基于VFP实现度分秒与度小数批量转换

度分秒和度小数角度之间的互相转换是工程测量领域常见的问题之一。利用VFP中追加、字符串处理、数学运算、循环等功能,批量实现度分秒与度小数之间的互相转换,能大幅度提高转换的正确性和可靠性,提高工作效率。

Acoustic location echo signal extraction of buried non-metallic pipelines based on EMD and wavelet threshold joint denoising

In the acoustic detection process of buried non-metallic pipelines,the echo signal is often interfered by a large amount of noise,which makes it extremely difficult to effectively extract useful signals.An denoising algorithm based on empirical mode decomposition(EMD)and wavelet thresholding was proposed.This method fully considered the nonlinear and non-stationary characteristics of the echo signal,making the denoising effect more significant.Its feasibility and effectiveness were verified through numerical simulation.When the input SNR(SNRin)is between-10 dB and 10 dB,the output SNR(SNRout)of the combined denoising algorithm increases by 12.0%-34.1%compared to the wavelet thresholding method and by 19.60%-56.8%compared to the EMD denoising method.Additionally,the RMSE of the combined denoising algorithm decreases by 18.1%-48.0%compared to the wavelet thresholding method and by 22.1%-48.8%compared to the EMD denoising method.These results indicated that this joint denoising algorithm could not only effectively reduce noise interference,but also significantly improve the positioning accuracy of acoustic detection.The research results could provide technical support for denoising the echo signals of buried non-metallic pipelines,which was conducive to improving the acoustic detection and positioning accuracy of underground non-metallic pipelines.

Approach for epileptic EEG detection based on gradient boosting

The automatic seizure detection is significant for epilepsy diagnosis and it can alleviate the work intensity of inspecting prolonged electroencephalogram （EEG）. This paper presents and investigates a novel machine learning approach utilizing gradient boosting to detect seizures from long-term EEG. We apply relative fluctuation index to extract features of long-term intracranial EEG data. A classifier trained with the gradient boosting algorithm is adopted to discriminate the seizure and non-seizure EEG signals. Smoothing and collar technique are finally used as post-processing in order to improve the detection accuracy further. The seizure detection method is assessed on Freiburg EEG datasets from 21 patients. The experimental results indicate that the proposed method yields an average sensitivity of 94. 60% with a false detection rate of 0. 18/h.

On the Total Domination Number of Graphs with Minimum Degree at Least Three

Let G be a simple graph with no isolated vertices. A set S of vertices of G is a total dominating set if every vertex of G is adjacent to some vertex in S . The total domination number of G , denoted by γ t (G) , is the minimum cardinality of a total dominating set of G . It is shown that if G is a graph of order n with minimum degree at least 3, then γ t (G)≤n/2 . Thus a conjecture of Favaron, Henning, Mynhart and Puech is settled in the affirmative.

Engineering properties of sintered waste sludge as lightweight aggregate in a densified concrete mixture

The global trend towards carbon reduction,energy conservation,and sustainable use of resources has led to an increased focus on the use of waste sludge in construction.We used waste sludge from a reservoir to produce high-strength sintered lightweight aggregate,and then used the densified mixture design algorithm to create high-performance concrete from the sintered aggregate with only small amounts of mixing water and cement.Ultrasonic,electrical resistance and concrete strength efficiency tests were perfo...

Characteristics of non-magnetic nanoparticles in magnetically fluidized bed by adding coarse magnets

The fluidization behavior of SiO2, ZnO and TiO2 non-magnetic nanoparticles was investigated in a magnetically fluidized bed （MFB） by adding coarse magnets. The effects of both the amount of coarse magnets and the magnetic field intensity on the fluidization quality of these nanoparticles were investigated. The results show that the coarse magnets added to the bed lead to a reduction in the size of the aggregates formed naturally by the primary nanopartieles. As the macroscopic performances of improved fluidization quality, the bed expansion ratio increases whilst the minimum fluidization velocity decreases with increasing the magnetic field intensity, but for TiO2 nanoparticles there exists a suitable magnetic field intensity of 0.059 6 T. The optimal amounts of coarse magnets for SiO2, ZnO and TiO2 non-magnetic nanoparticles are 40%, 50% and 60% （mass fraction）, respectively. The bed expansion results analyzed by the Richardson-Zaki scaling law show that the exponents depend on both the amount of coarse magnets and the magnetic field intensity.

