Beschreibung: To provide a long-time reliable orientation, sensor fusion technologies are widely used to integrate available inertial sensors for the low-cost orientation estimation. In this paper, a novel dual-linear Kalman filter was designed for a multi-sensor system integrating MEMS gyros, an accelerometer, and a magnetometer. The proposed filter precludes the impacts of magnetic disturbances on the pitch and roll which the heading is subjected to. The filter can achieve robust orientation estimation for different statistical models of the sensors. The root mean square errors (RMSE) of the estimated attitude angles are reduced by 30.6% under magnetic disturbances. Owing to the reduction of system complexity achieved by smaller matrix operations, the mean total time consumption is reduced by 23.8%. Meanwhile, the separated filter offers greater flexibility for the system configuration, as it is possible to switch on or off the second stage filter to include or exclude the magnetometer compensation for the heading. Online experiments were performed on the homemade miniature orientation determination system (MODS) with the turntable. The average RMSE of estimated orientation are less than 0.4° and 1° during the static and low-dynamic tests, respectively. More realistic tests on two-wheel self-balancing vehicle driving and indoor pedestrian walking were carried out to evaluate the performance of the designed MODS when high accelerations and angular rates were introduced. Test results demonstrate that the MODS is applicable for the orientation estimation under various dynamic conditions. This paper provides a feasible alternative for low-cost orientation determination.

Beschreibung: Remote Sensing, Vol. 9, Pages 1139: Hyperspectral Image Spatial Super-Resolution via 3D Full Convolutional Neural Network Remote Sensing doi: 10.3390/rs9111139 Authors: Shaohui Mei Xin Yuan Jingyu Ji Yifan Zhang Shuai Wan Qian Du Hyperspectral images are well-known for their fine spectral resolution to discriminate different materials. However, their spatial resolution is relatively low due to the trade-off in imaging sensor technologies, resulting in limitations in their applications. Inspired by recent achievements in convolutional neural network (CNN) based super-resolution (SR) for natural images, a novel three-dimensional full CNN (3D-FCNN) is constructed for spatial SR of hyperspectral images in this paper. Specifically, 3D convolution is used to exploit both the spatial context of neighboring pixels and spectral correlation of neighboring bands, such that spectral distortion when directly applying traditional CNN based SR algorithms to hyperspectral images in band-wise manners is alleviated. Furthermore, a sensor-specific mode is designed for the proposed 3D-FCNN such that none of the samples from the target scene are required for training. Fine-tuning by a small number of training samples from the target scene can further improve the performance of such a sensor-specific method. Extensive experimental results on four benchmark datasets from two well-known hyperspectral sensors, namely hyperspectral digital imagery collection experiment (HYDICE) and reflective optics system imaging spectrometer (ROSIS) sensors, demonstrate that our proposed 3D-FCNN outperforms several existing SR methods by ensuring higher quality both in reconstruction and spectral fidelity.

Beschreibung: Sensors, Vol. 18, Pages 179: A Continuous Identity Authentication Scheme Based on Physiological and Behavioral Characteristics Sensors doi: 10.3390/s18010179 Authors: Guannan Wu Jian Wang Yongrong Zhang Shuai Jiang Wearable devices have flourished over the past ten years providing great advantages to people and, recently, they have also been used for identity authentication. Most of the authentication methods adopt a one-time authentication manner which cannot provide continuous certification. To address this issue, we present a two-step authentication method based on an own-built fingertip sensor device which can capture motion data (e.g., acceleration and angular velocity) and physiological data (e.g., a photoplethysmography (PPG) signal) simultaneously. When the device is worn on the user’s fingertip, it will automatically recognize whether the wearer is a legitimate user or not. More specifically, multisensor data is collected and analyzed to extract representative and intensive features. Then, human activity recognition is applied as the first step to enhance the practicability of the authentication system. After correctly discriminating the motion state, a one-class machine learning algorithm is applied for identity authentication as the second step. When a user wears the device, the authentication process is carried on automatically at set intervals. Analyses were conducted using data from 40 individuals across various operational scenarios. Extensive experiments were executed to examine the effectiveness of the proposed approach, which achieved an average accuracy rate of 98.5% and an F1-score of 86.67%. Our results suggest that the proposed scheme provides a feasible and practical solution for authentication.

