Linguistic Uncertainty Research Articles

Assessing invasion risks using EICAT-based expert elicitation: application to a conservation translocation

Conservation translocations are widely used to recover threatened species, but can pose risks to recipient ecosystems, particularly in the case of conservation introductions. Because of limited data and uncertainty, risk assessments for such projects often rely on extrapolated evidence and expert opinion, further complicating decision making. The Environmental Impact Classification for Alien Taxa (EICAT) serves to classify the realised impacts of invasive species. We developed a protocol combining EICAT and formal expert elicitation to predict these impacts. We applied our protocol to the extinct-in-the-wild sihek (Guam kingfisher; Todiramphus cinnamominus), for which introduction outside the known historical range is being considered. We elicited from multiple experts probability estimates of impact levels across four impact mechanisms and five candidate release sites. We aggregated estimates using simulation-based and Bayesian approaches, with and without accounting for expert confidence. Experts generally agreed that sihek introduction might impact the recipient ecosystem through predation, competition, and disease, although they disagreed about the likely impact levels. Releases to Palmyra Atoll were considered to pose the lowest risk across candidate sites, so this site was selected for further detailed ecological assessments and risk mitigation efforts. EICAT, with its standardized impact mechanisms and definitions, helped reduce the linguistic uncertainty and subjectivity common to expert-based assessments. Expressing judgments as probabilities allowed us to evaluate uncertainty transparently and to assess the weight of expert confidence on the overall risk estimation. Formal quantitative elicitation and aggregation then allowed a transparent evaluation of results, facilitating communication with stakeholders and decision-makers.

The Influence of Digital and Technology Equipment in Learning Activities on Students' Written Skills

This research aims to observe how students develop their written narrative skills. This research uses survey instruments and questionnaires as data collection methods. Statistical methods are used in data analysis. One hundred students were involved in this research, except those who only wrote less than seven texts from the research sample. The study results show that students experience significant development in their linguistic expression in written communication situations. Their ability to produce texts becomes richer at the linguistic level, with increased lexical diversity in nominal and verbal areas. They also showed a better ability to use sentence-connecting devices. However, there are differences between students who use their mother tongue and those who use their second language in terms of lexis and syntax. Students who use their mother tongue tend to use less and less varied lexis than their second language. In addition, students also showed higher linguistic uncertainty, especially in terms of case inflection and syntax. Nevertheless, there are no significant differences between the two language groups regarding the global structure of the texts. The results of this study provide important insights for language education at the primary school level, showing that students who use their mother tongue have sufficient ability to carry out narrative tasks in a manner comparable to students who use a second language of the same age. However, it should be noted that the development of language skills in students who use their mother tongue may take longer and require special attention in language learning.

Korpora im DaF-Unterricht: Einsatz im Schulbereich

Corpora are electronic resources that students can use – in the context of data-driven learning – to explore language and clear up any linguistic uncertainties, by searching, for example, for frequent co-occurrences and collocations through a search query. Corpora serve as input factors (cf. Fandrych/Tschirner 2007) that draw the learners’ attention to recurring linguistic patterns (cf. Drumbl 2011: 67) and promote autonomous and explorative learning. This process also enables the development of language awareness (cf. Boulton 2010), which is a key element of multilingual competence (cf. Jessner 2008). The use of corpora is increasingly being integrated into university foreign language teaching but remains rather unknown in the school sector to date. This article explores how corpora could be used in schools and the extent to which students could work with them autonomously to improve their language skills and develop, over time, multilingual competence. To answer this question, a project carried out in an Italian high school specialized in the study of foreign languages (Liceo Linguistico) is examined and presented. The project took place in 2021 and required students to undertake several corpus analysis tasks.

