Research on Wind Field Characteristics Measured by Lidar in a U-Shaped Valley at a Bridge Site

Currently, research on wind fields of U-shaped valleys is rarely reported, and anemometers or wind observation towers are usually used for field measurement, but the measured position is limited and the cost is high. In order to study the wind characteristics in a mountainous U-shaped valley, a long-range, all-weather, high-precision Wind3D 6000 lidar was placed at a bridge site located in a U-shaped valley. Then, according to the data effective ratio and wind speed, nearly 6 months of original data ranging from 0 m to 810 m were analyzed statistically. It was found that the spatio-temporal distribution of wind speed and direction is obviously not uniform, and the wind parameters are correlated among different virtual wind towers (VWTs). By classification, the effective data of midspan position is taken as the research object, and the wind speed profile is divided into three categories. Type-1 shows disorderly characteristics; Type-2 shows a linear relationship; and Type-3 shows a nonlinear relationship. The wind direction is consistent with the main wind direction at the bridge site and the average wind direction of different VWTs has a high consistency. The concept of wind-direction deflection rate is put forward to describe the variation of wind direction with height. These measured wind parameters could be used as a reference for bridge wind-resistant design.

Fruit maturity and location identification of beef tomato using R-CNN and binocular imaging technology

The objective of this study was to identify the maturity and position of tomatoes in greenhouse. Three parts have been included in this study: building the model of image capturing and object detection, position identification of mature fruits and prediction of the size of the mature fruits. For the first part, image capturing in different time and object detection will be conducted in the greenhouse for identification of mature fruits. For the second part, the relative 3D position of the mature fruits calculated by the binocular vision was compared with the actual measured position. For the third part, the size of the bounding box from the object detection was compared with the actual size of the mature fruit, and the correlation was calculated in order to pre-adjust the width of the gripper for plucking operation in the future. The precision and the recall of the mature fruits of this study are over 95%. The average error of the 3D position is 0.5 cm. The actual size of the fruits and the R-squared of the size of the bounding box are over 0.9.

Moving People Tracking and False Track Removing with Infrared Thermal Imaging by a Multirotor

Infrared (IR) thermal imaging can detect the warm temperature of the human body regardless of the light conditions, thus small drones equipped with the IR thermal camera can be utilized to recognize human activity for smart surveillance, road safety, and search and rescue missions. However, the unpredictable motion of the drone poses more challenges than a fixed camera. This paper addresses the detection and tracking of people through IR thermal video captured by a multirotor. For object detection, each frame is first registered with a reference frame to compensate for its coordinates. Then, the objects in each frame are segmented through k-means clustering and morphological operations. Falsely detected objects are removed considering the actual size and the shape of the object. The centroid of the segmented area is considered the measured position for target tracking. The track is initialized with two-point differencing initialization, and the target states are continuously estimated by the interacting multiple model (IMM) filter. The nearest neighbor association rule assigns the measurement to the track. Tracks that move slower than the minimum speed are terminated at the proposed criteria. In the experiments, three videos were captured with a long-wave IR band thermal imaging camera mounted on a multirotor. In the first and second videos, eight pedestrians on a pavement and three hikers on a mountain on winter nights were captured, respectively. In the third video, two walking people with complex backgrounds were captured on a windy summer day. The image characteristics vary between videos depending on the climate and surrounding objects, but the proposed scheme shows the robust performance in all cases; the average root mean squared errors in position and velocity are obtained as 0.08 m and 0.53 m/s, respectively for the first video, 0.06 m and 0.58 m/s, respectively for the second video, and 0.18 m and 1.84 m/s, respectively for the third video. The proposed method reduces false tracks from 10 to 1 in the third video.

Gesture Recognition of Sign Language Alphabet Using a Magnetic Positioning System

Hand gesture recognition is a crucial task for the automated translation of sign language, which enables communication for the deaf. This work proposes the usage of a magnetic positioning system for recognizing the static gestures associated with the sign language alphabet. In particular, a magnetic positioning system, which is comprised of several wearable transmitting nodes, measures the 3D position and orientation of the fingers within an operating volume of about 30 × 30 × 30 cm, where receiving nodes are placed at known positions. Measured position data are then processed by a machine learning classification algorithm. The proposed system and classification method are validated by experimental tests. Results show that the proposed approach has good generalization properties and provides a classification accuracy of approximately 97% on 24 alphabet letters. Thus, the feasibility of the proposed gesture recognition system for the task of automated translation of the sign language alphabet for fingerspelling is proven.

Geoeffectiveness Prediction of CMEs

Coronal mass ejections (CMEs), the most important pieces of the puzzle that drive space weather, are continuously studied for their geomagnetic impact. We present here an update of a logistic regression method model, that attempts to forecast if a CME will arrive at the Earth and it will be associated with a geomagnetic storm defined by a minimum Dst value smaller than −30 nT. The model is run for a selection of CMEs listed in the LASCO catalogue during the solar cycle 24. It is trained on three fourths of these events and validated for the remaining one fourth. Based on five CME properties (the speed at 20 solar radii, the angular width, the acceleration, the measured position angle and the source position – binary variable) the model successfully predicted 98% of the events from the training set, and 98% of the events from the validation one.

