Identification of Hammerstein systems with asymmetric dead-zone nonlinearities using canonical parameterized model

A non-iterative identification method with parameterization of the unknown dead-zone is proposed for Hammerstein systems in presence of asymmetric dead-zone nonlinearities.The canonical parameterized model which is a single expression without segmentation is utilized to describe the dead-zone,based on which a universal-type parametric model can be established to approximate the entire system.This model can be established without separating the nonlinear part from the linear part.The dead-zone parameters and the coefficients in the linear transfer function can be estimated simultaneously according to the proposed algorithm.Numerical experiments are presented to illustrate the effectiveness of the proposed scheme.     

面向应用型人才培养程序设计课程教材改革探讨

根据南通大学独立学院培养应用型人才的目标,学院对高级语言程序设计课程提出了新的要求.为了进行课程改革,文章详细分析了高级语言程序设计课程存在的问题,提出了拟编新教材的具体方案,总结了新编教材所应具备的特色.     

Comparison of Representative Heuristic Algorithms for Multi-Objective Reservoir Optimal Operation

Heuristic algorithms (HAs) are widely used in multi-objective reservoir optimal operation (MOROO) due to the rapidity of the calculation and simplicity of their design. The literature usually focuses on one or two categories of HAs and simply reviews the state of the art. To provide an overall understanding and a specific comparison of HAs in MOROO, differential evolution (DE), particle swarm optimisation (PSO), and artificial physics optimisation (APO), which serve as typical examples of the three categories of HAs, are compared in terms of the development and applications using a designed experiment. Besides, the general model with constraints and fitness function, and the solution process using a hybrid feasible domain restoration method and penalty function method are also presented. Taking a designed experiment with multiple scenarios, the mean average of the optimal objective function values, the standard deviation of optimal objective function values, the mean average of the computational time, and population diversity are used for comparisons. Results of the comparisons show that (a) the problem of optimal multipurpose reservoir long-term operation is a mathematic programming problem with narrow feasible region and monotonic objective function; (b) it is easy to obtain the same optimal objective function value, but different optimal solutions using HAs; and (c) comparisons do not result in a clear winner, but DE can be more appropriate for MOROO.

     

A novel dual-biological-community swarm intelligence algorithm with a commensal evolution strategy for multimodal problems

The Journal of Supercomputing - For sophisticated applications, engineers should always consider multi-objective, multi-task or multi-modal problems, especially in the Internet of Things, such as...     

Anomaly detection via a combination model in time series data

Since the time series data have the characteristics of a large amount of data and non-stationarity, we usually cannot obtain a satisfactory result by a single-model-based method to detect anomalies in time series data. To overcome this problem, in this paper, a combination-model-based approach is proposed by combining a similarity-measurement-based method and a model-based method for anomaly detection. First, the process of data representation is performed to generate a new data form to arrive at the purpose of reducing data volume. Furthermore, due to the anomalies being generally caused by changes in amplitude and shape, we take both the original time series data and their amplitude change data into consideration of the process of data representation to capture the shape and morphological features. Then, the results of data representation are employed to establish a model for anomaly detection. Compared with the state-of-the-art methods, experimental studies on a large number of datasets show that the proposed method can significantly improve the performance of anomaly detection with higher data anomaly resolution.

     

An improved generative adversarial network for translating clothes from the human body to tiled image

Neural Computing and Applications - Nowadays, purchasing the products similar to the styles of stars’ products has become a new trend in e-commerce platforms. Clothing transaction constitutes...     

果园数据采集和监控的低功耗节点设计

针对果园种植密度大、障碍物多使得通信受阻的缺点,设计了一种适合果园数据采集和监控的低成本、低功耗的传感器节点;节点的微控制器采用低功耗ATmega128L,射频模块采用CC2420,并采用SHT11空气温湿度传感器、ISL29010光照传感器、FDS-100土壤水分传感器、Pt1000土壤温度传感器作为传感器模块,对节点的软件进行了详细设计,改进了操作系统任务调度方法,通过引入休眠机制设计了MAC层和网络层通信协议;通过将文中节点应用于南通海安市的大公镇果园试验基地,结果表明:文中设计的节点在采样周期为1 050 s时,能正常工作116天,具有低功耗和生命周期长的优点,同时其采样湿度的平均误差仅为0.213％,具有数据采集精度高的优点,能满足果园信息采集和监控的要求.     

基于云自适应遗传算法的NoC路径分配研究

路径分配是NoC设计流程中的两个关键步骤之一;路径分配的结果对NoC系统的性能尤其是通讯延时有着很重要的影响;多约束条件下的NoC路径分配问题是NP完全问题,要求出其最优解比较困难,目前常用的方法是利用启发式算法求得其较优解;文中提出一种基于云自适应遗传算法的NoC路径分配解决方案,该算法利用云模型对传统遗传算法加以改进,采取新的方法自动调整遗传算法过程中的交叉概率pc和变异概率pm,将适应度与云模型的3个参数Ex、En、He相互结合,从而达到优化遗传算法的目的;将此算法应用于2D-Mesh拓扑结构的NoC中,以平衡链路负载和联合优化为实验目标,以优化静态通讯分配结果;实验证明,文章所采取的算法在平衡链路负载和联合优化方面均取得了良好的效果。     

遗传算法模糊PID测控系统在环控试验台中的应用

飞机环控试验台须模拟流量0～14000kg/h、压力0～2.5MPa和常温～500℃的空气环境;项目要求测控范围广、精度±1%且不超调;空气状态具有非线性、时变等特点,且控制参数之间存在复杂耦合;针对以上难点,设计了分布式测控系统,提出了改进的智能PID控制方案;通过遗传算法分段整定PID参数,离线建立PID数据库,使系统能够根据控制目标值选择最优PID初值;在此基础上,结合模糊推理在线调整PID参数,使系统具有了自适应性,能在具体工况和干扰下达到很好的控制效果;实际应用中完全满足了指标要求,解决了传统PID的控制难点,对类似的复杂系统有一定借鉴意义。     

Enterprise architecture,IT effectiveness and the mediating role of IT alignment in US hospitals

Despite the possible benefits of implementing healthcare information technologies, successful implementation of effective healthcare information technology is constrained by cultural and regulatory concerns and technical obstacles encountered when establishing or upgrading an organisation's enterprise infrastructure. In this paper, we advance Ross' four‐stage model of enterprise architecture maturity as a valuable IT resource for helping healthcare organisations sustain a competitive advantage. We use partial least squares (PLS) structural equation modelling to analyse survey data from 164 US hospitals at different stages of EA maturity. Our results provide evidence that enterprise architecture maturity directly influences the effectiveness of hospitals' IT resources for achieving strategic goals. Further, enterprise architecture maturity indirectly influences the effectiveness of IT resources when IT alignment is incorporated as a mediating variable. We discuss the implications of our findings for research and practice and suggest opportunities for future research.