An adaptive over/under data combination method

The traditional ＂dephase and sum＂ algorithms for over/under data combination estimate the ghost operator by assuming a calm sea surface. However, the real sea surface is typically rough, which invalidates the calm sea surface assumption. Hence, the traditional ＂dephase and sum＂ algorithms might produce poor-quality results in rough sea conditions. We propose an adaptive over/under data combination method, which adaptively estimates the amplitude spectrum of the ghost operator from the over/under data, and then over/under data combinations are implemented using the estimated ghost operators. A synthetic single shot gather is used to verify the performance of the proposed method in rough sea surface conditions and a real triple over/under dataset demonstrates the method performance.

Research on Data Combination for Phased-Array Ground Penetrating Radar

To resolve the data combination of Phased-array Ground Penetrating Radar (PAGPR), we first build a model of PAGPR and a layered model, and then a new data combination algorithm is presented based on it. This method calculates time delay of multi-receivers, basing on the signal of the nearest receiver, then shifts other signals and adds them up, and gets one signal at last. It has been proved that this method can restrain noise, multiple waves, clutter waves and improve the precision of time location. In the end, an example is given to prove the method's efficiency.

Determination of Light Rare Earths by a Spectrophoto-metry Based on the Linear Combination of Multiwavelength Data

The present paper proposes a new method of spectrophotometry based on linear combination of multiwavelength data by means of selecting a set of properly weighted coefficients and combination methods. It is clear that the weighted combination absorbance attained is only in direct proportion to the concentration of the analysed component and independent of coexisting interferents.The accuracy of the analytical results is improved greatly for the analysis of light rare earths with the coexistence of heavy rare earths.The analyti- cal error from the reagent blank and co-coloration of light and heavy rare earths have also been overcome. The greatly improved linearity and additivity of absorbance are obtained.

Combination of structure tensor and tilt angle in the edge detection of potential field data

Edge detection is a commonly requested task in the interpretation of potential field data. Different methods have different results for varied depths and shapes of geological bodies. In this paper,we propose using the combination of structure tensor and tilt angle to detect the edges of the sources,which can display the edges of shallow and deep bodies simultaneously. Through tests on synthetic potential field data,it is obvious that the proposed edge detection methods can display the sources edges more clearly and precisely,compared with other commonly used methods. The application on real potential field data shows similar result,obtaining the edges of layers and faults clearly. In addition,another advantage of the new method is its insensitivity to noise.

Target recognition based on modified combination rule

Evidence theory is widely used in the field of target recognition. The invalidation problem of this theory when dealing with highly conflict evidences is a research hotspot. Several alternatives of the combination rule are analyzed and compared. A new combination approach is proposed. Calculate the reliabilities of evidence sources using existing evidences. Construct reliabilities judge matrixes and get the weights of each evidence source. Weight average all inputted evidences. Combine processed evidences with D-S combination rule repeatedly to identify a target. The application in multi-sensor target reeognition as well as the comparison with typical alternatives all validated that this approach can dispose highly conflict evidences efficiently and get reasonable reeognition results rapidly.

Determination of combined effect of ampli- fication and attenuation of soft rock site us- ing digital seismic data

In the paper, for the application of stochastic simulation of ground motion, we put forward a method to determine ″the combined effect of amplification and attenuation″ (combined effect for short) of soft rock site by using digital seismic data of moderate and small earthquakes. Our approach aims at solving the problem of the combined effect of soft rock site, which is difficult to determine in most regions of China because fewer measures were done for S-wave velocity structure. The combined effect of soft rock site can be determined by using the approach recom- mended by us. An example is given to discuss the practical application of the method.

Phylogeny of subclass Scuticociliatia(Protozoa,Ciliophora) using combined data inferred from genetic,morphological,and morphogenetic evidence

Gene sequence-based genealogies of scuticociliates are different from those produced by morphological analyses.For this reason,11 representative scuticociliates and two ambiguously related genera were chosen to test the ability of combined phylogenetic analyses using both gene sequences and morphological/morphogenetic characteristics.Analyses of both the SSrRNA gene sequences and the combined datasets revealed a consistent branching pattern.While the terminal branches and the order level relationships were generally well resolved,the family level relationships remain unresolved.However,two other trees based on ITS1-5.8S-ITS2 region sequences and morphological/morphogenetic characters showed limited information,due to a lack of informative sites in these two datasets.Our data suggest,however,that the combined analysis of morphological/morphogenetic characters and gene sequences did produce some changes to the phylogenetic estimates of this group.

