MATLAB Algorithm Research Articles

Predicting Single Cell Lag Time and Maximum Specific Growth Rate of Proteus mirabilis using Curve Fitting Machine Learning Algorithm (MLA)

The lack of adequate assessment methods for pathogens especially in food is a critical problem in microbiology. Traditional predictive methods are not able to accurately describe the trend of low-density bacterial growth behavior observed in the laboratory. The purpose of this study was to leverage state-of-the-art of machine learning algorithms (MLA) to develop a predictive model for bacterial growth of Proteus mirabilis after treatment of bay leaf extract. The experimental data are fitted to three models, namely logistic, Gompertz, and Richard models. These models are trained using simulation data and a curve-fitting optimization algorithm in MATLAB called fminsearch is applied to the data to obtain the optimal parameters of the models. The results show that this method provides a breakthrough in bacterial growth modeling. Various forms of mathematical models such as Gompertz, Richard, and others are no longer necessary to model bacterial behavior. Additionally, the generated model can help microbiologists in understanding the growth characteristics of bacteria after disinfectant treatment, and provides a theoretical reference and a method of risk management for better assessment of pathogens in food.

Thermal entry flow problem for Rabinowitsch fluid subject to circular tube and flat channel with uniform heat flux boundary conditions

The heat exchangers, chemical reactors, cooling/heating systems and haemodialysis are specific areas due to which Graetz thermal problem is considered as fundamental flow in the duct along with heat and mass transfer aspects. Owing to its importance we examine the thermal entry flow problem for Rabinowitsch liquid in the pipe and channel ducts along with heat transfer aspects. The heat equation with uniform heat flux conditions is tackled via the superposition principle and separation of variable approach due to the involvement of non-homogeneous boundary conditions. The transformed boundary value problem is solved with the MATLAB algorithm for the calculation of eigenvalues and related eigenfunctions. The special cases for simplified Phan-Thien–Tanner (SPTT) fluid and finite extendable non-linear elastic peterline (FENE-P) fluids are also discussed. For SPTT and FENE-P models the controlling parameter can only take positive values and hence these models can only predict shear-thinning effects. The graphical illustrations of fully developed temperature, local and mean Nusselt numbers are displayed through the main effect brought by the controlling parameter.

Development of a Low-Power Automatic Monitoring System for Spodoptera frugiperda (J. E. Smith)

Traditional traps for Spodoptera frugiperda (J. E. Smith) monitoring require manual counting, which is time-consuming and laborious. Automatic monitoring devices based on machine vision for pests captured by sex pheromone lures have the problems of large size, high power consumption, and high cost. In this study, we developed a micro- and low-power pest monitoring device based on machine vision, in which the pest image was acquired timely and processed using the MATLAB algorithm. The minimum and maximum power consumption of an image was 6.68 mWh and 78.93 mWh, respectively. The minimum and maximum days of monitoring device captured image at different resolutions were 7 and 1486, respectively. The optimal image resolutions and capture periods could be determined according to field application requirements, and a micro-solar panel for battery charging was added to further extend the field life of the device. The results of the automatic counting showed that the counting accuracy of S. frugiperda was 94.10%. The automatic monitoring device had the advantages of low-power consumption and high recognition accuracy, and real-time information on S. frugiperda could be obtained. It is suitable for large-scale and long-term pest monitoring and provides an important reference for pest control.

Wind farm active power dispatching algorithm based on grey incidence

This study proposes a wind farm active power dispatching (WFAPD) algorithm based on the grey incidence method, which does not rely on an accurate mathematical model of wind turbines. Based on the wind turbine start-stop data at different wind speeds, the weighting coefficients, which are the participation degrees of a variable speed system and a variable pitch system in power regulation, are obtained using the grey incidence method. The incidence coefficient curve is fitted by the B-spline function at a full range of wind speeds, and the power regulation capacity of all wind turbines is obtained. Finally, the WFAPD algorithm, which is based on the regulating capacity of each wind turbine, is compared with the wind speed weighting power dispatching (WSWPD) algorithm in MATLAB. The simulation results show that the active power fluctuation of the wind farm is smaller, the rotating speed of wind turbines is smoother, and the fatigue load of high- speed turbines is effectively reduced.

Evaluation of RETRO-Mapping for electrophysiological features including direction of plane activity during atrial fibrillation using multipolar catheters in humans.

