Search Results (74)

Semantic Textual Similarity (STS) serves as a metric for evaluating the semantic symmetry between texts, playing a pivotal role in various natural language processing (NLP) tasks. To facilitate the accurate measurement of semantic symmetry, high-quality text representation is essential. This paper studies how to utilize constituent parsing for text representation in STS. Unlike most existing syntax models, we propose a heterogeneous graph attention network that integrates constituent parsing (HGAT-CP). The heterogeneous graph contains meaningfully connected sentences, verb phrase (VP), noun phrase (NP), phrase, and word nodes, which are derived from the constituent parsing tree. This graph is fed to a graph attention network for context propagation among relevant nodes, which effectively captures the relations of inter-sentence components. In addition, we leverage the relationships between verb phrases (VPs) and noun phrases (NPs) across sentence pairs for data augmentation, which is denoted as HGAT_CP(NP, VP). We extensively evaluate our method on three datasets, and experimental results demonstrate that our proposed HGAT_CP(NP, VP) achieves significant improvements on the majority of the datasets. Notably, on the SICK dataset, HGAT_CP(NP, VP) achieved improvements of 0.39 and 1.84 compared to SimCSE-ROBERTa_large and SimCSE-ROBERTa_base, respectively. Full article

Introduction: Transperineal prostate (TP) biopsy has emerged as a substantial alternative to the conventional transrectal (TR) approach for prostate sampling by its ability to sample specific areas of the prostate more effectively. The objective of this review is to conduct a comparative analysis of the current literature regarding diagnostic accuracy, complication rate and clinical outcome of transrectal vs. transperineal approaches in prostate biopsy-naïve patients and in repeated biopsy scenarios. Materials and Methods: An extensive search of the literature in PubMed, Scopus, and Web of Science was conducted between September 2010 and September 2024. We utilized a robust and comprehensive retrieval strategy including phrasing the two approaches as follows: (perineal or transperineal) and (rectal or transrectal). Conclusions: The transperineal and transrectal approaches show similar results in the detection of PCa in biopsy-naïve men, similar rates of infection, urinary retention and effectiveness managing biopsy-associated pain. However, in the rebiopsy scenario, the TP approach has demonstrated increased accuracy compared to the TR approach. This has significant implications in decision making and patient counselling. Full article

Background/Objectives: Localization deficit is often said to be a symptom of Auditory Processing Disorder (APD). However, no clinically viable assessment of localization ability has been developed to date. The current study presents pilot data for a new assessment of absolute auditory localization using headphones. Methods: Speech phrases encoded with non-individualized head-related transfer functions (HRTF) using real-time digital processing were presented to two cohorts of participants with normal hearing. Variations in the simulated environment (anechoic and reverberant) and signal to noise ratio (SNR) were made to assess each of these factors’ influences on localization performance. Experiment 1 assessed 30 young adults aged 21–33 years old and Experiment 2 assessed 28 young adults aged 21–29 years old. All participants had hearing thresholds better than 20 dB HL. Results: Participants performed the localization task with a moderate degree of accuracy (Experiment 1: Mean RMS error = 25.9°; Experiment 2: Mean RMS error 27.2°). Front–back errors (FBEs) were evident, contributing to an average RMS error that was notably elevated when compared to similar free-field tasks. There was no statistically significant influence from the simulated environment or SNR on performance. Conclusions: An exploration of test viability in the pediatric and APD-positive populations is warranted alongside further correction for FBEs; however, the potential for future clinical implementation of this measure of absolute auditory localization is encouraging. Full article

Universities and journals increasingly rely on software tools for detecting textual overlap of a scientific text with the previously published literature to detect potential plagiarism. Although software outputs need to be carefully reviewed by competent humans to verify the existence of plagiarism, university and journal staff, for various reasons, often erroneously interpret the degree of plagiarism based on the percentage of textual overlap shown in the similarity report. This is often accompanied by explicit recommendations to the author(s) to paraphrase the text to achieve an “acceptable” percentage of overlap. Here, based on the available literature and real-world examples from similarity reports, we provide a classification with extensive examples of phrases that falsely inflate the similarity index and argue the futility and dangers of rephrasing such statements just for the sake of reducing the similarity index. The examples provided in this paper call for a more reasonable assessment of text similarity. To fully endorse the principles of academic integrity and prevent loss of clarity of the scientific literature, we believe it is important to shift from pure bureaucratic and quantificational view on the originality of scientific texts to human-centered qualitative assessment of the manuscripts, including the software outputs. Full article

