Matlab Programming

The PCA toolbox for MATLAB is a collection of modules freely available via Internet.The toolbox calculates PCA, Cluster Analysis and Multidimensional Scaling.An easy-to-use graphical user interface (GUI) environment is available.Theory of methods, toolbox features, and an example of application are described.Principal Component Analysis is a multivariate method to project data in a reduced hyperspace, defined by orthogonal principal components, which are linear combinations of the original variables. In this way, data dimension can be reduced, noise can be excluded from the subsequent analysis, and therefore, data interpretation is extremely facilitated. For these reasons, Principal Component Analysis is nowadays the most common chemometric strategy for unsupervised exploratory data analysis.In this paper, the PCA toolbox for MATLAB is described. This is a collection of modules for calculating Principal Component Analysis, as well as Cluster Analysis and Multidimensional Scaling, which are two other well-known multivariate methods for unsupervised data exploration. The toolbox is freely available via Internet and comprises a graphical user interface (GUI), which allows the calculation in an easy-to-use graphical environment. It aims to be useful for both beginners and advanced users. The use of the toolbox is discussed here with an appropriate practical example.

The purpose of this article is to offer a deeper perspective towards a topic, hastily considered trivial by many engineers. The determination of principal axes and mass moments of inertia is regarded as an eigenvector and eigenvalue problem. Some theoretical background is provided for the case when no axes or planes of symmetry exist. The practical application is emphasized via example. Manual calculation is conducted and a MATLAB code is provided as well.

License Plate Recognition (LPR) plays an important role on the traffic monitoring and parking management. A robust and efficient method for enhancing accuracy of license plate characters recognition based on K Nearest Neighbours (K-NN) classifier is presented in this paper. The system first prepares a contour form of the extracted character, then the angle and distance feature information about the character is extracted and finally K-NN classifier is used to character recognition. Angle and distance features of a character have been computed based on distribution of points on the bitmap image of character. In K-NN method, the Euclidean distance between testing point and reference points is calculated in order to find the k-nearest neighbours. We evaluated our method on the available dataset that contain 1200 sample. Using 70% samples for training, we tested our method on whole samples and obtained 99% correct recognition rate.Further, we achieved average 99.41% accuracy using three...

Illumination invariance remains the most researched, yet the most challenging aspect of automatic face recognition. In this paper we investigate the discriminative power of colour-based invariants in the presence of large illumination changes between training and test data, when appearance changes due to cast shadows and non-Lambertian effects are significant. Specifically, there are three main contributions: (i) we employ a more sophisticated photometric model of the camera and show how its parameters can be estimated, (ii) we derive several novel colour-based face invariants, and (iii) on a large database of video sequences we examine and evaluate the largest number of colour-based representations in the literature. Our results suggest that colour invariants do have a substantial discriminative power which may increase the robustness and accuracy of recognition from low resolution images.

In this paper, both flap-wise and edge-wise natural frequencies of vibration of a variable blade length wind turbine are calculated.  A stepped beam with two portions has been used to approximate the blade. The two portions of the blade have been approximated by a hollow beam and a solid beam with rectangular cross section. As the outboard portion of the blade can be slid in and out of the inboard portion, ten different configurations of the stepped beam have been investigated. A MATLAB program has been developed for a finite element analysis of a one dimensional model of the stepped beam. Subsequently a three dimensional model of the stepped beam has been developed in the finite element program Unigraphics NX4. The results found using the MATLAB program have been compared with those found with NX4 and satisfactory agreement between these results has been found. Additionally, the influence of varying the blade length on the natural frequencies has been investigated.

