This work was supported by the National Natural Science Foundation of China under Grant 62103308, Grant 62173255, Grant 62073247, and Grant 61773144.

In this work, three separate visualized examples are provided to enhance teaching and learning and research, which can be accessed via the Networked Control System Laboratory (NCSLab&#160;https://www.powersim.whu.edu.cn/react).
1. Example 1: First-order system using circuit-based experimentation protocol
<ol>
	<li>Access the NCSLab system.
	<ol>
		<li>Open a mainstream web browser and enter the URL&#160;https://www.powersim.whu.edu.cn/react.</li>
		<li>Click on the Start Experiment button on the left side of the main page to log in to the system. User name: whutest; password: whutest. 
		NOTE: This step also suits for other two examples (Example&#160;2 and Example 3).</li>
		<li>Enter the WHULab in the left side sub-laboratory list and choose WHUtypicalLinks for experimentation. 
		NOTE: Six sub-interfaces are designed and implemented for different purposes to support simulation and real-time experimentation.</li>
		<li>Enter the Algorithm Design sub-interface. 
		NOTE: The user can choose a public algorithm model designed and shared by other authorized users or create a new model.</li>
		<li>Choose and click on the Create New Model button and enter the web-based algorithm interface. Build a circuit diagram using the provided blocks, as shown in Figure 1. 
		NOTE: Another operational amplifier (op-amp) (Op-Amp2 in Figure 1) is used to cancel the 180&#176; phase shift. To ensure that the input, the resistors, and the capacitor are tunable, one variable capacitor and two variable resistors in the ELECTRIC ELEMENTS library and four constant blocks from the SOURCES library are selected from the left-side block library panel.</li>
		<li>Double click the corresponding blocks to set parameters as listed in Table 1. Set the X-axis range of the chart to 8 s. 
		NOTE: A popup window will be triggered after a double click to the block, which includes the descriptions of the block and can be used for setting the parameter. An example of the Resistor (R3) is illustrated in Figure 1.</li>
		<li>Click on the Start Simulation button; the simulation result will be provided in the interface, as included in Figure 1. 
		NOTE: This step also suits the two other examples with other test rigs. The simulation results can provide information for users to recheck the designed circuit-based system to avoid a wrong circuit. However, a faulty circuit will cause no harm to the users or the system, so the users do not have to worry about the consequences.</li>
		<li>Click on the Start Compilation button. Wait until the designed block diagram is generated into an executable control algorithm that can be downloaded and executed into the remote controller deployed at the test rig side to implement control algorithms. 
		NOTE: This step also suits the following experiments with other test rigs.</li>
		<li>Conduct real-time experiments using the generated control algorithm. Click on the Request Control button to apply for control of the circuit system. 
		NOTE: &#34;Request control&#34; is the scheduling mechanism for the system. Once a user is granted the control privilege, the user can conduct experiments with the corresponding test rig. Only one user can occupy the test rig at a time for physical test rigs, and the queue scheduling mechanism has been implemented to schedule other potential users based on the First Come First Served rule11. For virtual test rigs, a massive number of users can be concurrently supported. 500 concurrent user experimentation has been tested effectively. For the circuit-based system, 50 users can access the system at a time.</li>
		<li>Click on the Return button to the Algorithm Design sub-interface. Find the executable control algorithm under the Private Algorithm Models panel. 
		NOTE: The executable control algorithm can also be found in the My Algorithm panel in the Control Algorithm sub-interface.</li>
		<li>Click on the Conduct An Experiment button to download the designed control algorithm to a remote controller.</li>
		<li>Enter the Configuration sub-interface and click on the Create New Monitor button to configure a monitoring interface, as shown in Figure 2. Four textboxes for parameter tuning and one curve chart for signal monitoring are included. 
		NOTE: The chart on the right in Figure 2 is the same chart as the one in the left, which was added to demonstrate the data using the Suspend button.</li>
		<li>Link the signals and parameters with the selected widgets. 
		NOTE: Parameter/ Input, Parameter/ R0, Parameter/ R1, and Parameter/ C for four textboxes, respectively, and Parameter/ Input and Signal/ Output for the curve chart.</li>
		<li>Click on the Start button to start the experiment. 
		NOTE: This step also suits the following experiments with other test rigs. Users can save the configuration for future use.</li>
		<li>Set the input voltage to 0 V, tune the capacitor C to 5 &#181;F (0.000005 in Figure 2), and then set the input voltage to 1 V; the dynamic process of the output voltage is illustrated in Figure 2.</li>
	</ol>
	</li>
	<li>Calculate the corresponding parameters K and T. 
	&#8203;NOTE: The time constant can be calculated when the output reaches 63.2% of the final value K after t = T, which is 0.63212. From Figure 2, it can be seen that the time duration is 1 s, thus, T = 1, which is consistent with the theory in which, T = R1C = 200000*0.000005 = 1, and K = R1/R0 = 200000 / 200000 = 1 (which equals the final value)12. Thus, the first-order system can be specified as: <img alt="Equation 1" src="/files/ftp_upload/63342/63342eq01.jpg" />.</li>
</ol>
2. Example 2: Interactive and visualized virtual experimentation protocol
<ol>
	<li>Use the NCSLab system to conduct simulation and real-time experimentation.
	<ol>
		<li>Log in to the NCSLab system. Enter the ProcessControl sub-laboratory and choose the dualTank test rig, and then enter the Algorithm Design sub-interface.</li>
		<li>Design a proportional-integral-derivative (PID) control algorithm using the web interface provided by NCSLab following the steps described in Example 1. Figure 3 is an algorithm example for the dual tank system.</li>
		<li>Double click on the PID controller, and tune the parameters for Proportional (P), Integral (I) and Derivative (D) terms. Set P = 1.12, I = 0.008 and D = 6.6, respectively. 
		NOTE: The P, I, and D terms should be tuned combined with the simulation result.</li>
		<li>Click on the Start Simulation button; the simulation result will pop up, which is included on the right side of Figure 3. 
		NOTE: It can be seen that the control performance is good, and the control algorithm is ready for real-time experimentation.</li>
		<li>Generate the executable control algorithm following the previously mentioned steps.</li>
		<li>Download the control algorithm to the remote controller and configure a monitoring interface with four textboxes for Set_point, P, I, and D, respectively.</li>
		<li>Include a chart for monitoring the water level and the corresponding Set_point. Choose a 3-D widget, which can provide all angles of the test rigs and animations of water level connected with the real-time data.</li>
		<li>Click on the Start button; then, the monitoring interface will be activated as shown in Figure 4, which provides a visualized virtual experiment.</li>
		<li>Set the Set_point from 10 cm to 5 cm, and then set I = 0.1 when the height of the water level in the controlled tank reaches and stabilizes at 5 cm. Reset the set-point from 5 cm to 15 cm; it can be seen from Figure 4 that there is an overshoot.</li>
		<li>Tune I from 0.1 to 0.01 and reset the set-point from 15 cm to 25 cm. It can be seen that the overshoot has been eliminated, and the water level can quickly stabilize at the set-point value of 25 cm.</li>
	</ol>
	</li>
</ol>
3. Example 3: Research with remote and virtual laboratories protocol
<ol>
	<li>Conduct a real-time experiment in NCSLab.
	<ol>
		<li>Log into the NCSLab system and choose Fan Speed Control&#160;in the Remote Laboratory&#160;sub-laboratory.</li>
		<li>Enter the Algorithm Design sub-interface. Drag the blocks to construct the internal model control (IMC) control algorithm diagram, as shown in Figure 5. 
		NOTE: The F(s) and Gm(s)-1 is designed as shown in Figure 5, in which the designed control algorithm using NCSLab is illustrated to control a fan speed control system in a remote and virtual laboratory mode.</li>
		<li>Generate the executable control algorithm and employ the fan speed control system to verify the designed IMC algorithm.</li>
		<li>Configure a monitoring interface. Link two textboxes with two parameters, namely, the Set_point and lambda (for&#160;&#955; which is the filter time constant) for tuning, and a real-time chart with the Set_point and Speed for monitoring. Select the 3-D model widget of the fan and the camera widget for monitoring.</li>
		<li>Click on the Start button to activate real-time experimentation. Reset the Set_point from 2,000 rpm to 1,500 rpm, and then reset it from 1,500 rpm to 2,500 rpm, the result of which is shown in Figure 6. 
		NOTE: It can be concluded that when&#160;&#955; = 1 the system can be stabilized to a step reference.</li>
	</ol>
	</li>
</ol>

