分光式光谱测色仪的定标及不确定度分析

论述了对分光式光谱测色仪的波长准确度、波长重复性、色度准确度、色度重复性进行定标的原理及方法，并通过实际定标测试，详细给出了色度测量的不确定度评定方法及具体评定过程，为色度计量领域提供了不确定度评估的参考范例。

HDC-Ⅱ环空测井组合仪器及其应用

HDC -Ⅱ环空测井组合仪是继分测式环空测井组合仪之后开发的新型仪器 ,该组合仪引入了多路遥传短节 (WTC) ,测量参数增加到 7种 ,其中持水率和流量用集流方式测量。单片机控制技术的应用大大简化了电子线路 ,改善了仪器的性能 ,一次下井可同时录取 7种参数的资料。它的推广应用 ,可为抽油机井的动态监测提供更准确、齐备的资料 ,同时还可缩短施工时间。文章阐述了仪器的结构特点。

Distributed Sampling Measurement Model in a Large-Scale High-Speed IP Networks

The distributed passive measurement is an important technology for networkbehavior research. To achieve a consistent measurement, the same packets should be sampled atdistributed measurement points. And in order to estimate the character of traffic statistics, thetraffic sample should be random in statistics. A distributed samplingmask measurement model isintroduced to tackle the difficulty of measuring the full trace of high-speed networks. The keypoint of the model is to choose some bits that are suitable to be sampling mask. In the paper, thebit entropy and bit flow entropy of IP packet headers in CERNET backbone are analyzed, and we findthat the 16 bits of identification field in IP packet header are fit to the matching field ofsampling mask. Measurement traffic also can be used to analyze the statistical character ofmeasurement sample and the randomicity of the model. At the same time the experiment resultsindicate that the model has a good sampling performance.

Optimization for Top DBR’s Reflectivity in RCE Photodectector

The monolithic integration of vertical-cavity surface-emitting lasers (VCSEL) with photodetectors is very important in the application of free-space optical interconnects.Theoretical and experimental results on the resonant-cavity-enhanced (RCE) photodetector with VCSEL Structure are presented.The compatible requirement in input mirror reflectivity between the VCSEL and the RCE detector is achieved by precisely etching the top mirror.In this way,the RCE detector with relatively high quantum efficiency and necessary optical bandwidth has been obtained.[KH8/9D]

ANALYSIS FOR THE BEZOUT IDENTITY OF GENERALIZED SYSTEMS

The state space representation of the Bezout identity for generalized systems proposed by (Wang and Balas, 1989) is discussed again. A more concise way of description and proof is presented and the physical significance of the result in is also analyzed. Thus, our work is of independent interest.

Construction of project quality health monitoring system based on life-cycle theory

In order to more effectively assess the health status of a project, the monitoring indices in a project＇s life cycle are divided into quality index, cost index, time index, satisfaction index, and sustainable development index. Based on the feature of qualitative and quantitative indices combining, the PCA-PR （principal component analysis and pattern recognition） model is constructed. The model first analyzes the principal components of the life-cycle indices system constructed above, and picks up those principal component indices that can reflect the health status of a project at any time. Then the pattern recognition model is used to study these principal components, which means that the real time health status of the project can be divided into five lamps from a green lamp to a red one and the health status lamp of the project can be recognized by using the PR model and those principal components. Finally, the process is shown with a real example and a conclusion consistent with the actual situation is drawn. So the validity of the index system and the PCA-PR model can be confirmed.

A model study of residual oil distribution jointly using crosswell and borehole-surface electric potential methods

Although high resolution can be provided by electrical logging, the measured electrical log range is narrow and is limited to near the well. Borehole-surface electric potential measurements are able to detect a wide enough range but its resolution is limited, particularly for reservoirs with complex oil and water distribution or complicated structure. In this study, we attempt to accurately locate the 3-D reservoir water and oil distribution by combining borehole-surface and crosswell electric potentials. First, the distributions of oil and water in both vertical and horizontal directions are detected by the borehole-surface and erosswell electric potential methods, respectively, and then the measured crosswell potential result is used to calibrate the measured borehole-surface electric potential data to improve vertical resolution so that the residual oil distribution is determined in a lower half-space with three dimensions. The evaluation of residual oil distribution is obtained by investigation of differences between the simulation results of the reservoir with and without water flooding. The finite difference numerical simulation results prove that the spatial residual oil distribution can be effectively determined by combining the crosswell and borehole-surface electric potentials.

