Which way is the bookstore? A closer look at the judgments of relative directions task

We present a detailed analysis of a widely used assay in human spatial cognition, the judgments of relative direction (JRD) task. We conducted three experiments involving virtual navigation interspersed with the JRD task, and included confidence judgments and map drawing as additional metrics. We also present a technique for assessing the similarity of the cognitive representations underlying performance on the JRD and map-drawing tasks. Our results support the construct validity of the JRD task and its connection to allocentric representation. Additionally, we found that chance performance on the JRD task depends on the distribution of the angles of participants’ responses, rather than being constant and 90 degrees. Accordingly, we present a method for better determining chance performance.     

Modeling and analysis of mover gaps in tubular moving-magnet linear oscillating motors

A tubular moving-magnet linear oscillating motor (TMMLOM) has merits of high efficiency and excellent dynamic capability. To enhance the thrust performance, quasi-Halbach permanent magnet (PM) arrays are arranged on its mover in the application of a linear electro-hydrostatic actuator in more electric aircraft. The arrays are assembled by several individual segments, which lead to gaps between them inevitably. To investigate the effects of the gaps on the radial magnetic flux density and the machine thrust in this paper, an analytical model is built considering both axial and radial gaps. The model is validated by finite element simulations and experimental results. Distributions of the magnetic flux are described in condition of different sizes of radial and axial gaps. Besides, the output force is also discussed in normal and end windings. Finally, the model has demonstrated that both kinds of gaps have a negative effect on the thrust, and the linear motor is more sensitive to radial ones.     

Validation of non-linear split window algorithm for land surface temperature estimation using Sentinel-3 satellite imagery: Case study; Tehran Province,Iran

In recent years, land surface temperature (LST) has become critical in environmental studies and earth science. Remote sensing technology enables spatiotemporal monitoring of this parameter on large scales. This parameter can be estimated by satellite images with at least one thermal band. Sentinel-3 SLSTR data provide LST products with a spatial resolution of 1 km. In this research, direct and indirect validation procedures were employed to evaluate the Sentinel-3 SLSTR LST products over the study area in different seasons from 2018 to 2019. The validation method was based on the absolute (direct) evaluation of this product with field data and comparison (indirect) evaluation with the MODIS LST product and the estimated LST using the non-linear split-window (NSW) algorithm. Also, two emissivity estimation methods, (1) NDVI thresholding method (NDVI-THM) and (2) classification-based emissivity method (CBEM), were used to estimate the LST using the NSW method according to the two thermal bands of Sentinel-3 images. Then, the accuracy of these methods in estimating LST was evaluated using field data and temporal changes of vegetation, which the NDVI-THM method generated better results. For indirect evaluation between the Sentinel-3 LST product, MODIS LST product, and LST estimated using NSW, four filters based on spatial and temporal separates between pairs of pixels and pixel quality were used to ensure the accuracy and consistency of the compared pairs of a pixel. In general, the accuracy results of the LST products of MODIS and Sentinel-3, and LST estimated using NSW showed a similar trend for LST changes during the seasons. With respect to the two absolute and comparative validations for the Sentinel-3 LST products, summer with the highest values of bias (?1.24 K), standard deviation (StDv = 2.66 K), and RMSE (2.43 K), and winter with the lowest ones (bias of 0.14 K, StDv of 1.13 K, and RMSE of 1.12 K) provided the worst and best results for the seasons in the period of 2018–2019, respectively. According to both absolute and comparative evaluation results, the Sentinel-3 SLSTR LST products provided reliable results for all seasons on a large temporal and spatial scale over our studied area.     