Эстологическое исследование государственной символики Японии

The study of problems of constitutional and legal regulation using estological methods continues. The origin, development and operation of the constitutional and legal status of the state symbols of Japan is considered (an estological study of one of the institutions of Japanese constitutional law). Empirical materials and authentic documents (sources of law, acts of interpretation of law, acts of implementation and application of law) of Japan are introduced into scientific circulation. Conclusive constitutional and legal norms that have significant signs of legal and linguistic uncertainty are subject to esthological research. Based on the study of the patterns of existence of interests in constitutional law and the interests of constitutional legal regulation in Japan, conclusions are synthesized about the meaning and content of state symbols, its legal and technical features. As a result of the study, the presence of a phenomenology of interests of constitutional and legal regulation is revealed. The hypothesis is confirmed that the interests of legal regulation differ from the political interests of subjects of constitutional law.

Methods of judicial argumentation in case of semantic uncertainty of a legal text

While in non-legal texts linguistic uncertainty either does not hinder normal linguistic practices or can be removed by clarifications, the elimination of uncertainty in legal texts is complicated since peculiarities of legal language precludes its complete exclusion. Accordingly, the task of overcoming legal uncertainty is delegated to the judge and the question arises as to what methods of dealing with the legal text are applicable. The article examines the approaches distinguished in the theory of legal argumentation to assess whether they can offer a methodology which will be able to overcome the policy consequences of the language “open texture” as a characteristic of uncertainty of the natural language in which legal texts are presented by formalizing the process of choosing one of the possible options of the legal text interpretation in judicial decisions. The author concludes that the methods to deal with an uncertain legal text offered by the topicalrhetorical and dialectical approach are limited to the formulation of requirements for the process of argumentation (which do not guarantee absolute predictability of the decision to be made), as well as criteria to evaluate the justification of the decision retrospectively. In turn, the possibility to critically assess the arguments limits the arbitrariness, forcing the judge to follow standards of acceptability and sufficiency of the reasoning to justify their decision.

A Model Proposal for Scaling the Productivity Increase in Agile Project Management Methodology

Project management in the software industry is the process of successfully planning, managing, and completing software development projects. Software projects can often be complex, constantly changing, and full of uncertainties, so project management is of particular importance in the software industry. There are two basic approaches to the execution of software projects. In the waterfall model, the project stages are operated in the determined order and after each stage is completed, the next stage is passed, while in the agile approach, the project is divided into small and priority parts, and the work processes are repeated at regular intervals and improvements are made depending on the feedback received. Recently, there has been a trend towards managing software projects with agile methodologies, as it provides flexibility and adaptability. However, there is no quantitative evaluation of the benefits of agile structuring both in the literature and in the sector, and this benefit is expressed with verbal expressions referring to the formation of a dynamic culture. For this reason, the productivity increase brought by the agile project approach cannot be measured and the benefit it provides cannot be scaled. In this study, a model that takes linguistic uncertainty into account is proposed to quantitatively scale the productivity increase provided by agile project structuring. The proposed model has been applied in a business where enterprise resource planning solutions have been developed and the effect of the transition from waterfall model to agile methodology on the productivity of the project has been investigated. Within the framework of the procedure proposed by the model, expert evaluations were taken in line with the determined quantitative and qualitative criteria, these criteria were listed with the fuzzy SWARA method, and the productivity increase provided by agile methodology was calculated using this information. The findings also allowed us to get an idea of the point of scaling the increase in productivity across the industry.

Commenting on learning Korean on TikTok and YouTube

ABSTRACT Online informal language learning has surged due to the growing interaction on social networking sites, such as TikTok and YouTube. One vital interaction method is through comments, revealing insights into learner behaviors and thoughts. Concurrently, the Korean Wave has made Korean a sought-after language. This study examined comments under Korean language learning hashtags on TikTok and YouTube in English and Spanish. From 570 comments, three themes were discerned: (1) those oriented towards the video creator, (2) those focused on the community, and (3) those highlighting Korean language understanding. Findings indicate that these comments foster a supportive environment for sharing experiences and resources while addressing content inaccuracies or linguistic uncertainties. However, there was no interaction in Korean within these comments. Hence, while videos provide linguistic input, comments mainly facilitate metalinguistic reflection, but not a space for interactive Korean language use.

