MATLAB Algorithm Research Articles

Minimizing the variance of the coverage ratio as an approach to optimize the exchange rate risk of Brent futures contracts

Derivatives markets show that their structure is always characterized by periods of strong price fluctuations. This is true regardless of the underlying asset of the futures contracts considered, whether they are commodities, interest rates, exchange rates, shares, stock market indices, etc. By locking in future prices, the primary objective of these markets is to limit the risks faced by operators. This article proposes a new method of optimizing the coverage ratio by futures contracts to minimize price variance and thus apply this new technique to reduce the risk associated with Brent price volatility for the period from January 2010 to December 2020. The variance minimization model of Ederington's (1979) is the first and most widely used coverage model and the one that dominates the literature on this area which helps to find the optimal coverage ratio, and is also the objective function in our particle assay optimization algorithm in MATLAB and we will better interpret our results with statistical analysis and lastly, we will evaluate the effectiveness of the coverage model.

Analysis of the Comprehensive Evaluation Model of Enterprise Technological Innovation Ability Based on Improved Genetic Algorithm

In an environment where technology is developing rapidly, product life cycles are constantly shortening, competition is increasing, and innovation resources are easily acquired by other competitors, it is particularly important for companies to successfully implement technological innovation. It is of great significance for companies to find the weak links of their technological innovation and prioritize improvement and enhancement of their technological innovation capabilities. As the main body of the agricultural machinery industry, private agricultural machinery enterprises are playing an increasingly important role. A correct understanding of the technological innovation activities of private agricultural machinery enterprises and the establishment of a reasonable evaluation index system for technological innovation capabilities are of great significance to the technological innovation management of private agricultural machinery enterprises. In accordance with the theory of technological innovation and the characteristics of private agricultural machinery enterprises, a technical innovation evaluation index system for private agricultural machinery enterprises has been established. The indicator system starts from the concept of private agricultural machinery enterprises, analyzes the status quo and development trend of the agricultural machinery industry, and takes private agricultural machinery enterprises in Heilongjiang Province as the research object. It summarizes the status quo and characteristics of technological innovation of private agricultural machinery enterprises and then establishes the private agricultural machinery enterprises. The system starts from the aspects of innovation resource input, innovation output, technology density, innovation effect, market realization, and innovation tendency, and selects 16 specific evaluation indicators. According to the established capability, projection pursuit is adopted. The method combined with the genetic algorithm and the genetic algorithm in MATLAB and the direct search toolbox were employed to comprehensively charge the capabilities of the five sample enterprises, and the evaluation results were objective and credible.

Modeling the Proposal of the Simultaneous Purchases and Sales of Electricity and Gas for the Energy Market in a Microgrid Using the Harmony Search Algorithm

The use of different energy carriers together, known as an energy hub, has been a hot topic of research in recent years amongst scientists and researchers. The term energy hub refers to the simultaneous operation of various infrastructures for energy generation and transfer, which has gained momentum in the form of microgrids (MGs). This paper introduces a new strategy for the optimal performance of an MG consisting of different energy carriers for each day. In a smart distribution network (DN), MGs can reduce their own costs in the previous-day market by bidding on sales and purchases. The sales and purchases bidding problem is challenging due to different uncertainties, however. This paper proposes a two-stage strategy for making an optimal bid on electricity sales and purchases with electricity and gas price dependency in the previous-day and real-time markets for an energy hub. In this model, the MG behavior regarding the electricity and gas energy sales/purchase, the simultaneous effects of electricity and gas prices, as well as the energy carriers’ dependence on one another are all examined. Due to the inherent uncertainty in the sources of clean energy production, the probabilistic model and the production and reduction scenario have been used in the paper to cover this issue. In the proposed grid, energy sales/purchases are presented in a multi-carrier MG in a two-stage model. This model is solved by using the harmony search algorithm in MATLAB. Numeric results demonstrate the benefits of this model in reducing energy hub costs of operation.

