Equalization Method Research Articles

A method of timbral equalization for Ambisonics reproduction with irregular loudspeaker configuration

Ambisonics is a spatial sound reproduction technique based on spatial harmonics decomposition and each order approximation of target sound field. Given a spatial region, Ambisonics is able to reconstruct target sound field accurately up to a frequency limit imposed by Shannon–Nyquist spatial sampling theorem. Above that limit, spatial aliasing in reconstructed sound field occurs, and therefore, timbre equalization in loudspeaker signals is needed to reduce perceived timbre coloration in reproduction. Power equalization is a common and effective method in which the overall power of loudspeaker signals are equalized to be independent of target source direction. The power equalization can be easily implemented in the Ambisonics reproduction with regular rather than loudspeaker configuration. In this study, a method of power equalization for Ambisonics reproduction with irregular loudspeaker configuration is proposed. The fluctuation of overall power of loudspeaker signals with target source direction is controlled within 3 dB by appropriate choice of the decoding coefficients of higher-order spatial harmonics in Ambisonics reproduction. This method is applicable to Ambisonics signals obtained by simulation or microphone array recording. Psychoacoustic experiments indicate that the current method reduces the timbral coloration to some extent while keeps the localization performance in reproduction.

Ni/ZnO@ZSM-5 Reaction Adsorption Desulfurization Catalyst for Octane Number Improvement

Reaction adsorption desulfurization technology is one of the main means of gasoline desulfurization. In this work, ZnO nanoparticles were prepared by pyrolytic oxidation using ZIF-8 as precursor. ZnO spheres with particle size of 5 nm can be formed after the pyrolysis of Zif-8. Ni/ZnO5nm prepared by equal volume impregnation method can achieve 99.2% desulfurization rate at 390°C, which has more excellent desulfurization performance compared to Ni/ZnO100nm. Ni/ZnO@ZSM-5 was synthesized by in-situ growth-pyrolysis oxidation-equal volume impregnation method. In the reaction adsorption desulfurization process of FCC gasoline, the desulfurization rate reached 99.5%, and the aromatic content in the product increased by 10.7 percentage points, showing excellent octane number improvement. This work provides new ideas for the synthesis of ZnO nanoparticles as well as novel reactive adsorbent desulfurizers, and promotes the development of S-Zorb process.

Comparison of Image Enhancement Methods for Diabetic Retinopathy Screening

The most common factor contributing to visual abnormalities that result in blindness is known as diabetic retinopathy (DR). Retinal fundus scanning, a non-invasive method that is integral to the picture pre-processing phase, can be used to identify and monitor DR. Low intensity, irregular lighting, and inhomogeneous color are some of the main issues with DR fundus photographs. Analysis of aberrant characteristics on retinal fundus images to identify diabetic retinopathy is one of the key responsibilities of image enhancement. However, a variety of approaches have been created and it is unknown whether one is best suited for use with images of the retinal fundus. This study investigated various image enhancement methods in order to see aberrant abnormalities on retinal fundus pictures more clearly. This study investigated various image enhancement methods in order to see aberrant abnormalities on retinal fundus pictures more clearly. The contrast-limited adaptive histogram equalization (CLAHE) method, the gray-level slicing method, the median filtering method, and the low light method are image improvement methods used to enhance images of the retinal fundus. The parameters Natural Image Quality Evaluator (NIQE), Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and entropy will be used to assess each image enhancement technique's performance. An ophthalmologist from Sains University Hospital (HUSM) provided the image data. The findings indicate that while each technique has its own benefits, the CLAHE technique, with a standard deviation MSE of 0.0004, is the best.

Optimal oxygen excess ratio tracking of proton exchange membrane fuel cell with uncertainty based on robust model predictive control strategy

AbstractTo address the challenge of tracking the optimal oxygen excess ratio (OER) in the cell stack cathode of the proton exchange membrane fuel cell (PEMFC), which is subject to norm‐bounded parameter uncertainty and frequent external perturbations, this manuscript provides a novel robust model predictive control strategy with a state feedback control structure and hard constraints. We aim to minimize the tracking error of OER while maximizing the net power under varying operational conditions of the PEMFC. Initially, a control‐oriented model for the air supply system is built and its accuracy is validated by comparing it with experimental results. Next, we construct the discrete state‐space equations for optimal control and employ the linear matrix inequality (LMI) method to transform the problem of difficult min‐max optimization solutions into a convex optimization problem with LMI constraints. Finally, the effectiveness of the proposed control algorithm is validated through simulation. The results demonstrate the strong robustness and superiority of the proposed controller against uncertainties in plant parameters for robust OER trajectory tracking. It improves the transient performance through robust precision tracking applications, which will eventually accelerate PEMFC commercialization.

