Zobrazeno 1 - 10
of 236 516
pro vyhledávání: '"KARIM, A."'
Autor:
Tran, Huan, Kim, Chiho, Gurnani, Rishi, Hvidsten, Oliver, DeSimpliciis, Justin, Ramprasad, Rampi, Gadelrab, Karim, Tuffile, Charles, Molinari, Nicola, Kitchaev, Daniil, Kornbluth, Mordechai
Polymer composite performance depends significantly on the polymer matrix, additives, processing conditions, and measurement setups. Traditional physics-based optimization methods for these parameters can be slow, labor-intensive, and costly, as they
Externí odkaz:
http://arxiv.org/abs/2412.08407
Metasurface research has shown significant potential for controlling the polarization, amplitude, phase and propagation direction of light. Nevertheless, control over the angular response of incident light still remains a long-standing problem. In th
Externí odkaz:
http://arxiv.org/abs/2412.06508
Autor:
Rahman, Anichur, Eidmum, MD. Zunead Abedin, Kundu, Dipanjali, Hossain, Mahir, Tashrif, MD Tanjum An, Karim, Md Ahsan, Islam, Md. Jahidul
In the developing topic of smart cities, Vehicular Ad-Hoc Networks (VANETs) are crucial for providing successful interaction between vehicles and infrastructure. This research proposes a distributed Blockchain-based Vehicular Ad-hoc Network (DistB-VN
Externí odkaz:
http://arxiv.org/abs/2412.04222
Assessing the importance of individual training samples is a key challenge in machine learning. Traditional approaches retrain models with and without specific samples, which is computationally expensive and ignores dependencies between data points.
Externí odkaz:
http://arxiv.org/abs/2412.04158
Considerable study has already been conducted regarding autonomous driving in modern era. An autonomous driving system must be extremely good at detecting objects surrounding the car to ensure safety. In this paper, classification, and estimation of
Externí odkaz:
http://arxiv.org/abs/2412.03490
This paper evaluates the use of metamorphic relations to enhance the robustness and real-world performance of machine learning models. We propose a Metamorphic Retraining Framework, which applies metamorphic relations to data and utilizes semi-superv
Externí odkaz:
http://arxiv.org/abs/2412.01958
Autor:
Elgammal, Karim, Maußner, Marc
This work demonstrates a systematic implementation of hybrid quantum-classical computational methods for investigating corrosion inhibition mechanisms on aluminum surfaces. We present an integrated workflow combining density functional theory (DFT) w
Externí odkaz:
http://arxiv.org/abs/2412.00951
Autor:
Sultan, Md. Fahim, Karim, Tasmin, Shaon, Md. Shazzad Hossain, Wardat, Mohammad, Akter, Mst Shapna
Software security is crucial in any field where breaches can exploit sensitive data, and lead to financial losses. As a result, vulnerability detection becomes an essential part of the software development process. One of the key steps in maintaining
Externí odkaz:
http://arxiv.org/abs/2412.00216
Autor:
Scirè, Alessandro, Bejgu, Andrei Stefan, Tedeschi, Simone, Ghonim, Karim, Martelli, Federico, Navigli, Roberto
After the introduction of Large Language Models (LLMs), there have been substantial improvements in the performance of Natural Language Generation (NLG) tasks, including Text Summarization and Machine Translation. However, LLMs still produce outputs
Externí odkaz:
http://arxiv.org/abs/2411.19655
Autor:
Tavanaei, Amir, Koo, Kee Kiat, Ceker, Hayreddin, Jiang, Shaobai, Li, Qi, Han, Julien, Bouyarmane, Karim
In this paper, we study the problem of generating structured objects that conform to a complex schema, with intricate dependencies between the different components (facets) of the object. The facets of the object (attributes, fields, columns, propert
Externí odkaz:
http://arxiv.org/abs/2411.19301