Style Of Semantics Research Articles

A Case for First-Class Environments

Formalizations of programming languages typically adopt the substitution model from the lambda calculus. However, substitution creates notorious complications for reasoning and implementation. Furthermore, it is disconnected from practical implementations, which normally adopt environments and closures. In this paper we advocate for formalizing programming languages using a novel style of small-step environment-based semantics , which avoids substitution and is closer to implementations. We present a call-by-value statically typed calculus, called λ E , using our small-step environment semantics. With our alternative environment semantics programming language constructs for first-class environments arise naturally, without creating significant additional complexity. Therefore, λ E also adopts first-class environments, adding expressive power that is not available in conventional lambda calculi. λ E is a conservative extension of the call-by-value Simply Typed Lambda Calculus (STLC), and employs de Bruijn indices for its formalization, which fit naturally with the environment-based semantics. Reasoning about λ E is simple, and in many cases simpler than reasoning about the traditional STLC. We show an abstract machine that implements the semantics of λ E , and has an easy correctness proof. We also extend λ E with references. We show that λ E can model a simple form of first-class modules, and suggest using first-class environments as an alternative to objects for modelling capabilities. All technical results are formalized in the Coq proof assistant. In summary, our work shows that the small-step environment semantics that we adopt has three main and orthogonal benefits: 1) it simplifies the notorious binding problem in formalizations and proof assistants; 2) it is closer to implementations; and 3) additional expressive power is obtained from first-class environments almost for free.

Trace Semantics for C++11 Memory Model

The C and C++ languages introduced the relaxed-memory concurrency into the language specification for efficiency purposes in 2011. Trace semantics can provide the mathematical foundation for the proposed C++11 memory model, and there is a lack of investigation of trace semantics for C++11. The Promising Semantics (PS) of Kang et al. provides the standard SC-style operational semantics for the C++11 concurrency model, where “SC” refers to “Sequential Consistency”. Inspired by PS, in this paper we first investigate the trace semantics for the relaxed read and write accesses under C++11, acting in the denotational semantics style. In our semantic model, a trace is in the form of a sequence of snapshots, and the snapshots record the modification in the relevant global or local variables, and the thread view. Moreover, the trace semantics for the release/acquire accesses under C++11 is also explored, based on the separated thread views and newly added message views. When considering this trace model, different accesses bring in their unique snapshots, and make distinguished effects on the production of the sequences. For any given program, the proposed trace semantics in this paper produces all the valid traces directly. Further, our trace semantics, together with that for TSO and MCA ARMv8, has the possibility to be the foundation of the meta model of the trace semantics for weak memory models.

STUDY OF CDA DURING SELENA GOMEZ'S DISCOURSE ON YOUTUBE

Critical Discourse Analysis (CDA) pertains to the examination of language or linguistic usage. The objectives of this investigation were twofold: firstly, to identify the types of CDA evident in Selena Gomez's speeches, and secondly, to delineate the social cognition apparent within her speeches. The researcher employed Teun A. Van Dijk's (1998) Critical Discourse Analysis theory as the theoretical framework. Employing qualitative and descriptive methodologies, this study aimed to depict and scrutinize the data. The analysis primarily focused on dissecting the critical discourse present in Selena Gomez's speech texts. Through this analysis, three categories of CDA elements were identified in Selena Gomez's speeches: firstly, thematic elements, comprising a single category; secondly, syntactic style elements, subdivided into five categories, namely Persuasion, Impression Management, Attribution, Cohesion, and Pronoun usage; thirdly, semantic style elements, which were further categorized into Background and Detail, as well as Presupposition; and fourthly, schemata, classified into three segments: the opening section, the content, and the closing section. Additionally, several elements contributing to social cognition were discerned, including person schemas, self-schemes, and role schemes

Evaluation of parametric sedan wheel hub based on Kansei Engineering and regression analysis