Obstruction-Aware Signal-Loss-Tolerant Indoor Positioning Using Bluetooth Low Energy

Indoor positioning is getting increased attention due to the availability of larger and more sophisticated indoor environments. Wireless technologies like Bluetooth Low Energy (BLE) may provide inexpensive solutions. In this paper, we propose obstruction-aware signal-loss-tolerant indoor positioning (OASLTIP), a cost-effective BLE-based indoor positioning algorithm. OASLTIP uses a combination of techniques together to provide optimum tracking performance by taking into account the obstructions in the environment, and also, it can handle a loss of signal. We use running average filtering to smooth the received signal data, multilateration to find the measured position of the tag, and particle filtering to track the tag for better performance. We also propose an optional receiver placement method and provide the option to use fingerprinting together with OASLTIP. Moreover, we give insights about BLE signal strengths in different conditions to help with understanding the effects of some environmental conditions on BLE signals. We performed extensive experiments for evaluation of the OASLTool we developed. Additionally, we evaluated the performance of the system both in a simulated environment and in real-world conditions. In a highly crowded and occluded office environment, our system achieved 2.29 m average error, with three receivers. When simulated in OASLTool, the same setup yielded an error of 2.58 m.

Measuring and characterizing the line profile of HARPS with a laser frequency comb

Aims. We study the 2D spectral line profile of the High Accuracy Radial Velocity Planet Searcher (HARPS), measuring its variation with position across the detector and with changing line intensity. The characterization of the line profile and its variations are important for achieving the precision of the wavelength scales of 10−10 or 3.0 cm s−1 necessary to detect Earth-twins in the habitable zone around solar-like stars. Methods. We used a laser frequency comb (LFC) with unresolved and unblended lines to probe the instrument line profile. We injected the LFC light – attenuated by various neutral density filters – into both the object and the reference fibres of HARPS, and we studied the variations of the line profiles with the line intensities. We applied moment analysis to measure the line positions, widths, and skewness as well as to characterize the line profile distortions induced by the spectrograph and detectors. Based on this, we established a model to correct for point spread function distortions by tracking the beam profiles in both fibres. Results. We demonstrate that the line profile varies with the position on the detector and as a function of line intensities. This is consistent with a charge transfer inefficiency effect on the HARPS detector. The estimate of the line position depends critically on the line profile, and therefore a change in the line amplitude effectively changes the measured position of the lines, affecting the stability of the wavelength scale of the instrument. We deduce and apply the correcting functions to re-calibrate and mitigate this effect, reducing it to a level consistent with photon noise.

Reliability Monitoring of Laser Scanner Based Navigation

Autonomous guided vehicles have great advantages over rigidly track-guided conveyor technology, as they can react flexibly to changes in the application area. Temporary obstacles can be easily avoided. The vehicles can circumnavigate bottlenecks and areas at risk of congestion switch to alternative routes. To avoid accidents, safety-relevant position detection is necessary in many areas. The current speed is derived from this driven trajectory and this is safely reduced in the working areas. Minimum distances can also be safely maintained. Therefore it is necessary to permanently control the measured position with regard to disturbance variables and to monitor the reliability of the position detection in real time.

Quantifying asymmetry of anterior cerebral arteries as a predictor of anterior communicating artery complex aneurysm

ObjectivesThe aim of this study was to establish an anatomical index for early prediction of the risk of development of aneurysms in anterior communicating arterial complex (AcomAC). The asymmetric diameter of one anterior cerebral artery (ACA) to other could alter haemodynamics and may contribute to formation of aneurysms in AcomAC and be a reliable predictor of the risk of development of aneurysms.Design and settingThis is a retrospective, observational and quantitative study, which used cerebral computed tomography angiography (CCTA) scans in South Australia.ParticipantsCCTA scans of 166 adult patients of both sexes were studied.Main outcome measuresThe internal diameters of the proximal segments of ACAs (A1s) were measured. Position and presence or absence of aneurysms in AcomAC were determined. The ratio of A1 diameters was taken as a measure of A1 asymmetry.ResultsThe ratio of diameters of A1s correlated with the occurrence of AcomAC aneurysms. The risk of development of aneurysms in AcomAC was much greater (80%, OR=47.3) when one A1 segment’s radius was at least 50% larger (ie, 2.25 times cross-sectional area) than the other.ConclusionThe general information on asymmetric A1 has been published previously. The present findings have significant contribution since the A1s asymmetry ratios have been categorised in ascending order and matched with the presence of AcomAC aneurysms. The asymmetry ratio of the A1 is a good predictor for the development of AcomAC aneurysms. Reconstruction of the asymmetric A1 could be done if the technology gets advanced.

Engineering and prototyping of ESS neutron beam extraction system

In the development of the European Spallation Source, the engineering phase of the Neutron Beam Extraction System is approaching its end. Currently, prototyping is ongoing to verify and increase the understanding of the manufacturing limitations in relation to the engineering aspects and beam extraction requirements from the instruments. After that the manufacturing of the suite of 16 neutron beam port inserts (NBPI) and light shutter systems (LSS) are phased into final detail design and manufacturing. The NBPIs have been developed as a close collaboration between ESS’ instruments design coordinators and intricately integrate a set of copper optics within a controlled atmosphere within the target monolith pressure vessel. The NBPIs therefore includes not only a processed atmosphere but also enables fine alignment of the optics assemblies within it, but also includes a system for inserting it into a very precisely aligned and measured position. Outside the NBPIs, along the neutron beam paths, sits the Neutron Beam Windows and sequentially, the LSS which incorporates an optical bridge beam guide before the beam enters the bunker area and the individual instrument beam transports. ESS have chosen the concept of LSS, which generates demanding requirements for alignment of moving shutter parts. These system parts are placed in the bunker area and bunker basement, areas that are partly accessible during maintenance periods.