Linguistic Variables Research Articles

A MAGDM model based on 2-tuple linguistic variables and power Hamacher aggregation operators for optimal selection of digital marketing strategies

A MAGDM model based on 2-tuple linguistic variables and power Hamacher aggregation operators for optimal selection of digital marketing strategies

Contextual Variables as Predictors of Verb Form: An Analysis of Gender and Stance in Peninsular Spanish Requests

The current experiment employs a variational pragmatics perspective to explore how the contextual variables of power, distance, and imposition jointly affect social groups’ and individuals’ choice of verb forms in requests in Madrid, Spain. Using a mixed-method approach to explore the requests of 111 Spanish speakers from Madrid, quantitative analyses determined the level of significance and hierarchical order of the predictor variables of power, distance, and imposition on verb form and also the distribution of verb forms by gender, with male and female participants exhibiting significant differences. Additionally, certain participants demonstrated decreased sensitivity to contextual factors, adopting more categorically indirect or direct request strategies. The examination of both gendered request patterns and the stances that single participants adopt through their verb-form selections contributes to our understanding of the social moves that are made by all speakers, not just those who fall within the gendered norms. The results highlight the different frames and social meanings attached to these forms at the micro- and macro-social levels, providing new insight into the complex relationship among linguistic variables, contextual factors, and social groups and individuals.

A FUZZY CONTROLLER FOR A MOBILE ROBOT WITH OBSTACLE AVOIDANCE

This research paper presents a mobile robot based on the MAMDANI fuzzy inference system. The mobile robot is equipped with three pairs of HC-SR04 ultrasonic sensors to detect the distance between the robot and obstacles. A fuzzy logic controller is built into the STM32F4 microcontroller platform to generate the actuation signal for the DC motor mounted on each robot wheel. To perform obstacle avoidance, a sensor capable of detecting the distance between the robot and the obstacle must be installed so that the controller can calculate and determine the appropriate control signal to send to the robot's actuator. In achieving this goal, the robot can perform movements at a constant speed or at a variable speed. When the distance between the robot and the obstacle is too far, the speed is too fast. Then, as the distance to the obstacle increases, the speed decreases. Such a control mechanism can be implemented with certain control methods installed in the controller. The data obtained from the ultrasonic sensors are expressed as linguistic variables that indicate the speed of movement of each wheel in fuzzy sets. A robot with a fuzzy logic controller based on a rule table is designed to achieve uninterrupted motion with obstacle avoidance capability. Keywords: STM32F4 microcontroller, Fuzzy logic, Fuzzy inference system, mobile robot, obstacle avoidance.

FUZZY LOGIC FOR OPTIMIZING ROOM SALES: SUGENO METHOD AND MAPE EVALUATION

The Indonesian hospitality industry has grown rapidly over the past decades and is one of the most important sectors of the national economy. The focus is on determining the number of rooms sold using the Sugeno method's fuzzy logic. This study optimizes room sales by developing a fuzzy logic-based system that can effectively determine the number of rooms sold considering availability, best available rates, and revenue target. The Sugeno method is a type of fuzzy inference system that determines the relationship between input variables (room availability, best available rate, revenue target) and output variables (number of rooms sold). Modeled by using linguistic variables and fuzzy rules, the Sugeno method can provide a quantitative output based on specified input conditions. To evaluate the accuracy of the proposed fuzzy logic model, the mean absolute percentage error (MAPE) is used as a performance measure. Target data 175,000,000 to 245,000,000, BAR standard room 225,000 to 335,000, BAR superior room 285,000 to 425,000, available standard room 68 rooms/day, superior room 10 rooms/day, model accuracy measurement result is 1,80% very accurate interpreted. As such, the proposed system is useful for decision-making related to optimizing room sales in the hospitality industry.