<p><strong>Purpose:</strong> Parametric design has become one of the most important means of sedan design. The purpose of this paper is to construct a linear regression model to explore the matching relationship between Kansei words and the morphological elements of sedan wheels and to incorporate perceptual factors into the rational thinking of parametric wheel hub design. <strong>Design/methodology/approach:</strong> To forecast the matching relationship between wheel shape design features and semantics, this research offers a multiple linear regression model. First, using sample similarity matrix data analysis and offline research, 20 typical samples of car wheels were collected. Third, the wheel shape design elements are obtained by applying the semantic difference (SD) method to four groups of users’ evaluation data on the perceived words of the car wheels. Firstly, the wheel shape is divided into six basic features and seventeen subdivided features using morphological analysis. The collected car wheel samples are then researched and coded. Ultimately, a multiple linear regression model is built utilizing shape coding matching to the styles to direct the wheel parametric design process, yielding sedan wheel design schemes with various semantics of style. <strong>Findings:</strong> The results show that the regression models can provide good prediction performance (R<sup>2</sup> values are greater than 0.7). This study shows that the use of multiple regression models can accurately and cost-effectively predict the wheel hub morphological elements that meet the user’s perceptual needs through morphological elements and Kansei words. <strong>Originality/value:</strong> This paper is the first to use a multiple regression model to predict a parametric wheel shape that fits the user’s sensibility, which helps the user to present and feel the design scheme in a digital environment. The different wheel hub schemes generated by parametric design can be virtually displayed in the metaverse, helping users and designers to carry out more convenient scheme selections.</p>

Embedding Ontologies in the Description Logic ALC by Axis-Aligned Cones

This paper is concerned with knowledge graph embedding with background knowledge, taking the formal perspective of logics. In knowledge graph embedding, knowledge— expressed as a set of triples of the form (a R b) (“a is R-related to b”)—is embedded into a real-valued vector space. The embedding helps exploiting geometrical regularities of the space in order to tackle typical inductive tasks of machine learning such as link prediction. Recent embedding approaches also consider incorporating background knowledge, in which the intended meanings of the symbols a, R, b are further constrained via axioms of a theory. Of particular interest are theories expressed in a formal language with a neat semantics and a good balance between expressivity and feasibility. In that case, the knowledge graph together with the background can be considered to be an ontology. This paper develops a cone-based theory for embedding in order to advance the expressivity of the ontology: it works (at least) with ontologies expressed in the description logic ALC, which comprises restricted existential and universal quantifiers, as well as concept negation and concept disjunction. In order to align the classical Tarskian Style semantics for ALC with the sub-symbolic representation of triples, we use the notion of a geometric model of an ALC ontology and show, as one of our main results, that an ALC ontology is satisfiable in the classical sense iff it is satisfiable by a geometric model based on cones. The geometric model, if treated as a partial model, can even be chosen to be faithful, i.e., to reflect all and only the knowledge captured by the ontology. We introduce the class of axis-aligned cones and show that modulo simple geometric operations any distributive logic (such as ALC) interpreted over cones employs this class of cones. Cones are also attractive from a machine learning perspective on knowledge graph embeddings since they give rise to applying conic optimization techniques.

Dual-Affinity Style Embedding Network for Semantic-Aligned Image Style Transfer.

Image style transfer aims at synthesizing an image with the content from one image and the style from another. User studies have revealed that the semantic correspondence between style and content greatly affects subjective perception of style transfer results. While current studies have made great progress in improving the visual quality of stylized images, most methods directly transfer global style statistics without considering semantic alignment. Current semantic style transfer approaches still work in an iterative optimization fashion, which is impractically computationally expensive. Addressing these issues, we introduce a novel dual-affinity style embedding network (DaseNet) to synthesize images with style aligned at semantic region granularity. In the dual-affinity module, feature correlation and semantic correspondence between content and style images are modeled jointly for embedding local style patterns according to semantic distribution. Furthermore, the semantic-weighted style loss and the region-consistency loss are introduced to ensure semantic alignment and content preservation. With the end-to-end network architecture, DaseNet can well balance visual quality and inference efficiency for semantic style transfer. Experimental results on different scene categories have demonstrated the effectiveness of the proposed method.

