Emotions and a Prior Knowledge Representation in Artificial General Intelligence

In this paper a prior knowledge representation for Artificial General Intelligence is proposed based on fuzzy rules using linguistic variables. These linguistic variables may be produced by neural network. Rules may be used for generation of basic emotions – positive and negative, which influence on planning and execution of behavior. The representation of Three Laws of Robotics as such prior knowledge is suggested as highest level of motivation in AGI.

'Er's from off:the indexicalization and enregisterment of Black Country dialect

This article considers how conscious use of dialect in writing is an intentional act and can be accounted for through the notion of enregisterment. It does this by exploring the value of dialect in social and ideological contexts in relation to a regional dialect of British speech, that of the Black Country in the West Midlands region of England. The article provides a summary of recent directions in sociolinguistic research and an overview of the Black Country speech community, including a summary of its distinctive linguistic variables. This description is then used as an external evaluation of the authenticity of written representations of Black Country speech and the items enregistered in writing. Analysis of three written texts taken from three different genres across a time span of 30 years reveals the extent to which identified linguistic features are drawn upon in each one of the three texts and the extent to which any one is enregisterd across all three. The article discusses the social and linguistic contexts within which the writing occurs by way of accounting for their enregisterment as markers of identity linked to region and place. It also considers the ways in which the texts juxtapose norms and values of those "within" the community with those from "outside" the community in ways that subvert traditional notions of linguistic hierarchy.

Dialect variation

Relatively little research on dialect variation has been based on corpora of naturally occurring language. Instead, dialect variation has been studied based primarily on language elicited through questionnaires and interviews. Eliciting dialect data has several advantages, including allowing for dialectologists to select individual informants, control the communicative situation in which language is collected, elicit rare forms directly, and make high-quality audio recordings. Although far less common, a corpus-based approach to data collection also has several advantages, including allowing for dialectologists to collect large amounts of data from a large number of informants, observe dialect variation across a range of communicative situations, and analyze quantitative linguistic variation in large samples of natural language. Although both approaches allow for dialect variation to be observed, they provide different perspectives on language variation and change. The corpus- based approach to dialectology has therefore produced a number of new findings, many of which challenge traditional assumptions about the nature of dialect variation. Most important, this research has shown that dialect variation involves a wider range of linguistic variables and exists across a wider range of language varieties than has previously been assumed. The goal of this chapter is to introduce this emerging approach to dialectology. The first part of this chapter reviews the growing body of research that analyzes dialect variation in corpora, including research on variation across nations, regions, genders, ages, and classes, in both speech and writing, and from both a synchronic and diachronic perspective, with a focus on dialect variation in the English language. Although collections of language data elicited through interviews and questionnaires are now commonly referred to as corpora in sociolinguistics and dialectology (e.g. see Bauer 2002; Tagliamonte 2006; Kretzschmar et al. 2006; D'Arcy 2011), this review focuses on corpora of naturally occurring texts and discourse. The second part of this chapter presents the results of an analysis of variation in not contraction across region, gender, and time in a corpus of American English letters to the editor in order to exemplify a corpus-based approach to dialectology.

O /R/ em posição de coda silábica na cidade de Uberlândia

The aim of this research is to describe and analyze the realization of the /R/ at the end of the syllable (coda) in the city of Uberlândia-MG, taking into account variationist aspects and possible phonological phenomena that permeates the variable realization of this segment. We used the labovian variationist methodology, that gave us the needed support to investigate and systematize the variation of one linguistic community. The corpus was compound by 5139 occurrences of /R/, which 2528 were retroflex realizations, 2480 were deletions and 132 were occurrences of other segments. The informants of this research were stratified by: sex; age group; scholarly; they were born in Uberlândia or they arrived in this city before fifth birthday. Beyond the extralinguistic variables (sex, age group and scholarty), we established as linguistic variables: following context; previous context; tonicity of syllable; lexical item; coda position in the syllable; and, at last, the word size. After the statistic analisis computed by the Goldvarb software, the favoring contexts to the retroflex realization were: coronal segments in the following context; labial segments in the previous context; unstressed syllables; nouns and others (non verbs); and words with one syllable. The favoring contexts to deletion were: dorsal segments int the following context and verbs. The extra linguistic variables favored the variation less scholarty. So, the factors male sex and age group from 26 to 49 years favored the retroflex variant, while the factors female and the age group with more than 49 years favored the deletion.

Um modelo de suporte à comunicação de agentes para tratamento de informação imprecisa baseada em sinônimos

Este trabalho propõe o desenvolvimento de um modelo de suporte á comunicação entre agentes e uma Ontologia com informações imprecisas. Os conceitos desta ontologia podem possuir sinônimos possibilitando a interpretação de termos linguísticos imprecisos. Tal problema é relacionado às questões de desenvolvimento da comunicação em Sistemas Multiagentes, possuindo como referência uma base de conhecimento da qual estes agentes possam requisitar informações. Neste estudo, a premissa do modelo é o de ser útil como componente na utilização por desenvolvedores que queiram utilizar de forma simplificada uma conexão com uma Ontologia para dar suporte na comunicação. Para o presente estudo são discutidos os conceitos sobre a comunicação no ambiente multiagentes. Também é realizada uma revisão sobre o desenvolvimento de Ontologias, de forma a criar uma ontologia para os agentes. A lógica nebulosa, baseado em variáveis linguísticas, servirá como modeladora da imprecisão da informação, dando suporte a essa questão com a Ontologia e a comunicação. De forma a validar o modelo proposto, é realizado um estudo de caso no sistema multiagentes das hortas urbanas do Parque San Jerónimo, de Sevilha, Espanha.

