High-definition Digital Camera Research Articles

Heliostat geometrical characterization by UAV-assisted, close-range photogrammetry

An innovative approach for the characterization of the mirror geometry of Concentrating Solar Thermal (CST) plants is presented in this article. The approach takes advantage of the current advances in the commercial unmanned aerial vehicle (UAV) technology to perform airborne, close-range photogrammetry for accurate characterization of the mirror’s geometry. To improve spatial resolution and, thus, reconstruction performance, the approach involves a projector for projecting a feature-rich image on the surface of the mirror to be characterized. A UAV flying on a predetermined flight path is used to capture overlapping snapshots of the projected image using its on-board high definition digital camera. By the use of photogrammetry tools, the snapshots are stitched together and processed accordingly to reconstruct the surface of the reflector. Although the approach was tested and validated experimentally by characterizing the mirror surface of a single-facet heliostat, the developed method can also be applied for the characterization of any type of solar concentrating mirror geometry.

Unmanned aerial vehicle digital image and hyperspectral data for estimating the comparison of leaf area index and biomass of potato at different growth stages

Abstract Leaf Area Index (LAI) and biomass (BIO) are essential agronomic parameters that reflect the growth of potatoes and are related to their biomass. Their precise estimation is capable of monitoring crop growth, guiding field management, and optimizing planting spatial patterns. Traditional potato leaf area indexing and biomass estimation primarily rely on field sampling surveys. This method is low in efficiency, high in cost, and limited by the number of samples. It cannot accurately reflect potato growth and meet the real-time estimation needs of large areas. Compared to the use of satellite remote sensing data (RSD) for estimating LAI and biomass, research on estimating these two phenotypic parameters using crewless aerial vehicle (UAV) RSD is relatively immature. Research on estimating crop growth index parameters by remote sensing primarily focuses on data obtained from specific types of sensors, targeting specific growth stages to compare and analyze the accuracy of different methods. However, there are few estimates of the impact of optimizing the best data types and optimal growth stage for LAI and biomass estimation by comparing and analyzing different sensor data and different growth stages. Multi-sensor integration technology has made it possible to study different crop phenotype information and estimate the best data type and optimal growth stage in crop phenotypic data estimation, establishing it as a new hot spot in the field. This paper integrates high-definition digital cameras and imaging hyperspectrometers on the UAV platform to obtain digital images and hyperspectral data simultaneously, along with ground-measured potato leaf area index and biomass data. Using the partial least squares regression (PLSR), random forest (RF), support vector machine (SVM), and backpropagation (BP) neural network methods, we got digital images and hyperspectral data from different stages of growth, put together a digital image index and a vegetation index, and looked at how they related to LAI and BIO. Then, we chose the index that had the strongest correlation. To establish LAI and biomass estimation models at various growth phases, this paper compared and analyzed the estimation impacts of various data types and models at various growth phases. It then selected the best data types for LAI estimation and biomass estimation at different growth stages, as well as the best growth phases for LAI and biomass estimation. The outcomes indicated that when potato LAI was estimated, the mean values of R 2 and RMSE of the four estimation models were 0.75 and 0.30 Kg/mu at the tuber growth stage, respectively, and the estimation effect was the best, indicating that this was the best growth phase for LAI estimation. The average values of R 2 and RMSE in the LAI estimation model using the hyperspectral vegetation index were 0.73 and 0.33 Kg/mu, respectively, indicating that hyperspectral data was the best data type for LAI estimation. When potato biomass was estimated, the mean values of R 2 and RMSE of the four methods were 0.67 and 15.25 Kg/mu, respectively, at the tuber growth stage, which were better than other growth phases, demonstrating that this was the best growth phase for biomass estimation. The average values of R 2 and RMSE of the biomass estimation model using the hyperspectral vegetation index were 0.67 and 20.08 Kg/mu, respectively, indicating that the hyperspectral data was the best data type for biomass estimation. The average values of R 2 of the LAI and biomass estimation model at the maturity stage were only 0.56 and 0.36, both of which indicated poor estimation effects. Our study can serve as a guide to selecting the most effective method for estimating parameters for essential indexes in crop growth monitoring.

