Reviewerly/exHarmony huggingface dataset:
Language Model Method for Collocation Rules of Parts of Speech in Machine Translation System

With the development of the times, modern society has now entered the Internet of Things (IoT) information age and Machine Translation (MT) plays an important role in increasingly frequent cross-language communication. In recent years, China's artificial intelligence industry has been in a stage of rapid construction, and the scale of its core industries has grown explosively, and a large number of artificial intelligence companies, including issuers, have emerged. Part of speech has always been a major problem in MT. One of the reasons is that there are a large number of multi-category words in Chinese and a large number of polysemy words in English, so part of speech collocation problems account for a large proportion of MT errors, which to some extent affects the credibility and accuracy of the translation. To reduce the error problem in MT of part of speech collocation, this paper used Machine Learning (ML) methods to study the Language Model (LM) of part of speech collocation based on recurrent neural network (NN) and compared it with the traditional statistical LM. In terms of the accuracy rate of the two LMS in the automatic evaluation index of machine translation, the experimental results show that the recursive NN LM established by the ML method had an accuracy rate of 80.42% and 83.57% respectively for the part-of-speech matching rules of the IoT machine translation system in the dialogue between Chinese and English and the translation of articles. The accuracy of traditional statistical LM evaluation was 71.29% and 69.52%, respectively. Compared to traditional statistical LM, the accuracy of translation was higher. This showed that the recurrent NN LM reduced the number of errors in the collocation of parts of speech in MT and improved the accuracy and credibility of MT.
Development of a management tool to prevent emotional burnout in project teams

The article studies the phenomenon of emotional burnout in the framework of project team management. The authors of the article have considered the concept of emotional burnout, identified the causes of stress among project team members during project implementation and concluded that probability of emotional burnout syndrome can be reduced due to effective selection of project team by manager and balanced distribution of responsibilities among team members. As a solution for project managers, the authors have considered a “functional map” tool. A comparison of the functional map and a job description has been made in order to visualize distinctive features of the functional map. Based on the tool’s advantages and disadvantages analysis, the authors have proposed innovations to minimize probability of burnout syndrome among project team members. In conclusion, the authors have given their recommendations to project managers on controlling emotional burnout in project teams.
Implementing Project-Based Learning to Enhance Students' Reading Skills in Report Text

This study concentrated on using project-based learning to help students become more proficient readers, particularly of report texts. This study had two goals, the first is to examine how project-based learning can be used to help students become better readers specially on report texts. Moreover, the study aims to track students' reactions to the implementation of project-based in reading learning. Mixed method design was used as the research design for this study. Additionally, the researchers used several instruments to gather data, including observation sheets, reading tests for students, questionnaires, and interview questions. The study's findings showed that project-based learning, when used to teach students in reading reports text with common themes and constant teacher guidance throughout the reading process may enhance students' reading comprehension. The average score of the students' reading tests taken chronologically shows that the students enhance their reading skills in the report text. The results also demonstrated that students responded positively to the implementation of project-based learning in reading report text. The opinions of the students demonstrated that they believed project-based learning improved their comprehension of the content of the report text. Additionally, since project-based learning enables students to read more comprehensively, it is advised that English teachers use it to teach reading skills for other genres of texts and other language skills.
Developers talking about code quality

Abstract There are many aspects of code quality, some of which are difficult to capture or to measure. Despite the importance of software quality, there is a lack of commonly accepted measures or indicators for code quality that can be linked to quality attributes. We investigate software developers’ perceptions of source code quality and the practices they recommend to achieve these qualities. We analyze data from semi-structured interviews with 34 professional software developers, programming teachers and students from Europe and the U.S. For the interviews, participants were asked to bring code examples to exemplify what they consider good and bad code, respectively. Readability and structure were used most commonly as defining properties for quality code. Together with documentation, they were also suggested as the most common target properties for quality improvement. When discussing actual code, developers focused on structure, comprehensibility and readability as quality properties. When analyzing relationships between properties, the most commonly talked about target property was comprehensibility. Documentation, structure and readability were named most frequently as source properties to achieve good comprehensibility. Some of the most important source code properties contributing to code quality as perceived by developers lack clear definitions and are difficult to capture. More research is therefore necessary to measure the structure, comprehensibility and readability of code in ways that matter for developers and to relate these measures of code structure, comprehensibility and readability to common software quality attributes.
<scp>Pre‐trained</scp>language models: What do they know?

