Modal identification based on Hilbert-Huang Transform of structural response with S VD preprocessing

In recent years, Empirical mode decomposition and Hilbert spectral analysis have been combined to identify system parameters. Singular-Value Decomposition is pro- posed as a signal preprocessing technique of Hilbert-Huang Transform to extract modal parameters for closely spaced modes and low-energy components. The proposed method is applied to a simulated airplane model built in Automatic Dynamic Analysis of Mechanical Systems software. The results demonstrate that the identified modal parameters are in good agreement with the baseline model.

The application of amplitude-preserved processing and migration for carbonate reservoir prediction in the Tarim Basin,China

Conventional seismic exploration method based on post-stack data usually fails to identify the distribution of fractured and caved carbonate reservoirs in the Tarim Basin,so the rich pre-stack information should be applied to the prediction of carbonate reservoirs.Amplitude-preserved seismic data processing is the foundation.In this paper,according to the feature of desert seismic data （including weak reflection,fast attenuation of high frequency components,strong coherent noises,low S/N and resolution）,a set of amplitude-preserved processing techniques is applied and a reasonable processing flow is formed to obtain the high quality data.After implementing a set of pre-stack amplitude-preserved processing,we test and define the kernel parameters of amplitude-preserved Kirchhoff PSTM （pre-stack time migration） and subsequent gathers processing,in order to obtain the amplitude-preserved gathers used to the isotropic pre-stack inversion for the identification of caved reservoirs.The AVO characteristics of obtained gathers fit well with the synthetic gathers from logging data,and it proves that the processing above is amplitudepreserved.The azimuthal processing techniques,including azimuth division and binning enlargement,are implemented for amplitude-preserved azimuthal gathers with the uniform fold.They can be used in the anisotropic inversion to detect effective fractures.The processing techniques and flows are applied to the field seismic data,and are proved available for providing the amplitude-preserved gathers for carbonate reservoir prediction in the Tarim Basin.

Pre-processing and post-processing method for geostress simulation using seismic interpretation results

In order to carry out numerical simulation using geologic structural data obtained from Landmark(seismic interpretation system), underground geological structures are abstracted into mechanical models which can reflect actual situations and facilitate their computation and analyses.Given the importance of model building, further processing methods about traditional seismic interpretation results from Landmark should be studied and the processed result can then be directly used in numerical simulation computations.Through this data conversion procedure, Landmark and FLAC(the international general stress software) are seamlessly connected.Thus, the format conversion between the two systems and the pre-and post-processing in simulation computation is realized.A practical application indicates that this method has many advantages such as simple operation, high accuracy of the element subdivision and high speed, which may definitely satisfy the actual needs of floor grid cutting.

Narrow-band interference suppression in Time-Division-Duplex CDMA systems using preprocessing techniques

This letter presents two preprocessing techniques for narrow-band interference （NBI） rejection in Time- Division-Duplex （TDD） CDMA systems. In the proposed methods, at the transmitter, by using Karhaunen-Loeve Transform and Discrete Fourier Transform, the transmitted power is set to zero in the directions of the eigenvectors that will be severely contaminated by NBI; and therefore less part of the transmitted energy will be polluted by NBI in channel. The processing is transferred from receiver to transmitter, and thus the complexity of the receiver is significantly reduced. It is assumed that channel state information can be estimated at the transmitter because in symmetric TDD systems each receiver in turn also acts as a transmitter.

Scientific data products and the data pre-processing subsystem of the Chang'e-3 mission

The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1） investigate the morphological features and geological structures at the landing site; （2） integrated in-situ analysis of minerals and chemical compositions; （3） integrated exploration of the structure of the lunar interior; （4） exploration of the lunar-terrestrial space environment, lunar sur- face environment and acquire Moon-based ultraviolet astronomical observations. The Ground Research and Application System （GRAS） is in charge of data acquisition and pre-processing, management of the payload in orbit, and managing the data products and their applications. The Data Pre-processing Subsystem （DPS） is a part of GRAS. The task of DPS is the pre-processing of raw data from the eight instruments that are part of CE-3, including channel processing, unpacking, package sorting, calibration and correction, identification of geographical location, calculation of probe azimuth angle, probe zenith angle, solar azimuth angle, and solar zenith angle and so on, and conducting quality checks. These processes produce Level 0, Level 1 and Level 2 data. The computing platform of this subsystem is comprised of a high-performance computing cluster, including a real-time subsystem used for processing Level 0 data and a post-time subsystem for generating Level 1 and Level 2 data. This paper de- scribes the CE-3 data pre-processing method, the data pre-processing subsystem, data classification, data validity and data products that are used for scientific studies.