Robust output regulation of a class of smart actuators described by a minimum phase LPV dynamics

This paper presents a new control strategy for a class of minimum phase linear parameter-varying (LPV) systems representative of smart material actuators. In position control applications of such devices, one is typically interested in achieving output regulation with an arbitrary exponential decay rate. In principle, this problem can be tackled by assigning an exponential decay rate to the full system state, by means of well-established linear matrix inequalities (LMI) methods. For the class of systems under investigation, however, this approach leads to excessively large controller gains in case the desired decay rate is faster than the open-loop zero dynamics. In addition, the existence of unmeasurable state variables related to the material microstructure makes it not possible to directly implement full state feedback laws which are commonly adopted in LPV theory. To overcome these issues, a new design strategy is proposed. The key idea relies on arbitrarily shaping the output exponential decay rate without requiring fast convergence of the full state vector. This goal is achieved by means of a partial state feedback control law which solely depends on the measurable system states. A LMI algorithm is also developed to systematically address the design of the partial state feedback controller. The method is validated by means of simulations on generic examples, as well as via experiments on a mechatronic positioning system based on a dielectric elastomer membrane. In case the desired output convergence speed is faster than the open-loop zero dynamics, it is shown that the new approach leads to better transient behaviors and significantly smaller controller gains than standard LPV design techniques.

ОБ АСИМПТОТИЧЕСКОЙ УСТОЙЧИВОСТИ РЕШЕНИЙ ЛИНЕЙНОГО ВОЛЬТЕРРОВА ИНТЕГРО-ДИФФЕРЕНЦИАЛЬНОГО УРАВНЕНИЯ ВТОРОГО ПОРЯДКА В СЛУЧАЕ НЕДИФФЕРЕНЦИРУЕМОСТИ СРЕЗАННЫХ ФУНКЦИЙ

Sufficient conditions are established for the asymptotic stability of any solution of a linear second-order Volterra integro-differential equation in the case when the truncated functions may be non-differentiable at some points of the semiaxis. To do this, first, using a non-standard method of reduction to a system, the equation under consideration is reduced to an equivalent system, and the method of transforming equations and the method of cutting functions are applied to this system. The truncated kernel and free term are associated with the coefficient of the new unknown function using the inequality between the geometric and arithmetic means of two functions. Using the method of integral inequalities, sufficient conditions are established for the boundedness on the semiaxis of all solutions of the system. Then the method of squaring equations is used to the first equation of the system and the Lyusternik-Sobolev lemma is applied. Finally, based on a non-standard substitution, we complete the proof of the asymptotic stability of solutions to a given second-order linear integro-differential equation. An illustrative example is given.

Event‐based reduced‐order H∞$H_{\infty }$ estimation for switched complex networks based on T‐S fuzzy model

AbstractThis paper investigates the design of a reduced‐order filter for a specific class of switched complex network systems with time‐varying delays. To handle the nonlinear components of the complex network, a T‐S fuzzy model is employed to convert them into a set of linear components. To tackle the issue of heavy network load, a memory‐based adaptive trigger mechanism is proposed. In this study, a reduced‐order state estimator is designed using the T‐S fuzzy model. To demonstrate the exponential stability of the error system, a suitable Lyapunov function is constructed based on the Lyapunov stability principle. The parameter matrix of the reduced‐order estimator is determined using the linear matrix inequality and convex linearization method. Additionally, a sufficient condition for the exponential stability of the error system at the suppression level is provided. Finally, the feasibility of the proposed scheme is validated through a simulation experiment.

