Self-tuning weighted measurement fusion Kalman filter and its convergence

For multisensor systems,when the model parameters and the noise variances are unknown,the consistent fused estimators of the model parameters and noise variances are obtained,based on the system identification algorithm,correlation method and least squares fusion criterion.Substituting these consistent estimators into the optimal weighted measurement fusion Kalman filter,a self-tuning weighted measurement fusion Kalman filter is presented.Using the dynamic error system analysis （DESA） method,the convergence of the self-tuning weighted measurement fusion Kalman filter is proved,i.e.,the self-tuning Kalman filter converges to the corresponding optimal Kalman filter in a realization.Therefore,the self-tuning weighted measurement fusion Kalman filter has asymptotic global optimality.One simulation example for a 4-sensor target tracking system verifies its effectiveness.

WEIGHTED LASSO ESTIMATES FOR SPARSE LOGISTIC REGRESSION:NON-ASYMPTOTIC PROPERTIES WITH MEASUREMENT ERRORS

For high-dimensional models with a focus on classification performance,the?1-penalized logistic regression is becoming important and popular.However,the Lasso estimates could be problematic when penalties of different coefficients are all the same and not related to the data.We propose two types of weighted Lasso estimates,depending upon covariates determined by the Mc Diarmid inequality.Given sample size n and a dimension of covariates p,the finite sample behavior of our proposed method with a diverging number of predictors is illustrated by non-asymptotic oracle inequalities such as the?1-estimation error and the squared prediction error of the unknown parameters.We compare the performance of our method with that of former weighted estimates on simulated data,then apply it to do real data analysis.

Improved calibration method for displacement transformation coefficient in optical and visual measurements

Optical and visual measurement technology is used widely in fields that involve geometric measurements,and among such technology are laser and vision-based displacement measuring modules(LVDMMs).The displacement transformation coefficient(DTC)of an LVDMM changes with the coordinates in the camera image coordinate system during the displacement measuring process,and these changes affect the displacement measurement accuracy of LVDMMs in the full field of view(FFOV).To give LVDMMs higher accuracy in the FFOV and make them adaptable to widely varying measurement demands,a new calibration method is proposed to improve the displacement measurement accuracy of LVDMMs in the FFOV.First,an image coordinate system,a pixel measurement coordinate system,and a displacement measurement coordinate system are established on the laser receiving screen of the LVDMM.In addition,marker spots in the FFOV are selected,and the DTCs at the marker spots are obtained from calibration experiments.Also,a fitting method based on locally weighted scatterplot smoothing(LOWESS)is selected,and with this fitting method the distribution functions of the DTCs in the FFOV are obtained based on the DTCs at the marker spots.Finally,the calibrated distribution functions of the DTCs are applied to the LVDMM,and experiments conducted to verify the displacement measurement accuracies are reported.The results show that the FFOV measurement accuracies for horizontal and vertical displacements are better than±15μm and±19μm,respectively,and that for oblique displacement is better than±24μm.Compared with the traditional calibration method,the displacement measurement error in the FFOV is now 90%smaller.This research on an improved calibration method has certain significance for improving the measurement accuracy of LVDMMs in the FFOV,and it provides a new method and idea for other vision-based fields in which camera parameters must be calibrated.

MEASUREMENT OF NUMBER AVERAGE MOLECULAR WEIGHT OF STYRENE OLIGOMER BY ^(13)C-NMR METHOD

^(13)C-NMR ~1H-decoupled spectra of styrene polymers were assigned by comparison with modelcompounds, then used in measurements of number average molecular weights. The higher limit of an exactdetermination of the end group signal is less than a molecular weight of 10~4. For polymer samples withM_n<10~3, the results obtained from ^(13)C-NMR spectra of saturated carbon region are in excellent agreementwith the values determined by ~1H-NMR, SEC, and VPO methods, while the results from ^(13)C-NMR spectra ofphenyl C-1 carbon region are somewhat higher than the values determined by other methods.