A quantifiable, automated standard of analyzing heart rhythm has long eluded cardiologists due, in part, to the limitations in technology and the ability to analyze large electrogram datasets. In this proof-of-concept study, we propose new measures to quantify plane activity in atrial fibrillation (AF) using our Representation of Electrical Tracking of Origin (RETRO)-Mapping software. We recorded 30 s segments of electrograms at the lower posterior wall of the left atrium using a 20-pole double loop catheter (AFocusII). The data were analyzed with the custom RETRO-Mapping algorithm in MATLAB. Thirty secondsegments were analyzed for number of activation edges, conduction velocity (CV), cycle length (CL), activation edge direction, and wavefront direction. These features were compared across 34 613 plane edges in three types of AF: persistent AF treated with amiodarone (11 906 wavefronts), persistent AF without amiodarone (14 959 wavefronts), and paroxysmal AF (7748 wavefronts). Change in activation edge direction between subsequent frames and change in overall wavefront direction between subsequent wavefronts were analyzed. All activation edge directions were represented across the lower posterior wall. The median change in activation edge direction followed a linear pattern for all three types of AF with R2 = 0.932 for persistent AF treated without amiodarone, R2 = 0.942 for paroxysmal AF, and R2 = 0.958 for persistent AF treated with amiodarone. All medians and the standard deviation error bars remained below 45° (suggesting all activation edges were traveling within a 90° sector, a criterion for plane activity). The directions of approximately half of all wavefronts (56.1% for persistent without amiodarone, 51.8% for paroxysmal, 48.8% for persistent with amiodarone) were predictive of the directions of the subsequent wavefront. RETRO-Mapping can measure electrophysiological features of activation activity and this proof-of-concept study suggests that this can be extended to the detection of plane activity in three types of AF. Wavefront direction may have a role in future work for predicting plane activity. For this study, we focused more on the ability of the algorithm to detect plane activity and less the differences between the types of AF. Future work should be in validating these results with a larger data set and comparing with other types of activation such as rotational, collision, and focal. Ultimately, this work can be implemented in real-time for prediction of wavefronts during ablation procedures.

Computation of the confluent hypergeometric function U(a,b,x) and its derivative for positive arguments

An algorithm and a MATLAB implementation for computing the Kummer function U(a,b,x) and its derivative is given in this paper. The algorithm is efficient and accurate. Numerical tests show that the MATLAB algorithm allows the computation of the function with sim 10^{-14} relative accuracy in the parameter region (a,b,x) ∈ (0,500) × (0,500) × (0,1000) in double-precision floating point arithmetic.

Improved fish migration optimization method to identify PEMFC parameters

In a worldwide environment context where the emergency need to decrease pollutant emissions is an important issue, the research for solutions is increasing. Fuel cell technology is anticipated to become a practicable approach for solving the problem of pollution due to its environmentally friendly characteristics. In this work, a novel problem formulation is suggested for the efficient recognition of PEMFC parameters which the solving is by using the Improved Fish Migration Optimizer (IFMO) technique. After coding the steps of the algorithm in MATLAB, the objective function is resolved for the fuel cell. Comprehensive simulations evaluate the formulation performance with the suggested and traditional objective functions; then, the outcomes are compared. To confirm the suggested formulation ascendancy compared to the traditional curve-fitting method, a complete assessment based on convergence rate, the value of the objective function, and the value of absolute voltage error are performed. The achieved value of the objective function, absolute voltage error, and average time of computation is 0.005, 0.4, and 1.63, respectively. Environmentally, the combustion of hydrogen and its use in PEMFC produce no carbon dioxide.

Energy, exergy, exergoeconomic and environmental (4E) analysis of cascade heat pump, recuperative heat pump and carbon dioxide heat pump with different temperature lifts

Air source heat pump is recognized as an effective environmental protection and energy-saving technology. The heating temperature lift is one of the key factors affecting the performance of heat pump systems. In this paper, an in-depth quantitative thermodynamic comparison of cascade heat pump, recuperative heat pump and CO2 heat pump for direct-heating and space heating was conducted. Aspen HYSYS was used to invoke advanced genetic algorithm in MATLAB to optimize the system parameters. The temperature matching in heat exchangers was employed to reveal the essence of the performances of different heat pump systems. The recuperative heat pump is more suitable for direct-heating with the temperature lift 60 °C, and its COP is up to 4.81 at the ambient temperature of 20 °C. The cascade heat pump performs best in space heating with the maximum COP of 2.47. The exergoeconomic factor of the compressor is less than 7%, which illustrated that the investment in compressor should be increased to further improve the system efficiency. The annual CO2 and SO2 lowest emissions is 4431 kg and 130 kg of recuperative heat pump for direct-heating, and the cascade heat pump has the lowest annual 4234 kg CO2 and 127 kg SO2 emissions for space heating.

