Academic Articles & Research Papers

Assessing climate and land use impacts on surface water yield using remote sensing and machine learning

Abstract Climate and land use changes are critical factors affecting watershed water yields, with significant implications for water resources at both local and regional levels. This study examined the combined effects of temporal and spati...

Explainable artificial intelligence: A survey

In the last decade, with availability of large datasets and more computing power, machine learning systems have achieved (super)human performance in a wide variety of tasks. Examples of this rapid development can be seen in image recognitio...

Natural Transports-Inspired Differential Semantic Communications: Intelligent Transceivers Carry Just Differences as Meanings

Communication is a fundamental process in the nature of interconnected entities. Conventional engineering models of information transmission and reception, namely Shannon’s bit communication and Weaver’s semantic communication...

SEMANTIC URBAN MESH SEGMENTATION BASED ON AERIAL OBLIQUE IMAGES AND POINT CLOUDS USING DEEP LEARNING

The use of deep machine learning methods for semantic classification of city mesh models is one of the current trends in geoscience development. Thanks to the thriving development of Convolutional Neural Networks (CNNs) it is now achievable...

AI-Driven Identification of Critical Dependencies in US-China Technology Supply Chains: Implications for Economic Security Policy

This research examines the critical dependencies within US-China technology supply chains through advanced artificial intelligence methodologies, addressing significant economic security implications in an era of strategic competition. The ...

Artificial intelligence: A powerful paradigm for scientific research

Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day li...

Tailoring industrial enzymes for thermostability and activity evolution by the machine learning-based iCASE strategy

Abstract The pursuit of obtaining enzymes with high activity and stability remains a grail in enzyme evolution due to the stability-activity trade-off. Here, we develop an isothermal compressibility-assisted dynamic squeezing index perturba...

Evaluating new technology for biodiversity monitoring: Are drone surveys biased?

Abstract Drones and machine learning‐based automated detection methods are being used by ecologists to conduct wildlife surveys with increasing frequency. When traditional survey methods have been evaluated, a range of factors have been fou...

Composition Design and Property Prediction for AlCoCrCuFeNi High-Entropy Alloy Based on Machine Learning

Based on the innovative mode driven by “data + artificial intelligence”, in this study, three methods, namely Gaussian noise (GAUSS Noise), the Generative Adversarial Network (GAN), and the optimized Generative Adversarial Network (GANPro),...

Artificial Intelligence

The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machi...

Machine Learning and Artificial Intelligence

An Overview of Artificial Intelligence Applications for Power Electronics

This is a preprint version of the manuscript submitted to IEEE on June 4, 2020. This paper gives an overview of the Artificial Intelligence (AI) applications for power electronic systems. The three distinctive life-cycle phases, design, con...

Harnessing Machine Learning for Procedural Content Generation in Gaming: A Comprehensive Review

Procedural Content Generation (PCG) through automated and algorithmic content generation is an active research field in the gaming industry. Recently, Machine Learning (ML) approaches have played a pivotal role in advancing this area. While...

Artificial intelligence in radiotherapy

Artificial intelligence (AI) has already been implemented widely in the medical field in the recent years. This paper first reviews the background of AI and radiotherapy. Then it explores the basic concepts of different AI algorithms and ma...

Machine learning models using longitudinal laboratory data predict survival in allogeneic stem cell recipients.

Normalized risk-based evaluation of machine learning-based classification models: A multiclass approach with applications in medical devices.

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...

Assessing carbon and economic loss from oak decline in Iran’s Zagros forests using Sentinel-2 and machine learning

Over recent decades, the decline of oak trees, which has emerged as the most significant challenge to the Zagros forests (ZFs), poses serious threats to carbon storage (CS) and economic valuation, jeopardizing the ecological and economic su...

Artificial intelligence and machine learning

Abstract Within the last decade, the application of “artificial intelligence” and “machine learning” has become popular across multiple disciplines, especially in information systems. The two terms are still used inconsistently in academia ...

The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare

INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including healthcare. This article reviews AI's present applications in healthcare, including its benefits, limitations and...