Universe Of Discourse Research Articles

An Interval Type-2 Fuzzy Logic System for Stock Index Forecasting Based on Fuzzy Time Series and a Fuzzy Logical Relationship Map

This paper proposes an interval type-2 fuzzy logic system (IT2FLS) for stock index forecasting based on a fuzzy time series and a fuzzy logical relationship map (FLRM). First, variations within the data are found with the maximum and minimum variations used for the interval settings of the universe of discourse. The time series variations are fuzzified into fuzzy sets in order to form fuzzy logical relationships, which are then used to construct the FLRM. Second, the input interval type-2 fuzzy sets (IT2FSs) and the output intervals of the IT2FLS are defined based on the maximum and minimum variations found. Third, the data variation between time t − 1 and time t, and the input IT2FSs are used as input for the IT2FLS, and the output of the IT2FLS is the forecasting variation, which is found between time t and time t + 1. An output interval is formed using the IT2FLS rule-base based on the FLRM. Finally, the forecast value at time t + 1 is defined as the data point at time t plus the forecast variation. In this paper, the proposed method is applied to data from the Taiwan Stock Exchange Capitalization Weighted Stock Index, the Dow Jones Industrial Average, and the National Association of Securities Dealers Automated Quotation. Existing methods are then compared with the proposed method using Wilcoxon non-parametric statistical testing, as opposed to simply comparing the average root-mean-square error. Based on the statistical analysis results, the proposed method is found to typically outperform the other methods.

O texto literário como corpus para análise lexical: "O Púcaro Búlgaro", de Campos de Carvalho

O universo de discurso literário engloba um sem-número de outros universos de discurso, transformando-o em um rico e frutífero ambiente para análises linguísticas, sobretudo no nível lexical. Este trabalho, portanto, de caráter modelar, tem como objetivo demonstrar de que maneiras o texto literário se apresenta como corpus para uma análise linguística. Por trabalhar com a arte, além da comunicação, o autor literário deve sempre objetivar a expressividade no uso da língua. É o que tentaremos demonstrar, utilizando como exemplo o romance O Púcaro Búlgaro, de Campos de Carvalho, uma narrativa composta, essencialmente, pela denúncia, renúncia e afastamento das questões de ordem lógica do mundo histórico e social. Para isso, o presente artigo retoma conceitos gerais a respeito da lexicologia e lexicografia, resume questões gerais a respeito do texto literário, e revisa alguns dos principais estudos recentes que trabalharam essa interface. Ao final, são apresentados modelos de análise lexical com a obra literária supracitada.

Time Series Seasonal Analysis Based on Fuzzy Transforms

We define a new seasonal forecasting method based on fuzzy transforms. We use the best interpolating polynomial for extracting the trend of the time series and generate the inverse fuzzy transform on each seasonal subset of the universe of discourse for predicting the value of an assigned output. In the first example, we use the daily weather dataset of the municipality of Naples (Italy) starting from data collected from 2003 to 2015 making predictions on mean temperature, max temperature and min temperature, all considered daily. In the second example, we use the daily mean temperature measured at the weather station “Chiavari Caperana” in the Liguria Italian Region. We compare the results with our method, the average seasonal variation, Auto Regressive Integrated Moving Average (ARIMA) and the usual fuzzy transforms concluding that the best results are obtained under our approach in both examples. In addition, the comparison results show that, for seasonal time series that have no consistent irregular variations, the performance obtained with our method is comparable with the ones obtained using Support Vector Machine- and Artificial Neural Networks-based models.

The paradoxical hybridity of words

abstractWords can be matched with the concept of sign (correspondence of a signifier to a signified) as long as they act as symbol-words endowed with some semantic self-sufficiency. But in discourse, they lose their wholeness as symbol-words and metamorphose intowording-symbols.They, suddenly, appear as mere signifier entities with a more or less loose allusion to their status as cultural symbols. In discourse, words are no longer signs buttoolscovering ephemeral collections ofneurosemes: the link of the sign breaks as soon as discourse takes over. The referential potential is no longer the schematic meaning issued from culture, but the universe of discourse under construction. This is why any attempt to account for meaning in language must integrate the neural process of meaning creation. It is now established that meaning is not the result of language activity but the result of cognition. However, whatlanguagedoes,viadiscourse, is to make this meaning communicable. For all these reasons, the task of linguistics should be to investigate the relationship between cognition and linguistic output in order to shed light on all the cognitive traces left within the surface strings. The role of morphosyntax thus has to be re-evaluated in this light.

