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The airport apron is a high-risk area for aircraft collisions due to its heavy operational load and high aircraft density. Currently, existing quantitative models for apron collision risk provide limited consideration and classification of risk areas. In response, this paper proposes a Petri net-based method for assessing aircraft collision risk. The method predicts the probability of aircraft reaching different areas at different times based on operational data, enabling the calculation of collision risks within the Petri net framework. This approach highlights areas with potential collision risks and provides a classification evaluation. Subsequently, aircraft path re-planning is carried out to reduce collision risks. The model simplifies the complex operations of the apron system, making the calculation process clearer. The results show that, during the mid-phase of aircraft taxiing, there is a significant deviation between the actual and ideal positions of aircraft. Areas with high taxiway occupancy are more prone to collision risks. On peak days, due to relatively high flight volumes, the frequency of collision risks is 14% higher than on regular days, with an average risk increase of 23.3%, and the risks are more concentrated. Therefore, reducing collision risks through path planning becomes more challenging. It is recommended to focus attention on areas with high taxiway occupancy during peak periods and carefully plan routes to ensure apron safety. [ABSTRACT FROM AUTHOR]

The safety of the civil aviation system has been of increasing concern with several accidents in recent years. It is urgent to put forward a precise accident prediction model, which can systematically analyze safety from the perspective of accident mechanism to enhance training accuracy. Furthermore, the predictive model is critical for stakeholders to identify risk and implement the proactive safety paradigm. In this work, to mitigate casualties and economic losses arising from aviation accidents and improve system safety, the focus is on predicting the aircraft damage severity, the injury/death severity, and the flight phases in the sequence of identifying event risk sources. This work establishes a multi-task deep convolutional neural network (MTCNN) learning framework to accomplish this goal. An innovative prediction rule will be developed to refine prediction results from two approaches: handling imbalanced classes and Bayesian optimization. By comparing the performance of the proposed multi-task model with other single-task machine learning models with ten-fold cross-validation and statistical testing, the effectiveness of the developed model in predicting aviation accident severity and flight phase is demonstrated. [ABSTRACT FROM AUTHOR]

This essay analyzes the interconnected struggles of US military occupation in Okinawa and Hawai'i through analysis of noise pollution, aircraft crashes, and community responses to these issues. While the violence of airbases transforms air into a space of violence, I turn to the ways that Okinawan and Hawaiian communities articulate their respective sovereignties through the wind. I read legal testimonies from the first noise pollution lawsuit in Okinawa and community testimonies from across O'ahu, putting them in conversation with poetry by Nakazato Yūgō and Brandy Nālani McDougall. Against military reports that implicate wind as a threat which facilitates aircraft accidents and death, the testimony and poetry elucidate how wind builds relation and enables the preservation of intergenerational memory. This archive challenges state formulations of "resolution" by elucidating how deeper histories than the state has considered press onto the body, carrying into the present not only historical wounds but also the capacity for their healing. The sovereignty of wind that they put forth marks a renewal of relationships to air and memory at the same time they are organized around radical returns of land, of night, of the body itself. [ABSTRACT FROM AUTHOR]

There is a growing risk to aircraft in flight from collisions with debris produced by the breakup of uncontrolled rocket bodies and satellites during atmospheric reentry. On one hand, the aviation industry has grown to almost 39 million flights per year, with a 63 % increase between 2004 and 2019. On the other hand, the number of successful rocket launches more than doubled between 2015 and 2023, from 87 to 212, respectively. During those 212 launches in 2023, 128 rocket bodies were abandoned in orbit, left to reenter uncontrollably. Such uncontrolled space object reentries are hard to predict, making mitigation measures difficult. In November 2022, a reentering Long March 5B rocket caused the closure of airspace over Europe, delaying 645 flights and having a plausible economic impact of millions of Euros. There are international and domestic laws that might enable the recovery of economic losses resulting from uncontrolled reentries, but such losses should not be allowed to occur in the first place. Instead of leaving the location of a reentry to chance, controlled reentries can be achieved with existing technologies and mission designs, directing reentries away from areas of high aircraft traffic. Moving to a controlled reentry regime would create a cost to space operators – but that cost is currently being externalized to the aviation industry. Multilateral solutions to create a controlled reentry regime should be pursued, as recommended in the 2023 Montreal Recommendations on Aviation Safety and Uncontrolled Space Object Reentries, before there is a tragedy caused by an aircraft collision with debris from a rocket body or satellite. • As the number of rocket launches and commercial aircraft flights increase, the probability of a catastrophic collision between an aircraft and reentering space debris is also growing. • Technologies and mission designs exist to enable all rocket bodies to be returned to Earth in a controlled manner, eliminating the casualty risk. • From a broad economic perspective, space companies are externalizing some of their risks and costs and imposing them on the aviation industry. • States are liable for damage caused by reentering space objects and could be liable for the economic costs caused by precautionary airspace closures. • The 2023 Montreal Recommendations offer actionable steps to reduce the risk of collisions between space debris and aircraft. [ABSTRACT FROM AUTHOR]

