Unsupervised Machine Learning Approaches for Test Suite Reduction by Anila Sebastian, Hira Naseem, Cagatay Catal

“…Therefore, the Test Suite Reduction (TSR) process is of great importance, contributing to the reduction of time and costs in executing test suites for complex software by minimizing the number of test cases to be executed. …”
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Data Reduction Method for Synthetic Transmit Aperture Algorithm by Piotr KARWAT, Ziemowit KLIMONDA, Michał SĘKLEWSKI, Marcin LEWANDOWSKI, Andrzej NOWICKI

“…The presented results of simulations and measurements with use of wire and tissue phantom prove that the proposed data reduction technique reduces the amount of data to be processed by half, while maintaining resolution and allowing only a small decrease of SNR and contrast of resulting images.…”
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Model reduction of structural mechanical response in the time domain by Xin Yan, Xinyu Guo, Ningya He, Jinglong Shi, Daquan Zhao

“…Subsequently, road load spectrum signal tests extract vibration acceleration and strain signals from these areas, forming the foundation for model reduction training and validation sets. Comprehensive research into machine learning and model reduction techniques is conducted, with a focus on polynomial order in response surface models and kernel functions in Gaussian process models. …”
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Effectiveness and Safety of Contrast Cryolipolysis for Subcutaneous-Fat Reduction by Marília Bueno Savacini, Débora Tazinaffo Bueno, Ana Carolina Souza Molina, Ana Caroline Almeida Lopes, Caroline Nogueira Silva, Renata Gomes Moreira, Stephani Almeida, Renata Michelini Guidi, Estela Sant’Ana, Richard Eloin Liebano

“…The purpose of the present study was to evaluate the safety and efficacy of contrast cryolipolysis for subcutaneous-fat reduction. Contrast cryolipolysis mixes the principles of conventional cryolipolysis and periods of heating in accordance with the contrast lipocryolysis process. …”
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Phytate reduction in sorghum grains cultivated in Saudi Arabia by Saeed Amer Asiri

“…Some minerals, like Fe, P, Zn, and Ca, were determined as indicators of phytate reduction and bioavailability of these minerals in soaking media. …”
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Reduction of aerodynamic resistance of inertial-vacuum ash collector by L. V. Mostovenko, V. P. Beloglazov

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Silicon whisker pressure sensors for noise reduction in silencers by Anatoliy Druzhinin, Oleksiy Kutrakov, Roman Zinko

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Reduction of myocardial hypertrophy after aortic valve replacement by Kostić-Mirković Andrijana, Otašević Ivan, Vujisić-Tešić Bosiljka

“…This study showed the presence of a significant reduction in the LV mass after AVR, and that the mean time required for this process was more than two years.…”
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Potential reduction of global colorectal cancer, 1990–2021 by Zilin Luo, Xuesi Dong, Le Wang, Yadi Zheng, Chenran Wang, Jiaxin Xie, Xiaolu Chen, Liang Zhao, Yongjie Xu, Wei Cao, Fei Wang, Lingbin Du, Ni Li

“…Conclusion: Our results quantitatively demonstrate the substantial burden reduction in colorectal cancer and the significant gain in life expectancy that can be achieved by eliminating modifiable lifestyle factors.…”
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Ecological Stability over the Period: Land-Use Land-Cover Change and Prediction for 2030 by Mária Tárníková, Zlatica Muchová

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Bayesian surrogate assisted neural network model to predict the hydrogen storage in 9-ethylcarbazole by Ahsan Ali, Mohammad Usman, Hafiz Muhammad Ali, Uzair Sajjad, Md. Abdul Aziz, M. Nasiruzzaman Shaikh

