GR1009026B - Method for the registration, processing and assessment of the users satisfaction index - system for the application of said method - Google Patents

Abstract

Novelty: a method designed for the registering, classification, processing and assessment of the reactions of services or product users is disclosed. Constitution-function: a system of devices receiving and registering the reactions of services users, a software program, a database and one or more servers. The satisfaction index results from the totality of the users reactions so that the operator of this method can be in position to extract, on the basis of weighted parameters defined by himself, liable and valid conclusions. The method consists in processing and evaluating the entered information on the basis of the concept of the simple equivalent reaction and composite equivalent reaction as well. Purpose: to deter misleading or noncommittal reactions; to draw liable conclusions from the fluctuation and finalization of the users satisfaction index.

Description

Description

Method of recording, processing and measuring user satisfaction index and system for implementing the method

A method that records, processes and evaluates, through a system of data input and recording devices, one or more network information servers, a database and a data processing software, the reactions of the users of the system, so as to provide its operator method the ability to draw, either at regular intervals or at any time and in an emergency, based on the parameters that he himself introduces, reliable conclusions about the quality of the services provided and the user satisfaction index.

Methods and systems for recording, processing and evaluating the reactions of users - recipients of various services, with the aim of ascertaining their degree of satisfaction and consequently the quality of the services provided, have already been devised (e.g. HappyOrNot Oy) and are applied to the market. This is completely reasonable and understandable, especially in the field of commercial enterprises, but also in wider sectors where services are provided to the general public, given the great importance that the accurate and as reliable as possible recording and evaluation of the degree has for the service providers user satisfaction. To this end, data entry and recording systems operate, with the help of which users are able to rate a service or a product and answer one or more questions, choosing each time one of the available keys, which make up a certain rating scale . The collected information is then processed, on the basis of which conclusions are drawn regarding the user satisfaction index.

To date, the methods of recording and processing user reactions are based on the evaluation of the gravity of a data input based on the time sequence of their input, i.e. the gravity of an input depends on its time distance from an initial point of calculation, as well as on the time sequence among the most imports within a certain period of time.

However, these methods are not safe, because a lot of cases are observed, in which: a) an incorrect key selection is made, unintentionally, i.e. a user accidentally presses an evaluation key and, in his attempt to correct his mistake, presses immediately after (within the critical time sequence) the button that he originally wanted to choose, b) deliberate misleading use is made, i.e. a user chooses the same evaluation button many times, or a different one many times, in an attempt to alter the result, as all its options are entered within the critical time sequence and c) use is made of the evaluation keys, without the intention of binding, but for the sake of humor and play.

The solutions given to date to the above disadvantages of the evaluation methods lie in the fact that the processing of the data, received from the input device, is based on the regularity of the input time sequence, which is based on a maximum number of data input, which is considered acceptable within a critical period of time. As soon as a difference is detected in the predetermined time sequence of data input (normality), then the incoming reactions - data cease to have the same weighting factor as the rest and now the weighting factor of each reaction is determined by a mathematical model, depending on how the time between the introduction of the reaction and the time point at which the differentiation was detected, as well as the time sequence of the introductions between them. However, despite the above adaptations and arrangements, the methods proposed to date do not satisfactorily solve the problem, continuing to suffer.

This is because: a) they officially consider the first data entry as absolutely valid, giving decreasing validity to subsequent entries, which are made within the predetermined, critical time unit. In this way, they unjustifiably arbitrarily and reduce the weighting factor, of the completely valid, possibly subsequent data inputs and b) in sequential or multiple data input, within the acceptable for the time sequence method, they are unable to identify if they come from more, different , unique (personalized) users or if it is multiple distinct imports (uses) originating from a single, unique (personalized) user.

The above disadvantages of the methods and systems for recording, processing and evaluating user reactions, which have been proposed to date, ultimately affect the reliability and consequently the safety and validity of the conclusions, which the operator of the method expects to draw, regarding the variation of user satisfaction index.

On the contrary, the proposed method and the corresponding system for collecting, processing and evaluating the incoming data - reactions, is based on the use of differentiated, per input device, parameters for measuring the gravity of each one of them, so as to exclude misleading or pointless counting response commitment and to draw reliable conclusions, regarding the variation of the user satisfaction index and consequently the quality of the services provided.

