MATLAB Interface Research Articles

Numerical simulation of natural convection heat transfer in a trapezoidal enclosure filled with nanoparticles

In this paper, we have investigated unsteady natural convection flow and heat transfer inside a trapezoidal enclosure filled with nine different types of nanofluids having various shapes of the nanoparticle following Tiwari and Das mathematical model. The left and right walls of the enclosure are kept at different temperatures, while the top and bottom walls of the cavity are thermally insulated. The Galerkin weighted residual based finite element method has been employed to solve the governing partial differential equations after converting them into a nondimensional form. The simulation is carried out through the pde solver COMSOL Multiphysics with Matlab interface. Comparison with the previously published result is made for a special case and an excellent agreement is found. The effects of various model parameters such as the Rayleigh number, the aspect ratio, the volume fraction and the shape factor of the nanoparticles on streamlines and isotherms have been displayed graphically and discussed. The heat transfer augmentation for various combinations of pertinent parameters has also been presented in light of the average Nusselt number on the left heated wall.

Multi-objective optimization based tuning tool for industrial 2doF PID controllers

A computer-aided control system design tool is presented. This tool is able to take advantage of a database of Pareto optimal PID controllers. The idea is to give to the control engineer an useful tool to close the gap between the optimization procedure and the final selection of the parameters. The input to the tool are the allowed degradation of the considered cost functions, the desired level of robustness and the information of the plant, in the form of second order plus time delay model or a set of input-output data. The tool is written as a graphical user interface in MATLAB© and freely available to anyone.

Software and Hardware Code Generation for Predictive Control Using Splitting Methods

This paper presents SPLIT, a C code generation tool for Model Predictive Control (MPC) based on operator splitting methods. In contrast to existing code generation packages, SPLIT is capable of generating both software and hardware-oriented C code to allow quick prototyping of optimization algorithms on conventional CPUs and field-programmable gate arrays (FPGAs). A Matlab interface is provided for compatibility with existing commercial and open-source software packages. A numerical study compares software, hardware and heterogeneous implementations of splitting methods and investigates MPC design trade-offs. For the considered testcases the reported speedup of hardware implementations over software realizations is 3x to 11x.

A Low-cost Laboratory Experiment Setup for Frequency Domain Analysis for a Feedback Control Systems Course

Increasing need in automation systems increases the need for control engineers that have practical experience from their undergraduate education. Having abstract mathematical concepts and condense theoretical materials, Feedback Control Systems classes are not generally well-comprehended by undergraduate students. In this paper, we propose a low-cost laboratory setup for Feedback Control Systems education to support learning of frequency domain characteristics of LTI systems. The proposed setup works based on identification and control of a DC motor and includes Matlab interface to be programmed by high level control design tools such as Simulink. This paper shows how students can experimentally validate the concepts like Bode plots, gain margin, phase margin and delay margin.

Error-Free Text Typing Performance of an Inductive Intra-Oral Tongue Computer Interface for Severely Disabled Individuals.

For severely paralyzed individuals, alternative computer interfaces are becoming increasingly essential for everyday life as social and vocational activities are facilitated by information technology and as the environment becomes more automatic and remotely controllable. Tongue computer interfaces have proven to be desirable by the users partly due to their high degree of aesthetic acceptability, but so far the mature systems have shown a relatively low error-free text typing efficiency. This paper evaluated the intra-oral inductive tongue computer interface (ITCI) in its intended use: Error-free text typing in a generally available text editing system, Word. Individuals with tetraplegia and able bodied individuals used the ITCI for typing using a MATLAB interface and for Word typing for 4 to 5 experimental days, and the results showed an average error-free text typing rate in Word of 11.6 correct characters/min across all participants and of 15.5 correct characters/min for participants familiar with tongue piercings. Improvements in typing rates between the sessions suggest that typing ratescan be improved further through long-term use of the ITCI.

Sleep spindle detection based on non-experts: A validation study.