A new approach to developing software projects by assigning teams to projects with interval-valued neutrosophic Z numbers

Software development projects are becoming increasingly important to achieve successful results in the global digitalization trend that has spread throughout the world at the time of the pandemic. The main software development methodologies (SDM) are waterfall and agile. This study investigates the achievement of success methodology through the evaluation of software development projects, personnel under the scope of SDM's. Software projects require strong human resources to be successful in terms of on-time completion and success. For software projects that include the human component, it is important to make project team SDM assignments more meaningful and accurate. The power of linguistic variables and the use of expert ratings in such assignments have been the focus of this paper. The reason for the strong representativeness is the conversion of linguistic variables to mathematical fuzzification, Interval Valued Neutrosophic Z-Numbers (NZN) are used to determine which SDM should be used first in projects. The results of the NZN are then incorporated into the NZN-Area model. This replaces the distance measurement equation used to rank alternatives with an area calculation. The NZN-Area Model is the new proposed form of the model. The NZN-Area model produced 22% better results in terms of defect numbers and 25% better results in terms of defect resolution time compared to the NZN method. Additionally, a sensitivity analysis was performed by comparing the NZN method and NZN-Area method with real data. The proposed NZN-Area method was found to be more consistent under variable conditions.

Evaluation of ecological governance in the Yellow River basin based on Uninorm combination weight and MULTIMOORA-Borda method

As a river of great strategic significance in China, the ecological governance of the Yellow River is an important issue. As a multi-attribute decision-making (MADM) problem, evaluating the ecological governance of the Yellow River involves many evaluation indexes. To accurately measure the importance of each indicator, this paper applies the best-worst method (BWM) based on linguistic variables to calculate the subjective weights of the indexes. The improved grey relational (IGR) method is proposed to calculate the objective weights. And the two weights are combined using the Uninorm operator to obtain the combination weights of the indexes. To evaluate the problem from multiple perspectives, we apply the MULTIMOORA method to the ecological governance problem. Then we propose the novel Borda method to aggregate the three evaluation results obtained by the MULTIMOORA method and thus construct the MULTIMOORA-Borda method. Based on the above methods, we analyze the evaluation results and provide policy recommendations for ecological governance of the Yellow River Basin.

A Fuzzy TOPSIS-Based Approach for Comprehensive Evaluation of Bio-Medical Waste Management: Advancing Sustainability and Decision-Making

Bio-medical waste management is critical for ensuring public health and environmental sustainability. However, due to the inherent ambiguities and complexities involved with waste characteristics and disposal techniques, measuring the efficiency of bio-medical waste management systems presents major hurdles. This study provides a Fuzzy TOPSIS-based (Technique for Order Preference by Similarity to Ideal Solution) strategy for thorough bio-medical waste management assessment. The suggested method combines the benefits of fuzzy logic and TOPSIS, allowing for the incorporation of subjective judgments and ambiguity in the evaluation procedure. Initially, a thorough set of criteria is constructed based on a review of current literature and recommendations from experts, comprising Environmental Impact, Compliance with Regulations, Health and Safety, Technological Feasibility, and Cost-effectiveness. To accurately represent the inherent ambiguity and imprecision in decision-making, each criterion is evaluated using linguistic variables. Furthermore, the Fuzzy TOPSIS approach is used to rate various bio-medical waste management systems depending on how well they perform in comparison to the identified criteria. The language judgments are represented as fuzzy numbers, and the idea of closeness coefficients is used for calculating the relative distance between each alternative and the ideal answer. An investigation in a healthcare facility is performed to demonstrate the feasibility and effectiveness of the suggested strategy. To assess numerous waste management approaches, the study uses real-world data on waste management practices, expert opinions, and linguistic analyses. The study’s findings emphasize the benefits of using a Fuzzy TOPSIS-based technique to evaluate bio-medical waste management. According to the findings of this research study, recycling is the best choice because it has the potential to reduce waste, recover resources, and preserve the environment. It assists decision-makers to account for uncertainties and subjectivity, increases transparency and consistency in decision-making, and aids in choosing of the best waste management system. The proposed approach advances sustainable waste management practices in the bio-medical area and provides a helpful tool for policymakers and practitioners looking to enhance waste management systems.