The innovation of the proposed method consists in the fact that each reaction recorded by the data input devices constitutes a unique and independent time stamp, that is, without it [the reaction] being correlated, connected, evaluated, initiated or included , during this initial phase, in a unit or group with other previous or subsequent reactions. The collected temporal data are analyzed, based on the proposed formulas, in order to derive the temporal density of their input, which is the main and most basic characteristic and innovation of the method.

Thus, user reactions and data are evaluated in relation to the time density of their input into the system and in addition in relation to the type and degree of satisfaction they indicate, based on the specific choice each time from the predetermined and calibrated scale of satisfaction. In addition, the specific placement of the data input device in the system and its particular position in the overall spatial or local layout of the entire system installation, based on the flow density of potential users from each device, determine the gravity values that each input receives a reaction.

The proposed invention, therefore, is a synthesis of a method of inputting, recording, classifying, processing and evaluating user reactions, based on their input density, in order to draw conclusions about their satisfaction index and about the quality of the services provided and a system which includes, based on a specific arrangement, the means that make possible the application of said method.

A. The Method

A. 1. Definitions

The method consists in recording, classifying and processing the input reactions - data, with the criterion of the "input density" parameter of reactions.

"Response" means any input [mechanical or touch] by the user on a data input device, which is connected to the system installation.

"Reaction type" means the user's selection of one of the available keys, based on a predefined and calibrated scale of options.

"Input" means any signal sent to the system, following a user response, through any data input device.

"Introduction density" means the number of reaction introductions [n] per time [t].

By [k] is meant the system of different types of reactions.

A'2. Input Density

A.2.1. Discrimination - Limit Values

The value that the 'input density' parameter takes each time reflects the correlation of time with respect to the reactions - uses entered by the reaction recorders. Depending on the value of the reaction input density, OL reactions are treated and evaluated differently.

Thus, starting from input density values close to zero and increasing the input density up to the limit of the "least marginal density", each reaction is assumed to come from a different user each time [see Figure 1, Interval D1].

Therefore "limit density" [DLmin] is called the maximum value of the reaction input density, up to the limit of which each reaction input can, due to the small input density, be considered as coming from a different [discrete] user each time.

For reaction input density values greater than the lower threshold density value, each reaction input can be considered OTL either from a different [discrete] user, or not (see Figure 1, Interval D2).

"Maximum Limit Density" (DLmax) is the maximum value of the reaction input density, up to the limit of which each reaction input can be considered to originate either from a different [distinct] user or not.

For reaction import density values, which are greater than the major marginal density value, all reaction imports are considered to have been made by the same and not by a different [distinct] user [see FIGURE 1, Space D3].

A.2.2. Parameterization

In the proposed method, the minor and major limiting density of input reactions are not predetermined and fixed quantities, but instead depend on variable parameters, set by the operator of the method, such as from the point where the input device of reactions - data is placed, in the whole layout of the system, from the density of the flow of potential users from the location of the device, etc. Therefore, the above values of the minor and major marginal density can be parameterized per device.

A.3. Simple Equivalent Reaction

A.3.1, Definition

Equivalent reaction input [PR] means the set of inputs resulting from the processing of received reactions, in such a way as to quantitatively and qualitatively reflect the set of different inputs, i.e. the input of reactions from different (distinct and unique) users. When the density tends to 0 (d ≈ 0), then the set of received reactions is identified with the equivalent response (Ρ ξ PR).

A.3.2. Calculation of Simple Equivalent Reaction

Suppose there is a system [k) of different types of reactions and where :

· P is the set of received reactions of all types P = {n1, n2, ... nk}

• PR is the set of reactions of all types after processing

• ni is the number of type i reactions

i = l, 2, ..., k

• G is the sum of ni

G = Sign

• Gmax is the maximum number of reactions considered not to be the result of intentionally misleading use of the input device.

