AIMC Topic: Neural Networks, Computer

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Physics-informed attention-based neural network for hyperbolic partial differential equations: application to the Buckley-Leverett problem.

Scientific reports
Physics-informed neural networks (PINNs) have enabled significant improvements in modelling physical processes described by partial differential equations (PDEs) and are in principle capable of modeling a large variety of differential equations. PINN...

A 16-Channel Fully Configurable Neural SoC With 1.52 μW/Ch Signal Acquisition, 2.79 μW/Ch Real-Time Spike Classifier, and 1.79 TOPS/W Deep Neural Network Accelerator in 22 nm FDSOI.

IEEE transactions on biomedical circuits and systems
With the advent of high-density micro-electrodes arrays, developing neural probes satisfying the real-time and stringent power-efficiency requirements becomes more challenging. A smart neural probe is an essential device in future neuroscientific res...

ANNet: A Lightweight Neural Network for ECG Anomaly Detection in IoT Edge Sensors.

IEEE transactions on biomedical circuits and systems
In this paper, we propose a lightweight neural network for real-time electrocardiogram (ECG) anomaly detection and system level power reduction of wearable Internet of Things (IoT) Edge sensors. The proposed network utilizes a novel hybrid architectu...

Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance.

Computational intelligence and neuroscience
Student performance is crucial to the success of tertiary institutions. Especially, academic achievement is one of the metrics used in rating top-quality universities. Despite the large volume of educational data, accurately predicting student perfor...

Emotion Analysis Method of Teaching Evaluation Texts Based on Deep Learning in Big Data Environment.

Computational intelligence and neuroscience
Accurate emotion analysis of teaching evaluation texts can help teachers effectively improve the quality of education and teaching. In order to improve the precision and accuracy of emotion analysis, this paper proposes an emotion recognition and ana...

Neural Network-Based Beam Pumper Model Optimization.

Computational intelligence and neuroscience
Beam pumper is the earliest and most popular rod pumper driven by surface dynamic transmission devices. Drawing on modern theories and methods of industrial model design, the model optimization of beam pumper could promote the diversity, serializatio...

A Study on Cross-Media Teaching Model for College English Classroom Based on Output-Driven Hypothetical Neural Network.

Computational intelligence and neuroscience
In the field of education, the development of educational big data has become an important strategic choice to promote the construction of the digital campus and educational reform, and educational big data has become a new driving force in the field...

Research on Earnings Management of Growth Enterprise Market in China Stock Market: Comparative Analysis Based on the BPNN, GBDT, and MLR Models.

Computational intelligence and neuroscience
This study, based on 2011-2020 China's listed companies on GEM as research samples, introduces the BPNN (BP neural network) and GBDT (Gradient Boosting Decision Tree) model into the research of the relationship between internal governance and earning...

Using Convolutional Neural Networks for the Assessment Research of Mental Health.

Computational intelligence and neuroscience
Existing mental health assessment methods mainly rely on experts' experience, which has subjective bias, so convolutional neural networks are applied to mental health assessment to achieve the fusion of face, voice, and gait. Among them, the OpenPose...

ZeVigilante: Detecting Zero-Day Malware Using Machine Learning and Sandboxing Analysis Techniques.

Computational intelligence and neuroscience
For the enormous growth and the hysterical impact of undocumented malicious software, otherwise known as Zero-Day malware, specialized practices were joined to implement systems capable of detecting these kinds of software to avert possible disastrou...