Universe Of Discourse Research Articles

Ancestralidade e identidade em Negrum3 - Uma pedagogia negra acerca de gênero e de sexualidade

Black Brazilian Cinema is a concept that affirms the presence and the black culture in cinema since the arrival of the first literate slaves in Brazil, at the same time that it questions the structure of cultural and knowledge production. In this article, we seek a pedagogical approach to black cinema. The objective is to work with the universe of meanings and discourses existing in the film NEGRUM3 (2018), by the filmmaker Diego Paulino. We consider that ancestry, converted into an analytical category, is a key concept to understand the discourse present in the analyzed film, in which it becomes evident the need to establish a dialogue with the African past, in an attempt to resignify the boundaries of gender and sexuality for Afrodiasporic populations in the present and in the future. In this sense, we analyze the film considering the concept of Pretagogia that values the body and the orality, as a producer of black epistemology and identity. We establish dialogues with black authors/authors and carry out an analysis that considers the film as an artistic work that grounds meanings in narrative structures by means of filmic, visual and sound apparatuses. Our article demarcates the pedagogical character of Brazilian Black Cinema and demonstrates how it can make paradigmatic changes through the way it portrays certain themes, making possible the reconstitution of black history and the establishment of a pedagogy of hope.

Group decision making based on weighted distance measure of linguistic intuitionistic fuzzy sets and the TOPSIS method

Linguistic intuitionistic fuzzy numbers (LIFNs) are useful to express the uncertainty of qualitative aspects of information, which have received many attentions in recent years. In this paper, we propose the distance measure of linguistic intuitionistic fuzzy sets (LIFSs), where the membership grade and the non-membership grade of each element in the universe of discourse belonging to a LIFS are represented by LIFNs. We also provide the proofs of the validity and some desirable properties of the proposed distance measure of LIFSs. Moreover, we also propose the weighted distance measure of LIFSs. Based on the proposed weighted distance measure of LIFSs and the “Technique for Order Preference by Similarity to Ideal Solution” (TOPSIS) method, we propose a new group decision making (GDM) approach in the environments of LIFNs. We also use some examples to illustrate the practicability and the feasibility of the proposed GDM approach. The proposed GDM approach can overcome the drawbacks of the existing GDM approaches, where they have the drawbacks that they cannot distinguish the ranking orders of the alternatives in some situations. It provides us a very useful method for dealing with GDM problems in the environments of LIFNs.

Fuzzy time series model based on red–black trees for stock index forecasting

Forecasting data is still an extensively investigated area of research specially in stock markets. The subjectivity of the elements that influence the market oscillation is the main challenge that any forecasting model faces. In this context, existing fuzzy models have attempted to increase forecasting accuracy in financial markets over the years. Fuzzy returns of the phenomenon under investigation helps to mitigate the subjective part of the financial market, specially regarding the human feeling influence over it. Although there are several data structures that can help to define the proper clusters from the universe of discourse of a fuzzy model, this paper proposes a novel fuzzy model from which the universe of discourse is based on a red–black tree (RBT) data structure so as to increase the possibilities of obtaining better predictions. The RBT data structure is a binary search three data structure that promotes a better balance, which allows a better accuracy in the forecasting results. The proposed model is compared to well known fuzzy models in the literature showing better forecasting results.

Three Dimensional Fuzzy Reliability for System Performance Evaluation

The research proposed a developed methodology for evaluation the system performance in uncertainty associated with traditional modelling methodology is focused on either load L or resistance R variability, but not both. A two-dimensional (2D) fuzzy set (traditional model), represent with the one dimension for universe of discourse (in x-direction) and the second dimension of his membership degree (in y-direction), is not full sufficient to handle both, load and resistance variation of system performance. The theoretical principle basis of this research is based on development of the three dimensional (3D) of fuzzy set that includes system performance variability in load and resistance from two dimensional. The proposed methodology (traditional model) extends the acceptance level of partial performance of system concept to a 3D-dimantion representation. This representation allows to capturing the changing of preferences of decision makers in load and resistance. The major objective of the research is to proposed the original methodology for evaluate system performance and management that is capable of; (a) addressing uncertainty caused by load and resistance variability and ambiguity; (b) integrating objective and subjective evaluation; and (c) assisting system performance management decision making based on a more detailed certainty evaluation of load and resistance variability. The study proposed two models for fuzzy reliability performance indexes: first traditional model included (I) 2D fuzzy reliability-vulnerability Rv index, (II) 2D fuzzy robustness Ro index; the second developed model (i) 3D fuzzy reliability-vulnerability Rv index, (ii) 3D fuzzy robustness Ro index; and comparing between them. These indexes have the capability of evaluating the operational performance of complex systems. Proposed methodology is illustrated by using the Al-Wathba Water Supply System (WWSS) as a case study.