Accurate and efficient detection of sleep spindles is a methodological challenge. The present study describes a method of using non-experts for manual detection of sleep spindles. We recruited five experts and 168 non-experts to manually identify spindles in stage N2 and stage N3 sleep data using a MATLAB interface. Scorers classified each spindle into definite and indefinite spindle (with weights of 1 and 0.5, respectively). First, a method of optimizing the thresholds of the expert/non-expert group consensus according to the results of experts and non-experts themselves is described. Using this method, we established expert and non-expert group standards from expert and non-expert scorers, respectively, and evaluated the performance of the non-expert group standards by compared with the expert group standard (termed EGS). The results indicated that the highest performance was the non-expert group standard when definite spindles were only considered (termed nEGS-1; F1 score = 0.78 for N2; 0.68 for N3). Second, four automatic spindle detection methods were compared with the EGS. We found that the performance of nEGS-1 versus EGS was higher than that of the four automated methods. Our results also showed positive correlation between the mean F1 score of individual expert in EGS and the F1 score of nEGS-1 versus EGS across 30 segments of stage N2 data (r = 0.61, P < 0.001). Further, we found that six and nine non-experts were needed to manually identify spindles in stages N2 and N3, respectively, while maintaining acceptable performance of nEGS-1 versus EGS (F1 score = 0.79 for N2; 0.64 for N3). In conclusion, this study establishes a detailed process for detection of sleep spindles by non-experts in a crowdsourcing scheme.

Combining turning point detection and Dijkstra’s algorithm to search the shortest path

In this study, image processing was combined with path-planning object-avoidance technology to determine the shortest path to the destination. The content of this article comprises two parts: in the first part, image processing was used to establish a model of obstacle distribution in the environment, and boundary sequence permutation method was used to conduct orderly arrangement of edge point coordinates of all objects, to determine linking relationship between each edge point, and to individually classify objects in the image. Then, turning point detection method was used to compare the angle size between vectors before and after each edge point and to determine vertex coordinates of polygonal obstacles. In the second part, a modified Dijkstra’s algorithm was used to turn vertices of convex-shaped obstacles into network nodes, to determine the shortest path by a cost function, and to find an obstacle avoidance path connecting the start and end points. In order to verify the feasibility of the proposed architecture, an obstacle avoidance path simulation was made by the graphical user interface of the programming language MATLAB. The results show that the proposed method in path planning not only is feasible but can also obtain good results.

Optoelectronic polarimeter controlled by a graphical user interface of Matlab

We show the design and implementation of an optical polarimeter using electronic control. The polarimeter has a software with a graphical user interface (GUI) that controls the optoelectronic setup and captures the optical intensity measurement, and finally, this software evaluates the Stokes vector of a state of polarization (SOP) by means of the synchronous detection of optical waves. The proposed optoelectronic polarimeter can determine the Stokes vector of a SOP in a rapid and efficient way. Using the polarimeter proposed in this paper, the students will be able to observe (in an optical bench) and understand the different interactions of the SOP when the optical waves pass through to the linear polarizers and retarder waves plates. The polarimeter prototype could be used as a main tool for the students in order to learn the theory and experimental aspects of the SOP for optical waves via the Stokes vector measurement. The proposed polarimeter controlled by a GUI of Matlab is more attractive and suitable to teach and to learn the polarization of optical waves.

Colour based sorting station with Matlab simulation

The paper presents the design process and manufacturing elements of a colour-based sorting station. The system is comprised of a gravitational storage, which also contains the colour sensor. Parts are extracted using a linear pneumatic motor and are fed onto an electrically driven conveyor belt. Extraction of the parts is done at 4 points, using two pneumatic motors and a geared DC motor, while the 4th position is at the end of the belt. The mechanical parts of the system are manufactured using 3D printer technology, allowing for easy modification and adaption to the geometry of different parts. The paper shows all of the stages needed to design, optimize, test and implement the proposed solution. System optimization was performed using a graphical Matlab interface which also allows for sorting algorithm optimization.

Parameter estimation for dynamical systems with discrete events and logical operations.

