Implementation Of Language Research Articles

Taking Back Control in an Intermediate Representation for GPU Computing

We describe our experiences successfully applying lightweight formal methods to substantially improve and reformulate an important part of Standard Portable Intermediate Representation SPIRV, an industry-standard language for GPU computing. The formal model that we present has allowed us to (1) identify several ambiguities and needless complexities in the way that structured control flow was defined in the SPIRV specification; (2) interact with the authors of the SPIRV specification to rectify these problems; (3) validate the developer tools and conformance test suites that support the SPIRV language by cross-checking them against our formal model, improving the tools, test suites, and our models in the process; and (4) develop a novel method for fuzzing SPIRV compilers to detect miscompilation bugs that leverages our formal model. The latest release of the SPIRV specification incorporates the revised set of control-flow definitions that have arisen from our work. Furthermore, our novel compiler-fuzzing technique has led to the discovery of twenty distinct, previously unknown bugs in SPIRV compilers from Google, the Khronos Group, Intel, and Mozilla. Our work showcases the practical impact that formal modelling and analysis techniques can have on the design and implementation of industry-standard programming languages.

Efficient Dual-Numbers Reverse AD via Well-Known Program Transformations

Where dual-numbers forward-mode automatic differentiation (AD) pairs each scalar value with its tangent value, dual-numbers reverse-mode AD attempts to achieve reverse AD using a similarly simple idea: by pairing each scalar value with a backpropagator function. Its correctness and efficiency on higher-order input languages have been analysed by Brunel, Mazza and Pagani, but this analysis used a custom operational semantics for which it is unclear whether it can be implemented efficiently. We take inspiration from their use of linear factoring to optimise dual-numbers reverse-mode AD to an algorithm that has the correct complexity and enjoys an efficient implementation in a standard functional language with support for mutable arrays, such as Haskell. Aside from the linear factoring ingredient, our optimisation steps consist of well-known ideas from the functional programming community. We demonstrate the use of our technique by providing a practical implementation that differentiates most of Haskell98.

Nero: A Deterministic Leaderless Consensus Algorithm for DAG-Based Cryptocurrencies

This paper presents the research undertaken with the goal of designing a consensus algorithm for cryptocurrencies with less latency than the current state-of-the-art while maintaining a level of throughput and scalability sufficient for real-world payments. The result is Nero, a new deterministic leaderless byzantine consensus algorithm in the partially synchronous model that is especially suited for Directed Acyclic Graph (DAG)-based cryptocurrencies. In fact, Nero has a communication complexity of O(n3) and terminates in two message delays in the good case (when there is synchrony). The algorithm is shown to be correct, and we also show that it can provide eventual order. Finally, some performance results are given based on a proof of concept implementation in the Rust language.

Image-based approximation of derivatives of traditional differential metrics of angular distortion in map projections

ABSTRACT Map projections are imaging procedures used to depict geographic features. We adopt the traditional differential metric and exploit the intrinsic image properties of map projections to establish an image-based differential metric for evaluating distortions in map projections, obtaining an effective, practical, and relatively accurate metric. We use bivariate polynomial functions to approximate the forward and inverse formulae of map projections. Thereafter, the proposed metric is conveniently calculated using the partial derivatives of the approximate forward functions based on polynomial functions, while complicated differential calculations are avoided. Moreover, multiple sampling and image filters mitigate the influence of imaging noise and achieve a high computation precision. Experiments were conducted using the NASA G.Projector mapping software to generate images from more than 200 map projections. Explicit equations of map projections were not required owing to the use of the mapping software. These images were then evaluated using the proposed metric through an implementation in the Julia programming language. The corresponding results confirmed that the proposed metric avoided the drawbacks of the great circle arc metric and provided considerably low errors (1.12° on average) and high consistency (0.999 on average) with respect to the traditional differential metric. Although there were errors, experimental results indicated that feasibility and high usability were achieved by the image-based method for evaluating distortions in small-scale map projections.