A new kind of Bi-variate $ \lambda $ -Bernstein-Kantorovich type operator with shifted knots and its associated GBS form

<p style='text-indent:20px;'>In this paper, we introduce a bi-variate case of a new kind of <inline-formula><tex-math id="M1">\begin{document}$ \lambda $\end{document}</tex-math></inline-formula>-Bernstein-Kantorovich type operator with shifted knots defined by Rahman et al. [<xref ref-type="bibr" rid="b31">31</xref>]. The rate of convergence of the bi-variate operators is obtained in terms of the complete and partial moduli of continuity. Next, we give an error estimate in the approximation of a function in the Lipschitz class and establish a Voronovskaja type theorem. Also, we define the associated GBS(Generalized Boolean Sum) operators and study the degree of approximation of Bögel continuous and Bögel differentiable functions by these operators with the aid of the mixed modulus of smoothness. Finally, we show the rate of convergence of the bi-variate operators and their GBS case for certain functions by illustrative graphics and tables using MATLAB algorithms.</p>

Notes on Fitting and Analysis Frameworks for QENS Spectra of (Soft) Colloid Suspensions

With continuously improving signal-to-noise ratios, a statistically sound analysis of quasi-elastic neutron scattering (QENS) spectra requires to fit increasingly complex models which poses several challenges. Simultaneous fits of the spectra for all recorded values of the momentum transfer become a standard approach. Spectrometers at spallation sources can have a complicated non-Gaussian resolution function which has to be described most accurately. At the same time, to speed up the fitting, an analytical convolution with this resolution function is of interest. Here, we discuss basic concepts to efficient approaches for fits of QENS spectra based on standard MATLAB and Python fit algorithms. We illustrate the fits with example data from IN16B, BASIS, and BATS.

A 3D printable perfused hydrogel vascular model to assay ultrasound-induced permeability.

The development of an in vitro model to study vascular permeability is vital for clinical applications such as the targeted delivery of therapeutics. This work demonstrates the use of a perfusion-based 3D printable hydrogel vascular model as an assessment for endothelial permeability and its barrier function. Aside from providing a platform that more closely mimics the dynamic vascular conditions in vivo, this model enables the real-time observation of changes in the endothelial monolayer during the application of ultrasound to investigate the downstream effect of ultrasound-induced permeability. We show an increase in the apparent permeability coefficient of a fluorescently labeled tracer molecule after ultrasound treatment via a custom MATLAB algorithm, which implemented advanced features such as edge detection and a dynamic region of interest, thus supporting the use of ultrasound as a non-invasive method to enhance vascular permeability for targeted drug therapies. Notably, live-cell imaging with VE-cadherin-GFP HUVECs provides some of the first real-time acquisitions of the dynamics of endothelial cell-cell junctions under the application of ultrasound in a 3D perfusable model. This model demonstrates potential as a new scalable platform to investigate ultrasound-assisted delivery of therapeutics across a cellular barrier that more accurately mimics the physiologic matrix and fluid dynamics.

Application research on neutron-gamma discrimination based on BC501A liquid scintillator

Abstract Liquid organic scintillators are widely used in non-destructive analysis, which plays an important role in nuclear disarmament verification. This paper focused on studying the neutron-gamma discrimination technology in the fast neutron multiplicity measuring counter based on BC501A liquid scintillation detector. First, the charge comparison method, the zero-crossing time method and the rise time method were compared via the Geant4 and Matlab algorithm, and the result shows that charge comparison has the highest Figure of Merit. Then, a neutron-gamma discrimination system based on the six-probe fast neutron multiplicity counter was built and tested with a conclusion that the mean value of Figure of merit is 1.08, which verify the satisfactory neutron-gamma discriminating capability of the system. Finally, for the uranium samples, the mass are detected by fast neutron multiplicity counter, and the enrichment are measured by the characteristic gamma-ray signals using the system. The experimental results are in good agreement with the actual data.

