Results 131 to 140 of about 850,977 (257)

Block Convolution Using Discrete Trigonometric Transforms and Discrete Fourier Transform

, 2008
We derive expressions for convolution multiplication properties of discrete cosine transform II (DCT II) starting from equivalent discrete Fourier transform (DFT) representations.
Suresh, K, Sreenivas, TV
core  

Cross‐Entropy of Power Spectral Density Function: A Modal Identification Framework

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT The power spectral density (PSD) function of measured structural response contains a significant amount of information, including the modal parameters (natural frequencies, damping ratios). Output‐only system identification or modal identification technique can be used for extracting such modal parameters from the measured response or its ...
Su‐Hong Kim, Jae‐Seung Hwang, Dae‐Kun Kwon, Ahsan Kareem   +3 more
wiley   +1 more source

Normalized Caputo-Fabrizio SVIR modeling and bifurcation analysis. [PDF]

Sci Rep
Shafqat R, Al-Quran A, Alsaadi A, Djaouti AM.   +3 more
europepmc   +1 more source

Learning Rocking Dynamics From Sparse Shake‐Table Data With Interpretable Physics‐Informed Neural Networks

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT We present a hybrid interpretable Physics‐Informed Neural Network Long‐Short Term Memory (Hybrid PINN LSTM) framework for predicting the seismic response of rocking blocks. Existing analytical models rely on uncertain idealizations, while purely data‐driven and machine‐learning approaches lack physical consistency and interpretability.
Shirley Shen, Christian Málaga‐Chuquitaype   +1 more
wiley   +1 more source

Roadmap on singular optics and its applications. [PDF]

Appl Phys B
Balasubramaniam GM, Allam SR, Anand V, Ansari MH, Arockiaraj FG, Arnon S, Badavath PS, Baliyan M, Bouchal P, Bouchal Z, Choudhary S, Dorrah AH, Duan Y, Everts K, Forbes A, Foreman MR, Gailevičius D, Gautam A, Gbur G, Gopinath S, Joshi N, Juodkazis S, Korotkova O, Kukli K, Kupferman J, Kumar P, Kumar R, Kumar V, Manavalan G, Mehra A, Nishchal NK, Omatsu T, Peters C, Reddy ANK, Reddy SG, Rodríguez-Fajardo V, Rosales-Guzmán C, Rosen J, Sarita, Shikder A, Singh RK, Su X, Tamm A, Velagala G, Viewegh P, Vilardell EP, Willner AE, Xavier API, Yadav A, Zhou H.   +49 more
europepmc   +1 more source

Tree‐Boost–Guided CNN–BiLSTM–Transformer for Solar Irradiance Forecasting: Cross‐Regional Evidence for Sustainable Energy Planning

Energy Science &Engineering, EarlyView.
This graphical abstract illustrates a reproducible pipeline that combines gradient‐boosting‐based feature selection with a CNN–BiLSTM–Transformer model to forecast solar irradiance across multi‐site satellite and ground datasets, delivering robust, high‐accuracy predictions that support sustainable grid planning and reliable PV integration.
Muhammad Farhan Hanif, Usama Hassan, Javid Hussain, Irfan Ali Khan, Yuldasheva Gulora, Syed Masood Arif Bukhari   +5 more
wiley   +1 more source

Convolutional neural network and wavelet composite against geometric attacks a watermarking approach. [PDF]

Sci Rep
Lakshmi C, Nithya C, Sivaraman R, Sridevi A, Santhiyadevi R, Ravichandran D, Banu SA, Mahalingam H, Meikandan PV, Amirtharajan R.   +9 more
europepmc   +1 more source

A Numerical Investigation of the Effects of Piston Bowl Geometry and Spray Angle on Combustion, Performance and Emission of a Diesel Engine

Energy Science &Engineering, EarlyView.
A piston bowl's design and spray angle improve air‐fuel mixing, resulting in more complete combustion and higher efficiency. Ansys Forte 2023 R1 a CFD software was used to analyze the effects of five combustion chamber geometries of cylinder, modified re‐entrant, re‐entrant, double‐stepped, and stepped on engine performance, combustion, and emission ...
Md. Nazmul Haque, Abdullah Al Rifat, Tafsirul Hassan, Md. Ifthaker Alam, Mohammad Mehedi Hasan Kazol, Md. Ashraful Islam, Abidur Rahman Adib, Mizanur Rahman   +7 more
wiley   +1 more source

Fault diagnosis of rolling bearing failures using a multi-stage e-CNN-GRU-SAM network. [PDF]

Sci Rep
Bisoyi S, Rathi AK, Mahato S.
europepmc   +1 more source

Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models

Energy Science &Engineering, EarlyView.
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani, Abdullahi Abubakar Mas'ud, Mohd Khairul Amri Kamarudin, Firdaus Muhammad‐Sukki, Abdullahi Mohammad   +4 more
wiley   +1 more source