A Comparative Study of Visual Identification Methods for Highly Similar Engine Tubes in Aircraft Maintenance, Repair and Overhaul.

Unique identification of machine parts is critical to production and maintenance, repair and overhaul (MRO) processes in the aerospace industry. Despite recent advances in automating these identification processes, many are still performed manually. This is time-consuming, labour-intensive and prone to error, particularly when dealing with visually similar objects that lack distinctive features or markings or when dealing with parts that lack readable identifiers due to factors such as dirt, wear and discolouration. Automation of these processes has the potential to alleviate these problems. However, due to the high visual similarity of components in the aerospace industry, commonly used object identifiers are not directly transferable to this domain. This work focuses on the challenging component spectrum engine tubes and aims to understand which identification method using only object-inherent properties can be applied to such problems. Therefore, this work investigates and proposes a comprehensive set of methods using 2D image or 3D point cloud data, incorporating digital image processing and deep learning approaches. Each of these methods is implemented to address the identification problem. A comprehensive benchmark problem is presented, consisting of a set of visually similar demonstrator tubes, which lack distinctive visual features or markers and pose a challenge to the different methods. We evaluate the performance of each algorithm to determine its potential applicability to the target domain and problem statement. Our results indicate a clear superiority of 3D approaches over 2D image analysis approaches, with PointNet and point cloud alignment achieving the best results in the benchmark.

Computational fluid dynamics modeling of cough transport in an aircraft cabin.

To characterize the transport of respiratory pathogens during commercial air travel, Computational Fluid Dynamics simulations were performed to track particles expelled by coughing by a passenger assigned to different seats on a Boeing 737 aircraft. Simulation data were post-processed to calculate the amounts of particles inhaled by nearby passengers. Different airflow rates were used, as well as different initial conditions to account for random fluctuations of the flow field. Overall, 80% of the particles were removed from the cabin in 1.3-2.6 min, depending on conditions, and 95% of the particles were removed in 2.4-4.6 min. Reducing airflow increased particle dispersion throughout the cabin but did not increase the highest exposure of nearby passengers. The highest exposure was 0.3% of the nonvolatile mass expelled by the cough, and the median exposure for seats within 3 feet of the cough discharge was 0.1%, which was in line with recent experimental testing.

A decentralized hybrid computing consumer authentication framework for a reliable drone delivery as a service.

The thriving adoption of drones for delivering parcels, packages, medicines, etc., is surging with time. The application of drones for delivery services results in faster delivery, fuel-saving, and less energy consumption. Giant companies like Google, Amazon, Facebook, etc., are actively working on developing, testing, and improving drone-based delivery systems. So far, a lot of work has been done for improving the design, speed, operating range, security of the delivery drones, etc. However, very limited work has been done to ensure a complete and reliable last-mile delivery from the merchant's store to the hands of the actual customer. To ensure a complete and reliable last-mile delivery, a drone must authenticate the consumer before dropping the package. Therefore, in this work, we propose a consumer authentication (Consumer-Auth) hybrid computing framework for drone delivery as a service to make sure that the parcel is perfectly delivered to the intended customer. The proposed Consumer-Auth framework enables a drone to reach the exact destination by using the GPS coordinates of the customer autonomously. After reaching the exact location, the drone waits for the customer to come to the specific pinned location then it starts a two-factor consumer authentication process, i.e., one-time password (OTP) verification and face Recognition. The experimental results manifest the effectiveness of the proposed Consumer-Auth framework to ensure a complete and reliable drone-based last-mile delivery.

The effects of 12 weeks of functional strength training on muscle strength, volume and activity upon exposure to elevated Gz forces in high-performance aircraft personnel.

BACKGROUND: Technological advancements in modern military and acrobatic jet planes have resulted in extraordinary psychophysiological loads being exerted upon flying personnel, including inducing neck and back pain. The purpose of this study was to examine the effects of 12 weeks of functional strength training on 1) the volume and strength of the neck and shoulder muscles and 2) muscular activity upon exposure to helmets of different masses and elevated Gz forces in a long-arm centrifuge in high-performance aircraft personnel. METHODS: Eighteen participants underwent 12 weeks of functional strength training (n = 12) or the control protocol (n = 6) without additional strength training. Pre- and post-intervention tests included evaluations of isometric strength of the head extensor muscles, flexion, and lateral flexion and rotation, as well as magnetic resonance imaging (MRI) to measure the volume of the m. sternocleidomastoideus, m. trapezius, and deep neck muscles. Furthermore, during a long-arm centrifuge (+ 1.4 and + 3 Gz) protocol, the muscular activity levels of the m. sternocleidomastoideus, m. trapezius and m. erector spinae muscles were assessed without a flight helmet, with a helmet, and with a helmet and night vision goggles. Each participant's perception of muscular strain was noted immediately after the long-arm centrifuge protocol. RESULTS: The maximal isometric strength in all exercises and muscle volumes increased in the training group but not the control group (P < 0.05). Relative muscle activity (%MVC) with a helmet decreased after the intervention in the training but not the control group (P = 0.01). Relative muscle activity while wearing a helmet and night vision goggles was higher after intervention in the control group than in the training group (P < 0.01). The perceived muscular strain of the neck muscles induced by the long-arm centrifuge did not differ between the groups. CONCLUSION: Twelve weeks of functional strength training improves the maximal isometric strength and volume of neck and shoulder muscles and leads to lower relative muscle activation upon exposure to elevated Gz forces in a long-arm centrifuge.

