Reviewerly/exHarmony huggingface dataset:
Understanding and Applying Program Logic Models

<section class="page-section"><div id="i640" class="chapter"> <span id="page50" class="page-wrapper"><span style="display: none" class="pb">[Page 50]</span></span> <div class="head Chapter"> Understanding and ...</div></div></section>
Introduction

This chapter provides the basic guidelines and the publicly available tools to conduct semantic network analysis. The combination of content analysis and network analysis is relatively new, but given the importance of both it seems to be indispensable. In parallel to the attempts to classify the functions of language and the meanings of words, there were two crucial and inter-related developments in the field: the use of computers in research and the emergence of network analysis. Semantic network analysis is less expensive and time-consuming than manual coding with traditional codebooks or qualitative approaches. In the construction phase researchers pay close attention to the relationships between these elements as a whole network. Semantic network analysis is less instrumental to understand the tone and valence, cynical expressions, hidden contexts, premises and assumptions, and underlying meanings. The chapter also presents an overview on the key concepts discussed in this book.
Extracting Frequent (Closed) Seasonal Gradual Patterns Using Closed Itemset Mining

In this paper, we address the issue of mining seasonal gradual patterns, which consists in identifying attribute co-variations in the form "when X increases/decreases, Y in-creases/decreases", that seasonally appear in data ("X and Y co-increase from March to June in more than 75% of the observed years"). Such kind of patterns has recently emerged for analyzing the sequences of temporal data and some algorithms have been proposed to automatically extract these patterns from numerical data. However, mining seasonal gradual patterns remains very challenging as the task is more complex than extracting gradual patterns in a simple sequence. In fact, one can note that extracting gradual patterns frequently appearing over a precise period of time (season) amounts to extracting, for each season, the gradual patterns common to multiple sequences. From this observation, we propose an algorithm to extract seasonal gradual patterns from temporal data sequences which exploits closed frequent itemsets mining algorithms to perform a search season by season. Experimental results obtained on a real world dataset show that compared to state-of-the-art algorithms, our proposed algorithm is efficient and can extract the complete set of frequent (closed) seasonal gradual patterns from the sequences of temporal numerical data.
Book graphics in the creation of the plastic artist Liudmyla Kozhokar

The fine arts artist Liudmyla Kozhokar had professional studies in Ukraine: the Arts Studio in Kherson (1975–1978) and the Ukrainian Polygraphic Institute „I. Fyodorov” in Lvov (1978–1983). Since 1984, Liudmyla Kozhokar participates in fine art exhibitions in Chisinau and abroad. Since then, the artist has collaborated with various Moldovan publishing houses, combining publishing with teaching in the field of fine arts. Since 1999 Liudmyla Kozhokar is a full member of the UAP of the Republic of Moldova, and since 2001 – a member of the A.I.A.P. UNESCO, Paris, France. Liudmyla Kozhokar’s works are in the collections of the National Art Museum of Moldova and in private ones in Romania, the Republic of Moldova, France, USA, Iraq, Italy, Germany, Japan, England, etc. The graphic designer illustrated books of different kinds: ABC books, textbooks, children’s stories, encyclopedic literature, etc. Liudmyla Kozhokar perceives each graphic book separately, finding new plastic formulas and stylistic methods, delving into the text and studying it to the last sentence.
Special Education Teachers’ Perception of Virtual Reality Education Spaces in Special Schools

The purpose of this study was to identify the considerations for the potential for use of virtual reality(VR) education spaces in special schools. To this end, in-depth interviews were conducted with five special school teachers concerning the operation of their VR education space with an eye toward the positive aspects as well as things to be improved. The results showed that the VR spaces in special schools mainly focused on physical education and were also used for non-curricular activities. The VR space allowed for educational activities that were free from the constraints of the physical environment and had many advantages in terms of teaching and learning. However, due to the limitations of the VR program itself, various efforts were required to increase its future use in education. Based on these results, we discussed several considerations for future educational use of VR were discussed.
Management of COVID-19 in Brazil

Letter to the editor about the current situation of the COVID-19 pandemic in Brazil.Cartao ao editor sobre a situação atual da pandemia da COVID-19 no Brasil.
IMPLEMENTATION OF AN INNOVATIVE PROGRAM OF DIGITAL TRANSFORMATION OF STUDENT-CENTERED LEARNING

This article was carried out within the framework of the project of the Ministry of Education and Science of the Republic of Kazakhstan IRN AR88857119 "Transformation of student-centered training of a future teacher in a digital environment". The content of the article is presented in accordance with the requirements of the state project "Digital Teacher". The authors emphasize that the educational programs of the new generation contribute to improving the professional training of future teachers. The article reveals the essence of the psychological justification of the idea of a competence-based approach as a means of transforming student-centered learning and integrated experience of digital education in the country and abroad.
Disruptive Innovation: A valuable experience in the teaching and learning process of Artificial Intelligence