Anthropometric measurements at birth as predictor of low birth weight

In developing countries, low birth weight (BW < 2500 grams) accounts for 60% - 80% of neonatal deaths. Early identification and referral of LBW babies for extra essential newborn care is vital in preventing neonatal deaths. Studies carried out in different populations have suggested that the use of newborn anthropometric surrogates of birth weight may be a simple and reliable method to identify LBW babies. previous studies reported correlation between birth weight to several anthropometric measurements and their predictive value. We aimed to evaluate the correlation between birth length, head, chest, and mid arm circumferences to birth weight. Methods: A cross sectional study has been conducted in SHARIATI Hospital in Tehran, from September 2008 to February 2009. All Consecutive full-term. Single ton, live born babies were included and anthropometric measurements carried out within 48 hours after birth by authors. Birth weight was measured by digital scale within the first 24 hours after delivery. Birth length by somatometer and head, chest, mid arm circumferences were measured 2 times by using plastic measuring tape. Result: Out of 500 newborn studied. 52.2% were male and 47.8% were female. The mean birth weight was 3195.4 ± 399.9 gram and 3.8% of newborns were low birth weight. It was evident a positive correlation of birth weight to all such anthropometric measurements with the highest correlation coefficient for chest circumference (r: 0.74). By ROC- AUC analyses, chest circumference (AUC = 0.91, 95% CI 0.84 to 0.97) and arm circumference (AUC = 0.87, 95% CI 0.79 to 0.95) were identified as the optimal surrogate indicators of LBW babies. The optimal cut-points for chest circumference and arm circumference to identify LBW newborns were ≥31.2 cm and ≥10.2 cm respectively. Conclusions: Chest and mid arm circumferences were the best anthropometric surrogates of LBW among studied Iranian population. Further studies are needed in the field to cross-validate our results. anthropometric values are simple, practicable, quick and reliable indicator for predicting LBW newborns in the community and can be easily measured by paramedical workers in developing nation.

Estimating the Parameters Geographically Weighted Regression (GWR) with Measurement Error

Geographically weighted regression models with the measurement error are a modeling method that combines the global regression models with the measurement error and the weighted regression model. The assumptions used in this model are a normally distributed error with that the expectation value is zero and the variance is constant. The purpose of this study is to estimate the parameters of the model and find the properties of these estimators. Estimation is done by using the Weighted Least Squares (WLS) which gives different weighting to each location. The variance of the measurement error is known. Estimators obtained are . The properties of the estimator are unbiased and have a minimum variance.

WEIGHTED ESTIMATES FOR COMMUTATORS OF MULTILINEAR CALDERóN-ZYGMUND OPERATORS WITH NON-DOUBLING MEASURES

Let μ be a nonnegative Radon measure on Rd, which only satisfies the polynomial growth condition. Under this assumption, the authors obtain some weighted weaktype estimates for the commutators generated by the multilinear CalderSn-Zygmund op- erators and RBMO（μ） functions.

Spatial Downscaling of the Tropical Rainfall Measuring Mission Precipitation Using Geographically Weighted Regression Kriging over the Lancang River Basin, China

Satellite-based precipitation products have been widely used to estimate precipitation, especially over regions with sparse rain gauge networks. However, the low spatial resolution of these products has limited their application in localized regions and watersheds.This study investigated a spatial downscaling approach, Geographically Weighted Regression Kriging(GWRK), to downscale the Tropical Rainfall Measuring Mission(TRMM) 3 B43 Version 7 over the Lancang River Basin(LRB) for 2001–2015. Downscaling was performed based on the relationships between the TRMM precipitation and the Normalized Difference Vegetation Index(NDVI), the Land Surface Temperature(LST), and the Digital Elevation Model(DEM). Geographical ratio analysis(GRA) was used to calibrate the annual downscaled precipitation data, and the monthly fractions derived from the original TRMM data were used to disaggregate annual downscaled and calibrated precipitation to monthly precipitation at 1 km resolution. The final downscaled precipitation datasets were validated against station-based observed precipitation in 2001–2015. Results showed that: 1) The TRMM 3 B43 precipitation was highly accurate with slight overestimation at the basin scale(i.e., CC(correlation coefficient) = 0.91, Bias = 13.3%). Spatially, the accuracies of the upstream and downstream regions were higher than that of the midstream region. 2) The annual downscaled TRMM precipitation data at 1 km spatial resolution obtained by GWRK effectively captured the high spatial variability of precipitation over the LRB. 3) The annual downscaled TRMM precipitation with GRA calibration gave better accuracy compared with the original TRMM dataset. 4) The final downscaled and calibrated precipitation had significantly improved spatial resolution, and agreed well with data from the validated rain gauge stations, i.e., CC = 0.75, RMSE(root mean square error) = 182 mm, MAE(mean absolute error) = 142 mm, and Bias = 0.78%for annual precipitation and CC = 0.95, RMSE = 25 mm, MAE = 16 mm, and Bias = 0.67% for monthly precipitation.

Fuzzy-Weighted Similarity Measures for Memory-Based Collaborative Recommender Systems

Memory-based collaborative recommender system (CRS) computes the similarity between users based on their declared ratings. However, not all ratings are of the same importance to the user. The set of ratings each user weights highly differs from user to user according to his mood and taste. This is usually reflected in the user’s rating scale. Accordingly, many efforts have been done to introduce weights to the similarity measures of CRSs. This paper proposes fuzzy weightings for the most common similarity measures for memory-based CRSs. Fuzzy weighting can be considered as a learning mechanism for capturing the preferences of users for ratings. Comparing with genetic algorithm learning, fuzzy weighting is fast, effective and does not require any more space. Moreover, fuzzy weightings based on the rating deviations from the user’s mean of ratings take into account the different rating scales of different users. The experimental results show that fuzzy weightings obviously improve the CRSs performance to a good extent.

