Simulation time required by numerical methods
\\n\\n
These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\\n\\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\\n\\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\\n\\n\\n\\n\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\n\nInitially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\nThese books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\n\n\n\n\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"3828",leadTitle:null,fullTitle:"Application of Nanotechnology in Drug Delivery",title:"Application of Nanotechnology in Drug Delivery",subtitle:null,reviewType:"peer-reviewed",abstract:"This book collects reviews and original articles from eminent experts working in the interdisciplinary arena of nanotechnology use in drug delivery. From their direct and recent experience, the readers can achieve a wide vision on the new and ongoing potentialities of nanotechnology application of drug delivery. Since the advent of analytical techniques and capabilities to measure particle sizes in nanometer ranges, there has been tremendous interest in the use of nanoparticles for more efficient methods of drug delivery. 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\r\n\tThe continuous growth in the development of electronic devices, cellular wireless communication systems, and medical electronic devices over the last twenty years resulted in most of the world’s population owning smartphones, smartwatches, tablets, and other similar devices. As a result, the number of unwanted electronic devices is growing at a rapid rate. With this huge number of devices being produced and discarded, a new environmental disaster strikes our planet. Electronic waste and discarded old electronics are filling up landfills at an alarming rate. These electric devices contain hazardous and toxic materials that endanger the environment and the health of local communities, increasing environmental pollution. Furthermore, the consumption of electrical energy is in rapid growth. Traditional energy sources such as fuel and coal significantly increase environmental pollution. Green technologies, as well as recycling electronic waste, old batteries, plastic waste, and bottles, are employed to decrease environmental pollution. Renewable energy is also a major factor in decreasing environmental pollution. This book's main objective is to present innovation in green electronic technologies and devices, enabling engineers, students, and scientists from all areas to follow and understand the topics presented in the book.
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You could say that the transmission of electricity is one of the most important contributions that engineering has offered to the modern civilization.
The distribution of current potential differences and the transfer of energy along a transmission line can be analyzed by various methods, and it is expected that all lead to the same result. In engineering problems, in general, it can not indiscriminately apply a single formula for solving a specific problem, without the full knowledge of the limitations and simplifications accepted in its derivation. It is worth mentioning that this circumstance would lead to its misuse. The so-called mathematical solutions of physical phenomena typically require simplifications and idealizations.
Therefore, there are several models that represent the transmission lines and can be classified as to the nature of their parameters in the model parameters constant and variable parameters the models with frequency.
The parameters in the models in terms of frequency are easy to use, but can not adequately represent the line in the entire range of frequencies at which these phenomena are transient in nature. In most cases, these designs increase the amplitude of the high order harmonics, distorting the waveform peaks and producing exaggerated errors.
For adequate representation of the transmission line should be considered that the longitudinal line parameters are strongly frequency dependent, including the variable parameters in the models with frequency, the sum of the effect of soil, developed by Carson and Pollaczek, with skin effect, whose behavior as a function of frequency can be calculated using formulas derived from the Bessel equations.
Models with variable parameters in terms of frequency are considered more accurate when compared to models that consider the constant parameters. The variation depends upon the frequency. This variation may be represented by series and parallel combination of resistive and inductive elements pure.
As transmission lines are inserted in an electrical system that has many nonlinear elements and, thus, it is difficult to represent them in the frequency domain, there is a preference for line models that are developed directly in the time domain.
Another factor, that makes the model lines developed directly in the time domain are most commonly used, is that the majority of programs that perform simulations electromagnetic transients in electrical systems require that the system components are represented in time domain.
Probably, the first model to represent the transmission line directly in the time domain is designed for H. W. Dommel, which was based on the method of the characteristics or Bergeron’s method. The model has combined the method of characteristics with the trapezoidal method numerical integration, resulting in an algorithm able to simulate transient electromagnetic networks whose parameters are distributed or discrete. This algorithm has undergone successive developments and is now known as the Electromagnetic Transients Program, or EMTP simply.
In situations where one wants to simulate the propagation of electromagnetic waves resulting from operations carried out maneuvers and switching the transmission lines, it can be represented the same as a cascade of π circuits.
In this model, each segment consists of a combination of series and parallel circuits composed by resistors and inductors. This results in an equivalent resistance and an inductance that depend on the frequency. It is considered in hese equivalent elements the ground and skin effects.
Due to the fact that EMTP-type programs are not easy to use, several authors suggest describing the currents and voltages in the cascade of π circuits by means of state variables. The state equations are then transformed into differential equations and can be solved using any computer language or mathematical software.
The representation of the line by means of state variables can be used in teaching basic concepts of wave propagation in transmission lines, the analysis of the distribution of currents and voltages along the line, and the simulation of electromagnetic transients in transmission lines with non-linear elements.
Although the technique of state variables is widely used in the representation of transmission lines, it can be seen in recent publications, that it was only used to represent the parameters of which longitudinal rows can be considered constant and independent of frequency.
However, it is recognized today that the use of constant parameters to represent the line in the whole frequency range, present in the signals during the occurrence of disturbances in it, may result in responses in which the high frequency harmonic components have larger amplitudes than the real ones.
Thus, in this chapter, it is intended, using the MatLabTM, to enter the effect of frequency on a line represented by π circuits connected in cascade and obtain the currents and voltages on the line from the use of the technique of state variables. The method is applied in a single-phase line, which considers the presence of soil and peel effect.
This line is approximated by a cascade of π circuits which will then be represented by state equations. The state equations, which are the voltages and currents along the line, will then be simulated in MatLabTM. The cascade will also be implemented in software such as EMTP, used for simulations of electromagnetic transients in power systems. Then the results obtained with MatlabTM and EMTP are compared, considering the single-phase line.
Besides this mentioned modeling, for MatLabTM software users, the main contribution of this chapter is to demonstrate the application of this program for analyzing and simulating transient phenomena in power systems. It is important for undergraduate students for understanding the basic concepts of wave propagation and transmission lines. On the other hand, specific programs, like EMTP type programs, use a specific numeric method for solving the linear systems through numeric integration. With MatLabTM basic tools, the graduate students can apply different numeric methods for solving the same problem, comparing the results and analyzing the accuracy, precision and computational time related to each method.
It is a brief equation that relates the numerical method for lumped parameters used by the ATP. Is an arbitrary differential equation given by:
The solution between the instants t0 and t is obtained by the following:
or finally:
The numerical solution of the equation is obtained at discrete instants of time, given:
The solution of equation (2.4) consists of numerical integration of a discrete function y(t) which must be performed in discrete steps size Δt, which solution is the area under the curve, limited by the instants t and t-Δt as shown in Figure 1.
(a) function y(t) slight to be integrated; (b) trapezoidal rule integration.
Solving equation (2.5) by the trapezoidal rule integration, which allows a linear variation between y (t-Δt) and y (t) of the integrated, as shown in figure 1 (b), as:
or:
in other words:
where:
It may be noted that the term historical hTR(t-Δ t) depends on x (t) and y (t) after t seconds, t, is already known during the solution.
Discussion will now represent a mathematical model for a transmission line using an electrical circuit. With this model, you can make a study of the behavior of a transmission line for energizing and switching transient simulations. A transmission line, whose parameters can be considered independent of frequency, can be represented in an approximate manner and following a series of restrictions, as a cascade of π circuits.
Each segment of π circuit consists of one resistor and one series inductance in series. Completing the circuit, there are components in parallel: capacitance and conductance. It is shown in Figure 2.
A π circuit.
It’s represented a transmission line through this model, connects to n π circuits in cascade. So Figure 3 shows a single-phase transmission line length d represented by n π circuits connected in cascade.
Line represented by a cascade of π circuits.
In Figure 3, the parameters R and L are the resistance and inductance of the longitudinal line, respectively. The parameters G and C are the capacitance and conductance of transverse dispersion, respectively. These parameters are written as:
In the equations (3.1) to (3.4), R \'and L\' are the resistance and inductance of the longitudinal row per unit length, respectively while the terms G \'and C\' are the capacitance and conductance per unit cross-sectional line in length.
