Academic Articles & Research Papers

Unmanned Aerial Vehicle for Precision Agriculture: A Review

Digital Precision Agriculture (DPA) is a comprehensive approach to agronomic management that utilizes advanced technologies, such as sensor data analysis and automation, to optimize crop productivity, enhance farm income, and minimize envir...

Enhancing AI Explainability Through the EXACT Framework: A User-Centric Approach

The increasing adoption of Artificial Intelligence (AI) in several industries has created a demand for user-centered explanations that align with how users think and understand concepts. This paper presents EXACT (EXplainable AI with Cognit...

Assessing and Optimizing Socio-Moral Reasoning Skills: Findings From the MorALERT Serious Video Game

BackgroundSocial cognition and competence are a key part of daily interactions and essential for satisfying relationships and well-being. Pediatric neurological and psychological conditions can affect social cognition and require assessment...

Enhancing Explainable Artificial Intelligence: Using Adaptive Feature Weight Genetic Explanation (AFWGE) with Pearson Correlation to Identify Crucial Feature Groups

The ‘black box’ nature of machine learning (ML) approaches makes it challenging to understand how most artificial intelligence (AI) models make decisions. Explainable AI (XAI) aims to provide analytical techniques to understand the behavior...

An automated deep learning framework for brain tumor classification using MRI imagery

Abstract The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment s...

A Study on the Effectiveness of Deep Learning-Based Anomaly Detection Methods for Breast Ultrasonography

In the medical field, it is delicate to anticipate good performance in using deep learning due to the lack of large-scale training data and class imbalance. In particular, ultrasound, which is a key breast cancer diagnosis method, is delica...

A review of optimization strategies for deep and machine learning in diabetic macular edema

Diabetic macular edema (DME) is a primary contributor to visual impairment in diabetic patients, necessitating precise and prompt analysis for optimal treatment. Recent breakthroughs in deep learning (DL) and machine learning (ML) have yiel...

Artificial Intelligence Today

Introduction to artificial intelligence

"Are we intelligent enough to understand intelligence? One approach to answering this question is "artificial intelligence," the field of computer science that studies how machines can be made to act intelligently. This book is intended to ...

Comparative architectural evaluation of CNN models with alternative classifiers for UAV-based detection of damaged green zones

Unmanned aerial vehicle imagery provides a practical and high-resolution data source for monitoring the spatial condition of urban and peri-urban green zones. However, the reliable detection of damaged, stressed, or declining vegetation are...

Artificial Intelligence: A Guide to Intelligent Systems

From the Publisher: Virtually all the literature on artificial intelligence is expressed in the jargon of commuter science, crowded with complex matrix algebra and differential equations. Unlike many other books on computer intelligence, t...

Explainable and perturbation-resilient model for cyber-threat detection in industrial control systems Networks

Abstract Deep learning-based intrusion detection systems (DL-IDS) have proven effective in detecting cyber threats. However, their vulnerability to adversarial attacks and environmental noise, particularly in industrial settings, limits pra...

MCoGCN-motif high-order feature-guided embedding learning framework for social link prediction

Abstract Traditional social link prediction models primarily concentrate on the adjacency features of the network, overlooking the rich high-order structural information within. Therefore, the study of effective extraction and encoding of t...

The Political Economy of Sanctions on Iran: Mechanism Design and Agent-Based Modeling Approach

I International relations are full of complexities due to their multifaceted and multilateral nature. To understand decision making processes and the payoffs of their strategies, players are enabled to utilize their capabilities to impact t...

Computer vision and AI-based cell phone usage detection in restricted zones of manufacturing industries

Phone calls are strictly forbidden in certain locations due to the potential security threats. Mobile phones’ growing capabilities have also increased the risk of their misuse in places that are restricted, like manufacturing plants. Unauth...

Cobdock: an accurate and practical machine learning-based consensus blind docking method

Abstract Probing the surface of proteins to predict the binding site and binding affinity for a given small molecule is a critical but challenging task in drug discovery. Blind docking addresses this issue by performing docking on binding r...

Emergentist View on Generative Narrative Cognition: Considering Principles of the Self-Organization of Mental Stories

We consider the essence of human intelligence to be the ability to mentally (internally) construct a world in the form of stories through interactions with external environments. Understanding the principles of this mechanism is vital for r...

An Ensemble Machine Learning Model for Early Prediction of Vancomycin-Induced Acute Kidney Injury in ICU Patients

Introduction: Acute Kidney Injury (AKI) is a severe complication of vancomycin treatment due to its nephrotoxic effects. However, research on predicting AKI in this high-risk group remains limited. This study presents a stacking ensemble ma...

Raman Spectroscopy Pre-Trained Encoder: A Self-Supervised Learning Approach for Data-Efficient Domain-Independent Spectroscopy Analysis

Deep-learning methods have boosted the analytical power of Raman spectroscopy, yet they still require large, task-specific, labeled datasets and often fail to transfer across application domains. The study explores pre-trained encoders as a...

Sparsity Increases Uncertainty Estimation in Deep Ensemble

Deep neural networks have achieved almost human-level results in various tasks and have become popular in the broad artificial intelligence domains. Uncertainty estimation is an on-demand task caused by the black-box point estimation behavi...