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Abstract The signing of the Regional Comprehensive Economic Partnership agreement brings new opportunities for the development of international air transportation. Faced with fierce competition, it is worth studying how hub airports should enhance competitiveness, and how low-cost carriers and full-service carriers should optimize the RCEP international airline network layout for better development. Aiming at providing suggestions for the development of hub airports, low-cost and full-service carriers in the RCEP international airline network, this paper identifies the hub airports, analyzes the layout of the RCEP international airline network, and the multi-layered characteristics based on an improved contribution matrix using data from 2010 to 2019 collected from the Official Airline Guide (OAG). This method comprehensively considers attributes of hub airports and the multi-layered characteristics of the airports and routes. The layout analysis indicates that the RCEP international transportation market presents a more open environment for competition and cooperation where base carriers are often the biggest supporters of hub construction. The multi-layered characteristics analysis reveals that low-cost carriers contribute more towards opening up new RCEP routes than full-service carriers. It is advised that carriers newly entering the RCEP international aviation transportation market and low-cost carriers dedicate to establishing new routes around their hub airports to monopolize this market and enhance their market share, whilst full-service carriers consolidate existing routes and increase route density to achieve economic benefits.

The continuous and strategic planning of full-service carriers plays a prominent role in transferring and adapting them into resilient full-service carrier network structures. The exploration of full-service carrier network structures using the latest long-term empirical data facilitates enhancing cognitive capabilities in aspects of identifying network development tendencies, readjusting network structures, and supporting determinations of strategic business routes. Aiming at providing sustainable transport network solutions with historical long-term network structure analysis, this paper researches the global top 10 full-service carriers’ air transport networks from 2007 to 2022, applied using social network analysis (SNA). The static metrics from local to path-based perspectives are adopted to explore the global network evolution trend, along with competitiveness characteristics over critical airports. The cascading failure model is applied as a key indicator to analyze the dynamic robustness capability for the network. The similarity changing feature among the selected networks over the past years from 2007 to 2022 is measured using the autocorrelation function (ACF). The results indicate that, from 2011 to 2019, the majority of full-service carrier networks belong to the network types of closed, structural symmetry and two-way transitivity. The critical airports in North America present superiority in terms of network efficiency over those in Europe, Asia, and Oceania. The 10 full-service carriers’ air transport networks all show the trend of being more destruction-resistant. During the COVID-19 pandemic period, the merger with other airlines and the signing of a joint venture agreement led to higher temporal variability in the network structure.

To enhance system reliability and mitigate the vulnerabilities of the Global Navigation Satellite Systems (GNSS), it is common to fuse the Inertial Measurement Unit (IMU) and visual sensors with the GNSS receiver in the navigation system design, effectively enabling compensations with absolute positions and reducing data gaps. To address the shortcomings of a traditional Kalman Filter (KF), such as sensor errors, an imperfect non-linear system model, and KF estimation errors, a GRU-aided ESKF architecture is proposed to enhance the positioning performance. This study conducts Failure Mode and Effect Analysis (FMEA) to prioritize and identify the potential faults in the urban environment, facilitating the design of improved fault-tolerant system architecture. The identified primary fault events are data association errors and navigation environment errors during fault conditions of feature mismatch, especially in the presence of multiple failure modes. A hybrid federated navigation system architecture is employed using a Gated Recurrent Unit (GRU) to predict state increments for updating the state vector in the Error Estate Kalman Filter (ESKF) measurement step. The proposed algorithm’s performance is evaluated in a simulation environment in MATLAB under multiple visually degraded conditions. Comparative results provide evidence that the GRU-aided ESKF outperforms standard ESKF and state-of-the-art solutions like VINS-Mono, End-to-End VIO, and Self-Supervised VIO, exhibiting accuracy improvement in complex environments in terms of root mean square errors (RMSEs) and maximum errors.

