Comparison of wind data from ERA-Interim and buoys in the Yellow and East China Seas

We compared data of sea surface wind from the European Centre for Medium-Range Weather Forecasts Interim Reanalysis(ERA-Interim) with that collected from eight buoys deployed in the Yellow and East China seas.The buoy data covered a period from 2010 to 2011,during which the longest time series without missing data extended for 329 days.Results show that the ERA-Interim wind data agree well with the buoy data.The regression coefficients between the ERA-Interim and observed wind speed and direction are greater than 0.7 and 0.79,respectively.However,the ERA-Interim wind data overestimate wind speed at most of the buoy stations,for which the largest bias is 1.8 m/s.Moreover,it is found from scatter plots of wind direction that about 13%of the ERA-Interim wind data can be classified as bad for wind speeds below6 m/s.Overall,the ERA-Interim data forecast both the wind speed and direction well,although they are not very representative of our observations,especially those where the wind speed is below 6 m/s.

Comparisons of OCO-2 satellite derived XCO_(2)with in situ and modeled data over global ocean

Atmospheric CO_(2)is one of key parameters to estimate air-sea CO_(2)flux.The Orbiting Carbon Observatory-2(OCO-2)satellite has observed the column-averaged dry-air mole fractions of global atmospheric carbon dioxide(XCO_(2))since 2014.In this study,the OCO-2 XCO_(2)products were compared between in-situ data from the Total Carbon Column Network(TCCON)and Global Monitoring Division(GMD),and modeling data from CarbonTracker2019 over global ocean and land.Results showed that the OCO-2 XCO_(2)data are consistent with the TCCON and GMD in situ XCO_(2)data,with mean absolute biases of 0.25×10^(-6)and 0.67×10^(-6),respectively.Moreover,the OCO-2 XCO_(2)data are also consistent with the CarbonTracker2019 modeling XCO_(2)data,with mean absolute biases of 0.78×10^(-6)over ocean and 1.02×10^(-6)over land.The results indicated the high accuracy of the OCO-2 XCO_(2)product over global ocean which could be applied to estimate the air-sea CO_(2)flux.

Evaluation of mouse bioassay results in an inter-laboratory comparison for paralytic shellfish poisoning toxins

An inter-laboratory comparison of the AOAC mouse bioassay for paralytic shellfish poisoning (PSP) toxicity in shellfish was carried out among 25 Chinese laboratories to examine the overall performance for PSP testing in China, and to analyze the main factors affecting the performance of this method. The toxic scallop Patinopecten yessoensis collected from coast of Bohai Sea, China, was used as a test sample in the comparison study. The results were reported and evaluated using robust statistical methods. The z scores showed that 80%, 8%, and 12% of laboratories reported satisfactory results, unsatisfactory results, and questionable results, respectively. This evaluation demonstrates that the PSP mouse bioassay is an appropriate method for screening and testing PSP toxicity in shellfish. However, it was found that the experience and skill of technicians, as well as the body weight and health status of mice being used significantly affected the accuracy of the method.

Use of REGWQ Multiple Comparisons of Qualitative Data

The REGWQ （Ryan-Einot-Gabriel-Welsch and Quiot） test produces allow us to compare a large numbers of data while controlling the probability of making at least one Type I error or Family wise error. The purpose of this study was to use the REGWQ multiple comparisons test of qualitative data. Okra characterization data was applied and submitted to ANOVA （P_0.05） with REGWQ for multiple comparisons of the means. The results of this study establish a summary strategy of following a significant ANOVA F with REGWQ test on multiple comparisons of means in summation a large entries/treatments to the small groups when variances are heterogeneous. Cluster analysis should be especially useful for grouping qualitative treatment and could also be used in conjunction of with REFWQ multiple produces. The development of study will be in REGWQ multiple producers in SAS option for distributed the large number of treatment to small group with summering the best choice of treatments.

