Values Of Control Parameters Research Articles

Bump Attractors and Waves in Networks of Leaky Integrate-and-Fire Neurons

Bump attractors are wandering localised patterns observed in in vivo experiments of spatially-extended neurobiological networks. They are important for the brain's navigational system and specific memory tasks. A bump attractor is characterised by a core in which neurons fire frequently, while those away from the core do not fire. We uncover a relationship between bump attractors and travelling waves in a classical network of excitable, leaky integrate-and-fire neurons. This relationship bears strong similarities to the one between complex spatiotemporal patterns and waves at the onset of pipe turbulence. Waves in the spiking network are determined by a firing set, that is, the collection of times at which neurons reach a threshold and fire as the wave propagates. We define and study analytical properties of the voltage mapping, an operator transforming a solution's firing set into its spatiotemporal profile. This operator allows us to construct localised travelling waves with an arbitrary number of spikes at the core, and to study their linear stability. A homogeneous "laminar" state exists in the network, and it is linearly stable for all values of the principal control parameter. Sufficiently wide disturbances to the homogeneous state elicit the bump attractor. We show that one can construct waves with a seemingly arbitrary number of spikes at the core; the higher the number of spikes, the slower the wave, and the more its profile resembles a stationary bump. As in the fluid-dynamical analogy, such waves coexist with the homogeneous state, are unstable, and the solution branches to which they belong are disconnected from the laminar state; we provide evidence that the dynamics of the bump attractor displays echoes of the unstable waves, which form its building blocks.

Complete and robust energy conversion by sum frequency generation based on invariant engineering.

An analytical method is proposed in this paper to achieve complete energy conversion in sum frequency generation based on the Lewis-Riesenfeld invariants theory. In the proposed scheme, a quasi-adiabatic single control parameter model is established, and the value of single control parameter is selected to make the initial eigenstate perfectly converted to the final eigenstate as needed. Corresponding to the nonlinear frequency conversion process, a nonlinear crystal structure is designed by inverse engineering using the optimal control theory. It is robust against perturbations of the coupling coefficient and phase mismatch, including variations in the pump intensity and crystal polarization period, and achieves almost 100% conversion efficiency at any crystal length. Theoretical simulations show that frequency conversion can be achieved in the wavelength range of 2.6 µm-3.6 µm, and the spectral bandwidth of conversion efficiency exceeds 50% and approaches 400 nm when the crystal length L = 1 mm.

Integrated control policies of production, returns’ replenishment and inspection for unreliable hybrid manufacturing-remanufacturing systems with a quality constraint

This paper deals with the production planning and control problem within unreliable Hybrid Manufacturing-Remanufacturing Systems (HMRSs) evolving in a stochastic and dynamic environment. The customer demand can then be fulfilled by either manufacturing of new units or remanufacturing of returned ones. However, both used materials and returns may contain a fraction of defective items. The paper investigates how companies could benefit from such integrated control policy to assist their managers in determining production rates, the sequence and the size of replenishment orders as well as their sample size to be inspected. The corresponding problem aims to propose an efficient control policy integrating four central decisions to coordinate remanufacturing, manufacturing, replenishment of returns and their quality control while minimizing the total cost and satisfying a quality constraint requested by customers. A simulation-based optimization approach is used to tackle the problem. It aims to determine the optimal values of control parameters of the proposed policy minimizing the total cost. The results provide relevant insights and bring effective solutions to help decision makers manage simultaneously manufacturing, remanufacturing, replenishment of returns and their quality control activities. A comparative study is also performed showing that our policy, based on sampling inspection of delivered returns, outperforms in terms of costs those most used in the literature where complete (i.e. 100%) or no inspection strategies are used.

Oscillatory and chaotic regimes of patterns and dark cavity solitons in cavities displaying EIT: Static multihead dual chimera states

Oscillating and chaotic regimes of honeycomb patterns and dark cavity solitons are studied in a cavity displaying electromagnetically induced transparency. Considering a three-level atomic system in a Λ configuration, transition to chaotically oscillating honeycombs is numerically investigated and their dynamical behavior is detailed for different control parameter values. We show that a branch of oscillating dark cavity solitons coexists with the honeycomb patterns. These oscillating cavity solitons are studied individually and in mutual interaction. In particular, it is shown that mutually coherent oscillating dark cavity solitons can be obtained by choosing an appropriate separation distance. Finally, we introduce a novel regime of chimera states consisting of a multitude of identically and non-locally coupled dark cavity solitons in which regions of in-phase and anti-phase coherence separated by incoherent areas coexist and are stationary. We discuss the unique features of these structures and categorize them as static multihead dual chimera states. We believe that this is the first time that such chimeric states are reported in a photonic system hosting oscillating and chaotic structures.

