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more and more mobile applications are designed and developed for the M-Learning. In this paper, a new mobile optimized application architecture using Ionic ...
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIE.2016.2620102, IEEE Transactions on Industrial Electronics IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Design a New Mobile Optimized Remote Laboratory Application Architecture for M-Learning Ning Wang, Student Member, IEEE, Xuemin Chen, Senior Member, IEEE, Gangbing Song, Member, IEEE, Qianlong Lan and Hamid Parsaei

Abstract—As Mobile Learning (M-Learning) has demonstrated increasing impacts on online education, more and more mobile applications are designed and developed for the M-Learning. In this paper, a new mobile optimized application architecture using Ionic framework is proposed to integrate the remote laboratory into mobile environment for the M-Learning. With this mobile optimized application architecture, remote experiment applications can use a common codebase to deploy native-like applications on many different mobile platforms such as iOS, Android, Windows Mobile, and Blackberry. To demonstrate the effectiveness of the proposed new architecture for M-Learning, an innovative remote networked Proportional-Integral-Derivative (PID) control experiment has been successfully implemented based on this new application architecture. The performance is validated by the Baidu mobile cloud testing bed. Index Terms — M-Learning, Unified Framework, Remote Laboratory, Mobile Optimized Application Architecture, Ionic Framework.

I. INTRODUCTION

D

URING recent decades, the rapid development of communications and wireless technologies have resulted in mobile devices (e.g., smartphones and tablets) becoming widely available, more convenient, and less expensive [1]. Mobile learning (M-Learning) [2] which is the delivery of learning, education or learning support on mobile phones or tablets has played an important role in E-Learning. According to research by Global Industry Analysts (GIA) published in

Manuscript received April 15, 2016; revised July 7, 2016 and August 31, 2016; accepted September 24, 2016. This work was supported by the Qatar National Research Fund under Grant No. NPRP 4-892-2-335. N. Wang is with the Department of Electrical and Computer Engineering, University of Houston, Houston, TX, 77204 (e-mail: [email protected]). X. Chen is with the Department of Engineering, Texas Southern University, Houston, TX, 77004 (e-mail: [email protected]). G. Song is with the Department of Mechanical Engineering, University of Houston, Houston, TX, 77204 (e-mail: [email protected]). Q. Lan is with the Department of Computer Science, Texas Southern University, Houston, TX, 77004 (e-mail: [email protected]). H. Parsaei is with the Department of Mechanical Engineering, Texas A&M University at Qatar, Doha, Qatar (e-mail: [email protected].).

2014 [3], it states that “the E-Learning market is one of the most rapidly growing sectors in the global education industry.” E-Learning, which was instituted on desktops in the beginning, has gradually shifted its base to portable tablets and smartphones [4]. Thus, more and more learning approaches, learning systems are configured and integrated for M-Learning [5]. Examples include a Microlecture Mobile Learning System at Guangdong University of Technology [6] and a smart learning mobile system for collaborative M-learning at BaekSeok Culture University [7], among others. It is expected that the teaching and learning actives will move more and more outside the classroom into the learners’ personal environment both real and virtual mediated by mobile devices [8]. Thus,it continues to be a major technology trend as we move in future. Because of its effectiveness, flexibility and cost-saving, the remote laboratory technology, as an important component of online learning, has made great progress. Many applications based on remote laboratory technology are being recognized in Science, Technology, Engineering and Math (STEM) education [9]. Till now, some of the most prominent examples of remote laboratories that have been successfully implemented include the MIT iLab [10], the WebLab-Deusto [11], the Networked Control System Laboratory (NCSLab) [12], the improved NCSLab 3-D [13], and the eComLab at UTSA [14]. Based on these successful examples, it has proven that remote laboratories can be highly effective tools in helping a wider range of students, regardless of geographical restrictions, to obtain practical experience needed for competency in science and engineering. The location independent access of a remote laboratory is especially useful in scenarios where space is limited, or for distance education [15]. To offer students a more flexible way to access remote laboratory, instead of forcing the learners to sit in front of a fixed computer to use a location independent environment for experimentation, a technology which is suitable for presenting remote laboratory on mobile devices becomes essential. In addition, integrating the remote laboratory into the mobile devices can offer students more flexible approach to learning and produce better outcomes as pointed out by May et al. [16] and Silva et al. [17]. So far, most of current research interests in mobile learning mainly focused on the various learning theories, there are only a smaller number of researches have focused on the design of framework and the mobile devices technologies which are compatible for M-learning systems [18][19]. How to

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIE.2016.2620102, IEEE Transactions on Industrial Electronics IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Mobile Remote Laboratory Example 1.An Android based remote laboratory application [24] 2. A field fluorometer experiment using smart phone[25] 3. J2ME-Based Mobile laboratory[26] 4. Virtual and Remote laboratory[27]

5. OMF Measurement Laboratory[28] 6. 3-D mobile application for remote experiments[29] 7. A web based mobile application based on WebLab-Deusto architecture[30] 8.A Mobile accessed remote laboratory application for VISIR [31] 9. PeTEX platform [32] 10. RExLab[33] 11. Remote Web-based mobile control laboratory[34] 12.iSES Remote Lab SDK for Smart Phone[35]

TABLE I EXAMPLES OF MOBILE REMOTE LABORATORY APPLICATION Description from Vendor Institution Year Mobile Application Type MIT 2012 Native Mobile Develop a remote Android client application Application based on MIT iLab Shared Architecture. University of Sydney 2015 Native Mobile Develop a novel portable fluorometer using Application android-based application framework. Princess Sumaya 2008 Native Mobile Develop a mobile remote lab application based on University Application J2ME framework. National University of 2013 Native Mobile Develop a remote lab application to support Distance Education Application portable devices based on EJS (Easy Java (UNED) Simulation). 2016 Native Mobile Add a measurement and monitoring tool University of Malaga Application TestelDroid into Android devices to control remote experiments. Indiana University 2016 Native Mobile Develop a 3-D remote laboratory experiments Northwest Application application based on 3-D mobile Augmented Reality Interface technology. University of Deusto 2008 Web Mobile Application Develop a remote laboratory using AJAX technology based on WebLab-Deusto architecture. Blekinge Institute of 2006 Web Mobile Application Develop a remote laboratory using HTML 5 Technology (BTH) technology and based on WebLab-Deusto platform. TU Dortmund University Federal University of Santa Catarina (UFSC) Complutense University