Bank Marketing Data Classification Using Optimized Voting Ensemble, Sine Cosine, and Genetic Algorithms

Nowadays, the banking industry is no exception to the general trend of massive data production in all spheres of modern life. In this research, we analyze the categorization of marketing data from banks using a variety of machine learning techniques. The term banking refers to the supply of services by a bank to an individual consumer. The data was first compiled from the UCI Machine Learning repository and the Kaggle website. Phone-based banking marketing statistics are the focus of this data set. Python is utilized as the language of implementation, and the Machine Learning concept is employed for statistical learning and data analysis in this work. An improved prediction is the primary goal of machine learning's model-building phase. In order to classify the results, a supervised Naive Bayes algorithm is used to the data. The primary goal of the modeling effort is to characterize whether or not the consumer has chosen a term deposit. The bank should devote substantial time to returning phone calls from prospective customers. Accuracy, precision, recall, and F1 score were all evaluated as a consequence of this study in the direction of term deposit forecasting.

MARPLE: программное обеспечение для мультифизического моделирования в задачах сплошных сред

The research code MARPLE was originally created to model high-speed dynamic processes caused by the action of high-intensity energy fluxes on matter. At present, it is a universal tool able to solve various continuum mechanics problems. The implemented physical models are the following: single-fluid two-temperature MHD model of plasma dynamics, including electron-ion energy exchange and generalized Ohm's law; model of electrical and thermal conductivity taking into account the anisotropy in the magnetic field; radiative heat transfer: models pertinent to optically thin as well as optically thick media: techniques for taking into account radiative cooling losses, spectral multigroup diffusion transfer, laser radiation propagation etc.; model of multicomponent flow. Calculations are performed using wide-range equations of state, transport and optical data. The MARPLE code utilises modern computational technologies based on block structured and unstructured meshes consisting of tetrahedral, hexahedral, prismatic elements and their combinations. The solvers implement conservation laws using high-resolution techniques. We apply the physical splitting to solve the governing system. The object-oriented approach to software design is used, as well as methods of object and generic programming (C++ implementation language). Design of computational domains is provided by means of integrated SALOME open source CAD-CAE system. Marple works as MPI application for modern HPC systems. The paper presents examples of problems in plasma dynamics, magnetohydrodynamics, astrophysics, and solid thermomechanics solved by means of the MARPLE code.

Alias Analysis and Calculus based on Segmentation Address Memory Model

We present a straightforward implementation of a simplified imperative programming language with direct memory access and address arithmetic, and a simple static analyzer for memory leaks. Our study continues a line of research attempted (in Innopolis University in years 2016-2022) on alias calculi for imperative programming languages with decidable pointer arithmetic but differs by memory address model – we study segmented memory model instead linear one.

Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

Radial Basis Function Neural Network (RBFNN) ensembles have long suffered from non-efficient training, where incorrect parameter settings can be computationally disastrous. This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network (SRBFNN) through the behavior’s integration of satisfiability programming. Inspired by evolutionary algorithms, which can iteratively find the near-optimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN-2SAT). The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language. With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. It has been confirmed that the EP algorithm is quite effective in training and obtaining the best output weight, accompanied by the slightest iteration error, which minimizes the objective function of SRBFNN-2SAT.

Значения прилагательного алаг / ала в бурятском и хакасском языках (на примере эпических произведений)

This paper presents a comparative analysis of epic works aimed at examining the semantic structures of two adjectives, alag in Buryat and ala in Khakas. The analysis findings provide a comprehensive picture of the semantic space of the words under study. Special attention is paid to word-to-word connections in the epic language, allowing the nomination motive to be identified. This study has contributed to uncovering the new meanings of the adjective alag, namely “brilliant,” “anxious,” and “dulled,” which are not specified in Mongolian-Russian dictionaries. The issue of the primary and secondary meanings is considered to be crucial in studying the semantic transitions within a polysemant. It is suggested that the meaning of “motley” was derived from the meaning “brilliant,” referring to the predominance of light spots or stripes. The word alag is assumed to have combined with the synonyms erēn “variegated” and sōhor “motley” in the epos language after losing the supposed primary meaning “brilliant.” Identifying the common meaning of “shining” in Turkic-Mongolian epic reflects the peculiarities of the national-cultural worldview of related peoples. The language representation of perceptual information is regarded as a result of the primary stage of self-knowledge, reflecting the mental-psychological and national-cultural specificity of Turkic-Mongolian people. Studying the semantic structure of the adjective alag / ala is expected to identify some general lines of the perceptual information implementation in Turkic and Mongolian languages.