Laboratory modeling of thermal and temporal cracking in swelling clays

Crack development in a changing environment is the controlling factor for the stability and strength of expansive soils. Expansive soils exhibit large volumetric changes with changes in their moisture conditions that may occasionally lead to reduced bearing capacity and foundation failures. This study purports to model crack initiation and its spatial progression in relation to the moisture content and drying period, respectively. Volumetric soil shrinkage is determined using high-definition digital camera imaging and Vernier scale methods, while the soil settlement under vertical shrinkage deformation could be captured through a tensile stress model for soils. It was revealed that a small change in suction could trigger crack initiation, which would propagate further under different environmental conditions. Furthermore, it was observed that the crack volume increased rapidly at specific moisture content and could penetrate as deep as 1 m after nearly 1.5 months that is fully consistent with the current model predictions. A comparison between the performance of the model proposed in this study and that of two existing models shows that the former predicts the vertical shrinkage strain values in closer agreement with those observed experimentally and is less conservative than those predicted by both models. Nevertheless, the findings from this study could be used to quantify the detrimental behavior of expansive soil present in pavement subgrades and shallow foundations for lightweight structures.

Monitoring of Soybean Maturity Using UAV Remote Sensing and Deep Learning

Soybean breeders must develop early-maturing, standard, and late-maturing varieties for planting at different latitudes to ensure that soybean plants fully utilize solar radiation. Therefore, timely monitoring of soybean breeding line maturity is crucial for soybean harvesting management and yield measurement. Currently, the widely used deep learning models focus more on extracting deep image features, whereas shallow image feature information is ignored. In this study, we designed a new convolutional neural network (CNN) architecture, called DS-SoybeanNet, to improve the performance of unmanned aerial vehicle (UAV)-based soybean maturity information monitoring. DS-SoybeanNet can extract and utilize both shallow and deep image features. We used a high-definition digital camera on board a UAV to collect high-definition soybean canopy digital images. A total of 2662 soybean canopy digital images were obtained from two soybean breeding fields (fields F1 and F2). We compared the soybean maturity classification accuracies of (i) conventional machine learning methods (support vector machine (SVM) and random forest (RF)), (ii) current deep learning methods (InceptionResNetV2, MobileNetV2, and ResNet50), and (iii) our proposed DS-SoybeanNet method. Our results show the following: (1) The conventional machine learning methods (SVM and RF) had faster calculation times than the deep learning methods (InceptionResNetV2, MobileNetV2, and ResNet50) and our proposed DS-SoybeanNet method. For example, the computation speed of RF was 0.03 s per 1000 images. However, the conventional machine learning methods had lower overall accuracies (field F2: 63.37–65.38%) than the proposed DS-SoybeanNet (Field F2: 86.26%). (2) The performances of the current deep learning and conventional machine learning methods notably decreased when tested on a new dataset. For example, the overall accuracies of MobileNetV2 for fields F1 and F2 were 97.52% and 52.75%, respectively. (3) The proposed DS-SoybeanNet model can provide high-performance soybean maturity classification results. It showed a computation speed of 11.770 s per 1000 images and overall accuracies for fields F1 and F2 of 99.19% and 86.26%, respectively.

Remote-sensing estimation of potato above-ground biomass based on spectral and spatial features extracted from high-definition digital camera images

Above-ground biomass (AGB) is a significant phenotypic index for evaluating photosynthesis capacity, healthy growth, and estimating crop yield. Accurately monitoring the AGB helps improve agricultural fertilization management and optimize planting patterns. Numerous studies have confirmed that canopy spectrum saturation causes optical vegetation indices (VIs) to underestimate the AGB of crops at multiple growth periods. To solve this problem, the present research used a remote sensing method to obtain RGB images of potato tuber formation-, tuber growth-, and starch accumulation- periods by a high-definition digital camera sensor on the unmanned aerial vehicle (UAV). From the ultrahigh spatial resolution RGB images, we then extracted RGB-VIs, textures (based on the gray level co-occurrence matrix, GLCM), and crop height (Hdsm) and analyzed the correlation between the three image features and the potato AGB for single and multiple growth periods. Finally, we estimated potato AGB at multiple growth periods based on (1) RGB-VIs, (2) RGB-VIs + GLCM-based textures, (3) RGB-VIs + Hdsm, and (4) RGB-VIs + GLCM-based textures + Hdsm by applying multiple stepwise regression (MSR) and extreme learning machine (ELM). The results showed that (i) unlike the texture features of wheat and maize that increased with growth period, the texture features and crop height of the potato canopy both increased first and then decreased with the growth period. (ii) The potato AGB was poorly estimated when using RGB-VIs, CLCM-based textures, or Hdsm individually; (iii) combining GLCM-based textures, Hdsm, and RGB-VIs solved the problem of underestimating the high AGB values of potato samples by the RGB-VIs model alone. Therefore, combining GLCM-based textures, Hdsm, and RGB-VIs obtained from UAV digital images could enhance the accuracy of potato AGB estimation under high coverage.

