Using Pearson’s System of Curves to Approximate the Distributions of the Difference between Two Correlated Estimates of Signal-to-Noise Ratios: The Cases of Bivariate Normal and Bivariate Lognormal Distributions

Background: The signal-to-noise ratio (SNR) is recognized as an index of measurements reproducibility. We derive the maximum likelihood estimators of SNR and discuss confidence interval construction on the difference between two correlated SNRs when the readings are from bivariate normal and bivariate lognormal distribution. We use the Pearsons system of curves to approximate the difference between the two estimates and use the bootstrap methods to validate the approximate distributions of the statistic of interest. Methods: The paper uses the delta method to find the first four central moments, and hence the skewness and kurtosis which are important in the determination of the parameters of the Pearsons distribution. Results: The approach is illustrated in two examples;one from veterinary microbiology and food safety data and the other on data from clinical medicine. We derived the four central moments of the target statistics, together with the bootstrap method to evaluate the parameters of Pearsons distribution. The fitted Pearsons curves of Types I and II were recommended based on the available data. The R-codes are also provided to be readily used by the readers.

Method for determining the position of landslide slip-surface with a typical inclinometric curves

In the actual monitoring of deep hole displacement,the identification of slip surfaces is primarily based on abrupt changes observed in the inclinometric curve.In conventional identification methods,inclinometric curves exhibiting indications of sliding can be categorized into three types:B-type,D-type,and r-type.The position of the slip surface is typically determined by identifying the depth corresponding to the point of maximum displacement mutation.However,this method is sensitive to the interval of measurement points and the observation scale of the coordinate axes and suffers from unclear sliding surfaces and uncertain values.Based on the variation characteristics of these diagonal curves,we classified the landslide into three components:the sliding body,the sliding interval,and the immobile body.Moreover,three different generalization models were established to analyze the relationships between the curve form and the slip surface location based on different physical indicators such as displacement rate,relative displacement,and acceleration.The results show that the displacement rate curves of an r-type slope exhibit a clustering feature in the sliding interval,and by solving for the depth of discrete points within the step phase,it is possible to determine the location of the slip surface.On the other hand,D-type slopes have inflection points in the relative displacement curve located at the slip surface.The acceleration curves of B-type slopes exhibit clustering characteristics during the sliding interval,while the scattered acceleration data demonstrate wandering characteristics.Consequently,the slip surface location can be revealed by solving the depth corresponding to the maximum acceleration with cubic spline interpolation.The approach proposed in this paper was applied to the monitoring data of a landslide in Yunnan Province,China.The results indicate that our approach can accurately identify the slip surface location and enable computability of its position,thereby enhancing applicability and reliability of the deep-hole displacement monitoring data.

A comparative study of data-driven battery capacity estimation based on partial charging curves

With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.

Analytical Determination of Size and Location of Roadside Horizontal Sightline Offsets for Compound Curves

AASHTO’s guideline for geometric design of highways and similar guidelines require that roadside areas on the inside of horizontal curves be cleared of high objects to provide stopping sight distance. The guidelines have analytical models for determining the extent of clearance, known as the horizontal sightline offset or clearance offset, for simple curves. Researchers in the past have developed analytical models for clearance offsets for spiraled and reverse curves. Very few researchers developed analytical models for available sight distances for compound curves. Still missing are models for horizontal sightline offsets and locations of the offsets for compound curves. The objective of this paper is to present development of analytical models and charts for determining horizontal sightline offsets and their locations for compound curves. The paper considers curves whose component arcs are individually shorter than stopping sight distance. The resulting models and the charts have been verified with accurate values determined using graphical methods. The models and the charts will find application in geometric design of highway compound curves.

Improving the Transmission Security of Vein Images Using a Bezier Curve and Long Short-Term Memory

The act of transmitting photos via the Internet has become a routine and significant activity.Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further enhanced.This study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous images.The main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image compression.This paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during transmission.By employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious actions.Furthermore,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been accomplished.For applications involving the transmission and sharing of images across a network.The suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture transfer.An effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of responsibilities.This scheme ensures a large reduction in computational and energy requirements while minimizing image quality loss.This approach employs multi-scale characteristics to improve the resistance of signatures against image deterioration.The proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.

