An Effective GNSS/PDR Fusion Positioning Algorithm on Smartphones for Challenging Scenarios.

The location-based smartphone service brings new development opportunities for seamless indoor/outdoor positioning. However, in complex scenarios such as cities, tunnels, overpasses, forests, etc., using only GNSS on smartphones cannot provide stable and reliable positioning results. Usually, additional sensors are needed to assist GNSS. This paper investigates the GNSS positioning algorithm assisted by pedestrian dead reckoning (PDR) in complex scenarios. First, we introduce a step detection algorithm based on the peak-valley of acceleration modulus, and the Weinberg model and the Mahony algorithm in PDR are used to estimate step length and heading. On this basis, we evaluated the performance of GNSS/PDR fusion positioning in an open scenario, a semiopen scenario, and a blocked scenario, respectively. Finally, we develop a GNSS/PDR real-time positioning software, called China University of Mining and Technology-POSitioning (CUMT-POS) version 1.0, on the Android 10 platform. By comparing GNSS solutions, PDR solutions, GNSS/PDR solutions, and real-time kinematic (RTK) solutions, we verify the potential auxiliary ability of PDR for GNSS positioning in complex environments, proving that multisource sensor fusion positioning significantly improves reliability and stability. Our research can help the realization of urban informatization and smart cities.

Data and Service Security of GNSS Sensors Integrated with Cryptographic Module.

Navigation and positioning are of increasing importance because they are becoming a new form of infrastructure. To ensure both development and security, this study designed a technical innovation structure to upgrade the GNSS (Global Navigation Satellite System) data transmission and real-time differential correction service system and proposed a new multiple cryptographic fusion algorithm to achieve the encryption and decryption of GNSS data and services. First, a GNSS station encrypts GNSS data with an encryption key and obtains a public key from a GNSS data center to encrypt the GNSS data encryption key. After that, identity authentication of a GNSS station is carried out, and an SSL VPN is established between the GNSS station and a GNSS data center before GNSS data are transmitted to the GNSS data center. Then, the GNSS data center decrypts the received GNSS data. The process of an intelligent terminal for real-time differential corrections is similar to that of the GNSS station and the GNSS data center. A GNSS sensor integrated with a cryptographic module was developed to validate the structure in an open environment. The results showed that the developed GNSS sensor was successful in encrypting the data, and the GNSS data center was able to decrypt the data correctly. For the performance test, a cryptography server was able support the requirements of GNSS applications. However, a cryptography server was optimal in supporting 40~50 GNSS stations simultaneously, whereas a cluster was suggested to be configured if the number of GNSS stations was more than 60. In conclusion, the method was able to ensure the validity, confidentiality, integrity, and non-repudiation of GNSS data and services. The proposed upgrading technology was suitable for coordinating GNSS development and security.

Characterization of Thermal and Electrical Transport in 6.4 nm Au Films on Polyimide Film and Fiber Substrates.

The surface and grain boundary scattering impact on the electrical and thermal conduction in the thin metallic films coated on organic substrates has not been studied thoroughly. In this work, we study heat and electron transport in the 6.4 nm thin Au films supported by polyimide (PI) substrate using the transient electro-thermal technique. Thermal and electrical conductivities of 6.4 nm thin Au film are much smaller than bulk value. The thermal and electrical conductivities of 6.4 nm Au film deposited on the PI fiber are reduced by 59.3% and 76.8% in the comparison with the value of bulk Au. For PI film, the reduction of thermal and electrical conductivities is 47.9% and 46.3%. Lorenz numbers of 6.4 nm Au film supported by PI fiber and PI film are 4.51 × 10-8 WΩK-2 and 2.12 × 10-8 WΩK-2, respectively. The thermal conductivities of PI fiber and PI film are 0.87 Wm-1K-1 and 0.44 Wm-1K-1. The results reveal that PI is a suitable substrate material in the flexible electronic devices field.

Research on Remote GPS Common-View Precise Time Transfer Based on Different Ionosphere Disturbances.

Propagation path delays are a major error for the remote precise time transfer of common view; these path delays contain the ionosphere and troposphere impact, while the contributions of the ionosphere and the troposphere from common-view satellites to receivers on the ground tend to become uncorrelated when the distance between these receivers increases. In order to select the appropriate ionospheric correction method for common view under different distances between receivers, a detailed test using multi-source data under different ionosphere disturbances are carried out in this paper. Here, we choose three different ionosphere disturbance methods and analyze the advantages and disadvantages of these methods for common-view time transfer and time comparison. At last, we put forward a suitable ionospheric correction method for different distances common view. The RMS shows that the method proposed for 3000 km remote common view can achieve 2.5 ns.

Precise Point Positioning Algorithm for Pseudolite Combined with GNSS in a Constrained Observation Environment.