Dynamically changing background ("dynamic background") still presents a great challenge to many motion-based video surveillance systems. In the context of event detection, it is a major source of false alarms. There is a strong need from the security industry either to detect and suppress these false alarms, or dampen the effects of background changes, so as to increase the sensitivity to meaningful events of interest. In this paper, we restrict our focus to one of the most common causes of dynamic background changes: that of swaying tree branches and their shadows under windy conditions. Considering the ultimate goal in a video analytics pipeline, we formulate a new dynamic background detection problem as a signal processing alternative to the previously described but unreliable computer vision-based approaches. Within this new framework, we directly reduce the number of false alarms by testing if the detected events are due to characteristic background motions. In addition, we introduce a new dataset suitable for the evaluation of dynamic background detection. It consists of real-world events detected by a commercial surveillance system from two static surveillance cameras. The research question we address is whether dynamic background can be detected reliably and efficiently using simple motion features and in the presence of similar but meaningful events such as loitering. Inspired by the tree aerodynamics theory, we propose a novel method named local variation persistence (LVP), that captures the key characteristics of swaying motions. The method is posed as a convex optimization problem whose variable is the local variation. We derive a computationally efficient algorithm for solving the optimization problem, the solution of which is then used to form a powerful detection statistic. On our newly collected dataset, we demonstrate that the proposed LVP achieves excellent detection results and outperforms the best alternative adapted from existing art in the dynamic background literature.

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Combined Cycle Gas Turbine (CCGT) integrates two cycles-Brayton cycle (Gas Turbine) and Rankine cycle (Steam Turbine) with the objective of increasing overall plant efficiency. In modern gas turbine the temperature of the exhaust gases is in the range of 500 o C to 550 o C. Modern steam power plants have steam temperature in the range of 500 o C to 630 o C. Hence gas turbine exhaust can be utilized by a waste-heat recovery boiler to run a steam turbine based on Rankine cycle. The efficiency of a gas turbine which ranges from 28% to 33% can be raised to about 60% by recovering some of the low grade thermal energy from the exhaust gas for steam turbine process. This paper is a study for the modelling of gas turbine and using this model for optimizing the power of CCGT by varying parameters. The performance model for CCGT plant was developed in MATLAB/Simulink.

In this paper numerical analysis is carried out to identify borehole log at a particular location of a site thus producing a number of parameters which are empirically related to SPT values. The Standard Penetration Test (SPT) remains the most common site investigation tool used throughout the world. Physical properties of soil is found by correlations with values of recommended standard N60, determined in SPT tests. Janjira Ap-proach road of ongoing Padma Multipurpose Bridge Project was considered for this study to collect 15 bore-hole log along 20 km stretch. Disturbed soil sample were collected up to 19.5m depth in every 1.5m interval to perform Sieve-analysis test. Spreadsheet was used to input of over 600 data including SPT-N values, Percent Sand & Percent Fines at depths, Reduce Level & Ground Water Table at different Chainage locations. By us-ing all these data- a mathematical model was developed in MATLAB, a high-level language and interactive environment for numerical compu...

— In this paper we present a Computer Vision based system developed to operate a manipulator. Images, representing some pre-configured gestures, are captured using a RGB-D sensor. A Machine Learning technique, known as Support Vector Machines (SVMs), is used to process these images. Each gesture indicates a different movement to be executed by the manipulator. In this system, each image is classified in a gesture and the respective command is sent to this equipment. Results show that it was possible to capture, process, classify and send the correct command to the manipulator to execute the predetermined movements.

Resumo— Neste trabalho é apresentado um sistema para operação de manipuladores robóticos baseado em técnicas de Visão Computacional. As imagens, representativas de gestos prestabelecidos, são capturadas por meio do sensor do tipo RGB-D e processadas por uma técnica de Aprendizado de Máquina, conhecida como Máquina de Vetores de Suporte (Support Vector Machines ou SVM). Uma vez classificados, cada gesto indica um movimento diferente a ser executado pelo manipulador robótico. Os comandos são enviados para esse dispositivo via comunicação serial. Os resultados obtidos demonstram que foi possível a captura, processamento, classificação e envio das informações corretas ao manipulador para execução dos movimentos predeterminados.