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<li>Zaman, M. A., Neustock, L. T., Hesselink, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((iLabs+as+an+online+laboratory+platform%3A+A+case+study+at+Stanford+University+during+the+COVID-19+Pandemic%5BTitle%5D)+AND+%222021+IEEE+Global+Engineering+Education+Conference+%28EDUCON%29%22%5BJournal%5D)">iLabs as an online laboratory platform: A case study at Stanford University during the COVID-19 Pandemic.</a> 2021 IEEE Global Engineering Education Conference (EDUCON). , 1615-1623 (2021).</li>
<li>Gomes, L., Bogosyan, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Current+trends+in+remote+laboratories%5BTitle%5D)+AND+%22IEEE+Transactions+on+Industrial+Electronics%22%5BJournal%5D)">Current trends in remote laboratories.</a> IEEE Transactions on Industrial Electronics. 56 (12), 4744-4756 (2009).</li>
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<li>Lei, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Unified+3-D+interactive+human-centered+system+for+online+experimentation%3A+Current+deployment+and+future+perspectives%5BTitle%5D)+AND+%22IEEE+Transactions+on+Industrial+Informatics%22%5BJournal%5D)">Unified 3-D interactive human-centered system for online experimentation: Current deployment and future perspectives.</a> IEEE Transactions on Industrial Informatics. 17 (7), 4777-4787 (2021).</li>
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The authors have nothing to disclose.

