Definition Language Research Articles

INTERCULTURALITY AND LANGUAGE TEACHING: EXPERIENCES IN A KOREAN COURSE

This work aims to highlight the importance of the intercultural perspective in teaching foreign languages, based on a case study in a Korean language course based on the author's experience. The definitions of identity, difference, culture, and language, as well as their interrelationships, and how intercultural perspectives can be applied in the classroom are analyzed. The study investigates the presence of interculturality in the educational environment and how theories are practiced. It is concluded that interculturality plays an essential role in teaching foreign languages, allowing students to better understand the culture of the target language, without resorting to stereotypes, and at the same time respect their own culture as the basis of identity. The theoretical framework includes authors such as Byram, Hall, and Hanna, who discuss identity, culture, and interculturality in the context of language teaching.

Bridging Data Models in Health Care With a Novel Intermediate Query Format for Feasibility Queries: Mixed Methods Study.

To advance research with clinical data, it is essential to make access to the available data as fast and easy as possible for researchers, which is especially challenging for data from different source systems within and across institutions. Over the years, many research repositories and data standards have been created. One of these is the Fast Healthcare Interoperability Resources (FHIR) standard, used by the German Medical Informatics Initiative (MII) to harmonize and standardize data across university hospitals in Germany. One of the first steps to make these data available is to allow researchers to create feasibility queries to determine the data availability for a specific research question. Given the heterogeneity of different query languages to access different data across and even within standards such as FHIR (eg, CQL and FHIR Search), creating an intermediate query syntax for feasibility queries reduces the complexity of query translation and improves interoperability across different research repositories and query languages. This study describes the creation and implementation of an intermediate query syntax for feasibility queries and how it integrates into the federated German health research portal (Forschungsdatenportal Gesundheit) and the MII. We analyzed the requirements for feasibility queries and the feasibility tools that are currently available in research repositories. Based on this analysis, we developed an intermediate query syntax that can be easily translated into different research repository-specific query languages. The resulting Clinical Cohort Definition Language (CCDL) for feasibility queries combines inclusion criteria in a conjunctive normal form and exclusion criteria in a disjunctive normal form, allowing for additional filters like time or numerical restrictions. The inclusion and exclusion results are combined via an expression to specify feasibility queries. We defined a JSON schema for the CCDL, generated an ontology, and demonstrated the use and translatability of the CCDL across multiple studies and real-world use cases. We developed and evaluated a structured query syntax for feasibility queries and demonstrated its use in a real-world example as part of a research platform across 39 German university hospitals.

Reseña del uso del lenguaje de programación Python en el Desarrollo de Software

Introduction: This article provides a concise and clear definition of the Python programming language, highlighting its key features and its significance in the current landscape of software development. Python, renowned for its simple and readable syntax, has gained popularity due to its versatility and ease of use. Objective: The primary objective of this study is to answer the question: What role does Python play in current software development and what are its future prospects? This analysis aims to understand the impact of Python on the software industry and assess how its evolution may influence future technological trends. Methods: To address this objective, a literature review was conducted to gather relevant information about Python. Rigorous selection criteria were established to ensure the quality and timeliness of the consulted sources, and a data analysis was carried out that combined qualitative and quantitative approaches. Results: The article summarizes the main advantages and disadvantages of Python, as well as exploring its various areas of application. Python offers advantages such as ease of learning and a robust ecosystem of libraries, but it also presents disadvantages such as slower execution speed compared to other languages. Conclusions: In conclusion, the study synthesizes the results obtained, evaluates the current use of Python in software development, and provides practical recommendations for developers, highlighting the importance of staying updated with the latest versions and tools available.

Review of Existing Tools for Software Implementation of Digital Twins in the Power Industry

Digital twin technology is an important tool for the digitalization of the power industry. A digital twin is a concept that allows for the creation of virtual copies of real objects that can be used for technical state analysis, predictive analysis, and optimization of the operation of power systems and their components. Digital twins are used to address different issues, including the management of equipment reliability and efficiency, integration of renewable energy sources, and increased flexibility and adaptability of power grids. Digital twins can be developed with the use of specialized software solutions for designing, prototyping, developing, deploying, and supporting. The existing diversity of software requires systematization for a well-informed choice of digital twin’s development tool. It is necessary to take into account the technical characteristics of power systems and their elements (equipment of power plants, substations and power grids of power systems, mini- and microgrids). The reviews are dedicated to tools for creating digital twins in the power industry. The usage of Digital Twin Definition Language for the description data of electromagnetic, thermal, and hydrodynamic models of a power transformer is presented.

