Reviewerly/exHarmony huggingface dataset:
DEVELOPMENT OF COMIC LEARNING MEDIA OF SOCIAL ARITHMETICS MATERIAL BY HIGHER ORDER THINKING SKILLS ORIENTED

This research was motivated by the lack of comic learning media on social arithmetic material in schools. This study aims to develop comic learning media in HOTS oriented social arithmetic materials for junior high school / MTs students. This research is included in research and development using the ADDIE development model, which consists of five stages: analysis, design, development, implementation, and evaluation. The research subjects were material experts, media experts, State Junior High School (SMP Negeri) 4 Sewon, and Muhammadiyah Junior High School (SMP Muhammadiyah) Sewon in Bantul regency. Data collection techniques used in this study are interviews used before product development. The research instrument used was interview guidelines to assess comic learning media that had been developed. Data analysis techniques use quantitative data analysis, converted into qualitative data with a Likert scale. Based on the results of the feasibility study of the product which was developed based on the calculation of the average score of the media expert obtained by 4.32 with very good criteria, from the expert material obtained at 4.29 with very good criteria, from the response of students in the small class test obtained at 4.38 with very good criteria, and from the students' responses to the trial of large class products obtained by 4.01 with good criteria. Based on these assessments, the mathematical comic learning media developed in social arithmetic is appropriate for the learning process.
Learning from class-imbalanced data: overlap-driven resampling for imbalanced data classification.

Classification of imbalanced datasets has attracted substantial research interest over the past years. This is because imbalanced datasets are common in several domains such as health, finance and security, but learning algorithms are generally not designed to handle them. Many existing solutions focus mainly on the class distribution problem. However, a number of reports showed that class overlap had a higher negative impact on the learning process than class imbalance. This thesis thoroughly explores the impact of class overlap on the learning algorithm and demonstrates how elimination of class overlap can effectively improve the classification of imbalanced datasets. Novel undersampling approaches were developed with the main objective of enhancing the presence of minority class instances in the overlapping region. This is achieved by identifying and removing majority class instances potentially residing in such a region. Seven methods under the two different approaches were designed for the task. Extensive experiments were carried out to evaluate the methods on simulated and well-known real-world datasets. Results showed that substantial improvement in the classification accuracy of the minority class was obtained with favourable trade-offs with the majority class accuracy. Moreover, successful application of the methods in predictive diagnostics of diseases with imbalanced records is presented. These novel overlap-based approaches have several advantages over other common resampling methods. First, the undersampling amount is independent of class imbalance and proportional to the degree of overlap. This could effectively address the problem of class overlap while reducing the effect of class imbalance. Second, information loss is minimised as instance elimination is contained within the problematic region. Third, adaptive parameters enable the methods to be generalised across different problems. It is also worth pointing out that these methods provide different trade-offs, which offer more alternatives to real-world users in selecting the best fit solution to the problem.
Using Class Activations to Investigate Semantic Segmentation

Semantic segmentation is one of the most popular tasks in computer vision. Its applications span from medical image analysis to self driving cars and beyond. For a given image, in semantic segmentation, we generate masks of image segments corresponding to each type or class. However, these segmented maps may either segment a region properly but assign it to a different class or they may have a possibly poor segmented region identification. Hence there is a need to visualize the regions of importance in an image for a given class. Class Activation Maps (CAMs) are popularly used in the classification task to understand the correlation of a class and the regions in an image that correspond to it. We propose a new framework to model the semantic segmentation task as an end to end classification task. This can be used with any deep learning based segmentation network. Using this, we visualize the gradient based CAMs (GradCAM) for the task of semantic segmentation. We also validate our results by using sanity checks for saliency maps and correlate them to those found for the classification task.
Desarrollo de un Sistema de información para Evaluación de la Confiabilidad de Cuestionarios mediante el coeficiente de Cronbach

