MicroRNAs manifest significant functions in brain neural stem cell (NSC) self-renewal and differentiation through the post-transcriptional regulation of neurogenesis genes. Let-7b is expressed in the mammalian brain and regulates NSC proliferation and differentiation by targeting the nuclear receptor TLX, which is an essential regulator of NSC self-renewal. Whether let-7b and TLX act as importa...

Many computer vision algorithms include a robust estimation step where model parameters are computed from a data set containing a significant proportion of outliers. The RANSAC algorithm is possibly the most widely used robust estimator in the field of computer vision. In the paper we show that under a broad range of conditions, RANSAC efficiency is significantly improved if its hypothesis eval...

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which ...

For the purpose of meeting the requirement for image chromatic information storage, data processing and transmission in turbulence precise detection, this paper presents a new data optimization method of turbulence image chromatic data based on energy optimization surface construction and multi-order Random Sample Consensus (RANSAC) estimation. Though extracting turbulence image’s chromatic dat...

The Random Sample Consensus (RANSAC) algorithm is a popular tool for robust estimation problems in computer vision, primarily due to its ability to tolerate a tremendous fraction of outliers. There have been a number of recent efforts that aim to increase the efficiency of the standard RANSAC algorithm. Relatively fewer efforts, however, have been directed towards formulating RANSAC in a manner...

We propose a new method that uses an iterative closest point (ICP) algorithm to fit three‐ dimensional points to a prior geometric model for the purpose of determining the position and orientation (pose) of a sensor with respect to a model. We use a method similar to the Random Sample and Consensus (RANSAC) algorithm. However, where RANSAC uses random samples of points in the fitting trials, DI...

Scene analysis is a prior stage in many computer vision and robotics applications. Thanks to recent depth camera, we propose a fast plane segmentation approach for obstacle detection in indoor environments. The proposed method Fast RANdom Sample Consensus (FRANSAC) involves three steps: data input, data preprocessing and 3D RANSAC. Firstly, range data, obtained from 3D camera, is converted into...

Amoeba is a capability-based distributed operating system designed for high performance interactions between clients and servers using the well-known RPC model. The paper starts out by describing the architecture of the Amoeba system, which is typified by specialized components such as workstations, several services, a processor pool, and gateways that connect other Amoeba systems transparently...

In this paper the uncertainty of a robust photometer circuit (RPC) was estimated. Here, the RPC was considered as a measurement system, having input quantities that were inexactly known, and output quantities that consequently were also inexactly known. Input quantities represent information obtained from calibration certificates, specifications of manufacturers, and tabulated data. Output quan...