An adaptive operation planning and EBO-BPNN optimization method for decision support systems

Formulating a course of action (COA) before a combat is crucial for operational command. Research in command and control (C2) artificial intelligence is currently focused on using intelligent auxiliary decision-making methods to implement COA. This paper proposes a COA planning method based on line of operation (LOO) and uses planning domain definition language (PDDL) to describe combat scenarios and COA. Following the effect-based optimization (EBO) principle, an effect evaluation model for COA was constructed, and dynamic bayesian networks (DBNs) was used to determine the reasoning and calculate the results of the effect evaluation network. To further improve the execution efficiency of the effect evaluation model in practical applications, the network was optimized through a back propagation neural network (BPNN). Relevant experiments based on the coordinated distributed air defense and anti-missile scenario were carried out using the LOO model to complete the planning of COA. A BPNN evaluation model based on the DBNs evaluation model was built. After training and fine-tuning, it achieved similar evaluation results, with a mean absolute percentage error (MAPE) of less than 0.02%. Compared with the DBNs model, the BPNN model achieved an efficiency improvement of no less than 65%, effectively reducing the consumption of computing resources. This research is the first time to realize the modeled description of COA planning, automatic evaluation, and calculation optimization of COA effects. It can support the development of decision support systems (DSS) and has the potential for practical application.

Double-Ended Bit-Stealing for Algebraic Data Types

Algebraic data types are central to the development and evaluation of most functional programs. It is therefore important for compilers to choose compact and efficient representations of such types, in particular to achieve good memory footprints for applications. Algebraic data types are most often represented using blocks of memory where the first word is used as a so-called tag, carrying information about the constructor, and the following words are used for carrying the constructor's arguments. As an optimisation, lists are usually represented more compactly, using a technique called bit-stealing, which, in its simplest form, uses the word-alignment property of pointers to byte-addressed allocated memory to discriminate between the nil constructor (often represented as 0x1) and the cons constructor (aligned pointer to allocated pair). Because the representation supports that all values can be held uniformly in one machine word, possibly pointing to blocks of memory, type erasure is upheld. However, on today's 64-bit architectures, memory addresses (pointers) are represented using only a subset of the 64 bits available in a machine word, which leave many bits unused. In this paper, we explore the use, not only of the least-significant bits of pointers, but also of the most-significant bits, for representing algebraic data types in a full ML compiler. It turns out that, with such a particular utilisation of otherwise unused bits, which we call double-ended bit-stealing, it is possible to choose unboxed representations for a large set of data types, while still not violating the principle of uniform data-representations. Examples include Patricia trees, union-find data structures, stream data types, internal language representations for types and expressions, and mutually recursive ASTs for full language definitions. The double-ended bit-stealing technique is implemented in the MLKit compiler and speedup ranges from 0 to 26 percent on benchmarks that are influenced by the technique. For MLKit, which uses abstract data types extensively, compilation speedups of around 9 percent are achieved for compiling MLton (another Standard ML compiler) and for compiling MLKit itself.

A Comprehensive Study on Gender Language and Its Differences in China

The study of language and gender, especially the study of gender language differences involves many fields such as psychology, sociology, anthropology, language and literature, news media, education, and so on. Starting from the broad definition of gender language, this paper composes and reviews the research history of domestic gender language and its differences. Around the research history of domestic gender language, the research period is divided according to the timeline into germination, genesis, and growth. Divided by theme and content, the main content is the phenomenon of sexism in language; the second is the study of gender language style differences; the third is the root causes of sexism and verbal gender differences, i.e., the construction of the corresponding theories; and the fourth is the discussion of the limitations of the study of gender language in foreign countries.

Descriptional Complexity of Finite Automata – Selected Highlights

The state complexity, respectively, nondeterministic state complexity of a regular language L is the number of states of the minimal deterministic, respectively, of a minimal nondeterministic finite automaton for L. Some of the most studied state complexity questions deal with size comparisons of nondeterministic finite automata of differing degree of ambiguity. More generally, if for a regular language we compare the size of description by a finite automaton and by a more powerful language definition mechanism, such as a context-free grammar, we encounter non-recursive trade-offs. Operational state complexity studies the state complexity of the language resulting from a regularity preserving operation as a function of the complexity of the argument languages. Determining the state complexity of combined operations is generally challenging and for general combinations of operations that include intersection and marked concatenation it is uncomputable.