Establishment of atmospheric weighted mean temperature model in the polar regions

Due to the special geographical location and extreme climate environment, the polar regions (Antarctic and Arctic) have an important impact on global climate change. Atmospheric weighted mean temperature (Tm) is a crucial parameter in the retrieval of precipitable water vapor (PWV) from the zenith wet delay (ZWD) of ground-based Global Navigation Satellite System (GNSS) signal propagation. In this paper, the correlation between weighted mean temperature and surface temperature (Ts) is studied firstly. It is shown that the correlation coefficients between Tm and Ts are 0.93 in the Antarctic and 0.94 in the Arctic. The linear regression Tm model and quadratic function Tm model of the Antarctic and the Arctic are established respectively using the radiosonde profiles of 12 stations in the Antarctic and 58 stations in the Arctic from 2008 to 2015. The accuracies of the linear regression Tm model, the quadratic function Tm model and GPT2w Tm model which is a state-of-the-art global Tm model are verified using the radiosonde profiles from 2016 to 2018 in the Antarctic and Arctic. Root Mean Square (RMS) errors of the linear regression Tm model, the quadratic function Tm model and GPT2w Tm model in the Antarctic are 3.07 K, 2.87 K and 4.32 K respectively, and those in the Arctic are 3.53 K, 3.38 K and 4.82 K, which indicates that the quadratic function Tm model has a higher accuracy compared to linear regression Tm model, and the accuracies of the two regional Tm models are better than that of GPT2w Tm model in the polar regions. In order to better evaluate the accuracy of Tm in the PWV retrieval, the PWV values of radiosondes are used for comparisons as the reference value. The RMS errors of PWV derived from the two Tm models are similar for 1.28 mm in the Antarctic and 1 mm in the Arctic respectively. In addition, the spatial and temporal variation characteristics of Tm are analyzed in the polar regions by spectral analysis of Tm data using fast Fourier transform. The results show that the Tm has obvious seasonality and annual periodicity in the polar regions, and the maximum difference between warm season and cold season is about 63 K. After comparing and analyzing the influences of latitude, longitude and elevation on the Tm in the polar regions, it is found that latitude and elevation have a greater influence on the Tm than the longitude. As the latitude and elevation increase, the Tm decreases, and vice versa in the polar regions.     

ADS-B监视报文参数统计及其所需性能

基于广播式自动相关监视（ADS-B）报文的位置导航不确定性指标（NUC_P）的监视质量备受关注。针对位置导航不确定性参数好、监视质量却不高的问题，深入研究广播式自动相关监视报文数据项及其与基于性能的通信与监视的相关性。在充分考虑通信导航监视相关性及全球卫星导航系统（GNSS）广域增强等因素基础上，推导、构建了监视所需性能估计模型，并给予合理简化。在测试空域利用2个具有运行资质的生产商ADS-B接收站，连续采集近2亿条ADS-B报文，统计分析报文各信息项的状态参数，并应用到所需性能估计模型评估计算这两个ADS-B站的所需监视性能。此外还将参考文献报文参数代入模型评估所需性能。结果显示，当考虑报文各信息项统计状态及具备广域增强服务支撑时，ADS-B所需监视性能参数估计值未达到99.9%要求。若缺乏广域增强服务及相关性因素等，系统所需性能与国际民航组织（ICAO）监视要求的差距则更大。     

A new modeling scheme for powered parafoil unmanned aerial vehicle platforms: Theory and experiments

A novel framework is established for accurate modeling of Powered Parafoil Unmanned Aerial Vehicle (PPUAV). The model is developed in the following three steps: obtaining a linear dynamic model, simplifying the model structure, and estimating the model mismatch due to model variance and external disturbance factors. First, a six degree-of-freedom linear model, or the structured model, is obtained through dynamic establishment and linearization. Second, the data correlation analysis is adopted to determine the criterion for proper model complexity and to simplify the structured model. Next, an active model is established, combining the simplified model with the model mismatch estimator. An adapted Kalman filter is utilized for the real-time estimation of states and model mismatch. We finally derive a linear system model while taking into account of model variance and external disturbance. Actual flight tests verify the effectiveness of our active model in different flight scenarios.     

