Flight Incident Research Articles

Explaining a collective false alarm: Context and cognition in the Oxford Street crowd flight incident

Explaining a collective false alarm: Context and cognition in the Oxford Street crowd flight incident

The role of foreign aid in the nexus between capital flight and unemployment in sub-Saharan Africa

PurposeThis study assesses the relevance of foreign aid to the incidence of capital flight and unemployment in 20 countries in sub-Saharan Africa.Design/methodology/approachThe study is for the period 1996–2018, and the empirical evidence is based on interactive quantile regressions in order to assess the nexuses throughout the conditional distribution of the unemployment outcome variable.FindingsFrom the findings, capital flight has a positive unconditional incidence on unemployment, while foreign aid dampens the underlying positive unconditional nexus. Moreover, in order for the positive incidence of capital flight to be completely dampened, foreign aid thresholds of 2.230 and 3.964 (% of GDP) are needed at the 10th and 25th quantiles, respectively, of the conditional distribution of unemployment. It follows that the relevance of foreign aid in crowding out the unfavourable incidence of capital flight on unemployment is significantly apparent only in the lowest quantiles or countries with below-median levels of unemployment. The policy implications are discussed.Originality/valueThe study complements the extant literature by assessing the importance of development assistance in how capital flight affects unemployment in sub-Saharan Africa.

Toward safer aviation: Application of GA-XGBoost-SHAP for incident cognition and model explainability

Flight incidents are characterized by complex mechanisms, leading to poor prediction model robustness and explainability. Based on the full-dimensional description of flight incidents, the explainable module is added to the prediction model to achieve its accuracy, stability, and explainability. Firstly, imbalance processing is performed employing the sampling method, and a genetic algorithm (GA) is applied for feature selection; these results are then considered as prediction model input. Secondly, an extreme gradient boosting algorithm (XGBoost)-based incident severity prediction model is established with five categories of none, minor, serious, fatal, and total as prediction labels; real data is used for validation, and the model shows good robustness and superiority. Finally, the SHapley Additive exPlanation (SHAP) is introduced to explain the correlation between incidents severity and input features and to measure feature importance. The results show that the proposed method has higher prediction accuracy and robustness. Which can provide some decision-making reference for aviation operation management departments to emergencies, learn the deep-seated law of incidents, and promote the paradigm of active safety management.

MPACT OF WEATHER CONDITIONS ON FLIGHTS AND AIRCRAFT

Examine the effects of three phases of flight—takeoff and climb, enroute, descent, and landing and five different forms of unfavorable weather—fog, wind shear, thunderstorm, icing, and snow on aircraft operations and accidents. Methods: collect statistically up-to-date data and compare the data to estimate the impact of the various meteorological conditions on flights and the dangers of flight incidents. Use EJM to establish expert systems to report the impact of various weather conditions on flights. Results: evaluate the impact of weather events on flights and the necessity of prevention systems. Discussion: define the need of advanced numerical modeling techniques of time in Air Traffic Management systems.

Evaluasi Pemanfaatan Teknologi Radar Dalam Rangka Penguatan Pertahanan Dan Kedaulatan Wilayah Udara Indonesia

One source of national wealth is airspace. There is a lot of potential in the airspace, including defense and commercial potential. However, the management of airspace in Indonesia is still not optimal. This can be analyzed from airspace issues related to the Indonesian FIR area on the border of the Natuna Islands. There is still overlap with the neighborhod country, Singapore, regarding the authority to control, use and regulate the Fligt Information Region (FIR) which could impact security and air defense if not resolved immediately. That's why this article presents insights through the literacy method regarding evaluating the use of radar technology to strengthen the defense and sovereignty of Indonesia's airspace. The evaluation was carried out in terms of the hazard related to the threat of jamming issues and flight incidents that occurred. Next, analyze the vulnerabilities related to the characteristics of the FIR and the distribution of radar capabilities. The last evaluation is related to capacity starting from the budget, policies, human resources to the infrastructure owned by air defense in Indonesia. So that from the elaboration of the evaluation it is hoped that it can become one of the inputs and insights to increase the usefulness of radar in order to strengthen defense and fully acquire the sovereignty of Indonesia's airspace.

