FEA-Based Design Procedure for IPMSM and IM for a Hybrid Electric Vehicle by Emad Roshandel, Amin Mahmoudi, Wen L. Soong, Solmaz Kahourzade, Nathan Kalisch

“…The differences between the performance parameters of the studied machines are discussed, and the advantages and disadvantages of each design are highlighted. …”
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Discrete Element-Based Design of a High-Speed Rotary Tiller for Saline-Alkali Land and Verification of Optimal Tillage Parameters by Shuai Zheng, Tong Lu, Jie Liu, Yu Tian, Miaomiao Han, Muhao Tai, Shuqi Gao, Tao Liu, Dongwei Wang, Zhuang Zhao

“…Using Design-Expert analysis software, we obtained the following optimal combination of parameters: a knife roller speed at 310 r/min, tillage depth of 13.2 cm, and machine forward speed of 4.8 km/h. …”
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Influence of Welding Parameters on Mechanical Properties and Microstructure of Similar Low-Carbon Steel AISI 1005 Welding by Resistance Spot Welding by Osamah Sabah Barrak, Sami Chatti, Slim Ben-Elechi

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Evaluation of the impact of printing and embroidery parameters in the process of obtaining utility comfort sensors used in protective clothing dedicated to premature babies by Ewa Skrzetuska, Grzegorz Szparaga, Karolina Wilgocka

“…This article describes the influence of screen printing and machine embroidery on the development of sensors designed to measure skin parameters such as temperature and humidity using a paste containing carbon nanotubes and four different electrically conductive yarns. …”
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Decision Tree for Determining Hospital Treatment for Covid-19 Patients Based on Hematology Parameters Using the C5.0 Algorithm by Joko Riyono, Christina Eni Pujiastuti, Supriyadi Supriyadi, Dody Prayitno, Aina Latifa Riyana Putri

“…Therefore, a classification analysis will be carried out to make decisions regarding determining COVID-19 patients who do not require hospitalization or who require Regular Ward, Semi-Intensive Care Unit, or Intensive Care Unit (ICU) in hospitals based on hematology parameters from the Machine Learning Repository. Kaggle Dataset uses the C5.0 algorithm assisted by Rstudio software. …”
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Investigation into Using CFD for Estimation of Ship Specific Parameters for the SPICE Model for Prediction of Sea Spray Icing: Part 1—The Proposal by Sujay Deshpande, Per-Arne Sundsbø

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Effect of Single-Point Incremental Forming Process Parameters on Roughness of the Outer Surface of Conical Drawpieces from CP Titanium Sheets by Marcin Szpunar, Robert Ostrowski, Department of Manufacturing and Production Engineering, Faculty of Mechanical Engineering and Aeronautics, Rzeszów University of Technology, al. Powstancow Warszawy 8, 35-959 Rzeszow, Poland

“…With the widespread use of numerically controlled machine tools, single-point incremental forming (SPIF) process has enjoyed growing interest in the industry. …”
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Fourier Features and Machine Learning for Contour Profile Inspection in CNC Milling Parts: A Novel Intelligent Inspection Method (NIIM) by Manuel Meraz Méndez, Juan A. Ramírez Quintana, Elva Lilia Reynoso Jardón, Manuel Nandayapa, Osslan Osiris Vergara Villegas

“…The results demonstrate that the NIIM offers 96.99% accuracy, low computational requirements, 100% inspection capability, and valuable information to improve machining parameters, as well as quality classification.…”
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Optimization of process parameters in Nano-particle mixed EDM of hardened die steel AISI H13 using RSM and GA by Tasfia Saba, AKM Nurul Amin, Sanjida Islam, Maisha Rahman Chaity, Noshin Tasnim Tuli, Adib Bin Rashid

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THE EFFECT OF COMBINED CHEMOTHERAPY IN WOMEN WITH BREAST CANCER ON THE STIFFNESS OF THE COMMON CAROTID ARTERY AND PULSE WAVE PARAMETERS STUDIED BY ECHO TRACKING by A. R. Zairova, A. N. Rogoza, A. A. Avalyan, E. V. Oshchepkova

