Information Security Evaluation of Industrial Control Systems Using Probabilistic Linguistic MCDM Method

Industrial control systems(ICSs)are widely used in various fields,and the information security problems of ICSs are increasingly serious.The existing evaluation methods fail to describe the uncertain evaluation information and group evaluation information of experts.Thus,this paper introduces the probabilistic linguistic term sets(PLTSs)to model the evaluation information of experts.Meanwhile,we propose a probabilistic linguistic multi-criteria decision-making(PL-MCDM)method to solve the information security assessment problem of ICSs.Firstly,we propose a novel subscript equivalence distance measure of PLTSs to improve the existing methods.Secondly,we use the Best Worst Method(BWM)method and Criteria Importance Through Inter-criteria Correlation(CRITIC)method to obtain the subjective weights and objective weights,which are used to derive the combined weights.Thirdly,we use the subscript equivalence distance measure method and the combined weight method to improve the probabilistic linguistic Visekriterijumska Optimizacija I Kompromisno Resenje(PL-VIKOR)method.Finally,we apply the proposed method to solve the information security assessment problem of ICSs.When comparing with the existing methods such as the probabilistic linguistic Tomada deDecisão Iterativa Multicritério(PL-TODIM)method and probabilistic linguistic Technique for Order Preference by Similarity to Ideal Solution(PL-TOPSIS)method,the case example shows that the proposed method can provide more reasonable ranking results.By evaluating and ranking the information security level of different ICSs,managers can identify problems in time and guide their work better.

An Evidence-Based CoCoSo Framework with Double Hierarchy Linguistic Data for Viable Selection of Hydrogen Storage Methods

Hydrogen is the new age alternative energy source to combat energy demand and climate change.Storage of hydrogen is vital for a nation’s growth.Works of literature provide different methods for storing the produced hydrogen,and the rational selection of a viable method is crucial for promoting sustainability and green practices.Typically,hydrogen storage is associated with diverse sustainable and circular economy(SCE)criteria.As a result,the authors consider the situation a multi-criteria decision-making(MCDM)problem.Studies infer that previous models for hydrogen storage method(HSM)selection(i)do not consider preferences in the natural language form;(ii)weights of experts are not methodically determined;(iii)hesitation of experts during criteria weight assessment is not effectively explored;and(iv)three-stage solution of a suitable selection of HSM is unexplored.Driven by these gaps,in this paper,authors put forward a new integrated framework,which considers double hierarchy linguistic information for rating,criteria importance through inter-criteria correlation(CRITIC)for expert weight calculation,evidence-based Bayesian method for criteria weight estimation,and combined compromise solution(CoCoSo)for ranking HSMs.The applicability of the developed framework is testified by using a case example of HSM selection in India.Sensitivity and comparative analysis reveal the merits and limitations of the developed framework.

Critical Discourse Analysis Based on Halliday’s Systemic Functional Linguistics: Taking The Economist’s First Commentation on the End of China’s Zero-COVID Policy as an Example

Based on Halliday’s systemic functional grammar,especially the ideational function,this research aims at disclosing the hidden ideologies and values of the seemingly objective news reports on China’s COVID-19 policies in The Economist.Transitivity,voice,and nominalization are the major analytical subjects.After China lifted the zero-COVID policy,western media began criticizing China’s lack of data sharing,with some misinformation and misleading reports.The denouncement of inertness and reluctance to fight against the pandemic disclaim the Chinese government’s efforts and depreciate China’s image.China is portrayed as the villain and destroyer of people’s health worldwide.Meanwhile,they also hold a hesitant attitude toward China’s diplomacy.The re-engaging with foreign countries and travel restrictions have been described as imprudent and rushed actions.They also consider China as the fuse of contradiction in the United Nations.What is overt is their view of breaking up China.

Linguistic Features of Oral English Corpora and Their Implications for English Teaching in Colleges and Universities

The main goal of English teaching in colleges and universities is to cultivate students’ability to use the language,but many students are still unable to complete oral communication fluently after years of study.For this reason,teachers need to deeply analyze and study the linguistic features of oral English corpora and formulate reasonable teaching strategies to improve students’oral expression skills.This paper outlines the linguistic features of oral English corpora,comparatively analyzes the differences between oral English corpora and written English corpora,and explores effective teaching strategies,hoping to provide guidelines for relevant teachers.