Application of fuzzy logic for the evaluation of livestock slaughtering

A lógica fuzzy admite infinitos valores lógicos intermediários entre o falso e o verdadeiro. Com esse princípio, foi elaborado neste trabalho um sistema baseado em regras fuzzy, que indicam o índice de massa corporal de animais ruminantes com objetivo de obter o melhor momento para o abate. O sistema fuzzy desenvolvido teve como entradas as variáveis massa e altura, e a saída um novo índice de massa corporal, denominado Índice de Massa Corporal Fuzzy (IMC Fuzzy), que poderá servir como um sistema de detecção do momento de abate de bovinos, comparando-os entre si através das variáveis linguísticas )Muito BaixaM, ,BaixaB, ,MédiaM, ,AltaA e Muito AltaM. Para a demonstração e aplicação da utilização deste sistema fuzzy, foi feita uma análise de 147 vacas da raça Nelore, determinando os valores do IMC Fuzzy para cada animal e indicando a situação de massa corpórea de todo o rebanho. A validação realizada do sistema foi baseado em uma análise estatística, utilizando o coeficiente de correlação de Pearson 0,923, representando alta correlação positiva e indicando que o método proposto está adequado. Desta forma, o presente método possibilita a avaliação do rebanho, comparando cada animal do rebanho com seus pares do grupo, fornecendo desta forma um método quantitativo de tomada de decisão para o pecuarista. Também é possível concluir que o presente trabalho estabeleceu um método computacional baseado na lógica fuzzy capaz de imitar parte do raciocínio humano e interpretar o índice de massa corporal de qualquer tipo de espécie bovina e em qualquer região do País.

Triangular Linguistic Fuzzy based performance measurement model for supply chain to assess leanness attributes

Increasing global competitiveness worldwide has forced manufacturing organizations to produce high-quality products more quickly and at a competitive cost. In order to reach these goals, they need good quality components from suppliers at optimum price and lead time. This actually forced all the companies to adapt different improvement practices such as lean manufacturing, Just in Time (JIT) and effective supply chain management. Applying new improvement techniques and tools cause higher establishment costs and more Information Delay (ID). On the contrary, these new techniques may reduce the risk of stock outs and affect supply chain flexibility to give a better overall performance. But industry people are unable to measure the overall affects of those improvement techniques with a standard evaluation model .So an effective overall supply chain performance evaluation model is essential for suppliers as well as manufacturers to assess their companies under different supply chain strategies. However, literature on lean supply chain performance evaluation is comparatively limited. Moreover, most of the models assumed random values for performance variables. The purpose of this paper is to propose an effective supply chain performance evaluation model using triangular linguistic fuzzy numbers and to recommend optimum ranges for performance variables for lean implementation. The model initially considers all the supply chain performance criteria (input, output and flexibility), converts the values to triangular linguistic fuzzy numbers and evaluates overall supply chain performance under different situations. Results show that with the proposed performance measurement model, improvement area for each variable can be accurately identified.

What variables condition syntactic transfer? A look at the L3 initial state

This study investigates transfer at the third-language (L3) initial state, testing between the following possibilities: (1) the first language (L1) transfer hypothesis (an L1 effect for all adult acquisition), (2) the second language (L2) transfer hypothesis, where the L2 blocks L1 transfer (often referred to in the recent literature as the ‘L2 status factor’; Williams and Hammarberg, 1998), and (3) the Cumulative Enhancement Model (Flynn et al., 2004), which proposes selective transfer from all previous linguistic knowledge. We provide data from successful English-speaking learners of L2 Spanish at the initial state of acquiring L3 French and L3 Italian relating to properties of the Null-Subject Parameter (e.g. Chomsky, 1981; Rizzi, 1982). We compare these groups to each other, as well as to groups of English learners of L2 French and L2 Italian at the initial state, and conclude that the data are consistent with the predictions of the ‘L2 status factor’. However, we discuss an alternative possible interpretation based on (psycho)typologically-motivated transfer (borrowing from Kellerman, 1983), providing a methodology for future research in this domain to meaningfully tease apart the ‘L2 status factor’ from this alternative account.

Linguistic epistemology and the notion of monolingualism

This article has several interrelated goals, all of which relate to an attempt at understanding why monolingualism is taken to be the default norm in linguistic inquiry (from sociolinguistics to formal linguistic theorizing). With others, I will take the position that comparing instances of multilingualism to so-called monolingualism is an unfair and inevitably inaccurate comparison since, among other variables, the social environments and access to input of multilinguals compared to monolinguals is most often unavoidably different (cf. Cruz-Ferreira 2006; Edwards 2004). Additionally, I will attempt to demonstrate that even so-called monolinguals have access to a variety of grammars related to different registers of speech and, therefore, are not truly monolingual in the sense that they poses one monolithic grammatical competence. Taken together, the present discussion questions both the default status of monolingualism as well as the functional adequacy of the term monolingualism.

