Results 181 to 190 of about 201,128 (321)
Interpretable Model-based Hierarchical Reinforcement Learning using Inductive Logic Programming
, 2021 Duo Xu, Faramarz Fekri
openalex +2 more sources
Flip‐Chip Integration of the Superconducting Quantum‐Classical Circuits: Coupling Types
Advanced Quantum Technologies, EarlyView.This article explores the use of 3D modular architectures with flip‐chip technology to overcome scalability challenges in superconducting quantum processors. Based onλ/4 and λ/2 resonators, the article systematically analyzes capacitive, inductive, and galvanic interconnects.
Rustam D. Yusupov +15 more
wiley +1 more source
A Fully Automated Robotic System for Tuning Optimization of RF Cavity Filter
Journal of Field Robotics, EarlyView.ABSTRACT The advancements in radar systems, electronic warfare, and telecommunication industries have generated a substantial demand for microwave filters. Among these, cavity filters have conventionally served in transmitters and receivers, facilitating the passage of desired signals in the passband while effectively rejecting harmonics and spurious ...
Yarkin Yigit, Engin Afacan
wiley +1 more source
Model Driven Development Transformations using Inductive Logic Programming [PDF]
, 2017 Adel Hamdi, Abderrahim El Moataz
openalex +1 more source
Knowledge and Information Systems, 2017 Rinaldo Lima, B. Espinasse, Fred Freitas
semanticscholar +1 more source
Science Education, EarlyView.ABSTRACT The increasing availability of digital tools in science classrooms can provide students with more frequent and easier access to large amounts of data. Large data sets have considerable epistemological potential, as they enable, for instance, the observation of otherwise unobservable phenomena, but it must be assumed that handling them places ...
Gregor Benz +2 more
wiley +1 more source
Parallel Constraint-Driven Inductive Logic Programming
, 2021 Andrew Cropper +3 more
openalex +2 more sources
Logic Programs as Declarative and Procedural Bias in Inductive Logic Programming
, 2013 Machine Learning is necessary for the development of Artificial Intelligence, as pointed out by Turing in his 1950 article ``Computing Machinery and Intelligence''. It is in the same article that Turing suggested the use of computational logic and background knowledge for learning.
openaire +4 more sources
Management Responses to Climate Change: An Analysis of Scholarly Recommendations
Sustainable Development, EarlyView.ABSTRACT This article analyzes management scholars' recommendations for business managers on how to respond to climate change. It distinguishes recommendations by whether they propose responsiveness to climate change that aims for adaptation, mitigation, and resilience as short‐term orientations as well as transformation and regeneration as long‐term ...
Jean‐Pierre Imbrogiano +2 more
wiley +1 more source