Agreement of the Apple Watch® and Fitbit Charge® for recording step count and heart rate when exercising in water.

This study examined the association and level of agreement between criterion methods and the Apple Watch 4® and Fitbit Charge 3® for recording step count and heart rate when exercising in water on an aquatic treadmill (ATM). Sixteen healthy participants (13 females and 3 males) volunteered to take part in this study. Participants were submerged in an ATM pool to the level of their xiphoid process and completed 3-min exercise bouts at intensities that corresponded to a comfortable walk, brisk walk, jog, and running. A Polar® T31 chest strap recorded heart rate (HR) and a high-definition digital camera was utilized for recording step count (SC). Significant associations (p < 0.001) were observed between criterion methods and the Apple® (HR: R2 = 0.99 and SC: R2 = 0.87) and Fitbit® (HR: R2 = 0.72 and SC: R2 = 0.83) devices. The mean absolute error and relative error (%) for recording step count were 19.8 (7.4%) in the Apple Watch and 21.4 (8.5%) in the Fitbit and 0.90 (0.76%) in the Apple Watch and 4.2 (3.0%) in the Fitbit for recording heart rate. Both devices displayed a reasonable level of agreement for recording step count and heart rate when exercising in water. Linear regression analysis demonstrating the association between each wearable device and the Apple Watch and Fit Bit Charge for recording step count and heart rate.

Performance of forensic facial comparison by morphological analysis across optimal and suboptimal CCTV settings

Facial comparison is an important yet understudied discipline in forensics. The recommended method for facial comparison in a forensic setting involves morphological analysis (MA) with the use of a facial feature list. The performance of this approach has not been tested across various closed-circuit television (CCTV) conditions. This is of particular concern as video and image data available to law enforcement is often varied and of subpar conditions. The present study aimed at testing MA across two types of CCTV data, representing ideal and less than ideal settings, also assessing which particular shortcomings arose from less-than-ideal settings. The study was conducted on a subset of the Wits Face Database arranged in a total of 225 face pools. Each face pool consisted of a target image obtained from either a high-definition digital CCTV camera or a low-definition analogue CCTV camera in monochrome, contrasted to 10 possible matches. The face pools were analysed and scored using MA and confusion matrices were used to analyse the outcomes. A notably high chance corrected accuracy (CCA) (97.3%) and reliability (0.969) was identified across the digital CCTV sample, while in the analogue CCTV sample MA appeared to underperform both in accuracy (CCA: 33.1%) and reliability (0.529). The majority of the errors in scoring resulted in false negatives in the analogue sample (75.2%), while across both CCTV conditions false positives were low (digital: 0.3%; analogue: 1.2%). Even though hit rates appeared deceptively high in the analogue sample, the various measures of performance used and particularly the chance corrected accuracy highlighted its shortfalls. Overall, CCTV recording quality appears closely associated to MA performance, despite the favourable error rates when using the Facial Identification Scientific Working Group feature list.

Experimental Investigation of the Partial Vegetation Effect on the Flood Wave Propagation Resulted from Dam Failure in Urkmez Residential Area by means of Distorted Physical Model

