A Deep Learning Framework for Real-Time Bird Detection and Its Implications for Reducing Bird Strike Incidents.

Bird strikes are a substantial aviation safety issue that can result in serious harm to aircraft components and even passenger deaths. In response to this increased tendency, the implementation of new and more efficient detection and prevention technologies becomes urgent. The paper presents a novel deep learning model which is developed to detect and alleviate bird strike issues in airport conditions boosting aircraft safety. Based on an extensive database of bird images having different species and flight patterns, the research adopts sophisticated image augmentation techniques which generate multiple scenarios of aircraft operation ensuring that the model is robust under different conditions. The methodology evolved around the building of a spatiotemporal convolutional neural network which employs spatial attention structures together with dynamic temporal processing to precisely recognize flying birds. One of the most important features of this research is the architecture of its dual-focus model which consists of two components, the attention-based temporal analysis network and the convolutional neural network with spatial awareness. The model's architecture can identify specific features nested in a crowded and shifting backdrop, thereby lowering false positives and improving detection accuracy. The mechanisms of attention of this model itself enhance the model's focus by identifying vital features of bird flight patterns that are crucial. The results are that the proposed model achieves better performance in terms of accuracy and real time responses than the existing bird detection systems. The ablation study demonstrates the indispensable roles of each component, confirming their synergistic effect on improving detection performance. The research substantiates the model's applicability as a part of airport bird strike surveillance system, providing an alternative to the prevention strategy. This work benefits from the unique deep learning feature application, which leads to a large-scale and reliable tool for dealing with the bird strike problem.

[Participation of aeromedicine specialists in complex forensic medical examination in aviation accidents]. / Uchastie spetsialistov v oblasti aviatsionnoi meditsiny pri provedenii kompleksnykh sudebno-meditsinskikh ekspertiz v sluchayakh aviatsionnykh katastrof.

The problem of flight safety and aviation injury were considered, data on aviation accidents in Civil aviation were shown, the main causes of aviation accidents were presented: technical failure, difficult meteorological conditions, deficiencies in flight organization and «human factor¼. The conditional classification of aviation injury was presented. Detection of primary injuries is especially important for aeromedicine (head impact on dashboard, bone fracture at the ankle, «loss of vital space¼, laceration between 1st and 2nd fingers from the control wheel), that determine the pattern of pilots' actions in an emergency situation. A three-link flight medical support system was remained to prevent flying under the influence of alcohol, drugs and psychoactive substances. The Department of Aerospace Medicine developed the algorithm of pilots' examination suspected of using toxic substances. The materials of pilot's psychological examination after an aviation accident in the state of posttraumatic stress disorder are presented.

An Orientation to Aviation Psychiatry: With 30 Case Examples and a 10-Year Follow-up.

ABSTRACT: This report orients general psychiatrists to assessment and care for "safety sensitive" aviation workers. Our case study of 30 sequential aviation patients consists of demographic, clinical, and aviation characteristics plus a 10-year follow-up. Relatively few pilots and other aviation workers self-identified their psychiatric condition. Aviation outcomes associated with psychiatric disorder included personnel injury and/or aircraft damage (three cases), imminent risk without injury or damage (nine cases), impaired aviation functioning without imminent risk (15 cases), and neither risk nor psychiatric disorder or impairment (three cases). Mood, anxiety, and substance use disorders comprised the most common diagnoses. Ten years later, 23 patients were employed (21 in aviation); seven were disabled or deceased. General psychiatrists will find aviation cases clinically familiar but requiring added evaluation for aviation safety and potential interaction with the Federal Aviation Agency and airline supervisors.

When Outcomes are not Enough: An Examination of Abductive and Deductive Logical Approaches to Risk Analysis in Aviation.

