Linguistic Variables Research Articles

Gray Uncertain Linguistic Multiattribute Group Decision Making Method Based on GCC-HCD

This article presents a multiattribute group decision-making (MAGDM) method using cloud models to handle decision problems with gray uncertain linguistic variables that contain both subjective and objective uncertainty. In this new method, the new concepts of gray uncertain linguistic variable and gray comprehensive cloud are defined, and a method for converting gray uncertain linguistic variables into gray comprehensive clouds is provided. A gray comprehensive clouds-weighted averaging (GCC-WA) operator is proposed to aggregate the information with multiple gray comprehensive clouds. A distance measure between two gray comprehensive clouds is defined to form the gray comprehensive cloud-hybrid closeness degree (GCC-HCD), which is then applied to rank the alternatives. An example of an offshore mining investment is applied to validate the method. Sensitivity analysis and comparison analysis are carried out with other congeneric methods.

FUZZY MODEL FOR TIME SERIES FORECASTING

Abstract: In 2007, in Kazakhstan, there was a transition of TDM (Time Division Multiplexing) circuit-switched technologies to IP (Internet Protocol) packet technology, which created a modern infrastructure for the ICT (information communication technologies) sphere. The advent of the IoT (Internet of Things) concept has led to the growth of a functioning network at a faster rate. It is currently developing in the direction of a cognitive infocommunication network. Its evolutionary development is characterized by a change in the volume of transmitted information, types of its presentation, methods of transmission and storage, the number of sources and consumers, distribution among users, requirements for timeliness and reliability (quality) [1]. Types of traffic and their structure are changing, therefore data processing becomes more complicated. For this reason, the tasks of analyzing and predicting network traffic remain relevant.
 In this work, the prediction of the measured traffic on a real network is performed. The series under study shows the totality of packets transmitted over the backbone network for each second. Forecasting of a one-dimensional time series is carried out on the basis of fuzzy logic methods. This class of models is well suited for modeling nonlinear systems and time series forecasting. The use of fuzzy sets is based on the ability of fuzzy models to approximate functions, as well as on the readability of rules using linguistic variables. The results of the software algorithm of fuzzy inference models were obtained using the Python environment. Membership functions, predictive graphs were built and their evaluation was carried out. The numerical values of the root mean square error (MSE) are calculated. As a result, it was found that the Cheng fuzzy prediction model has higher forecast accuracy than the Chen forecasting method.

Математическая модель интеллектуальной системы поддержки принятия управленческих решений в энергосистемах

The article considers the problem of taking into account the information uncertainty for building knowledge bases in decision support systems for the operational management of the electric power system modes on the example of the Pridnestrovian Moldavian Republic power system. As part of the study, the categorical method “Universal Interaction Scheme” is used, because it allows building a conceptual model of the Pridnestrovian Moldavian Republic power systems necessary for the further development of a mathematical model. To create a mathematical model of an intelligent management decision support system in power systems, the Decision-Support System knowledge base method based on fuzzy logic is used. It is substantiated that formulating the control logic is carried out mainly at the level of qualitative representations and concepts. The latter can be formalised in terms of logical-linguistic models, which should be considered from the viewpoint of the theory of fuzzy sets and linguistic variables. The analysis of existing approaches to representing and processing fuzzy knowledge about the power system management is carried out. An approach to demonstrating the incorporation of various forms of professional ontology representation based on fuzzy logic is substantiated. The research methods involve using the apparatus of fuzzy logic, formal languages, the theory of artificial intelligence systems and decision support systems.

