An intelligent automatic correlation method of oilbearing strata based on pattern constraints:An example of accretionary stratigraphy of Shishen 100 block in Shinan Oilfield of Bohai Bay Basin,East China

Aiming at the problem that the data-driven automatic correlation methods which are difficult to adapt to the automatic correlation of oil-bearing strata with large changes in lateral sedimentary facies and strata thickness,an intelligent automatic correlation method of oil-bearing strata based on pattern constraints is formed.We propose to introduce knowledge-driven in automatic correlation of oil-bearing strata,constraining the correlation process by stratigraphic sedimentary patterns and improving the similarity measuring machine and conditional constraint dynamic time warping algorithm to automate the correlation of marker layers and the interfaces of each stratum.The application in Shishen 100 block in the Shinan Oilfield of the Bohai Bay Basin shows that the coincidence rate of the marker layers identified by this method is over 95.00%,and the average coincidence rate of identified oil-bearing strata reaches 90.02% compared to artificial correlation results,which is about 17 percentage points higher than that of the existing automatic correlation methods.The accuracy of the automatic correlation of oil-bearing strata has been effectively improved.

Automatic Measurement of Fetal Abdominal Biometric Parameters—Feasibility on a Portable Ultrasound Device

An automatic method for measuring the fetal mean abdominal diameter (MAD) or abdominal circumference (AC) with ultrasound is proposed. From a correctly presented abdominal section suitable for MAD or AC measurement, the location of fetal abdomen is detected by image processing. Thereafter, an active contour model is converged along the abdominal boundary for measurement purposes. The validation data set contained 310 images of fetuses with gestational age (GA) from 14 to 41 weeks. The measurement success rate was 88.1%. By manually indicating the location of the abdomen, the success rate was further improved to 95.8% for the failed cases. The correlation between manual and automatic measurements was 0.95 and the intraclass correlation coefficient (ICC) was 0.976 (95% confidence interval (CI);0.969 - 0.981). The average method execution time was 0.3 s. The mean error was lower in young fetuses (0.4%) than in older fetuses (-2.1%). The proposed cross-platform method was implemented on a portable, low-cost ultrasound machine prototype targeted for low- and middle-income countries (LMIC);the results achieved were comparable to those of other state-of-the-art automatic methods.

Adjusting precipitation measurements from the TRwS204 automatic weighing gauge in the Qilian Mountains, China

With the popularity of the automatic precipitation gauges in national weather stations,testing their performance and adjusting their measurements are top priorities. Additionally,because different climatic conditions may have different effects on the performance of the precipitation gauges, it is also necessary to test the gauges in different areas. This study mainly analyzed precipitation measurements from the single-Altershielded TRwS204 automatic weighing gauge(TRwS_(SA)) relative to the adjusted manual measurements(reference precipitation) from the Chinese standard precipitation gauge in a doublefence wind shield(CSPG_(DF)) in the Hulu watershed in the Qilian Mountains, China. The measurements were compared over the period from August 2014 to July2017, and the transfer function derived from the work by Kochendorfer et al.(2017 a) for correcting windinduced losses was applied to the TRwS_(SA) measurements. The results show that the average loss of TRwS_(SA) measurements relative to the reference precipitation decreased from 0.55 mm(10.7%) to 0.51 mm(9.9%) for rainfall events, from 0.35 mm(8.5%)to 0.22 mm(5.3%) for sleet events, and from 0.49 mm(18.9%) to 0.33 mm(12.7%) for snowfall events after adjustment. The uncorrected large biases of TRwS_(SA) measurements are considered to be mainly caused by specific errors of TRwS_(SA), different gauge orifice area and random errors. These types of errors must be considered when comparing precipitation measurements for different gauge types, especially in the mountains.

