Performance analysis of multi-channel order statistics detector for range-spread target

The problem of two order statistics detection schemes for the detection of a spatially distributed target in white Gaussian noise are studied.When the number of strong scattering cells is known,we first show an optimal detector,which requires many processing channels.The structure of such optimal detector is complex.Therefore,a simpler quasi-optimal detector is then introduced.The quasi-optimal detector,called the strong scattering cells’ number dependent order statistics（SND-OS） detector,takes the form of an average of maximum strong scattering cells with a known number.If the number of strong scattering cells is unknown in real situation,the multi-channel order statistics（MC-OS） detector is used.In each channel,a various number of maximums scattered from target are averaged.Then,the false alarm probability analysis and thresholds sets for each channel are given,following the detection results presented by means of Monte Carlo simulation strategy based on simulated target model and three measured targets.In particular,the theoretical analysis and simulation results highlight that the MC-OS detector can efficiently detect range-spread targets in white Gaussian noise.

Analysis of linear weighted order statistics CFAR algorithm

CFAR technique is widely used in radar targets detection fields. Traditional algorithm is cell averaging (CA), which can give a good detection performance in a relatively ideal environment. Recently, censoring technique is adopted to make the detector perform robustly. Ordered statistic (OS) and trimmed mean (TM) methods are proposed. TM methods treat the reference samples which participate in clutter power estimates equally, but this processing will not realize the effective estimates of clutter power. Therefore, in this paper a quasi best weighted (QBW) order statistics algorithm is presented. In special cases, QBW reduces to CA and the censored mean level detector (CMLD).

Passive Steganalysis Based on Higher Order Image Statistics of Curvelet Transform

Steganographic techniques accomplish covert communication by embedding secret messages into innocuous digital images in ways that are imperceptible to the human eye. This paper presents a novel passive steganalysis strategy in which the task is approached as a pattern classification problem. A critical part of the steganalyser design depends on the selection of informative features. This paper is aimed at proposing a novel attack with improved performance indices with the following implications： 1） employing higher order statistics from a curvelet sub-band image representation that offers better discrimination ability for detecting stego anomalies in images, as compared to other conventional wavelet transforms; 2） increasing the sensitivity and specificity of the system by the feature reduction phase; 3） realizing the system using an efficient classification engine, a neuro-C4.5 classifier, which provides better classification rate. An extensive experimental evaluation on a database containing 5600 clean and stego images shows that the proposed scheme is a state-of-the-art steganalyser that outperforms other previous steganalytic methods.

Asymptotic Analysis for U-Statistics and Its Application to Von Mises Statistics

Let - be i.i.d. random variables taking values in a measurable space ( Χ, B ). Let φ1: Χ →□ and φ: Χ2→□ be measurable functions. Assume that φ is symmetric, i.e. φ(x,y)=φ(y.x), for any x,y∈Χ . Consider U-statistic, assuming that Eφ1(Χ)=0, Eφ(x, X)=0 for all x∈X, Eφ2(x,X)<∞, Eφ21(X)<∞. We will provide bounds for ΔN=supx|F(x)-F0(x)-F1(x)|, where F is a distribution function of T and F0 , F1 are its limiting distribution function and Edgeworth correction respectively. Applications of these results are also provided for von Mises statistics case.

Combinatorial analysis on spatial information statistics for the karst water environment in Guiyang,China

The karst groundwater system is extremely vulnerable and easily contaminated by human activities.To understand the spatial distribution of contaminants in the groundwater of karst urban areas and contributors to the contamination,this paper employs the spatial information statistics analysis theory and method to analyze the karst groundwater environment in Guiyang City.Based on the karst ground water quality data detected in 61 detection points of the research area in the last three years,we made Kriging evaluation isoline map with some ions in the karst groundwater,such as SO4 2-,Fe 3+,Mn 2+and F -,analyzed and evaluated the spatial distribution,extension and variation of four types of ions on the basis of this isoline map.The results of the analysis show that the anomaly areas of SO4 2-,Fe 3+,Mn 2+,Fand other ions are mainly located in Baba’ao,Mawangmiao and Sanqiao in northwestern Gui- yang City as well as in its downtown area by reasons of the original non-point source pollution and the contamination caused by human activities(industrial and domestic pollution).