Near-wall topological patterns and flow structures over a simplified Danaus plexippus model

Studies on the high-lift mechanisms of butterfly gliding flights shed light on the design of the micro air vehicles. The flow field around a simplified Danaus plexippus model is investigated using the hydrogen bubble visualization and the Particle Image Velocimetry (PIV) techniques. There are three near-wall topological patterns with different Angles of Attack (AoAs): the separation bubble, the Leading-Edge Vortex (LEV) and the high AoAs flow. For the separation bubble pattern, two saddles and two foci form in the middle of the model. The features of the LEV pattern are the leading-edge separation lines. The topological characteristics of the separation lines are changed by the interaction between the LEV and the Wing-Tip Vortex (WTV). For the high AoAs flow pattern, four unstable foci are found at the forewing and the hindwing respectively. The angle between the trajectory of the WTV and the model increases with increasing AoA even though the slope of the WTV angle versus AoA curve declines at the moderate AoAs.     

Rotating machinery fault diagnosis based on convolutional neural network and infrared thermal imaging

Rotating machinery is widely applied in industrial applications. Fault diagnosis of rotating machinery is vital in manufacturing system, which can prevent catastrophic failure and reduce financial losses. Recently, Deep Learning (DL)-based fault diagnosis method becomes a hot topic. Convolutional Neural Network (CNN) is an effective DL method to extract the features of raw data automatically. This paper develops a fault diagnosis method using CNN for InfRared Thermal (IRT) image. First, IRT technique is utilized to capture the IRT images of rotating machinery. Second, the CNN is applied to extract fault features from the IRT images. In the end, the obtained features are fed into the Softmax Regression (SR) classifier for fault pattern identification. The effectiveness of the proposed method is validated using two different experimental data. Results show that the proposed method has a superior performance in identification various faults on rotor and bearings comparing with other deep learning models and traditional vibration-based method.     

Application of Wuhan Ionospheric Oblique Backscattering Sounding System (WIOBSS) for the investigation of midlatitude ionospheric irregularities

An upgrade of Wuhan Ionospheric Backscattering Sounding System (WIOBSS) was developed in 2015. Based on the Universal Serial Bus (USB), and a high performance FPGA, the newly designed WIOBSS has a completely digital structure, which makes it portable and flexible. Two identical WIOBSSs, which were situated at Mile (24.31°N, 103.39°E) and Puer (22.74°N, 101.05°E) respectively, were used to investigate the ionospheric irregularities. The comparisons of group distance, Doppler shift and width between Mile-Puer and Puer-Mile VHF ionospheric propagation paths indicate that the reciprocity of the irregularities is satisfied at midlatitude region. The WIOBSS is robust in the detection of ionospheric irregularities.     

Evaluation of SARAL/AltiKa performance using GNSS/IMU equipped buoy in Sajafi,Imam Hassan and Kangan Ports

Performance of SARAL/AltiKa mission has been evaluated within 2016 altimeter calibration/validation framework in Persian Gulf through three campaigns conducted in the offshore waters of Sajafi, Imam Hassan and Kangan Ports, while the altimeter overflew the passes 470, 111 and 25 on 13 Feb, 7 March and 17 June 2016, respectively. As the preparation, a lightweight buoy was equipped with a GNSS receiver/choke-ring antenna and a MEMS-based IMU to measure independent datasets in the field operations. To obtain accurate sea surface height (SSH) time series, the offset of the onboard antenna from the equilibrium sea level was predetermined through surveying operations as the buoy was deploying in the onshore waters of Kangan Port. Accordingly, the double-difference carrier phase observations have been processed via the Bernese GPS Software v. 5.0 so as to provide the GNSS-derived time series at the comparison points of the calibration campaigns, once the disturbing effects due to the platform tilt and heave have been eliminated. Owing to comparing of the SSH time series and the associating altimetry 1?Hz GDR-T datasets, the calibration/validation of the SARAL/AltiKa has been performed in the both cases of radiometer and ECMWF wet troposphere corrections so as to identify potential land contamination. An agreement of the present findings in comparison with those attained in other international calibrations sites confirms the promising feasibility of Persian Gulf as a new dedicated site for calibration/validation of ongoing and future altimetry missions.