Automatic Detection and Measurement of Fetal Biparietal Diameter and Femur Length —Feasibility on a Portable Ultrasound Device

An automatic method able to recognize a presented section through the biparietal plane of the fetal head and a section through the fetal femur in ultrasound images is developed. Once the correct anatomical section for measurement is identified by the machine, the placement of the measurement calipers is automatically determined by fitting an active contour model to the structure of interest. The fetal biparietal diameter (BPD) and femur length (FL) are then measured automatically. The validation data set contained 167 and 197 B-mode images for BPD and FL measurements, respectively. The images were acquired using 4 different ultrasound scanners, which resulted in varied image quality and gain settings. The mean gestational age (GA) of the fetuses was 19.4 weeks, range 16 to 41 weeks. A measurement success rate of 90% was achieved for both BPD and FL. The correlation coefficients between the manual and automatic measurements were 0.995 (BPD) and 0.967 (FL), mean errors were 0.5 mm (BPD) and -1.7 mm (FL) and error range with 95% confidence interval (CI) were ﹣3.8 - 4.8 mm (BPD) and ﹣11.4 - 8.1 mm (FL). The automatic measurement results were consistent in both high and low gain settings. The intraclass correlation coefficients between manual and automatic measurements were 0.995 (95% CI;0.981 - 0.999) for BPD in high gain, 1.0 (95% CI;0.998 - 1.0) for BPD in low gain, 0.998 (95% CI;0.991 - 0.999) for FL in high gain and 0.999 (95% CI;0.996 - 1.0) for FL in low gain settings. The method was implemented on a prototype, portable ultrasound machine designed to be used in low- and middle-income countries (LMIC). The overall performance of the method supports our hypothesis that automated methods can be used and are beneficial in a clinical setting.

Automatic measurement of air-pressure sensor based on two-pressure control instrument

To measure the performance of high precision air-pressure sensors in below normal pressure,an automatic measurement instrument has been designed and implemented.It can simulate environment of low pressure from 300hPa to 1 000hPa with high accuracy by proportional-integral-derivative(PID)control quickly,and it can also generate various relative humidity by two-pressure control.The results show that this instrument can reach controlled pressure quickly.And it works well with the minimum average pressure difference,and the fluctuation is±0.02hPa at 500hPa.And it can keep in a stable status for a long time.It works well in performance testing of pressure sensors.The structure of the system is simple,takes small investment,and can be operated conveniently.

Design of a Modularized Automatic Measurement and Control System for LaserInduced Breakdown Spectrometer

In order to improve the compatibility of laser-induced breakdown spectroscopy( LIBS) instrument for different types of parts and optimize the analysis and testing processes,a modularized automatic measurement and control system was developed. Based on the characteristics of each LIBS component, the following development steps have been performed:( 1) a summary of characteristic parameters of the component are established;( 2) the integration mechanism of multiple electrical interfaces is designed;( 3) the component control instruction library is developed. The experimental results indicate that the measurement and control system is compatible with most LIBS parts in the market.Spectrometer and laser can be compatible with at least three different types of parts. In addition,a multilayer iterative testing process is designed to improve the efficiency of optimization process of LIBS parameters. The experimental results have shown that the automatic optimization of the delay time compared to the manual testing provides significant gain in testing efficiency. The range of delay time in the experiments is 1. 28 to 10. 28 μs and the step value is 1,0. 5,0. 2 and 0. 1 μs. The gain in testing efficiency has been found to be increased by 73. 76%,75. 93%,78. 81% and 80. 42%,respectively.

Measurement of Stone Diameter with Three Sizes of Automatically Fixating Stone Baskets

