A graphical user interface(GUI)for model-based radiation-induced acoustic computed tomography

Radiation-induced acoustic computed tomography(RACT)is an evolving biomedical imaging modality that aims to reconstruct the radiation energy deposition in tissues.Traditional backprojection(BP)reconstructions carry noisy and limited-view artifacts.Model-based algorithms have been demonstrated to overcome the drawbacks of BPs.However,model-based algorithms are relatively more complex to develop and computationally demanding.Furthermore,while a plethora of novel algorithms has been developed over the past decade,most of these algorithms are either not accessible,readily available,or hard to implement for researchers who are not well versed in programming.We developed a user-friendly MATLAB-based graphical user interface(GUI;RACT2D)that facilitates back-projection and model-based image reconstructions for twodimensional RACT problems.We included numerical and experimental X-ray-induced acoustic datasets to demonstrate the capabilities of the GUI.The developed algorithms support parallel computing for evaluating reconstructions using the cores of the computer,thus further accelerating the reconstruction speed.We also share the MATLAB-based codes for evaluating RACT reconstructions,which users with MATLAB programming expertise can further modify to suit their needs.The shared GUI and codes can be of interest to researchers across the globe and assist them in e±cient evaluation of improved RACT reconstructions.

Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning

The corrosion rate is a crucial factor that impacts the longevity of materials in different applications.After undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion rate.However,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still lacking.The current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 alloy.The Taguchi L27 design of experiments was used for the experimental analysis.In addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion rate.The shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified factors.This study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.

Generating Graphic User Interface of Web Applications Using Source Code Generator Based on Dynamic Frames

This paper deals with a problem of application generation together with their Graphic User Interface （GUI）. Particularly, the source code generator based on dynamic frames was improved for more effective specification of GUI. It＇s too demanding for the developers to have specification of the application that contain all physical coordinates and other details of buttons and other GUI elements. The developed solution for this problem is based on post-processing of generated source code using iterators for specifying coordinates and other values of graphic elements. The paper includes two examples of generating web applications and their GUI.

Graphical User Interface for the Monitoring of CAN Frames by Means of a SoC Cyclone V

In this paper, the design of a Graphical User Interface for CAN data frame monitoring is presented. The GUI has been developed in the Qt Creator IDE. A touch screen for visualization and control is used, which in turn is controlled by a development board with a SoC Cyclone V, through which a Linux operating system is executed.

An Efficient Text Recognition System from Complex Color Image for Helping the Visually Impaired Persons

The challenge faced by the visually impaired persons in their day-today lives is to interpret text from documents.In this context,to help these people,the objective of this work is to develop an efficient text recognition system that allows the isolation,the extraction,and the recognition of text in the case of documents having a textured background,a degraded aspect of colors,and of poor quality,and to synthesize it into speech.This system basically consists of three algorithms:a text localization and detection algorithm based on mathematical morphology method(MMM);a text extraction algorithm based on the gamma correction method(GCM);and an optical character recognition(OCR)algorithm for text recognition.A detailed complexity study of the different blocks of this text recognition system has been realized.Following this study,an acceleration of the GCM algorithm(AGCM)is proposed.The AGCM algorithm has reduced the complexity in the text recognition system by 70%and kept the same quality of text recognition as that of the original method.To assist visually impaired persons,a graphical interface of the entire text recognition chain has been developed,allowing the capture of images from a camera,rapid and intuitive visualization of the recognized text from this image,and text-to-speech synthesis.Our text recognition system provides an improvement of 6.8%for the recognition rate and 7.6%for the F-measure relative to GCM and AGCM algorithms.

An Educational GUI-Based Software for Dynamic Analysis of Framed Structural Models

This paper introduces a new version of the open-source educational software, LESM (Linear Elements Structure Model), developed in MATLAB for structural analysis of one-dimensional models such as frames, trusses, and grillages. The updated program includes dynamic analysis, which incorporates inertial and damping effects, time-dependent load conditions, and a transient solver with multiple time integration schemes. The software assumes small displacements and linear-elastic material behavior. The paper briefly explains the theoretical basis for these developments and the reorganization of the source code using Object-Oriented Programming (OOP). The updated Graphical User Interface (GUI) allows interactive use of dynamic analysis features and displays new results such as animations, envelope diagrams of internal forces, phase portraits, and the response of degrees-of-freedom in time and frequency domain. The new version was used in a structural dynamics course, and new assignments were elaborated to improve students’ understanding of the subject.