ИСПОЛЬЗОВАНИЕ МОДУЛЯЦИИ LORA В СРЕДСТВАХ РАДИОСВЯЗИ, НАВИГАЦИИ И НАБЛЮДЕНИЯ ДЛЯ РЕШЕНИЯ ЗАДАЧ УПРАВЛЕНИЯ ВОЗДУШНЫМ ДВИЖЕНИЕМ

The paper considers the use of LoRa technology in the data transfer system for performing aircraft position-fixing by means of the network of multilateration ground stations. The urgency of the problem is that the methods used for transferring data do not meet the requirements for safety and security of the transmitted information so such systems are not protected against unauthorized access. The information transmitted is strategically important for performing air traffic management tasks on the territory of the Russian Federation. Unauthorized access can result in intercepting and spoofing the coordinate information of aircraft location. This is possible only in exceptional circumstances which lead to reduction in flight safety and transition of flight incidents to flight accidents. The security of transmitted information can be improved by applying noise-like signals which ensure better security indexes of transmitted signals and possess higher jamming resistance. A new LoRa technology of transferring data is widespread nowadays. The technology is based on the linear frequency modulation which has been used in radar systems for several decades. The paper presents the algorithm of operating the multilateration data transfer system and its hardware-in-the-loop simulation implemented as a virtual device.

Safety Control Design With Flight Envelope Protection and Reference Command Generation

When confronting different levels of aircraft actuator faults, a safety control system without considering the postfault performance degradation raises the probability of flight incidents. This article presents a safety control scheme against actuator malfunctions, on the basis of flight envelope protection and reference command regeneration. First, with respect to a high-fidelity aircraft model, a flight envelope estimation method is developed to respect to the state limits of postfault aircraft (i.e., trim and maneuvering envelopes). Simultaneously, in an attempt to alleviate the burden of the damaged actuators, a degraded reference command is online regenerated, thus, maintaining the closed-loop aircraft within the safe flight envelope. Second, a sliding mode control scheme with the integration of a prescribed performance function is proposed to track the degraded reference command. When comparing to the existing control schemes, the gap between safety control and reference command regeneration is bridged to ameliorate practical flight safety. Finally, comparative simulation studies, based on the high-fidelity Boeing 747 longitudinal model, are conducted to examine the effectiveness of the proposed scheme.

External debt and economic growth in selected sub-Saharan African countries: The role of capital flight

The paper estimate an augmented endogenous economic growth model to investigates the extent to which capital flight affects the impact of external debt on economic growth in selected sub-Saharan African countries. The estimations was done with the aid of a dynamic system generalized method of moments technique with data from 2000 to 2015. The direct impact of both capital flight and external debt as well as their combined effect on economic growth was found to be negative and statistically significant. Additionally, the marginal effects results show that a low level of capital flight has no noticeable effect on the negative impact of external debt on economic growth. In contrast, a high incidence of capital flight exacerbates the negative impact of external debt on economic growth. Based on the findings, we conclude that efforts to promote efficient external debt management should focus on reducing capital flight in sub-Saharan African.

