MATLAB Interface Research Articles

Thermal Performance of Cattaneo-Christov Heat Flux in MHD Radiative Flow of Williamson Nanofluid Containing Motile Microorganisms and Arrhenius Activation Energy

The aim of this study is to characterize the Cattaneo-Christov heat flux in magnetohydrodynamics (MHD) radiative flow of Williamson nanofluid through a stretched sheet when confronted with heat source, Arrhenius activation energy and motile microorganisms. Also, the Darcy-Forchheimer model is a widely used and precise technique for modeling fluid dynamics in porous medium. The controlling partial differential equations (PDE) are minimized to ordinary differential equations (ODE) using suitable similarities. The final outcomes were computed numerically using the BVP4C MATLAB interface. The graphical portrayal serves to comprehensively show and build upon the effect of several aspects. The results reveal the increased velocity distribution with the intensifying values of magnetic field, porosity, suction, and Forchheimer number. The thermal gradient is enhanced with the increase in heat source, and radiation, while it diminishes with the augmentation of the thermal relaxation parameter. Furthermore, the concentration maximizes when the activation energy is large. This research shows a favorable link between Peclet quantity and motile microbe density. Additionally, this work numerically analyses and tabulates important engineering metrics such as skin friction, Nusselt number, Sherwood number, and motile density number. The present study has huge interest due to its applications such as food processing, crystal formation in rocks, microelectronic semiconductors, crystal fiber, electronic power plants, and many more.

Pliocene shorelines and the epeirogenic motion of continental margins: a target dataset for dynamic topography models

Abstract. Global mean sea level during the mid-Pliocene epoch (∼3 Ma), when CO2 and temperatures were above present levels, was notably higher than today due to reduced global ice sheet coverage. Nevertheless, the extent to which ice sheets responded to Pliocene warmth remains in question owing to high levels of uncertainty in proxy-based sea level reconstructions as well as solid Earth dynamic models that have been used to evaluate a limited number of data constraints. Here, we present a global dataset of 10 wave-cut scarps that formed by successive Pliocene sea level oscillations and which are observed today at elevations ranging from ∼6 to 109 m above sea level. The present-day elevations of these features have been identified using a combination of high-resolution digital elevation models and field mapping. Using the MATLAB interface TerraceM, we extrapolate the cliff and platform surfaces to determine the elevation of the scarp toe, which in most settings is buried under meters of talus. We correct the scarp-toe elevations for glacial isostatic adjustment and find that this process alone cannot explain observed differences in Pliocene paleo-shoreline elevations around the globe. We next determine the signal associated with mantle dynamic topography by back-advecting the present-day three-dimensional buoyancy structure of the mantle and calculating the difference in radial surface stresses over the last 3 Myr using the convection code ASPECT. We include a wide range of present-day mantle structures (buoyancy and viscosity) constrained by seismic tomography models, geodynamic observations, and rock mechanics laboratory experiments. Finally, we identify preferred dynamic topography change predictions based on their agreement with scarp elevations and use our most confident result to estimate a Pliocene global mean sea level based on one scarp from De Hoop, South Africa. This inference (11.6 ± 5.2 m) is a downward revision and may imply that ice sheets were relatively resistant to warm Pliocene climate conditions. We also conclude, however, that more targeted model development is needed to more reliably infer mid-Pliocene global mean sea level based on all scarps mapped in this study.

Graphical Interface in MATLAB for design and analysis of reflectors for lighting systems or solar collectors on parabolic surfaces

This project introduces the successful development of a MATLAB graphical interface for the design and analysis of reflectors and solar concentrators on parabolic surfaces. The integration of spline techniques for precise modeling of these surfaces has been implemented, along with the capability to generate STL files for 3D printing. The interface not only enables detailed and adaptable design of reflectors but also includes an advanced simulator for projecting incident rays and analyzing their reflection on the parabolic surface, focusing specifically on the focal point location. This has led to a significant increase in the efficiency of solar concentrators and lighting systems by enabling the precise placement of absorbers to maximize energy transfer. The obtained results confirm the initial hypothesis, demonstrating that the interface enhances the precision and efficiency in the design of these systems, thereby offering a valuable tool in both educational and professional realms in the fields of solar energy and lighting.

