AIMC Topic: Computer Simulation

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Energetic analysis and experiments of earthworm-like locomotion with compliant surfaces.

Bioinspiration & biomimetics
The energy consumption of worm robots is composed of three parts: heat losses in the motors, internal friction losses of the worm device and mechanical energy locomotion requirements which we refer to as the cost of transport (COT). The COT, which is...

Multi-source adaptation joint kernel sparse representation for visual classification.

Neural networks : the official journal of the International Neural Network Society
Most of the existing domain adaptation learning (DAL) methods relies on a single source domain to learn a classifier with well-generalized performance for the target domain of interest, which may lead to the so-called negative transfer problem. To th...

Network-based in silico drug efficacy screening.

Nature communications
The increasing cost of drug development together with a significant drop in the number of new drug approvals raises the need for innovative approaches for target identification and efficacy prediction. Here, we take advantage of our increasing unders...

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.

Computational intelligence and neuroscience
Constraint satisfaction problems are of special interest for the artificial intelligence and operations research community due to their many applications. Although heuristics involved in solving these problems have largely been studied in the past, l...

Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System.

PloS one
Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system...

Machine Learning Capabilities of a Simulated Cerebellum.

IEEE transactions on neural networks and learning systems
This paper describes the learning and control capabilities of a biologically constrained bottom-up model of the mammalian cerebellum. Results are presented from six tasks: 1) eyelid conditioning; 2) pendulum balancing; 3) proportional-integral-deriva...

Learning to Produce Syllabic Speech Sounds via Reward-Modulated Neural Plasticity.

PloS one
At around 7 months of age, human infants begin to reliably produce well-formed syllables containing both consonants and vowels, a behavior called canonical babbling. Over subsequent months, the frequency of canonical babbling continues to increase. H...

Prototype-based models in machine learning.

Wiley interdisciplinary reviews. Cognitive science
An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the contex...

Using Support Vector Machine (SVM) for Classification of Selectivity of H1N1 Neuraminidase Inhibitors.

Molecular informatics
Inhibition of the neuraminidase is one of the most promising strategies for preventing influenza virus spreading. 479 neuraminidase inhibitors are collected for dataset 1 and 208 neuraminidase inhibitors for A/P/8/34 are collected for dataset 2. Usin...