Inflight Polymerase Chain Reaction of samples with drones.

A system devised to conduct Polymerase Chain Reaction (PCR) in-flight on drones that uses the spatial displacement of capillary tubes on thermal blocks kept at 94 °C, 58 °C and 72 °C corresponding to cycling temperatures for denaturation, annealing and extension is demonstrated here. The use of acetal as the thermal block material reduced heat loss and the input power (within 18.5 W) needed to maintain the required temperatures. Tests showed that concentrations of samples down to 1.16 × 106 DNA copies/µL could be significantly and consistently detected above the background emission of the fluorescence signal intensity.

Human Mirror Neuron System Based Alarms in the Cockpit: A Neuroergonomic Evaluation.

Controlled Flight Into Terrain (CFIT) events still remain among the deadliest accidents in aviation. When facing the possible occurrence of such an event, pilots have to immediately react to the ground proximity alarm ("Pull Up" alarm) in order to avoid the impending collision. However, the pilots' reaction to this alarm is not always optimal. This may be at least partly due to the low visual saliency of the current alarm and the deleterious effects of stress that alleviate the pilot's reactions. In the present study, two experiments (in a laboratory and in a flight simulator) were conducted to (1) investigate whether hand gesture videos (a hand pulling back the sidestick) can trigger brainwave frequencies related to the mirror neuron system; (2) determine whether enhancing the visual characteristics of the "Pull Up" alarm could improve pilots' response times. Electrophysiological results suggest that hand gesture videos attracted more participants' attention (greater alpha desynchronization in the parieto-occipital area) and possibly triggered greater activity of the mirror neuron system (greater mu and beta desynchronizations at central electrodes). Results obtained in the flight simulator revealed that enhancing the visual characteristics of the original "Pull Up" alarm improved the pilots' reaction times. However, no significant difference in reaction times between an enlarged "Pull Up" inscription and the hand gesture video was found. Further work is needed to determine whether mirror neuron system based alarms could bring benefits for flight safety, in particular, these alarms should be assessed during a high stress context.

Field performance of sterile male mosquitoes released from an uncrewed aerial vehicle.

Genetic control methods of mosquito vectors of malaria, dengue, yellow fever, and Zika are becoming increasingly popular due to the limitations of other techniques such as the use of insecticides. The sterile insect technique is an effective genetic control method to manage insect populations. However, it is crucial to release sterile mosquitoes by air to ensure homogeneous coverage, especially in large areas. Here, we report a fully automated adult mosquito release system operated from an uncrewed aerial vehicle or drone. Our system, developed and tested in Brazil, enabled a homogeneous dispersal of sterile male Aedes aegypti while maintaining their quality, leading to a homogeneous sterile-to-wild male ratio due to their aggregation in the same sites. Our results indicate that the released sterile males were able to compete with the wild males in mating with the wild females; thus, the sterile males were able to induce sterility in the native female population. The use of drones to implement the sterile insect technique will lead to improvements in areal coverage and savings in operational costs due to the requirement of fewer release sites and field staff.

Drones against vector-borne diseases.

Uncrewed aerial vehicles can reduce the cost of preventative measures against vector-borne diseases.

Multidrone aerial surveys of penguin colonies in Antarctica.

Speed is essential in wildlife surveys due to the dynamic movement of animals throughout their environment and potentially extreme changes in weather. In this work, we present a multirobot path-planning method for conducting aerial surveys over large areas designed to make the best use of limited flight time. Unlike current survey path-planning solutions based on geometric patterns or integer programs, we solve a series of satisfiability modulo theory instances of increasing complexity. Each instance yields a set of feasible paths at each iteration and recovers the set of shortest paths after sufficient time. We implemented our planning algorithm with a team of drones to conduct multiple photographic aerial wildlife surveys of Cape Crozier, one of the largest Adélie penguin colonies in the world containing more than 300,000 nesting pairs. Over 2 square kilometers was surveyed in about 3 hours. In contrast, previous human-piloted single-drone surveys of the same colony required over 2 days to complete. Our method reduces survey time by limiting redundant travel while also allowing for safe recall of the drones at any time during the survey. Our approach can be applied to other domains, such as wildfire surveys in high-risk weather conditions or disaster response.