High Speed Regular Expression Matching Engine with Fast Pre-Processing

Regular expression matching is playing an important role in deep inspection. The rapid development of SDN and NFV makes the network more dynamic, bringing serious challenges to traditional deep inspection matching engines. However, state-of-theart matching methods often require a significant amount of pre-processing time and hence are not suitable for this fast updating scenario. In this paper, a novel matching engine called BFA is proposed to achieve high-speed regular expression matching with fast pre-processing. Experiments demonstrate that BFA obtains 5 to 20 times more update abilities compared to existing regular expression matching methods, and scales well on multi-core platforms.

Review of pre-processing technologies for ice cores

High-resolution ice core records covering long time spans enable reconstruction of the past climatic and environmental conditions allowing the investigation of the earth system's evolution. Preprocessing of ice cores has direct impacts on the data quality control for further analysis since the conventional ice core processing is time-consuming, produces qualitative data, leads to ice mass loss, and leads to risks of potential secondary pollution. However, over the past several decades, preprocessing of ice cores has received less attention than the improvement of ice drilling, the analytical methodology of various indices, and the researches on the climatic and environmental significance of ice core records. Therefore, this papers reviews the development of the processing for ice cores including framework, design as well as materials, analyzes the technical advantages and disadvantages of the different systems. In the past, continuous flowanalysis(CFA) has been successfully applied to process the polar ice cores. However, it is not suitable for ice cores outside polar region because of high level of particles, the memory effect between samples, and the filtration before injection. Ice core processing is a subtle and professional operation due to the fragility of the nonmetallic materials and the random distribution of particles and air bubbles in ice cores, which aggravates uncertainty in the measurements. The future developments of CFA are discussed in preprocessing, memory effect, challenge for brittle ice, coupling with real-time analysis and optimization of CFA in the field. Furthermore, non-polluting cutters with many different configurations could be designed to cut and scrape in multiple directions and to separate inner and outer portions of the core. This system also needs to be coupled with streamlined operation of packaging, coding, and stacking that can be implemented at high resolution and rate, avoiding manual intervention. At the same time, information of the longitudinal sections could be scanned andidentified, and then classified to obtain quantitative data. In addition, irregular ice volume and weight can also be obtained accurately. These improvements are recorded automatically via user-friendly interfaces. These innovations may be applied to other paleomedias with similar features and needs.

Image pre-processing research of coal level in underground coal pocket

Mathematical morphology is widely applicated in digital image procesing.Vari- ary morphology construction and algorithm being developed are used in deferent digital image processing.The basic idea of mathematical morphology is to use construction ele- ment measure image morphology for solving understand problem.The article presented advanced cellular neural network that forms mathematical morphological cellular neural network (MMCNN) equation to be suit for mathematical morphology filter.It gave the theo- ries of MMCNN dynamic extent and stable state.It is evidenced that arrived mathematical morphology filter through steady of dynamic process in definite condition.

Research of Image pre-processing Algorithm in Automation Fingerprint Identification

In the paper, a valid method of fingerprint Image pre- processing is introduced. Experiment results show that this kind of algorithm can availably wipe off yawp imported by the incom- plete leave fingerprint - marking of sensor surface when finger- print sensor record fingerprint. Meanwhile, it can extract the ef- fective and uneffective zone of fingerprint effectively, and also further enhance ridge line and vale line of fingerprint so that make the lines of fingerprint clear, continuum, lubricity and has better contrast, at the same time, has quite quick speed, this fingerprint Image pre- processing time can be shorten greatly.

Intelligent Data Pre-processing Model in Integrated Ocean Observing Network System

There are a number of dirty data in observation data set derived from integrated ocean observing network system.Thus,the data must be carefully and reasonably processed before they are used for forecasting or analysis.This paper proposes a data pre-processing model based on intelligent algorithms.Firstly,we introduce the integrated network platform of ocean observation.Next,the pre-processing model of data is presented,and an intelligent cleaning model of data is proposed.Based on fuzzy clustering,the Kohonen clustering network is improved to fulfill the parallel calculation of fuzzy c-means clustering.The proposed dynamic algorithm can automatically find the new clustering center with the updated sample data.The rapid and dynamic performance of the model makes it suitable for real time calculation,and the efficiency and accuracy of the model is proved by test results through observation data analysis.

