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Optical detection methods such as Rayleigh-Brillouin scattering spectrum can be used for physical parameter measurement in solids, liquids, and gas. In this paper, a new method based on spectral characteristics is proposed to realize temperature and pressure retrieval simultaneously in gas. The characteristics of Rayleigh-Brillouin spectrum are firstly utilized to establish the retrieval model by fitting Tenti-S6 line shape with 3Voigt model at different temperatures and pressures, and then deriving the retrieval equations via regression fitting procedure. Through theoretical and measured error analyses, the characteristic retrieval model based on Rayleigh linewidth and the whole linewidth of Rayleigh-Brillouin scattering spectrum is shown to be optimal. Afterward, the retrieval model is verified using the experimental Rayleigh-Brillouin scattering spectra of N2 and air. The results indicate that, compared with the current method based on the whole linewidth or line shape of spectrum, the proposed method not only produces lower theoretical and retrieval errors but also can simultaneously retrieve the temperature and pressure of gases. The novel retrieval method provides a new idea for obtaining valuable information on gas parameters and promotes the application of Brillouin lidar remote sensing in meteorology and space science.

The customized bus (CB) transit is recognized as an effective transportation mode offering more flexible and demand-responsive service than traditional bus transit with fixed route and schedule, especially during the peak hours. The novelty of this study is the development of a mixed integer non-linear model for optimizing multi-terminal CB service in an urban setting. According to the estimated spatiotemporal passenger demand, the objective total cost, consisting of supplier's and users' costs, is minimized subject to capacity and time window constraints. A mixed bus fleet with various bus sizes is employed to accommodate passenger demand, which increases vehicle utilization and reduces supplier's cost. The inconvenience of passengers caused by early arrival at the destination is treated as penalty and considered in users' cost. The study optimization problem is combinatorial with many decision variables including trip assignment, bus routing and associated timetables, and fleet size. A hybrid genetic algorithm (HGA) which integrates the features of genetic algorithm (GA) and simulated annealing (SA) is developed to effectively search for the optimal solution. A real-world CB network is employed to demonstrate the applicability of the developed model and explore the relation between the model parameters and optimized results. It was found that the total cost can be reduced by 16.5% after employing multiple terminals and a mixed bus fleet.

Based on semantically annotated Web APIs, automatic Web API composition can be implemented easily. The operation can greatly improve efficiency of building a software system. However, in real world, semantic annotation for Web APIs will encounter various difficulties, because of their distribution and function diversity, such as disunited API description formats, response result with complex structure, shortage of business domain ontologies, semantic conflicts among distributed knowledge, and so on. To solve these difficulties, we propose a JSON-LD based Web API semantic annotation approach (JWASA). JWASA can assist professional developers to semi-automatically complete semantic annotation of Web APIs. A common Web API description ontology is firstly defined, including necessary vocabularies about invocation information, functional semantics, and non-functional features. Then, JWASA automatically converts a Web API description into a document in an united JSON format, and assist developers to semi-automatically embed semantic information of crucial elements of the API by means of a lightweight Linked Data format JSON-LD. Meanwhile, a semantic annotation specification is proposed to deal with various complex situations in Web API description, e.g: too many response parameters, no request parameters, etc. In addition, to improve efficiency of annotation, JWASA provides some extra operations, including automatic new ontology or vocabulary creation, automatic functional semantics extraction etc. Also, JWASA provides semi-automatically bridge rule generation algorithm, which can infer implied relationships among vocabularies (e.g: sub-class, super-class, equality). JWASA focuses on the semantic annotation of functionality of Web APIs, and can create effective semantic Web APIs for future API automatic composition. We implement a prototype system and carry out a series of experiments to evaluate JWASA on real Web APIs crawled from Internet. Experiments show that our approach is effective and efficient.

Distributed consensus formation tracking problem of slow convergence and low accuracy for multiple quad rotors are solved in this paper. Continuous nonsingular terminal sliding model algorithm (CNTSMA) under Inner-Outer loop control structure is considered to deal with the control problem of nonlinear, strong coupling and underactuated characteristic of a quad rotor. For better convergence and higher tracking accuracy, an adaptive algorithm (denoted by ACNTSMA) further focused on coupling of x and y directions, with sliding model observer (SMO) to compensate system disturbances and uncertainties is proposed. Furthermore, to solve the consensus formation tracking problem, a consensus control protocol under a full-connected topology based on ACNTSMA is proposed, including formation pattern consensus controller and formation distance consensus controller. Stability theory and simulation results prove the proposed control algorithm is able to accurately achieve the first-order (position and velocity) consensus for multiple quad rotors' formation tracking. Besides, stability analysis of the proposed consensus control protocol illustrates that all sliding modes with finite-time stability applicable to second-order integral models are supposed to be established. And the proposed controller also has better convergence and faster response speed with no chattering for trajectory tracking.

Cruise ships are widely used in water quality monitoring but suffer from path planning problems in a surface water environment. Solutions to path planning problems have higher requirements of path planning distance and path planning time and the ability of real-time obstacles avoidance. This paper introduces a hybrid path planning method to solve the path planning problem when using unmanned cruise ships. First, a model of the surface water environment with unknown districts is established by the grid method. Then, the global path is planned by the A* algorithm based on such a model, and in unknown areas of the model, the artificial potential filed (APF) is employed for local path planning. The problem of obtaining unreachable targets and falling into a local minimum introduced by the APF is improved by using the optimized repulsion potential field function and adding the directional random escape strategy. The A* algorithm with self-learning ability is proposed for secondary planning and cases where a local path cannot be generated. Finally, the optimal path combined with the global path and the local path is smoothed. The simulation results show that the proposed algorithm has better performance than other algorithms from the aspects of distance cost and time cost.

Virtual base stations (BS) with scalable resources and flexible functions are necessary for the fifth-generation and future mobile systems. The virtualization platform is the fundamental component of virtual BSs and plays a very important role in determining BS performance. As BS virtualization platforms can be provided by both conventional BS manufactures and third-party software vendors, it is crucial to define unified methodology to evaluate the performance of different virtualization platforms. In this paper, for the first time in literature, we design a set of comprehensive performance metrics and propose evaluation methods for BS virtualization platforms. More specifically, there are two types of metrics, i.e., micro level and macro level metrics. Micro level metrics quantify the virtualization platforms’ basic performances including real-time performance and virtualization overhead. Macro level metrics quantify the platforms ability to support BS resource and function virtualization while satisfying the radio access network requirements. Correspondingly, two-level evaluation methodology is designed to collect micro and macro level metrics from different parts of a virtual BS by running proper workloads. Finally, using the proposed methodology, two representative virtualization platforms, i.e., KVM hypervisor and Super BS virtualization platform are evaluated. These experiments verify that the proposed methodology can effectively evaluate the performance of different platforms to provide a valuable reference for the selection of virtual BS platforms. Moreover, the proposed evaluation methodology is a significant step toward constructing an open ecosystem for radio access networks.