The Determination Method of Product Engineering Features Based on Linguistic Variables

To overcome the problem of imprecise and unclear information in the development of quality functions,a method for determining the priority of engineering features based on mixed linguistic variables is proposed.First,the evaluation member uses the determined linguistic variable to give the correlation strength evaluation matrix of customer requirements and engineering features.Secondly,the relative importance of the evaluation member and customer requirements are aggregated.Finally,the priority of engineering features is obtained by calculating the deviation.The feasibility and practicability of this method are proven by taking the design of a new product of a long bag low-pressure pulse dust collector as an example.

A Study on the Utilization of Applied Linguistics in Contemporary English Teaching

In the context of globalization,the importance of teaching English as a common language in the world becomes increasingly apparent.Applied Linguistics belongs to one of the sub-disciplines of linguistics,which plays an important role in contemporary English teaching.The knowledge of applied linguistics can help students learn the grammar,semantics,vocabulary,writing,and other contents in English,deepen their knowledge and understanding of English,and enhance the effectiveness of English teaching.This paper mainly describes the important role played by English linguistics in English teaching and focuses on its utilization strategies in the hope of providing references on this topic.

A Study of English Grammar Teaching and Cultural Introduction from the Perspective of Applied Linguistics

Grammar teaching is the main content of university English teaching,and the quality of teaching will affect the effect of university talent cultivation.Based on the perspective of applied linguistics,it is crucial to use cultural introduction teaching for English grammar teaching.This paper will combine the basic concepts of applied linguistics and cultural introduction teaching,analyze the role of using the cultural introduction teaching method to innovate grammar teaching mode under the perspective of applied linguistics,and put forward a scientific English grammar teaching strategy with the goal of improving teaching quality.

Evolution and Continuity of Linguistic Systems

In the inspiring extract highlighted in this paper,Saussure observes how the relation between the elements of the sign change and evolve over time.In his Cours,he also details the elements of the linguistic sign and the principles governing them,defining language as a system of signs.Despite the natural resistance to changes in language in order to enable it to continually fulfill its function,that is,despite the necessary immutability of linguistic signs,they change over time,by being in constant contact with the communities of speakers,to whom language actually belongs.This may seem paradoxical because language is composed of arbitrary relations between signified and signifier that seek to represent concepts.Saussure refers to a principle of change in language linked to a principle of continuity.The present study focuses on the semiotic and communicational aspects of the development of linguistic systems in time,understood from a systemic perspective.It is sought to evince how signs perpetuate themselves and evolve through their constant interaction with real communities of language users.This approach can offer new insights about the continuity of linguistic systems as systems of signs that present immutable and mutable characters,and whose evolution can be understood based on open systems parameters,such as permanence,autonomy and sensitivity to flows of information,as studied by current theories and authors,showing that,to preserve its semiological life (CGL,1959,p.76),a living language must continuously reflect the purposes of its users.

The Application of Systemic-Functional Linguistics in Discourse Analysis

Systemic-functional linguistics considers function and semantics as the basis of human language and communicative activity. In recent years, Systemic-functional linguistics has been applied in such areas as natural language processing, early language learning, language education, stylistics, foreign language teaching, translation and stylistics. It sheds new light on the further application of this linguistic theory in other fields.

Systemic-Functional Linguistics and Foreign Language Teaching

Systemic-functional linguistics is one of the most influential linguistics schools in the recent 20 years.Though M.A.K.Halliday,the founder of Systemic-functional Linguistics,has not taken up any language teaching research by himself,he has been putting great emphasis on language teaching and language learning.With the increasing influence of Systemic-functional Linguistics,more and more applied linguists and foreign language teachers are trying to use his theories to solve the problems in language teaching and learning,and have achieved a lot.

