Reviewerly/exHarmony huggingface dataset:
INFORMATION AND COMMUNICATION TECHNOLOGIES AS A TEACHER'S SELF-DEVELOPMENT TOOL

The article is devoted to the problem of self-development of a pedagogical employee of a general secondary education institution. An overview of the teacher's self-development model in the context of informal education, using information and communication technologies, was made. The analysis of various studies showed that ICT for educational activities has a significant impact and is a Russian lever in providing quality educational content. Mastery of basic principles, skills and abilities with the use of digital tools is currently a priority task for all institutions of general secondary education. Competence with ICT is currently the basis for self-development and self-organization of a teacher in the process of sustainable development of a specialist's personality. But having modern and practical skills in the use of ICT for a teacher is more necessary than a simple desire for improvement. The approach to teaching using ICT tools of teachers of different cycles can be implemented, taking into account the following confirmation: new approaches to teaching, increased flexibility; user orientation, greater autonomy for students; support and use of new technologies; strengthening network connections between institutions and partnerships between interested parties in the field of education (stakeholders); improved access allows those with fewer resources to only advance in knowledge. Separate components of the teacher's self-development: internal and external. The first group approves work on oneself, acceptance and manifestation of oneself in the world. The second is a balanced deep work with him, which is his own personality. The external components of a teacher's self-development include the following characteristics: environment, relationships, priorities, activities. external aspects that need development, the teacher should not look for internal ones that are the driving force in this process: self-knowledge, understanding, planning, implementation. An analysis of the results of the survey was made regarding the use and use by teachers of secondary schools of the Internet platform and resources before and after the introduction of quarantine restrictions
Better Incentives for Proof-of-Work

This work proposes a novel proof-of-work blockchain incentive scheme such that, barring exogenous motivations, following the protocol is guaranteed to be the optimal strategy for miners. Our blockchain takes the form of a directed acyclic graph, resulting in improvements with respect to throughput and speed. More importantly, for our blockchain to function, it is not expected that the miners conform to some presupposed protocol in the interest of the system’s operability. Instead, our system works if miners act selfishly, trying to get the maximum possible rewards, with no consideration for the overall health of the blockchain.
MOTIVATION FOR PROFESSIONAL SELF-DEVELOPMENT OF TEACHERS OF HIGHER EDUCATION INSTITUTIONS

The article is devoted to the theoretical justification of the motivation for professional self-development of teachers of higher education institutions and the generalization of the results of empirical research on the needs of self-development motivation. We define professional self-development as a conscious purposeful process of personal and professional self- improvement with the aim of creative self-realization while performing professional activities. However, we believe that teaching activity involves the dynamic involvement of both proficient and personal qualities and competences; therefore, the professional self-development of a teacher is aimed at self-cognition, self-affirmation, and self-improvement in all spheres of life. The process of professional self-development of teachers of higher education institutions requires a deeply realized value of its necessity, stable internal motivation, but it should be supplemented by external incentives in a creative educational environment, which was confirmed by empirical research. The conducted research has proved the need to make up practical recommendations for teachers regarding professional self-development, which can become the basis for further research.
An Internet-assisted Dixit-playing AI

This paper investigates the development of an Artificial Intelligence (AI) agent which plays the voting phase of the board game Dixit. Given a set of open cards and a lexical “hint” provided by a player, our algorithm aims to predict which card the hint originally refers to. The AI agent is developed using Machine Learning (ML) algorithms for Natural Language Processing (NLP). The AI agent is equipped with models that explore data of human-played games and retrieves information from the internet to deal with any shortage of information. We show that the Dixit AI agent we developed is more accurate than the average human player in finding the card which corresponds to a hint.
Beam Search: Faster and Monotonic

Beam search is a popular satisficing approach to heuristic search problems that allows one to trade increased computation time for lower solution cost by increasing the beam width parameter. We make two contributions to the study of beam search. First, we show how to make beam search monotonic; that is, we provide a new variant that guarantees nonincreasing solution cost as the beam width is increased. This makes setting the beam parameter much easier. Second, we show how using distance-to-go estimates can allow beam search to find better solutions more quickly in domains with non-uniform costs. Together, these results improve the practical effectiveness of beam search.
Anomaly Detection in Video Surveillance using SlowFast Resnet-50

