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关键词： Learning style   Instruction explicitness   Multimedia glossing  

摘要： This study investigates the roles of instruction explicitness and learning styles on the relative effectiveness of multimedia glossing with texts and cognitive linguistics-based image schemas presented in two modalities, i.e., static and animated, on Taiwanese college EFL students learning three polysemous prepositions: above, on, and over. Based on a pre-post-test design, the experiments consist of a free writing test and a gap-fill test, respectively used to gauge the active and passive aspects of learners' receptive lexical gain. Three groups of intermediate learners were recruited, receiving the same text annotations but different treatments configured in presentation modes and explicitness: SI group with text-static imagery annotations under implicit instruction, AI group with text-animation annotations under implicit instruction, and AE group with text-animation annotations under explicit instruction. The results suggest the following: (1) animations, compared with static imagery, seem able to better enrich the meaningfulness of image schemas and elicit larger and more durable learning effects, especially on the more active aspects of the receptive gain;(2) explicit verbal cues enhanced the learning effects on the active aspects of the receptive gains;(3) visualizers benefit more from animations than verbalizers in both active and passive aspects of the receptive gains, especially if verbal cues are provided. Pedagogical suggestions include the utilization of image schema visual aids in a dynamic presentation mode accompanied by sufficient explicit instruction to optimize the effects of learning polysemous words.

关键词： Field programmable gate arrays (FPGA)  

摘要： Online intelligent remote classrooms subject to Chinese Linguistics and FPGA (Field-programmable gate array) procedures are used to handle complex blends of teaching and work estimations. FPGA (Field-Programmable Gate Array) is regularly realized as ASICs (Application-Specific Integrated Circuit) because of the high model thickness and execution essentials. Embedded designs regularly don't achieve high efficiency and low power application. The FPGA (Field-Programmable Gate Array) online course replication, appropriately giving the Fault Distributed Algorithm and hardware stage to organizing and evaluating new features before silicon is set into usage. Chinese Linguistics causes the network interface to grow faster and decline the ASIC design cycle. The Fault Distributed Algorithm is the improved forefront FPGA (Field-Programmable Gate Array) introduced another maximize card that reinforces the latest ASIC and FPGA plans that are a bit of checking trigger. The delivered output is taken care of in a model group and set aside in the data line that makes up an amount model pack. Considering the produced test set, the proposed system discovers each level's progression closeness, ultimately the overall likeness. © 2020

关键词： Distributed linguistic trust   Consensus   Feedback mechanism   Trust propagation   Self-esteem degree   Group decision making  

摘要： This paper focuses on consensus reaching process (CRP) under social network in which the trust relationship expressed by linguistic information. A new feedback mechanism in social network group decision making (SN-GDM) is proposed, which mainly consists of the following two aspects: (1) The propagation of distributed linguistic trust is investigated to study trust relation among experts;(2) A maximum self-esteem degree based feedback mechanism is developed to produce personalized advice for reaching higher group consensus. To do so, a novel linguistic trust propagation method is proposed to obtain the complete trust relationship among group. The self-esteem degree is used to define the extent that an individual makes concessions. Then, a maximum self-esteem degree based optimal feedback mechanism is built to produce personalized advice to help inconsistent experts make change of their opinion. Its novelty lies in the establishment of an optimization model with the nonlinear group self-esteem degree function as the objective function while group consensus threshold as the restrictions. Therefore, the inconsistent experts will reach a group consensus with the minimum loss of self-esteem degree, and then, it achieves the optimal balance between individual self-esteem and group consensus. Finally, a ranking process is applied to derive the appropriate consensus solution.

摘要： This meta-analysis examined associations between the quantity and quality of parental linguistic input and children's language. Pooled effect size for quality (i.e., vocabulary diversity and syntactic complexity;k = 35;N = 1,958;r = .33) was more robust than for quantity (i.e., number of words/tokens/utterances;k = 33;N = 1,411;r = .20) of linguistic input. For quality and quantity of parental linguistic input, effect sizes were stronger when input was observed in naturalistic contexts compared to free play tasks. For quality of parental linguistic input, effect sizes also increased as child age and observation length increased. Effect sizes were not moderated by socioeconomic status or child gender. Findings highlight parental linguistic input as a key environmental factor in children's language skills.

关键词： Fuzzy sets   Hedge algebras   Human-computer interaction   Knowledge discovery   Linguistic data summarization   Natural languages  

摘要： The effect of the linguistic (L-) summarization mined from a given dataset D by a human-made method M strongly depends on the fuzzy sets constructed to represent the L-words of dataset attributes. One can observe that the semantics of words is objective (commonly understood the same between human experts,) and worddomains of dataset attributes have their inherent semantic structures. It suggests that to limit the intuitive human influences on such construction, in this study, it requires that the constructed fuzzy set (fs-) representations of the declared word-sets should be the isomorphic images of their words. Such fs-representations of the word-domains are called, in this study, interpretable based on the concept of interpretability in the math-logical theories of A. Tarski et al. It requires the interpretability of the inherent semantic structures of the declared wordsets in their fs-representations structures. With this new feature, the study proposes a data-summarization method that can reveal L-distributions of fuzzy groups of objects represented by a given dataset to the desired dataset L-attribute. The set of all such mined LSs satisfies essential specific human usual L-knowledge, the scalability of its current attributes word-sets, and the current knowledge itself. An experimental study using the Bank Marketing dataset taken from the UCI dataset repository is performed to show the specific advantages of the proposed method.