A quality learning environment: an assessment of spaciousness of architectural design studios of Iraqi Kurdistan region universities using fuzzy logic

PurposeSpaciousness is defined as “the feeling of openness or room to wander” that has been affected by various physical factors. The purpose of this paper is to assess the spaciousness of space to determine how spacious the space is. Furthermore, the study intends to propose a fuzzy-based model to assess the degree of spaciousness in terms of physical parameters such as area, proportion, the ratio of window area to floor area and color value.Design/methodology/approachFuzzy logic is the most appropriate mathematical model to assess uncertainty using nonhomogeneous variables. In contrast to conventional methods, fuzzy logic depends on partial truth theory. MATLAB Fuzzy Logic Toolbox was used as a computational model including a fuzzy inference system (FIS) using linguistic variables called membership functions to define parameters. As a result, fuzzy logic was used in this study to assess the spaciousness degree of design studios in universities in the Iraqi Kurdistan region.FindingsThe findings of the presented fuzzy model show the degree to which the input variables affect a space perceived as larger and more spacious. The relationship between parameters has been represented in three-dimensional surface diagrams. The positive relationship of spaciousness with the area, window-to-floor area ratio and color value has been determined. In contrast, the negative relationship between spaciousness and space proportion is described. Moreover, the three-dimensional surface diagram illustrates how the changes in the input values affect the spaciousness degree. Besides, the improvement in the spaciousness degree of the design studio increases the quality learning environment.Originality/valueThis study attempted to assess the degree of spaciousness in design studios. There has been no attempt carried out to combine educational space learning environments and computational methods. This study focused on the assessment of spaciousness using the MATLAB Fuzzy Logic toolbox that has not been integrated so far.

Identifying an Appropriate Picture Stimulus for a Bangla Picture Description Task.

The absence of culture- and language-specific aphasia assessment in Bangla underscores a critical problem in communication sciences and disorders. Aphasia occurs in ~41% of Bangla-speaking stroke survivors. In the past 40 years, stroke incidence has doubled in low- and middle-income countries, such as Bangladesh and India, where there are ~250 million native Bangla speakers. This study aims to initiate the first step toward identifying an appropriate picture stimulus for the Bangla picture description task (PDT) intended for inclusion in a Bangla aphasia assessment. Researchers have reported the importance of cultural relevance and three visuographic variables of a picture (high-context, color, and photograph vs. black-and-white line drawing) for faster comprehension and comprehensive language production in people with aphasia and neurologically healthy adults. Ninety-six neurologically healthy native Bangla speakers of three age groups (young 19-30, middle age 40-55, and older 65-89 years) were recruited to compare spontaneous language production for four selected culturally related and nonrelated picture stimuli with and without the three visuographic variables. Five linguistic variables were used to analyze the language samples. The results demonstrated a significant (a) picture type effect for moving-average type-token ratio, words per minute (WPM), and mean length of utterance in morphemes (MLU) and (b) age group effect for WPM, MLU, and complexity index. This study suggests that a culturally related high-context color photograph is the optimal choice for the Bangla PDT. This study also indicates reduced fluency, grammatical complexity, and syntactic complexity in healthy Bangla-speaking adults aged 65 years and above. https://doi.org/10.23641/asha.22233664.

The non-human animal reading the mind in the eyes test (NARMET): A new measure for the assessment of social cognition.

The Reading the Mind in the Eyes test (RMET) is a widely applied test of social cognition, based on mental state judgments in response to photographs of human eyes, which can elicit impairment in patients with numerous psychiatric and neurological disorders. However, interpretation of task performance is limited without the use of appropriate control tasks. In addition to a matched task requiring age judgments of the RMET stimuli, it was recently shown that a mental state judgment task of comparable difficulty, could be developed using photographs of domestic cat eyes. The current study aimed to further develop a Non-human Animal RMET (NARMET) by testing additional stimuli in the form of photographs of domestic dog eyes. A variety of additional tasks were used alongside the eyes test stimuli in a large sample of healthy young adults, to explore how alexithymia, schizotypal features, and autistic tendencies may differentially influence mental state attribution in response to cat, dog, and human eyes test stimuli. The resulting NARMET features both cat and dog trials, depicting a similar range of complex mental states to the human RMET. It shows favorable psychometric properties as well as being well matched to the RMET in terms of linguistic variables, length and difficulty. However, reading measures predicted performance on the RMET, but not on the NARMET. Although further testing is required in samples with a higher proportion of males, future application of the NARMET in neuropsychiatric populations exhibiting cognitive and behavioral difficulties could offer enhanced assessment of social cognitive skills.

