Spatial Distribution Pattern and Influencing Factors of Bed-and-breakfasts(B&Bs)from the Perspective of Urban-rural Differences:A Case Study of Jiaodong Peninsula,China

There are significant differences between urban and rural bed-and-breakfasts(B&Bs)in terms of customer positioning,economic strength and spatial carrier.Accurately identifying the differences in spatial characteristics and influencing factors of each type,is essential for creating urban and rural B&B agglomeration areas.This study used density-based spatial clustering of applications with noise(DBSCAN)and the multi-scale geographically weighted regression(MGWR)model to explore similarities and differences in the spatial distribution patterns and influencing factors for urban and rural B&Bs on the Jiaodong Peninsula of China from 2010 to 2022.The results showed that:1)both urban and rural B&Bs in Jiaodong Peninsula went through three stages:a slow start from 2010 to 2015,rapid development from 2015 to 2019,and hindered development from 2019 to 2022.However,urban B&Bs demonstrated a higher development speed and agglomeration intensity,leading to an increasingly evident trend of uneven development between the two sectors.2)The clustering scale of both urban and rural B&Bs continued to expand in terms of quantity and volume.Urban B&B clusters characterized by a limited number,but a higher likelihood of transitioning from low-level to high-level clusters.While the number of rural B&B clusters steadily increased over time,their clustering scale was comparatively lower than that of urban B&Bs,and they lacked the presence of high-level clustering.3)In terms of development direction,urban B&B clusters exhibited a relatively stable pattern and evolved into high-level clustering centers within the main urban areas.Conversely,rural B&Bs exhibited a more pronounced spatial diffusion effect,with clusters showing a trend of multi-center development along the coastline.4)Transport emerged as a common influencing factor for both urban and rural B&Bs,with the density of road network having the strongest explanatory power for their spatial distribution.In terms of differences,population agglomeration had a positive impact on the distribution of urban B&Bs and a negative effect on the distribution of rural B&Bs.Rural B&Bs clustering was more influenced by tourism resources compared with urban B&Bs,but increasing tourist stay duration remains an urgent issue to be addressed.The findings of this study could provide a more precise basis for government planning and management of urban and rural B&B agglomeration areas.

Mapping and measuring urban-rural inequalities in accessibility to social infrastructures

Equal access to social infrastructures is a fundamental prerequisite for sustainable development,but has long been a great challenge worldwide.Previous studies have primarily focused on the accessibility to social infras-tructures in urban areas across various scales,with less attention to rural areas,where inequality can be more severe.Particularly,few have investigated the disparities of accessibility to social infrastructures between urban and rural areas.Here,using the Changsha-Zhuzhou-Xiangtan urban agglomeration,China,as an example,we investigated the inequality of accessibility in both urban and rural areas,and further compared the urban-rural difference.Accessibility was measured by travel time of residents to infrastructures.We selected four types of social infrastructures including supermarkets,bus stops,primary schools,and health care,which were funda-mentally important to both urban and rural residents.We found large disparities in accessibility between urban and rural areas,ranging from 20 min to 2 h.Rural residents had to spend one to two more hours to bus stops than urban residents,and 20 min more to the other three types of infrastructures.Furthermore,accessibility to multiple infrastructures showed greater urban-rural differences.Rural residents in more than half of the towns had no access to any infrastructure within 15 min,while more than 60%of the urban residents could access to all infrastructures within 15 min.Our results revealed quantitative accessibility gap between urban and rural areas and underscored the necessity of social infrastructures planning to address such disparities.

