L1范数与IQR统计量组合的GNSS坐标序列粗差探测算法

GNSS坐标时间序列中不可避免地含有粗差,未剔除的粗差将会导致参数估计有偏。因此,粗差探测与剔除是GNSS坐标序列分析中一项重要的数据预处理工作。针对GNSS坐标时间序列特点,提出了一种将L1范数(L1-norm)估计与四分位距统计量IQR(interquartile range)组合的移动开窗粗差探测算法,称之为L1_Mod IQR。该方法的主要思想是,首先利用L1范数估计得到较"真实"的残差,然后再对残差采用IQR统计量进行粗差探测。将L1_Mod IQR法与"3σ"法、基于最小二乘的τ检验法等粗差探测算法进行了模拟计算与对比,验证了该算法的有效性。进一步采用L1_Mod IQR算法对中国区域10个IGS站的高程时间序列进行了分析,结果表明中国区域IGS站高程序列的粗差剔除率最小为0.1%,最大为2.6%。并且以WUHN站为例与SOPAC提供的结果进行了对比,结果表明SOPAC提供的"Clean"数据仍含有大量的粗差,而L1_Mod IQR算法能够有效地剔除粗差。

Customized Optimization for Vehicle Acoustic Statistical Energy Analysis

Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NVH targets based on the specific needs of different project teams during the initial project stages.This approach innovatively integrates dynamic optimization,Radial Basis Function(RBF),and Fuzzy Design Variables Genetic Algorithm(FDVGA) into the optimization process of Statistical Energy Analysis(SEA),and also takes vehicle sheet metal into account in the optimization of sound packages.In the implementation process,a correlation model is established through Python scripts to link material density with acoustic parameters,weight,and cost.By combining Optimus and VaOne software,an optimization design workflow is constructed and the optimization design process is successfully executed.Under various constraints related to acoustic performance,weight and cost,a globally optimal design is achieved.This technology has been effectively applied in the field of Battery Electric Vehicle(BEV).

Cranial morphometric study of four giant flying squirrels(Petaurista)(Rodentia:Sciuridae) from China

The present study revisited the controversial taxonomic status ofPetaurista yunanensis, P. philippensis, P. hainana, and P. petaurista by using a considerably extended set of morphometrical characters （26 cranial variables from 60 adult specimen skulls）. The results revealed no sexual dimorphism in any of the four species but confirmed significant craniometric differences among the four species in both the principal components analysis （PCA） and discriminant function analysis （DFA）, with the greatest distinction observed between P. petaurista and other Petaurista species. Both univariate and multivariate analysis indicated that the morphological differences between P. yunanensis and P. philippensis were less than that between P. philippensis and P. hainana. The morphometric results were concordant in geographic patterns with mtDNA data from previous studies and indicated that P. petaurista, P. hainana, P. philippensis, and P. yunanensis could be recognized as valid species.

Identification and Quantification of Non-Spherical Particles

In commercial applications of phase Doppler anemometry (PDA), the effectiveness of non sphericity of particles is present and the response of PDA system deviates from the theoretical prediction. In this paper, the statistic characteristics of PDA signal related to irregular particles is analyzed and a method of statistic classification of irregular particles is proposed.It proves that the parameter of PDA signal for irregular particles is an unbiased estimation for spherical ones, the mean of the phase difference is in direct proportion to the mean diameter of particles and the standard deviation of the phase difference increases linearly with the standard deviation of irregular particles. As an application of the identification of irregular objects, fuzzy patterns and similarities of haemocytes are used to recognize and quantify cell samples.The statistic classification of particles is more significant in practice.

Application of Statistic Analysis on the Selection of Quantitative Characteristics Listed in the DUS Test Guideline of Tagetes L.

[Objective] This paper researched how to use specific approach to select quantitative characteristics which would be listed in the DUS Test Guideline of Tagetes L. [Method] With the aid of statistic analysis, the uniformity, stability and correlation of 14 pre-selected characteristics were analyzed. [Result] The expression of peduncle length of terminal flower had low uniformity within a variety; the expres- sion of main stem thickness was not stable in continuous growing cycles; there were four pairs of quantitative characteristics which are （very） significantly correlated, namely, leaf length and leaf width, diameter of flower head and length of outer ligu- late floret, number of ligulate floret whorls and number of ligulate floret, leaf width and width of terminal leaflet of pinnate leaves. Based on the requirements of char- acteristic selection and the results of statistic analysis, five characteristics including peduncle length of terminal flower, thickness of the main stem, leaf width, length of outer ligulate floret and number of ligulate floret were deleted. [Conclusion] For the first time, this paper introduced the application of statistic analysis on the selection of quantitative characteristics.

A New Approach for on-Line Blind Equalization and Channel Identification

A new approach for blind equalization and channel identification is proposed in this paper. The equalization scheme is based on over sampling technique and an independent component analysis network. The equalized sequence and its higher order statistics are used to identify the channel parameters. Compared to traditional equalization methods, the proposed approach is with a simple architecture, and does not need learning sequences. Computer simulations show the validity of the proposed method.

