Zobrazeno 1 - 10
of 66 968
pro vyhledávání: '"Aslan IN"'
Autor:
Faraj Al-Bhadely, Aslan İnan
Publikováno v:
Sensors, Vol 24, Iss 13, p 4109 (2024)
In the contemporary context of power network protection, acknowledging uncertainties in safeguarding recent power networks integrated with distributed generation (DG) is imperative to uphold the dependability, security, and efficiency of the grid ami
Externí odkaz:
https://doaj.org/article/a26a5ffc283b41fa8b080e9de10c6e19
Publikováno v:
Applied Sciences, Vol 14, Iss 9, p 3795 (2024)
In order to drive electric vehicle adoption and bolster grid stability, the incorporation of battery swapping stations (BSSs) into the power grid is imperative. Conversely, network reconfiguration plays a crucial role in optimizing energy exchange wi
Externí odkaz:
https://doaj.org/article/fbcb3852f02d40719049ea79c2d3a18d
Publikováno v:
Energies, Vol 17, Iss 1, p 110 (2023)
In recent years, battery swapping stations have become increasingly popular in smart energy networks. Its advantages include reducing the time required for recharging energy, balancing the grid’s load, and extending the battery’s lifespan. Despit
Externí odkaz:
https://doaj.org/article/44a5cd8b80b44ce693c808cbe3594a7b
Autor:
Faraj Al-Bhadely, Aslan İnan
Publikováno v:
Energies, Vol 16, Iss 20, p 7031 (2023)
In recent years, with the growing popularity of smart microgrids in distribution networks, the effective coordination of directional overcurrent relays (DOCRs) has presented a significant challenge for power system operators due to the intricate and
Externí odkaz:
https://doaj.org/article/68e0890075fc4a9786fdc219ac070393
Autor:
Tsesmelis, Theodore, Palmieri, Luca, Khoroshiltseva, Marina, Islam, Adeela, Elkin, Gur, Shahar, Ofir Itzhak, Scarpellini, Gianluca, Fiorini, Stefano, Ohayon, Yaniv, Alali, Nadav, Aslan, Sinem, Morerio, Pietro, Vascon, Sebastiano, Gravina, Elena, Napolitano, Maria Cristina, Scarpati, Giuseppe, Zuchtriegel, Gabriel, Spühler, Alexandra, Fuchs, Michel E., James, Stuart, Ben-Shahar, Ohad, Pelillo, Marcello, Del Bue, Alessio
This paper proposes the RePAIR dataset that represents a challenging benchmark to test modern computational and data driven methods for puzzle-solving and reassembly tasks. Our dataset has unique properties that are uncommon to current benchmarks for
Externí odkaz:
http://arxiv.org/abs/2410.24010
Autor:
Son, Guijin, Yoon, Dongkeun, Suk, Juyoung, Aula-Blasco, Javier, Aslan, Mano, Kim, Vu Trong, Islam, Shayekh Bin, Prats-Cristià, Jaume, Tormo-Bañuelos, Lucía, Kim, Seungone
Large language models (LLMs) are commonly used as evaluators in tasks (e.g., reward modeling, LLM-as-a-judge), where they act as proxies for human preferences or judgments. This leads to the need for meta-evaluation: evaluating the credibility of LLM
Externí odkaz:
http://arxiv.org/abs/2410.17578
Publikováno v:
ACCV2024
Jigsaw puzzle solving is a challenging task for computer vision since it requires high-level spatial and semantic reasoning. To solve the problem, existing approaches invariably use color and/or shape information but in many real-world scenarios, suc
Externí odkaz:
http://arxiv.org/abs/2410.16857
Human actions are based on the mental perception of the environment. Even when all the aspects of an environment are not visible, humans have an internal mental model that can generalize the partially visible scenes to fully constructed and connected
Externí odkaz:
http://arxiv.org/abs/2410.12372
Conventional tomographic reconstruction typically depends on centralized servers for both data storage and computation, leading to concerns about memory limitations and data privacy. Distributed reconstruction algorithms mitigate these issues by part
Externí odkaz:
http://arxiv.org/abs/2410.06106
Autor:
Aslan, Sipan, Ombao, Hernando
One fundamental challenge of data-driven analysis in neuroscience is modeling causal interactions and exploring the connectivity between nodes in a brain network. Various statistical methods, using different perspectives and data modalities, have bee
Externí odkaz:
http://arxiv.org/abs/2409.10374