Age-specific differences in the association between prediabetes and cardiovascular diseases in China:A national cross-sectional study

BACKGROUND Cardiovascular disease(CVD)is a leading cause of morbidity and mortality worldwide,the global burden of which is rising.It is still unclear the extent to which prediabetes contributes to the risk of CVD in various age brackets among adults.To develop a focused screening plan and treatment for Chinese adults with prediabetes,it is crucial to identify variations in the connection between prediabetes and the risk of CVD based on age.AIM To examine the clinical features of prediabetes and identify risk factors for CVD in different age groups in China.METHODS The cross-sectional study involved a total of 46239 participants from June 2007 through May 2008.A thorough evaluation was conducted.Individuals with prediabetes were categorized into two groups based on age.Chinese atherosclerotic CVD risk prediction model was employed to evaluate the risk of developing CVD over 10 years.Random forest was established in both age groups.SHapley Additive exPlanation method prioritized the importance of features from the perspective of assessment contribution.RESULTS In total,6948 people were diagnosed with prediabetes in this study.In prediabetes,prevalences of CVD were 5(0.29%)in the younger group and 148(2.85%)in the older group.Overall,11.11%of the younger group and 29.59% of the older group were intermediate/high-risk of CVD for prediabetes without CVD based on the Prediction for ASCVD Risk in China equation in ten years.In the younger age group,the 10-year risk of CVD was found to be more closely linked to family history of CVD rather than lifestyle,whereas in the older age group,resident status was more closely linked.CONCLUSION The susceptibility to CVD is age-specific in newly diagnosed prediabetes.It is necessary to develop targeted approaches for the prevention and management of CVD in adults across various age brackets.

Extraction of Acoustic Normal Mode Depth Functions Using Range-Difference Method with Vertical Linear Array Data

Data-derived normal mode extraction is an effective method for extracting normal mode depth functions in the absence of marine environmental data.However,when the corresponding singular vectors become nonunique when two or more singular values obtained from the cross-spectral density matrix diagonalization are nearly equal,this results in unsatisfactory extraction outcomes for the normal mode depth functions.To address this issue,we introduced in this paper a range-difference singular value decomposition method for the extraction of normal mode depth functions.We performed the mode extraction by conducting singular value decomposition on the individual frequency components of the signal's cross-spectral density matrix.This was achieved by using pressure and its range-difference matrices constructed from vertical line array data.The proposed method was validated using simulated data.In addition,modes were successfully extracted from ambient noise.

Differential pressure difference based altitude control of a stratospheric satellite

An autonomous altitude adjustment system for a stratospheric satellite(StratoSat)platform is proposed.This platform consists of a helium balloon,a ballonet,and a two-way blower.The helium balloon generates lift to balance the platform gravity.The two-way blower inflates and deflates the ballonet to regulate the buoyancy.Altitude adjustment is achieved by tracking the differential pressure difference(DPD),and a threshold switching strategy is used to achieve blower flow control.The vertical acceleration regulation ability is decided not only by the blower flow rate,but also by the designed margin of pressure difference(MPD).Pressure difference is a slow-varying variable compared with altitude,and it is adopted as the control variable.The response speed of the actuator to disturbance can be delayed,and the overshoot caused by the large inertia of the platform is inhibited.This method can maintain a high tracking accuracy and reduce the complexity of model calculation,thus improving the robustness of controller design.

TSCND:Temporal Subsequence-Based Convolutional Network with Difference for Time Series Forecasting

Time series forecasting plays an important role in various fields, such as energy, finance, transport, and weather. Temporal convolutional networks (TCNs) based on dilated causal convolution have been widely used in time series forecasting. However, two problems weaken the performance of TCNs. One is that in dilated casual convolution, causal convolution leads to the receptive fields of outputs being concentrated in the earlier part of the input sequence, whereas the recent input information will be severely lost. The other is that the distribution shift problem in time series has not been adequately solved. To address the first problem, we propose a subsequence-based dilated convolution method (SDC). By using multiple convolutional filters to convolve elements of neighboring subsequences, the method extracts temporal features from a growing receptive field via a growing subsequence rather than a single element. Ultimately, the receptive field of each output element can cover the whole input sequence. To address the second problem, we propose a difference and compensation method (DCM). The method reduces the discrepancies between and within the input sequences by difference operations and then compensates the outputs for the information lost due to difference operations. Based on SDC and DCM, we further construct a temporal subsequence-based convolutional network with difference (TSCND) for time series forecasting. The experimental results show that TSCND can reduce prediction mean squared error by 7.3% and save runtime, compared with state-of-the-art models and vanilla TCN.