DESIGN OF WINDOW BASED AND OBJECT ORIENTED GUI

This paper discusses the design concept and method about window based and object oriented Graphic User Interface(GUI),and describes the definition of each class in detail. It is developed with Watcom C ++ in DOS environment.The GUI can be redeveloped conveniently and effectively by users.It consists of window,popup menu,icon,button and other components.

Water quality forecast through application of BP neural network at Yuqiao reservoir

This paper deals with the study of a water quality forecast model through application of BP neural network technique and GUI (Graphical User Interfaces) function of MATLAB at Yuqiao reservoir in Tianjin. To overcome the shortcomings of traditional BP algorithm as being slow to converge and easy to reach extreme minimum value,the model adopts LM (Leven-berg-Marquardt) algorithm to achieve a higher speed and a lower error rate. When factors affecting the study object are identified,the reservoir's 2005 measured values are used as sample data to test the model. The number of neurons and the type of transfer functions in the hidden layer of the neural network are changed from time to time to achieve the best forecast results. Through simulation testing the model shows high efficiency in forecasting the water quality of the reservoir.

Automated Identification Algorithm Using CNN for Computer Vision in Smart Refrigerators

Machine Learning has evolved with a variety of algorithms to enable state-of-the-art computer vision applications.In particular the need for automating the process of real-time food item identification,there is a huge surge of research so as to make smarter refrigerators.According to a survey by the Food and Agriculture Organization of the United Nations(FAO),it has been found that 1.3 billion tons of food is wasted by consumers around the world due to either food spoilage or expiry and a large amount of food is wasted from homes and restaurants itself.Smart refrigerators have been very successful in playing a pivotal role in mitigating this problem of food wastage.But a major issue is the high cost of available smart refrigerators and the lack of accurate design algorithms which can help achieve computer vision in any ordinary refrigerator.To address these issues,this work proposes an automated identification algorithm for computer vision in smart refrigerators using InceptionV3 and MobileNet Convolutional Neural Network(CNN)architectures.The designed module and algorithm have been elaborated in detail and are considerably evaluated for its accuracy using test images on standard fruits and vegetable datasets.A total of eight test cases are considered with accuracy and training time as the performance metric.In the end,real-time testing results are also presented which validates the system’s performance.

Implementation of a new PC based controller for a PUMA robot

This paper describes the replacement of a controller for a programmable universal machine for assembly (PUMA) 512 robot with a newly designed PC based (open architecture) controller employing a real-time direct control of six joints. The original structure of the PUMA robot is retained. The hardware of the new controller includes such in-house designed parts as pulse width modulation (PWM) amplifiers, digital and analog controllers, I/O cards, signal conditioner cards, and 16-bit A/D and D/A boards. An Intel Pentium IV industrial computer is used as the central controller. The control software is implemented using VC++ programming language. The trajectory tracking performance of all six joints is tested at varying velocities. Experimental results show that it is feasible to implement the suggested open architecture platform for PUMA 500 series robots through the software routines running on a PC. By assembling controller from off-the-shell hardware and software components, the benefits of reduced and improved robustness have been realized.

An Engineering Application Tool for Visual Assessment of the Equilibrium Beach

An engineering application tool for prediction of the static equilibrium bay （ Beach Mod） is established to describe two bay shape formulas by use of the programming software ＂MATLAB＂ with a graphic user interface （ GUI）. The tool is user-friendly for engineering students for the design of beach shapes. This tool was tested through application on three types of beaches in Taiwan and Australia. By implementing the concept of Headland Control, the Beach Mod program allows users to draw a structure and create an ＇artificial headland. The results indicate that Beach Mod can efficiently forecast beach changes as well as MEPBAY, a competing software package, while boasting a better user interface.