COMBINATION OF ECMWF REANALYZED DAILY RAINFALL AND PENTAD CMAP IN CHINA

In this study, 16 combinations of the ECMWF (European Centre for Medium Range Weather Forecast) reanalyzed daily rainfall and the pentad CMAP in China for the period 1980-1993(1 May-31 Dec.) were calculated. Correlation analysis was used to roughly evaluate daily rainfall for the whole of China and a combination of RPC (rotated principal component) and wavelet analyses was applied to data on observed and combined daily rainfall to obtain a detailed evaluation of the quality of these combined datasets in 6 selected major rainfall regions of eastern China. The results showed that except for intraweekly fluctuation, the best combination was roughly similar to or accorded well with observation in the aspects of space variation patterns and long period rainfall fluctuations related to monsoon onset and serious meteorologic disasters, indicating that this combination yielded better values of long term daily mean and standard deviation through the pentad CMAP (CPC Merged Analysis of Precipitation), and can also represent rainfall fluctuations through the reanalyzed daily rainfall.

Evaluating the Potentials of PLSR and SVR Models for Soil Properties Prediction Using Field Imaging,Laboratory VNIR Spectroscopy and Their Combination

Pedo-spectroscopy has the potential to provide valuable information about soil physical,chemical,and biological properties.Nowadays,wemay predict soil properties usingVNIRfield imaging spectra(IS)such as Prisma satellite data or laboratory spectra(LS).The primary goal of this study is to investigate machine learning models namely Partial Least Squares Regression(PLSR)and Support Vector Regression(SVR)for the prediction of several soil properties,including clay,sand,silt,organic matter,nitrate NO3-,and calcium carbonate CaCO_(3),using five VNIR spectra dataset combinations(%IS,%LS)as follows:C1(0%IS,100%LS),C2(20%IS,80%LS),C3(50%IS,50%LS),C4(80%IS,20%LS)and C5(100%IS,0%LS).Soil samples were collected at bare soils and at the upper(0–30 cm)layer.The data set has been split into a training dataset 80%of the collected data(n=248)and a validation dataset 20%of the collected data(n=61).The proposed PLSR and SVR models were trained then tested for each dataset combination.According to our results,SVR outperforms PLSR for both:C1(0%IS,100%LS)and C5(100%IS,0%LS).For Soil Organic Matter(SOM)prediction,it achieves(R^(2)=0.79%,RMSE=1.42%)and(R^(2)=0.76%,RMSE=1.3%),respectively.The data fusion has improved the soil property prediction.The highest improvement was obtained for the SOM property(R^(2)=0.80%,RMSE=1.39)when using the SVR model and applying the second Combination C2(20% of IS and 80%LS).

基于机械过冷的双温蒸发CO_(2)数据中心冷却供热系统性能

为实现数据中心绿色高效制冷,并提高能源综合利用率,提出了集成机械过冷和双温蒸发技术的CO_(2)数据中心冷却供热系统(DMS-DE)。建立了系统热力学和碳排放特性分析模型,并与基本CO_(2)系统(Base)和单温蒸发机械过冷CO_(2)系统(DMS-SE)进行对比分析。结果表明:DMS-DE存在最大COP(性能系数)、最优过冷度和排气压力。采用机械过冷技术和双温蒸发技术可显著提升系统COP和效率。与Base和DMS-SE相比,COP分别提高14.1%和9.0%,效率分别提高13.24%和4.31%。DMS-DE的生命周期碳排放相对Base和DMS-SE分别降低16.1%和9.3%。

基于数据挖掘分析赵海滨教授治疗心肌梗死合并抑郁组方用药规律

目的基于数据挖掘探讨赵海滨教授治疗心肌梗死合并抑郁的组方用药规律。方法医案资料来源于赵教授2020年1月至2023年12月在北京中医药大学东方医院治疗心肌梗死合并抑郁的患者医案245份。采用中医传承计算平台(V3.5),分析用药频次、性味、归经,采用关联规则和聚类算法分析常用药物组合及潜在新方。结果共纳入处方245首,涉及中药187味,常用中药为茯苓、丹参、柴胡、郁金、黄芩、桂枝、石菖蒲、贯叶金丝桃、首乌藤、桃仁等,以活血化瘀类、清热类、补虚类为主;药性以寒为主,其次为温、平;药味以苦居多,其次为辛、甘;归经主要归心、肺、肝、脾经。通过关联规则分析得到核心药物8味,处方核心组合3个。结论本研究分析赵教授治疗心肌梗死合并抑郁的组方用药规律,提取核心处方,对临床治疗具有指导意义。