Ordinary differential equation (ODE) models are frequently used to describe the dynamic behaviour of biochemical processes. Such ODE models are often extended by events to describe the effect of fast latent processes on the process dynamics. To exploit the predictive power of ODE models, their parameters have to be inferred from experimental data. For models without events, gradient based optimization schemes perform well for parameter estimation, when sensitivity equations are used for gradient computation. Yet, sensitivity equations for models with parameter- and state-dependent events and event-triggered observations are not supported by existing toolboxes. In this manuscript, we describe the sensitivity equations for differential equation models with events and demonstrate how to estimate parameters from event-resolved data using event-triggered observations in parameter estimation. We consider a model for GFP expression after transfection and a model for spiking neurons and demonstrate that we can improve computational efficiency and robustness of parameter estimation by using sensitivity equations for systems with events. Moreover, we demonstrate that, by using event-outputs, it is possible to consider event-resolved data, such as time-to-event data, for parameter estimation with ODE models. By providing a user-friendly, modular implementation in the toolbox AMICI, the developed methods are made publicly available and can be integrated in other systems biology toolboxes. We implement the methods in the open-source toolbox Advanced MATLAB Interface for CVODES and IDAS (AMICI, https://github.com/ICB-DCM/AMICI ). jan.hasenauer@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

Kinect as a Generalised Interface for Games and PC Control

The use of motion controllers and cameras such as Microsoft Kinect as a gaming peripheral have increased the immersion of computer games today. Moving to using gestures instead of conventional handheld game controllers has increased the interest of players. Xbox 360, Xbox-One and the games that have been developed to be used with Kinect enable users to play using gestures, but this limits us to play our old favorite games and the new non-Kinect based games with same conventional peripherals. To overcome this limitation, we have developed a user friendly interface in MATLAB that replaces keyboard and mouse controls with our own designed gestures and enables us to play all non-Kinect based games using Kinect. For testing and demonstration purpose, we have applied the developed interface to three games which are Counter-Strike Global Offense, Candy Crush and Asphalt 8 Airborne.

Development of Exterior Wall Painting Robot

Objective: Exterior wall painting is one of the major tasks in con-struction field. For apartment building exterior wall painting is risky. Painter will be hanging on the wall with support of rope. While painting the painter has to slide down carefully, even sometimes need to move left and right along the wall. There is a chance of falling if not alert. Method: In this paper, research is carried out for development of exterior wall painting robot (PAINTBOT-EW). Hardware is divided into two sectors, robot and suspension system. Robot is fabricated by attaching paint feed roller to the frame. DC motor drives the roller ver-tically up and down on the frame using rotating disc and connecting rod. Robot is connected to the cables at top right and left corners. The other ends of cables are connected to DC geared motors through the pulleys mounted on the wall at required distance. UI part includes cre-ating Graphical User Interface (GUI) in MATLAB, coding the program and to control the movement of the robot using Arduino Uno. Find-ings: From experiments it is observed that painting robot covers 2 square feet area of wall approximately in 34 mins as the stroke length of the roller is found to be 28 cm. Alignment of robot while moving from one co-ordinate to other may vary but once it reaches the required co-ordinate it aligns itself straight. Motors which were fixed to the robot for movement; in earlier, robot was attached to the ground in order to reduce vibrations generated in robot. As well as continuous paint flow is maintained while painting using pump which is not possible in case of compressor used in earlier robot. Applications: Wall painting is carried out with 65% reduction in cost along with reduction in vibrations generated in the earlier model.

MARE2DEM: a 2-D inversion code for controlled-source electromagnetic and magnetotelluric data

This work presents MARE2DEM, a freely available code for 2-D anisotropic inversion of magnetotelluric (MT) data and frequency-domain controlled-source electromagnetic (CSEM) data from onshore and offshore surveys. MARE2DEM parametrizes the inverse model using a grid of arbitrarily shaped polygons, where unstructured triangular or quadrilateral grids are typically used due to their ease of construction. Unstructured grids provide significantly more geometric flexibility and parameter efficiency than the structured rectangular grids commonly used by most other inversion codes. Transmitter and receiver components located on topographic slopes can be tilted parallel to the boundary so that the simulated electromagnetic fields accurately reproduce the real survey geometry. The forward solution is implemented with a goal-oriented adaptive finite-element method that automatically generates and refines unstructured triangular element grids that conform to the inversion parameter grid, ensuring accurate responses as the model conductivity changes. This dual-grid approach is significantly more efficient than the conventional use of a single grid for both the forward and inverse meshes since the more detailed finite-element meshes required for accurate responses do not increase the memory requirements of the inverse problem. Forward solutions are computed in parallel with a highly efficient scaling by partitioning the data into smaller independent modeling tasks consisting of subsets of the input frequencies, transmitters and receivers. Non-linear inversion is carried out with a new Occam inversion approach that requires fewer forward calls. Dense matrix operations are optimized for memory and parallel scalability using the ScaLAPACK parallel library. Free parameters can be bounded using a new non-linear transformation that leaves the transformed parameters nearly the same as the original parameters within the bounds, thereby reducing non-linear smoothing effects. Data balancing normalization weights for the joint inversion of two or more data sets encourages the inversion to fit each data type equally well. A synthetic joint inversion of marine CSEM and MT data illustrates the algorithm's performance and parallel scaling on up to 480 processing cores. CSEM inversion of data from the Middle America Trench offshore Nicaragua demonstrates a real world application. The source code and MATLAB interface tools are freely available at http://mare2dem.ucsd.edu.