While airlines generate massive amounts of operational data every year, the ability to use the collected material to improve safety has begun to plateau. With the increasing demand for air travel, the aviation industry is continually growing while simultaneously being required to ensure the level of safety within the system remains constant. The purpose of this article is to explore whether the traditional analysis methods that have historically made aviation ultra-safe have reached their theoretical limits or merely practical ones. This analysis argues that the underlying logic governing the traditional (and current) approaches to assess safety and risk within aviation (and other safety critical systems) is abductive and therefore focused on creating explanations rather than predictions. While the current "fly-fix-fly" approach has, and will continue to be, instrumental in improving what (clearly) fails, alternative methods are needed to determine if a specific operation is more or less risky than others. As the system grows, so too does the number of ways it can fail, creating the possibility that more novel accidents may occur. The article concludes by proposing an alternative approach that explicitly adds temporality to the concepts of safety and risk. With this addition, a deductive analysis approach can be adopted which, while low in explanatory power, can be used to create predictions that are not bound to analyzing only outcomes that have occurred in the past but instead focuses on determining the deviation magnitude between the operation under analysis and historically commensurate operations.

Development of a Metric Concept that Differentiates Between Normal and Abnormal Operational Aviation Data.

There is a strong and growing interest in using the large amount of high-quality operational data available within an airline. One reason for this is the push by regulators to use data to demonstrate safety performance by monitoring the outputs of Safety Performance Indicators relative to targeted goals. However, the current exceedance-based approaches alone do not provide sufficient operational risk information to support managers and operators making proximate real-time data-driven decisions. The purpose of this study was to develop and test a set of metrics which can complement the current exceedance-based methods. The approach was to develop two construct variables that were designed with the aim to: (1) create an aggregate construct variable that can differentiate between normal and abnormal landings (row_mean); and (2) determine if temporal sequence patterns can be detected within the data set that can differentiate between the two landing groups (row_sequence). To assess the differentiation ability of the aggregate constructs, a set of both statistical and visual tests were run in order to detect quantitative and qualitative differences between the data series representing two landing groups prior to touchdown. The result, verified with a time series k-means cluster analysis, show that the composite constructs seem to differentiate normal and abnormal landings by capturing time-varying importance of individual variables in the final 300 seconds before touchdown. Together the approaches discussed in this article present an interesting and complementary way forward that should be further pursued.

Research on Aviation Safety Prediction Based on Variable Selection and LSTM.

Accurate prediction of aviation safety levels is significant for the efficient early warning and prevention of incidents. However, the causal mechanism and temporal character of aviation accidents are complex and not fully understood, which increases the operation cost of accurate aviation safety prediction. This paper adopts an innovative statistical method involving a least absolute shrinkage and selection operator (LASSO) and long short-term memory (LSTM). We compiled and calculated 138 monthly aviation insecure events collected from the Aviation Safety Reporting System (ASRS) and took minor accidents as the predictor. Firstly, this paper introduced the group variables and the weight matrix into LASSO to realize the adaptive variable selection. Furthermore, it took the selected variable into multistep stacked LSTM (MSSLSTM) to predict the monthly accidents in 2020. Finally, the proposed method was compared with multiple existing variable selection and prediction methods. The results demonstrate that the RMSE (root mean square error) of the MSSLSTM is reduced by 41.98%, compared with the original model; on the other hand, the key variable selected by the adaptive spare group lasso (ADSGL) can reduce the elapsed time by 42.67% (13 s). This shows that aviation safety prediction based on ADSGL and MSSLSTM can improve the prediction efficiency of the model while keeping excellent generalization ability and robustness.

Penguins, Birds, and Pilot Knowledge: Can an Overlooked Attribute of Human Cognition Explain Our Most Puzzling Aircraft Accidents?