Short text similarity, as a pivotal research domain within Natural Language Processing (NLP), has been extensively utilized in intelligent search, recommendation systems, and question-answering systems. Most existing short-text similarity models focus on aligning the overall semantic content of an entire sentence, often ignoring the semantic associations between individual phrases in the sentence. It is particular in the Chinese context, as synonyms and near-synonyms can cause serious interference in the computation of text similarity. To overcome these limitations, a novel short text similarity computation method integrating both sentence-level and phrase-level semantics was proposed. By harnessing vector representations of Chinese words/phrases as external knowledge, this approach amalgamates global sentence characteristics with local phrase features to compute short text similarity from diverse perspectives, spanning from the global to the local level. Experimental results demonstrate that the proposed model outperforms previous methods in the Chinese short text similarity task. Specifically, the model achieves an accuracy of 90.16% in LCQMC, which is 2.23% and 1.46%, respectively, better than ERNIE and Glyce + BERT. Full article

A Domain Generation Algorithm (DGA) employs botnets to generate domain names through a communication link between the C&C server and the bots. A DGA can generate pseudo-random AGDs (algorithmically generated domains) regularly, a handy method for detecting bots on the C&C server. Unlike current DGA detection methods, AGDs can be identified with lightweight, promising technology. DGAs can prolong the life of a viral operation, improving its profitability. Recent research on the sensitivity of deep learning to various adversarial DGAs has sought to enhance DGA detection techniques. They have character- and word-level classifiers; hybrid-level classifiers may detect and classify AGDs generated by DGAs, significantly diminishing the effectiveness of DGA classifiers. This work introduces WordDGA, a hybrid RCNN-BiLSTM-based adversarial DGA with strong anti-detection capabilities based on NLP and cWGAN, which offers word- and hybrid-level evasion techniques. It initially models the semantic relationships between benign and DGA domains by constructing a prediction model with a hybrid RCNN-BiLSTM network. To optimize the similarity between benign and DGA domain names, it modifies phrases from each input domain using the prediction model to detect DGA family categorizations. The experimental results reveal that dodging numerous wordlists and mixed-level DGA classifiers with training and testing sets improves word repetition rate, domain collision rate, attack success rate, and detection rate, indicating the usefulness of cWGAN-based oversampling in the face of adversarial DGAs. Full article

This study addresses the challenge of automating the creation of Exchange Information Requirements (EIRs) for construction projects using Building Information Modelling (BIM) and Digital Twins, as specified in the ISO 19650 standard. This paper focuses on automating the classification of EIR paragraphs according to the ISO 19650 standard’s categories, aiming to improve information management in construction projects. It addresses a gap in applying AI to enhance BIM project management, where barriers often include technological limitations, a shortage of specialists, and limited understanding of the methodology. The proposed method uses Word2Vec for text vectorisation and Support Vector Machines (SVMs) with an RBF kernel for text classification, and it attempts to apply Word2Vec with cosine similarity for text generation. The model achieved an average F1 score of 0.7, with predicted categories for provided sentences and similar matches for selected phrases. While the text classification results were promising, further refinement is required for the text generation component. This study concludes that integrating AI tools such as Word2Vec and SVM offers a feasible solution for enhancing EIR creation. However, further development of text generation, particularly using advanced techniques such as GPT, is recommended. These findings contribute to improving managing complex construction projects and advancing digitalization in the AECO sector. Full article

Today, various interactive tools or partially available artificial intelligence applications are actively used in educational processes to solve multiple problems for resource-rich languages, such as English, Spanish, French, etc. Unfortunately, the situation is different and more complex for low-resource languages, like Kazakh, Uzbek, Mongolian, and others, due to the lack of qualitative and accessible resources, morphological complexity, and the semantics of agglutinative languages. This article presents research on early childhood learning resources for the low-resource Kazakh language. Generally, a dictionary for children differs from classical educational dictionaries. The difference between dictionaries for children and adults lies in their purpose and methods of presenting information. A themed dictionary will make learning and remembering new words easier for children because they will be presented in a specific context. This article discusses developing an approach to creating a thematic children’s dictionary of the low-resource Kazakh language using artificial intelligence. The proposed approach is based on several important stages: the initial formation of a list of English words with the use of ChatGPT; identification of their semantic weights; generation of phrases and sentences with the use of the list of semantically related words; translation of obtained phrases and sentences from English to Kazakh, dividing them into bigrams and trigrams; and processing with Kazakh language POS pattern tag templates to adapt them for children. When the dictionary was formed, the semantic proximity of words and phrases to the given theme and age restrictions for children were taken into account. The formed dictionary phrases were evaluated using the cosine similarity, Euclidean similarity, and Manhattan distance metrics. Moreover, the dictionary was extended with video and audio data by implementing models like DALL-E 3, Midjourney, and Stable Diffusion to illustrate the dictionary data and TTS (Text to Speech) technology for the Kazakh language for voice synthesis. The developed thematic dictionary approach was tested, and a SUS (System Usability Scale) assessment of the application was conducted. The experimental results demonstrate the proposed approach’s high efficiency and its potential for wide use in educational purposes. Full article