The presented protocol&#160;describes a hybrid online laboratory system that integrates physical test rigs for remote experimentation and 3-D virtual test rigs for virtual experimentation. Several different block libraries are provided for the algorithm design process, such as the electrical elements for circuit-based design. Users from control backgrounds can focus on learning without programming skills. The proper design of a control algorithm that can be applied to a suitable test rig should be considered. It is also challenging to design a controller to guarantee a good control performance (considering control performance index, including overshoot, settling time, and steady error) before applying it to the controlled test rig. Before compiling a control algorithm that can be used for real-time experimentation, simulation should be conducted to address potential issues. Control algorithms can be applied to other different test rigs using the system once they are integrated into the proposed system.
The background and theoretical knowledge regarding the three examples are as follows.
For the first-order system, the principle of the first-order system can be analyzed using circuit theory with the provided circuit in Figure 7. According to circuit theory12, the following two equations can be obtained. From the input side view of the op-amp, the current is
<img alt="Equation 2" src="/files/ftp_upload/63342/63342eq02.jpg" /> (1)
From the output side view of the op-amp, Equation 2 can be obtained
<img alt="Equation 3" src="/files/ftp_upload/63342/63342eq03.jpg" /> (2)
where <img alt="Equation 4" src="/files/ftp_upload/63342/63342eq04.jpg" /> is the impedance of the RC parallel circuit.
By combining Equation 1 and 2, the transfer function of the system can be calculated as
<img alt="Equation 5" src="/files/ftp_upload/63342/63342eq05.jpg" /> (3)
in which the minus sign (-) indicates a 180&#176; phase shift of the output voltage, which is neglected in the analysis in the following steps.
Denote K = R1/R0, T = R1C, and then the transfer function of the system can be represented as
<img alt="Equation 6" src="/files/ftp_upload/63342/63342eq06.jpg" /> (4)
For the dual tank system, the designed 3-D water tank system is illustrated in Figure 8. The design and implementation of a previous version using Flash have been explored in the work of W. Hu et al. in 201413. The control purpose of this test rig is to control the water level in the second tank to the value of the set point. A PID controller has been used to control the dual tank. Theoretically, the PID can be expressed as14
<img alt="Equation 7" src="/files/ftp_upload/63342/63342eq07.jpg" /> (5)
where Kp, Ki, Kd are the coefficients for P, I, and D terms, respectively.
IMC is simple to tune with good set-point tracking performance and has been widely used to control real-life applications15. The control architecture of IMC is shown in Figure 9, in which G(s) is the real plant and Gm(s) is the model of the plant. Gm(s) is usually obtained through system identification. Gm(s)-1 is the inverse model of Gm(s), and F(s) is the filter. R(s), Y(s), and E(s) are the reference, output, and error, respectively. The F(s), Gm(s)-1, and Gm(s) constitute the IMC controller. A standard default filter F(s)16 is used in this work as Equation 6
<img alt="Equation 8" src="/files/ftp_upload/63342/63342eq08.jpg" /> , (6)
where &#955; is the filter time constant, and order n is selected to ensure a proper or semi-proper IMC compensator (F(s)*Gm(s)-1).
The IMC control algorithm has been designed and applied to control the physical fan speed system through calculation, analysis, and proper design. In this work, G(s) represents a physical fan speed control system, whose model Gm(s) is identified as a second-order system
<img alt="Equation 9" src="/files/ftp_upload/63342/63342eq09.jpg" />. (7)
The order n of the filter F(s) is set to 1. For tuning purposes, the lambda in Figure 5 represents the reciprocal of the &#955; in Equation 6 and can be easily tuned. The filter is set to be the following
<img alt="Equation 10" src="/files/ftp_upload/63342/63342eq10.jpg" />. (8)
Web-based algorithm design allows users at an advanced level to design more complex algorithms with the support of S-function. However, more advanced control strategies for research and education, such as control strategies for multi-agent systems or networked control strategies with time constraints, are under consideration for further upgrading the proposed laboratory system.
The circuit-based system is based on simulation. One of the advantages of simulation is that the users can conduct their operations freely. They do not have to worry about the consequences since their misoperation will cause no harm to themselves and the system and test rigs, especially in an online experimentation system.
After a circuit-based system is designed, the user is supposed to run a simulation. For some cases, such as failing to ground the circuit, the simulation and compilation results will warn the users, which can help them to recheck the designed circuit (Supplementary Figure 1 and Supplementary Figure 2). For other cases, for example, reversing the capacitor&#39;s polarity (Supplementary Figure 3), no warning message will be shown when a user tries to conduct a simulation or compilation, the result of which is similar to that of a correct circuit as shown in Supplementary Figure 4.
Currently, the main limitation of the online experimentation system is that it can primarily be used for users with a control background. The circuit-based system can only be used for simulation with no hardware setups. To cover diverse engineering fields, hardware for circuit systems that can be applied to electrical and electronics engineering can be integrated. More test rigs for other areas should also be considered.
Compared with MATLAB/Simulink, a standalone MATLAB/Simulink for each user is not required using the proposed methodology. Moreover, real-time experimentation with 3-D virtual test rigs and physical test rigs is more than pure simulation in the proposed laboratory. Compared with the MATLAB/Simulink-based remote laboratory presented by I. Santana et al.9, the proposed laboratory can be used to design controllers and the entire control system with the circuit-based system, 3-D virtual, and physical test rigs. Experimentation environment (EE) offers practical controller design methods with Blockly-based visual design for simple experiments and a JavaScript-based textual design for complex experiments5. Considering students are more familiar with MATLAB/Simulink, a block-based algorithm design interface similar to MATLAB/Simulink can be a good option&#160;for designing the control system.
The proposed system can be utilized for teaching, learning, and research for teachers, students, and researchers. Currently, the system has been mainly used in control engineering-related disciplines. The system can potentially be applied to electrical and electronics engineering, industrial electronics, and industrial control.