Counting penguins with drones.

A multidrone path-planning algorithm enables drones to scout Adélie penguin colonies in Antarctica.

Good vibrations for flapping-wing flyers.

Studies of insect flight reveal how flapping-induced vibrations augment flight stability of tailless flapping-wing flyers.

Drone for medical products transportation in maternal healthcare: A systematic review and framework for future research.

INTRODUCTION: Medical products transportation has become an important research topic requiring multidisciplinary collaboration among experts in medicine, engineering, and health economics. Current modes of transportation are unable to overcome the limited settings in maternal healthcare, particularly during the event of obstetric emergencies. The drone is a promising medical product aerial transportation (MedART) that holds an enormous potential for delivery of medical supplies in the healthcare system. We conducted a systematic review to examine scientific evidence of positive impact of drone transportation on maternal health. METHODS: The following electronic databases were searched from inception to July 2019: ScienceDirect, PubMed, and EMBASE. The report was made in accordance with the principles of PRISMA guidelines. The search terms used were related to drones including unmanned aerial vehicle (UAV) and unmanned aerial system (UAS), and related to obstetric/maternal including obstetric emergencies and postpartum hemorrhage. Studies were selected if the intervention used were drones, and if any direct or indirect maternal health indicators were reported. Meta-analysis was not done throughout the study in view of the anticipated heterogeneity of each study. RESULTS: Our initial search yielded a total of 244 relevant publications, from which 236 were carried forward for a title and abstract screening. After careful examination, only two were included for systematic synthesis. Among the reasons for exclusion were irrelevance to maternal health purpose, and irrelevance to drone applications in healthcare. An updated search yielded one additional study that was also included. Overall, two studies assessed drones for blood products delivery, and one study used drones to transport blood samples. CONCLUSION: A significant deficiency was found in the number of reported studies analyzing mode of medical products transportation and adaptation of drones in maternal healthcare. Future drone research framework should focus on maternal healthcare-specific drone applications in order to reap benefits in this area.

Feasibility of bystander-administered naloxone delivered by drone to opioid overdose victims.

BACKGROUND: Currently, ≤5% of bystanders witnessing an opioid overdose (OD) in the US administer antidote to the victim. A possible model to mitigate this crisis would be a system that enables 9-1-1 dispatchers to both rapidly deliver naloxone by drone to bystanders at a suspected opioid OD and direct them to administer it while awaiting EMS arrival. METHODS: A simulated 9-1-1 dispatcher directed thirty subjects via 2-way radio to retrieve naloxone nasal spray from atop a drone located outside the simulation building and then administer it using scripted instructions. The primary outcome measure was time from first contact with the dispatcher to administration of the medication. RESULTS: All subjects administered the medication successfully. The mean time interval from 9 -1-1 contact until antidote administration was 122 [95%CI 109-134] sec. There was a significant reduction in time interval if subjects had prior medical training (p = 0.045) or had prior experience with use of a nasal spray device (p = 0.030). Five subjects had difficulty using the nasal spray and four subjects had minor physical impairments, but these barriers did not result in a significant difference in time to administration (p = 0.467, p = 0.30). A significant number of subjects (29/30 [97%], p = 0.044) indicated that they felt confident they could administer intranasal naloxone to an opioid OD victim after participating in the simulation. CONCLUSIONS: Our results suggest that bystanders can carry out 9-1-1 dispatcher instructions to fetch drone-delivered naloxone and potentially decrease the time interval to intranasal administration which supports further development and testing of a such a system.

Hybrid multi-mode machine learning-based fault diagnosis strategies with application to aircraft gas turbine engines.

In this work, a novel data-driven fault diagnostic framework is developed by using hybrid multi-mode machine learning strategies to monitor system health status. The coexistence of multi-mode and concurrent faults and their adverse coupling effects pose serious limitations for developing reliable diagnostic methodologies. A novel framework is proposed by exploiting inherent embedded health information contained in the I/O sensor data. The proposed hybrid strategies consist of optimal integration of recurrent neural network-based feature generation and self-organizing map diagnostic modules. To construct reliable fault diagnostic modules, a systematic clustering and modeling methodology is developed that has two primary advantages: (i) it does not require any a priori knowledge of data set characteristics or system mathematical model, and (ii) it does address and resolve the key limitations and challenges in conventional self-organizing map approaches. The effectiveness of our proposed framework is validated by utilizing sensor data including healthy and various degradation modes in application to compressor and turbine of an aircraft gas turbine engine. Comparisons with other machine learning-based methods in the literature are provided to demonstrate the performance and superiority of our proposed framework in fault diagnostic accuracy, false alarm rates, and in dealing with multi-mode and concurrent fault scenarios.