In the study of different qualitative researches, evaluation questionnaires are used, these questionnaires have to be validated in their reliability, the present work presents the development of an information system that evaluates the reliability coefficient; using the Cronbach Coefficient formula, which allows estimating the reliability of a measurement instrument through a set of items, with Likert values from 1 to 5, where reliability is better the closer the value of alpha 1.0 is. . The methodology used for the development of the system is Scrum, it is an agile methodology where partial and regular deliveries of the final product are made, prioritized by the benefit that they contribute to the recipient of the project. Therefore, Scrum is especially suitable for projects in complex environments, where you need to get results soon, where requirements are changing or poorly defined, where innovation, competitiveness, flexibility and productivity are fundamental. The development of this evaluation system allowed evaluating 7 questionnaires applied to students of UTSJR, in the use of virtual platforms for software engineering subjects, it is worth mentioning that questionnaires or surveys can be evaluated to evaluate reliability in qualitative research projects.
O protagonismo do Arquivo Nacional na configuração da Arquivologia no Brasil (1838-1991)

The National Archives was created as the Empire Public Archives in 1838 as a result of Regulation No.2, of January 2, in compliance with the 1824 Constitution. Since then, it has been and has activelypursued and developed various facets of the Archival Science in Brazil. This article aims to present thehistorical epistemological path of Archival Science in Brazil by the work and the protagonism of theNational Archives between 1838 to 1991. It is a descripti ve and qualitative study carried out throughbibliographic research that was organized and analized by five points (foreign researchers visits ;associations of archivists; A rchival Science manuals; paper and conferences and; archivists educationand courses ). As a result of the analyzes, it is noted that the National Archives carries out a myriad ofsine qua non facets which help Archival Science out in its maturation in Brazil.
Collector and Philatelic Press in the RSFSR/USSR during the First Half of the 1920s: From Pluralism to Monopolism

Periodicals is a “mirror” of society. On the one hand, they reflect the social and cultural climate of a particular historical epoch. On the other one, retain the memory of the past times. Magazines and newspapers can influence the public opinion and provide feedback in the management of society through the prism of ideology and propaganda, thereby serving the interests of the state. This paper considers collector periodicals of the Soviet Russia in the first half of the 1920s. During this period, all printed materials were either private or state-owned. The publishing development and the editorial attitudes in the collector periodicals of that time were determined by the Soviet reality and reflected it. For this reason, the Soviet collector periodicals, including philatelic magazines, serve as an invaluable source of evidence of the growing pressure produced by the party policies in propaganda, agitation, and publishing industry. A number of periodicals that received little support from the state were unable to engage in any pro-active resistance. In the early 1920s, the number of collector periodicals rocketed. By the end of 1922–first half of 1923, the dialog between them finally turned into a monologue of one edition promoting the positions of the state. As a result, the privately owned collector magazines disappeared. The remaining magazine turned out to perform mostly ideological and educational functions. Therefore, the general tasks and problems of collecting, in particular the philatelic ones, were replaced by the vital economic problems making the collector periodicals a tool used for bringing up an ideal Soviet person.
LibGuides: Remote Learning Resources: Faculty Resources

Online learning resources for students and teachers. Online learning resources for faculty, teacher, and staff
LibGuides: Licensing Agreements for Electronic Materials in Libraries: Reports

This LibGuide provides an overview of the many issues surrounding licensing agreements in public and academic libraries, both from a Canadian perspective and from other jurisdictions.
Using Graph and Transformer Embeddings for Vector Based Retrieval in Scopus

For the longest time, term-based vector representations based on whole-document statistics, such as TF-IDF, have been the staple of efficient and effective information retrieval. The popularity of Deep Learning over the past decade has resulted in the development of many interesting embedding schemes. Like term-based vector representations, these embeddings depend on structure implicit in language and user behavior. Unlike them, they leverage the distributional hypothesis, which states that the meaning of a word is determined by the context in which it appears. These embeddings have been found to better encode the semantics of the word, compared to term-based representations. Despite this, it has only recently become practical to use embeddings in Information Retrieval at scale. In this presentation, we will describe how we applied two new embedding schemes to the subset of documents available in Scopus and the CORD-19 dataset. Both schemes are based on the distributional hypothesis but come from very different backgrounds. The first embedding is a graph embedding called node2vec, that encodes papers using citation relationships between them as specified by their authors. The second embedding leverages Transformers, a recent innovation in the area of Deep Learning, that are essentially language models trained on large bodies of text. These two embeddings exploit the signal implicit in these data sources and produce semantically rich user and content-based vector representations respectively. We evaluate search results from these embedding schemes against judgement lists from the TREC-COVID competition. Finally, we will describe how RELX staff can access these embeddings for their own data science needs, independent of the search application.
Teaching Vocabulary by Using English Kid Songs for the 3rd Grade Students of Linguistic Class Program (LCP) at MI Muhammadiyah 1 Pare – Kediri