VEMI: a flexible interface for 3D tomographic inversion of time‐ and frequency‐domain electrical data in EIDORS

ABSTRACTThe aim of this work is to present a MATLAB interface called Versatile interface for Electrical data Modelling and Inversion included in the EIDORS software. The interface is able to invert 2D and 3D electrical data acquired in the time or the frequency domain, both for cylindrical and prismatic geometries. Therefore, it can be a flexible tool for inversion of both real‐ and complex‐valued resistivity tomography data acquired in the laboratory and in the field. The forward solver has been proved to be stable and accurate through a comparison with an analytical solution, whereas the inverse solution, achieved through a Gauss‐Newton routine with an optimised damping inner loop, can be performed with the help of other useful tools incorporating a priori information in the inversion process. The reliability of the Versatile interface for Electrical data Modelling and Inversion has been tested through a 3D laboratory example, where both time‐ and frequency‐domain data and two 3D field example with time‐domain data were acquired. The 3D laboratory example, simulating a shallow aquifer contaminated by a chlorinated solvent (hydrofluoroether), demonstrated the reliability of the Versatile interface for Electrical data Modelling and Inversion to detect the contaminant pathway within the physical model. Hydrofluoroether is clearly visible on phase and chargeability models, where the highest phase values are located underneath the spilling point, even though it remains undistinguishable in the resistivity and amplitude ones. Through the combined analysis of the inverted chargeability and phase models, we can reduce the degree of uncertainty in the interpretation of geophysical models. These results were also validated through comparison with the respective synthetic models simulated in a previous paper by the same authors. Real‐world tests have been performed on a closed landfill where few a priori information are available about the original design and on an industrial site contaminated by chlorinated solvents. In the former case, we reconstruct a three‐layer configuration (covering, waste and bottom liner), where the effective layering inferred from the resistivity model is confirmed by the chargeability one. In the latter case, we detect the chlorinated solvents within the deeper aquifer through a combined analysis of the resistivity and chargeability models, where the very high resistivity values are associated with high chargeability.

HybridMT: A MATLAB/Shell Environment Package for Seismic Moment Tensor Inversion and Refinement

We present the software package hybridMT which allows performing seismic moment tensor inversion and refinement, optimized for earthquake data recorded by regional‐to‐local seismic networks as well as for acoustic emission activity. The provided software package is designed predominantly for use in MATLAB (see [Data and Resources][1])/shell environments. The algorithm uses first P ‐wave amplitudes to invert for unconstrained full, deviatoric, and double‐couple constrained moment tensors. Uncertainty assessment is performed by bootstrap resampling. The moment tensor inversion may be performed directly in the shell environment (by a dedicated command‐line tool) or conveniently through the MATLAB interface (m‐functions). In addition to moment tensor inversion, we also provide the MATLAB implementation of the hybrid moment tensor technique. This methodology increases the quality of calculated seismic moment tensors from events forming a spatial cluster by assessing and correcting for poorly known path and site effects. We tested hybridMT on synthetic datasets, acoustic emission data recorded during laboratory rock deformation experiments, and induced seismicity data from a geothermal reservoir. The package is supplemented with extensive documentation, tutorials, and a dedicated website. HybridMT is freely available and distributed under General Public License. [1]: #sec-10

Demand side management scheme in smart grid with cloud computing approach using stochastic dynamic programming

Summary This paper proposes a cloud computing framework in smart grid environment by creating small integrated energy hub supporting real time computing for handling huge storage of data. A stochastic programming approach model is developed with cloud computing scheme for effective demand side management (DSM) in smart grid. Simulation results are obtained using GUI interface and Gurobi optimizer in Matlab in order to reduce the electricity demand by creating energy networks in a smart hub approach.