2011

Web Mobile Application

2016

Web Mobile Application

2015

Web Mobile Application

2016

Web Mobile Application

University of Prague

design and implement a mobile optimized and easy-to-use application for M-learning has become an emerging research topic [20][21]. Generally, two approaches, the native mobile application and the web-based application, are used to integrate the remote laboratory into mobile devices. 1) Native remote laboratory application for mobile devices: Native remote laboratory applications are developed using different native codes, different tools, build systems, application programming interfaces (APIs), and mobile devices with different capabilities for different platforms such as Apple iOS, Android, Windows Mobile, etc. Meanwhile, native remote laboratory applications are compiled and they directly call the underlying APIs of the different platforms. Although the native remote laboratory applications can achieve best performance on mobile devices with different platforms, it is hard to implement the cross-platform interface [22]. In Table I, examples 1-6 are the native mobile remote laboratory applications or mobile industrial applications that were developed with native application approach for different mobile systems. However, they are hard to be ported to other mobile systems [23]. 2) Web-based remote laboratory application for mobile devices: web-based remote laboratory applications normally are created in HyperText Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript; and they run in the different web browsers (such as Safari, Chrome, Microsoft IE, Firefox, etc.) [36]. In Table I, the examples 7-12 are the web-based mobile remote laboratory applications. Example 8 used jQuery mobile framework to implement the mobile remote laboratory

Develop a remote laboratory using HTML 5 technology and based on Moodle LMS. Develop mobile remote experiment application using HTML5 and jQuery Mobile framework. Develop a mobile remote lab application using HTML 5 technology and Node.js server. Using “iSES Remote Lab SDK” for Arduino-UNO and web technology to develop a mobile remote laboratory application.

application. Examples 9-12 were implemented by web development technology as well. All of these mobile remote laboratory applications can be easily run on different mobile phone systems via different web browsers, however their performance depends on JavaScript rendering and mobile web browsers. With the rapid development of web technology, the web application running performance has been significantly improved. However, for some special user interfaces (UI), e.g., example 6 in Table I, the web application running performance is still a major issue. In addition, some mobile applications need to use sensors in mobile devices, e.g., example 2 and 5 in Table I. Thus native application is the only option. The other main drawback of web application is the limited access to mobile device hardware. Therefore, how to design a mobile remote laboratory application architecture, which has the native-like performance and native functional capability, also can run on cross-platform easily and take low cost and development efforts like web applications, is already an essential issue [22][23][36]. To address this essential issue to better support the M-Learning, a new mobile optimized remote laboratory application architecture based on Ionic framework is proposed and implemented in this paper. To the best knowledge of the authors, that is the first study to build a mobile optimized application architecture for remote laboratory application development based on Ionic framework. To demonstrate the feasibility of this new architecture, an innovative remote networked Proportional-Integral-Derivative (PID) control experiment based on such an architecture is designed and implemented. The Baidu Mobile cloud testing tool is used to

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIE.2016.2620102, IEEE Transactions on Industrial Electronics IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Client Application

Network Port 80 Node-Http-Proxy Network Port 80

Network Port 5001

Apache Web Server Engine

Experiment Video

Node.js Web Server Engine

Database Server application

LabVIEW

Experiment Control Application

Fig. 1. The architecture of the unified framework [37].

test the performance of the new architecture. Since smart phone has been widely used in industry such as a field fluorometer experiment using smart phone [25], OMF Measurement remote experiment using android [28], etc., the new mobile optimized remote laboratory application architecture can provide a new development tool for mobile industrial electronic devices with less efforts. The rest of this paper is organized as follows. In Section II, previous work on the unified framework for remote laboratory development and the comparison of mobile development frameworks is introduced. To upgrade the unified framework, a new methodology for optimized mobile applications based on Ionic framework is presented in Section III. In Section IV, a new mobile-optimized remote PID motor speed control experiment application for M-Learning is presented. The future works are summarized in Section V. Concluding remarks are drawn in Section VI. II. PREVIOUS W ORKS A unified framework proposed in [37][38][39] has solved several critical issues to improve the remote experiment performance and user experience. The remote laboratory based on the unified framework can provide the students real-time video and real-time data transmission without software plugins and the firewall issue. To integrate the advantages of unified framework into mobile environment for better supporting M-Learning, an efficient and stable mobile framework must be selected as the foundational framework. To select the efficient and stable mobile framework for remote experiment, the comparison of mobile development frameworks is also introduced in this section. A. A Unified Framework for Remote Laboratory Development For the remote laboratory implementation, many of the solutions used Web 2.0 and Web Services/ Service Oriented Architecture (SOA) technology to produce the better quality remote laboratories without software plugins [40]. However, the main drawback of web services is slow data transmission resulting in poor support for real-time data communication [40][41]. To improve the real-time data transmission and keep

the advantages of web services, a unified framework for remote laboratory development was proposed and implemented. This unified framework provides the UI level and platform level APIs to integrate and implement the remote experiments. The unified framework is based on the combination solution of both Apache web engine and Node.js web engine, and it uses a Node-HTTP-based technology to resolve the real-time communication between experiment equipment with end users [37]. The subsequent iteration of the design resolved challenges of developing cross-browser and cross-device web UI as an improvement to the unified framework [38][39]. The system architecture of the unified framework is shown in Fig. 1. This unified framework is based on the Web 2.0 technology and includes three parts: client web application, server application, and experiment control application. 1) Client web application: The client web application runs on most of current popular browsers, and is based on HTML, CSS, and JQuery/JQuery-Mobile JavaScript libraries. Further, it uses the server-based Mashup technology for UI development. 2) Server application: To improve the web services technology performance issue, for the server application implementation, the combination solution of both Apache HTTP web engine and Node.js web engine implements the real-time communication between experiment hardware and end users. Apache HTTP web engine is the world's most used web server software and supports a variety of UI features development [42]. Node.js is an open source, cross platform runtime environment for developing server side Web applications. It also enables web developers to create an entire web application in JavaScript for both server side and browser side. In the Node.js server side software system, Socket.IO, a JavaScript library for real time web applications, is used to support real time communication between server side and client side [43][44]. Thus, the server application is directly built on the top of an Apache HTTP web engine, a Node.js web engine, and a MySQL database. For the database operations, only the Apache server communicates with MySQL using PHP and SQL for user management and scheduling system. The experiment data are directly saved into the file system using Node.js. Meanwhile, the Operation System of the server uses CentOS for better support the server application. 3) Experiment control application: The experiment control application is developed with the LabVIEW, and runs on a workstation with Windows OS. To implement real time communication between the client application and the LabVIEW experiment equipment control application, a new Socket.IO based application transmission protocol, LtoN (LabVIEW to Node.js), was designed and developed in the unified framework [38]. This new protocol is designed and implemented based on Socket.IO protocol. Socket.IO is the module of Node.js, and is designed based on web socket protocol. For the entire framework, three vital technologies were used. These technologies include: a) Socket.IO protocol and

