Search Results (8)

Airline customers will often complain to the relevant authorities if they encounter an unpleasant flight experience. The specific complaint information can directly reflect the various service problems encountered, so conducting in-depth research on public air transport passenger complaints can reveal important details for improving service. Therefore, by analyzing the passenger complaint data of relevant civil aviation departments in China, we propose a method for identifying key topics of passenger complaints based on text mining. We organically integrate sentiment analysis, topic modeling and association rule mining. A new complaint text analysis framework is constructed, which provides new perspectives and ideas for complaint text analysis and related application fields. First, we calculate the sentiment orientation of the complaint text based on the sentiment dictionary method and filter complaint texts with strong negative sentiment. Then, we compare the two topic modeling methods of LDA (Latent Dirichlet Allocation) and LSA (Latent Semantic Analysis). Finally, we select the better LDA method to extract the main topics hidden in the passenger complaint text with high negative emotional intensity. We use the Apriori algorithm to mine the association rules between the complaint topic words and the service problem classification labels on the complaint text. We use the FP-growth algorithm to mine the association rules between the complaint subject words and the service problem classification labels on the complaint text. By comparing the Apriori algorithm with the FP-growth algorithm, the results of mining the support, confidence and promotion of the association rules show that the Apriori algorithm is more efficient. Finally, we analyze the causes of specific service problems and suggest improvement strategies for airlines and airports. Full article

Advanced Aerial Mobility (AAM) platforms are poised to begin high-density operations in urban areas nationwide. This new category of aviation platforms spans a broad range of sizes, from small package delivery drones to passenger-carrying vehicles. Unlike traditional aircraft, AAM vehicles operate within the urban boundary layer, where large structures, such as buildings, interrupt the flow. This study examines the response of a package delivery drone, a general aviation aircraft, and a passenger-carrying urban air mobility aircraft through an urban wind field generated using Large Eddy Simulations (LES). Since it is burdensome to simulate flight dynamics in real-time using the full-order solution, reduced-order wind models are created. Comparing trajectories for each aircraft platform using full-order or reduced-order solutions reveals little difference; reduced-order wind representations appear sufficient to replicate trajectories as long as the spatiotemporal wind field is represented. However, examining control usage statistics and time histories creates a stark difference between the wind fields, especially for the lower wing-loading package delivery drone where control saturation was encountered. The control saturation occurrences were inconsistent across the full-order and reduced-order winds, advising caution when using reduced-order models for lightly wing-loaded aircraft. The results presented demonstrate the effectiveness of using a simulation environment to evaluate reduced-order models by directly comparing their trajectories and control activity metrics with the full-order model. This evaluation provides designers valuable insights for making informed decisions for disturbance rejection systems. Additionally, the results indicate that using Reynolds-averaged Navier–Stokes (RANS) solutions to represent urban wind fields is inappropriate. It was observed that the mean wind field trajectories fall outside the 95% confidence intervals, a finding consistent with the authors’ previous research. Full article

Bearing in mind the socio-economic consequences of COVID-19 on airports and passengers, this study considers cleaning and hygiene a top priority in airports and airlines’ operating processes. Both airport operators and passengers should be aware that the COVID-19 pathogen has not yet gone away and, thus, continues to spread despite mass vaccination. In this context, this paper’s objective is to show the importance of cleaning and hygiene in the air transport industry to encourage the passengers’ confidence in making decisions to travel on commercial airlines and help airport and airline operators make better decisions in their efforts to improve the cleaning and hygiene protocols. Passengers’ awareness of hygiene and cleanliness has increased, but unfortunately, airports and airlines have reduced cleaning and hygiene activities to save costs. Although there is much to do to help the aviation sector recover, we also see plenty of reasons to be optimistic about the air transport industry’s future, as long as airport and airline operators can guarantee an adequate quality of service with regard to cleaning and hygiene in order to ensure passengers’ safety and well-being. Airports and airlines cannot lower their guard because the SARS, H1N1, MERS, and COVID-19 viruses remain active in society. Full article

The COVID-19 pandemic has sharply reduced air travel demand since early 2020. This paper aims to identify factors influencing Korean passengers’ air travel confidence after COVID-19 based on three countermeasure classifications: social distancing, health, and vaccination. Data were collected online from 307 Korean air passengers from December 2021 to January 2022. Structural equation modeling (SEM) was used to examine countermeasure influence on air passenger confidence. Health measures (face mask, temperature screening, and hand sanitizing) scored the highest on importance and air travel safety sensitivity. Social distancing measures (physical distancing, contactless boarding process, and sneeze guards) scored the lowest but were still perceived to be important. Only vaccine measures (vaccine pass check-in, vaccination rates, and personal vaccination status) were identified as having a significantly positive influence on Korean air travel confidence. The study’s results do not support past studies showing social distancing and health measures partially or fully influencing air travel confidence. This finding has significant implications for understanding how Korean passengers’ perceptions and perceived sense of safety are different or have changed two years into the crisis, as well as for achieving sustainability of the aviation and travel industries after COVID-19. Full article

