Reviewerly/exHarmony huggingface dataset:
A Comparison of Security Analysis Methods for Smart Contracts Built on the Ethereum Blockchain

Blockchain technology is one of the superior technologies of recent times. It is a decentralized distributed ledger to record transactions in an immutable way. Smart contracts are digital contracts, i.e., an auto executable small piece of code, written to be deployed on the blockchain. Ethereum is a mostly used blockchain platform for writing and deploying the smart contract. The immutability feature of blockchain poses threats to smart contracts because if a smart contract is uploaded on the blockchain, it becomes immutable. The EVM design and solidity programming language pose some security issues, which should be analyzed properly. So smart contracts must be analyzed for vulnerabilities before deployment. Several smart contracts security analysis approaches are proposed in the literature based on symbolic execution, taint analysis, formal verification, rule-based pattern detection, etc. A comparative study of the above techniques is performed in this paper, which will help the researchers select an efficient method to analyze the Ethereum smart contracts and pave the way for future research directions.
STRUCTURAL AND FUNCTIONAL ANALYSIS OF THE LEARNING ACTIVITY OF MODERN HIGH SCHOOL STUDENTS

The article examines the structural and functional organisation of educational activities of modern high school students. The sample is represented by students of a secondary general education school (form 11) aged 16–17. The work was aimed at analysing the relationship between the components of the structure of educational activity of 11th-form students studying in 2014 and 2023, as well as determining the functional significance of each component in the structure of educational activity of 11th-form students studying in 2014 and 2023.
USE OF ASPECTS OF ECONOMIC ACTIVITY IN TEACHING ECONOMIC DISCIPLINES TO UNIVERSITY STUDENTS OF NON-ECONOMIC SPECIALTIES (BASED ON TEACHING A CONCEPT)

The article is devoted to teaching of economic disciplines to students of noneconomic specialties. Using the example of teaching an economic concept, the sequence of going through aspects of economic activity and possible options for constructing tasks based on them are shown. The proposed methodology may be of interest to teachers of non-core economic disciplines in universities.
AXIOLOGY OF ACADEMIC LEADERSHIP IN ENGINEERING EDUCATION OF THE “PRIORITY 2030” PROGRAMME OF THE BRIDGE BUILDING SPECIALISATION

The system of improving domestic engineering education is the most important condition that determines the technological sovereignty and security of the state. The changes carried out in higher technical school over the past decades have shown that management models implemented from the outside on the national basis, as a rule, do not take into account the objective essential relationships of the education system with the state’s goal setting for technological development. The State Programme “Priority 2030” launched in 2021, aimed at the synergy of goal-setting in achieving academic leadership, creates these mechanisms. The analysis of the programme’s intermediate stages shows that the methodology for its implementation requires refinement in terms of mechanisms that take into account the values and traditions of engineering schools. The article is devoted to the systematisation of practical experience and the development of methods in the context of the comparative axiological analysis of the trajectories of achieving the academic leadership “Priority 2030”.
THE TYPOLOGY OF TASKS OF THE ALL-RUSSIAN SOCIAL SCIENCE OLYMPIAD FOR SCHOOLCHILDREN BASED ON THE REQUIRED CRITICAL THINKING SKILLS

This article presents the typology of assignments of the All-Russian Social Science Olympiad for schoolchildren. The sample includes the tasks for the graduating classes, which were used at the regional and final stages of the Olympiad from 2009 to 2021. The analysis of task types was based on the skills described in the expert consensus report on critical thinking (The Delphi Report). The results of the analysis showed the importance of using critical thinking skills at different stages of the Olympiad. In conclusion, the author of the article presents a new type – a “logical and statistical” task – and its distinctive characteristics. It is argued that this typology of tasks and its connection with the skills of critical thinking emphasises the importance of developing critical thinking in preparation © Кахраман Гокмен, 2023 152 Научное мнение № 7–8 (2023) for the olympiads. This in turn will develop methods for designing tasks and more effective work with them in the future. Keywords: school olympiads, critical thinking, social sciences, gifted children, typology of tasks, argumentation skills
The universalism of rock art: an appeal to the fundamental principles of culture