Digital Pathology Enables Automated and Quantitative Assessment of Inflammatory Activity in Patients with Chronic Liver Disease.

Traditional histological evaluation for grading liver disease severity is based on subjective and semi-quantitative scores. We examined the relationship between digital pathology analysis and corresponding scoring systems for the assessment of hepatic necroinflammatory activity. A prospective, multicenter study including 156 patients with chronic liver disease (74% nonalcoholic fatty liver disease-NAFLD, 26% chronic hepatitis-CH etiologies) was performed. Inflammation was graded according to the Nonalcoholic Steatohepatitis (NASH) Clinical Research Network system and METAVIR score. Whole-slide digital image analysis based on quantitative (I-score: inflammation ratio) and morphometric (C-score: proportionate area of staining intensities clusters) measurements were independently performed. Our data show that I-scores and C-scores increase with inflammation grades (p < 0.001). High correlation was seen for CH (ρ = 0.85–0.88), but only moderate for NAFLD (ρ = 0.5–0.53). I-score (p = 0.008) and C-score (p = 0.002) were higher for CH than NAFLD. Our MATLAB algorithm performed better than QuPath software for the diagnosis of low-moderate inflammation (p < 0.05). C-score AUC for classifying NASH was 0.75 (95%CI, 0.65–0.84) and for moderate/severe CH was 0.99 (95%CI, 0.97–1.00). Digital pathology measurements increased with fibrosis stages (p < 0.001). In conclusion, quantitative and morphometric metrics of inflammatory burden obtained by digital pathology correlate well with pathologists’ scores, showing a higher accuracy for the evaluation of CH than NAFLD.

A A 57-64 GHz High-gain Amplifier using Ultra-wideband Inductors in the IMNs and Optimization by PCA and SDSM

In this paper, the design and optimization of a cascaded common source four-stage millimeter wave amplifier in a 130 nm CMOS technology has been presented. First, Pi-shaped wideband impedance matching networks (IMNs) were used in the input / output impedance matching networks (IOIMNs) and inter-stages. Next, single stubs were converted to symmetrical double stubs in the IOIMNs and an ultra-wideband inductor replaced each stub. Ultra-wideband inductors were also used in series in the inter-stage IMNs to achieve higher gain in wider frequency bandwidth. Then, the impedance matrices of IOIMNs and inter-stages were calculated using planar circuit analysis (PCA), which is based on the planar waveguide model and segmentation/desegmentation methods (SDSM). Finally, by optimizing the length and characteristic impedance of each segment of microstrip line in the IMNs through using an intelligent algorithm in MATLAB, the excellent IMNs were designed, which resulted in an amplifier with &nbsp;, &nbsp;and &nbsp;in the frequency range of 57- 64 GHz. With this design method, in addition to incorporating the effect of discontinuities, the fringing fields at the edges of the microstrip as well as the conductor and dielectric losses, the effects of dispersion would be minimized by choosing a substrate whose thickness is much smaller than the wavelength and its relative permittivity is low.

Onset and Contiguity

Onset (metric position) and contiguity (pitch adjacency and time proximity) are two melodic features that contribute to the salience of individual notes (core tones) in a monophonic voice or polyphonic texture. Our approach to reductions prioritizes contextual features like onset and contiguity. By awarding points to notes with such features, our process selects core tones from melodic surfaces to produce a reduction. Through this reduction, a new form of musical pattern discovery is possible that has similarities to Gjerdingen’s (".fn_cite_year($gjerdingen_2007).") galant schemata. Recurring n-grams (scale degree skeletons) are matched in an algorithmic approach that we have tested manually (with a printed score and pen and paper) and implemented computationally (with symbolic data and scripted algorithms in MATLAB). A relatively simple method successfully identifies the location of all statements of the subject in Bach’s Fugue in C Minor (BWV 847) identified by Bruhn (".fn_cite_year($bruhn_1993).") and the location of all instances of the Prinner and Meyer schemata in Mozart’s Sonata in C Major (K. 545/i) identified by Gjerdingen (".fn_cite_year($gjerdingen_2007)."). We also apply the method to an excerpt by Kirnberger analyzed in Rabinovitch (".fn_cite_year($rabinovitch_2019)."). Analysts may use this flexible method for pattern discovery in reduced textures through software freely accessible at https://www.atavizm.org. While our case studies in the present article are from eighteenth-century European music, we believe our approach to reduction and pattern discovery is extensible to a variety of musics.

