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A comparative study on the spatial vitality of national squares: A visualization analysis based on multi-source data
As urbanization advances into its later stages, the need for critical reflection and reform in the design of urban public spaces becomes increasingly important. National squares, as symbolic examples of urban space, serve as vivid indicators of a city's vitality and design characteristics. This research investigates the connection between the vitality representation of squares and vitality construction, aiming to identify strategies for optimizing square design. Using OpenStreetMap trajectory data, remote sensing imagery, and spatial syntax, we analyze these squares at both the urban block and square scales. Our findings reveal four distinct behavioral patterns within these national squares: pausing, interaction, traversing, and boundary crossing. We find that pausing and interaction are closely linked to various vitality construction, such as spatial centripetal force, comfort, safety, aesthetics, and functionality. In contrast, the patterns of passage and boundary crossing are influenced by the permeability of the space and the details of its design. Ultimately, this study offers valuable insights and a scientific foundation for enhancing the vitality of urban square design. By utilizing an expert evaluation system and quantitative data, we establish meaningful connections between design elements and user behaviors, facilitating informed decisions for optimizing square spaces.
Journal Article
Prosodic studies : challenges and prospects
\"Prosody is one of the core components of language and speech, indicating the information about syntax, turn-taking in conversation, types of utterance, such as questions or statements, as well as speakers' attitudes and feelings. This edited volume takes studies in prosody on Asian languages as well as examples from other languages. It brings together the most recent research in the field and also charts the influence on such diverse fields as multi-media communication and SLA. Intended for a wide audience of linguists that includes neighbouring disciplines such as computational sciences, psycholinguists, and specialists in language acquisition, Prosodic Studies is also ideal for scholar and researchers those working in intonation who want a complement of information on specifics\"--Provided by publisher.
Book
Analysis of neighborhood identity and socio-spatial relations with typo-morphogical analysis and spatial intelligence: A case study of Zile historic city
In historic cities, which are important components of urban identity and a significant part of urban heritage, new residential areas are rapidly developing as population growth occurs. This phenomenon creates numerous problems for fragile historic cities. This study proposes an approach that combines changes in typo-morphological parameters in historic urban areas and new development areas with a spatial syntax methodology. This study aims to reveal the changes in social relations between historical neighborhoods and other neighborhoods, and to offer design strategies for the continuity of urban identity for these neighborhoods. This paper also aims to contribute to research on typographic morphology using spatial syntax as a method. Focusing on the neighborhoods of Zile in Türkiye, this study employs the method of examining typographic morphology parameters and spatial syntax metrics. For this purpose, a multivariate statistical analysis was performed on typo-morphological data. Hierarchical cluster analysis revealed six clusters with similar characteristics. The metrics of the Space Syntax Method (SSA) were used to analyze the relationship between spatial integration, accessibility, and social structure. These results overlaid with Point of Interest (POI) data for comparison with social data. The findings reveal the spatial factors of multi-layered cities and provide insight into the relationship between the physical layout and social structure of neighborhoods. This study offers guidance in demonstrating the potential of spatial syntax theory in neighborhood-specific contexts and socio-spatial relationships.
Journal Article
Memorization and the compound-phrase distinction : an investigation of complex constructions in German, French and English
\"Over the last decades, it has been hotly debated whether and how compounds, i.e. word-formations, and phrases differ from each other. The book discusses this issue by investigating compounds and phrases from a structural, semantic-functional and, crucially, cognitive perspective. The analysis focuses on compounds and phrases that are composed of either an adjective and a noun or two nouns in German, French and English. Having distinguished compounds from phrases on structural and semantic-functional grounds, the author claims that compounds are by their nature more appropriate to be stored in the mental lexicon than phrases and supports his argument with empirical evidence from new psycholinguistic studies. In sum, the book maintains the separation between compounds and phrases and reflects upon its cognitive consequences\"-- Provided by publisher.
Book
Text analysis framework for identifying mutations among non-small cell lung cancer patients from laboratory data
Background
Laboratory data can provide great value to support research aimed at reducing the incidence, prolonging survival and enhancing outcomes of cancer. Data is characterized by the information it carries and the format it holds. Data captured in Alberta’s biomarker laboratory repository is free text, cluttered and rouge. Such data format limits its utility and prohibits broader adoption and research development. Text analysis for information extraction of unstructured data can change this and lead to more complete analyses. Previous work on extracting relevant information from free text, unstructured data employed Natural Language Processing (NLP), Machine Learning (ML), rule-based Information Extraction (IE) methods, or a hybrid combination between them.
Methods
In our study, text analysis was performed on Alberta Precision Laboratories data which consisted of 95,854 entries from the Southern Alberta Dataset (SAD) and 6944 entries from the Northern Alberta Dataset (NAD). The data covers all of Alberta and is completely population-based. Our proposed framework is built around rule-based IE methods. It incorporates topics such as Syntax and Lexical analyses to achieve deterministic extraction of data from biomarker laboratory data (i.e., Epidermal Growth Factor Receptor (EGFR) test results). Lexical analysis compromises of data cleaning and pre-processing, Rich Text Format text conversion into readable plain text format, and normalization and tokenization of text. The framework then passes the text into the Syntax analysis stage which includes the rule-based method of extracting relevant data. Rule-based patterns of the test result are identified, and a Context Free Grammar then generates the rules of information extraction. Finally, the results are linked with the Alberta Cancer Registry to support real-world cancer research studies.
