Optimization of Short-Lag Spatial Coherence Imaging Method by Jakub DOMARADZKI, Marcin LEWANDOWSKI, Norbert ŻOŁEK, Marcin LEWANDOWSKI

“…The approach has been tested by comparing results obtained with the original SLSC algorithm on data acquired from tissue phantoms. …”
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Driving Supply Chain Transformation with IoT and AI Integration: A Dual Approach Using Bibliometric Analysis and Topic Modeling by Jerifa Zaman, Atefeh Shoomal, Mohammad Jahanbakht, Dervis Ozay

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Optimized Reduction in Draft Tube Pressure Pulsation for a Francis Turbine by J. Lu, R. Tao

“…Therefore, based on the genetic algorithm (GA) and pulsation tracking network (PTN), this article optimizes the draft tube pressure pulsation (DTPP) problem of the Francis turbine and finds that the DTPP is mainly dominated by rotation frequencies (fn) of 0.2, 0.4, 0.6, and 0.8. …”
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Review and Mapping of Search-Based Approaches for Program Synthesis by Takfarinas Saber, Ning Tao

“…Results: Through analysis, we identified and categorised the main techniques with their trends. We have also mapped and shed light on patterns connecting the problem, the representation and the search algorithm type. …”
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A Fused Multiscale Pictorial Sequence Learning Mechanism Applied to Pavement Detection by Zhang Jiazhen, Wang Xiulai, Zhao Shuxu

“…Using the SVM classifier with the global sequence alignment algorithm as the main kernel function, the data classification module detects anomalies, so that the algorithm can mine valuable feature attributes from multiple angles as much as possible while stably exerting its classification function. …”
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The Problem of Finding the Maximal Multiple Flow in the Divisible Network and its Special Cases by A. V. Smirnov

“…If k ≥ 3, the problem is NP-complete. The algorithms for each polynomial subclass are suggested. …”
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Comprehensive MILP Formulation and Solution for Simultaneous Scheduling of Machines and AGVs in a Partitioned Flexible Manufacturing System by Cheng Zhuang, Jingbo Qu, Tianyu Wang, Liyong Lin, Youyi Bi, Mian Li

“…This paper proposes a comprehensive Mixed-Integer Linear Programming (MILP) formulation for the simultaneous scheduling of machines and Automated Guided Vehicles (AGVs) within a partitioned Flexible Manufacturing System (FMS). The main objective is to numerically optimize the simultaneous scheduling of machines and AGVs while considering various workshop layouts and operational constraints. …”
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Simulation and Optimization of Metro Train Braking Rate under the Timing Condition by PAN Yang

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Virtual power plant to ensure reliable power supply and accident-free operation of process equipment of a mining enterprise by Telmanova E.D., Abdrakhmanov I.D.

“…To ensure real-time integrated control and coordination with various energy and technological objects, the algorithm for solving combinatorial optimization problems "fruit fly" or "fruit fly algorithm" (BAS) is proposed. …”
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On Some Approaches to the Solution of the Problem «Useful Proof-of-work for Blockchains» by Valeriy G. Durnev, Dmitry M. Murin, Valery A. Sokolov, Dmitry Ju. Chalyy

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Comparative Study on Prediction Models for Crack Opening Degree in Concrete Dam by HUANG Song, WU Jie, FANG Zhanchao, CHU Huaping, WU Yan'gang, XUE Zilong, HE Linbo

“…In this study, multiple linear regression, stepwise regression, and random forest algorithm were used to establish models for the crack opening degree of a concrete gravity dam based on the monitoring data of the crack opening degree of the concrete gravity dam. …”
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Gradient Descent Algorithm with Greedy Repositioning Using Power Deficit Aggregation of Wakes to Accelerate the Offshore Wind Farm Layout Optimization Problem in Irregular Concessi... by Angel Gaspar Gonzalez-Rodriguez, Juan Manuel Roldan-Fernandez, Javier Serrano-Gonzalez, José Vicente Muñoz-Díez

“…A new layout optimization method for offshore wind farms is proposed to minimize power deficits due to the wake effect without limitation on the number of turbines, the shape, or the extension of the concession area. The main engine of the algorithm is a gradient-descent method in which throughout the optimization process, new turbines are progressively and randomly included within the concession area and quickly expand outward, looking for areas with less perturbation, in turn, pushing the previous ones. …”
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Optimisation of Aluminium Alloy Variable Diameter Tubes Hydroforming Process Based on Machine Learning by Yong Xu, Xuewei Zhang, Wenlong Xie, Shihong Zhang, Yaqiang Tian, Liansheng Chen