Conceptual orthospaces—Convexity meets negation

Neural networks and in general subsymbolic learning approaches perform well on usual learning tasks, but they are black boxes lacking desired properties such as explainability or trustworthiness. Fully integrated symbolic/subsymbolic systems account for these properties, e.g., through the injection of symbolic information into a subsymbolic learning framework. Systems relying on embeddings can be considered as specific examples of such systems where facts, expressed in some logic, are embedded into a continuous space. Instances mentioned in the facts are mapped to points and the relations/concepts mentioned in the facts are mapped to a region in that space. This allows to exploit geometric regularities in order to tackle typical learning tasks such as link prediction. Embeddings provide the first step towards filling the gap between qualitative, Tarskian style semantics, which is used for deductive reasoning over the facts, and quantitative structures, which are used for representing objects, relations, and concepts for learning purposes. However, to enable meaningful reasoning, embeddings of relations and concepts are not allowed to be shaped arbitrarily. Especially, convex sets turned out to be appropriate due to their computational advantages and due to their foundation in cognition. Convexity can be defined with a ternary betweenness relation and concepts can be defined as betweenness-closed (= convex) sets. Though many interesting phenomena of cognitive reasoning can be explained in such a framework, it is at least not obvious how to use betweenness for other, more logico-formal aspects of reasoning that, e.g., require defining logical operators. In particular, for the logical operator of negation other mathematical structures such as the orthoframes of Goldblatt (1974) [13] have proven more useful. In this paper, we provide results on the connection between convexity and orthoframes. In particular, we investigate the construction of convex concepts equipped with an orthogonality relation. We give a universal construction of a betweenness relation over an orthoframe and show that based on Euclidean betweenness (thus using the classical notion of convexity) and under some natural restrictions, convex cones are the only structures capable of modeling such a space.

A novel intrarenal multimodal 2D/3D registration algorithm and preliminary phantom study.

Retrograde intrarenal surgery (RIRS) is a widely utilized diagnostic and therapeutic tool for multiple upper urinary tract pathologies. The image-guided navigation system can assist the surgeon to perform precise surgery by providing the relative position between the lesion and the instrument after the intraoperative image is registered with the preoperative model. However, due to the structural complexity and diversity of multi-branched organs such as kidneys, bronchi, etc., the consistency of the intensity distribution of virtual and real images will be challenged, which makes the classical pure intensity registration method prone to bias and random results in a wide search domain. In this paper, we propose a structural feature similarity-based method combined with a semantic style transfer network, which significantly improves the registration accuracy when the initial state deviation is obvious. Furthermore, multi-view constraints are introduced to compensate for the collapse of spatial depth information and improve the robustness of the algorithm. Experimental studies were conducted on two models generated from patient data to evaluate the performance of the method and competing algorithms. The proposed method obtains mean target error (mTRE) of 0.971±0.585mm and 1.266±0.416mm respectively, with better accuracy and robustness overall. Experimental results demonstrate that the proposed method has the potential to be applied to RIRS and extended to other organs with similar structures.

Uslûb Dalâlî (Semantic Style) Qur'anic Verses and Their Absorption in Nature Sentence Patterns for Learning

This study aims to analyze Uslûb Dalâlî or semantic style in Qur'anic Verses and its absorption in sentences for learning. This research is qualitative with a library research approach. Research data is a corpus of verses of the Makiyyah Qur'an with semantic style values. The source of the data is the Qur'an. Data collection techniques are carried out with documentation. At the same time, data analysis uses content analysis. There were four discourses as a result of the study. First is the aspect of takrar (repetition). That repetition is contained in QS. Al-Baqarah: 4, QS. Ali Imran: 54, QS. An-Nur: 40, and QS. An-Nur 45. The absorption of sentence patterns is further projected for learning, like learning that continues to be repeated and all knowledge considered useful. Secondly, the Qasr (focusing) aspect appears in QS. Al-Baqarah: 5, QS. Al-Baqarah: 254, and QS. An-Nisa: 151. Absorbing sentence patterns reduces learners’ readiness for learning and consistent and honest practice. Third, the number of mu'taridah (discontinuous structures). Marked in QS. Al-Baqarah: 24; QS. Al-Baqarah 116; and QS. Al-Mumtahanah: 110. Absorption of sentence patterns is good learning that must end with evaluation/assessment truth, iltifat (pronoun distillation) contained in QS. Al-Baqarah: 128, QS. Al-Baqarah: 159, QS Ali-Imran: 11; QS. Ali-Imran: 81, and QS. Al-Maidah: 13. The pattern of sentence absorption reduces to the need, to be honest in the educational process and punishment for undisciplined students. Thus, the Qur'an is the greatest literary book with multi-meaning in each verse unit.

