提高应力波反射法检测信度的探讨

本文通过低应变检测及分析过程中影响检测信度方面的问题,在传感器的选择、振源的选择、传感器的安装及频域分析等方面的具体影响,阐述了处理这些问题的一些体会。

认知无线电网络中的最佳可信度频谱检测算法

由于认知无线电网络中的典型硬决策协作频谱检测在数据融合时未考虑各认知用户检测结果的差异性,不能很好地提高检测性能,因此,提出了一种基于检测可信度的协作频谱检测算法.首先,利用各认知用户的平均接收信噪比来获得它们的检测可信度;然后,综合各认知用户的检测结果以及检测可信度来判断授权用户是否使用频带,从而提高了检测性能.仿真结果表明,在低信噪比情况下,相比典型硬决策协作频谱检测,该算法具有较优的接收特性曲线,并在合理选取认知用户检测阈值的条件下,具有较低的检测错误概率.

基于模型检测的财经舆情可信度研究

财经舆情的可信度评估影响企业发展和投资者利益,为了获得可信度判别标准并判断其准确性,本文设计了一个基于模型检测技术的可信度检测框架。利用决策树算法代替传统的人工归纳过程来构建财经舆情的可信度判断规则,并以CTL形式化语言描述。将财经舆情数据库表示为基于时序逻辑关系的可信度待检测模型,并将模型以kripke结构表示。通过模型检测器NuSMV对待检测模型进行自动化的规则验证,判断待检测模型是否符合可信度检测规则,将不符合规则的模型中的路径输出为反例路径,即为不可信财经舆情的检测路径。最后,结合实证研究对提出的框架进行了有效性验证。结果表明,本文提出的框架可以快速有效实现财经舆情可信度的自动检测,帮助投资者分析和预测财经舆情的真实性。

基于校验点的非测距锚节点可信度检测安全算法

作为一种开放网络,无线传感器网络时常受到来自各内部或外部的攻击。这种攻击会导致锚节点发出错误的定位信息,从而影响定位精度。另外,WSN常常部署于河流、丘陵区域,其拓扑结构呈现X型及C型。这些特殊网络环境使得节点的定位精度进一步受到影响。针对这一情况,提出了一种基于校验点的非测距锚节点可信度检测算法(Node Position and Hops Verification Algorithm Based on Range-free Method in WSN Localization,RFPHV)。通过建立仿真,表明算法仅利用节点之间的连通性即可对锚节点位置及跳数进行检测,验证其可信度。

基于SNP数据检测染色体拷贝数结果可信度分析

利用SNP数据检测肿瘤细胞染色体拷贝数变异是癌症相关研究的一个热点,目前已有多种方法可以通过分析SNP array数据检测染色体拷贝数。然而在某些情况下,这些检测方法检测结果与真实拷贝数具有一定错误率。目前并没有方法研究预测结果发生错误的规律。本文分别分析了GPHMM,ASCAT两种检测方法结果信息熵与检测正确率的关系,发现检测正确率与信息熵存在很强的相关性。通过对比不同肿瘤细胞比例下信息熵与正确率关系,本文发现随着肿瘤细胞比例的增大,检测结果信息熵平均值增大,方差减小;同时平均检测正确率也越来越大,方差显著减小。这些结果显示信息熵的大小可以反映出检测结果正确率的高低。最后,本文以高肿瘤细胞比例下拷贝数检测结果为例,研究了在变异类型单一,信息熵小的情况下,染色体倍性检测的正确率。结果表明信息熵可以作为衡量检测结果可信度的指标:即信息熵越高,检测结果越可信。

应用于物联网云安全可信度检测的算法仿真

已有的高校物联网云安全可信度检测方法的用户身份加密过程易出现漏洞,导致无法直接判断云数据的安全性。为此,提出基于二次加密算法的物联网云安全可信度检测方法。利用RSA加密算法完成学生身份的认证。结合DES加密算法实现二次加密。再采用K-L散度高斯混合模型聚类入侵数据,利用特征标准划分待测数据集,获取检测优先级,判断云安全内是否存在入侵数据,完成物联网云安全可信度检测。实验证明:所提二次加密算法下的云安全可信度由于单一加密算法,且根据所提方法的检测结果可直接判断数据是否存在威胁。

Intrusion detection model based on deep belief nets

This paper focuses on the intrusion classification of huge amounts of data in a network intrusion detection system. An intrusion detection model based on deep belief nets （DBN） is proposed to conduct intrusion detection,and the principles regarding DBN are discussed.The DBN is composed of a multiple unsupervised restricted Boltzmann machine （RBM） and a supervised back propagation （BP）network.First,the DBN in the proposed model is pre-trained in a fast and greedy way,and each RBM is trained by the contrastive divergence algorithm.Secondly,the whole network is fine-tuned by the supervised BP algorithm,which is employed for classifying the low-dimensional features of the intrusion data generated by the last RBM layer simultaneously.The experimental results on the KDD CUP 1999 dataset demonstrate that the DBN using the RBM network with three or more layers outperforms the self-organizing maps （SOM）and neural network （NN）in intrusion classification.Therefore,the DBN is an efficient approach for intrusion detection in high-dimensional space.