EvoBank: An evolutionary game solution for Bankruptcy problem

There has long been a debate surrounding the bankruptcy problem and how to share bankrupt entity inventory among its claimants. In this paper, we propose a novel inventory sharing algorithm that is based on a population game and evolutionary dynamics. In contrast with most existing sharing rules, In our approach, all claimants are involved in deciding on participating in a game. We set up a population game in which its players corespond to claimants, and available sharing rules are their actions. Then we find the asymptotically stable state of the game or Nash Equilibrium based on pairwise proportional imitation (replicator dynamics). Finally, we propose the founded equilibrium profile in the mentioned game as a novel sharing rule. According to the rationality principle in game theory, there is no profitable individual deviation from any claimants’ equilibrium profile. So, the NE profile is a self-enforcement agreement between all claimants. The implementation of our proposed algorithm in MATLAB confirms its effectiveness completely.

On Daphnia’s path: a semi‐automatic system to analyze three‐dimensional movement patterns

AbstractAnalyzing movement is essential for understanding complex behavioral interactions. Up to date, there are different movement analysis methods. Previous studies working with 2D movement analysis systems provided first insights into this field. 2D systems can capture only two of three spatial dimensions and thus allow analyses of movements on surfaces. 3D systems include all three spatial dimensions. Thus, 3D movement analysis is essential for analyzing movements in air or in water. Especially during the last years, 3D movement analysis has progressed a lot thanks to technological advances. Unfortunately, these technological advanced systems are often very expensive and handling flexibility is limited. Therefore, we implemented a customizable 3D movement analysis system for aquatic organisms. The system is composed of an experimental arena, backgrounds with different contrasts, three visible light diode spots, one infrared diode spot for analysis in the dark, and two Raspberry Pi 3 Model B V 1.2 equipped with cameras without infrared filters. We assembled a user‐friendly system that is controlled directly via a graphical user interface (GUI). It not only delivers raw data but also runs detailed analyses of common behavioral parameters. The accuracy of those analyses can be enhanced by the integrated manual error‐correction method that allows to interrupt the automatic track analysis and to correct detection errors by hand. In our case study, we show the spectrum of opportunities of the system by determining the swimming behavior of the freshwater crustacean Daphnia magna. We successfully recorded its swimming behavior under visible light and infrared light (simulating darkness for the daphniids) conditions and analyzed swimming velocity, motion patterns, depth selection, and tendency of clustering. In our case study, we show that using the integrated manual error‐correction method leads to a clear accuracy improvement. Our movement analysis system is not restricted to aquaria but can be adopted to movements in cages and even open areas of different sizes both in water or air, which emphasizes its potential. Together with a user manual, the open‐source MATLAB algorithm and the recommended hardware components, the here presented system enables semi‐automatic 3D movement analysis, which can be adapted to the individual needs.

Perancangan Sistem Deteksi Plagiarisme Skripsi (Judul Dan Abstrak) Berbasis Matlab Menggunakan Algoritma Winnowing

Plagiarism is an act of plagiarizing the work of others who will then acknowledge the work as one's own work without mentioning the source of the work. This research aims to create a plagiarism detection system using the winnowing algorithm in MATLAB to prevent plagiarism in the final project of the Mathematics Department students. In order to get the best k-gram value and window size that will be used in the system, a testing process is carried out between document I (100% data) and document II (80% data) by using variations in k-gram values ​​and window sizes. The test results show that the best k-gram ​​and window size are 12 and 4.