This article examines the films "Sully" and "Flight" and their portrayal of prevailing ideologies. Released during Barack Obama's presidency, both films focus on skilled pilots rather than passengers. "Sully" presents a white male hero who opposes regulation, while "Flight" features an African American antihero who finds redemption in jail. Both films affirm mainstream ideologies of individualism and redemption, while also highlighting the challenges and contradictions within the United States. The article argues that both films ultimately reinforce American nationalism and fail to address the social and political realities of their time. [Extracted from the article]

The case study on Airblue chronicles the events that led to the biggest plane crash in the aviation history of Pakistan. Airblue flight 202 destined from Karachi to Islamabad crashed while attempting to land under adverse weather conditions. The flight carried 146 passengers and 6 crew members; all died in the crash. Later investigations identified gross errors in judgment and decision making by the cockpit crew and unprofessional attitude as the sole cause of the crash. The case study documents the events that unfolded prior to the crash and identifies a number of major factors that are important while communicating and making decisions under critical situations. It touches upon the themes of superior-subordinate communication and relationships, empowerment, sense of responsibility under life-threatening situations, making sense of crises, the role of initiative, self-confidence, and reliance on others. The case is suitable to be taught on topics dealing with communication, decision making, teamwork, and leadership in crises, at the graduate level (MBA) and in executive training courses on team building, leadership and crisis management. It highlights the situations which emerge as crises and where teamwork is paramount for the effective achievement of goals. Furthermore, it focuses on the possible relapses when effective teamwork and communication are not in play. [ABSTRACT FROM AUTHOR]

The popularity of ultralight planes in non-commercial aviation is on the rise; however, non-compliance with regulations and the use of faulty equipment poses significant risks. This study explores the consequences of such lapses in adherence to safety standards by thoroughly examining the conditions leading to an ultralight plane crash, focusing on data related to causative factors. The accident involved an unregistered ultralight aircraft, lacking proper inspection and the required license. The pilot's error during takeoff led to a stall, resulting in a fatal crash. Upon impact with the ground, the pilot's shoulder and lap belts were torn off, leading to immediate death. This case underscores the critical importance of compliance with safety regulations in ultralight aviation. The findings illuminate the dire consequences of non-compliance with safety regulations and the utilization of unregistered, uninspected ultralight aircraft in private aviation. The tragic accident analyzed herein underscores the pivotal role of adherence to safety standards in mitigating the risks associated with ultralight planes. The pilot's fatal error during takeoff, compounded by the absence of proper inspection and licensing, serves as a stark reminder of the potential dangers inherent in neglecting established safety protocols. [ABSTRACT FROM AUTHOR]

Background. Civil aviation comprises airlines/charters and general aviation (GA). Currently, airlines are experiencing a pilot shortage, partly reflecting scheduled retirements mandatory for airline (but not GA) pilots aged 65 years, fueling a debate as to whether the retirement age should be increased. Herein, using 16–40 years-of-age aviators as a reference, we determined whether GA pilots aged 60+ years (i) incurred an elevated accident rate, employing, for the first time, age-tiered flight time as a measure of risk exposure and (ii) carried an excess risk for cognitive deficiency-related fatal accidents. Methods. Airplane accidents (2002–2016) involving Class 3 medical certificated pilots were per the National Transportation Safety Board (NTSB) databases. Age-tiered pilot risk exposure represented a summation of flight hours per Class 3 medical applications. Cognitive decline measures were per NTSB field codes. Statistical analyses employed Chi-Square, Mann–Whitney, logistic regression, and binomial tests. Results. Using flight hours as the denominator, the fatal accident rate for older pilots (41–80 years) was unchanged compared with aviators aged 16–40 years. In the logistic regression, no cognitive deficiency measure was predictive (p = 0.11, p = 0.15) for pilots aged 61+ years who were involved in fatal accidents. Conclusion. These findings question the necessity of an automatic disqualification of air transport pilots at 65 years of age. [ABSTRACT FROM AUTHOR]

