Active time scheduling for rechargeable sensor networks

Recent progress in energy harvesting technologies made it possible to build sensor networks with rechargeable nodes which target an indefinitely long operation. In these networks, the goal of energy management is to allocate the available energy such that the important performance metrics, such as the number of detected threats, are maximized. As the harvested energy is not sufficient for continuous operation, the scheduling of the active and inactive time is one of the main components of energy management. The active time scheduling protocols need to maintain the energy equilibrium of the nodes, while considering the uncertainties of the energy income, which is strongly influenced by the weather, and the energy expenditures, which are dependent on the behavior of the targets. In this paper, we describe and experimentally compare three active time scheduling protocols: (a) static active time, (b) dynamic active time based on a multi-parameter heuristic and (c) utility-based uniform sensing. We show that protocols which take into consideration the probabilistic models of the energy income and expenditure and can dynamically adapt to changes in the environment, can provide a significant performance advantage.     

Innovative product design based on customer requirement weight calculation model

In the processes of product innovation and design, it is important for the designers to find and capture customer's focus through customer requirement weight calculation and ranking. Based on the fuzzy set theory and Euclidean space distance, this paper puts forward a method for customer requirement weight calculation called Euclidean space distances weighting ranking method. This method is used in the fuzzy analytic hierarchy process that satisfies the additive consistent fuzzy matrix. A model for the weight calculation steps is constructed; meanwhile, a product innovation design module on the basis of the customer requirement weight calculation model is developed. Finally, combined with the instance of titanium sponge production, the customer requirement weight calculation model is validated. By the innovation design module, the structure of the titanium sponge reactor has been improved and made innovative.     

基于改进惯性权重的粒子群优化算法

惯性权重是粒子群算法中平衡全局搜索和局部搜索能力的重要参数,提出了一种基于改进惯性权重的粒子群优化算法。该算法在进化初期采用基于不同粒子不同维的动态自适应惯性权重策略,加快收敛速度,在进化后期采用线性递减权重策略,同时为防止陷入局优,适时引入混沌变异增加种群多样性。对5个典型测试函数的测试结果表明,NPSO在收敛速度、收敛精度、稳定性和全局搜索能力等方面比线性权重PSO(LDIWPSO)均有很大程度上的提高。     

Designing of MIP-based QCM sensor for the determination of Cu(II) ions in solution

A novel quartz crystal microbalance (QCM) sensor with a high selectivity and sensitivity has been developed for the determination of Cu(II) ions, based on the modification of Cu(II) ion-imprinted polymer (Cu(II)-IIP) film onto a quartz crystal. The performance of the developed MIP-QCM sensor was evaluated and the results indicated that a sensitive MIP-QCM sensor could be fabricated. The obtained MIP-QCM sensor presents high-selectivity monitoring of Cu(II) ions, better reproducibility, shorter response time (6 min), wider linear range (0.001–50 μM) and lower detection limit (8 × 10⁻⁴ μM). The practical analysis of the MIP-QCM sensor confirms the feasibility of Cu(II) determination in wastewater.     

数据丢失情况下的最小二乘参数辨识算法

现有系统参数辨识方法大多是建立在输入输出数据可以完全测量和完全获取的基础上,而在实际系统中,由于传感器故障或网络传输机构故障,使得数据丢失现象经常发生。研究一类线性系统在输入或输出数据丢失情况下的系统辨识问题,并将数据丢失现象描述为随机伯努利序列,在此基础上提出新的辨识算法来估计数据丢失情况下系统的参数。最后,通过仿真示例验证所提算法对数据丢失的影响。结果表明,所提出的算法相较于递推最小二乘法有更好的收敛性。     

一种基于改进谱熵的语音端点检测方法

针对常规谱熵端点检测法在非平稳噪声环境下检测效果差的缺陷,提出了一种基于子带谱熵幅度积参数的语音端点检测方法。该方法利用非平稳信号处理技术将语音信号的时域分析和频域分析相结合,在常规谱熵的基础上计算出子带谱熵,再结合时域中的短时平均幅度进行端点检测。仿真结果表明,与常规谱熵端点检测算法和短时平均幅度算法相比,该方法在各种噪声环境下的检测效果都比较好,鲁棒性增强,其有效性得到验证。     

基于无线通讯技术脉搏检测仪的设计与实现

脉搏是反映人体生理健康状况最常见的重要生理现象,临床上有许多疾病,特别是心脏病都可使脉搏发生变化,因此脉搏信息检测与处理在临床医学具有十分重要的现实价值和意义;传统脉搏检测仪多以在线直测的方式检测,检测装置使用灵活度较低,不适用于普通家庭检测;针对此问题,对传统测量方法加以改进优化,提出了基于无线通讯技术的研究方案,方案以单片机为信号处理单元,以无线传输为控制核心,以ST188光电传感器为采集单元,同时结合nRF24l01无线传输模块,通过硬软件设计实现脉搏数据的采集与处理,以及无线发射、接收和脉搏数据的显示;实验表明,该脉搏检测仪具有检测数据准确、检测效率高等优点;同时,脉搏检测仪器精巧便于携带,而且成本较低,便于普通家庭使用。     

望目特性连续型参数稳健设计遗传优化方法

针对一类可通过理论计算得到输出特性值的望目特性连续型参数稳健设计问题,提出了一种遗传进化方法。描述了研究的问题;提出了望目特性连续型参数稳健设计遗传进化方法的技术思路：以密集抽样取代离散化处理,以个体取代试验方案,以变化的种群取代固定的内表,通过遗传进化得到最优设计方案。提出并设计了一种望目特性连续型参数稳健设计遗传算法,阐述了算法的计算流程、个体编码、适应度、种群初始化、解码操作及遗传操作。通过案例分析验证了所提方法的有效性。     

基于区分服务的流媒体传输模型

流媒体在网络上的应用经常会受到数据包丢失或错误以及网络带宽资源不足的干扰,使得接收方播放质量受到严重影响。本文建立了一种适合流媒体传输的区分服务模型,该模型能够使高优先级数据流（实时流媒体数据流）占用更多的带宽。仿真结果表明：该策略能使流媒体数据流获得较高的吞吐量和较低的丢包率,有效提高流媒体传输的可靠性和实时性。     

水体下综放开采可行性分析

余吾煤业现有630万吨煤炭资源处在绛河水体下,煤层厚度在4.0～6.2m之间,现导水裂隙带经验公式不能够满足其水体下安全开采,存在开采后突水隐患,为了确定开采后上覆岩层导水裂隙带极限高度是否波及地表,研究区在9个井下钻孔进行了井下仰孔双栓塞分段注水测试和仰孔直观法电视成像仪探测,对涌水量进行了监测、水质进行了对比研究,并通过模拟实验进一步研究不同采厚条件下发育高度.观测、监测及模拟结果表明:采动后导水裂隙带发育高度取决于采厚,为水体下采煤水的防治提供了可靠数据,三个工作面的试采成功,为水体下采煤提供了应用范例.