Using this representation of the line, a state model is formulated for the energy system that uses the voltages on the capacitors and the currents through the inductors as state variables. The system that describes the state equations is transformed into a set of differential equations whose solution is given by the use of trapezoidal integration. The state variables are found by solving the set of equations.
Although the technique of state variables is widely used in the representation of transmission lines, it is applied only to depictions of longitudinal lines whose parameters can be considered constant and independent of frequency.
However, it is recognized today that the use of constant parameters to represent the line in the whole frequency range, present in the signals during the occurrence of disturbances in it, may result in responses in which the high frequency harmonic components have larger amplitudes than are actually.
The representation of transmission lines through cascades of π circuits, taking into account the effect of frequency, is usually implemented in EMTP-type programs.
Another drawback of the type EMTP programs is that they limit the amount of π circuit that can be used to represent the line. Thus, depending on the length of the line to be depicted, the quality of results obtained from simulations may be compromised.
To circumvent the difficulties mentioned, it is suggested to describe the cascade of π circuits by means of state equations. However, some authors disregarded the effect of frequency on the parameters of the longitudinal line.
Circuit that represents the longitudinal parameters of the line.
The models proposed by would become more complete if the effect of frequency on the longitudinal parameters of the line was inserted in them.
So, the parameters of a transmission line can be synthesized by means of a circuit of the type shown in Figure 4.
It’s used a cascade of π circuits to represent a transmission line taking into account the effect of frequency on the longitudinal parameters. In this case, every π circuit will be shown in Figure 5.
Cascade of π circuits considering the effect of frequency.
In Figure 5, the RL parallel associations are as many as necessary to represent the variation of parameters in each decade of frequency that will be considered. First, arrays are displayed in a state for a line represented by a single π circuit, whereas the effect of frequency is synthesized by n RL associations. Then, the results will be extended to a line represented by a cascade of n π circuit, considering n RL associations to synthesize the effect of frequency.
Before being certain state equations for a line represented by a cascade of n π circuits, it will be shown in detail the development of equations of state considering only one π circuit.
Then, the development done for a single π circuit element can be extended to a generic cascade with any quantity of these circuits.
Considering, as shown in the Figure 5, a transmission line represented by a single π circuit, the effect of frequency on the longitudinal parameters is represented by n RL associations.
In line shown in Figure 5, the voltages at terminals A and B are u(t) and vk(t), respectively. It is also considering that the currents ik0, ik1,..., ikm are circulating through the inductors L0, L1, L2,..., Lm, respectively. These currents are dependent time functions and the notations do not include the time dependence for more simplicity. This simplification is also applied to the vk(t) state variable. From the currents and voltages in the circuit of Figure 5 it can be determined:
The equations (4.1) to (4.5), describing the circuit shown in figure 4.2, can be written as:
For one circuit, the A matrix is substituted by:
In the equations (4.8) and (4.9), BT e xkT correspond to transposed B and xk, respectively.
The obtained results show that the vesctor xk have (m + 2) elements and the matrix A is a (m + 2) order square matrix.
Based on the equations and the results for one π circuit, it can be extended the analysis to a cascade of π circuits. Thus, the matrix A will have an order of n(m +2) and the vector x has dimension n(m +2). The A matrix can be written as:
The elements x1, x2, …, xn are describe by equation (4.9). In equation (4.11), A is a tridiagonal matrix which elements are square matrices of order (m +2). In this case, a generic element AKK at main diagonal of the matrix A is written as:
The A π matrix is defined in equation (4.7).
An element of any upper subdiagonal in equation (4.11) is a square matrix of order (m +2) which the only one nonzero element is located in the first column of last row and has the value
The structure is:
The subdiagonal elements in the equation (4.11) are square matrices of order (m +2). These arrays have a single nonzero element which is in the last column of first row. It is a value of
Considering a cascade of π circuits, the vector B has the dimension of n(m +2) and if it is connected a u(t) source at the beginning of the line, the vector B has a single nonzero element, which is the first array element and it has the value
The state equation, that describes a line representation by a cascade of π circuits cant be solved by numerical methods, like Euler and Heun methods. Other numeric methods are described in the next item
Besides the trapezoidal integration, there are also other numeric methods that can be used for solving state equations related to the modeling of transient phenomena in transmission lines. Among them, it may be mentioned, for example, the Simpson’s and the Runge-Kutta’s method. The following items will describe these methods. In this case, the MatLabTM is important because it facilitates the comparisons among the mentioned methods. With this software, undergraduate students can analyze the application of different numeric methods for solving an engineering problem, besides the analysis about wave propagation and the transmission line modeling. Graduated students can analyze what it is the best option for specific transmission line characteristics and develop the numeric method related to the simulation of transient phenomena in power systems.
Simpson’s rule is based on the assumption that, given short intervals of time the derivative of the function to be integrated, the function (y\') can be approximated by a second degree function as shown in Figure 6.
From Figure 1, it is obtained:
From (5.1) and (4.6), it is obtained:
Equation (5.2) is applied Simpson\'s rule for solving the state equation of state of the type shown in (5.1). In this case, the matrices
It is defined the following terms:
Approximation of the derivative of the function to be integrated (solid curve) by a function of the second degree (dashed curve).
Runge-Kutta’s rule is defined by the following:
The terms in the last equation are described by:
The MatlabTM software is easily applied for the development of numeric routines. Using this characteristic, it is possible to compare different numerical methods. Figure 7 shows the results for the three methods investigated for the simulation of electromagnetic transients in a single-phase transmission line.
Comparisons among the three numerical methods.
In the last figure, it is shown the result obtained with the application of a step voltage source on the initial transmission line. This is a 20 kV step voltage source. The transmission line is modeled as a mono-phase circuit and the linear system is solved using three numeric methods: trapezoidal rule, Simpson’s rule and Range-Kutta’s one.
Based on the results shown in Figure 7, the three numeric methods lead to similar results considering the method accuracy. Because of these results, it is necessary to analyze the other characteristics. An important characteristic for the application of the numeric methods for transient analysis in transmission lines is the simulation time. For example, this is important for analysis in very short simulation times. The next table shows the simulation time comparisons obtained with the MatLabTM software.
Step of calculating (µs) | Computational effort (simulation time) | ||
Heun | Simpson | Runge-Kutta | |
0,1 | t1 | 22,52 t1 | 0,63 t1 |
0,5 | t2 | 8,94 t2 | 0,23 t2 |
1,0 | t3 | 8,40 t3 | 0,26 t3 |
Simulation time required by numerical methods
Table 1 shows the time relationship between the applied numerical methods. It is possible to carry out these comparisons because the MatlabTM provides a simple way to replace the codes related to the numeric routine without changing the structure of the main code, maintaining the same computational flowchart. Using this characteristic, it is possible to determine the simulation time of each numeric method, because the computational time for introducing the data and other characteristics of the simulated transmission line is equal for all compared numeric methods. Because of this, the MatLabTM is an adequate tool for developing new models and numeric routines used for analysis and simulations of transient phenomena in transmission lines.
In this section, it is presented the implementation of a single-phase transmission line through a cascade of π circuits, considering the effect of frequency on their longitudinal parameters and using the concept of state variables. Then, the results obtained are compared with results obtained with EMTP.
The model that represents the single-phase line was implemented in a microcomputer using the software MatLabTM.
Data from single-phase transmission line are read in the first part of the program, then the parameters are calculated from the transmission line considering the influence of frequency.
After observing the behavior of single-phase line parameters as a function of frequency, it is necessary to represent this influence on the transmission line model proposed in item 4. This was done using the method called vector fitting and the longitudinal single phase line parameters are fitted by means of rational functions.
With these parameters synthesized and distributed in the proposed model of a single-phase line, it is possible to calculate the voltages and currents at the terminals of this line or at any point of the line.
The model represented by a cascade π circuits can be represented by a linear system that is represented by state variables. For the solution of the system represented by
Figure 8 is shown a block diagram of the algorithm of the program developed for single-phase line.
Block diagram of the routine developed for a single-phase.
It’s possible to bring the longitudinal parameters of single-phase line by means of rational functions. Using the vector fitting method and allowing the fitting the frequency dependence of these parameters, this effect is entered in the discrete parameter model.