Background: Complications after endoscopic retrieval of kidney and ureter stones are obviously related to the size of the stones as well as the experience of the surgeon and other factors. During the procedure it is sometimes difficult for surgeons to estimate stone size and therefore give prognostic advises. The visual perception of the stone size depends on the shape, colour, distance to the renoscope and dilatation of the ureter. This is the so-called binding problem, because shape, color and direction of motion are processed separately by different population of optical neurons. In order to establish a better prognostic rational especially for less experienced surgeons, we established an intra operative semi-quantitative measurement of the stone size supported by a stone basket. Materials and Methods: We modified the tipped, nitinol stone baskets from the company Urotech with diameters of 2.5, 3.0 and 4 FR. The handle of this basket has a spring mechanism, which automatically closes the basket and provides a predefined fixation force of the stones within the basket. On the handle we established a non-linear scale in mm by grabbing standardized balls or standardized screws. Result: The scales are nonlinear because of the nonlinear relation between the diameter of the stone and the distance of the slider. Also the scales differ in between the basket size, because of the different strain conditions due to the different wire sizes and materials or the spring and basket. Conclusion: This scale could be an important orientation for a surgeon during endourological procedures to estimate stone sizes. After further clinical experience a semi-quantitative visualization like green, yellow and red colors could help to predict potential complications due to large stone sizes. Finally it could bevery interesting for other disciplines like gastroenterology.

Design of mobile sensing system for automatical measurement

移动设备人机交互能力较差且计算能力有限,因此开发基于移动设备的测量系统的难度较高。本文设计了一种移动传感系统,它具备构件、配置和运行测量程序的功能,由移动设备和传感器探头两部分组成。在移动设备中安装了小型化虚拟仪器平台,该平台具有面向对象的架构,并可以通过XML文件进行配置,且这些配置文件可以被写入传感器探头。因此,探头和移动设备之间可以通过自组网形成测量系统。为测试该系统的性能,本文基于某安卓手机和一个测量探头设计了声音采集和柔性力测量程序,体现出移动传感平台具备可重构、自动化和柔性化程度高的特点。

Automatic Recognition Method for Optical Measuring Instruments Based on Machine Vision

Based on a comprehensive study of various algorithms, the automatic recognition of traditional ocular optical measuring instruments is realized. Taking a universal tools microscope(UTM) lens view image as an example, a 2-layer automatic recognition model for data reading is established after adopting a series of pre-processing algorithms. This model is an optimal combination of the correlation-based template matching method and a concurrent back propagation(BP) neural network. Multiple complementary feature extraction is used in generating the eigenvectors of the concurrent network. In order to improve fault-tolerance capacity, rotation invariant features based on Zernike moments are extracted from digit characters and a 4-dimensional group of the outline features is also obtained. Moreover, the operating time and reading accuracy can be adjusted dy-namically by setting the threshold value. The experimental result indicates that the newly developed algorithm has optimal recognition precision and working speed. The average reading ratio can achieve 97.23%. The recognition method can automatically obtain the results of optical measuring instruments rapidly and stably without modifying their original structure, which meets the application requirements.

Method of Predicting Water Content in Crude Oil Based on Measuring Range Automatic Switching

Water content in output crude oil is hard to measure precisely because of wide range of dielectric coefficient of crude oil caused by injected dehydrating and demulsifying agents.The method to reduce measurement error of water content in crude oil proposed in this paper is based on switching measuring ranges of on-line water content analyzer automatically.Measuring precision on data collected from oil field and analyzed by in-field operators can be impressively improved by using back propogation （BP） neural network to predict water content in output crude oil.Application results show that the difficulty in accurately measuring water-oil content ratio can be solved effectively through this combination of on-line measuring range automatic switching and real time prediction,as this method has been tested repeatedly on-site in oil fields with satisfactory prediction results.

AN AUTOMATIC HEAT FLUX-TEMPERATURE MEASURING SYSTEM AND ITS APPLICATION

An automatic heat flux-temperature measuring system can be used to measure local body heat flux, local skin temperature, body core temperature, and ambient temperature, as well as mean body heat flux, mean skin temperature, physiological shell thermal insulation and suit thermal insulation. This paper describes the measuring principle, hardware construction, software program and the application in thermal measurements on divers.