Review on Service Curves of Typical Scheduling Algorithms

In recent years,various internet architectures,such as Integrated Services(IntServ),Differentiated Services(DiffServ),Time Sensitive Networking(TSN)and Deterministic Networking(DetNet),have been proposed to meet the quality-of-service(QoS)requirements of different network services.Concurrently,network calculus has found widespread application in network modeling and QoS analysis.Network calculus abstracts the details of how nodes or networks process data packets using the concept of service curves.This paper summarizes the service curves for typical scheduling algorithms,including Strict Priority(SP),Round Robin(RR),Cycling Queuing and Forwarding(CQF),Time Aware Shaper(TAS),Credit Based Shaper(CBS),and Asynchronous Traffic Shaper(ATS).It introduces the theory of network calculus and then provides an overview of various scheduling algorithms and their associated service curves.The delay bound analysis for different scheduling algorithms in specific scenarios is also conducted for more insights.

Sensitive Information Security Based on Elliptic Curves

The elliptic curve cryptography algorithm represents a major advancement in the field of computer security. This innovative algorithm uses elliptic curves to encrypt and secure data, providing an exceptional level of security while optimizing the efficiency of computer resources. This study focuses on how elliptic curves cryptography helps to protect sensitive data. Text is encrypted using the elliptic curve technique because it provides great security with a smaller key on devices with limited resources, such as mobile phones. The elliptic curves cryptography of this study is better than using a 256-bit RSA key. To achieve equivalent protection by using the elliptic curves cryptography, several Python libraries such as cryptography, pycryptodome, pyQt5, secp256k1, etc. were used. These technologies are used to develop a software based on elliptic curves. If built, the software helps to encrypt and decrypt data such as a text messages and it offers the authentication for the communication.

The Effectiveness of the Havriliak-Negami Model in Predicting the Master Curves of the Asphalt Blends with SBS Triblock Copolymer and Organic-Montmorillonite at Different Temperatures and Frequencies

The dynamic viscoelastic properties of asphalt AC-20 and its composites with Organic-Montmorillonite clay (OMMt) and SBS were modeled using the empirical Havriliak-Negami (HN) model, based on linear viscoelastic theory (LVE). The HN parameters, α, β, G0, G∞and τHN were determined by solving the HN equation across various temperatures and frequencies. The HN model successfully predicted the rheological behavior of the asphalt and its blends within the temperature range of 25˚C - 40˚C. However, deviations occurred between 40˚C - 75˚C, where the glass transition temperature Tg of the asphalt components and the SBS polymer are located, rendering the HN model ineffective for predicting the dynamic viscoelastic properties of composites containing OMMt under these conditions. Yet, the prediction error of the HN model dropped to 2.28% - 2.81% for asphalt and its mixtures at 100˚C, a temperature exceeding the Tg values of both polymer and asphalt, where the mixtures exhibited a liquid-like behavior. The exponent α and the relaxation time increased with temperature across all systems. Incorporating OMMt clay into the asphalt blends significantly enhanced the relaxation dynamics of the resulting composites.

基于小波变换和CNN-Transformer模型的测井储层流体识别

针对具有复杂储集空间和极强的非均质性的低孔低渗储层,常规测井响应特征不够明显,使用传统解释手段难以有效识别储层流体的问题,提出了一种基于小波变换和CNN-Transformer混合模型的储层流体识别方法。首先,使用小波变换将测井信号从时域扩展到时频域,并生成时频谱图以增强信号特征,然后使用滑动时窗沿着测井曲线深度方向滑动采样,获取代表解释深度处地层信息的频谱特征图,最后,通过训练CNN-transformer模型深度挖掘特征图信息,实现储层流体识别。混合模型在利用储层对应深度处测井数据的同时,又兼顾测井曲线随深度的变化趋势和地层前后信息的关联性,挖掘时频谱图的局部细节和全局特征表示,自动识别流体类型。将模型应用于大港油田22口实测测井资料中,并与CNN和BiLSTM等多个模型的流体识别效果进行对比分析,基于小波变换和CNN-Transformer模型识别效果明显优于其他方法,在测试集上识别准确率达到了92.7%。研究结果表明该方法可以作为低孔渗油藏常规测井资料识别储层流体的有效手段,为流体评价提供了新思路。

PASCO-Tracker实验系统的搭建及其对热机效率的测量

为使热机p-V图线的测量和由图线计算热机效率的整体过程可成为大学物理实验中易于操作的一部分,笔者首先搭建了PASCO-Tracker实验系统,然后在两种高温热源温度下,通过该系统分别实践了热机工作中p-t、V-t关系图线的测量,并在此基础上得到了p-V图线,在拟合出p-V关系函数后,通过原理公式的计算得到了热机效率与高温热源温度及气缸内装入的钢丝质量间的关系。测量结果表明,压强、体积的周期均随钢丝质量的增加而减小,效率随钢丝质量的增加而增加,二者具有非线性关系。热机效率随高温热源温度的增加而增加。本实验系统可用于演示热机工作过程的实时监控和热机效率的测量与计算。

