Academic Articles & Research Papers

An agent-based modeling framework for the design of a dynamic closed-loop supply chain network

Abstract The supply chain is a dynamic and uncertain system consisting of material, information, and fund flows between different organizations, from the acquisition of the raw materials to the delivery of the finished products to the end c...

Assessment of Spatiotemporal Variations in the Water Quality of the Han River Basin, South Korea, Using Multivariate Statistical and APCS-MLR Modeling Techniques

This study evaluated the spatiotemporal variability of water quality in the Han River Basin (HRB) as well as the contributions of potential pollution sources using multivariate statistical and absolute principal component score-multiple lin...

Quantum Internet: Networking Challenges in Distributed Quantum Computing

The Quantum Internet, a network interconnecting remote quantum devices through quantum links in synergy with classical ones, is envisioned as the final stage of the quantum revolution, opening fundamentally new communications and computing ...

Feed-forward neural networks

One critical aspect neural network designers face today is choosing an appropriate network size for a given application. Network size involves in the case of layered neural network architectures, the number of layers in a network, the numbe...

Pointwise Convolutional Neural Networks

Deep learning with 3D data such as reconstructed point clouds and CAD models has received great research interests recently. However, the capability of using point clouds with convolutional neural network has been so far not fully explored....

Neural network design for engineering applications

Neural networks in the capital markets

PART ONE: NEURAL NETWORKS: Introduction Design Considerations Methods for Optimal Network Design Data Modelling Considerations Testing Strategies and Metrics PART TWO: EQUITY APPLICATIONS: Modelling Stock Returns in the Framework of APT: A ...

Neural Network Design

Multistage Convolutional Neural Network With Deformable Attention for Word-Level Offline Text-Independent Writer Identification

Offline writer identification is an essential component of biometric and forensic security fields, focusing on identifying the authors of handwritten documents in physical form. Historically, this approach has focused on text-dependent iden...

Efficient One-Dimensional Network Design Method for Underwater Acoustic Target Recognition

Many studies have used various time-frequency feature extraction methods to convert ship-radiated noise into three-dimensional (3D) data suitable for computer vision (CV) models, which have shown good results in public datasets. However, tr...

Monocular Depth Estimation using Transfer learning-An Overview

Depth estimation is a computer vision technique that is critical for autonomous schemes for sensing their surroundings and predict their own condition. Traditional estimating approaches, such as structure from motion besides stereo vision s...

Unmixing-Guided Convolutional Transformer for Spectral Reconstruction

Deep learning networks based on CNNs or transformers have made progress in spectral reconstruction (SR). However, many methods focus solely on feature extraction, overlooking the interpretability of network design. Additionally, models excl...

A Generative Super‐Resolution Model for Enhancing Tropical Cyclone Wind Field Intensity and Resolution

Abstract Extreme winds associated with tropical cyclones (TCs) can cause significant loss of life and economic damage globally, highlighting the need for accurate, high‐resolution modeling and forecasting for wind. However, due to their coa...