The equation that summarizes the parameters of longitudinal single-phase line is given by:
The values of R and L in the equation (6.1) found by the method vector fitting are shown in Table 2.
From the values of Table 1, it can view a summary of the parameters of longitudinal line as follows: replacing the values of Table 1 in the expression (6.1) and attribute values are included in the frequency range 101 to 106 for it is possible to calculate the longitudinal impedance synthesized.
In the equivalent circuit, the values were considered in the frequency range from 101 to 106, because transients that occur in the transmission line are within this frequency range. So the four blocks RL in parallel, shown in Figure 9, are representing the influence of frequency on longitudinal parameters of single-phase transmission line.
Circuit that represents the longitudinal parameters of the line.
Resistors (Ω/km) | Inductors (mH/km) | |||
0,026 | 2,209 | |||
1,470 | 0,74 | |||
2,354 | 0,12 | |||
20,149 | 0,10 | |||
111,111 | 0,05 |
Values of elements R e L for a single-phase.
The corona discharge mechanism is an electrostatic phenomenon due to ionization in an insulating material, usually a gas, subject to electric field intensities above a critical level.
Electrical discharges in gases are usually triggered by an electric field that accelerates free electrons therein. When these electrons acquire enough energy from the electric field, they can produce new electrons from the collision with other atoms. It is the process of impact ionization. During its acceleration in the electric field, each free electron collides with atoms of oxygen, nitrogen and other present gases, missing, that collision, part of its kinetic energy. Occasionally, it can achieve an electron atom with sufficient force so as to excite it. Under these conditions, the atom is achieved to a higher energy state. The orbital state of one or more electrons and the electron moves colliding with the atom loses some of its energy to create this state. Subsequently, the atom can hit revert to its initial state, releasing the excess energy as heat, light, electromagnetic radiation and acoustic energy. An electron can also collide with a positive ion, converting it into neutral atom. This process, called recombination, also releases excess energy.
After the pioneering work of Peek (1915), several measurements have made on lines and experimental laboratories have examined the nature of the corona and its influence on wave propagation in transmission lines. These works have had fundamental importance, contributing to the understanding of the basic mechanism of the corona.
In 1954, Wagner et al. (1954) and Wagner and Lloyd et al. (1955) published two articles that would be a reference for future work on corona. Voltage experimental measurements were made of in the laboratory of a conductor under corona (project called Tidd 500 kV).
Through these experimental results, it has developed empirical formulas and procedures for considering the effects of attenuation and distortion in the spread of outbreaks. These formulas and procedures are based on the voltage gradient, and voltage curves are obtained from attenuation measurements and the power dissipation due to the corona effect. The usefulness of these methods is limited however, because it requires different approaches and uses abacuses.
The corona model can be divided into three classes: analog models, mathematical models and physical models. The electrical circuit analog models are designed to reproduce the geometric increase in the capacitance of the conductor to the voltage reaches critical ionization.
Like the analog models, mathematical models roughly reproduce the characteristics of drivers under the corona, but by means of mathematical equations. Several authors have empirical formulations for the variation of capacitance of the line based on functions and constants derived from measurements. Most models show a linear relationship between capacitance and dynamic tension.
Due to the complexity in describing mathematically the physical phenomena involved and the insufficient amount of data propagation in corona, it is not available generic models of this nature yet.
The equations describing the corona effect is not easily implemented in the differential equations of the transmission line in order to obtain a solution formulation easyly. Thus, to obtain responses directly in the time domain, numerical models are used such as the finite difference method and the method of the characteristics. This last category of models has been developed to be implemented in EMTP-type programs. Some of these models use non-linear resistors and capacitors that are dependent on the voltage applied on them. However, most existing models of corona present satisfactory results only for a specific situation.
The mechanism of the corona effect can also be represented by the model of Gary, using a capacitance and a non-linear conductance to represent the accumulation and the pressure drops in the line. The capacitance and conductance mentioned above are variables with the applied voltage on them and are called corona capacitance (Cc) and corona conductance (Gc). Cc and Gc elements are obtained by known analytical function, and, therefore, this representation for the corona effect is called analytical model of the corona effect. This model for the corona effect can be inserted in lines represented by a cascade of circuits, where currents and voltages along line is described by state variables.
If the capacitance is represented by Gary’s corona model, it is defined as:
In equation (7.1), CC is the corona capacitance, C is the geometric capacitance of the line segment represented by a π circuit, v is the voltage being applied to the line capacitance, CV is the minimum voltage required to the corona effect accurrance and η is a coefficient defined as:
where: r the radius of the conductor in centimeters.
Thus, given the presence of the corona effect and the effect of frequency, a differential element row can be represented as shown in Figure 10.
A differential element of line considering the corona effects
The corona conductance to Gary’s model is defined as:
Gary’s model considers that the corona effect is manifested only if the voltage VC is greater than v and the rate of variation over time v is positive. Thus, if the corona effect is manifested at a given point P of the line, the voltage Vp at this point must satisfy the following conditions:
Thus, for the corona effect is present at a generic point of the line represented by a cascade of circuits, as shown in figure 10, it is necessary that the voltage at this point satisfying the two conditions shown in equation (7.4). If a condition is not met, this point will not have increased the capacitance and conductance representing corona. Therefore, the A matrix shown in equation (4.6) should be changed for each iteration as a function of cross-line voltage.
Checking the effectiveness of the developed model, it is simulated the energizing of a transmission line shown in figure 11, considering frequency independent line parameters and frequency dependent ones.
Single phase line representation with opened terminal.
In Figure 11, S is a switch that be closed at time t = 0, energizing the line through a voltage source u(t). In the current procedure, the terminal B is open and the other terminal is powered by a constant voltage source. For frequency dependent line parameters, it is considered that the longitudinal parameters of the line per unit length can be perfectly summed up by a circuit consisting of four RL parallel blocks connected in series. The structure is completed using a RL series block as shown in Figure 9.
The values of R and L used to synthesize the effect of frequency on the longitudinal parameters of the line were obtained using the method proposed by [10] and are shown in Table 1. The parameters of the unit transverse line shown in figure 3 are G′=0,556 μS/km e C′ =11,11nF/km.
In all simulations, it is used the following values: the transmission line has 10 kilometers. It is represented through 200 π circuits. The time step used in the simulations is 50 ns and the simulation period is 600 μs. The voltage in the initial of the line is 1 kV. It can also be considered as 1 pu.
Since the values of R and L elements of the cascade of π circuits that describe the line are known, it can be obtained the state equations that describe the behavior of currents and voltages along the line. The simulations using the model proposed in this chapter were performed in MatLabTM program, using the trapezoidal integration method. Considering the frequency independent line parameters, the circuit of Figure 4 is reduced to the R0 and L0 elements. In this case, the values are: R0 = 0.05 Ω/km and L0 = 1 mH/km.
The values of Table 9.1 are written per kilometer for the generic circuit. For the simulation, it used the values represented in the Table 9.2 that are resistance and inductance [] and [H], respectively. In the Figs 12-21, it is used the values of Table 4.
Figures 12-17 show the relationship between the number of RL parallel blocks and the inclusion of the frequency influence. In Figure 12, the resistance values are obtained using only one RL parallel block related to the high frequencies. Because of this, the resistance values for all frequency values are equal. In this case, the value is equal to the R4 value per length unit.
Parameter | 100 circuits | 200 circuits |
R | 5 mΩ | 2.5 mΩ |
L | 100 mH | 50 mH |
G | 556 µS | 278 µS |
C | 1.111 nF | 555.5 nF |
Values of line parameter used in all simulations without frequency.
Resistors(Ω) | Inductors(µH) | ||
R0’ | 0.0013 | L0’ | 110.45 |
R1’ | 0.0735 | L1’ | 37 |
R2’ | 0.1177 | L2’ | 6 |
R3’ | 1.0075 | L3’ | 5 |
R4’ | 5.5556 | L4’ | 2.5 |
Values of line parameter used in simulations with 200 circuits.
