Academic Articles & Research Papers

Robust Probabilistic Inference in Distributed Systems

Probabilistic inference problems arise naturally in distributed systems such as sensor networks and teams of mobile robots. Inference algorithms that use message passing are a natural fit for distributed systems, but they must be robust to ...

Fault-tolerant clock synchronization in distributed systems

Existing fault-tolerant clock synchronization algorithms are compared and contrasted. These include the following: software synchronization algorithms, such as convergence-averaging, convergence-nonaveraging, and consistency algorithms, as ...

Synergizing Generative AI and Cybersecurity: Roles of Generative AI Entities, Companies, Agencies, and Government in Enhancing Cybersecurity

The digital landscape of the modern world has witnessed a remarkable evolution over the past few decades, with technological advancements permeating every facet of our lives. While these innovations have brought forth unprecedented convenie...

A Survey of Cybersecurity of Digital Manufacturing

The Industry 4.0 concept promotes a digital manufacturing (DM) paradigm that can enhance quality and productivity, which reduces inventory and the lead time for delivering custom, batch-of-one products based on achieving convergence of addi...

Cybersecurity

The Internet has given rise to new opportunities for the public sector to improve efficiency and better serve constituents. But with an increasing reliance on the Internet, digital tools are also exposing the public sector to new risks. Thi...

Recurrent Neural Networks for Prediction

New technologies in engineering, physics and biomedicine are demanding increasingly complex methods of digital signal processing. By presenting the latest research work the authors demonstrate how real-time recurrent neural networks (RNNs) ...

State-of-the-art in artificial neural network applications: A survey

This is a survey of neural network applications in the real-world scenario. It provides a taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of current and emerging trends in ANN applications research and ar...

Self-Normalizing Neural Networks

Deep Learning has revolutionized vision via convolutional neural networks (CNNs) and natural language processing via recurrent neural networks (RNNs). However, success stories of Deep Learning with standard feed-forward neural networks (FNN...

PG-MACO Optimization Method for Ship Pipeline Layout

Aimed at the problem of low efficiency of ship pipeline design, an optimization method of pipeline layout is proposed. An optimization mathematical model is established by comprehensively considering the engineering background of safety, ec...

The pure Yang-Mills field, I: fixed time existence

The convergence of renormalized perturbation theory to all finite orders is defined and shown to be valid for the fixed time perturbation theory of a pure Yang-Mills field. Two pure Yang-Mills quantum gauge field theories are constructed, o...

Investigating Convergence of the ICD-11 Personality Disorder Model and the DSM-5's Alternative Model of Personality Disorders.

A quantum fuzzy logic-enhanced evolutionary framework for energy-latency optimization in 6G Edge-IioT

Abstract The transition toward 6G-enabled Industrial Internet of Things (IIoT) requires strict Ultra-Reliable Low-Latency Communication (URLLC), creating a fundamental trade-off with energy consumption. Orchestrating resources in dense, hyp...

Coalition of explainable artificial intelligence and quantum computing in precision medicine

This survey examines the convergence of Explainable Artificial Intelligence (XAI) and Quantum Computing (QC) toward precision medicine. We review developments from 2018 to 2025, summarizing quantum algorithms, quantum-machine-learning model...

Practical Vulnerability-Information-Sharing Architecture for Automotive Security-Risk Analysis

Emerging trends that are shaping the future of the automotive industry include electrification, autonomous driving, sharing, and connectivity, and these trends keep changing annually. Thus, the automotive industry is shifting from mechanica...

Spacing Allocation Method for Vehicular Platoon: A Cooperative Game Theory Approach

Recently, spacing policies of the vehicular platoon have been widely developed to enhance safety, traffic efficiency, and fuel consumption. However, the integrated spacing policies aim to maximum overall benefit, and the distributed spacing...

Advanced DFE, MLD, and RDE Equalization Techniques for Enhanced 5G mm-Wave A-RoF Performance at 60 GHz

This article presents the decision feedback equalizer (DFE), the maximum likelihood detection (MLD), and the radius-directed equalization (RDE) algorithms designed in MATLAB-R2018a to equalize the received signal in a dispersive optical lin...

Motion-Compensated PET Image Reconstruction via Separable Parabolic Surrogates

The effective resolution of positron emission tomography (PET) can be significantly degraded by patient motion during data acquisition. This is especially true in the thorax due to respiratory motion. This study concentrates on the improvem...

Solving Composite Fixed Point Problems with Block Updates

Various strategies are available to construct iteratively a common fixed point of nonexpansive operators by activating only a block of operators at each iteration. In the more challenging class of composite fixed point problems involving op...

Evolution of transfer learning in natural language processing

In this paper, we present a study of the recent advancements which have helped bring Transfer Learning to NLP through the use of semi-supervised training. We discuss cutting-edge methods and architectures such as BERT, GPT, ELMo, ULMFit amo...

Commercial applications of natural language processing

Vast quantities of text are becoming available in electronic form, ranging from published documents (e.g., electronic dictionaries, encyclopedias, libraries and archives for information retrieval services), to private databases (e.g., marke...