Academic Articles & Research Papers

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...

The meta-analysis of smart data international researches

Smart data is the raw material for many activities such as automation, intelligent systems, artificial intelligence and for the fourth industrial revolution. The purpose of this study is to systematically analyze all smart data related stud...

Artificial intelligence in medicine

INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting ou...

Tachyon: Enhancing stacked models using Bayesian optimization for intrusion detection using different sampling approaches

The integration of sensors in the monitoring of essential bodily measurements, air quality, and energy consumption in buildings demonstrates the importance of the Internet of Things (IoT) in everyday life. These security breaches are caused...

Optimized CNN-BiLSTM framework for reactive power management and voltage profile improvement in renewable energy based power grids

Abstract This article describes a method for improving power grid voltage profiles by more effectively regulating reactive power through the integration of hybrid renewable energy systems (HRES) in smart grids. The unpredictable nature of r...

Multi-objective Particle Swarm Optimization Algorithm Guided by Extreme Learning Decision Network

When solving multi-objective optimization problems, particle swarm optimization algorithms usually employ preset example selection methods and search strategies, which cannot be adjusted according to specific optimization states. In the fac...

Enhancing Online Security: A Novel Machine Learning Framework for Robust Detection of Known and Unknown Malicious URLs

The rapid expansion of the internet has led to a corresponding surge in malicious online activities, posing significant threats to users and organizations. Cybercriminals exploit malicious uniform resource locators (URLs) to disseminate har...

Artificial Intelligence

Scientists Doing Research On Artificial Intelligence are still far from their ultimate goal — a computer-based analog of the human brain. Nevertheless, their efforts have regularly produced results useful in applied computer science. For ex...

ID-Det: Insulator Burst Defect Detection from UAV Inspection Imagery of Power Transmission Facilities

The global rise in electricity demand necessitates extensive transmission infrastructure, where insulators play a critical role in ensuring the safe operation of power transmission systems. However, insulators are susceptible to burst defec...

Electromagnetic Field Distribution Mapping: A Taxonomy and Comprehensive Review of Computational and Machine Learning Methods

Electromagnetic field (EMF) exposure mapping is increasingly important for ensuring compliance with safety regulations, supporting the deployment of next-generation wireless networks, and addressing public health concerns. While numerous su...

A Comparison of Several AI Techniques for Authorship Attribution on Romanian Texts

Determining the author of a text is a difficult task. Here, we compare multiple Artificial Intelligence techniques for classifying literary texts written by multiple authors by taking into account a limited number of speech parts (prepositi...

A comprehensive review of explainable AI for disease diagnosis

Nowadays, artificial intelligence (AI) has been utilized in several domains of the healthcare sector. Despite its effectiveness in healthcare settings, its massive adoption remains limited due to the transparency issue, which is considered ...

Introduction to Artificial Intelligence

The Quest for Artificial Intelligence

Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) ...

A Comparative Analysis of Supervised and Unsupervised Models for Detecting Attacks on the Intrusion Detection Systems

Intrusion Detection Systems are expected to detect and prevent malicious activities in a network, such as a smart grid. However, they are the main systems targeted by cyber-attacks. A number of approaches have been proposed to classify and ...

Image Segmentation Using Active Contours with Hessian-Based Gradient Vector Flow External Force

The gradient vector flow (GVF) model has been widely used in the field of computer image segmentation. In order to achieve better results in image processing, there are many research papers based on the GVF model. However, few models includ...

Information Extraction Tool Text2ALM: From Narratives to Action Language System Descriptions

In this work we design a narrative understanding tool Text2ALM. This tool uses an action language ALM to perform inferences on complex interactions of events described in narratives. The methodology used to implement the Text2ALM system was...