The pandemic caused by Covid-19 affected all educational levels throughout the world. Several countries established periods of confinement for their inhabitants, and this led many teachers to adapt their courses for virtual development. This adaptation reduced in many cases to generating a rapid and emergency response through the digitization of what designed for a face-to-face environment, for example, with classes through videoconferences, redesigning activities to solve in a virtual environment, and solving online questionnaires. However, this article presents the adaptation of a university curricular space, specially designed for virtuality. It's about the educational innovation carried out on the Artificial Intelligence subject, which designed to take advantage of the potential of web 3.0 tools and mitigate the inconveniences of non-face-to-face classes. The results obtained highlight the innovative academic value of this initiative, and its transferability and sustainability over time.
Book of Papers: XIV Simpósio Nacional de Sistemas Prediais [SISPRED 2021]

Book of Papers: XIV Simpósio Nacional de Sistemas Prediais [SISPRED 2021]
AI Diagnosis: Rise of AI-Powered Assessments in Modern Education Systems

The literature on the limitations on the current archaic education system is limitless, the consequences of which have only been exacerbated in the current lockdown scenario. The timed evaluations have not only failed as an assessment tool during these times but research has shown there are increased rates of using unfair means and proctoring as a result. Not only was the system faulty to begin with, it is failing miserably under current lockdown situations. Simultaneously the current literature keeps positing that since technology has become an integral part of our life already, it would not be long before technology integrates with education and assessments. Taking into consideration the need and potential of an integrative system, this paper aims to explore how artificial intelligence can be effectively introduced into education and improve learning outcomes. The paper performs a Comprehensive Literature Review (CLR), and analyses data based on the framework developed by Onwuegbuzie and Frels (2015). The paper thus reviews literature with the aim to explore current models of AIEd and relevant psychological concepts relating to learning and career outcomes.
CONTINUITY OF TEACHING AND LEARNING DURING THE COVID-19 MOVEMENT CONTROL ORDER THROUGH ONLINE: A RESOLUTION OF THE MINISTRY OF EDUCATION

The Covid-19 pandemic is an unexpected pandemic. It is not only faced by the Malaysian community, but also the presence of the world. The spread of this epidemic is very fast and difficult to block. Almost most of all countries in the world are affected by its presence so that various sectors experience its fuel including in the field of education. To curb the spread of Covid-19, the Malaysian government has declared a Movement Control Order (MCO) from 18 March 2020 until now with the recovery phase being carried out and closing all sector operations including the education sector. Thus, this study aims to look at the resolution taken by the Ministry of Education (KPM) to ensure the continuity of education of students throughout the Movement Control Order (MCO). This study focuses on the analysis of The Ministry of Education Malaysia's Letter of Release (KPM) No. 3 of 2020 which is the guidelines for the implementation of Teaching and Learning during movement control order due to the spread of Covid-19 infection dated March 27, 2020. To ensure the continuity of education for students, KPM encourages all teachers to use the learning methods through the learning platform provided by MOE-DL and the appropriate online learning platform with the help of Information Technology. Although normal methods of teaching and facilitation (PdPc) occur in the classroom, in dealing with this virus the PdPc method needs to be changed in line with the 21st Century Learning (PAK21). With the help of this study, parents, students, and teachers were able to realize KPM's desire to keep the knowledge from stalling due to the Covid-19 pandemic.
Role of Mobile Platforms in Learning and Teaching English Language - A Study

As we know English is the language of International communication, there is a dire need for learning English both as a student and a teacher.It's a fact that learning English language will allow one's to communicate effectively with the people around us.Since English is the language called an international link language, not only in India but also in abroad it has its own impact on people in making themselves professionally succeeded.Learning English improves one's communication and helps us become urbane in the society.An effective communication makes a person to become a good social being.At this juncture, while the pandemic is spreading the world there was no proper communication between the people.Thus there are lots of apps introduced to entice people interacting and communicating globally by enhancing English language skills.Thus the prime idea of this paper to make us aware of several apps whose can be improves our skills in learning English language.For example, BBC Learning English app, one of the most popular providers of English language teaching material which help students becomes impromptu speakers.
Energy-Efficient Routing for Performance and Network Lifetime Enhancement in Wireless Sensor Networks