Pre-processing filter design at transmitters for IBI mitigation in an OFDM system

In order to meet the demands for high transmission rates and high service quality in broadband wireless communication systems, orthogonal frequency division multiplexing （OFDM） has been adopted in some standards. However, the inter-block interference （IBI） and inter-carrier interference （ICI） in an OFDM system affect the performance. To mitigate IBI and ICI, some pre-processing approaches have been proposed based on full channel state information （CSI）, which improved the system performance. A pre-processing filter based on partial CSI at the transmitter is designed and investigated. The filter coefficient is given by the optimization processing, the symbol error rate （SER） is tested, and the computation complexity of the proposed scheme is analyzed. Computer simulation results show that the proposed pre-processing filter can effectively mitigate IBI and ICI and the performance can be improved. Compared with pre-processing approaches at the transmitter based on full CSI, the proposed scheme has high spectral efficiency, limited CSI feedback and low computation complexity.

The Role of Combined OSR and SDF Method for Pre-Processing of Microarray Data that Accounts for Effective Denoising and Quantification

Microarray data is inherently noisy due to the noise contaminated from various sources during the preparation of microarray slide and thus it greatly affects the accuracy of the gene expression. How to eliminate the effect of the noise constitutes a challenging problem in microarray analysis. Efficient denoising is often a necessary and the first step to be taken before the image data is analyzed to compensate for data corruption and for effective utilization for these data. Hence preprocessing of microarray image is an essential to eliminate the background noise in order to enhance the image quality and effective quantification. Existing denoising techniques based on transformed domain have been utilized for microarray noise reduction with their own limitations. The objective of this paper is to introduce novel preprocessing techniques such as optimized spatial resolution (OSR) and spatial domain filtering (SDF) for reduction of noise from microarray data and reduction of error during quantification process for estimating the microarray spots accurately to determine expression level of genes. Besides combined optimized spatial resolution and spatial filtering is proposed and found improved denoising of microarray data with effective quantification of spots. The proposed method has been validated in microarray images of gene expression profiles of Myeloid Leukemia using Stanford Microarray Database with various quality measures such as signal to noise ratio, peak signal to noise ratio, image fidelity, structural content, absolute average difference and correlation quality. It was observed by quantitative analysis that the proposed technique is more efficient for denoising the microarray image which enables to make it suitable for effective quantification.

基于结构-语义融合的评论文本情感分类研究

为了解决当前部分情感分析模型片面依赖文本语义特征、忽视句法结构特征的问题,提出了一种基于结构-语义融合的情感分类模型SF-TLSTM(sentiment-fusion-tree LSTM),即将句法结构信息与语义信息进行融合,全面提取文本特征。首先,将BERT(bidirectional encoder representation from transformers)模型引入TreeLSTM(tree-structured bidirectional LSTM)网络结构中;其次,利用SimCSE(simple contrastive learning of sentence embeddings)模型的自监督训练对BERT获得的向量表示进行数据增强;最后,通过节点编码的方式在构建的TreeLSTM网络上实现结构语义特征融合,并与基线模型进行多组对比分析。结果表明:在斯坦福大学发布的SST(stanford sentiment tree-bank)数据集上,SF-TLSTM模型相较于经典树形结构情感分类模型获得更高的准确率,其中在二分类任务中的准确率达到了96.79%。所提方法能够全面有效地提取评论文本的特征,增强文本的向量表示,对自然语言处理领域中的文本处理具有重要意义。

融合TF-IDF算法和预训练模型的文本数据增强

针对自然语言处理领域的数据增强问题,首次提出了一种基于TF-IDF算法和预训练语言模型BERT融合的文本数据增强方法。首先,改进传统的基于随机策略的词元选择方法,避免对语义起到关键作用的词元进行改写,利用TF-IDF算法提取样本的非核心词,得到替换的目标词元;之后针对现有算法在生成新数据时,依赖输入样本而导致的增强样本多样化受限问题,融合BERT模型预测目标替换词元,并使用预测的结果替换目标词元。实验结果表明,基于TF-IDF和BERT预训练模型融合的文本数据增强算法有效提升深度学习模型的性能达5.8%,优于现有的文本数据增强算法。