High Speed Monitoring System for Electrical Equipments.

The modern electric equipments include performant monitoring systems based on microcontrollers. The hardware architecture and software structure depend on the application. The paper deals with an experimental monitoring system developed based on a versatile microcontroller and suited transducers, as well as with the user interface that allows the on-line configuration of the hardware system. In order to obtain an optimised code, the assembling programming was chosen, by using the well developed interruption system of the microcontroller. The user interface was developed by the way of Graphic User Interface of Matlab.

Response surface optimization and support vector regression modeling of microwave-assisted essential oil extraction from cumin seeds

The current research involved creating models using Response Surface Methodology (RSM) and Support Vector Regression (SVR) to forecast the amount of extractable essential oil that can be obtained from powdered cumin seeds. Influence of microwave power (140–280–420–560–700 W), amount of water (500–600–700–800–900 ml), duration of distillation (30–45–60–75–90 min) and soak time (15–30–45–60–75 min) on essential oil yield were investigated. Microwave Assisted Extraction (MAE) allowed higher recoveries compared to conventional Soxhlet extraction, without altering the chemical components of the extract. A five-level four FCC experimental design was developed using Minitab (15.1.20.0). A total of 31 runs were performed in microwave-assisted extraction apparatus. Experimental data obtained was then used for developing RSM and SVR models for the prediction of the yield of essential oil. The optimum conditions for maximum yield of cumin oil were given by RSM. Maximum yield of 3.4 ml (0.017 ml/g) was found at 140 W of microwave power, 500 ml of water, 90 min duration of distillation, and 15 min of soak time. In this work, epsilon SVR with RBF kernel was used. The grid search (depth-first search) methodology was applied for tuning the values of epsilon, gamma, and cost using the LIBSVM module on the MATLAB interface. The statistical parameters namely, average absolute relative error (AARE), coefficient of determination (R2), standard deviation (SD), and root mean square error (RMSE) were selected as the performance parameters. The developed SVR model was compared with the RSM model. The AARE values of 2.27% and 1.29%, R2 values of 0.86 and 0.99, SD values of 1.73 and 0.29, and RMSE values of 0.0284 and 0.0132 were obtained for RSM and SVR models respectively. It is found that SVR is more accurate and better tool for modeling of MAE process.

Integrating hydro and wind resources for effective congestion management in a hybrid electricity market

Congestion management in deregulated electricity systems threatens system security and reliability. Integration of renewable energy sources, unpredictable wind power, load demand, and the requirement for quickly deployable reserves make congestion management more difficult. While deciding the dispatch of the generating units, many factors have to be considered for the economic, secure, and reliable operation of the power system. This study presents a congestion management strategy that has been developed specifically for hybrid power systems. Within a pool and bilateral power supply market structure, it introduces a generator rescheduling-based congestion management technique. Ensuring safe bilateral transactions between these companies is crucial. Renewable sources affect congestion management dynamics, according to the research. The optimization issue includes operational limitations for scenarios with and without renewable source units. Monte Carlo simulation (MCS) was used to sample hourly wind speed from the Weibull PDF wind model. GAMS CONOPT solver used the model. General Algebraic Modeling System (GAMS)-MATLAB interface imported the model into MATLAB to extract the response. The best combination of renewable sources is 2 hydro + 1 wind unit as savings of congestion cost are $1403.6/h and $1855.18/h in case 1 (3-line congestion) and case 2 (2-line congestion), respectively. Results were accomplished by updating the IEEE-24 bus reliability test system with hydro and wind generators.

A Study of Engineering Student IQ and EQ Based on Analyzing of Electroencephalogram (EEG) Signals