The impact of resilience, hope, second language proficiency, and number of foreign languages on Chinese college students’ creativity

Creativity has been widely discussed as a contributor to foreign language (FL) learning. However, there is a lack of research that combines psychology and linguistics to investigate the complex mechanisms of creativity in FL learners. Thus, the present study explored whether and how psychological variables (i.e., resilience and hope) and linguistic variables (i.e., second language [L2] proficiency and number of FLs learned) jointly affect Chinese college FL students’ creativity. A questionnaire survey was conducted with 282 students learning at least one FL at two Chinese universities; the responses were mediated and moderated using the PROCESS macro for SPSS. The results showed that: (1) FL learners’ resilience, hope, and creativity were positively correlated; (2) the direct effect of resilience on creativity was not statistically significant; (3) hope had a significant positive mediating effect between resilience and creativity; (4) L2 proficiency had a positive moderating effect between resilience and hope; (5) and the number of FLs learned had a negative moderating effect between hope and creativity, which is a surprising finding that deserves attention. The results can provide theoretical and practical guidance for introducing positive psychology-related interventions and reforming instructional methods in FL teaching.

Dependence assessment in human reliability analysis using the 2-tuple linguistic information and DEMATEL method

Human reliability analysis (HRA), which is to analyze human contribution to system risk, is an effective way to model and assess human errors. Dependence assessment among human errors is an essential part of HRA, which often depends on the judgments of experts. As real-world problems often involve many complex factors, the judgments provided by the experts are often linguistic terms, even under uncertainty. To this end, by integrating 2-tuple linguistic variables and DEMATEL method, this paper presents a novel way to assess the dependence among human actions in HRA. In the proposed method, the linguistic judgments of the experts are modeled using 2-tuple linguistic variables, and the weights of the influential factors are determined using DEMATEL method, furthermore, the conditional human error probability is calculated by aggregating the 2-tuples of different influential factors based on the 2-tuple weighted average operator, where a novel weight calculation method is developed to determine the weights of different experts. Finally, a case study is presented to demonstrate the effectiveness and reliability of the proposed method. By adopting 2-tuple linguistic variables and DEMATEL method, the proposed method could effectively address the uncertainty in the dependence assessment while capturing the relationship among the influential factors.

SOCIOPHONETIC STUDY OF DIALECT CHANGE IN IRAQ

This study investigates the occurrence of dialect levelling in the variety of Arabic spoken in Anah, Iraq in terms of the current phonological patterns and change triggered mainly by dialect contact between qeltu and gilit speakers. The study provides a quantitative sociophnetic description of the speech of 60 (30 males and 30 females) Arabic Iraqi Ani (AIA henceforth) speakers. This study investigates the change in two phonological processes: qaf velarisation and Imala (deflexion) under the effect of informants’ age and gender and social network. Following Labov’s (1984) conversational network method, all informants were interviewed individually to collect the linguistic variables required for analysis. Results show that according to the increasing adoption of gilit features by Ani speakers, levelling is occurring in the AIA. Results also revealed that levelling has not yet reached the completion level, yet it is in a very advanced phase.

An Advanced Entropy Measure of IFSs via Similarity Measure

The Entropy measure of an intuitionistic fuzzy set (IFS) plays a significant role in decision making sciences, for instance, medical diagnosis, pattern recognition, criminal investigation, etc. The inadequate nature of an entropy measure may lead to some invalid results. Therefore, it is significant to use an efficient entropy measure for studying various decision-making problems under IFS environment. This paper first proposes a novel similarity measure for IFS. Based on the proposed similarity measure, an advanced entropy measure is defined with a different axiomatic approach. This axiomatic approach allows us to measure an IFS's entropy with the help of a similarity measure. To show the efficiency of the proposed similarity measure, a comparative study is performed with the existing similarity measures. Some structural linguistic variables are taken as examples to show the validity and consistency of the proposed entropy measure along with the existing entropy measures. Finally, based on the proposed entropy measure, a multi-criteria decision-making problem is performed.