Laboratories are vital infrastructure for research and education. When conventional laboratories are not available and/or accessible due to different causes, for example, unaffordable purchases and maintenance cost, safety considerations, and crises such as the coronavirus disease 2019 (COVID-19) pandemic, online laboratories can offer alternatives1,2,3. Like conventional laboratories, significant progress such as interactive features4 and customizable experiments5 have been achieved in the online laboratories. Before and during the COVID-19 pandemic, online laboratories are providing experimental services to users throughout the world6,7.
Among online laboratories, remote laboratories can provide users with an experience similar to hands-on experiments with the support of physical test rigs and cameras8. With the advancement of the Internet, communication, computer graphics, and rendering technologies, virtual laboratories also provide alternatives to conventional laboratories1. The effectiveness of remote and virtual laboratories to support research and education has been validated in related literature1,9,10.
Providing visualized experiments is crucial for online laboratories, and visualization in online experimentation has become a trend. Different visualization techniques are achieved in online laboratories, for example, curve charts, two-dimensional (2-D) test rigs, and three-dimensional (3-D) test rigs11. In control education, numerous theories, concepts, and formulas are obscure to comprehend; thus, visualized experiments are vital to enhancing teaching, student learning, and research. The involved visualizing can be concluded into the following three categories: (1) Visualizing theories, concepts, and formulas with web-based algorithm design and implementation, with which simulation and experimentation can be conducted; (2) Visualizing the experimental process with 3-D virtual test rigs; (3) Visualizing control and monitoring using widgets such as a chart and a camera widget.

<table><tbody><tr><td>Fan speed control system</td><td>/</td><td>/</td><td>Made by our team</td></tr><tr><td>https://www.powersim.whu.edu.cn/react</td><td></td><td></td><td>Made by our team</td></tr></tbody></table>

interactive and visualized online experimentation system for engineering education and research

Experimentation is crucial in engineering education. This work explores visualized experiments in online laboratories for teaching and learning and also research. Interactive and visualizing features, including theory-guided algorithm implementation, web-based algorithm design, customizable monitoring interface, and three-dimensional (3-D) virtual test rigs are discussed. To illustrate the features and functionalities of the proposed laboratories, three examples, including the first-order system exploration using a circuit-based system with electrical elements, web-based control algorithm design for virtual and remote experimentation, are provided. Using user-designed control algorithms, not only can simulations be conducted, but real-time experiments can also be conducted once the designed control algorithms have been compiled into executable control algorithms. The proposed online laboratory also provides a customizable monitoring interface, with which users can customize their user interface using provided widgets such as the textbox, chart, 3-D, and camera widget. Teachers can use the system for online demonstration in the classroom, students for after-class experimentation, and researchers to verify control strategies.

