Fuzzy Difference Equations in Diagnoses of Glaucoma from Retinal Images Using Deep Learning

The intuitive fuzzy set has found important application in decision-making and machine learning.To enrich and utilize the intuitive fuzzy set,this study designed and developed a deep neural network-based glaucoma eye detection using fuzzy difference equations in the domain where the retinal images converge.Retinal image detections are categorized as normal eye recognition,suspected glaucomatous eye recognition,and glaucomatous eye recognition.Fuzzy degrees associated with weighted values are calculated to determine the level of concentration between the fuzzy partition and the retinal images.The proposed model was used to diagnose glaucoma using retinal images and involved utilizing the Convolutional Neural Network(CNN)and deep learning to identify the fuzzy weighted regularization between images.This methodology was used to clarify the input images and make them adequate for the process of glaucoma detection.The objective of this study was to propose a novel approach to the early diagnosis of glaucoma using the Fuzzy Expert System(FES)and Fuzzy differential equation(FDE).The intensities of the different regions in the images and their respective peak levels were determined.Once the peak regions were identified,the recurrence relationships among those peaks were then measured.Image partitioning was done due to varying degrees of similar and dissimilar concentrations in the image.Similar and dissimilar concentration levels and spatial frequency generated a threshold image from the combined fuzzy matrix and FDE.This distinguished between a normal and abnormal eye condition,thus detecting patients with glaucomatous eyes.

Almost perfect sequences based on cyclic difference sets

The perfect sequences are so ideal that all out-of-phase autocorrelation coefficients are zero, and if the sequences are used as the coding modulating signal for the phase-modulated radar, there will be no interference of side lobes theoretically. However, it has been proved that there are no binary perfect sequences of period 4 < n≤ 12100. Hence, the almost perfect sequences with all out-of-phase autocorrelation coefficients as zero except one are of great practice in engineering. Currently, the cyclic difference set is one of most effective tools to analyze the binary sequences with perfect periodic autocorrelation function. In this article, two characteristic formulas corresponding to the autocorrelation and symmetric structure of almost perfect sequences are calculated respectively. All almost perfect sequences with period n, which is a multiple of 4, can be figured out by the two formulas. Several almost perfect sequences with different periods have been hunted by the program based on the two formulas and then applied to the simulation program and practical application for ionospheric sounding.

Difference Sets of Null Density Subsets of N

Let , and for any , . If is positive, then B is considered as a large set with . Its difference set has both high density and rich structure. The set with is also relatively large and it is a long standing conjecture that like sets with positive upper density they have arithmetic progression of arbitrary length. Here we show their difference set may not be substantial;for any there exists such that and .

RITT-WU'S CHARACTERISTIC SET METHOD FOR ORDINARY DIFFERENCE POLYNOMIAL SYSTEMS WITH ARBITRARY ORDERING

In this paper,a Ritt-Wu's characteristic set method for ordinary difference systems is proposed,which is valid for any admissible ordering. New definition for irre-ducible chains and new zero decomposition algorithms are also proposed.

Effects of Second-Order Sum-and Difference-Frequency Wave Forces on the Motion Response of a Tension-Leg Platform Considering the Set-down Motion

This paper presents a study on the motion response of a tension-leg platform(TLP) under first-and second-order wave forces, including the mean-drift force, difference and sum-frequency forces. The second-order wave force is calculated using the full-field quadratic transfer function(QTF). The coupled effect of the horizontal motions, such as surge, sway and yaw motions, and the set-down motion are taken into consideration by the nonlinear restoring matrix. The time-domain analysis with 50-yr random sea state is performed. A comparison of the results of different case studies is made to assess the influence of second-order wave force on the motions of the platform. The analysis shows that the second-order wave force has a major impact on motions of the TLP. The second-order difference-frequency wave force has an obvious influence on the low-frequency motions of surge and sway, and also will induce a large set-down motion which is an important part of heave motion. Besides, the second-order sum-frequency force will induce a set of high-frequency motions of roll and pitch. However, little influence of second-order wave force is found on the yaw motion.

A Construction of Relative Difference Set

In this paper, we give a construction of RDS in Galois ring by using some bent function, and obtain the equivalent relationship between RDS and a kind of bent function. At the same time, its existence is demonstrated.