Fuzzy Inference System (FIS) Model for the Seismic Parameters of Code-Based Earthquake Response Spectra

The response spectra defined in seismic design codes include crisp classifications of seismic parameters, which directly affect the spectra’s shape and greatly alter seismic design loads. The optimum design phase seismic forces have an important role in the efficiency of the construction costs and structural safety. Various parameters are used to calculate the seismic design forces, especially presented in the codes with earthquake design spectra. This study presents a rule-based fuzzy inference model with fuzzy sets to determine these parameters using fuzzy inference system (FIS) modelling, which is the most appropriate approach among the different alternatives because both the input and output variables have numerical and linguistic uncertainties in the earthquake problem. Using the seismic zone factor of the region and shear wave velocity of the soil profile as inputs, the model generates the seismic coefficients and peak ground acceleration values of the response spectra specified in the Uniform Building Code (UBC, 1997). The response spectra in this code can be easily generated with these seismic coefficients after their fuzzification. Response spectra of twenty-five different sample cases with and without the FIS model are generated, which provide comparisons for the model superiority assessment. Significant differences are observed between the crisp logic and the FIS model-generated spectra. It is suggested that the FIS model can be modified and applied to various parameters to generate response spectra in different seismic design codes.

The Problem of Language Insecurity of Azerbaijani School Graduates Living in Russia: Methods of Overcoming it

The object of the study is the linguistic uncertainty of Azerbaijanis who live in Russia. The subject of the study is the causes of the phenomenon of language insecurity among graduates of Azerbaijani schools who received education in Russian in Azerbaijan, as well as the main reasons of a social and individual nature that contribute to its manifestation. The article describes the main reasons that have become the source of language insecurity among graduates of Azerbaijani schools who have received general secondary education in Russian in Azerbaijan. The authors of the article investigated the existing methods of teaching Russian in schools in Azerbaijan, the main problems that arise during the teaching of students, as well as obstacles that may affect the process of formation of language skills and knowledge of students. In order to study the causes of language insecurity among graduates of Azerbaijani schools in the course of communication while in the Russian Federation, we conducted a series of interviews with graduates of a number of schools in the capital of the country, in the city of Baku. The definition of the concept of language insecurity is given and the main reasons of both social and individual nature are shown, contributing to the manifestation of language insecurity in a number of students who have graduated from Azerbaijani schools with the Russian language of instruction.

Canonical triangular interval type-2 fuzzy set linguistic distribution assessment TODIM approach: A case study of FMEA for electric vehicles DC charging piles

Linguistic distribution assessment (LDA) plays a prominent role in describing the subjective uncertainties and objective distribution of decision-maker (DM) opinions. Although there have been several studies on LDA, few of these studies have paid attention to the different understandings of language semantics provided by DMs. To address the issue, type-2 (T2) fuzzy sets (T2FSs) are a well-known approach because T2FSs can accurately model the understanding of individuals with linguistic uncertainty. A trapezium (or trapezoidal) interval type-2 fuzzy set (TrIT2FS) is a common application of T2 fuzzy logic. Accordingly, this paper discusses a novel LDA called a canonical triangular interval type-2 fuzzy set (CTriIT2FS)-LDA in a T2 fuzzy environment. The CTriIT2FS-LDA combines a CTriIT2FS simplified from a TrIT2FS with LDA, which can simplify the computation while retaining their advantages. To facilitate the calculation of the CTriIT2FS-LDA, the basic operations of the CTriIT2FSs and the CTriIT2F-LDA, such as the defuzzied (crisp) function, distance measurement, and entropy measurement, are defined. Based on the TODIM approach, a CTriIT2F-LDA-TODIM is developed for FMEA for interval type-2 fuzzy environments. Furthermore, the proposed approach is applied in a practical case for FMEA for the electric vehicle DC charging piles of the State Grid Corporation of China.

When linguistic uncertainty spreads across pieces of information: Remembering facts on the news as speculation.