Protection is one of the key factors to be considered in application development. Every application should follow some security mechanisms to be free from fraudulent users. One of the important criteria to ensure security is Access control. [4]The reliability and security of the cloud and user are assured and effectively guaranteed during its interaction in the cloud computing environment. But these traditional models were unable to determine the vulnerability and ambiguity created by these open conditions. So the main focus throughout the evolution of new access control methods is on creating a mutual trust relationship between both interaction parties. The paper proposes a mutual access control model which is trust-based (MTBAC). Trust relationships between both interaction bodies are secured by mutual trust mechanisms. This model takes both the cloud service node’s trustworthiness and user’s action trust into consideration.
Persepsi Kesiapan Mahasiswa Akuntansi dalam Menghadapi Tantangan di Era Revolusi Industri 4.0

This research examines the influence of accounting understanding, soft skills, information technology knowledge on the readiness of accountants in facing the challenges of the industrial revolution era 4.0. This study uses primary data in the form of questionnaires that contain statements related to research, data collection using purposive sampling techniques that are sampling with certain criteria. The sample in this study is the final semester students majoring in accounting of Bali State Polytechnic. The number of samples in this study was 137 samples. The questionnaire deployment data is statistically analyzed using the SPSS program with multiple linear regression methods, classical assumption tests, T and F tests, and coefficients of determination. The test results showed a significant positive influence between accounting understanding, soft skills, and information technology knowledge on readiness to face the challenges of the industrial revolution era 4.0.&#x0D; Keywords: Accounting Understanding; Soft skills; IT Comprehension; Industry 4.0.
Learning Automata with Hyperlink Features for Detecting Venomous Social Trolls on the Social Media Platform

Nowadays the widening of illegal activity in the social media, intelligent machinery to detect harmful web pages is required. URL analysis is the best method for detecting phishing and other assaults. Venomous internet robots create fraud posts and start the communication by impersonating a follower or generating several fraud social accounts that are used for venomous purposes. Furthermore, hostile internet robots use shortened harmful URLs in tweets to send queries from online social networking users to venomous servers. As a result, distinguishing harmful internet robots from legitimate users is one of the Twitter network's and instagram's utmost critical responsibilities. To identify harmful internet robots, hyperlink-based data (such as Hyperlink redirect, number of shared hyperlinks, and garbage material in URLs) takes small amount of duration to extract than social chart-based factors (which repeat on the social communication of peoples). A Learning Automata algorithm is used to find the real users of the social media network.
Application of AI Video Image Technology in Soft Ladder Strength Teaching and Training System

Ladder strength training is an important content of athletes’ daily training, is the focus of athletes’ teaching, and one of the more difficult techniques to master. Today’s soft ladder strength teaching training is mainly based on subjective judgments and experience-based traditional teaching methods. Teachers rely on subjective observations to guide, correct and objectively evaluate students’ technical movements. They cannot communicate teaching content to students intuitively, vividly and vividly. Exploring a set of practice methods suitable for enthusiasts of ladder strength training and teaching methods suitable for teachers is the research direction of ladder strength training workers. In this paper, 24 male students in a domestic university are used as the research entity, through the use of traditional decomposition teaching mode combined with AI video image technology, a comparative study with traditional teaching methods, and related experiments on 24 students. Experiments show that AI video image technology combined with traditional teaching mode is of great help to the improvement of students’ ladder strength training performance.
Digital access rights management in the information systems of e-libraries and digital archives

The author reviews the basic types of digital document content protection from unauthorized access and dissemination applied by publishers and book trading companies. The principles of digital rights management (DRM) while accessing digital documents. The author suggests that DRM systems are efficient to be applied to certain types and formats of digital documents in libraries and archives. He also reviews several commercial solutions for DRM-systems plied to the most popular PDF-format and substantiates the importance of DRM-systems standardization for digital document friendliness both for the users and rights holders disseminating digital publications. Existing and newly introduced international standards for DRM-systems are discussed. The typology of digital rights protection software as provided for by the standards is presented along with regulated DRM-system features based on data coding. Readium project by international non-profit Readium Foundation exemplifies standard approach to DRM-system design. The project goal is to develop software modules to integrate standard DRM-technology into computer information systems including ALIS.
Kalibrasi Model Soil Moisture Accounting dengan Software HEC-HMS di Stasiun Debit Pasir Pangaraian

This research aims to compare the results of the calibration of the Soil Moisture Accounting (SMA) model using Percent Error in Volume (PEV) and Peak Weighted Root Mean Square Error (RMSE). The SMA model calibration uses the HEC-HMS (Hydrologic Engineering Center – Hydrologic Modeling System). There are 12 calibrated parameters by automatic calibration. The input data are the area of ​​the watershed, daily rainfall, daily discharge data and climatological data. The data used is data from 2008 to 2017. The results show that PEV performance shows good results. While the RMSE showed poor results. PEV results are best at 7 years of calibration and 3 years of verification. The length of the calibration data has not affected the verification results.
Action Research on the Implementation of Student-Generated Questions Online Classroom Design