Surveillance systems are widely used in malls, colleges, schools, shopping centers, airports, etc.This could be due to the increasing crime rate in daily life.It is a very tedious task to monitor and detect abnormal activities 24x7 from the surveillance system.So the detection of abnormal events from videos is a hugely demanding area of research.In this paper, the proposed framework is used for deep learning concepts.Here SlowFast Resnet50 has been used to extract and process the features.After that, the deep neural network has been applied to generate a class using the Softmax function.The proposed framework has been applied to the UCF-Crime dataset using Graphics Processing Unit (GPU).It includes 1900 videos with 13 classes.Our proposed algorithm is evaluated by accuracy.Our proposed algorithm works better than the existing algorithm.It achieves 47.8% more accuracy than state of art method and also achieves good accuracy compared to other approaches used for detecting abnormal activity on the UCF-Crime dataset.
Extensive use of hybrid-flexible modality (Hyflex) in Computer Science 2

Due to the pandemic, at Universidad ORT Urugua y, the Programming 2 course of the Systems Engineering, Electrical, Electronics, Telecommunications, and Systems Degree careers was taught in the 2nd semester of 2020 in online mode, with a pilot group with 37 students in hybrid-flexible format ("Hyflex"). In a previous study, this pilot course was compared with the face-to-face (used in 2019) and online (used in the 1st semester of 2020) modalities, with no differences detected in the approval results. In the 1st semester of 2021, due to the health situation, it was given only in an online format and in the 2nd. semester Hyflex was included for all students of the morning courses of 8/2021. In this work and, as a continuation of said previous work, the extensive use of the Hyflex format is reported and analyzed through its application in the seven morning groups, totaling 189 students. Strong emphasis was placed on teacher training, course coordination, and technical support. The approval results are similar to those of the pilot course, but the perception of the theoretical course and the acceptance of the Hyflex forma t wa s improved.
Design of the educational environment for the preparation of teachers

The notion of the educational environment, as well as its elements and structural characteristics, are examined in the article. The idea of designing an educational environment was presented. The technological, didactic, and social elements of the educational environment design for the Ternopil Volodymyr Hnatiuk National Pedagogical University (TNPU) teachers' professional training are outlined. The characteristics of this environment are taken into consideration, including information saturation and openness, digital change, social practices, and cooperation. On the basis of TNPU, a study on the efficiency of the educational environment for teachers' professional development was conducted. 432 master's degree holders from across the University's disciplines took part in the study overall. The study processed the results statistically using the approach of expert evaluations. The goal of the study was to evaluate the relative significance of each indicator for each element of the educational environment design. The study's findings show how the technological and social aspects of the university's learning environment have undergone major changes that have a big impact on teachers' professional development.
Trustless, Permissionless, Non-Custodial Stablecoins in Decentralized Autonomous Organizations (DAO)

The benefits offered by cryptocurrencies are a great many: transaction cost and speed, security and transparency, to name a few.Yet, there is also a major drawback represented by their extremely high volatility.Stablecoins offer an ideal solution since they preserve all the advantages of blockchain-based currencies, while reducing considerably the volatility issue.Currently, stablecoins are almost exclusively pegged to the US Dollar and secured by noncrypto assets held in account at custodial institutions.In this article, we present the design of a decentralized organization aimed at issuing stablecoins backed by crypto-assets stored on-chain and pegged to assets different from fiat money.Our model offers several advantages, in particular, it allows the issuance of stablecoins in a trustless, permission-less and non-custodial environment.
Analysis Problems of Low Skill English Speaking for Senior High School Students in Indonesia

Indonesian students learn to speak English from elementary school to university, but they still get lower skill in using English actively especially in speaking. It shows that there is serious problem of learning English in Indonesia. This research to elaborate the real problem of student in senior high school in learning English especially in speaking. Survey method is used in this study to find responses from students in Empat Lawang regency South Sumatera, Indonesia. After analysing data, the result of research can be presented as: the first, in the mind of students of senior high school English is difficult, not subtantive for their future and only formality subject. Secondly, students’ problem in learning especially speaking skill such as unconfident mentality, low motivation and lack of practice. So it can be concluded that problem of learning English for senior high school is from inner and outher class room. It recommended that teaching English in senior high school must be disigned as interesting and necessity based for students.
Decision-theoretic foundations for statistical causality: Response to Pearl

Abstract I thank Judea Pearl for his discussion of my paper and respond to the points he raises. In particular, his attachment to unaugmented directed acyclic graphs has led to a misapprehension of my own proposals. I also discuss the possibilities for developing a non-manipulative understanding of causality.
Underwater Path Planning of UUV Based on UDWA