The purpose of this study is to investigate the effect of partial vegetation on the wave propagation resulted from sudden dam failure in a residential area. Temporal variations of water depths and flood wave propagation velocities were determined and compared with those obtained from the experiments performed without vegetation. The experiments were performed on the distorted physical model of Urkmez Dam and its downstream region. The distorted physical model with horizontal scale of 1/150 and vertical scale of 1/30 contains the dam reservoir, the dam body, the residential area of Urkmez coastal town until the sea and the partial vegetation. In the model, the reservoir has an active volume of 11.222 m3, the dam body has a length of 2.84 m and a height of 1.07 m, and the downstream area is nearly 200 m2. Water depths were measured by e+ WATER L level sensors placed at various locations of the downstream region. Velocities were measured by ultrasonic velocity profilers (UVP) located near the level sensors. Flood wave propagation was recorded by the high definition digital camera. Experimental findings obtained from the physical model were converted to the prototype values, in nature. The changes in water depths and elapsed times, also the changes in velocities and their occurrence times were determined for different zones of the downstream area in the presence of vegetation. The experimental results revealed that in such a dam failure, the flood arrives at the sea in 6 s in the absence of vegetation, while in 10 s in the presence of vegetation. These values correspond to 2.74 min and 4.57 min, respectively in the prototype. The existence of vegetation resulted in decrease in flood propagation velocities mainly in the dense residential area, as expected. It was observed that the maximum water depths were increased at the left bank and decreased at the right bank, except at level sensor S6 which is very close to the creek. It was observed that the maximum depth averaged velocities were decreased in the sparse and dense residential areas. The existence of the vegetation changed considerably the local velocities during rising and recession stages of the water depth. It was found that the order of magnitude of the prototype velocities was high and such velocities can cause serious damage mainly in the buildings close to the dam body. Because the presence of vegetation caused a decrease in flood propagation velocities in the sparse and dense residential areas, it would reduce the damages on the buildings in these areas.

The VITOM® exoscope in oculoplastic surgery: the 5 year Coventry experience.

BackgroundIntraoperative imaging is a desirable tool in oculoplastic surgery; however, there are few modalities which allow surgeons to capture and edit the images in real time without compromising the sterility of the surgical field. We describe the set-up of the VITOM® exoscope system based on our 5 years’ experience of using it as an effective intraoperative video imaging and teaching modality for extraocular surgery.MethodsThe VITOM® is a specially designed exoscope mounted onto a versatile mechanical arm. It is attached to a high definition (HD) digital camera displayed on the HD video monitor of a standard endoscopy stack. This technology has been utilised in other surgical subspecialties, but there is no documented use within extraocular surgery.ResultsThe exoscope was simple to set-up and allowed real-time recording and editing with an HD image display system. The theatre team were able to view the precise surgical steps, contributing to improved theatre flow. Trainees reported that the VITOM® images significantly improved their visualisation and understanding of key surgical anatomy and steps.ConclusionsOur experience showed that the VITOM® exoscope is an excellent intraoperative video imaging and teaching aid, as it allows real-time capture and editing of open surgery and seems to improve theatre flow. With newer models using 3D stereoscopic vision, it could be further evaluated as a heads-up viewing system within extraocular and oculoplastic surgery.

Locomotor activity in Branchipus schaefferi (Fischer, 1834) (Branchiopoda: Anostraca) under thermal variation

The behavioral responses of Branchipus schaefferi Fisher, 1834 males and females to short-term thermal stress in six different rearing conditions are studied. The swimming performance was tested in pure tap water and water collected from both male and female culture mediums. The animal's behavior was recorded using a high-definition digital video camera mounted approximately 30 cm above the experimental containers. The swimming track and the thoracopod beating rates were recorded manually for each animal at different temperatures. The results indicate that in most cases, a significant increase in active swimming and limb beating rate occurred with increasing temperature. However, the animals tested in the different male and female culture medium were significantly less active compared to those in tap water, under similar thermal stress. Animals seem to produce substances in the culture media that influence their locomotor behavior under thermal stress.

Analysis of Instability Mode and Limit Support Pressure of Shallow Tunnel Face in Sands

The stability analysis of the tunnel face is not only essential for guaranteeing the safe construction of urban shallow tunnels, but also directly affecting the influence degree of tunnel construction on nearby structures. The primary concerns in the stability analysis of the tunnel face are the instability mode of surrounding rocks and the limit support pressure on the tunnel face. In this paper, face stability of shallow tunnels in sands was conducted using a symmetrical model test. The ground surface settlement, support pressure on the tunnel face and progressive instability modes of sands at tunnel face are measured by using an LVDT (Linear Variable Differential Transformer) displacement sensor, high-precision pressure sensor and high-definition digital camera, respectively. The test results indicate that the shear failure band appears in sands in front of the tunnel face and develops from the tunnel invert to the tunnel crown. The upper sands undergo stress redistribution, and the pressure arch appears with initial form of “ellipsoid”, then of the “pyramid”. Moreover, the support pressure on the tunnel face experiences four stages, namely, rapid decline stage, the minimum stage, slowly raises stage and stable stage during tunnel excavation. The research results of this paper will provide theoretical support for the reasonable value of the support pressure on the tunnel face in practical engineering.