Sine Cosine Optimization with Deep Learning-Based Applied Linguistics for Sentiment Analysis on COVID-19 Tweets

Applied linguistics is an interdisciplinary domain which identifies,investigates,and offers solutions to language-related real-life problems.The new coronavirus disease,otherwise known as Coronavirus disease(COVID-19),has severely affected the everyday life of people all over the world.Specifically,since there is insufficient access to vaccines and no straight or reliable treatment for coronavirus infection,the country has initiated the appropriate preventive measures(like lockdown,physical separation,and masking)for combating this extremely transmittable disease.So,individuals spent more time on online social media platforms(i.e.,Twitter,Facebook,Instagram,LinkedIn,and Reddit)and expressed their thoughts and feelings about coronavirus infection.Twitter has become one of the popular social media platforms and allows anyone to post tweets.This study proposes a sine cosine optimization with bidirectional gated recurrent unit-based senti-ment analysis(SCOBGRU-SA)on COVID-19 tweets.The SCOBGRU-SA technique aimed to detect and classify the various sentiments in Twitter data during the COVID-19 pandemic.The SCOBGRU-SA technique follows data pre-processing and the Fast-Text word embedding process to accomplish this.Moreover,the BGRU model is utilized to recognise and classify sen-timents present in the tweets.Furthermore,the SCO algorithm is exploited for tuning the BGRU method’s hyperparameter,which helps attain improved classification performance.The experimental validation of the SCOBGRU-SA technique takes place using a benchmark dataset,and the results signify its promising performance compared to other DL models.

A Hybrid Learning Method for the Data-Driven Design of Linguistic Dynamic Systems

In lots of data based prediction or modeling applications,uncertainties and/or noises in the observed data cannot be avoided.In such cases,it is more preferable and reasonable to provide linguistic(fuzzy)predicted results described by fuzzy memberships or fuzzy sets instead of the crisp estimates depicted by numbers.Linguistic dynamic system(LDS)provides a powerful tool for yielding linguistic(fuzzy)results.However,it is still difficult to construct LDS models from observed data.To solve this issue,this paper first presents a simplified LDS whose inputoutput mapping can be determined by closed-form formulas.Then,a hybrid learning method is proposed to construct the data-driven LDS model.The proposed hybrid learning method firstly generates fuzzy rules by the subtractive clustering method,then carries out further optimization of centers of the consequent triangular fuzzy sets in the fuzzy rules,and finally adopts multiobjective optimization algorithm to determine the left and right end-points of the consequent triangular fuzzy sets.The proposed approach is successfully applied to three real-world prediction applications which are:prediction of energy consumption of a building,forecasting of the traffic flow,and prediction of the wind speed.Simulation results show that the uncertainties in the data can be effectively captured by the linguistic(fuzzy)estimates.It can also be extended to some other prediction or modeling problems,in which observed data have high levels of uncertainties.

An Exploration of the English Reading Instruction Model with a Systemic Functional Linguistic Perspective

Reading is an important channel for students to acquire knowledge and information.Therefore,exploring an effective reading instructional model to improve students’reading ability is one of the main goals of today’s university English teaching.The model of English reading instruction based on the theory of systemic functional linguistics is designed to study how teachers can apply this theory to the teaching of reading in order to improve students’reading comprehension.

10-Elements Linguistic Truth-Valued Intuitionistic Fuzzy First-Order Logic System

This paper presents 10-elements linguistic truth-valued intuitionistic fuzzy algebra and the properties based on the linguistic truth-valued implication algebra which is fit to express both comparable and incomparable information.This method can also deal with the uncertain problem which has both positive evidence and negative evidence at the same time.10-elements linguistic truthvalued intuitionistic fuzzy first-order logic system has been established in the intuitionistic fuzzy algebra.

Resolution Method of Six-Element Linguistic Truth-Valued First-Order Logic System

Based on 6-elements linguistic truth-valued lattice implication algebras this paper discusses 6-elements linguistic truth-valued first-order logic system. With some special properties of 6-elements linguistic truth-valued first-order logic, we discussed the satisfiable problem of 6-elements linguistic truth-valued first-order logic and proposed a resolution method of 6-elements linguistic truth-valued firstorder logic. Then the resolution algorithm is presented and an example illustrates the effectiveness of the proposed method.

On Boolean elements and derivations in 2-dimension linguistic lattice implication algebras

A 2-dimension linguistic lattice implication algebra(2DL-LIA)can build a bridge between logical algebra and 2-dimension fuzzy linguistic information.In this paper,the notion of a Boolean element is proposed in a 2DL-LIA and some properties of Boolean elements are discussed.Then derivations on 2DL-LIAs are introduced and the related properties of derivations are investigated.Moreover,it proves that the derivations on 2DL-LIAs can be constructed by Boolean elements.

