Simulation of γ spectrum-shifting based on the parameter adjustment of Gaussian function space

Based on the statistical characteristics of energy spectrum and the features of spectrum-shifting in spectrometry,the parameter adjustment method of Gaussian function space was applied in the simulation of spectrum-shifting.The transient characteristics of energy spectrum were described by the Gaussian function space,and then the Gaussian function space was transferred by parameter adjustment method.Furthermore,the spectrum-shifting in measurement of energy spectrum was simulated.The applied example shows that the parameters can be adjusted flexibly by this method to meet the various requirements in simulation of energy spectrum-shifting.This method was one parameterized simulation method with good performance for the practical application.

Algorithm of neural-network about solving nonlinear least squares adjustment by parameters

Study on solving nonlinear least squares adjustment by parameters is one of the most important and new subjects in modern surveying and mapping field . Many researchers have done a lot of work and gained some solving methods. These methods mainly include iterative algorithms and direct algorithms mainly. The former searches some methods of rapid convergence based on which surveying adjustment is a kind of problem of nonlinear programming. Among them the iterative algorithms of the most in common use are the Gauss-Newton method, damped least quares, quasi-Newton method and some mutations etc. Although these methods improved the quantity of the observation results to a certain degree, and increased the accuracy of the adjustment results, what we want is whether the initial values of unknown parameters are close to their real values. Of course, the model of the latter has better degree in linearity, that is to say, they nearly have the meaning of deeper theories researches. This paper puts forward a kind of method of solving the problems of nonlinear least squares adjustment by parameters based on neural network theory, and studies its stability and convergency. The results of calculating of living example indicate the method acts well for solving parameters problems by nonlinear least squares adjustment without giving exact approximation of parameters.

Need for multiple biomarkers to adjust parameters of closed-loop deep brain stimulation for Parkinson's disease

Closed-loop deep brain stimulation（DBS）：DBS has been established as a surgical therapy for movement disorders and select neuropsychiatric disorders.Various efforts to improve the clinical outcomes of the procedure have been previously made.Several factors affect the DBS clinical outcomes such as lead position,programming technique,

PSO算法下GP-周期随机共振的微弱OFDM信号检测

为了解决传统随机共振系统在微弱正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)信号解调应用中存在的人工选择参数困难、解调效果差的问题,提出一种基于粒子群优化(Particle Swarm Optimization,PWO)算法的GP(Gaussian Potential)-周期随机共振系统的微弱OFDM信号检测方法。该方法利用GP-周期随机系统对OFDM信号经正交变换后的两路高频信号分别进行随机共振,同时运用阻尼参数与信号频率之间的关系对两路信号进行降频处理,使得上下两路信号都能够发生随机共振;然后使用PWO算法对随机共振的系统参数进行优化处理,以使得上下两路信号达到最优的共振效果;最后,将上下两路共振之后的信号合成完成OFDM信号解调,得到最终的数字序列。本文探讨了优化前后GP-周期随机共振系统的共振效果,研究了优化前后GP-周期随机共振诱导下的OFDM系统星座图的聚集程度以及误码率情况,对比分析了经典双稳随机共振、经典三稳随机共振和所提模型对OFDM信号检测的影响。仿真结果表明:相比常用的传统随机共振模型,该方法用于OFDM信号检测的星座图中信号点的聚集程度更高,同时OFDM系统误码率在同样的信噪比下降低50%左右。

Dynamics and adaptive control of a dual-arm space robot with closed-loop constraints and uncertain inertial parameters

A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the po- sition and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane＇s equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters be- ing estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov＇s method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach.

