Zobrazeno 1 - 10
of 14 875
pro vyhledávání: '"P. Bahar"'
Autor:
Siemensma, Thiemen, Haghighat, Bahar
Inspection of infrastructure using static sensor nodes has become a well established approach in recent decades. In this work, we present an experimental setup to address a binary inspection task using mobile sensor nodes. The objective is to identif
Externí odkaz:
http://arxiv.org/abs/2412.14646
Advancements in sensor technology offer significant insights into vehicle conditions, unlocking new venues to enhance fleet operations. While current vehicle health management models provide accurate predictions of vehicle failures, they often fail t
Externí odkaz:
http://arxiv.org/abs/2412.04350
Autor:
Popesso, P., Biviano, A., Marini, I., Dolag, K., Vladutescu-Zopp, S., Csizi, B., Biffi, V., Lamer, G., Robothan, A., Bravo, M., Lovisari, L., Ettori, S., Angelinelli, M., Driver, S., Toptun, V., Dev, A., Mazengo, D., Merloni, A., Comparat, J., Ponti, G., Mroczkowski, T., Bulbul, E., Grandis, S., Bahar, E.
By using eROSITA data in the eFEDS area, we provide a measure of the hot gas fraction vs. halo mass relation over the largest halo mass range, from Milky Way-sized halos to massive clusters, and to the largest radii ever probed so far in local system
Externí odkaz:
http://arxiv.org/abs/2411.16555
Autor:
Li, Pengfei, Liu, Ang, Kluge, Matthias, Comparat, Johan, Tian, Yong, Júlio, Mariana P., Pawlowski, Marcel S., Sanders, Jeremy, Bulbul, Esra, Schwope, Axel, Ghirardini, Vittorio, Zhang, Xiaoyuan, Bahar, Y. Emre, Ramos-Ceja, Miriam E., Balzer, Fabian, Garrel, Christian
Publikováno v:
A&A 692, A253 (2024)
The mass of galaxy clusters is a critical quantity for probing cluster cosmology and testing theories of gravity, but its measurement could be biased given assumptions are inevitable. In this paper, we employ and compare two mass proxies for galaxy c
Externí odkaz:
http://arxiv.org/abs/2411.09735
Autor:
Friederich, Nils, Sitcheu, Angelo Jovin Yamachui, Nassal, Annika, Pesch, Matthias, Yildiz, Erenus, Beichter, Maximilian, Scholtes, Lukas, Akbaba, Bahar, Lautenschlager, Thomas, Neumann, Oliver, Kohlheyer, Dietrich, Scharr, Hanno, Seiffarth, Johannes, Nöh, Katharina, Mikut, Ralf
Microfluidic Live-Cell Imaging (MLCI) generates high-quality data that allows biotechnologists to study cellular growth dynamics in detail. However, obtaining these continuous data over extended periods is challenging, particularly in achieving accur
Externí odkaz:
http://arxiv.org/abs/2411.05030
Robotic simulators provide cost-effective and risk-free virtual environments for studying robotic designs, control algorithms, and sensor integrations. They typically host extensive libraries of sensors and actuators that facilitate rapid prototyping
Externí odkaz:
http://arxiv.org/abs/2411.03176
Autor:
Gil-Rodrigo, Sofia, López-Martín, Raúl, Yener, Görsev, Wiersema, Jan R., Güntekin, Bahar, Zanin, Massimiliano
Functional networks representing human brain dynamics have become a standard tool in neuroscience, providing an accessible way of depicting the computation performed by the brain in healthy and pathological conditions. Yet, these networks share multi
Externí odkaz:
http://arxiv.org/abs/2411.01522
Autor:
Grönquist, Peter, Bhattacharjee, Deblina, Aydemir, Bahar, Ozaydin, Baran, Zhang, Tong, Salzmann, Mathieu, Süsstrunk, Sabine
In the evolving landscape of deep learning, there is a pressing need for more comprehensive datasets capable of training models across multiple modalities. Concurrently, in digital humanities, there is a growing demand to leverage technology for dive
Externí odkaz:
http://arxiv.org/abs/2410.20459
Advanced automated AI techniques allow us to classify protein sequences and discern their biological families and functions. Conventional approaches for classifying these protein families often focus on extracting N-Gram features from the sequences w
Externí odkaz:
http://arxiv.org/abs/2410.17293
Autor:
Dogangun, Fatih, Bahar, Serdar, Yildirim, Yigit, Temir, Bora Toprak, Ugur, Emre, Dogan, Mustafa Doga
As robotics continue to enter various sectors beyond traditional industrial applications, the need for intuitive robot training and interaction systems becomes increasingly more important. This paper introduces Robotic Augmented Reality for Machine P
Externí odkaz:
http://arxiv.org/abs/2410.13412