Triangular Fuzzy Time Series for Two Factors High-order based on Interval Variations

Fuzzy time series (FTS) firstly introduced by Song and Chissom has been developed to forecast such as enrollment data, stock index, air pollution, etc. In forecasting FTS data several authors define universe of discourse using coefficient values with any integer or real number as a substitute. This study focuses on interval variation in order to get better evaluation. Coefficient values analyzed and compared in unequal partition intervals and equal partition intervals with base and triangular fuzzy membership functions applied in two factors high-order. The study implemented in the Shen-hu stock index data. The models evaluated by average forecasting error rate (AFER) and compared with existing methods. AFER value 0.28% for Shen-hu stock index daily data. Based on the result, this research can be used as a reference to determine the better interval and degree membership value in the fuzzy time series.

The Russian demography in 2010–2020: scientometric analysis according Elsevier data

The actuality of demographic research is permanently at high level both in Russia and in the world. The purpose of the study is to establish placement of studies and researchers in Russia on the world map of demographic science. The scientometric analysis was applied to the base of international quoting Scopus (Elsevier). The analysis of universe of discourse "Demography" was implemented using SciVal (Elsevier) on the basis of number of publications, number of viewing abstracts or full texts of publications, number of quoting, weighted-average impact-factor of journals. To compare trends according number of publications and quoting in the universe of discourse eLibrary data was used. The results of analysis demonstrated significant lagging of Russian publication activity on demography from countries-leaders on scientometric indices. At that, increased interest to Russian scientific results was established at the level of publications viewing. The most notable place in research of prominent topics in demography the Russian researchers assign to problematics of natality and inner migration. The number of directions targeting to ameliorate considered situation and to place the results of Russian demographic studies on world map of demographic science was proposed.

The Greek Mathematical Corpus: a Quantitative Appraisal

This paper assesses the Greek mathematical corpus as a whole using quantitative methods and discusses the methodological import of this approach. A number of dynamics within the corpus are also outlined. They corroborate the view that, in Greek antiquity, demonstrative and non-demonstrative mathematics belonged to one and the same universe of discourse.

Multidimensional fuzzy implications

Multidimensional fuzzy sets (MFS) is a new extension of fuzzy sets on which the membership values of an element in the discourse universe are increasingly ordered vectors on the set of real numbers in the interval [0,1]. This paper aims to investigate fuzzy negations and, mainly, fuzzy implications on the set of increasingly ordered vectors on [0,1], i.e. on L∞([0,1]), MFN and MFI in short, with respect to some partial order. In this paper we study partial orders, giving special attention to admissible orders on L∞([0,1]). In addition, some properties and methods to construct such operators from fuzzy negations and fuzzy implications, respectively, are provided and we demonstrate that the action of the group of automorphisms on fuzzy implications on L∞([0,1]) preserves several original properties of the implication. Finally, through a specific type of representable MFI, we are able to generate a class of MFN called natural m-negations.

A SURVEY REPORT ON PROJECTOMATE

The Agile Development approach to systems development is the new fundamental for developers. Twelve Principles supporting the Agile Manifesto were elaborated in support. Hence the team always has to look towards identifying and proposing appropriate reference disciplines which are manifest in the Agile Development Universe of Discourse. The Manifesto evokes some reference disciplines to support its various aspects. Why is it desirable and necessary to search for such reference disciplines? The answer is Alternative Software Development and Project Management approaches, such as Software Prototyping and Rapid Development and now including Agile Development, all seemed based on pragmatic experience and have been designed mostly by consultants and practitioners. While this is not in any way to denigrate or deprecate them, it is felt that support for these approaches needs to also come from other disciplines, such as management studies, leadership studies, and the like to give Agile Development a more solid theoretical and intellectual basis.

Kitainik axioms do not characterize the class of inclusion measures based on contrapositive fuzzy implications

In this short communication, we refute the conjecture by Fodor and Yager from [5] that the class of inclusion measures proposed by Kitainik coincides with that of inclusion measures based on contrapositive fuzzy implications. In particular, we show that the conjecture only holds when the considered universe of discourse is finite.

