BACKGROUND: Pairwise relationships extracted from biomedical literature are insufficient in formulating biomolecular interactions. Extraction of complex relations (namely, biomedical events) has become the main focus of the text-mining community. How...
Among the many related issues of diabetes management, its complications constitute the main part of the heavy burden of this disease. The aim of this paper is to develop a risk advisor model to predict the chances of diabetes complications according ...
Computational intelligence and neuroscience
Apr 19, 2015
This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO) system (TRMS) considering most promising evolutionary techniques. These are gravitational search algorithm (GSA), particle swarm opti...
Computational intelligence and neuroscience
Apr 19, 2015
Most Active Contour Models (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods hav...
Gene selection plays a crucial role in constructing efficient classifiers for microarray data classification, since microarray data is characterized by high dimensionality and small sample sizes and contains irrelevant and redundant genes. In practic...
Physical review. E, Statistical, nonlinear, and soft matter physics
Apr 17, 2015
Recently, there has been much progress in creating microswimmers or microrobots capable of controlled propulsion in fluidic environments. These microswimmers have numerous possible applications in biomedicine, microfabrication, and sensing. One type ...
This paper studies an adaptive neural control for nonlinear multiple-input multiple-output systems in interconnected form. The studied systems are composed of N subsystems in pure feedback structure and the interconnection terms are contained in ever...
Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashio...
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...
In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market tech...
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