Significance of Nonsimilar Numerical Simulations in Forced Convection from Stretching Cylinder Subjected to External Magnetized Flow of Sisko Fluid

The practice of flowing effort is participating in various industries especially in nutrition productions all around the world. These fluids practices are utilized extensively in nutrition handling productions by making use of sticky liquids to produce valuable food manufactured goods in bulk. Nevertheless, such productions ought to guarantee that involved equipment such as pipelines are maintained clean as well as are cleared out for the efficient movement of fluids. The nonsimilar characteristics of involuntary convection from circular cylinder stretching in the axial direction subjected to an external flow of Sisko fluid characterized by the freely growing boundary layers (BL) are presented in this research. A circular cylinder is submerged in a stationary fluid. The axial stretching of the cylinder causes external fluid flow. The magnetic force of strength ″ B 0 ″ is enforced in the transverse direction. Because of the fluid's high viscosity, frictional heating due to viscous dissipation is quite significant. The flow is three dimensional but with no circumferential variations. The governing equations for axisymmetric flow that include the mass balance, x -momentum, and heat equation are modeled through conservation laws. The dimensionless system is developed by employing appropriate nonsimilar transformations. The numerical analyses are presented by adapting local nonsimilarity via finite-difference (FDM)-based MATLAB algorithm bvp4c. The characteristics of dimensionless numbers are determined by graphs that are plotted on momentum and heat equations. The nonsimilar simulations have been compared with the existing local similar solutions. Fluid velocity is increased as the material and curvature parameters are increased, resulting in improved heat transfer. The deviation in skin friction and local Nusselt number against the various dimensionless numbers is also analyzed.

Simulation model for Covid-19 pandemic

This paper outlines computer modeling algorithms designedto predict and forecast a COVID-19. In this paper, we considera deterministic model. Theongoing COVID-19 epidemic quicklyspread across the globe. Significant behavioural, social initiativesto limit city transport, case identification and touch tracking,quarantine, advice, and knowledge to the public, creationof detection kits, etc. and state measures were conducted toreduce the epidemic and eliminate coronavirus persistence inhumans around theworld from stopping the global coronavirusoutbreak. In this paper, we propose a basic SIR epidemic modelto show a simulation, the MATLAB algorithm using bouncingdots to depict safe and sick people to simulate infection spread.The graphical model shown here is implemented using MATLABpackage version 3.0.In this paper, we discuss the importance of models becausethey help one explore what could happen. They demonstratehow different possible futures might be shaped by what weare doing now. We can examine the effects of specific interventionsin different ways such as quarantine or a lockdown &amp;explore how simulations may predict, how infectious diseasesadvanced to show the possible result of an outbreak, and betterguide initiatives in public health regarding the pandemicresponse andpandemic past including an overview of the keycharacteristics of adverse pandemic consequences and epidemicoutbreak.

Optimization of control rod travel for a small pressurized water reactor

The flexible operating conditions of small pressurized water reactors (SPWRs) demand frequent movement of control rods, causing a serious problem of control rod wear and tear. This study focused on the optimization of the control rod travel for an SPWR. Three optimization strategies were proposed to improve the reactor power control scheme by introducing proportional-derivative, lead–lag, and incomplete differential control modules in the power deviation channel, and a weighting factor in the temperature deviation channel. The parameters of the three control modules and the weighting factor were tuned using the non-smooth optimization algorithm in MATLAB. The optimization strategies were implemented in a control simulation platform of the SPWR, based on which dynamic simulations of the SPWR were performed under typical load change transients at different power levels. The results demonstrate that the optimization strategies can significantly reduce the control rod travel of the SPWR with satisfactory control performance.