Adjustment of Model Parameters to Estimate Distribution Transformers Remaining Lifespan

Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution companies to apply data analysis techniques to manage resources more efficiently at different levels (avoiding damages, better contingency management, maintenance planning, etc.). The Smart Grids in Argentina progresses slowly due to the high costs involved. In this context, the estimation of the lifespan reduction of distribution transformers is a key tool to efficiently manage human and material resources, maximizing the lifetime of this equipment. Despite the current state of the smart grids, the electricity distribution companies can implement it using the available data. Thermal models provide guidelines for lifespan estimation, but the adjustment to particular conditions, brands, or material quality is done by adjusting parameters. In this work we propose a method to adjust the parameters of a thermal model using Genetic Algorithms, comparing the estimation values of top-oil temperature with measurements from 315 kVA distribution transformers, located in the province of Tucumán, Argentina. The results show that, despite limited data availability, the adjusted model is suitable to implement a transformer monitoring system.

Tuning method for governor control parameters of hydropower generator in isolated grid considering primary frequency performance and small-signal stability

This paper presents a method of tuning governor control parameters of an isolated hydropower generator considering the primary frequency performance and small-signal stability. First, generators that can be operated in isolated state are identified. Second, different schemes are proposed for generator mode switching from on-grid to off-grid state through comparison and mechanism analysis. Third, the time domain model and frequency domain model of the isolated generator governor are constructed to respectively estimate the primary frequency performance and small signal stability. Parameter sets that satisfy the primary frequency performance and small signal stability are acquired as optimal values of governor control parameters. Finally, the measurement-based parameters of the governor are identified and validated using simulations to demonstrate the feasibility and effectiveness of the method.

Stellar parameters of main sequence turn-off star candidates observed with LAMOST and Kepler

Main sequence turn-off （MSTO） stars since their ages can be robustly estimated from have advantages as indicators of Galactic evolution atmospheric parameters. Hundreds of thousands of MSTO stars have been selected from the LAMOST Galactic survey to study the evolution of the Galaxy, and it is vital to derive accurate stellar parameters. In this work, we select 150 MSTO star candidates from the MSTO star sample of Xiang that have asteroseismic parameters and determine accurate stellar parameters for these stars by combining asteroseismic parameters deduced from Kepler photometry and atmospheric parameters deduced from LAMOST spectra. With this sample, we examine the age determination as well as the contamination rate of the MSTO star sample. A comparison of age between this work and Xiang shows a mean difference of 0.53 Gyr （7%） and a dispersion of 2.71 Gyr （28%）. The results show that 79 of the candidates are MSTO stars, while the others are contaminations from either main sequence or sub-giant stars. The contamination rate for the oldest stars is much higher than that for younger stars. The main cause for the high contamination rate is found to be the relatively large systematic bias in the LAMOST surface gravity estimates.

Powell dynamic identification of displacement parameters of indeterminate thin-walled curve box based on FCSE theory

The FCSE controlling equation of pinned thinwalled curve box was derived and the indeterminate problem of continuous thin-walled curve box with diaphragm was solved based on flexibility theory. With Bayesian statistical theory,dynamic Bayesian error function of displacement parameters of indeterminate curve box was founded. The corresponding formulas of dynamic Bayesian expectation and variance were deduced. Combined with one-dimensional Fibonacci automatic search scheme of optimal step size,the Powell optimization theory was utilized to research the stochastic identification of displacement parameters of indeterminate thin-walled curve box. Then the identification steps were presented in detail and the corresponding calculation procedure was compiled. Through some classic examples,it is obtained that stochastic performances of systematic parameters and systematic responses are simultaneously deliberated in dynamic Bayesian error function. The one-dimensional optimization problem of the optimal step size is solved by adopting Fibonacci search method. And the Powell identification of displacement parameters of indeterminate thin-walled curve box has satisfied numerical stability and convergence,which demonstrates that the presented method and the compiled procedure are correct and reliable.During parameters鈥？iterative processes,the Powell theory is irrelevant with the calculation of finite curve strip element（FCSE） partial differentiation,which proves high computation effciency of the studied method.