县级政府公共服务能力评价体系的构建

提高县级政府公共服务水平不仅需要转变其职能,还需要建立一套科学有效的公共服务能力评价体系对其进行客观衡量。依据科学发展观的要求,构建客观指标和主观指标相结合的县级政府公共服务能力评价体系,通过内容效度比对指标体系进行内容信度检测,并运用专家调查法确定指标体系的权重。构建政府公共服务评价体系是一个系统的、动态的工程,需要随着历史条件变化不断修正和发展。

新时期农民专业合作社在脱贫中的地位与作用——基于贫困户满意度测评

农民专业合作社是新时期农民群众顺应农村生产力发展要求的重大创造和农业产业化经营的创新组织,研究贫困户视角下合作社对于脱贫的地位与作用,具有理论与现实意义。在江西省萍乡市进行实地问卷调查,选取4个潜变量、14个可测变量,结合信度和效度检测以及结构方程模型,评价了农民专业合作社对于贫困户脱贫的重要作用。最终在结构方程总效应模型下得出合作社经济能力、技术力量以及制度建设对贫困户收入、满意度和积极性具有显著性统计意义,而管理者文化水平对于贫困户的满意度测评指标未通过显著性检验,并提出相应建议与对策。

Fatigue damage evaluation by metal magnetic memory testing

Tension-compression fatigue test was performed on 0.45% C steel specimens.Normal and tangential components of magnetic memory testing signals,Hp(y) and Hp(x) signals,with their characteristics,K of Hp(y) and Hp(x)M of Hp(x),throughout the fatigue process were presented and analyzed.Abnormal peaks of Hp(y) and peak of Hp(x) reversed after loading; Hp(y) curves rotated clockwise and Hp(x) curves elevated significantly with the increase of fatigue cycle number at the first a few fatigue cycles,both Hp(y) and Hp(x) curves were stable after that,the amplitude of abnormal peaks of Hp(y) and peak value of Hp(x) increased more quickly after fatigue crack initiation.Abnormal peaks of Hp(y) and peak of Hp(x) at the notch reversed again after failure.The characteristics were found to exhibit consistent tendency in the whole fatigue life and behave differently in different stages of fatigue.In initial and crack developing stages,the characteristics increased significantly due to dislocations increase and crack propagation,respectively.In stable stage,the characteristics remained constant as a result of dislocation blocking,K value ranged from 20 to 30 A/(m·mm)-1,and Hp(x)M ranged from 270 to 300 A/m under the test parameters in this work.After failure,both abnormal peaks of Hp(y) and peak of Hp(x) reversed,K value was 133 A/(m·mm)-1 and Hp(x)M was-640 A/m.The results indicate that the characteristics of Hp(y) and Hp(x) signals were related to the accumulation of fatigue,so it is feasible and applicable to monitor fatigue damage of ferromagnetic components using metal magnetic memory testing(MMMT).

Feasibility investigation on deep ocean compact autonomous Raman spectrometer developed for in-situ detection of acid radical ions

A newly developed Deep Ocean Compact Autonomous Raman Spectrometer （DOCARS） system is introduced and used for in-situ detection of acid radical ions in this paper. To evaluate the feasibility and capability of DOCARS for quantitative analysis of the acid radical ions in the deep ocean, extensive investigations have been carried out both in laboratory and sea trials during the development phase. In the laboratory investigations, Raman spectra of the prepared samples （acid radical ions solutions） were obtained, and analyzed using the method of internal standard normalization in data processing. The Raman signal of acid radical ions was normalized by that of water molecules. The calibration curve showed that the normalized Raman signal intensity of SO4^2-, NO3^-, and HCO^-3 increases linearly as the concentration rises with correlation coefficient R^2 of 0.99, 0.99, and 0.98 respectively. The linear function obtained from the calibration curve was then used for the analysis of the spectra ,data acquired in the sea trial under a simulating chemical field in the deep-sea environment. It was found that the detected concentration of NO3 according to the linear function can reflect the concentration changes of NO~ after the sample was released, and the detection accuracy of the DOCARS system for SO^2-_4 is 8%. All the results showed that the DOCARS system has great potential in quantitative detection of acid radical ions under the deep-sea environment, while the sensitivity of the DOCARS system is expected to be improved.

NOVEL ADAPTIVE MULTIUSER DETECTIONALGORITHM BASED ON WAVELET TRANSFORM

The wavelet transform-based adaptive multiuser detection algorithm is presented. The novel adaptive multiuser detection algorithm uses the wavelet transform for the preprocessing, and wavelet-transformed signal uses LMS algorithm to implement the adaptive multiuser detection. The algorithm makes use of wavelet transform to divide the wavelet space, which shows that the wavelet transform has a better decorrelation ability and leads to better convergence. White noise can be wiped off under the wavelet transform according to different characteristics of signal and white noise under the wavelet transform. Theoretical analyses and simulations demonstrate that the algorithm converges faster than the conventional adaptive multiuser detection algorithm, and has the better performance. Simulation results reveal that the algorithm convergence relates to the wavelet base, and show that the algorithm convergence gets better with the increasing of regularity for the same series of the wavelet base. Finally the algorithm shows that it can be easily implemented.