Abstract Large language models (LLMs) have substantially pushed artificial intelligence (AI) research and applications in the last few years. They are currently able to achieve high effectiveness in different natural language processing (NLP) tasks, such as machine translation, named entity recognition, text classification, question answering, or text summarization. Recently, significant attention has been drawn to OpenAI's GPT models' capabilities and extremely accessible interface. LLMs are nowadays routinely used and studied for downstream tasks and specific applications with great success, pushing forward the state of the art in almost all of them. However, they also exhibit impressive inference capabilities when used off the shelf without further training. In this paper, we aim to study the behavior of pre‐trained language models (PLMs) in some inference tasks they were not initially trained for. Therefore, we focus our attention on very recent research works related to the inference capabilities of PLMs in some selected tasks such as factual probing and common‐sense reasoning. We highlight relevant achievements made by these models, as well as some of their current limitations that open opportunities for further research. This article is categorized under: Fundamental Concepts of Data and Knowledge &gt; Key Design Issues in Data Mining Technologies &gt; Artificial Intelligence
Building Tiny house from waste

This paper contributes to the understanding of how critical reflection can be applied to sustainability. This was accomplished by tracing the progression of a tiny-house project over time and the associated activities, which involved sourcing secondhand and discarded materials. We are a group of researchers and practitioners who worked together to explore and challenge the established norms of sustainability in housing practices: who is building, what is being built, with what materials, and through which processes. The use of discarded materials as resources for building a tiny house came to be decisive in shaping a platform for inclusion and sustainable practices. While the most common practice of building involves buying the materials needed at a lumber yard, working with discarded and secondhand materials requires time and flexibility. Tools play a central role in adapting random waste to specific purposes, a process that also demands skills in handling tools creatively. Additionally, gathering, organizing, and cleaning are activities that should be given special attention when working with these types of materials. In this paper, we explain how we reinjected waste materials into the production chain and how our work contributes to sustainable development from environmental and social perspectives. The argument for sustainability in our research revolves around exploring processes that include more groups in society and alternative ways of organizing the resources available.
The Mental Causality Exclusion Argument and the Levels of Organization of Living Objects

The paper aims to demonstrate the possibility of consistently accepting the existence of effective mental causality in the fundamentally physical world. We suppose that the concept of causality in J. Kim’s exclusion argument against mental causation, which implies а generative conception of causal relations, can be revised taking into account the specificity of the multilevel organization of living objects. Rejection of the mechanistic model of causality as a linear process, allows you to maintain commitment to the principle of causal closure of the physical world and at the same time explain how top-down causality at the macro level is possible. For this, we use the model of a fractal tree of causal chains by J. Lowe, in which mental causality plays the role of an indirect cause of a fact. We carry out a meaningful distinction between the causality of facts and events by resorting to the multilevel model of J. Ellis, in which mental causality can be considered as a macro-level fact that has a selective effect on physical events of lower levels, taking into account a wide environmental context.
Evaluation of Blockchain Networks’ Scalability Limitations in Low-Powered Internet of Things (IoT) Sensor Networks

With the development of Internet of Things (IoT) technologies, industries such as healthcare have started using low-powered sensor-based devices. Because IoT devices are typically low-powered, they are susceptible to cyber intrusions. As an emerging information security solution, blockchain technology has considerable potential for protecting low-powered IoT end devices. Blockchain technology provides promising security features such as cryptography, hash functions, time stamps, and a distributed ledger function. Therefore, blockchain technology can be a robust security technology for securing IoT low-powered devices. However, the integration of blockchain and IoT technologies raises a number of research questions. Scalability is one of the most significant. Blockchain’ scalability of low-powered sensor networks needs to be evaluated to identify the practical application of both technologies in low-powered sensor networks. In this paper, we analyse the scalability limitations of three commonly used blockchain algorithms running on low-powered single-board computers communicating in a wireless sensor network. We assess the scalability limitations of three blockchain networks as we increase the number of nodes. Our analysis shows considerable scalability variations between three blockchain networks. The results indicate that some blockchain networks can have over 800 ms network latency and some blockchain networks may use a bandwidth over 1600 Kbps. This work will contribute to developing efficient blockchain-based IoT sensor networks.
Ethical Challenges of Data Commingling in Business

Data commingling involves merging data from various sources into a shared infrastructure. However, this poses ethical challenges for businesses. This article delves into the ethical issues that arise from data commingling and its impact on organizations. It also provides recommendations for responsible data management. Real-world cases, such as LinkedIn's data handling, highlight the consequences of data commingling on customer trust and company credibility. To overcome these challenges, businesses should explore the creation of multi-cloud data lakes, offer employee training, and advocate for global regulations on data commingling.
«NOTRE-DAME DE PARIS» Aktualema as the Subject of Translingual Communication: Means and Methods of Explication in Network Texts

&lt;p&gt;&amp;laquo;NOTRE-DAME DE PARIS&amp;raquo; aktualema is reviewed in the article as an instance of translingual communication, the subject of which is worldwide, and not only national, heritage.&lt;/p&gt;
Is the «Inverted» Curriculum Solution or Problem?