珠江口盆地AD15洼构造沉积演化控制下的油气运聚模式

珠江口盆地是南海地区重要的油气产区,其中,AD15洼是重要的富生烃洼陷。但由于对复式油气藏认识有限,AD15洼未取得重大勘探进展。本文基于“源-汇-聚”的评价思路,针对AD15洼北部缓坡带,利用三维地震资料,结合测井资料及地化资料,开展了深入系统的油气运聚模式研究,得到以下认识:边界断裂差异演化控制了AD15富烃洼陷的形成,裂陷高峰期强烈断裂活动促使AD南部形成“连片湖盆”,沉降速率大,湖盆广而深,文昌组文四段、文三段时期大规模发育生烃潜力大的中深湖优质烃源岩。继承型流体运移构造脊控制油气主运聚方向,早、晚期断裂纵向差异性疏导与侧向砂体耦合组建了油气的接替立体输导模式。区域盖层控制下,油气沿构造脊高孔渗储层高效汇聚,则构建了AD15洼缓坡带“断-盖-脊”联控的油气长距离运聚成藏模式。上述研究对于研究区进一步深化油气勘探获取新的突破,具有一定的指导及借鉴意义。

On the Presentation of Social Class Difference in The Garden Party in terms of its Narrative Style and Settings Description

Katherine Mansfield was a predominant modernist writer who had written the well-known short story The Garden Party, which explicitly interprets the idea of social class difference between the upper class and the working class. This paper discusses its presentation of social class difference from two aspects, including the narrative style and the settings.

利用TDOA相关系数的ADS- B欺骗式干扰检测

目前,为了检测飞机位置异常点,已安装的ADS-B系统通过比较飞机广播位置与两个基站计算获得的TDOA(Time Difference of Arrival,TDOA)和由两基站实际接收信号的TDOA来达到目的,该方法简单,但性能受基站同步误差和飞机报告位置误差影响较大。本文提出了一种利用TDOA相关系数的ADS-B欺骗式干扰检测方法,同样使用两个基站来接收ADS-B信号,首先根据飞机报告的位置和两基站的位置计算信号到达两基站的TDOA,然后通过两基站接收信号时刻计算TDOA,集合同一架飞机的各个航迹点,则得到一组由报文计算的时间差和一组由基站计算得到的时间差,最后通过两组时间差的相关系数来识别真实目标和欺骗干扰。本文方法不需要反推飞机位置,对基站同步误差和飞机报告位置误差稳健。仿真实验验证了方法的有效性。

利用双天线相位差的ADS-B欺骗式干扰检测方法

广播式自动相关监视技术(Automatic Dependent Surveillance-Broadcast,简称ADS-B)相比于传统监视系统具有定位精度高、更新速率快和设备成本低等优点,受到国际民航组织的大力推广。但由于其共享开放式的特点使得系统容易受到各种欺骗式干扰的影响,严重威胁空中交通安全。本文提出了一种利用双天线相位差进行欺骗式干扰检测的方法:对同一信源广播的一组位置消息,首先根据其广播内容计算一组表征目标相对于接收机方向变化的量;其次根据双天线之间的相位差计算一组同样表征此方向变化的量;最后通过两组变量的相关系数判别真实目标和欺骗干扰。此外,针对与空中真实目标ICAO(International Civil Aviation Organization,简称ICAO)地址相同的虚假ADS-B消息可能导致的误检测,我们也提出了信源一致性检测方法。本文方法不需要估计信号来向,对天线的幅相误差稳健,仿真实验和实测数据均验证了方法的有效性。

基于ADS-B数据的雷达精度测量方法

分析了采用全球定位系统数据测量雷达精度的适用范围,介绍了广播式自动相关监视系统(ADS-B)的工作原理、数据格式、系统测量精度,并提出了一种基于ADS-B数据测量雷达精度的方法。文中验证了该方法在雷达精度考核中的可行性,试验结果表明,该方法可以满足精度较高的相控阵雷达精度测量和考核,且操作简单,易于评估。

基于ADS的射频前端预选器的设计与仿真

预选器作为射频接收前端的主要组成部分,对整个射频信号的接收有着重要的作用;针对实际无线通信环境下的应用,使用ADS软件设计了一种20 MHz^3.6GHz的射频前端预选器;在该设计中采用了亚倍频程滤波器组进行分段滤波和抑制镜像信号,并利用低噪声放大器(LNA)对信号进行放大并减小噪声,并对设计的预选器关键部分的插入损耗、增益、噪声系数等指标进行了仿真;仿真结果显示,所设计的预选器各项性能指标均已达到了预期的要求,对接收机前端系统的研究和完善具有重要的参考价值。

C-ADS强流质子直线加速器调谐系统测试分析

调谐系统是C-ADS超导直线加速器不可或缺的一部分,在加速器运行过程决定了超导腔的运行频率,直接影响了粒子加速的效果。为了充分了解调谐系统的工作情况和分析调谐系统出现的问题,设计了实验对调谐系统进行全方位测试。首先对调谐器的杠杆机构和剪叉机构进行了力学分析,而后对半波长谐振(HWR)超导腔在不同状态下进行了电场模拟,得出设计的调谐力和调谐位移满足HWR腔频率调谐要求。最后通过详细实验,采用自动、手动等方式测试了恒温器CM1,CM2,CM3中超导腔调谐器工作时的线性度、回程差、直线单元部分的线性度及回程。结果显示:CM1的调谐器基本满足慢调谐需要,CM2存在1200步回程,主要原因在于直线单元部分;CM3中调谐器的回程差较大,线性度不高,需要进一步改进。

