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The stock indexes are an important issue for investors, and in this paper good trading strategies will be aimed to be adopted according to the accurate prediction of the stock indexes to chase high returns.

To avoid the problem of insufficient financial data for daily stock indexes prediction during modeling, a data augmentation method based on time scale transformation (DATT) was introduced. After that, a new deep learning model which combined DATT and NGRU (DATT-nested gated recurrent units (NGRU)) was proposed for stock indexes prediction. The proposed models and their competitive models were used to test the stock indexes prediction and simulated trading in five stock markets of China and the United States.

The experimental results demonstrated that both NGRU and DATT-NGRU outperformed the other recurrent neural network (RNN) models in the daily stock indexes prediction.

A novel RNN with NGRU and data augmentation is proposed. It uses the nested structure to increase the depth of the deep learning model.

The micro-vision system is designed for micro-fabrication. This system with force sensor controls micro-fabrication operation. The focus is calculated by one order moment. Gradient evaluation function and frequency domain evaluation function are combined as evaluation function in auto-focus technology. Image definition evaluation function based on gradient is adopted in large step. Image definition evaluation function based on frequency-domain is adopted in small step. Search strategy adopts threshold method and curve fitting method. Edge invariant moment is to recognize objects. The system can measure the distance of three dimensions between the cutting tool and the work-piece. Then the micro-fabrication operation is completed.

The purpose of this paper is to describe how the authors gained a better understanding of the variety of library users' data needs, and how gradually some new data services were established based on current capabilities.

This paper uses a case study of the new data services at the John Cotton Dana Library, at Rutgers, The State University of New Jersey, Newark campus, to demonstrate the possible ways to extend data reference services and provide data computing services. A content analysis of services records shows how each user group falls into the multiple data services levels and subcategories.

Library users can be classified into many different categories, and each of these may have different needs. Research centers might have big projects involving data gathering and applications where a librarian can mainly provide consultation; while an individual faculty member or student might need the librarians as research partners, with help for their specific problems. Computing data services can involve group training and statistical analysis assistance, where researchers need emergent help. Data librarians can take various opportunities for data management education, thereby gradually raising awareness and cultivating better research habits among researchers.

Library data computing services can make unique contributions to faculty and students' research and study. Institution, library and users' interaction determines the levels and extent of data services and is generalized from the description and analysis of typical data service examples. Classic concept of data services levels is applied to a concrete case of data services program, and sub‐categories of each data services level and user types are developed based on the authors' services record.

The purpose of this paper is to present a conference report on the unique organizational features and the common themes found among the three keynote speeches of the Library 2.011 World Wide Virtual Conference held on the internet on November 2‐4, 2011.

This report was generated based on the author’s personal participation and observation of a virtual conference and a descriptive method was used to report on and summarize the major subjects of three keynote presentations.

The paper finds that Library 2.0 is still a live practice among libraries, and the concept itself has become an inspiring theoretical starting point for re‐examining information profession, information literacy, and information management behaviours.

This article sorts out the theoretical directions of Library 2.0’s research, which will provide a reflective and guiding tool for evaluating current library practice and designing future innovative library services.

The classical advection-dispersion equation (ADE) model cannot accurately depict the gas transport process in natural geological formations. This paper aims to study the behavior of CO₂ transport in fractal porous media by using an effective Hausdorff fractal derivative advection-dispersion equation (HFDADE) model.

Anomalous dispersion behaviors of CO₂ transport are effectively characterized by the investigation of time and space Hausdorff derivatives on non-Euclidean fractal metrics. The numerical simulation has been performed with different Hausdorff fractal dimensions to reveal characteristics of the developed fractal ADE in fractal porous media. Numerical experiments focus on the influence of the time and space fractal dimensions on flow velocity and dispersion coefficient.

The physical mechanisms of parameters in the Hausdorff fractal derivative model are analyzed clearly. Numerical results demonstrate that the proposed model can well fit the history of gas production data and it can be a powerful technique for depicting the early arrival and long-tailed phenomenon by incorporating a fractal dimension.

To the best of the authors’ knowledge, first time these results are presented.

An optimal solution method based on 2-norm is proposed in this study to solve the inverse kinematics multiple-solution problem caused by a high redundancy. The current research also presents a motion optimization based on the 2-Norm of high-redundant mobile humanoid robots, in which a kinematic model is designed through the entire modeling.

The current study designs a highly redundant humanoid mobile robot with a differential mobile platform. The high-redundancy mobile humanoid robot consists of three modular parts (differential driving platform with two degrees of freedom (DOF), namely, left and right arms with seven DOF, respectively) and has total of 14 DOFs. Given the high redundancy of humanoid mobile robot, a kinematic model is designed through the entire modeling and an optimal solution extraction method based on 2-norm is proposed to solve the inverse kinematics multiple solutions problem. That is, the 2-norm of the angle difference before and after rotation is used as the shortest stroke index to select the optimal solution. The optimal solution of the inverse kinematics equation in the step is obtained by solving the minimum value of the objective function of a step. Through the step-by-step cycle in the entire tracking process, the kinematic optimization of the highly redundant humanoid robot in the entire tracking process is realized.

Compared with the before and after motion optimizations based on the 2-norm algorithm of the robot, its motion after optimization shows minimal fluctuation, improved smoothness, limited energy consumption and short path during the entire mobile tracking and operating process.

In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot.

In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot.

In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot.

Motion optimization based on the 2-norm of a highly redundant humanoid mobile robot with the entire modeling is performed on the basis of the entire modeling. This motion optimization can make the highly redundant humanoid mobile robot’s motion path considerably short, minimize energy loss and shorten time. These researches provide a theoretical basis for the follow-up research of the service robot, including tracking and operating target, etc. Finally, the motion optimization algorithm is verified by the tracking and operating behaviors of the robot and an example.