Application of Computer UAV Remote Sensing Technology in Building Engineering Surveying and Mapping

UAV remote sensing systems are widely used in environmental investigations. It is mainly used to classify land resources and monitor environmental land in urban areas to fully grasp urban land resource information. At present, some government departments in China have tried to use unmanned aerial vehicle remote sensing systems for environmental investigations. Using high-definition digital cameras equipped with unmanned aerial vehicles to carry out environmental surveys in rural and urban land resources. The unmanned aerial vehicle remote sensing system obtains a remote sensing map to provide a basis for the measurement of land use rights, reduces the investment in traditional land measurement manpower and material resources, greatly improves the measurement efficiency and meets the precise requirements of government departments for environmental monitoring. This article analyzes and explores the application of UAV remote sensing technology in surveying and mapping.

The Exoscope versus operating microscope in microvascular surgery: A simulation non-inferiority trial.

BackgroundThe Exoscope is a novel high-definition digital camera system. There is limited evidence signifying the use of exoscopic devices in microsurgery. This trial objectively assesses the effects of the use of the Exoscope as an alternative to the standard operating microscope (OM) on the performance of experts in a simulated microvascular anastomosis.MethodsModus V Exoscope and OM were used by expert microsurgeons to perform standardized tasks. Hand-motion analyzer measured the total pathlength (TP), total movements (TM), total time (TT), and quality of end-product anastomosis. A clinical margin of TT was performed to prove non-inferiority. An expert performed consecutive microvascular anastomoses to provide the exoscopic learning curve until reached plateau in TT.ResultsTen micro sutures and 10 anastomoses were performed. Analysis demonstrated statistically significant differences in performing micro sutures for TP, TM, and TT. There was statistical significance in TM and TT, however, marginal non-significant difference in TP regarding microvascular anastomoses performance. The intimal suture line analysis demonstrated no statistically significant differences. Non-inferiority results based on clinical inferiority margin (Δ) of TT=10 minutes demonstrated an absolute difference of 0.07 minutes between OM and Exoscope cohorts. A 51%, 58%, and 46% improvement or reduction was achieved in TT, TM, TP, respectively, during the exoscopic microvascular anastomosis learning curve.ConclusionsThis study demonstrated that experts’ Exoscope anastomoses appear non-inferior to the OM anastomoses. Exoscopic microvascular anastomosis was more time consuming but end-product (patency) in not clinically inferior. Experts’ “warm-up” learning curve is steep but swift and may prove to reach clinical equality.

In-Plane Behavior of Auxetic Non-Woven Fabric Based on Rotating Square Unit Geometry under Tensile Load.

This paper reports the auxetic behavior of modified conventional non-woven fabric. The auxetic behavior of fabric was achieved by forming rotating square unit geometry with a highly ordered pattern of slits by laser cutting. Two commercial needle-punched non-woven fabric used as lining and the reinforcement fabric for the footwear industry were investigated. The influence of two rotating square unit sizes was analyzed for each fabric. The original and modified fabric samples were subjected to quasi-static tensile load by using the Tinius Olsen testing machine to observe the in-plane mechanical properties and deformation behavior of tested samples. The tests were recorded with a full high-definition (HD) digital camera and the video recognition technique was applied to determine the Poisson’s ratio evolution during testing. The results show that the modified samples exhibit a much lower breaking force due to induced slits, which in turn limits the application of such modified fabric to low tensile loads. The samples with smaller rotating cell sizes exhibit the highest negative Poisson’s ratio during tensile loading through the entire longitudinal strain range until rupture. Non-woven fabric with equal distribution and orientation of fibers in both directions offer better auxetic response with a smaller out-of-plane rotation of rotating unit cells. The out-of-plane rotation of unit cells in non-homogenous samples is higher in machine direction.