6A01-T5铝合金/304不锈钢的缝隙腐蚀行为研究

目的 研究6A01-T5铝合金和304不锈钢异种金属间的缝隙腐蚀行为规律。方法 采用常温常压浸泡腐蚀方法,结合SEM、EDS、XRD和白光干涉检测,对6A01-T5铝合金/304不锈钢缝隙结构在碱性Na Cl溶液中的腐蚀行为进行研究。结果 6A01-T5铝合金/304不锈钢缝隙腐蚀表现为在缝口处产生沿缝口方向的凹陷渠,在缝内,以局部减薄和腐蚀坑为主,并随着腐蚀时间的延长,腐蚀程度逐渐加重。不同区域腐蚀产物的形貌和成分组成不尽相同,缝外暴露区的腐蚀产物表现为晶体颗粒状,主要成分为Ca CO3和Al(OH)3等铝的腐蚀产物。缝口附近沿缝口方向形成一层有明显界线的腐蚀产物覆盖层,缝隙内部的腐蚀产物相对较少,表现为尺寸相对较小的结块,主要成分为Al(OH)3等铝的腐蚀产物。结论 在6A01-T5铝合金与304不锈钢非电连接情况下,6A01-T5铝合金/304不锈钢缝隙内2种金属分别独立发生缝隙腐蚀,因2种金属在腐蚀过程中争夺O2,使得304不锈钢对6A01-T5铝合金的缝隙腐蚀起到抑制作用。

摆动模式对7005-T6铝合金激光焊接头力学性能及腐蚀行为的影响

采用摆动激光焊对7005-T6铝合金进行焊接。利用光学显微镜、扫描电子显微镜、透射电子显微镜、电子背散射衍射和电化学工作站等研究了三种激光摆动模式对接头微观组织、力学性能和腐蚀行为的影响。结果表明:使用摆动激光焊可以有效改善焊缝成型和降低柱状晶区域宽度;引入摆动模式可以细化焊缝处晶粒,减少气孔缺陷,提高焊缝处硬度和抗拉强度;摆动模式下焊缝晶界析出相尺寸更小,分布更加弥散,降低了腐蚀倾向和明显减少剥落腐蚀失重,同时可减少剥落腐蚀影响深度。经综合性能对比,发现摆动模式优于无摆动,无穷模式优于三角模式。

挤压态6082-T6铝合金的高温拉伸力学性能及微观组织

通过Gleeble3500热模拟试验机研究了变形温度和应变速率对挤压态6082-T6铝合金高温拉伸力学性能的影响,采用光学显微镜(OM)、扫描电镜(SEM)和透射电镜(TEM)分析了合金在高温拉伸过程中的微观组织演变。结果表明:在恒定的应变速率下,挤压态6082-T6铝合金的拉伸强度随着拉伸温度的升高而下降;在恒定的拉伸温度下,其拉伸强度随着应变速率的升高而上升。挤压态6082-T6铝合金在高温(300~450℃)拉伸条件下表现为韧性断裂,在较高的变形温度和较低应变速率条件下,合金的韧窝增大且更深,表现出较好的塑性。在高温变形过程中,随着拉伸温度的升高,合金内部的位错密度下降,并出现了析出相粗化现象,导致合金的变形抗力下降。

7050-T7451铝合金铣削参数多指标优化研究

通过Spike切削力测量设备及在线监控系统,采用单因素试验,研究硬质合金刀具铣削7050-T7451铝合金时,主轴转速、铣削宽度、铣削深度、进给速度以及顺、逆铣加工方式分别对刀具所受弯矩、表面粗糙度及功率的影响。运用正交试验法,通过S/N比分析和方差分析,获得7050-T7451铝合金的最优铣削参数。研究表明:顺铣更适用于7050-T7451铝合金的铣削加工;刀具所受弯矩随着主轴转速的增加而逐渐减小,最终趋于平稳,并随着铣削宽度、铣削深度及进给速度的增加而增加;表面粗糙度随主轴转速的增加呈先减小后增加;各铣削参数与加工功率均呈正相关关系;为获得较低加工弯矩和功率、较好表面质量,应取较高的主轴转速、较低的进给速度和铣削宽度,7050-T7451铝合金的最优铣削参数水平为A_(3)B_(1)C_(2)D_(1),即n=6000r/min,a_(e)=3.0mm,a_(p)=1.6mm,v_(f)=1500mm/min。