Aiming at the path planning requirements of UUV to achieve the optimal global path and dynamic obstacle avoidance in real-time environment in underwater environment, the DWA algorithm used in traditional land robot path planning research is improved to meet the corresponding conditions of underwater environment. The influence of ocean current and weight factor is introduced to optimize the heuristic function, so as to improve the evaluation function in the traditional DWA(Dynamic Window Approach) algorithm and improve its search efficiency in a specific environment. Experiments show that in dynamic situations, the proposed UDWA(Underwater Dynamic Window Approach) algorithm can significantly improve the efficiency of UUVs underwater, flexibly avoid obstacles, and have excellent path planning effects.
FedGE: Break the scalability limitation of Graph Neural Network with Federated Graph Embedding

Neighborhood aggregation algorithms, represented as graph convolutional networks, have attained non-negligible success in numerous topological structure-based scenarios with the assumption that the topological structure of the given graph is pre-defined and relatively small. However, a real-world graph generally is a super large graph consisting of many small graphs that are interconnected and overlapping. Which makes graph embedding in real-life industries, by nature, fall into the federated learning scheme. While current graph-based algorithms are only able to capture the individual topology of each natural graph, learning the complete structural information of the merged large graph remains challenging due to the unsustainable computational cost of graph convolutional operations. We propose a tailored federated graph embedding framework to learn the intact structural information of the numerous inherently linked small-scale graphs and the embedding of each node. We leverage graphs with around two and a half million nodes to validate the effectiveness and the correctness of the proposed framework.
Segmentation of breast mammogram images using level set method

Breast cancer is recognized as one of the biggest current challenges impacting the lives of thousands of women around the world. An early diagnosis based on the study of mammogram is one of the most powerful methods to prevent this disease. Segmenting images or extracting object boundaries is one of the major computer vision and image processing issues. Active contours are used widely for segmentation as a high-level technology for boundary recognition. Chan-Vese was used as a method for segmenting i.e., geometric active contours. This method is particularly powerful when dealing with homogeneous images, Therefore, she has difficulty segmenting the mammogram images because It lacks contrast between the tumour and the surrounding breast tissue. Work was done to increase the contrast through pre-processing where he used CLAHE to improve the mammogram images and thus help Chan-Vese to define the tumour boundaries. The method was tested on the MIAS mini database, and the highest quantitative results were as follows (0.88, 0.94, 0.99, 0.98, 0.99) for Jaccard, Dice, PF-Score, Precision, and Sensitivity respectively.
Kesalahan Penggunaan EYD terhadap Paragraf Eksposisi

The purpose of this study is to analyze the use of EYD in the exposition paragraph. This type of research is qualitative research using descriptive methods. Based on the results of the study, the errors in using EYD for exposition paragraphs are grouped into three parts, namely capital letters, preposition and punctuation. Writing capital letters results in 279 cases of error, the use of prepositions of data results in 24 cases of errors, while the use of punctuation is further divided into the use of a period (.) And the use of a comma (,), the use of a period of data results in 26 cases of errors, while the use of commas obtained data results as many as 36 cases of errors. Thus it can be concluded that the misuse of EYD was caused by students' lack of understanding of the writing procedure according to the EYD system.&#x0D; Keywords: Exposition Text, EYD Usage Error
Towards Developing a Global Federated Learning Platform for IoT

Federated learning (FL) is an approach that enables collaborative machine learning (ML) without sharing data over the network. Internet of Things (IoT) and Industry 4.0 are promising areas for FL adoption. Nevertheless, there are several challenges to overcome before the deployment of FL methods in existing large-scale IoT environments. In this paper, we present one step further toward the adoption of FL systems for IoT. More specifically, we developed a prototype that enables distributed ML model deployment, federated task orchestration, and monitoring of system state and model performance. We tested the prototype on a network that contains multiple Raspberry Pi for a use case of modeling the states of conveyors in an airport.
Phonetics Instruction's Effect on Adult Learners and the Production of Second Language Sounds at Ignatius Ajuru University of Education

The influence of phonetics education on adult learners and the creation of second language sounds was examined at the Ignatius Ajuru University of Education. The study was guided by four research questions. A questionnaire on the influence of phonetics education on adult learners in the generation of English sounds was used in a qualitative study design. A total of 10,000 people were studied with a sample size of 200 people. To obtain responses from the respondents, random and purposive selection approaches were utilized. The data was analyzed using the mean and standard deviations. According to the research, adult second-language learners who learn phonetics improve their pronunciation of English sounds. Adult second-language learners who received phonetics training improved their intonation. After obtaining phonetics education, adult second language learners improve in the placing of emphasis on words. Phonetics teaching helped adults who were learning a new language improve their word pronunciation.
Implementasi Electronic Data Processing Untuk meningkatkan Efektifitas dan Efisiensi Pada Text Mining