Соотношение языковой и этнической идентификации

The proposed article is devoted to the substantiation of the introduction into scientific use of the concept “linguoethnos”, defined as an association of people for whom a certain language is their native one. This concept is used as a basis for identifying possible types of correlation between linguistic and ethnic identification of a person: linguoethnos establishes the peculiarities of the implementation of ethnic self-determination in relation to the linguistic identity of a person. The definition of the linguoethnos is based on the concepts of “national language” and “native language”. In this concept, the national language is a complex of idioms associated with one ethnic group, for which one linguonym is used as a hyperonym. The article describes the situations of the formation of a superordinate linguoethnos combining several basic linguoethnoses that use different national variants of the same language, and the lack of a linguonymic definition of an idiom. Peripheral characteristics of the national language are “the presence of a literary form of existence” and “the presence of an official status.” When describing the features of the first characteristic, the situation of linking several literary standards with one national language is considered separately: geographically loose (Bukmol and Nynorsk in Norway) and geographically fixed (Mari meadow, Gornomari and northwestern Mari in Mari El). The latter case is interpreted as a situation of formation of a superordinate linguistic ethnos. When describing the second characteristic, a list of official language statuses is given (state, official language of the province, regional language). Two approaches to the definition of a native language are stated: constructivist (native language is the language of my nation) and primordial (native language is functionally the first language of an individual). The primordial approach is considered the only acceptable one for determining the linguoethnos, since it takes into account the deep connection of language with ethnic identity. Two types of relations between linguoethnos and ethnos are established: isomorphic (basic, transformed and selective) and non-isomorphic (genetic and opportunistic).

THE IMPACT OF THE ETYMOLOGICAL STUDY OF THE CONSTITUENTS OF THE CONCEPT LANGUAGE POLICY ON THE FORMATION OF A CONCEPTUAL METAPHOR

The article is dedicated to the study of the semantic features of the constituent lexemes language and policy in the English worldview, which are analysed as components of the concept LANGUAGE POLICY, as well as the peculiarities of their influence on the formation of aconceptual metaphor. It has been established that the word combination language policy is rarely found in general language dictionaries, so it is appropriate to study its lexemes-constituents by their origin in order to find out how their cognitive components interact with each other. 17 and 22 definitions of the lexeme-constituents language and policy have been analysed, respectively. It is noted that the cognitive component a course of action of the lexeme-constituent policy explains the meaning of policy as directed actions on this or that issue. Cognitive components body of words; body of methods of combination of words and used by a nation, people, or race of the lexemes-constituent language explain language as a grouping of words, methods of their combination used by people. It has been established that the expediency of such an analysis consists in a detailed study of the verbalizers of the nominative field of the concept LANGUAGE POLICY. This requires a comprehensive analysis of the concept, taking into account qualitative and quantitative studies. Several conceptual metaphors are identified such as ECOLOGY, LANGUAGE PLANNING IS AN ORGAN, LANGUAGE IS STATUS, LANGUAGE IS FIGHT,MULTILINGUALISM IS MOSAIC, MULTILINGUALISM IS CONSTELLATION and LANGUAGE IS A FLOWER.It was noted that the etymological analysis of the combination of lexemes-constituents narrowed the meaning of lexemes in such a combination, which affected the LANGUAGE POLICY conceptual metaphor.

BIT: A template-based approach to incremental and bidirectional model-to-text transformation

Model-driven development is a model-centric software development paradigm that automates the development process by converting high-level models into low-level code and documents. To maintain synchronization between models and code/documents — which can evolve independently — this paper introduces BIT, a bidirectional language that can serve as a conventional template language for model-to-text transformations. However, a BIT program can function as both a printer, generating text by filling template holes with values from the input model, and a parser, putting parsed values back into the model. BIT comprises a surface language for better usability and a core language for formal definition. We define the semantics of the core language based on the theory of bidirectional transformation, and provide the translation from the surface to the core. We present the proof sketch of the well behavedness of BIT as a formal evidence of soundness. We also conduct three case studies to empirically demonstrate the expressiveness and the effectiveness of BIT. Based on the proof and the case studies, BIT covers the major features of existing template languages, and offers sufficient expressiveness to define real-world model-to-text transformations that can be executed bidirectionally and incrementally.

Black Languaging IS Translanguaging: We Not Just Talkin Bout It, We Bout It Bout It!