Deep reinforcement learning using least-squares truncated temporal-difference

Policy evaluation(PE)is a critical sub-problem in reinforcement learning,which estimates the value function for a given policy and can be used for policy improvement.However,there still exist some limitations in current PE methods,such as low sample efficiency and local convergence,especially on complex tasks.In this study,a novel PE algorithm called Least-Squares Truncated Temporal-Difference learning(LST2D)is proposed.In LST2D,an adaptive truncation mechanism is designed,which effectively takes advantage of the fast convergence property of Least-Squares Temporal Difference learning and the asymptotic convergence property of Temporal Difference learning(TD).Then,two feature pre-training methods are utilised to improve the approximation ability of LST2D.Furthermore,an Actor-Critic algorithm based on LST2D and pre-trained feature representations(ACLPF)is proposed,where LST2D is integrated into the critic network to improve learning-prediction efficiency.Comprehensive simulation studies were conducted on four robotic tasks,and the corresponding results illustrate the effectiveness of LST2D.The proposed ACLPF algorithm outperformed DQN,ACER and PPO in terms of sample efficiency and stability,which demonstrated that LST2D can be applied to online learning control problems by incorporating it into the actor-critic architecture.

Study on sex differences and potential clinical value of threedimensional computerized tomography pelvimetry in rectal cancer patients

BACKGROUND Laparoscopic rectal cancer radical surgery is a complex procedure affected by various factors.However,the existing literature lacks standardized parameters for the pelvic region and soft tissues,which hampers the establishment of consistent conclusions.AIM To comprehensively assess 16 pelvic and 7 soft tissue parameters through computerized tomography(CT)-based three-dimensional(3D)reconstruction,providing a strong theoretical basis to address challenges in laparoscopic rectal cancer radical surgery.METHODS We analyzed data from 218 patients who underwent radical laparoscopic surgery for rectal cancer,and utilized CT data for 3D pelvic reconstruction.Specific anatomical points were carefully marked and measured using advanced 3D modeling software.To analyze the pelvic and soft tissue parameters,we emp-loyed statistical methods including paired sample t-tests,Wilcoxon rank-sum tests,and correlation analysis.RESULTS The investigation highlighted significant sex disparities in 14 pelvic bone parameters and 3 soft tissue parameters.Males demonstrated larger measurements in pelvic depth and overall curvature,smaller measurements in pelvic width,a larger mesorectal fat area,and a larger anterior-posterior abdominal diameter.By contrast,females exhibited wider pelvises,shallower depth,smaller overall curvature,and an increased amount of subcutaneous fat tissue.However,there were no significant sex differences observed in certain parameters such as sacral curvature height,superior pubococcygeal diameter,rectal area,visceral fat area,waist circumference,and transverse abdominal diameter.CONCLUSION The reconstruction of 3D CT data enabled accurate pelvic measurements,revealing significant sex differences in both pelvic and soft tissue parameters.This study design offer potential in predicting surgical difficulties and creating personalized surgical plans for male rectal cancer patients with a potentially“difficult pelvis”,ultimately improving surgical outcomes.Further research and utilization of these parameters could lead to enhanced surgical methods and patient care in laparoscopic rectal cancer radical surgery.

Analysis of Extended Fisher-Kolmogorov Equation in 2D Utilizing the Generalized Finite Difference Method with Supplementary Nodes

In this study,we propose an efficient numerical framework to attain the solution of the extended Fisher-Kolmogorov(EFK)problem.The temporal derivative in the EFK equation is approximated by utilizing the Crank-Nicolson scheme.Following temporal discretization,the generalized finite difference method(GFDM)with supplementary nodes is utilized to address the nonlinear boundary value problems at each time node.These supplementary nodes are distributed along the boundary to match the number of boundary nodes.By incorporating supplementary nodes,the resulting nonlinear algebraic equations can effectively satisfy the governing equation and boundary conditions of the EFK equation.To demonstrate the efficacy of our approach,we present three numerical examples showcasing its performance in solving this nonlinear problem.