Beschreibung: Energies, Vol. 11, Pages 2449: Numerical Study of the Respirable Coal Dust Removal Performance of a Vortex Ventilation System at an Excavation Face Energies doi: 10.3390/en11092449 Authors: Xiaofei Liu Ping Chang Enyuan Wang Zhenguo Zhang Shuai Yang Coal dust is one of the most serious issues in coal mines. The miners at an excavation face have a high potential for exposure to high concentrations of coal dust. The main method for removing coal dust is by ventilation. To better control the coal dust at the excavation face, it is important to understand the coal dust movement patterns and distribution characteristics. This paper used the computational fluid dynamics (CFD) approach to simulate coal dust movement under two different ventilation systems. The Eulerian-Lagrange method was used to study the gas‒solid two-phase fluid behavior. The coal dust concentration distributions under the two ventilation systems are presented and further compared. From the comparison results, it is found that a vortex ventilation system has better coal dust removal performance. This ventilation system is recommended for excavation for better coal dust control and miners’ health protection.

Beschreibung: Background: With the rapid increase in the incidence and mortality of lung cancer, a growing number of lung cancer patients and their families are faced with a tremendous economic burden because of the high cost of treatment in China. This study was conducted to estimate the economic burden and patient responsibility of lung cancer patients and the impact of this burden on family income. Methods: This study uses data from a retrospective questionnaire survey conducted in 10 communities in urban China and includes 195 surviving lung cancer patients diagnosed over the previous five years. The calculation of direct economic burden included both direct medical and direct nonmedical costs. Indirect costs were calculated using the human capital approach, which measures the productivity lost for both patients and family caregivers. The price index was applied for the cost calculation. Results: The average economic burden from lung cancer was $43,336 per patient, of which the direct cost per capita was $42,540 (98.16%) and the indirect cost per capita was $795 (1.84%). Of the total direct medical costs, 35.66% was paid by the insurer and 9.84% was not covered by insurance. The economic burden for diagnosed lung cancer patients in the first year following diagnosis was $30,277 per capita, which accounted for 171% of the household annual income, a percentage that fell to 107% after subtracting the compensation from medical insurance. Conclusions: The economic burden for lung cancer patients is substantial in the urban areas of China, and an effective control strategy to lower the cost is urgently needed.

Beschreibung: Remote Sensing, Vol. 10, Pages 1400: Source Model and Stress Disturbance of the 2017 Jiuzhaigou Mw 6.5 Earthquake Constrained by InSAR and GPS Measurements Remote Sensing doi: 10.3390/rs10091400 Authors: Shunying Hong Xin Zhou Kui Zhang Guojie Meng Yanfang Dong Xiaoning Su Lei Zhang Shuai Li Keliang Ding Seismogenic fault geometry, especially for a blind fault, is usually difficult to derive, based only on the distribution of aftershocks and interference fringes of Interferometric Synthetic Aperture Radar (InSAR). To better constrain the fault geometry of the 2017 Jiuzhaigou Mw 6.5 earthquake, we first carried out a nonlinear inversion for a single fault source using multi-peak particle swarm optimization (MPSO), Monte Carlo (MC), and Markov Chain Monte Carlo (MCMC) algorithms, respectively, with constraints of InSAR data in multiple SAR viewing geometries. The fault geometry models retrieved with different methods were highly consistent and mutually verifiable, showing that a blind faulting with a strike of ~154° and a dip angle of ~77° was responsible for the Jiuzhaigou earthquake. Based on the optimal fault geometry model, the fault slip distribution jointly inverted from the InSAR and Global Positioning System (GPS) data by the steepest descent method (SDM) and the MC method showed that the slip was mainly concentrated at the depth of 1–15 km, and only one slip center appeared at the depth of 5–9 km with a maximum slip of about 1.06 m, some different from previous studies. Taking the shear modulus of μ = 32 GPa, the seismic moment derived from the distributed slip model was about 7.85 × 1018 Nm, equivalent to Mw 6.54, which was slightly larger than that from the focal mechanism solutions. The fault spatial geometry and slip distribution could be further validated with the spatial patterns of the immediate aftershocks. Most of the off-fault aftershocks with the magnitude > M2 within one year after the mainshock occurred in the stress positive stress change area, which coincided with the stress triggering theory. The static Coulomb stress, triggered by the mainshock, significantly increased at the Tazang fault (northwest to the epicenter), and at the hidden North Huya fault, and partial segments of the Minjiang fault (west of the epicenter).