基于深度学习与高斯差分法的ADS-B异常数据检测模型

受地形结构、气象条件等多种因素的影响,用于低空通航飞行器定位的广播式自动相关监视(Automatic de-pendent surveillance-broadcast,ADS-B)设备获取的位置信息存在异常数据。为检测异常数据,提出一种基于深度学习与高斯差分法的ADS-B异常数据检测模型。首先,依据ADS-B位置数据的特点,将ADS-B位置数据转换到以起飞点为原点的坐标系中,利用运动学原理去除ADS-B位置数据中的离群点。然后,利用高斯差分法(Difference of Gaussian,DoG)获取位置数据的细节信息。最后,利用长短期记忆单元(Long short-term memory,LSTM)神经网络优化在ADS-B位置数据中梯度减小严重的循环神经网络(Recurrent neural network,RNN)。通过LSTM神经网络构成的seq2seq(Sequence to sequence)模型对位置数据进行重构,利用重构误差检测异常数据。通过实际数据对模型进行验证和对比分析表明:利用seq2seq模型对ADS-B位置数据重构的方法能有效地检测异常数据,运行时间得到减少,而且相较于RNN神经网络,检测的平均准确率提高了近2.7%,相较于传统的异常检测模型具有更高的准确率。

ADS-B IN技术相关规章研究

针对ADS-B IN技术的最低运行性能标准,FAA与RTCA都颁布了相关文件提供参考,最主要的分别是TSO-C195与RTCA DO-317。这两个文件内容包含对ADS-B IN的技术要求规范,但又存在差异。该文通过对两个文件进行翻译、整理、对比与分析,阐述了ADS-B IN技术基本的技术规范,总结了这两部文件的异同。

OPTIMIZATION OF THE METHOD OF SELECTING THE TOOTH NUMBER SERIES IN A SET OF CHANGE GEARS Part Ⅱ The Rules for Permuting the DBL’s of the First Order and Their Intercalated Sets

The problem in practice of determining the proper combination of Zi in a set of changegears may be abstracted to the problem of finding the proper combination and permutation ofthe elements ai,i+1 of the set A1 to give maximum M-d. Some results to find optimal combina-tions of the elements of the set A1 have been reported in part I. In this part, some rules forpermuting these elements are introduced. By means of these rules, three kinds of intercalated setsof A1 have been found, namely: （1） Sets with an even left wing, （2） Sets with coincidence of bothwings, and （3） Sets with circulated elements.

Study on covering rough sets with topological methods

The authors study the covering rough sets by topological methods. They combine the covering rough sets and topological spaces by means of defining some new types of spaces called covering rough topological (CRT) spaces based on neighbourhoods or complementary neighbourhoods. As the separation axioms play a fundamental role in general topology, they introduce all these axioms into covering rough set theories and thoroughly study the equivalent conditions for every separation axiom in several CRT spaces. They also investigate the relationships between the separation axioms in these special spaces and reveal these relationships through diagrams in different CRT spaces.

Feature Selection Based on Difference and Similitude in Data Mining

Feature selection is the pretreatment of data mining. Heuristic search algorithms are often used for this subject. Many heuristic search algorithms are based on discernibility matrices,which only consider the difference in information system. Because the similar characteristics are not revealed in discernibility matrix,the result may not be the simplest rules. Although difference similitude(DS) methods take both of the difference and the similitude into account,the existing search strategy will cause some important features to be ignored. An improved DS based algorithm is proposed to solve this problem in this paper. An attribute rank function,which considers both of the difference and similitude in feature selection,is defined in the improved algorithm. Experiments show that it is an effective algorithm,especially for large-scale databases. The time complexity of the algorithm is O (|C |2|U|2).

A NOTE ON q-DIFFERENCE OPERATOR AND RELATED LIMIT DIRECTION

The growth of entire functions under the q-difference operators is studied in this paper, and then some properties of Julia set of entire functions under the higher order q-difference operators are obtained.

A matching algorithm based on hybrid matrices consisting of reference differences and disparities

Unique correct correspondence cannot be obtained only by use of gray correlation technique, which describes gray similar degree of feature points between the left and right images too unilaterally. The gray correlation technique is adopted to extract gray correlation peaks as a coarse matching set called multi-peak set. The disparity gradient limited constraint is utilized to optimize the multi-peak set. Unique match will be obtained by calculating the correlation of hybrid matrices consisting of reference differences and disparities from the multi-peak set. Two of the known corresponding points in the left and right images, respectively, are set as a pair of reference points to determine search direction and search scope at first. After the unique correspondence is obtained by calculating the correlation of the hybrid matrices from the multi-peak set, the obtained match is regarded as a new reference point till all feature points in the left (or right) image have been processed. Experimental results proved that the proposed algorithm was feasible and accurate.