Purpose: The purpose of this article is to provide a foundational understanding of translanguaging in order to conceptualize Black Languaging as translanguaging and to expand our definition of multilingualism and reframe how we think about Black Language in schools. Method: The authors summarize seminal literature in translanguaging and raciolinguistic ideologies in order to theorize about Black Language within a translanguaging framework. Results: Centering Black Languaging within a translanguaging framework further implicates the sociopolitical ideologies that shape our conceptualizations of language and dialect and the educational experiences of racially and linguistically minoritized students. Conclusion: A sociopolitically informed definition of Black Language allows us to blur the boundaries of languages and dialects and think of all students—especially racially minoritized students—as translanguaging in co-community.

Linguistics-based formalization of the antibody language as a basis for antibody language models.

Apparent parallels between natural language and antibody sequences have led to a surge in deep language models applied to antibody sequences for predicting cognate antigen recognition. However, a linguistic formal definition of antibody language does not exist, and insight into how antibody language models capture antibody-specific binding features remains largely uninterpretable. Here we describe how a linguistic formalization of the antibody language, by characterizing its tokens and grammar, could address current challenges in antibody language model rule mining.

A framework for neurosymbolic robot action planning using large language models.

Symbolic task planning is a widely used approach to enforce robot autonomy due to its ease of understanding and deployment in engineered robot architectures. However, techniques for symbolic task planning are difficult to scale in real-world, highly dynamic, human-robot collaboration scenarios because of the poor performance in planning domains where action effects may not be immediate, or when frequent re-planning is needed due to changed circumstances in the robot workspace. The validity of plans in the long term, plan length, and planning time could hinder the robot's efficiency and negatively affect the overall human-robot interaction's fluency. We present a framework, which we refer to as Teriyaki, specifically aimed at bridging the gap between symbolic task planning and machine learning approaches. The rationale is training Large Language Models (LLMs), namely GPT-3, into a neurosymbolic task planner compatible with the Planning Domain Definition Language (PDDL), and then leveraging its generative capabilities to overcome a number of limitations inherent to symbolic task planners. Potential benefits include (i) a better scalability in so far as the planning domain complexity increases, since LLMs' response time linearly scales with the combined length of the input and the output, instead of super-linearly as in the case of symbolic task planners, and (ii) the ability to synthesize a plan action-by-action instead of end-to-end, and to make each action available for execution as soon as it is generated instead of waiting for the whole plan to be available, which in turn enables concurrent planning and execution. In the past year, significant efforts have been devoted by the research community to evaluate the overall cognitive capabilities of LLMs, with alternate successes. Instead, with Teriyaki we aim to providing an overall planning performance comparable to traditional planners in specific planning domains, while leveraging LLMs capabilities in other metrics, specifically those related to their short- and mid-term generative capabilities, which are used to build a look-ahead predictive planning model. Preliminary results in selected domains show that our method can: (i) solve 95.5% of problems in a test data set of 1,000 samples; (ii) produce plans up to 13.5% shorter than a traditional symbolic planner; (iii) reduce average overall waiting times for a plan availability by up to 61.4%.

Plotting: a case study in lifted planning with constraints

We study a planning problem based on Plotting, a tile-matching puzzle video game published by Taito in 1989. The objective of this turn-based game is to remove a target number of coloured blocks from a grid by sequentially shooting blocks into the same grid. Plotting features complex transitions after every shot: various blocks are affected directly, while others can be indirectly affected by gravity. We consider modelling and solving Plotting from two perspectives. The puzzle is naturally cast as an AI Planning problem and we first discuss modelling the problem using the Planning Domain Definition Language (PDDL). We find that a model in which planning actions correspond to player actions is inefficient with a grounding-based state-of-the-art planner. However, with a more fine-grained action model, where each change of a block is a planning action, solving performance is dramatically improved. We also describe two lifted constraint models, able to capture the inherent complexities of Plotting and enabling the application of efficient solving approaches from SAT and CP. Our empirical results with these models demonstrates that they can compete with, and often exceed, the performance of the dedicated planning solvers, suggesting that the richer languages available to constraint modelling can be of benefit when considering planning problems with complex changes of state. CP and SAT solvers solved almost all of the largest and most challenging instances within 1 hour, whereas the best planning approach solved approximately 30%. Finally, the flexibility provided by the constraint models allows us to easily curate interesting levels for human players.