Modeling-Based Design of the Control Pattern for Uniform Macrostep Morphology in Solution Growth of SiC

In the solution growth of the SiC crystal, macrosteps with sufficient height on an off-axis substrate are required to reduce defects and achieve a high-quality grown layer. However, over-developed macrosteps can induce new defects and adversely affect the crystal quality. To better understand and control the behavior of macrosteps corresponding to the control parameters of the growth system, a simulation method that consists of a global two-dimensional computational fluid dynamic (CFD) model, a local three-dimensional CFD model near the growth front, and a kinetics model that describes the movement of macrosteps on the crystal surface is proposed. The simulation method is first applied to investigate the effect of the crystal rotation speed on macrostep morphology. Although the results indicate that a higher crystal rotation speed results in less step bunching, constantly rotating the crystal in one direction is demonstrated to be incapable of yielding a uniform macrostep distribution on the whole surface. Accordingly, a sophisticated control pattern is designed by periodically switching the flow direction underneath the crystal surface, where the proposed simulation method is critical to determine detailed control-parameter values. When the control pattern suggested by the simulation is used, a grown crystal with a uniform macrostep morphology and ideal step height on the whole surface is obtained in the practical experiment.

An Improved Chaos Driven Hybrid Differential Evolutionand Butterfly Optimization Algorithm for Passive Target Localization Using TDOA Measurements

This paper addresses the problem of time difference of arrival (TDOA) based passive target localizationand proposes an improved chaos-driven hybrid differential evolution (DE) algorithm and butterfly optimization algorithm (BOA), named ICDEBOA, to solve this complex optimization problem. The proposed algorithm consists of a new mutation strategy with the mechanisms of the BOA algorithm incorporated into the DE algorithm. To boost optimization effectiveness, chaos theory is employed to adjust the control parameter values. The considered localization problem is formulated using the maximum likelihood estimator. To perform the accuracy comparison, the convex constrained weighting least squares algorithm is applied to the considered localization problem as the widely used method in literature. The statistical analysis shows that the proposed modifications to the ICDEBOA algorithm improve its optimization performance, as demonstrated by the improved performance on the CEC2014 benchmark problems. The ICDEBOA algorithm is also shown to be more robust than existing algorithms in noisy environments. Numerical simulation results show that the proposed ICDEBOA algorithm meets the CRLB and achieves better performance than the CWLS, DE, and BOA algorithms.

The task of technological adjustment of an axial-rotor type grain combine

One of the promising approaches to improve the efficiency and effectiveness of the harvesting process of grain crops using a combine method is the use of an intelligent information system in the form of a decision support system. The expansion of the use of high-performance rotary-type combines in production conditions puts the task of optimal technological adjustment of the working bodies and the entire combine as a whole into the category of topical ones. When performing harvesting work with an axial-rotary threshing and separating device (ARTSD), as a result of continuously changing external harvesting factors, deviations in the values of work quality indicators from acceptable values are possible. For their timely elimination, it is important to know the relationships between the groups of signs: “environmental factors - parameters of the working bodies - indicators of the quality of work.” The lack of knowledge leads to non-optimal decisions on the choice of specific values of the controlled parameters and, as a result, to the loss of grain and other resources. To select the optimal strategy for managing the technological process of harvesting using a rotary harvester, we propose a new approach based on the use of an intelligent information system (expert system), which corresponds to the concept of intellectualization of a new type of machine. The article presents the results of research into the process of technological adjustment of a rotary harvester, as well as an analysis of the empirical knowledge of experts with extensive production experience in operating combines of this type. The concepts of parameters, causes and methods for eliminating violations of the technological process are introduced. As a result of expert analysis, decision trees were formed for the first time, on the basis of which the rules of the knowledge base are formulated. To create a knowledge base, it is proposed to use a production model of knowledge. An example of constructing a decision tree when searching for the cause of the appearance of one of the external signs of a violation of the quality of the work of a rotary harvester is given. A fragment of the system of production rules for solving the problem of adjusting the values of control parameters is presented.