Modern media enable rapid reporting that does not refer to facts alone but is often interspersed with unconfirmed speculations. Whereas previous research has concentrated primarily on how unconfirmed contents might propagate, potential memory effects of reporting confirmed facts among speculations have so far been widely disregarded. Across four experiments, we show that the presence of speculative news (indexed by uncertainty cues such as "might") can reduce the remembered certainty of unrelated facts. The participants read headlines with exclusively speculative news, exclusively factual news, or a mixture of both. Our results indicate that uncertainty cues spread onto one's recollection of unrelated facts after having read a mixture of facts and speculations. This tendency persisted when both types of news were presented sequentially (e.g., factual news first), suggesting that the presence of speculative news does not specifically affect encoding-but can overshadow memories of facts in retrospect. Further, the tendency to misremember facts as speculations emerged even when the proportion of speculations among factual news was low (6/24 headlines) but increased linearly with the number of speculations intermingled. Given the widespread dissemination of speculative news, this bias poses a challenge in effectively getting confirmed information across to readers. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Type-1 and Interval Type-2 Fuzzy Systems [AI- eXplained

Fuzzy sets are suitable for modeling human linguistic uncertainties, and the resulting fuzzy systems can then be used to perform inferences based on a linguistic rulebase. They have been successfully used in numerous applications, particularly controls. This short paper introduces the basics of type-1 and interval type-2 fuzzy sets and systems, particularly for newcomers. The online full paper at IEEE Xplore provides detailed examples for better understanding, and interactive components for a hands-on exploration.

Эстологическое исследование государственной символики Монголии

The genesis of the formation and the current constitutional and legal status of the state symbols of Mongolia is considered. The material is built on the basis of the use of the latest author’s methodology and scientific research technology (esthological research of the constitutional law of Mongolia). Empirical materials and authentic documents (sources of law, acts of interpretation of law, acts of implementation and application of law) of Mongolia are introduced into scientific circulation. Conclusive constitutional and legal norms are subject to esthological research, which, according to the author, have significant signs of legal and linguistic uncertainty. Based on the study of the patterns of existence of interests in constitutional law and the interests of constitutional and legal regulation in Mongolia, conclusions are synthesized about the meaning and content of state symbols, its legal and technical features. As a result of the study, the presence of a phenomenology of interests of constitutional and legal regulation is revealed. The hypothesis is confirmed that the interests of legal regulation differ from the political interests of subjects of constitutional law.

Applications of Fuzzy in the Field of Medicine

Abstract: In this paper fuzzy sets have been applied to many fields in which uncertainty plays a key role. Medicine, often on the borderline between science and art, is an excellent exponent: vagueness, linguistic uncertainty, hesitation, measurement imprecision, natural diversity, subjectivity all these are prominently present in medical diagnosis.

АНАЛИЗ ТОНАЛЬНОСТИ ТЕКСТОВЫХ ОТЗЫВОВ С ПРИМЕНЕНИЕМ ТОНАЛЬНЫХ СЛОВАРЕЙ И КАРДИНАЛЬНОСТИ НЕЧЕТКОГО МНОЖЕСТВА

Sentiment or opinion analysis aims to determine the polarity of people's opinions in relationto any product, service, event or any person. One of the most common methods used in sentimentanalysis of text content is natural language processing. Sentiment analysis of natural languagetext can be assessed using numerous methodologies such as machine learning algorithms andstatistical tools, while the application of fuzzy logic is not common. The use of fuzzy logic waschosen for the following reasons. First, fuzzy logic handles linguistic uncertainty well. This way ofdefining the problem leads to a reduction in bias, both positively and negatively. Secondly, learning approaches based on fuzzy rules are fundamentally different from those learning approachesthat are widely used in sentiment classification, such as support vector machines, naive Bayes,etc., as they relate to generative learning, i.e. i.e. the goal of learning is to assess the degree towhich an instance belongs to each individual class. The proposed model for sentiment analysis oftext reviews is based on the use of tone lexicons using fuzzy logic and consists of four main stages.The steps include tokenization, word bag model formulation, sentiment fuzzy score formulation,and polarity assignment. In the proposed model, the power of the fuzzy set is used as a measure ofthe evaluation of the indicators of the polarity of words. Word polarity values are obtained byapplying two sentiment lexicons: SentiWordNet and AFINN. Two versions of the model were createddepending on the type of vocabulary used: based on SentiWordNet and AFINN. Comparisonof the presented approach based on fuzzy logic with other dictionary-based methods demonstratesthe superiority of the developed models based on the application of fuzzy logic.

