Comparative analysis of the torsional strength of ABS material for additive systems with closed and open working chambers by Jacek Bernaczek, Wiktor Kędzierski

“…Three sets of samples were made – four piecesfor each variant (according to the indicated infill parameters) – with the same manufacturing process parameters for both techniques,which were subjected to final processing; the so-called (postprocessing). …”
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Study the effective factors on the industrial hardfacing for low carbon steel based on Taguchi method by Abdulrazzaq Mohammed Abdulraoof

“…Taguchi method with L9 orthogonal array was applied to study the effect of different hardfacing parameters. Travel speed, hardfacing current, and hardfacing layers were selected as independent input parameters while impact resistance of the weld deposit was the output response. …”
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Gaussian barebone mechanism and wormhole strategy enhanced moth flame optimization for global optimization and medical diagnostics. by Jingjing Ma, Zhifang Zhao, Lin Zhang

“…Employing BWEMFO, we optimize the kernel parameters of the kernel-limit learning machine, thereby crafting the BWEMFO-KELM methodology for medical diagnosis and prediction. …”
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Effectiveness of Cutting Speed ​​of SS 316 L Material on Surface Roughness in Laser Cutting Process by Sigit Arrohman, Andri Sulistyo, Catur Harsito

“…The aim of this research is to determine the cutting speed parameters in laser cutting using SS 316 L material. …”
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SugarViT-Multi-objective regression of UAV images with Vision Transformers and Deep Label Distribution Learning demonstrated on disease severity prediction in sugar beet. by Maurice Günder, Facundo Ramón Ispizua Yamati, Abel Barreto, Anne-Katrin Mahlein, Rafet Sifa, Christian Bauckhage

“…The efficient retrieval of large-scale field imagery combined with machine learning techniques shows success in various tasks like phenotyping, weeding, cropping, and disease control. …”
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Wireless Temperature Monitoring of a Shaft Based on Piezoelectric Energy Harvesting by Piotr Micek, Dariusz Grzybek

“…Wireless structural health monitoring is needed for machine elements of which the working motions prevent wired monitoring. …”
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Ensuring the Quality of Surgical Instruments with Artificial Intelligence: A Focus on Sternum Wire by Neda HOUSHMANDSHARIFI, Murat Taha BILIŞIK

“…Results: The study revealed that the automated machine vision systems markedly reduced inspection time while achieving an overall accuracy of 96% in detecting needle quality, compared to 80% accuracy with manual inspections. …”
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Strength and microstructural evaluation of sustainable geopolymer mortars using calcium carbonate sludge and fly ash as precursors by Menglim Hoy, Soe Thandar, Suksun Horpibulsuk, Avirut Chinkulkijniwat, Apichat Suddeepong, Apinun Buritatum, Teerasak Yaowarat, Teerat Tesanasin, Jitwadee Horpibulsuk, Mantana Julvorawong

“…Furthermore, this study uniquely integrates machine learning (XGBoost and SHAP analysis) to predict compressive strength and revealed that the sodium silicate-to-sodium hydroxide ratio was the most influential parameter, followed by NaOH molarity. …”
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Sequencing Silicates in the Spitzer Infrared Spectrograph Debris Disk Catalog. I. Methodology for Unsupervised Clustering by Cicero X. Lu, Tushar Mittal, Christine H. Chen, Alexis Y. Li, Kadin Worthen, B. A. Sargent, Carey M. Lisse, G. C. Sloan, Dean C. Hines, Dan M. Watson, Isabel Rebollido, Bin B. Ren, Joel D. Green

“…Our analysis allows us to explore a vast parameter space in debris disk mineralogy and also offers broader applications in fields such as protoplanetary disks and solar system objects. …”
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Transformation rate maps of dissolved organic carbon in the contiguous US by L. Li, H.-Y. Li, G. Abeshu, J. Tang, L. R. Leung, C. Liao, Z. Tan, H. Tian, P. Thornton, X. Yang