Improving Posture Accuracy of Non-Holonomic Mobile Robot System with Variable Universe of Discourse

This paper presents a method to decrease imprecision and inaccuracy that have the tendency to influence the posture of non-holonomic mobile by using the adaptive tuning of universe of discourse. As such, the primary objective of the study is to force the posture error of x(t), y(t) and θ(t) towards zero. Hence, for each step of tuning the fuzzy domain, about 20% of imprecision and inaccuracy had been added automatically into the variable universe fuzzy, while the control input was bound via scaling gain. Furthermore, the experimental results showed that the tuning of universe fuzzy parameters could increase the performance of the system from the aspects of response time and error for steady state through better control of inaccuracy. Besides, the domains of universe fuzzy input [-4,4] and output [0,6] exhibited good performance in inching towards zero values as the steady state error was about 1% for x(t) position, 0.02% for y(t) position, and 0.16% for θ(t) orientation, whereas the posture error in the given reference was about 0.0002%.

A Scientific Theology? A Programmatic Account of the Problems and Prospects for Confessional and Scientific Theology

There are at least three kinds of arguments against the possibility of scientific and confessional theology: The first kind of argument tries to show that there is no universe of discourse that theology could investigate as a scientific discipline. The second kind of argument is not directed against the existence of theology’s putative universe of discourse. Instead, this kind of argument tries to show that even if there is a universe of discourse theology could investigate, it fails to do so by using scientific methods. The third kind of argument tries to show that even if theology has a universe of discourse and deploys scientific methods, it is still not a scientific discipline because it conflicts with the historical and natural sciences that are supposed to be more reliable than theology. In what follows, I clarify the importance of the scientificness of confessional theology for the plausibility of religious worldviews. I analyse the arguments put forward against the possibility of scientific and confessional theology. I indicate systematic weaknesses in the arguments that the theologian should use to show that they do not stand up to scrutiny and suggest a programmatic list of tasks the theologian has to engage in to demonstrate that scientific and confessional theology is indeed possible, if not already at hand

Navigating an Immersive Narratology

In direct response to the rise in fake news as a socio-cultural and political phenomenon, this article presents an analysis of the factors that may help to explain the reception of fake news. In addition, recent pronouncements made by the Trump White House seem to challenge the nature of an objective truth. An immersive narratology emphasizes that different universes of discourse can intermingle and overlap, with fact and fiction becoming difficult to distinguish in our increasingly mediated lives. A tenable definition of fake news is offered prior to exploring historical antecedents of fake news. Persuasion, construction, immersion, distribution, and polarization represent the core factors that demystify the reception of fake news regardless as to whether an individual believes a story. A concluding discussion offers a critical evaluation of the potential of fake news to augment the news media landscape in the coming years.

Foucault in English

It is something of a cliché to affirm that translations into English are almost always domestications, privileging fluency and naturalness over fidelity to the source text. However, back in the 1970s, many of Michel Foucault’s major texts, which were introduced to the English-speaking public for the first time through Alan Sheridan Smith’s translations for Tavistock Publications, were not domesticated at all. Despite the fact that the originals are grounded in a non-empiricist theory of knowledge and use terms drawn from a universe of discourse that would have been completely alien in the English-speaking world, these translations closely follow the patterns of the French, with few or no concessions to the target reader’s knowledge and expectations. This paper analyses passages from Sheridan Smith’s English translations ofLes Mots et les chosesandL’Archéologie du savoirin order to discuss the long-term effects of this translation strategy. It then goes on to compare and assess two very different translations of Foucault’s lectureL’ Ordre du discours(1970), an early one by Rupert Swyer(1971), which brings the text to the English reader, and a later one byIan McLeod (1981), which obliges the reader to go to the text. The paper concludes by reiterating the need for Anglophone academic culture to open up to foreign perspectives, and suggests, following Goethe (Book of West and East,1819) that new epistemes are best introduced gradually in order to avoid alienating or confusing a public that might not be ready for them.

TIME-VARYING FUZZY SETS BASED ON A GAUSSIAN MEMBERSHIP FUNCTIONS FOR DEVELOPING FUZZY CONTROLLER

The paper presents a novel type of fuzzy sets, called time-Varying Fuzzy Sets (VFS). These fuzzy sets are based on the Gaussian membership functions, they are depended on the error and they are characterized by the displacement of the kernels to both right and left side of the universe of discourse, the two extremes kernels of the universe are fixed for all time. In this work we focus only on the midpoint movement of the universe, all points of supports (kernels) are shifted by the same distance and in the same direction excepted the two extremes points of supports are always fixed for all computation time. To show the effectiveness of this approach we used these VFS to develop a PDC (Parallel Distributed Compensation) fuzzy controller for a nonlinear and certain system in continuous time described by the T-S fuzzy model, the parameters of the functions defining the midpoint movements are optimized by a PSO (Particle Swarm Optimization) approach.

