Analytical study on cantilever resonance type magnet-integrated sensor device for micro-magnetic field detection

A beam-shaped cantilever resonance type magnetic sensor device has been proposed with a micro magnet. Two structural designs, named as design 1 and design 2, have been comparatively analyzed using ANSYS in order to obtain larger frequency shifts (higher magnetism sensitivity) due to the applied exterior magnetic field. The analytical results show that, in the range of 0–10 mT, the frequency shifts are small, while under 100 mT, a relatively larger frequency shift of about 30 Hz can be theoretically obtained. The power consumption of the proposed devices has been further theoretically studied for preliminary understanding. Using the well-known displacement equations, the estimated power consumption is around 0.21 μW, which is very lower than that of the reported magnetic field sensors. This implies that it is possible to fabricate higher sensitive magnetic field sensor with lower power consumption.     

Exact and approximate flexible aggregate similarity search

Aggregate similarity search, also known as aggregate nearest-neighbor (Ann) query, finds many useful applications in spatial and multimedia databases. Given a group Q of M query objects, it retrieves from a database the objects most similar to Q, where the similarity is an aggregation (e.g., \({{\mathrm{sum}}}\), \(\max \)) of the distances between each retrieved object p and all the objects in Q. In this paper, we propose an added flexibility to the query definition, where the similarity is an aggregation over the distances between p and any subset of \(\phi M\) objects in Q for some support \(0< \phi \le 1\). We call this new definition flexible aggregate similarity search and accordingly refer to a query as a flexible aggregate nearest-neighbor ( Fann ) query. We present algorithms for answering Fann queries exactly and approximately. Our approximation algorithms are especially appealing, which are simple, highly efficient, and work well in both low and high dimensions. They also return near-optimal answers with guaranteed constant-factor approximations in any dimensions. Extensive experiments on large real and synthetic datasets from 2 to 74 dimensions have demonstrated their superior efficiency and high quality.     

Chaotic feature analysis and forecasting of Liujiang River runoff

Because most of runoff time series with limited amount of data reveal inherently nonlinear and stochastic characteristics and tend to show chaotic behavior, strategies based on chaotic analysis are popular methods to analyze them from real systems in nonlinear dynamics. Only one kind of predicted method for yearly rainfall-runoff forecasting cannot achieve perfect performance. Thus, a mixture strategy denoted by WT-PSR-GA-NN, which is composed of wavelet transform (WT), phase space reconstruction (PSR), neural network (NN) and genetic algorithm (GA), is presented in this paper. In the WT-PSR-GA-NN framework, the process to deal with time series gathered from Liujiang River runoff data is given as follows: (1) the runoff time series was first decomposed into low-frequency and high-frequency sub-series by wavelet transformation; (2) the two sub-series were separately and independently reconstructed into phase spaces; (3) the transformed time series in the reconstructed phase spaces were modeled by neural network, which is trained by genetic algorithm to avoid trapping into local minima; (4) the predicted results in low-frequency parts were combined with the ones of high-frequency parts, and reconstructed with wavelet inverse transformation, to form the future behavior of the runoff. Experiments show that WT-PSR-GA-NN is effective and its forecasting results are high in accuracy not only for the short-term yearly hydrological time series but also for the long-term one. The comparison results revealed that the overall forecasting performance of WT-PSR-GA-NN proposed by us is superior to other popularity methods for all the test cases. We can conclude that WT-PSR-GA-NN can not only increase the forecasted accuracy, but also its own competitiveness in efficiency, effectiveness and robustness.     

Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis

 Envelope analysis is an effective method for characterizing impulsive vibrations in wired condition monitoring (CM) systems. This paper depicts the implementation of envelope analysis on a wireless sensor node for obtaining a more convenient and reliable CM system. To maintain CM performances under the constraints of resources available in the cost effective Zigbee based wireless sensor network (WSN), a low cost cortex-M4F microcontroller is employed as the core processor to implement the envelope analysis algorithm on the sensor node. The on-chip 12 bit analog-to-digital converter (ADC) working at 10 kHz sampling rate is adopted to acquire vibration signals measured by a wide frequency band piezoelectric accelerometer. The data processing flow inside the processor is optimized to satisfy the large memory usage in implementing fast Fourier transform (FFT) and Hilbert transform (HT). Thus, the envelope spectrum can be computed from a data frame of 2048 points to achieve a frequency resolution acceptable for identifying the characteristic frequencies of different bearing faults. Experimental evaluation results show that the embedded envelope analysis algorithm can successfully diagnose the simulated bearing faults and the data transmission throughput can be reduced by at least 95% per frame compared with that of the raw data, allowing a large number of sensor nodes to be deployed in the network for real time monitoring.     

Distinct element method analysis of a retaining wall using a steel frame and fill materials

A technique is developed to clearly establish the shear resistance of a cellular structure, retaining wall composed of a steel frame and fill materials with both continuous and discontinuous characteristics. To overcome the limitation of the existing analysis approach based on continuum mechanics, in which the shear behavior and interaction between the frames and fill material of this type of structure are difficult to describe, this paper introduces displacement incremental analysis into the distinct element method. The results obtained by using the proposed approach are compared with experimental results to verify its accuracy. The results show an internal friction angle of fill materials and overburdening load are major factor determining the shear resistance of a retaining wall with a cellular structure type. From the results of the parametric study on the shear behavior of this type of structure, this paper also proposes a shear resistance moment-shear displacement formula for designing a retaining wall with a cellular structure type.     

听知觉在景观设计中的应用分析

通过对人、景观、声音这三个景观中的声音环境构成要素的阐述,分析了听知觉在景观设计中的应用方向,并提出营造乐音和创造记忆空间在景观设计中听知觉的具体应用,以期更好地为景观设计师提供设计参考。     

高校保卫部门工作网站建设

随着校园网在高校的迅速普及,高校保卫部门网站建设为高校保卫部门工作的开展增添了新方法和新途径,是法制宣传教育新阵地新手段。充分利用校园网络资源,介绍了保卫部门网站建设的原则及内容,并提出了网站维护和推广的新思路,可高效地完成对保卫处各项事务的处理,为师生员工创建一个平安校园保驾护航。     

基于XML元素加密的Web服务安全策略

Web服务使开发人员能够建立一种面向服务的、平台无关的、分布式的应用程序架构,另一方面Web服务使用XML在网络中进行数据交换,如何提高Web服务的安全性则成为需要解决的关键问题。本文论述了基于对XML文件中的元素进行加密的策略,从而保证了Web服务安全性。     

基于系统动力学的煤矿物联网模型研究设计

采用系统动力学方法研究了煤矿系统中的安全管理与控制问题,找出了煤矿安全管理系统中各要素之间的复杂关系,建立起系统关系网,然后结合物联网技术,构建起一个更加完整的智能矿山管理系统。该研究设计可为煤炭企业管理和科研人员提供一种新的研究思路和设计参考。