Optimal dimensional synthesis of one degree of freedom fixed cam-link four-bar mechanisms to generate filleted rectangular paths

Optimal dimensional synthesis of path generating mechanism with one degree of freedom to move the tool on a prescribed filleted rectangular path encompassing larger dimensions is investigated. Synthesis of these mechanisms are done using hybrid optimization combining Genetic Algorithm and Pattern Search tools of MATLAB. Dimensional synthesis of mechanisms is carried out employing harmonic spacing of precision points along straight lines and arcs of desired profile paths. A novel mechanism model method is adopted to reconstruct path points on coupler path corresponding to uniformly incremented input crank angle value of the mechanism. Synthesized links and cam are used to trace the filleted rectangular profile path and compared with the desired profile path simulating the mechanism with the help of a CAD package. Results are discussed and suggestions are proposed for future work.

Flow Structure Investigations during Novec Refrigerant Condensation in Minichannels.

This article presents the results of flow visualization studies of Novec refrigerants during condensation in minichannels. Experimental investigation of two-phase flow regimes was conducted in minichannels with internal diameter dh = 2.5, 2.0, 1.2, and 0.5 mm. Images of the two-phase flow structures were analyzed by using the MATLAB algorithm. To calculate void fraction, a two-dimensional areal quantitative stereology technique was used. Observation of flow structures formed during the process of condensation was the major aim of the investigations. The condensation studies were conducted over a wide range of mass flux densities (G = 80–5500 kg/m2s) and saturation temperatures (ts = 30–70 °C). Visualization results and image analysis methods are described in this paper. Based on the experimental results, a flow structure map was constructed and presented.

PoreScript: Semi-automated pore size algorithm for scaffold characterization

The scaffold pore size influences many critical physical aspects of tissue engineering, including tissue infiltration, biodegradation rate, and mechanical properties. Manual measurements of pore sizes from scanning electron micrographs using ImageJ/FIJI are commonly used to characterize scaffolds, but these methods are both time-consuming and subject to user bias. Current semi-automated analysis tools are limited by a lack of accessibility or limited sample size in their verification process. The work here describes the development of a new MATLAB algorithm, PoreScript, to address these limitations. The algorithm was verified using three common scaffold fabrication methods (e.g., salt leaching, gas foaming, emulsion templating) with varying pore sizes and shapes to demonstrate the versatility of this new tool. Our results demonstrate that the pore size characterization using PoreScript is comparable to manual pore size measurements. The PoreScript algorithm was further evaluated to determine the effect of user-input and image parameters (relative image magnification, pixel intensity threshold, and pore structure). Overall, this work validates the accuracy of the PoreScript algorithm across several fabrication methods and provides user-guidance for semi-automated image analysis and increased throughput of scaffold characterization.

Genetic algorithm based design optimization of crashworthy honeycomb sandwiched panels of AA7075-T651 aluminium alloy for aerospace applications

Crashworthiness studies, for decades have been an area of tremendous interest in aerospace and automotive sectors, as ensuring the safety of the occupants in the vehicle is a primary goal. Honeycomb sandwich panels are generally used for building floor, ceiling and other important fuselage parts in a commercial airliner to make the structures shock-resistant. In this work, optimization of the design of crashworthy sandwiched honeycomb structure was carried out using a non-dominated sorting genetic algorithm (NSGA) . The stated algorithm had actively monitored the variation of the geometric parameters. To study the shape effect of the cells which absorb impact energy, three cellular shapes namely hex-grid, ortho-grid and iso-grid structures were considered for analyzing their deformation behavior under impact loading. A multi objective function in the genetic algorithm was implemented in MATLAB, where the objectives were to minimize weight and to maximize the absorbed impact energy while constraining the maximum transmitted force and displacement due to crushing. Sandwiched aluminum (AA7075-T651) honeycomb structures were modeled in ABAQUS using python scripts , with the number of core cells and the wall thickness of each core cell being optimized through genetic algorithm in MATLAB using an interactive mechanism. Significant improvements were observed in terms of reduction of weight and increase in the ability to absorb the specific energy during crushing in the sandwiched panels after 450 iterations of optimization cycles. A novel methodology in the domain of crash analysis of aerostructures was established with design optimization of honeycomb sandwiched panels.