The cultural comprehension rock art monuments are of gains special relevance. Due to the need to evaluate this cultural text in the context of the changed socio-cultural peculiarities of life. In rock paintings depicted the oldest strata of human consciousness, which influence to the culture of the nations, historically divided by time and space, and that indicates on generally anthropological quality of archaic art. In terms of methodology, the rock art is considered based on the principle of unity of the world historical process and the existence of a common universal core of human nature. With the help of image is designated by invisible and not perceived supernatural world of spirits, totemic ancestors, gods and other creatures. The contemporary complicating situation in the world forces us to look for answers to the most significant problems of life, turning, among other things, to the fundamental to the fundamentals culture: universalism, archaic and traditional syncretism, nature-centrism.
The Activities of Russian Libraries in the Dissemination of Scientific Knowledge

The issue of spreading scientific knowledge is relevant at the present stage of development of society. The library, as the most accessible cultural institution, is able to ensure the dissemination of this knowledge in all social strata of the population. The purpose of the article is to study the intensity and forms of events of scientific, popular science and educational content of federal, republican, regional and regional Russian libraries, reflected on official websites. The article deals with information about the popular scientific activities of the leading Russian libraries. The ongoing projects and mass events of scientific, popular science and educational content are described. Content analysis has become the main method of collecting information. The study was performed at the end of 2022 and the beginning of 2023. The site analysis showed that libraries, as cultural institutions, hold a sufficient number of various mass events in the form of lectures, master classes, intellectual games, quizzes, but the scientific or popular science content of these events is not always confirmed. Basing on two stages of the study the following conclusions were made: science promotion activities were present in an average of 33 % of the libraries surveyed. The most popular form of such events was a lecture with the participation of a guest lecturer. Most of the activities were aimed at young people.
Meritokracija: zgodba o regulativni ideji našega časa

In the initial chapters of the present book, we analyzed the social conditions that significantly contributed to the emergence and rise of meritocracy as the dominant rationality. We have argued that over the last three centuries it has reshaped, shifted the values of, and, in general, significantly determined the way the world and the lives of individuals in Western societies have been perceived. At the same time, we have argued that its position in society has been sustained by politicians, teachers, parents, and other members of the public. We have attributed the success of the basic idea of meritocracy—rewarding the individual according to his or her abilities and efforts—in large part to the way it fits within the twin pillars of democracy and the market economy. Democracy relies on, and to a large extent enables, freedom and equal formal opportunities for all; the rise of wage labor and market mechanisms, on the other hand, requires the harnessing of all possible national and global potentials of “human capital.” We have thematized Young’s innovative criterion for evaluating meritocracy using the formula “effort + IQ brings merit” (1958) and argued that the two key elements in the formula did not come about by chance.
Using Bayesian Ridge Algorithm to Predict Effectiveness of Body Fat Measurement

Body fat is an important aspect in understanding and managing one's physical condition. Accurate measurement of body fat percentage is essential to help accurately plan future health plans. Currently, the method of measuring body fat is still traditional and quite difficult, so what is needed is a more effective method. The Bayesian Ridge Algorithm is a linear regression technique that uses Bayesian inference to estimate the parameters of the model. In this study, it was used to predict the effectiveness of measuring body fat, which is a method often used to evaluate a person's overall health and physical condition. This algorithm takes into account factors such as age, gender, and body mass index (BMI) to make predictions about a person's body fat percentage. The results from this study can be used to improve the accuracy of body fat measurement and help individuals better understand and manage their health. The results of this study indicate that the model has very high accuracy (more than 99%).
Policy Suggestions through Social Perception Analysis of Defense YouTube Channels

YouTube is a platform that delivers video content on diverse topics and enables communication, making it the most utilized service for conveying knowledge and exchanging information. The Korean Army is also proactively operating official Defense YouTube channels related to the military and producing videos to promote a positive perception and instill faith in the military among the general public and soldiers. However, there is a lack of research on the current status of the content and societal perceptions of defense-related channels. To understand societal awareness, we qualitatively analyzed video content and comments. In addition, we used big data analysis methods such as keyword derivation, term frequency analysis, word cloud visualization, word association analysis, and sentiment analysis of comments based on a Korean sentiment dictionary. These analyses identify current defense channel strategies and society's awareness of these strategies and provide a foundation for improving and perfecting future video creation and operation processes.
Understanding Deep Learning for LoS prediction via Latent space visualization