Study on Factors Influencing the Quality of Automatic Monitoring Data of Pollution Sources and Technical Assurance Measures

Automatic monitoring data of pollution sources is an important basis for environmental supervision and management.At present,it is difficult to guarantee the quality of automatic monitoring data of pollution sources,and it is difficult to play the role of the monitoring data.In response to this problem,the factors influencing the quality of automatic monitoring data of pollution sources were analyzed in detail,and technical assurance measures for the quality of automatic monitoring data of pollution sources in Shandong Province were studied.Besides,the dynamic management and control idea of automatic monitoring of pollution sources was proposed,and specific technical measures were analyzed from five aspects of standardizing automatic monitoring equipment of pollution sources,improving the data collection and transmission system,establishing a mechanism for reporting operating status information of monitoring equipment,setting alarm rules and alarm processing procedures,and statistically analyzing the operating status of the equipment.Practice has proved that the dynamic management and control system can effectively ensure the quality of automatic monitoring data of pollution sources.

Intelligent Segmentation and Measurement Model for Asphalt Road Cracks Based on Modified Mask R-CNN Algorithm

Nowadays, asphalt road has dominated highways around the world. Among various defects of asphalt road, crackshave been paid more attention, since cracks often cause major engineering and personnel safety incidents. Currentmanual crack inspection methods are time-consuming and labor-intensive, and most segmentation methods cannot detect cracks at the pixel level. This paper proposes an intelligent segmentation and measurement model basedon the modified Mask R-CNN algorithm to automatically and accurately detect asphalt road cracks. The modelproposed in this paper mainly includes a convolutional neural network (CNN), an optimized region proposalnetwork (RPN), a region of interest (RoI) Align layer, a candidate area classification network and a Mask branch offully convolutional network (FCN). The ratio and size of anchors in the RPN are adjusted to improve the accuracyand efficiency of segmentation. Soft non-maximum suppression (Soft-NMS) algorithm is developed to improvethe segmentation accuracy. A dataset including 8,689 images (512× 512 pixels) of asphalt cracks is established andthe road crack is manually marked. Transfer learning is used to initialize the model parameters in the trainingprocess. To optimize the model training parameters, multiple comparison experiments are performed, and the testresults show that the mean average precision (mAP) value and F1-score of the optimal trained model are 0.952 and0.949. Subsequently, the robustness verification test and comparative test of the trained model are conducted andthe topological features of the crack are extracted. Then, the damage area, length and average width of the crackare measured automatically and accurately at pixel level. More importantly, this paper develops an automatic crackdetection platform for asphalt roads to automatically extract the number, area, length and average width of cracks,which can significantly improve the crack detection efficiency for the road maintenance industry.

Easy calibration method of vision system for in-situ measurement of strain of thin films

An easy calibration method was presented for in-situ measurement of displacement in the order of nanometer during micro-tensile test for thin films by using CCD camera as a sensing device. The calibration of the sensing camera in the system is a central element part to measure displacement in the order of nanometer using images taken with the camera. This was accomplished by modeling the optical projection through the camera lens and relative locations between the object and camera in 3D space. A set of known 3D points on a plane where the film is located on is projected to an image plane as input data. These points, known as a calibration points, are then used to estimate the projection parameters of the camera. In the measurement system of the micro-scale by CCD camera, the calibration data acquisition and one-to-one matching steps between the image and 3D planes need precise data extraction procedures and repetitive user's operation to calibrate the measuring devices. The lack of the robust image feature extraction and easy matching prevent the practical use of these methods. A data selection method was proposed to overcome these limitations and offer an easy and convenient calibration of a vision system that has the CCD camera and the 3D reference plane with calibration marks of circular type on the surface of the plane. The method minimizes the user's intervention such as the fine tuning of illumination system and provides an efficient calibration method of the vision system for in-situ axial displacement measurement of the micro-tensile materials.

Automatic Partition of Chinese Sentence Group

Automatic partition of Chinese sentence group is very important to the statistical machine translation system based on discourse. This paper presents an approach to this issue:first,each sentence in a discourse is expressed as a feature vector; second,a special hierarchical clustering algorithm is applied to present a discourse as a sentence group tree. In this paper,local reoccurrence measure is proposed to the selection of key phrases and the evaluation of the weight of key phrases. Experimental results show our approach promising.

