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The purpose of this study is to master the development process and the construction effectiveness of backbone circulation network in an all-round way, formulate regional logistics development planning as well as promote the development of logistics industry by scientifically evaluating the logistics development of node cities with a view to analyzing their spatial differentiation features.

In this paper, an integrated evaluation model is constructed by adopting factor analysis, gray target decision-making model based on cone volume and other methods so as to evaluate the logistics development of node cities. The dimensionality of three-dimensional panel data is reduced by factor analysis at first. Then, the gray target decision-making method based on cone volume is adopted to evaluate the development of node cities, whose evaluation results are carried out through the clustering analysis. The clustering analysis is used to determine the development level of node cities and to extract the spatial differentiation features of node cities.

The results show that the proposed model can comprehensively evaluate the logistics level of node cities and clarify the overall logistics development and spatial differentiation of node cities, which could provide objective evidence for formulating national policies as well as promoting the balanced and coordinated development of regional logistics in China.

The paper succeeds in overcoming the disadvantages of existing methods assessing the logistics development level, such as principal component analysis and factor analysis, which are not applicable to panel data.

The purpose of this paper is to propose a grey target decision model based on cobweb area in order to overcome the effect and influence from the extreme value of the index on the decision result. However, it does not take into account the impact of the correlation between indicators on the angle of the index, and produce a certain degree decision information distortion as a result of the equal angle between the indicators. In order to solve the above problems, a novel grey decision-making model based on cone volume is proposed.

In this paper, the model uses the whitening weight function to whiten the interval grey number, and the Delphi method and the maximal entropy method are exploited to integrate the weight of the index. On the basis of this, the center of the bull’s eye, the weight and the index value are constructed as the center circle, the radius, and the high cone, respectively. The scheme is selected by the volume of the cone, the decision is made according to the order relation, and the example is utilized to prove and analyze the validity of the proposed model.

The results show that the proposed model can well improve the traditional grey target decision-making model from the modeling object and modeling method.

The method exposed in the paper can be used to deal with the grey target decision-making problems which characteristics are multi-indexes, and the attribute values are interval grey numbers.

The paper succeeds in overcoming the disadvantages of grey target decision making based on the target center distance and the cobweb area.

Fractional Fokker-Planck equation (FFPE) and time fractional coupled Boussinesq-Burger equations (TFCBBEs) play important roles in the fields of solute transport, fluid dynamics, respectively. Although there are many methods for solving the approximate solution, simple and effective methods are more preferred. This paper aims to utilize Laplace Adomian decomposition method (LADM) to construct approximate solutions for these two types of equations and gives some examples of numerical calculations, which can prove the validity of LADM by comparing the error between the calculated results and the exact solution.

This paper analyzes and investigates the time-space fractional partial differential equations based on the LADM method in the sense of Caputo fractional derivative, which is a combination of the Laplace transform and the Adomian decomposition method. LADM method was first proposed by Khuri in 2001. Many partial differential equations which can describe the physical phenomena are solved by applying LADM and it has been used extensively to solve approximate solutions of partial differential and fractional partial differential equations.

This paper obtained an approximate solution to the FFPE and TFCBBEs by using the LADM. A number of numerical examples and graphs are used to compare the errors between the results and the exact solutions. The results show that LADM is a simple and effective mathematical technique to construct the approximate solutions of nonlinear time-space fractional equations in this work.

This paper verifies the effectiveness of this method by using the LADM to solve the FFPE and TFCBBEs. In addition, these two equations are very meaningful, and this paper will be helpful in the study of atmospheric diffusion, shallow water waves and other areas. And this paper also generalizes the drift and diffusion terms of the FFPE equation to the general form, which provides a great convenience for our future studies.

The purpose of this paper is to build cyber-physical-psychological ternary fusion crowd intelligence network and realize comprehensive, real, correct and synchronous projection in cyber–physical–psychological ternary fusion system. Since the network of crowd intelligence is the future interconnected network system that takes on the features of large scale, openness and self-organization. The Digital-selfs in the network of crowd intelligence interact and cooperate with each other to finish transactions and achieve co-evolution eventually.

To realize comprehensive, real, correct and synchronous projection between cyber–physical–psychological ternary fusion system, the authors propose the rules and methods of projection from real world to the CrowdIntell Network. They build the mental model of the Digital-self including structure model and behavior model in four aspects: identity, provision, demand and connection, thus forming a theoretical mental model framework of Digital-self.

The mental model is excepted to lay a foundation for the theory of modeling and simulation in the research of crowd science and engineering.

This paper is the first one to propose the mental model framework and projection rules and methods of Digital-selfs in network of crowd intelligence, which lays a solid foundation for the theory of modeling, simulation, intelligent transactions, evolution and stability of CrowdIntell Network system, thus promoting the development of crowd science and engineering.

The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell.

In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making.

The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest.

In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.