Training Neuro-Fuzzy by Using Meta-Heuristic Algorithms for MPPT

It is one of the topics that have been studied extensively on maximum power point tracking (MPPT) recently. Traditional or soft computing methods are used for MPPT. Since soft computing approaches are more effective than traditional approaches, studies on MPPT have shifted in this direction. This study aims comparison of performance of seven meta-heuristic training algorithms in the neuro-fuzzy training for MPPT. The meta-heuristic training algorithms used are particle swarm optimization (PSO), harmony search (HS), cuckoo search (CS), artificial bee colony (ABC) algorithm, bee algorithm (BA), differential evolution (DE) and flower pollination algorithm (FPA). The antecedent and conclusion parameters of neuro-fuzzy are determined by these algorithms. The data of a 250 W photovoltaic (PV) is used in the applications. For effective MPPT, different neuro-fuzzy structures, different membership functions and different control parameter values are evaluated in detail. Related training algorithms are compared in terms of solution quality and convergence speed. The strengths and weaknesses of these algorithms are revealed. It is seen that the type and number of membership function, colony size, number of generations affect the solution quality and convergence speed of the training algorithms. As a result, it has been observed that CS and ABC algorithm are more effective than other algorithms in terms of solution quality and convergence in solving the related problem.

The effects of hair-cell polarity on the dynamics of two coupled hair-cell bundles of the inner ear

Hair cells are the sensory receptors of the auditory and vestibular systems. A bundle of cilia situated atop each hair cell, termed the hair-cell bundle, is deflected upon an impinging of a mechanical force. This modulates the open probability of mechanically gated ion channels and subsequently alters the hair cell’s membrane potential. Owing to the asymmetry in the hair bundle’s geometry, individual hair cells are polarized and display the maximal response to a force applied toward a direction that opens the ion channels. The auditory organs of most vertebrates comprise primarily of hair cells with identical polarity, whereas hair cells of the vestibular organs are organized in two opposing polarities. To understand the advantages of the bi-polarity arrangement of vestibular hair cells, we employed the theoretical framework that describes each hair-cell bundle as an active nonlinear oscillator displaying a Hopf bifurcation. Our results from numerical simulations revealed that coupling of two hair-cell bundles with opposite polarities significantly altered the value of the critical control parameter at a Hopf bifurcation. When driven by a step force, coupled hair-cell bundles with identical polarities displayed a maximal displacement in the direction which closed the ion channels. On the other hand, reversing the polarity of a hair-cell bundle rendered the system sensitive to bi-directional step forces. Lastly, we showed that coupling hair-cell bundles with opposite polarities did not significantly alter the response to sinusoidal forces.

Influence of the occurrence and duration of partial remission on short-term metabolic control in type 1 diabetes: the DIABHONEY pediatric study.

To evaluate the residual effect of partial remission (PR) on immediate post-PR glycemic control according to its occurrence and duration in a cohort of children with type 1 diabetes mellitus (T1DM). Values of glycemic control parameters [i.e. HbA1C, insulin dose-adjusted hemoglobin A1C (IDAA1C), glycemic target-adjusted HbA1C (GTAA1C)] and data from glucose monitoring devices from 189 pediatric patients with new-onset type 1 diabetes were collected retrospectively from 24 months. Patients were characterized according to their remission status (PR+ and PR-). PR+ patients were subdivided into three subgroups regarding PR duration [i.e. short (⩾3-⩽6 months), intermediate (>6-⩽12 months), and long PR (>12-⩽14 months)]. We compared glycemic control data from each PR+ subgroup at +6 and +12 months post-PR with PR- patients at the same postdiagnosis time. Second, PR+ subgroups were compared with each other. PR+ patients showed improved glycemic control (i.e. HbA1C, IDAA1C, and GTAA1C) at + 6 months post-PR when compared with nonremitters (PR-), independently of the PR duration subgroups (p < 0.05). Interestingly, patients in long PR+ subgroup exhibited higher positive residual effect than short PR+ subgroup with lower GTAA1C scores (p = 0.02), better time in range (TIR) (p = 0.003), less time in hypoglycemia (10.45 versus 16.13%, p = 0.03) and less glycemic variability (83.1 mg/dl versus 98.84 mg/dl, p = 0.03). No significant differences were found for glucose control between PR+ and PR- patients at +12 months post-PR. This study supports the positive impact of PR occurrence and duration on short-term metabolic control (better HbA1C levels, IDAA1C and GTAA1C scores, TIR, and less glycemic variability) with the residual effect increasing according to PR duration.