Direct Pointwise Comparison of FE Predictions to StereoDIC Measurements:Developments and Validation Using Double Edge-Notched Tensile Specimen

To compare finite element analysis(FEA)predictions and stereovision digital image correlation(StereoDIC)strain measurements at the same spatial positions throughout a region of interest,a field comparison procedure is developed.The procedure includes(a)conversion of the finite element data into a triangular mesh,(b)selection of a common coordinate system,(c)determination of the rigid body transformation to place both measurements and FEA data in the same system and(d)interpolation of the FEA nodal information to the same spatial locations as the StereoDIC measurements using barycentric coordinates.For an aluminum Al-6061 double edge notched tensile specimen,FEA results are obtained using both the von Mises isotropic yield criterion and Hill’s quadratic anisotropic yield criterion,with the unknown Hill model parameters determined using full-field specimen strain measurements for the nominally plane stress specimen.Using Hill’s quadratic anisotropic yield criterion,the point-by-point comparison of experimentally based full-field strains and stresses to finite element predictions are shown to be in excellent agreement,confirming the effectiveness of the field comparison process.

A Comparison Study of Tropical Pacific Ocean State Estimation:Low-Resolution Assimilation vs.High-Resolution Simulation

A comparison study is performed to contrast the improvements in the tropical Pacific oceanic state of a low-resolution model respectively via data assimilation and by an increase in horizontal resolution. A low resolution model (LR) (1°lat by 2°lon) and a high-resolution model (HR) (0.5°lat by 0.5°lon) are employed for the comparison. The authors perform 20-yr numerical experiments and analyze the annual mean fields of temperature and salinity. The results indicate that the low-resolution model with data assimilation behaves better than the high-resolution model in the estimation of ocean large-scale features. From 1990 to 2000, the average of HR's RMSE (root-mean-square error) relative to independent Tropical Atmosphere Ocean project (TAO) mooring data at randomly selected points is 0.97℃ compared to a RMSE of 0.56℃ for LR with temperature assimilation. Moreover, the LR with data assimilation is more frugal in computation. Although there is room to improve the high-resolution model, the low-resolution model with data assimilation may be an advisable choice in achieving a more realistic large-scale state of the ocean at the limited level of information provided by the current observational system.

Monitoring Land-Use Change in Nakuru (Kenya) Using Multi-Sensor Satellite Data

Recently land-use change has been the main concern for worldwide environment change and is being used by city and regional planners to design sustainable cities. Nakuru in the central Rift Valley of Kenya has undergone rapid urban growth in last decade. This paper focused on urban growth using multi-sensor satellite imageries and explored the potential benefits of combining data from optical sensors (Landsat, Worldview-2) with Radar sensor data from Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data for urban land-use mapping. Landsat has sufficient spectral bands allowing for better delineation of urban green and impervious surface, Worldview-2 has a higher spatial resolution and facilitates urban growth mapping while PALSAR has higher temporal resolution compared to other operational sensors and has the capability of penetrating clouds irrespective of weather conditions and time of day, a condition prevalent in Nakuru, because it lies in a tropical area. Several classical and modern classifiers namely maximum likelihood (ML) and support vector machine (SVM) were applied for image classification and their performance assessed. The land-use data of the years 1986, 2000 and 2010 were compiled and analyzed using post classification comparison (PCC). The value of combining multi-temporal Landsat imagery and PALSAR was explored and achieved in this research. Our research illustrated that SVM algorithm yielded better results compared to ML. The integration of Landsat and ALOS PALSAR gave good results compared to when ALOS PAL- SAR was classified alone. 19.70 km2 of land changed to urban land-use from non-urban land-use between the years 2000 to 2010 indicating rapid urban growth has taken place. Land-use information is useful for the comprehensive land-use planning and an integrated management of resources to ensure sustainability of land and to achieve social Eq- uity, economic efficiency and environmental sustainability.

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR-SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.