Keep in mind sex differences when prescribing psychotropic drugs

Women represent the majority of patients with psychiatric diagnoses and also the largest users of psychotropic drugs.There are inevitable differences in efficacy,side effects and long-term treatment response between men and women.Psychopharmacological research needs to develop adequately powered animal and human trials aimed to consider pharmacokinetics and pharmacodynamics of central nervous system drugs in both male and female subjects.Healthcare professionals have the responsibility to prescribe sex-specific psychopharmacotherapies with a priority to differentiate between men and women in order to minimize adverse drugs reactions,to maximize therapeutic effectiveness and to provide personalized management of care.

Finite Difference-Peridynamic Differential Operator for Solving Transient Heat Conduction Problems

Transient heat conduction problems widely exist in engineering.In previous work on the peridynamic differential operator(PDDO)method for solving such problems,both time and spatial derivatives were discretized using the PDDO method,resulting in increased complexity and programming difficulty.In this work,the forward difference formula,the backward difference formula,and the centered difference formula are used to discretize the time derivative,while the PDDO method is used to discretize the spatial derivative.Three new schemes for solving transient heat conduction equations have been developed,namely,the forward-in-time and PDDO in space(FT-PDDO)scheme,the backward-in-time and PDDO in space(BT-PDDO)scheme,and the central-in-time and PDDO in space(CT-PDDO)scheme.The stability and convergence of these schemes are analyzed using the Fourier method and Taylor’s theorem.Results show that the FT-PDDO scheme is conditionally stable,whereas the BT-PDDO and CT-PDDO schemes are unconditionally stable.The stability conditions for the FT-PDDO scheme are less stringent than those of the explicit finite element method and explicit finite difference method.The convergence rate in space for these three methods is two.These constructed schemes are applied to solve one-dimensional and two-dimensional transient heat conduction problems.The accuracy and validity of the schemes are verified by comparison with analytical solutions.

Three-dimensional analysis of age and sex differences in femoral head asphericity in asymptomatic hips in the United States

BACKGROUND The sphericity of the femoral head is a metric used to evaluate hip pathologies and is associated with the development of osteoarthritis and femoral-acetabular impingement.AIM To analyze the three-dimensional asphericity of the femoral head of asymptomatic pediatric hips.We hypothesized that femoral head asphericity will vary significantly between male and female pediatric hips and increase with age in both sexes.METHODS Computed tomography scans were obtained on 158 children and adolescents from a single institution in the United States(8-18 years;50%male)without hip pain.Proximal femoral measurements including the femoral head diameter,femoral head volume,residual volume,asphericity index,and local diameter difference were used to evaluate femoral head sphericity.RESULTS In both sexes,the residual volume increased by age(P<0.05).Despite significantly smaller femoral head size in older ages(>13 years)in females,there were no sex-differences in residual volume and aspherity index.There were no age-related changes in mean diameter difference in both sexes(P=0.07)with no significant sex-differences across different age groups(P=0.06).In contrast,there were significant increases in local aspherity(maximum diameter difference)across whole surface of the femoral head and all quadrants except the inferior regions in males(P=0.03).There were no sex-differences in maximum diameter difference at any regions and age group(P>0.05).Increased alpha angle was only correlated to increased mean diameter difference across overall surface of the femoral head(P=0.024).CONCLUSION There is a substantial localized asphericity in asymptomatic hips which increases with age in.While 2D measured alpha angle can capture overall asphericity of the femoral head,it may not be sensitive enough to represent regional asphericity patterns.

Analysis of Regional Difference of Agricultural Land Productivity in Heilongjiang Province

The sustenance of humanity is contingent upon the production of food.The foundation of this production is agriculture,which in turn is dependent upon the cultivation of the land.As a fundamental element of agricultural advancement,the rational development and utilization of land play a pivotal role in the process of rural revitalization.Agricultural land productivity serves as a principal indicator of the efficacy of land utilization and the extent of agricultural advancement.Nevertheless,there is a paucity of research examining the productivity of agricultural land,particularly a lack of specialized research on large agricultural provinces.In light of the aforementioned considerations,this paper presents a comprehensive examination of agricultural land productivity and its regional variations in Heilongjiang Province in 2022,with the aid of pertinent statistical data.The findings of the analysis indicate that among the prefecture-level cities,Daqing and Suihua exhibit the highest levels of agricultural land productivity.Additionally,Zhaodong City,Zhaozhou,Qinggang,Wangkui,and Lanxi counties exhibit high levels of agricultural land productivity within their respective prefecture-level cities.There are notable disparities in agricultural land productivity across various regions,including Yichun,Heihe,Harbin,Daqing,Hegang,and Suihua.In contrast,other regions demonstrate a more balanced spatial distribution.In order to facilitate the prosperous development of the agricultural industry in Heilongjiang Province,it is essential to optimize the spatial planning of the land,to investigate the potential for agricultural development in each region,to establish effective collaboration between resources and industries,and to create a development synergy that will collectively advance rural revitalization.