Investigation of structural parameters and self-aggregation of Algerian asphaltenes in organic solvents

Elemental analysis, Fourier transform infrared （FTIR）, 1H-NMR, fluorescence spectroscopy, and surface tension methods have been used to characterize the molecular structure and the aggregation behaviors of two asphaltenic fractions derived, respectively, from an Alge- rian petroleum well and a corresponding storage tank deposit. Elemental analysis, FTIR, ~H-NMR, and fluores- cence spectroscopy were used to investigate the chemical composition and structural parameters of asphaltenes, while the surface tension method was used to measure the critical micelle concentration （CMC） in organic solvents with different solubility parameters and polarities in order to characterize the asphaltenes＇ aggregation behaviors. Results show that the unstable asphaltenes fraction extracted from the storage tank deposit possesses a higher polarity （higher heteroatoms content） and a lower aro- maticity than stable asphaltenes from the petroleum well. The CMC results indicate that asphaltenes with high polarity and low aromaticity have a high solubility in polar solvents such as nitrobenzene, whereas asphaltenes with low polarity and high aromaticity are more soluble in solvents with weak polarity, like toluene. It is concludedthat the difference of structure of asphaltene samples and polarity of solvents can lead to difference of aggregation behaviors.

基于带阈值的BPE-dropout多任务学习的端到端语音识别

针对语音识别任务中出现的未登录词问题,提出一种带阈值的BPE-dropout多任务学习语音识别方法.该方法采用带随机性的字节对编码算法,在形成子词时引入带字数阈值的策略,将子词作为建模单元,编码器部分采用Conformer结构,与链接时序分类和注意力机制相结合.为进一步提升模型性能,引入动态参数对损失函数进行动态调节,并同时进行多任务训练和解码.实验结果表明,该方法采用子词作为建模单元可有效解决未登录词问题,在多任务学习框架下进一步提升了模型的识别性能.在公开数据集THCHS30和ST-CMDS上,该模型实现了超过95%的识别准确率.

Adaptive algorithm for solving different types and different precisions and nonlinear surveying and mapping parameters adjustment

Approximate linear methods and nonlinear methods were adopted usually for solving models of nonlinear surveying and mapping parameters adjustment. But, these iterative algorithms need to compare harsh initial value. A kind of new algorithm-adaptive algorithm based on analyzing the general methods was put forward. The new algorithm has quick rate of convergence and low dependence for initial value, so it can avoid calculating complex second derivative of the target function. The results indicate that its performance is better than those of the others.

Energy Balance-related Behaviors Are Related to Cardiometabolic Parameters and Predict Adiposity in 8-14-year-old Overweight Chinese Children One Year Later

To identify target energy balance-related behaviors（ERBs）,baseline data from 141overweight or obese schoolchildren（aged 8-14years old）was used to predict adiposity[body mass index（BMI）and fat percentage]one year later.The ERBs included a modified Dietary Approach to Stop Hypertension diet score（DASH score）,leisure-time physical activity（PA,days/week）,and leisure screen time（minutes/day）.Several cardiometabolic variables were measured in the fasting state, including systolic blood pressure （SBP）, diastolic blood pressure （DBP）, blood glucose （GLU）, total cholesterol （TC）, triglycerides （TG）, low-density lipoprotein （LDL-C）, and high-density lipoprotein （HDL-C）.

CONTROLLING HYPERCHAOS IN PLANAR SYSTEMS BY ADJUSTING PARAMETERS

For the two_parameter family of planar mapping, a method to stabilize an unstable fixed point without stable manifold embedding in hyperchaos is introduced. It works by adjusting the two parameters in each iteration of the map. The explicit expressions for the parameter adjustments are derived, and strict proof of convergence for method is given.

The W UMa binaries USNO-A2.0 1350-17365531,V471 Cas,V479 Lac and V560 Lac:light curve solutions and global parameters based on Gaia distances

We present photometric observations in Sloan filters g′, i′of the eclipsing W UMa stars USNOA2.0 1350-17365531, V471 Cas, V479 Lac and V560 Lac. The sinusoidal-like O-C diagram of V471 Cas indicates the presence of a third body with mass 0.12 M_⊙(a red dwarf) at distance 897 R_⊙. The O-C diagram of V479 Lac reveals a period decrease of d P/dt =-1.69 × 10-6d yr-1. The results of the light curve solutions are:(i) the targets are overcontact binaries with small fill-out factors;(ii) their components are F–K stars, comparable in size, whose temperature differences are below 80 K;(iii) all targets undergo partial eclipses and to limit the possible mass ratios we carried out two-step q-search analysis. The target global parameters(luminosities, radii, masses) were obtained on the basis of their Gaia distances and the results of our light curve solutions. The obtained total mass of V560 Lac turns out to be smaller than the lower mass limit for presently known W UMa binaries of 1.0-1.2 M_⊙, i.e. this target is a peculiar overcontact system.