In view of the above notations, the following cases of calculation of the simple equivalent reaction can be distinguished:

A.3.2.1. In case the value of the input density of reactions is less than the minimum limiting density (d < DLmin), then the formula for calculating the simple equivalent reaction is as follows:

A.3.2.2. In case the value of the input density of reactions is greater than the minor limiting density, but less than the major limiting density [DLmin ≤ d < DLmax), then the calculation formula of the simple equivalent reaction is as follows:

A.3.2.3. In case the value of the input density of reactions is greater than the major limiting density (d ≥ DLmax) then the following sub-cases arise:

A.3.2.3.1. When the number of reactions is greater than the maximum number of reactions Gmax (G > Gmax), then all reactions are considered invalid and are not taken into account in the final result, regarding the formation of the single equivalent reaction index.

ni = 0

ΡR= {0, ...,0}

A.3.2.3.2. When the number of reactions is less than or equal to the maximum number of reactions Gmax (G ≤ Gmax), then the following two further subcases are distinguished:

A.3.2.3.2. i. When the users' reactions are of similar type, then the simple equivalent reaction calculation formula is as follows:

If it is assumed that all reactions are of type j, then PR is given by the general formula:

PR= (n1,n2,...,Nk}

where

{ 1 i =j

<n>i<=>{0 i =j

A.3.2.3.2. ii. When users' reactions are of different types, then all reactions are considered invalid and are not taken into account for the construction of the simple equivalent reaction index.

ni = 0

PR<=>{0, .. , 0

A.3.3. Examples of Simple Equivalent Antiradiator Calculation Suppose there is:

•    a system (k) with five [5] types of user reactions from a graded reaction scale: A, B, C, D, E

•    DLmin = 1

• DLmax= 2

• Gmax= 3

Then :

A.3.3.1. Example 1 (see FIGURE 2)

In each density event, the reaction density is less than both the minor and major limiting densities. Therefore:

PR= P = {1,2, 0, 0, 1}

A.3.3.2. Example 2 (see FIGURE 3)

In the central density case of the example, the reaction density is greater than the minor marginal density and less than the major marginal density.

Therefore, the simple equivalent reaction resulting from the specific incident is formulated as follows:

with the simple equivalent reaction to the set of density cases [of the example) being formulated as follows:

A.3.3.3. Example 3 (see FIGURE 4)

In the first density case (d1) of the example, the reaction density is greater than the major marginal density, the number of reactions is less than Gmax, and all reactions are of the same type A.

Therefore, the simple equivalent reaction resulting from the first density incident is formulated as follows:

{1,0,0,0,0}

In the next density event (d2) of the example, the reaction density is greater than the major marginal density, the number of reactions is less than Gmax, and the reactions are of a different type.

Therefore, the simple equivalent reaction resulting from the specific incident is formulated as follows:

{0,0, 0,0,0}

In the third density case ( d3 ) of the example, the reaction density is greater than the major marginal density, the number of reactions is greater than G max, while all OL reactions are of the same type B.

Therefore, the simple equivalent reaction resulting from the specific incident is formulated as follows:

{0,0, 0,0,0}

with the simple equivalent reaction to the set of density cases (of the example) being formulated as follows:

PR= {1, 0, 0,0, 1}

A.4. Complex Equivalent Reaction

A.4.1. Definition

It is possible for the operator of the method to adapt and connect to the facilities of the system, in which the proposed method is applied and implemented, peripheral devices, which will make it possible to collect additional data on the origin of each introduced reaction.

This additional data concerns the origin of each reaction either from different users each time (i.e. distinct) users (e.g. through the use of sensors) or from personalized (i.e. unique] users (e.g. through the use of beacons).

If the proposed method is applied with a system, in the facilities of which the above-mentioned devices have been connected, and if the result obtained according to the rules for calculating the simple equivalent reaction does not coincide with the result indicated by the additional data, then the result resulting from the use of these additional data.

In this last case, we are talking about a complex equivalent reaction, that is, a method of calculating the user satisfaction index that takes into account the additional data, coming from the additional reaction input devices (means), which have been connected to the system.

The complex equivalent reaction is divided into two categories, the one that takes into account the diversity (distinctiveness) data of the users and the one that takes into account the individuality (uniqueness) data of the users.

A.4.2. Computation of Complex Equivalent Reaction with user diversity (distinctiveness) data

"Event" means the period of time during which a user is in a position to potentially operate a response input device connected to the system. Each "event" corresponds to a different (distinct) user.

Suppose there is a system (k) of different types of reactions and where :

· P is the set of received reactions of all types P = {ni, n2, ... nk}

• PR is the set of reactions of all types after processing

PR = {m, n2, ... nk}

· ni is the number of reactions of type i

i = 1, 2, ..., k

• G is the sum of ni

G = Sni

• Gmax is the maximum number of reactions considered not to be the result of intentionally misleading use of the input device.