Study on induction hardening performance of 34CrNi3MoA steel crankshaft

The evolution of the temperature field, microstructure field, and residual stress field of a 34CrNi3MoA steel marine diesel engine crankshaft during medium-frequency induction hardening was studied based on an electromagnetic-thermal-transformation-stress coupled numerical model, which considers the effect of internal stress induced by transformation induced plasticity on residual stress. Using the equal conversion rate method, the austenitizing region of the crankshaft was determined during the induction heating stage. In the quenching stage, the parameters of the phase transformation model are derived from the continuous heating expansion curve and the continuous cooling transformation curve, and the phase transformation kinetics equation is used to analyze the phase transformation process of the crankshaft. The results indicate that extending the heating time can enhance the uniformity of the surface temperature of the crankshaft and the thickness of the hardened layer. The simulation results are validated by measurements of hardened layer, hardness and residual stress, and the simulation results are in good agreement with the experimental results.

Sensitivity Equalization and Dynamic Range Expansion with Multiple Optofluidic Microbubble Resonator Sensors.

A novel multi-optofluidic microbubble resonator (OMBR) sensitivity equalization method is presented that equalizes the sensing signal from different OMBRs. The method relies on the fact that the ratio of the wavelength shifts to the bulk refractive index sensitivity (BRIS) does not depend on the physical dimensions of the OMBR. The proof of concept is experimentally validated and the sensing signals from individual OMBRs can be directly compared. Furthermore, a wide dynamic range of sensing with favorable consistency and repeatability is achieved by piecing together signals from 20 OMBRs for HIV-1 p24 antigen detection from 50 fg/mL to 100 ng/mL (2.1 fM to 4.2 nM), indicating significant potential for practical applications, such as in drug screening and disease diagnosis.

A Study On Hydrogen Production Methods Using the TOPSIS Method

For humanity and social health, energy is essential. Hydrogen is one of several potential energy carriers for green technologies. The Black Sea seas are a rich source of "hydrogen Sulphide (H2S)", which is also a known environmental contaminant. The main drivers of hydrogen technology are global warming and the depletion of fossil fuels. Additionally, the nation's economies that depend on the importation of conventional fuel have been exposed as a result of the rising prices of these fuels due to the rising energy demand. Future renewable technologies need to be carbon-free and renewable to combat climate change on a long-term basis and reduce our reliance on foreign oil. Hydrogen can be produced using a variety of traditional and unconventional sources of energy, including "natural gas, coal, nuclear power, biomass, solar, and wind". The most ecological hydrogen production method using H2S is chosen in this research using the "technique for order of preference by similarity to ideal solution (TOPSIS)", taking into account sustainable factors which are inescapable in energy managerial problems. The "Equal Weights Method (EWM)" allocates weights to many criteria, most notably relevance weights. The rank of alternatives using the TOPSIS method for Thermal is second, Electrochemical is third, Thermochemical is fourth, Photochemical is fifth and Plasma is first. The analysis's findings indicate that plasma is the best and most suitable method for producing hydrogen in terms of delivering high conversion efficiency and environmentally friendly operations, such as handling, shipping, and storing dangerous chemicals.

Energy Efficiency State Identification for Cogeneration Units Based on Benchmark Value

In China, cogeneration units predominantly employ a flexible operation mechanism. However, it is possible that this could lead to a decline in performance and an increase in energy consumption. This paper introduces a methodology that utilizes the data mining technique to ascertain the benchmark value section of the energy efficiency status index for cogeneration units. The equal interval division method is utilized for the purpose of categorizing the operating conditions. The Gaussian mixture model is utilized to ascertain the benchmark value section in relation to the fluctuating operating conditions by estimating the probability of historical data. The methodology is verified by utilizing historical data from a functioning cogeneration unit. The findings suggest that the unit’s total heat consumption can be decreased by 32.5–50 kJ·(kW·h)−1 when compared to the design-based approach.

Boundary Value Problem for a Loaded Pseudoparabolic Equation with a Fractional Caputo Operator

Differential equations containing fractional derivatives, for both time and spatial variables, have now begun to attract the attention of mathematicians and physicists; they are used in connection with these equations as mathematical models of various processes. The fractional derivative equation tool plays a crucial role in describing plenty of natural processes concerning physics, biology, geology, and so on. In this paper, we studied a loaded equation in relation to a spatial variable for a linear pseudoparabolic equation, with an initial and second boundary value condition (the Neumann condition), and a fractional Caputo derivative. A distinctive feature of the considered problem is that the load at the point is in the higher partial derivatives of the solution. The problem is reduced to a loaded equation with a nonlocal boundary value condition. A way to solve the considered problem is by using the method of energy inequalities, so that a priori estimates of solutions for non-local boundary value problems are obtained. To prove that this nonlocal problem is solvable, we used the method of continuation with parameters. The existence and uniqueness theorems for regular solutions are proven.