New communication technologies integrated into modern vehicles offer an opportunity for better assistance to people injured in traffic accidents. Recent studies show how communication capabilities should be supported by artificial intelligence systems capable of automating many of the decisions to be taken by emergency services, thereby adapting the rescue resources to the severity of the accident and reducing assistance time. To improve the overall rescue process, a fast and accurate estimation of the severity of the accident represent a key point to help emergency services better estimate the required resources. This paper proposes a novel intelligent system which is able to automatically detect road accidents, notify them through vehicular networks, and estimate their severity based on the concept of data mining and knowledge inference. Our system considers the most relevant variables that can characterize the severity of the accidents (variables such as the vehicle speed, the type of vehicles involved, the impact speed, and the status of the airbag). Results show that a complete Knowledge Discovery in Databases (KDD) process, with an adequate selection of relevant features, allows generating estimation models that can predict the severity of new accidents. We develop a prototype of our system based on off-the-shelf devices and validate it at the Applus+ IDIADA Automotive Research Corporation facilities, showing that our system can notably reduce the time needed to alert and deploy emergency services after an accident takes place.

A theoretical study on the F-16 will be presented in this project. The study will involve several stages, a development of the linear and non-linear mathematical model will be evaluated using certain assumptions, and accordingly an autopilot will be designed considering different cases and assuming whole state measurements; using the SimuLink software to measure the performance of the autopilot, then a linear controller will be added to achieve the desired performance. From the results achieved a conclusion, and future recommendation will be presented.

Tomatoes are best known grown fruits in greenhouses. In order to decrease the high labor cost and increase the efficiency, recently many researches have tried to harvest tomatoes automatically. To help the harvesting robot picking the fruit precisely, the main challenges are to identify and localize red mature tomato fruit accurately. In this paper, we presented a robust and effective method for challenging task of segmentation and localization of on-plant tomatoes in the greenhouse, for automatic tomato harvesting purpose. A low-cost RGB-D Kinect V2 camera was used to accomplish the task. Color images and depth images of tomatoes on-plants in the greenhouse were captured in day time using Kinect V2 camera. Along with color and depth images, the corresponding color coordinates, depth coordinates, and camera coordinates were also saved. The proposed method was divided into two stages: fruit segmentation and fruit localization. At the first stage, an improved HSV algorithm and watershed algorithm were used to segment mature fruits from a complex background. An improved HSV algorithm was used to enhance the feature of red mature fruits. After that, Otsu method and morphological operations were used to segment mature fruits from the background and then watershed was implemented to further separate touched fruits. Subsequently, each detected fruit was separately labeled to calculate the pixel coordinates values in color image. At the second stage, a fusion of color and depth information was carried out on the basis of the mapping relationship between color, depth and camera coordinates, to map the obtained fruit pixel coordinates in color image with acquired 3D point cloud data. Then the corresponding point cloud data of each labeled fruit were generated. To remove the noise in the cloud data, a filtration process was performed, and the final point cloud was generated. To verify the proposed method, 18 pairs of images were experimented containing the different numbers of measured fruits with measuring distance, ranging from 0.58 to 1.50 m. The average fruit localization error rate was 1.2 cm for depth distance and 1.9 cm for ground distance. Final results showed that the proposed method has good performance and robustness for segmentation and localization and have good potential to be implemented on the tomato harvesting robot in the greenhouse.

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10-4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications.

Plot Entropy as a function of probability of a symbol %Plot Entropy as a function of probability of a symbol %Binary Symmetric Channel: X=[0 , 1] %Take the symbol 0 %Entropy H(X)=-[p(1)*log(p(1))]-[p(0)*log(p(0))] %Since p(1)+p(0)=1 %So we can write => p(1)=1-p(0) %Entropy as a function of probability of symbol 0 is as following %H=-[p(0)*log(p(0))]-[(1-p(0))*log(1-p(0))]

