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High-speed Indium Phosphide (InP) HBTs have been widely used to design high-speed analog, digital and mixed-signal integrated circuits. The purpose of this study is to propose a new parameter extraction procedure for determining an improved T-topology small-signal equivalent circuit of InP heterojunction bipolar transistors (HBTs).

The alternating current crowding effect is considered through adding the intrinsic base capacitance in the small-signal equivalent circuit. All of the circuit parameters are extracted directly without using any approximation.

The extraction technique is more easily understood and clearer than other extraction methods, as the equations are derived from the S-parameters by peeling peripheral elements from small-signal models to get reduced ones and extracting each equivalent-circuit parameter using each equation.

To validate the presented parameter extraction technology, an n-p-n emitter-up InP HBT was analyzed adopting the method. Excellent agreement between measured and modeled S-parameters is obtained up to 40 GHz.

The purpose of this paper is to propose a bi‐level programming optimization model to reduce traffic congestion of transportation network while evacuating people to safe shelters during disasters or special events.

The previous optimization model for contra flow configuration only considered the character of the manager. However, the traffic condition is not only controlled by managers, but also depended on the root choice of travelers. A bi‐level programming optimization model, which considered managers and evacuees' character, is proposed to optimize the contra flow of transportation network in evacuation during special events. The upper level model aims to minimize the total evacuation time, while the lower level based on user equilibrium assignment. A solution method based on discrete particle swarm optimization and Frank‐Wolfe algorithm is employed to solve the bi‐level programming problem.

It is found that the bi‐level programming based contra flow optimization model can improve evacuation efficiency and decrease evacuation time 30 per cent or more. With the increase of traffic demand, the evacuation time will decrease significantly by contra flow configuration.

In the optimization model, the background traffic is ignored for simplification and the contra flow is configured absolutely as 0 or 1, which ensures vehicles do not go back into the evacuation area.

An efficient optimization model for traffic managers to reduce congestion and evacuation time of evacuation network.

The new bi‐level programming model not only considers managers' character, but also considers evacuees' reaction. The paper is aimed to optimize contra flow for transportation network.

Although big data analytics has reaped great business rewards, big data system design and integration still face challenges resulting from the demanding environment, including challenges involving variety, uncertainty, and complexity. These characteristics in big data systems demand flexible and agile integration architectures. Furthermore, a formal model is needed to support design and verification. The purpose of this paper is to resolve the two problems with a collective intelligence (CI) model.

In the conceptual CI framework as proposed by Schut (2010), a CI design should be comprised of a general model, which has formal form for verification and validation, and also a specific model, which is an implementable system architecture. After analyzing the requirements of system integration in big data environments, the authors apply the CI framework to resolve the integration problem. In the model instantiation, the authors use multi-agent paradigm as the specific model, and the hierarchical colored Petri Net (PN) as the general model.

First, multi-agent paradigm is a good implementation for reuse and integration of big data analytics modules in an agile and loosely coupled method. Second, the PN models provide effective simulation results in the system design period. It gives advice on business process design and workload balance control. Third, the CI framework provides an incrementally build and deployed method for system integration. It is especially suitable to the dynamic data analytics environment. These findings have both theoretical and managerial implications.

In this paper, the authors propose a CI framework, which includes both practical architectures and theoretical foundations, to solve the system integration problem in big data environment. It provides a new point of view to dynamically integrate large-scale modules in an organization. This paper also has practical suggestions for Chief Technical Officers, who want to employ big data technologies in their companies.

The purpose of this paper is to attempt to solve a decision‐making problem for breeding target character showed as an interval number.

A new comprehensive evaluation method was proposed based on similarity‐difference theory and interval number theory. The data from Winter Wheat Group I Variety Regional Test in Henan Province in 2009‐2010 were analysed using the proposed method.

The results showed that Zhou 99233 was a good variety, Yuxhan No.7, An 05‐28, Xun K8, Jinyumai 378 and Zhoumai 18 were better ones, 08 luo 36, and Xuke 718 ordinary ones, and others worse ones. Based on this, the feasibility of the method was discussed. It showed that the proposed method had some obvious merits, such as arithmetic was simple, operation convenient, flexible and practical, fast and effective, etc.

Application to a living example indicated that its evaluation effect was satisfactory. Consequently, the application prospect of the method will be very vast.

The paper succeeds in solving a decision‐making problem for breeding target character shown as an interval number.

This paper aims to study the evolution of innovation-based dynamic capabilities in informal copycat-style firms. As a kind of informal economical organizations, copycat-style firms in many emerging economies play an important role in their development of the economics. The development of Shanzhai firms, Chinese-style copycat firms, from imitation to innovation has become an important micro-foundation of China’s economic growth and the manufacturing development. With the cluster development of the Chinese mobile phone industry as the macro and industrial environment background, this paper chose Beijing Tianyu Communication Equipment Co. Ltd as the typical example of innovation in Shanzhai firms and studied the evolution of innovation-based dynamic capabilities in this company.

This paper chose Beijing Tianyu Communication Equipment Co. Ltd as the typical example of innovation in Shanzhai firms and studied the evolution of innovation-based dynamic capabilities in this company by adopting the leading-edge dynamic capability theory, innovation theory and industrial cluster theory. The authors further discussed how to improve the dynamic capabilities in Shanzhai firms in China.

It is finally suggested that Shanzhai firms should reduce innovation failures and lower damage degree of dynamic capabilities through consistent innovation and paying attention to their innovation improvement.

It will be very significant to research the survival or diminishing of Shanzhai firms from a theoretical perspective, which will eventually enhance property right protection and innovation development in China.