Homogenized Daily Mean/Maximum/Minimum Temperature Series for China from 1960-2008

Inhomogeneities in the daily mean/maximum/ minimum temperature （Tm/Tmax/Tmin） series from 1960- 2008 at 549 National Standard Stations （NSSs） in China were analyzed by using the Multiple Analysis of Series for Homogenization （MASH） software package. Typical biases in the dataset were illustrated via the cases of Beijing （B J）, Wutaishan （WT）, Urumqi （UR） and Henan （HN） stations. The homogenized dataset shows a mean warming trend of 0.261/0.193/0.344℃/decade for the annual series of Tm/Tmax/Tmin, slightly smaller than that of the original dataset by 0.006/0.009/0.007℃/decade. However, considerable differences between the adjusted and original datasets were found at the local scale. The adjusted Tmin series shows a significant warming trend almost everywhere for all seasons, while there are a number of stations with an insignificant trend in the original dataset. The adjusted Tm data exhibit significant warming trends annually as well as for the autumn and winter seasons in northern China, and cooling trends only for the summer in the middle reaches of the Yangtze River and parts of central China and for the spring in southwestern China, while the original data show cooling trends at several stations for the annual and seasonal scales in the Qinghai, Shanxi, Hebei, and Xinjiang provinces. The adjusted Tmax data exhibit cooling trends for summers at a number of stations in the mid-lower reaches of the Yangtze and Yellow Rivers and for springs and winters at a few stations in southwestern China, while the original data show cooling trends at three/four stations for the annual/autumn periods in the Qinghai and Yunnan provinces. In general, the number of stations with a cooling trend was much smaller in the adjusted Tm and Tmax dataset than in the original dataset. The cooling trend for summers is mainly due to cooling in August. The results of homogenization using MASH appear to be robust; in particular, different groups of stations with consideration of elevation led to minor effects in the results.

Accuracy Analysis of Geopotential Coefficients Recovered from In-situ Disturbing Potential by Energy Conservation Method

The characteristics of the normal equation created in recovering the Earth gravity model （EGM） by least-squares （LS） adjustment from the in-situ disturbing potential is discussed in detail. It can be concluded that the normal equation only depends on the orbit, and the choice of a priori gravity model has no effect on the LS solution. Therefore, the accuracy of the recovered gravity model can be accurately simulated. Starting from this point, four sets of disturbing potential along the orbit with different level of noise were simulated and were used to recover the EGM. The results show that on the current accuracy level of the accelerometer calibration, the accuracy of the EGM is not sufficient to reflect the time variability of the Earth＇s gravity field, as the dynamic method revealed.

Quantile Trends in Temperature Extremes in China

A number of recent studies have examined trends in extreme temperature indices using a linear regression model based on ordinary least-squares. In this study, quantile regression was, for the first time, applied to examine the trends not only in the mean but also in all parts of the distribution of several extreme temperature indices in China for the period 1960–2008. For China as a whole, the slopes in almost all the quantiles of the distribution showed a notable increase in the numbers of warm days and warm nights, and a significant decrease in the number of cool nights. These changes became much faster as the quantile increased. However, although the number of cool days exhibited a significant decrease in the mean trend estimated by classical linear regression, there was no obvious trend in the upper and lower quantiles. This finding suggests that examining the trends in different parts of the distribution of the time-series is of great importance. The spatial distribution of the trend in the 90 th quantile indicated that there was a pronounced increase in the numbers of warm days and warm nights, and a decrease in the number of cool nights for most of China, but especially in the northern and western parts of China, while there was no significant change for the number of cool days at almost all the stations.

Back analysis of general slope under earthquake forces using upper bound theorem

Long time monitoring is acquired to obtain the displacement data for displacement-based geotechnical material back analysis, and these data are hard to be measured under some special condition, such as earthquake. For a simple homogeneous slope, the position of a critical failure surface is determined by value of c/tan ~b. Utilizing upper bound theorem of limit analysis, the external work rate and internal energy for normal slope under earthquake forces are given, and the formula for minimum safety factor is derived. On this basis, the equation of slip surface and the surface depth of a given position are solved. In this way, the strength parameter can be analyzed by known slip surface depth. For practical use, the surface depth for a given slope under varying strength parameter is presented. Finally, two examples are given to show its simplicity and effectiveness.