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIE.2016.2620102, IEEE Transactions on Industrial Electronics IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

TABLE II COMPARISON BETWEEN DIFFERENT MOBILE APPLICATIONS Optimized Native Web Features Applications Applications Applications Running Performance 4 5 3

1. Ionic framework

User Interface

4

5

4

Development Time

3

2

5

Development Cost

3

2

5

Native-Like Feature

4

5

1

5 3.8

1 3.3

5 3.8

Cross-Platform Porting Average

Node-HTTP-Proxy used for experiment data and control commands transmission and traversing firewall [38]. b) The novel video transmission approach is based on HTTP Live Streaming (HLS) protocol for real-time system monitoring [39]. c) The server based Mashup technology is used for UI implementation. This unified framework has been used to implement several remote experiments for engineering education. For example, the new Smart Vibration Platform (SVP) remote experiment is now used to teach students in mechanical engineering courses as reported in [45]. The remote SVP experiment offered students hands-on experience on structural vibration control by using a Magneto-Rheological (MR) and Shape Memory Alloy (SMA) braces to control the vibration of a one story model. B. Mobile Application Development Framework Selection Currently, most of mobile remote laboratory applications are implemented using native application approach and web-based application approach. With the continuous improvement of mobile application development technology, developers are migrating to mobile optimized application development tools such as, PhoneGap, jQuery Mobile, Adobe Air, Titanium, etc. to reduce the cost of development and reach out to maximum users across several platforms [46]. Mobile optimized application is a mix of native and web technologies that are leveraged to deliver a mix of web content and native capabilities. Native mobile applications are developed for one platform and can take full advantage of mobile device capabilities. Web-based applications are not exactly mobile applications but are websites that are mobile formalized. However, native features such as interaction with device sensors cannot be ignored. Mobile optimized application can be

TABLE III COMPARISON BETWEEN DIFFERENT FRAMEWORKS Native-Like Performance 7/10

Support Cordova/AngularJS Yes/Yes

2. Onsen UI

6/10

No/Yes

3. Framework 7

8/10

No/No

4. React Native

8/10

No/No

5. jQuery Mobile

3/10

No/No

6. Native Script

8/10

No/No

Framework

the most suited for cross-platform requirements since the same HTML content needs to be accessed from different mobile platforms. As compared with web applications, the mobile optimized application has better performance which supports cross-platform development, and has similar native functional capability with native application. Moreover, the code portability of mobile optimized application is better than native applications. Meanwhile, development cost of mobile optimized application is lower than native application. The comparison between different applications is shown in Table II. In Table II, the evaluation values are presented on a scale of 1 (very poor) to 5 (Excellent) [47]. With the HTML5 technology development, more and more different mobile optimized application frameworks for developing and building mobile applications emerge in endlessly. An overview of the different cross platform tools is shown in the Fig. 2. From the result of our literature review, the PhoneGap framework is the best framework for mobile optimized application development based on [48][49][50][51]. The PhoneGap is an open source framework that provides developers with an environment where developers can create applications in HTML, CSS, and JavaScript and still call native device features and sensors via a common JavaScript API. The PhoneGap framework contains the native-code pieces to interact with the underlying operating system and pass information back to the JavaScript app running in the WebView container. However, to deliver better user experience, Ionic framework emerges as the first full-stack service platform based on the PhoneGap framework to build and scale the mobile applications with HTML5 technology, and Ionic framework can support most of current hot mobile systems, e.g., Android, iOS, Windows Mobile, Blackberry, Amazon Fire OS, Firefox OS, Ubuntu Mobile OS, and Tizen [52]. Ionic framework is mainly focused on the end users looking,

Fig. 2. Usage distribution among cross-platform tool users in 2013, according to market analysis by Research2guidance [51].

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIE.2016.2620102, IEEE Transactions on Industrial Electronics IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Mobile Optimized Applications Mobile OS APIs

Web App

Rendering Engine

Cordova Plugins Cordova Plugins

Ionic Framework Cordova APIs HLS Video Server

Video Transmission

Node.js and Apache Web Server LtoN APIs Experiment Control and Data Tranmission

The Unified Framework

Fig. 3. Mobile optimized remote laboratory architecture.

feeling, and user experience interaction of the mobile applications [53]. The Ionic framework is not a replacement of the PhoneGap framework. Instead, Ionic framework simply fits in well with these projects which need to simplify the complex UI part of the mobile applications. Meanwhile, it also offers a library of mobile optimized HTML, CSS and JavaScript components, gestures, and tools to build highly interactive applications. The Ionic framework works based on two kernel components, Apache Cordova and AngularJS. From the Table III, the result of comparison with other frameworks shows that the Ionic framework has the unique advantage. Ionic framework enables high native-like performance, around 70%. Meanwhile, it can be supported by both of two development environments, Apache Cordova framework and AngularJS framework. Based on Apache Cordova and AngularJS, the mobile optimized applications, which are developed by JavaScript language, can be built without any native code (e.g., Java, Objective-C) in mobile devices [48]. In this way, Ionic framework can be used to implement interactive mobile applications with the unified framework smoothly on different mobile operation systems. Therefore, the Ionic can be the best candidate for the foundational platform of mobile optimized application architecture. III. A N EW M OBILE O PTIMIZED A PPLICATION A RCHITECTURE To answer our research question, “How to develop a mobile remote laboratory application running cross-platform easily with competitive running performance and hardware accessibility as native application?”, a new mobile optimized application architecture is proposed. This new architecture which combines Ionic framework with the unified framework together can have the advantages of both two frameworks. We expect it has better support for M-Learning. A. Propose a New Mobile Optimized Application Architecture The mobile optimized application architecture includes two layers, optimized application layer and unified framework layer as shown in Fig. 3. 1) Mobile optimized application layer The mobile optimized application layer can support