ABSTRAK KALKULATOR AKTIVITAS ISOTOP MENGGUNAKAN GUI MATLAB.Dibutuhkan cara mudah dan cepat dalam menghitung Aktivitas Isotop terutama bagi para pelajar, peneliti ataupun pekerja radiasi. Melalui Kalkulator aktivitas isotop ini diharapkan mampu mengurangi kerugian waktu akibat pengukuran secara manual. Kalkulator ini dilengkapi 49 isotop yang biasa digunakan pada bidang medis dan industri, selain itu dilengkapi pula dengan waktu sekarang atau real time. Dari project ini telah berhasil untuk membuat aplikasi kalkulator aktivitas isotop yang dapat mempermudah dan mempercepat perhitungan aktivitas. Selain itu melalui aplikasi ini juga berfungsi untuk memprediksi aktivitas isotop sehingga dapat memperkirakan nilai aktivitas isotop untuk waktu tertentu. Kata kunci: aktivitas isotop, kalkulator, GUI Matlab. ABSTRACT CALCULATOR ISOTOP ACTIVITIES USING MATLAB GUI. It takes an easy and fast way to calculate Isotope Activities, especially for students, researchers or radiation workers. Through this isotope activity calculator is expected to be able to reduce the loss of time due to manual measurement. This calculator is equipped with 49 isotopes commonly used in the medical and industrial fields, besides that it is also equipped with real time. From this project it has succeeded in creating an isotope activity calculator application that can simplify and speed up the calculation of activity. In addition, through this application it also functions to predict isotope activity so that it can estimate the value of isotope activity for a certain time..

Rock mass characterization requires a deep geometric understanding of the discontinuity sets affecting rock exposures. Recent advances in Light Detection and Ranging (LiDAR) instrumentation currently allow quick and accurate 3D data acquisition, yielding on the development of new methodologies for the automatic characterization of rock mass discontinuities. This paper presents a methodology for the identification and analysis of flat surfaces outcropping in a rocky slope using the 3D data obtained with LiDAR. This method identifies and defines the algebraic equations of the different planes of the rock slope surface by applying an analysis based on a neighbouring points coplanarity test, finding principal orientations by Kernel Density Estimation and identifying clusters by the Density-Based Scan Algorithm with Noise. Different sources of informationsynthetic and 3D scanned datawere employed, performing a complete sensitivity analysis of the parameters in order to identify the optimal value of the variables of the proposed method. In addition, raw source files and obtained results are freely provided in order to allow to a more straightforward method comparison aiming to a more reproducible research.

El presente trabajo ha sido pensado como proyecto
final de la carrera de ingeniería electrónica. En él se relacionan
modelos de software con un Controlador Lógico Programable
(“Programmable Logic Controller”, PLC) por medio de un
servidor que utiliza un Marco para la Vinculación y el Embebido
de Objetos (“Object Linking and Embedding”, OLE) específico
para el control de procesos (“OLE for Process Control”, OPC).
Dicho servidor OPC oficia como una vía para el intercambio de
datos entre diversos modelos de plantas simuladas con MatLab y
los bloques de control de lazos Proporcional Integral y Derivativo
(“Proportional Integral Derivative”, PID) implementados en el
software estándar para programación de autómatas Siemens
Step7.
Palabras clave—PLC; OPC server; Matlab.

An important aspect of any engineering design problem is to achieve efficiency and efficacy. This can be in terms of energy consumption, performance, time, total weight and costs. In many cases, there are multiple solutions to a problem and you should select the one which satisfies better the criteria. This engineering design process is
known as optimization. Optimization plays an important role in various engineering applications. Engineers are in continuity, challenged to design structures that use the least amount of resources and satisfy the structural requirements. The optimal design of structures can be decomposed into three major categories: topology, shape
and size optimization. These methods have evolved with time and they may be divided in two maxi-groups: deterministic and non-deterministic algorithms. Size optimization of non-deterministic methods with genetic algorithms (GA) are investigated in this article and applied to some steel trusses in MATLAB soft R2017a. This is done by building an algorithm consisting in scripts and sub-functions, which are applied to the trusses for different constraints on stresses, displacements and buckling, depending on the case analyzed. Different values for the GA parameters are analyzed in such way to achieve the best design. The results are put in comparison with previous studies.

Whether you want to enhance your holiday photographs or make a professional banner image for your website, you need a software tool that offers you quick and easy ways to accomplish it. All-in-one tools tend to be rare, and Matlab is one of the best available.