In urban canyon environments, Global Navigation Satellite System (GNSS) satellites are heavily obstructed with frequent rise and fall and severe multi-path errors induced by signal reflection, making it difficult to acquire precise, continuous, and reliable positioning information. To meet imperative demands for high-precision positioning of public users in complex environments, like urban canyons, and to solve the problems for GNSS/pseudolite positioning under these circumstances, the Global Navigation Satellite System (GNSS) Precision Point Positioning (PPP) algorithm combined with a pseudolite (PLS) was introduced. The former problems with the pseudolite PPP technique with distributed pseudo-satellites, which relies heavily on known points for initiation and prerequisite for previous high-precision time synchronization, were solved by means of a real-time equivalent clock error estimation algorithm, ambiguity fixing, and validation method. Experiments based on a low-cost receiver were performed, and the results show that in a weak obstructed environment with low-density building where the number of GNSS satellites was greater than seven, the accuracy of pseudolite/GNSS PPP with fixed ambiguity was better than 0.15 m; when there were less than four GNSS satellites in severely obstructed circumstances, it was impossible to obtain position by GNSS alone, but with the support of a pseudolite, the accuracy of PPP was able to be better than 0.3 m. Even without GNSS, the accuracy of PPP could be better than 0.5 m with only four pseudolites. The pseudolite/GNSS PPP algorithm presented in this paper can effectively improve availability with less GNSS or even without GNSS in constrained environments, like urban canyons in cities.

Concrete Condition Assessment Using Impact-Echo Method and Extreme Learning Machines.

The impact-echo (IE) method is a popular non-destructive testing (NDT) technique widely used for measuring the thickness of plate-like structures and for detecting certain defects inside concrete elements or structures. However, the IE method is not effective for full condition assessment (i.e., defect detection, defect diagnosis, defect sizing and location), because the simple frequency spectrum analysis involved in the existing IE method is not sufficient to capture the IE signal patterns associated with different conditions. In this paper, we attempt to enhance the IE technique and enable it for full condition assessment of concrete elements by introducing advanced machine learning techniques for performing comprehensive analysis and pattern recognition of IE signals. Specifically, we use wavelet decomposition for extracting signatures or features out of the raw IE signals and apply extreme learning machine, one of the recently developed machine learning techniques, as classification models for full condition assessment. To validate the capabilities of the proposed method, we build a number of specimens with various types, sizes, and locations of defects and perform IE testing on these specimens in a lab environment. Based on analysis of the collected IE signals using the proposed machine learning based IE method, we demonstrate that the proposed method is effective in performing full condition assessment of concrete elements or structures.

The effect of temperature on cell growth and astaxanthin accumulation of Haematococcus pluvialis during a light-dark cyclic cultivation.

Haematococcus pluvialis is the best source of natural astaxanthin known as "the king of antioxidants". The mass outdoor culture is the most workable strategy for astaxanthin production, but the effects of daytime and night temperatures on the biomass concentration and astaxanthin content of H. pluvialis have received little attention. This study indicated that, raising the daytime or night temperature could stimulate night accumulation of astaxanthin until temperature up to 28°C; the night biomass loss increased firstly and then decreased along with the daytime temperature reducing; decreasing the night temperature can lessen night biomass loss; the daytime temperature of 28°C and the night temperature below 28°C were optimal for achieving high biomass and astaxanthin content. Subsequently, the outdoor culture strategy has been improved and can increase the net biomass and astaxanthin productivities by 5 and 2.9-fold as compared to the former strategy.

Ameloblastic carcinoma: An analysis of 12 cases with a review of the literature.

The diagnosis of ameloblastic carcinoma is often difficult and the optimal treatment methods remain controversial. The current study retrospectively investigated the optimal diagnosis and treatment methods of 12 ameloblastic carcinoma patients at the West China Hospital of Stomatology, Sichuan University (Chengdu, China), and 20 patients selected from the PubMed database, were reviewed. The clinical features, diagnosis and outcome of the different treatments were evaluated. Ameloblastic carcinoma occurred in 12 out of a total of 538 ameloblastoma patients; the majority were of the primary type. Of the 538 ameloblastoma patients, 294 were male, 244 were female with a male to female ratio of 1.2:1. The predilection age is 20-30 years, which accounts for 40% of the total. In total, 461 cases were in the mandible and 77 were located in the maxilla. The cure rate of the primary type and the recurrence rate of the secondary type tumors were higher in the patients from the West China Hospital of Stomatology compared with those reported in the literature. In particular, a case with a long-term survival of 30 years is presented, which is considered to be relatively rare. The evolution of the clinical course has experienced three stages: Ameloblastoma (1978) followed by metastatic ameloblastoma (2000) and finally ameloblastic carcinoma (2008). To avoid recurrence, wide local excision with postoperative radiation therapy is required. While novel therapeutic regimens should also be considered as appropriate, including carbon ion therapy and Gamma Knife stereotactic radiosurgery. However, controlled studies with larger groups of patients are required to increase the accuracy of results.