&lt;p&gt;Continuous monitoring and prediction of Length of Stay (LoS) for critically ill patients admitted to Intensive Care Units (ICU) can help anticipate on their needs, thereby reducing risks of adverse events occurring, efficiently allocate resources and improve care. In this work, four different sequence-to-sequence deep learning models (Long-Short Term Memory, Gated Recurrent Units, Temporal Convolution Network and the Transformer network) were implemented to predict hourly remaining LoS, using 271 input features extracted from 20,489 ICU stays. Input sequences for model training were created using two approaches: (i) by stacking data one hour at a time and (ii) by using a sliding window of length $l$ shifted one hour at a time. To enhance model explainability, both the models’ latent space visualization and feature importance ranking were used. Compared against baseline models, the sequential models reported the best performance, reducing the prediction error by almost 3 days. Moreover, the sliding window approach showed improvement both in terms of performance and training time whilst requiring less resources. The latent space visualization of each model using t-SNE revealed that, with only 6 hours of data, the models are able to learn early clinical patterns that separate short ($0&lt;\text{LoS}\leq3$ days) from medium ($3&lt;\text{LoS}&lt;7$ days) and long ($7\leq\text{LoS}&lt;+\infty$ days) stays, and, the models are able to capture existing correlations between long LoS and risk of mortality, the latter not used during modeling. The benefit of this approach in a true hospital setting, besides LoS prediction, is that early clustering enables the early identification of long stays with shown existing risk of death, to whom prompt allocation of focus and adequate resources can be delivered.&lt;/p&gt;
A blockchain‐based user authorization management method for information exchanging of federation of industry and commerce

Abstract The blockchain does not need the central organization to make trust endorsement, which is suitable for large scale information exchange between different regions. In addition, blockchain has the characteristics of decentralization and tamper resistant, so that it no longer needs an intermediary platform. A blockchain‐based user authorization management method is proposed, which applies blockchain as an underlaying security mechanism for distributed user authorization management within a trusted community of a distributed information exchange sites of federation of industry and commerce. This method can ensure the reliability, consistency, and integrity of user authorization information. With this method, an elastic data exchange trusted community can be built between the data owner and the authorized data user according to the data exchange needs to achieve reliable distributed access authorization.
MARS: An Augmented Reality-Based Marine Chart Display System

The visualization system of nautical charts enhances the safety navigation on sea, particularly in critical areas. Nowadays nautical chart visualization technology considers the benefit of inventive information technology to produce three-dimensional and real-time models which can be easily used. Therefore, this study attempted to develop an Android-based application with Augmented Reality (AR) approach. A digitation of the conventional nautical chart was performed to build a digital nautical chart. This process implemented regulation from United States (US) Chart No. 1 and International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA) Maritime Buoyage System. There are two substantial results of this research: Marine Augmented Reality System (MARS) to display a nautical chart in a three-dimensional form, and Marine Augmented Reality System GPS (MARSGPS) which focuses on integrating the model with its vicinity environment. This brings users to better acknowledge the situation of their environment. The usability test of these products shows that the overall feasibility value is 83.71%. The coordinate accuracy of MARSGPS application has a Root Mean Square Error (RMSE) value of 4.30m, which can be improved through a ground-truth measurement. Nevertheless, this approach provides an essential reference for future research on a three-dimensional nautical chart visualization.
Integrated Framework for Virtual Tours and 3D Visualization of Cultural Tourism in Pattani, Thailand Based on WebGIS Platform

This paper presents a framework for developing a lightweight WebGIS platform as a web map service for publishing and servicing cultural tourism information. The archaeological sites, history, and cultural arts in Pattani Province were used as case studies in this article. It incorporates various digital technologies to create digital archives in providing web-based information services, including geospatial databases, virtual tours and virtual reality, 3D models, and online cultural maps for tourism. The framework describes the necessary infrastructure based on open-source code that is specially developed and provides libraries with free software interoperability, which can be considered as a real-time data management facility and simple completion. It is a relatively low-cost but a reasonably efficient system that is very useful and suitable for local authorities and small organizations with budget constraints to be able to implement practical cultural heritage management for a digital tourism experience that can be displayed on computer equipment, smartphones, and VR headgear efficiently. Furthermore, it also offers a conceptual framework in disclosing future research directions.
An Empirical Study of Higher Vocational College Students’ Learning Motivation on Academic Achievement in Anhui Province, China

This empirical study aims to examine the relationship between learning motivation and academic achievement among higher vocational college students in Anhui Province, China. Anhui Province has a significant population of higher vocational college students, and understanding the factors that influence their learning motivation and its impact on academic achievement is crucial for educational institutions in the region. The study utilizes a quantitative research design, employing surveys and academic performance data to collect relevant information. Participants consist of higher vocational college students from various disciplines and academic backgrounds in Anhui Province. Statistical analyses, including correlation and regression analysis, are conducted to explore the relationship between learning motivation and academic achievement. The study's findings will provide valuable insights for educators and policymakers in Anhui Province to enhance students' learning motivation and improve academic outcomes.
Real-Time Rainfall Prediction in Kathmandu, Kapan Area using Sensor Data with Machine Learning and Linear Regression