Research of NS dataflow mechanism and its analyzer implementation

This paper analyzes the main elements in NS network simulator, makes adetailed view of dataflow management in a link, a node, and an agent, respectively, and introducesthe information described by its trace file. Based on the analysis of transportation and treatmentof different packets in NS, a dataflow state machine is proposed with its states exchange triggeringevents and a dataflow analyzer is designed and implemented according to it. As the machine statefunctions, the analyzer can make statistic of total transportation flux of a specified dataflow andoffer a general fluctuation diagram. Finally, a concrete example is used to test its performance.

Probabilistic Top-k Query:Model and Application on Web Traffic Analysis

Top-k ranking of websites according to traffic volume is important for Internet Service Providers(ISPs) to understand network status and optimize network resources. However, the ranking result always has a big deviation with actual rank for the existence of unknown web traffic, which cannot be identified accurately under current techniques. In this paper, we introduce a novel method to approximate the actual rank. This method associates unknown web traffic with websites according to statistical probabilities. Then, we construct a probabilistic top-k query model to rank websites. We conduct several experiments by using real HTTP traffic traces collected from a commercial ISP covering an entire city in northern China. Experimental results show that the proposed techniques can reduce the deviation existing between the ground truth and the ranking results vastly. In addition, we find that the websites providing video service have higher ratio of unknown IP as well as higher ratio of unknown traffic than the websites providing text web page service. Specifically, we find that the top-3 video websites have more than 90% of unknown web traffic. All these findings are helpful for ISPs understanding network status and deploying Content Distributed Network(CDN).

New Resolution to Coupling Loss Factor of Beam Plate Structure

The transmission of transverse vibrational energy of a vertically rigid beam plate coupled structure is analyzed to get the theoretical results of coupling loss factor(CLF), a very important parameter in statistical energy analysis(SEA). The modal analysis method is used to discuss the vibration energy of the typical model, as well as the power flow between the two subsystems. Furthermore, the resolution to the coupling loss factor is also derived and compared with the measured values. The analytical results of the coupling loss factor agree with the measured ones fully, this new resolution is significant for the application of SEA.

CLASSIFICATION OF MPSK SIGNALS USING CUMULANT INVARIANTS

A new feature based on higher order statistics is proposed for classification of MPSKsignals, which is invariant with respect to translation (shift), scale and rotation transforms of MPSK signal constellations, and can suppress additive color or white Gaussian noise. Application of the new feature to classification of MPSK signals, at medium signal-to-noise ratio with specified sample size, results in high probability of correct identification. Finally, computer simulations and comparisons with existing algorithms are given.

Performance Monitoring and Diagnosis of Multivariable Model Predictive Control Using Statistical Analysis

A statistic-based benchmark was proposed for performance assessment and monitoring of model predic- tive control; the benchmark was straightforward and achievable by recording a set of output data only when the control performance was good according to the user’s selection. Principal component model was built and an auto- regressive moving average filter was identified to monitor the performance; an improved T2 statistic was selected as the performance monitor index. When performance changes were detected, diagnosis was done by model validation using recursive analysis and generalized likelihood ratio (GLR) method. This distinguished the fact that the per- formance change was due to plant model mismatch or due to disturbance term. Simulation was done about a heavy oil fractionator system and good results were obtained. The diagnosis result was helpful for the operator to improve the system performance.

A Statistical Parameter Analysis and SVM Based Fault Diagnosis Strategy for Dynamically Tuned Gyroscopes

Gyro's fault diagnosis plays a critical role in inertia navigation systems for higher reliability and precision. A new fault diagnosis strategy based on the statistical parameter analysis (SPA) and support vector machine (SVM) classification model was proposed for dynamically tuned gyroscopes (DTG). The SPA, a kind of time domain analysis approach, was introduced to compute a set of statistical parameters of vibration signal as the state features of DTG, with which the SVM model, a novel learning machine based on statistical learning theory (SLT), was applied and constructed to train and identify the working state of DTG. The experimental results verify that the proposed diagnostic strategy can simply and effectively extract the state features of DTG, and it outperforms the radial-basis function (RBF) neural network based diagnostic method and can more reliably and accurately diagnose the working state of DTG.

Numerical Analysis of a Blocking Mass Attenuating Wave Propagation

Based on wave theory, blocking mass impeding propagation of flexural waves was analyzed with force excitation applied on a ship pedestal. The analysis model of a complex structure was developed by combining statistical energy analysis and the finite element method. Based on the hybrid FE-SEA method, the vibro-acoustic response of a complex structure was solved. Then, the sound radiation of a cylindrical shell model influenced by blocking mass was calculated in mid/high frequency. The result shows that blocking mass has an obvious effect on impeding propagation. The study provides a theoretical and experimental basis for application of the blocking mass to structure-borne sound propagation control.