Prosody is known to scaffold the learning of language, and thus understanding prosodic development is vital for language acquisition. The present study explored the unfolding prosody model of prosodic development (proposed in Frota’s et al. study in 2016) beyond early production data, to examine whether it predicted the development of early segmentation abilities. European Portuguese-learning infants aged between 5 and 17 months were tested in a series of word segmentation experiments. Developing prosodic structure was evidenced in word segmentation as proposed by the unfolding model: (i) a simple monosyllabic word shape crucially placed at a major prosodic edge was segmented first, before more complex word shapes under similar prosodic conditions; (ii) the segmentation of more complex words was easier at a major prosodic edge than in phrase-medial position; and (iii) the segmentation of complex words with an iambic pattern preceded the segmentation of words with a trochaic pattern. These findings demonstrated that word segmentation evolved with unfolding prosody, suggesting that the prosodic units developed in the unfolding process are used both as speech production planning units and to extract word-forms from continuous speech. Therefore, our study contributes to a better understanding of the mechanisms underlying word segmentation, and to a better understanding of early prosodic development, a cornerstone of language acquisition. Full article

(1) Background: “To change the world, we must first change the way the babies are being born”, said Michel Odent, the famous French obstetrician and pioneer of the “natural birth” movement. This quotable phrase has been widespread in activism campaigns, and it refers to a project for social change that goes beyond birth. Conceiving childbirth in the broader social context, it is not surprising that this emblematic quote inspires emancipatory struggles around birth. This paper results from a study of childbirth activism in different European contexts, where the author explores the emergence and modes of action of social movements advocating for the humanization of childbirth and women’s rights in pregnancy and childbirth. (2) Methods: Starting from the analysis of the main characteristics of childbirth activism, in this paper the author briefly analyzes the cases of organizations from Portugal, Spain and the Netherlands, as well as a campaign promoted by the European Network of Childbirth Associations (ENCA). The author mobilizes empirical data resulting from a triangulation approach, essentially based on documentary analysis, complemented by conversations and participant observation in different settings. (3) Results: Preliminary results show how childbirth activism is contributing to the construction of alternative conceptions of birth, challenging established paradigms. (4) Conclusion: In its differences and similarities, childbirth activism assumes distinct features, but it also has the ability to adapt and promote changes, depending on the specificities of the contexts where it operates. Full article

This paper investigates the production of numerically-quantified phrases (NQPs) by monolingual and bilingual speakers of Russian, with Hebrew as the dominant language for the latter group. Russian NQPs exhibit a complex system of noun forms, distinguishing between singular (odin gorod ‘one city’), paucal (dva goroda ‘two cities’), and plural (pjat’ gorodov ‘five cities’); the endings of paucal and plural nouns vary depending on nominal declension class, which in turn correlates with gender. Adult and child bilinguals dominant in Hebrew (n = 37 and n = 27, respectively) were compared to monolingual Russian-speaking controls (n = 21 and n = 20, respectively). Production data were collected using a numeral-noun elicitation task, which involved eliciting 24 numerical phrases manipulated for gender (masculine, feminine) and number (paucal, plural). Compared to the monolingual controls, the bilinguals showed lower accuracy, with oversuppliance of nominative plural endings and overtly marked genitive plural endings. These non-target responses indicate the reliance on default forms and phonetically salient inflections, confirming that these factors influence non-target attainment in bilingual (heritage) grammars. The amount of exposure to Russian (as measured by age of bilingualism onset and proficiency) influenced performance significantly, underscoring the role of input in shaping bilingual grammars. The production of NQPs by Hebrew-dominant Russian speakers was similar to that by English-dominant Russian speakers as reported in previous studies, which may appear surprising given that Hebrew is characterized by richer morphology than English, and that may play a role in the maintenance of morphology in the weaker language. We offer some considerations for this lack of effect. Full article