Tourism Statistics and the Business Register in Italy： A Comparative Analysis and future Outlooks for Integration

After the proposal of a possible insertion of tourism statistics （supply side） （TS） into Framework Regulation Integrating Business Statistics （FR1BS） on which an interesting debate is in progress between Eurostat and NSls, Istat （Italian Institute of Statistics） has started a costs/benefits analysis of this integration. ASIA （Statistical Register of Active Enterprises）, built up by Istat, represents in Italy the official source about the structure and the economic performance of the enterprises. ASIA, whose statistical units are enterprises of industry and services, has been developed through the statistical integration of different administrative sources, other minor archives available （covering particular sectors） and structural business statistics currently produced by Istat. The supply side TS are produced by lstat through surveys via Intermediate Bodies （Local Authorities）： each Intermediate Body has its own local register of accommodation establishments based on Local Kind-of-activity unit （LKAU）. In this paper, the results of a comparative analysis between the statistical units as recorded in ASIA and as surveyed by TS are presented; from first outcomes, considerable issues about data quality appear both at level of coverage for the three Nace groups of the TS （also underlined in the Methodological Manual on Tourism Statistics where for Italy a difference of 70% is reported） and for loss information relating to the location of the activities （switching from LKAU to Enterprises） as well as for timeliness （ASIA has two years of delay）. Then, the administrative local tourism registers （LTR） are analysed to understand： how many they are, their dissemination in the Italian territories, their primary purpose and source, the variables contained, the frequency of updates. This preliminary analysis is needed to identify the operative activities that Istat, together with the Intermediate Bodies, should start to use administrative archives for statistical purposes and to develop a unique tourism satellite archive （TSA）, facing many difficulties related to the reception of several LTR as well as methodological issues for record linkage. On the other hand, a TSA would lead numerous advantages： a unique and official list of internal accommodation establishments; a step towards integration of TS into FRIBS; a starting point to begin to use also administrative data produced by the Italian Police （mandatory communications on guests in the interests of public safety）, having a comparison term to assess their coverage.

Analysis on n-gram statistics and linguistic features of whole genome protein sequences

To obtain the statistical sequence analysis on a large number of genomic and proteomic sequences available for different organisms, the n-grams of whole genome protein sequences from 20 organisms were extracted. Their linguistic features were analyzed by two tests: Zipf power law and Shannon entropy, developed for analysis of natural languages and symbolic sequences. The natural genome proteins and the artificial genome proteins were compared with each other and some statistical features of n-grams were discovered. The results show that: the n-grams of whole genome protein sequences approximately follow the Zipf law when n is larger than 4; the Shannon n-gram entropy of natural genome proteins is lower than that of artificial proteins; a simple uni-gram model can distinguish different organisms; there exist organism-specific usages of "phrases" in protein sequences. It is suggested that further detailed analysis on n-gram of whole genome protein sequences will result in a powerful model for mapping the relationship of protein sequence, structure and function.

Microarray Analysis Using Rank Order Statistics for ARCH Residual Empirical Process

Statistical two-group comparisons are widely used to identify the significant differentially expressed (DE) signatures against a therapy response for microarray data analysis. We applied a rank order statistics based on an Autoregressive Conditional Heteroskedasticity (ARCH) residual empirical process to DE analysis. This approach was considered for simulation data and publicly available datasets, and was compared with two-group comparison by original data and Auto-regressive (AR) residual. The significant DE genes by the ARCH and AR residuals were reduced by about 20% - 30% to these genes by the original data. Almost 100% of the genes by ARCH are covered by the genes by the original data unlike the genes by AR residuals. GO enrichment and Pathway analyses indicate the consistent biological characteristics between genes by ARCH residuals and original data. ARCH residuals array data might contribute to refining the number of significant DE genes to detect the biological feature as well as ordinal microarray data.