The proposed laboratory system has been used in several different disciples at Wuhan University, such as the Automation, Power and Energy Engineering, Mechanical Engineering, and other universities, such as Henan Agricultural University6.
Teachers/students/researchers are provided with great flexibility to explore the system using different virtual and/or physical test rigs, define their control algorithms, and customize their monitoring interface; thus, users at different levels can benefit from the proposed system. The visualized experiments provided by the proposed approach can potentially enhance understanding theories, concepts, and formulas.
The proposed system can be used for different types of algorithm design (Figure 1 and Figure 3 are two examples) and multi-purposes such as teaching, learning, and research (three protocols can be regarded as three application examples). The first-order system is an example that the system can be applied to typical system analysis using circuit-based diagrams.
Figure 3 and Figure 5 demonstrate that the proposed online laboratory can design simple and complex control algorithms using the designed blocks, verified through simulation and real-time experimentation with 3-D virtual and physical test rigs, respectively, as shown in Figure 4 and Figure 6.
The three examples demonstrate that the proposed interactive and visualized laboratory can achieve the following visualization as aforementioned. (1) Theory, formulas, and schematic diagrams can be visualized through web-based algorithm design and implementation, with which simulation and experimentation can be conducted. (2) With the support of the 3-D virtual test rigs, experimental processes can be visualized in the absence of physical test rigs and cameras deployed at the test rig site. In remote laboratories, the integration of 3-D test rigs can also benefit users, allowing users to view the details of the test rigs from different angles. Combining 3-D virtual test rigs with physical test rigs at the remote side can potentially enhance user experience. (3) Using developed widgets such as a chart, a camera widget, and a textbox, the monitoring, and control during the experimental process can be visualized.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63342/63342fig01.jpg" /> 
Figure 1: Construction of the first-order system with blocks from the ELECTRICAL ELEMENTS library in NCSLab. The user can drag any block from the left-side block library panel and construct a system by linking the selected blocks properly. <a href="https://www.jove.com/files/ftp_upload/63342/63342fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/63342/63342fig02.jpg" /> 
Figure 2: Real-time experiment of the first-order system with the designed control algorithm. The parameters are tunable, and the signals can be monitored with the provided widgets. <a href="https://www.jove.com/files/ftp_upload/63342/63342fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/63342/63342fig03.jpg" /> 
Figure 3: Web-based PID control algorithm design and implementation for the dual tank system. The simulation result is included, which shows that the water level of the second tank can be controlled to the set-point value of 10 cm. <a href="https://www.jove.com/files/ftp_upload/63342/63342fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/63342/63342fig04.jpg" /> 
Figure 4: Real-time experimentation with the dual tank system. After tuning the integral term from 0.1 to 0.01, the set-point is reset from 15 cm to 25 cm. It can be seen that the overshoot has been eliminated. <a href="https://www.jove.com/files/ftp_upload/63342/63342fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/63342/63342fig05.jpg" /> 
Figure 5: IMC control of the fan speed control system. The inverse model of the identified fan model is an improper transfer function (for a proper transfer function, the order of the transfer function numerator must be less than or equal to the order of the denominator), which is constructed with general blocks based on the identified model. To enable a tunable filter, the filter is also built with blocks. The lambda&#160;in the figure represents the reciprocal of the&#160;&#955; in Equation 6 and can be tuned easily. <a href="https://www.jove.com/files/ftp_upload/63342/63342fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/63342/63342fig06.jpg" /> 
Figure 6: Real-time control and fan speed monitoring using the fan speed control remote laboratory combined with a 3-D virtual fan system. The physical fan system is located at Wuhan University and provides remote laboratory services to users worldwide. <a href="https://www.jove.com/files/ftp_upload/63342/63342fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/63342/63342fig07.jpg" /> 
Figure 7: Schematic diagram of the first-order system. The first-order circuit design and implementation in NCSLab are based on this diagram. <a href="https://www.jove.com/files/ftp_upload/63342/63342fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/63342/63342fig08.jpg" /> 
Figure 8: 3-D virtual dual tank system in NCSLab. The purpose of the control is to control the water level in the second tank to the set-point value. <a href="https://www.jove.com/files/ftp_upload/63342/63342fig08large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/63342/63342fig09.jpg" /> 
Figure 9: Schematic of the internal model control architecture. Gm(s) is the model of the real plant G(s), Gm(s)-1 is the inverse model of Gm(s), F(s) and is the filter. The F(s), Gm(s)-1, and Gm(s) constitute the IMC controller. <a href="https://www.jove.com/files/ftp_upload/63342/63342fig09large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Parameter</td>
			<td>Value</td>
		</tr>
		<tr>
			<td>R0</td>
			<td>200 k&#937;</td>
		</tr>
		<tr>
			<td>R1</td>
			<td>200 k&#937;</td>
		</tr>
		<tr>
			<td>C</td>
			<td>1 &#181;F</td>
		</tr>
		<tr>
			<td>R2</td>
			<td>200 k&#937;</td>
		</tr>
		<tr>
			<td>R3</td>
			<td>200 k&#937;</td>
		</tr>
		<tr>
			<td>Input</td>
			<td>1 V</td>
		</tr>
	</tbody>
</table>
Table 1: Parameter configurations for the first-order circuit system. R2 and R3 are used to cancel the phase shift combined with the op-amp.
Supplementary Figure 1: Simulation warning interface when a user fails to ground a circuit. The result will warn the users, which can help them to recheck the designed circuit. <a href="https://www.jove.com/files/ftp_upload/63342/Figure 10.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 2: Compilation warning interface when a user fails to ground a circuit. The result will warn the users, which can help them to recheck the designed circuit. <a href="https://www.jove.com/files/ftp_upload/63342/Figure 11.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 3: Simulation result when a user reverses the polarity of the capacitor. A regular capacitor instead of the variable capacitor has been selected to illustrate this example. No warning message is shown, and the result is similar to Supplementary Figure 4. <a href="https://www.jove.com/files/ftp_upload/63342/Figure 12.pdf" target="_blank">Please click here to download this File.</a>
Supplementary Figure 4: Simulation result when the polarity of the capacitor is correct. A regular capacitor instead of the variable capacitor has been selected to illustrate this example. The simulation result will pop up to help the users to check the circuit. <a href="https://www.jove.com/files/ftp_upload/63342/Figure 13.pdf" target="_blank">Please click here to download this File.</a>

Watch this Scientific Journal Video about Interactive and Visualized Online Experimentation System for Engineering Education and Research at JoVE.com

Interactive and Visualized Online Experimentation System for Engineering Education and Research

This work describes an online experimentation system that provides visualized experiments, including the visualization of theories, concepts, and formulas, visualizing the experimental process with three-dimensional (3-D) virtual test rigs, and visualizing the control and monitoring system using widgets such as charts and cameras.