Comparing Data Mining Techniques in HIV Testing Prediction

Introduction: The present work compared the prediction power of the different data mining techniques used to develop the HIV testing prediction model. Four popular data mining algorithms (Decision tree, Naive Bayes, Neural network, logistic regression) were used to build the model that predicts whether an individual was being tested for HIV among adults in Ethiopia using EDHS 2011. The final experimentation results indicated that the decision tree (random tree algorithm) performed the best with accuracy of 96%, the decision tree induction method (J48) came out to be the second best with a classification accuracy of 79%, followed by neural network (78%). Logistic regression has also achieved the least classification accuracy of 74%. Objectives: The objective of this study is to compare the prediction power of the different data mining techniques used to develop the HIV testing prediction model. Methods: Cross-Industry Standard Process for Data Mining (CRISP-DM) was used to predict the model for HIV testing and explore association rules between HIV testing and the selected attributes. Data preprocessing was performed and missing values for the categorical variable were replaced by the modal value of the variable. Different data mining techniques were used to build the predictive model. Results: The target dataset contained 30,625 study participants. Out of which 16,515 (54%) participants were women while the rest 14,110 (46%) were men. The age of the participants in the dataset ranged from 15 to 59 years old with modal age of 15 - 19 years old. Among the study participants, 17,719 (58%) have never been tested for HIV while the rest 12,906 (42%) had been tested. Residence, educational level, wealth index, HIV related stigma, knowledge related to HIV, region, age group, risky sexual behaviour attributes, knowledge about where to test for HIV and knowledge on family planning through mass media were found to be predictors for HIV testing. Conclusion and Recommendation: The results obtained from this research reveal that data mining is crucial in extracting relevant information for the effective utilization of HIV testing services which has clinical, community and public health importance at all levels. It is vital to apply different data mining techniques for the same settings and compare the model performances (based on accuracy, sensitivity, and specificity) with each other. Furthermore, this study would also invite interested researchers to explore more on the application of data mining techniques in healthcare industry or else in related and similar settings for the future.

Research on Comparison and Evaluation Studies of Several Smoothing Denoising Method Based on γ-ray Spectrum Detector

The extraction of spectral parameters is very difficult because of the limited energy resolution for NaI （TI） gamma-ray detectors. For statistical fluctuation of radioactivity under complex environment, some smoothing filtering methods are proposed to solve the problem. These methods include adopting method of arithmetic moving average, center of gravity, least squares of polynomial, slide converter of discrete funcion convolution etc. The process of spectrum data is realized, and the results are assessed in H/FWHM（ Peak High/Full Width at Half Maximum） and peak area based on the Matlab programming. The results indicate that different methods smoothed spectrum have respective superiority in different ergoregion, but the Gaussian function theory in discrete function convolution slide method is used to filter the complex y-spectrum on Embedded system nlatform, and the statistical fluctuation of y-snectrum filtered wall.

Study on the Applicability of ERA5 Reanalysis Data at Lake Taihu

Lakes are an important component of the earth climate system. They play an important role in the study of basin weather forecasting, air quality forecasting, and regional climate research. The accuracy of driving variables is the basic premise to ensure the rationality of lake mode simulation. Based on the in-situ observations at Bifenggang site of the Lake Taihu Eddy flux Network from 2012 to 2017, this paper investigated temporal variations in temperature, relative humidity, wind speed, radiation components at different time scales (hourly, seasonal and interannual). ERA5 reanalysis data were compared with in-situ observation to quantify the error and evaluate the performance of reanalysis data. The results show that: 1) On the hourly scale, the ERA5 reanalysis data described air temperature, and downward long-wave radiation more accurately. 2) On the seasonal variation scale, the ERA5 reanalysis data described air temperature, and downward long-wave radiation more accurately. However, the descriptions of wind speed, relative humidity and downward short-wave have large deviations. 3) On the interannual scale, the ERA5 reanalysis data show a good performance for temperature, followed by downward longwave radiation, downward shortwave radiation and relative humidity.

基于优化算法竞赛场景的改进data profile技术

数值比较是评估最优化算法特别是全局优化算法必不可少的手段,通常利用已知全局最优值的测试函数集来对优化算法进行性能评估。Data profile技术是用于比较确定性最优化算法的一种数据分析技术,最近被推广到随机优化算法的数值比较中。但data profile技术存在一个不良性质,得到的profile曲线会随着参与比较的优化算法的不同而改变。这一“传递无效性”缺陷不利于普通用户对该技术的认识和使用。分析表明,导致“传递无效性”的根源在于data profile的“收敛条件”定义,笔者提出的新“收敛条件”可以消除该缺陷,条件是需要用到目标函数的全局最优值,因而适用于最优值已知的众多优化算法竞赛场景。大量数值实验表明,改进的data profile技术消除了“传递无效性”缺陷,有利于不同算法竞赛之间结果的相互验证和推广使用。

薄膜电容器数据挖掘与分析

作为电力系统的重要元件之一,薄膜电容器因长使用寿命、高可靠性等优点而受到广泛应用,然而却极少有研究从数据角度挖掘电容器的自身属性。为了填补这一空白,本文选取收集自网络的40793条薄膜电容器数据作为分析基础,首先利用散点图和箱线图从横向角度分析了不同材料制备而成的电容器的容值、最高最低温度、交直流运行电压等差异,然后利用饼图从纵向角度对比了电容器的运行温度和应用场合,最后计算出这些性能指标的皮尔逊系数并进行了相关性分析。结果表明金属化聚丙烯材料作为目前的主流材料在容值和交直流运行电压方面比其他材料均具有显著的优势,而金属化聚苯硫醚在运行温度上占优,电容器除温度和运行电压外的各项参数之间的相关性并不显著。未来可以进一步对数据进行处理和学习,达到性能预测的效果。