An Improved TOPSIS Method Based on a New Distance Measure and Its Application to the House Selection Problem

It is difficult to choose an appropriate house for homebuyers. This is due to the difficulty of evaluating the multitude of factors, such as price, location, size, and so on. In order to help homebuyers in choosing an appropriate house, a method integrating the interval-valued Pythagorean FAHP and FTOPSIS is proposed. In the proposed approach, the evaluation criteria were determined by the experts, and the linguistic variables of interval-valued Pythagorean fuzzy numbers were used in the evaluations of the homebuyers and experts. A new distance between two IVPFNs is proposed. The weights of the evaluation criteria were determined by the interval-valued Pythagorean FAHP method by the homebuyers, and house selections were evaluated by interval-valued Pythagorean FTOPSIS method taking into account the new distance. Finally, a case study was executed to verify the feasibility of the proposed approach. The case study results reveal that the weights of criteria obtained by FAHP are not the same according to opinions of the different homebuyers.

Fuzzy‐based unequal clustering protocol for underwater wireless sensor networks

SummaryUnderwater wireless sensor network (UWSN) is a network made up of underwater sensor nodes, anchor nodes, surface sink nodes or surface stations, and the offshore sink node. Energy consumption, limited bandwidth, propagation delay, high bit error rate, stability, scalability, and network lifetime are the key challenges related to underwater wireless sensor networks. Clustering is used to mitigate these issues. In this work, fuzzy‐based unequal clustering protocol (FBUCP) is proposed that does cluster head selection using fuzzy logic as it can deal with the uncertainties of the harsh atmosphere in the water. Cluster heads are selected using linguistic input variables like distance to the surface sink node, residual energy, and node density and linguistic output variables like cluster head advertisement radius and rank of underwater sensor nodes. Unequal clustering is used to have an unequal size of the cluster which deals with the problem of excess energy usage of the underwater sensor nodes near the surface sink node, called the hot spot problem. Data gathered by the cluster heads are transmitted to the surface sink node using neighboring cluster heads in the direction of the surface sink node. Dijkstra's shortest path algorithm is used for multi‐hop and inter‐cluster routing. The FBUCP is compared with the LEACH‐UWSN, CDBR, and FBCA protocols for underwater wireless sensor networks. A comparative analysis shows that in first node dies, the FBUCP is up to 80% better, has 64.86% more network lifetime, has 91% more number of packets transmitted to the surface sink node, and is up to 58.81% more energy efficient than LEACH‐UWSN, CDBR, and FBCA.

Application of fuzzy group decision-making selecting green supplier: a case study of the manufacture of natural laurel soap

The selection of suppliers alone is one of the most important competitive challenges facing organizations today. With today's increasing awareness and facing many significant environmental pressures, the process of selecting the right suppliers for green supply chain management is even more difficult for decision-makers. The process of developing and implementing decision-making tools seek to face these challenges is rapidly evolving, especially in a fuzzy environment whose data are incomplete. The purpose of this article is to investigate prospective green chain suppliers for a laurel soap producing company based on a framework using MCDA fuzzy technologies such as Fuzzy GRA, Fuzzy TOPSIS, and Fuzzy VIKOR. During this paper, a discussion of fuzzy set was discussed with Fuzzy MCDM. Within a realistic case study, where a comparison was made between the tools, and it was noted that the results were consistent between the two tools Fuzzy TOPSIS and Fuzzy GRA, and the arrival of similar results and a slight difference with results was observed in Fuzzy VIKOR interpreted. The most detailed analyses were conducted on distance measurements, linguistic variables, assembly functions, and confusion processing. This study introduces the Fuzzy MCDM method to help researchers choose a more effective approach for green supplier selection and the conclusions and other study directions are offered toward the conclusion of the paper.