This paper elaborates about the analyzing of Intelligent Quotient (IQ) and Emotional Quotient (EQ) of an engineering student based on Electroencephalogram (EEG) or brain signals using a computing tool such as MATLAB. The influence of individual’s IQ and EQ on the development of innovative thinking is significant. An IQ alone is not adequate to measure the success of a person. An EQ somehow is found to have a substantial correlation with individual’s performance which shows that both IQ and EQ are important in determining the character and manner of individual’s thinking skills. The main objective of this project is to analyze the output of EEG signals produced by an engineering student based on their IQ and EQ level. A comparison of which quotient influences the student’s thinking skill is also observed in this study. In this project, a single channel EEG amplifier is used to record the EEG signals from 6 different subjects with three different conditions: while not doing anything, during an IQ test and during an EQ test. The data is recorded using the EEG sensors with Unicorn Recorder software that is connected to the amplifier while recording is run. The result of the experiment also explained in terms of the mean value and standard deviation of the EEG bands for each subject and condition. The results of the study conclude that the IQ level of an individual is affected by the Beta band of the EEG signals. Meanwhile, Alpha band of the EEG signals is more dominant in the determination of EQ level of an individual. When Alpha band is higher than Beta band, it shows that the subject is dominant to an EQ dominant person. If Beta band is higher than Alpha band, then IQ is the dominant quotient for the subject. The highest k-NN classification accuracy is obtained at 80:20 classification with 81.84% accuracy using Mean features and 79.53% accuracy using Standard Deviaton features. This study also included the development of Graphical User Interface (GUI) in MATLAB. The GUI is used for the classification of the chosen EEG features. Theta, Alpha, and Beta power band are observed from the EEG signals to identify brain activity. In addition, IQ and EQ analyzer is constructed using Arduino microcontroller once the analysis of the EEG signals are done through GUI.

Eksplorasi Motif Geblek Renteng: Aplikasi Grup Kristalografi dengan Graphical User Interface (GUI)

Geblek is one of Kulon Progo's specialty foods made from cassava flour with a shape resembling a figure eight. Geblek is the main pattern used in the batik typical of Kulon Progo. The batik motif uses repetitive and symmetrical patterns. The application of mathematics, especially cryptography, can be used to find repetitive patterns that can inspire batik motifs. This research aims to describe how a basic geblek pattern from Kulon Progo can be transformed into various other patterns using the concept of plane crystallography. The geblek pattern is applied to 17 crystallographic groups, resulting in 17 batik motifs. The use of Graphical User Interface (GUI) in MATLAB will make it easier to form batik motifs. Based on the exploration results, 17 patterns were derived from the basic pattern of Kuln Progo geblek. Uniquely, from these 17 patterns, there are the same and similar patterns. In other words, the patterns found from the basic geblek pattern do not reach 17 patterns. The development pattern of Kulon Progo geblek is further described in this article.

Thermodynamic analysis of cumene production plant for identification of energy recovery potentials

In this work, exergy analysis of cumene production plant is carried out in an integrated environment of Aspen Plus and MATLAB. Physical exergy is calculated in Aspen plus V.10 while an interface of MATLAB and Aspen plus was used to calculate chemical exergy of the process. For systematic analysis and comparison, the cumene plant is divided into three sections: preheating section, reaction section and separation section. Then exergy efficiency, irreversibilities, and exergetic improvement potential were calculated. The overall plant exergy efficiency, irreversibility, and improvement potential were 84.93%, 95960.52 kW and 15102.5 kW respectively. The reaction section had the highest exergy efficiency of 87.44%, while the separation section had the lowest exergy efficiency of 58.95%. The analyses performed in this study will provide a basis for optimization of design and operation of the plant.

An in-depth thermo-electrical evaluation of a rooftop PV technology for a residential building using advanced infrared thermography

The investigated performance criteria of photovoltaic (PV) modules in the studies have been limited to current, voltage, power, and temperature. It means that a study with the aim of a comprehensive investigation of a number of key thermo-electrical indicators of the system, namely, photocurrent (Iph), parallel resistance (Rp), thermal voltage of diode (Vt), and diode reverse saturation current (I0), has not been done yet. Considering this point, a PV system installed on the roof of a residential building in Tehran, Iran, is experimentally studied here. For this system, the data gathered during a year is employed to find the values of the four indicated thermo-electrical characteristics. In order to enhance the accuracy, advanced infrared thermography is utilized, in which the photos taken by the thermal imaging camera is processed with developed code on the MATLAB interface. The results show that thermo-electrical indicators of the PV system change significantly throughout the year. With 32.3%, Vt is the indicator with the lowest annual variation. Rp and Iph change 1004.1 and 1943.9%, respectively, as well. Moreover, the simultaneous application of cooling techniques and concentrating strategies is suggested as a very efficient way to enhance the system performance.