Updated catalogue of bony fishes observed in deep waters at Isla del Coco National Park and Las Gemelas Seamount, Costa Rica (Eastern Tropical Pacific)

From 2006 to date the submersible DeepSee has been used to study the deep waters in and around Isla del Coco National Park, Costa Rica. Over these years, images and samples have been collected at depths between 50 and 450 m. Here we present a catalogue of bony fishes recorded by the submersible in deep waters of Isla del Coco, 500 km south-southwest of mainland Costa Rica, and at Las Gemelas Seamount within the designated Seamounts Management Area, 50 km southwest of Isla del Coco. A database with video-images of bony fishes was created from videos taken by the submersible’s high-definition digital camera from 2006 to 2015. Additional information on the distribution of fishes was obtained from 11 dives (24.3 hrs) using the remotely operated vehicle Hela at Las Gemelas Seamount during February 2012. Images of bony fishes were obtained during 376 dives (365 DeepSee dives plus 11 Hela dives) in 18 different locations, and here we report on a total of 85 taxa (i.e. putative species). In this catalogue we present images that are the first color photographs published for some species. In other cases, identifications were possible only to the level of genus (11), family (5) or order (1); hence the information is presented in terms of putative taxa. Four new records are reported for Isla del Coco: Leptenchelys vermiformis (Ophichthidae), Hyporthodus mystacinus (Serranidae), Kathetostoma averruncus (Uranoscopidae), and Symphurus diabolicus (Cynoglossidae). Depth ranges of twenty-six species are expanded beyond previously published records; three were observed in shallower water, twenty-two in deeper water and one was observed both shallower and deeper than in previous reports. As might be expected, increased bottom time with the submersible resulted in additions to the list of documented species. This highlights the importance of maintaining systematic research efforts in the deep waters around Isla del Coco, both for scientific purposes as well as conservation.

The toxic edge-A novel treatment for refractory erythema and flushing of rosacea.

Rosacea is a common, chronic facial skin disease that affects the quality of life. Treatment of facial erythema with intradermal botulinum toxin injection has previously been reported. The primary objective of the study was the safety and efficacy of thermal decomposition of the stratum corneum using a novel non-laser thermomechanical system (Tixel, Novoxel, Israel) to increase skin permeability for Botulinum toxin in the treatment of facial flushing of rosacea. A retrospective review of16 patients aged 23-45 years with Fitzpatrick Skin Types II to IV and facial erythematotelangiectatic rosacea treated by Tixel followed by topical application of 100 U of abobotulinumtoxin. A standardized high-definition digital camera photographed the patients at baseline and 1, 3, and 6 months after the last treatment. Objective and subjective assessments of the patients were done via Mexameter, the Clinicians Erythema Assessment (CEA), and Patients self-assessment (PSA) scores and the dermatology life quality index (DLQI) validated instrument. The average Maxameter, CEA, and PSA scores at 1, 3, and 6 months were significantly improved compared with baseline (all had a P-value <0.001). DLQI scores significantly improved with an average score of 18.6 at baseline at 6 months after treatment (P < 0.001). Self-rated patient satisfaction was high. There were no motor function side-effects or drooping. Thermal breakage of the stratum corneum using the device to increase skin permeability for botulinum toxin type A in the treatment of facial flushing of rosacea seems both effective and safe. Lasers Surg. Med. © 2018 Wiley Periodicals, Inc.

A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera

Timely and accurate estimates of crop parameters are crucial for agriculture management. Unmanned aerial vehicles (UAVs) carrying sophisticated cameras are very pertinent for this work because they can obtain remote-sensing images with higher temporal, spatial, and ground resolution than satellites. In this study, we evaluated (i) the performance of crop parameters estimates using a near-surface spectroscopy (350~2500 nm, 3 nm at 700 nm, 8.5 nm at 1400 nm, 6.5 nm at 2100 nm), a UAV-mounted snapshot hyperspectral sensor (450~950 nm, 8 nm at 532 nm) and a high-definition digital camera (Visible, R, G, B); (ii) the crop surface models (CSMs), RGB-based vegetation indices (VIs), hyperspectral-based VIs, and methods combined therefrom to make multi-temporal estimates of crop parameters and to map the parameters. The estimated leaf area index (LAI) and above-ground biomass (AGB) are obtained by using linear and exponential equations, random forest (RF) regression, and partial least squares regression (PLSR) to combine the UAV based spectral VIs and crop heights (from the CSMs). The results show that: (i) spectral VIs correlate strongly with LAI and AGB over single growing stages when crop height correlates positively with AGB over multiple growth stages; (ii) the correlation between the VIs multiplying crop height and AGB is greater than that between a single VI and crop height; (iii) the AGB estimate from the UAV-mounted snapshot hyperspectral sensor and high-definition digital camera is similar to the results from the ground spectrometer when using the combined methods (i.e., using VIs multiplying crop height, RF and PLSR to combine VIs and crop heights); and (iv) the spectral performance of the sensors is crucial in LAI estimates (the wheat LAI cannot be accurately estimated over multiple growing stages when using only crop height). The LAI estimates ranked from best to worst are ground spectrometer, UAV snapshot hyperspectral sensor, and UAV high-definition digital camera.