Bridging the BCI illiteracy gap: a subject-to-subject semantic style transfer for EEG-based motor imagery classification.

Brain-computer interfaces (BCIs) facilitate direct interaction between the human brain and computers, enabling individuals to control external devices through cognitive processes. Despite its potential, the problem of BCI illiteracy remains one of the major challenges due to inter-subject EEG variability, which hinders many users from effectively utilizing BCI systems. In this study, we propose a subject-to-subject semantic style transfer network (SSSTN) at the feature-level to address the BCI illiteracy problem in electroencephalogram (EEG)-based motor imagery (MI) classification tasks. Our approach uses the continuous wavelet transform method to convert high-dimensional EEG data into images as input data. The SSSTN 1) trains a classifier for each subject, 2) transfers the distribution of class discrimination styles from the source subject (the best-performing subject for the classifier, i.e., BCI expert) to each subject of the target domain (the remaining subjects except the source subject, specifically BCI illiterates) through the proposed style loss, and applies a modified content loss to preserve the class-relevant semantic information of the target domain, and 3) finally merges the classifier predictions of both source and target subject using an ensemble technique. We evaluate the proposed method on the BCI Competition IV-2a and IV-2b datasets and demonstrate improved classification performance over existing methods, especially for BCI illiterate users. The ablation experiments and t-SNE visualizations further highlight the effectiveness of the proposed method in achieving meaningful feature-level semantic style transfer.

Semantic-Aware Noise Driven Portrait Synthesis and Manipulation

Semantic portrait synthesis has drawn consistent attention and has made significant progress, yet achieving style diversity and semantic controllability simultaneously is still a challenge. Existing methods either 1) directly take a semantic label map as input, ignoring various possibilities of semantic styles, or 2) sample global noise as input, ignoring controllability of local semantics. To fill this gap, we propose semantic-aware noise, a simple but effective input that tackles both issues and shows improved results over baselines. Semantic-aware noise introduces semantic information into noise, and each semantic is sampled from the noise separately, combining the semantic controllability and the noise sampling diversity. To further expand and manipulate real images, we propose a novel ternary network structure, allowing simultaneous diverse semantic image synthesis and real image manipulation in a unified framework. Extensive experiments demonstrate that the proposed method achieves quantitatively superior and perceptually pleasing results compared to state-of-the-art methods. We also analyze the performance of our method with respect to different noise structures and real-life applications in diverse synthesis, interactive manipulation, and extreme pose scenarios.

The deep semantics of the rhetorical style in the speech of the dignified guests of Abraham

This research deals with the study of rhetorical methods/styles from the perspective of semantics and rhetoric in the speech of the honored guests of Abraham in the three positions in the holy Koran. The researcher attempted to reveal the semantic secrets and the moral tones underlying the structures of these rhetorical methods after deep analysis and exploration of the depths of the moral fields that came/were used to express them. The researcher insisted on revealing how the previous and subsequent contexts affected and were affected by those methods and their implications. By careful exploration and induction, it has been found that the speech has carefully used the predicate of the subject with all its types, questioning, metaphor, synecdoche, euphemism. The research concluded that deep connotations and precise moral tones of the structures of these methods were observed through exploring the topics that came/were used to express them in the speech of the guests to their host. The research also proved that no other structures could be used to convey the same message.

Justification logic and type theory as formalizations of intuitionistic propositional logic

Abstract We explore two ways of formalizing Kreisel’s addendum to the Brouwer–Heyting–Kolmogorov interpretation. To do this, we compare Artemov’s justification logic with simply typed $\lambda $ calculus. First, we provide a completeness result for Kripke style semantics of the implicational fragment of the intuitionistic logic of proofs. Then we introduce a map from justification terms into $\lambda $ terms, which can be viewed as a method of extracting the computational content of the justification terms. Then we examine the interpretation of Kreisel’s addendum in justification logic along with the image of the resulting justification terms under our map.