By introducing the basic concepts and theories of the philosophy of information created by Kun Wu, and making some comparisons of the philosophy of information and related information theories between Wu and other scholars, this paper aims to have Chinese philosophy of information widely known and understood by more people in the world, thus promoting the international exchanges between Chinese and Western scholars on the topic of philosophy of information.

The main research methods used in this paper are the literature review and the comparative study. On the one hand, it reviews some related concepts and theories in Kun Wu's academic works of philosophy of information. On the other hand, it compares the thoughts and viewpoints of Kun Wu with those of other scholars.

First, Kun Wu is the first person who has established a complete and comprehensive theoretical system of philosophy of information in China; second, Kun Wu's philosophy of information is significant in originality and value, which could be thought as the intellectual quintessence of information age, thus worth learning. Third, with more international exchanges, Chinese philosophy of information created by Wu will surely be more and more influential in philosophical circles at home and abroad.

It is a very valuable first-hand material for Western scholars to know and understand Chinese philosophy of information.

The focus of this paper is in Q-Lasso introduced in Alghamdi et al. (2013) which extended the Lasso by Tibshirani (1996). The closed convex subset Q belonging in a Euclidean m-space, for m∈IN, is the set of errors when linear measurements are taken to recover a signal/image via the Lasso. Based on a recent work by Wang (2013), we are interested in two new penalty methods for Q-Lasso relying on two types of difference of convex functions (DC for short) programming where the DC objective functions are the difference of l1 and lσq norms and the difference of l1 and lr norms with r>1. By means of a generalized q-term shrinkage operator upon the special structure of lσq norm, we design a proximal gradient algorithm for handling the DC l1−lσq model. Then, based on the majorization scheme, we develop a majorized penalty algorithm for the DC l1−lr model. The convergence results of our new algorithms are presented as well. We would like to emphasize that extensive simulation results in the case Q={b} show that these two new algorithms offer improved signal recovery performance and require reduced computational effort relative to state-of-the-art l1 and lp (p∈(0,1)) models, see Wang (2013). We also devise two DC Algorithms on the spirit of a paper where exact DC representation of the cardinality constraint is investigated and which also used the largest-q norm of lσq and presented numerical results that show the efficiency of our DC Algorithm in comparison with other methods using other penalty terms in the context of quadratic programing, see Jun-ya et al. (2017).

As the world's largest emerging market, the evidence of momentum effect in China is also mixed. Meanwhile, prior studies mainly examined individual stock momentum in China, with little concern for industry momentum and its relationship with trading volume. The motivation of this study is to investigate industry momentum in China and examine whether trading volume can enhance its profitability.

Firstly, the authors test the existence of industry momentum in China; secondly, the authors test the correlation between trading volume and momentum returns using the double ranking method; finally, the authors test whether trading volume enhances the momentum returns using Fama–French five-factor model.

The authors find that there is a significant industry momentum effect in China, and the momentum returns jointly come from winner and loser portfolios. The intervals between the formation and holding periods have an impact on the performance of momentum portfolios. In terms of trading volume, the authors find that high-volume industries have industry momentum effects while low-volume industries do not. The industry momentum strategies achieve higher excess returns in high-volume industries.

Prior literature found higher momentum returns in low-volume stocks in China, but the research in this study suggests that implementing an industry momentum strategy in low-volume industries will miss out on higher returns or even bring losses, and instead the investors should invest in high-volume industries to get the best performance.

This study extends existing research by focusing on industry momentum and its relationship with trading volume in the Chinese stock market and finds an interesting relationship between industry momentum returns and trading volume, which is different from related studies.

This paper aims to investigate the micro-plastic behavior of granular material in three-body friction interface and its effect on friction characteristics.

A numerical model of particle breakage in friction contact was constructed based on the discrete element method. The influence of friction pair working condition and internal bonding strength on the micro-plastic behavior of particulate matter was analyzed. A reciprocating linear tribometer was used to verify the simulation results.

The results show that when the granular materials are squeezed and sheared by the friction pair, a shear zone inclined to the left is gradually formed, which leads to particle breakage. The breakage of the particle leads to the reduction of load-bearing capacity and the increase of friction coefficient. Due to the differences in bond strength and friction pairs working conditions, the particle plastic behavior is divided into the following three states: elastic deformation, breakage and plastic rheology.

This study is helpful to understand the effect of the micro-plastic behavior of particles on the three-body friction characteristics.

This paper aims to investigate the influence of oil–air lubrication flow behavior on point contact sliding wear characteristics.

Oil–air lubrication equations between point contact counterparts were established on the basis of volume of fluid model. The effects of oil supply and injection azimuth on oil-phase volume fraction and its pressure distribution were simulated with commercial software Fluent. Characteristics of point contact sliding wear were then tested with an MFT-3000 friction tester under oil–air lubrication condition. The influence of flow behavior on wear characteristic was investigated combined with numerical and experimental results. The wear mechanism was revealed using SEM, EDS and ferrography.

When air supply speed is constant, the oil-phase volume fraction increases with the increase in oil supply, which helps form continuous oil film and decrease the sliding wear evidently. The injection angle and distance considerably influence the oil–air flow behavior. When injecting at a certain distance and angle, the oil-phase volume fraction reaches its maximum, and the abrasion loss is minimal. Under the test conditions in this study, abrasive particles are mainly debris and a few spiral cuttings. The wear mechanism is abrasive wear.

The influence of the behavior of oil–air lubrication flow on the characteristic of point contact sliding wear is analyzed. This work provides guidance for the application of oil–air lubrication technology in point contact friction pairs.