Understanding students’ educational emotion is important for learning process, however, it is challenging to detect in an online learning environment. Deep learning architectures show excellent performance for emotion detection from facial ...

While network attacks play a critical role in many advanced persistent threat (APT) campaigns, an arms race exists between the network defenders and the adversary: to make APT campaigns stealthy, the adversary is strongly motivated to evade the detection ...

Low-light images have low contrast and unclear details, resulting in the reduction of available information for human vision. The current mainstream enhancement algorithms have problems such as noise amplification, color distortion, and dependence on ...

Many colleges in China have adopted the policy of recruiting students by academic subject categories in order to optimize the talent training mode. To solve the problems in major selection after enrollment, this paper has designed an intelligent ...

Fall detection is an emerging topic for health care and smart surveillance. Non-intrusive radar-based fall detection is a challenging but promising problem. Compared with ideal fall samples in the training set, the fall events in practical situations ...

Many real-world datasets suffer from the unavoidable issue of missing values, and therefore classification with missing data has to be carefully handled since inadequate treatment of missing values will cause large errors. In this paper, we ...

In computational fluid dynamics, the Boussinesq approximation is a popular model for the numerical simulation of natural convection problems. Although using the Boussinesq approximation leads to significant performance gains over a full-fledged ...

Object detection based on artificial intelligence is ubiquitous in today’s computer vision research and application. The training of the neural networks for object detection requires large and high-quality datasets. Besides datasets based on image ...

Modern consumer electronic devices have started executing deep learning-based intelligence services on devices, not cloud servers, to keep personal data on devices and to reduce network and cloud costs. We find such a trend as the opportunity to ...

This paper innovatively integrates preset performance control technology with adaptive neural network control targeting a dual-arm robot system with nonlinear uncertainties, developing a strategy demonstrating exceptional control performance under ...

A mathematical model of the problem of calculating the weight coefficients of a binary neural network is presented. It is proved that in the case of step functions of neuron activation, this model is a system of linear inequalities, which is ...

Context: The proliferation of technologies based on Large Language Models (LLM) is reshaping various domains, also impacting on programming code creation and review. Problem: The decision-making process in adopting LLM in software development demands an ...

In the field of software engineering, effectively managing software systems is essential. A key aspect of this management is the issue-commit link, which connects reported problems or enhancement requests (issues) with the actual code changes implemented ...

Adaptive output feedback control based on output feedback exponential passivity (OFEP) has a simple structure and strong robustness in regard to disturbances and system uncertainties. However, it is difficult for most nonlinear systems to ...

Osteoporosis is a medical disorder that causes bone tissue to deteriorate and lose density, increasing the risk of fractures. Applying Neural Networks (NN) to analyze medical imaging data and detect the presence or severity of osteoporosis ...

We introduce On-NAS, a memory-efficient on-device neural architecture search (NAS) solution, that enables memory-constrained embedded devices to find the best deep model architecture and train it on the device. Based on the cell-based differentiable NAS, ...

Current neural network approaches mostly consider the synaptic signal transfer as a basis of interneuronal communication. At the same time, extrasynaptic signaling plays important role in the animal behavior. In the paper processes of information ...

Purpose of I&C (instrumentation and control) system is monitor and control of processing procedure and equipment for reaching main goal of nuclear power plant (NPP) – electric energy generation providing nuclear and radiological safety and ...

Fuzzy testing is one of the most popular vulnerability mining techniques recently, it plays a huge role in exploiting software security vulnerabilities and improving software security. Fuzzy testing mainly performs specific variations on the collected ...

Applying services computing to neural networks, a service provider may provide inference with a pre-trained neural network as a service. Clients use the service to get the neural network's output on their input. To protect sensitive data, secure neural ...