The Role of Cognitive Biases in the Prescribing and Deprescribing of Opioids

The policies and guidelines which have shaped the attitude and practice relating to the use of opioids for the treatment of chronic pain have undergone remarkable changes. Recent decades have witnessed a surge, followed by a decline, and near prohibition, in the use of opioids. Cognitive biases appeared to be play an important role in how the scientific data upon which policy and guidelines are based is presented, and interpreted. These biases may have had a greater influence on policymakers than the data itself. This paper reviews data from four key areas identified as relating to the use of opioids, and the creation of guidelines including (a) the surge and decline in opioid prescribing, (b) sham distinctions, (c) reliance on the numerical pain rating (NPR) and (d) the consequences associated with the use/discontinuation of opioids. Published studies, commentaries, and guidelines were selected based on their ability to illustrate a particular bias and/or to highlight discrepancies in the scientific literature. Discrepancies and inconsistences in the presentation and interpretation of data in these areas were identified. Focused illusion, linguistic uncertainty, and heuristic failure were found to be prevalent cognitive biases. Cognitive biases appear to be influential in the making of policy and guidelines related to the sue of opioids. Overlooking these biases may result in decisions that negatively impact clinical practice and patient safety

Enhanced type-2 Wang-Mendel Approach

ABSTRACT The Wang-Mendel Approach (WMA) focuses on combining the numerical as well as linguistic information for achieving greater explainability for inference models. The standard WMA models the linguistic information using type-1 (T1) fuzzy sets (FSs), which have a reduced capability to model the semantics of linguistic information. Therefore, we propose a novel Enhanced WMA, which models the linguistic information using the type-2 (T2) FSs. Further, our Enhanced T2 FS-based WMA can be modified to reflect the use of interval type-2 (IT2) FSs, for modelling linguistic uncertainty. IT2 FSs are suitable when better uncertainty handling capabilities are required compared to T1 FSs, however, at a computational cost lesser than the T2 FSs. Performance of Enhanced WMA is demonstrated through a real-world crop-yield prediction problem in smart agriculture and an additional exemplar application on users’ satisfaction ratings. Further, we have compared our approach with the performance obtained from the T1 FS-based WMA and the original estimations given in the original data. We found that our Enhanced WMA provides more precise estimates than the other two with 95% confidence level. To the best of our knowledge, this is the first proposal of a T2 FSs method for enhancing the modeling of linguistic uncertainty in the WMA.

Novel Distance-Measures-Based Extended TOPSIS Method under Linguistic Linear Diophantine Fuzzy Information

The advantages of the intuitionistic fuzzy set, Pythagorean fuzzy set, and q-rung orthopair fuzzy set are all carried over into the linear Diophantine fuzzy set by extending the restrictions on the grades. Linear Diophantine fuzzy sets offer a wide range of practical applications because the reference parameters allow evaluation andto express their judgments about membership and nonmembership degrees in a variety of ways. Linguistic-valued information cannot be described by linear Diophantine fuzzy numbers since precise numbers are used in linear Diophantine fuzzy systems. In this paper, we first present the novel idea of a linguistic linear Diophantine fuzzy set, which is the hybrid structure of the linear Diophantine fuzzy set and the linguistic term set. Furthermore, some basic operational rules with novel distance measures, namely, Hamming, Euclidean, and Chebyshev distance measures, are established. Based on the newly defined concept of distance measure, an extended TOPSIS technique is presented to tackle the linguistic uncertainty in real-world decision support problems. A numerical example is illustrated to support the applicability of the proposed methodology and to analyze symmetry of the optimal decision. A comparison analysis is constructed to show the symmetry, validity, and effectiveness of the proposed method over the existing decision support techniques.