The Influence of Blocking Mass Parameters on the Vibration Isolation Performance of a Power Cabin

Rigid blocking masses are located in the typical base structure of a power cabin based on the impedance mismatch principle.By combining the acoustic-structural coupling method and statistical energy analysis,the full-band vibration and sound radiation reduction effect of vibration isolation masses located in a base structure was researched.The influence of the blocking mass’ cross-section size and shape parameters and the layout location of the base isolation performance was discussed.Furthermore,the effectiveness of rigid vibration isolation design of the base structure was validated.The results show that the medium and high frequency vibration and sound radiation of a power cabin are effectively reduced by a blocking mass.Concerning weight increment and section requirement,suitably increasing the blocking mass size and section height and reducing section width can result in an efficiency-cost ratio.

Impacts of Packet Collisions on Link Throughput in CSMA Wireless Networks

It is known that packet collisions in wireless networks will deteriorate system performance, hence substantial efforts have been made to avoid collision in multi-user access designs. Also, there have been many studies on throughput analysis of CSMA wireless networks. However, for a typical CSMA network in which not all nodes can sense each other, it is still not well investigated how link throughputs are affected by collisions. We note that in practical 802.11-like networks, the time is divided into mini-timeslots and packet collisions are in fact unavoidable. Thus, it is desirable to move forward to explore how collisions in such a network will affect system performance. Based on the collision-free ideal CSMA network(ICN) model, this paper attempts to analyze link throughputs when taking the backoff collisions into account and examine the effect of collisions on link throughputs. Specifically, we propose an Extended Ideal CSMA Network(EICN) model to characterize the collision effects as well as the interactions and dependency among links in the network. Based on EICN, we could directly compute link throughputs and collision probabilities. Simulations show that the EICN model is of high accuracy. Under various network topologies and protocol parameter settings, the computation error of link throughputs using EICN is kept to 4% or below. Interestingly, we find that unlike expected, the effect of collisions on link throughputs in a modest CSMA wireless network is not significant, which enriches our understanding on practical CSMA wireless networks such as Wi-Fi.

Application of Two-Order Difference to Gap Statistic

Gap statistic is a well-known index of clustering validity, but its realization is difficult to be comprehended and accurately determined. A direct method is presented to improve the performance of the Gap statistic, which applies the two-order difference of within-cluster dispersion to replace the constructed null reference distribution in the Gap statistic. Hence, the realization of the Gap statistic becomes easy and is reformulated, and its uncertainty in applications is reduced. Also, the limitation of the Gap statistic is analyzed by two typical examples, that is, the Gap statistic is difficult to be applied to the dataset that contains strong-overlap or uneven-density clusters. Experiments verify the usefulness of the proposed method.

A novel adaptive classification scheme for digital modulations in satellite communication

To make the modulation classification system more suitable for signals in a wide range of signal to noise ratios （SNRs）, a novel adaptive modulation classification scheme is presented in this paper. Differ-ent from traditional schemes, the proposed scheme employs a new SNR estimation algorithm for small samples before modulation classification, which makes the modulation classifier work adaptively according to estimated SNRs. Furthermore, it uses three efficient features and support vector machines （SVM） in modulation classification. Computer simulation shows that the scheme can adaptively classify ten digital modulation types （i.e. 2ASK, 4ASK, 2FSK, 4FSK, 2PSK, 4PSK, 16QAM, TFM, π/4QPSK and OQPSK） at SNRS ranging from 0dB to 25dB and success rates are over 95% when SNR is not lower than 3dB. Accuracy, efficiency and simplicity of the proposed scheme are obviously improved, which make it more adaptive to engineering applications.

Involvement of the Nerve Fibers in the Human Skin Neurofibromatosis

Neurofibromatosis type 2 is a well known disease of the human skin. Its microscopic and ultramicroscopic features are also well defined. Aim： The aim of this work was to study the involvement of catecholaminergic nerve fibers in the human skin neurofibromatosis. Bioptic fragments of the human skin have been harvested from healthy and diseased subjects. On these specimens the following analysis were performed： 1） light microscopic observation after colouring with hematoxyline-Eosine. 2） lmmunochemical staining for Protein Gene Product 9.5.3） Fluorescent staining for catecholaminergic nerve fibers. 4） Quantitative analysis of images by means of the Quantimet analyzer Leica. 5） Statistical analysis of the quantitative morphological data comparing the healthy with diseased subjects. Comparing the light microscopy images in normal and pathological subjects the authors can affirm that the skin neurofibromatosis induces a strong decrease of the nerve fibers cutted in small pieces and destroyed. Also the catecholaminergic nerve fibers are strongly reduced and destroyed. Quantitative analysis of images and statistical analysis of the morphological data confirm that neurofibromatosis induces strong changes of the skin nerve fibers. The authors＇ results confirm that the neurofibromatosis type 2 induces an almost total destruction of the skin nerve fibers.

New Methodology for Direct Algorithms in Russell Projection ＂Stereographic Projection＂

Projections of geodetic are important for all countries all over the world, where using system coordinates for solving any problems in measurements of surveying works. Russell projection is one of projections used in some countries. Direct algorithms in this projection use two methods. The first method uses partial differential equation, which is not after six orders in the series. While, the second method uses traditional series （exponential series）, which is very difficult and requires complex statistical analysis. New methodology has been applied for direct algorithms in Russell projection using general law of unlimited algorithms by simple method.