From the results of Figures 13 and 14, it is observed that the synthesis of the effect of frequency on the resistance can only be considered when inserted in the cascade of π circuits, at least, two RL parallel blocks, because each block is related to a frequency set point.
So, if more blocks are used, more frequency set points are obtained. It is confirmed through the results shown in Figures 15, 16 and 17 where the inductance values are presented. So, it is concluded that the synthesis of the longitudinal line parameters is improved with the increase of the number of RL parallel blocks.
Synthesis of resistance per unit length using R’4L’4 parallel block.
Synthesis of resistance per unit length using R’1L’1 and R’4L’4 parallel blocks.
Synthesis of resistance per unit length using four RL parallel blocks.
Synthesis of inductance per unit length using only R’4L’4 parallel block.
Synthesis of inductance per unit length using R’1L’1 and R’4L’4 parallel blocks.
Synthesis of inductance per unit length using four RL parallel blocks.
The result of the simulation made for the voltage input signal u(t) can be seen in Figure 18. It is shown the output voltage at the receiving end terminal of the line without the frequency influence. Using the routine without the influence of frequency from the results of Figure. 18, it is observed that there is a period of time related to the time of signal propagation through the line.
Energization of the transmission line without the effect of frequency considering 200 π circuits.
Thus, it represents a time delay between input signal and output signal. After the delay, there are oscillations associated with wave reflections on the transmission line terminals that make up the output voltage shown.
Voltage at the end of the transmission line with the effect of frequency considering 200 π circuits.
Using the routine with frequency influence in longitudinal parameters, it is obtained the results of Figure 20. In this figure, comparing to Figure 19, the voltage signal is attenuated because the inclusion of the frequency influence.
Figures 21 and 22 show the influence of frequency on the current results. Without the frequency influence, the obtained signal current is not attenuated and is highly modified by numeric oscillations (Figure 14). On the other hand, when the routine considers the influence of frequency (Figure 22), it is clear that the current signal could not contain those oscillations shown in Figure 21. So, those oscillations are numeric oscillations and they can be associated to the representation of the longitudinal line parameters which does not consider the frequency influence.
Current at the end of the transmission line without the effect of frequency.
Current at the end of the transmission considering the effect of frequency.
So, for the sequence of this work, it should be investigated what is the saturation point for the number of the π circuits and the number of the RL parallel blocks. It is carried out using the simulation results from several voltage signals that will be used as voltage sources at the initial line terminal.
For Figures 22 and 23, using the routine without the effect of frequency, it is analyzed a particular stretch of the simulation at the end of the line. It is shown the voltage values without frequency influence. In Figures. 22 and 23 it is used the values of Table 2, using 100 and 200 π circuits, respectively.
Specific portion of the simulation at the end of the line with 100 π circuits and without the effect of frequency.
Based on the mentioned results, it concludes that increasing the number of π circuits leads to a decrease in the numerical oscillations.
Specific portion of the simulation at the end of the line with 200 π circuits and without the effect of frequency.
In Figure 23, it is clearly a greater condensation of numerical oscillations in both x and y axes in contrast to Figure 23, where the period of the oscillations and the peak value are higher than those obtained in Figure 23. In Figures 24, 25 and 26, it is used the routine with the effect of frequency, analyzing the number of the RL parallel blocks inserted in the cascade of π circuits, searching for reducing of numerical oscillations. In Figures 24, 25 and 26, it was used the values of Tables 3 and 1, as well as, 3 and 4 RL parallel blocks, respectively.
From the results of Figures 24, 25 and 19, it is observed that the used routine including the effect of frequency in the cascade of π circuits obtains considerably fewer numerical oscillations when compared to Figures 22 and 23. From these results, it is evident that if it is increased the number of the RL parallel blocks, it is reduced the numerical oscillations and the voltage in the line end has a smoothly curve in the time domain.
Voltage at the end of the line with the effect of frequency considering 200 π circuits and using R4L4 parallel block.
Voltage at the end of the line with the effect of frequency considering 200 π circuit and using R0L0, R2L2 e R4L4 parallel blocks.
Comparison of
Concluding the analysis of the results, Figure 26 shows a comparison among the results of Figures 24, 25 and 19, leaving a clear decrease in the numerical oscillations. In this figure, it is shown a time range of the time simulation used at the last three figures. In this case, it is clearly shown that, increasing the number of RL parallel blocks, the numerical oscillations are decreased and the frequency influence is better reproduced through the state equations in mathematical software.
Considering the corona effect, Gary’s model is applied with the routine described in the previous items. It is used the line representation without frequency influence, because the representation with frequency influence has not hardly analyzed. The corona effect is introduced by
In this case, RCOND is the conductor phase radius in [cm], C is the transversal line capacitance and the CC is the new value of the transversal line capacitance because the corona effect. In this chapter, the RCOND value is 2.54 cm. The simulations are carried out for some relations between V and VC. The V value is 1 pu for all following shown simulations.
Considering Figures 27-31, the corona effect is related to the 10 π circuits in the middle line. It corresponds to the 500 m of the represented line. Figures 27-30 show results for different relative values of the corona voltage when compared to the line nominal voltage. In Figure 31, it is shown the comparisons among the results for the voltage values in the receiving end terminal. So, using a simple routine based on π circuits for transmission line representation, undergraduate students can analyze and simulate traveling wave phenomena in transmission lines.
The time domain simulations with the corona effect for VCORONA = 0,35 V.
The time domain simulations with the corona effect for VCORONA = 0,5 V.
The time domain simulations with the corona effect for VCORONA = 0,7 V.
The time domain simulations with the corona effect for VCORONA = 0,9 V.
Based on Figure 10, it’s simulated the corona effect with effect of frequency for some relations between V and VC. The V value is 1 pu to the following shown simulation.
Comparisons of the time domain simulations with the corona effect for some VCORONA values.
Comparisons of the time domain simulations with the corona effect with effect of frequency for some VCORONA values.
It is described the application the MatLabTM software in analysis and simulations of transient phenomena in transmission lines. Using the characteristics of this software, transmission lines are easily modeled as a mono-phase circuit. Transient simulations are also easily carried out. For these applications, it is used basic and simple tools of the MatLabTM software. So, this software improves the analysis of the proposed problem, because it is possible to obtain several types of the graphic results that are not available in the specific programs for transient analysis like the EMTP programs. So, it is possible to analyze the resistance and inductance values that depend on the frequency when it is considered detailed transmission line models. It is possible to analyze the application of different numeric methods for solving the differential state equations by numeric integration routines. On the other hand, with a simple model of the transmission lines and the MatLabTM software, it is possible to develop a routine that is used by undergraduate students, making easy the learning about important concepts as wave propagation, transient phenomena and transmission lines. This routine can be modified, introducing elements that are able to consider the frequency influence in the transmission line parameters. These parameters have their characteristics distributed along the line and this is considered in the mentioned routine.
The shown analysis and results can be used by undergraduate students for learning about the important concepts of power systems, transmission lines and wave propagation, for example. Related to the graduated students, it can be used for analyzing transient phenomena, developing transmission line models, improving numeric routines and comparing different numeric integration methods. So, the MatLabTM software is an excellent tool for basic and profound studies of transient phenomena in transmission lines.
Modern society depends on open and fair debates to shape democracy. For a debate to be successful, it is essential that different viewpoints can be addressed and discussed. This requires fairness and trust. Traditional locations for debates are Town Halls, TV Debates and Universities. Debates guide public policy and serve to increase the legitimacy of measures since they have originated from citizens or are supported by citizen groups [1]. Debates often consist of a group of citizens with a large amount of information, which then deliberate on public policy directions, intending to reach consensus towards specific recommendations [2]. Naturally, citizen groups have been identified as a promising effort to promote deliberative democracy [3]. Research predominantly focuses on such debates and how the participants are transformed through the experience.
“[…] in the long term, deliberative civic engagement efforts could transform not only their participants but also the larger public. Those participating in, engaged with, or captivated by such actions should report stable (or rising) public trust levels and signs of reduced civic neglect” [4].
“[…] in the long term, deliberative civic engagement efforts could transform not only their participants but also the larger public. Those participating in, engaged with, or captivated by such efforts should report stable (or rising) levels of public trust and signs of reduced civic neglect” [5, 6, 7].