UTP semantics for the MCA ARMv8 architecture

Hardware architectures like x86 and ARM provide relaxed memory models for efficiency reasons. The revised ARMv8 architecture is multi-copy atomic (MCA), which brings relaxed-memory effects through thread-local out-of-order, speculative execution and thread-local buffering. In this paper, we investigate the trace semantics for the MCA ARMv8 architecture, acting in the denotational semantics style based on Unifying Theories of Programming (UTP). In order to present all the valid execution results including reorderings of any program under ARMv8, a trace expressed as a sequence of snapshots is introduced, and it relies heavily on various dependencies among program statements. We also study the algebraic laws for MCA ARMv8, including a set of sequential and parallel expansion laws, which are implemented in the rewriting engine Maude. The concept of head normal form is explored for each program, and every program is described in the form of guarded choice which can model the execution of a program with reorderings. Therefore, the linearizability for ARMv8 is supported. Finally, we provide a strategy for deriving the trace semantics from the algebraic semantics. Using the strategy, the trace semantics for each program can be calculated.

Iraida Ciobanu, in the three hypostases of her self-affirmation

Iraida Ciobanu is one of the few plastic artists for whom her creations are synonymous with the genres she practices in painting – static nature and landscape, the most explored forms in rendering poetry and lyrics. Formed as an artist in the early `90s, the artist is devoted to these two genres throughout the time, approaching the landscape as an appeal to the memory arising from lyrical projections, oriented towards the past, while the static nature is a projection of future emotional states. Her works could reveal the following: the static nature returns to the present, being refreshed up by a unique and distinctive compositional, semantic and chromatic style. Moreover, as a professor of fine arts, as well as a scientific researcher concerned with the evolution of static nature as a genre in the post-war Moldovan fine arts, it ensures continuity. Nature and its inexhaustible beauties fully define the artist in a thematic aspect, she finding unique ways to discover continuity in her canvases.

The Design of Regional Cultural Service of the Maritime Silk Road Based on Symbolic Semantics

Objective to solve the puzzle of the lack of guiding theory of regional culture public goods service design in the field of service design, and to explore the psychological and emotional representation and association connotation of public goods service under specific regional culture. Methods By symbolic semantics, the cultural semantics, folk semantics and regional environment semantics of regional cultural public goods service design were characterized and analyzed from three levels: personal emotion, group affiliation and historical folklore. Combining symbolic semantic analysis with user behavior model, the historical intention of regional culture is abstracted and decomposed into multidimensional design factors layer by layer, and the framework of service design factors is further established. Results Taking the product service system of "Maritime Silk Road in western Guangdong" as an example, with the help of image scale map and semantic style analysis of symbolic semantics, the common feelings on the cultural level of "Maritime Silk Road Culture" were analyzed, and the folk journey scenarios and service blueprints were constructed, which were presented in the form of the design of regional cultural service system in western Guangdong. Conclusion It promotes the emotional resonance and cultural identity experience of users in the design of public goods and services by regional culture, and provides theoretical guidance for the design of regional culture products and services.

Deep color calibration for UAV imagery in crop monitoring using semantic style transfer with local to global attention

Color cast of the UAV imagery is inevitable due to the temperature and illuminance changes during the UAV flight. Since color is an important feature in crop monitoring, color cast often produces misleading inference in estimation of crop stress, nutrient, and productivity. Therefore, color calibration is a necessary step to remove the negative effects of color variation for UAV based crop monitoring. Nowadays, the state of art color calibration methods usually use the semantic correspondences for accurate color transfer. However, the mainstream color calibration methods ignore the integration of semantic segmentation and style transfer, and suffer the problem of semantic mismatch. To address this problem, this study proposed a multi decoder architecture that builds the integration of sematic segmentation and style transfer for the color transfer in an end to end mode. Also, this paper introduced an Crop Oriented adaptive instance normalization (AdaIN) method to estimate the color cast in the crop areas, and used that estimated information for color calibration over the whole image area with a local to global attention mechanism. Each proposed module was evaluated in ablation study to test its effectiveness, respectively. Also, the proposed method was evaluated on several crop types and compared with the state of art methods. Experimental results showed that our proposed method achieved state of art or close to state of art performance in all metrics. The research of this work is expected to obtain a general framework to remove the color cast of UAV imagery for crop monitoring, which may build a good foundation for the following data interpretation. Our dataset and codes are can be downloaded at http://github.com/huanghsheng/deep-color-calibration.

