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Academic Articles & Research Papers
Showing 20 of 656 academic articles
L.G.S. Assunção, S.M. Eloi-Santos, S.V. Peixoto • Brazilian Journal of Medical and Biological Research
(2012)
The measurement of the serum concentration of the acute-phase reactant C-reactive protein (CRP) provides a useful marker in clinical practice. However, the distribution of CRP is not available for all age and population groups. This study a...
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Open Access (DOAJ)
Martin Andersson, Mark Jones, Kurt Valentin Mikkelsen, Fengqi You et al. • Current Opinion in Chemical Engineering
(2021)
Chemical process design has for long been benefiting from computer-aided methods and tools to develop new processes and services that can meet the needs of society. Chemical and biomolecular product design could also benefit from the use of...
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DOI: https://doi.org/10.1016/j.coche.2021.100754
Agostino Migliore, Anna Napoli, Antonino Messina • Results in Physics
(2021)
The rapidly increasing capability to modulate the physicochemical properties of atomic groups and molecules by means of their coupling to radiation, as well as the revolutionary potential of quantum computing for materials simulation and pr...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.rinp.2021.104690
Valeria Cimini, Mandar M. Sohoni, Federico Presutti, Benjamin K. Malia et al. • npj Quantum Information
(2026)
Abstract A Gaussian boson sampler (GBS) is a special-purpose quantum computer that can be practically realized at a large scale in optics. Here we report on experiments in which we used a frequency-multiplexed GBS with > 400 modes as a quan...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41534-026-01251-w
Anup Basnet Chetry, Keisuke Ohto • Journal of Cheminformatics
(2025)
Abstract Chemoinformatics is a rapidly advancing field that integrates chemistry, computer science, and data analysis to enhance the study and application of chemical systems. This interdisciplinary approach leverages computational tools an...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s13321-025-00978-6
Tim Bauer, Francesco Buccheri, Alessandro De Martino, Reinhold Egger • Physical Review Research
(2024)
For a Weyl semimetal (WSM) in a magnetic field, a semiclassical description of the Fermi-arc surface state dynamics is usually employed for explaining various unconventional magnetotransport phenomena, e.g., Weyl orbits, the three-dimension...
DOAJ
Open Access (DOAJ)
DOI: 10.1103/PhysRevResearch.6.043201
Aya Ali, Fatima Alshaali, Mejd Almheiri, Mahmoud Abdel-Hafiez • Results in Physics
(2025)
Transition metal dichalcogenides (TMDs) are a fascinating class of materials known for their various electronic properties and potential applications in nanoelectronics, quantum computing, and energy storage. This review explores the intric...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.rinp.2025.108154
Carlos Outeiral, Martin Strahm, Jiye Shi, Garrett M. Morris et al. • Wiley Interdisciplinary Reviews Computational Molecular Science
(2020)
Abstract Quantum computers can in principle solve certain problems exponentially more quickly than their classical counterparts. We have not yet reached the advent of useful quantum computation, but when we do, it will affect nearly all sci...
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DOI: https://doi.org/10.1002/wcms.1481
G.R. Nudd, Darren J. Kerbyson, E. Papaefstathiou, S. C. Perry et al. • The International Journal of High Performance Computing Applications
(2000)
This paper describes a methodology that provides detailed predictive performance information throughout the software design and implementation cycles. It is structured around a hierarchy of performance models that describe the computing sys...
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DOI: https://doi.org/10.1177/109434200001400306
James W. Mickens, Brian D. Noble (2006)
Loosely-coupled distributed systems have significant scale and cost advantages over more traditional architectures, but the availability of the nodes in these systems varies widely. Availability modeling is crucial for predicting per-machin...
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Maysam Yabandeh, Nikola Knežević, Dejan Kostić, Viktor Kunčak • Infoscience (Ecole Polytechnique Fédérale de Lausanne)
(2009)
We propose a new approach for developing and deploying distributed systems, in which nodes predict distributed consequences of their actions, and use this information to detect and avoid errors. Each node continuously runs a state explorati...
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Yan Jia, Yulu Qi, Huaijun Shang, Rong Jiang et al. • Engineering
(2018)
Cyberattack forms are complex and varied, and the detection and prediction of dynamic types of attack are always challenging tasks. Research on knowledge graphs is becoming increasingly mature in many fields. At present, it is very signific...
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DOI: https://doi.org/10.1016/j.eng.2018.01.004
Feixue Yan, Sheng Wen, Surya Nepal, Cécile L. Paris et al. • International Journal of Intelligent Systems
(2022)
Machine learning (ML) techniques are increasingly important in cybersecurity, as they can quickly analyse and identify different types of threats from millions of events. In spite of the increasing number of possible applications of ML, suc...
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DOI: https://doi.org/10.1002/int.23088
Fabien Charmet, Harry Chandra Tanuwidjaja, Solayman Ayoubi, Pierre-François Gimenez et al. • Annals of Telecommunications
(2022)
Abstract With the extensive application of deep learning (DL) algorithms in recent years, e.g., for detecting Android malware or vulnerable source code, artificial intelligence (AI) and machine learning (ML) are increasingly becoming essent...
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DOI: https://doi.org/10.1007/s12243-022-00926-7
Yang Liu, Meng Zhang • Computational Linguistics
(2017)
Deep learning has attracted dramatic attention in recent years, both in academia and industry. The popular term deep learning generally refers to neural network methods. Indeed, many core ideas and methods were born years ago in the era of ...
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DOI: https://doi.org/10.1162/coli_r_00312
Carly D. Robinson, Michael Yeomans, Justin Reich, Chris S. Hulleman et al. • International Conference on Learning Analytics and Knowledge (LAK)
(2016)
Student intention and motivation are among the strongest predictors of persistence and completion in Massive Open Online Courses (MOOCs), but these factors are typically measured through fixed-response items that constrain student expressio...
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DOI: https://doi.org/10.1145/2883851.2883932
Fredrik Olsson • KTH Publication Database DiVA (KTH Royal Institute of Technology)
(2009)
Active learning is a supervised machine learning technique in which the learner is in control of the data used for learning. That control is utilized by the learner to ask an oracle, typically a human with extensive knowledge of the domain ...
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Jakob Gawlikowski, Cedrique Rovile Njieutcheu Tassi, Mohsin Ali, Jong‐Seok Lee et al. • Artificial Intelligence Review
(2023)
Abstract Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more a...
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DOI: https://doi.org/10.1007/s10462-023-10562-9
Jianlin Cheng, Zheng Wang, Gianluca Pollastri • International Joint Conference on Neural Networks (IJCNN)
(2008)
Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional neural network to learn ordinal categories. Our approach is a gen...
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Open Access
DOI: https://doi.org/10.1109/ijcnn.2008.4633963
Nachimuthu Karunanithi, Darrell Whitley, Yashwant K. Malaiya • IEEE Software
(1992)
It is shown that neural network reliability growth models have a significant advantage over analytic models in that they require only failure history as input and not assumptions about either the development environment or external paramete...
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DOI: https://doi.org/10.1109/52.143107