A Fuzzy Inference System for enhanced groundwater quality assessment and index determination

Abstract Groundwater is a vital resource for human consumption, particularly in rural areas with limited access to treated water. The conventional Water Quality Index models used for this purpose have limitations related to data volatility and judgment uncertainties. To overcome these limitations, our study introduces a novel approach that employs a Fuzzy Inference System to determine the Water Quality Index. The dataset used in our research includes multiple parameters such as pH, EC, TDS, Ca, Mg, Na, K, HCO3, Cl, SO4, TH, DWQI, and other physio-chemical and chemical parameters. Our approach utilizes linguistic variables, fuzzy rules, and the hyperbolic tangent set function to handle imprecise and uncertain water quality data. By employing Fuzzy C-Means clustering, we group similar water samples based on quality parameters and map membership values to linguistic terms representing water quality categories. Suitable defuzzification methods are then applied to convert fuzzy outputs into precise results. This proposed approach provides a comprehensive framework for accurate water quality assessment, enabling informed decision-making and more reliable and precise evaluations of groundwater quality.

Assessment of information security risks of automated system using neuro-fuzzy logic

Objective. Automated systems are widely used in production, and an important criterion for their reliability is information security. The aim of the study is to provide a balance between possible losses as a result of the implementation of threats and the cost of protection tools that reduce risks using neuro-fuzzy logic.Method. The developed model is based on the use of fuzzy logic.Result. A model of integrated information security risk assessment has been obtained, which can be practically applied for a comprehensive analysis of the effectiveness of organizing a protection system for automated systems operating in various fields of activity. The risk indicators of information security of an automated system, described with the help of linguistic variables, are revealed. Based on these indicators, information security risk assessments were obtained from the state of: software; technical support; information support; organizational and methodological support; the level of training and motivation of employees. The fuzzy production rules of the model are formulated to determine the integrated assessment of the information security of an automated system, providing a full account of all factors that have a significant impact on the level of security of an automated system.Conclusions. A feature of the proposed approach is the formalization of the assessment process, reducing the level of subjectivity in the formation of risk assessments.

Policy framework for selecting medical tourism destinations: fuzzy- IPA approach

ABSTRACT Using Fuzzy Importance-Performance Analysis (IPA) method, this study sought to develop a framework to identify and prioritize the factors influencing the selection of Iran by medical tourists. After a literature review, three main dimensions and 38 factors affecting tourism destination choices were identified. A Fuzzy SWARA questionnaire was used to ask experts how important each of the identified factors was to a medical tourist’s choice of destination. In addition, medical tourists employed linguistic variables to assess the performance of the aforementioned factors. The results of the study revealed that “recommendations by friends and acquaintances,” ‘medical tourist’s previous experiences, ‘“image/brand of the host country”, “having friends or relatives in the destination country,” and “international accreditation” were the top priorities for Iran’s medical tourism policymakers and managers.

Linguistic Empathy: Behavioral measures, neurophysiological correlates, and correlation with Psychological Empathy

Relations among behavioral, psychological, and electrophysiological correlates of Linguistic Empathy were examined in two experiments using lateralized stimuli. Linguistic Empathy is defined as a linguistic manifestation of the point of view the speaker assumes toward the content of the utterance, and of the speaker's attitude toward/identification with the referents therein. Linguistic choices made by the speaker among multiple logically and referentially synonymous lexical and grammatical options reveal the speaker's perspectives. In experiment 1, acceptability ratings were measured for Context-Target sentence pairs that did or did not violate two Empathy Hierarchies (Person Empathy Hierarchy and Topic Empathy Hierarchy); the Empathy Quotient (EQ) test of Psychological Empathy was also administered. Ratings were lower for sentence pairs that violated both hierarchies than for those violating neither and were intermediate for sentences violating only one hierarchy. Linguistic Empathy (LE) was operationalized as the difference in ratings between sentences violating both vs. neither empathy hierarchy; this measure correlated positively with EQ. Experiment 2 replicated those results with new participants and measured reaction time and EEG during ratings. While there were no effects of hemisphere or visual field on the linguistic variables, the amplitude of a positive event-related potential deflection at 380 ms provided a partial electrophysiological correlate for LE. Its difference measure correlated with behavioral LE but not with EQ. Though preliminary, these experiments show that Linguistic Empathy may share information processing computations with Psychological Empathy and have an electrophysiological correlate.