Relationship between Selic rate and Basel III parameters - A statistics approach and a fuzzy forecasting model

In this work the relationship between the Selic rate and some bank parameters defined by the so-called Basel Accords is studied. The cross-correlation between the Selic rate and the parameters is used to explain how these parameters affect the Selic rate and vice-versa so as to define the predictability of the Selic rate using (some of) these parameters as inputs. A model is then proposed for predicting the Selic rate based on some specific parameters using fuzzy logic ideas, which dealt with a partitioning of the universe of discourse using clusters related to the output data distribution. The proposed model is compared to four other known models in the literature and showed to have better performance in average compared to all other models.

Without Commitment to an Ontology, There Could Be No Causal Inference.

Without Commitment to an Ontology, There Could Be No Causal Inference.

Fuzzy Time Series Forecasting Approach using LSTM Model

In the present scenario, fuzzy time series forecasting (FTSF) is an interesting concept by the researchers to approach the uncertainty in the dataset. In the current study, we proposed a fuzzy long short term memory (FLSTM) model to forecast a wide range of time series (TS) dataset with less computational complexity. The present research mainly focuses on two issues such as 1) in order to obtain the number of intervals (NOIs) of the universe of discourse (UOD) the trend based discretization (TBD) approach is applied, and 2) the subscript of the fuzzy set associated with the crisp observation is considered to establish the fuzzy logical relationships (FLRs) for the proposed FLSTM model. To demonstrate the forecasting ability of the FLSTM model, six TS datasets with three profound FTSF models are considered. The empirical result analysis revealed that, in all measured the proposed model outperformed and showed better result than its alternatives. The outcome of the different FTSF models on different measures proves the outperformance of the FLSTM model than its competitors.

PERAMALAN PRODUKSI KARET INDONESIA MENGGUNAKAN FUZZY TIME SERIES DUA FAKTOR ORDE TINGGI RELASI PANJANG BERDASARKAN RASIO INTERVAL

The fuzzy time series method for forecasting continues to develop over time. This research discusses fuzzy time series, which considers two factors for high order using interval partitioning based on interval ratio with long relation construction for getting different accuracy in forecasting between combination method and existing method. The first step is the formation of the universe of speech. Second, divide the universe of discourse into several intervals using interval ratios. Third, fuzzification. Fourth, build fuzzy logic relations and fuzzy logic relation groups, and fifth, defuzzification. The previous methods would be compared with the fuzzy logic relation construction result. The simulation used Indonesian rubber production data for 2000-2020. The results and errors were tested using the average forecasting error rate (AFER). AFER value of the forecasting method is 1.863% obtained.Keywords: Forecasting, fuzzy time series, long relationMSC2020: 62M10, 62M20, 62M86, 03E72

Avoidance of operational sampling errors in drinking water analysis

AbstractThe internal audits carried out in the first half of 2019 in water laboratories as part of quality accreditation in accordance with ISO/IEC 17025:2017 showed a high frequency of adverse events in connection with sampling. These faults can be a consequence of a wide range of causes, and in some cases, the information about them can be insufficient or unclear. Considering that sampling has a major influence on the quality of the analytical results provided by water laboratories, this work presents a system for reporting and learning adverse events. Its aim is to record nonconformities, errors, and adverse events, making possible automatic data analysis aiming to ensure continuous improvement in operational sampling. The system is based on the Eindhoven Classification Model and enables automatic data analysis and reporting to identify the main causes of failure. Logic programming is used to represent knowledge and support the reasoning mechanisms to model the universe of discourse in scenarios of incomplete, contradicting, or even unknown information. In addition to suggesting solutions to the problem, the system provides formal evidence of the solutions presented, which will help to continuously improve drinking water quality and promote public health.

Particle swarm optimization based interval type 2 fuzzy logic control for motor rotor position control of artificial heart pump

Artificial heart pump (AHP) is employed to replace the native damaged heart and perform its functions. Bearingless brushless DC (BBLDC) motors are used for the implementation of the AHP. BBLDC motor is a highly nonlinear model with uncertainties and its mathematical model is hard to be found accurately. In this paper, BBLDC motor is simulated. Proportional plus integral (PI) controller is proposed to control the rotor suspension current. Furthermore, a type 2 proportional plus integral plus derivative-like fuzzy logic controller (T2 PID-Like FLC) is proposed to control the motor rotor (x, y) positions. Particle swarm optimization (PSO) technique is employed to find the best controller scaling factors and to optimize the controller inputs membership functions distribution within its universe of discourse. Simulation results showed enhancement in levitating the rotor to the required position, when using T2 PID-like FLC as compared with using type 1 PID-like fuzzy logic controller. The enhancement is measured using integral of absolute error (IAE) as a cost function to achieve 64.18% and 81.81% in the x and y axes respectively. The Performance of the motor is enhanced by 20%, which decreases the rotor oscillation and increases the ability to withstand the system disturbances and nonlinearity