Comparison of univariate and multivariate anthropometric design requirements methods for flight deck design application.

Designing aircraft cockpits to accommodate the wide range of body sizes and shapes existing in the world population has always been a difficult problem for crew station engineers. There is no consensus on the best method for obtaining measurements for body forms that statistically represent the variation within a population. The aim of this research is to compare the two most commonly used anthropometric approaches for dimension specification and flight deck design: the boundary cases multivariate and the percentile univariate. The multivariate approach captured more subjects than the percentile approach (p < .05) for all accommodation assessments using Brazilian Air Force pilots' anthropometry, but was not as effective as had been suggested in the literature. This study showed that the Boundary Cases Multivariate Method was better at evaluating design criteria for cockpit accommodation than the Percentile Univariate Method for accommodation of the central 90% envelope for the Brazilian Air Force crew application. Practitioner summary: The findings show that the Multivariate Boundary Cases approach can better provide anthropometric limits for the desired accommodation level when multiple body dimensions need to be simultaneously considered in a design. It will help researchers, designers, and engineers to solve complex design situations, make improved judgement and take right decisions. Abbreviations: FAR: federal aviation regulation; CS: certification specification; FAA: federal aviation administration; EASA: European union aviation safety agency; EMB: embraer; FAB: Brazilian Air Force; CAD: computer-aided design; MAM: multivariate anthropometric method; USAF: United States Air Force; PCA: principal component analysis; PC: principal component; JSF: joint strike fighter; NATO: North atlantic treaty organization; ISO: International Organization for Standardization; BPAD: Brazilian pilots anthropometric database; RD: radial distance; Error = A-E: error = achieved - expected; SPSS: statistical package for the social sciences; IBM Corp.: International business machines corporation; Acr. Ht, st: acromion height, sitting; But-kn lgt: buttock-knee length; Eye Ht, sit: eye height, sitting; Knee Ht, sit: knee height, sitting; Sitting Ht: sitting height; Thumbtip rch: thumbtip reach; Accom %: accommodated percentage; Af, Am, …, Zf, Zm: cases A-D and W-Z ("f" for female subjects and "m" for male subjects); T: trainer; A: atack; KC: anker and cargo; F: fighter; NG-BR: new generation - Brasil; PPE: personal protective equipment.

Considerations for Development of Exposure Limits for Chemicals Encountered During Aircraft Operation.

BACKGROUND: Military aircrews' health status is critical to their mission readiness, as they perform physically and cognitively demanding tasks in nontraditional work environments. Research Objectives: Our objective is to develop a broad operational risk assessment framework and demonstrate its applicability to health risks to aircrews because of airborne chemical exposure, considering stressors such as heat and exertion. METHODS: Extrapolation of generic exposure standards to military aviation-specific conditions can include computation of risk-relevant internal dosimetry estimates by incorporating changes in breathing patterns and blood flow distribution because of aspects of the in-flight environment. We provide an example of the effects of exertion on peak blood concentrations of 1,2,4-trimethylbenzene computed using a physiologically based pharmacokinetic model. RESULTS: Existing published collections on the effects of flight-related stressors on breathing patterns and blood flow address only a limited number of stressors. Although data exist that can be used to develop operational exposure limits specific to military aircrew activities, efforts to integrate this information in specific chemical assessments have been limited. CONCLUSIONS: Efforts to develop operational exposure limits would benefit from guidance on how to make use of existing assessments and expanded databases of the impact of environmental stressors on adult human physiology.

Social Acceptance of Increased Usage of the Ballistic Parachute System in a General Aviation Aircraft.