applications to run on most of popular mobile platforms. As this layer is implemented based on Ionic framework, it also works on two kernel components, Apache Cordova and AngularJS. a.) Apache Cordova: Apache Cordova is an open-source mobile development framework. To avoid each mobile platforms' native development language, it allows developer to use standard web technologies (such as, HTML5, CSS3, and JavaScript, etc.) for cross-platform development. Mobile applications are executed within wrappers on different platforms, and they rely on the standard APIs to access the different device's sensors, data, and network status. To maximize the native mobile devices hardware capabilities the Apache Cordova framework, as a plugin, is integrated into the new application architecture. b.) AngularJS: AngularJS is a structural framework for dynamic web applications development. Developers can use HTML as the template language, and extend HTML's syntax to express the application's components clearly and succinctly. It also provides the data binding function and dependency injection function to eliminate the redundant code of the target mobile application. As more and more new APIs are constantly developed for the interactive features of mobile applications, the Ionic framework supports more and more mobile systems, e.g., Android, iOS, Windows Mobile, Blackberry, Amazon Fire OS, Firefox OS, Ubuntu Mobile OS, and Tizen. To enhance the mobile optimized application performance, Crosswalk as the rendering runtime engine is integrated into the mobile optimized application. Moreover, the Crosswalk also runs as a runtime engine in the different mobile systems to automatically update the rendering engine based on the different platforms. To develop an easy-to-use application UI, the optimized application layer relies on standard APIs of WebView for the application presentation layer. As the WebView can effectively improve the performance and user experience, it works as a middleware between the Web technology (such as, AngularJS, HTML5, Apache Cordava, etc.) and native mobile systems. Depending on the different framework (such as, AngularJS, Apache Cordava, etc.), many different type WebViews can be used for mobile application implementation. The detail modules of the optimized application layer are listed as follows. • Apache Cordova module. • Web Application support module (Implemented with AngularJS, Ionic framework and Common Codebase). • WebView (Crosswalk Rendering runtime engine). • Mobile systems native APIs module (Android, iOS, Windows Mobile, etc.). 2) Unified framework layer In order to integrate the remote laboratory technology into the new mobile optimized application architecture, the unified framework is merged into this new mobile application framework. The unified framework is based on the combination solution of both Apache web engine and Node.js web engine, and it uses a Node-HTTP-based technology to implement the real-time communication between experiment equipment with end users. The subsequent iteration of the design resolved challenges of developing cross-browser and cross-device web

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIE.2016.2620102, IEEE Transactions on Industrial Electronics IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

user interface as an improvement to the unified framework. To implement the real-time communication between experiment equipment with mobile application without plug-ins, a real-time communication module based on LtoN protocol and an experiment control program are developed using LabVIEW which stands for Laboratory Virtual Instrument Engineering Workbench. National Instrument’s LabVIEW software is one of the popularly deployed technologies for remote panel over Internet [54]. With the development of computer technology, LabVIEW also integrated a new feature to interact with the experiment Virtual Instruments by using RESTful web services technology. REST (Representational State Transfer) provides a lightweight protocol accessible to a wide variety of clients. The architecture does not require complex message passing and provides a simple interface for user to begin using Web services in LabVIEW. However, it requires the client interface to be developed using different technologies, and LabVIEW plug-ins must be installed in the web browsers [55]. To resolve this plug-in issue and support the new Mobile Optimized Remote Laboratory Application Architecture, the new application communication module was implemented based on the LtoN protocol. This module includes three parts, a client part that runs in mobile optimized application, a server part runs in the Node.js web server and a control module runs in LabVIEW experiment equipment control program. Client part and server part were developed with JavaScript language and the control module was developed in LabVIEW. With this new application communication module, the mobile optimized application can real-time communicate with experiment equipment without LabVIEW plug-ins in client side. The detail modules of unified framework layer are listed as follows. • Real time video transmission module (Implemented based on HLS protocol). • Real-time experiment data transmission module (Implemented based on LtoN protocol based on web socket). • Combinational Server Engine (Node.js web server and Apache Web server) • Common Codebase (HTML, JavaScript, CSS). • Data Management System (MySQL). • Experiment equipment control module (Implemented by LabVIEW VIs). B. Characteristics

of

the

New

Mobile

Optimized

Fig. 4. The equipment of the PID motor control experiment.

TABLE IV CHARACTERISTIC OF THE REMOTE EXPERIMENT OPTIMIZED APPLICATIONS

Characteristic 1. Cross-Platform

Technology Apache Cordova

2. Native-Like features

Apache Cordova/AngularJS

3. Code Reusable

HTML/JavaScipt/CSS/WV (WebView)

4. Fragmented OS Compatible

Crosswalk Runtime Engine

5. High Performance

Ionic Framework/AngularJS

6. User Friendly

Ionic Framework

7. Real-Time Experiment

The Unified Framework

8. Global Firewall Transmission

The Unified Framework

Application Architecture Table IV depicts the characteristics of the new mobile optimized application architecture. As the Apache Cordova framework supports cross-platform application development, the mobile optimized architecture can support most of the popular mobile systems. In addition, since the AngularJS framework can support dynamic web applications development, lots of native features of different mobile systems can be realized based on the new mobile optimized application architecture. WebView is also the key technology in this new architecture to support reusing the common codebase. Therefore, developers can deploy the mobile optimized applications without spending much time on rewriting the code for different mobile platforms based on the new application architecture. IV. IMPLEMENTATION OF THE NEW APPLICATION A Mechanical Engineering (ME) experiment, PID motor speed control experiment, has been incorporated as part of the remote laboratory series used in the Mechanics, Controls and Vibrations Laboratory (MCVL) course at the University of Houston. In the MCVL course, the assignment for the remote PID control of a DC Motor includes two labs. In the first lab, the students are asked to design three sets of experiments to clearly show the characteristics of the P controller, I controller and D controller based on the knowledge they have learned from the other control theory courses. In the second lab, the students are required to estimate the values of the damping ratio, gain, and natural frequency of a 2nd order system model of the open-loop DC motor system. And based on the values estimated, the model of the DC motor is built with Matlab/Simulink and verified with the experiment data. For the remote experiment integration, the detail process is given below.

Fig. 5. Close up of DC motor.