In view of the above notations, the following cases of calculation of the complex equivalent reaction with data of diversity (distinctiveness) of the users can be distinguished:

A.4.2.1. When the number of reactions is greater than the maximum number of reactions Gmax (G > Gmax), then all reactions are considered invalid and are not taken into account in the final result, regarding the formation of the composite equivalent reaction index.

ni=O

ΡR= {0, ...,0 }

A.4.2.2. When the number of reactions is less than or equal to the maximum number of reactions Gmax (G ≤ Gmax), then two subcases are distinguished:

A.4.2.2.1. When oi reactions are of similar type, then the way of calculating the complex equivalent reaction is as follows: Suppose that all reactions are of type j.

Then PR is given by the general formula:

PR =

{n1,n2,...,nk}

where

{ 1 i =j

ni = { 0 ί =j

A.4.2.2.2. When the reactions are of different type, then the last reaction taken is taken into account.

Suppose the last reaction is of type j.

Then PR is given by the general formula:

PR= {n1,n2, ...,nk}

where

= { 1 i =j

<n>i { 0 i =j

A.4.3. Calculation of Complex Equivalent Reaction with user individuality (uniqueness) data

"Event" means the period of time during which a user is in a position to potentially operate a response input device connected to the system. Each "event" corresponds to an individual (unique) user.

Time interval "Tmin" means the minimum amount of time beyond which a single user is likely to have a different experience and thus is able to validly introduce a new reaction into the system.

Suppose there is a system (k) of different types of reactions and where :

• P is the set of received reactions of all types P = {n1, n2, ... nk}

· PR is the set of reactions of all types after processing

PR = {n1, n2, ... nk}

• ni is the number of type i reactions

i = 1, 2, ..., k

· G is the sum of ni

G = Sign

• Gmax is the maximum number of reactions considered not to be the result of intentionally misleading use of the input device.

· H is the set of events

• Hmax is the maximum number of events from the same user within Tmin that are not considered to be the result of intentionally deceptive use of the input device.

In view of the above notations and definitions, the following cases of calculation of the complex equivalent reaction with individuality (uniqueness) data of the users can be distinguished:

A.4.3.1. In the event that several reactions are entered into the system by the same unique user and they are separated by a shorter time interval than the Tmin interval, then the following cases can be distinguished:

A.4.3.1.1. When the number of reactions is greater than the maximum number of events Hmax (H > Hmax), then all reactions from all events are considered invalid and are not taken into account in the final result, regarding the formation of the composite equivalent reaction index.

n = 0

PR= {0, ...,0}

A.4.3.1.2. When the number of reactions is less than or equal to the maximum number of events Hmax (H ≤ Hmax), then the reactions from each event are further processed to derive the composite equivalent response index.

The way of processing reactions in each complex equivalent reaction event with user individuality (uniqueness) data coincides with the way of processing reactions with user diversity (distinctiveness) data (see above A.4.2.)

Subsequently, the 0 to H reactions - as they have resulted from the above processing of each event - are processed again in a way that coincides with the way of processing the reactions in the complex equivalent reaction with difference (distinctiveness) data (see above A. 4.2.).

A.4.3.2. In the event that multiple reactions are entered into the system by the same unique user and they are separated by more than the time interval Tmin, then each reaction is considered a self-contained, independent evaluation, which is taken into account in the calculation of the complex equivalent reaction with data individuality (uniqueness). The imported reactions in this case are processed in a way that coincides with the way reactions are processed in the complex equivalent reaction with difference (distinctiveness) data (see above A.4.2.).

A.4.4. Examples of Complex Equivalent Reaction Calculation Suppose there is:

•    a system (k) with five (5) types of user reactions from a graded reaction scale: A, B, C, D, E

Gmax = 3

•    The max = 2

•    Tmin = 24 hours

Then :

A.4.4.1. Example 1 see FIGURE 5)

The number of user reactions is less than the maximum number of reactions Gmax, while the reactions are of the same type, so the resulting complex equivalent reaction is formed as follows:

ΡR= {0, 1, 0, 0,0}

A.4.4.2. Example 2 (see FIGURE 6)

The number of user reactions is less than the maximum number of reactions Gmax, while OL reactions are of a different type, therefore the resulting complex equivalent reaction is formed as follows:

ΡR= {0, 0, 1,0,0}

A.4.4.3. Example 3 (see FIGURE )

In this example, user X and user Y are considered.