In other words, public debates can be considered a remedy to political distrust. Studies focused on how such debates can promote social learning [8], change the participant’s preferences [9]. Such debates are often seen as the most advanced method to institutionalise deliberative democracy [10].
Currently, a general agreement has been reached that small circle debate, also defined as mini-publics, is one component of deliberative democracy [11, 12, 13]. The possibility of utilising the emerging information and communication technologies for new ways of citizen participation since network technologies allow for ease of access to civic involvement in politics [14, 15]. Additional benefits have been identified in terms of democratic discussions among people [16, 17], such as eliminating physical and social barriers that have a restrictive impact on offline mini-publics [18]. Even Supreme Court Justice Anthony Kennedy pointed out that discussions nowadays do not happen in streets and parks and instead happen via electronic media. Therefore, he reiterated the publics ability to participate in discussions would change due to changes in communication technologies [19]. Thus, one of the main challenges is how to ‘translate’ the traditional public forum into a more modern technological environment. Yet, at the same time, preserve the most important ideals of public forums such as insurance that speakers have access to a broad audience, equal time of speaking and that the public has a shared exposure to diverse views and opinions.
Recent events about the global COVID-19 pandemic have proven that in the presence of a worldwide mass lockdown of society for a considerable period, a scalable online deliberative platform would become increasingly more critical for the preservation of democracy and for decision making, which affects both local and global diverse communities and interests. Yet, most research and initiatives on online deliberative publics do not contemplate the effects new media concepts, such as Social Media and online forums, have on how and where debates are conducted. It can be argued that both online and offline deliberation can lead to further polarisation [19]. Specifically, with the advent of Social Media Platforms, the overall debating landscape has resulted in a complex global plethora of constantly changing media interactions affecting the individual citizen. New media experiences that are user-driven new phenomena have emerged, known as Filter Bubbles [20] and Echo Chambers [21]. Both phenomena create a distorted view of the overall reality in which the debate is held. This became very clear during the last US elections in which the primarily east coast based liberal press debated a for them sure candidate, Hillary Clinton, hence creating an Echo Chamber. The debate was biased entirely towards the opinion of the liberal news outlets creating a distorted view of the overall US picture [22]. This phenomenon is propelled by Filter Bubbles, in which content of interest is prioritised, leaving out the range of friends that are of a different opinion [23]. The overall challenge is a constant misunderstanding or artificial bias within online spaces that facilitate debate. On the flip side, however, it is not easy to scale a physical discussion and organise it in a transparent, inclusive and fair manner. About fairness, the concept of bias plays a vital key and is often misunderstood. Biases within debates are inherently necessary because it represents the opinion or value system of the debating parties. However, it is essential for a debate that these biases are known to everyone.
A further challenge in modern digital or physical debates is Fake News. This topic has played a significant role in the last US election and has become known as the Cambridge Analytica scandal. Fake News’s core is beyond simply posting or circulating false news, but the danger lies more in the nuance of its influence. In the form of ads, news articles can subtly influence members of society to vote for a different party and have become known as the Cambridge Analytica scandal [24]. Therefore, it can be argued that Fake News is endangering an open and honest democratic process due to the lack of reflection and debate around the opinions of the members of a democratic society.
Furthermore, it can be argued that the emergence of Deep Fake, which uses high-end AI technology to create a falsified video, which is close to impossible for a human to identify as false. It will lead to even more distrust in media in general and further weaken the public’s trust in the modern media landscape [25]. Similarly, behavioural and attention economics in the digital context shape media content, creating shorter and addictive content rather than a deep and reflective one that requires more time.
This publication introduces the HELIOSPHERE concept to introduce a participant focused, fair, sustainable and technologically advanced debating concept to empower a transparent, inclusive and honest debate. It is about inclusiveness by facilitating a hybridisation of the online and offline, digital and physical, real and virtual. HELIOSPHERE, therefore, forms a conceptual and theoretical base for modern debates that empowered by modern media technology without weakening the core of the discussion: honest, respectful and trustworthy communication between citizens. At its core, HELIOSPHERE empowers online, and offline debates with sophisticated Machine Learning analytics that results in a media value chain that supports the moderation of a discussion to ensure the debate is transparent, inclusive and fair. A pertinent point in the current environment is the ability of HELIOSPHERE to be functional and help citizens during massive societal lock-downs due to its online nature and ability to include people even in the most stringent social distancing environments.
The HELIOSPHERE is an inclusive, transparent and fair debating platform that addresses the lack of trust in public, online and offline debates to support the democratic process of modern society. It implements an easy-to-apply solution that can be used in any public setting, whether entirely online or as a hybrid concept, both offline and online and with minimal effort. The main component about trust is the AI-supported real-time debate analytics solution, which supports both the moderation and the offline/online audience in identifying and adjusting to elements of debates that create bias, manipulation, monopolisation etc. Participants can share, design and validate the debate with relevant content. HELIOSPHERE utilises Machine Learning models trained on datasets collected from already held debates and speeches that enable the debate to become more transparent and fairer and data gathered from media, political and other resources (see below the data engine section). The platform is not limited to a particular language, border limitations. It includes multilingual real-time modules, Cross-Border Content Rights, Data Privacy embedded from the start, Freedom of Speech to understand how meaningful debates can increase the trust in the political and democratic communication process in modern society.
In other words, public debates can be considered a remedy to political distrust. Studies focused on how such debates can promote social learning [8], change the participant’s preferences [9]. This type of debate is viewed as the most advanced method to institutionalise deliberative democracy [10].
To increase transparency, inclusiveness and fairness during the debate, the HELIOSPHERE visualisation focuses on the following analytics results:
Information on the number and duration of male or female contributions may help the moderator to find a balance in this respect.
Statements can be weighted according to their overall popularity, based on the results of the analytics before the debate - not to support these statements and to give the impression they would be more plausible but to put the finger on it and give the speaker the chance to react to this fact.
Most importantly, the fact-checker provides an analysis of the plausibility of any statement so that the moderator or any participant in the debate can pick up a line and bring it up again to avoid that populists win a debate based on good rhetoric alone.
Sensible guidelines support moderators in making fair use of this information to ensure that they will increase fairness and reason throughout the debate rather than making it easier for any speaker to win an argument through clever manipulation. The HELIOSPHERE system will continue to learn and monitor the topic’s coverage and identify when the time has come to re-open the debate or have a new debate on the subject based on significant recent developments. In the following sections, we describe the platform architecture and its components.
The HELIOSPHERE Engine Architecture is developed in a modular manner to support transparent and inclusive debates [26]. The architecture has four main goals: data collection, machine model training and deployment of the tools, visualisation during and after debates. There are three main parts of the platform: Data Engine, Machine Learning Engine and Customizable Visualisation Engine.
The HELIOSPHERE Data Engine is responsible for storing and pre-processing all the collected data, including Data collected from the debates themselves. During the debate, an automatic speech to text module transforms the speech into text. Additionally, data collected from other sources, including related initiatives, historical events, business/academic, political entities, published speeches (video, audio, transcripts), documents from governmental and non-governmental institutions (including UN, UNESCO, EU Council, EU Parliament, National Legislative Bodies, WTO, World Bank, IMF) and NGO’s published data. Data collected from publicly available content from TV and print media, publicly available social media postings (Twitter, Facebook, Reddit, YouTube, Steemit or any relevant or future social media platform) related to the debate topics are pre-processed and stored within the data engine.
Since the data collected is heterogeneous, it requires collecting raw data, which is parsed, pre-processed and standardised to be compliant with reusability and compatibility. The raw data is pre-processed, prepared and annotated before including it in the data storage engine continuously. As such, the technological solution would necessitate a distributed environment, such as Hadoop1 system to provide real-time queries and interactive aggregations even with tens of thousands of data points. The data engine is structured to provide fast (1–2 seconds query access) to the data, requested either by the ML and visualisation engine, third parties through the APIs or other services. Furthermore, specific blockchain smart contracts need to be included in the Data engine to guarantee data privacy.