Fuzzy linguistic model for bioelectrical impedance vector analysis

Backgrounds Ea aims: The boundaries between the categories of body composition provided by vectorial analysis of bioimpedance are not well defined. In this paper, fuzzy sets theory was used for modeling such uncertainty. Methods: An Italian database with 179 cases 18-70 years was divided randomly into developing (n = 20) and testing samples (n = 159). From the 159 registries of the testing sample, 99 contributed with unequivocal diagnosis. Resistance/height and reactance/height were the input variables in the model. Output variables were the seven categories of body composition of vectorial analysis. For each case the linguistic model estimated the membership degree of each impedance category. To compare such results to the previously established diagnoses Kappa statistics was used. This demanded singling out one among the output set of seven categories of membership degrees. This procedure (defuzzification rule) established that the category with the highest membership degree should be the most likely category for the case. Results: The fuzzy model showed a good fit to the development sample. Excellent agreement was achieved between the defuzzified impedance diagnoses and the clinical diagnoses in the testing sample (Kappa = 0.85, p < 0.001). Conclusions: fuzzy linguistic model was found in good agreement with clinical diagnoses. If the whole model output is considered, information on to which extent each BIVA category is present does better advise clinical practice with an enlarged nosological framework and diverse therapeutic strategies. (C) 2012 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Costs and benefits of orthographic inconsistency in reading:evidence from a cross-linguistic comparison

We compared reading acquisition in English and Italian children up to late primary school analyzing RTs and errors as a function of various psycholinguistic variables and changes due to experience. Our results show that reading becomes progressively more reliant on larger processing units with age, but that this is modulated by consistency of the language. In English, an inconsistent orthography, reliance on larger units occurs earlier on and it is demonstrated by faster RTs, a stronger effect of lexical variables and lack of length effect (by fifth grade). However, not all English children are able to master this mode of processing yielding larger inter-individual variability. In Italian, a consistent orthography, reliance on larger units occurs later and it is less pronounced. This is demonstrated by larger length effects which remain significant even in older children and by larger effects of a global factor (related to speed of orthographic decoding) explaining changes of performance across ages. Our results show the importance of considering not only overall performance, but inter-individual variability and variability between conditions when interpreting cross-linguistic differences.

A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

The effect of borders on the linguistic production and perception of regional identity in Louisville, Kentucky

A great deal of scholarly research has addressed the issue of dialect mapping in the United States. These studies, usually based on phonetic or lexical items, aim to present an overall picture of the dialect landscape. But what is often missing in these types of projects is an attention to the borders of a dialect region and to what kinds of identity alignments can be found in such areas. This lack of attention to regional and dialect border identities is surprising, given the salience of such borders for many Americans. This salience is also ignored among dialectologists, as nonlinguists‟ perceptions and attitudes have been generally assumed to be secondary to the analysis of “real” data, such as the phonetic and lexical variables used in traditional dialectology. Louisville, Kentucky is considered as a case study for examining how dialect and regional borders in the United States impact speakers‟ linguistic acts of identity, especially the production and perception of such identities. According to Labov, Ash, and Boberg (2006), Louisville is one of the northernmost cities to be classified as part of the South. Its location on the Ohio River, on the political and geographic border between Kentucky and Indiana, places Louisville on the isogloss between Southern and Midland dialects. Through an examination of language attitude surveys, mental maps, focus group interviews, and production data, I show that identity alignments in borderlands are neither simple nor straightforward. Identity at the border is fluid, complex, and dynamic; speakers constantly negotiate and contest their identities. The analysis shows the ways in which Louisvillians shift between Southern and non-Southern identities, in the active and agentive expression of their amplified awareness of belonging brought about by their position on the border.

Cross-correlations between weather variables in Australia

The information on climate variations is essential for the research of many subjects, such as the performance of buildings and agricultural production. However, recorded meteorological data are often incomplete. There may be a limited number of locations recorded, while the number of recorded climatic variables and the time intervals can also be inadequate. Therefore, the hourly data of key weather parameters as required by many building simulation programmes are typically not readily available. To overcome this gap in measured information, several empirical methods and weather data generators have been developed. They generally employ statistical analysis techniques to model the variations of individual climatic variables, while the possible interactions between different weather parameters are largely ignored. Based on a statistical analysis of 10 years historical hourly climatic data over all capital cities in Australia, this paper reports on the finding of strong correlations between several specific weather variables. It is found that there are strong linear correlations between the hourly variations of global solar irradiation (GSI) and dry bulb temperature (DBT), and between the hourly variations of DBT and relative humidity (RH). With an increase in GSI, DBT would generally increase, while the RH tends to decrease. However, no such a clear correlation can be found between the DBT and atmospheric pressure (P), and between the DBT and wind speed. These findings will be useful for the research and practice in building performance simulation.