Optimization Study of Outburst Prevention Measures for Tuzhu Coal Mine Based on Fixed Weight Clustering Analysis

Affected by many involved factors, different dimensions, data with large difference, incomplete information and so on, the most optimal selection of regional outburst prevention measures for outburst mine has become a complicated system project. The traditional way of outburst prevention measure selection belongs to qualitative method, which may cause high-cost of gas control, huge quantities of drilling work, long construction time and even secondary disaster. To solve the above-mentioned problems, in light of occurrence status of coal seam gas in No. 21 mining area of Jinzhushan Tuzhu Mine, through grey fixed weight clustering theory and a combination method of qualitative and quantitative analysis, the judging model with multi-objective classification for optimization of outburst prevention measures was established. The three weight coefficients of outburst prevention technology scheme are sorted, in order to determine the advantages and disadvantages of each outburst prevention technology scheme under the comprehensive evaluation of multi-target. Finally, the problem of quantitative selection for regional outburst prevention technology scheme is solved under the situation of multi-factor mode and incomplete information, which provides reasonable and effective technical measures for prevention of coal and gas outburst disaster.

ABSOLUTE CONTINUITIES OF EXIT MEASURES AND TOTAL WEIGHTED OCCUPATION TIME MEASURES FOR SUPER-α-STABLE PROCESSES

Suppose X is a super-α-stable process in R^d, （0 〈 α〈 2）, whose branching rate function is dr, and branching mechanism is of the form ψ（z） = z^1＋β （0 〈0 〈β ≤1）. Let Xγ and Yγ denote the exit measure and the total weighted occupation time measure of X in a bounded smooth domain D, respectively. The absolute continuities of Xγ and Yγ are discussed.

Preliminary Measurement of Internal Organs of Congjiang Fragrance Pig and Huanjiang Fragrance Pig

Fragrance pig is a famous miniature local breed in China,which is similar to human on the aspects of physical structure,anatomy,nutrition,metabolism and blood biochemical indicators. The internal organs of Congjiang fragrance pig and Huanjiang fragrance pig with different month ages were weighed. The results showed that the proportion of stomach in body weight in Congjiang fragrance pig was higher than that in Min pig,Harbin white and Landrace,and the proportion of large intestine in body weight in Congjiang fragrance pig was also higher than that in ordinary pigs; the weights of heart,liver and kidney in 8- 10 months old Congjiang fragrance pig were similar to that in Chinese adults. This provided reference data for future in-depth development and utilization of fragrance pig.

Measuring Musical Rhythm Similarity: Further Experiments with the Many-to-Many Minimum-Weight Matching Distance

Musical rhythms are represented as sequences of symbols. The sequences may be composed of binary symbols denoting either silent or monophonic sounded pulses, or ternary symbols denoting silent pulses and two types of sounded pulses made up of low-pitched (dum) and high-pitched (tak) sounds. Experiments are described that compare the effectiveness of the many-to-many minimum-weight matching between two sequences to serve as a measure of similarity that correlates well with human judgements of rhythm similarity. This measure is also compared to the often used edit distance and to the one-to-one minimum-weight matching. New results are reported from experiments performed with three widely different datasets of real- world and artificially generated musical rhythms (including Afro-Cuban rhythms), and compared with results previously reported with a dataset of Middle Eastern dum-tak rhythms.

基于熵权法的我国区域性金融风险测度与评价

坚决守住不发生系统性金融风险的底线是当前我国经济工作的重要任务,因此科学、准确地测度区域性金融风险显得尤为重要。针对目前区域性金融风险测度所存在的环境适应性低、指标构建随意和合成处理欠科学等问题,构建基于熵权法的区域性金融风险测度模型,实证测度2012—2020年我国31个省份的区域性金融风险,以此为依据,对我国区域性金融风险进行分析和评价,研究表明,基于熵权法测度区域性金融风险具有可行性和科学性,测度结果具有客观性和准确性;我国区域性金融风险整体呈上升趋势,其中,东、中、西、东北地区区域性金融风险呈逐次递减态势,且西部和东北部地区区域性金融风险的省际差异较大。对此文章提出防控区域性金融风险的主要策略:一是将东、中部地区作为我国区域性金融风险防控的重点区域;二是对于西部和东北地区,应重点关注陕西、吉林等区域性金融风险较高的省份。

