IEEE

A Simulated Annealing Global Maximum Power Point Tracking Approach for PV Modules Under Partial Shading Conditions

Abstract: This paper proposes a simulated annealing (SA)-based global maximum power point tracking (GMPPT) technique designed for photovoltaic (PV) systems which experience partial shading conditions ...
IEEE

3D Instance Embedding Learning With a Structure-Aware Loss Function for Point Cloud Segmentation

Abstract: This letter presents a framework for 3D instance segmentation on point clouds. A 3D convolutional neural network is used as the backbone to generate semantic predictions and instance ...
IEEE

Component-based Point Spread Function Modeling for an Adaptive Multi-Pinhole SPECT with Full-Ring Detectors

Abstract: We developed an adaptive whole-body SPECT/CT with a full detector ring and eight sets of multi-pinhole (MPH) collimators. Each MPH collimator was designed for specific clinical practices ...
Hosted on MSN

Web VPython tutorial: Building a standard deviation function

Learn how to build a standard deviation function in VPython with this step-by-step web tutorial! Perfect for coding, data analysis, and physics simulations. #VPython #PythonTutorial #StandardDeviation ...
IEEE

LSTM Network Assisted Construction of the Angle-Dependent Point Spread Function and Its Applications in Seismic Imaging

Abstract: Migration is the core link in reflection seismic exploration. Seismic images are often extended into angle domain for interpretations. However, affected by limited acquisition aperture and ...
Hosted on MSN

Spreadsheet tutorial: Calculate and plot mathematical functions

Learn how to calculate and plot mathematical functions using a spreadsheet. This tutorial shows step-by-step how to set up formulas, visualize data, and create clear graphs for math and science ...
IEEE

IGASA: Integrated Geometry-Aware and Skip-Attention Modules for Enhanced Point Cloud Registration

Abstract: Point cloud registration (PCR) is a fundamental task in 3D vision and provides essential support for applications such as autonomous driving, robotics, and environmental modeling. Despite ...
IEEE

Learning Activation Functions in Deep (Spline) Neural Networks

Abstract: We develop an efficient computational solution to train deep neural networks (DNN) with free-form activation functions. To make the problem well-posed, we augment the cost functional of the ...
IEEE

AotmAuth: Atomic Function Module-Based 6G Authentication Protocol Combination Framework

Abstract: Over the years, various mobile communication technologies have been developed and operated simultaneously, which made the mobile communication networks evolved from single-mode access to ...
Nature

Network Synthesis: Synthesis of a Finite Four-Terminal Network from its Prescribed Driving-Point Functions and Transfer Function

THIS work is an interesting exercise, and its subtitle is accurate. The main title alone, however, is quite misleading, for the reader who goes to this book for a general and comprehensive treatment ...