“…The minimum wall thickness, maximum wall thickness, and maximum expansion height of the formed tubes are included in the main evaluation factors of the forming results. A variety of machine learning algorithms are used to predict, and the prediction results are compared with the finite element model in terms of error. …”
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A novel mobile robot path planning method based on neuro-fuzzy controller by Abbas Mostafanasab, Mohammad Bagher Menhaj, Mahnaz Shamshirsaz, Rasul Fesharakifard

“…Also, this algorithm is able to distance the robots from the obstacles (i.e. it  provides a solution to the obstacle avoidance problem). …”
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Diagnosis of Pain Deception Using Minnesota Multiphasic Personality Inventory-2 Based on XGBoost Machine Learning Algorithm: A Single-Blinded Randomized Controlled Trial by Hyewon Chung, Kihwan Nam, Subin Lee, Ami Woo, Joongbaek Kim, Eunhye Park, Hosik Moon

“…For analyzing the MMPI-2, the XGBoost ML algorithm was applied. <i>Results</i>: Of a total of 96 participants, 50 and 46 were assigned to the ND group and the D group, respectively. …”
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PSO-FDM (Particle Swarm Optimization-Finite Difference Method)-Based Simulation Model of Temperature and Velocity of Full-Scale Continuous Annealing Furnace by Yang Liu, Qiang Guo, Tieheng Yuan, Yingrui Han, Chao Liu, Wenquan Sun

“…To improve the prediction accuracy for different strip sizes, the PSO optimization algorithm was employed to determine the optimal heat transfer coefficient for each strip size. …”
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Food Cooking Process Modeling With Neural Networks by Javier Fananas-Anaya, Gonzalo Lopez-Nicolas, Carlos Sagues, Sergio Llorente

“…Specifically, we propose a Nonlinear AutoRegressive with eXogenous inputs Neural Network (NARX-NN). The main novelty is that we define a novel training algorithm adapted to the modeling of real-time dynamical systems, allowing a NARX-NN with a simple structure to obtain a negligible error compared to the results of the original FEM model. …”
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Machine Learning Algorithm-Aided Determination of Predictors of Mortality from Diabetic Foot Sepsis at a Regional Hospital in South Africa During the COVID-19 Pandemic by Carlos Matsinhe, Shingirai Brenda Kagodora, Tshifhiwa Mukheli, Tshepo Polly Mokoena, William Khabe Malebati, Maeyane Stephens Moeng, Thifhelimbilu Emmanuel Luvhengo

“…Supervised machine learning algorithms were used to compare their ability to predict mortality due to diabetic foot sepsis. …”
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MODEL OF ORGANIZATION OF KIDNEY CANCER EARLY DIAGNOSIS by V. G. Moreva, G. N. Alekseeva, P. F. Kiku, L. I. Gurina, K. M. Sabirova, V. N. Rasskazova

“…The model included a population questionnaire to identify risk factors and algorithm of patient routing («roadmap») with suspected kidney cancer for in-depth examination and treatment. …”
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Virtual care for prostate cancer survivorship: protocol for an evaluation of a nurse-led algorithm-enhanced virtual clinic implemented at five cancer centres across Canada by Antonio Finelli, Ricardo Rendon, Joseph A Cafazzo, Robert Hamilton, Alejando Berlin, Jacqueline L Bender, Denise Bryant-Lukosius, Quynh Pham, Jason Hearn, Ian Brown, Andrew H Feifer, Geoffrey Gotto

“…Despite the promise of the Ned Clinic, the model remains limited by its dependence on oncology specialists, lack of an autonomous triage algorithm, and has only been implemented among PCa survivors living in Ontario.Methods and analysis Our programme of research comprises two main research objectives: (1) to evaluate the process and cost of implementing and sustaining five nurse-led virtual PCa survivorship clinics in three provinces across Canada and identify barriers and facilitators to implementation success and (2) to assess the impact of these virtual clinics on implementation and effectiveness outcomes of enrolled PCa survivors. …”
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