OBJECTIVE: We extend the theory of conceptual categories to flight safety events, to understand variations in pilot event knowledge. BACKGROUND: Experienced, highly trained pilots sometimes fail to recognize events, resulting in procedures not being followed, damaging safety. Recognition is supported by typical, representative members of a concept. Variations in typicality ("gradients") could explain variations in pilot knowledge, and hence recognition. The role of simulations and everyday flight operations in the acquisition of useful, flexible concepts is poorly understood. We illustrate uses of the theory in understanding the industry-wide problem of nontypical events. METHOD: One hundred and eighteen airline pilots responded to scenario descriptions, rating them for typicality and indicating the source of their knowledge about each scenario. RESULTS: Significant variations in typicality in flight safety event concepts were found, along with key gradients that may influence pilot behavior. Some concepts were linked to knowledge gained in simulator encounters, while others were linked to real flight experience. CONCLUSION: Explicit training of safety event concepts may be an important adjunct to what pilots may variably glean from simulator or operational flying experiences, and may result in more flexible recognition and improved response. APPLICATION: Regulators, manufacturers, and training providers can apply these principles to develop new approaches to pilot training that better prepare pilots for event diversity.

Absence of Pilot Monitoring Affects Scanning Behavior of Pilot Flying: Implications for the Design of Single-Pilot Cockpits.

OBJECTIVE: This study examines whether the pilot flying's (PF) scanning behavior is affected by the absence of the pilot monitoring (PM) and aims at deriving implications for the design of single-pilot cockpits for commercial aviation. BACKGROUND: Due to technological progress, a crew reduction from two-crew to single-pilot operations (SPO) might be feasible. This requires a redesign of the cockpit to support the pilot adequately, especially during high workload phases such as approach and landing. In these phases, the continuous scanning of flight parameters is of particular importance. METHOD: Experienced pilots flew various approach and landing scenarios with or without the support of the PM in a fixed-base Airbus A320 simulator. A within-subject design was used and eye-tracking data were collected to analyze scanning behavior. RESULTS: The results confirm that the absence of the PM affects the PF's scanning behavior. Participants spent significantly more time scanning secondary instruments at the expense of primary instruments when flying alone. Moreover, the frequency of transitions between the cockpit instruments and the external view increased while mean dwell durations on the external view decreased. CONCLUSION: The findings suggest that the PM supports the PF to achieve efficient scanning behavior. Information should be presented differently in commercial SPO to compensate for the PM's absence and to avoid visual overload. APPLICATION: This research will help inform the design of commercial SPO flight decks providing adequate support for the pilot particularly in terms of efficient scanning behavior.

Quantifying Risk in Air Sports: Flying Activity and Incident Rates in Paragliding.

INTRODUCTION: The volume, nature, and risks of paragliding are poorly quantified. More comprehensive understanding, including incident rates allowing comparison to similar disciplines, will help direct and appraise safety interventions. METHODS: Paraglider pilots were surveyed regarding experience, incidents, recordkeeping, and risk perception. The survey could not capture those who had left the sport or died, so a subset of responses from UK pilots was compared to records from an incident database. RESULTS: There were 1788 (25%) responses from 7262 surveyed. Respondents flew a total of 87,909 h in 96,042 flights during 2019. Local flying was most frequent (n=37,680 flights, 39%) but a higher proportion of hours were spent flying cross-country (n=33,933 h, 39%). The remainder were spent in competition, hike and fly, tandem, aerobatic, or instructional flight. Flying incidents led to 103 (6%) respondents seeking medical attention, attending hospital, or missing a day of work in 2019. Near misses were reported by 423 (26%) pilots. Asymmetry and rotational forces typically led to incidents, and limb and back injuries resulted. Pilots frequently failed to throw their reserve parachutes. Only 3 (0.6%) incidents involved equipment failure, with the remainder attributed to control or decision errors. Incident rates of paragliding were estimated as 1.4 (1.1-1.9) deaths and 20 (18-27) serious injuries per 100,000 flights, approximately twice as risky as general aviation and skydiving. CONCLUSIONS: Incidents usually resulted from pilot error (control and decision), rather than equipment failure. Future safety interventions should focus on improving glider control skills and encouraging reserve parachute deployment.