考虑季节特性与数据窗口的短期光伏功率预测组合模型

光伏功率的间歇性和随机性因季节变化呈现出不同的特点,考虑季节特性对提高光伏功率预测精度具有重要意义。因此,文中提出一种考虑季节特性和数据窗口的短期光伏功率预测组合模型。首先,通过皮尔逊相关系数法确定对光伏功率贡献度高的气象因素,降低预测模型的输入特征维数。其次,对比不同季节下不同模型的光伏功率预测精度,选择光伏功率预测误差最小且相关性最低的2个模型构建组合模型,即门控循环单元(gated recurrent unit,GRU)模型和极限梯度提升(extreme gradient boosting,XGboost)模型。然后,分析历史气象数据中不同输入窗口对GRU-XGboost模型预测精度的影响,确定最优数据窗口。最后,在此基础上分别采用GRU和XGboost对光伏功率进行预测,将2个预测结果加权组合得到最终预测结果。结果表明,与其他模型相比,所提模型具有更强的适应性和更高的预测精度。

基于多模态信息融合的猪肉价格指数预测研究

本文基于2012年1月至2024年2月猪肉价格指数月度同比数据,提出了一种运用多模态数据开展预测的LSTM模型。本文采用三次样条插值方法将原本146个月度数据扩充为581个周度数据,同时,从各大新闻网站爬取与猪肉价格相关的新闻数据共10634条并进行文本预处理。利用Transformer结构在新闻文本中提取的特征向量与市场价格信息相融合,引入LSTM对猪肉价格指数进行预测。通过与其他传统模型的预测效果对比发现,SARIMA和SVR模型对于拐点的预测存在滞后性,而LSTM模型则能够准确捕捉到真实值的拐点变化,对走势预测较为准确。相比较而言,加入新闻文本信息和市场数据的多模态组合LSTM模型的各项指标均优于对比模型,对于指数拐点的预测较为及时,且预测误差较小,取得了更好的预测效果。

Contrast-enhanced ultrasound in association with serum biomarkers for differentiating combined hepatocellular-cholangiocarcinoma from hepatocellular carcinoma and intrahepatic cholangiocarcinoma

BACKGROUND Combined hepatocellular-cholangiocarcinoma(CHC)is a rare type of primary liver cancer.Due to its complex histopathological characteristics,the imaging features of CHC can overlap with those of hepatocellular carcinoma(HCC)and intrahepatic cholangiocarcinoma(ICC).AIM To investigate the possibility and efficacy of differentiating CHC from HCC and ICC by using contrast-enhanced ultrasound(CEUS)Liver Imaging Reporting and Data System(LI-RADS)and tumor biomarkers.METHODS Between January 2016 and December 2019,patients with histologically confirmed CHC,ICC and HCC with chronic liver disease were enrolled.The diagnostic formula for CHC was as follows:(1)LR-5 or LR-M with elevated alphafetoprotein(AFP)and carbohydrate antigen 19-9(CA19-9);(2)LR-M with elevated AFP and normal CA19-9;or(3)LR-5 with elevated CA19-9 and normal AFP.The sensitivity,specificity,accuracy and area under the receiver operating characteristic curve were calculated to determine the diagnostic value of the criteria.RESULTS After propensity score matching,134 patients(mean age of 51.4±9.4 years,108 men)were enrolled,including 35 CHC,29 ICC and 70 HCC patients.Based on CEUS LI-RADS classification,74.3%(26/35)and 25.7%(9/35)of CHC lesions were assessed as LR-M and LR-5,respectively.The rates of elevated AFP and CA19-9 in CHC patients were 51.4%and 11.4%,respectively,and simultaneous elevations of AFP and CA19-9 were found in 8.6%(3/35)of CHC patients.The sensitivity,specificity,positive predictive value,negative predictive value,accuracy and area under the receiver operating characteristic curve of the aforementioned diagnostic criteria for discriminating CHC from HCC and ICC were 40.0%,89.9%,58.3%,80.9%,76.9%and 0.649,respectively.When considering the reported prevalence of CHC(0.4%-14.2%),the positive predictive value and NPV were revised to 1.6%-39.6%and 90.1%-99.7%,respectively.CONCLUSION CHCs are more likely to be classified as LR-M than LR-5 by CEUS LI-RADS.The combination of the CEUS LI-RADS classification with serum tumor markers shows high specificity but low sensitivity for the diagnosis of CHC.Moreover,CHC could be confidently excluded with high NPV.

Data fusion in oil and gas detection

Data fusion, a new research domain, is the integration and extension of modem information techniques and many other subjects. The data fusion concept is introduced and the Dempster-Shafer evidence deduction is described and applied to oil and gas detection. An example of the method is shown using numerical simulation data. The processing result indicates that the data fusion method can be widely used in hydrocarbon detection.