Emotional differences based on comments on doctor-patient disputes with varying levels of severity

BACKGROUND The risks associated with negative doctor-patient relationships have seriously hindered the healthy development of medical and healthcare and aroused wide-spread concern in society.The number of public comments on doctor-patient relationship risk events reflects the degree to which the public pays attention to such events.Thirty incidents of doctor-patient disputes were collected from Weibo and TikTok,and 3655 related comments were extracted.The number of comment sentiment words was extracted,and the comment sentiment value was calculated.The Kruskal-Wallis H test was used to compare differences between each variable group at different levels of incidence.Spearman’s correlation analysis was used to examine associations between variables.Regression analysis was used to explore factors influencing scores of comments on incidents.RESULTS The study results showed that public comments on media reports of doctor-patient disputes at all levels are mainly dominated by“good”and“disgust”emotional states.There was a significant difference in the comment scores and the number of partial emotion words between comments on varying levels of severity of doctor-patient disputes.The comment score was positively correlated with the number of emotion words related to positive,good,and happy)and negatively correlated with the number of emotion words related to negative,anger,disgust,fear,and sadness.CONCLUSION The number of emotion words related to negative,anger,disgust,fear,and sadness directly influences comment scores,and the severity of the incident level indirectly influences comment scores.

Efficient Finite Difference WENO Scheme for Hyperbolic Systems withNon-conservativeProducts

Higher order finite difference weighted essentially non-oscillatory(WENO)schemes have been constructed for conservation laws.For multidimensional problems,they offer a high order accuracy at a fraction of the cost of a finite volume WENO or DG scheme of the comparable accuracy.This makes them quite attractive for several science and engineering applications.But,to the best of our knowledge,such schemes have not been extended to non-linear hyperbolic systems with non-conservative products.In this paper,we perform such an extension which improves the domain of the applicability of such schemes.The extension is carried out by writing the scheme in fluctuation form.We use the HLLI Riemann solver of Dumbser and Balsara(J.Comput.Phys.304:275-319,2016)as a building block for carrying out this extension.Because of the use of an HLL building block,the resulting scheme has a proper supersonic limit.The use of anti-diffusive fluxes ensures that stationary discontinuities can be preserved by the scheme,thus expanding its domain of the applicability.Our new finite difference WENO formulation uses the same WENO reconstruction that was used in classical versions,making it very easy for users to transition over to the present formulation.For conservation laws,the new finite difference WENO is shown to perform as well as the classical version of finite difference WENO,with two major advantages:(i)It can capture jumps in stationary linearly degenerate wave families exactly.(i)It only requires the reconstruction to be applied once.Several examples from hyperbolic PDE systems with non-conservative products are shown which indicate that the scheme works and achieves its design order of the accuracy for smooth multidimensional flows.Stringent Riemann problems and several novel multidimensional problems that are drawn from compressible Baer-Nunziato multiphase flow,multiphase debris flow and twolayer shallow water equations are also shown to document the robustness of the method.For some test problems that require well-balancing we have even been able to apply the scheme without any modification and obtain good results.Many useful PDEs may have stiff relaxation source terms for which the finite difference formulation of WENO is shown to provide some genuine advantages.

