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.

基于粗糙注意力融合机制与Group Transformer的视网膜血管分割网络

视网膜血管的形态学变化对早期眼科疾病的诊断具有重要意义,除眼科疾病外,糖尿病、心血管疾病等同样可以通过视网膜血管的形态判别疾病进展。然而,视网膜血管本身具有复杂的组织结构,且易受到光线等因素的影响,对其准确分割并不容易。针对上述问题,提出了一种视网膜血管分割网络。该网络中首先设计了粗糙注意力融合模块(rough attention fusion module,RAFM),该模块基于粗糙集上下近似理论,利用全局最大池化与全局平均池化对注意力系数进行上下限描述,并串行融合通道注意力机制与空间注意力机制;然后,将粗糙注意力融合模块融入Group Transformer U network(GT U-Net),构建一种基于粗糙注意力融合机制与Group Transformer的视网膜血管分割网络;最后,基于公开DRIVE彩色眼底图像数据集进行对比实验,该网络结构在测试集上的准确率、F_(1)分数、AUC值分别达到了0.9631、0.8488和0.9812,与GT U-Net模型相比,F_(1)分数、AUC值分别提升了0.35%、0.21%;与其他当前主流的视网膜血管分割网络进行对比,具有一定优势。

It’s Time for New Insights into Renovascular Hypertension at the Molecular Level

At the cellular level, reduced kidney perfusion in atherosclerotic renal arthery disease (ARVD), induces hypoxia, activation of the renin-angiotensin-aldosterone system (RAAS) and cytokine activation. Impaired blood flow in the kidneys creates a microenvironment triggering significant cytokine production, contributing to vascular damage and endothelial disfunction. Interactions between cytokines and endothelial, glomerular, and tubular cells often result in increased vessel permeability, and fibrosis, and contribute to the development of chronic kidney disease (CKD). Molecules such as endothelins, prostaglandins, and nitric oxide play a crucial role at the molecular level. The imbalance between vasoconstrictor and vasodilator factors contributes to vascular dysfunction. Oxidative stress and inflammatory processes at the cellular level contribute to endothelial damage and structural changes in blood vessels. Mineralocorticoid receptor antagonists (MRAs) therapy in the context of ARVD holds promise in reducing fibrosis, promoting angiogenesis and enhancing overall outcomes in patients with this pathology. Recent data also indicates the antioxidative, anti-inflammatory, and antifibrotic effects of SGLT2 inhibitors. They reduce oxidative stress caused by hypoxic conditions and enhance renal perfusion, contributing to the preservation of cellular function. Studies employing Blood Oxygen Level-Dependent (BOLD) imaging have identified adaptations to reduced blood flow, volume, and glomerular filtration rate in post-stenotic kidneys that preserve oxygenation in the medulla and cortex during medical therapy. Data from the literature indicate that despite the partial recovery of renal hypoxia and restoration of blood flow after revascularization, inflammatory cytokines and injury biomarkers remain elevated, and the glomerular filtration rate (GFR) does not recover in ARVD. Restoration of vascular patency alone has failed to reverse tubulointerstitial damage and partially explains the limited clinical benefit of renal stenting. Considering these findings, BOLD MR imaging emerges as a technique capable of providing insights into the critical juncture of irreversibility in ARVD. However, further research is needed to monitor renal hypoxia following renal artery stenting and the inflammatory response over an extended period in conjunction with optimal therapy involving MRAs and SGLT2 agonists. The aim of research at the molecular level enables the identification of potential therapeutic modalities targeting specific molecular pathways, opening the door to innovative approaches in treating renovascular hypertension.

Pseudo-Semi-Overlap Functions-Based Fuzzy Rough Sets Applied to Image Edge Extraction

As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and further extended for applications in image edge extraction. Firstly, a new clustering function, the pseudo-semi-overlap function, is introduced by eliminating the symmetry and right continuity present in the overlap function. The relaxed nature of this function enhances its applicability in image edge extraction. Secondly, the definitions of (I, PSO)-fuzzy rough sets are provided, using (I, PSO)-fuzzy rough sets, a pair of new fuzzy mathematical morphological operators (IPSOFMM operators) is proposed. Finally, by combining the fuzzy C-means algorithm and IPSOFMM operators, a novel image edge extraction algorithm (FCM-IPSO algorithm) is proposed and implemented. Compared to existing algorithms, the FCM-IPSO algorithm exhibits more image edges and a 73.81% decrease in the noise introduction rate. The outstanding performance of (I, PSO)-fuzzy rough sets in image edge extraction demonstrates their practical application value.