0 user Ψ uses the system once and only once, while his reaction is one and only, therefore the original reaction is identical to the processed reaction.

ΡR= Ρ = {0, 0, 1, 0,0}

In the case of user X, the number of events within Tmin is equal to the maximum number of events Hmax, therefore the way to calculate the complex equivalent reaction is as follows:

For the first event, the number of reactions is less than Gmax, while OL reactions are of the same type, so the resulting complex equivalent reaction is formed as follows:

ΡR= {1, 0.0, 0.0}

For the second event, the reaction is one, hence the complex equivalent reaction is formulated as follows:

ΡR= Ρ = {0, 1.0, 0.0}

Therefore, the complex equivalent reaction resulting in the set of events, given that the reactions are of different types, is formulated as follows:

ΡR= {0, 1, 0, 0,0}

A.5. (see FIGURE 8)

The method of recording, processing and measuring the user satisfaction index, according to which, the feedbacks entered by the input devices of the system, are analyzed and classified into groups of time density (d), with criteria set, with variables values, limits of the minor (DLmin) and major marginal density (DLmax) (FIGURE 8.1.) and with the criterion of the diversity (distinctiveness) (FIGURE 8.2.) and individuality [uniqueness) of the users (FIGURE 8.3.) is briefly presented in the claims.

B. The System

The system includes a number of user data input devices, one or more information servers, a database and a data processing software, which operates and processes the input data based on the proposed density method introduction of reactions and corollary of simple and complex equivalent reaction, as a result of which it acquires an innovative peculiarity characterized by reliable conclusions regarding the user satisfaction index.

The system, in particular, based on which the proposed method is implemented, includes in an installation arrangement (connected):

1. Devices for inputting - inputting reactions - data from users. The devices are floor-mounted, wall-mounted, table-top and portable, carry option keys, which are arranged in a linear arrangement, based on the degree [intensity] and characteristics [type] of the user's satisfaction or dissatisfaction and with a predetermined scale of calibration and grading of options. OL these devices are connected wired or wirelessly to the network servers [servers], so that through the latter the imported data to be processed is transmitted.

2.  Parallel and in combination with the above devices for inputting user reactions, the system has peripheral recognition devices, which are devices that have been equipped and operate e.g. with beacons technology, in which case the possibility of recognizing the electronic identity of the users [uniqueness] is provided, respecting, however, those characteristics that characterize the protected privacy [privacy], individuality and personality of the user, as well as facial recognition devices or of user footprints [diversity] with respect again to the user's individuality characteristics. The data collected OL these devices are necessary to derive the complex equivalent reaction and these devices aim to clarify the characteristics of the input data, in the sense of whether the data originates either from different [distinct] users or from personalized [unique ] users. These devices are connected wired or wirelessly either directly or through the input devices to the network servers.

3. One or more network servers to which the reaction and data input devices of all the above categories are connected.

4. Information - data base, where all input reactions - data, as sent by the input devices, are registered and classified.

5.  Software that implements the proposed method, which is the main subject of this application. Based on the software, the input, recording, classification, processing and evaluation of the information entered and stored in the database is carried out.

6. Possibility of connections with other computers and external electronic networks or communication systems, through which it is possible to provide the possibility of control, changes, adjustments, modifications of the parameterization of the reaction input devices, as well as receiving the results of the processing based on the proposed method .

7. Reaction input devices may be predetermined, at the option of the system operator, to operate and record uniformly, based on the proposed method, or with differentiated criteria and based on either the simple equivalent reaction or the complex equivalent reaction of diversity (distinctiveness) and uniqueness (individuality). It is also possible to configure each device differently, depending on its specific position in the entire system and/or the density and speed of the flow of users from it.