To mitigate and recognise fake, deep fake information and illegal content, the engine ensures the utilisation of blockchain technology to provide traceability, transparency, and decentralisation. As such, Blockchain implementation offers reliable support for verifying both the content and its source. Different actors, people involved in the debate, can access a public blockchain where data is tagged and can, in turn, define a ‘Debunker Community’ and can give opinions on the content during the debate. These opinions may be registered in the tamper-free, publicly accessible ledger. However, complex queries on the blockchain’s data cannot be directly supported by the blockchain itself due to performance and scalability issues. HELIOSPHERE, therefore, provides an interface between the blockchain and the Data Engine so that the Data Engine can retrieve the data on the blockchain to support complex data analysis efficiently. The Data Engine will also store the result of complex aggregation queries in the blockchain. This ensures the results of the study available to the actors of the debate and immutable.
The HELIOSPHERE Machine Learning Engine is responsible for providing the AI models used for various components. The deployment of algorithms/models rely on three main parts - (1) data queried from the Data engine, which are needed for the training and testing phases, (2) the neural and ML models, candidates for each component, and finally (3) the code required to implement everything together. The engine’s iterative nature and its way of functioning - a neural model, is proposed, trained on available data. All suitable candidate models are compared and evaluated, which informs selecting the most suitable one for the task at hand. Then the model is deployed for the next debate or innovation cycle.
The engine utilises both tensorflow2 and pytorch3 options, allowing further Enrichment for the model building (code phase). The models can be accessed through internal API calls or the APIs of the partners. Based on the models and structure, several main components will be available, for instance:
The Speech-to-text component is a real-time component and used during the debate as an automatic tool for closed captioning and improving the speech-to-text in case errors occur during the live transcription. This separates the audio stream into segments of a predefined length with a buffer option for uninterruptible service. Each segment denoising and feature extraction is performed (which comprises the pre-processing phase), leading to the acoustic model generation and the language model. A speaker diarisation tool is used for discovering different speakers and enabling the segmenting of the incoming audio stream into individual speaker profiles. This allows a normalisation of the predictive models for each speaker. Since debates are often situated in a noisy environment, a separate voice frequency from background sounds before submitting it to the speech-to-text engine is identified. The speech-to-text conversion distinguishes between different speakers and currently disregards background music, fast or garbled speech, interruptions (such as applause, crowd cheering, or other speakers butting in). The final output is a textual format saved into the Data engine module with the required annotations for each debate and each participant. The output is also available for visualisation on the dashboard.
The Language Model specifies all word combinations with semantic meaning formed and their probability of occurrence. The Dictionary is required to integrate phonemes and transcriptions of different pronunciations for a word. The level of granularity characterises it for transcription in phonemes.
Speech-to-Speech translation is implemented as a hybrid speech-to-speech system for three main reasons:
There is no sufficient amount of parallel audio data to allow researchers and developers to train efficient end-to-end speech translation systems. Decomposing the speech-to-speech translation tasks into smaller tasks can take advantage of the lower training data requirements for each of the underlying functions compared to the end-to-end model.
Exploiting different components in a distributed fashion is computationally more efficient at training time, allows for better controllability and is easier to upgrade.
A composite system can share components from other subsystems of the HELIOSPHERE ecosystem.
The ASR and Synthesis components are shared with other subsystems of the HELIOSPHERE ecosystem. As such, we will focus on developing the MT system and developing communication protocols with different methods to ensure a coherent speech-to-speech MT component. To potentially synchronise an avatar with the text, intermediate post-processing is conducted to generate a set of visemes and timecode based on the translated text’s phonemes. We will also consider this post-processing as part of the MT component.
The MT component has two objectives: (i) to provide inclusiveness via translation for users that conduct the debates in different languages and (ii) to provide inclusiveness via translation of the debates into English to generate content in the correct language and format for the analytics component. We apply three different MT systems to handle speech (in the form of audio input) and text: (i) a text-to-text bilingual MT to translate from and to English; (ii) a text-to-text multilingual MT that encapsulates multiple languages, including English, aiming to provide translation between language pairs for which bilingual parallel data is not available and (iii) a multimodal, speech-text-to-text translation system that exploits both speech and text to improve the text translation.
HELIOSPHERE exploits neural MT approaches using open and free software, such as OpenNMT4 and Marian5, which provide speech-to-text and multi-source translation. The goal is to improve our models’ efficiency and the architecture of our system to make it suitable for an HPC ecosystem. The third type of the MT-system mentioned above systems conducts a second stage translation similar to automatic post-editing systems. It uses two types of inputs -- speech (user-generated audio) and text (result from ASR or the first-stage translation) -- and produces an improved version of the initial translation. Following positive examples from domain-adapted MT, gender-aware MT, and others, we will develop a context-aware MT conditioned on the debate’s topic. HELIOSPHERE provides additional context information regarding the subject and the speakers that can help the translation system generate better translations. In this way, we will ensure a coherent translation and reduce biases. The MT component has a distributed architecture. It operates in real-time and adapts to traffic through a series of scaling up/down policies that maintain the required number of resources for optimal performance. It is accessed via a set of API calls that allow human users and other components of the HELIOSPHERE ecosystem to interact with the MT component efficiently. This reduces the efforts for connecting the MT component has to the other components of the HELIOSPHERE ecosystem. We envisage a request handling fleet that will listen and store MT requests in a queue; another system will consume requests from the queue and invoke the requested action; once the action is completed, a response will be sent directly endpoint provided with the initial request.
Other components interact with the MT Pipeline via internal API calls. The viseme and timecode post-processing, as any post-processing, are invoked if necessary and is assumed to be a part of the MT action.
Natural Language Processing Component extracts features, including tokenization, word segmentation, Part of Speech (POS) tagging, parsing techniques, named entity recognition, n-gram language model, emotional and sentiment analysis, text/debate summarisation, structural relations modelled using semantic compositionality, K-means clustering, Affinity Propagation, Latent Dirichlet Analysis, Events analysis. Established toolkits such as nltk6, gensim7, SpaCy8, pattern9, and others will be used.
Additional NLP endpoints are specifically targeted towards the real-time analysis of live discussion streams applicable in the HELIOSPHERE platform. These include:
a pipeline for unsupervised training of domain-dependent, aspect-based sentiment analysis classifiers: this allows topic-specific sentiment analyzers to be easily pre-trained in advance of a heliosphere-event. During an event, these classifiers will extract and quantify observed opinion-aspect pairs in real-time relevant to the topic of the discussion.
stance detection identifies and tracks on which side of the argument actors in the discussion are situated. This not only allows for the visualisation of (possibly shifting trends in) the stance of the participants but also serves to pinpoint bias in the discussion, for example, when sure sides of the argument are given an unproportionate amount of time during the debate (e.g. majority vs. minority voices).
level-of-disagreement detection: Internet pioneer and essayist Paul Graham identified seven types of disagreement, which are most often used in online arguments, ranging from name-calling (level 1) to refuting the central point.
The HELIOSPHERE Visualisation Engine’s primary purpose is to provide visualisation and interactivity capabilities to moderators, participators, and audiences. The goal is to ensure transparency and fairness during a debate. Through a customizable visualisation, the analysis generated from the data, implemented through the Machine Learning Engine, is available to the public in real-time. This allows participants to see in real-time the textual representation of their deliberations, how much time each participant spent talking, what are the word frequency (word clouds, n-grams and word co-occurrence) of the conversation, topic detection, point summarisation, graph representation of topics, entities relations and main points, as well as the capability to switch to a different language. Crucially, the customization capabilities are suited to the users’ particular needs - whether moderators, participants, online participants, giving them an easy and personalised set of graphical interfaces, which relies on both the Data Engine and the Machine Learning Engine.
Moreover, to increase inclusiveness, the system provides a hybridization of online and offline participants - via an advanced avatar technology seek to provide bi-directional inclusiveness. Therefore, the HELIOSPHERE platform provides a spatial virtual physical concept that uses avatar technology to include large numbers of online debate participants (scale). Such capabilities become increasingly more critical in times of global pandemics, where offline gatherings of more than two people are prohibited for an extended time.