For the success of online classes, more active student participation and engagement are required than face-to-face classes. This study conducted four repeated action studies to explore the conditions for supporting students to generate and develop their own questions in an online classroom situation. Students read the textbook before class and asked questions on the online question board. The instructor adjusted the content of the class by reflecting on the students’ list of questions. The students’ Q&A board questioning activities were conducted in the following order: “Student Question-Teacher Answer,” “Student 1 Question - Student 1 Answer,” “Student 1 Question - Student 2 Answer,” and “Writing a Self-reflection Journal.” A total of two or more different perspectives on one''s question helped develop the question. Meaningful education was provided when one took responsibility and reflected on the development process of one''s own questions. Reflecting this, a student-generated question online classroom design was proposed. For the student-generated question online classes to be successful, the instructor''s meticulous class design and interaction strategy are needed to generate, maintain, and develop student questions.
A Systematic Survey on Multi-document Text Summarization

Automatic text summarization is a technique of generating short and accurate summary of a longer text document. Text summarization can be classified based on the number of input documents (single document and multi-document summarization) and based on the characteristics of the summary generated (extractive and abstractive summarization). Multi-document summarization is an automatic process of creating relevant, informative and concise summary from a cluster of related documents. This paper does a detailed survey on the existing literature on the various approaches for text summarization. Few of the most popular approaches such as graph based, cluster based and deep learning-based summarization techniques are discussed here along with the evaluation metrics, which can provide an insight to the future researchers.
ICT Infrastructure for the Uptake of One Laptop Per Child Project in Homa Bay County, Kenya

The study was investigating the status of ICT infrastructure in preparation for the launch of Digital Literacy Programme (DLP) in public primary schools in Homa Bay County.Mixed approach research design was adopted.A total of 845 public primary schools were eligible for study.In addition, 845 public primary school head teachers and 6529 teachers were also targeted for interviews.The study randomly picked 85 schools, 6 head teachers and 12 primary school teachers for the study across the six sub counties of Homa Bay.The major findings showed that the general ICT infrastructure was low; however, majority of schools had computer laptop safes (79.9%), electric power (74.8%) and power sockets (90.0%) in readiness for DLP.The study concluded that ICT infrastructures were inequitably distributed in Homa Bay County and a lot was still needed to be done for the DLP rollout to be a success.It was recommended that the government through its line ministries of ICT and energy to improve on both electric power and internet supply to make the project a reality.
PREDICT AND DIAGNOSE CARDIOVASCULAR HEALTHCARE ILLNESSES BASED ON RADIOACTIVITY WITH MACHINE LEARNING MODELS

An Internet of Things (IoT)-based Healthcare program to track and detect serious illnesses is being created to provide better service to the user utilizing online health services.In this work, an effective system for predicting heart illness is developed using the UCI repository data and also healthcare devices due to radioactivity.In addition, classification methods are applied to categorize patient records to detect cardiovascular problems.The classification would be developed utilizing information from the testing set during the training period.During the development stage, individual patients system can track whether or not illness exists.Reference data is used for testing, and a variety of classifications, including J48, Logistic Regression (LR), Multilayer Perception (MLP), and Support Vector Machine (SVM), are used.According to the modeling, the J48 classifications outperform other classifications in terms of effectiveness, clarity; remember F-score, and kappa values.
Adaptive Semi-automatic Robot Control by Tongue in a Remote Setting for Individuals with Tetraplegia

Individuals with tetraplegia are severely limited in terms of independence, which can lead to depression and premature death. The field of robotics has sought to create solutions for increased independence by enabling individuals with tetraplegia to perform physical activities. This includes semiautomatic solutions. The use case of an assistive robotic manipulator (ARM) and thus increased independence could be expanded by allowing remote control, e.g. when the user is lying in bed. This study presents and evaluates semi-autonomous intraoral tongue-based control of a seven degree of freedom ARM/gripper in a near and remote setting. The system consists of a tongue control interface (iTongue), a semi-automatic framework based on YOLOv5 and adaptive levels of automation, an Intel Realsense D435i camera and a JACO robotic manipulator. Two study participants completed ten rounds of controlling the JACO ARM to reach and pick up a soda bottle and pour from it in a cup. The semi-automation improved the grasping performance for both of the study participants, particularly when controlling in a remote setting, decreasing the cognitive load and the overall task completion time. The presented system has the potential to increase the independence and quality of life for individuals with tetraplegia, by enabling the user to perform physical activities even when lying in bed. Future work should include expanding the semi-automation to other activities of daily living and evaluating the system in a greater population and by individuals with tetraplegia.