Early-fusion based pulsar identification with smart under-sampling

Sensor Fusion-Based Middleware for Smart Homes

Smart homes are sensor-rich environments that contain dynamic sets of interacting components. These components often use competing and closed standards and form a message-based architecture. This complicates the development of applications that require information from disparate sources. It becomes difficult to add new components or to allow components from different applications to interact wi...

Pulsar Candidate Identification with Artificial Intelligence Techniques

Discovering pulsars is a significant and meaningful research topic in the field of radio astronomy. With the advent of astronomical instruments such as he Five-hundredmeter Aperture Spherical Telescope (FAST) in China, data volumes and data rates are exponentially growing. This fact necessitates a focus on artificial intelligence (AI) technologies that can perform the automatic pulsar candidate...

Multi-feature Fusion Face Recognition Based on Kernel Discriminate Local Preserve Projection Algorithm under Smart Environment

In this paper, a new face recognition method based on kernel discriminate local preserve projection(KDLPP) and Multi-feature fusion under smart environment is proposed . In order to solve the small sample size problem, combined with kernel theory and QR decomposition, a new face recognition algorithm named kernel discriminate local preserve projection is proposed based on discriminate local pre...

Smart Sampling without Reinforcement

We conducted an experiment to compare the effect of natural frequencies and active, trial-by-trial sampling on participants’ estimation of proportions in a population. The two information formats evoked similar degrees of accuracy, sensitivity to subtle statistical properties of the environment, and sensitivity to the estimates’ accuracy. However, in some situations participants who didn’t have...

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