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This paper aims to propose an environmentally adaptive trajectory planning system considering the dynamic characteristics of unmanned aerial vehicles (UAVs) and the distance between obstacles and the UAV. The system generates a smooth and safe flight trajectory online.

First, the hybrid A* search method considering the dynamic characteristics of the quadrotor is used to find the collision-free initial trajectory. Then, environmentally adaptive velocity cost is designed for environment-adaptive trajectory optimization using environmental gradient data. The proposed method adaptively adjusts the autonomous flight speed of the UAV. Finally, the initial trajectory is applied to the multi-layered optimization framework to make it smooth and dynamically viable.

The feasibility of the designed system is validated by online flight experiments, which are in unknown, complex situations.

The proposed trajectory planning system is integrated into a vision-based quadrotor platform. It is easily implementable onboard and computationally efficient.

A hybrid A* path searching method is proposed to generate feasible motion primitives by dispersing the input space uniformly. The proposed method considers the control input of the UAV and the search time as the heuristic cost. Therefore, the proposed method can provide an initial path with the minimum flying time and energy loss that benefits trajectory optimization. The environmentally adaptive velocity cost is proposed to adaptively adjust the flight speed of the UAV using the distance between obstacles and the UAV. Furthermore, a multi-layered environmentally adaptive trajectory optimization framework is proposed to generate a smooth and safe trajectory.

The purpose of this paper is to present a solution space searching method to study the initial design of interplanetary low thrust gravity assist trajectory.

For reducing the complexity and nonlinearity of the initial design problem, a sixth degree inverse polynomial shape based approach is brought. Then some improvements are provided for solving the parameters in the shape function and a quasi‐lambert solver is brought through the shape based method, the thrust profile can be generated under the given time of flight, boundary states including positions and velocities for low thrust phase. Combining gravity assist model, the problem is summarized and an improved pruning technique is used for searching the feasible solution space for low thrust gravity assist trajectory.

Using the solution space searching method, the feasible solution region would be generated under the given mission condition. The treatment about gravity assist demonstrates more accurate than previous method. Also another advantage is that the searching method can be used to design different types of mission trajectory, including flyby and rendezvous trajectories.

The method can be used as an efficient approach to search the feasible region for the complex low thrust gravity assist trajectory, and it can provide appropriate initial guesses for the low thrust gravity assist trajectory in mission design phase.

Feasible solution space would be obtained through the searching method. The quasi‐Lambert solver in the paper is found under the shape‐based method and relative improvement, and it shows its availability during the searching process. Through mission trajectory design, the effectiveness of the method is shown.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

This study aims to present a new web page recommendation system that can help users to reduce navigational time on the internet.

The proposed design is based on the primacy effect of browsing behavior, that users prefer top ranking items in search results. This approach is intuitive and requires no training data at all.

A user study showed that users are more satisfied with the proposed search methods than with general search engines using hot keywords. Moreover, two performance measures confirmed that the proposed search methods out‐perform other metasearch and search engines.

The research has limitations and future work is planned along several directions. First, the search methods implemented are primarily based on the keyword match between the contents of web pages and the user query items. Using the semantic web to recommend concepts and items relevant to the user query might be very helpful in finding the exact contents that users want, particularly when the users do not have enough knowledge about the domains in which they are searching. Second, offering a mechanism that groups search results to improve the way search results are segmented and displayed also assists users to locate the contents they need. Finally, more user feedback is needed to fine‐tune the search parameters including α and β to improve the performance.

The proposed model can be used to improve the search performance of any search engine.

First, compared with the democratic voting procedure used by metasearch engines, search engine vector voting (SVV) enables a specific combination of search parameters, denoted as α and β, to be applied to a voted search engine, so that users can either narrow or expand their search results to meet their search preferences. Second, unlike page quality analysis, the hyperlink prediction (HLP) determines qualified pages by simply measuring their user behavior function (UBF) values, and thus takes less computing power. Finally, the advantages of HLP over statistical analysis are that it does not need training data, and it can target both multi‐site and site‐specific analysis.

Many search engines in digital libraries are restricted to the terms presented in users’ queries. When users cannot represent their information needs in terms of keywords in a query, the search engine fails to provide appropriate results. In addition, most search engines do not have the ability to visualize search results for users to help them in their information journey. The purpose of this paper is to develop a new approach for search result visualization in digital libraries. The visualization approach enables subject-based visualization of search results and search queries.

