Data-driven testing methodology for RFID systems

A radio-frequency identification (RFID) system including hardware and software may be updated from time to time after first time deployment. To ensure the reliability of the system, extensive tests are required. However, enumerating all test cases is infeasible, especially when the tests involve time-consuming hardware operations. To solve this problem, we propose a testing methodology for RFID systems which does not enumerate all test cases but rather those which are representative. A clustering method is adopted in selecting representative test cases. Although a small number of selected test cases are run, we can still obtain a relatively high bug detection rate compared with running the enumerated test cases. Our extensive experiments show the efficiency and effectiveness of our testing methodology.     

Using system dynamics for simulation and optimization of one coal industry system under fuzzy environment

In this paper, we have developed a model that integrates system dynamics with fuzzy multiple objective programming (SD-FMOP). This model can be used to study the complex interactions in a industry system. In the process of confirming sensitive parameters and fuzzy variables of the SD model, we made use of fuzzy multi-objective programming to help yield the solution. We adopted the chance-constraint programming model to convert the fuzzy variables into precise values. We use genetic algorithm to solve FMOP model, and obtain the Pareto solution through the programming models. It is evident that FMOP is effective in optimizing the given system to obtain the decision objectives of the SD model. The results recorded from the SD model are in our option, reasonable and credible. These results may help governments to establish more effective policy related to the coal industry development.     

A multi-objective decision making model for the vendor selection problem in a bifuzzy environment

In this paper, we focus on the vendor selection problem (VSP) for material supply in large-scale water conservancy and hydropower construction projects, and establish a corresponding model to solve this problem. After stating the problem, we introduce some basic knowledge of level-2 fuzzy sets and the way to transform them to normal fuzzy sets. Then we use the CCP model to handle the bifuzzy objective functions and constraints, based on a series of preparations, we transform the multi-objective integer model under bifuzzy environment into a deterministic model, then use particle swarm optimization (PSO) to solve this problem. The model is illustrated with an actual application to construction material supply.     

A method based on preference degrees for handling hybrid multiple attribute decision making problems

In this paper, we investigate hybrid multiple attribute decision making problems with various forms of attribute values (real numbers, linguistic labels, interval numbers, intuitionistic fuzzy numbers and interval intuitionistic fuzzy numbers). We propose a method based on preference degrees which may take the forms of fuzzy numbers, intuitionistic fuzzy numbers and interval intuitionistic fuzzy numbers. The method first normalizes various forms of attribute values into preference degrees, and then uses a preference degree-based weighted averaging operator to aggregate the normalized preference degrees. Meanwhile, for convenience of calculation, a new linguistic representation model is presented, whose feasibility is verified by comparing it with the traditional 4-tuple linguistic representation model, and from our model, the mapping relationship between interval intuitionistic fuzzy numbers and linguistic labels can be constructed. Finally, we illustrate the rationality and practicality of the proposed method by an application example.     

A best method of demodulation algorithm for UNFSK applied in transportation

The frequency shift of the ultra-narrow frequency shift keying (UNFSK) is far less than the ordinary binary frequency shift keying (FSK) method. Because the two frequencies of UNFSK are extremely close, the traditional demodulation method cannot separate them successfully. This study aims to successfully demodulate the UNFSK signals by applying cycle extension and notch filter. The signal processing procedure is as follows: First, the sampling signals have been made cycle extension to enlarge their spectrum difference between signal 0 and 1; secondly, the cycle extension signals have been processed by the notch filter algorithm and finally, we could get the information by sentencing the filtering result. Finally, the method is applied in transportation. The simulation results proved that the algorithm greatly enhanced UNFSK signal demodulation performance, compared to the traditional demodulation method. There can be 2–3 dB improvement in performance, which is very suitable for UNFSK.     

双向流水槽模拟潮汐的控制软件设计与实现

在双向流水槽中模拟潮汐是研究海岸灾害防护的重要手段之一,而潮汐模拟过程中,系统控制软件的性能决定仿真精度.利用双向流水槽结合尾门和双向水泵控制的模拟潮汐控制软件可实现对水位和流速精确控制.首先由下位机获取检测仪器采集的水位和流速数据,并进行非线性校正处理;然后上位机通过自适应水位水流控制算法求得控制量、发出控制指令调节现场尾门和双向水泵状态,从而生成模拟潮汐.实验通过对周期为48小时的不规则潮汐进行模拟,得到水位和流速的误差均小于5%.结果表明该控制软件具有高精度和稳定性,可满足科研需求.     

基于ADO.NET的应用程序访问后台数据的模块划分研究

在三层结构中,应用程序访问后台数据库数据是最重要的环节,而应用程序访问后台数据是通过调用类方法来实现的.很显然,类方法实现的是模块功能,所以,在设计类方法之前必须研究清楚应用程序访问后台数据库数据的模块划分.通过对应用程序访问后台数据的典型访问模式及实现研究,得出了应用程序访问后台数据模块划分的普遍规律.     

城市综合管理"大联动"系统软件构架研究与实践

城市综合管理包括城市日常管理与应急事务处理两大部分,与城市治安相互补充.以闵行区大联动中心系统建设为依据,从大联动系统的业务流程、组织管理、技术路线等方面,进行系统的论述与总结,并对其中一些关键的技术环节和技术难点进行了探讨与研究.     

安全事件模糊等量约束的因果关联算法研究

通过对异构网络的安全事件特点的深入分析,指出在大量不完整、模糊的安全事件中准确地定位潜在的安全威胁,对态势和威胁及其重要程度进行全面及时的评估,是当前安全管理的一个技术难题.提出一种基于时间关联窗口的安全事件模糊关联算法,在一定程度上解决安全事件的漏报与领域知识的不完备性问题,对当前的安全态势、安全威胁及其重要程度进行全面及时评估提供有力的支持.     

一种结合了纹理和颜色的运动目标跟踪算法

运动目标跟踪是智能视频监控中的关键技术之一,怎样描述运动目标是该技术的一个关键问题。提出一种新的运动目标跟踪算法,结合改进的LBP纹理和色度来描述运动目标,并采用Camshift算法的思想进行目标跟踪。为了降低算法的复杂性,在保证跟踪精确度的前提下,LBP纹理和色度的种类被极大地精简。实验证明提出的方法能有效地跟踪运动目标,在常规的视频分辨率下能达到实时性,比同类的其它算法性能更好。