A Matlab based interface for infrared thermographic diagnosis of pediatric musculoskeletal injuries

Background and objectiveOne of the main causes of emergency medical consultations done by children are musculoskeletal injures. In such cases, radiological tests are a common practice to diagnose the gravity of the trauma and determine the likely existence of a fracture. In order to avoid, or at least to reduce, the use of ionizing radiations with children, the infrared thermographic technique was studied as an alternative solution, since it is a non-harmful, non-invasive and non-contact technique, without excessive technical complications and moderate cost when compared to other types of imaging tools. MethodologyWhen an infrared thermographic diagnostic test is performed, and once the pictures of the studied limb are taken accordingly to the established methodology, an imaging post-processing protocol becomes necessary to make a correct interpretation and diagnosis. Aimed at performing the analysis in situ and in real time, in this work we present a software tool based on a Matlab interface. The software programming is based on the results obtained in clinical tests, where several variables were took into consideration. The program is able to determine the probability of fracture basing the diagnosis on a non-linear cataloguing approach, using decision trees. ResultsThe tool implemented allows to diagnose musculoskeletal injures in children shortly after taking the infrared thermographic picture. ConclusionsThe diagnosis tool provides the means for the interpretation of the IT pictures, allows to obtain a diagnosis in a fast way, and may help to decrease the radiation doses in children.

Graphical processing unit (GPU) acceleration for numerical solution of population balance models using high resolution finite volume algorithm

Abstract Population balance modeling is a widely used approach to describe crystallization processes. It can be extended to multivariate cases where more internal coordinates i.e., particle properties such as multiple characteristic sizes, composition, purity, etc. can be used. The current study presents highly efficient fully discretized parallel implementation of the high resolution finite volume technique implemented on graphical processing units (GPUs) for the solution of single- and multi-dimensional population balance models (PBMs). The proposed GPU-PBM is implemented using CUDA C++ code for GPU calculations and provides a generic Matlab interface for easy application for scientific computing. The case studies demonstrate that the code running on the GPU is between 2–40 times faster than the compiled C++ code and 50–250 times faster than the standard MatLab implementation. This significant improvement in computational time enables the application of model-based control approaches in real time even in case of multidimensional population balance models.

Sensor RGB para detectar cambios de color en piel de frutas

In this work an optical sensing setup is designed and implemented to estimate the ripening in fruits. Here by white light reflected signal the color fruit can be calculated to provide information about the fruit condition. The main components in the proposed system are red, green and blue (RGB) module, photodetector and an optical plastic fiber. Moreover the sensing system is compact and versatile, due to the light signal used in the system can me adequate according to some fruit requirements by using a Labview interface, besides the detection and result displaying is proposed by a microcontroller device and Matlab interface. In order to demonstrated the system proposed a guava fruit was used to show the evolution color changes during its ripeness.

Machine learning for solar irradiance forecasting of photovoltaic system

Photovoltaic generation of electricity is an important renewable energy source, and large numbers of relatively small photovoltaic systems are proliferating around the world. Today it is widely acknowledged by power producers, utility companies and independent system operators that it is only through advanced forecasting, communications and control that these distributed resources can collectively provide a firm, dispatchable generation capacity to the electricity market. One of the challenges of realizing such a goal is the precise forecasting of the output of individual photovoltaic systems, which is affected by a lot of factors. This paper introduces our short-term solar irradiance forecasting algorithms based on machine learning methodologies, Hidden Markov Model and SVM regression. A series of experimental evaluations are presented to analyze the relative performance of the techniques in order to show the importance of these methodologies. The Matlab interface, the Weather Forecasting Platform, has been used for these evaluations. The experiments are performed using the dataset generated by Australian Bureau of Meteorology. The experimental results show that our machine learning based forecasting algorithms can precisely predict future 5–30 min solar irradiance under different weather conditions.