The rainfall in the Kapan area is one of the most challenging aspects due to flooding in many parts of the area. The rainfall in the area of Milanchowk, Kapan, Nepal is one of the most challenging aspects that all the researchers, engineers, and geologists are trying to figure out. The research work is simply forecasting the weather and predicting it using machine learning techniques. The data from nearly half a month is collected in real time using sensor data through raspberry pi computer, and then the data is cleaned and processed for linear regression model-based precipitation. The work is carried out with a case study of the area, with appropriate steps taken to monitor in real-time and process the data accordingly.
TEACHING STUDENT’S WRITING SKILL BY USING COLLABORATIVE WRITING STRATEGY IN DESCRIPTIVE TEXT AT NINTH GRADERS OF SMP PLUS DARUSSALAM BLOKAGUNG IN ACADEMIC YEAR 2021/2022

In learning English, writing is one of the important skills that must be learned for students in junior high school. One good strategy that can be used by teachers in English classrooms is the collaborative writing strategy. Collaborative writing strategy is one good strategy to express their ideas and be applied in written form. The research problem is: 1). How is using collaborative is using collaborative writing strategy in descriptive text. 2). what the advantages and disadvantages using collaborative writing strategy in descriptive text. The objectives of this study are: (1) to describe the implementation of the collaborative writing strategy in writing. (2) To find out the advantages and disadvantages for students when the teacher applies the collaborative writing strategy in teaching writing descriptive texts. This study uses a qualitative method that uses descriptive qualitative to analyze data. This research was conducted at ninth graders and ninth grade English teacher SMP Plus Darussalam Blokagung. The findings in this study using collaborative writing in teaching descriptive text have some advantages and disadvantages for students and teachers in teaching descriptive text. First, this strategy can improve writing skills. Secondly, students can easily write descriptive texts in their own words. Third, increase students' feelings and motivation. Also the disadvantages is first, the teacher cannot distinguish between students working on assignments individually or in groups. Second, it is difficult for teachers to know the abilities of each student. Third, it cannot be used with a large number of students.
A Study on the Current Situation and Optimization Path of Junior English Majors' English Writing

English writing, as an important output of English learning, fully reflects the comprehensive ability of English learners. In this study, 227 junior English majors in Guangdong University of Science and Technology were studied on their English writing by means of questionnaires, interviews and writing tests. The study finds that the English writing level of junior English majors is relatively low, with problems such as lack of vocabulary expression, weak grammar knowledge and shortage of discourse construction ability and writing strategies. Meanwhile, students are insufficiently engaged in learning English writing, neglect the importance of English writing, have less interest in writing, and are dissatisfied with English writing in classroom teaching. In view of these, this study analyzes the causes of English writing problems among junior English majors, and then proposes ways to optimize the English writing level at three levels: students, teachers and schools, in order to improve students' English writing level and overall language application ability.
Vision-Text Cross-Modal Fusion for Accurate Video Captioning

In this paper, we introduce a novel end-to-end multimodal video captioning framework based on cross-modal fusion of visual and textual data. The proposed approach integrates a modality-attention module, which captures the visual-textual inter-model relationships using cross-correlation. Further, we integrate temporal attention into the features obtained from a 3D CNN to learn the contextual information in the video using task-oriented training. In addition, we incorporate an auxiliary task that employs a contrastive loss function to enhance the model’s generalization capability and foster a deeper understanding of the inter-modal relationships and underlying semantics. The task involves comparing the multimodal representation of the video-transcript with the caption representation, facilitating improved performance and knowledge transfer within the model. Finally, a transformer architecture is used to effectively capture and encode the interdependencies between the text and video information using attention mechanisms. During the decoding phase, the transformer allows the model to attend to relevant elements in the encoded features, effectively capturing long-range dependencies and ultimately generating semantically meaningful captions. The experimental evaluation, carried out on the MSRVTT benchmark, validates the proposed methodology, which achieves BLEU4, ROUGE, and METEOR scores of 0.4408, 0.6291 and 0.3082, respectively. When compared to the state-of-the-art methods, the proposed approach shows superior performance, with gains in performance ranging from 1.21% to 1.52% across the three metrics considered.