The immersive multimedia debate concept combines a look around - where all participants, local or virtual, are situated around the same round table and can be viewed by everyone in their positions rather than on opposite sides of a rectangular table - with a look inside - where AI-driven analytics support the addition and verification of insights by analysing a given pool of trustworthy media sources of multiple origins. This guarantees the real-time detection of fake assumptions and bias. The HELIOSPHERE dashboard visualises certain meta-aspects of the debate, signalling preference and contradicting opinions while they are detected. Especially in cases where debutants contradict their assumptions, this ensures participants stick to rational and honest statements and explain a possible change of opinion - after all, a difference of opinions is usually legitimate and often recommendable. Still, it should be treated openly and fairly by both speaker and listener.
With the spread of online interaction possibilities, the graphical representation of users has become ever more ubiquitous. With the origins for on-screen representation of users lying in 1980s computer games, and then spreading to personal icons in 1990s web culture, new messaging apps provide playful personalization as standard features (e.g., “Memoji/Animoji” on iOS, BitMoji on Snapchat, face filters on Instagram). Avatars offer users a sense of anonymity (they are not as recognisable as profile pictures or video chats) while retaining a sense of familiarity and personality to other participants. In a debating or conversational setting, we will use these properties of the medium to facilitate and improve online participation in physical contexts.
When avatars are displayed as audience members on screens, this brings them one step closer to the audience that can look at each other in the eye. Understandably, various modes in which online audiences can be blended in with a physical group of people - be that through 2D interfaces like monitors and screens, or 3D presences using hologram technology or robotics can be utilised to understand the most suitable solution depending on the gathering. Robotic presence is already used in classrooms worldwide to represent a teacher in the home of missing students or distant students in a school. The interaction challenge is explored to find the natural fit for engaging groups of audiences while retaining the possibility for anonymity and keeping the tone of the conversation straightforward and open.
Finally, the visualisation engine integrates rich-media of user-generated and broadcaster provided content to empower participants to point to content (host-based, web or social media) to support or debunk arguments within a debate. Moreover, users can participate in validating if statements and content are valid and trustworthy.
To support live debates in hybrid (both online and offline) environments, HELIOSPHERE implements an immersive and interactive experience for an online debate calls for a variety of media elements such as 360° live video, Live video from remote individuals, Live generated closed captions, and automatic subtitles in different languages. This contributes to the immersive experience for Citizen participation and active contribution to a debate.
All interacting components need to be fast and synchronised so that they reach all viewers simultaneously. Since the diverse participants in the debate have differing roles and needs, these elements need to be i) object-based, ii) individually configurable, and iii) have low latency.
It is envisaged that the HELIOSPHERE provides the capability of covering debates on TV as an enhanced and interactive experience. This can be made possible via a central integration system offered by broadcasters. Moreover, data can be made available centrally and accessed directly by all interested journalists and newsrooms with just a few clicks. The use and republishing of the content are free of charge. The new content exchange platform is intended to enable citizens, and the content created is made available via diverse channels.
This can be provided as a recording or as a live debate. In this way, specific topics provided for free by the broadcasters can also be made available. For a debate to be planned, a schedule is to be developed, which allows the debate’s organiser to define the services available for each debate, for example, Dashboard, 360° streaming, Link sharing for Twitter, Xing, LinkedIn, etc.
An initial trial with a basic configuration of the HELIOSPHERE concept was carried out over two events in the Science Gallery Dublin10, Ireland. In both cases, the HELIOSPHERE was part of the Science Gallery Book Club11. The first book club, which was on 26 November 2019, discussed the book ‘Invisible Women: Data Bias in a World Designed for Men’ by Caroline Criado Perez, and the second book club on 25 March 2020 focused on ‘Clearing the Air: the Beginning and the End of Air Pollution’ by Tim Smedley. It is worth pointing out that for the first book club, ‘Invisible Women’ HELIOSPHERE deployed a live 360 camera and language analytics features with an audience of over 20 people participating live and 15 online, for the second Bookclub ‘Clearing the air’ a purely online event with about 13 participants was conducted and no 360-degree camera was used. This was due to the COVID19 pandemic and allowed testing the HELIOSPHERE concept purely online and not hybrid offline and online.
To increase the inclusiveness of all attending participants, the layout was circular (see Figure 1). For each book club, two moderators were active, one primary and one support. During the ‘Invisible Women’ event, the two moderators were seated at a round table, capable of holding up to five people. Three more tables were positioned around the table, each hosting one sub-moderator with three to five participants. For the first 40–50 minutes, the participants at each of the tables discussed the book among themselves and a designated sub-moderator. Once the initial discussion was completed, each table’s sub-moderators joined the main round discussion table with the leading two moderators. Here, a 360-degree live feed camera was placed to include online viewers and participate in the debate. Their comments were relayed to the moderators via an iPad on the main table. For transparency and fairness, the HELIOSPHERE AI analytics component was enabled and displayed on a screen. A microphone in the moderation table’s centre captured the discussion and encoded the audio to the AI module for further analysis. Figure 2 depicts the view from the 360-degree camera during the live stream and debate. The table scene is the audience discussing the book with one of the moderators. The bright screen is set to showcase the debate analytics in real-time. The top left corner presents a control for the camera, so each online participant has a complete view of what is happening in real-time in the room. Additionally, the online audience can ask questions/comments, which are then raised by the moderators and addressed during the discussion.
HELIOSPHERE spatial concept.
HELIOSPHERE 360 camera angle.
The AI analytics module used speech-to-text technology to encode the live voice feed in real-time, including the conversation between moderators, the author, the present and the online audience. During and after the debate, several types of analysis were performed. For transparency, the most frequently used words during the entire conversation were displayed live (see Figures 3 and 4 as representations due to the live feed not being captured at these events for privacy reasons).
Example of real-time keyword extraction.
Example of real-time keyword extraction.
The moderators understood the general audience attitude during the debates based on real-time sentiment analysis and the emotional disposition during the debate (Figure 5 for Invisible women discussion and Figure 6 for Clearing the Air). In the two particular debates, the sentiment analysis for ‘Invisible women’ mainly was positive. Simultaneously, the topic of pollution and current societal problems emerging for the issue produces slightly more negative sentiments than the invisible women discussion.
Sentiment example.
Sentiment example.
To gain a more in-depth overview, we included a graph representation of words and topics. Each debate concept graph is connected to the overall “Heliosphere” of topics, themes, with the possibility of further analysis on the HELIOSPHERE website. Moreover, it included an n-gram analysis for both debates. This allowed us to build go-occurrence networks (graphs). For the ‘Invisible Women’ the words most often associated with the word “women” are indicated, which include “need”, “lot”, “many”, “gained, “educational”, “potential”, “body”, as well as others. For the ‘Clearing the Air’ discussion, the co-occurrence graph is presented in. The lower plot presents the words associated with the word “air”, which include “chemica”, “reaction”, “pollution”, “breathe”, “monitor”, “clear”, “city”, “world”, “quality”, among others.
The creation of n-grams serves several simultaneous purposes. First, it provides a real-time interactive concept map for users to browse and click on each node (word or n-gram) to bring up more detailed information about the entity, concept, word. Through the concept mapping, HELIOSPHERE attempts to level the information accessible to all participants to make more informed and transparent choices/arguments. Moreover, since all participants have access to the same set of facts/data, we reduce false information while enriching the informational landscape. Technically, such information is extracted from the sources described in Section 2 of the current work. When a falsehood is present, it is labelled as such in the concept map, so users have a clear idea of the presented information’s truthfulness (Figure 7).
Example of entity extraction.
Second, the n-grams provide the initial structure for the argument module, which allows us to track the participants’ position on topics (whether they are for, against or neutral). The stance tracking would be crucial during debates on essential/current social, political or economic issues. The modules serve as an indispensable tool to track the electorate’s mood, thereby creating an instantaneous snapshot in the discourse. Additionally, the module connects to the AIF database through API (programmable application interface) to query AIF argument structures, enriching the debate in real-time while providing ground truth for debates. For instance, within the ‘Clearing the Air’ debate, the pollution due to livestock eating was debated, which the system detects and queries aid to supplement the discussion further (Figure 8).