Predicting and mitigating failures on the flight deck: an aircraft engine bird strike scenario.

Engine damage as a consequence of foreign object debris (FOD) during flight is frequently caused by birds. One approach to minimising disruption caused by this damage is to provide flight crew with accurate information relating to the continuing operational status of the aircraft's engines. Before designing such avionic systems however, understanding of current procedures is needed. Hierarchical Task Analysis (HTA) and Systematic Human Error Reduction and Prediction Approach (SHERPA) were used to identify potential failures that flight crew may make when managing an engine bird strike. Workshops with commercial pilots generated insights into current practice and a commercial pilot SME reviewed outputs for accuracy. Over 200 potential failures were identified, most commonly related to communication. Remedial measures, considering future avionic systems, are proposed to mitigate identified failures. This analysis provides a starting point for future design concepts for assisting flight crew in dealing with engine malfunction due to FOD strikes. Practitioner summary: Hierarchical Task Analysis was conducted to show all tasks involved in dealing with an in-flight aircraft engine bird strike. Systematic Human Error Reduction and Prediction Approach analysis was performed and over 200 possible failures were identified when managing this event. Remedial measures are proposed to help mitigate possible failures.

Comparison of trauma scores and total prehospital time in the prediction of clinical course in a plane crash: Does timing matter?

OBJECTIVE: To investigate how the total prehospital time (TPT), Abbreviated Injury Scale (AIS), Injury Severity Score (ISS), and Trauma Score-Injury Severity Score (TRISS) affect the outcome of plane crash victims from anatomical, physiological and psychological perspectives. The accuracy or strength of these scores and TPT in predicting hospitalization and surgery, sequelae development and psychiatric complications [permanent temporary disability (PoTDs)] and PTSD can allow medical professionals to direct and prioritize management efforts of the victims of mass casualties in general. METHODS: The study was designed as a single-center retrospective study. By examining the records of victims of a plane crash transferred to the ED, AIS, ISS, TRISS and TPT were calculated on admission. The clinical severity of the patients was determined by a joint decision of five clinicians. The performances of the trauma scores on hospitalization, surgery, PTSD and PoTDs were compared. The study data were analyzed via the Mann-Whitney U test and descriptive statistical methods. Pearson's chi-square test was used for the comparison of qualitative data, and ROC analyses were employed to determine cutoff levels. RESULTS: The AIS, ISS, and TRISS scores of the victims with an indication for hospitalization, calculated on admission to the ED, were significantly higher than those of the other victims (p = 0.001). In addition, TPT, AIS, ISS, and TRISS scores were significantly higher in hospitalized patients than in outpatients (p < 0.05). The cutoff levels for AIS and ISS were ≥ 1.50 and ≥ 4.50, respectively, while they were ≥ 123.5 min for TPT with regard to hospitalization decisions. The AIS, ISS, and TRISS scores calculated on admission for the patients who underwent surgery were significantly higher than those who did not (p = 0.001). Cutoff levels for AIS and ISS were ≥ 2.50 and ≥ 11.50, respectively, while they were ≥ 135.5 min for TPT with respect to the decision to operate on the victims. CONCLUSIONS: It is expected that everyone who practices medicine be equipped to handle multiple casualties. As the number of people involved in mass casualties increases, diagnostic tools, workups such as laboratory and radiological studies, and prognostic markers such as trauma scores should be simpler and more user-friendly.

Leadership, Engineering and Ethical Clashes at Boeing.

