AIMC Topic: Algorithms

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Consensus analysis of networks with time-varying topology and event-triggered diffusions.

Neural networks : the official journal of the International Neural Network Society
This paper studies the consensus problem of networks with time-varying topology. Event-triggered rules are employed in diffusion coupling terms to reduce the updating load of the coupled system. Two strategies are considered: event-triggered strategy...

Machine learning classification of medication adherence in patients with movement disorders using non-wearable sensors.

Computers in biology and medicine
Medication non-adherence is a major concern in the healthcare industry and has led to increases in health risks and medical costs. For many neurological diseases, adherence to medication regimens can be assessed by observing movement patterns. Howeve...

Multiple Representations-Based Face Sketch-Photo Synthesis.

IEEE transactions on neural networks and learning systems
Face sketch-photo synthesis plays an important role in law enforcement and digital entertainment. Most of the existing methods only use pixel intensities as the feature. Since face images can be described using features from multiple aspects, this pa...

Extracting Biomedical Event with Dual Decomposition Integrating Word Embeddings.

IEEE/ACM transactions on computational biology and bioinformatics
Extracting biomedical event from literatures has attracted much attention recently. By now, most of the state-of-the-art systems have been based on pipelines which suffer from cascading errors, and the words encoded by one-hot are unable to represent...

Prediction of telephone calls load using Echo State Network with exogenous variables.

Neural networks : the official journal of the International Neural Network Society
We approach the problem of forecasting the load of incoming calls in a cell of a mobile network using Echo State Networks. With respect to previous approaches to the problem, we consider the inclusion of additional telephone records regarding the act...

An Effective Antifreeze Protein Predictor with Ensemble Classifiers and Comprehensive Sequence Descriptors.

International journal of molecular sciences
Antifreeze proteins (AFPs) play a pivotal role in the antifreeze effect of overwintering organisms. They have a wide range of applications in numerous fields, such as improving the production of crops and the quality of frozen foods. Accurate identif...

Hadoop neural network for parallel and distributed feature selection.

Neural networks : the official journal of the International Neural Network Society
In this paper, we introduce a theoretical basis for a Hadoop-based neural network for parallel and distributed feature selection in Big Data sets. It is underpinned by an associative memory (binary) neural network which is highly amenable to parallel...

APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction.

Computational biology and chemistry
Tertiary protein structure prediction is one of the most challenging problems in structural bioinformatics. Despite the advances in algorithm development and computational strategies, predicting the folded structure of a protein only from its amino a...

A similarity-based data warehousing environment for medical images.

Computers in biology and medicine
A core issue of the decision-making process in the medical field is to support the execution of analytical (OLAP) similarity queries over images in data warehousing environments. In this paper, we focus on this issue. We propose imageDWE, a non-conve...

Multi-Objective Particle Swarm Optimization Approach for Cost-Based Feature Selection in Classification.

IEEE/ACM transactions on computational biology and bioinformatics
Feature selection is an important data-preprocessing technique in classification problems such as bioinformatics and signal processing. Generally, there are some situations where a user is interested in not only maximizing the classification performa...