Academic Articles & Research Papers

Empirical methods for artificial intelligence

Empirical research exploratory data analysis basic issues in experiment design hypothesis testing and estimation computer-intensive statistical methods performance assessment explaining performance - interactions and dependencies modelling ...

Ranking-Based Case Retrieval with Graph Neural Networks in Process-Oriented Case-Based Reasoning

In Process-Oriented Case-Based Reasoning (POCBR), experiential knowledge from previous problem-solving situations is retrieved from a case base to be reused for upcoming problems. The task of retrieval is approached in previous work by usin...

Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions

Autonomous driving has achieved significant milestones in research and development over the last two decades. There is increasing interest in the field as the deployment of autonomous vehicles (AVs) promises safer and more ecologically frie...

A unified multi-modal foundation model for end-to-end emergency care.

Human-supervised LLM triage of pig butchering complaints: A validation study of multi-model identifier extraction.

Prediction of bank transaction fraud using TabNet—an adaptive deep learning architecture

The development of online banking has brought about an increase in fraudulent operations, which is a major problem for banks. This study delves into the urgent requirement for interpretable, scalable, and top-notch fraud detection systems b...

Insights into the entire building life cycle assessment (LCA): existing trends, challenges and prospective framework

Building sustainability assessment increasingly demands life cycle coverage that captures environmental burdens and trade-offs beyond operational energy, including embodied impacts and end of life (EoL) outcomes under circular economy (CE) ...

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...

Evidence for Dynamical Filtering: High Binary Fraction, Hard-binary Excess, and Unresolved Triples in the Surviving Core of NGC 6791

We present a deep photometric analysis of the main-sequence (MS) population in the old, metal-rich open cluster (OC) NGC 6791 using Gaia Data Release 3 data. After correcting for differential reddening, we use the Bayesian model comparison ...

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 for waste management in smart cities: a review

The rising amount of waste generated worldwide is inducing issues of pollution, waste management, and recycling, calling for new strategies to improve the waste ecosystem, such as the use of artificial intelligence. Here, we review the appl...

Using LLMs for Augmenting Hierarchical Agents with Common Sense Priors

Solving long-horizon, temporally-extended tasks using Reinforcement Learning (RL) is challenging, compounded by the common practice of learning without prior knowledge (or tabula rasa learning). Humans can generate and execute plans with te...

Artificial Intelligence Voluntary Disclosures and Their Effect on Firms’ Financial Performance: Evidence from Egypt Firms on the EGX30 Index

The present paper, thus, investigates the link between AI-disclosure in annual reports and firm performance in the Egyptian financial industry. It explains how the number of appertained AI-words in the corporate disclosures would correspond...

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...

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...

QATIPANA: Processes of Individuation on the Relationship Between Art, Machine and Natural Systems

The present research turns around the concepts and processes of Becoming and Individuation where it evidences a functional model based on the articulation of an informational processing system based on the approaches of the philosopher Gilb...

Generating preferred plans with ethical features

Normative ethics has been shown to help automated planners take ethically aware decisions. However, state- of-the-art planning technologies don’t provide a sim- ple and direct way to support ethical features. Here, we propose a new theoreti...

From “usefulness” to “dependence”: the dynamic evolution mechanism of generative AI use behaviors

BackgroundAs generative artificial intelligence (GenAI) rapidly permeates Chinese higher education, university students’ AI use behaviors have come to be characterized by “high frequency, wide penetration, and rapid iteration.” Yet, a syste...

Generality in artificial intelligence

My 1971 Turing Award Lecture was entitled "Generality in Artificial Intelligence." The topic turned out to have been overambitious in that I discovered I was unable to put my thoughts on the subject in a satisfactory written form at that ti...

Microplastic Pollution and Risk of Cancer: A Prospective Study Based on UK Biobank.