A NEW UNSUPERVISED CLASSIFICATION ALGORITHM FOR POLARIMETRIC SAR IMAGES BASED ON FUZZY SET THEORY

In this letter, a new method is proposed for unsupervised classification of terrain types and man-made objects using POLarimetric Synthetic Aperture Radar (POLSAR) data. This technique is a combi-nation of the usage of polarimetric information of SAR images and the unsupervised classification method based on fuzzy set theory. Image quantization and image enhancement are used to preprocess the POLSAR data. Then the polarimetric information and Fuzzy C-Means (FCM) clustering algorithm are used to classify the preprocessed images. The advantages of this algorithm are the automated classification, its high classifica-tion accuracy, fast convergence and high stability. The effectiveness of this algorithm is demonstrated by ex-periments using SIR-C/X-SAR (Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar) data.

Thinking of Countryside Image and New Countryside Planning with the Renovation Planning of Dazhuang Village as a Study Case

With the construction of new socialist countryside as the background, theories of constructing new countryside were discussed in this study, and approaches to construct new socialist countryside with Chinese countryside landscape images were explored.

基于改进型SM-ADRC的PMSM控制策略研究

在永磁同步电机(PMSM)控制中,传统的滑模自抗扰控制(SM-ADRC)能够减小外部负载变化和参数变化导致控制系统性能下降所带来的影响,但是还存在控制器参数太多,整定过于复杂化的问题,故提出一种改进型SM-ADRC方法。设计了一种新型变指数趋近律及新型控制函数将其引入扩展状态观测器(ESO)和非线性状态误差反馈控制律(NLSEF),得到新型滑模状态观测器(SM-ESO)和新型滑模状态误差反馈控制律(SM-NLSEF),减少了SM-ESO和SM-NLSEF待整定参数个数,简化了SM-ADRC参数整定。建立Simulink仿真模型和Links-RT半实物仿真实验平台,仿真和实验结果均表明:与传统SM-ADRC相比,改进型SM-ADRC在简化参数整定的同时提高了系统的响应速度和系统的抗扰性能,减小了电流脉动。

“技术-组织-环境”因素联动对企业数字创新的影响——基于新一代信息技术企业的QCA分析

基于“技术-组织-环境”(TOE)框架,使用沪深A股新一代信息技术产业上市企业数据,通过模糊集定性比较分析(fsQCA)方法探寻技术、组织与环境3个层面7个前因条件对企业数字创新的影响。研究发现。(1)企业通过多因素联动实现数字创新,存在4类能够产生高水平数字创新的组态,即技术环境联动的学习转化型、技术环境联动的捕获突破型、技术环境联动的协调开拓型和技术支持的自驱求变型;(2)企业吸收能力在实现高水平数字创新中发挥着重要作用,感知能力则在一定程度上可以替代外部环境对于企业的正向影响作用,环境要素中对数字创新起主要推动作用的是市场竞争程度;(3)缺失数字基础设施、高层次人才、感知能力、吸收能力这4个因素对非高水平数字创新的形成有着相对普遍的作用。因此政府应进一步优化市场竞争与政府支持的动态协同机制,构建企业良好的数字创新环境;新一代信息技术企业则应遵循系统性原则,结合自身优势和外部环境选择提升数字创新绩效的模式,并要积极培育支撑组织数字创新的动态能力,以提升企业创新效率和创新质量。

A new level set model for cell image segmentation

In this paper we first determine three phases of cell images： background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.

