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.

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.

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.

GridDroid--An Effective and Efficient Approach for Android Repackaging Detection Based on Runtime Graphical User Interface

Repackaging brings serious threats to Android ecosystem.Software birthmark techniques are typically applied to detect repackaged apps.Birthmarks based on apps'runtime graphical user interfaces(GUI)are effective,especially for obfuscated or encrypted apps.However,existing studies are time-consuming and not suitable for handling apps in large scale.In this paper,we propose an effective yet efficient dynamic GUI birthmark for Android apps.Briefly,we run an app with automatically generated GUI events and dump its layout after each event.We divide each dumped layout into a grid,count in each grid cell the vertices of boundary rectangles corresponding to widgets within the layout,and generate a feature vector to encode the layout.Similar layouts are merged at runtime,and finally we obtain a graph as the birthmark of the app.Given a pair of apps to be compared,we build a weighted bipartite graph from their birthmarks and apply a modified version of the maximum-weight-bipartite-matching algorithm to determine whether they form a repackaging pair(RP)or not.We implement the proposed technique in a prototype,GridDroid,and apply it to detect RPs in three datasets involving 527 apks.GridDroid reports only six false negatives and seven false positives,and it takes GridDroid merely 20 microseconds on average to compare a pair of birthmarks.

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.

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.

An embedded lightweight GUI component library and ergonomics optimization method for industry process monitoring

Developing an efficient and robust lightweight graphic user interface （GUI） for industry process monitoring is always a challenging task. Current implementation methods for embedded GUI are with the matters of real-time processing and ergonomics performance. To address the issue, an embedded lightweight GUI component library design method based on quasar technology embedded （Qt/E） is proposed. First, an entity-relationship （E-R） model for the GUI library is developed to define the functional framework and data coupling relations. Second, a cross-compilation environment is constructed, and the QI/E shared library files are tailored to satisfy the requirements of embedded target systems. Third, by using the signal-slot communication interfaces, a message mapping mechanism that does not require a call-back pointer is developed, and the context switching performance is improved. According to the multi-thread method, the parallel task processing capabilities fbr data collection, calculation, and display are enhanced, and the real-time performance and robustness are guaranteed. Finally, the human-computer interaction process is optimized by a scrolling page method, and the ergonomics pertbrmance is verified by the industrial psychology methods Two numerical cases and five industrial experiments show that the proposed method can increase real-time read-write correction ratios by more than 26% and 29%, compared with Windows-CE-GUl and Android-GUl, respectively. The component library can be tailored to 900 KB and supports 12 hardware platforms. The average session switch time can be controlled within 0.6 s and six key indexes for ergonomics are verified by different industrial applications.

加权优选方法在信号分解中的应用与软件研制

应用EMD(empirical mode decomposition)分解信号的效果与包络拟合函数、端点延拓方法、IMF(intrinsic mode function)筛分准则有关,其中每种方法皆有多个选项,这些选项没有对错的区别,只有是否合适的区别,因此提出一种加权优选方法,能够通过ERE(energy relative error)等评价指标自主甄选出最适合目标处理信号的方法集。实验结果表明,相较于经验选择方法,该方法可以更大限度地还原信号原有的波形。最后将该方法基于Matlab GUI(graphical user interface)进行软件模块化设计与研制,是对GPS信号处理与挖掘方法的重要补充。

DUSM： A Method for Requirements Specification and Refinement Based on Disciplined Use Cases and Screen Mockups

In this work, we present DUSM （Disciplined Use Cases with Screen Mockups）, a novel method for describing and refining requirements specifications based on disciplined use cases and screen mockups. Disciplined use cases are characterized by a quite stringent template to prevent common mistakes, and to increase the quality of the specifications. Use cases descriptions are formulated in a structured natural language, which allows to reach a good level of precision, avoiding the need for further notations and complex models. Screen mockups are precisely associated with the steps of the use cases scenarios and they present the corresponding GUIs （graphical user interfaces） as seen by the human actors before/after the steps executions, improving the comprehension and the expression of the non-functional requirements on the user interface. DUSM has been proposed and fine-tuned during several editions of a software engineering course at the University of Genova. Then, by means of a series of case studies and experiments, we validated the method and evaluated： 1） its effectiveness in improving the comprehension and, in general, the quality of the produced requirements specification, and 2） its applicability in the industry, where the method has been found useful and not particularly onerous.

RIM: A Matlab Software Tool for Recursive Identification Methods

This paper introduces a recursive identification methods toolbox(called RIM) running under Matlab environment for dynamic system identification from available data. The RIM includes many methods which are generally used. The RIM helps users to validate the theoretical results and to carry out comparison between identifications methods without the need of algorithms programming. Furthermore, the RIM can be used as an education platform to study the identification parameters effect on model validity and results accuracy. To show its performance and capability, the RIM is evaluated through many application examples.