BackgroundGlobal positioning system (GPS)-based navigation apps are very useful in our lives. However, whether and how the usage of these apps affects spatial cognition and the sense of direction is still unclear.MethodsA total of 108 individuals were recruited and completed the GPS dependence, internet gaming behavior, and impulsivity test using scales. The eye-tracking-based general mental rotation (MR) task and target finding (TF; require individuals to find a target specified in a 3D street map in a rotated version of top 2D view map) task were used to assess their spatial cognition and the sense of direction. The correlation was used to relate GPS navigation usage, spatial cognition ability, and impulsivity. Subgroup analyses stratifying by gaming hours of individuals (< 2 h or ≥ 2 h) or maps (countryside or city) in TF task were performed. The moderating and mediating effect analyses were conducted to verify these relationships.ResultsThe GPS dependency score was nominal positively correlated with fixations in the TF task in the entire cohort (r = 0.202, unadjusted p = 0.036); it was significant in city (r = 0.254, p = 0.008) and gaming time of < 2 h (r = 0.459, p = 0.001) subgroups. The high-score (upper 30%) group of GPS dependency had more fixations on the original target building in the training area and indicative building in the test area than the low-score (lower 30%) group. GPS dependency was not associated with the correct rate and reaction time in the TF task or any of the indicators in the MR task (p > 0.05). The GPS dependency mediated the indirect effect of impulsivity on the fixations on TF. The internet gaming time moderated the association between GPS dependency and fixations on TF.ConclusionThe dependency on GPS-based navigation apps was associated with impaired spatial cognition but may not significantly affect the sense of direction.

Individuals with high risk of internet gaming disorder (HIGD) showed abnormal psychological performances in response inhibition, impulse control, and emotion regulation, and are considered the high-risk stage of internet gaming disorder (IGD). The identification of this population mainly relies on clinical scales, which are less accurate. This study aimed to explore whether these performances have highly accurate for discriminating HIGD from low-risk ones. Eye tracking based anti-saccade task, Barratt impulsiveness scale (BIS), and Wong and Law emotional intelligence scale (WLEIS) were used to evaluate psychological performances in 57 individuals with HIGD and 52 matched low risk of internet gaming disorder (LIGD). HIGD group showed significantly increased BIS total (t = −2.875, p = 0.005), attention (t = −2.139, p = 0.035), motor (t = −2.017, p = 0.046), and non-planning (t = −2.171, p = 0.032) scores, but significantly decreased WLEIS emotion regulation score (t = 2.636, p = 0.010) and correct rate of eye tracking anti-saccade task (t = 2.294, p = 0.024) compared with LIGD group. BIS total score was negatively correlated with the WLEIS total (r = −0.473, p < 0.001) and WLEIS emotion regulation (r = −0.366, p < 0.001) scores. A combination of the WLEIS emotion regulation score and the correct rate of anti-saccade task could discriminate HIGD from LIGD with 91.23% sensitivity, 82.69% specificity, and 87.16% accuracy. Participants with higher gaming hours daily were 40 times more likely to be high risk than their counterparts (p < 0.001). Hence, psychological performances were worse in HIGD. A combination of abnormal emotion regulation and response inhibition might be a potential marker to identify HIGD individuals.

BackgroundEscapism-based motivation (EBM) is considered as one of the diagnostic criteria for internet gaming disorder (IGD). However, how EBM affects the high risk of IGD (HIGD) population remains unclear.MethodsAn initial number of 789 college students participated in the general, internet gaming behavior, and motivation surveys. After multiple evaluations, 57 individuals were identified as HIGD (25 with EBM, H-EBM; 32 with non-EBM, H-nEBM). In addition, 51 no-gaming individuals were included as the control group (CONTR). The cohorts completed the psychological assessments and eye-tracking tests, and analyses of group differences, correlations, and influencing factors of the indicators were performed.ResultsThe Barratt impulsiveness score of H-nEBM and H-EBM was significantly higher than that of CONTR (MD = 3.605, P = 0.017; MD = 3.744, P = 0.022). In addition, emotional intelligence self-emotion management ability was significantly lower in the H-EBM than in CONTR (MD = –2.038, P = 0.004). Correct rates and reaction times in the anti-saccade task differed significantly between the three groups (F = 3.525, P = 0.033; F = 4.459, P = 0.014). However, no differences were found in the comparison of the digital span test (DST), trail making test (TMT), animal verbal fluency test, Stroop test, and mental rotation test results. The anti-saccade test indicators were positively correlated with the DST results but negatively correlated with the Stroop test results (P < 0.05). Correct rates in the mental rotation test were negatively correlated with the TMT results but positively correlated with the DST results (P < 0.05). The participants with high Stroop test scores and no lover experience and who were raised by their grandparents were likely to develop EBM to engage in high risk of internet gaming disorder (P < 0.05).ConclusionEBM has a significantly negative effect on impulsivity, self-emotion management ability, and response inhibition in the HIGD participants.