&lt;p&gt;The article is devoted to the current problem of reforming higher education in connection with the abolition of the Bologna system. Some experts suggest the idea of an "inverted" plan, where the initial stages of training are devoted to practical disciplines, and theoretical ones are transferred to senior courses. However, this approach raises a number of objections, the most significant of which is that students will not be interested in continuing their studies at all. The authors propose certain measures for the transformation of educational programs, in particular, the modification of the topics of practical classes in theoretical disciplines, the formation of unified sets of mandatory competencies at different levels, the active use of project-based learning, and a change in teaching style. These measures will improve the quality of students' training.&lt;/p&gt;
Forecasting the Rating of a New Movie Based on its Metadata

&lt;p&gt;The article describes an approach to predicting the rating of a new film based on data known prior to its release, using classic machine learning models.&lt;/p&gt;
Development of Software to Test Transitivity of Fuzzy Relations

&lt;p&gt;The problem of fuzzy relation transitivity checking and transitive closure finding is considered in the paper. Solution algorithms are formulated and corresponding software is described. A logical scheme is given.&lt;/p&gt;
Scenario Approach when Conducting Practical Training in Information Technology

&lt;p&gt;The article describes an approach based on a formalized description of technological techniques for performing exercises in information technology courses. The language of description of such techniques is given, which makes it possible to organically fit technological features into the text of the exercise in natural language. Fragments of real scenarios of practical training in information technology are given.&lt;/p&gt;
Conceptual Foundations of the Formation of Linguistic Socialization Abroad

&lt;p&gt;The article provides an analysis of the conceptual foundations of the formation of linguistic socialization in the 20th century. Special attention is paid by the authors to the study of the pragmatics of the development of Elinor Ochs and Bambi Schieffelin, which became the basis for the emergence of linguistic socialization, exploring how children perceive and act out the &amp;laquo;context of the situation&amp;raquo; in relation to the &amp;laquo;context of culture&amp;raquo;. The authors described the existing relationships between linguistic socialization and language acquisition, linguistics and anthropology. It was revealed that linguistic socialization combines discursive and ethnographic methods that fix social structures and cultural interpretations of semiotic forms, practices that allow children to properly build interaction in society in the future. The authors conclude that studies devoted to the process of language acquisition prioritise the mother-child conversation as the object of study, while studies of language socialization extend it to the range of communicative partners &amp;mdash; adults and children &amp;mdash; with whom the child or other new community member typically interacts to some degree in socioculturally configured settings.&lt;/p&gt;
Countability of Material Existence: Discreteness, Continuity or Indivisibility

The article formulates the question about the countability of material existence, which is the key question for determining the structure of the universe. There are three answers to this question: material existence is count-able, unquantifiable or indivisible. The ontologically grounded and unambiguous definition of the concepts “division of matter” and “motion of matter” allows excluding the variants of unquantifiable and indivisible mate-rial existence. By analyzing the known laws of nature development (transition of quantitative changes into qualitative ones and negation of negation) it is evident that they correspond to the countable material being. Isomorphism phenomenon is considered, the existence of which serves as evidence of the ultimate complexity of material existence and, consequently, of its countability. It is stated that being is a totality of matter (in the form of primary particles) and emptiness possessing primary properties determining all the variety of forms and laws of the universe.
Calculation of the Complexity of Game Tests for the PLines System

&lt;p&gt;The paper proposes a method for calculating the complexity of game tests. Calculations are carried out for the PLines gaming system. Brief information about the PLines system is provided.&lt;/p&gt;
NeighborNet: improved algorithms and implementation

NeighborNet constructs phylogenetic networks to visualize distance data. It is a popular method used in a wide range of applications. While several studies have investigated its mathematical features, here we focus on computational aspects. The algorithm operates in three steps. We present a new simplified formulation of the first step, which aims at computing a circular ordering. We provide the first technical description of the second step, the estimation of split weights. We review the third step by constructing and drawing the network. Finally, we discuss how the networks might best be interpreted, review related approaches, and present some open questions.
Psychological and Pedagogical Methods of Working on the Mistakes of Younger Schoolchildren in the Development of Mathematical Concepts

