AIMC Topic: Computer Simulation

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A general proof of consistency of heuristic classification for cognitive diagnosis models.

The British journal of mathematical and statistical psychology
The Asymptotic Classification Theory of Cognitive Diagnosis (Chiu et al., 2009, Psychometrika, 74, 633-665) determined the conditions that cognitive diagnosis models must satisfy so that the correct assignment of examinees to proficiency classes is g...

The potential of AOP networks for reproductive and developmental toxicity assay development.

Reproductive toxicology (Elmsford, N.Y.)
Historically, the prediction of reproductive and developmental toxicity has largely relied on the use of animals. The adverse outcome pathway (AOP) framework forms a basis for the development of new non-animal test methods. It also provides biologica...

A priori data-driven multi-clustered reservoir generation algorithm for echo state network.

PloS one
Echo state networks (ESNs) with multi-clustered reservoir topology perform better in reservoir computing and robustness than those with random reservoir topology. However, these ESNs have a complex reservoir topology, which leads to difficulties in r...

In silico prediction of anti-malarial hit molecules based on machine learning methods.

International journal of computational biology and drug design
Machine learning techniques have been widely used in drug discovery and development in the areas of cheminformatics. Aspartyl aminopeptidase (M18AAP) of Plasmodium falciparum is crucial for survival of malaria parasite. We have created predictive mod...

Learning Receptive Fields and Quality Lookups for Blind Quality Assessment of Stereoscopic Images.

IEEE transactions on cybernetics
Blind quality assessment of 3D images encounters more new challenges than its 2D counterparts. In this paper, we propose a blind quality assessment for stereoscopic images by learning the characteristics of receptive fields (RFs) from perspective of ...

Measuring predictability of autonomous network transitions into bursting dynamics.

PloS one
Understanding spontaneous transitions between dynamical modes in a network is of significant importance. These transitions may separate pathological and normal functions of the brain. In this paper, we develop a set of measures that, based on spatio-...

Semantic network mapping of religious material: testing multi-agent computer models of social theories against real-world data.

Cognitive processing
Agent-based modeling allows researchers to investigate theories of complex social phenomena and subsequently use the model to generate new hypotheses that can then be compared to real-world data. However, computer modeling has been underutilized in r...

Mean square delay dependent-probability-distribution stability analysis of neutral type stochastic neural networks.

ISA transactions
The aim of this manuscript is to investigate the mean square delay dependent-probability-distribution stability analysis of neutral type stochastic neural networks with time-delays. The time-delays are assumed to be interval time-varying and randomly...

Accurate in silico identification of protein succinylation sites using an iterative semi-supervised learning technique.

Journal of theoretical biology
As a widespread type of protein post-translational modifications (PTMs), succinylation plays an important role in regulating protein conformation, function and physicochemical properties. Compared with the labor-intensive and time-consuming experimen...

Screening Internet forum participants for depression symptoms by assembling and enhancing multiple NLP methods.

Computer methods and programs in biomedicine
Depression is a disease that can dramatically lower quality of life. Symptoms of depression can range from temporary sadness to suicide. Embarrassment, shyness, and the stigma of depression are some of the factors preventing people from getting help ...