A design methodology based on two dimensional fuzzy linguistic variables for attribute control charts with real case applications

Attribute control charts (ACCs) effectively evaluate process’ situation based on nonconforming items (NCIs) and defects of items in a process. The traditional control charts (CCs) that analyze process control situations need a major adjustment to take into account uncertainties into eal case problems that can occur due to human evaluations and hesitancies, measurement systems errors, and process situations. The fuzzy set theory (FST) has been used successfully to reach this aim. Recently, some fuzzy set extensions have been integrated into traditional CCs to more extensively and sensitively model the uncertainty by involving other uncertainty parameters, such as non-membership value and hesitancy function. In this paper, one of these extensions, Pythagorean fuzzy sets (PFSs), has been adjusted with CCs to model the vagueness of human evaluations, their hesitancies, and uncertainties regarding the process. For this aim, the well-known ACCs based on the total count of defects and NCIs and called c, u, p, and np CCs, respectively, have been re-designed by using PFSs. Additionally, the control procedure of these CCs has been deeply analyzed with respect to fuzzy limit values and fuzzy measurements. Also, a rule-based approach that checks in-control and out-of-control situations regarding distance measurements is suggested to check the sample’s status more accurately. The proposed CCs based on PFSs have also been applied on a real case study from a manufacturing factory. The obtained results confirm that the CCs based on PFSs have an ability to create accurate, sensitive, and flexible results by using the input data while analyzing the process’ stability.

An optimisation study of PCM triple glazing for temperate climatic conditions – Dynamic analysis of thermal performance

PCM-windows can play an important role in the protection of buildings against overheating but also as systems for effective storage of solar energy. The presented study indicated the optimal solution for the triple-glazed window where one cavity is fullfilled with phase change material (PCM) in temperate climatic conditions characteristic for Poland. Regarding different thicknesses, positions, and temperatures of phase change material, the a recommended solution was determined using the simulation technique. The computational model was developed, numerically verified, and experimentally validated. The entire meteorological year analyses were done for the climatic conditions of Central Europe, considering windows exposed to facing the South. The optimal solution was determined using two methods - the Weighted Sum method and the Fuzzy Sets method. Both point out a variant with a PCM layer located in the inner cavity and the average melting temperature of PCM equal to 25 °C. However, different criteria and sets of linguistic variables in fuzzy sets determined different optimal PCM thicknesses ranging from 5 to 20 mm.

Spanish in the Southeast: What a Swarm of Variables Can Tell Us about a Newly Forming Bilingual Community

The southeastern United States has experienced rapid growth in the Hispanic population in recent decades, giving rise to a newly forming bilingual community. The present study builds on previous work by the authors via expansion of a “variable swarm”: the analysis of multiple linguistic variables simultaneously for the same set of speakers, with the goal of understanding patterns of accommodation and change within the community. The initial study included four linguistic variables (prosodic rhythm, bilingual discourse markers, the realization of /bdg/ and vowel space), and the present study adds an additional four variables (bilingual filled pauses, subject pronoun realization, code switching, and the labiodental realization of orthographic <v>) for 23 speakers of Mexican and Central American origin across two sociolinguistic generations (G1 vs. G2). Results for individual speakers show a pattern of adoption of some features by speakers of both generations (such as English-influenced prosodic rhythm and phonological filled pauses), while other, possibly more salient forms directly integrated from English (English discourse markers and code switching) exhibit later, highly variable rates of adoption, suggesting that speakers may consciously manipulate these variables as part of a process of active identity construction. Likewise, G1 speakers show fewer correlations among linguistic variables than G2 speakers, and patterns reveal that some bilingual forms are incorporated in tandem due to shared phonological traits or discourse functions. The innovative swarm analysis further contributes to the advancement of techniques employed in sociolinguistic research by serving as a bridge between traditional first- and second-wave studies that focus on a single variable, and third-wave studies that focus more on variation at the individual level.