Adaptive Fractional‐Order Super‐Twisting Sliding Mode Controller for Lower Limb Rehabilitation Exoskeleton in Constraint Circumstances Based on the Grey Wolf Optimization Algorithm

In this work, a lower limb exoskeleton with uncertainties and external disturbances under constrained motion has been controlled by developing a model‐free adaptive optimal fractional‐ordersuper‐twisting sliding mode (AOFSTSM) controller. Contrary to popular existing modeling methods, the modeling of the lower limb exoskeleton has been accomplished in the case of contact with the ground. A fractional‐order operator and super‐twisting sliding mode control have been combined to achieve an excellent tracking performance, chatter‐free control inputs, and robustness to external disturbances and uncertainties. The controller structure is model‐independent which has been derived without needing to know the dynamics of the system. An adaptive control strategy has been adopted as an approximating method to evaluate the uncertain dynamics of the system without the necessity for knowing the prior knowledge of the upper bounds. A grey wolf optimization technique has been used to find the optimal values of controller parameters. The stability of the overall system has been investigated and derived from the Lyapunov stability criterion. To validate the effectiveness of our proposed controller structure, a series of comparative simulations have been conducted with optimal fractional‐order super‐twisting sliding mode (OFSTSM) controller and fractional‐order super‐twisting sliding mode (FSTSM) controller. The comparative simulations have been also carried out with other types of recently existing control methods and recently existing optimization algorithms. The results of numerical simulations indicate the superiority of the AOFSTSM controller over other types of recently existing optimization algorithms and controllers in terms of tracking error and robustness towards the uncertainties and external disturbances.

О выборе областей с доминирующим типом зависимости при анализе данных производственного контроля

The formation of representative databases determines the interest in forecasting and managing the quality of metal based on data mining using special software products often based on regression analysis and not always taking into account the statistical nature of an object of study itself. This can lead to misinterpretation of the results or incomplete extracted information reducing the efficiency of statistical processing. Based on the analysis of the production database of the technology for producing 13G1S-U sheet steel, the authors evaluated the possibilities of multiple linear regression for predicting the quality of a steel sheet. The study shows that the type of distribution of the values of control parameters, the distribution nature of which was estimated based on the determination of the skewness and kurtosis coefficients, limits the regression forecast depth. Due to the great deviation of the predicted models from the experimental values in the right tail area of the distribution of the impact strength values, in this work, the authors developed the methods for separating data arrays and proposed criteria to compare the obtained results. To assess the accuracy of the results obtained, arrays with a deliberately asymmetric distribution were selected from the initial sample, against which the statistical characteristics were also compared. Based on the proposed techniques, the authors identified the dominant chemical elements that contribute to the difference in the distribution of the values of acceptance properties existing within the same standard technology. The study shows that the proposed separation method can be used as a variation of cognitive graphics techniques to identify areas with a dependence dominant type based on the correlation of skewness and kurtosis coefficients.

Intelligent Networked Control of Vasoactive Drug Infusion for Patients with Uncertain Sensitivity

Abnormal high blood pressure or hypertension is still the leading risk factor for death and disability worldwide. This paper presents a new intelligent networked control of medical drug infusion system to regulate the mean arterial blood pressure for hypertensive patients with different health status conditions. The infusion of vasoactive drugs to patients endures various issues, such as variation of sensitivity and noise, which require effective and powerful systems to ensure robustness and good performance. The developed intelligent networked system is composed of a hybrid control scheme of interval type-2 fuzzy (IT2F) logic and teaching-learning-based optimization (TLBO) algorithm. This networked IT2F control is capable of managing the uncertain sensitivity of the patient to anti-hypertensive drugs successfully. To avoid the manual selection of control parameter values, the TLBO algorithm is mainly used to automatically find the best parameter values of the networked IT2F controller. The simulation results showed that the optimized networked IT2F achieved a good performance under external disturbances. A comparative study has also been conducted to emphasize the outperformance of the developed controller against traditional PID and type-1 fuzzy controllers. Moreover, the comparative evaluation demonstrated that the performance of the developed networked IT2F controller is superior to other control strategies in previous studies to handle unknown patients’ sensitivity to infused vasoactive drugs in a noisy environment.

Safety action over oscillations of a beam excited by moving load via a new active vibration controller.