INTRODUCTION: The European Air Transport Command (EAT C) is a seven-nation integrated command. One of its core capabilities is strategic aeromedical evacuation (AE). During the global COVID-19 pandemic and Ukrainian crisis, EAT C proved that acting in concert is a valuable, effective, and reliable option. METHODS: By pooling and sharing aircraft and personnel, EAT C has privileged access to a diverse fleet and pool of experts. Cooperation is based on a common set of rules and regulations, which ensures that EAT C can address any problem with expertise. RESULTS: During the COVID-19 pandemic, 1060 COVID-19-positive patients were transported in 198 missions, with neither death nor disease transmission reported during those strategic AE flights. EAT C transferred 986 military cases, mostly routine priority (91.4%); the other 74 cases were civilians, who were transported in 17 missions, with 81.1% categorized as urgent. During the Ukrainian crisis, 251 patients were transported, 112 military and 139 civilians, including 30 children. Among the recorded injuries were cerebrocranial, abdominal, and chest injuries, as well as fractures (180) and amputations (48) of the extremities. DISCUSSION: EAT C is recognized as a center of expertise within the AE community, where interoperability and harmonization of concepts are key to safety and success. Cross-national missions, where a patient is evacuated by an aircraft and medical crew provided by another nation, offer maximum flexibility. Complex situations, such as the COVID-19 pandemic and the Ukrainian crisis, have shown that multinational cooperation is not only achievable but also provides robust, effective, and reliable solutions for AE in particular. [ABSTRACT FROM AUTHOR]

This paper investigates the usage of a systemic neutralized taxonomy for understanding human factors to foster a restorative culture when studying adverse events. The available studies supporting accident analysis from a system‐theoretic perspective with human factors‐based methods are grounded on error taxonomies and do not reinforce the non‐judgemental dimension that is encouraged by modern safety science. We propose a methodology to integrate the system‐theoretic accident analysis technique, Causal Analysis based on System Theory, with a neutralized taxonomy of human explanatory factors. The proposed methodology has been applied to an aviation accident involving a military aircraft and a glider. This case revealed various critical interactions among system components, which require dedicated safety recommendations that go beyond the identification of single points of failures and root causes, leading to a deeper understanding of socio‐technical orchestrations. Despite the use case in aviation, the proposed methodology remains suitable for various types of safety occurrences in diverse domains and industrial settings. It also represents the basis for supporting future proactive safety‐related decision‐making processes. [ABSTRACT FROM AUTHOR]

This study proposes a probabilistic model to assess the likelihood of passenger survival in fires resulting from aircraft accidents. The model evaluates the risk of passenger death in a fire, considering the type of aircraft and airline. By comparing the time available for passengers to fully evacuate a burning plane with the time required for evacuation using modern means and technologies, onboard rescue equipment, and the qualifications of crew members and rescue personnel, we introduce a comprehensive approach to quantify passenger survival rates. Additionally, the concept of the hazard coefficient is introduced, which accounts for factors such as cabin temperature and toxic components. [ABSTRACT FROM AUTHOR]

This article provides an overview of the mental health challenges faced by pilots and air traffic controllers (ATCs), whose stressful professional lives may negatively impact global flight safety and security. The adverse effects of mental health disorders on their flight performance pose a particular safety risk, especially in sudden unexpected startle situations. Therefore, the early detection, prediction and prevention of mental health deterioration in pilots and ATCs, particularly among those at high risk, are crucial to minimize potential air crash incidents caused by human factors. Recent research in artificial intelligence (AI) demonstrates the potential of machine and deep learning, edge and cloud computing, virtual reality and wearable multimodal physiological sensors for monitoring and predicting mental health disorders. Longitudinal monitoring and analysis of pilots' and ATCs physiological, cognitive and behavioral states could help predict individuals at risk of undisclosed or emerging mental health disorders. Utilizing AI tools and methodologies to identify and select these individuals for preventive mental health training and interventions could be a promising and effective approach to preventing potential air crash accidents attributed to human factors and related mental health problems. Based on these insights, the article advocates for the design of a multidisciplinary mental healthcare ecosystem in modern aviation using AI tools and technologies, to foster more efficient and effective mental health management, thereby enhancing flight safety and security standards. This proposed ecosystem requires the collaboration of multidisciplinary experts, including psychologists, neuroscientists, physiologists, psychiatrists, etc. to address these challenges in modern aviation. [ABSTRACT FROM AUTHOR]