BACKGROUND: An airframe parachute ("Chute") available in certain aircraft is designed to lower the airplane safely to the ground for emergency situations that occur 500 ft (152 m) above ground level (AGL): the "Chute altitude envelope." This study will explore the change in Chute use before and after 2012 to better understand factors that increased usage and improved accident outcomes.METHODS: Using the public National Transportation Safety Board (NTSB) accident database from January 1, 2001, through August 31, 2018, a regression model was developed to identify factors that may predict Chute use.RESULTS: In accidents occurring after January 1, 2013, pilots were 5 times more likely to use the Chute, while 2.9 times less likely to use the Chute when the accident involved pilot-related causes. The presence of passengers did not predict Chute use. Injuries were likely to be more severe when the Chute was used outside the Chute altitude envelope.DISCUSSION: In contrast to General Aviation (GA) overall, accidents outcomes in aircraft equipped with a Chute have seen great improvements between 2013 and 2018, with increased use of the Chute and improved injury outcomes. Results suggest that changes to pilot training in 2012 have increased the social acceptance of Chute use. Results highlight increased risk of injury outcomes for Chute use in accidents that occur outside the Chute altitude envelope.Kirby J. Social acceptance of increased usage of the ballistic parachute system in a general aviation aircraft. Aerosp Med Hum Perform. 2020; 91(2):86-90.

What the eyes reveal: Investigating the detection of automation failures.

In order to detect automation failures in a timely manner, operators are required to monitor automated systems efficiently. The present study analysed eye movements to predict whether or not participants could detect an automation failure. Eye movements were recorded whilst 101 participants were monitoring an automated system where automation failures occurred at irregular intervals. A main result is that about 75.6 per cent of automation failure detections were predicted successfully by the corresponding eye movements. In cases where failures were detected successfully, relevant information is monitored more often and more intensively, in particular shortly before an automation failure happens and while it is happening. The findings are discussed in the context of the personnel selection and training of aviation operatives, as well as incident reporting as used in air traffic control (ATC).

Identification of Swimmers in Distress Using Unmanned Aerial Vehicles: Experience at the Mont-Tremblant IRONMAN Triathlon.

Background: This preliminary report describes our experience using unmanned aerial vehicles (UAVs) to identify swimmers in distress at the 2018 Mont-Tremblant IRONMAN triathlon (Quebec, Canada). Methods: In a prospective pilot study, we sought to determine whether UAV surveillance could identify swimmers showing signs of distress quicker than conventional methods (i.e., lifeguards on the ground and on watercraft). In addition, we investigated the feasibility of using UAVs for medical surveillance at a triathlon event in terms of operations, costs, safety, legal parameters, and added value. Prior to the race, we screened participants for medical conditions that could elevate their risk of injury during the swim portion of the triathlon. Athletes deemed to be at increased risk were given a yellow swimming cap to enhance their surveillance by trained observers watching a live video feed from the UAVs. Results: On race day, a total of 3 UAVs (2 mobile, 1 tethered) were launched over Lake Tremblant and provided 3 observers with live video of the swimmers. Of the 2,473 race participants, there were 25 athletes with pre-identified medical conditions who wore a yellow cap during the swim. We did not detect any signs of distress among swimmers wearing yellow caps. Among the remaining 2,448 athletes, there were 5 swimmers who demonstrated signs of distress and required mobilization of water rescue boats; UAV surveillance identified 1 of these 5 distress events before it was seen by lifeguards on rescue boats. None of the athletes in the IRONMAN suffered an adverse event while swimming. Several technical and safety issues related to UAV surveillance arose including poor visibility, equipment loss, and flight autonomy. Conclusion: While our preliminary findings suggest that using UAVs to identify distressed swimmers during an IRONMAN race is feasible and safe, more research is necessary to determine how to optimize UAV surveillance at mass sporting events and integrate this technology within the existing emergency response teams.

Eyes in the Sky: Assessing the Feasibility of Low-Cost, Ready-to-Use Unmanned Aerial Vehicles to Monitor Primate Populations Directly.

Primates face many climate and land use change threats, making long-term population monitoring critical to prioritizing conservation efforts. Ground-based line transects are typically conducted to estimate and monitor primate populations. However, transects may be costly and logistically challenging. We sought to test whether low-cost (<5,000 USD), ready-to-use unmanned aerial vehicles (UAVs) could effectively monitor primate populations in north-eastern Madagascar. Critically Endangered [A3cd] golden-crowned sifakas (Propithecus tattersalli) are medium-sized, white lemurs whose creamy colour contrasts against defoliated tree canopies, making them an ideal study species for aerial counts. Quad-copter UAV flights over sifaka groups did not elicit antipredator responses. Photographs demonstrated the ability of UAVs to capture viable imagery of sifakas from approximately 20 m above ground level. Unfortunately, crashes resulting from an inability to programme automated flights over hilly forests cut this pilot study short, highlighting several challenges that remain to implementing UAVs in remote field studies. This study demonstrates that while UAVs offer considerable promise in the future of primate research and conservation, high start-up costs and remote field conditions provide challenging obstacles to first time users hoping to use this exciting new technology. Furthermore, we strongly recommend that thermal cameras be used for direct primate counts with UAVs.