This paper presents a mixed active controller (NNPDCVF) that combines cubic velocity feedback with a negative nonlinear proportional derivative to reduce the nonlinear vibrating behavior of a nonlinear dynamic beam system. Multiple time-scales method treatment is produced to get the mathematical solution of the equations for the dynamical modeling with NNPDCVF controller. This research focuses on two resonance cases which are the primary and 1/2 subharmonic resonances. Time histories of the primary system and the controller are shown to demonstrate the reaction with and without control. The time-history response, as well as the impacts of the parameters on the system and controller, are simulated numerically using the MATLAB program. Routh-Hurwitz criterion is used to examine the stability of the system under primary resonance. A numerical simulation, using the MATLAB program software, is obtained to show the time-history response, the effect of the parameters on the system and the controller. An investigation is done into how different significant effective coefficients affect the resonance's steady-state response. The results demonstrate that the main resonance response is occasionally impacted by the new active feedback control's ability to effectively attenuate amplitude. Choosing an appropriate control Gaining quantity can enhance the effectiveness of vibration control by avoiding the primary resonance zone and unstable multi-solutions. Optimum control parameter values are calculated. Validation curves are provided to show how closely the perturbation and numerical solutions are related.

Comparative Characteristics of Quality Parameters of Waters of the Oka River in Places of Water Intake of Utility and Drinking Water System in Ryazan

INTRODUCTION: Surface water sources play an important role in supply of large cities with water. Their waters are subject to anthropogenic pollution with different chemical compounds which may be significant risk factors for the health of the population. The article presents the results of comparative sanitary-hygienic characteristics of the water quality of the Oka river in places of water intake of utility and drinking water supply system of Ryazan. Being the only surface source of water supply, the Oka river provides 53% of the total water consumption of the Ryazan population, therefore a rational choice of the place of water intake can have a considerable impact on the effectiveness of water conditioning and purification and on the final quality of drinking water.&#x0D; AIM: To give a comparative sanitary-hygienic characteristic of the water quality of the Oka river in places of the water intake of the utility and drinking water supply system of Ryazan.&#x0D; MATERIALS AND METHODS: A comparative evaluation of the water quality of the Oka river, as a surface source of water supply, was carried out based on the average long-term values of control parameters (organoleptic, microbiological, chemical) and the proportion of samples that do not meet hygienic standards in the sections of three water intakes in Ryazan in 20122019. The average parameters were compared by the method of variance analysis; for paired comparisons, Scheffe and Tamhein criteria were used, taking into account the results of Levene test. The statistical parameters were calculated in SPSS Statistics 19 program.&#x0D; RESULTS: The chemical composition of the Oka river water was characterized by the greatest pollution with iron (2+) and aluminum. The water of Oksky and Borkovskoy water intakes was characterized by higher average concentrations of iron (2+) and ammonia, as well as greater contamination with generalized and thermotolerant coliform bacteria, compared with the water of Sokolovsky water intake.&#x0D; CONCLUSION: A lower initial quality of the water in Oksky and Borkovskoy water intakes may be due to their location in the 'blind' river course characterized by the processes of eutrophication and slowed down water exchange. High concentrations of iron (2+) may be associated with supply of stream water from the underground sources or with anthropogenic pollution.

РЕШЕНИЕ ЗАДАЧИ РАЗМЕЩЕНИЯ ЭЛЕМЕНТОВ ЭВА НА ОСНОВЕ ИНТЕГРАЦИИ МЕТОДОВ ЭВОЛЮЦИОННОГО ПОИСКА И НЕЧЕТКОГО УПРАВЛЕНИЯ

The problem of elements placement in digital computing equipment are consider in the article.The analysis of the current state of research on this topic is carried out, the relevance of theproblem under consideration is noted. The importance of developing new effective methods forsolving engineering design problems is emphasized. The prospects of developing and using hybrid approaches and models for solving complex semi-formalized design and optimization problems arenoted. The statement of the problem of placement of circuit elements of digital computing equipmentis given. The importance of a qualitative solution of the placement problem from the point of view ofthe successful implementation of the subsequent stages of design is noted. The analysis of variousapproaches and algorithms for solving the placement problem is carried out. Options for choosingvarious criteria for assessing the quality of placement are given. A complex additive criterion forassessing the quality of placement is proposed. The objective function and limitations of the consideredplacement problem as an optimization problem are given. A hybrid approach to solving theplacement problem is proposed. To increase the efficiency and reduce the running time of the algorithm,a model of a parallel multipopulation genetic algorithm is proposed. To synchronize evolutionaryprocesses in a multipopulation genetic algorithm, a modified migration operator has beendeveloped. An analysis of the efficiency of the proposed migration operator has been carried out andrecommendations for its use have been formulated. In order to increase the speed of the algorithm forsolving the placement problem, a model for organizing parallel evolutionary computations throughthe use of multithreading at the local level is proposed. The principles of operation of the fuzzy controlmodule are described. The procedure of logical inference using the rule base is described.The structure of a multilayer neural network that implements the Gaussian function is proposed.A model of a fuzzy logic controller for dynamically changing the values of control parameters of agenetic algorithm is proposed. The control parameters of the fuzzy logic controller are determined.The proposed hybrid algorithm is implemented as an application program. A series of computationalexperiments were carried out to determine the efficiency of the developed algorithm and to select theoptimal values of the control parameters.