Technological developments make the distribution of the amount of data more and more and continue to grow every day, these developments can be used to mine data which can later be processed into text/information needed for its use. Preprocessing is part of text mining where the process is divided into several stages, namely case folding, symbol removal, slangword conversion, stopword removal, stemming and tokenization. The news obtained is raw data from the xlm file from google alert which is then inputted into a system developed using the PHP programming language and mysql database. The data processing method in this research is Electronic Data Processing. The use of this system is expected to help the data preprocessing process where the process takes a long time, especially if a large sample of data is needed. The results of the study showed that a crawling process data processing information system for 20 data records only takes 0.0079004486401876 Mins and the data cleaning process or preprocessing for 88 data records only takes 0.012900729974111 Mins. In other words, data processing using the system is more effective and efficient for the next process.
Generalized Reference Kernel for One-class Classification

In this paper, we formulate a new generalized reference kernel hoping to improve the original base kernel using a set of reference vectors. Depending on the selected reference vectors, our formulation shows similarities to approximate kernels, random mappings, and Non-linear Projection Trick. Focusing on small-scale one-class classification, our analysis and experimental results show that the new formulation provides approaches to regularize, adjust the rank, and incorporate additional information into the kernel itself, leading to improved one-class classification accuracy.
The Benefits of Pre-Requirements Specification Traceability

Requirements traceability is the ability to trace requirements to other software engineering artifacts. Traceability can be classified as either pre- or post-requirements specifications (RS) traceability. Pre-RS traceability is the ability to trace between requirements and their origin. However, the benefits of pre-RS traceability are often not clear. In this article, we systematically lay out the benefits of pre-RS traceability. We present results from both a literature review and a qualitative survey of practitioners involved with documenting and utilizing such trace links. We find that the benefits strongly depend on the practitioners, their tasks, and the project environment. Awareness of these relationships supports a clearer understanding of the benefits of pre-RS traceability and thus motivates successful implementation of the required practices. The results of our research motivates the adoption of pre-RS traceability and present problem areas for future research.
GREIMAS'S ACTANTIAL MODEL IN THE HUNGER GAMES MOVIE

This article focuses on applying the two of the narrative syntax theories proposed by Algirdas Greimas to find the basic structures of fairy tales, namely the Narrative Quest Model and the Actantial Model, to analyze Hunger Games movie. As Greimas’ claims to have found theories which are applicable to all narrative structures, the writer is interested to see whether the two chosen theories are indeed applicable to scheme in the movie. The theories are not used to explore the theme or the message that underlies the story; instead it focuses mainly to find the basic structure of the narrative as trajectory and the schema or paradigmatic connection among the major elements in the story. The research uses descriptive qualitative approach in which the data are obtained through a series of thorough reading before the story is redacted into a summary. Afterwards, the summary is divided into smaller narrative units using the Narrative Quest Model and the major elements and characters of the story are selected based on their functions in Greimas’ Actantial Model.
Towards Improved Certification of Complex FinTech Systems – A Requirements-based Approach

Context: Financial Technology (FinTech) systems, especially those involving custody of digital assets such as cryptocurrencies, are quickly emerging as a new class of software systems with associated high risks. So far, incidents involving such systems have costed billions of dollars. Problem: Providing regulators and insurers with certification cannot simply rely on simple reports generated by auditors. Current practices require a more rigorous and systematic approach for capturing and communicating the design rationale in order to certify such systems. Method: The User Requirements Notation (URN) is used to model and analyze the requirements of a FinTech system and capture its design rationale. Then, the Systems Theoretic Process Analysis (STPA) method is applied to the URN model to evaluate system hazards and introduce safety constraints/requirements that aim to avoid bad situations from happening (e.g., loss of assets, private data, or reputation). The results augment the URN model and are conveyed to the stakeholders (especially regulators, auditors, and insurers) in the form of assurance cases. Results: Guidelines are now available to model the requirements of FinTech systems and produce assurance cases for certification. The guidelines are illustrated with a real digital asset custodian example. Conclusion: This work provides new requirements-based guidelines exploiting URN and STPA that can potentially facilitate the certification process of FinTech systems.