Experimentation is crucial in engineering education. This work explores visualized experiments in online laboratories for teaching and learning and also ...

interactive-visualized-online-experimentation-system-for-engineering

Universidad Científica del Sur

Research

JoVE Journal

Engineering

2.4K Views.  Wuhan University. This work describes an online experimentation system that provides visualized experiments, including the visualization of theories, concepts, and formulas, visualizing the experimental process with three-dimensional (3-D) virtual test rigs, and visualizing the control and monitoring system using widgets such as charts and cameras.

Video: Interactive and Visualized Online Experimentation System for Engineering Education and Research

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

The increasing development of computing (hardware and software) in the last decades has impacted scientific research in many fields including materials science, biology, chemistry and physics among many others. A new computational system for the accurate and fast simulation and 3D/VR visualization of nanostructures is presented here, using the open-source molecular dynamics (MD) computer program LAMMPS. This alternative computational method uses modern graphics processors, NVIDIA CUDA technology and specialized scientific codes to overcome processing speed barriers common to traditional computing methods. In conjunction with a virtual reality system used to model materials, this enhancement allows the addition of accelerated MD simulation capability. The motivation is to provide a novel research environment which simultaneously allows visualization, simulation, modeling and analysis. The research goal is to investigate the structure and properties of inorganic nanostructures (e.g., silica glass nanosprings) under different conditions using this innovative computational system. The work presented outlines a description of the 3D/VR Visualization System and basic components, an overview of important considerations such as the physical environment, details on the setup and use of the novel system, a general procedure for the accelerated MD enhancement, technical information, and relevant remarks. The impact of this work is the creation of a unique computational system combining nanoscale materials simulation, visualization and interactivity in a virtual environment, which is both a research and teaching instrument at UC Merced.

A new computational system featuring GPU-accelerated molecular dynamics simulation and 3D/VR visualization, analysis and manipulation of nanostructures has been implemented, representing a novel approach to advance materials research and promote innovative investigation and alternative methods to learn about material structures with dimensions invisible to the human eye.

The increasing development of computing (hardware and software) in the last decades has impacted scientific research in many fields including materials ...

VisualEyes: A Modular Software System for Oculomotor Experimentation

Eye movement studies have provided a strong foundation forming an understanding of how the brain acquires visual information in both the normal and dysfunctional brain.1 However, development of a platform to stimulate and store eye movements can require substantial programming, time and costs. Many systems do not offer the flexibility to program numerous stimuli for a variety of experimental needs. However, the VisualEyes System has a flexible architecture, allowing the operator to choose any background and foreground stimulus, program one or two screens for tandem or opposing eye movements and stimulate the left and right eye independently. This system can significantly reduce the programming development time needed to conduct an oculomotor study. The VisualEyes System will be discussed in three parts: 1) the oculomotor recording device to acquire eye movement responses, 2) the VisualEyes software written in LabView, to generate an array of stimuli and store responses as text files and 3) offline data analysis. Eye movements can be recorded by several types of instrumentation such as: a limbus tracking system, a sclera search coil, or a video image system. Typical eye movement stimuli such as saccadic steps, vergent ramps and vergent steps with the corresponding responses will be shown. In this video report, we demonstrate the flexibility of a system to create numerous visual stimuli and record eye movements that can be utilized by basic scientists and clinicians to study healthy as well as clinical populations.

Neural control and cognitive processes can be studied through eye movements. The VisualEyes software allows an operator to program stimuli on two computer screens independently using a simple, custom scripting language. The system can stimulate tandem eye movements (saccades and smooth pursuit) or opposing eye movements (vergence) or any combination.

Eye movement studies have provided a strong foundation forming an understanding of how the brain acquires visual information in both the normal and ...

Neuroscience

Research and Development of High-performance Explosives

Developmental testing of high explosives for military applications involves small-scale formulation, safety testing, and finally detonation performance tests to verify theoretical calculations. For newly developed formulations, the process begins with small-scale mixes, thermal testing, and impact and friction sensitivity. Only then do subsequent larger scale formulations proceed to detonation testing, which will be covered in this paper. Recent advances in characterization techniques have led to unparalleled precision in the characterization of early-time evolution of detonations. The new technique of Photonic Doppler Velocimetry (PDV) for the measurement of detonation pressure will be shared and compared with traditional fiber-optic detonation velocity and plate-dent calculation of detonation pressure. In particular, the role of aluminum in explosive formulations will be discussed. Recent developments led to the development of explosive formulations that result in reaction of aluminum very early in the detonation product expansion. This enhanced reaction leads to changes in the detonation velocity and pressure due to reaction of the aluminum with oxygen in the expanding gas products.

Developmental testing of high explosives for military applications involves small-scale formulation, safety testing, and finally detonation performance tests to verify theoretical calculations. This paper will share typical development tests associated with the measurement of detonation velocity and detonation pressure.

Developmental testing of high explosives for military applications involves small-scale formulation, safety testing, and finally detonation performance ...

Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation

Advective exchange between the pore space of sediments and the overlying water column, called hyporheic exchange in fluvial environments, drives solute transport in rivers and many important biogeochemical processes. To improve understanding of these processes through visual demonstration, we created a hyporheic flow simulation in the multi-agent computer modeling platform NetLogo. The simulation shows virtual tracer flowing through a streambed covered with two-dimensional bedforms. Sediment, flow, and bedform characteristics are used as input variables for the model. We illustrate how these simulations match experimental observations from laboratory flume experiments based on measured input parameters. Dye is injected into the flume sediments to visualize the porewater flow. For comparison virtual tracer particles are placed at the same locations in the simulation. This coupled simulation and lab experiment has been used successfully in undergraduate and graduate laboratories to directly visualize river-porewater interactions and show how physically-based flow simulations can reproduce environmental phenomena. Students took photographs of the bed through the transparent flume walls and compared them to shapes of the dye at the same times in the simulation. This resulted in very similar trends, which allowed the students to better understand both the flow patterns and the mathematical model. The simulations also allow the user to quickly visualize the impact of each input parameter by running multiple simulations. This process can also be used in research applications to illustrate basic processes, relate interfacial fluxes and porewater transport, and support quantitative process-based modeling.

This manuscript describes how to create regular bedforms in a flume, visualize flow through the bedforms, and use computer simulations to simulate the hyporheic flow. The computer simulations compare well with the experimental observations. This coupled simulation and experiment is well-suited for both research and educational purposes.

Advective exchange between the pore space of sediments and the overlying water column, called hyporheic exchange in fluvial environments, drives solute ...

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Investigating the interactions among multiple participants is a challenge for researchers from various disciplines, including the decision sciences and spatial cognition. With a local area network and dedicated software platform, experimenters can efficiently monitor the behavior of the participants that are simultaneously immersed in a desktop virtual environment and digitalize the collected data. These capabilities allow for experimental designs in spatial cognition and navigation research that would be difficult (if not impossible) to conduct in the real world. Possible experimental variations include stress during an evacuation, cooperative and competitive search tasks, and other contextual factors that may influence emergent crowd behavior. However, such a laboratory requires maintenance and strict protocols for data collection in a controlled setting. While the external validity of laboratory studies with human participants is sometimes questioned, a number of recent papers suggest that the correspondence between real and virtual environments may be sufficient for studying social behavior in terms of trajectories, hesitations, and spatial decisions. In this article, we describe a method for conducting experiments on decision-making and navigation with up to 36 participants in a networked desktop virtual reality setup (i.e., the Decision Science Laboratory or DeSciL). This experiment protocol can be adapted and applied by other researchers in order to set up a networked desktop virtual reality laboratory.

This paper describes a method for conducting multi-user experiments on decision-making and navigation using a networked computer laboratory.

Investigating the interactions among multiple participants is a challenge for researchers from various disciplines, including the decision sciences and ...

Behavior

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences

Over the past ten years, research into students&#39; emotions in educational environments has increased. Although researchers have called for more studies that rely on objective measures of emotional experience, limitations on utilizing multi-modal data sources exist. Studies of emotion and emotional regulation in classrooms traditionally rely on survey instruments, experience-sampling, artifacts, interviews, or observational procedures. These methods, while valuable, are mainly&#160;dependent on participant or observer subjectivity and is limited in its authentic measurement of students&#39; real-time performance to a classroom activity or task. The latter, in particular, poses a stumbling block to many scholars seeking to objectively measure emotions and other related measures in the classroom, in real-time.
The purpose of this work is to present a protocol to experimentally study students&#39; real-time responses to exam experiences during an authentic assessment situation. For this, a team of educational psychologists, engineers, and engineering education researchers designed an experimental protocol that retained the limits required for accurate physiological sensor measurement, best-practices of salivary collection, and an authentic testing environment. In particular, existing studies that rely on physiological sensors are conducted in experimental environments that are disconnected from educational settings (e.g., Trier Stress Test), detached in time (e.g., before or after a task), or introduce analysis error (e.g., use of sensors in environments where students are likely to move). This limits our understanding of students&#39; real-time responses to classroom activities and tasks. Furthermore, recent research has called for more considerations to be covered around issues of recruitment, replicability, validity, setups, data cleaning, preliminary analysis, and particular&#160;circumstances (e.g., adding a variable in the experimental design) in academic emotions research that relies on multi-modal approaches.

An experimental design was developed to investigate the real-time influences of an examination experience to assess the emotional realities students experience in higher education settings and tasks. This design is the result of a cross-disciplinary (e.g., educational psychology, biology, physiology, engineering) and multi-modal (e.g., salivary markers, surveys, electrodermal sensor) approach.

Over the past ten years, research into students&#39; emotions in educational environments has increased. Although researchers have called for more studies ...