Robust background subtraction in traffic video sequence

For intelligent transportation surveillance, a novel background model based on Mart wavelet kernel and a background subtraction technique based on binary discrete wavelet transforms were introduced. The background model kept a sample of intensity values for each pixel in the image and used this sample to estimate the probability density function of the pixel intensity. The density function was estimated using a new Marr wavelet kernel density estimation technique. Since this approach was quite general, the model could approximate any distribution for the pixel intensity without any assumptions about the underlying distribution shape. The background and current frame were transformed in the binary discrete wavelet domain, and background subtraction was performed in each sub-band. After obtaining the foreground, shadow was eliminated by an edge detection method. Experimental results show that the proposed method produces good results with much lower computational complexity and effectively extracts the moving objects with accuracy ratio higher than 90%, indicating that the proposed method is an effective algorithm for intelligent transportation system.

Particle filter based on iterated importance density function and parallel resampling

The design, analysis and parallel implementation of particle filter(PF) were investigated. Firstly, to tackle the particle degeneracy problem in the PF, an iterated importance density function(IIDF) was proposed, where a new term associating with the current measurement information(CMI) was introduced into the expression of the sampled particles. Through the repeated use of the least squares estimate, the CMI can be integrated into the sampling stage in an iterative manner, conducing to the greatly improved sampling quality. By running the IIDF, an iterated PF(IPF) can be obtained. Subsequently, a parallel resampling(PR) was proposed for the purpose of parallel implementation of IPF, whose main idea was the same as systematic resampling(SR) but performed differently. The PR directly used the integral part of the product of the particle weight and particle number as the number of times that a particle was replicated, and it simultaneously eliminated the particles with the smallest weights, which are the two key differences from the SR. The detailed implementation procedures on the graphics processing unit of IPF based on the PR were presented at last. The performance of the IPF, PR and their parallel implementations are illustrated via one-dimensional numerical simulation and practical application of passive radar target tracking.

Cardinal temperatures and required biological days from sowing to emergence of three millet species （common, foxtail, pearl millet）

The modeling of germination and seedling emergence is required for the construction of a simulation model of three species of millet （panicum miliaceum, pennisetum galucum and setaria italica）. This study provides the necessary temperature parameters to model these processes. For this purpose, different non-linear regression models including fiat, logistic, quadratic, sigmoidal, dent-like, segmented, beta and curvilinear were used. Root Mean Square of Errors, coefficient of determination and regression coefficients of predicted values versus observed were used to find the appropriate model. Investigating regression coefficients indicated that dent-like model has the least RMSE and a coefficient （RMSE=0.000009, a=0.0006） and the biggest R2 and b coefficient （R2=0.96, b=0.98） in common millet. These coefficients were （RMSE=0.01, a=0.005） and （R2=0.94, b=0.97）, and （RMSE=0.004, a=0.05） and （R2=0.99, b=0.99）, for beta in foxtail and pearl millet, respectively. According to these coefficients, dent-like, was chosen as the best model to describe the response of common millet germination to temperature （Tb=7~C and Tc=49.50℃）. Also beta, was chosen for foxtail millet （Tb=7℃, Tc=49.50℃）. Beta, was chosen as the best model for pearl millet （Tb=6.5 ℃ and To=4 ℃ ）. These parameters can be used in millet simulation models to predict sowing to emergence duration based on a thermal time concept. Also, required biological days from sowing to emergence using these models varied from 3.57, 4.29 and 5.54, for common millet, foxtail millet and pearl millet, respectively.

Improved geologic surface approximation using a multiquadric method with additional constraints

Geologic surface approximation is profoundly affected by the presence, density and location of scattered geologic input data. Many studies have recognized the importance of utilizing varied sources of information when reconstructing a surface. This paper presents an improved geologic surface approximation method using a multiquadric function and borehole data. Additional information, i.e., inequality elevation and dip-strikes data extracted from outcrops or mining faces, is introduced in the form of physical constraints that control local changes in the estimated surface. Commonly accepted hypothesis states that geologic surfaces can be approximated to any desired degree of exactness by the summation of regular, mathematically defined, surfaces: in particular displaced quadric forms. The coefficients of the multiquadric functions are traditionally found by a least squares method. The addition of physical constraints in this work makes such an approach into a non-deterministic polynomial time problem. Hence we propose an objective function that represents the quality of the estimated surface and that includes the additional constraints by incorporation of a penalty function. Maximizing the smoothness of the estimated surface and its fitness to the additional constraints then allows the coefficients of the multiquadric function to be obtained by iterative methods. This method was implemented and demonstrated using data collected from the 81'st coal mining area of the Huaibei Coal Group.