“…Arterial stiffness parametres (β-stiffness index, Ep-elastic modulus, AC-arterial compliance, PWV-pulse wave velocity) and AI - augmentation index were studied in the distal CCA at a distance of 2 cm from bifurcation on an Aloka ProSound α7 ultrasound machine using echo tracking technology.Results. After combined chemotherapy the parameters b, Ep, PWV not significantly changed (9,3±4,3 vs 8,9±4,5, р=0,63 ;128,73±65,9 vs 119,0±69,5 кПа, р=0,29 ; 6,7±1,5 vs 6,3±1,5 m/s, р=0,24 respectively). …”
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Synergistic Framework for Fuel Cell Mass Transport Optimization: Coupling Reduced-Order Models with Machine Learning Surrogates by Shixin Li, Qingshan Liu, Yisong Chen

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Regional stream temperature modeling in pristine Atlantic salmon rivers: A hybrid deterministic–Machine Learning approach by Ilias Hani, André St-Hilaire, Taha B.M.J. Ouarda

“…Key explanatory variables include low cloud coverage, high wind speed quantiles, upstream land cover areal coverage, distance to the coast, watershed orientation, and topographical features describing surface curvature and elevation. The machine learning-based regionalization approach provides a robust approach for deriving water temperature model parameters from watershed attributes, provided flow measurements are available. …”
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Unveiling processing–property relationships in laser powder bed fusion: The synergy of machine learning and high-throughput experiments by Mahsa Amiri, Zahra Zanjani Foumani, Penghui Cao, Lorenzo Valdevit, Ramin Bostanabad

“…Here, we propose a methodology embracing the synergy between high-throughput (HT) experimentation and hierarchical machine learning (ML) to unveil the complex relationships between a large set of process parameters in Laser Powder Bed Fusion (LPBF) and selected mechanical properties (tensile strength and ductility). …”
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Identification and Experimental Study of Sand Gravel Formations Driven by an Earth Pressure Balance Shield Machine Based on GTNet by Peng Zhou, Qian Wang, Ziwen Wang, Jiacan Xu, Zi Wang

“…The effects of different parameters were weighted using the ablation study for tunneling parameters. …”
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Insights into Machining Techniques for Additively Manufactured Ti6Al4V Alloy: A Comprehensive Review by Abdulkadir Mohammed Sambo, Muhammad Younas, James Njuguna

“…Investigation into the post-processing machinability of Ti6Al4V alloy is increasingly crucial in the manufacturing industry, particularly in the machining of additively manufactured (AM) Ti6Al4V alloy to ensure effective machining parameters. …”
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The effect of mechanical milling for enhanced recycling Ti6Al4V powder from machining chips by Seyyed Amir Reza Alavizadeh, Mehrdad Shahbaz, Majid Kavanlouei, Sang Sub Kim

“…Abstract This study investigates the optimization of mechanical milling parameters to enhance the recycling of Ti6Al4V machining chips, addressing a significant challenge in sustainable materials processing. …”
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Investigation & analysis of Electrical Discharge Machining on Titanium Diboride Ceramic material with various Electrode materials and dielectric fluids by Karthik S, Sivakumar Annamalai

“…Its strength poses a problem to traditional machining methods. This work aims to compare two different dielectric fluids and four different electrode materials to improve EDM process parameters in TiB _2 material. …”
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Interpretable machine learning modeling of temperature rise in a medium voltage switchgear using multiphysics CFD analysis by Mahmood Matin, Amir Dehghanian, Amir Hossein Zeinaddini, Hossein Darijani

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Accelerated design of eutectic high-entropy alloys using high-throughput phase diagram calculations and machine learning by Mingxu Wu, Bang Guan, Junfeng Wang, Shubin Wang, Chao Yang, Chuan Zhang, Da Shu, Chengbo Xiao, Baode Sun

“…This study introduces a machine learning (ML) based classification model to assist the high-throughput thermodynamic calculations (HTCs), improving the efficiency by identifying eutectic, near-eutectic and non-eutectic compositions in the VNbTiTaSi system using the parameters that determine the eutectic forming ability. …”
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Evaluation of Machine Learning Algorithms for NB-IoT Module Energy Consumption Estimation Based on Radio Channel Quality by Dusan Bortnik, Vladimir Nikic, Srdjan Sobot, Dejan Vukobratovic, Ivan Mezei, Milan Lukic

“…Each data point, generated upon UDP packet transmission, includes metadata such as radio channel quality parameters, temporal parameters (TX and RX time), transmission and reception power, and coverage extension mode. …”
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