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

This work presents a set of comprehensive virtual experiments to detect material deformation and failure. The most commonly used pieces of equipment in mechanics and material disciplines, such as a metallographic cutting machine and a high-temperature universal creep testing machine, are integrated into a web-based system to provide different experimental services to users in an immersive and interactive learning environment. The protocol in this work is divided into five subsections, namely, the preparation of the materials, molding the specimen, specimen characterization, specimen loading, nanoindenter installation, and SEM in situ experiments, and this protocol aims to provide an opportunity for users regarding the recognition of different equipment and the corresponding operations, as well as the enhancement of laboratory awareness, etc., using a virtual simulation approach. To provide clear guidance for the experiment, the system highlights the equipment/specimen to be used in the next step and marks the pathway that leads to the equipment with a conspicuous arrow. To mimic the hands-on experiment as closely as possible, we designed and developed a three-dimensional laboratory room, equipment, operations, and experimental procedures. Moreover, the virtual system also considers interactive exercises and registration before using chemicals during the experiment. Incorrect operations are also allowed, resulting in a warning message informing the user. The system can provide interactive and visualized experiments to users at different levels.

This work presents a three-dimensional virtual simulation experiment for material deformation and failure that provides visualized experimental processes. Through a set of experiments, users can become familiar with the equipment and learn the operations in an immersive and interactive learning environment.

This work presents a set of comprehensive virtual experiments to detect material deformation and failure. The most commonly used pieces of equipment in ...

Mixed Reality for Education (MRE) Implementation and Results in Online Classes for Engineering

The COVID-19 pandemic has changed many industries, empowering some sectors and causing many others to disappear. The education sector is not exempt from major changes; in some countries or cities, classes were taught 100% online for at least 1 year. However, some university careers need laboratory practices to complement learning, especially in engineering areas, and having only theoretical lessons online could affect their knowledge. For this reason, in this work, a mixed reality system called mixed reality for education (MRE) was developed to help students develop laboratory practices to complement online classes. An experiment was carried out with 30 students; 10 students did not use MRE, 10 used MRE, and 10 more used MRE with teacher feedback. With this, one can see the advantages of mixed reality in the education sector. The results show that using MRE helps to improve knowledge in engineering subjects; the students obtained qualifications with grades 10% to 20% better than those who did not use it. Above all, the results show the importance of feedback when using virtual reality systems.

Mixed Reality for Education MRE Implementation and Results in Online Classes for Engineering

In this work, a mixed reality system called MRE was developed to help students develop laboratory practices complementing online classes. An experiment was carried out with 30 students; 10 students did not use MRE, 10 used MRE, and 10 more used MRE with teacher feedback.

The COVID-19 pandemic has changed many industries, empowering some sectors and causing many others to disappear. The education sector is not exempt from ...

WebVR-Based Virtual Reality Laboratory System for Immersive Online Experiments

Online Virtual Reality Networked Control Laboratory Applied in Control Engineering Education

Online laboratories play an important role in engineering education. This work discusses a WebVR-based virtual laboratory system. The user enters the simulated laboratory environment through a virtual reality (VR) device and interacts with the experimental equipment, similar to hands-on experiments in a physical laboratory. In addition, the proposed system allows users to design their own control algorithms and observe the effects of different control parameters to enhance their understanding of the experiment. To illustrate the features of the proposed virtual laboratory, an example is provided in this paper, which is an experiment on a double inverted pendulum system. The experimental results show that the proposed system allows users to conduct experiments in an immersive and interactive manner and provides users with a complete experimental process from principal design to experimental operation. A solution is also provided to change any virtual laboratory into a WebVR-based virtual laboratory for education and training.

Author Spotlight: Enhancing Engineering Education via WebVR-Based Online Laboratories

This study describes a WebVR-based online virtual reality (VR) laboratory system that provides users with immersive and interactive experimentation capabilities supported by VR devices. The proposed system not only helps to enhance the realism of user participation in online experiments but is also applicable to a wide range of online laboratory frameworks.

Online laboratories play an important role in engineering education. This work discusses a WebVR-based virtual laboratory system. The user enters the ...

From Theory to Design: The Role of Creativity in Designing Experiments

Source: Laboratories of <a href="https://www.jove.com/author/Gary_Lewandowski">Gary Lewandowski</a>, Dave Strohmetz, and Natalie Ciarocco&#8212;Monmouth University

Research studies come into being when a researcher speculates about human thought, emotions, or behavior, and has a theory that offers a potential explanation. Often the researcher&#8217;s theory is firmly situated in everyday common experiences that may not naturally lend themselves to direct empirical study. 
 
For example, researchers speculated that perception of a person on Facebook is influenced by the appearances and comments of the person&#8217;s Facebook friends.1 It is difficult to test this theory using real-life Facebook profiles. Instead, researchers must use their creativity to design a study&#8212;in this case, using fake profiles that look highly realistic&#8212;to test their theory.&#160;

This video demonstrates how researchers test a central tenet of a popular social psychology theory. Specifically, this video shows a test of whether engaging in a self-expanding activity leads a person to feel a greater sense of self-efficacy.2

Psychological studies often use higher sample sizes than studies in other sciences. A large number of participants helps to ensure that the population under study is better represented, i.e., the margin of error accompanied by studying human behavior is sufficiently accounted for. In this video, we demonstrate this experiment using just 2 participants, one for each condition. However, as represented in the results, we used a total of 100 (50 for each condition) participants to reach the experiment&#8217;s conclusions.