AIMC Topic: Algorithms

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Sensor Fault Diagnosis Method Based on -Grey Wolf Optimization-Support Vector Machine.

Computational intelligence and neuroscience
Aimed to address the low diagnostic accuracy caused by the similar data distribution of sensor partial faults, a sensor fault diagnosis method is proposed on the basis of Grey Wolf Optimization Support Vector Machine (-GWO-SVM) in this paper. Firstl...

Relation classification via BERT with piecewise convolution and focal loss.

PloS one
Recent relation extraction models' architecture are evolved from the shallow neural networks to natural language model, such as convolutional neural networks or recurrent neural networks to Bert. However, these methods did not consider the semantic i...

Predicting drug sensitivity of cancer cells based on DNA methylation levels.

PloS one
Cancer cell lines, which are cell cultures derived from tumor samples, represent one of the least expensive and most studied preclinical models for drug development. Accurately predicting drug responses for a given cell line based on molecular featur...

Exploring the Predictability of Temperatures in a Scaled Model of a Smarthome.

Sensors (Basel, Switzerland)
In modern smarthomes, temperature regulation is achieved through a mix of traditional and emergent technologies including air conditioning, heating, intelligent utilization of the effects of sun, wind, and shade as well as using stored heat and cold....

A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning.

Sensors (Basel, Switzerland)
Recent advances in Internet of Things (IoT) technologies and the reduction in the cost of sensors have encouraged the development of smart environments, such as smart homes. Smart homes can offer home assistance services to improve the quality of lif...

Pinning multisynchronization of delayed fractional-order memristor-based neural networks with nonlinear coupling and almost-periodic perturbations.

Neural networks : the official journal of the International Neural Network Society
This paper concerns the multisynchronization issue for delayed fractional-order memristor-based neural networks with nonlinear coupling and almost-periodic perturbations. First, the coexistence of multiple equilibrium states for isolated subnetwork i...

Nonlinear tensor train format for deep neural network compression.

Neural networks : the official journal of the International Neural Network Society
Deep neural network (DNN) compression has become a hot topic in the research of deep learning since the scale of modern DNNs turns into too huge to implement on practical resource constrained platforms such as embedded devices. Among variant compress...

Waste image classification based on transfer learning and convolutional neural network.

Waste management (New York, N.Y.)
The rapid economic and social development has led to a rapid increase in the output of domestic waste. How to realize waste classification through intelligent methods has become a key factor for human beings to achieve sustainable development. Tradit...

A meta-analysis on the effectiveness of anthropomorphism in human-robot interaction.

Science robotics
The application of anthropomorphic design features is widely assumed to facilitate human-robot interaction (HRI). However, a considerable number of study results point in the opposite direction. There is currently no comprehensive common ground on th...

Research on RNA secondary structure predicting via bidirectional recurrent neural network.

BMC bioinformatics
BACKGROUND: RNA secondary structure prediction is an important research content in the field of biological information. Predicting RNA secondary structure with pseudoknots has been proved to be an NP-hard problem. Traditional machine learning methods...