Consistency in impact assessments of invasive species is generally high and depends on protocols and impact types

Impact assessments can help prioritising limited resources for invasive species management. However, their usefulness to provide information for decision-making depends on their repeatability, i.e. the consistency of the estimated impact. Previous studies have provided important insights into the consistency of final scores and rankings. However, due to the criteria to summarise protocol responses into one value (e.g. maximum score observed) or to categorise those final scores into prioritisation levels, the real consistency at the answer level remains poorly understood. Here, we fill this gap by quantifying and comparing the consistency in the scores of protocol questions with inter-rater reliability metrics. We provide an overview of impact assessment consistency and the factors altering it, by evaluating 1,742 impact assessments of 60 terrestrial, freshwater and marine vertebrates, invertebrates and plants conducted with seven protocols applied in Europe (EICAT; EPPO; EPPO prioritisation; GABLIS; GB; GISS; and Harmonia+). Assessments include questions about diverse impact types: environment, biodiversity, native species interactions, hybridisation, economic losses and human health. Overall, the great majority of assessments (67%) showed high consistency; only a small minority (13%) presented low consistency. Consistency of responses did not depend on species identity or the amount of information on their impacts, but partly depended on the impact type evaluated and the protocol used, probably due to linguistic uncertainties (pseudo-R2 = 0.11 and 0.10, respectively). Consistency of responses was highest for questions on ecosystem and human health impacts and lowest for questions regarding biological interactions amongst alien and native species. Regarding protocols, consistency was highest with Harmonia+ and GISS and lowest with EPPO. The presence of few, but very low, consistent assessments indicates that there is room for improvement in the repeatability of assessments. As no single factor explained largely the variance in consistency, low values can rely on multiple factors. We thus endorse previous studies calling for diverse and complementary actions, such as improving protocols and guidelines or consensus assessment to increase impact assessment repeatability. Nevertheless, we conclude that impact assessments were generally highly consistent and, therefore, useful in helping to prioritise resources against the continued relentless rise of invasive species.

Application of Type 2 Fuzzy for Maximum Power Point Tracker for Photovoltaic System

Photovoltaic systems (PV) are becoming more popular as a way to make electricity because they offer so many benefits, such as free solar irradiation to harvest and low maintenance costs. Moreover, the system is environmentally friendly because it neither emits noxious gases nor generates environmental noise. Consequently, during the operation of a PV system, the working environment is free of all types of pollution. Despite the aforementioned advantages, a photovoltaic (PV) system’s performance is significantly impacted by the fluctuation in electrical charges from the panel, such as shading conditions (PSC), weather conditions, and others, which significantly lowers the system’s efficiency. To operate the PV modules at their peak power, maximum-power point tracking (MPPT) is employed. As a result of the various peaks present during fluctuating irradiance, the P-V curves become complex. Traditional methods, such as Perturb and Observe (P and O) have also failed to monitor the Global Maximum Power Point (GMPP), therefore they usually live in the Local Maximum Power Point (LMPP), which drastically lowers the efficiency of the PV systems. This study compares type 2 fuzzy logic (T2-FLC) with the traditional Perturb and Observe Method (P and O) in three different scenarios of irradiance, temperature, and environmental factors, in order to track the maximum power point of photovoltaics. Type 1 fuzzy logic (T1-FLC) is not appropriate for systems with a high level of uncertainty (complex and non-linear systems). By modelling the vagueness and unreliability of information, type 2 fuzzy logic is better equipped to deal with linguistic uncertainties, thereby reducing the ambiguity in a system. The result for three conditions in terms of four variables; efficiency, settling time, tracking time, and overshoot, proves that this strategy offers high efficiency, dependability, and resilience. The performance of the proposed algorithm is further validated and compared to the other three tracking techniques, which include the Perturb and Observe methods (P and O). The particle swarm algorithm (PSO) and incremental conductance method results show that type 2 fuzzy (IT2FLC) is better than the three methods mentioned above.