Factors that moderate global similarity in initial L3 transfer

Abstract Much of the formal linguistic research on third language (L3) acquisition has focused on transfer source selection, with the overall finding that (global) structural similarity between the L1/L2 and L3 is the strongest predictor of initial transfer patterns. Recently, Cabrelli and Pichan (2021) reported data from the production of underlyingly intervocalic voiced stops in L3 Brazilian Portuguese (BP) and L3 Italian that highlight the notion that global similarity is likely moderated by other factors. Specifically, data from heritage Spanish/English bilinguals learning L3 BP reflected reliance on (non-facilitative, but globally more similar) Spanish, while L3 Italian data reflected greater reliance on (facilitative, but globally less similar) English. The current study is a first step towards identifying the source(s) of the disparity, in which we examine the roles of degree of dominance and explicit knowledge in heritage Spanish/English bilinguals. Thirty-four L3 Italian learners completed a delayed repetition task in all three languages. We report English-like patterns that contradict the L3 BP data and cannot be accounted for by degree of dominance or explicit knowledge. We connect these results to existing L3 transfer accounts and the need for further consideration of linguistic and methodological variables, particularly acoustic salience in L3 input and task modality.

Ukraine labour potential modelling based on using the theory of unclear logic

Purpose. To develop an effective approach to assessing the labour potential of Ukraine. Methodology. The research method is mathematical modelling based on the use of the “theory of fuzzy logic”. Findings. The factors influencing the labour potential of Ukraine are summarized and systematized, which are grouped into three groups: medical-demographic, socio-economic, and behavioural ones. The modelling algorithm is generalized and the linguistic variables that characterize the comprehensive assessment of the level of labour potential of Ukraine are proposed. A tree of logical conclusions of hierarchical relationships of factors with selected terms for evaluating the labour potential of Ukraine was built. Statistical data for Ukraine and 21 countries that are part of the EU is summarized, that made it possible to estimate the level of labour potential (R) for strategic partner countries ‒ Poland and Ukraine, which are 6.4 and 5.95, respectively. Recommendations are offered as for the development of the labour potential of Ukraine. Originality. The scientific novelty of the study is the development of a theoretical-methodological approach to the assessment of the labour potential of Ukraine, which allows comprehensively taking into account the system of fuzzy terms, to evaluate the medical-demographic, socio-economic and behavioural factors of influence on the labour potential of Ukraine based on the use of the theory of fuzzy logic. That, in turn, will allow increasing the effectiveness of the management decision-making system in the direction of improving all components that form the labour potential. Practical value. The importance of assessing labour potential for Ukraine lies in many aspects, the main ones are the following: increasing the efficiency of state administration in the field of labour potential formation; timely identification of problems, determination of the state and formation of strategic prospects for its development, which will allow accelerating the process of Ukraine’s transition from a candidate for EU membership to an EU member and revive the economy, that is currently based on the military rails.

Предварительная экспертная оценка глубины проработки задач, поставленных в диссертации, как косвенный показатель сроков ее завершения

The paper considers an approach that allows reducing the subjectivity of experts’ opinions when evaluating dissertations, as well as assessing the likelihood of their completion being successful. The approach is based on using expert evaluation expressed as linguistic variables on graduate students (adjuncts)’ elaboration depth of individual sections of their dissertations. Following this, an analytical model is formed, which is grounded on the theory of experiment planning.