A computational technique for the Caputo fractal-fractional diabetes mellitus model without genetic factors.

The concept of a Caputo fractal-fractional derivative is a new class of non-integer order derivative with a power-law kernel that has many applications in real-life scenarios. This new derivative is applied newly to model the dynamics of diabetes mellitus disease because the operator can be applied to formulate some models which describe the dynamics with memory effects. Diabetes mellitus as one of the leading diseases of our century is a type of disease that is widely observed worldwide and takes the first place in the evolution of many fatal diseases. Diabetes is tagged as a chronic, metabolic disease signalized by elevated levels of blood glucose (or blood sugar), which results over time in serious damage to the heart, blood vessels, eyes, kidneys, and nerves in the body. The present study is devoted to mathematical modeling and analysis of the diabetes mellitus model without genetic factors in the sense of fractional-fractal derivative. At first, the critical points of the diabetes mellitus model are investigated; then Picard's theorem idea is applied to investigate the existence and uniqueness of the solutions of the model under the fractional-fractal operator. The resulting discretized system of fractal-fractional differential equations is integrated in time with the MATLAB inbuilt Ode45 and Ode15s packages. A step-by-step and easy-to-adapt MATLAB algorithm is also provided for scholars to reproduce. Simulation experiments that revealed the dynamic behavior of the model for different instances of fractal-fractional parameters in the sense of the Caputo operator are displayed in the table and figures. It was observed in the numerical experiments that a decrease in both fractal dimensions and leads to an increase in the number of people living with diabetes mellitus.

Evaluation of Natural Frequency of a Cable Stayed Bridge Using System Identification Technique

Abstract: System Identification is an emerging area in the domain of structural engineering specially under structural health monitoring. For dynamic analysis or stimulation, the dynamic system parameters (i.e. natural frequency, mode shape, damping ratio etc.) are most important. Vibration data of actual structures are collected by different sensors. These data are analyzed with the help of different system identification technique to get inside view of the structure. This paper presents the synthetic vibration data generation of the model structure using Time History Analysis with the help of SAP2000 software. Time history analysis is performed on a cable stayed bridge. Joint acceleration, mode shapes, natural frequency etc. are found from this analysis. For system identification purpose the acceleration time history data of different locations are used to get the natural frequency of the cable stayed bridge which is a significant system identification parameter. This identification is done with the help of power spectral density (PSD) using MATLAB algorithm

An adaptive EWMA control chart based on Hampel function to monitor the process location parameter

AbstractThe classical memory Exponential Weighted Moving Average (EWMA) and Cumulative Sum (CUSUM) control charts (CCs) are important to detect small‐to‐moderate sizes of shift in the process location and/or dispersion parameters. To make the memory control chart (CC) more efficient for broad range of shift, the score functions in particular Huber and Bi‐square functions are incorporated in the classical memory CCs. These score functions help to formulate the parameters of memory CCs and are called Adaptive EWMA (AEWMA) and Adaptive CUSUM (ACUSUM). The AEWMA and ACUSUM are capable to handle various sizes (i.e., small, moderate, and large) of shift. The aim of this study is to utilize Hampel function as the alternative of the mentioned score functions, and propose a new AEWMA CC, symbolized as AEWMAHample. To develop the proposed AEWMAHampleCC, the standard EWMA statistic and Hampel function are incorporated in the classical EWMA CC structure. The proposed AEWMAHampleCC is also efficient to handle certain sizes of shift in the process location parameter. Performance evaluation procedures, like average run length is considered for a particular shift. Similarly, the performance comparison index, relative average run length, and extra quadratic loss function are estimated over a range of shift. All these performance measures are calculated from run length (RL) characteristic of the proposed control chart. An algorithm in MATLAB is developed based on Monte Carlo simulation procedure to generate the RLs. Some existing control charts including EWMA, CUSUM, MEC, MCE, , , IACCUSUM, , and are taken for comparison reason. For specific sizes of shift, the proposed AEWMAHampleCC reveals the superiority. Besides, to address the practical significance for practitioners and quality engineers, the real‐life and simulated data examples are considered.