APPLICATION OF HOMOTOPY ANALYSIS METHOD (HAM) TO THE NON-LINEAR KDV EQUATIONS

In this work, approximate analytic solutions for different types of KdV equations are obtained using the homotopy analysis method (HAM). The convergence control parameter h helps us to adjust the convergence region of the approximate analytic solutions. The solutions are obtained in the form of power series. The obtained solutions and the exact solutions are shown graphically, highlighting the effects of non-linearity. We have compared the approximate analytical results which are determined by HAM, with the exact solutions and shown graphically with their absolute errors. By choosing an appropriate value of the convergence control parameter, we can obtain the solution in few iterations. All the computations have been performed using the software package MATHEMATICA.

INFLUENCES OF THE GAIN COEFFICIENT ON THE NONLINEAR OSCILLATOR’S DYNAMICAL REGIMES OF MACH-ZEHNDER MODULATOR MZM WITH OPTOELECTRONIC FEEDBACK

In this research we have modeled the Mach-Zehnder Modulator MZM with optoelectronic feedback OEF as optoelectronic oscillator OEO. The model is based on the Integro-Differential equation, which includes nonlinear effects from MZM device with time delay feedback arise from optoelectronic feedback OEF. Numerical simulation of our OEO model demonstrated wide regimes of complex oscillations, ranged from period one, period doubling, mixed mode, quasi-period and chaotic oscillations, that is with increasing the value of the linear gain coefficient. This effect was verified by the bifurcation diagram of maxima values of RF-voltages versus control parameter which in this case is the linear gain coefficient value, which depicted the route to chaos of OEO system. Keywords: Optoelectronic Feedback, Optoelectronic Oscillator, Chaos Control

Multidisciplinary optimization-based path planning for underwater gliders executing multi-point exploration missions

The underwater glider is an energy-saving autonomous observation platform for long-term ocean exploration missions. In this paper, we carry out theoretical research to solve the path planning problem for multi-point exploration missions of underwater gliders. First, performance evaluation models of the glider are established, including the dynamic model, the voyage range and velocity models, and the energy consumption and utilization rate models. Based on the performance evaluation models, a path planning method is proposed to determine the optimal path that can make the glider complete the multi-point exploration mission by consuming less energy and time. The path planning method consists of three steps. In the first step, the surrogate models of performance evaluation parameters are obtained by using the polynomial functions to fit the dynamic simulation results. In the second step, the multi-objective optimization algorithms and the surrogate models are used for determining the control parameter values that can maximize the glider energy utilization rate and voyage velocity simultaneously. Then, under the given path, the correlation between the glider performance and the number of profiles is studied. In the third step of the path planning method, we establish an optimization objective function by using the energy consumption and time consumption of the glider motion. Meanwhile, the path planning problem is regarded as a traveling salesman problem, and it is solved by using the genetic algorithm. Finally, several numerical cases are given to demonstrate the proposed path planning method. The research work can provide certain theoretical guidance for the actual application of underwater gliders.

A two-stage histogram equalization enhancement scheme for feature preservation in retinal fundus images

Early detection of ophthalmologic complications in the retinal fundus images is crucial and requires a quality image for accurate analysis and diagnosis. This often proves tricky due to the visual complexities of some retinal fundus images resulting in over-enhancement, non-uniform contrast, artificial boundaries, abrupt colour change, and other undesirable limitations in the performance of the existing image enhancement methods. In this paper, the uneven illumination and colour balance are globally adjusted using a histogram match. At the same time, the luminance component (V) of the HSV colour space is equalized with CLAHE for local contrast enhancement. Eight control parameter values are investigated to choose the most suitable values to restrict excessive enhancement and control the quality of the enhanced image. The performance of the proposed enhancement algorithm on the STARE, DRIVE, HRF, and DIARETDB1 databases shows that the method can prominently enhance colour retinal fundus images. The visual and quantitative comparisons of the proposed method with state-of-the-art techniques are remarkably outstanding. The statistical analysis test achieves a ρ-value far<0.05 justifying the statistical significance of the quantitative metrics and the high-quality performance of our enhancement framework.