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

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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Enhancing cyber threat detection with an improved artificial neural network model

Identifying cyberattacks that attempt to compromise digital systems is a critical function of intrusion detection systems (IDS). Data labeling difficulties, incorrect conclusions, and vulnerability...

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Enhancing imbalanced text classification: an overlap-based refinement approach

The inherent class imbalance within textual data poses a significant challenge for machine learning-based techniques, as the available data often fails to adequately represent all classes. This scarcity...

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Particle swarm optimization-enhanced machine learning and deep learning techniques for Internet of Things intrusion detection

The exponential escalation of cyber threats and attacks targeting Internet of Things (IoT) devices in this decade necessitates the development of effective intrusion detection methods. This paper presents...

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Prediction of retail commodity hot-spots: a machine learning approach

The accurate prediction of hot-spot commodities in the retail market is crucial for inventory management and market strategy formulation. Traditional methods focus on analyzing the sales trends of listed...

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Automatic method for identification of cycles in Covid-19 time-series data

All previous methods identify cycles in Covid-19 daily and weekly data based on a subjective interpretation of the results. This poses difficulties for researchers interested in conducting comprehensive...

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Unlocking the power of machine learning in big data: a scoping survey

Machine learning (ML) plays a crucial role in big data (BD) by serving as the cornerstone of efficient data processing and analysis. In particular, ML provides BD with the ability to extract valuable...

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Identifying Accounting Control Issues from Online Employee Reviews

This paper presents and describes an approach to generate innovative labeled datasets that enable automated text classifiers to automatically detect online employee reviews referring to accounting control...

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Counterfactual synthetic minority oversampling technique: solving healthcare’s imbalanced learning challenge

The application of machine learning in the healthcare domain has groundbreaking potential across a wide range of scenarios. However, this potential is often stalled by data-related challenges, such...

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Climate physical risks: catalyst or constraint for the convergence of the digital and low-carbon economies?

The digital economy and the low-carbon economy are crucial catalysts of global economic change and sustainable development. This research focuses on China and thoroughly examines the coupling and coordination...

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Impact of China’s outward foreign direct investment on the Belt and Road Initiative countries’ digital economy and energy transition

Digital economy (DE) is on the verge of becoming a pivotal facilitator of energy transition (ET). However, it remains to be seen to what extent China’s outward foreign direct investment (OFDI) can stimulate...

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The Impact of mHealth Apps’ Affordance on Consumers’ Novel Food Purchasing Decisions

Mobile health apps (MHAs) provide users with exercise support and dietary recommendations. They also suggest a wide range of novel foods. However, some users may face food neophobia, a reluctance to...

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The effect of green mergers and acquisitions on the green transformation of heavily polluting enterprises: empirical evidence from China

This study examines the impact of green mergers and acquisitions (GMAs) on the green transformation of heavily polluting enterprises (HPPs) with the following key findings. (1) GMAs significantly promote...

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Electroencephalogram-Based Emotion Recognition: A Comparative Analysis of Supervised Machine Learning Algorithms

Emotion recognition from electroencephalogram (EEG) signals has garnered significant attention owing to its potential applications in affective computing, human-computer interaction, and mental health...

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Meta -model-based optimization of rule-based energy management in second-hand plug-in hybrid electric vehicles

This study presents a methodology to enhance energy management systems (EMS) in hybrid electric vehicles (HEVs) to reduce fuel consumption and greenhouse gas emissions. A novel surrogate-assisted optimization...

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User-centric avatar design: a cognitive walkthrough approach for metaverse in virtual education

Metaverse, once a concept confined to science fiction, has emerged as a transformative reality during the digital era. As this immersive virtual world gains prominence, the role of avatars and the digital...

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Trust and involvement of Cameroonian software developers in open-source projects

Although recent studies have examined collaboration within open-source software projects, the focus has primarily been on their motivations and governance. This study explores the complex dynamics of...

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Will China’s carbon-trading policy foster coordinated innovation in green technologies?

Accelerating green innovation is crucial for achieving high-quality development in China. Despite this importance, empirical evidence on the harmonization techniques in the context of carbon-trading...

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Trust framework for self-sovereign identity in metaverse healthcare applications

The research community and digital sector are currently engaged in the development of diverse services within the metaverse ecosystems. Conversely, as concerns about safeguarding personal privacy mount,...

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Bibliometric analysis of the art market: from art price to market efficiency

This study addresses a significant gap in the existing literature by conducting a comprehensive systematic review of the art market over the past 50 years, utilizing big data analysis and bibliometric...

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Analysis of digital twin and its physical object: exploring the efficiency and accuracy of datasets for real-world application

The concept of digital twin (DT) has recently gained popularity due to its ability to create a virtual representation of systems in order to improve the performance of its cyber-physical counterpart....

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Comparative analysis of manual and programmed annotations for crowd assessment and classification using artificial intelligence

Funding agencies play a pivotal role in bolstering research endeavors by allocating financial resources for data collection and analysis. However, the lack of detailed information regarding the methods...

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Quality of life issues in rural settlements: assessment by social media users

Disparity in the quality of life of people living in rural and urban areas is among the major problems, often leading to greater depression among the rural population compared to those in urban areas...

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Application of user preference mining algorithms based on data mining and social behavior in brand building

Small and medium-sized enterprises currently suffer from a lack of branding. Therefore, to further promote their active branding, this study proposes a user preference mining algorithm based on data...

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