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Parisa Mahya and Johannes Fürnkranz
Recently, some effort went into explaining intransparent and black-box models, such as deep neural networks or random forests. So-called model-agnostic methods typically approximate the prediction of the intransparent black-box model with an interpretabl...
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Thomas J. Tewes, Michael C. Welle, Bernd T. Hetjens, Kevin Saruni Tipatet, Svyatoslav Pavlov, Frank Platte and Dirk P. Bockmühl
Numerous publications showing that robust prediction models for microorganisms based on Raman micro-spectroscopy in combination with chemometric methods are feasible, often with very precise predictions. Advances in machine learning and easier accessibil...
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Vincenzo Benedetto, Francesco Gissi, Gioele Ciaparrone and Luigi Troiano
Gravitational wave research presents a range of intriguing challenges, each of which has driven significant progress in the field. Key research problems include glitch classification, glitch cancellation, gravitational wave denoising, binary black hole s...
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Marek Kciuk, Zygmunt Kowalik, Grazia Lo Sciuto, Sebastian Slawski and Stefano Mastrostefano
The promising research on flexible and tactile sensors requires conducting polymer materials and an accurate system for the transduction of pressure into electrical signals. In this paper, the intelligent sensitive mat, based on Velostat, which is a poly...
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Xiaoguo Mu, Hu Gao, Haijun Li, Fucheng Gao, Ying Zhang and Lin Ye
This study aimed to address the crop growth and development issues caused by environmental factors in the area of the Liupan Mountains in Ningxia. In this area, there is a large temperature difference between day and night due to drought and low rainfall...
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