AIMC Topic: Physical Phenomena

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Towards Convolutional Neural Network Acceleration and Compression Based on -Means.

Sensors (Basel, Switzerland) Jun 6, 2022
Convolutional Neural Networks (CNNs) are popular models that are widely used in image classification, target recognition, and other fields. Model compression is a common step in transplanting neural networks into embedded devices, and it is often use...
Neural Networks, Computer Algorithms Acceleration Data Compression Physical Phenomena
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MobilePrune: Neural Network Compression via Sparse Group Lasso on the Mobile System.

Sensors (Basel, Switzerland) May 27, 2022
It is hard to directly deploy deep learning models on today's smartphones due to the substantial computational costs introduced by millions of parameters. To compress the model, we develop an ℓ0-based sparse group lasso model called MobilePrune which...
Neural Networks, Computer Algorithms Data Compression Physical Phenomena
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Energy and thermal modelling of an office building to develop an artificial neural networks model.

Scientific reports May 27, 2022
Nowadays everyone should be aware of the importance of reducing CO emissions which produce the greenhouse effect. In the field of construction, several options are proposed to reach nearly-Zero Energy Building (nZEB) standards. Obviously, before unde...
Neural Networks, Computer Physical Phenomena Greenhouse Effect
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: A Deep Learning-Based Data-Driven Analytics Scheme for Energy Theft Detection.

Sensors (Basel, Switzerland) May 26, 2022
Integrating information and communication technology (ICT) and energy grid infrastructures introduces smart grids (SG) to simplify energy generation, transmission, and distribution. The ICT is embedded in selected parts of the grid network, which par...
Deep Learning Support Vector Machine Computer Communication Networks Physical Phenomena Theft
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An efficient ANFIS-EEBAT approach to estimate effort of Scrum projects.

Scientific reports May 13, 2022
Software effort estimation is a significant part of software development and project management. The accuracy of effort estimation and scheduling results determines whether a project succeeds or fails. Many studies have focused on improving the accur...
Machine Learning Software Algorithms Physical Phenomena
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Sensor Screening Methodology for Virtually Sensing Transmission Input Loads of a Wind Turbine Using Machine Learning Techniques and Drivetrain Simulations.

Sensors (Basel, Switzerland) May 11, 2022
The ongoing trend of building larger wind turbines (WT) to reach greater economies of scale is contributing to the reduction in cost of wind energy, as well as the increase in WT drivetrain input loads into uncharted territories. The resulting intens...
Machine Learning Research Computer Simulation Physical Phenomena
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Modeling of energy consumption factors for an industrial cement vertical roller mill by SHAP-XGBoost: a "conscious lab" approach.

Scientific reports May 9, 2022
Cement production is one of the most energy-intensive manufacturing industries, and the milling circuit of cement plants consumes around 4% of a year's global electrical energy production. It is well understood that modeling and digitalizing industri...
Humans Artificial Intelligence Machine Learning Physical Phenomena Physiological Phenomena
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Progressive compressive sensing of large images with multiscale deep learning reconstruction.

Scientific reports May 4, 2022
Compressive sensing (CS) is a sub-Nyquist sampling framework that has been employed to improve the performance of numerous imaging applications during the last 15 years. Yet, its application for large and high-resolution imaging remains challenging i...
Humans Algorithms Deep Learning User-Computer Interface Imaging, Three-Dimensional Data Compression Physical Phenomena
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Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder.

Journal of chemical information and modeling Feb 17, 2022
Some of the most common applications of machine learning (ML) algorithms dealing with small molecules usually fall within two distinct domains, namely, the prediction of molecular properties and the design of novel molecules with some desirable prope...
Machine Learning Algorithms Physical Phenomena
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Flexible Neural Network Realized by the Probabilistic SiO Memristive Synaptic Array for Energy-Efficient Image Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Feb 16, 2022
The human brain's neural networks are sparsely connected via tunable and probabilistic synapses, which may be essential for performing energy-efficient cognitive and intellectual functions. In this sense, the implementation of a flexible neural netwo...
Humans Neural Networks, Computer Algorithms Learning Synapses Physical Phenomena
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