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIE.2016.2620102, IEEE Transactions on Industrial Electronics IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

A. Experiment Hardware Setup As shown in Fig. 4 and Fig. 5, a remote PID motor controller experiment is built to help students to understand the characteristics of P, PI, PD and PID controllers and visualize the process of remote tuning. The experiment shows student the principle of dynamic systems analysis as well as how to achieve the system optimal behaviors depending on different applications. The controller is designed to control the angular velocity of a DC motor to follow various input signals (i.e. sinusoidal, triangular or square waves) at frequencies of 0.1Hz to 1Hz. Both the input and output angular velocity can be adjusted and displayed in real time, while the rotation of motor will be able to observe through a webcam in the remote laboratory. Saved data include input angular velocity, measured output angular velocity and time in seconds. The remote PID motor control hardware, as shown in Fig. 4, contains a) DC motor with tachometer, b) power amplifier c) power supply for the amplifier, d) NI USB-6361 X Series DAQ and e) PC workstation. The NI USB-6361 X Series DAQ is utilized to both measure the voltage signal from tachometer as the rotation speed of DC motor and generate analog output voltage as control signal. The power amplifier and power supply provide the electronic power to drive the DC motor rotating. In this experimental setup, the LabVIEW VIs which execute on the PC workstation are used to control the motor. During the experiment, LabVIEW generates the reference signal, such as square wave or triangle wave at designated amplitude and frequency. Based on the reference signal and the feedback DC motor speed signal, the PID VIs compute the control signal applied on the DC motor. To optimize the performance of the system, all the P, I and D parameters can be tuned both locally and remotely. B. Experiment Software Integration For the new mobile optimized remote PID motor speed control experiment software integration, three tasks (i.e., the optimized application layer implementation, the unified framework layer integration, and integrate the LtoN module to the new application architecture) have to be done. 1) Mobile optimized remote experiment application implementation To implement the mobile optimized remote experiment application, three key technologies, the Ionic framework, the Crosswalk runtime engine, and the Apache Cordova framework, have to be used. With Web 2.0 technology, Ionic framework uses the common codebase, which includes HTML, CSS and AngularJS/JavaScript. In application implementation process, the common codebase is wrapped into the Cordova framework and is rendered in the UI layer with the Crosswalk runtime engine. Normally, the common codebase is reusable to deploy the mobile optimized application to the different mobile platforms. The Crosswalk works as a middleware to connect the Ionic framework with the unified framework. With these three key technologies, all of the source code and software plugins are packaged with a new mobile optimized remote experiment application. To package the new mobile optimized application, the Eclipse, a popular Integrated Development Environment (IDE) is used. The mobile optimized remote PID

Fig. 6. Block diagram of the new mobile optimized remote PID motor speed control experiment user interface.

motor speed control experiment application UI on three popular mobile operating systems is shown in Fig. 6. The UI includes three parts: a) experiment real-time video; b) real-time experiment data display; c) experiment control components. With the server-based Mashup technology, the data are analyzed and reformatted on the server side, and then the data are transmitted to the users’ mobile Crosswalk rendering runtime engine. The architecture of the new client side rendering scheme is divided into three parts: a) Presentation/Interaction: the new mobile optimized application architecture uses the Crosswalk, as a rendering runtime engine, to render the user interface WebView. b) Web Services: the system functionality can be accessed using the API services. Three protocols, JSON-RPC, REST and SOAP are used. c) Real-time data transmission: the data are handled in three ways, sending, storing and receiving. JSON and Socket.IO are used for data transmission. 2) The unified framework layer integration The unified framework layer is directly built on the top of an assembled server engine scheme. It includes two server engines working together, Apache HTTP server engine and Node.js server engine. With the server-based Mashup technology, the Apache HTTP server engine is used to combine the UI widgets and web content (such as, the real-time experiment data, the real-time experiment video, etc.) together. Meanwhile, the Node.js web engine handles the real-time experiment data transmission. The experiment scheduler system and user management system are also integrated into the unified framework. For the data management, the MySQL 5.5 database management system is used. 3) Integrate the LtoN module to the new mobile optimized application architecture A real time experiment data transmission protocol, named LtoN, is designed and developed based on Socket.IO protocol. With the new real time transmission protocol, students can conduct the experiment, and save the experiment data. To integrate the LtoN protocol to the new mobile optimized application architecture, some improvements need to be implemented. More details of the improved LtoN protocol are illustrated in the followings. a) The new application communication protocol includes two parts, client part running in Crosswalk rendering runtime engine and server part running in web server. It is developed by AngularJS/JavaScript language and enhanced by the web socket protocol. b) In this new application transmission protocol, we defined our own special communication instruction set to implement real time

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TABLE V PERFORMANCE TEST RESULT Optimized Remote Control Experiment Test Items Application (PID Motor Speed Control) CPU Occupancy Rate 2.66667%

Native Remote Control Experiment Application (RoboLiterate) 5.68%

Memory Usage

53322KB

18847.55KB

Package Size

1459 KB

4.5MB

Starting Duration

321 ms

506.21 ms

Content Loading Time

1010 ms

1010 ms

Charge Depleting

167.234 mA

0.15 mA

Frame Rate Test

3.28 FPS

2.68 FPS

experiment control commands and experimental data transmission. With the new communication instruction set, we can secure the data communication when user is conducting the remote experiment. To implement the improved LtoN protocol, only two JavaScript files need to be created. One for the client application is running in Crosswalk rendering runtime engine, and the other one for the server application is running in web server. Meanwhile, the new Node.js task needs to be created to run the protocol in server-side, and this server-side application must hold running status forever. To ensure the normal real-time communication tasks, the server-side protocol application must be held the active status. On the client side, a set file of communication instruction functions are used to support the normal operation of the remote experiment optimized application in Crosswalk rendering runtime engine. C. Performance of the Mobile Optimized Remote PID Motor Speed Control Experiment Application To test the performance of the new mobile optimized remote PID motor speed control experiment application, the Baidu mobile cloud testing center (http://mtc.baidu.com) is used. Baidu mobile cloud testing center provides free mobile application testing and porting service to any mobile application developers. After uploading the applications into the testing center, developers can test all functions of applications from startup to shut down, and once testing is complete the test center will provide a test report. The mobile optimized application has been tested via automated testing. It has over 10000 mobile devices which cover 1500 different mobile platforms. Automated testing uses scripting environment, which we can call the application functionality via scripts (For example, Python) to customize some tests. Such as phone calls, send text messages, browse the web, and so on. The testing center can expand mobile application API, and calls the API in python scripts, enabling extensive testing. To compare the performance with native remote experiment, we found an open source native remote experiment application namely RoboLiterate. RoboLiterate is the all-in-one Bluetooth remote control experiment to control Lego Mindstorms NXT robot. Table V depicts the test result. In this test, we compared the mobile optimized remote PID experiment application with a native remote control experiment application, RoboLiterate. Because these two applications have big difference package