English cannot be separated from vocabulary learning, because it is a very important aspect in language skills in addition to aspects of speaking, listening and writing. In this case, the vocabulary is not only used for communication it can also improve English skills such as writing, speaking and listening skills. Lacking vocabulary is the reason why English is difficult to master. The students have been studying English for long time with the several methods, but they do not have an adequate vocabulary in English. Descriptive qualitative method is used by the researcher as research design. This research is intended to find out the descriptive outcome of the collected data and the interpretation of which as the conclusion to know how the curriculum, syllabus and implementation of teaching. The response of students toward the teaching of vocabulary process was consist of three terms, they are students' difficulties, students' perception on teaching learning process, and the advantages which can be taken by following this class. The first was about students' difficulties, students had the problem in pronouncing and memorizing the vocabulary. The second was about their perception in teaching learning process. Generally the students enjoy this program because the teacher always asks the students to sing a song together. The students really like learning while singing a song. Even though they had some problems in the class; they liked this program because it gave them advantage to prepare themselves to build their vocabulary. By following this program, it increased their knowledge about vocabulary.Key word: Teaching Vocabulary, English Kid's Song.
CT and the Readiness of the Education in Jakarta to Face VUCA Due to the Covid-19 Pandemic.

Abstract Jakarta as the capital city is viewed as the barometer of every city in Indonesia. The city preparedness to face VUCA (Volatility, Uncertainty, Complexity and Ambiguity) caused by Covid-19 pandemic is also in the national spotlight. One of the main solutions to face VUCA is Computational Thinking (CT). CT provides the ability to approach VUCA characteristics by systematically ingraining abstraction, algorithmic thinking, decomposition, and pattern recognition in mind. For this reason, Jakarta plans to disseminate this concept to students as early as possible, namely by embedding CT to every subject in primary and secondary schools. The activity began with online CT socialization, which was attended by 1,761 teachers, of which 238 via Google Meet and 1,523 via live streaming. In this activity we also distributed questionnaires to 258 elementary and junior high school teachers spread across 41 sub-districts of 44 sub-districts in Jakarta. The result is that 93.8% of teachers in Jakarta do not understand CT, excitingly 69.4% of teachers wish to teach CT in the subjects they can afford even though it is not compulsory, but if it is obligatory then all teachers will implement it.
From Text to Scheme: Problems in Identifying Arguments from Expert Opinion

We show how to solve common problems in identifying arguments from expert opinion, illustrated by five examples selected from The Economist. Our method started by intuitively identifying many appeals to alleged experts in The Economist and comparing them to the argumentation scheme for argument from expert opinion. This approach led us to (i) extending the existing list of possible faults committed when arguments from expert opinion are performed and (ii) proposing the extension of the list of linguistic cues that would allow analysts to identify arguments from expert opinion. Our ultimate aim is to help argument identification by argument mining connect better with techniques of argument analysis and evaluation.
Identifying the factors affecting the innovation capacity of Iranian ICT firms

The purpose of this study was to identify innovation capacity in Information and communication technology-based firms. In this descriptive and analytical study, the research method was quantitative-qualitative, which was performed in two parts. The first part was done qualitatively through a literature review and interviews with nine policy makers, experts, and managers of companies in the field of information and communication technology. In the second part, the model obtained from the previous stage was surveyed by distributing a questionnaire among 275 companies active in this field to assess the validity of the proposed model. In this research, the most important organizational factors affecting innovation capacity were collaboration and communication, resources of the idea, individual factors, organizational culture, strategies and technology management, knowledge management and organizational learning, and allocation of resources to innovation. In addition, the environmental factors affecting the innovation capacity were respectively institutional support, macroeconomic factors, and the firm location. The innovation outcomes, market outcomes, financial outcomes, and human outcomes were also the most important indicators of innovation capacity measurement. Additionally, environmental factors in promoting the innovation capacity of ICT firms were more important than organizational factors. The reason for this significance seems to be the high impacts of economic growth, stability, competitiveness, and government support for innovation on ICT NTBFs.
Interactive Visualization for Fostering Trust in AI (Dagstuhl Seminar 20382)