A web-based application for eliciting narrative discourse from Greek-speaking people with and without language impairments

In this paper we present a web-based data collection method designed to elicit narrative discourse from adults with and without language impairments, both in an in-person set up and remotely. We describe the design, methodological considerations and technical requirements regarding the application development, the elicitation tasks, materials and guidelines, as well as the implementation of the assessment procedure. To investigate the efficacy of remote elicitation of narrative discourse with the use of the technology-enhanced method presented here, a pilot study was conducted, aiming to compare narratives elicited remotely to narratives collected in an in-person elicitation mode from ten unimpaired adults, using a within-participants research design. In the remote elicitation setting, each participant performed the tasks of a narrative elicitation protocol via the web application in their own environment, with the assistance of an investigator in the context of a virtual meeting (video conferencing). In the in-person elicitation setting, the participant was in the same environment with the investigator, who administered the tasks using the web application. Data were manually transcribed, and transcripts were processed with Natural Language Processing (NLP) tools. Linguistic features representing key measures of spoken narrative discourse were automatically calculated: linguistic productivity, content richness, fluency, syntactic complexity at clausal and inter-clausal level, lexical diversity, and verbal output. The results show that spoken narratives produced by the same individuals in the two different experimental settings do not present significant differences regarding the linguistic variables analyzed, in sixty six out of seventy statistical tests. These results indicate that the presented web-based application is a feasible method for the remote collection of spoken narrative discourse from adults without language impairments in the context of online assessment.

Challenges and opportunities for harmonization of cross-cultural neuropsychological data.

In this position article, we highlight the importance of considering cultural and linguistic variables that influence neuropsychological test performance and the possible moderating impact on our understanding of brain/behavior relationships. Increasingly, neuropsychologists are realizing that cultural and language differences between countries, regions, and ethnic groups influence neuropsychological outcomes, as test scores may not have the same interpretative meaning across cultures. Furthermore, attempts to apply the same norms across diverse populations without accounting for culture and language variations will result in detrimental ethical dilemmas, such as misdiagnosis of clinical conditions and inaccurate interpretations of research outcomes. Given the lack of normative data for ethnically and linguistically diverse communities, it is often challenging to merge data across diverse populations to investigate research questions of global significance. Methodological Considerations: We highlight some of the inherent challenges, limitations, and opportunities for efforts to harmonize cross-cultural neuropsychological data. We also explore some of the cultural factors that should be considered when attempting to harmonize cross-cultural neuropsychological data, sources of variance that should be accounted for in data analyses, and the need to identify evaluative criteria for interpreting data outcomes of cross-cultural harmonization approaches. In the future, it will be important to further solidify principles for aggregating data across diverse cultural and linguistic cohorts, validate whether assumptions are being satisfied regarding the relationship between neuropsychological measures and the brain and/or behavior of individuals from diverse cultural and linguistic backgrounds, as well as methods for evaluating relative successful validation for data harmonization efforts. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Analyzing the use of expert systems in improving the quality of decision-making

The success of institutions is in providing good services to customers through making various and strategic decisions as quickly and accurately as possible. Expert systems are important in making strategic decisions by improving the quality of decision-making. An expert system is an information system that relies on systems based on knowledge bases. It may also contain a knowledge base in a particular field and advanced programming methods that make a computer capable of thinking, deducing, and providing advice and expertise. This research aims to improve the period of time in decision making by using multiple experts systems and decision support system. The new system is implemented in MATLAB. For analyzing the proposed system, the data is collected by the questionnaire method and distributing 70 questionnaires to managers, heads of departments, employees, and those responsible for making various decisions in the institution under study. The valid questionnaires were 63. A questionnaire and the data were analyzed using the statistical program (SPSS). Based on the obtained data, the linguistic variables were created for the time period of the data, and the skills of the decision-maker as inputs for the proposed expert system, and a stage was added to the stages of the proposed expert system to diagnose the problem and set the goal to obtain the correct strategic decision. To obtain this advantage, let’s use expert systems compared to traditional methods of decision-making

Fuzzy-MACBETH Hybrid Method: Mathematical Treatment of a Qualitative Scale Using the Fuzzy Theory