ПРАГМАТИКА КЛИШЕ ДА НЕТ В СОВРЕМЕННОМ МЕДИЙНОМ ДИАЛОГЕ

The article is about the use of “da net (yes no)” speech cliche in modern Russian newspaper, internet- and radiotexts. The analysis of the Kommersant publishing house in 2022–2023 makes it possible to identify such functions of the construction as mitigation of denial, organization of a questionand-answer passage, ironic clarification of the author’s thought, involvement of the addressee in the process of reasoning. In general, the conversational communicative provides dialogization of media text. The article notes that linguistic dictionaries lack adequate information about the meaning and use of the speech cliche “yes no”, and the task is to clarify the lexicographic fixation of the turnover, taking into account its implementation in modern Russian media language.

Top-Down Learning Pedagogy for Real Time Embedded System Design

Abstract : This paper presents an innovative pedagogical approach for average learners to implement projects by effectively fitting their knowledge in solving real-world problems. In particular, it concentrates on embedded systems and embedded signal processing as the current world is experiencing through digital era. Even though both courses are taught, only less numbers of students are opting for embedded projects due to fear of coding and lack of fitting their knowledge appropriately. The focus of this study is to make students to come out of fear by following top-down teaching learning methodology for the design and implementation of Electro Cardio Gram (ECG) data acquisition system. Accordingly, initial interest has been generated by taking the students to the hospital where doctors acquire ECG routinely for their patients and do Fast Fourier Transform (FFT) to observe the spectrum for diagnosis purpose. Every real time system uses high level language for implementation. However, noncomputer science students always found it difficult. In order to make the students to come out of fear, simple scripting language MATLAB was tried first. MATLAB coding demo was given to observe the waveforms and an exercise was made to correlate with actual workplace. After interest creation phase, the relationship has been established between the practical they did and the workplace instrument. In the final stage, their learning process was activated by applying inquiry-based (Masoodhu Banu et al. (2020)) learning. Once the quest for real time implementation was created, it was observed that the student's curiosity was increased enormously and was instituted to be effective coders in solving real time applications with more confidence Keywords: Top-Down learning, Bottom-up learning, ECG, Active learning, embedded system

UNISONOST JEZIČKE POLITIKE I PLANIRANjA U SRBIJI I EVROPSKOJ UNIJI

The aim of the paper is, by comparing the results of the implemented language policy in Serbia and the European Union in the past twenty years of this century, to find an answer to the research question whether the language policy and language planning are a „choice” of a social community or whether it represents the adoption and implementation of that pol- icy by the relevant authorities, not taking into account religious, socio-cultural, political and other characteristics of the countries at a certain historical moment. The paper applies the operational method of content analysis of documents, as well as the comparative analysis of statistical data of the relevant bodies in the Republic of Serbia and the EU. In the EU member countries, 83.3% of all students learn at least one world language, while that percentage in the Republic of Serbia is 100%. It should be borne in mind that the lower percentage in the EU results from the fact that only 14 member states have compulsory early learning of world languages, i.e. the first world language between the ages of 6 and 7, and in those 14 countries 99% of all the students are covered by the above-mentioned language policy. Furthermore, 79.4% of students in the EU learn English as the first foreign language, while that percentage in Serbia is 97.34%. Therefore, the tendency of the growth of English language learning in the period between 2009 and 2016 or 2022 continues both in the Republic of Serbia and the EU. Today, in the Republic of Serbia, only 2.74% of students in the first educational cycle do not learn English as the first foreign language, while that percentage of younger students in the EU is 20.6%. The research results also indicate that in the Republic of Serbia the second world language is German, which is learnt by almost one half of all primary school students, followed by French, Russian, Italian and Spanish, while in the EU, the predominant second world language is French, followed by German and Spanish as the only world language with the percentage of its learners increasing in the past decade. The research results show that the proclaimed multilingualism from the end of the 20th century has remained just ink on the paper because English, both in Serbia and in the EU member countries, has reached the first place by its presence as the first and often the only foreign language that is learnt. Based on the relevant research in this field, such dominance does not take the Foreign Language Learning Strategy in Serbia into account.