When there are disasters in our society, whether on an individual, organizational or systemic level, individuals or groups of individuals are often singled out for blame, and commonly it is assumed that the alleged culprits engaged in deliberate misdeeds. But sometimes, at least, these disasters occur not because of deliberate malfeasance, but rather because of complex organizational and systemic circumstances that result in these negative outcomes. Using the Boeing Corporation and its 737 MAX aircraft crashes as an example, this ethical analysis will examine some of the organizational problems that led to changes in management in Boeing and ultimately resulted in the fatal accidents. We will examine ethical blind spots within the company that led to the deadly accidents, and we will study the kinds of circumstances that are particularly acute in organizations such as Boeing, and which contributed to the malfunctions in the 737 MAX and the two resulting crashes. The Boeing 737 MAX example is not a singular case, but rather shares similarities with other engineering disasters such as the Challenger and Columbia explosions, and the ignition switch failures at General Motors each of which seem to have been at least partly the result of organizational shortcomings involving a compromise in commitment to safety. These parallels lead us to conclude that organizational malfeasance poses a serious ethical challenge for engineers and their organizations. We will conclude with some tentative suggestions for avoiding such tragic incidents in the future.

The reconstruction of the pilot in command murder case in the aircraft OK ADN L410 Turbolet.

The aim of this paper is to reconstruct the hijacking case of an aircraft on the Mariánské Lázně - Prague route in 1972 and the shooting of its pilot in command in light of new facts, mainly autopsy reports from both Germany and Czechoslovak Socialist Republic. These reports contained absolutely opposite findings, both in terms of the findings themselves and their resulting interpretations. Since it is still not yet known exactly what happened in the plane, a reconstruction was carried out in an identical aircraft in the Aviation Museum in Kunovice. During the reconstruction, all possible (including theoretical) situations that may have occurred in the aircraft were examined. It was found that this could not have been a premeditated intentional murder, but that the shot could only have occurred during a passenger skirmish, and one that must have resulted in a very rare situation at that. From a political-medical point of view however, there are still several questions that cannot be answered even with the best of intentions.

Trajectories of grief, depression, and posttraumatic stress in disaster-bereaved people.

BACKGROUND: Previous latent trajectory studies in adult bereaved people have identified individual differences in reactions postloss. However, prior findings may not reflect the complete picture of distress postloss, because they were focused on depression symptoms following nonviolent death. We examined trajectories of symptom-levels of persistent complex bereavement disorder (PCBD), depression, and posttraumatic stress disorder (PTSD) in a disaster-bereaved sample. We also investigated associations among these trajectories and background and loss-related factors, psychological support, and previous mental health complaints. METHODS: Latent class growth modeling was used to identify distinct trajectories of PCBD, depression, and PTSD symptoms in people who lost loved ones in a plane disaster in 2014. Participants (N = 172) completed questionnaires for PCBD, depression, and PTSD at 11, 22, 31, and 42 months postdisaster. Associations among class membership and background and loss-related variables, psychological support, and previous mental health complaints were examined using logistic regression analyses. RESULTS: Two PCBD classes emerged: mild (81.8%) and chronic (18.2%) PCBD. For both depression and PTSD, three classes emerged: mild (85.6% and 85.2%), recovered (8.2% and 4.4%), and chronic trajectory (6.2% and 10.3%). People assigned to the chronic PCBD, depression, or PTSD class were less highly educated than people assigned to the mild/recovered classes. CONCLUSIONS: This is the first latent trajectory study that offers insights in individual differences in longitudinal symptom profiles of PCBD, depression, and PTSD in bereaved people. We found support for differential trajectories and predictors across the outcomes.

Aortic Bifurcation Reconstruction after a Plane Crash.

We report the case of a 26-year-old woman who presented to the emergency room after an airplane crash. The assessment of the lesions revealed a dissection of the left common iliac artery, which was treated by reimplantation of the left common iliac artery in the right common iliac artery.

Human Factors Contributions to the Development of Standards for Displays of Unmanned Aircraft Systems in Support of Detect-and-Avoid.