Airports can be attractive places for fauna to find food resources, especially for large birds, which can cause severe collisions with aircraft. At many Brazilian airports, the Crested Caracara (Caracara plancus) is considered a problem due to the high rates of collisions and sightings in risk areas. Therefore, strategies to manage the species at airports are needed. We use an airport located in Central Brazil as a model system to evaluate the density and space-time distribution of Crested Caracara at the airport and in nearby regions. We studied the fortnightly temporal distribution and density of Crested Caracara in five different areas throughout one year, including the airport. Using circular statistics, we found that the spatiotemporal distribution was uneven throughout the year in all observed areas, with sightings peaking at different times. The airport's distribution differed from three out of four other areas. The density was higher in the region farthest from the city center. In the airport, the density was one of the lowest. The difference between density and temporal distribution patterns can be explained by the species' foraging dynamics, which shift according to the availability and abundance of resources, which vary randomly over time in the urban landscape. Our research is the first to evaluate the temporal distribution of problematic bird species in airports and their surroundings. The results can contribute to management plans to mitigate the risk imposed by fauna. [ABSTRACT FROM AUTHOR]

Fatal aviation accidents are a critical concern for armed forces, necessitating precise toxicological analysis of postmortem blood samples. This paper introduces a novel spectrophotometric method for quantifying cyanide in blood samples with an aim to aid in aircraft accident reconstruction in the future. Blood samples were collected from healthy non-smokers aged 20–45 years, excluding individuals with hepatic impairment, or those using drugs affecting blood cyanide levels. The spectrophotometric method involved cyanide adsorption in a sodium hydroxide solution using microdiffusion discs and chemical reactions resulting in a pinkish-purple end product. The optimal absorption wavelength (λ max) was determined, and the lower limits of detection and quantitation were established. The method underwent validation for precision, sensitivity, specificity, linearity, and accuracy. The procedure yielded a pinkish-purple compound with an optimal absorption wavelength (λ max) of 531 nm. The established limits of detection (LoD) and quantitation (LoQ) were 0.0625 μg/ml and 0.125 μg/ml, respectively. The method demonstrated strong linearity up to cyanide concentrations of 4 μg/ml. It exhibited a sensitivity of 99.7% and accuracy of 85.92%. The intraday and inter-day precision were determined as 9.04% and 4.27%, respectively. The method was highly specific, showing no interference with blanks at the peak wavelength with a working range of 0.125–4 μg/ml. The study describes developing and validating a sensitive method for quantitatively estimating cyanide in blood samples. Incorporating this method into the existing postmortem toxicological sample collection and investigation protocol will enhance the analysis capabilities and improve aircraft accident investigation outcomes within the country. [ABSTRACT FROM AUTHOR]

Air traffic controllers' mental workload significantly impacts their operational efficiency and safety. Detecting their mental workload rapidly and accurately is crucial for preventing aviation accidents. This study introduces a mental workload detection model for controllers based on power spectrum features related to gamma waves. The model selects the feature with the highest classification accuracy, β + θ + α + γ, and utilizes the mRMR (Max-Relevance and Min-Redundancy) algorithm for channel selection. Furthermore, the channels that were less affected by ICA processing were identified, and the reliability of this result was demonstrated by artifact analysis brought about by EMG, ECG, etc. Finally, a model for rapid mental workload detection for controllers was developed and the detection rate for the 34 subjects reached 1, and the accuracy for the remaining subjects was as low as 0.986. In conclusion, we validated the usability of the mRMR algorithm in channel selection and proposed a rapid method for detecting mental workload in air traffic controllers using only three EEG channels. By reducing the number of EEG channels and shortening the data processing time, this approach simplifies equipment application and maintains detection accuracy, enhancing practical usability. [ABSTRACT FROM AUTHOR]