Results
Of the original 5512 entries in the SAD dataset and 5017 entries in the NAD dataset which were filtered for EGFR, the framework yielded 5129 and 3388 extracted EGFR test results from the SAD and NAD datasets, respectively. An accuracy of 97.5% was achieved on a random sample of 362 tests.
Conclusions
We presented a text analysis framework to extract specific information from unstructured clinical data. Our proposed framework has shown that it can successfully extract relevant information from EGFR test results.
Journal Article
Assessing the morphological distribution of urban green spaces for the future sustainable greenery planning: a case study of Penang, Malaysia
Urban green spaces are among the resources that provide many social and physical effects to decrease the adverse effects of urbanization. Their inappropriate locations can make them less accessible and, therefore, less sustainable or underutilized. This study presents the citywide and local characteristics of the size and morphological distribution of urban green spaces in Penang Island, Malaysia, using the space syntax method. Space syntax analyses were used to identify if there is a rational pattern for urban green spaces' size and accessibility and to determine the spatial distribution of needs and accessibility. To this aim, physical measurements of 24 parks and green recreational centers were calculated, followed by an axial mapping of the study area which was conducted to perform space syntax analysis. The results first showed that the locations of the green spaces were not equitably distributed, and larger green spaces were established in areas with less accessibility. Second, based on space syntax data, we evaluated the flood risk, land surface temperature, and population density maps. Finally, we proposed potential sites for future green spaces. This paper demonstrates new insights into the consideration for spatial priorities to reshape future urban green space planning in delivering more sustainable greenery.
Journal Article
Acquisition of English Translation Examples Incorporating Shallow Syntactic Analysis Based on Network Technology
The example of English translation is the source of machine translation. The researchers found that the key to improve the quality of English translation is to study the methods of obtaining English translation examples. However, there are still many disadvantages in the acquisition of English translation examples. In recent years, with the extensive popularization and progress of shallow syntax research technology, the progress of syntactic analysis provides sufficient basis for the acquisition of English translation examples. This paper mainly uses the existing English and shallow syntactic analysis methods to deal with the related translation of the language database. In this way, we can find effective ways to obtain English translation examples.
Journal Article
Semantic Feature Extraction Using SBERT for Dementia Detection
Dementia is a neurodegenerative disease that leads to the development of cognitive deficits, such as aphasia, apraxia, and agnosia. It is currently considered one of the most significant major medical problems worldwide, primarily affecting the elderly. This condition gradually impairs the patient’s cognition, eventually leading to the inability to perform everyday tasks without assistance. Since dementia is an incurable disease, early detection plays an important role in delaying its progression. Because of this, tools and methods have been developed to help accurately diagnose patients in their early stages. State-of-the-art methods have shown that the use of syntactic-type linguistic features provides a sensitive and noninvasive tool for detecting dementia in its early stages. However, these methods lack relevant semantic information. In this work, we propose a novel methodology, based on the semantic features approach, by using sentence embeddings computed by Siamese BERT networks (SBERT), along with support vector machine (SVM), K-nearest neighbors (KNN), random forest, and an artificial neural network (ANN) as classifiers. Our methodology extracted 17 features that provide demographic, lexical, syntactic, and semantic information from 550 oral production samples of elderly controls and people with Alzheimer’s disease, provided by the DementiaBank Pitt Corpus database. To quantify the relevance of the extracted features for the dementia classification task, we calculated the mutual information score, which demonstrates a dependence between our features and the MMSE score. The experimental classification performance metrics, such as the accuracy, precision, recall, and F1 score (77, 80, 80, and 80%, respectively), validate that our methodology performs better than syntax-based methods and the BERT approach when only the linguistic features are used.
Journal Article
An Innovative Approach to Syntax-Free Interpretation in Functional Programming Languages
In the realm of programming languages, interpreters fundamentally rely on syntax analysis (parsing) for establishing a correct evaluation hierarchy. Traditional parsing methods, however, present limitations in terms of optimization. This study introduces an innovative approach that circumvents syntax analysis in the interpretation of functional programming languages. The proposed method employs a novel subroutine, transforming program expressions into a series of atomic expressions, herein referred to as the \"molecular program.\" Each atomic expression within this molecular program constitutes an element of the program’s lexicon, assigned a unique identifier that supplants its role in the original expression. The evaluation process adopts a recursive methodology, where the evaluation of a single variable invariably leads to the sequential evaluation of related variables. For the purposes of clarity and demonstration, this approach is exemplified using Lucid, a notable functional programming language. It is posited that this syntax-free interpretation method can be universally applied to any functional programming language that operates on the principles of expressions, functions, or formulas. The efficacy of this method is validated through rigorous testing, suggesting an enhancement in the efficiency of programming language interpretation.
Journal Article