“…Temperature (r = 0.15) exhibited a weak relationship, suggesting nonlinear dependencies. To enhance the predictive accuracy and develop an optimal DNN model, Bayesian Surrogate Random Forest (BSRF), Bayesian Surrogate Gaussian Process (BSGP), and Bayesian Surrogate Gradient Boost Regression Trees (BSGBRT) were integrated with deep neural networks (DNNs). …”
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Synthesis and purification of nano-sized titanium carbide particles through vacuum carbothermal reduction for enhanced mechanical, microstructural morphology, and tribological properties in friction stir processed A356-based aluminum composites by Shashi Prakash Dwivedi, Vijay Chaudhary, Shubham Sharma, Ashutosh Pattanaik, P Vijaya Kumar, Yashwant Singh Bisht, Varinder Singh, Mohamed Abbas, Dražan Kozak, Jasmina Lozanovic, Abhinav Kumar

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A new analytical model for process-microstructure-hardness relationships of directed energy deposited nickel alloys by Jiale Wang, Bo Yin, Kai Qin, Haohao Miao, Yu Yin, Petro Pavlenko, Yuefeng Yuan, Jinbao Wang, David Henry StJohn, Zhao Zhang, Hao Yi

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Correlation analysis between key volatile compounds and core functional bacterial community during Sichuan black tea processing by Si-yu Liao, Shuang Yang, Bi-lin Li, Xue Xia, Wen-bao Jia, Yi-qiao Zhao, Ling Lin, Jin-lin Bian, Tunyaluk Bouphun, Wei Xu

Subjects: “…Black tea processing…”
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Use the 4S (Signal-Safe Speckle Subtraction): Explainable Machine Learning Reveals the Giant Exoplanet AF Lep b in High-contrast Imaging Data from 2011 by Markus J. Bonse, Timothy D. Gebhard, Felix A. Dannert, Olivier Absil, Faustine Cantalloube, Valentin Christiaens, Gabriele Cugno, Emily O. Garvin, Jean Hayoz, Markus Kasper, Elisabeth Matthews, Bernhard Schölkopf, Sascha P. Quanz

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Fuzzy Galaxies or Cirrus? Decomposition of Galactic Cirrus in Deep Wide-field Images by Qing Liu, Roberto Abraham, Peter G. Martin, William P. Bowman, Pieter van Dokkum, Shany Danieli, Ekta Patel, Steven R. Janssens, Zili Shen, Seery Chen, Ananthan Karunakaran, Michael A. Keim, Deborah Lokhorst, Imad Pasha, Douglas L. Welch

Subjects: “…Astronomy data reduction…”
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Adaptive biases-incorporated latent factorization of tensors for predicting missing data in water quality monitoring networks by Xuke Wu, Xuke Wu, Lan Wang, Lan Wang, Miao Ge, Miao Ge, Jing Jiang, Jing Jiang, Yu Cai, Bing Yang, Bing Yang

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In-Field Forage Biomass and Quality Prediction Using Image and VIS-NIR Proximal Sensing with Machine Learning and Covariance-Based Strategies for Livestock Management in Silvopasto... by Claudia M. Serpa-Imbett, Erika L. Gómez-Palencia, Diego A. Medina-Herrera, Jorge A. Mejía-Luquez, Remberto R. Martínez, William O. Burgos-Paz, Lorena A. Aguayo-Ulloa

“…However, the limited availability of reliable handheld sensors for timely pasture quality prediction hinders farmers’ ability to make informed decisions. …”
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Degradation modeling and remaining useful life prediction for electronic device under multiple stress influences by Changjun Li, Jinjun Cheng, Haizhen Zhu, Bincheng Wen, Xin Zhao, Weijie Kang

“…To monitor the degradation state of electronic devices and predict their remaining useful life at different moments, this paper obtains the degradation data of the samples by carrying out accelerated degradation experiments of power driver devices under the influence of multiple stresses, and proposes a new multi-stress-coupled accelerated degradation model based on the Wiener process. …”
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Prediction of rare and anomalous minerals using anomaly detection and machine learning techniques by Abish Sharapatov, Alisher Saduov, Nazerke Assirbek, Madiyar Abdyrov, Beibit Zhumabayev

“…These anomalies were further grouped using KMeans clustering into three categories, each linked to different geological formation environments: evaporitic, metamorphic, and magmatic processes. The study also evaluates the reliability of these machine learning models using a statistical benchmark and explores the role of deep learning in improving anomaly detection. …”
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