Experimental investigation of crossflow air effect on spray characteristics of gelled Jet-A1 fuel using an internally impinging air-blast atomizer

The present study aims to experimentally analyse the influence of crossflow aerodynamic parameters on the spray characteristics of gelled Jet-A1 fuel. A Jet-A1 gel fuel is prepared by combining 85 percentage by weight (wt. %) of Jet-A1 liquid as base fuel with an organo-gel solution having Thixatrol ST (7.5 wt. %) as gelling agent and Rectified xylene (7.5 wt. %) as solvent. Shear flow test is performed on the gel fuel using a rotational rheometer, to understand its non-Newtonian rheological properties. An internally impinging air blast atomizer is used to study the gel spray characteristics by injecting the gel fuel transversely into the subsonic cross flowing airstream environment. Gel spray images are captured by generating a laser sheet along the midplane of the test section across the crossflow air stream direction using the Laser Sheet Photography (LSP) technique. The captured gel spray images are used to visualize the gel spray structure in both spray axis as well as the crossflow air stream direction. These images are then investigated by developing an algorithm in MATLAB using an image processing tool. By incorporating the canny edge detection method into the MATLAB code, gel spray characteristics such as droplet size distribution, Sauter-mean-diameter, Arithmetic-mean-diameter, windward trajectories, and maximum penetration height are determined. Further, the effect of aerodynamic parameters such as crossflow Reynolds’ number and aerodynamic Weber number on the gel spray characteristics are investigated. Droplet size distribution and maximum penetration height of gelled Jet-A1 spray revealed its dependence on crossflow Reynolds’ number. Sauter-Mean-Diameter of gel droplets and windward trajectories of the gel spray decreases significantly as the aerodynamic Weber number increases. Thus, it can be concluded that the fineness of the spray is also a function of the crossflow aerodynamic parameters other than the atomizer.

NOISE THEORITICAL INVESTIGATIONS FOR TRI-DIMMENSIONAL NMR CIRCUIT: TOWARDS THE NANOSCALE

In recent years, NMR/MRI portable devices have drawn attention of numerous researcher teams. They are used for variety of applications, from medical diagnosis to archaeological analysis, nondestructive material testing evaluation of water presence in building materials and food emulsions. Different magnets designs have been proposed by many groups of research. They can be divided into two groups: the magnets ex-situ and the magnets in situ .The first group has the simple configuration with the sensitive volume near their surface and the samples under test are located outside the magnets. Thus, they can be used for the experimental investigation of objects with any dimension. Although the ex-situ magnets have simple shape and light weight, they are difficult to achieve in terms of homogeneity of the magnetic field in the sensitive volume. 
 In comparison, the in-situ magnets have their static field reinforced inside their bore center and canceled outside of the structure. Thus, their magnetic field is roughly homogeneous inside the structure. 
 But drawbacks still exist and can be amplified, especially the in depth problem of Signal/Noise. Calculations, in a microscopic point of view, are develop, first applied to resistances and inductances imbedded in this circuit. 
 Before, from any point source, we calculate the impedance spreading out. For this, our approach is using Transmission Line Model, over or into a multi-layered substrate; it can be also derived by solving Poisson's equation analytically to obtain the associated Green’s kernel. We implement our algorithms in MATLAB. Thus, it permits to extract impedances between any two embedded contacts, real or virtual, of any shape or thickness.