Clear‐Air Turbulence (CAT) is associated with wind shear in the vicinity of jet streams in upper atmospheric levels. This turbulence occurs in cloudless regions and causes most weather‐related aircraft accidents. Recent studies have shown that in response to climate change, CAT could significantly increase over certain regions as a consequence of strengthening of jet streams. In this study we use several atmospheric reanalyses and coupled model experiments database to evaluate CAT recent and future changes in the Northern Hemisphere. Several CAT diagnostics are computed to assess the sensitivity of the results to different turbulence representations. A significant positive trend in CAT frequency is found in the reanalyses in different Northern Hemisphere regions over the period 1980–2021. The signal‐to‐noise analysis shows that over North Africa, East Asia and Middle East the increase of CAT occurrence in the last decades is likely attributed to the response to anthropogenic forcing. In contrast, over the North Atlantic and North Pacific the response to external forcing is not detectable due to a weak signal to noise ratio related to large internal variability. Future climate projections show that over several Northern Hemisphere regions, CAT is projected to increase with a high model agreement and independently of the CAT diagnostic used. The largest increase in CAT is projected to occur over East Asia. In the North Atlantic, large uncertainty remains due to lack of model agreement and different results between the various CAT diagnostics. Plain Language Summary: Aircrafts in flight can be subject to Clear‐Air Turbulence (CAT), which is defined as all turbulence that occurs in the atmosphere away from a visible convective activity, and which is particularly difficult to detect by pilots and using on‐board radar. CAT can injure passengers and flight attendants, cause structural damage to planes and induce considerable economic loss. In this study we use several atmospheric reanalyses and coupled model experiments database to evaluate CAT recent and future changes in the Northern Hemisphere. We also compute several CAT diagnostics to evaluate the sensitivity of results to different turbulence representations. Our results show that over several regions in the Northern Hemisphere, in particular East Asia, positive CAT trends are found as a consequence of anthropogenic forcing, indicating that the response of CAT to global warming can be already detectable in the recent decades. Positive trends in CAT frequency are projected to increase for different global warming levels over these regions at aircraft cruising altitudes. Nevertheless, over the North Atlantic region there are still many uncertainties in the response of climate models and also in CAT diagnostics used. The changes in CAT described in this study could have important consequences for aviation safety. Key Points: Atmospheric reanalyses show increases in the frequency of Clear‐Air Turbulence (CAT) in recent decades over several regionsThe increases over some of these regions is attributable to external forcingCAT frequency is projected to increase in the future over East Asia, Middle East, North Africa, North Pacific and North America [ABSTRACT FROM AUTHOR]

Purpose: The research aimed to verify the usefulness of selected subjective methods of task load assessment for evaluating task load in general aviation organizations and forecasting preflight load. The study also highlighted the importance of the pilot's task load in the context of flight safety. Design/methodology/approach: The study included a comprehensive literature review to present the specifics of general aviation organization and the role of the human factor in aviation accidents. The research discussed the division of task load methods and characterized four selected subjective task load methods (NASA-TLX, SWAT, ISA, Bedford Scale). Expert assessments were conducted to evaluate these methods' effectiveness from the perspective of post-flight load assessment and pre-flight load prediction, considering the feasibility of implementation in general aviation organizations. Findings: The findings emphasized the need to develop a dedicated method for predicting task load before a flight. The study concluded that the methods used should be simple and require minimal financial outlay, considering the specificity of general aviation organizations. Research limitations/implications: Future research should focus on developing a dedicated pre-flight task load prediction method tailored to the unique requirements of general aviation. Identified limitations include the need for further validation of the subjective methods in different organizational contexts. Practical implications: The research suggests that implementing simple and cost-effective task load assessment methods can enhance flight safety in general aviation. The development of a specialized pre-flight load prediction tool could significantly improve operational planning and pilot performance. Social implications: By improving task load assessment and prediction in general aviation, the research can contribute to enhanced flight safety, thereby potentially reducing accident rates and improving public trust in aviation safety measures. Originality/value: This paper contributes to the field by addressing the gap in pre-flight task load prediction in general aviation. It provides valuable insights for aviation safety researchers, practitioners, and policymakers interested in optimizing pilot performance and ensuring flight safety. [ABSTRACT FROM AUTHOR]

In the aftermath of the Germanwings crash in 2015, several regulations have been instituted around pilots' mental health issues and flight safety. One of these (CAT.GEN.MPA.215) stipulates that European operators are to implement a Peer Support Program to encourage pilots' self-referral of mental health issues and identify mental wellbeing issues as early as possible. However, knowledge is scarce regarding how effective these programs are on a range of outcomes. This systematic review aimed to identify articles investigating peer support programs and their effectiveness in preventing and detecting mental health issues, in commercial aviation and other high-risk organizations. A systematic search was performed in three databases, following the structure of the PRISMA guidelines. All articles (2.123) were exported to Rayyan Citation, where the screening process was performed. Four articles met the final inclusion criteria. Overall, the search revealed little empirical evidence of the effectiveness of peer support in detecting and preventing mental health. Although there is limited or no evidence in any direction, the peer support programs seem to be without evident harm and were generally appreciated. The insufficient empirical evidence is nonetheless concerning, with these programs being implemented throughout Europe in such a high-risk context as the aviation industry. The results highlight the importance of more research on peer support in aviation. [ABSTRACT FROM AUTHOR]