To enable subject-based visualization of search results in digital libraries, new subject-based document retrieval is proposed in which each document is represented as a vector of subjects as well. Then, using a vector space model for information retrieval, along with the subject-based vector, related documents to the user’s query are retrieved, whilst each document is visualized through a ring chart, showing the inherent subjects within each document and the query.

The proposed subject-based retrieval and visualization approach is evaluated from various perspectives to amplify the impact of the visualization approach from users’ opinions. Users have evaluated the performance of the proposed subject-based retrieval and search result visualization, whilst 67% of users prefer subject-based document retrieval and 80% of them believe that the proposed visualization approach is practical.

This research has provided a subject-based representation scheme for search result visualization in a digital library. The implication of this research can be viewed from two perspectives. First, the subject-based retrieval approach provides an opportunity for the users to understand their information needs, beyond the explicit terms in the query, leading to results, which are semantically relevant to the query. Second, the simple subject-based visualization scheme, helps users to explore the results easily, whilst allowing them to build their knowledge experience.

A new vectorized subject-based representation of documents and queries is proposed. This representation determines the semantic and subject-based relationship between a given query and documents within a digital scientific library. In addition, it also provides a subject-based representation of the retrieved documents through which users can track the semantic relationship between the query and retrieve documents, visually.

The purpose of this paper is to search for the critical-scenarios of autonomous vehicles (AVs) quickly and comprehensively, which is essential for verification and validation (V&V).

The author adopted the index F1 to quantitative critical-scenarios' coverage of the search space and proposed the improved particle swarm optimization (IPSO) to enhance exploration ability for higher coverage. Compared with the particle swarm optimization (PSO), there were three improvements. In the initial phase, the Latin hypercube sampling method was introduced for a uniform distribution of particles. In the iteration phase, the neighborhood operator was adapted to explore more modals with the particles divided into groups. In the convergence phase, the convergence judgment and restart strategy were used to explore the search space by avoiding local convergence. Compared with the Monte Carlo method (MC) and PSO, experiments on the artificial function and critical-scenarios search were carried out to verify the efficiency and the application effect of the method.

Results show that IPSO can search for multimodal critical-scenarios comprehensively, with a stricter threshold and fewer samples in the experiment on critical-scenario search, the coverage of IPSO is 14% higher than PSO and 40% higher than MC.

The critical-scenarios' coverage of the search space is firstly quantified by the index F1, and the proposed method has higher search efficiency and coverage for the critical-scenarios search of AVs, which shows application potential for V&V.

Summer vacation employment plays an important role in the financial survival of students in higher education. Examines what job search methods are used and questionnaire evidence is analysed to establish how success in job search is dependent on a number of control and job search variables. Finds that for students seeking temporary full‐time employment, a search process including either the use of Job Centres and/or responses to newspaper advertisements increases the probability of gaining work. However, females were found to be less likely to gain full‐time temporary work than males. The success of those students seeking part‐time employment was improved by the use of a private employment agency. A mature student was found to be more likely to obtain a job in all of the models.

The goal of this research is to investigate the convergence behavior of the Newton iteration, when solving the nonlinear problem with consideration of hysteresis effects. Incorporating the vector hysteresis model in the magnetic vector potential formulation has encountered difficulties. One of the reasons is that the Newton method is very sensitive regarding the starting point and states distinct requirements for the nonlinear function in terms of monotony and smoothness. The other reason is that the differential reluctivity tensor of the material model is discontinuous due to the properties of the stop operators. In this work, line search methods to overcome these difficulties are discussed.

To stabilize the Newton iteration, line search methods are studied. The first method computes an error-oriented search direction. The second method is based on the Wolfe-Powell rule using the Armijo condition and curvature condition.

In this paper, the differentiation of the vector stop model, used to evaluate the Jacobian matrix, is studied. Different methods are applied for this nonlinear problem to ensure reliable and stable finite element simulations with consideration of vector hysteresis effects.

In this paper, two different line search Newton methods are applied to solve the magnetic field problems with consideration of vector hysteresis effects and ensure a stable convergence successfully. A comparison of these two methods in terms of robustness and efficiency is presented.

Examines the development of online public access catalogues of the last 15 years and how this has promoted the use of automated information retrieval systems. Investigates how end‐users use the system available to them and the type of subject searches which they carry out. Compares two techniques for mapping searches. Concludes that there is a need for effective diagnosis and monitoring methods and an efficient method of analysis of end‐user use is essential.