Nanostructured (Ti,Cu)N Dry Electrodes for Advanced Control of the Neuromuscular Activity

This research reports a novel concept of dry surface electrodes designed to act in a dual-role biofeedback process: monitoring and stimulating the muscle’s electrical activity. A new strategy based on 3-D printed polymeric disk-shaped substrates functionalized with nanostructured (Ti,Cu)N thin films to be integrated into rehabilitation wearables. Five different chemical compositions with different microstructural features were grown by dc magnetron sputtering on polyurethane (PU), polylactide, and cellulose polymers and tested as electrodes. In the first phase, the electromyography (EMG) activity for both resting and muscle contraction of the bicep muscle was assessed using the LabVIEW software coupled to a NI 9234 signal data acquisition system and processed with MATLAB algorithms. The second phase tested the maximum electrical stimulation capable of being delivered without crosstalking between stimulation and sensing processes, using a TENS 7000 commercial unit. The tests highlighted the potential of the flexible PU bases among their counterparts, whereas the dense and soft electrodes of titanium doped with 25.6.% of copper were able to stimulate at a 100-mA full current output without discomfort for the subject exhibiting simultaneously the lowest EMG detection limit. The research conducted enhances the strong potential of using dry electrodes in new technologies and strategies capable of delivering primary and integrated care adapted to foster functional abilities.

Exploration of Newtonian Heating, Viscous Dissipation Effects on MHD Mixed Convection Flow of Williamson Fluid Against Radially Stretched Penetrable Wedge: A Numerical Study

An investigation on framing the features of Newtonian heating, suction/blowing, viscous dissipation on magneto hydrodynamic mixed convective Williamson fluid flow over a porous stretching wedge that is influenced by thermal radiation. The con-temporary model is employed to simulate the non-Newtonian behavior of fluid over porous wedge which stretches faster or slower than free stream velocity. Practical applications of wedge flow are drug delivery, cancer treatment, biotechnology and biomedicine. Initially, the major partial differential equations are transformed into ordinary differential equations via a suitable set of similarity transformation and then solved by the developed bvp4c algorithm in MATLAB. A comprehensive analysis of definite parameters on the profiles of velocity, temperature, [Formula: see text], and skin friction coefficient is explained and scrutinized. The results indicate that elaboration in [Formula: see text] and We shows a decline in velocity profile at [Formula: see text] but an opposite trend for [Formula: see text]. However, temperature increases for both [Formula: see text]. Furthermore, (at [Formula: see text]), an augmentation in Pr results in uphill local Nusselt number. The consequences of the present exploration are compared with the existing works in specific situations and more agreement has been perceived.

Optical modulation of excitation-contraction coupling in human-induced pluripotent stem cell-derived cardiomyocytes

Non-genetic photostimulation is a novel and rapidly growing multidisciplinary field that aims to induce light-sensitivity in living systems by exploiting exogeneous phototransducers. Here, we propose an intramembrane photoswitch, based on an azobenzene derivative (Ziapin2), for optical pacing of human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). The light-mediated stimulation process has been studied by applying several techniques to detect the effect on the cell properties. In particular, we recorded changes in membrane capacitance, in membrane potential (Vm), and modulation of intracellular Ca2+ dynamics. Finally, cell contractility was analyzed using a custom MATLAB algorithm. Photostimulation of intramembrane Ziapin2 causes a transient Vm hyperpolarization followed by a delayed depolarization and action potential firing. The observed initial electrical modulation nicely correlates with changes in Ca2+ dynamics and contraction rate. This work represents the proof of principle that Ziapin2 can modulate electrical activity and contractility in hiPSC-CMs, opening up a future development in cardiac physiology.

A virtual reality tool to aid in soundscapes in the built environment (SiBE) through machine learning

Regarding the function and context of the space, virtual reality (VR) can be used for soundscapes design if the user behavior is predictable. This study enables the acoustic characterization of VR development tools to measure auditory perception based on user behavior. The research question is whether soundscapes can be modeled according to the variable acoustic environments defined by the existing architectural features (e.g., prismatic, courtyard, vault, arched, mezzanine). A sound simulation algorithm in MATLAB was developed to extract room impulse response (RIR) of the test environment in a virtual environment and to compare it with the real environment (RE). In the developed program, image source model (ISM) and ray trace were used to be performed the real-time acoustic source generation and real-time signal recording, image functions, data processing, metric calculation operations (e.g., tonality and spectrogram). B&K 4292 omni-power loudspeaker, B&K 2716 power amplifier, and B&K 2250 hand-held analyzer were used to measure RIR in the RE. In addition to RIR and RT30, psychoacoustic metrics (e.g., loudness, sharpness, roughness, and fluctuation strength) were measured in both environments. The results showed that sound simulation, based on ISM, demonstrates the validity and can be used for the acoustic characterization of VR development environments.