预检-挂号一体化信息系统在改进急诊科就诊流程及提升患者就诊体验中的作用分析

目的探讨分析预检-挂号一体化信息系统在改进急诊科就诊流程及提升患者就诊体验中的作用。方法选取2022年1月至12月浙江大学医学院附属儿童医院收治的100例急诊患者,为对照组,实施传统就诊模式,即预检与挂号分开进行;选取2023年1月至12月医院收治的100例急诊患者,为观察组,实施预检-挂号一体化就诊模式。对比两组患者分诊时间、分诊准确率、候诊时间、医务人员满意度及患者满意度。结果观察组分诊时间短于对照组,分诊准确率高于对照组,差异有统计学意义(P<0.05)。观察组总候诊时间较对照组短,差异有统计学意义(P<0.05)。观察组医护人员各条目及总分满意度评分均高于对照组,且差异有统计学意义(P<0.05)。观察组患者各条目评分及满意度总分均高于对照组,差异有统计学意义(P<0.05)。结论预检-挂号一体化信息系统可改进急诊科就诊流程,缩短分诊及候诊时间,提高分诊准确率,并可有效提升医务人员及患者的就诊满意度。

软-硬互层岩体节理峰前循环剪切疲劳损伤机理研究

三峡库区频发微小地震下岩体节理循环剪切疲劳损伤对边坡动力稳定性具有重要影响。通过室内峰前循环剪切试验和PFC2D细观数值计算,研究了考虑一阶起伏角、含水率、剪切速率、剪切幅度、法向应力及循环剪切次数影响的软-硬互层岩体节理宏细观疲劳损伤机理。研究表明:①岩体节理剪切应力-剪切位移曲线历经初始非线性压剪变形、近似线弹性压剪变形、循环剪切疲劳损伤变形、应力缓升压剪变形、应力陡升压剪变形及应力脆性跌落压剪变形六个演化阶段。②岩体节理峰值(残余)剪切强度和疲劳剪切(法向)位移在相同一阶起伏角、含水率、剪切速率、剪切幅度或法向应力下随循环剪切次增多而分别降低和增大;且其在相同循环剪切次数下随一阶起伏角或法向应力变大而分别增大和降低,而随含水率、剪切速率或剪切幅度变大则分别降低和增大。③宏细观结果总体上吻合较好,且岩体节理细观剪切疲劳损伤裂纹数量随剪切位移变化呈前期微增-陡增、中期缓增及后期陡增-缓增-陡增的发展特征,而其随循环剪切次数变化则呈前期陡增和后期缓增的发展特征。④岩体节理宏细观剪切疲劳损伤典型演化过程可概述为压密-起裂破坏、循环错动-贯通破坏及分离-啃断破坏3个渐进性发展阶段,且宏细观剪切疲劳损伤裂纹近似呈“倒U形”密集分布于岩体节理附近。

STUDY OF PREPARATION AND PROPERTY OF YBa_2Cu_3O_(7-δ)-Ag_x COMPOSITE SUPERCONDUCTORS PREPARED BY SOL-GEL PROCESS

YBa2Cu3O7-δ-Agx composite superconductors were prepared by hybrid sintering process using YBa2Cu3O7-δ-Agx ultrafine powder and Ag2O finepower, which were prepared by sol-gel process and precipitation process respectively. The effect of the Ag content on superconducting crictical transition temperature of YBa2Cu3O7-δ-Agx was not evident as long as YBa2Cu3O7-δ-Agx can form continuous network. But Ag can increase superconduction crictical current and density of the composite superconductors. The normal state (i.e. non-superconducting state at room temperature) resistivity shows a percolation threshold at 20%-30% Ag, whereas the superconducting net-work shows a percolationthreshold at 70% -80% Ag.

PCP-tuning:面向小样本学习的个性化连续提示调优

随着“提示学习”的兴起,预训练语言模型在少样本学习中取得了显著的表现,其中的关键问题是如何为每个训练样本构建合适的提示.近年来研究人员提出了一系列提示构造方法,有的构造离散型的提示,有的构造连续型的提示,但通常都是将一个提示应用到整个数据集上.然而,实验结果表明,很难找到一个能够适用于任务中所有样本的提示.为此,提出了一种用于小样本学习的个性化连续型提示调优方法(PCP-tuning),其目的是根据数据集中每个样本的语义来生成个性化的连续型提示.同时,还提出了两种校准技术来控制生成的连续型提示的分布,以获得更好的下游任务表现.最后在10个基准任务上进行大量实验,证明了新方法的优越性能.