The existing learning resource recommendation systems suffer from data sparsity and missing data labels, leading to the insufficient mining of the correlation between users and courses. To address these issues, we propose a learning resource recommen...
Educational research is increasingly paying attention to students’ out-of-class learning. Students’ out-of-class learning is linked to improved class performance and constitutes an important part of learner development. Prior research has...
Understanding a learner’s resources as a system of interacting components, the success of a learning process is determined by the effectiveness of their interactions. Theoretical assumptions and empirical findings clearly show the importance of...
Network Slicing and Deep Reinforcement Learning (DRL) are vital enablers for achieving 5G and 6G networks. A 5G/6G network can comprise various network slices from unique or multiple tenants. Network providers need to perform intelligent and efficien...
In Chinese character learning, distinguishing similar characters is challenging for learners regardless of their proficiency. This is due to the complex orthography (visual word form) linking symbol, pronunciation, and meaning. Multimedia learning is...
Mineral resource estimation involves the determination of the grade and tonnage of a mineral deposit based on its geological characteristics using various estimation methods. Conventional estimation methods, such as geometric and geostatistical techn...
In the modern digital age, traditional teaching methods are increasingly giving way to innovative approaches that actively engage all students’ senses. Integrating diverse media formats into learning stimulates students’ visual, auditory,...
It is essential to encourage scientific understanding of water resources. However, how to achieve this for different objects needs to be researched further. Therefore, the purpose of this study is to analyze the impact of game-based teaching on eleme...
Background: This paper has identified a gap in the extant Human Resource higher education literature in relation to the use of sustainable e-learning pedagogy. As such, a scoping review has been undertaken to draw conclusions to help narrow this gap....
Water resource modeling is an important means of studying the distribution, change, utilization, and management of water resources. By establishing various models, water resources can be quantitatively described and predicted, providing a scientific...
The recent adoption of deep learning for diverse applications has required infrastructures to be scaled horizontally and hybrid configured vertically. As a result, efficient resource management for distributed deep learning (DDL) frameworks is becomi...
The increasing demand for smart vehicles with many sensing capabilities will escalate data traffic in vehicular networks. Meanwhile, available network resources are limited. The emergence of AI implementation in vehicular network resource allocation...
This document explores the concept of Learning Styles (LSs) and their implications for Adaptive Learning Systems (ALSs). It begins by defining LSs as distinct patterns of behavior and thought that influence how individuals process information, drawin...
Machine learning (ML) is increasingly applied in earth sciences, including in mineral resource estimation. A critical step in this process is domaining, which significantly impacts estimation quality. However, the importance of domaining within ML-ba...
Personalized learning resource recommendation is an essential component of intelligent tutoring systems. To address the issue of the plethora of learning resources and enhance the learner experience in intelligent tutoring systems, learning resource...
It is widely accepted that environmental awareness is essential, yet does not inevitably lead to responsible use of resources. Additional factors on the individual level include the meaning constructed by the term “resources” and the individual and s...
The space information networks (SIN) have a series of characteristics, such as strong heterogeneity, multiple types of resources, and difficulty in management. Aiming at the problem of resource allocation in SIN, this paper firstly establishes a hier...
Satellite communications (SatComs) systems are facing a massive increase in traffic demand. However, this increase is not uniform across the service area due to the uneven distribution of users and changes in traffic demand diurnal. This problem is a...
Network slicing to create multiple virtual networks, called network slice, is a promising technology to enable networking resource sharing among multiple tenants for the 5th generation (5G) networks. By offering a network slice to slice tenants, netw...
The existing research on dependent task offloading and resource allocation assumes that edge servers can provide computational and communication resources free of charge. This paper proposes a two-stage resource allocation method to address this issu...
In classical schedule problems, the actual processing time of a job is a fixed constant, but in the actual production process, the processing time of a job is affected by a variety of factors, two of which are the learning effect and resource allocat...
Managing resource use in cloud and edge environments is crucial for optimizing performance and efficiency. Traditionally, this process is performed with detailed knowledge of the available infrastructure while being application-specific. However, it...
This paper offers a comprehensive overview of machine learning (ML) methodologies and algorithms, highlighting their practical applications in the critical domain of water resource management. Environmental issues, such as climate change and ecosyste...
This study investigates the impact of community participation in sustainable learning resource development through the mediating effect of awareness in Bangkok, Thailand. The determinants of community participation comprise three levels: top-level pa...
Building an effective automatic speech recognition system typically requires a large amount of high-quality labeled data; However, this can be challenging for low-resource languages. Currently, self-supervised contrastive learning has shown promising...