This paper describes the research procedures adopted in developing a triangular fuzzy number scale based on the semantic scale of MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique). The objective was to mathematically treat the uncertainty and subjectivity of linguistic variables used to assess a decision problem. A matrix was initially obtained based on a decision maker’s assessment of a given context analysis. This decision matrix was then fuzzified based on a triangular Fuzzy numbers scale. Next, the inference process was performed using F-LP-MACBETH linear programming problem proposed here, resulting in a Fuzzy scale. This scale was then defuzzified using the centroid method, from which a crisp basic scale emerged, which was then cardinalized. The results show that the MACBETH Fuzzy method proposed here can overcome the classical method’s cardinal inconsistency problem, which facilitates its application in complex contexts. Hence, the MACBETH Fuzzy Hybrid method generated numerical values based on the decision makers’ semantically consistent assessments in a decision matrix, which by the classical method presents cardinal inconsistency. Therefore, the advantage of the proposed method consists in the possibility of obtaining a cardinal scale aligned to the decision makers’ preferences without the need to reassess the context.

A hydroponic greenhouse fuzzy control system: design, development and optimization using the genetic algorithm

Aim of study: The design and development of a hydroponic greenhouse fuzzy control system. Area of study: The evaluation was performed using experimental data obtained from the literature. The construction and evaluation of the fuzzy control hydroponic greenhouse system was carried out in a greenhouse in Tehran, Iran. Material and methods: The greenhouse environmental conditions, including temperature, humidity, and carbon dioxide, were controlled. The design of a fuzzy controller begun with the selection of linguistic variables, process status, and input and output variables. The fuzzy control system consisted of three modules: 1) fuzzy module, 2) cost function, and 3) genetic algorithm for the adjustment of the greenhouse environmental conditions.The next step was to select a set of linguistic rules and the type of fuzzy inference process. The rules were set once, and the fuzzy set and output value needed to be specified after the inference, along with the development of a non-fuzzy strategy. Main results: The mean temperatures provided by the fuzzy control system during the day and night were 34.25°C and 23.22°C, respectively, which were improved to 31.17°C and 21.96°C after optimization. The mean humidity was 39.4% and 56.5% during the day and the night, respectively, which turned 60.22% and 74.59% after optimization. The control system also achieved desirable conditions in terms of CO2 amount. Research highlights: The results showed that the measured values of temperature and relative humidity of the greenhouse were improved after optimization with genetic algorithm.

The Selection of a Possible Organizational Structure of Railway Companies by Application Fuzzy-ARAS Method

The European railway sector doesn't represent a single, generic type of organizational structure. The Directives from the 1990s offer the possibility for national interpretation giving a wide range of organizational structures for European railways. Different organizational structures of railways are present in the European railway market, and all of them are aligned with the national belief of the country - how to manage the railway. This paper focuses on Multi-Criteria Decision Making (MCDM) methods for ranking and selecting organizational structures of railways. In decision-making, we deal with different types of uncertainty and inaccuracy. For this purpose, we need to use some specific tools. In this paper, we use triangular fuzzy numbers to quantify linguistic data. To overcome the complexity of the decision-making problem, we propose the fuzzy Additive Ratio ASsessment (ARAS) method, which also includes linguistic variables and a group approach to decision-making. With the proposed methodology an evaluation of the alternatives to the organization structure of the railway company in Bosnia and Herzegovina is considered. Separation of railway transport from infrastructure management is ranked as the best organizational structure for this company.

A socio-stylistic analysis of Death in Dickinson’s and Whitman’s selected poems

This paper attempts a socio-stylistic analysis of four well-known American poems by focusing on their treatment of death as a central theme. The poems are “Because I Could not Stop for Death,” “There’s Been A Death in the Opposite House” by Emily Dickinson, “Pensive on Her Dead Gazing,” and “Vigil Strange” by Walt Whitman. The poems are analysed for their use of grammatical stylistic devices and the extraction of general grammatical deviations. The strength of the paper lies in its integration of the aforementioned stylistic devices in a way that is consistent with the linguistic variable of gender. Therefore, a poet and a poetess were selected to compare and contrast the two poets’ styles and perspectives. Whitman’s poems employ a greater variety of stylistic devices than Dickinson’s. Dickinson employed a wide range of stylistic devices, many of which appear multiple times. While Whitman’s work frequently recycles the same devices and their variants. Examining the poems in this way lends credence to the paper’s argument that language and gender are intricately intertwined in the presentation of such a massive topic as death, which leads each gender to express death from their perspective as well as their surrounding society.