Novel stability conditions for some generalization of Nicholson's blowflies model with stochastic perturbations

We consider a generalization of the well-known nonlinear Nicholson blowflies model with stochastic perturbations. Stability in probability of the positive equilibrium of the considered equation is studied. Two types of stability conditions: delay-dependent and delay-independent conditions are obtained, using the method of Lyapunov functionals and the method of linear matrix inequalities. The obtained results are illustrated by numerical simulations by means of some examples. The results are new, and complement the existing ones. doi: 10.1017/S1446181123000147

Quantitative Factor Exploration Based on Insider Trading Detection

Factor research has always been the focus of financial quantitative forecasting research. In the existing multi-factor strategies, we have noticed that the combination modes of factors are different and arbitrary. We hope to develop a more accurate and effective multi-factor model by selecting the most common and most interpretable multi-factors and combining them with equal weight method and assigned weights developed by Hidden Markov Model after some optimizations applied to selected multi-factors. At the same time, we noticed that in the existing data information, there are reports or information that reveal the insider trading of related companies. The existing reports show that the abnormal data volume caused by insider trading will make the prediction of the model inaccurate. Therefore, we added insider trading as a factor into our model training through the order imbalance algorithm to obtain more accurate prediction results. The results show that the multi-factor model is interpretable and effective, and its effect is better than the predicted value than that of the single factor model. After adding the related factors of insider trading into the forecast, it has a certain normalization effect on the original predicted value with large deviation, but has little influence on the effect of the original value with small deviation, which proves the effectiveness of our factor based on insider trading.

Brightness segmentation-based plateau histogram equalization algorithm for displaying high dynamic range infrared images

Third-generation thermal cameras produce images with high dynamic range (HDR), low contrast, and blurry edges, which makes them difficult to visualize on traditional display devices. Thus, tone mapping methods are required to adapt the recorded signal to the display in order to maintain, and possibly improve, object’s visibility and contrast. Since the traditional global tone mapping methods cannot take account of the trade-off between clearly displaying the details of dark regions and bright regions of the infrared image, this paper proposes a global tone mapping algorithm based on brightness segmentation for the enhancement and display of HDR infrared images. Firstly, the HDR infrared image is divided into different brightness regions in accordance with the characteristics of the human visual system’s ability to perceive brightness. Secondly, the determination of the boundary value of each brightness region is optimized by combining the gray statistics of the HDR infrared image, to achieve the adaptive brightness region segmentation of the infrared image from various scenes. Thirdly, the plateau histogram equalization method is designed to enhance different brightness regions separately, according to their brightness levels. Finally, the enhanced brightness regions are recombined to produce a more visually pleasing output image. The effectiveness of the proposed method is analyzed of HDR infrared images taken from different scenes. A comparison of the proposed method with well-established global tone mapping techniques is provided, along with subjective and objective evaluation methods that demonstrate the potential benefits of this method in enhancing brightness, compressing dynamic range, and improving global contrast.

Risk assessment for hurricane-induced pluvial flooding in urban areas using a GIS-based multi-criteria approach: A case study of Hurricane Harvey in Houston, USA

As one of the most destructive nature hazards, hurricane-induced flooding generates serious adverse impacts on populations, infrastructure, and the environment globally. In urban areas, complex characteristics such as high population and infrastructure densities increase flood disaster risks. Consequently, the assessment of flood risks is becoming increasingly important for understanding potential impacts on an urban area and proposing disaster risk mitigation strategies. After conducting a comprehensive literature review, this study finds that most urban flood risk assessments often overlook urban ecosystem elements, focusing more on social and economic aspects. Hence, the role of urban ecosystems cannot be fully understood. To address this gap, this study proposes a social-ecological systems (SES) flood risk assessment framework for urban areas. Based on this framework, a comprehensive list of indicators collected through a literature review is provided for urban flood risk assessments. A comparative study of flood risk during Hurricane Harvey (2017) in Houston, Texas, USA, is carried out using the improved analytic hierarchy process (IAHP) weighting method and the equal weighting method for indicator weighting. Results are then compared with the damage data of Hurricane Harvey published by the U.S. Federal Emergency Management Agency (FEMA). The analysis identifies that the western part of Houston had the highest flood risks, while the center of Houston was at lower flood risk. Comparisons between the results from the IAHP and equal weighting methods show that the latter produces a broader range of high flood risk areas than the former. This study also highlights the role of urban ecosystems in mitigating flood risks and advocates for more holistic, social-ecological assessments of flood risk. Such assessments could utilize the proposed framework and the indicator list but contextualize these to the specific urban area's contexts being investigated.

