Dynamic deviation reduction‐based concurrent dual‐band digital predistortion

This article introduces the concurrent dual‐band digital predistortion (DPD) architecture with only one upconvertion unit, which is suitable for the linearization of wideband power amplifiers (PAs) excited by concurrent dual‐band signals. By extending the conventional dynamic deviation reduction (DDR) model to the concurrent dual‐band mode, we propose two DDR‐based concurrent dual‐band models, the dual‐band DDR (DB‐DDR) model and the simplified dual‐band DDR (SDB‐DDR) model. The performance of these two models is experimentally assessed with two types of wideband PAs (a GaN Class F PA and a GaN Doherty PA) driven by the concurrent dual‐band signal, and compared with the prior two‐dimensional digital predistortion (2D‐DPD) model and the two‐dimensional modified memory polynomial (2D‐MMP) model. The results prove the good DPD performance and low computational complexity of the proposed models. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:401–411, 2014.     

基于SOAP的企业异构信息系统集成

阐述了SOAP通信协议的构成和实现机制以及与相似协议的比较。基于它的跨平台的能力,将其运用于企业的分布式环境中,实现了异构信息系统间的互操作和跨部门的数据处理,提高企业数据处理的效能,同时为企业异构信息系统集成提供了新的方法。     

Evaluation of two alternative carbon capture and storage technologies: A stochastic model

In this paper we evaluate two alternative CCS technologies at a coal-fired power plant from an investor's point of view. The first technology uses CO₂ for enhanced oil recovery (EOR) paired with storage in deep saline formations (DSF) and the second merely stores CO₂ in DSF. The paper updates and improves on an earlier publication by Tzimas et al. (2005). For projects of this type there are many sources of risk, three of which stand out: the price of electricity, the price of oil and the price of carbon allowances. In this paper we develop a general stochastic model that can be adapted to other projects such as enhanced gas recovery (EGR) or industrial plants that use CO₂ for either EOR or EGR with CCS. The model is calibrated with UK data and applied to help understand the conditions that generate the incentives needed for early investments in these technologies. Additionally, we analyse the risks of these investments. Investments with EOR and secondary DSF storage can only be profitable (NPV > 0) when there is a high long-term equilibrium price for oil of more than $56.38/barrel. When the investment decision can be made at any time, i.e. there is an option value, then the trigger value for optimal investment is significantly higher.     

Challenges in real-time virtualization and predictable cloud computing

Cloud computing and virtualization technology have revolutionized general-purpose computing applications in the past decade. The cloud paradigm offers advantages through reduction of operation costs, server consolidation, flexible system configuration and elastic resource provisioning. However, despite the success of cloud computing for general-purpose computing, existing cloud computing and virtualization technology face tremendous challenges in supporting emerging soft real-time applications such as online video streaming, cloud-based gaming, and telecommunication management. These applications demand real-time performance in open, shared and virtualized computing environments. This paper identifies the technical challenges in supporting real-time applications in the cloud, surveys recent advancement in real-time virtualization and cloud computing technology, and offers research directions to enable cloud-based real-time applications in the future.     

Differential geometry properties of lines of curvature of parametric surfaces and their visualization

We present algorithms for computing the differential geometry properties of lines of curvature of parametric surfaces. We derive a unit tangent vector, curvature vector, binormal vector, torsion, and algorithms to evaluate their higher-order derivatives of lines of curvature of parametric surfaces. Among these quantities, it is shown that the curvature and its first derivative of the lines of curvature lend a hand for the formation of curved plates in shipbuilding. We also visualize the twist of lines of curvature, which enables us to observe how much the osculating plane of the line of curvature turns about the tangent vector.     

New results on PWARX model identification based on clustering approach

This paper deals with the problem of piecewise auto regressive systems with exogenous input(PWARX) model identification based on clustering solution. This problem involves both the estimation of the parameters of the affine sub-models and the hyper planes defining the partitions of the state-input regression. The existing identification methods present three main drawbacks which limit its effectiveness. First, most of them may converge to local minima in the case of poor initializations because they are based on the optimization using nonlinear criteria. Second, they use simple and ineffective techniques to remove outliers. Third, most of them assume that the number of sub-models is known a priori. To overcome these drawbacks, we suggest the use of the density-based spatial clustering of applications with noise(DBSCAN) algorithm. The results presented in this paper illustrate the performance of our methods in comparison with the existing approach. An application of the developed approach to an olive oil esterification reactor is also proposed in order to validate the simulation results.     

A New Risk Assessment Approach for Cloud Consumer

The cloud computing introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. Consequently, there is a need of risk assessment approach adapted to cloud computing. With such an approach, the cloud consumers can be guaranteed the effectiveness of data security and the cloud providers can win the trust of their cloud consumers. This paper requires the formalization of risk assessment method for conventional system as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.     

Generating Web Traffic Based on User Behavioral Model

Generating web traffic is of great importance to analyze performance of new designed network, test new equipment, and verify new protocols, etc.. However, most existing traffic generation systems tend to simulate the overall characteristics of network traffic, while neglecting of the behavior of the individual users. Nevertheless, in principle, the emerged characteristics of overall traffic originate from the aggregation of individual users＇ access behavior. In this paper, we propose an innovative web traffic generating method based on user browsing behavior. Our method simulates the real users＇ accessing behavior, and visits the real web servers. Then, we design and develop a web traffic generating system. Because our system accesses the real websites, it can produce almost the real network traffic. The test results show that the traffic generated by our system has characteristics of burstiness and self-similarity, which are widely found and characterized in many real networks. In addition, our system can better reflect real user＇s web browsing behavior.