Artificial intelligence (AI), and in particular machine learning algorithms, are of increasing importance in many application areas but interpretability and understandability as well as responsibility, accountability, and fairness of the algorithms' results, all crucial for increasing the humans' trust into the systems, are still largely missing. Big industrial players, including Google, Microsoft, and Apple, have become aware of this gap and recently published their own guidelines for the use of AI in order to promote fairness, trust, interpretability, and other goals. Interactive visualization is one of the technologies that may help to increase trust in AI systems. During the seminar, we discussed the requirements for trustworthy AI systems as well as the technological possibilities provided by interactive visualizations to increase human trust in AI.
Implementation of portable mini wind power generator as renewable energy simulation media

Abstract This study aims to implement the portable mini wind power generator as simulation media, Indonesia as a country with two-thirds of its territory is the ocean, crowning the Indonesian nation as the world’s maritime axis. To face these challenges, the balance of technology and natural resources (oceans) is the responsibility of all Indonesian citizens, especially in the field of education which has a role to create and foster human resources. Vocational High Schools take an important role in creating skilled and competent students in their fields. The design functions to design the design of the system to be made, to sort out the functions and usefulness of the tool, as well as the components used so that there are no difficulties in making the system to be built. After the design is continued, the process of making and assembling tools. In the research implementation of Portable Mini Generator Wind Power as a simulation medium for alternative renewable electrical energy by making portable mini wind generator. Based on data from measurement and analysis results, it can be concluded that the working principle of portable mini wind power generators is to use wind as a mini generator drive, which in turn will result in a change in mechanical energy source motion into a renewable electrical energy source.
MOTIVASI DAN KECERDASAN EMOSIONAL DAN IMPLIKASINYA DALAM PEMBELAJARAN

Intelligence gives the biggest influence on a child's learning progress. It is needed a certain intelligence in order to be success including intellectual intelligence (IQ). But, the intellectual intelligence can not guarantee the success of someone's life. Daniel Goleman, the professor at Harvard University, in his book about Emotional Intelligence, explains that there are other factors determine the success of someone, one of them is emotional intelligence. Emotional intelligence is a number of capabilities and skills related to the development of social relations with the environment refer to the ability to recognize the self and others, the ability to motivate oneself, and the ability to control emotions and in relationships with others. Emotional intelligence has the biggest role in determining the success of someone's life, especially when they are still in the process of formal education shown by the success of learning achievement. Positive emotions can accelerate the learning process and achieve better learning outcomes. Therefore, the successful learning must begin by creating positive emotions in students themselves. To create positive emotions on students themselves can be done in various ways, such as by creating a fun learning environment and excitement of learning.
PERANCANGAN TATA KELOLA MANAJEMEN DAN LAYANAN PERPUSTAKAAN BERDASARKAN METODE KUALITATIF

In this study, the authors used a qualitative method in which there were no calculations that required going directly to the location, simply by looking for references and several journals that were used as a basis. Then this method is motivated by library management governance, developing book collections, supporting and inhibiting factors, and increasing reading interest. Then also in terms of human resources, if not managed properly, these natural resources will decline compared to other resources. So both librarians and visitors and human resources (HR) must support each other in improving library management. That is why the quality level of human consciousness is important because school libraries and university libraries are an integral part of supporting the educational process. With the synergy of intellectual quality and rationality, there is no degradation of education, elements that must be fulfilled such as service, quality, abilities, and good attitudes from librarians and visitors, and the existence of library management functions with the fulfillment of Human Resources (HR) and collections that meet library standards based on Law No. 43 of 2007.
ImputeRNN: Imputing Missing Values in Electronic Medical Records

Electronic Medical Records (EMRs), which record visits of patients to the hospital, are the main resources for medical data analysis. However, plenty of missing values in EMRs limit the model capability for various researches in healthcare. Recently, many imputation methods have been proposed to address this challenging problem, but they fail to take medical bias into account. Medical bias is a ubiquitous phenomenon that the missingness of medical data is missing not at random because doctors prone to measure features related to the disease of patients. It reflects the physical conditions of patients, which helps impute missing data with accurate and practical values. In this paper, we propose a novel joint recurrent neural network (RNN) model called ImputeRNN, which considers medical bias for EMR imputation. We model the medical bias by an additional RNN based on a mask (missing or not) matrix, whose hidden vectors are incorporated into the model as contexts by a fusion layer. Extensive experiments on two real-world EMR datasets demonstrate that ImputeRNN outperforms state-of-the-art methods on imputation and downstream prediction tasks.