A new software for automated counting of glistenings in intraocular lenses in vivo

AIM:To assess the performance of a bespoke software for automated counting of intraocular lens(IOL)glistenings in slit-lamp images.METHODS:IOL glistenings from slit-lamp-derived digital images were counted manually and automatically by the bespoke software.The images of one randomly selected eye from each of 34 participants were used as a training set to determine the threshold setting that gave the best agreement between manual and automatic grading.A second set of 63 images,selected using randomised stratified sampling from 290 images,were used for software validation.The images were obtained using a previously described protocol.Software-derived automated glistenings counts were compared to manual counts produced by three ophthalmologists.RESULTS:A threshold value of 140 was determined that minimised the total deviation in the number of glistenings for the 34 images in the training set.Using this threshold value,only slight agreement was found between automated software counts and manual expert counts for the validating set of 63 images(κ=0.104,95%CI,0.040-0.168).Ten images(15.9%)had glistenings counts that agreed between the software and manual counting.There were 49 images(77.8%)where the software overestimated the number of glistenings.CONCLUSION:The low levels of agreement show between an initial release of software used to automatically count glistenings in in vivo slit-lamp images and manual counting indicates that this is a non-trivial application.Iterative improvement involving a dialogue between software developers and experienced ophthalmologists is required to optimise agreement.The results suggest that validation of software is necessary for studies involving semi-automatic evaluation of glistenings.

Revealing the Circadian Rhythm of Taliang Crocodile Newt(Liangshantriton taliangensis) During Breeding Migration Using a Novel Monitoring Technique

Many animals migrate during the breeding season.It is important to study the patterns of breeding migration of wild animals,especially rare and endangered species.However,current data acquisition methods are too coarse and imprecise for investigating the circadian rhythms of migrations in amphibians.Based on the frustrated total reflection image(FTRI),we developed a new device and recorded the precise migration time of an endangered salamander,Liangshantriton taliangensis.During the breeding period,a total of 33 individuals were effectively recorded.Analysis of the data indicated that the circadian rhythm of breeding migration in L.taliangensis was bimodal,and migration mainly occurred from 05:00 to 13:00(81.82%of the total migration records).The average relative activity intensity index(RAI)of breeding migration peaked in the temperature range of 14.0–16.0°C.With increased average relative air humidity,the activity intensity first increased and then decreased,reaching a peak in the humidity range of 91.0%–97.0%.These results demonstrate that our new device is a viable and accurate method for recording the migration time of target species.It is important to reveal the breeding migration pattern of L.taliangensis,which is important for the conservation of this species.Meanwhile,this new device can be used for field monitoring and conservation studies of amphibians,reptiles and other animals.

New normalized nonlocal hybrid level set method for image segmentation

This article introduces a new normalized nonlocal hybrid level set method for image segmentation.Due to intensity overlapping,blurred edges with complex backgrounds,simple intensity and texture information,such kind of image segmentation is still a challenging task.The proposed method uses both the region and boundary information to achieve accurate segmentation results.The region information can help to identify rough region of interest and prevent the boundary leakage problem.It makes use of normalized nonlocal comparisons between pairs of patches in each region,and a heuristic intensity model is proposed to suppress irrelevant strong edges and constrain the segmentation.The boundary information can help to detect the precise location of the target object,it makes use of the geodesic active contour model to obtain the target boundary.The corresponding variational segmentation problem is implemented by a level set formulation.We use an internal energy term for geometric active contours to penalize the deviation of the level set function from a signed distance function.At last,experimental results on synthetic images and real images are shown in the paper with promising results.

New Image Recognition Method Based on Rough-Sets and Fuzzy Theory

A new image recognition method based on fuzzy rough sets theory is proposed, and its implementation discussed. The performance of this method as applied to ferrography image recognition is evaluated. It is shown that the new method gives better results than fuzzy or rough sets method when used alone.

Feature Selection for Image Classification Based on a New Ranking Criterion

In this paper, a feature selection method combining the reliefF and SVM-RFE algorithm is proposed. This algorithm integrates the weight vector from the reliefF into SVM-RFE method. In this method, the reliefF filters out many noisy features in the first stage. Then the new ranking criterion based on SVM-RFE method is applied to obtain the final feature subset. The SVM classifier is used to evaluate the final image classification accuracy. Experimental results show that our proposed relief- SVM-RFE algorithm can achieve significant improvements for feature selection in image classification.