未确知测度理论在盾构下穿既有隧道安全风险评价中的应用

盾构下穿既有隧道工程施工通常存在较大风险,为了对风险等级做出准确有效的评价,提出了基于未确知测度理论的盾构下穿既有隧道安全风险评价模型。首先,通过对相关规范和现有文献的研究,并结合盾构下穿隧道施工的特点,构建了盾构下穿既有隧道安全风险评价指标体系,包括盾构掘进参数、新建隧道条件、既有隧道条件、地质条件和施工管理条件5个一级指标,以及掘进速度、掘进推力、注浆压力等19个二级指标;其次,将综合安全风险划分为5个等级,并明确了各指标的等级划分标准;然后基于熵权-未确知测度理论构建盾构下穿既有隧道安全风险评价模型,采用熵权法确定指标权重,根据未确知测度理论构建各指标的单指标未确知测度函数,将各指标数据值代入单指标未确知测度函数中得到单指标测度评价矩阵,结合指标权重和单指标测度评价矩阵计算得到多指标测度评价向量,依照置信度准则确定安全风险等级;最后,将提出的模型应用于实际盾构下穿既有隧道工程中,对其进行安全风险等级评价。结果表明,模型评价结果与实际风险等级一致,并通过与模糊层析分析法对比验证了所提模型应用于工程实践的有效性,研究结果可为实际施工安全管理提供决策支持。

基于未确知测度方法的装配式建筑吊装风险研究

为实现对装配式建筑吊装风险的科学评价,基于AHP-熵组合赋权的未确知测度方法提出装配式建筑吊装风险量化评价方法。首先,遵循“4M1E”原则对风险因素进行梳理,从“人、物、技、环、管”5个方面对装配式建筑吊装风险因素进行识别,建立风险量化评价指标体系;然后,运用AHP计算评价指标主观权重,熵权法计算评价指标客观权重,结合最小熵原理计算组合权重,基于该权重与未确知测度方法提出装配式建筑吊装风险量化评价方法;最后,对湖南地区某装配式住宅项目进行实例研究。研究表明:该项目吊装总体风险判定为c4级(风险较小)。AHP-熵组合赋权未确知测度方法的可操作性较强,可用于装配式建筑吊装风险的量化评价。

数字普惠金融对乡村振兴的影响效应与机制分析

金融助农是破解我国“三农”问题的“金钥匙”。文章选取2012—2020年我国30个省的面板数据,从产业兴旺、生态宜居、生活富裕、乡风文明、治理有效五个方面构建乡村振兴评价指标体系,对数字普惠金融助推乡村振兴的可能路径进行了理论分析和实证检验。结果显示:(1)数字普惠金融的发展能显著提升乡村振兴水平,且这种提升作用在我国中西部乡村更为明显,拆分数字普惠金融指数进行分项回归发现,数字化程度对中西部乡村的促进作用更为显著、使用深度次之;(2)数字普惠金融能通过“推动产业融合、促进科技创新”途径来提升乡村振兴水平;(3)农村互联网普及程度的提升能显著强化数字普惠金融对乡村振兴的促进作用。鉴于此,本文提出应加快数字普惠金融发展进程以下沉惠农性质金融服务,营造良好的产业融合和科技创新环境以激发乡村发展的内生动力,完善数字普惠金融的基础设施建设、加速推进“宽带中国”和“互联网+”战略为乡村振兴增势赋能。

2001–2020年中国广西及东盟区域1 km分辨率降尺度月度降水数据集

中国广西及东盟区域位于亚洲东南部,同属亚热带季风气候,降水充沛,洪涝灾害频发,直接影响社会经济活动,高分辨率、高精度降水资料可有效支撑区域水资源、农业、灾害及生态等管理和研究。本研究以2001–2020年全球降水观测计划降水数据(GPM IMERG)为因变量,结合中分辨率成像光谱仪(MODIS)增强植被指数(EVI)、地表蒸散发(ET)、地表温度(LST)、先进星载热发射和反射辐射仪(ASTER)海拔(ELV)等解释变量,引入考虑变量随地理环境影响变化的地理加权回归(GWR)模型,构建空间分辨率为10 km的年尺度模型,经过测试选取验证精度良好的指数核函数。通过回代,基于空间分辨率为1 km的解释变量,构建了2001–2020年中国广西及东盟区域1 km年度降水数据集,并进一步采用比例指数法获得研究区2001–2020年1 km月度降水数据集。采用2001–2020年2679个地面观测站点数据对降尺度数据集进行验证,相关系数、均方根误差和偏差分别为0.792、74.610mm、-0.122%。本数据集能够有效反映1 km分辨率下的降水时空分布及其差异性,可广泛应用于水资源、农业、生态环境、灾害模拟等研究领域。