Computation of Sakiadis flow of an Eyring-Powell rheological fluid from a moving porous surface with a non-Fourier heat flux model

This article examines theoretically and numerically the effect of non-Fourier heat flux on non-Newtonian (Eyring-Powell) Sakiadis convective flow from a moving permeable surface accompanied by a parallel free-stream velocity, as a simulation of polymeric coating processes. The Cattaneo-Christov model is deployed which features thermal relaxation effects as these are important in thermal polymer processing. The physical flow problem is modeled in a Cartesian coordinate system and the governing conservation differential equations and associated boundary conditions are rendered dimensionless by applying suitable transformations. Liquid velocity and thermal distributions are computed considering numerical procedure namely, a shooting method in conjunction with the 5th order Runge–Kutta algorithm (R-K5) executed in a symbolic software. Validation with the three-stage Lobatto IIIA algorithm in MATLAB is included. The impact of key parameters on streamline distributions is also computed. Velocity is increased with increment in Eyring-Powell first parameter for the Sakiadis case whereas it is reduced with Eyring-Powell second parameter for the case where sheet and liquid are inspiring in the similar direction. The special case of Blasius flow is also examined (stationary sheet). For higher injection, there is a solid dampening in the boundary-layer flow for both Sakiadis and Blasius scenarios.

Graded index all-dielectric lens antenna designed by phase manipulation and optical path rescaling

A rotationally symmetric all-dielectric lens antenna is designed by defining the phase function inside the dielectric directly via a closed-form series formula. The refractive index of the lens is modified using state-of-the-art optical path rescaling to keep the refractive index within practical values. The lens optimization is done using the genetic algorithm in MATLAB, where each case is evaluated by conducting linked ray tracing and full-wave electromagnetic simulation in COMSOL. A lens prototype is shown to provide a directivity enhancement of 5.1 dB compared to the optimal conical horn antenna, an improvement of 2 dB compared to the Luneburg lens, and an improvement of 3.8 dB compared to a reference graded index lens. All the examined cases shared a similar length of 5λ for the center frequency of 10 GHz. The prototype lens antenna has a maximum refractive index of 2.1, a reflection coefficient of −22 dB, and a side-lobe level of −25 dB at the center frequency of 10 GHz. The lens’ performance is consistent in the 9–11 GHz band supported by the standard circular waveguide. The results from a prototype with a discretized refractive index simulated in CST Studio Suite are in excellent agreement with the ones with a continuous refractive index profile simulated in COMSOL.

99m-Tc MDP Bone Scan Image Enhancement using Pipeline Application of Dynamic Stochastic Resonance Algorithm and Block-Matching 3D Filter.

In this pilot study, we have proposed and evaluated pipelined application of the dynamic stochastic resonance (DSR) algorithm and block-matching 3D (BM3D) filter for the enhancement of nuclear medicine images. The enhanced images out of the pipeline were compared with the corresponding enhanced images obtained using individual applications of DSR and BM3D algorithm. Twenty 99m-Tc MDP bone scan images acquired on SymbiaT6 SPECT/CT gamma camera system fitted with low-energy high-resolution collimators were exported in DICOM format to a personal computer and converted into PNG format. These PNG images were processed using the proposed algorithm in MATLAB. Two nuclear medicine physicians visually compared each input and its corresponding three enhanced images to select the best-enhanced image. The image quality metrics (Brightness, Global Contrast Factor (GCF), Contrast per pixel (CPP), and Blur) were used to assess the image quality objectively. The Wilcoxon signed test was applied to find a statistically significant difference in Brightness, GCF, CPP, and Blur of enhanced and its input images at a level of significance. Images enhanced using the pipelined application of SR and BM3D were selected as the best images by both nuclear medicine physicians. Based on Brightness, Global Contrast Factor (GCF), CPP, and Blur, the image quality of our proposed pipeline was significantly better than enhanced images obtained using individual applications of DSR and BM3D algorithm. The proposed method was found to be very successful in enhancing details in the low count region of input images. The enhanced images were bright, smooth, and had better target-to-background ratio compared to input images. The pipelined application of DSR and BM3D algorithm produced enhancement in nuclear medicine images having following characteristics: bright, smooth, better target-to-background ratio, and improved visibility of details in the low count regions of the input image, as compared to individual enhancements by application of DSR or BM3D algorithm.