The splitting-based semi-implicit finite-difference schemes for simulation of blood flow in arteries

This paper is devoted to construction and analysis of splitting-based finite-difference schemes for simulation of blood flow in applications of one-dimensional models. Proposed schemes are constructed for inviscid and viscid models of blood. The proposed approach is based on the modification of averaged incompressibility condition, rewritten for the square root of a cross-sectional area. It is approximated by an absolutely stable scheme with a skew-symmetric operator. The constructed schemes can be classified as semi-implicit. The stability of proposed schemes is analyzed by the method of energy inequalities. Sufficient stability conditions are obtained. For the problems with analytical solutions, it is demonstrated that a second-order convergence rate is achieved in practice.The proposed schemes are compared with the widely used explicit finite-difference schemes, such as Lax–Wendroff, Lax–Friedrichs and McCormack schemes. The benchmark problems for simulation of flows in the following vascular systems are considered: human carotid artery, human aorta with bifurcation, vessel with bifurcation and absorbing outflow conditions, and networks with 31, 63, and 127 vessels. It is demonstrated that the computations based on the splitting-based semi-implicit schemes can be performed much faster than for the explicit schemes with close values of relative errors.

A Novel Gabor Filtering and Adaptive Histogram Equalization Method for Improving Images

The correct information may only sometimes be effectively conveyed by images due to various factors, such as excessively bright or dark lighting and low or high contrast. As a result, picture improvement has become an essential part of digital image processing. This proposed method aims to develop an algorithm for improving photos captured in dark environments. This letter presents a new picture-enhancing approach that combines median and Gabor filtering using the wavelet domain with histogram equalization working over a spatial domain. The proposed method in this paper combines spatial and transformed domains for image enhancement and has been simulated using MATLAB. The simulation results of two different photos show that the suggested approach extends the histogram over a wide range of grayscale, offering a superior improvement to the original image. The novel proposed algorithm aims to improve image quality and visibility, making identifying essential details within the image easier. Further, the proposed technique's success is manifested by examining the produced photos' contrast and brightness. The findings reveal that the suggested technique beats the other strategies for improving low-contrast photos.

Event-Triggered Sliding-Mode Control for Fuzzy Semi-Markovian Jump Systems With Dead Zone Input and Application to Circuit Systems

This paper investigates event-triggered sliding mode control (SMC) for fuzzy semi-Markovian jump systems (S-MJSs) subject to limited communication capacity, in which we consider the network-induced transmission delay, dead-zone input and partially unknown transition rates of jumping mode in a whole framework. First, an event-triggered mechanism(ETM) is employed in the sensor-to-controller channel to save network resources efficiently. Then, a novel integral sliding surface is obtained with the aid of the event-triggered state information, and some new sufficient conditions on the stochastic stability of the overall closed-loop system are given in the sense of partially unknown transition rates via stochastic stability theory and matrix inequality method. Furthermore, a mode-depended sliding mode controller is designed to guarantee the reachability of the sliding surface in finite time by using the Lyapunov stability theory. Finally, a TD circuit model is provided to illustrate the validity of the proposed control scheme.

REGULARIZED JACOBI-TYPE ADMM-METHOD FOR FINDING SOLUTIONS TO GENERALIZED NASH EQUILIBRIUM PROBLEM

In this paper, we extended the well-known alternating direction method of multipliers (ADMM) for optimization problems to generalized Nash equilibrium problems (GNEP) with shared constraints. We developed an ADMM-type algorithm with fixed regularization to tackle the problem (GNEP) where an upper estimate for the operator norm is not known and then we apply a multiplier-penalty in order to get rid of the joint constraints. We equipped the Hilbert space with an appropriate weighted scalar product and it turns out to be weakly convergent under a lipschitz and monotonicity assumption. A proximal term is then added to improve the convergence properties. Furthermore, a comparative analysis of quasi-variational inequality method, interior point method, penalty method and the proposed method are discussed.