Estimating Photometric Redshifts with Artificial Neural Networks and Multi-Parameters

We calculate photometric redshifts from the Sloan Digital Sky Survey Data Release 2 （SDSS DR2） Galaxy Sample using artificial neural networks （ANNs）. Different input sets based on various parameters （e.g. magnitude, color index, flux information） are explored. Mainly, parameters from broadband photometry are utilized and their performances in redshift prediction are compared. While any parameter may be easily incorporated in the input, our results indicate that using the dereddened magnitudes often produces more accurate photometric redshifts than using the Petrosian magnitudes or model magnitudes as input, but the model magnitudes are superior to the Petrosian magnitudes. Also, better performance resuits when more effective parameters are used in the training set. The method is tested on a sample of 79 346 galaxies from the SDSS DR2. When using 19 parameters based on the dereddened magnitudes, the rms error in redshift estimation is σz = 0.020184. The ANN is highly competitive tool compared to the traditional template-fitting methods when a large and representative training set is available.

基于GWO-XGBoost的工业污水水质关键数据预测算法

为解决XGBoost模型参数调整复杂和预测水质数据准确率低的问题,设计了一种基于灰狼算法(GWO)优化XGBoost的预测算法。首先利用灰狼优化算法全局寻参收敛能力强的优点,使用GWO优化XGBoost的超参数(最大生成树数目、学习率以及树的最大深度)进行优化,获取XGBoost的最佳预测表现。其次通过对水质关键数据的预处理提高数据的可靠性,使用多种算法进行对比分析实验。结果表明:与LSTM、未经GWO优化参数的XGBoost相比,采用灰狼算法优化后的XGBoost模型具有较好的非线性预测能力,模型的决定因数R^(2)达到0.85以上。

Cosmological parameters for spatially flat dust filled Universe in Brans-Dicke theory

We have investigated late time acceleration for a spatially fiat dust filled Universe in Brans- Dicke theory in the presence of a positive cosmological constant A. Expressions for Hubble＇s constant, luminosity distance and apparent magnitude have been obtained for our model. The theoretical results are compared with observed values of the latest 287 high redshift （0.3 ≤ z ≤1.4） Type Ia supernova data taken from the Union 2.1 compilation to estimate present values of matter and dark energy parame- ters, （Ωm）0 and （ΩA）0. We have also estimated the present value of Hubble＇s constant H0 in light of an updated sample of Hubble parameter measurements including 19 independent data points. The results are found to be in good agreement with recent astrophysical observations. We also calculated various physical parameters such as matter and dark energy densities, present age of the Universe and decelera- tion parameter. The value for Brans-Dicke-coupling constant ω is set to be 40 000 based on accuracy of solar system tests and recent experimental evidence.

Investigations of the electron paramagnetic resonance parameters and the tetragonal local structure for (VCl_6)^(4-) coordination complex in MCl:V^(2+) (M=Na,K,Rb) systems

By simulating the electron paramagnetic resonance （EPR） and optical spectra on the basis of the 120 × 120 complete energy matrix, this paper determines the local lattice structure parameters R1 and R2 for MCl：V2＋ （M=Na, K, Rb） systems at 77K, 195 K and RT （room temperature 295 K or 302 K）, respectively. The theoretical results indicate that there exists a compressed distortion in MCl：V2＋ systems. Meanwhile, it finds that the structure parameters R1, R2 and ｜△R｜（ = R1 - R2） increase with the rising temperature. Subsequently, from the analysis it concludes that the relation of EPR parameter D vs. △R is approximately linear. Finally, the effects of orbital reduction factor k on the g factors for the three systems have been discussed.