摘要： Linguistic landscape (LL) research has been subject to a great deal of attention since the publication of the well-known research paper by Landry and Bourhis (1997), whose most quoted definition of LL covers diverse linguistic tokens, including but not restricted to government-related inscriptions, street-name signs, commercial signs, and noticeboards. There is an increasing number of contributions on the use of English in many LLs worldwide. However, there are relatively few LL publications on the use of English in the LL in Arabic-speaking countries (but see Al-Naimat & Alomoush, 2018;Alomoush, 2019). The vast majority of previous LL studies in non-Arabic contexts (e.g. Backhaus, 2007;Griffin, 2004;Hasanova, 2010;Jaworksi & Thurlow, 2010;Lanza & Woldemariam, 2014;Ross, 1997;Schlick, 2003) focus on analysing language on fixed or relatively stable signs, such as shop names.

关键词： two-dimensional uncertain linguistic variables   community question answering   fuzzy multicriteria decision-making   information quality  

摘要： Evaluating the information quality of cQA (community question-answering) websites helps users select a cQA website with high-quality information and improves the information quality. In this paper, an approach to evaluating the information quality of cQA based on a novel hybrid multicriteria decision-making (MCDM) model is proposed. First, the source, content, expression and usefulness criteria for evaluating the information quality of the cQA are established. Then, considering the ambiguity and inner correlations of the criteria, DANP ([DEMATEL]-based Analytic Network Process) and TODIM (interactive and multiple attribute decision making, in Portuguese) methods are combined in a two-dimensional linguistic environment to process linguistic evaluation information. Lastly, the proposed approach is applied to evaluate the quality of five popular cQA websites. The key criteria are identified, and the evaluation results are derived comprehensively. The key factors consist of reputation, coverage, politeness, usability, helpfulness, clarity, readability and conciseness. The websites, Know almost and Baidu knows, perform better in terms of information quality. The application, along with the sensitivity analysis and comparative analysis, shows the effectiveness of the proposed model. The proposed approach has both practical and research implications. It provides an approach for users to choose websites, and, for operators, to improve the information quality of their website. The evaluation criteria and their relations provide a reference for research on the information quality. The evaluation method considers the user's psychological information to provide a more accurate MCDM approach. The comprehensive aspects of the experiment can be used to verify the other MCDM methods.

关键词： bilingual word processing   linguistic experience   orthotactic regularities   word learning  

摘要： The current study examines how monolingual children and bilingual children with languages that are orthotactically similar and dissimilar learn novel words depending on their characteristics. We contrasted word learning for words that violate or respect the orthotactic legality of bilinguals' languages investigating the impact of the similarity between those two languages. In Experiment 1, three groups of children around the age of 12 were tested: monolinguals, Spanish-Basque bilinguals (orthotactically dissimilar languages), and Spanish-Catalan bilinguals (orthotactically similar languages). After an initial word-learning phase, they were tested in a recognition task. While Spanish monolinguals and Spanish-Catalan bilingual children recognized illegal words worse than legal words, Spanish-Basque bilingual children showed equal performance in learning illegal and legal patterns. In Experiment 2, a replication study was conducted with two new groups of Spanish-Basque children (one group with high Basque proficiency and one group with a lower proficiency) and results indicated that the effects were not driven by the proficiency in the second language, as a similar performance on legal and illegal patterns was observed in both groups. These findings suggest that word learning is not affected by bilingualism as such, but rather depends on the specific language combinations spoken by the bilinguals.

关键词： Linguistics   Biological system modeling   Numerical models   Computational modeling   Semantics   Decision making   Hafnium   Comparative linguistic expressions (CLEs)   group decision making   optimization consensus model   personalized individual semantics (PIS)   self-confidence  

摘要： Comparative linguistic expression preference relations (CLEPRs) are an effective tool to represent uncertain opinions of decision makers in group decision making (GDM). Nevertheless, multiple self-confidence levels are not considered by existing research on CLEPRs. Thus, this article proposes CLEPRs with self-confidence by considering multiple self-confidence levels and presents a way to measure their consistency level. Meanwhile, personalized individual semantics (PIS), indicating that words mean different things for different people, have been highlighted and investigated in the GDM with linguistic assessment information. Considering PIS in comparative linguistic expressions, this article proposes an optimization model based on the consistency-driven methodology to assess individual semantics in CLEPRs with self-confidence. Particularly, the PIS are described and addressed by setting different numerical scales of linguistic terms for different decision makers. Finally, an optimization-based consensus model is proposed to obtain a consensual collective solution, which seeks to minimize the information loss between the decision makers' preference relations with self-confidence and corresponding individual preference vectors.

关键词： Spoken Dutch   Speech corpus   Talker variability   Linguistic variability  

摘要： Speech perception and spoken word recognition are not only affected by what is being said, but also by who is speaking. Currently, publicly available corpora of spoken Dutch do not offer a wide variety of linguistic materials produced by multiple talkers. The VariaNTS (Variatie in Nederlandse Taal en Sprekers) corpus is a Dutch spoken corpus that was developed to maximize both linguistic and talker variability. It contains 1000 items from 11 linguistic subcategories, recorded by 8 male and 8 female native speakers of standard Dutch. The corpus contains audio recordings, orthographic transcriptions, item-specific details such as word frequencies, neighborhood densities and phonotactic probabilities, and talker details. The VariaNTS corpus aims to provide new materials to be used for broad assessment of speech perception and word recognition in Dutch clinical and academic settings.