Academic Articles & Research Papers

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...

Planning on the Verge of AI, or AI on the Verge of Planning

The urban planning process is complex, involving social, economic, environmental, and political systems. Knowledge of how these systems interact is the domain of professional planners. Advances in artificial intelligence (AI) present planne...

Study on the impact of meteorological factors on influenza in different periods and prediction based on artificial intelligence RF-Bi-LSTM algorithm: to compare the COVID-19 period with the non-COVID-19 period

Abstract Objective At different times, public health faces various challenges and the degree of intervention measures varies. The research on the impact and prediction of meteorology factors on influenza is increasing gradually, however, th...

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...

Artificial Intelligence

Wearable E-Textiles for Cardiovascular Monitoring: Materials, Devices, and Integrated Systems.

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...

Artificial intelligence in nanotechnology

During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biologica...

A Primer on Generative Artificial Intelligence

Many educators and professionals in different industries may need to become more familiar with the basic concepts of artificial intelligence (AI) and generative artificial intelligence (Gen-AI). Therefore, this paper aims to introduce some ...

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...

Smart_Eye: A Navigation and Obstacle Detection for Visually Impaired People through Smart App

Vision is extremely important in our lives. The loss of sight is a serious issue for anyone. According to the WHO, one-sixth of the world's population suffers from vision impairment. According to World Health Organization (WHO) statistics p...

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...

AI-assisted neurocognitive assessment protocol for older adults with psychiatric disorders

IntroductionEvaluating neurocognitive functions and diagnosing psychiatric disorders in older adults is challenging due to the complexity of symptoms and individual differences. An innovative approach that combines the accuracy of artificia...

Validity and reliability of the Chinese translation of the attitude scale towards the use of artificial intelligence technologies in nursing (ASUAITIN)- a cross-sectional study

Abstract Aim This study aimed to test the psychometric properties of the Attitudes Toward Artificial Intelligence in Nursing Scale (ASUAITIN) in Chinese culture. Methods A convenience sampling method was employed to recruit 499 clinical nur...

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...