Optimal scale selection in dynamic multi-scale decision tables based on sequential three-way decisions

It has been recognized that optimal scale selection in rough set theory is one of the most important problems in the study of multi-scale decision tables. Recently, much attention has been paid to this issue and quite a few appealing results have been obtained. However, the existing results are not applicable to the situation where the objects or attributes in a multi-scale decision table are sequentially updated, although this situation is frequently encountered in many real-world problems. Motivated by the fact that sequential three-way decisions are an effective mathematical tool in dealing with the data with information sequentially updated, we therefore use this methodology to investigate the optimal scale selection problem in a dynamic multi-scale decision table. Specifically, a sequential three-way decision model is first developed in multi-scale information tables, which can be viewed as multi-granularity of the universe of discourse. Then, this model is employed to present an optimal scale selection approach for such multi-scale decision tables that the number of objects is increasing. Finally, numerical experiments are conducted to evaluate the performance of the proposed optimal scale selection approach. Compared to the existing methods, the current approach does not need to consider the consistent and the inconsistent multi-scale decision tables separately and is especially suitable for updating the optimal scales of the multi-scale decision tables with new objects added.

Implementasi Metode Fuzzy Time Series Cheng untuk prediksi Kosentrasi Gas NO2 Di Udara

The forecasting process is essential for determining air quality to monitor NO2 gas in the air. The research aims to develop prediction information system of NO2 gas in air. The method used is Fuzzy Time Series Cheng method. The process of acquiring NO2 gas data is integrated with Multichannel-Multistasion. The data acquisition process uses Wireless Sensor Network technology via broadband internet that is sent and stored in an online database form on the web server. Recorded data is used as material for prediction. Acquisition result of NO2 gas data is obtained from the sensor which is sent to the web server in the data base in the network by on line, then for futher it is predicted using fuzzy time series Cheng applying re-divide to the results of intervals the first partition of the value of the universe of discourse by historical data fuzzification to determine Fuzzy Logical Relationship dan Fuzzy Logical Relationship Group, so that is obtained result value prediction of NO2 gas concentration. By using 36 sample data of NO2 gas, it is obtained that the value of root of mean squared error of 2.08%. This result indicates that the method of Fuzzy Time Series Cheng is good enough to be used in predicting the NO2 gas.

A two-phase method of forming a granular representation of signals

This study focuses on a granular representation of signals. The development process dwells upon the use of the principle of justifiable granularity encountered in Granular Computing and the least square error method. This process consists of two phases where the construction of granular representatives of a family of signals (temporal data) is realized by invoking the design at the local and global level. At the local design level involving individual elements of the universe of discourse (time moments), the principle of justifiable granularity is applied to construct (a vertical part) information granules. At the global level, the least square error method is invoked to develop the bounds (envelopes) of the information granules already formed at the local level. Experimental studies are reported for the granular representation of synthetic data and publicly available ECG signals. Furthermore we demonstrate that the proposed approach can be used to construct fuzzy sets of type-2.

Modeling, stability analysis, and computational aspects of some simplest nonlinear fuzzy two-term controllers derived via center of area/gravity defuzzification

The mathematical models reported in the literature so far have been found using Center of Sums (CoS) defuzzification method only. It appears that no one has found models using Center of Area (CoA) or Center of Gravity (CoG) defuzzification method. Although there have been some works reported to deal with modeling of fuzzy controllers via Centroid method, all of them have in fact used CoS method only. In this paper, for the first time mathematical models of the simplest Mamdani type fuzzy Proportional Integral (PI)/Proportional Derivative (PD) controllers via CoG defuzzification are presented. L-type and Γ-type membership functions over different Universes of Discourse (UoDs) are considered for the input variables. L-type, Π-type and Γ-type membership functions are considered for the output variable. Three linear fuzzy control rules relating all four input fuzzy sets to three output fuzzy sets are chosen. Two triangular norms namely Algebraic Product (AP) and Minimum (Min), Maximum (Max) triangular co-norm, and two inference methods, Larsen Product (LP) and Mamdani Minimum (MM), are used. Properties of the models are studied. Stability analysis of closed-loop systems containing one of these controller models in the loop is done using the Small Gain theorem. Since digital controllers are implemented using digital processors, computational and memory requirements of these fuzzy controllers and conventional (nonfuzzy) controllers are compared. A rough estimate of the computational time taken by the digital computer while implementing any of these discrete-time fuzzy controllers is given. Two nonlinear plants are considered to show the superiority of the simplest fuzzy controller obtained using CoA or CoG defuzzification method over the simplest fuzzy controller obtained using CoS method and reported recently. Real-time implementation of one of the developed controller models is done on coupled tank experimental setup to show the feasibility of the developed model.