size, 1459KB vs 4.5MB, the mobile device CPU occupancy rate, memory usage, starting duration are not difference. As we know, the key evaluation metric for mobile application is the content loading time. From the result, these two applications’ content loading time is the same. Consequently, the mobile optimized remote PID experiment application has native-like performance as it blends some advantages of native functions of mobile devices and some mobile web browser capabilities for M-Learning. V. FUTURE W ORKS Although the new mobile optimized remote laboratory application architecture delivers a new development tool to support student-centered mobile learning, there are still further development required to improve the new architecture stability and usability. More specifically, issues that need improvement are as follows: 1) Integrating the new mobile optimized remote laboratory application architecture into the Learning Management Systems (LMS). Currently, we developed our own remote laboratory management platform, and it includes a scheduler, a user management module, and a learning materials management module. In future, we plan to integrate our mobile optimized remote laboratory application architecture into an open source LMS (e.g., Moodle) to avoid double registration of students. 2) Cloud Computing technology will be used to more new mobile optimized remote experiment applications deployment in future. The new mobile optimized remote laboratory application architecture is still version 1.0. So far, only a few sample pilot tests were conducted. Some bugs in the software package have been fixed through students’ feedback. More comprehensive testing and user survey need to be done. VI. CONCLUSION In this paper, a new mobile optimized application architecture was designed and implemented successfully to provide a new tool for M-Learning application and industrial electronics application development. The new mobile optimized application architecture integrated the advantages of both native mobile applications and web applications. It improved the running performance and solved hardware accessibility issue of web applications. It also solved the cross-platform running issue of native application. Moreover, it seamlessly combined the unified framework and Ionic framework together to deliver the excellent remote laboratory services to students. As a pilot M-Learning application based on the new architecture, a new mobile remote PID experiment application was implemented successfully. It can connect the students to the real PID motor speed control experiment through the M-Learning environment anywhere and anytime. The future work will be to further refine and improve this mobile optimized application architecture for M-Learning. ACKNOWLEDGMENT The authors would like thank to anonymous referees for their

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helpful comments and suggestions. REFERENCES [1]

[2]

[3] [4] [5] [6]

[7] [8]

[9] [10]

[11]

[12]

[13]

[14]

[15]

[16]

[17]

[18] [19]

[20]

[21]

[22]

[23]

G. Papagiannakis, G. Singh, and N. Magnenat‐Thalmann, “A survey of mobile and wireless technologies for augmented reality systems,” CAVW, vol. 19, no. 1, pp.3-22, Mar. 2008. M. Saylor, “Active Learning and Virtual Worlds,” The mobile wave: how mobile intelligence will change everything, Vanguard Press. pp. 176-180. ISBN 978-1593157210, Jan. 2013. G.I. Analysts. “ELearning (MCP-4107): A global strategic business report,” Global Industry Analysts, Inc. pp.9-11, Mar. 2014. A. Kukulska-Hulme, “Smart devices or people? A mobile learning quandary”. IJLM, vol. 4, no. 3-4, pp.73-77, Aug. 2012. M. Ally, and J. Prieto-Blázquez, “What is the future of mobile learning in education?” RUSC, vol. 11, no. 1, pp.142-151, Jan. 2014. C. Wen, and J. Zhang, "Design of a Microlecture Mobile Learning System Based on Smartphone and Web Platforms," IEEE Trans. Edu., vol. 58, no. 3, pp. 203-207, Aug. 2015. J.S. Sung, "Design of Smart Learning in Mobile Environment." IJSEIA, vol. 9, no. 12, pp. 373-380, Dec. 2015. W.H. Wu, Y.C.J. Wu, C.Y. Chen, H.Y. Kao, C.H. Lin, and S.H. Huang, “Review of trends from mobile learning studies: A meta-analysis,” Computers & Education, vol. 59, no. 2, pp. 817-827, Sep. 2012. L. Gomes and S. Bogosyan, "Current trends in remote laboratories," IEEE Trans. Ind. Electron., vol. 56, no. 12, pp. 4744-4756, Dec. 2009. V. J. Harward, J. A. DelAlamo, S. R. Lerman, P. H. Bailey, J. Carpenter, K. DeLong, C. Felknor, J. Hardison, B. Harrison, I. Jabbur, P. D. Long, T. Mao, L.Naamani, J. Northridge,M. Schulz,D. Talavera, C.Varadharajan, S. Wang, K. Yehia, R. Zbib, and D. Zych, “The iLab shared architecture: A web services infrastructure to build communities of internet accessible laboratories,” Proc. IEEE, vol. 96, no. 6, pp. 931–950, Jun. 2008. P. Orduna, J. Irurzun, L. Rodriguez-Gil, J. Garcia-Zubia, F. Gazzola, and D. Lopez-de-Ipina, “Adding new features to new and existing remote experiments through their integration in WebLab-Deusto,” iJOE, vol. 7, no. S2, pp. 33–39, Jun. 2011. W. S. Hu, G. P. Liu & H. Zhou “NCSLab: A web-based global-scale control laboratory with rich interactive features,” IEEE Trans. Ind. Electron., vol. 57, no. 10, pp. 3253-3265. Oct. 2010 Y. L. Qiao, G. P. Liu, G. Zheng & W. S. Hu “Web-Based 3-D Control Laboratory for Remote Real-Time Experimentation,” IEEE Trans. Ind. Electron., vol. 60, no. 10, pp. 4673-4682, Oct 2013. A. Melkonyan, A. Gampe, M. Pontual and G. Huang, "Facilitating Remote Laboratory Deployments Using a Relay Gateway Server Architecture", IEEE Trans. Ind. Electron., vol. 61, no. 1, pp. 477-485, Jan. 2014. A. A. Kist, P. Gibbings, A. D. Maxwell, and H. Jolly, "Supporting remote laboratory activities at an institutional level," iJOE, vol. 9, no. S5, pp. 38-47, Oct. 2013. D. May, C. Terkowsky, T. Haertel, and C. Pleul, “Bringing Remote Labs and Mobile Learning together,” iJIM, vol. 7, no. 3, pp.54-62, Sep. 2013. J. B. Silva, W. Rochadel, J. P. Simão, R. Marcelino, and V. Gruber. "Using Mobile Remote Experimentation to Teach Physics in Public School." In Proc. Int. Conf. CABL. 2013, pp. 46-51. S. A. Saleh, and B. S. Ahmad. "Mobile Learning: A Systematic Review." IJOCA, vol. 114, no. 11, pp. 1-5, Nov. 2015. H. Crompton, D. Burke, K.H. Gregory, and C. Gräbe, “The Use of Mobile Learning in Science: A Systematic Review.” JSET, vol. 25, issue 2, pp. 149-160, Apr. 2016. D. Ivanc, R. Vasiu and M. Onita, "Usability evaluation of a LMS mobile web interface." Information and Software Technologies, Springer Berlin Heidelberg, ISBN 978-3-642-33308-8, pp. 348-361, Oct. 2013. S. Teri, A. Acai, D. Griffith, Q. Mahmoud, D.W. Ma and G. Newton, "Student use and pedagogical impact of a mobile learning application." Biochemistry and Molecular Biology Education, vol. 42, no. 2, pp. 121-135, Apr. 2014. A. Juntunen, E. Jalonen, and S. Luukkainen, “Html 5 in mobile devices– drivers and restraints,” In Proc. 46th IEEE HICSS. Int. Conf. 2013, pp. 1053–1062. A. Charland and B. Leroux, “Mobile application development: web vs. native,” Communications of the ACM, vol. 54, no. 5, pp. 49–53, May. 2011.