Investigation of Combination Characteristic of Damage Location and Intensity in Arch Using Wavelet Coefficient

Arch is a typical complex structure comparing with beam and plate in bridge system. This paper investigates the damage characteristic combining the crack location with the crack intensity in arch. Initially, the first four displacement modes of intact and different damaged arch are simulated and the displacement mode changes are obtained. Next, the wavelet transformation is applied to the displacement mode changes in arch and wavelet coefficients at damage loci are picked. Finally, the damage index including damage location and damage intensity in arch is provided and plotted. The results show that wavelet coefficient module maximum of mode changes can be the damage indicator and is influenced by damage location and damage intensity. The damage indicator is proportional to the damage intensity and present monotonic trend according to damage location which depend on the mode order. At the same time, the large modulus maximum corresponds to small damage combination of location and intensity in the first four modes.

Minimizing Tardy Jobs in a Single Machine Scheduling Problem with Fuzzy Processing Times and Due Dates

The optimality of a fuzzy logic alternative to the usual treatment of uncertainties in a scheduling system using fuzzy numbers is examined formally. Processing times and due dates are fuzzified and presented by fuzzy numbers. With introducing the necessity measure, we compare fuzzy completion times of jobs with fuzzy due dates to decide whether jobs are tardy. The object is to minimize the numbers of tardy jobs. The efficient solution method for this problem is proposed. And deterministic counterpart of this single machine scheduling problem is a special case of fuzzy version.

Female Executives＇ Experiences of Contrapower Sexual Harassment From Male Subordinates in the Workplace

This paper examines female executives＇ experiences of contra-power sexual harassment （CPSH）. One hundred and fifteen respondents, consisting of 67 female executives and 48 male subordinates, were purposively selected. Both quantitative and qualitative data were utilized. Female executives perceived and experienced three out of the 11 acts-male subordinates grabbing their groins before female executives, male subordinates bragging about their sexual organs as hefty before female executives, and male subordinates bragging about their prowess in bed before female executives-as most sexually harassing And 35~6 of the male respondents reported that they grabbed their groins before female executives, 60.4% bragged of the size of their sexual organs, and 52.1% bragged of their prowess in bed. The focused group discussions （FGDs） revealed that CPSH may induce low job satisfaction, job commitment and reduced productivity, increase feelings of loss of control over the body, destroy gender identity, and increase the tendency to quit the job. Female executives ignored the acts and maintained strict formal relationships with their male subordinates as ways of coping with the acts. Conclusively, as powerful as female executives are in position of authority, they are still powerless as regards CPHS.

A NEW NON-INVASIVE METHOD FOR VALVE STICTION DECTION USING WAVELET TECHNOLOGY

In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavelet transform is used to decompose the data at different resolution scales. Based on the Lipschitz regularity theory, wavelet coefficients analysis across scales is performed to detect the jumps in the controlled variables. Adaptive wavelet de-noising is then applied to the data. Features of the valve stiction patterns are extracted from the de-noised data and the valve stiction probability is calculated.

Orthogonal Multiple Vector-Valued Wavelet Packets

The multiple vector-valued wavelet packets are defined and investigated. A procedure for constructing the multiple vector-valued wavelet packets is presented. The properties of multiple vector-valued wavelet packets are discussed by using integral transformation and operator theory. Finally, new orthogonal bases of L^2（R, C^s×s） is constructed from the orthogonal multiple vector-valued wavelet packets.

On Completeness and Minimality of Random Exponential System in a Weighted Banach Space of Functions Continuous on the Real Line

In this paper, the completeness and minimality properties of some random exponential system in a weighted Banach space of complex functions continuous on the real line for convex nonnegative weight are studied. The results may be viewed as a probabilistic version of Malliavin＇s classical results.