A novel and fast MIMO fuzzy inference system based on a class of fuzzy clustering algorithms with interpretability and complexity analysis

CFIS is more accurate and faster than other FISs.CFIS is more interpretable and less complex than other FISs.Fuzzy clusters on dense regions of data in input space serve as CFIS rules.THEN part of CFIS accommodates any function of input variables.IF part of CFIS needs no parameter identification. A data driven Fuzzy Inference System (FIS) employs Membership Functions (MFs) with adjustable parameters in its IF part to fuzzify the input data. The input space is partitioned simply by dividing universe of discourse of each input variable into some fuzzy subspaces. The MFs are then defined on the fuzzy subspaces of the input variables. Parameters of the MFs are tuned for maximum accuracy of the system (which demands high runtime) without considering the data structure which impairs interpretability of the FIS and degenerates the system into a black-box tool. Such a FIS does not represent actual structure of the data and its MFs are not necessarily in accord with the data distribution in the input space. In addition, the FIS suffers from exponential complexity of order O(Tr) where T is number of linguistic terms (number of subspaces on the universe of discourse of input variables) and r is number of input variables. This article presents a novel Multiple-Input and Multiple-Output Clustering based Fuzzy Inference System (MIMO CFIS) which is made directly from a class of fuzzy clustering algorithms to overcome these shortcomings. CFIS identifies dense regions of the input data using fuzzy clustering and then places a cluster on each of these regions. These fuzzy clusters represent actual structure of the data and serve as fuzzy rules in the rule base of CFIS and provide MFs that exactly fit the dense regions of the data that makes the system more interpretable and avoids redundant rules. These MFs are normal, convex, and continuous and have no parameter to be tuned (which makes CFIS much faster than other FISs) and fuzzify the input data according to their membership in the clusters. THEN part of CFIS is generalized form of THEN part of Takagi-Sugeno (TS) fuzzy system which accommodates any function of input variables. Despite less number of adjustable parameters, testing error of CFIS is less than that of TS system and its modified versions. Moreover, number of fuzzy rules in CFIS rule base is the same as the number of linguistic terms (or fuzzy clusters) and consequently its complexity is of orderO(T). Also, CFIS is a MIMO system and avoids inconsistent (contradictory) rules by generating well-separated fuzzy clusters whereas TS system is MISO and never guarantees generation of consistent rules. In addition, CFIS satisfies most of the interpretability criteria of FISs.

A novel fuzzy time series forecasting method based on the improved artificial fish swarm optimization algorithm

Recently, many forecasting methods have been proposed for the analysis of fuzzy time series. The main factors that affect the results of the forecasting of these models are partition universe of discourse and determination of fuzzy relations. In this paper, a novel fuzzy time series forecasting method which uses a hybrid artificial fish swarm optimization algorithm for the determination of interval lengths is proposed. Firstly, we introduce the chemotactic behavior of Bacterial foraging optimization into foraging behavior. Secondly, the Levy flight is used as the mutation operator for a mutation strategy. Finally, the new proposed method is applied to a fuzzy time series forecasting and the experimental results show that the proposed model obtain better forecasting results than those of other existing models. It proves the feasibility and validity of above-mentioned approaches.

Coordinated Chassis Control Based on Vehicle Lateral Acceleration Using Fuzzy Logic Control

This paper presents an advanced coordination of integrated control system which consist of three different controllers namely Electronic Stability Control (ESC), Active Front Steering (AFS), and Active Suspension (AS) using Fuzzy Logic Control (FLC) in order to improve vehicle handling, cornering stability, and rollover prevention with anti-lock brakingsystem (ABS) to avoid wheel locking during generating differential braking by ESC control. Based on a well-developed and validated fourteen degrees of freedom full vehicle model with non-linear tire characteristics, a reference yaw-roll plane vehicle model is introduced to compare and therefore control the yaw rate, side slip angle, and roll angle of the vehicle body. For rollover prevention indices, the dynamic load transfer ratio is defined to check the effectiveness of the proposed controller. The Coordination chassis control is based on the lateral acceleration value as input to FLC, and the outputs are the increment factors to the three controllers varying from zero to one. Three membership functions are chosen to represent the lateral acceleration as input to the supervisor controller, to define the control authority for each actuator. The universe of discourse for each membership function is selected according to the study of the effect of eachcontroller stand alone in vehicle performance. The numerical modelling is carried out through the MATLAB / Simulink environment which suits the control and optimization process. Different standard test maneuvers namely J-turn,fishhook, and double lane change have been carried out by considering standard test maneuvers with different driving speeds. The simulation results are compared during three cases namely, the uncontrolled system, the combined controller, and the proposed coordinated controller. The results show a substantial improvement of the vehicle stability in terms ofvehicle lateral acceleration, side slip angle, yaw rate, roll angle, and the for the developed coordinated controller compared to combined controller or the conventional system without control.