To conduct the Turkish adaptation of the Flight Anxiety Situations Questionnaire (FAS) and the Flight Anxiety Modality Questionnaire (FAM). The FAS measures the anxiety levels in different flight situations, while FAM assesses the somatic and cognitive symptoms of anxiety or anticipatory anxiety in different flight situations. The FAS and the FAM have been adapted to different cultures and used in different studies. 645 adults from different regions of Turkey participated in this study (Mage = 25.58, SDage = 10.43, 59.2% women). A Socio-demographic Information Form, the Visual Analog Flight Anxiety Scale (VAFAS), the FAS, the FAM and the State-Trait Anxiety Inventory (STAI) were used for data collection. Exploratory factor analysis showed that the Turkish forms of the FAS and the FAM had similar factor structures to the original forms. The FAS consisted of three factors and the FAM consisted of two factors with factor loadings between.56 and.85. High Cronbach's alpha scores (.78–.97) of the FAS, the FAM and their subscales supported internal consistency reliability. Convergent and discriminant validity of the scales were supported with correlation analysis and independent samples t-test. The Turkish forms of the FAS and the FAM provided psychometrically sound self-report measures of flight anxiety. It is thought that these measures will be useful in clinical assessments, interventions and future cross-cultural research about flight anxiety in the Turkish community. [ABSTRACT FROM AUTHOR]

Ice formation on aircraft surfaces poses significant safety risks, and current detection systems often struggle to provide accurate, real-time predictions. This paper presents the development and comprehensive evaluation of a smart ice control system using a suite of machine learning models. The system utilizes various sensors to detect temperature anomalies and signal potential ice formation. We trained and tested supervised learning models (Logistic Regression, Support Vector Machine, and Random Forest), unsupervised learning models (K-Means Clustering), and neural networks (Multilayer Perceptron) to predict and identify ice formation patterns. The experimental results demonstrate that our smart system, driven by machine learning, accurately predicts ice formation in real time, optimizes deicing processes, and enhances safety while reducing power consumption. This solution holds the potential for improving ice detection accuracy in aviation and other critical industries requiring robust predictive maintenance. [ABSTRACT FROM AUTHOR]

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The vertical deviation is one of the important stages in commercial aircraft flights because indications of malfunction can be detected faster by the pilot rather than in other flight phases. The purpose of this study is to investigate whether the PK-LQP airplane experienced unusual altitude movements during the vertical deviation phase since the airplane taking off from Seattle (Boeing Manufacture's home base) until the airplane crash. The airplane, which is of the type B737 MAX8, had operated for 83 days, during which it completed 438 flights using a total of 107 flight codes, and it travelled to 36 airports. According to the findings of an investigation of the data, we found that only 69 (39%) were included in tier 1, which had an ADS-B data update interval message below 10 seconds, complying with ICAO and FAA-AVN standards. With this class 1 and tier 1 dataset, we conducted an EDA to find the data insight, which revealed that there was a disturbance in the speed and altitude indications on the airplane instrumentation, causing a misperception for the pilot and causing the airplane to drastically drop in altitude (more than 100 feet). [ABSTRACT FROM AUTHOR]

The industry has been significantly enhanced by recent developments in UAV collision avoidance systems. They made collision avoidance controllers for self-driving drones both affordable and hazardous. These low-maintenance, portable devices provide continuous monitoring in near-real time. It is inaccurate due to the fact that collision avoidance controllers necessitate trade-offs regarding data reliability. Collision avoidance control research is expanding significantly and is disseminated through publications, initiatives, and grey literature. This paper provides a concise overview of the most recent research on the development of autonomous vehicle collision avoidance systems from 2017 to 2024. In this paper, the state-of-the-art collision avoidance system used in drone systems, the capabilities of the sensors used, and the distinctions between each type of drone are discussed. The pros and cons of current approaches are analyzed using seven metrics: complexity, communication dependency, pre-mission planning, resilience, 3D compatibility, real-time performance, and escape trajectories. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Comparative Politics is the property of Journal of Comparative Politics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Hazards threaten railway safety by their potential to trigger railway accidents, resulting in significant costs and impacting the public's willingness to use railways. Whilst many prior works investigate railway hazards, few offer a holistic view of hazards across jurisdictions and time because the large number of primary sources make synthesising such learnings time consuming and potentially incomplete. The conceptual framework HazardMap is developed to overcome this gap, employing open-sourced Natural Language Processing topic modelling for the automated analysis of textual data from Rail Accident Investigation Branch (RAIB), Australian Transport Safety Bureau (ATSB), National Transportation Safety Board (NTSB) and Transportation Safety Board of Canada (TSB) railway accident reports. The topic modelling depicts the relationships between hazards, railway accidents and investigator recommendations and is further extended and integrated with the existing risk theory and epidemiological accident models. The results allow the different aspects of each hazard to be listed along with the potential combinations of hazards that could trigger railway accidents. Better understanding of the aspects of individual hazards and the relationships between hazards and previous accidents can inform more effective hazard mitigation policies including technical or regulatory interventions. A case study of the risk at level crossings is provided to illustrate how HazardMap works with real-world data. This demonstrates a high degree of coverage within the existing risk management system, indicating the capability to better inform policymaking for managing risks. The primary contributions of the framework proposed are to enable a large amount of knowledge accumulated to be summarised for an intuitive policymaking process, and to allow other railway investigators to leverage lessons learnt across jurisdictions and time with limited human intervention. Future research could apply the technique to road, aviation or maritime accidents. • A framework HazardMap is developed for mapping hazards in the railway system. • A case study of the risk at level crossing is implemented. • Opportunities for practitioners in learning across jurisdiction and time. • Enabling knowledge accumulated to be summarised for policymaking process. [ABSTRACT FROM AUTHOR]