PV Characterization and MPPT Based on Characteristic Impedance Using Arduino Board and MATLAB Interface

PV Characterization and MPPT Based on Characteristic Impedance Using Arduino Board and MATLAB Interface

Kinematic Analysis of Constrained General Planner Mechanisms Using MATLAB Graphical User Interface (GUI)

Mechanisms are significant in mechanical engineering as they are required for proper motion transition. This work studies the kinematic analysis of the planar mechanisms using constraint properties between links and joints. A joint library has been built by two types of joints (revolute and prismatic) and has been modeled to be extended in the future. The Kinematic Analysis of General Planer Mechanisms (KAGPM) has been described and implemented through the Graphical User Interface in MATLAB. The Newton-Raphson method was utilized as a numerically computational technique to resolve the kinematic constraint equations. The proposed KAGPM program has been in the kinematic analysis of a slider crank mechanism for the purpose of validation with Haug. For more validation of the program, the effects of some effective parameters have been investigated (the geometric of the mechanism, the initial conditions, and the transient of the mechanism).

MISARA: Matlab Interface for Seismo-Acoustic aRray Analysis

AbstractVolcanic activity produces a broad spectrum of seismic and acoustic signals whose characteristics provide important clues on the underlying magmatic processes. Networks and arrays of seismic and acoustic sensors are the backbone of most modern volcano monitoring programs. Investigation of the signals gathered by these instruments requires efficient workflows and specialist software. The high sampling rates, typically 50 Hz or greater, at which seismic and acoustic waveforms are recorded by multistation networks and dense arrays leads to the rapid accumulation of large volumes of data, making the implementation of efficient data analysis workflows for volcano surveillance a challenging task. Here, we present an open-source MATLAB graphical user interface, MISARA (Matlab Interface for Seismo-Acoustic aRray Analysis), designed to provide a user-friendly workflow for the analysis of seismoacoustic data in volcanic environments. MISARA includes efficient algorithm implementations of well-established techniques for seismic and acoustic data analysis. It is designed to support visualization, characterization, detection, and location of volcano seismoacoustic signals. Its intuitive, modular, structure facilitates rapid, semiautomated, inspection of data and results, thus reducing user effort. MISARA was tested using seismoacoustic data recorded at Etna Volcano (Italy) in 2010, 2011, and 2019, and is intended for use in education and research, and to support routine data analysis at volcano observatories.

A collaborative hybrid approach for integrated tolerance allocation

ABSTRACT In concurrent engineering era, the collaboration between engineering and manufacturing is a vital condition for remaining competitive. For that, an interactive computer-aided design method is required for optimal tolerance allocation. In this regard, dimension transfer and tolerance allocation approaches serve as crucial tools for design engineers to reduce the total manufacturing cost of mechanical assembly as well as to ameliorate the product quality. This paper proposes an efficient collaborative hybrid tool for computer-aided integration to an optimal tolerance allocation based on a combination of unique transfer and difficulty coefficient evaluation. The tolerance allocation approach is based on manufacturing difficulty quantification using tools for the study and analysis of reliability of the design or the process, as the Failure Mode, Effects and Criticality Analysis and Ishikawa diagram. The proposed method is performed to produce allocated tolerances according to difficulty requirements to reach a mechanical assembly with high quality and low cost. To validate the proposed concepts and methods, an integrated tool is implemented using graphical user interface in MATLAB. Hence, an Integrated CAT tool for Dimension Transfer and Tolerance Allocation, named CAD_DT&TA, is proposed to expose various tolerance allocation approaches respecting functional and manufacturing requirements. Several examples can be executed using the proposed interface to highlight the benefits of the accomplished integrated tool. The results identify the real benefits of the innovative dimension transfer and tolerance allocation approach as reducing total cost and improving the quality of assembly product.

A Novel Automatic Audiometric System Design Based on Machine Learning Methods Using the Brain's Electrical Activity Signals.