This book is a practical guide full of step-by-step examples and exercises that will enable you to use Matlab as a powerful, complete, and versatile alternative to traditional image and video processing software.

You will start off by learning the very basics of grayscale image manipulation in Matlab to master how to analyze 3-dimensional images and videos using the same tool. The methods you learn here are explained and expanded upon so that you gradually reach a more advanced level in Matlab image and video processing.

You will be guided through the steps of opening, transforming, and saving images, later to be mixed with advanced masking techniques both in grayscale and in color. More advanced examples of artistic image processing are also provided, like creating panoramic photographs or HDR images. The second part of the book covers video processing techniques and guides you through the processes of creating time-lapse videos from still images, and acquiring, filtering, and saving videos in Matlab.

You will learn how to use many useful functions and tools that transform Matlab from a scientific software to a powerful and complete solution for your everyday image and video processing needs.

The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.

In many ways, managing a large computer programming project
is like managing any other large undertaking—in more ways
than most programmers believe. But in many other ways
it is different—in more ways than most professional managers
expect.

The lore of the field is accumulating. There have been several
conferences, sessions at AFIPS conferences, some books,
and papers. But it is by no means yet in shape for any systematic
textbook treatment. It seems appropriate, however, to offer this
little book, reflecting essentially a personal view.

Electrocardiogram (ECG) is commonly used in medical field in order to diagnose different cardiovascular diseases and patient's general health. ECG Signal are often affected by artifacts from the environment including baseline wander, power line interference and electromyographic (EMG) noise. In this project, ECG Signal to be processed is collected from MIT/BIH (Massachusetts Institute of Technology-Beth Israel Hospital) Arrythmia Database [1]. This method is being tested on one dataset only and serves as a beginner guide to digital signal processing with MATLAB for an affordable, precise, and portable Electrocardiogram device that may be used at underserved hospitals. With MATLAB, to remove the baseline wander, Detrend function can be used to remove low frequency below 0.5 Hz. Powerline interference (50 Hz or 60 Hz) can be filtered out by using bandstop IIR filter. EMG and high frequency noise can be reduced by using IIR low-pass filter to cut off high frequency signal. The resulting signal is filtered out successfully with less noise and P wave, QRS complex, T wave can be inferred properly.

Tema ovog rada je upotrebom MATLAB programskog jezika izraditi grafičko sučelje za upravljanje servo motora. Pri samoj izradi aplikacije koristiće se serial port za komunikaciju računara i Arduino razvojne pločoce putem koje će se vršiti upravljanje servo motora. Kompletan rad će se sastojati od aplikaciju izrađene u MATLAB-u koja sadrži animaciju servo motora kojeg upravljamo i programa napisanog u Arduino grafickom sučelju u kojem se koristi modifikovani C programski jezik. MATLAB je pogodan za izradu ove aplikacije zbog lake izrade animacije i lake komunikacije sa serial port-om također i Arduino razvojna pločica ima mogućnost komunikacije sa računarom putem serial port-a putem USB ulaza što je puno lakše za razliku od dosadašnjeg RS232 priključka.

This Finite Element MATLAB Code Has Been Written For Stress And Buckling Analysis Of A VAWT Base As A 8 Node And 12 Element 3D Truss. The Limit Analysis Is Also Considered By Varying Load And We Can See Deflections And Results While Program Calculates And They Will Be Stored In Program Path.

In this chapter we will explore how Matlab stores various types of numbers. First, we will investigate the various integer types that Matlab offers. After a thorough discussion of integer storage, we will move on to the more difficult topic of floating point numbers, the technique used to store approximations of real numbers in Matlab.

A Cathode Ray Oscilloscope or CRO is an unavoidable tool as far as any signal analysis is concerned. Whenever we need to find shape, amplitude, phase or frequency of the signal, use of CRO is most compulsory. But for a student, conventional CROs are too costly to purchase and to bulky as far as mobility is concerned. So we bring a cheaper solution to this by PC Based oscilloscope which will use our computer screen as a display for any kind of signals.