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This paper presents a fully automatic registration method of dental cone-beam computed tomography (CBCT) and face scan data. Difficulties in accurately merging facial scans and CBCT images arise from the different image acquisition methods and limited area of correspondence between the two facial surfaces. In addition, it is difficult to use machine learning techniques because they use face-related 3D medical data with radiation exposure, which are difficult to obtain for training. The proposed method addresses these problems by reusing an existing machine-learning-based 2D landmark detection algorithm in an open-source library and developing a novel mathematical algorithm that identifies paired 3D landmarks from knowledge of the corresponding 2D landmarks. A main contribution of this study is that the proposed method does not require annotated training data of facial landmarks because it uses a pre-trained facial landmark detection algorithm that is known to be robust and generalized to various 2D face image models. Note that this reduces a 3D landmark detection problem to a 2D problem of identifying the corresponding landmarks on two 2D projection images generated from two different projection angles. Here, the 3D landmarks for registration were selected from the sub-surfaces with the least geometric change under the CBCT and face scan environments. For the final fine-tuning of the registration, the Iterative Closest Point method was applied, which utilizes geometrical information around the 3D landmarks. The proposed method achieved an averaged mean surface distance error of 0.74 mm for three pairs of CBCT and face scan datasets.

The laser power transfer system is one of the most promising systems in the long-range wireless power transfer field. However, the low efficiency at photovoltaic (PV) receiver limits the performance of an implemented system due to the Gaussian laser beam. Since the irradiance profile of the Gaussian laser beam is not uniform, the PV array exhibits complex output characteristics with multiple peaks, leading that the conventional maximum power point tracking (MPPT) method is not acceptable either on tracking accuracy or on tracking speed. In this article, a simple and rapid voltage-location global MPPT (VL-GMPPT) method is proposed for PV array under Gaussian laser beam condition (GLBC) in terms of reducing the voltage searching range. In order to do so, the mathematical model of PV array's global maximum power point (GMPP) is developed under GLBC. Then, the VL-GMPPT method incorporates voltage-location mechanism to directly move the operating point to the vicinity of GMPP and employs IncCond method to accurately find the GMPP. The experimental and simulation results are shown to verify the proposed GMPPT method. It was found that the proposed method can reduce 90% of tracking time that is consumed by the conventional global searching method. [ABSTRACT FROM AUTHOR]

Atmospheric water vapor plays an essential role in climate change and weather forecasting. However, monitoring water vapor with high spatial and temporal resolutions remains a challenge, especially over ocean regions where observations are insufficient. Shipborne global navigation satellite systems (GNSSs) contribute to enriching water vapor measurements over oceans and also can help validate satellite observations. Due to the lack of long-time serial observations, the performance of shipborne GNSS-derived precipitable water vapor (PWV) is inadequately evaluated on the global ocean scale. In this study, an overall assessment of shipborne GNSS PWV over global oceans is performed based on six voyages from 2014 to 2018. In coastal areas, the PWV differences of shipborne GNSS with respect to (w.r.t.) ground-based GNSS and ground-launched radiosonde data are 2.64 and 2.85 mm in the root mean square (rms), respectively. In open oceans, compared to ship-launched radiosonde profiles and satellite measurements, shipborne GNSS PWV shows the rms of differences of 2.54 and 2.53 mm, respectively. In addition, the rms of PWV differences between the whole track of shipborne GNSS PWV and National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2) products is 2.96 mm. The intertechnique validations demonstrate that the accuracy of shipborne GNSS PWV is superior to 3 mm, which meets the requirements of climate research and numerical weather prediction (NWP). [ABSTRACT FROM AUTHOR]

This article presents a low-cost circuit that generates narrow pulses with programmable waveform, amplitude, and position based on the spectrum stitching method. Specifically in this article, narrow pulses are generated through stitching the spectra of five subsignals, and the subsignals are generated by three regular arbitrary waveform generators with a bandwidth of 200 MHz. The experimental results of pulse generation with various waveforms, amplitude profiles, and position profiles are demonstrated. The pulses demonstrated in this article have a pulse width between 2 and 4 ns, with spectral coverage of about 500 MHz, which is well beyond the capacity of each of the three arbitrary waveform generators used in this work. The experimental results of this article indicate that the spectrum stitching technique has excellent potential to increase the effective bandwidth of arbitrary waveform generators using low-cost circuits. [ABSTRACT FROM AUTHOR]