Acquiring reviewers for academic submissions is a challenging recommendation scenario. Recent graph learning-driven models have made remarkable progress in the field of recommendation, but their performance in the academic reviewer recommendation task may ...

Social regulation, which is highly situated and cyclical in nature, enables students to reach a higher level of shared understanding of new concepts and co-create new knowledge. However, little empirical evidence has been examined on the effects of ...

Over the past two decades, Minimum Simplex Volume-based (MV) methods for linear hyperspectral unmixing have attracted considerable academic attention due to their robustness in the absence of pure pixels. Within this framework, certain prevalent ...

\beginabstract Segmenting an urban area into regions is fundamentally important for many spatio-temporal applications. The traditional grid-based method offers a simple solution as it divides the city map into equal-sized grids, but it fails to preserve ...

The nodes set in the current centralized regional positioning method for power supply quality are mostly independent and not connected with the data center, which eventually leads to the increasing of the absolute error of positioning and affects the ...

This study proposes a deep learning-based analytical model to conduct an in-depth study of the relationship between consumer trust, perceived benefits, and purchase intention. This model combines natural language processing and sentiment analysis, using ...

In the face of the rapid development of digital business, accurate forecasting is of significant importance. This study constructs a business forecasting model based on deep learning to improve prediction accuracy. Data from tourism platform users and ...

Emotions can significantly affect the learning effect. The affective states of students can be automatically recognized through behavioral cues using machine learning techniques. However, in the field of education, researchers mainly focus on the ...

In the context of e-learning, learners often struggle to make informed decisions about what and how to learn when they have access to a vast array of learning resources. To address this issue, several approaches have been proposed from different ...

Spiking neural P systems (SN P systems) are bio-inspired neural-like computational devices that mimic the communication between two nearby neurons and the spike changes in the neuron. This study incorporates concepts of the weight of ...

Emotions significantly affect learning. The affective states of students can be automatically recognized through behavioral cues using machine learning and deep learning techniques. The accuracy and robustness of the recognition results mainly ...

• A database of the facial expressions and hand gestures of students is compiled.
• Images are obtained from videos recorded during actual online learning.
• Images are labeled by both novice judges and researchers using academic ...

The Harris hawks optimization (HHO) algorithm is a new metaheuristic algorithm proposed in recent years. Due to the shortcomings of this algorithm in solving complex high-dimensional optimization problems with a slow convergence speed, low ...

In deep neural networks, the generalization is a vital evaluation metric. As it contributes to avoid over-fitting, Dropout plays an important role in improving the generalization of deep neural networks. Without fully utilizing the training data ...

This meta-analysis examined research on the effects of different teaching approaches on students’ computational thinking (CT) from 2010 to 2022. A total of 35 articles met inclusion criteria and were included in the final analysis with a total of 49 ...

Minimal solutions for relative rotation and translation estimation tasks have been explored in different scenarios, typically relying on the so-called co-visibility graphs. However, how to build direct rotation relationships between two frames ...

When taking images in low light conditions, images often suffer from low visibility. In addition to affecting the sensory quality of images, this poor quality may also significantly limit the performance of various computer vision systems. Many ...

The understanding of people’s inter-regional mobility behaviors, such as predicting the next activity region (AR) or uncovering the intentions for regional mobility, is of great value to public administration or business interests. While there are ...

Online healthcare services can provide unlimited and in-time medical information to users, which promotes social goods and breaks the barriers of locations. However, understanding the user intents behind the medical related queries is a challenging ...

The aim of low-light image enhancement algorithms is to improve the luminance of images. However, existing low-light image enhancement algorithms inevitably cause an enhanced image to be over- or underenhanced and cause color distortion, both of ...

Long range radio access (LoRa) is supposed to be a promising low-power wide-area network (LPWAN) technique for the massive Internet-of-Things (mIoT) applications. It can support up to six end devices (EDs) to transmit ...