MPPT method implementing the INC algorithm, while the storage system is managed by a PI controller to control battery charging and discharging. …”
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A Novel Method for Mechanical Fault Diagnosis Based on Variational Mode Decomposition and Multikernel Support Vector Machine by Zhongliang Lv, Baoping Tang, Yi Zhou, Chuande Zhou

“…A novel fault diagnosis method based on variational mode decomposition (VMD) and multikernel support vector machine (MKSVM) optimized by Immune Genetic Algorithm (IGA) is proposed to accurately and adaptively diagnose mechanical faults. …”
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