Quantification of Equivocal Findings in F18-Fluciclovine PET/CT Scans for Biochemical Recurrence of Localized Prostate Cancer

PET/CT scans are being used to assess patients who have experienced biochemical failure following surgery or radiation therapy for localized prostate cancer. We aimed to evaluate the language used in report impressions and to determine the level of confidence that radiologists have when reporting on lesions in various anatomic sites. Between 2015 and 2021, 295 F18-fluciclovine PET/CT scan reports were identified. Thirteen phrases commonly used by radiologists in the report impression section to describe a lesion of interest were identified and categorized into three confidence categories: definitive (positive and negative), likely (consistent with, most likely, favors, probable), and unsure (suspicious for, concerning for, non-specific, conspicuous, compatible with, borderline, unknown). The use of definitive language varied depending on the anatomic site, with the highest use in bone (87.1%) and the lowest use in the intact prostate (34.6%). In patients with a PSA < 0.5, there was the highest degree of definitive certainty (89.2%), whereas in patients with a PSA > 1, there was the least definitive certainty (66.2%). The language used in these reports has not been standardized, with definitive, likely, and unsure findings reported in 68.6%, 9.7%, and 21.7% of scans, respectively.

From words to pictures: Row-column combinations and Chomsky-Schützenberger theorem

The row-column combination RCC maps two (word) languages over the same alphabet onto the set of rectangular arrays, i.e., pictures, such that each row/column is a word of the first/second language. The resulting array is thus a crossword of the component words. Depending on the family of the components, different picture (2D) language families are obtained: e.g., the well-known tiling-system recognizable languages are the alphabetic projection of the crossword of local (regular) languages. We investigate the effect of the RCC operation especially when the components are context-free, also with application of an alphabetic projection. The resulting 2D families are compared with others defined in the past. The classical characterization of context-free languages, known as Chomsky-Schützenberger theorem, is extended to the crosswords in this way: the projection of a context-free crossword is equivalent to the projection of the intersection of a 2D Dyck language and the crossword of strictly locally testable language. The definition of 2D Dyck language relies on a new more flexible so-called Cartesian RCC operation on Dyck languages. The proof involves the version of the Chomsky-Schützenberger theorem that is non-erasing and uses a grammar-independent alphabet.

Learning Safe Action Models with Partial Observability

A common approach for solving planning problems is to model them in a formal language such as the Planning Domain Definition Language (PDDL), and then use an appropriate PDDL planner. Several algorithms for learning PDDL models from observations have been proposed but plans created with these learned models may not be sound. We propose two algorithms for learning PDDL models that are guaranteed to be safe to use even when given observations that include partially observable states. We analyze these algorithms theoretically, characterizing the sample complexity each algorithm requires to guarantee probabilistic completeness. We also show experimentally that our algorithms are often better than FAMA, a state-of-the-art PDDL learning algorithm.

Generalized Planning for the Abstraction and Reasoning Corpus

The Abstraction and Reasoning Corpus (ARC) is a general artificial intelligence benchmark that poses difficulties for pure machine learning methods due to its requirement for fluid intelligence with a focus on reasoning and abstraction. In this work, we introduce an ARC solver, Generalized Planning for Abstract Reasoning (GPAR). It casts an ARC problem as a generalized planning (GP) problem, where a solution is formalized as a planning program with pointers. We express each ARC problem using the standard Planning Domain Definition Language (PDDL) coupled with external functions representing object-centric abstractions. We show how to scale up GP solvers via domain knowledge specific to ARC in the form of restrictions over the actions model, predicates, arguments and valid structure of planning programs. Our experiments demonstrate that GPAR outperforms the state-of-the-art solvers on the object-centric tasks of the ARC, showing the effectiveness of GP and the expressiveness of PDDL to model ARC problems. The challenges provided by the ARC benchmark motivate research to advance existing GP solvers and understand new relations with other planning computational models. Code is available at github.com/you68681/GPAR.

Auditives Dekodierungstraining zur Unterstützung der Dolmetscherausbildung: Die Rolle der deutschen Sprachvarietäten und der neuen Technologien

The paper aims to propose a reflection on the importance of German varieties in the preparation of interpreters. Like many other languages, German is classified as a pluricentric language, i. e. a language officially spoken in more than one centre or nation. This makes it a very variegated language that boasts a multitude of both standard and non-standard varieties. The task of interpreters who choose German as a foreign language is therefore to be able to understand and translate into another language what is spoken by native speakers of German, many of whom, according to the previous statement, often speak different varieties. To do this, the interpreters’ preparation must consider the inclusion of the different language varieties of both standard and non-standard German, especially at the level of auditory decoding, in order to facilitate the understanding of the message at a receptive level. Starting from the definition of a pluricentric language, this contribution will highlight the main difficulties of interpreters at the level of listening comprehension, most of which are found at the level of auditory decoding, before proposing training aimed at decoding the different varieties of standard and non-standard German realised through the use of new technologies.