Statistics Analysis:FDI Obsorbing in Jan-Jun

According to China's Customs' statistics,from January to May 2008,the import and export volume of foreign- invested enterprises totaled US$563.612 billion,an increase of 21.28 percent over the same period of last year,5.02 percent lower than the growth rate of the country (26.30 percent) in the same period,accounting for 55.69 percent of the total import and export of the country.(See Chart 1)

Parameter estimation for rigid body after micro-Doppler removal based on L-statistics in the radar analysis

In traditional inverse synthetic aperture radar （ISAR） imaging of moving targets with rotational parts, the micro-Doppler （m-D） effects caused by the rotational parts influence the quality of the radar images. Recently, L. Stankovic proposed an m-D removal method based on L-statistics, which has been proved effective and simple. The algorithm can extract the m-D effects according to different behaviors of signals induced by rotational parts and rigid bodies in time-frequency （T-F） domain. However, by removing m-D effects, some useful short time Fourier transform （STFT） samples of rigid bodies are also extracted, which induces the side lobe problem of rigid bodies. A parameter estimation method for rigid bodies after m-D removal is proposed, which can accurately re- cover rigid bodies and avoid the side lobe problem by only using m-D removal. Simulations are given to validate the effectiveness of the proposed method.

Statistics and Analysis on Papers Published on Journal ‘Advanced Technology of Electrical Engineering and Energy’

The paper presented the statistics and analysis on papers published on the journal 'Advanced Technology of Electrical Engineering and Energy' from 1996 to 2008: the paper acceptance rate,the paper category,the first author's affiliations,the top 7 first authors,the top 10 coauthors and also the journal evaluation indexes of the journal.It offers details of the journal to anyone interested,especially to our editorial board and our broad readers.

A brief statistics and analysis on residential electricity consumption in China

The statistic data of residential electricity consumptionshown in the table P.58 are quoted from the EnergyStatistical Year Book published by the National Statistic Bureau andthe statistics issued by the Ministry of Energy.The reason of the differences between the data from the twosaid sources is that the latter does not include the consumption sup-plied by the local small power sources.From the statistical data we can see that:

Cryo-EM Data Statistics and Theoretical Analysis of KaiC Hexamer

Cryo-electron microscopy(cryo-EM) provides a powerful tool to resolve the structure of biological macromolecules in natural state. One advantage of cryo-EM technology is that different conformation states of a protein complex structure can be simultaneously built, and the distribution of different states can be measured. This provides a tool to push cryo-EM technology beyond just to resolve protein structures, but to obtain the thermodynamic properties of protein machines. Here, we used a deep manifold learning framework to get the conformational landscape of Kai C proteins, and further obtained the thermodynamic properties of this central oscillator component in the circadian clock by means of statistical physics.

Estimation of Peanut Maturity Using Color Image Analysis

Peanuts pods grow underground and mature unevenly, resulting that choosing the correct time to harvest is more complicated than other crops. Pod maturity can be determined by blasting with a pressure washer to remove outer skin of the pod (exocarp) to expose the color of the middle layer (mesocarp). The mesocarp color changes with maturity from white to yellow, orange, brown and finally black. The sum of percentage from orange, brown, and black mesocarp (OBB) color and black color (BL) represents the kernels that are mature enough to harvest. The goal of this research is to identify methodologies to estimate OBB and BL of the pods using RGB images taken in the field and validate the proposed model using other pod images. The Mahalanobis distance classification method was used to process sets of images and calculate pod area (number of pixels) corresponding to two classes (mesocarp and background) with nine different color groups. The results showed a performance of 94% effectiveness for mesocarp using Mahalanobis distance classification. Statistical regression for OBB and BL was developed based on 315 images of peanut pods taken from the field. The R2 and root mean square error of predicted and actual OBB were 0.93 and 4.1%, respectively. The R2 and root mean square error of predicted and actual BL were 0.88 and 1.8%, respectively. The validation of OBB using other images provided reasonable estimation (R2 = 0.98 and RMSE = 2.73%). This study introduces a novel, cost-effective, and non-destructive method for estimating peanut maturity using RGB imagery and Mahalanobis distance classification in the field. This innovative approach addresses the limitations of traditional methods and offers a robust alternative for real-time maturity assessment.

Lottery Numbers and Ordered Statistics

The lottery has long captivated the imagination of players worldwide, offering the tantalizing possibility of life-changing wins. While winning the lottery is largely a matter of chance, as lottery drawings are typically random and unpredictable. Some people use the lottery terminal randomly generates numbers for them, some players choose numbers that hold personal significance to them, such as birthdays, anniversaries, or other important dates, some enthusiasts have turned to statistical analysis as a means to analyze past winning numbers identify patterns or frequencies. In this paper, we use order statistics to estimate the probability of specific order of numbers or number combinations being drawn in future drawings.