Claims (5)

Claims 1. Method of recording, processing and measuring the user satisfaction index, so as to provide the operator of the method with the possibility to draw, in real time and on the basis of the weighted parameters that he enters, reliable conclusions about the quality of the services provided, the which is characterized by the fact that, after the input of the reactions from the data input devices and their transfer to the system processor, the input reactions are analyzed and classified into groups of time density (d), based on the criteria set, with variable values, limits of the minor (DLmin) and major limiting density (DLmax) (8.1.) namely: · in the time density group (reaction input density value) that is less than the limit of the lower limit density (d<DLmin), so all reactions belonging to this group are considered to come from different (distinct) users and are all perceived as valid, • in the time density group (reaction input density value) that is greater than or equal to the limit of the lower limit density (DLmin≤d) and lower than the limit of the higher limit density (d<DLmax), i.e. between the lower limit and the higher limit density ( DLmin≤d<DLmax), so, since it is not certain whether the reactions come from the same or different users, each reaction is perceived with a fractional weight, with each reaction as a numerator and the number of reactions as a denominator, and finally • in the time group density (reaction input density value) that is greater than or equal to the limit of the major limiting density (d≥DLmax), whenever all reactions are considered to be from the same user and then: • if the number of reactions is greater than the set, with variable values, limit of reactions [Gmax), then all reactions are perceived as invalid, as a product of intentional misleading use; and if the number of reactions is less than the above set limit of reactions (Gmax], then further, if all the reactions are of the same type, only one reaction is perceived as valid, and if OL reactions are dissimilar, they are all perceived as invalid, as a product of intentional misleading use- 2. A method of recording, processing and measuring the user satisfaction index, according to claim 1, characterized in that the operator of the method, by adding suitable and convenient devices to the system, has the possibility of ascertaining the introduction of reactions from distinct [different] users [8.2.] and further for each distinct user, with the criteria set, with variable values, limit of the number of reactions [Gmax] that he enters, he has the ability to: • if the number of reactions is greater than the set limit of the number of reactions [number of reactions > Gmax], then reject all reactions as invalid, as a product of intentional misleading use • if the number of reactions is less than or equal to from the above set limit of the number of reactions (number of reactions ≤ Gmax], then further, if all the reactions are of the same type, to accept only one reaction as valid, and if the reactions are dissimilar, to accept only the last one as valid from them. 3. A method of recording, processing and measuring the user satisfaction index, according to claim 1, which is characterized in that the operator of the method, with the addition of suitable and convenient devices to the system, has the possibility to determine the introduction of reactions from individualized [unique] users [8.3.] and further for each individualized user, based on the set variable-valued concept of time interval (Tmin ), as the minimum time interval beyond which a unique user is allowed to have a different experience and is therefore able to validly introduce a new reaction into the system, as well as by the criterion of the maximum number of reactions from the same user within Tmin, which are considered not to be misleading (Hmax), has the ability to: • if the reactions from the single user occur outside the limits of the above time interval Tmin, then process and evaluate the reactions according to the rules of distinctness of dependent claim 2 • if the reactions from the unique user occur within the limits of the above time interval Tmin , then further, if the number of reactions is greater than the maximum number of reactions allowed by the same user (number of reactions > H max], then to reject all reactions as invalid, as the product of intentional misleading use, and if the number of reactions is less than or equal to the maximum number of reactions allowed by the same user (number of reactions ≤ Hmax], then process and evaluate the reactions according with its rules distinctness of dependent claim 2. 4. System which includes the means and devices necessary to implement the method according to claim 1, characterized by input devices - input reactions - user data, one or more information servers - network (servers), a database and a data processing software, which operates and processes the input data based on the proposed method of input density of reactions and in accordance with the criteria of simple and complex equivalent reaction. 5. System according to claim 4, characterized by: a) from input devices - data input and recording of user reactions, OL which may be table, floor, wall or portable, attached in a fixed way, on a horizontal or vertical surface, or operating portable, with a wired or wireless connection to the network server (server) that carry a series of option keys, which are placed in a linear arrangement, based on the degree (intensity) and characteristics (type) of the user's satisfaction or dissatisfaction and with a predetermined scale of calibration and grading of his options. These devices are connected to the network servers [servers], so that, through the latter, the imported data are transmitted to be processed by the software operating on the basis of the proposed method. b] by devices, which make it possible and convenient to recognize the diversity (distinctiveness) and individuality [uniqueness] of users, by exploiting various kinds of technological means of motion detection or technological possibilities of electronic identity recognition [e.g. through the utilization of beacon technology], respectively c] by one or more information servers or network [servers], which are connected according to the above on the one hand to the data input devices and on the other hand to the computer where the software of the method is installed. d] from a computer where the software of the proposed method is installed and e] from a database.