A Lite Fireworks Algorithm with Fractal Dimension Constraint for Feature Selection

As the use of robotics becomes more widespread, the huge amount of vision data leads to a dramatic increase in data dimensionality. Although deep learning methods can effectively process these high-dimensional vision data. Due to the limitation of computational resources, some special scenarios still rely on traditional machine learning methods. However, these high-dimensional visual data lead to great challenges for traditional machine learning methods. Therefore, we propose a Lite Fireworks Algorithm with Fractal Dimension constraint for feature selection (LFWA+FD) and use it to solve the feature selection problem driven by robot vision. The "LFWA+FD" focuses on searching the ideal feature subset by simplifying the fireworks algorithm and constraining the dimensionality of selected features by fractal dimensionality, which in turn reduces the approximate features and reduces the noise in the original data to improve the accuracy of the model. The comparative experimental results of two publicly available datasets from UCI show that the proposed method can effectively select a subset of features useful for model inference and remove a large amount of noise noise present in the original data to improve the performance.Comment: International Conference on Pharmaceutical Sciences 202

MicroRNAs, an active and versatile group in cancers

microRNAs (miRNAs) are a class of non-coding RNAs that function as endogenous triggers of the RNA interference pathway. Studies have shown that thousands of human protein-coding genes are regulated by miRNAs, indicating that miRNAs are master regulators of many important biological processes, such as cancer development. miRNAs frequently have deregulated expression in many types of human cancers, and play critical roles in tumorigenesis, which functions either as tumor suppressors or as oncogenes. Recent studies have shown that miRNAs are highly related with cancer progression, including initiating, growth, apoptosis, invasion, and metastasis. Furthermore, miRNAs are shown to be responsible for the cancer-related inflammation, anti-cancer drug resistance, and regulation of cancer stem cells. Therefore, miRNAs have generated great interest as a novel strategy in cancer diagnosis and therapy. Here we review the versatile roles of miRNAs in cancers and their potential applications for diagnosis, prognosis, and treatment as biomarkers

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