[24] B. Deaky, D.G. Zutin and P.H. Bailey "The First Android Client Application for the iLab Shared Architecture," iJOE, vol.8, no. 1, pp. 4-7, Mar. 2012. [25] A. Hossain, J. Canning, S. Ast, P.J. Rutledge, T.L. Yen, and A. Jamalipour, “Lab-in-a-phone: smartphone-based portable fluorometer for pH measurements of environmental water,” IEEE Sensors, vol. 15, no. 9, pp. 5095-5102, Sep. 2015. [26] A. Alkouz, A. Y. Al-Zoubi, and O. Mohammed. "J2ME-based mobile virtual laboratory for engineering education," iJIM, vol. 2, no. 2, pp. 5-10, Jun. 2008. [27] D. Chaos, J. Chacón, J.A. Lopez-Orozco, and S. Dormido, “Virtual and remote robotic laboratory using EJS, MATLAB and LabVIEW,” Sensors, vol. 13, no. 2, pp.2595-2612, Feb. 2013. [28] C. A. Garc and P. Merino, “Remote control and instrumentation of Android devices,” In Proc. IEEE Int. Conf. REV Instrum. 2016, pp. 190-195. [29] C. Onime and O. Abiona, “3D Mobile Augmented Reality Interface for Laboratory Experiments,” IJCNS, vol. 9, no. 4, p.67-76, Apr. 2016. [30] J. Garcia-Zubia, D. López-de-Ipiña and P. Orduña, "Mobile devices and remote labs in engineering education," In Proc. 8th IEEE Int. Conf. on Adv. Learn. Tech., 2008, July, pp. 620-622. [31] I. Gustavsson, K. Nilsson, J. Zackrisson, J. Garcia-Zubia, U. Hernandez-Jayo, A. Nafalski, Z. Nedic, O. Gol, J. Machotka, M.I. Pettersson and T. Lago, “On objectives of instructional laboratories, individual assessment, and use of collaborative remote laboratories,” IEEE Trans. Learn. Technol., vol. 2, no. 4, pp. 263-274, Oct-Dec. 2009. [32] C. Terkowsky, C. Pleul, I. Jahnke, and A.E. Tekkaya, “Tele-Operated Laboratories for Online Production Engineering Education-Platform for E-Learning and Telemetric Experimentation (PeTEX),” iJOE, vol. 7, no. S1, pp.37-43, Mar. 2011. [33] J. B. Silva, W. Rochadel, J. P. S. Simao, S.M.S. Bilessimo, P. C. Nicolete, “Using Mobile Devices for Conducting Experimental Practices in Basic Education,” Online Experimentation: Emerging Technologies and IoT, IFSA Publishing, ISBN-13: 978-8460859772, vol. 1, pp. 401-418, Dec. 2015. [34] J. B. Ortega, E.B. Portas, J.A.L. Orozco, J.A. B. Seco, and J.M. Cruz, “Remote Web-based Control Laboratory for Mobile Devices based on EJsS, Raspberry Pi and Node.js,” IFAC-PapersOnLine, vol. 48, no. 29, pp.158-163, Nov. 2015. [35] F. Lustig, J. Dvorak, and P. Brom, “Simple modular system "iSES Remote Lab SDK" for creation of remote experiments accessible from PC, tablets and mobile phones: Workshop,” In Proc. IEEE Int. Conf. REV Instrum. 2016, pp. 406-408. [36] N. Serrano, J. Hernantes and G. Gallardo, “Mobile web apps,” IEEE Software, vol. 30, no. 5, pp.22-27, Sept-Oct. 2013. [37] N. Wang, X. Chen, G. Song, and H. Parsaei, “Remote experiment development using an improved unified framework,” in Proc. Int. Conf. E-Learning 2014, vol. 2014, no. 1, pp. 2003–2010. [38] N. Wang, X. Chen, G. Song, and H. Parsaei, “Using Node-HTTP-Proxy for Remote Experiment Data Transmission Traversing Firewall,” iJOE, vol. 11, no. 2, pp.60-67, Jun. 2015. [39] N. Wang, X. Chen, G. Song, and H. Parsaei, “A novel real-time video transmission approach for remote laboratory development,” iJOE, vol. 11, no. 1, pp. 1–4, Mar. 2015. [40] J. García-Zubia, P. Orduňa, D. López-de-Ipiňa, and G.R. Alves, "Addressing software impact in the design of remote laboratories," IEEE Trans. Ind. Electron., vol. 56, no. 12, pp. 4757-4767, Dec. 2009. [41] M. Tawfik, D. Lowe, C. Salzmann, D. Gillet, E. Sancristobal, and M. Castro. "Defining the Critical Factors in the Architectural Design of Remote Laboratories," IEEE-RITA, vol. 10, no. 4, pp. 269-279. Nov. 2015. [42] R.T. Fielding and G. Kaiser, “The Apache HTTP server project,” IEEE Int. Comp., vol. 1, no. 4, pp.88-90. Jul-Aug.1997. [43] D. Herron “The capabilities of Node,” Node Web Development, Second Edition, Birmingham: Packt Publishing, ISBN 184951514X, pp.8-9, Jul. 2013. [44] R. Rai "The Socket.IO protocol," Socket.IO Real-time Web Application Development, Sebastropol: O'Reilly Media, pp. 87-91, ISBN 178-2-1607-87, Feb. 2013. [45] X. Chen, D. Osakue, N. Wang, H. Parsaei and G. Song, "Development of a Remote Experiment under a Unified Remote Laboratory Framework," in Proc. Int. Conf. WCEE 2013. H.R. Parsaei and K.S. Warraich, eds.