In writing assessment, expert human evaluators ideally judge individual essays with attention to variance among writers’ syntactic patterns. There are many ways to compose text successfully or less successfully. For automated writing evaluation (AWE) systems to provide accurate assessment and relevant feedback, they must be able to consider similar kinds of variance. The current study employed natural language processing (NLP) to explore variance in syntactic complexity and sophistication across clusters characterized in a large corpus (n = 36,207) of middle school and high school argumentative essays. Using NLP tools, k-means clustering, and discriminant function analysis (DFA), we observed that student writers employed four distinct syntactic patterns: (1) familiar and descriptive language, (2) consistently simple noun phrases, (3) variably complex noun phrases, and (4) moderate complexity with less familiar language. Importantly, each pattern spanned the full range of writing quality; there were no syntactic patterns consistently evaluated as “good” or “bad”. These findings support the need for nuanced approaches in automated writing assessment while informing ways that AWE can participate in that process. Future AWE research can and should explore similar variability across other detectable elements of writing (e.g., vocabulary, cohesion, discursive cues, and sentiment) via diverse modeling methods. Full article

In the task of matching Chinese sentences, the key semantics within sentences and the deep interaction between them significantly affect the matching performance. However, previous studies mainly relied on shallow interactions based on a single semantic granularity, which left them vulnerable to interference from overlapping terms. It is particularly challenging to distinguish between positive and negative examples within datasets from the same thematic domain. This paper proposes a sentence-matching model that incorporates multi-granularity contextual key semantic interaction. The model combines multi-scale convolution and multi-level convolution to extract different levels of contextual semantic information at word, phrase, and sentence granularities. It employs multi-head self-attention and cross-attention mechanisms to align the key semantics between sentences. Furthermore, the model integrates the original, similarity, and dissimilarity information of sentences to establish deep semantic interaction. Experimental results on both open- and closed-domain datasets demonstrate that the proposed model outperforms existing baseline models in terms of matching performance. Additionally, the model achieves matching effectiveness comparable to large-scale pre-trained language models while utilizing a lightweight encoder. Full article

The separately stored type herbarium of the Herbarium Greuter in Palermo is comprised of 339 sheets, corresponding to 336 specimens pertaining to 328 different names. Material from the Mediterranean area, especially Greece, predominates, followed by that from the Caribbean (Cuba) and Australia. The list includes transcribed label data and links to the digital specimen images and to the protologue texts. A new type of terminology is introduced, with the terms “first-step holotype” and “second-step holotype” designating type categories parallel to the similar terms already in use for lectotypes, and the phrase “detailed here” is used as an equivalent to “designated here” in second-step typification. Full article

This study explores the extent to which Palenquero/Spanish bilinguals, a population that is said to have a residual high tone of African origin, keep their two languages temporally and intonationally distinct across statements. While creole languages that emerged from the contact of African and European languages, such as Palenquero, may develop hybrid prosodic systems with tones from substrate languages, and stress from the majority language, language-specific prosody might be expected to converge or simplify over the course of time. As prosodic convergence seems to be inescapable under Palenquero’s circumstances, which factors could support language-specific prosody in this population, if there are any? Two-hundred and thirty-four five-syllable statements were elicited through a discourse completion task, with the participation of ten Palenquero/Spanish bilinguals, in two unilingual sessions. Both phrase-final lengthening and F0 contours were assessed using linear mixed-effects models testing their association with final stress, language, and generation. F0 contours were dimensionally reduced using functional principal component analysis. Despite the strong similarities between the two languages, results indicate that both groups keep their two languages intonationally distinct using plateau-shaped contours in Palenquero initial rises followed by steeper declinations in Spanish. However, elderly bilinguals implement penultimate lengthening language-specifically, being more pronounced in Palenquero. Adults, in contrast, do not show this distinction. In addition to this, elderly speakers show hyperarticulation in Spanish intonation, increasing the difference between their languages. This leads us to believe that adults exhibit a more simplified prosodic system between their languages, relative to elderly bilinguals. In spite of such differences, both generations seem to have the same underlying process (perhaps a substrate effect) driving plateau-shaped intonation in Palenquero, which enhances language differentiation. Full article