A Novel Contour Tracing Algorithm for Object Shape Reconstruction Using Parametric Curves

Parametric curves such as Bézier and B-splines, originally developedfor the design of automobile bodies, are now also used in image processing andcomputer vision. For example, reconstructing an object shape in an image,including different translations, scales, and orientations, can be performedusing these parametric curves. For this, Bézier and B-spline curves can be generatedusing a point set that belongs to the outer boundary of the object. Theresulting object shape can be used in computer vision fields, such as searchingand segmentation methods and training machine learning algorithms. Theprerequisite for reconstructing the shape with parametric curves is to obtainsequentially the points in the point set. In this study, a novel algorithm hasbeen developed that sequentially obtains the pixel locations constituting theouter boundary of the object. The proposed algorithm, unlike the methods inthe literature, is implemented using a filter containing weights and an outercircle surrounding the object. In a binary format image, the starting point ofthe tracing is determined using the outer circle, and the next tracing movementand the pixel to be labeled as the boundary point is found by the filter weights.Then, control points that define the curve shape are selected by reducing thenumber of sequential points. Thus, the Bézier and B-spline curve equationsdescribing the shape are obtained using these points. In addition, differenttranslations, scales, and rotations of the object shape are easily provided bychanging the positions of the control points. It has also been shown that themissing part of the object can be completed thanks to the parametric curves.

盐碱胁迫下苹果矮化砧木M9-T337对外源柠檬酸(CA)的响应

【目的】探究不同浓度外源柠檬酸(CA)对盐碱胁迫下苹果(砧木)幼苗生理特性的影响。【方法】以1年生苹果砧木M9-T337为试材,采用盆栽试验法,设置清水浇灌(CK1)、盐碱胁迫(CK2)、盐碱胁迫+0.2 mmol·L^(-1)CA(T1)、盐碱胁迫+0.6 mmol·L^(-1)CA(T2)、盐碱胁迫+1.0 mmol·L^(-1)CA(T3)、盐碱胁迫+1.4 mmol·L^(-1)CA(T4)6个处理,测定各处理叶片的光合荧光参数、叶绿素含量、根系形态、相对电导率(REC)、Na^(+)含量、K^(+)含量、抗氧化酶活性和渗透调节物质含量,并结合主成分分析对结果进行综合分析。【结果】喷施不同浓度柠檬酸可有效降低盐碱胁迫下M9-T337叶片电导率(REC)、胞间二氧化碳浓度(C_(i))以及Na^(+)含量的升高幅度,显著降低叶片相对含水量(RWC)、根系活力、根鲜质量比、叶绿素a(Chl a)含量、叶绿素b(Chl b)含量、叶绿素a+b(Chla+b)含量、净光合速率(P_(n))、气孔导度(G_(s))、蒸腾速率(T_(r))、初始荧光(F_(0))、最大荧光(F_(m))、光化学淬灭系数(qP)、非调节性能量耗散Y(NO)、超氧化物歧化酶(SOD)活性、过氧化氢酶(CAT)活性与过氧化物酶(POD)活性的下降幅度,以及显著增加脯氨酸(Pro)含量,并在T3处理下达到峰值;根据主成分得分排名可知,外源CA对M9-T337盐碱胁迫缓解能力由高到低为:CK1>T3>T2>T4>T1>CK2。【结论】1.0 mmol·L^(-1)的外源CA可更好地增强盐碱胁迫下M9-T337的光合能力,提高抗氧化酶活性,增强生物膜的稳定性以及促进Na^(+)外排、K^(+)区隔化和抑制K~+外排,从而起到缓解盐碱胁迫的作用。

考虑平均应力影响的7075-T651铝合金疲劳性能研究

研究了平均应力效应对7075-T651铝合金疲劳性能的影响,选取了R=0.5、0.3、0.1和-0.1四组应力比进行疲劳试验。结果表明,同一应力比下,随着峰值应力水平的增加,疲劳寿命逐渐降低;而同一峰值应力水平下,随着应力比的提高,疲劳寿命则呈现出逐渐升高的趋势。同时,使用扫描电子显微镜(Scanning Electron Microscopy,SEM)观察疲劳断口形貌发现,在峰值应力相同的情况下,裂纹萌生及扩展区的扇形面积随平均应力的增大而增大。最后,基于7075-T651铝合金疲劳实验结果,提出了一种考虑S-N-R的改进型预测模型,结果对比显示相较于其他模型,此模型在一定程度上对7075-T651铝合金具有更好的疲劳寿命预测效果。