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[46] I. Dalmasso, S.K. Datta, C. Bonnet and N. Nikaein, “Survey, comparison and evaluation of cross platform mobile application development tools,” In Proc. 9th. IWCMC. Int. Conf., 2013, pp. 323-328. [47] S. Ottka, “Comparison of mobile application development tools for multi-platform industrial applications,” Master Thesis of Degree Programme in Computer Science and Engineering, Aalto University, Finland. 2015. [48] R. M. Babu, M.B. Kumar, R. Manoharan, M. Somasundaram, and S.P. Karthikeyan, “Portability of mobile applications using phonegap: A case study,” In Proc. ICSEMA. Int. Conf., 2012, pp. 1-6. [49] H. Heitkötter, T.A. Majchrzak, B. Ruland, and T. Weber, “Evaluating Frameworks for Creating Mobile Web Apps,” In Proc. the 9th WEBIST. Int. Conf. 2013, pp. 209-221. [50] M. Ciman, O. Gaggi, and N.Gonzo, “Cross-platform mobile development: a study on apps with animations,” In Proc. 29th Annual ACM Symp. Appl. Comp. conf., 2014, pp. 757-759. [51] Research2guidance. “Cross Platform Tool Benchmarking 2013 Hidden champions of the app economy,” Technical Report, http://www.research2guidance.com/r2g/Cross-Platform-Tool-Benchmar king-2013.pdf, Oct. 2013. [52] A. Biharisingh. (2015) “Build Your First Mobile App With The Ionic Framework – Part,” http://gonehybrid.com/build-your-first-mobile-app-with-the-ionic-frame work-part-1, posted, Jan. 2015 [53] R. Khanna and M. Harlington, “Anatomy of a Hybrid Mobile App,” Getting Started with Ionic, Packt Publishing, ISBN: 978-1-78439-057-0, pp. 4-5, Jan. 2016. [54] N. Duro, R. Dormido, H. Vargas, S. Dormido-Canto, J. Sánchez, G. Farias, S. Dormido and F. Esquembre, “An Integrated Virtual and Remote Control Lab: The Three-Tank System as a Case Study,” Computing in Science & Engineering, vol. 10, no. 4, p.50-59, Jul-Aug. 2008. [55] P. Orduña, J. García-Zubia, L. Rodriguez-Gil, J., Irurzun, D. López-de-Ipiña, and F. Gazzola, “Using LabVIEW remote panel in remote laboratories: Advantages and disadvantages,” In Proc. IEEE Global Eng. EDUCON, 2012, pp. 1-7. Ning Wang (SM’14) was born in Gansu, China. He received his B.S. degree from the Department of Information Management System at China Agriculture University (CAU) in 2002, Beijing, China. He received the M.S in Software Management Science at Hong Kong Polytechnic University (HKPU) in 2008 and the M.S in Computer Science at Texas Southern University (TSU) in 2014. He is currently working toward the PhD degree in the Department of Electrical and Computer Engineering at the University of Houston (UH). He received the COSET distinguished graduate student award from the Texas Southern University in 2014. He is a student member of the IEEE. He published over 6 peer reviewed journal papers, and over 13 conference papers. His research interests include remote laboratory, remote control, network technology, electrical control and embed system software design.

Gangbing Song (SM’93-M’96) was born in Wuhan, China. He received his Ph.D. and MS degrees from the Department of Mechanical Engineering at Columbia University in the City of New York in 1995 and 1991, respectively. He received his B.S. degree in 1989 from Zhejiang University, China. Dr. Song is the founding Director of the Smart Materials and Structures Laboratory and a Professor of Mechanical Engineering, Civil and Environmental Engineering, and Electrical & Computer Engineering at the University of Houston (UH). Dr. Song holds the John and Rebeca Moores Professorship at UH. Dr. Song is a member of ASCE, ASME, and IEEE. He has published more than 400 papers, including 200 peer reviewed journal articles. Dr. Song is also an inventor or co-inventor of 11 US patents and 11 pending patents. Qianlong Lan was born in Guangxi, China, in 1991. He received the B.S. degree in network engineering from the Shanghai Second Polytechnic University, Shanghai, China, in 2013, and started the M.S. degrees in computer science from the Texas Southern University (TSU) Houston, Texas, U.S, in August, 2014. In 2014, he joined the Department of Computer Science, Texas Southern University, as a research assistant. He published five conference papers in his two years study in Texas Southern University Mr. Lan is the recipient of the COSET Research Enrichment Scholarship of the Texas Southern University for his contributions to the field of research in 2016. Hamid R. Parsaei was born in Tehran, Iran. He received his BS degree from the National University of Iran and MS and Ph.D. degrees in Industrial Engineering from Western Michigan University and the University of Texas at Arlington in 1980 and 1984, respectively. He is currently serving as Professor of Mechanical Engineering at Texas A&M University at Qatar and holds the title of professor with tenure in the Department of Industrial and Systems Engineering at Texas A&M University in College Station, Texas. He served as Associate Dean for Academic Affairs at Texas A&M University at Qatar (2010-2014), Professor and Chair of the Department of Industrial Engineering at University of Houston (2001-2010), Professor of Industrial Engineering at University of Louisville (1986-2000), and the State University of New York in Utica (1984-1986). Dr. Parsaei has published over 270 articles in peer reviewed archival journals and conference proceedings. He is a fellow of the Institute of Industrial and Systems Engineers and the American Society for Engineering Education. Dr. Parsaei is a registered professional engineer in the State of Texas, USA.

Xuemin Chen (M’99-SM’08) was born in Jiangsu, China. He received his B.S., M.S. and Ph.D. degrees in Electrical Engineering from the Nanjing University of Science and Technology (NJUST), China, in 1985, 1988 and 1991 respectively. He joined Texas Southern University (TSU) in 2006. Currently, he is an Associate Professor in engineering department at TSU. He was postdoc fellow and then a research assistant professor in electrical and computer engineering department at the University of Houston from 1998 to 2006. He was faculty member of Department of Automation at NJUST from 1991 to 1998. Dr. Chen initiated the Virtual and Remote Laboratory (VR-Lab) and served as founding director of VR-Lab at TSU in 2008.

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