Flight Anomaly Detection via a Deep Hybrid Model

In the civil aviation industry, security risk management has shifted from post-accident investigations and analyses to pre-accident warnings in an attempt to reduce flight risks by identifying currently untracked flight events and their trends and effectively preventing risks before they occur. The use of flight monitoring data for flight anomaly detection is effective in discovering unknown and potential flight incidents. In this paper, we propose a time-feature attention mechanism and construct a deep hybrid model for flight anomaly detection. The hybrid model combines a time-feature attention-based convolutional autoencoder with the HDBSCAN clustering algorithm, where the autoencoder is constructed and trained to extract flight features while the HDBSCAN works as an anomaly detector. Quick access record (QAR) flight data containing information of aircraft landing at Kunming Changshui International and Chengdu Shuangliu International airports are used as the experimental data, and the results show that (1) the time-feature-based convolutional autoencoder proposed in this paper can better extract the flight features and further discover the different landing patterns; (2) in the representation space of the flights, anomalous flight objects are better separated from normal objects to provide a quality database for subsequent anomaly detection; and (3) the discovered flight patterns are consistent with those at the airports, resulting in anomalies that could be interpreted with the corresponding pattern. Moreover, several examples of anomalous flights at each airport are presented to analyze the characteristics of anomalies.

Research on Flight Professional Spirit and Skill Capability Based on Human Factors Analysis Model

The professional spirit and skill capability of pilots are directly related to flight safety. In this study, 36 typical Cina civil aviation flight incidents caused by crew responsibility from January 2017 to June 2019 were taken as the research objects. After using the human factor analysis model, the study had deeply analyzed the typical problems of flight professional spirit and skill capability, and put forward the corresponding measures for the industry and airline.

Pollen Flow of Winter Triticale (x Triticosecale Wittmack) Investigated with Transgenic Line Expressing β-Glucuronidase Gene

A transgenic winter triticale line expressing the uidA gene, encoding β-glucuronidase, was used to assess the pollen flow in field experiments over two consecutive vegetation seasons in central Poland. The experimental design included two variants of mixed transgenic and non-transgenic lines. Pollen grains were collected using passive traps located at 0, 10, 30, 60 and 85 m from the transgenic line. GM pollen grains were detected histochemically by staining with x-Gluc. A positive effect of temperature increase, as well as the strength and direction of the wind on the number and spread of pollen grains was observed. Regardless of the experiment year and variant, only few pollen grains were observed at a distance of 85 m. In the first year of the study the amount of pollen grains at 85 m was 300-fold lower than at the source and 140-fold lower in the second year. The number of transgenic pollen grains was two times lower when the field with the transgenic triticale was surrounded by a non-transgenic line, compared to an empty field. On the basis of the obtained results, we suggest 100 m as the distance for triticale pollen migration, although longer flight incidents are possible in extreme atmospheric conditions.

The use of information technologies in risk management for the flight safety of aviation

At present, the problem of ensuring the necessary level of state aviation flights safety in terms of hu-man and organizational factors is very urgent. Despite the ongoing measures aimed at expanding and strengthening control over the processes of aviation activity, flight incidents caused by insufficient reli-ability of personnel work and organizational errors continue to occupy leading positions. There is an in-sufficient efficiency of the flight safety management system to identify hazardous factors in their latent stage, which is necessary for the early prevention of accidents. The difficulty of timely identification of the aviation system dangerous states associated with these factors is due to the need to account, corre-late and analyze data of a very large dimension and multifacetedness. According to the authors, a suc-cessful solution to this problem is possible through the use of automated processing and cognitive com-bination of large heterogeneous information arrays based on centralized electronic systems for collect-ing, information and analytical processing and storage of information about the functioning of the avia-tion system, identified abnormal and dangerous conditions, and incidents that have already occurred. The article presents the concept of creating a promising automated flight safety management system for state aviation. The proposed system will make it possible to implement the principle of proactive detec-tion and prevention of hazardous factors and risks for flight safety, taking into account human and or-ganizational factors, based on the implementation of processes for centralized collection, generalization and analysis of big data on the state of the aviation system. Topical scientific tasks for the creation of a methodological basis for the development of special software for such an automated system have been formulated.

