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Open access

ISSN: 2666-7649
CN: 61-1530/TN
p-ISSN: 2097-3187

Factors influencing readiness for artificial intelligence: a systematic literature review

Public-and private-sector organizations have adopted artificial intelligence (AI) to meet the challenges of the Fourth Industrial Revolution. The successful implementation of AI is a challenging task,...

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Does the application of industrial robots reduce the intensity of CO2 emissions embodied in manufacturing exports?

Industrial robot application (IRA) provides an opportunity for the low-carbon development of trade. This study focuses on the green revolution of manufacturing export trade, analyzes the mechanism by...

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A novel method for a technology enhanced learning recommender system considering changing user interest based on neural collaborative filtering

This study introduces an advanced recommender system for technology enhanced learning (TEL) that synergizes neural collaborative filtering, sentiment analysis, and an adaptive learning rate to address...

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Engaging in sports via the metaverse? An examination through analysis of metaverse research trends in sports

In sports, virtual spaces are sometimes utilized to enhance performance or user experience. In this study, we conducted a frequency analysis, semantic network analysis, and topic modeling using 134...

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Determinants of continuous usage intention of branded apps in omni-channel retail environment: comparison between experience-oriented and transaction-oriented apps

Branded applications (apps) have become core touchpoints for improving consumer shopping experiences in omni-channel retailing, and many firms have developed different types of branded apps to provide...

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Assessing the impact of artificial intelligence on customer performance: a quantitative study using partial least squares methodology

The purpose of this research is to examine the impact of artificial intelligence (AI) on customer performance and identify the factors contributing to its effectiveness by employing a quantitative approach,...

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Original optimal method to solve the all-pairs shortest path problem: Dhouib-matrix-ALL-SPP

The All-pairs shortest path problem (ALL-SPP) aims to find the shortest path joining all the vertices in a given graph. This study proposed a new optimal method, Dhouib-matrix-ALL-SPP (DM-ALL-SPP) to...

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The relationship between attribute performance and customer satisfaction: an interpretable machine learning approach

Understanding the relationship between attribute performance (AP) and customer satisfaction (CS) is crucial for the hospitality industry. However, accurately modeling this relationship remains challenging....

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Optimizing data aggregation and clustering in Internet of things networks using principal component analysis and Q-learning

The Internet of things (IoT) is a wireless network designed to perform specific tasks and plays a crucial role in various fields such as environmental monitoring, surveillance, and healthcare. To address...

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When cryptography stops data science: strategies for resolving the conflicts between data scientists and cryptographers

The advent of the digital era and computer-based remote communications has significantly enhanced the applicability of various sciences over the past two decades, notably data science (DS) and cryptography...

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Survival strategies for family-run homestays: analyzing user reviews through text mining

Online booking of homestays through e-travel portals is based on the virtual brand and perception, which are largely affected by user-generated electronic word-of-mouth (eWOM). With the objective of...

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Development of a machine learning model for predicting abnormalities of commercial airplanes

Airplanes are a social necessity for movement of humans, goods, and other. They are generally safe modes of transportation; however, incidents and accidents occasionally occur. To prevent aviation accidents,...

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Machine acceleration time series prediction for dimensional accuracy of 3D printed parts

This study explores the influence of infill patterns on machine acceleration prediction in the realm of three-dimensional (3D) printing, particularly focusing on extrusion technology. Our primary objective...

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Residual-enhanced graph convolutional networks with hypersphere mapping for anomaly detection in attributed networks

In the burgeoning field of anomaly detection within attributed networks, traditional methodologies often encounter the intricacies of network complexity, particularly in capturing nonlinearity and sparsity....

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Understanding users' effective use of generative conversational AI from a media naturalness perspective: A hybrid SEM-ANN approach

Although generative conversational artificial intelligence (AI) can answer questions well and hold conversations as a person, the semantic ambiguity inherent in text-based communication poses challenges...

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An Explainable Feature Selection Framework for Web Phishing Detection with Machine Learning

In the evolving landscape of cyber threats, phishing attacks pose significant challenges, particularly through deceptive webpages designed to extract sensitive information under the guise of legitimacy....

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Design of knowledge transaction protection mechanism in the open innovation community based on blockchain technology

Open innovation communities (OICs) are important for the development of modern enterprises. However, there are still many safety hazards and trust crises on community platforms. This paper proposes...

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Effects of feature selection and normalization on network intrusion detection

The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence (AI) techniques (such as machine learning (ML) and deep learning...

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Digital Volunteer Services in Emergency Situations: Typological Characteristics, Advantages, and Challenges

Volunteer engagement in emergency management, focusing on mitigating adverse consequences, has attracted scholarly and practitioner attention. Digital volunteering helps overcome the limitations of...

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Forecast Uncertainties Real-Time Data-Driven Compensation Scheme for Optimal Storage Control

This study introduces a real-time data-driven battery management scheme designed to address uncertainties in load and generation forecasts, which are integral to an optimal energy storage control system....

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Dual-market quantitative trading: The dynamics of liquidity and turnover in financial markets

Financial market liquidity is a popular research topic. Investor-driven research uses the turnover rate to measure liquidity and generally finds that the higher the stock turnover rate, the lower the...

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A Model for Predicting Dropout of Higher Education Students

Higher education institutions are becoming increasingly concerned with the retention of their students. This work is motivated by the interest in predicting and reducing student dropout, and consequently...

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Comparative study of IoT- and AI-based computing disease detection approaches

The emergence of different computing methods such as cloud-, fog-, and edge-based Internet of Things (IoT) systems has provided the opportunity to develop intelligent systems for disease detection....

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Using multi-criteria decision-making and machine learning for football player selection and performance prediction: a systematic review

Evaluating and selecting players to suit football clubs and decision-makers (coaches, managers, technical, and medical staff) is a difficult process from a managerial-financial and sporting perspective....

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Topic prevalence and trends of metaverse in healthcare: a bibliometric analysis

Metaverse technology is an advanced form of virtual reality and augmented technologies. It merges the digital world with the real world, thus benefitting healthcare services. Medical informatics is...

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