An Intelligent IEQ Monitoring and Feedback System:Development and Applications

Indoor environmental quality(IEQ)significantly affects human health and wellbeing.Therefore,continuous IEQ monitoring and feedback is of great concern in both the industrial and academic communities.However,most existing studies only focus on developing sensors that cost-effectively promote IEQ measurement while ignoring interactions between the human side and IEQ monitoring.In this study,an intelligent IEQ monitoring and feedback system-the Intelligent Built Enviroment(IBEM)-is developed.Firstly,the IBEM hardware instrument integrates air temperature,relative humidity,CO_(2),particulate matter with an aerodynamic diameter no greater than _(2.5)μm(PM_(2.5)),and illuminance sensors within a small device.The accuracy of this integrated device was tested through a co-location experiment with reference sensors;the device exhibited a strong correlation with the reference sensors,with a slight deviation(R^(2)>0.97 and slopes between 1.01 and 1.05).Secondly,a wireless data transmission module,a cloud storage module,and graphical user interfaces(i.e.,a web platform and mobile interface)were built to establish a pathway for dataflow and interactive feedback with the occupants of the indoor environments.Thus,the IEQ parameters can be continuously monitored with a high spatiotemporal resolution,interactive feedback can be induced,and synchronous data collection on occupant satisfaction and objective environmental parameters can be realized.IBEM has been widely applied in 131 buildings in 18cities/areas in China,with 1188 sample locations.Among these applications,we report on the targeted IEQ diagnoses of two individual buildings and the exploration of relationships between subjective and objective IEQ data in detail here.This work demonstrates the great value of IBEM in both industrial and academic research.

A Novel Approach to the Convergence Proof of Ant Colony Algorithm and Its MATLAB GUI-Based Realization

Although ant colony algorithm for the heuristic solution of hard combinational optimization problems enjoy a rapidly growing popularity, but little is known about its convergence properties. Based on the introduction of the basic principle and mathematical model, a novel approach to the convergence proof that applies directly to the ant colony algorithm is proposed in this paper. Then, a MATLAB GUI- based ant colony algorithm simulation platform is developed, and the interface of this simulation platform is very friendly, easy to use and to modify.

Design of a Tree Ring Structure Analysis System to Estimate the Accurate Age of Tree Species in Sri Lanka

Determination of an age in a particular tree species can be considered as a vital factor in forest management.In this research we have introduced a novel scheme to determine the accurate age of the tree species in Sri Lanka.This is initially developed for the tree species called‘Hora’(Dipterocarpus zeylanicus)in wet zone of Sri Lanka.Here the core samples are extracted and further analyzed by means of the different image processing techniques such as Gaussian kernel blurring,use of Sobel filters,double threshold analysis,Hough line tran sformation and etc.The operations such as rescaling,slicing and measuring are also used in line with image processing techniques to achieve the desired results.Ultimately a Graphical user interface(GUI)is developed to cater for the user requirements in a user friendly environment.It has been found that the average growth ring identification accuracy of the proposed system is 93%and the overall average accuracy of detecting the age is 81%.Ultimately the proposed system will provide an insight and contributes to the forestry related activities and researches in Sri Lanka.

Development of Autonomous Travelling Device for Oil Palm FFB （Fresh Fruit Bunches） Harvester

Robot technology is a very promising technology for agricultural sector, but the existing industrial robot could not deliver the above-mentioned criteria. Industrial robot mainly uses high voltage electrical power, which is not available at field and outdoor operation. The only available and reliable power is a hydraulic from the tractor. The harvester robot consumes the hydraulic power from the tractor and at the same time the tractor can be used as a traveling device for the robot. This paper describes the study on the development of autonomous tractor for the oil palm harvester. The development took considerations on the design of the electro-hydraulic system and the control software for the robot structure to be flexible enough to operate in plantation environment.

Propagation of P-and S-waves in initially stressed gravitating half space

The present paper contributes in studying the phase velocities of P- and S-waves in a half space subjected to a compressive initial stress and gravity field. The density and acceleration due to gravity vary quadratically along the depth. The dispersion equation is derived in a closed form. It is shown that the phase velocities depend not only on the initial stress, gravity, and direction of propagation but also on the inhomogeneity parameter associated with the density and acceleration due to gravity. Various particular cases are obtained, and the results match with the classical results. Numerical investigations on the phase velocities of P- and S-waves against the wave number are made for various sets of values of the material parameters, and the results are illustrated graphically. The graphical user interface model is developed to generalize the effect.