Unascertained measurement classifying model of goal collapse prediction

Based on optimized forecast method of unascertained classifying,a unascer- tained measurement classifying model (UMC) to predict mining induced goaf collapse was established,The discriminated factors of the model are influential factors including over- burden layer type,overburden layer thickness,the complex degree of geologic structure, the inclination angle of coal bed,volume rate of the cavity region,the vertical goaf depth from the surface and space superposition layer of the goaf region.Unascertained mea- surement (UM) function of each factor was calculated.The unascertained measurement to indicate the classification center and the grade of waiting forecast sample was determined by the UM distance between the synthesis index of waiting forecast samples and index of every classification.The training samples were tested by the established model,and the correct rate is 100%.Furthermore,the seven waiting forecast samples were predicted by the UMC model.The results show that the forecast results are fully consistent with the ac- tual situation.

RFD-Rao and RFD-Wald tests for distributed targets with range walking effect

Two novel adaptive distributed target detectors, the range frequency domain-Rao （RFD-Rao） and range frequency domain-Wald （RFD-Wald） tests are proposed in this work. The application methods for these tests consider a partially homogeneous disturbance environment and a target range walking effect in a coherent processing interval （CPI）. The asymptotic performance of the detectors is analyzed, and the constant false alarm rate （CFAR） properties with respect to the clutter covariance matrix and power level are shown. The performances of the proposed adaptive detectors are assessed through Monte-Carlo simulations, and the results are presented to demonstrate the effectiveness of the proposed detection algorithms compared to those of similar existing detectors.

Development of neutron moisture gauge in China

According to measuring mode (in-hopper,surface,transmitted and scattered neutron moisture gauge),this paper introduced the development and application of neutron moisture gauge in China since 1970s.

Generalized Square Conservative Multistep Finite Difference Scheme Incorporating Historical Observations

In this paper,a multistep finite difference scheme has been proposed,whose coefficients are determined taking into consideration compatibility and generalized quadratic conservation,as well as incorporating historical observation data.The schemes have three advantages:high-order accuracy in time,generalized square conservation,and smart use of historical observations.Numerical tests based on the one-dimensional linear advection equations suggest that reasonable consideration of accuracy,square conservation,and inclusion of historical observations is critical for good performance of a finite difference scheme.

GSM-MRF based classification approach for real-time moving object detection

Statistical and contextual information are typically used to detect moving regions in image sequences for a fixed camera.In this paper,we propose a fast and stable linear discriminant approach based on Gaussian Single Model(GSM)and Markov Random Field(MRF).The performance of GSM is analyzed first,and then two main improvements corresponding to the drawbacks of GSM are proposed:the latest filtered data based update scheme of the background model and the linear classification judgment rule based on spatial-temporal feature specified by MRF.Experimental results show that the proposed method runs more rapidly and accurately when compared with other methods.

VOICE ACTIVITY DETECTION UNDER RAYLEIGH DISTRIBUTION

This paper presents an improved Voice Activity Detection （VAD） algorithm which uses the Signal-to-Noise Ratio （SNR） measure. We assume that noise Power Spectral Density （PSD） in each spectral bin follows a Rayleigh distribution. Rayleigh distributions with its asymmetric tail characteristics give a better description of the noise PSD distribution than Gaussian distribution. Under this asstlmption, a new threshold updating expression is derived. Since the analytical integral of the false alarm probability, the threshold updating expression can be represented without the inverse complementary error function and low computational complexity is achieved in our system. Experimental results show that the proposed VAD outperforms or at least is comparable with the VAD scheme presented by Davis under several noise environments and has a lower computational complexity.