地中海弧菌117-T6的溶藻活性

为验证地中海弧菌117-T6(Vm 117-T6)是否具有广谱溶藻性,本实验观察了其对赤潮异湾藻、颗石藻、叉鞭金藻和东海原甲藻的溶藻作用,并对其溶藻物质的特性进行了分析。结果表明,紫菜黄斑病致病菌Vm 117-T6对赤潮异湾藻、颗石藻、叉鞭金藻和东海原甲藻等微藻具有较强溶藻活性,可使藻类叶绿素含量显著降低,是一株广谱性溶藻细菌。Vm 117-T6能在40 min内使赤潮异弯藻的活动能力下降,光合作用受抑,感染120 min即可导致藻体裂解并产生白色絮状沉淀。该菌株能降解卡拉胶,不能降解果胶、纤维素和几丁质。Vm 117-T6菌体、胞内及胞外提取物均具有较强的溶藻活性,其胞外溶藻物质易溶于水、不溶于石油醚和乙酸乙酯,具较强极性;耐高温、不易被活性炭吸附、乙醇处理会降低溶藻活性。Vm 117-T6在常规与易感条件下的关键差异蛋白包括大量的ABC转运蛋白、外膜蛋白、鞭毛蛋白及少量毒素。上述结果提示,Vm 117-T6毒力效应物中含有极性的内毒素物质,且与毒力因子转运、分泌以及细胞黏附相关的蛋白可能在其毒力作用中发挥重要作用。本实验为解析该菌株溶藻机制提供了证据,为该菌的防治及应用提供了参考。

Characterization of the generalized permeability jail in tight reservoirs by analyzing relative-permeability curves and numerical simulation

This study comprehensively characterizes the boundary values of generalized permeability jail in tight reservoirs through relative-permeability curve analysis,numerical simulation,and economic evaluation.A total number of 108 relative-permeability curves of rock samples from tight reservoirs were obtained,and the characteristics of relative-permeability curves were analyzed.The irreducible water saturation(Swi)mainly ranges from 20% to 70%,and the residual gas saturation(Sgr)ranges from 5% to 15% for 55% of the samples.The relative-permeability curves are categorized into six types(Category-Ⅰ to Ⅵ)by analyzing the following characteristics:The relative permeability of gas at Swi,the relative permeability of water at Sgr,and the relative permeability corresponding to the isotonic point.The relative permeability curves were normalized to facilitate numerical simulation and evaluate the impact of different types of curves on production performance.The results of simulation show significant difference in production performance for different types of relative-permeability curves:Category-Ⅰ corresponds to the case with best well performance,whereas Categories-Ⅴ and Ⅵ correspond to the cases with least production volume.The results of economic evaluation show a generalized permeability jail for Categories-Ⅳ,Ⅴ,and Ⅵ,and the permeability jail develops when the relative permeability of gas and water is below 0.06.This study further quantifies the range of micro-pore parameters corresponding to the generalized permeability jail for a tight sandstone reservoir.

Investigation of magnetization reversal and domain structures in perpendicular synthetic antiferromagnets by first-order reversal curves and magneto-optical Kerr effect

Perpendicular synthetic-antiferromagnet(p-SAF) has broad applications in spin-transfer-torque magnetic random access memory and magnetic sensors. In this study, the p-SAF films consisting of (Co/Ni)3]/Ir(tIr)/[(Ni/Co)3are fabricated by magnetron sputtering technology. We study the domain structure and switching field distribution in p-SAF by changing the thickness of the infrared space layer. The strongest exchange coupling field(Hex) is observed when the thickness of Ir layer(tIr) is 0.7 nm and becoming weak according to the Ruderman–Kittel–Kasuya–Yosida-type coupling at 1.05 nm,2.1 nm, 4.55 nm, and 4.9 nm in sequence. Furthermore, the domain switching process between the upper Co/Ni stack and the bottom Co/Ni stack is different because of the antiferromagnet coupling. Compared with ferromagnet coupling films, the antiferromagnet samples possess three irreversible reversal regions in the first-order reversal curve distribution.With tIrincreasing, these irreversible reversal regions become denser and smaller. The results from this study will help us understand the details of the magnetization reversal process in the p-SAF.