Results 141 to 150 of about 115,711 (260)

Sustainable Live Sound Monitoring and Classification System Enabled by a Triboelectric Nanogenerator and Machine Learning Techniques

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
A high‐performance Triboelectric Nanogenerator (TENG) acoustic sensor using polyimine/graphite polypropylene (PI/GP) was developed for real‐time, sustainable sound monitoring and classification. The self‐powered device delivers 25.67 μW output power, 92.7% accuracy with MobileNet V1, and powers a wireless transmission circuit, demonstrating dual ...
Majid Haji Bagheri, Araz Rajabi‐Abhari, Owen Gibbs, Pengcheng Xi, Asif Abdullah Khan, Fangzheng Huang, Md Soyaeb Hassan, Ning Yan, Dayan Ban   +8 more
wiley   +1 more source

A Practical Real‐Time Observer‐Based Radiation Prediction Algorithm for Solar Plants

Energy Science &Engineering, EarlyView.
A novel radiation prediction method is proposed. The model's existence is verified by applying real data to an offline identifier. An adaptive state/parameter estimator is developed to identify the model. The identification process occurs in real‐time, independent of specific situations. The method offers universal radiation prediction.
S. Sepehr Tabatabaei, S. Ayoub Mirtavousi, Mohammadreza Dehghan   +2 more
wiley   +1 more source

Tomtit‐Raven Evolutionary Selector‐Reinforced Attention‐Driven: A High‐Performance and Computationally Efficient Cyber Threat Detection Framework for Smart Grids

Energy Science &Engineering, EarlyView.
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga, Praveen Kumar Balachandran, Umawathy Techanamurthy, Muhammad Ammirrul Atiqi Mohd Zainuri   +3 more
wiley   +1 more source

Predicting Parameters Affecting Building Energy Consumption Using Machine Learning Models

Energy Science &Engineering, EarlyView.
This framework integrates long‐term weather forecasting with building energy simulation to predict energy demand. The CNN–LSTM model achieved the highest accuracy (R2 ≈ 0.95), supporting smart HVAC control with ~ 15% energy savings. ABSTRACT The rapid growth of population and the construction industry have led to an increase in energy demand and an ...
Bassam Musheer Kareem, Abdolsalam Ebrahimpour, Jafar Ghafouri, Roghayyeh Motallebzadeh   +3 more
wiley   +1 more source

A Semi-Supervised Method for Multimodal Classification of Consumer Videos

International Journal of Information and Communication Technology Research, 2013
In large databases, lack of labeled training data leads to major difficulties in classification process. Semi-supervised algorithms are employed to suppress this problem. Video databases are the epitome for such a scenario.
Mahmood Karimian, Mostafa Tavassolipour, Shohreh Kasaei   +2 more
doaj  

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

Using Deep Learning Conditional Value‐at‐Risk Based Utility Function in Cryptocurrency Portfolio Optimisation

International Journal of Finance &Economics, EarlyView.
ABSTRACT One of the critical risks associated with cryptocurrency assets is the so‐called downside risk, or tail risk. Conditional Value‐at‐Risk (CVaR) is a measure of tail risks that is not normally considered in the construction of a cryptocurrency portfolio.
Xinran Huang, Linzhi Tan, Haozhe Su, Jeremy Eng‐Tuck Cheah   +3 more
wiley   +1 more source

From Reactive to Proactive Volatility Modeling With Hemisphere Neural Networks

Journal of Applied Econometrics, EarlyView.
ABSTRACT We revisit maximum likelihood estimation (MLE) for macroeconomic density forecasting through a novel neural network architecture with dedicated mean and variance hemispheres. Our architecture features several key ingredients making MLE work in this context.
Philippe Goulet Coulombe, Mikael Frenette, Karin Klieber   +2 more
wiley   +1 more source

A Comparative Study on Signal Decomposition Techniques for Stimulated Raman Photoacoustic Microscopy

Journal of Biophotonics, EarlyView.
Comparison of sO2 maps generated using signal decomposition methods. ABSTRACT In this paper, we present a comparative study of signal decomposition techniques in multispectral photoacoustic microscopy (MS‐PAM) systems that are based on the use of stimulated Raman spectroscopy (SRS).
Amir Khansari, Hossein Khodavirdi, Seyed Mohsen Ranjbaran, Mohsin Zafar, Mohammad Javad Beirami, Kamran Avanaki   +5 more
wiley   +1 more source

On Regular Quaternary Hadamard Matrices

Journal of Combinatorial Designs, EarlyView.
ABSTRACT Through the use of regularizing vectors, all regular quaternary Hadamard matrices of orders 10 and 18 have been successfully identified. Of these, two matrices of order 10 and 184 matrices of order 18 were found to have unbiased mates. Converting the quaternary Hadamard matrices of order 18 to real Hadamard matrices, the study uncovered that ...
Hadi Kharaghani, Behruz Tayfeh‐Rezaie, Vlad Zaitsev   +2 more
wiley   +1 more source