Three-dimensional point cloud is an efficient and flexible representation of three-dimensional structures. Recently, neural network algorithm has shown superior performance in the tasks of three-dimensional point cloud classification and segmentation. However, the good results shown in these tasks were experimentally obtained using complete and aligned 3D point cloud data, whereas real-world 3D point cloud data is missing and unaligned. The key to the difficulty of learning non- aligned point cloud data is how to obtain invariance of geometric transformation. To solve this problem, we propose a new spatial transformation network named residual space transformation network to process point cloud data. Different from the existing spatial transformation networks, the network is inspired by traditional image and point cloud alignment algorithms and residual learning, and predicts the three-dimensional space transformation through a multi-step estimation method. The experiment shows that compared with the baseline, the network performs better in the classification and attitude prediction of missing point cloud data.

Objective: The aim of our study was to explore the impact of maternal vasodilatationon on peripheral arterial tonometry used for assessing the endothelial function as physiological adaptation to pregnancy progress. Methods: Thirty-one healthy pregnant women of gestational weeks from 13 to 34 were tested using sphygmomanometer, peripheral arterial tonometry and photoplethysmographic assessment. Blood pressure, heart rate, reactive hyperemia index, augmentation index and reflection index were obtained in resting conditions. Data was analyzed in two groups divided as 2ndand 3rdtrimester and further divided into three groups of early 2ndtrimester, late 2ndtrimester and 3rdtrimester. Results: A rise of reactive hyperemia index of peripheral arterial tonometry from early 2ndto late 2ndtrimester and then a fall to 3rdtrimester had been found in association with continuous decrease of augmentation index derived either from peripheral arterial tonometry or photoplethysmography as well as reflection index from photoplethysmography and continuous increase of heart rate, during which blood pressure remained almost unchanged. A moderate level of correlation was observed between augmentation index derived from peripheral arterial tonometry and photoplethysmography. Conclusions: The reactive hyperemia index of peripheral arterial tonometry method is vasodilation dependent and likely to be less reliable in testing of endothelial function when more vasodilated.

The drones formation control in 5G wireless sensor network is discussed. The base station (BS) is used to receive backhaul position signals from the lead drone in formation and launches the beam to the lead one as the fronthaul flying signal enhancement. It is a promising approach to raise the formation strength of drones during flight control. The BS can transform the direction of the antennas and transmit energy to the lead drone that could widely enlarge the number of the receivers and increase the transmission speed of the data links. The millimeter‐Wave (mmWave) communication system offers new opportunities to meet this requirement owing to the tremendous amount of available spectrums. However, the massive non‐line‐of‐sight (NLoS) transmission and the site constraints in urban environment are severely challenging the conventional deploying terrestrial low power nodes (LPNs). Simulation experiments have been performed to verify the availability and effectiveness of mmWave in 5G wireless sensor network.

This paper develops a multi-dimensional geometric features extraction method for monocular Simultaneous Localization and Mapping(SLAM), in order to meet the self-navigation need for light- weighted robots, e.g. small drones. The monocular SLAM mapping based on feature points method is vulnerable to noisy samples, and thus must be enhanced for better efficiency in complex environments. Our proposed method introduces the line and plane features to the three-dimensional map building process, so as to improve the speed of monocular SLAM applications system's key frames matching and overall stability. In particular, we develop a rapid line matching algorithm, where three-dimensional lines were drawn by two- dimensional lines matching. Numerical results show that our approach can significantly reduce redundant information in the SLAM applications.