APPLICATION OF SITUATIONAL MANAGEMENT METHODOLOGY IN FORENSIC INVESTIGATION OF AIR ACCIDENT CIRCUMSTANCES

Urgency of the research. The authors solve the following praxeological questions: How do we perceive a dangerous flight situation, a flight incident and an air accident? Which basic stages of the investigation do we use? How to implement a situational management methodology for investigating the circumstances of an air accident? Target setting. The article presents the analysis of the current state of information issues in the investigation of air accident circumstances in the military and civil aviation by using the methodology of situational management of forensic investigation processes. Actual scientific researches and issues analysis. An integral part of this development is also the tackling the concept of development of the Air Force, with an emphasis on the training of personnel and the level of the flight operations and the flight safety. Uninvestigated parts of general matters defining. The forensic investigation of air accidents and incidents is perceived as the specific application area of the Forensic Engineering. The research objective. The core output of article is in the proposal of the investigation of air accident circumstances in the military and civil aviation. The statement of basic materials. We use the tools of analysis and synthesis, the expert method with the inductive method based on the close observations and experimentation/investigation in the terrain, in the aviation practice. Conclusions. It is therefore necessary to subject on the permanent pay attention to the theoretical and practical level. Some specific issues addressed in the monograph can be extended with the further proposals and selected issues to address within the scope of research and scientific base of the armed forces.

Topic based hierarchical summarisation of Twitter

Twitter has become a rich source of information nowadays. The data generated however is so large in volume that it is not possible to manually go through each and every tweet to understand the context of data. One of the ways to get insight into the bulk of data at hand is to know the topics contained in it. As in the context of Twitter, we define topics to be long-lasting subjects around which the conversations of people revolve, such as sports, music and politics amongst others. However, the topics identified may be large in number and might be cumbersome for human interpretation. Considering these views, in this paper we address the information overload problem of Twitter data and propose a topic based hierarchical summarisation framework for the same. In contrast to imposing restrictions on topic models to depict the hierarchical structure, we propose an algorithm which constructs a topic hierarchy out of any given number of topics. We showcase the effectiveness of the proposed algorithm for the Twitter dataset prepared for Egyptair MS181 flight incident.

Civil aviation safety evaluation based on deep belief network and principal component analysis

Civil aviation in modern industries is becoming increasingly automatic, precise, and efficient. Serious accidents and unsafe incidents are used to describe and investigate the safety level. Therefore, effectively predicting big data from these features and accurately identifying the safety level with advanced theories are new issues in civil aviation. The prediction of serious flight incident rate for unsafe events is proposed on the basis of deep learning considering the characteristics of big data. In this method, deep belief network (DBN) is combined with Principal Component Analysis (PCA). The deep architecture is beneficial for safety prediction because each layer learns more complex features than the layers before. Compared with the previous prediction based on historical accident data, The DBN predicts the serious flight incident rate based on the results from PCA. Results indicate that the prediction data of PAC-DBN is consistent with the actual data of serious flight incident rate. The proposed method is superior to forecasting the serious flight incident rate compared with the gray neural network method, support vector regression, DBN. Simultaneously, the main influencing factors can be extracted to reduce flight incident rate.

Influence of primary disease incidence on the psycho-physiological adaptation of pilots in the Far North

The analysis of three years of primary disease incidence of flight and ground personnel in the Far North is presented as well as the analysis of the main meteorological factors, their complex characteristics and amount of respiratory diseases in flight crews on the day of observation and the subsequent 4 days. Assessment of influence of meteorological factors was carried out simultaneously in two directions: determined differential impact on the body of flight crews of each meteorological factor and simultaneous identification of their complex actions. It was found that pilots (navigators), showed a statistically significant (p0,001) increase in the average incidence of diseases compared with average index of primary morbidity from other members of the flight crews. It was revealed that flight crews serving in the area of the Far North for less than one year, shows a statistically significant (p0,01) increase in the average index of primary morbidity, compared with flight crews serving in the area of the Far North more than one year. Thus, a statistically significant increase in the average primary incidence of the pilots (navigators), compared with the average indicators of the primary morbidity from other members of the flight crews and ground troops means that physiological adaptation of pilots (navigators) to the Extreme North occurs with a larger psychoemotional stress than in soldiers of other specialties. The obtained results on the incidence of primary aircrew in the Far North allow to better understand mechanisms of influence of health state on the successful adaptation to extreme climatic conditions.

