Added Benefit of the BDS III B2a Signal for Precise GNSS Positioning with Automotive Grade Receivers

2021 ◽  
Author(s):  
Stefan Junker ◽  
Nataliya Mishukova ◽  
Victor Gomez ◽  
Aeson Copeland ◽  
Michael Reupold ◽  
...  
Keyword(s):  
Gnss Positioning ◽  
Added Benefit

scholarly journals Occluded Grape Cluster Detection and Vine Canopy Visualisation Using an Ultrasonic Phased Array

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2182
Author(s):  
Baden Parr ◽  
Mathew Legg ◽  
Stuart Bradley ◽  
Fakhrul Alam
Keyword(s):  
Near Field ◽  
Low Frequency ◽  
Volume Estimation ◽  
Yield Estimation ◽  
3D Scan ◽  
Management Processes ◽  
Canopy Volume ◽  
Ultrasonic Phased Array ◽  
Added Benefit ◽  
Grape Yield

Grape yield estimation has traditionally been performed using manual techniques. However, these tend to be labour intensive and can be inaccurate. Computer vision techniques have therefore been developed for automated grape yield estimation. However, errors occur when grapes are occluded by leaves, other bunches, etc. Synthetic aperture radar has been investigated to allow imaging through leaves to detect occluded grapes. However, such equipment can be expensive. This paper investigates the potential for using ultrasound to image through leaves and identify occluded grapes. A highly directional low frequency ultrasonic array composed of ultrasonic air-coupled transducers and microphones is used to image grapes through leaves. A fan is used to help differentiate between ultrasonic reflections from grapes and leaves. Improved resolution and detail are achieved with chirp excitation waveforms and near-field focusing of the array. The overestimation in grape volume estimation using ultrasound reduced from 222% to 112% compared to the 3D scan obtained using photogrammetry or from 56% to 2.5% compared to a convex hull of this 3D scan. This also has the added benefit of producing more accurate canopy volume estimations which are important for common precision viticulture management processes such as variable rate applications.

scholarly journals LumNet

2021 ◽  
Vol 5 (2) ◽  
pp. 1-20
Author(s):  
Prince U.C. Songwa ◽  
Aaqib Saeed ◽  
Sachin Bhardwaj ◽  
Thijs W. Kruisselbrink ◽  
Tanir Ozcelebi
Keyword(s):  
Control Systems ◽  
Real Life ◽  
Visual Performance ◽  
Lighting Control ◽  
Domain Specific ◽  
Real Life Setting ◽  
Added Benefit ◽  
Measurement Devices ◽  
Indoor Spaces ◽  
Learned Features

High-quality lighting positively influences visual performance in humans. The experienced visual performance can be measured using desktop luminance and hence several lighting control systems have been developed for its quantification. However, the measurement devices that are used to monitor the desktop luminance in existing lighting control systems are obtrusive to the users. As an alternative, ceiling-based luminance projection sensors are being used recently as these are unobtrusive and can capture the direct task area of a user. The positioning of these devices on the ceiling requires to estimate the desktop luminance in the user's vertical visual field, solely using ceiling-based measurements, to better predict the experienced visual performance of the user. For this purpose, we present LUMNET, an approach for estimating desktop luminance with deep models through utilizing supervised and self-supervised learning. Our model learns visual representations from ceiling-based images, which are collected in indoor spaces within the physical vicinity of the user to predict average desktop luminance as experienced in a real-life setting. We also propose a self-supervised contrastive method for pre-training LUMNET with unlabeled data and we demonstrate that the learned features are transferable onto a small labeled dataset which minimizes the requirement of costly data annotations. Likewise, we perform experiments on domain-specific datasets and show that our approach significantly improves over the baseline results from prior methods in estimating luminance, particularly in the low-data regime. LUMNET is an important step towards learning-based technique for luminance estimation and can be used for adaptive lighting control directly on-device thanks to its minimal computational footprint with an added benefit of preserving user's privacy.

scholarly journals Spectroscopy as a useful tool for the identification of changes with time in post-mortem vitreous humor for forensic toxicology purposes

2021 ◽  
Author(s):  
Anna Wójtowicz ◽  
Agata Mitura ◽  
Renata Wietecha-Posłuszny ◽  
Rafał Kurczab ◽  
Marcin Zawadzki
Keyword(s):  
Ir Spectra ◽  
Forensic Toxicology ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Vitreous Humor ◽  
Attenuated Total Reflection ◽  
Glass Slides ◽  
Added Benefit ◽  
Ft Ir ◽  
Non Destructive