Development of an Open-Source Laparoscopic Simulator Capable of Motion and Force Assessment: High Tech at Low Cost.

Laparoscopic simulators help improve surgical skills in an ex vivo setting. New simulators incorporate force and motion assessment, but often at high financial cost. Our goal is to establish global access to a laparoscopic simulator, which offers both traditional summative assessment (time to task completion and precision) as well as advanced formative assessment (force and motion sensing capabilities) so that educators anywhere may be able to create simulators with increased educational value. A low-cost laparoscopic simulator incorporating an off-the-shelf optical sensor, inertial measurement unit, holders, and a housing unit for a microcontroller was integrated into a plastic box with a high-definition digital camera and a three-dimensional mouse. Open source software was developed to offer real-time feedback in force and motion. The system was calibrated for accuracy and consistency. The simulator was assembled from off-the-shelf components and open-source software. Total estimated cost was $350 United States Dollars. The mouse was calibrated by applying known forces in known directions. Linear forces measured in all axes showed linear output trends with r2-values of between 0.988 and 0.999. Accuracy in motion evaluation was evaluated and this demonstrated low average errors in the motion sensors of 5.4% to 6.8%. This low-cost, off-the-shelf, open-access laparoscopic simulator provides accurate and consistent measures of force and motion. We believe that collaborative efforts between surgeons and engineers can allow the creation of these surgical teaching devices at a reasonable cost such that they can be used in resource-rich and resource-limited settings.

Design of Electric Patrol UAVs Based on a Dual Antenna System

China completed the construction of more than 1.15 million kilometers of transmission lines with conventional voltage levels spanning its vast territory in 2014. This large and complicated power grid structure relies mainly on manual operation and maintenance of lines. Unmanned aerial vehicles (UAVs) equipped with high-definition digital video cameras and cameras and GPS positioning systems can conduct autonomous patrols along the grid. However, the presence of electromagnetic fields around high-voltage transmission lines can affect the UAV’s magnetometer, resulting in a wrong heading and thus unsafe flight. In this paper, the traditional method of UAV heading calculation using a magnetometer was analyzed, and a novel method for calculating UAV heading based on dual antennas was proposed. Experimental data showed that the proposed method improves the anti-magnetic interference characteristics of UAVs and increases UAV security and stability for power inspection applications.

The visualization of the surgical field in tubular assisted spine surgery: Is there a difference between HD-endoscopy and microscopy?

ObjectiveExpert spinal surgeons criticized endoscopic procedures for poor image quality, in comparison to microscopic visualization. The recent introduction of high definition (HD) digital cameras has shown good results in spinal endoscopy. The aim of this study was to assess endoscopic HD image quality in comparison with microscopic visualization. Patients and methodsAll posterior lumbar and cervical spinal surgeries of this study were performed with the EasyGO-system in HD resolution. For each comparison, anatomical structures were predefined intraoperatively. A junior resident was randomly required to enter the operating theatre and to identify those structures either using HD-endoscopic or microscopic visualization through the endoscopic working sheath. ResultsThirteen lumbar and three cervical procedures were performed. Thirty-four comparisons with a total of 214 predefined anatomical structures were analyzed. The number of predefined structures ranged from 5 to 9 per surgical field. Out of 214 predefined structures, 124 structures (65.8%) were correctly identified under endoscopic view and 88 (41.1%) under microscopic view (p=0.001). Subjective impression of visualization quality were rated 1.25 (very good) for endopscopic images and 1.6 (very good to good) for microscopic view (p=0.02). ConclusionsWhen using a working trocar and live images, endoscopic HD camera imaging accounted for significantly more reliable identifications of anatomical structures compared to the microscopic view. The subjective impression of video quality is significantly better with HD-optics. The goal of further studies should be to evalute if these findings results in improved surgical outcome.