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Giorgio Lazzarinetti, Riccardo Dondi, Sara Manzoni and Italo Zoppis
Solving combinatorial problems on complex networks represents a primary issue which, on a large scale, requires the use of heuristics and approximate algorithms. Recently, neural methods have been proposed in this context to find feasible solutions for r...
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Mahammad Khalid Shaik Vadla, Mahima Agumbe Suresh and Vimal K. Viswanathan
Understanding customer emotions and preferences is paramount for success in the dynamic product design landscape. This paper presents a study to develop a prediction pipeline to detect the aspect and perform sentiment analysis on review data. The pre-tra...
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Romain Amyot, Noriyuki Kodera and Holger Flechsig
Simulation of atomic force microscopy (AFM) computationally emulates experimental scanning of a biomolecular structure to produce topographic images that can be correlated with measured images. Its application to the enormous amount of available high-res...
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Paulo Marcelo Vieira Ribeiro and Pierre Léger
Concrete dams are massive unreinforced quasi-brittle structures prone to cracking from multiple causes. The structural safety assessment of cracked concrete dams is typically performed using computational analysis through numerical methods, with adequate...
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Zixin Feng, Teligeng Yun, Yu Zhou, Ruirui Zheng and Jianjun He
Geometric mean metric learning (GMML) algorithm is a novel metric learning approach proposed recently. It has many advantages such as unconstrained convex objective function, closed form solution, faster computational speed, and interpretability over oth...
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