AIMC Topic: Computer Simulation

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Synchrony measure for a neuron driven by excitatory and inhibitory inputs and its adaptation to experimentally-recorded data.

Bio Systems Sep 15, 2017
The aim of the current work is twofold: firstly to adapt an existing method measuring the input synchrony of a neuron driven only by excitatory inputs in such a way so as to account for inhibitory inputs as well and secondly to further appropriately ...
Guinea Pigs Neurons Auditory Cortex Neural Inhibition Neural Networks, Computer Models, Neurological Action Potentials Computer Simulation Animals
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Global exponential stability of nonautonomous neural network models with unbounded delays.

Neural networks : the official journal of the International Neural Network Society Sep 14, 2017
For a nonautonomous class of n-dimensional differential system with infinite delays, we give sufficient conditions for its global exponential stability, without showing the existence of an equilibrium point, or a periodic solution, or an almost perio...
Neural Networks, Computer Computer Simulation Time Factors
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The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem.

Computational intelligence and neuroscience Sep 14, 2017
A two-stage artificial neural network (ANN) based on scalarization method is proposed for bilevel biobjective programming problem (BLBOP). The induced set of the BLBOP is firstly expressed as the set of minimal solutions of a biobjective optimization...
Programming, Linear Computer Simulation Humans Neural Networks, Computer Decision Making Problem Solving Algorithms
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Synaptic convergence regulates synchronization-dependent spike transfer in feedforward neural networks.

Journal of computational neuroscience Sep 12, 2017
Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of ...
Nerve Net Normal Distribution Synaptic Transmission Computer Simulation Animals Models, Neurological Action Potentials Neurons Synapses Humans Neural Networks, Computer
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Nonlinear Semi-Supervised Metric Learning Via Multiple Kernels and Local Topology.

International journal of neural systems Sep 11, 2017
Changing the metric on the data may change the data distribution, hence a good distance metric can promote the performance of learning algorithm. In this paper, we address the semi-supervised distance metric learning (ML) problem to obtain the best n...
Nonlinear Dynamics Pattern Recognition, Automated Computer Simulation Cluster Analysis Supervised Machine Learning Humans Artificial Intelligence Algorithms
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New Dandelion Algorithm Optimizes Extreme Learning Machine for Biomedical Classification Problems.

Computational intelligence and neuroscience Sep 11, 2017
Inspired by the behavior of dandelion sowing, a new novel swarm intelligence algorithm, namely, dandelion algorithm (DA), is proposed for global optimization of complex functions in this paper. In DA, the dandelion population will be divided into two...
Heart Diseases Humans Tomography, Emission-Computed, Single-Photon Taraxacum Neural Networks, Computer Blood Transfusion Machine Learning Visual Perception Electroencephalography Brain Heart Computer Simulation
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Computer-assisted cytologic diagnosis in pancreatic FNA: An application of neural networks to image analysis.

Cancer cytopathology Sep 8, 2017
BACKGROUND: Fine-needle aspiration (FNA) biopsy is an accurate method for the diagnosis of solid pancreatic masses. However, a significant number of cases still pose a diagnostic challenge. The authors have attempted to design a computer model to aid...
Humans Neural Networks, Computer Computer Simulation Adenocarcinoma Diagnosis, Differential Pancreatic Neoplasms Cytodiagnosis Reproducibility of Results Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Biopsy, Fine-Needle Pancreatectomy Carcinoma, Pancreatic Ductal Bile Duct Neoplasms Pancreas
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Reconstructing cell cycle and disease progression using deep learning.

Nature communications Sep 6, 2017
We show that deep convolutional neural networks combined with nonlinear dimension reduction enable reconstructing biological processes based on raw image data. We demonstrate this by reconstructing the cell cycle of Jurkat cells and disease progressi...
Cell Cycle Mitosis Cell Division DNA Flow Cytometry Jurkat Cells Diabetic Retinopathy Neural Networks, Computer Machine Learning Computer Simulation Humans Reproducibility of Results Disease Progression
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Machine Learning Using Combined Structural and Chemical Descriptors for Prediction of Methane Adsorption Performance of Metal Organic Frameworks (MOFs).

ACS combinatorial science Sep 5, 2017
Using molecular simulation for adsorbent screening is computationally expensive and thus prohibitive to materials discovery. Machine learning (ML) algorithms trained on fundamental material properties can potentially provide quick and accurate method...
Computer Simulation Machine Learning Metals Adsorption Software Organometallic Compounds Algorithms
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Machine learning techniques for the optimization of joint replacements: Application to a short-stem hip implant.

PloS one Sep 5, 2017
Today, different implant designs exist in the market; however, there is not a clear understanding of which are the best implant design parameters to achieve mechanical optimal conditions. Therefore, the aim of this project was to investigate if the g...
Hip Prosthesis Weight-Bearing Arthroplasty, Replacement Arthroplasty, Replacement, Hip Femur Software Finite Element Analysis Algorithms Computer Simulation Humans Decision Making Imaging, Three-Dimensional Machine Learning Prosthesis Design Stress, Mechanical
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