DPHM: A FAULT DETECTION PROTOCOL BASED ON HEARTBEAT OF MULTIPLE MASTER-NODES

In most of fault detection algorithms of distributed system, fault model is restricted to fault of process, and link failure is simply masked, or modeled by process failure. Both methods can soon use up system resource and potentially reduce the availability of system. A fault Detection Protocol based on Heartbeat of multiple Master-nodes (DPHM) is proposed, which can immediately and accurately detect and locate faulty links by adopting voting and electing mechanism among master-nodes. Thus, DPHM can effectively improve availability of system. In addition, in contrast with other detection protocols, DPHM reduces greatly the detection cost due to the structure of master-nodes.

Research on location of underground explosion center based on distributed testing system

Distributed testing system has strong applicability in the field of dynamic testing,which can centrally manage the testing equipment in different locations through the local area network,and meet the new requirements of the test.Based on the theory of seismic location,the location of underground explosion center was studied.The applicability of seismic location theory to the location of underground explosion center was verified by simulating the underground explosion with LS-DYNA simulation platform.Combined with distributed testing system theory and weighting method,the optimal distribution method of test points was summarized through data analysis.

Distributed Fabry-Perot Measurement System

The theoretic analysis indicates that if the lengths of the cascaded and paralleled Fabry-Perot sensors are properly selected, the crosstalk can be well restricted.And the experiment simulation results agree with that of the theoretic analysis.

Frequency-Feedback Based Islanding Detection Algorithm for Micro-Grid

The unintentional islanding of micro-grid may cause negative impacts on distribution loads and distributed generations,so it must be detected within the acceptable duration.In this paper a new islanding detection algorithm is proposed.This algorithm introduces the frequency feedback method by the reactive power compensation to derive the frequency continuous shift. Accordingly,the islanding can be detected by monitoring the frequency within 0.1 s.The simulation results prove that this algorithm has extremely small non-detection zone,and meanwhile it presents an excellent islanding detection speed as well.

Statistical Prediction under an Order Restriction

In this paper,a statistical prediction problem under ordered location and scale parameters are considered.Double-shrinkage predictors are given which use all the available data and improve on single-shrinkage predictors,and hence the best equivariant predictors.

Distributed Adaptive Compressed Video Sensing Using Smoothed Projected Landweber Reconstruction

A novel Compressed-Sensing-based(CS-based)Distributed Video Coding(DVC)system,called Distributed Adaptive Compressed Video Sensing(DISACOS),is proposed in this paper.In this system,the input frames are divided into key frames and non-key frames,which are encoded by block CS sampling.The key frames are encoded as CS measurements at substantially higher rates than the non-key frames and decoded by the Smoothed Projected Landweber(SPL)algorithm using multi-hypothesis predictions.For the non-key frames,a small number of CS measurements are first transmitted to detect blocks having low-quality Side Information(SI)generated by the conventional interpolation or extrapolation at the decoder;then,another group of CS measurements are sampled again upon the decoder’s request.To fully utilise the CS measurements,we adaptively allocate these measurements to each block in terms of different edge features.Finally,the residual frame is reconstructed using the SPL algorithm and the decoded non-key frame is simply determined as the sum of the residual frame and the SI.Experimental results have revealed that our CS-based DVC system yields better rate-distortion performance when compared with other schemes.

Intrusion Detection for Wireless Mesh Networks using Finite State Machine

Wireless Mesh Networks is vulnerable to attacks due to the open medium, dynamically changing network topology, cooperative algorithms, Lack of centralized monitoring and management point. The traditional way of protecting networks with firewalls and encryption software is no longer suffi- cient and effective for those features. In this paper, we propose a distributed intrusion detection ap- proach based on timed automata. A cluster-based detection scheme is presented, where periodically a node is elected as the monitor node for a cluster. These monitor nodes can not only make local intrusion detection decisions, but also cooperatively take part in global intrusion detection. And then we con- struct the Finite State Machine （FSM） by the way of manually abstracting the correct behaviors of the node according to the routing protocol of Dynamic Source Routing （DSR）. The monitor nodes can verify every node＇s behavior by the Finite State Ma- chine （FSM）, and validly detect real-time attacks without signatures of intrusion or trained data.Compared with the architecture where each node is its own IDS agent, our approach is much more efficient while maintaining the same level of effectiveness. Finally, we evaluate the intrusion detection method through simulation experiments.