Signal detection, identification, and characterization are among the major challenges in aerial communication systems. The ability to detect and recognize signals using cognitive technologies is still under active development when addressing uncertainties regarding signal parameters, such as blank spaces available within the transmitted signal and the utilized bandwidth. This paper proposes a learning-based identification framework for heterogeneous signals with orthogonal frequency division multiplexing (OFDM) modulation as generated in a simulated environment at an a priori unknown frequency. The implemented region-based signal identification method utilizes cyclostationary features for robust signal detection. Signal characterization is performed using a purposely-built, lightweight, region-based convolutional neural network (R-CNN). It is shown that the proposed framework is robust in the presence of additive white Gaussian noise (AWGN) and, despite its simplicity, shows better performance compared with conventional popular network architectures, such as GoogLeNet, AlexNet, and VGG 16. The signal characterization performance is validated under two degraded environments that are unknown to the system: Doppler shifted and small-scale fading. High performance is demonstrated under both degraded conditions over a wide range of signal to noise ratios (SNRs) and it is shown that the detection probability for the proposed approach is improved over those for conventional energy detectors. It is found that the signal characterization performance deteriorates under extreme conditions, such as lower SNRs and higher Doppler shifts.

This paper addresses the alliance route network design problem considering uncertainty in the unit transportation cost. An alliance route network was constructed based on a hub-and-spoke (HS) network, in which airlines could achieve inter-area passenger transport through their international gateways. The design problem was formulated with a robust model containing a set of uncertain cost parameters. The model was established based on a three-subscript model of an HS network. A case study with real-world data was used to test the proposed model. The results showed that this robust solution can reduce the impact of cost uncertainty.

To enable an efficient dynamic power and channel allocation (DPCA) for users in the downlink multi-channel non-orthogonal multiple access (MC-NOMA) systems, this paper regards the optimization as the combinatorial problem, and proposes three heuristic solutions, i.e., stochastic algorithm, two-stage greedy randomized adaptive search (GRASP), and two-stage stochastic sample greedy (SSD). Additionally, multiple complicated constraints are taken into consideration according to practical scenarios, for instance, the capacity for per sub-channel, power budget for per sub-channel, power budget for users, minimum data rate, and the priority control during the allocation. The effectiveness of the algorithms is compared by demonstration, and the algorithm performance is compared by simulations. Stochastic solution is useful for the overwhelmed sub-channel resources, i.e., spectrum dense environment with less data rate requirement. With small sub-channel number, i.e., spectrum scarce environment, both GRASP and SSD outperform the stochastic algorithm in terms of bigger data rate (achieve more than six times higher data rate) while having a shorter running time. SSD shows benefits with more channels compared with GRASP due to the low computational complexity (saves 66% running time compared with GRASP while maintaining similar data rate outcomes). With a small sub-channel number, GRASP shows a better performance in terms of the average data rate, variance, and time consumption than SSG.

In anticipation of wide implementation of 5G technologies, the scarcity of spectrum resources for the unmanned aerial vehicles (UAVs) communication remains one of the major challenges in arranging safe drone operations. Dynamic spectrum management among multiple UAVs as a tool that is able to address this issue, requires integrated solutions with considerations of heterogeneous link types and support of the multi-UAV operations. This paper proposes a synthesized resource allocation and opportunistic link selection (RA-OLS) scheme for the air-to-ground (A2G) UAV communication with dynamic link selections. The link opportunities using link hopping sequences (LHSs) are allocated in the GCSs for alleviating the internal collisions within the UAV network, offloading the on-board computations in the spectrum processing function, and avoiding the contention in the air. In this context, exclusive technical solutions are proposed to form the prototype system. A sub-optimal allocation method based on the greedy algorithm is presented for addressing the resource allocation problem. A mathematical model of the RA-OLS throughput with above propositions is formulated for the spectrum dense and scarce environments. An interference factor is introduced to measure the protection effects on the primary users. The proposed throughput model approximates the simulated communication under requirements of small errors in the spectrum dense environment and the spectrum scarce environment, where the sensitivity analysis is implemented. The proposed RA-OLS outperforms the static communication scheme in terms of the utilization rate by over 50% in case when multiple links are available. It also enables the collaborative communication when the spectral resources are in scarcity. The impacts from diverse parameters on the RA-OLS communication performance are analyzed.