Risk Analysis of Runway Incursion Based on Fuzzy Bayesian Network

Runway incursion is a kind of unsafe flight incident which can easily lead to catastrophic collision of aircraft. It is of great significance to analyze the risk and improve the safety of air traffic management. Many factors affect the runway incursion unsafe event, and the analysis of influence degree of various factors has certain difficulty, and the Bayesian network is a kind of uncertainty causality model which can deal with uncertain problems and effectively express and merge multi-source information, therefore, this problem is studied by Bayesian network based on the actual operation data of some domestic airports. Bayesian network calculation model of runway incursion was built based on the analysis of factors by SHELLO model, calculated prior probability based on historical data, then the probability of the occurrence of runway incursion affected by factors was obtained by the model, it turns out L-S cause 66% of the runway incursions, the importance degree of factors and measures are sorted in the final.

Dealing With Unexpected Events on the Flight Deck: A Conceptual Model of Startle and Surprise

Objective:A conceptual model is proposed in order to explain pilot performance in surprising and startling situations.Background:Today’s debate around loss of control following in-flight events and the implementation of upset prevention and recovery training has highlighted the importance of pilots’ ability to deal with unexpected events. Unexpected events, such as technical malfunctions or automation surprises, potentially induce a “startle factor” that may significantly impair performance.Method:Literature on surprise, startle, resilience, and decision making is reviewed, and findings are combined into a conceptual model. A number of recent flight incident and accident cases are then used to illustrate elements of the model.Results:Pilot perception and actions are conceptualized as being guided by “frames,” or mental knowledge structures that were previously learned. Performance issues in unexpected situations can often be traced back to insufficient adaptation of one’s frame to the situation. It is argued that such sensemaking or reframing processes are especially vulnerable to issues caused by startle or acute stress.Conclusion:Interventions should focus on (a) increasing the supply and quality of pilot frames (e.g., though practicing a variety of situations), (b) increasing pilot reframing skills (e.g., through the use of unpredictability in training scenarios), and (c) improving pilot metacognitive skills, so that inappropriate automatic responses to startle and surprise can be avoided.Application:The model can be used to explain pilot behavior in accident cases, to design experiments and training simulations, to teach pilots metacognitive skills, and to identify intervention methods.

Passive control of the flow around unsteady aerofoils using a self-activated deployable flap

ABSTRACTSelf-activated feathers are used by many birds to adapt their wing characteristics to the sudden change of flight incidence angle. In particular, dorsal feathers are believed to pop-up as a consequence of unsteady flow separation and to interact with the flow to palliate the sudden stall breakdown typical of dynamic stall. Inspired by the adaptive character of birds feathers, some authors have envisaged the potential benefits of using of flexible flaps mounted on aerodynamic surfaces to counteract the negative aerodynamic effects associated with dynamic stall. This contribution explores more in depth the physical mechanisms that play a role in the modification of the unsteady flow field generated by a NACA0020 aerofoil equipped with an elastically mounted flap undergoing a specific ramp-up manoeuvre. We discuss the design of flaps that limit the severity of the dynamic stall breakdown by increasing the value of the lift overshoot also smoothing its abrupt decay in time. A detailed analysis on the modification of the turbulent and unsteady vorticity field due to the flap flow interaction during the ramp-up motion is also provided to explain the more benign aerodynamic response obtained when the flap is in use.

The Incidence of Capital Flight in an African Open Economy

This study investigated the incidence of capital flight in Nigeria. A combination of the push factors theory and the portfolio risk approach was employed. The policy and economic environments and political developments were suspected enabling factors. The analysis was confined to the short run in order to avoid the ambiguity inherent in the long run effects of some explanatory variables. Following from the preliminary data analysis, estimates were provided for non-ratio and ratio specifications. Whereas the overall goodness of fit was very impressive under the two specifications, particular variables’ performances were somewhat converse. However, a common denominator emerged from the results to tip off policy direction.