Resource bricolage, centered on breaking through resource constraints, emphasizes providing innovation momentum for new ventures by creatively reorganizing existing resources at hand. Existing studies have confirmed that resource bricolage exerts an...
Since Internet-based resources provides various and practical forms of English learning materials, Internet-based resources English learning is a common way for the younger generation. However, not like adult learning, university students need strong...
The application of artificial intelligence enhances the ability of sensor and networking technologies to realize smart systems that sense, monitor and automatically control our everyday environments. Intelligent systems and applications often automat...
This systematic literature review analyzes machine learning (ML)-based techniques for resource management in fog computing. Utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, this paper focuses on ML a...
We aim to identify the engagement strategies that higher education students, engaging in emergency online learning in low-resource settings, perceive to be effective. We conducted a sequential mixed-methods study based on Moore’s interaction fr...
This research discusses the potential of using big data for vocabulary learning from the perspective of learner-generated pictorial annotations. Pictorial annotations lead to effective vocabulary learning, the creation of which is however challenging...
The purpose of this research is to determine the level of teacher candidates’ lifelong learning competence and basic motivation resources and to examine the lifelong learning competence and basic motivation of teacher candidates in terms of some vari...
Device-to-device (D2D) communication is an essential feature for the future cellular networks as it increases spectrum efficiency by reusing resources between cellular and D2D users. However, the performance of the overall system can degrade if there...
The development of medical data and resources has become essential for enhancing patient outcomes and operational efficiency in an age when digital innovation in healthcare is becoming more important. The rapid growth of the Internet of Medical Thing...
Federated learning is a promising technique in cloud computing and edge computing environments, and designing a reasonable resource allocation scheme for federated learning is particularly important. In this paper, we propose an auction mechanism for...
The future of marine sustainability depends on public understanding and trust in the policy recommendations that emerge from scientific research. For common pool marine resource decisions made by the people who depend on these resources for their foo...
Machine learning (ML) can be a valuable tool for discovering opportunities to save energy and resources in manufacturing systems. However, the hype around ML in the context of Industry 4.0 in the past few years has led to blind usage of the approach,...
This paper studies the single-machine group scheduling problem with convex resource allocation and learning effect. The number of jobs in each group is different, and the corresponding common due dates are also different, where the processing time of...
The integrated character of the sustainable development goals in Agenda 2030, as well as research in environmental security, flag that sustainable peace requires sustainable and conflict-sensitive natural resource use. The precise relationship betwee...
Critical infrastructures (e.g., energy and transportation systems) are essential lifelines for most modern sectors and have utmost significance in our daily lives. However, these important domains can fail to operate due to system failures or natural...
Federated learning (FL) is a promising technique to provide intelligent services for the internet of things (IoT). By transmitting the model parameters instead of user data between the client and central server, FL greatly improves the user privacy a...
In the competitive landscape of online learning, developing robust and effective learning resource recommendation systems is paramount, yet the field faces challenges due to high-dimensional, sparse matrices and intricate user–resource interact...
Mobile communications have experienced exponential growth both in connectivity and multimedia traffic in recent years. To support this tremendous growth, device-to-device (D2D) communications play a significant role in 5G and beyond 5G networks. Howe...
The interest in the reengineering process of human resources and entrepreneurial learning contributes to enhancing the success of organizational revitalization, especially concerning corporate sustainability. This study builds a conceptual research f...
This article presents a transfer-learning-based method to improve the synthesized speech quality of the low-resource Dungan language. This improvement is accomplished by fine-tuning a pre-trained Mandarin acoustic model to a Dungan language acoustic...
Federated learning enables devices to train models collaboratively while protecting data privacy. However, the computing power, memory, and communication capabilities of IoT devices are limited, making it difficult to train large-scale models on thes...
The high number of devices with limited computational resources as well as limited communication resources are two characteristics of the Industrial Internet of Things (IIoT). With Industry 4.0 emerges a strong demand for data processing in the edge,...
Resource management is a key issue that needs to be addressed in the future smart Internet of Things (IoT). This paper focuses on a Federated Learning (FL)-based resource management mechanism in IoT. It incorporates blockchain technology to guarantee...
The efficient scheduling of resources within emergency departments (EDs) is crucial to minimizing patient length of stay (LoS) times and maximizing the utilization of limited resources. Reducing patient wait times can enhance the operation of emergen...
Vocational training aims to facilitate the acquisition of a series of professional skills by students, specified through a series of Learning Outcomes described in the official curricula. This requires teachers to adopt a wide variety of teaching met...
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