Clues as information, the semiotic gap, and inferential investigative processes, or making a (very small) contribution to the new discipline, Forensic Semiotics

AbstractIn this article, we try to contribute to the new discipline Forensic Semiotics – a discipline introduced by the Canadian polymath Marcel Danesi. We focus on clues as information and criminal investigative processes as inferential. These inferential (and Peircean) processes have a certain complexity consisting of the interrelation between the collateral observations of the investigator, e. g., his background knowledge concerning criminal and technical analysis, the context that the investigator acts within or in relation to (the universe of discourse), e. g., the scene of crime or the criminal law, as well as the clues as information that will cause the inferential processes in the first place. We believe that this focus can tell us something about crime solving that is not just sensitive to epistemological factors (how to know), but also ontological (what to know) and normative factors as well (how to value the processes of crime solving).

A multi-factor and high-order stock forecast model based on Type-2 FTS using cuckoo search and self-adaptive harmony search

With the developing economy, an increasing number of factors and high-order data have considerably influenced fluctuations in stock. The fuzzy time series (Type-1) model has been recently studied by many scholars. In this study, an enhanced model on the study of stock forecasting is proposed. This model is a multi-factor and high-order time series forecast model that the Type-2 fuzzy time series model by integrating several other factors. We first employ the cuckoo search algorithm instead of the conventional average method to partition the universe of discourse, and then propose a novel self-adaptive harmony search algorithm to optimize the high-order weight. Furthermore, the Shanghai Stock Exchange Composite Index and Taiwan Stock Exchange Capitalization Weighted Stock Index are used to verify the better performance of the proposed method. Experimental results show that the proposed method outperforms other baseline methods.

Multigranulation fuzzy rough set over two universes and its application to decision making

The original Pawlak’s rough set approach based on indiscernibility relation (single granularity) has been extended to multigranulation rough set structure in the recent years. Multigranulation rough set approach has become a flouring research direction in rough set theory. This paper considers rough approximation of a fuzzy concept under the framework of multigranulation over two different universes of discourse, i.e., multigranulation fuzzy rough set models over two universes. We present three types of multigranulation fuzzy rough set over two universes by the constructive approach, respectively. Some interesting properties of the proposed models are discussed and also the interrelationships between the proposed models and the existing rough set models are given. We then propose a new approach to a kind of multiple criteria group decision making problem based on multigranulation fuzzy rough set model over two universes. The decision rules and algorithm of the proposed method are given and an example of handling multiple criteria group decision making problem of clothes ranking illustrates this approach. The main contribution of this paper is twofold. One is to establish the multigranulation fuzzy rough set theory over two universes. Another is to try presenting a new approach to multiple criteria group decision making based on multigranulation fuzzy rough set over two universes. The proposed models not only enrich the theory of multigranulation rough set but also make a tentative to provide a new perspective for multiple criteria group decision making with uncertainty.

Der er en verden uden for sproget. Om at sikre kvalitet i oversættelse af fagsproglige tekster

Translation of LSP-texts is not merely the transfer of "the meanings of a profession" but also the creation of a new text. Therefore, an important parameter is the neutrality of the translated text: It should observe norms and standards of original texts of a profession, written in the given target language. As many translations show, however, translators often seem not to be acquainted with such norms and standards, a subject which is normally not dealt with in dictionaries. Since a professional world has a restricted professional universe of discourse, being reflected in the - quite stereotype - texts of the profession (which is shown in the present paper with respect to technical texts), it should be possible for the translator trainee to learn what professional texts look like through the study of genuine texts of a profession, getting, at the same time, a certain understanding of the professional world reflected in the texts. It is suggested that, in teaching translation, the focus should at an early stage be put on texts of the target language, as this would secure the familiarity of the translator trainee with genuine structures of the target language before actually beginning the translation of source texts.