This study uses machine learning to perform the hearing test (audiometry) processes autonomously with EEG signals. Sounds with different amplitudes and wavelengths given to the person tested in standard hearing tests are assigned randomly with the interface designed with MATLAB GUI. The person stated that he heard the random size sounds he listened to with headphones but did not take action if he did not hear them. Simultaneously, EEG (electro-encephalography) signals were followed, and the waves created in the brain by the sounds that the person attended and did not hear were recorded. EEG data generated at the end of the test were pre-processed, and then feature extraction was performed. The heard and unheard information received from the MATLAB interface was combined with the EEG signals, and it was determined which sounds the person heard and which they did not hear. During the waiting period between the sounds given via the interface, no sound was given to the person. Therefore, these times are marked as not heard in EEG signals. In this study, brain signals were measured with Brain Products Vamp 16 EEG device, and then EEG raw data were created using the Brain Vision Recorder program and MATLAB. After the data set was created from the signal data produced by the heard and unheard sounds in the brain, machine learning processes were carried out with the PYTHON programming language. The raw data created with MATLAB was taken with the Python programming language, and after the pre-processing steps were completed, machine learning methods were applied to the classification algorithms. Each raw EEG data has been detected by the Count Vectorizer method. The importance of each EEG signal in all EEG data has been calculated using the TF-IDF (Term Frequency-Inverse Document Frequency) method. The obtained dataset has been classified according to whether people can hear the sound. Naïve Bayes, Light Gradient Strengthening Machine (LGBM), support vector machine (SVM), decision tree, k-NN, logistic regression, and random forest classifier algorithms have been applied in the analysis. The algorithms selected in our study were preferred because they showed superior performance in ML and succeeded in analyzing EEG signals. Selected classification algorithms also have features of being used online. Naïve Bayes, Light Gradient Strengthening Machine (LGBM), support vector machine (SVM), decision tree, k-NN, logistic regression, and random forest classifier algorithms were used. In the analysis of EEG signals, Light Gradient Strengthening Machine (LGBM) was obtained as the best method. It was determined that the most successful algorithm in prediction was the prediction of the LGBM classification algorithm, with a success rate of 84%. This study has revealed that hearing tests can also be performed using brain waves detected by an EEG device. Although a completely independent hearing test can be created, an audiologist or doctor may be needed to evaluate the results.

Guidelines for the Simulations of Nitroxide X-Band cw EPR Spectra from Site-Directed Spin Labeling Experiments Using SimLabel.

Site-directed spin labeling (SDSL) combined with continuous wave electron paramagnetic resonance (cw EPR) spectroscopy is a powerful technique to reveal, at the local level, the dynamics of structural transitions in proteins. Here, we consider SDSL-EPR based on the selective grafting of a nitroxide on the protein under study, followed by X-band cw EPR analysis. To extract valuable quantitative information from SDSL-EPR spectra and thus give a reliable interpretation on biological system dynamics, a numerical simulation of the spectra is required. However, regardless of the numerical tool chosen to perform such simulations, the number of parameters is often too high to provide unambiguous results. In this study, we have chosen SimLabel to perform such simulations. SimLabel is a graphical user interface (GUI) of Matlab, using some functions of Easyspin. An exhaustive review of the parameters used in this GUI has enabled to define the adjustable parameters during the simulation fitting and to fix the others prior to the simulation fitting. Among them, some are set once and for all (gy, gz) and others are determined (Az, gx) thanks to a supplementary X-band spectrum recorded on a frozen solution. Finally, we propose guidelines to perform the simulation of X-band cw-EPR spectra of nitroxide labeled proteins at room temperature, with no need of uncommon higher frequency spectrometry and with the minimal number of variable parameters.

Efficient Feature Extraction for Recognition of Human Emotions through Facial Expressions Using Image Processing Algorithms

Face emotion recognition is a challenging problem in computer vision that has been extensively studied in recent years. The project investigates the performance of Local Binary Pattern (LBP), Histogram of Oriented Gradients (HOG), K- Nearest Neighbour (KNN), and Support Vector Machine (SVM) for face emotion recognition. The aim of this study is to evaluate the performance of different combinations of these techniques and to identify the most effective approach for this task. To achieve this, we first collected a dataset of facial expressions that includes seven basic emotions such as happy, sad, angry, surprise, Neutral, fear, and disgust. We then extract LBP and HOG features from the facial images and then KNN and SVM classifiers to classify the emotions. We experimented with various combinations of LBP, HOG, KNN, and SVM and evaluated the performance of each approach using metrics such as accuracy, precision, recall, and F1 score. This study demonstrates the effectiveness of combining LBP and HOG features with KNN and SVM for face emotion recognition. Our results suggest that SVM is the most effective model for this task, when it is combined with HOG features and can further improve the system39;s performance. The model can be implemented using MATLAB and GUI Interface. These findings have important implications for the development of accurate and reliable face emotion recognition systems for various applications, including human-computer interaction, gaming, and healthcare.