Sci-FTS: Using soft clustering on Intrinsic Mode Functions to model Fuzzy Time Series

<h2>Abstract</h2> This manuscript introduces a new software, <i>sci</i>-FTS, which models time series by combining Signal Processing tools and Fuzzy Set Theory. Firstly, time series are decomposed into Intrinsic Mode Functions (IMFs), emphasizing instantaneous frequencies and amplitudes. Secondly, <i>sci</i>-FTS combines IMFs to extract deterministic influences, removing noises. Next, <i>sci</i>-FTS executes an algorithm that finds an adequate space partitioning to produce the fuzzy sets. Finally, Fuzzy Time Series steps are considered to predict observations. Our contributions are twofold: <i>sci</i>-FTS finds out similar patterns in observations to better model the universe of discourse; ii) models produced by <i>sci</i>-FTS overcome studies from the literature.

Developing a Fuzzy Time Series Forecasting Model Based on Hedge Algebras and Particle Swarm Optimization

In recent years, numerous fuzzy time series (FTS) forecasting models have been widely used. One of the important factors for obtaining high forecasting accuracy in fuzzy time series model is that the lengths of intervals in the universe of discourse. In this study, a hybrid forecasting model which uses hedge algebra (HA) and particle swarm optimization (PSO) is proposed to determine optimal lengths of intervals in FTS models. In that, HA is utilized as a tool to partition the universe of discourse into intervals with unequal-size corresponding to the semantic intervals calculated from the linguistic terms. After processing of generating the intervals, we define fuzzy sets based on the observation data of times series and use them to establish fuzzy relationship groups. Then, the proposed model is combined with the PSO technique to find the appropriate length of each interval with view to reaching the better forecasting accuracy rate. The performance of the proposed model is evaluated with the historical data of enrolments at the University of Alabama. The simulated results obtained indicate that the proposed model achieves higher forecasting accuracy compared other existing forecasting models and it can obtain better quality solutions for both the 1st-order and high-order FTS model.&#x0D; HIGHLIGHTS&#x0D; &#x0D; In fuzzy time series forecasting model, the length of intervals and the order of fuzzy relationships are two critical factors for forecasting accuracy&#x0D; Hedge algebra and PSO are utilized as a tool to partition the universe of discourse into intervals with unequal - size corresponding to the semantic intervals calculated from the linguistic terms&#x0D; The defuzzification principles are used to calculate the forecasting results based on the fuzzy relationship groups&#x0D; &#x0D; GRAPHICAL ABSTRACT

Diversification of the defense industry: The state of research

Subject. This article reviews various research works in the field of diversification of defense enterprises, namely their topics, methods, and results. Objectives. The article aims to systematize the trends of research in the subject area under consideration. Methods. For the study, I used bibliometric and sampling analyses of relevant publications related to the universe of discourse. Results. The article identifies areas of research indicating the search for mechanisms for financial and organizational support of diversification, and the observation of current trends in the procurement of weapons and technologies used. Conclusions. Keyword analysis has limited potential as a domain description tool. Works on industry diversification describe success factors in a rather abstract way. All special issues are looked into in detail in the relevant thematic areas, but the words diversification or industry are not used.

The Prayer. Structure and Universe of Discourse

The prayer is a particular type of text, with a particular structure and a specific purpose. This paper aims to address the prayer from the perspective of text linguistics developed by Eugeniu Coșeriu, analyzing the textual structure of the prayer and, in particular, one of the specific mechanisms that contribute to the articulation of its meaning, i.e. the relative clause. The starting point of our approach – and its fundamental theoretical landmark – is the study of Eugeniu Coșeriu Orationis fundamenta. The Prayer as a Text, in which Eugeniu Coșeriu analyzes the prayer Our Father from the viewpoint of text linguistics as hermeneutics of the meaning (Coșeriu 2010). This paper indicates that relative clauses have a special status within the textual structure of the prayer. In terms of semantics, it can be emphasized that relative clauses have a significant role in articulating textual meaning, therefore in the intrinsic functionality of the text. The concept of the “universe of discourse”, which represents a system of meaning that grants validity and meaning (Coșeriu 2013, 69), also becomes a relevant landmark to our research.