AbstractVitreous humor (VH) is an alternative biological matrix with a great advantage of longer availability for analysis due to the lack of many enzymes. The use of VH in forensic toxicology may have an added benefit, however, this application requires rapid, simple, non-destructive, and relatively portable analytical analysis methods. These requirements may be met by Fourier transform infrared spectroscopy technique (FT-IR) equipped with attenuated total reflection accessory (ATR). FT-IR spectra of vitreous humor samples, deposited on glass slides, were collected and subsequent chemometric data analysis by means of Hierarchical Cluster Analysis and Principal Component Analysis was conducted. Differences between animal and human VH samples and human VH samples stored for diverse periods of time were detected. A kinetic study of changes in the VH composition up to 2 weeks showed the distinction of FT-IR spectra collected on the 1st and 14th day of storage. In addition, data obtained for the most recent human vitreous humor samples—collected 3 and 2 years before the study, presented successful discrimination of all time points studied. The method introduced was unable to detect mephedrone addition to VH in the concentration of 10 µg/cm3. Graphic abstract

Hybrid-Data Approach for Estimating Trip Purposes

2021 ◽  
pp. 036119812110184
Author(s):  
Xiaoling Luo ◽  
Adrian Cottam ◽  
Yao-Jan Wu ◽  
Yangsheng Jiang
Keyword(s):  
Transportation Systems ◽  
Data Driven ◽  
Trip Purpose ◽  
Additional Information ◽  
Point Of Interest ◽  
Average Accuracy ◽  
Hybrid Data ◽  
Added Benefit ◽  
Data Source ◽  
High Level

Trip purpose information plays a significant role in transportation systems. Existing trip purpose information is traditionally collected through human observation. This manual process requires many personnel and a large amount of resources. Because of this high cost, automated trip purpose estimation is more attractive from a data-driven perspective, as it could improve the efficiency of processes and save time. Therefore, a hybrid-data approach using taxi operations data and point-of-interest (POI) data to estimate trip purposes was developed in this research. POI data, an emerging data source, was incorporated because it provides a wealth of additional information for trip purpose estimation. POI data, an open dataset, has the added benefit of being readily accessible from online platforms. Several techniques were developed and compared to incorporate this POI data into the hybrid-data approach to achieve a high level of accuracy. To evaluate the performance of the approach, data from Chengdu, China, were used. The results show that the incorporation of POI information increases the average accuracy of trip purpose estimation by 28% compared with trip purpose estimation not using the POI data. These results indicate that the additional trip attributes provided by POI data can increase the accuracy of trip purpose estimation.

Baseline Concussion Testing Increases Agreement With Favorable Concussion Safety Decisions in Hypothetical Scenarios

2021 ◽  
pp. 109019812110035
Author(s):  
Christina Deuschle ◽  
Julian Keith ◽  
Kelly Dugan ◽  
Mark Williams ◽  
Sasi Taravath ◽  
...  
Keyword(s):  
General Population ◽  
National Collegiate Athletic Association ◽  
Effective Means ◽  
Safety Behavior ◽  
Knowledge And Attitudes ◽  
Attitudes And Perceptions ◽  
Student Version ◽  
Baseline Testing ◽  
Added Benefit ◽  
Concussion Knowledge

Background Dangers of sports-related concussion are well documented, and those participating in sports involving significant contact are at an even higher risk relative to the general population. Despite extensive concussion education, athletes still make decisions that would be considered unsafe, such as underreporting and continuing to play despite experiencing symptoms. Although baseline testing is an increasingly common practice at all levels of sport, little is known about its ability to improve player safety perceptions. Aims The current study examines whether taking part in a standardized baseline concussion assessment changes athletes’ knowledge, attitudes, or perceptions of concussion safety decisions. Method A total of 229 club and National Collegiate Athletic Association athletes completed a modified Rosenbaum Concussion Knowledge and Attitudes Survey–Student Version (RoCKAS-ST), which was used to evaluate knowledge, attitudes, and perceptions of concussion safety decisions in hypothetical scenarios. Athletes were randomly assigned to either complete baseline concussion testing prior to the RoCKAS-ST or complete baseline testing after the RoCKAS-ST. Results Athletes randomly assigned to complete baseline testing before the RoCKAS-ST demonstrated greater agreement with favorable concussion safety decisions in hypothetical scenarios relative to athletes completing baseline testing after the RoCKAS-ST. The two conditions did not differ with respect to concussion knowledge or attitudes. Discussion Baseline testing appears to have an added benefit of resulting in more favorable perceptions toward making safe decisions following suspected concussions. Conclusion Baseline testing may provide an effective means of improving a broader constellation of concussion safety behavior, particularly in club athletes, who are typically underserved in terms of concussion-related resources and care.

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