Implementation science in plain language: The use of nonjargon terms to facilitate collaboration.

Interdisciplinary collaboration and stakeholder engagement are key ingredients in implementation science research. However, effective and efficient collaboration can be limited by the complexity of implementation science terms. In this article, we argue that the development and use of plain language implementation science terms is an essential step to facilitate collaboration and engagement. We present an example of plain language development to portray the process and the potential benefits plain language can have on implementation science research. Implementation scientists and intervention experts codeveloped plain language implementation terms as a part of an implementation-effectiveness trial in western Kenya and in preparation for a stakeholder collaborative design meeting. The developed plain language terms facilitated wider stakeholder understanding and integration of implementation science findings that could inform the design of a stakeholder-led implementation coaching program. We encourage the use of the plain language terms presented in this article, further translation, and additional development of other plain language terms for implementation science constructs.

Data Migration from Visual Basic Interfaces to Excel Tables Prevent Conflict Using Proposed Models

In relational and complex spreadsheets, relational and non-relational database models, high-speed data migration with scalable structure using visual Basic Excel programming language implementations with proposed migration model. One of the primary purposes behind making a point of interaction through the Visual Basic Application (VBA) is that most PC clients with logical preparation will currently know about Succeed and its significant capabilities (like arranging furthermore, plotting datasets). Even though Excel itself is in many cases utilized as an information storehouse by clients. The time factor, reliability, and credibility of migrating this data from one table to another through programming interfaces were measured using the link codes between the tables. In this paper, the migration and migration of homogeneous and heterogeneous data are investigated by using two types of different migration models of data to measure and match these data and the extent of their integration after migration. Specifies the target data for migration from the input tables in the Excel program to the target tables in larger databases. Furthermore, the two models (A, B) middleware provide an architecture that can be extended to support Relational database management systems (RDBMS) and other graphing databases. Experiments were performed using excel tables, both of which are related as source information bases, and as the data set for the source and target datasets, the migration time between these tables for the two models was calculated While retaining the same characteristics.

Categorical Data Structures for Technical Computing

Many mathematical objects can be represented as functors from finitely-presented categoriesCtoSet. For instance, graphs are functors toSetfrom the category with two parallel arrows. Such functors are known informally asC-sets. In this paper, we describe and implement an extension ofC-sets having data attributes with fixed types, such as graphs with labeled vertices or real-valued edge weights. We call such structures acsets, short for attributedC-sets. Derived from previous work on algebraic databases, acsets are a joint generalization of graphs and data frames. They also encompass more elaborate graph-like objects such as wiring diagrams and Petri nets with rate constants. We develop the mathematical theory of acsets and then describe a generic implementation in the Julia programming language, which uses advanced language features to achieve performance comparable with specialized data structures.

Performance Evaluation of C/C++, MicroPython, Rust and TinyGo Programming Languages on ESP32 Microcontroller

The rapid growth of the Internet of Things (IoT) and its applications requires high computational efficiency, low-cost, and low-power solutions for various IoT devices. These include a wide range of microcontrollers that are used to collect, process, and transmit IoT data. ESP32 is a microcontroller with built-in wireless connectivity, suitable for various IoT applications. The ESP32 chip is gaining more popularity, both in academia and in the developer community, supported by a number of software libraries and programming languages. While low- and middle-level languages, such as C/C++ and Rust, are believed to be the most efficient, TinyGo and MicroPython are more developer-friendly low-complexity languages, suitable for beginners and allowing more rapid coding. This paper evaluates the efficiency of the available ESP32 programming languages, namely C/C++, MicroPython, Rust, and TinyGo, by comparing their execution performance. Several popular data and signal processing algorithms were implemented in these languages, and their execution times were compared: Fast Fourier Transform (FFT), Cyclic Redundancy Check (CRC), Secure Hash Algorithm (SHA), Infinite Impulse Response (IIR), and Finite Impulse Response (FIR) filters. The results show that the C/C++ implementations were fastest in most cases, closely followed by TinyGo and Rust, while MicroPython programs were many times slower than implementations in other programming languages. Therefore, the C/C++, TinyGo, and Rust languages are more suitable when execution and response time are the key factors, while Python can be used for less strict system requirements, enabling a faster and less complicated development process.