To reveal complex causes of aircraft events, this paper aims to mine association rules between the trigger probability and relative strength via a modified Apriori algorithm. Clustering is adopted for data preprocessing and TF–IDF value calculation. Causative item sets of aircraft events are obtained based on the accident causation 2–4 model and are coded to establish code indicators. By avoiding the use of statistical methodologies to resolve not-a-number (NaN) values for altering the interrelations among causes, an enhancement in the Apriori algorithm is proposed by considering frequent items. By extracting frequent patterns, in this paper, all the association rules that satisfy three perspectives (support, confidence and lift) are determined by constantly generating and pruning candidate item sets. A network graph is used to visualize the association rules between different unsafe events and all types of causes. Finally, 9835 representative pieces of data, including general unsafe events, general incidents and serious incidents from the Southwest Air Traffic Management Bureau, are selected for analysis. The results show that improper energy allocation, poor conflict resolution ability, inadequate onsite management duties, adoption of a luck mentality, and occurrence of controller oversight are highly correlated with general unsafe events, and failure to rectify incorrect recitation is notably correlated with general incidents, while inadequate manual promotion, lack of conflict judgement and insufficient safety management are strongly correlated with serious incidents. This study quantitatively reveals the potential patterns and characteristics of mutual interactions among various types of historical aircraft events and highlights directions for controllable prevention and prediction of aircraft events. [ABSTRACT FROM AUTHOR]

Most of the existing literature on crisis communication focuses on the crisis response immediately following a crisis. There is a dearth of research examining postcrisis communication efforts. Postcrisis communication is especially important in the context of tragic crises, which leave stakeholders deeply affected and traumatized. This paper examines the multifaceted nature of memorials and their significance in postcrisis communication. Using the 2015 Germanwings crash as an illustrative case study, the paper highlights how memorials serve as artifacts of grief, remembrance and celebration of life. Postcrisis communication that centres on victim needs is a keystone to better crisis management. Moreover, I argue that postcrisis communication should facilitate healing by serving the needs of victims, which supersede those of organizations. The paper examines the notions of victim‐centred crisis communication and ethics of care by looking at memorials as artefacts of postcrisis communication. [ABSTRACT FROM AUTHOR]

Over 8000 weather-related aviation accidents in the USA from 2000 to 2020 are investigated, in order to find possible connections between atmospheric instability and severe aviation accidents – defined here as events that recorded serious or fatal injuries. We use the bootstrapped median values for multiple meteorological parameters extracted from North America Regional climate reanalysis for each accident cause. To check the possibility of predicting severe accidents, we applied a logistic regression model containing several meteorological variables as predictands. Results show that approximately 67% of the weather-related severe aviation accidents can be explained by meteorological parameters like relative humidity, temperature, visibility or total cloud fraction. The monthly frequency of weather-related accidents shows a 6-months peak, corresponding to the peak of the convective season in North America. Older pilots (> 60 years) are more likely to be involved in a severe accident during adverse weather, while flight experience seems less relevant. Our study aims to better understand which meteorological variables are more significant in the outcome of severe aviation accidents during adverse meteorological conditions, and to investigate the roles of age and experience in pilots' response during extreme weather. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Anbar University for Law & Political Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Safety in General Aviation has been a continuous concern. About 12% of all airplane accidents in General Aviation involve nose-overs and nose-down events. A total of 134 accidents reported by the National Transportation Safety Board that include nose-overs and nose-downs were analyzed for their main causes. It was found that 35% of the defining events involved a loss of control on the ground while 58% of the total dataset involved tailwheel-type aircraft. A relatively high proportion of aircraft built before 1950 were found, which are also aircraft that have tailwheel-type landing gear, and thereby a higher propensity for ground loops and nose-overs. It is shown that the high accident rate in General Aviation, especially for accidents that did not result in a fatality, was, to an important extent, explained by tailwheel and older aircraft in the US General Aviation airplane fleet struggling with controlling the aircraft on the ground. Attention to this group of aircraft in future studies may help to more effectively address the relatively high accident rates in General Aviation. [ABSTRACT FROM AUTHOR]