&lt;p&gt;The article continues a series of publications devoted to the methodology being developed for the development of students&amp;rsquo; initial ideas to scientific concepts. The reasons for the mistakes made by younger schoolchildren when mastering mathematical concepts are considered. Examples of children&amp;rsquo;s mistakes are shown on the material of the topic &amp;ldquo;Subtraction&amp;rdquo;, their types are highlighted. The techniques of working on errors in the development of mathematical concepts are described. A method of organizing developmental assessment aimed at analyzing errors from the point of view of students&amp;rsquo; misconceptions behind them is presented in detail. The stages of collecting error data, determining their type and causes, and eliminating error patterns are highlighted. Attention is paid to errors associated with a lack of reading skills. Recommendations are given on the organization of quasi-research activities and polylogue in elementary school math lessons, their mutual relationship is revealed. There are deficiencies in the skills of primary school teachers to organize an educational discussion and work with children&amp;rsquo;s hypotheses. The example of the topic &amp;ldquo;Subtraction with a transition through a digit&amp;rdquo; shows a way to create a problem situation and use numerical models. The prospects for the organization of quasi-research and polylogue in this lesson are outlined.&lt;/p&gt;
FFeatures of the Preparation of Primary School Teachers for the Teaching of Literary Reading According to the System of Developmental Education

&lt;p&gt;The article considers peculiarities of preparation of bachelors, future teachers of primary school, to teaching literature according to the system of developing education. Reading attitudes of students were identified that interfere with the competent analysis of literary texts and the competent teaching of literature. This is the setting to read the &amp;ldquo;morality&amp;rdquo; of the work as a variant of the naive-realistic reader&amp;rsquo;s setting, the setting to find the only correct interpretation of the work, the absence of the set to read the author&amp;rsquo;s point of view, the low level of readiness for independent reflection on the motives and character of the book&amp;rsquo;s heroes. It was revealed that these attitudes complicate the understanding of epic texts to a greater extent, while the understanding of a lyrical work is at a higher level. The article discusses the forms of work within the framework of studying the methodology of primary literary education, primarily related to the formation of an attitude towards teaching literature as a subject of the aesthetic cycle.&lt;/p&gt;
F-E Fusion: A Fast Detection Method of Moving UAV Based on Frame and Event Flow

In recent years, the widespread application of UAVs has caused threats to public security and personal privacy. This paper presents a fast and low-cost method for UAV detection and tracking from fixed-position cameras. In our method, we capture event data and video frames through Dynamic Vision Sensor (DVS) and conventional camera respectively. We use the combination of Dynamic Neural Field (DNF) and clustering algorithm to locate the moving objects in the scene from the event data collected by DVS. Then we obtain high-resolution images from the corresponding regions of the video frame according to the calculated positions for classification. Compared with YOLO or R-CNN, our proposed method reduces the computational overhead by calculating the location of moving objects through event flow. Experimental results show that our method has more than 40 times faster recognition speed on the same platform than YOLO v3. The data and the code of the proposed method will be publicly available at https://github.com/Xiaoxun-NUDT/F-E-fusion.
Few-Shot Relational Triple Extraction Based on Evaluation of Token-Level Semantic Similarity

Relational Triple Extraction refers to extracting entities and classifying relation between different entities from text, which is a non-trivial step in the construction of knowledge graph. However, Traditional relational triple extraction methods require a large amount of labeled data, which is often not available due to the long-tail distribution of entity pairs and relations between entities, thus yielding limited performance of relational triple extraction. In order to address these problems, few-shot relational triple extraction aims at extracting relational triple from text using only few labeled samples. Previous works lack attention on the similarity of token-level information between the query set and support set. Therefore, we propose an evaluation method of Token-Level Similarity of entity tags (TLSM), which exploits the semantic similarity information between tokens in the few annotated samples and unseen samples to improve the accuracy of entity extraction, thereby improving the overall performance of relational triple extraction. In addition, in order to balance the optimization process of two subtasks, entity recognition and relation classification, which have different levels of difficulty, we utilize dynamically weighted balanced loss to enable the model to automatically learn the weight coefficients of the losses of two subtasks. Finally, extensive experiments are conducted on the FewRel dataset to demonstrate the effectiveness of our method.