“…As a first attempt to fill this gap, we propose a generic formula that directly connects SOC concentration with DOC concentration in headwater streams, where a single parameter, the transformation rate from SOC in the soil to DOC leaching flux (<span class="inline-formula"><i>P</i>_r</span>), accounts for the overall processes governing SOC conversion to DOC and leaching from soils (along with runoff) into headwater streams. …”
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Developing a Mobile Application for Estimating Patient’s Radiation Dose by Thanyawee Pengpan, Nuttida Nulnukul, Thanakorn Kongthai, Suranchana Boonrueng

“…Calculation of the ESAK and effective dose requires both X-ray machine parameters and patient exposure parameters. …”
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Utility of artificial intelligence in a binary classification of soft tissue tumors by Jing Di, Caylin Hickey, Cody Bumgardner, Mustafa Yousif, Mauricio Zapata, Therese Bocklage, Bonnie Balzer, Marilyn M. Bui, Jerad M. Gardner, Liron Pantanowitz, Shadi A. Qasem

“…Using an image analysis software (QuPath) and a cohort of 95 cases, several cell-specific parameters were found to be statistically significant, most notably cell count, nucleus/cell area ratio, nucleus hematoxylin density mean, and cell max caliper. (3) Evaluation of machine learning library (Scikit-learn) in differentiating benign and malignant STTs. …”
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FRANet: A Feature Refinement Attention Network for SAR Image Denoising by Shuaiqi Liu, Yu Lei, Qi Hu, Ming Liu, Bing Li, Weiming Hu, Yu-Dong Zhang

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Application of SVM algorithm in fluid prediction of volcanic reservoirs in Nanpu Sag, Bohai Bay Basin by ZHANG Ying,QU Lili,ZHU Lu,ZHANG Yan,HAN Siyang,ZENG Cheng

“…For this reason, the SVM（Support Vector Machine） algorithm of machine learning is used to predict the fluids of unknown reservoirs for the volcanic rock reservoirs in the Nanpu Sag of the Bohai Bay Basin. …”
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AUTOMATED DEVICE FOR ICE SURFACE QUALITY ASSESSMENT by M. V. Davydov, P. A. Belous

“…The worst values of the range of the device were obtained with the following parameters: ice surface temperature – from –5,3 to –5,4 °С, filled water temperature – 30–35 °С, the top layer of ice was not cutby an ice-filling machine.…”
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A High Accuracy Pedestrian Detection System Combining a Cascade AdaBoost Detector and Random Vector Functional-Link Net by Zhihui Wang, Sook Yoon, Shan Juan Xie, Yu Lu, Dong Sun Park

“…During the offline training phase, the parameters of a cascade AdaBoost detector and random vector functional-link net are trained by standard dataset. …”
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Parametric Analysis of Auxetic Honeycombs by Stefan Tabacu, Ana-Gabriela Badea, Alina-Ionela Aparaschivei, Daniel-Constantin Anghel

“…The machine-learning section investigates the influence of several parameters on the response and the effect of complete versus incomplete datasets.…”
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Constructing a Classification Model for Cervical Cancer Tumor Tissue and Normal Tissue Based on CT Radiomics by Jinghong Pei BD, Jing Yu BD, Ping Ge BD, Liman Bao BD, Haowen Pang MS, Huaiwen Zhang MS

“…Subsequently, we built classification models using five state-of-the-art machine learning algorithms: Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), and Decision Tree (DT). …”
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Betamethasone administration as a treatment of choice in local post-tattoo complications by O. N. Karymov, A. A. Vorobyov, S. A. Kalashnikova, L. V. Polyakova, M. N. Vyskub

“…The study found out that in the process of the betamethasone administration using a tattoo machine, the drug was uniformly administrated over the entire area of the tattoo; hereby, the phenomena of edema and inflammatory infiltration were insignificant. …”
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Providing a Framework for Assessing and Evaluating Network Data Studies in the Fight Against Social Anomalies by Mohammad Khalili, Hamzehali Nourmohammadi, Nader Naghshineh

“…The application of data mining techniques, along with various machine learning methods, can yield significant benefits in identifying, predicting, and preventing crime in any society. …”
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