基于高分子电容式湿敏元件传感技术的传感器特性分析比较

为了研究目前气象行业使用的高分子电容式湿敏元件传感器的测量精确度,文章选择了三种不同型号基于高分子电容式湿敏元件传感技术的湿度传感器作为实验对象进行测试。按照自动气象站湿度传感器检定规程,对不同温度下传感器的湿度示值误差进行了分析和比较。实验结果表明,基于高分子电容式湿敏元件传感器的湿度特性存在一定差异。比较湿度传感器的结果对湿度传感器的选择和使用有参考价值。

数据驱动模式下基于非平行超平面SVM算法的贸易经济预测

数据驱动的多元化发展导致数据异构性增强、维度提升和特征量规模扩大,给贸易经济分析带来更大挑战。为了提高贸易经济分析的科学性,采用非平行超平面支持向量机算法(support vector machine,SVM)对贸易经济进行预测分析。首先,根据贸易经济影响因素进行主成分分析,获取影响贸易经济的关键特征,并对特征进行量化和去噪处理。然后,采用广义特征值最接近支持向量机(proximal support vector machine via generalized eigenvalues,GEPSVM)进行贸易经济预测分类。根据预测指标要求,选择核函数GEPSVM算法(KGEPSVM算法)对分类的非平行超平面求解,通过类别划分函数获得经济预测结果。实证分析表明,对比常用的非平行超平面支持向量机算法,所提算法的贸易经济预测性能更优,而且在常用贸易经济指标的预测中,表现出较高预测精度和稳定性。

研究生教育对区域经济发展的影响研究

以省际面板数据为样本,以第三产业经济和人均GDP为经济度量指标,以研究生教育和科技创新等为解释变量,构建了31个省以及东中西部三大区域的各类回归模型。实证分析表明:我国的研究生教育可直接促进区域经济增长(硕士的影响效应高于博士),并通过科技创新变量间接推进经济发展。对三大区域进行纵横比较发现,东部整体态势较好,显著优于中部和西部;中西部地区硕士对经济的影响力显著高于博士,西部研究生教育和产业结构明显不匹配。

ICON/MIGHTI与TIMED/SABER探测温度数据的对比

ICON卫星为临近空间环境特性研究、建模和预报提供了新数据.通过对ICON/MIGHTI与TIMED/SABER在90~105 km高度探测温度数据的比较,计算两者的年平均温度偏差和均方根误差,同时分析月平均温度偏差在不同月份中随高度和纬度的分布情况,为MIGHTI和SABER温度探测数据在临近空间大气建模和预报应用提供参考依据.结果表明,MIGHTI和SABER的温度垂直廓线变化趋势基本吻合,数值上有所差异.在12°S-42°N范围内,MIGHTI探测温度与SABER相比,在90~93 km时偏低,偏差最大值约2.5 K,在93~105 km偏高,偏差的绝对值最大约10 K.在不同季节,白天的温度偏差通常高于夜晚.SABER和MIGHTI的月平均温度偏差随季节和纬度的变化显著,夏季时的月平均温度偏差最大,且温度的均方根误差最大.

中法海洋卫星与ERA5数据在中国邻近海域的波高对比分析

中法海洋卫星CFOSAT搭载的高性能海浪谱仪SWIM获得了连续、大范围的海浪数据。CFOSAT海浪波高数据在全球范围已开展了许多验证与校准工作,但大多是与站点数据的比对,将卫星数据应用于面域波浪场特性研究时缺乏与已有成熟数据集的对比。通过将中国邻近海域作为研究区域,对CFOSAT与ERA5数据的有效波高进行对比,分析了二者间的差异。结果表明,CFOSAT数据与ERA5数据在波浪的面域观测上表现相似,相关性较高;二者有效波高的差值呈现季节变化特征,秋冬季节的数据离散程度较大,春夏季节较稳定;随海浪高度的增加,CFOSAT与ERA5数据的差异明显增加。