INTRODUCTION: A gricultural aircraft operations are associated with unique challenges. In particular, these include maintaining awareness of obstacles associated with flight at very low altitudes. Wire strikes are a common cause of accidents in these operations. METHODS: Focus groups were completed during the 2022 Ag Aviation Expo hosted by the National Agricultural Aviation Association with pilots who had experienced wire-strike events (N = 22). The researchers coded the transcripts using a human factors framework. RESULTS: Notably, unplanned "trim passes" were a key stage of flight during wire-strike events. Cognitive risk factors that may have affected their performance included situation awareness, decision-making choices, and pressure to perform. Over half of subjects reported being aware of the wire before collision. Possible prevention strategies include not spraying the field due to safety risks, paying better attention to where they were in the field, and avoiding deviation from the planned route. DISCUSSION: Wire-strike events often occur due to momentary lapses in attention, even when the pilot is already aware of the wire. This study shows that targeted approaches to prevent wire strikes in agricultural aviation operations require addressing a number of cognitive risks and human factors, rather than implementing increased preflight surveillance. These results have implications for preventing future wire-strike accidents based directly on pilot perceptions, both within agricultural operations and general aviation more broadly. [ABSTRACT FROM AUTHOR]

This study investigates the impact of wind shear on the flight dynamics of commercial aircraft where C* and C*U control laws are employed during the approach phase. Given the high incidence of flight accidents during takeoff and landing attributed to wind shear, this research aims to enhance aviation safety by analyzing control law behavior under varying wind shear conditions. A nonlinear flight simulation model was developed, utilizing aerodynamic and engine data from a B737, to explore the aircraft's response to different wind shear intensities. The simulation analysis was used to compare the response of the aircraft with C* and C*U controllers, respectively, under different wind shear, and to evaluate the effectiveness of its stability enhancement in wind shear. It was found that in most cases, the controller can achieve a good stabilization effect, but in some cases of wind fields, the aircraft suffered more significant oscillation. [ABSTRACT FROM AUTHOR]

Results are presented from the Rum Creek fire during the California Fire Dynamics Experiment (CalFiDE). An instrumented payload aboard the NOAA Twin Otter (TO) aircraft, which included a scanning micro‐pulsed Doppler lidar (DL) and in situ chemistry packages, was used to address the evolution of a buoyant plume jet (BPJ) and transport dynamics over the southwest corner of the fire between 09/01/2022 and 09/02/2022. An approach previously developed to isolate updrafts was modified to account for the Gaussian core structure when addressing the evolution of the updraft, plume‐top entrainment, lateral entrainment, and the role of fire‐atmosphere interactions on the characteristics of the BPJ during four overpasses. A persistent cross‐valley flow leading up to the BPJ was observed for all four overpasses, with flow enhancement during the second overpass that coincided with changes in the BPJ structure and turbulence characteristics surrounding the BPJ. Length scales and entrainment rates were estimated at the lateral edges and the top of the plume. In the case of the latter, an analytical form of the BPJ profile above the vertical velocity maximum of the updraft was derived using a simplified form of the vertical momentum equation following a partial budget analysis that accounted for plume‐top entrainment and the boundary layer (BL) inversion. Velocity core strength and characteristics were analyzed away from the updraft with similar relationships between depth‐to‐widths of velocity cores found in a forthcoming study focused on wildfire plumes. Plain Language Summary: The goal of the California Fire Dynamics Experiment (CalFiDE) during the fall of 2022 was to survey wildfire dynamics and impacts on air quality over areas historically affected by wildfires. The Rum Creek fire, which occurred west of Medford, Oregon, was one of several fires observed using data collected aboard the NOAA Twin Otter (TO) aircraft. In this study, we focused on a smoke plume at the southwest corner of the fire that featured strong upward motion. Multiple flyovers of this plume led to an analysis of how the plume changed with time, and how the conditions surrounding the plume supported its development. The work presented details the internal structure of the plume and the influence of background winds on the evolution of the plume, which has implications for understanding the transport of smoke away from the fire. Key Points: Airborne Doppler lidars are capable of resolving small scale dynamics over short distances spanning the width of the firelineComplex interactions between fire‐induced updrafts and the surrounding atmosphere can lead to non‐ideal representation of the updraft profileTerrain and fire‐modified winds are important for updraft evolution and transport dynamics [ABSTRACT FROM AUTHOR]