Multidimensional Quality Evaluation of Graduate Thesis:Based on the Probabilistic Linguistic MABAC Method

Graduate education is the main way to train high-level innovative talents,the basic layout to cope with the global talent competition,and the important cornerstone for implementing the innovation-driven development strategy and building an innovation-driven country.Therefore,graduate education is of great remarkably to the development of national education.As an important manifestation of graduate education,the quality of a graduate thesis should receive more attention.It is conducive to promoting the quality of graduates by supervising and examining the quality of the graduate thesis.For this purpose,this work is based on textmining,expert interviews,and questionnaire surveys to obtain the factors influencing the quality of a graduate thesis first.Then,through three rounds of expert consultation,a multidimensional evaluation indicator system for the graduate thesis quality is built.Furthermore,probabilistic linguistic termsets(PLTSs)are utilized to obtain the initial evaluation information and apply the stepwise weight assessment ratio analysis method to determine the weights of attributes.In the ensuing step,the novel multi-attribute border approximation area comparison based on the PLTS method is established.Finally,the proposed method is employed in a case study concerning the quality evaluation of a graduate thesis and the effectiveness of this approach is further illustrated.

A Multi-Attribute Decision-Making Method Using Belief-Based Probabilistic Linguistic Term Sets and Its Application in Emergency Decision-Making

Probabilistic linguistic term sets(PLTSs)are an effective tool for expressing subjective human cognition that offer advantages in the field ofmulti-attribute decision-making(MADM).However,studies have found that PLTSs have lost their ability to accurately capture the views of decision-makers(DMs)in certain circumstances,such as when the DM hesitates between multiple linguistic terms or the decision information is incomplete,thus affecting their role in the decision-making process.Belief function theory is a leading streamof thought in uncertainty processing that is suitable for dealing with the limitations of PLTS.Therefore,the purpose of this study is to extend PLTS to incorporate belief function theory.First,we provide the basic concepts of the extended PLTS(i.e.,belief-based PLTS)through case analyses.Second,the aggregation operator of belief-based PLTS is defined with the ordered weighted average(OWA)-based soft likelihood function,which is improved by considering the reliability of the information source.Third,to measure the magnitude of different belief-based PLTSs,the belief interval of singleton is calculated,and the comparison method of belief-based PLTS is constructed based on probabilities.On the basis of the preceding discussion,we further develop an emergency decision framework that includes several novel techniques,such as attribute weight determination and decision information aggregation.Finally,the usefulness of the framework is demonstrated through a case study,and its effectiveness is illustrated through a series of comparisons.

Linguistic Knowledge Representation in DPoS Consensus Scheme for Blockchain

The consensus scheme is an essential component in the real blockchain environment.The Delegated Proof of Stake(DPoS)is a competitive consensus scheme that can decrease energy costs,promote decentralization,and increase efficiency,respectively.However,how to study the knowledge representation of the collective voting information and then select delegates is a new open problem.To ensure the fairness and effectiveness of transactions in the blockchain,in this paper,we propose a novel fine-grained knowledge representation method,which improves the DPoS scheme based on the linguistic term set(LTS)and proportional hesitant fuzzy linguistic term set(PHFLTS).To this end,the symmetrical LTS is used in this study to express the fine-grained voting options that can be chosen to evaluate the blockchain nodes.PHFLTS is used to model the collective voting information on the voted blockchain nodes by aggregating the voting information from other blockchain nodes.To rank the blockchain nodes and then choose the delegate,a novel delegate selection algorithm is proposed based on the cumulative possibility degree.Finally,the numerical examples are used to demonstrate the implementation process of the proposed DPoS consensus algorithm and also its rationality.Moreover,the superiority of the proposed DPoS consensus algorithm is verified.The results show that the proposed DPoS consensus algorithm shows better performance than the existing DPoS consensus algorithms.

Eco-discourse Analysis within the Framework of Systemic Functional Linguistics

Ecolinguistics has become an important field on a worldwide scale,within the systemic functional framework,the data collected from British Broadcasting Corporation concerning about natural environment is analyzed from 3 aspects:lexical level,morphology and transitivity,in order to enhance people’s ecological awareness and their responsibility for nature.