An Analysis of the Fragmentation of Observing Time At the Muztagh-Ata Site

Cloud cover plays a pivotal role in assessing observational conditions for astronomical site-testing.Except for the fraction of observing time,its fragmentation also wields a significant influence on the quality of nighttime sky clarity.In this article,we introduce the functionΓ∈[0,1],designed to comprehensively capture both the fraction of available observing time and its continuity.Leveraging in situ measurement data gathered at the Muztagh-Ata site between 2017 and 2021,we showcase the effectiveness of our approach.The statistical result illustrates that the Muztagh-Ata site affords approximately 122 nights that were absolutely clear and 205 very good nights annually,corresponding toΓ≥0.9 andΓ≥0.36 respectively.

Quantitative analysis and prediction of the sound field convergence zone in mesoscale eddy environment based on data mining methods

The mesoscale eddy(ME)has a significant influence on the convergence effect in deep-sea acoustic propagation.This paper use statistical approaches to express quantitative relationships between the ME conditions and convergence zone(CZ)characteristics.Based on the Gaussian vortex model,we construct various sound propagation scenarios under different eddy conditions,and carry out sound propagation experiments to obtain simulation samples.With a large number of samples,we first adopt the unified regression to set up analytic relationships between eddy conditions and CZ parameters.The sensitivity of eddy indicators to the CZ is quantitatively analyzed.Then,we adopt the machine learning(ML)algorithms to establish prediction models of CZ parameters by exploring the nonlinear relationships between multiple ME indicators and CZ parameters.Through the research,we can express the influence of ME on the CZ quantitatively,and achieve the rapid prediction of CZ parameters in ocean eddies.The prediction accuracy(R)of the CZ distance(mean R:0.9815)is obviously better than that of the CZ width(mean R:0.8728).Among the three ML algorithms,Gradient Boosting Decision Tree has the best prediction ability(root mean square error(RMSE):0.136),followed by Random Forest(RMSE:0.441)and Extreme Learning Machine(RMSE:0.518).

Failure evolution and disaster prediction of rock under uniaxial compression based on non-extensive statistical analysis of electric potential

Rock failure can cause serious geological disasters,and the non-extensive statistical features of electric potential(EP)are expected to provide valuable information for disaster prediction.In this paper,the uniaxial compression experiments with EP monitoring were carried out on fine sandstone,marble and granite samples under four displacement rates.The Tsallis entropy q value of EPs is used to analyze the selforganization evolution of rock failure.Then the influence of displacement rate and rock type on q value are explored by mineral structure and fracture modes.A self-organized critical prediction method with q value is proposed.The results show that the probability density function(PDF)of EPs follows the q-Gaussian distribution.The displacement rate is positively correlated with q value.With the displacement rate increasing,the fracture mode changes,the damage degree intensifies,and the microcrack network becomes denser.The influence of rock type on q value is related to the burst intensity of energy release and the crack fracture mode.The q value of EPs can be used as an effective prediction index for rock failure like b value of acoustic emission(AE).The results provide useful reference and method for the monitoring and early warning of geological disasters.

Load Statistics Priority Random Access Technology Based on Air-Space-Ground Integrated Network

In today's world where everything is interconnected, air-space-ground integrated networks have become a current research hotspot due to their characteristics of high, long and wide area coverage. Given the constantly changing and dynamic characteristics of air and space networks, along with the sheer number and complexity of access nodes involved, the process of rapid networking presents substantial challenges. In order to achieve rapid and dynamic networking of air-space-ground integrated networks, this paper focuses on the study of methods for large-scale nodes to randomly access satellites. This paper utilizes a cross-layer design methodology to enhance the access success probability by jointly optimizing the physical layer and medium access control(MAC) layer aspects. Load statistics priority random access(LSPRA) technology is proposed.Experiments show that when the number of nodes is greater than 1 000, this method can also ensure stable access performance, providing ideas for the design of air-space-ground integrated network access systems.