Optimal energy management of a solar-assisted heat pump water heating system with a storage system

Water heating is the fourth largest energy consumer in the commercial building sector, accounting for >40 % of the energy consumed in South Africa. Traditional electric storage tank water heaters (ESTWHs) have been the most frequently used systems in the past, owing to their low electricity costs and implementation. It was low enough at that time that energy costs were not considered. These systems have grown increasingly hostile to consumers as power prices have risen, particularly to the undesirable high morning and afternoon peaks.The indirect-expansion solar-assisted heat pump water heater (IDX-SAHPWH), for the commercial sector, to reduce energy consumption of hot water production while maintaining the users' thermal comfort level, has been proposed in this paper. The system is operated under an optimal energy control scheme, integrated with the load shifting by time-of-use (TOU) pricing plan. The comparison of the performance of the proposed optimally controlled system and the electric storage tank water heater (ESTWH) was performed through the simulation approach using the Solving Constraint Integer Programs (SCIP) solver, in the MATLAB interface optimization toolbox. The simulations reveal that the proposed system operates during off-peak hours, when power prices are lower, as compared to ESTWH system.The techno-economic analysis was conducted and presented for a project lifespan of 20 years. The proposed optimally controlled system demonstrates the cost savings obtained from the winter and summer seasons, as well as annual, as 76.0 %, 75.6 % and 75.8 %, respectively. The break-even point of the project is during the 9th month of the first year of the project, with a possible savings of 71.5 % at the end of the project's lifetime.

Comprehensive Approach to Mitigating Solar Photovoltaic Power Penetration Effects in a Microgrid

High solar photovoltaic (PV) penetration in the electrical grid can result in undesired effects on the voltage quality, leading to line loss and voltage magnitude increases. One of the main criteria to ensure the safe penetration of high-power solar systems in the main grid is maintaining an acceptable voltage magnitude when a disturbance occurs (e.g., 0.95 and 1.05 per unit) with respect to total installed power generation capacity of PV power plants. This manuscript analyzes the effects of high solar PV penetration per unit of voltage stability using the Fast Voltage Stability Index and total power loss. Moreover, we investigate the flexibility benefits of coordinated voltage control based on a smart inverter of solar PV capacitor banks (SI-CBs) under five cases in a typical microgrid (MG) test model. For the test of the SI-CBs, MG modeling is developed on a modified IEEE 123 test feeder, which includes 11 building load solar PVs with smart inverters and capacitor banks with real-time data from an area in Los Angeles, California, USA. The simulation results are presented to validate the effectiveness of the proposed approach using a real-time MATLAB interface to the Open Distribution System Simulator (OpenDSS).

Generation of the mathematical model to analyze the dynamical behaviour of the blood flow

This paper focuses on the mathematical model based on the input output realization with a view to analyzing the time-invariant dynamical behaviour of the blood flow through carotid artery. The entire system’s characteristic is governed by the Navier-Stokes equation which is represented in this paper as differential-algebraic matrix representation. This mathematical representation is commonly known as state space model that is extracted from the Taylor-hood finite element discretization of the physical model. Later, for computational convenient, this model is divided into different sub-blocks studying the sparsity patterns of the matrices each of which contains the system’s parameters responsible for any dynamical changes. This form is well-known as index-II descriptor data model representing the relationship between the input external force applying to the artery’s boundary and the output measuring the changes in the blood velocity and the pressure. Based on the input-output realization, MATLAB interface is used to carry out numerical experiments and the results illustrate the numerical behaviour of the generated state space model for analyzing the blood flow nature through carotid artery.