Academic Articles & Research Papers

Predicting Urban Quality of Life Using Machine Learning on Street Images and Personal Information with Statistical Feature Selection: A Comparative Study of Bangkok and London

This study proposes a machine learning framework for predicting perceived urban quality of life (QoL) by integrating visual features from street-level imagery with personal attributes, including demographic, socioeconomic, and travel behavi...

Machine Learning in Action

SummaryMachine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to bui...

An Introduction to Machine Learning

In the last few years, machine learning (ML) and artificial intelligence have seen a new wave of publicity fueled by the huge and ever-increasing amount of data and computational power as well as the discovery of improved learning algorithm...

Automated, economical, and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization

The increasing impact of the greenhouse effect on ecosystems is prompting transportation agencies to seek methods for reducing CO2 emissions during pavement construction and maintenance. Additionally, the laboratory mix design process, whic...

Evaluating Model Resilience to Data Poisoning Attacks: A Comparative Study

Machine learning (ML) has become a cornerstone of critical applications, but its vulnerability to data poisoning attacks threatens system reliability and trustworthiness. Prior studies have begun to investigate the impact of data poisoning ...

Perbandingan Algoritma Decision Tree dan K-Nearest Neighbor untuk Klasifikasi Serangan Jaringan IoT

Seiring dengan perkembangan jumlah penggunaan Internet of Things yang terus meningkat dan meluas. Ancaman keamanan pada jaringan IoT juga meningkat. Terdapat beberapa teknik yang diterapkan untuk mengatasi ancaman keamanan ini. Salah satuny...

Machine learning-derived prediction of in-hospital mortality in patients with severe acute respiratory infection: analysis of claims data from the German-wide Helios hospital network

Abstract Background Severe acute respiratory infections (SARI) are the most common infectious causes of death. Previous work regarding mortality prediction models for SARI using machine learning (ML) algorithms that can be useful for both i...

EEG Sensor-Based Computational Model for Personality and Neurocognitive Health Analysis Under Social Stress

This paper introduces an innovative EEG sensor-based computational framework that establishes a pioneering nexus between personality trait quantification and neural dynamics, leveraging biosignal processing of brainwave activity to elucidat...

Artificial intelligence model to predict pregnancy and multiple pregnancy risk following in vitro fertilization-embryo transfer (IVF-ET)

Objective: To decrease multiple pregnancy risk and sustain optimal pregnancy chance by choosing suitable number of embryos during transfer, this study aims to construct artificial intelligence models to predict the pregnancy outcome and mul...

Predicting Choroidal Nevus Transformation to Melanoma Using Machine Learning

Purpose: To develop and validate machine learning (ML) models to predict choroidal nevus transformation to melanoma based on multimodal imaging at initial presentation. Design: Retrospective multicenter study. Participants: Patients diagnos...

PERMEPSY: a multicentre, randomized, double-blind proof-of-concept trial of personalized metacognitive training for adults with psychosis — a study protocol

BackgroundWhile psychological interventions are effective at improving symptoms of psychosis, accessible, cost- and time-efficient treatments remain limited. Personalized medicine has emerged as a promising approach, tailoring interventions...

Social and juristic challenges of artificial intelligence

Abstract Artificial intelligence is becoming seamlessly integrated into our everyday lives, augmenting our knowledge and capabilities in driving, avoiding traffic, finding friends, choosing the perfect movie, and even cooking a healthier me...

Artificial intelligence: Implications for the future of work

Artificial intelligence (AI) is a broad transdisciplinary field with roots in logic, statistics, cognitive psychology, decision theory, neuroscience, linguistics, cybernetics, and computer engineering. The modern field of AI began at a smal...

Which features best differentiate Sjögren's-related from non-Sjögren's-related dry eye disease?

MONITORING SYSTEM FOR CRITICAL INFRASTRUCTURE OBJECTS BASED ON DIGITAL TWINS

Critical infrastructures are fundamental to the seamless operation of modern societies, encompassing sectors such as energy, healthcare, transportation, and communications. Ensuring their reliability, performance, continuous operation, safe...

The Integration of Cone Beam Computed Tomography, Artificial Intelligence, Augmented Reality, and Virtual Reality in Dental Diagnostics, Surgical Planning, and Education: A Narrative Review

(1) Background: Advancements in dental imaging technologies have significantly transformed diagnostic and surgical practices. The integration of cone beam computed tomography (CBCT), artificial intelligence (AI), augmented reality (AR), and...

Introducing Artificial Intelligence Training in Medical Education

Health care is evolving and with it the need to reform medical education. As the practice of medicine enters the age of artificial intelligence (AI), the use of data to improve clinical decision making will grow, pushing the need for skillf...

Natural Transports-Inspired Differential Semantic Communications: Intelligent Transceivers Carry Just Differences as Meanings

Communication is a fundamental process in the nature of interconnected entities. Conventional engineering models of information transmission and reception, namely Shannon’s bit communication and Weaver’s semantic communication...

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...

Prototype-oriented contrastive mean-teacher for unsupervised domain adaptive object detection

Abstract Unsupervised domain adaptive object detection (UDA-OD) aims to deploy a detector trained on source domain(s) to a new, unlabeled target domain. Carrying out mean-teacher self-training for UDA-OD poses a significant challenge, given...