An Automatic Synchronization Method for Distributed Power Electronics System

Currently, the high-speed serial fiber-optic ring net communication is a main method for performing the distributed control network topology and control mode. Because of a network transmission delay inherent in the topology, synchronization between nodes has become a critical issue which needs to be studied. The existing synchronization methods largely depend on the complex communication protocol. Therefore, this paper has proposed a method of automatic measurement and compensation of synchronization delay, and analyzed its operating principle and implementation procedure in detail. The results obtained from the experiments prove the proposed method to be correct, effective and practicable.

Design of Automatic Batch Calibration and Correction System for IMU

Thanks to its light weight,low power consumption,and low price,the inertial measurement units(IMUs)have been widely used in civil and military applications such as autopilot,robotics,and tactical weapons.The calibration is an essential procedure before the IMU is put in use,which is generally used to estimate the error parameters such as the bias,installation error,scale factor of the IMU.Currently,the manual one-by-one calibration is still the mostly used manner,which is low in efficiency,time-consuming,and easy to introduce mis-operation.Aiming at this issue,this paper designs an automatic batch calibration method for a set of IMUs.The designed automatic calibration master controller can control the turntable and the data acquisition system at the same time.Each data acquisition front-end can complete data acquisition of eight IMUs one time.And various scenarios of experimental tests have been carried out to validate the proposed design,such as the multi-position tests,the rate tests and swaying tests.The results illustrate the reliability of each function module and the feasibility automatic batch calibration.Compared with the traditional calibration method,the proposed design can reduce errors caused by the manual calibration and greatly improve the efficiency of IMU calibration.

Automatic System for Failure Detection in Hydro-Power Generators

This paper presents an automatic system for failure detection in hydro-power generators. The main idea of this system is to detect failure using current and voltage signals acquired without any type of internal interference in the generator operation. The detected failures could be mechanical or electrical origins, such as: problems in bearings, unwanted vibrations, partial discharges, misalignment, unbalancing, among others. It is possible because the generator acts as a transducer for mechanical problems, and they appear in current and voltage signals. This automatic system based on electric signature analysis has been installed in Itapebi Power Plant generators since 2012. Some results are presented in this paper.

MC-LRF based pose measurement system for shipborne aircraft automatic landing

Due to the portability and anti-interference ability,vision-based shipborne aircraft automatic landing systems have attracted the attention of researchers.In this paper,a Monocular Camera and Laser Range Finder(MC-LRF)-based pose measurement system is designed for shipborne aircraft automatic landing.First,the system represents the target ship using a set of sparse landmarks,and a two-stage model is adopted to detect landmarks on the target ship.The rough 6D pose is measured by solving a Perspective-n-Point problem.Then,once the rough pose is measured,a region-based pose refinement is used to continuously track the 6D pose in the subsequent image sequences.To address the low accuracy of monocular pose measurement in the depth direction,the designed system adopts a laser range finder to obtain an accurate range value.The measured rough pose is iteratively optimized using the accurate range measurement.Experimental results on synthetic and real images show that the system achieves robust and precise pose measurement of the target ship during automatic landing.The measurement means error is within 0.4in rotation,and 0.2%in translation,meeting the requirements for automatic fixed-wing aircraft landing.

Automatic Sentiment Classification of News Using Machine Learning Methods

With the rapid development of social economy,the society has entered into a new stage of development,especially in new media under the background of rapid development,makes the importance of news and information to get the comprehensive promotion,and in order to further identify the positive and negative news,should be fully using machine learning methods,based on the emotion to realize the automatic classifying of news,in order to improve the efficiency of news classification.Therefore,the article first makes clear the basic outline of news sentiment classification.Secondly,the specific way of automatic classification of news emotion is deeply analyzed.On the basis of this,the paper puts forward the concrete measures of automatic classification of news emotion by using machine learning.