Skin lesion classification system using a Knearest neighbor algorithm

One of the most critical steps in medical health is the proper diagnosis of the disease.Dermatology is one of the most volatile and challenging fields in terms of diagnosis.Dermatologists often require further testing,review of the patient’s history,and other data to ensure a proper diagnosis.Therefore,finding a method that can guarantee a proper trusted diagnosis quickly is essential.Several approaches have been developed over the years to facilitate the diagnosis based on machine learning.However,the developed systems lack certain properties,such as high accuracy.This study proposes a system developed in MATLAB that can identify skin lesions and classify them as normal or benign.The classification process is effectuated by implementing the K-nearest neighbor(KNN)approach to differentiate between normal skin and malignant skin lesions that imply pathology.KNN is used because it is time efficient and promises highly accurate results.The accuracy of the system reached 98%in classifying skin lesions.

Design Principles-Based Interactive Learning Tool for Solving Nonlinear Equations

Interactive learning tools can facilitate the learning process and increase student engagement,especially tools such as computer programs that are designed for human-computer interaction.Thus,this paper aims to help students learn five different methods for solving nonlinear equations using an interactive learning tool designed with common principles such as feedback,visibility,affordance,consistency,and constraints.It also compares these methods by the number of iterations and time required to display the result.This study helps students learn these methods using interactive learning tools instead of relying on traditional teaching methods.The tool is implemented using the MATLAB app and is evaluated through usability testing with two groups of users that are categorized by their level of experience with root-finding.Users with no knowledge in root-finding confirmed that they understood the root-finding concept when interacting with the designed tool.The positive results of the user evaluation showed that the tool can be recommended to other users.

Design and Development of Remote Laboratories with Internet of Things Setting

Given the recent developments of Internet of Things (IoT) researchers and academics are trying to utilize this concept for different innovative applications. One of those applications of IoT is the remote laboratories, where real hardware/software experimentation systems can be controlled and manipulated over the web. During the COVID-19 pandemic, this has become almost essential for academic and research activities. The paper starts with highlighting the necessity and current status of remote laboratories in terms of shortcomings and possible recourse. With these in mind, the second part illustrates an infrastructure of a remote laboratory facility as well as describes the development of a number of prototype remote laboratories that are utilized for academic activities.

Novel rockburst prediction criterion with enhanced explainability employing CatBoost and nature-inspired metaheuristic technique

Rockburst is a major challenge to hard rock engineering at great depth.Accurate and timely assessment of rockburst risk can avoid unnecessary casualties and property losses.Despite the existence of various methods for rockburst assessment,there remains an urgent need for a comprehensive and reliable criterion that is easy to both apply and interpret.Developing a new rockburst criterion based on simple parameters can potentially fill this gap.With its advantages,this criterion can facilitate a more effective and efficient prediction of rockburst potential,thereby contributing significantly to enhancing safety measures.In this paper,combined with the internal and external factors of rockburst,four control variables(i.e.,integrity index,stress index,brittleness index,and elastic energy index)were selected to be incorporated into a comprehensive rockburstability index(RBSI).Based on 116 sets of rockburst cases,the rockburst potential was accurately quantified and predicted using the categorical boosting(CatBoost)model and the nature-inspired metaheuristic African vultures optimization algorithm(AVOA).In its performance validation,the criterion achieved the highest accuracy of 90.48%,verifying the reliability and effectiveness of the proposed RBSI criterion.Additionally,an interpretive method was applied to analyze the variable influence on the criterion,facilitating the explanation of predictions and the analysis of the formula’s robustness under different conditions.In general,compared with existing criterion methods involving relevant indicators,the newly proposed RBSI criterion enhances the accuracy of rockburst potential prediction,and it can effectively and swiftly evaluate the preliminary risk of rockburst.Lastly,a graphical user interface was developed to provide a clear visualization of the assessment of rockburst potential.