A Novel Approach in Oil Spill Detection, Identification, and Classification via Multisource Technologies and Artificial Intelligence by T. Avikasis Cohen, D. Angel, A. Brook

“…This study promotes an anomaly-based approach, treating oil spills as environmental outliers, and utilizes baseline water parameter comparisons to detect and monitor sea oil spills effectively. …”
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Multiple-Fault Diagnosis Method Based on Multiscale Feature Extraction and MSVM_PPA by Min Zhang, Zhenyu Cai, Wenming Cheng

“…In this paper, a novel method called multiscale feature extraction (MFE) and multiclass support vector machine (MSVM) with particle parameter adaptive (PPA) is proposed. …”
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Research on energy optimization control strategy for parallel hybrid tractor based on AIPSO. by Xiaohui Liu, Yiwei Wu, Jingyun Zhang, Yifan Zhao, Yangming Hu, Xianghai Yan

“…The study includes the design of power system parameters and the construction of a dynamic model for the entire machine. …”
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Topology optimization of the plate using neural networks by Yu. S. Selivanov, K. A. Matveev

“…The algorithm is based on the reparametrization of virtual densities by neural network parameters, which are optimized. The method of adaptive moment estimation is used as an optimization algorithm directly by the parameter of the neural network. …”
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EFFECT OF FLASK VIBRATION ON GRAY CAST IRON CHARACTERISTICS PREPARED BY LOST FOAM CASTING by Sutiyoko Sutiyoko, Lutiyatmi Lutiyatmi, Suyitno Suyitno, R. Soekrisno

“…Parameter selection in lost foam casting can reduce the casting defect. …”
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Analysis and Optimization of Cutting Tool Coating Effects on Surface Roughness and Cutting Forces on Turning of AA 6061 Alloy by Mahir Akgün, Fuat Kara

“…The present work has been focused on cutting force (Fc) and analysis of machined surface in turning of AA 6061 alloy with uncoated and PVD-TiB2 coated cutting inserts. …”
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AutoRL-Sim: Automated Reinforcement Learning Simulator for Combinatorial Optimization Problems by Gleice Kelly Barbosa Souza, André Luiz Carvalho Ottoni

“…Reinforcement learning is a crucial area of machine learning, with a wide range of applications. …”
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Revisiting universal extra-dimension model with gravity mediated decays by Kirtiman Ghosh, Katri Huitu, Rameswar Sahu

“…We derive updated constraints on the model’s parameter space by recasting ATLAS mono-photon, di-photon, and multi-jet search results using 139 inverse femtobern of integrated luminosity data. …”
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A REVIEW OF STARCH DAMAGE ON PHYSICOCHEMICAL PROPERTIES OF FLOUR by Nia Ariani Putri, Ila Maratush Shalihah, Alina Femi Widyasna, Riska Putri Damayanti

“…The presence of starch damage is an important parameter to determine the physicochemical properties of flour. …”
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PROBLEMS OF COMMERCIAL BANK ATM NETWORK FORMATION by J. V. Domashova

“…The problem of building an automatic teller machine (ATM) network of a commercial bank consists of both identifying analytical indicators of its efficiency, and developing its construction model. …”
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Application of Simulated Annealing Algorithm in the Construction of Online Examination System for Tax Law Courses by da Pan

“…Future enhancements include integrating machine learning techniques to refine SA’s parameter tuning and further improving exam personalization.…”
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Interpretable Evaluation of Sparse Time–Frequency Distributions: 2D Metric Based on Instantaneous Frequency and Group Delay Analysis by Vedran Jurdana

“…These benefits highlight its usability in advanced methods and machine-related applications.…”
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Fault Detection Enhancement in Rolling Element Bearings Using the Minimum Entropy Deconvolution by Tomasz BARSZCZ, Nader SAWALHI

“…Minimum Entropy Deconvolution (MED) has been recently introduced to the machine condition mon- itoring field to enhance fault detection in rolling element bearings and gears. …”
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Nondestructive Detection and Quality Grading System of Walnut Using X-Ray Imaging and Lightweight WKNet by Xiangpeng Fan, Jianping Zhou

“…To solve the challenges of walnut quality detection, we presented the first comprehensive investigation of walnut quality detection method using X-ray imaging and deep learning model. An X-ray machine vision system was designed, and a walnut kernel detection (called WKD) dataset was constructed. …”
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Solution of a flexible jobshop scheduling problem using an Estimation of Distribution Algorithm. by R. Pérez, S. Jöns, A. Hernández

“…The flexible jobshop scheduling problem permits the operation of each job to be processed by more than one machine. The configuration mentioned generally seeks to minimize the completion time of all jobs known in the literature as ‘makespan’. …”
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Adaptation of k-means to automated forecasting of poorly structured time series of economic dynamics by Dunskaia Lada, Popova Elena

“…Data mining methods used in machine learning or deep learning allow to take into account complex patterns and nonlinear dependencies in the data. …”
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AI enabled, mobile soil pH classification with colorimetric paper sensors for sustainable agriculture. by Ademir Ferreira da Silva, Ricardo Luis Ohta, Jaione Tirapu Azpiroz, Matheus Esteves Ferreira, Daniel Vitor Marçal, André Botelho, Tulio Coppola, Allysson Flavio Melo de Oliveira, Murilo Bettarello, Lauren Schneider, Rodrigo Vilaça, Noorunisha Abdool, Vanderlei Junior, Wellington Furlaneti, Pedro Augusto Malanga, Mathias Steiner

“…The classification task is performed by a machine-learning model which was trained on the colorimetric pH indicators deployed on the paper sensor. …”
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Quantifying the Spatiotemporal Evolution of Radiation Belt Electrons Scattered by Lower Band Chorus Waves: An Integrated Model by Weixin Chen, Song Fu, Xin Ma, Binbin Ni, Deyu Guo, Qiongyue Zhang, Xiangyuan Tong, Yibo Zhao, Xing Cao, Zheng Xiang, Yuan Lei

“…Here we present a new model, by integrating the machine learning technique and kinetic simulations, to analyze the spatiotemporal evolution of radiation belt electrons scattered by lower band chorus (LBC). …”
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Deep neural networks for endemic measles dynamics: Comparative analysis and integration with mechanistic models. by Wyatt G Madden, Wei Jin, Benjamin Lopman, Andreas Zufle, Benjamin Dalziel, C Jessica E Metcalf, Bryan T Grenfell, Max S Y Lau

“…Our work also provides valuable insights into more effectively integrating machine learning models with mechanistic models to enhance public health responses to measles and similar infectious disease systems.…”
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Design and Simulation of Chinese Cabbage Harvester by Simo Liu, Xuhui Yang, Zhe Zhang, Jianing Xu, Ping Zhao, Subo Tian, Lihua Wei, Xiaofeng Ning

“…Based on the actual operating conditions of the Chinese cabbage harvester and the simulated operating parameters, the optimal parameter combination was finally determined as follows: rotating speed of the root cutting device was 200 r/min, rotating speed of the flexible clamping conveyor belt was 160 r/min, rotating speed of the drawing device was 100 r/min, and machine walking speed was 1.4 km/h, respectively. …”
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