Academic Articles & Research Papers

Artificial Intelligence for Enhancing Resilience

In an increasingly complex and unpredictable world, resilience-the ability to withstand and recover from adverse conditions is essential across various sectors. This research paper investigates the transformative potential of artificial int...

Applications of artificial intelligence in intelligent manufacturing: a review

Based on research into the applications of artificial intelligence (AI) technology in the manufacturing industry in recent years, we analyze the rapid development of core technologies in the new era of ‘Internet plus AI’, which is triggerin...

Generative AI: reconfiguring supervision and doctoral research

The uptake of generative artificial intelligence (GenAI) tools has implications for doctoral research and academic publication practices within both construction management and the wider academic context. Unless these implications are under...

Evolution of strategies in iterated games: a deep multi-agent reinforcement learning approach with hybrid genetic and CMA-ES optimization

The emergence of cooperation among self-interested agents in social dilemmas remains a central unsolved problem in evolutionary game theory, multi-agent systems, and behavioral science. While memory-one reciprocal strategies such as Tit-for...

A Generalized Framework for Adopting Regression-Based Predictive Modeling in Manufacturing Environments

In this paper, the growing significance of data analysis in manufacturing environments is exemplified through a review of relevant literature and a generic framework to aid the ease of adoption of regression-based supervised learning in man...

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...

Neuromorphic Computing Using Synaptic Plasticity of Supercapacitors

Abstract Neuromorphic computing systems convert multimodal signals to electrical responses for artificial intelligence recognition. Energy is consumed during both the response enhancement and depression, making the systems suffer from high ...

Economic Evaluations of Artificial Intelligence Implementation in Diabetic Retinopathy Screening

Diabetic retinopathy (DR) is a common complication of diabetes that damages retinal blood vessels and can lead to vision impairment. The application of Artificial Intelligence (AI) in DR screening offers a promising alternative to conventio...

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 ...

Evolutionary Grey Wolf Optimizer with Cross-Search and Memory Mechanisms for Complex Optimization Problems

Abstract —Large-scale engineering optimization problems, characterized by hundreds or thousands of decision variables, complex constraints, and highly nonlinear objective functions, present significant challenges for conventional optimizati...

Artificial Intelligence and Business Value: a Literature Review

Abstract Artificial Intelligence (AI) are a wide-ranging set of technologies that promise several advantages for organizations in terms off added business value. Over the past few years, organizations are increasingly turning to AI in order...

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...

Artificial intelligence in pancreatic cancer

Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%. The pancreatic cancer patients diagnosed with early screening have a median overall survival of nearly ten years, compared with 1.5 years for th...

Developing mini-HTA to support evidence-based decision making in the Norwegian health services.

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...

Applying the radiated emission to the specific emitter identification

During the last years we have observed fast development of the electronic devices and electronic warfare systems (EW). One of the most principal functions of the ESM/ELINT system is gathering basic information from the entire electromagneti...

Semantic Interpretation for Convolutional Neural Networks: What Makes a Cat a Cat?

Abstract The interpretability of deep neural networks has attracted increasing attention in recent years, and several methods have been created to interpret the “black box” model. Fundamental limitations remain, however, that impede the pac...

Design of the Digital Pathology Workspace for Artificial Intelligence Integration

Designing an optimal digital pathology workspace is essential to ensure diagnostic accuracy and safeguard the long-term well-being of pathologists. While digital pathology improves reproducibility, facilitates multidisciplinary collaboratio...

Adaptive habitat biogeography-based optimizer for optimizing deep CNN hyperparameters in image classification

Deep Convolutional Neural Networks (DCNNs) have shown remarkable success in image classification tasks, but optimizing their hyperparameters can be challenging due to their complex structure. This paper develops the Adaptive Habitat Biogeog...