Web Platform for Folklore Research Based on Domain Ontology

In this paper, we take a close look at a web platform that provides the tools necessary for working with folklore materials and conducting scientific research based on them. Folklore studies consist of working with audio and video materials, which contain the reproduction of elements of folk art in national languages, creating specific text recordings with translation and comments, written in a public language, and building a picture of the worlds based on available resources. To structure and present this content, we use an ontology-based approach, which allows linguists to describe not only the resources, but also subject knowledge in the Semantic Web style, i.e. using hierarchies of classes, objects and relationships between them. The main feature of folklore research is the need for synchronization of translations, which is achieved by creating a parallel corpora of texts, and the ability to label texts with entities of the subject area, which is called semantic markup. Moreover, each corpus is connected with a certain nationality and has both its own national language and unique system of concepts of the world around it. Such representation imposes many non-standard requirements for the platform, such as working with arbitrary languages, supporting many ontologies, ensuring the creation and editing of national subject ontologies, semantic text markup, presentation, navigation, and search across heterogeneous resources. The developed platform provides all the necessary tools for research, including tools for the development of ontologies in specific national subject areas and manual annotation of texts in real time by several specialists. Resources of the web-platform are located in the resource ontology, which includes such concepts as corpus, video resource, audio resource, graphic image, person, geographical location, genre of text, etc. Ontologies of subject areas are presented in the form of a hierarchy, where the ontology of universals, common to all folklore studies, is located at the top level. At the same time, inherited ontologies are specialized for each represented national corpus. The web application is built with Python Django framework and the TypeScript React library. Data storage is implemented using the Postgres database.

A logical and graphical framework for reaction systems

Reaction Systems (RSs) are a successful computational framework inspired by biological systems. A RS pairs a set of entities with a set of reactions over them. Entities can be used to enable or inhibit each reaction, and are produced by reactions. Entities can also be provided by an external context sequence to simulate in silico biological experiments. In this paper we define an extension of RSs considering nondeterministic and recursive context operators, and give an original labelled transition system (LTS) for extended RSs in the structural operational semantics (SOS) style. Thanks to extended contexts, a single LTS can now account for several biological experiments. The rich information recorded in transition labels is useful to guarantee the compositionality of SOS inference rules as well as to define an assertion language to tailor behavioural and logical equivalences on some specific properties or entities. The SOS rules have been also exploited to design a flexible prototype implementation in logic programming that allows to inspect the LTS and to extract useful information when performing experiments on a RS. Our implementation provides a rapid prototyping tool for (extensions of) RSs, with a user friendly online interface to our interpreter. A parser allows to introduce the logical formulas and the contexts using the usual comfortable concrete syntax. The user can visualise and inspect the LTS for a RS and make some analysis of its underlying computation patterns, can check if the main RS satisfies a given property and if it is equivalent to a second adversarial RS. Finally, the SOS approach is suited to drive additional enhancements of RSs.

UML Sequence Diagram: An Alternative Model

The UML sequence diagram is the second most common UML diagram that represents how objects interact and exchange messages over time. Sequence diagrams show how events or activities in a use case are mapped into operations of object classes in the class diagram. The general acceptance of sequence diagrams can be attributed to their relatively intuitive nature and ability to describe partial behaviors (as opposed to such diagrams as state charts). However, studies have shown that over 80% of graduating students were unable to create a software design or even a partial design, and many students had no idea how sequence diagrams were constrained by other models. Many students exhibited difficulties in identifying valid interacting objects and constructing messages with appropriate arguments. Additionally, according to authorities, even though many different semantics have been proposed for sequence diagrams (e.g., translations to state machines), there exists no suitable semantic basis refinement of required sequence diagram behavior because direct style semantics do not precisely capture required sequence diagram behaviors; translations to other formalisms disregard essential features of sequence diagrams such as guard conditions and critical regions. This paper proposes an alternative to sequence diagrams, a generalized model that provides further understanding of sequence diagrams to assimilate them into a new modeling language called thinging machine (TM). The sequence diagram is extended horizontally by removing the superficial vertical-only dimensional limitation of expansion to preserve the logical chronology of events. TM diagramming is spread nonlinearly in terms of actions. Events and their chronology are constructed on a second plane of description that is superimposed on the initial static description. The result is a more refined representation that would simplify the modeling process. This is demonstrated through remodeling sequence diagram cases from the literature.