Background: The main goal of this case study is to analyze the air traffic, air cargo, and the safety-hygiene air corridor between UK and Spain, in airports managed by MAG Group (UK) and AENA Group (Spain). Methods: To review the specific paradigm of research which discusses, investigates, and analyses the air traffic, air cargo, and the safety-hygiene air corridor between UK and Spain at airports managed by MAG (UK) and AENA (Spain). Results: The air traffic that airlines project onto the UK-Spain corridor has decreased due to the pandemic, but the result of this research shows that in the medium term, to implement the new Safety-Hygiene Air Corridor (SHAC) will return to economically nurture airlines, airports and destination thanks to vaccines, the digital COVID-19 certificate that will give more confidence to passengers to travel, and with new COVID-19 safety regulations at airports and airlines. Furthermore, the results of the research show the need to create Safety-Hygiene Air Corridor Elements (SHACE) to improve the air activity of these countries. Conclusions: The study contributes towards providing solutions such as those we propose in this study, the UK-Spain SHAC and SHACE will guarantee the value of corridors between countries, reduce the uncertainty of airlines, organizations, and passengers, to restore the tourism and aviation industries. Full article

The pandemic causes social distancing and lockdown, which impedes consumer confidence and contracts the economy. Hence, this study analyzes the corona (COVID-19) impact on the airline industry revenues (ALR) and forecast by the vector autoregression (VAR) method. The results indicate that gross domestic product (GDP) and air cargo are the best predictors of ALR. The forecasting outcomes explore if ALR will decline and expect to back to pre-COVID-19 in 2023. Our results resemble both the V-shaped and U-shaped, which suggests slow gradual recovery with longer lockdown and border disclosure. The government can restore confidence building by providing economic stimulus packages and can encourage the airline to return to travel. Furthermore, softening the passenger rules concerning the refund of unflown ticket, reducing taxes, and reducing overflight taxes, all reduce the costs. Similarly, the mutually recognized global standards are crucial for effective execution, and any temporary measures taken by the government should have a clear exit strategy. The study major limitation includes the lack of relevant research and data availability. Full article

In recent years, African swine fever (ASF) has become prevalent in many areas, including Asia. The repeated detection of the ASF virus (ASFV) genome in pork products brought in air passenger’s luggage (PPAP) was also reported from Japanese airports. In the present study, the risk of ASFV exposure to susceptible hosts in Japan via three different pathways was assessed. Two quantitative stochastic risk assessment models were built to estimate the annual probability of ASFV exposure to domestic pigs, which could be attributed to foreign job trainees or foreign tourists. A semi-quantitative stochastic model was built to assess the risk of ASFV exposure to wild boar caused by foreign tourists. The overall mean annual probability of ASFV exposure to domestic pigs via PPAP carried by foreign job trainees was 0.169 [95% confidence interval (CI): 0.000–0.600], whereas that by foreign tourists was 0.050 [95% CI: 0.000–0.214], corresponding to approximately one introduction every 5.9 and 20 years, respectively. The risk of ASFV exposure to domestic pigs was dispersed over the country, whereas that of wild boar was generally higher in the western part of Japan, indicating that the characteristics of the potential ASF risk in each prefecture were varied. Full article

In this paper, a novel algorithm for estimating clothing insulation is proposed to assess thermal comfort, based on the non-contact and real-time measurements of the face and clothing temperatures by an infrared camera. The proposed method can accurately measure the clothing insulation of various garments under different clothing fit and sitting postures. The proposed estimation method is investigated to be effective to measure its clothing insulation significantly in different seasonal clothing conditions using a paired t-test in 99% confidence interval. Temperatures simulated with the proposed estimated insulation value show closer to the values of actual temperature than those with individual clothing insulation values. Upper clothing’s temperature is more accurate within 3% error and lower clothing’s temperature is more accurate by 3.7%~6.2% error in indoor working scenarios. The proposed algorithm can reflect the effect of air layer which makes insulation different in the calculation to estimate clothing insulation using the temperature of the face and clothing. In future, the proposed method is expected to be applied to evaluate the customized passenger comfort effectively. Full article