The purpose of this paper is to detect abnormal data of complex and sophisticated industrial equipment with sensors quickly and accurately. Due to the rapid development of the Internet of Things, more and more equipment is equipped with sensors, especially more complex and sophisticated industrial equipment is installed with a large number of sensors. A large amount of monitoring data is quickly collected to monitor the operation of the equipment. How to detect abnormal data quickly and accurately has become a challenge.

In this paper, the authors propose an approach called Multiple Group Correlation-based Anomaly Detection (MGCAD), which can detect equipment anomaly quickly and accurately. The single-point anomaly degree of equipment and the correlation of each kind of data sequence are modeled by using multi-group correlation probability model (a probability distribution model which is helpful to the anomaly detection of equipment), and the anomaly detection of equipment is realized.

The simulation data set experiments based on real data show that MGCAD has better performance than existing methods in processing multiple monitoring data sequences.

The MGCAD method can detect abnormal data quickly and accurately, promote the intelligent level of smart articles and ultimately help to project the real world into cyber space in CrowdIntell Network.

The purpose of this study is to examine the effects of internal audit function (IAF) quality on the operational efficiency of Chinese firms.

The authors use regression models with a sample of Chinese listed companies to test their research hypotheses.

The authors find that IAF quality is positively associated with firm operational efficiency. The result is unchanged after correcting for endogeneity via the instrumental variable method and using an alternative measure of firm operational efficiency. The authors show that IAF competence improves firm operational efficiency, but the relationship between IAF independence and firm operational efficiency is insignificant. Additionally, they find that IAF quality can only significantly improve firm operational efficiency in the presence of effective corporate governance at the firm level and strong institutions at the province level. Using path analysis, the authors find that an IAF can improve firm operational efficiency directly or indirectly by promoting firm internal control quality.

The findings of this study suggest the need for a balance between IAF competence and independence to achieve the goals of IAF. Additionally, the authors study suggests that the effectiveness of IAF is contingent on corporate governance and market-based institutions.

The study’s findings contribute to the burgeoning literature on the relationship between IAF and firm operational performance and deepen the authors’ understanding of the role of IAF in an emerging economy whose government plays a major role in promoting and enforcing internal audits. The study also empirically support the Internal Audit Governance Maturity Model proposed by the Institute of Internal Auditors.

Today’s software engineers often work in teams to develop complex software systems. Therefore, successful software engineering in practice require team members to possess not only sound programming skills such as analysis, design, coding and testing but also soft skills such as communication, collaboration and self-management. However, existing examination-based assessments are often inadequate for quantifying students’ soft skill development. The purpose of this paper is to explore alternative ways for assessing software engineering students’ skills through a data-driven approach.

In this paper, the exploratory data analysis approach is adopted. Leveraging the proposed online agile project management tool – Human-centred Agile Software Engineering (HASE), a study was conducted involving 21 Scrum teams consisting of over 100 undergraduate software engineering students in multi-week coursework projects in 2014.

During this study, students performed close to 170,000 software engineering activities logged by HASE. By analysing the collected activity trajectory data set, the authors demonstrate the potential for this new research direction to enable software engineering educators to have a quantifiable way of understanding their students’ skill development, and take a proactive approach in helping them improve their programming and soft skills.

To the best of the authors’ knowledge, there has yet to be published previous studies using software engineering activity data to assess software engineers’ skills.

In the high-altitude, high-voltage electromagnetic interference operation environment, due to the parameters perturbation for robot control model caused by uncertainties and disturbances, and with the poor effective of the conventional proportional–integral–derivative (PID) control to parameters perturbation system, the mathematical model of power cable live operation robot joint PID closed-loop control system is established.

The corresponding joint motion robust PID control method is also proposed based on Kharitonov theory, the system robust stability conditions including the sufficient and necessary conditions are deduced and obtained and the solving process of robust PID control parameters stability region is provided.

Finally, the simulation research on robot joint motion PID control system is also launched in MATLAB environment based on Kharitonov theory. The results show that the conventional PID control obtains better control effect only to nominal model but is ineffective to parameter perturbation system, while robust PID obtains sound control effect to parameter perturbation system. Compared with H8 robust PID, the Kharitonov robust PID has better control effect which meet the system design requirements of joint motor quickly response, high tracking accuracy and sound stability. Finally, the validity and engineering practicability are verified by 220-kV living replacing damper operation experiment.

This paper has described the development of a damper replacement power cable live maintenance robot experimental prototype, which greatly improves operation efficiency and deals with the safety problem of operation in a high-voltage environment. A general manipulator motion control model of the power cable robot is established; the Kharitonov theory-based parameter perturbation robust motion control method of damper replacement robot is also obtained. Through the simulation comparison, it is verified that the Kharitonov control has more superiority for dealing with the parameter perturbation systems under the premise of ensuring the stability motion. The field experiment has further confirmed the engineering practicability.