Investigating the Drivers of Knowledge-Based Growth Management Using Fuzzy MICMAC: A Case Study in Iran

Attention to a city’s physical development is necessary for urban development plans. In Iran, the rapid physical expansion of cities in the form of unplanned and unbalanced growth due to various reasons, including indiscriminate migration, is considered a fundamental problem. This phenomenon is known as urban sprawl, which is one of the results of this type of growth. The research aims to identify and prioritize the indicators of the realization of knowledge-based growth management (KBGM) in the city of Tabriz, using foresight methods to analyze the effective drivers. The fuzzy linguistic MICMAC method was used to analyze mutual effects by converting linguistic variables into fuzzy numbers. In addition, using the theory of fuzzy sets for experts participating in research, the relationships between the 32 research variables were investigated. This research showed that the city of Tabriz had a scattered, isolated, fast, and unplanned growth, and it has relative compatibility. Despite the possibility of development within the limits of urban growth, most of the construction activities were outside the boundaries of urban growth. Key factors affecting the management of knowledge-based growth in Tabriz city were identified. Based on our findings, the university’s reputation, government effectiveness, urban competitiveness, city branding, quality of life, and strategic planning will impact the knowledge-based development process in Tabriz.

Energy Efficiency Issues in Buildings: Analysis of World Practice

At present, the volume of world energy consumption is continuously and rapidly increasing, which is a consequence of the industrialization process, population growth, increase in energy costs for the extraction of natural resources, etc. Therefore, the importance of solving the problem of energy efficiency is of paramount importance for modern civilization. In this work, there is an analysis of international experience of energy efficient construction. The main directions of energy-efficient development are highlighted. It’s shown that the classical method of heat loss calculations wrongly takes into account the wind effect. The more correct one is required. At the same time, it is worth applying linguistic variables and fuzzy logic, which adequately describe states that are described by verbal statements, and not by numerical values. In conclusion, the most emerging tasks for our Republic are selected: optimal placement of the building on the general plan of the city, incl. maintaining the distance between buildings under the construction and urban-planning regulations; proper heat insulation of the building envelope by the orientation of facades and depending on the climatic parameters of the outside air; air-tightening of building avoiding in- and exfiltration; maximum possible automation of engineering systems up to integration from smart house to smart city level; modernization and optimization of the operation of engineering systems; maximum use of renewable and secondary (such as exhaust air) energy sources; rejection of the classical calculation method of heat loss estimation, which takes into account the effect of wind speed, and to develop a new methodology.

A new approach for spherical fuzzy TOPSIS and spherical fuzzy VIKOR applied to the evaluation of hydrogen storage systems

This study proposes a new perspective of the TOPSIS and VIKOR methods using the recently introduced spherical fuzzy sets (SFSs) to handle the vagueness in subjective data and the uncertainties in objective data simultaneously. When implementing these techniques using SFSs, two main problems might arise that can lead to incorrect results. Firstly, the reference points might change with the utilized score function. Secondly, the distance between reference points might not be the largest, as known, among the available ratings. To overcome these deficiencies and increase the robustness of these two methods, they are implemented without utilizing any reference points to minimize the effect of defuzzification and without measuring the distance to eliminate the effect of distance formulas. In the proposed methods, when using an SFS to express the performance of an alternative for a criterion, this SFS per se can be viewed as a measure of proximity to the aspired level. On the other hand, the conjugate of the SFS can be viewed as a measure of proximity to the ineffectual level. Two practical applications are presented to demonstrate the proposed techniques. The first example handles a warehouse location selection problem. The second example evaluates hydrogen storage systems for automobiles with different types of data (crisp, linguistic variables, type 1 fuzzy sets). These data are transformed to SFSs to provide a more comprehensive analysis. A comparative study is conducted with earlier versions of TOPSIS and VIKOR to explicate the adequacy of the proposed methods and the consistency of the results.