OBJECTIVE: The aim is to provide a high-level synthesis of human factors research that contributed to the development of detect-and-avoid display requirements for unmanned aircraft systems (UAS). BACKGROUND: The integration of UAS into the U.S. National Airspace System is a priority under the Federal Aviation Administration's Modernization and Reform Act. For UAS to have routine access to the National Airspace System, UAS must have detect-and-avoid capabilities. One human factors challenge is to determine how to display information effectively to remote pilots for performing detect-and-avoid tasks. METHOD: A high-level review of research informing the display requirements for UAS detect-and-avoid is provided. In addition, description of the contributions of human factors researchers in the writing of the requirements is highlighted. RESULTS: Findings from human-in-the-loop simulations are used to illustrate how evidence-based guidelines and requirements were established for the display of information to assist pilots in performing detect-and-avoid. Implications for human factors are discussed. CONCLUSION: Human factors researchers and engineers made many contributions to generate the data used to justify the detect-and-avoid display requirements. Human factors researchers must continue to be involved in the development of standards to ensure that requirements are evidence-based and take into account human operator performance and human factors principles and guidelines. APPLICATION: The research presented in this paper is relevant to the design of UAS, the writing of standards and requirements, and the work in human-systems integration.

Blending Human and Machine: Feasibility of Measuring Fatigue Through the Aviation Headset.

OBJECTIVE: To determine viability of drowsiness detection, researchers study the feasibility of photoplethysmogram (PPG) data collection from the geography of the aviation headset, correlating to electrocardiogram (ECG) reference. BACKGROUND: Fatigue has been a probable cause, contributing factor, or a finding in 20% of transportation incidents and accidents studied between January 2001 and December 2012. This operational hazard is particularly troublesome within aviation and airline operations. METHOD: PPG and ECG data were collected synchronously from Federal Aviation Administration (FAA) commercially rated pilots during flight simulation in the window of circadian low (WOCL). Valid PPG and ECG data from 14 participants were analyzed, which yielded approximately 2 hr of data per participant for fatigue-related analysis. RESULTS: The results of the study demonstrate clear trends toward decreased heart rate for both ECG and PPG and suggest progression of drowsiness between four separate periods (T1, T2, T3, and T4) selected during the study; however, the mean heart rate change from T1 to T4 was statistically significant. CONCLUSION: The results suggest that ECG and PPG data can be an important tool to observe conditions where drowsiness or fatigue may add risk to the operation. In addition, the data show high correlation between ECG and PPG data, further suggesting that a simpler PPG sensor, mounted within the geography of the aviation headset, may streamline the operationalization of important physiological data. APPLICATION: Incorporation of PPG sensors and associated signal processing methods into facilitating equipment, such as the aviation headset, may add a layer to operational safety.

Responding to an Unexpected In-Flight Event: Physiological Arousal, Information Processing, and Performance.

OBJECTIVE: The study was designed to investigate whether a simulated unexpected abnormal flight event can lead to startle and explore differences in behavioral responses between expected and unexpected abnormal flight events. BACKGROUND: Recent research suggests startle (an autonomic response to an acute stimulus) following unexpected abnormal flight events can impact pilot performance and can increase the probability of a negative outcome following the event. METHOD: Information processing, physiological measures, and performance differences between responses to expected and unexpected flight events were compared. General aviation (GA) pilots flew a series of flights in a fixed-base flight simulator including two experimental flights which included an unexpected and an expected, engine failure. During the flights, heart rate, eye tracking, and flight data were recorded. RESULTS: During the unexpected engine failure, pilots showed greater increases in heart rate and pupil dilation. Significant differences in scanning were evident with fewer areas scanned following the unexpected event. During the unexpected engine failure, performance was impaired when compared to the expected events. However, poor performance was not associated with higher levels of arousal. CONCLUSION: The study provides an empirical demonstration of impaired pilot response to unexpected events with associated symptoms consistent with the induction of startle. The present research builds on Landman et al.'s conceptual model of startle and surprise. APPLICATION: Standardized training protocols may not adequately prepare pilots to deal with the unexpected effects of startle in real-world encounters. Introducing greater variety into training events may be useful. The effects of startle in disrupting well-trained responses may also occur in areas other than aviation where critical events may occur unexpectedly or present in an unfamiliar manner.