AIF argument example structure.
The core concept of HELIOSPHERE is to overcome the crisis of trust seeded by the use of Social Media to influence and manipulate large parts of society towards opinion forming. HELIOSPHERE, by its architecture, does not rely on storing information or using a centralised architecture to avoid similar pitfalls. The independent infrastructure via small, portable and affordable computer units described above ensures is specifically designed to provide no information needs to be stored or processed on an external server. Therefore, it can be argued that HELIOSPHERE works based on a trust-by design paradigm, which empowers real-time support from the AI approach. To increase ensure, privacy-sensitivity is provided. HELIOSPHERE does not rely on any personal information. The speech to text approach is not designed to identify specific and unique patterns over time but focuses on overall sentiment and terminology usage. There is, therefore, no temporal tracking in place that allows a comprehensive analysis of a specific individual. Ethically the concept has to evolve to ‘explain’ how the information has been collected and summarised. Hence, explainable AI needs to be applied to ensure ethical considerations can be taken into account, such as data decision transparency. Furthermore, it has to be assured that the approach does not evolve to ‘making decisions’ for both the moderator and the participants. Concepts that imply trust at its core are support mechanisms and should not undermine the moderators or participants trust in their judgement.
This publication introduces and discusses the HELIOSPHERE concept. The foundations are to support the democratic process by empowering debates, both offline and online. Moreover, the HELIOSPHERE presents a hybrid image in which offline (physical) and offline are blended. To support the discussion, three main dimensions are addressed: transparency, inclusiveness, fairness. To empower openness and fairness, an AI dashboard was presented, including an initial trial. The AI dashboards support both the participants and the moderators to balance the debate based on objective data related to sentiment and most debated topics. Concerning inclusiveness state of the art camera technology such as 360-degree cameras were introduced.
Concerning future work, all three areas, transparency, inclusiveness, and fairness, are to be extended towards the vision presented in the publication’s introduction. Specifically, concerning transparency and fairness, the AI dashboard is being developed and tested towards speaker time detection, speaker gender detection, off-topic detection and bias detection. More advanced technological approaches are being tested concerning inclusiveness, such as avatar technology, to overcome the barrier between online and offline audiences. For HELIOSPHERE, it is essential that not only the online audience is to be included more in the debate via camera, voice and commenting technology but also that the offline (physical) audience are more aware of the online audience, which is currently mainly an image or face on a screen. Using more advanced avatar representations makes it possible to bring the online audience closer to the experience within the space.
A further area that can be extended is to detect sentiment in debate and towards mentioned topics. This allows a moderator to ‘take the heat out of a debate. On the flip side, a moderator can also be informed that the overall debate has slowed down too much and needs to be reignited. Features such as speaking time per gender and other balancing metrics are possible and can also be extended to more sophisticate areas such as bias and off-topic detection.
Finally, it has to be noted that the recent surge in sizeable real-time scale online debating platforms such as Clubhouse12 have become very popular and has reached over 10 M active users weekly13. Competitors such as Twitter and Facebook are rumoured to be developing alternative real-time debating platforms with the same premisses that the conversations are not recorded or post-analysed.
In conclusion, it can be stated that the introduction of the HELIOSPHERE concept forms a solid and foundational concept to blend complex online and offline communication, such as highly interactive debates, and with that support democracy as one of the foundations of society, which is democracy.
This work is supported by the ADAPT Centre, funded under the Science Foundation Ireland Research Centres Programme (Grant 13/RC/2106).
Intro
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On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. 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Salt negatively effects the crop production worldwide. Because most of the cultivated plants are salt-sensitive glycophytes. Salt stress affects the seed germination and seedling establishment through osmotic stress, ion toxicity, and oxidative stress. Salinity may adversely influence seed germination by decreasing the amounts of seed germination stimulants such as GAs, enhancing ABA amounts, and altering membrane permeability and water behavior in the seed. Rapid seed germination and subsequent seedling establishment are important factors affecting crop production under salinity conditions. Seed priming is one of the useful physiological approaches for adaptation of glycophyte species to saline conditions during germination and subsequent seedling establishment. In seed priming, seeds are exposed to an eliciting solution for a certain period that allows partial hydration without radicle protrusion. Seed priming is a simple, low cost, and powerful biotechnological tool used to overcome the salinity problem in agricultural lands.",book:{id:"10363",slug:"abiotic-stress-in-plants",title:"Abiotic Stress in Plants",fullTitle:"Abiotic Stress in Plants"},signatures:"Cüneyt Uçarlı",authors:[{id:"189302",title:"Dr.",name:"Cüneyt",middleName:null,surname:"Uçarlı",slug:"cuneyt-ucarli",fullName:"Cüneyt Uçarlı"}]},{id:"67884",title:"Adaptation of Halophytes to Different Habitats",slug:"adaptation-of-halophytes-to-different-habitats",totalDownloads:1663,totalCrossrefCites:6,totalDimensionsCites:13,abstract:"In recent years, global climate change has been altering environmental (severe drought, soil salinization, irregular precipitation, etc.), around world, decreasing crop yield and upsetting the balance of ecosystems. Nonetheless, a group of plants known as halophytes have the ability to survive and develop in saline soils (wetlands, deserts or temperate zones), may be used in agriculture as a possible alternative to crops (salt-sensitive), as well as for fodder, energy production, medicinal purposes, and desalination of salt-affected areas (phytoremediation). This chapter provides a comprehensive summary of the adaptive strategies used by the annual and perennial halophytes on ecophysiological perspectives, to survive in diverse habitats. The results show a great diverse strategies, such as heteromorphism, seed banks, dormancy, rapid germination, and recovery capacity, from saline shock, favoring the chances of seed survival, although these mechanisms depend on light, moisture, temperature, and the type of salt, in which seeds germinate. In addition, it has been included some molecular, and biochemical aspects, discovered in last years, that might improve our understanding of physiology of these plants. It can conclude that halophytes may be as a possible alternative to ease pressure on cropping systems, restored lands degraded, or confer stress tolerance trough gene transfer.",book:{id:"8033",slug:"seed-dormancy-and-germination",title:"Seed Dormancy and Germination",fullTitle:"Seed Dormancy and Germination"},signatures:"Milagros Bueno González",authors:[{id:"298374",title:"Prof.",name:"Milagros",middleName:null,surname:"Bueno",slug:"milagros-bueno",fullName:"Milagros Bueno"}]},{id:"52387",title:"Plant Pathogens",slug:"plant-pathogens",totalDownloads:4609,totalCrossrefCites:6,totalDimensionsCites:10,abstract:"Plants cover the most area of the earth’s living environment as trees, grasses, flowers, and so on. Plants play different important roles in the environment such as ecosystem balance and food supplement for animals and humans. Moreover, wild or cultivated plants are considered the powerful biofertilizers for the soil, where the plant debris after death and degradation provides the soil with sufficient organic matters. Accordingly, plant care is a great duty and hard mission, which must be constantly improved. The study of plant pathogens belongs to the branch of biology known as plant pathology. The latter is also concerned to overcome the plant diseases arising from the biotic and/or abiotic origin. Biotic (infectious) diseases are developed owing to microbial infection, while abiotic (noninfectious) diseases are developed due to environmental factors. 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It is commonly a moderately salt-sensitive crop. Salinity stress is the main abiotic factor that arrests the physiological characteristics and plant growth of a maize plant. It causes the osmotic effect, associated with an increase in phytotoxic ions, oxidative stress by increased reactive oxygen species (ROS) production, and ionic effect in the cytosol. These salinity effects hinder the maize plant’s physiological processes such as respiration, photosynthesis, transpiration, stomatal functioning, hormone regulation, and functioning, seed germination, and dormancy and water relation with plants and ultimately reduce the plant growth and yield. However, the physiology of maize subjected to salinity shows various responses that depend on the genetic responses and growth stages. Maize plant undergoes many physiological changes and adapts some mechanism internally to cope with salinity stress. Numerous mitigating strategies such as application of chemicals, application of plant growth-promoting rhizobacteria (PGPR), application of hormones, and use of genetic and molecular techniques are used to handle salinity. 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