High-speed broadband data acquisition system based on FPGA

A field-programmable gate array(FPGA)based high-speed broadband data acquisition system is designed.The system has a dual channel simultaneous acquisition function.The maximum sampling rate is 500 MSa/s and bandwidth is200 MHz,which solves the large bandwidth,high-speed signal acquisition and processing problems.At present,the data acquisition system is successfully used in broadband receiver test systems.

基于贪心组合优化的分布极端不平衡分类算法

现有针对不平衡数据分类的研究主要从重采样、特征、代价和算法等4个角度展开,方法多样,但针对极端不平衡的数据分布仍缺乏有效算法.本文的目标是通过结合各种算法的特性获取一个最优性能的组合算法.本文假设算法间的组合满足次模函数性质,并采用贪心的组合优化方法.具体而言,选择深度森林算法为基础,依次组合最优重采样方法、以异常检测思想的特征提取方法对数据进行的特征处理方法或基于贝叶斯优化的最优代价敏感矩阵方法.在3种组合算法中选择分类性能最优的算法组合,再次组合其余角度的方法,判断分类性能是否再次提升.实验选择两组极端不平衡数据——真实饮用水数据和UCI数据库中的page-blocks数据进行验证.结果表明,基于贪心优化对算法间进行组合,在3轮迭代后得到的算法组合,较单一算法其分类性能能有进一步的提升.

融合多源数据挖掘信息的非轴对称端壁/叶身联合成型设计空间知识挖掘

为厘清联合成型设计空间各造型方法对涡轮叶栅性能提升的贡献,将基于总变差分析的全局敏感性分析方法与平行坐标系及直方图、散点图等可视化技术相结合,提出了将多源数据挖掘信息进行融合的设计空间知识挖掘框架,并利用该框架对某小展弦比叶栅端壁/叶身联合成型设计空间进行知识挖掘。结果表明:叶栅气动损失增减对基元型线微调十分敏感;非轴对称端壁所带来的损失减少量与型线微调接近,但设计空间内不同非轴对称端壁样本性能波动较小,导致其重要性被全局敏感性分析方法低估;虽然单独采用弯叶片难以整体降低小展弦比叶栅损失,但将弯、型线微调和非轴对称端壁造型相结合可获得“1+1+1>3”的性能增益;在端壁/叶身联合成型设计空间内,将基元型线朝着后加载方向微调,并采用喉部附近下凹较深的非轴对称端壁造型及反弯叶片设计,可获得气动损失较小的叶栅设计。研究结果明晰了端壁/叶身联合成型设计空间优化解特征,可为类似小展弦比叶栅设计优化提供借鉴。

基于数据挖掘的胆石症动物模型特点及应用分析

目的对现有胆石症动物模型进行整理归纳,探索可更好反映中西医临床病证特点,满足中医药临床与基础研究发展需要的动物模型。方法检索中国知网、万方、维普、SinoMed、PubMed等数据库,对国内外胆石症相关实验研究的动物模型进行搜集和整理,对模型的动物种类、造模方法、造模周期、检测指标和阳性药等数据进行统计和分析。结果纳入的128篇文献中,胆石症模型的动物种类以豚鼠、家兔和C57BL/6小鼠为主。使用最多的造模方法为高脂饲料法,饲料喂养周期集中在8周。高频检测指标为成石率、总胆固醇、磷脂、总胆红素、总胆汁酸等。较多使用的干预方式为中药复方、西药和单味中药或提取物,西药干预以熊去氧胆酸(Ursodeoxycholic acid,UDCA)为主,中药干预以中药复方为主,还包括针灸、运动、饮食等其他干预方式。实验设立阳性对照药多为UDCA。结论随着胆石症动物模型的不断完善和发展,目前有较多种造模方法都较好地模拟了胆石症中西医临床表现特点,但也存在一定局限性。该文分析结果可为胆石症模型的选择、应用和完善提供参考。

基于商用密码的水利重要数据点面结合安全保护方法

为保障数字孪生流域建设过程中的重要数据安全,针对破解海量高精度数据汇集面临的数据窃取、泄露、损毁等问题隐患开展研究,提出网络安全基础—数据分类分级—数据安全防护的数字孪生流域数据安全总体防护方案。针对数据安全传输、存储、使用中的安全薄弱点,提出全面通用防护和应用内加密相结合的点面结合加密保护方法,利用商用密码技术对数据进行机密性、完整性、可用性保护。本研究方法已在全国水利一张图等重要系统中得到应用,可实现数据安全保护和便捷高效应用平衡,广泛适用于数字孪生流域建设中的水利重要数据全生命周期保护。