New Edge-Directed Interpolation Based-Lifting DWT and MSPIHT Algorithm for Image Compression

The amount of image data generated in multimedia applications is ever increasing. The image compression plays vital role in multimedia applications. The ultimate aim of image compression is to reduce storage space without degrading image quality. Compression is required whenever the data handled is huge they may be required to sent or transmitted and also stored. The New Edge Directed Interpolation (NEDI)-based lifting Discrete Wavelet Transfrom (DWT) scheme with modified Set Partitioning In Hierarchical Trees (MSPIHT) algorithm is proposed in this paper. The NEDI algorithm gives good visual quality image particularly at edges. The main objective of this paper is to be preserving the edges while performing image compression which is a challenging task. The NEDI with lifting DWT has achieved 99.18% energy level in the low frequency ranges which has 1.07% higher than 5/3 Wavelet decomposition and 0.94% higher than traditional DWT. To implement this NEDI with Lifting DWT along with MSPIHT algorithm which gives higher Peak Signal to Noise Ratio (PSNR) value and minimum Mean Square Error (MSE) and hence better image quality. The experimental results proved that the proposed method gives better PSNR value (39.40 dB for rate 0.9 bpp without arithmetic coding) and minimum MSE value is 7.4.

Campus Design Strategies Based on Spatial Images： A Case Study of Four New Campuses in Chengdu

From 1999, with the rapid expansion of enrollment scale, colleges have experienced fast development and construction of new campuses. However, the urgency of the demand for campus space at that time led to the shortcomings of paying more attention to speed than connotation during the construction of the new campus. Even now the evaluation of new campuses which have been used for nearly twenty years and whether the space of new campuses has played its due role will affect the display of the heritage and temperament of colleges. This paper uses the typical spatial cognitive concept—spatial image to analyse the elements of spatial images on campuses, summarizes the perceptions of teachers and students towards the space of four new campuses in Chengdu through questionnaire survey and analysis, puts forward the principles of campus space design and the strategies of classification design, and intends to take spatial images as the research cut-in point to provide new ideas and suggestions for the design and improvement of campus space from the perspective of users.

Language Analysis of Liaoning Urban Image in Chinese,American,and Canadian News Framework

The research chose the reports about the cities in Liaoning Province,Dalian,Shenyang,and Anshan as the objects of study.These reports came from the three newspapers China Daily,New York Times,and Globe and Mail.This research was based on Frame Work Theory,and used language analysis and case study as the research methods to identify the discourse and organization.The first result is that there is serious stereotyping about the image of Liaoning cities in American and Canadian news.And Chinese news did not cover entire comprehensive topics and was too late to emergency events,so they lost the chance to be an original source of news and the possibility to set the agenda,even lost the discourse power.The second result is that the differences between Chinese reports and American and Canadian reports implied culture differences,the similarities between Canadian and American reports refer to the culture intercommunity.Third,American and Canadian news used multi-framework to make the reports more reliable,but the lack of multi-dimensional reports declined the trustworthiness.

The Influence of Short Video on City Image Dissemination in the New Media Era——Taking Tik Tok as an Example

With the popularity and rise of Chongqing,Chengdu,Xi’an and other cities on the short video platform,short video is increasingly becoming a new weapon for the construction and dissemination of the city image.Researching on the content,methods and effects of the hottest video APP Tik Tok,this paper adopts research methods of case analysis and text analysis to investigate how short videos promote the spread of urban image,and explore how they can enhance urban image transmission in the new media era in a better way.

A New Approach Based on Set Partitioning in Hierarchical Tree Algorithm for Image Compression

In this paper, the authors propose a new approach to image compression based on the principle of Set Partitioning in Hierarchical Tree algorithm （SPIHT）. Our approach, the modified SPIHT （MSPIHT）, distributes entropy differently than SPIHT and also optimizes the coding. This approach can produce results that are a significant improvement on the Peak Signal-to-Noise Ratio （PSNR） and compression ratio obtained by SPIHT algorithm, without affecting the computing time. These results are also comparable with those obtained using the Embedded Zerotree Wavelet （EZW） and Joint Photographic Experts Group 2000 （JPG2） algorithms.

The Influence of Consumer Culture on American New Woman and Their Literary Image in the Early 20th Century

By the study of three great American literary works, The Great Gatsby, Tender is the Night and The Age of Innocence, this paper aims to give a holistic interpretation of"New Woman"and their intrinsic relationship with consumer culture in the light of Baudrillard's theories about the consumer society and the consumer culture.