Stability and accuracy of central difference method for real-time dynamic substructure testing considering mass participation coefficient

For real-time dynamic substructure testing(RTDST),the influence of the inertia force of fluid specimens on the stability and accuracy of the integration algorithms has never been investigated.Therefore,this study proposes to investigate the stability and accuracy of the central difference method(CDM)for RTDST considering the specimen mass participation coefficient.First,the theory of the CDM for RTDST is presented.Next,the stability and accuracy of the CDM for RTDST considering the specimen mass participation coefficient are investigated.Finally,numerical simulations and experimental tests are conducted for verifying the effectiveness of the method.The study indicates that the stability of the algorithm is affected by the mass participation coefficient of the specimen,and the stability limit first increases and then decreases as the mass participation coefficient increases.In most cases,the mass participation coefficient will increase the stability limit of the algorithm,but in specific circumstances,the algorithm may lose its stability.The stability and accuracy of the CDM considering the mass participation coefficient are verified by numerical simulations and experimental tests on a three-story frame structure with a tuned liquid damper.

Influences of clean fracturing fluid viscosity and horizontal in-situ stress difference on hydraulic fracture propagation and morphology in coal seam

The viscosity of fracturing fluid and in-situ stress difference are the two important factors that affect the hydraulic fracturing pressure and propagation morphology. In this study, raw coal was used to prepare coal samples for experiments, and clean fracturing fluid samples were prepared using CTAB surfactant. A series of hydraulic fracturing tests were conducted with an in-house developed triaxial hydraulic fracturing simulator and the fracturing process was monitored with an acoustic emission instrument to analyze the influences of fracturing fluid viscosity and horizontal in-situ stress difference on coal fracture propagation. The results show that the number of branched fractures decreased, the fracture pattern became simpler, the fractures width increased obviously, and the distribution of AE event points was concentrated with the increase of the fracturing fluid viscosity or the horizontal in-situ stress difference. The acoustic emission energy decreases with the increase of fracturing fluid viscosity and increases with the increase of horizontal in situ stress difference. The low viscosity clean fracturing fluid has strong elasticity and is easy to be compressed into the tip of fractures, resulting in complex fractures. The high viscosity clean fracturing fluids are the opposite. Our experimental results provide a reference and scientific basis for the design and optimization of field hydraulic fracturing parameters.

Temporal and spatial differences in human activities performed in Urban Green Spaces of Vilnius(Lithuania)

Urban green spaces(UGS)are relevant to city well-being,as recognized by the United Nations’Sustainable Development Goals(SDGs).However,few studies have studied the temporal use of UGS.This work assessed the seasonal,weekly,and daily use of three urban green spaces(Vingis Park,Bernardino Garden,and Jomantas Park)in Vilnius(Lithuania).The study is based on an on-site observation-based survey,which recorded users’characteristics,activities,and weather conditions during summer and winter.The results showed that UGS’s seasonal,weekly,and daily use differed according to park and users’characteristics.Parks with a higher diversity of facilities had a high seasonal difference in the number of observed activities.User numbers were higher in the summer for activities with children,social activities,sports,and water activities than in the winter.Jomantas Park had the lowest variability in user characteristics.Weather variables were linked to changes in users’activities.Higher precipitation and lower temperature were associated with reducing the number of users and the diversity of registered activities.Most of the stationary activities were observed during summer.The diversity of the observed activities was associated with the available facilities rather than the park size.The distribution of stationary activities was spatially correlated with facility/equipment(benches,playgrounds,sports,and fitness equipment)and proximity to water features.The results of this study are relevant for UGS design,planning,and management.

A High Order Accurate Bound-Preserving Compact Finite Difference Scheme for Two-Dimensional Incompressible Flow

For solving two-dimensional incompressible flow in the vorticity form by the fourth-order compact finite difference scheme and explicit strong stability preserving temporal discretizations,we show that the simple bound-preserving limiter in Li et al.(SIAM J Numer Anal 56:3308–3345,2018)can enforce the strict bounds of the vorticity,if the velocity field satisfies a discrete divergence free constraint.For reducing oscillations,a modified TVB limiter adapted from Cockburn and Shu(SIAM J Numer Anal 31:607–627,1994)is constructed without affecting the bound-preserving property.This bound-preserving finite difference method can be used for any passive convection equation with a divergence free velocity field.

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.