Underwater Optical Fiber Fluorescent System for Measuring Chlorophyll-a Concentration

Using optical fiber fluorescent technology,a new method for measuring alga concentration in water is presented. The system can realize on line measurement for alga concentration using He Ne laser as the light source. It can also effectively detect weak signals. The system with a passive sensor head has such advantages as simple structure, high sensitivity and high accuracy. It has been demonstrated that this system can be used to monitor water quality and can also be used to survey some matter.

High-speed corner detection based on fuzzy ID3 decision tree

A high-speed comer detection algorithm based on fuzzy ID3 decision tree was proposed. In the algorithm, the Bresenham circle with 3-pixel radius was used as the test mask, overlapping the candidate comers with the nucleus. Connected pixels on the circle were applied to compare the intensity value with the nucleus, with the membership function used to give the fuzzy result. The pixel with maximum information gain was chosen as the parent node to build a binary decision tree. Thus, the comer detector was derived. The pictures taken in Fengtai Railway Station in Beijing were used to test the method. The experimental results show that when the number of pixels on the test mask is chosen to be 9, best result can be obtained. The comer detector significantly outperforms existing detector in computational efficiency without sacrificing the quality and the method also provides high performance against Poisson noise and Gaussian blur.

Using of Synthetic Images on Accuracy Assessment of Change Detection

Land cover change detection is the major goal in multitemporal remote sensing studies. It is well known that remotely-sensed images of the same area acquired on different dates tend to be affected by radiometric differences and registration problems. These influences are considered as noise in the process and may induce the user to both： signalling false changes and masking real surface changes. The difference image produced by subtracting two co-registered images is a standard initial step in change detection algorithms. This image naturally appears to be noisier than the original ones and has at least two populations： （1） the noise-like and （2） the real changes. The problem that arises is how to discriminate them. There are several approaches to perform change detection reported in the literature and some studies have employed synthetic images. By using synthetic images, the accuracy assessment of specific algorithm can be done more accurately. The question at this point is： what is the acceptable noise level to be added on the synthetic images to simulate a real problem？ This paper attempts to answer this question by suggesting values of SNR （signal-to-noise ratio） obtained from experiments performed on TM-Landsat-5 and CCD-CBERS-2B images.

Multi-scale bistable stochastic resonance array: A novel weak signal detection method and application in machine fault diagnosis

Weak signal detection based on stochastic resonance （SR） can hardly succeed when noise intensity exceeds the optimal value of SR. This paper explores a novel parallel bistable SR array mechanism by decomposed multi-scale noises from input signal. A smoother output with lower noise is obtained from the combination of colored noise SR ellect and parallel bistable SR array. The influence of noise intensity and array size on the SR effect and output noise intensity is analyzed through numerical simu- lation. A signal detection method based on the new SR mechanism and normalized scale transform is proposed for the case of heavy background noise. Simulation is conducted to confirm the effectiveness of parameter tuning and amplitude tuning of normalized scale transform on the proposed SR model. The proposed method has three advantages： the input noise intensity of each unit is reduced by wavelet decomposition; the output noise level decreases due to array ensemble average; the SR effect of each unit is optimized by normalized scale transform for high frequency signal. Experiment on bearing inner and outer race fault diagnosis has verified the effectiveness and advantages of the proposed SR model in comparison with traditional SR method and kurlogram.

Abundance of Asymmetric Dark Matter in Brane World Cosmology

Relic abundance of asymmetric Dark Matter particles in brane world cosmological scenario is investigated in this article. Hubble expansion rate is enhanced in brane world cosmology and it affects the relic abundance of asymmetric Dark Matter particles. We analyze how the relic abundance of asymmetric Dark Matter is changed in this model. We show that in such kind of nonstandard cosmological scenario, indirect detection of asymmetric Dark Matter is possible if the cross section is small enough which let the anti-particle abundance kept in the same amount with the particle. We show the indirect detection signal constraints can be used to such model only when the cross section and the 5-dimensional Planck mass scale are in appropriate values.

Artifacts of Functional Electrical Stimulation on Electromyograph

The purpose of this study is to investigate different factors of the artifact in surface electromyography(EMG) signal caused by functional electrical stimulation(FES). The factors investigated include the size of stimulation electrode pads, the amplitude, frequency, and pulse width of the stimulation waveform and the detecting electrode points. We calculate the root mean square(RMS) of EMG signal to analyze the effect of these factors on the M-wave properties. The results indicate that the M-wave mainly depends on the stimulation amplitude and the distribution of detecting electrodes,but not on the other factors. This study can assist the reduction of artifact and the selection of detecting electrode points.