一种低功耗集中供热实时温度采集系统设计

从系统性能,运行效率和经济效益等方面出发,设计出一种低功耗的多路温度采集与实时检测系统,既可为供热部门提供实际温度参数,合理调度锅炉运行时间,降低能耗;又可以为监管部门提供可靠的供热质量信息,方便协调和管理,化解供需的矛盾。具有较好的经济效益和社会效益。     

浅析产品形象设计中的型与色

产品形象设计是为实现企业形象总体目标的细化,使产品内在的品质形象、产品外在的视觉形象与社会形象形成统一性而展开的。良好的产品形象有利于树立良好的企业形象,增加客户对品牌的美誉度和信任度,提高企业的竞争实力。本论文是通过对产品设计的色彩与造型两方面进行分析,来阐述其在产品形象设计中的造型价值。     

固有频率和阻尼度的测试方法研究

文章介绍了阶跃激励法、正弦激励法、脉冲激励法三种动态扭矩计量测试方法,并对不同时间做的两次试验进行了对比,得出的数据相差在3%以内,证明了上述动态特性的测试方法具有重复性和追溯性,可用作扭矩传感器动态特性的测试。     

基于组件技术的城市公共交通地理信息系统的研究

针对城市公共交通系统中涉及到大量的基础数据,分析现有交通管理的不足,开发出一种针对道路交通管理部门的城市公共交通管理信息系统,该系统应用组件式GIS技术在VB6.0平台上对GeoMap二次开发而得到。可实现对数据进行实时修改,能大大提高管理数据的有效性和科学性,并且能挖掘现有数据中隐含的一些重要信息。     

基于胜任力模型的高校人力资源管理系统

针对中国高校人力资源在过去计划经济管理体制下未得到充分的开发和利用,提出一个基于胜任力模型的采用JSP相关技术实现的高校人力资源管理系统解决方案。     

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.