Éléments de la syntaxe générative du TEMPS en AT

The main aim of this article is the study of the notion of time in the verbal utterance in Amazigh Tashelhit (AT), one of the three variants of the Amazigh language in Morocco. Our study aims to examine certain aspects relating to the expression of temporality in the verbal presentations of Amazigh people. Note that the theoretical framework underlying our analysis is the Minimalist Generative Grammar Program. The central problem to which this work attempts to provide some answers is that of identifying the mechanisms that the Amazigh language implements to express time in the verbal sentence.

RegCPython: A Register-based Python Interpreter for Better Performance

Interpreters are widely used in the implementation of many programming languages, such as Python, Perl, and Java. Even though various JIT compilers emerge in an endless stream, interpretation efficiency still plays a critical role in program performance. Does a stack-based interpreter or a register-based interpreter perform better? The pros and cons of the pair of architectures have long been discussed. The stack architecture is attractive for its concise model and compact bytecode, but our study finds that the register-based interpreter can also be implemented easily and that its bytecode size only grows by a small margin. Moreover, the latter turns out to be appreciably faster. Specifically, we implemented an open source Python interpreter named RegCPython based on CPython v3.10.1. The former is register based, while the latter is stack based. Without changes in syntax, Application Programming Interface, and Application Binary Interface, RegCPython is excellently compatible with CPython, as it does not break existing syntax or interfaces. It achieves a speedup of 1.287 on the most favorable benchmark and 0.977 even on the most unfavorable benchmark. For all Python-intensive benchmarks, the average speedup reaches 1.120 on x86 and 1.130 on ARM. Our evaluation work, which also serves as an empirical study, provides a detailed performance survey of both interpreters on modern hardware. It points out that the register-based interpreters are more efficient mainly due to the elimination of machine instructions needed, while changes in branch mispredictions and cache misses have a limited impact on performance. Additionally, it confirms that the register-based implementation is also satisfactory in terms of memory footprint, compilation cost, and implementation complexity.

Heritage Language Long-Distance Acquisition in Remote Areas—Implementing Telecollaboration in Social Media to Increase Exposure to Polish Language and Culture

This paper reports on a study conducted during the implementation of the Polish language and culture promotion project, run by Maria Curie-Skłodowska University and financed by the Polish National Agency for Academic Exchange. In this project, Polish students were involved in telecollaboration with Brazilians from the Ijui region. The aim of this study was to investigate the possibilities of arranging heritage language acquisition through telecollaboration via social media. Due to the isolation of many communities, telecollaboration can be a useful method facilitating heritage language and culture acquisition across the world. This article used the case study method, in which the “Language Clinic” component of the project was taken under detailed scrutiny.
 The project showed language shift and translanguaging as it happened—initially, the students from Brazil used English as a lingua franca and as a classroom language; however, once they grew more confident, they replaced English with Polish as the target language. For Polish student assistants, participation in the project brought about many benefits: increased orthophonic awareness, gaining an understanding of how careless articulation and inappropriate intonation of the utterance may lead to communication breakdown.

TOWARDS THE APPROACH TO BUILDING SMART CONTRACTS BASED ON BUSINESS RULES USING NATURAL LANGUAGE PROCESSING

This paper considers the smart contracts development process based on business rules using natural language processing as the research object. The research subject includes software components for creating smart contracts based on business rules using natural language processing. The research aims to simplify the software component development for decentralized systems by using smart contracts generation from business rules written in natural language. This study considers smart contract development approaches and technologies, intelligent text processing methods, as well as software development techniques using the Python programming language for the experimental implementation of the proposed solution. This study outlines the relevance of this research, provides a state-of-the-art analysis, proposes the improved procedure of smart contracts’ development and deployment, and suggests an algorithm for smart contract generation based on business rules.