Reviewerly/exHarmony huggingface dataset:
Peran Orangtua Terhadap Hasil Belajar Kognitif Siswa Kelas III SDN Sumur Peteuy Baros Tahun Ajaran 2019/2020

Abstract. This research is motivated by the findings of problems obtained from parents' complaints about student learning outcomes at school, because it is difficult for parents to guide their children to study at home since the Covid 19 outbreak in Indonesia. In addition, it is difficult for children to be asked to learn by their parents and to do assignments from the teacher who are sent through social media. Apart from that lack of parental knowledge. The purpose of this study was to determine the role of parents on student cognitive learning outcomes, to determine student cognitive learning outcomes, the relationship between parental roles and cognitive learning outcomes of third grade students at SDN Sumur Peteuy Baros for the 2019/2020 academic year. The method used in this research is correlation. Types and sources of data used are quantitative data, while data sources used are primary and secondary data. Data collection techniques are using questionnaires and documentation. The conclusion in this study is that it shows that rcount is greater than rtable (0.633> 0.312) so that H1 is accepted, this means that there is a positive and significant relationship between the role of parents on the cognitive learning outcomes of third grade students of SDN Sumur Peteuy, Baros District. In the interpretation the relationship is included in the high category at the interval 0.60-0.799.Keywords: The Role Of Parents, Cognitive Learning outcomes
Research Guides: Using Primo: The Library Discovery Search Tool: Sign In

Learn how to use the features of Primo, including how to SEARCH EVERYTHING - books, e-books, journal or newspaper articles, how to borrow print materials from the UFindNJ network of academic libraries, and how to access and manage your library account.
Deep geothermal-induced seismicity: controlling factors and hazard mitigation measures

&amp;lt;p&amp;gt;As many industrial activities impacting the underground, deep geothermal projects can be associated with the occurrence of induced seismic events. This seismicity is sometimes a direct consequence of stimulation operations needed to enhance the permeability of geothermal reservoirs, but, in other cases, it can also occur in different phases of geothermal projects, as during wells shut-in, after injection operations, or during the production phase, which generally implies lower flow rates and injection pressures. The intensity of this seismicity, in terms of magnitudes of seismic events, can be extremely variable, from microseismic events (M &amp;lt; 2), not felt at the surface, to large earthquakes (M &amp;gt; 5) that pose a serious risk to neighboring populations and may lead to the abandon of geothermal projects. In this context, it is of paramount importance to: i) better characterize and understand the interactions between natural and anthropogenic factors which may lead to geothermal-induced seismicity and ii) evaluate currently applied approaches to handle and minimize associated risks.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The objective of this work is to establish a state of the art about deep geothermal-induced seismicity, by describing factors that have a bearing on the generation of seismic events, as well as by discussing existing means to handle their occurrence. Based on a worldwide review of geothermal projects, we created a large database describing each selected case study in terms of geological properties and tectonic setting, operational parameters and type of geothermal systems, as well as spatio-temporal characteristics of the observed induced seismicity. Collected data are analyzed in order to better understand possible cause-effect relationships between induced seismicity and geothermal operations with the aim of identifying the most important preexisting and anthropogenic factors, as well as their interactions, which may have a key role on the occurrence of seismic activity. &amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;lt;/p&amp;gt;
Ecologías de aprendizaje de los docentes universitarios de Ingeniería y Arquitectura

This research focuses on analysing the Learning Ecologies of university professors of Engineering and Architecture. This study was carried out through the mixed method. To develop the qualitative phase, the case study was used as a methodological strategy. Through purposive sampling, we selected the five best professors of Engineering and Architecture of Universidade da Coruna. The in-depth interview was chosen as the data collection technique. The content analysis carried out allowed us to identify the dimensions and elements that make up the ecologies of these professors. This finding made possible the design of the questionnaire used in the quantitative phase. In this second phase, a non-experimental correlational design was used. Through convenience sampling, we selected a sample of 353 Spanish university professors. Three motivational profiles were identified by latent class analysis. The results of the analysis of variance seem to corroborate that motivation influences the activities carried out, the resources used and the interactions established. In this way, it is concluded that there is a relationship between the two dimensions of the identified ecologies.
Emotion Ratings: How Intensity, Annotation Confidence and Agreements are Entangled.

When humans judge the affective content of texts, they also implicitly assess the correctness of such judgment, that is, their confidence. We hypothesize that people’s (in)confidence that they performed well in an annotation task leads to (dis)agreements among each other. If this is true, confidence may serve as a diagnostic tool for systematic differences in annotations. To probe our assumption, we conduct a study on a subset of the Corpus of Contemporary American English, in which we ask raters to distinguish neutral sentences from emotion-bearing ones, while scoring the confidence of their answers. Confidence turns out to approximate inter-annotator disagreements. Further, we find that confidence is correlated to emotion intensity: perceiving stronger affect in text prompts annotators to more certain classification performances. This insight is relevant for modelling studies of intensity, as it opens the question wether automatic regressors or classifiers actually predict intensity, or rather human’s self-perceived confidence.
Knowledge Graph Construction for Electric Power Science and Technology Achievements

The management of power technology requires great effort and cost due to its wide coverage and complex data types. However, under the current technical background of deepening informatization degree, negative effects such as large information redundancy and ambiguous information makes it facing greater challenges. Based on this, this paper proposes to realize the effective management of electric power science and technology information by means of knowledge graph. We use the data of electric power science and technology achievements from 2005 to 2018 to build the knowledge graph through the knowledge graph building platform, so as to provide effective management methods for the management of electric power sci-tech achievements
Customized Wheelchair Navigation System

In India, the amount of disabled persons is growing per annum. For persons with disability, special developed aids for mobility are helpful for moving and a substitute for walking particularly within the inside and outside environment also. Wheelchairs and stretchers are generally employed medical equipment for hauling. Especially when a sick person has to shift between beds and wheel chairs, the aiding person will suffers lot due to over-weight, larger height, etc. Realizing the wide-ranging problems within the moving gears and establishing a new design is going to be a benefit for the medical industry for persons with disability. The requirement for a wheelchair based stretcher to help the persons with disability to move and also to supply novel gear to be used within the hospitals and houses. The numbers of persons with disability are rising by various sorts of mishaps are monitored. With subsequent studies, the benefit of requirement for wheelchair associated stretcher was permitted for the Indian hospitals. The currently employed wheelchair based stretcher isn't sufficient to satisfy the patients or old age peoples requirement. Hence, we prefer a stretcher which could be operated with the help of electric current and also capable of transforming itself between a wheel chair to stretcher and vise-versa.
이슬람과 국내 언론의 시각: 2011-2019년을 중심으로

Media portraits social frames of opinions on social matters. This paper presents quantitative text-mining based analysis of Korean news agencies ''Islam and Muslims perspectives'' from 2011 to 2019. As a method, the author applied machine learning based on unsupervised learning with the media contents. For reproductivity of the research, this paper used R and London School of Economics (LSE)''s social sciences text mining package Qanteda. The analysis conducted with topic analysis with Latent Dirichlet Allocation (LDA) and Co-occurrence network analysis. Based on the above method, research was able to find Korean media interests in the Islamic world. The author found that the Korean media portrayed Arab spring, ISIS, and halal, Islam related issues on South Asia.
Class Imbalance Applied to Medical Neuroimaging for Classification of Alzheimer’s Disease

Class imbalance is an issue that naturally occurs when a database is sparse or incomplete.This can occur in medical diagnostics when a large percentage of tests ran to return negative results rather than a positive.Classification models are sensitive to an imbalanced training set, and training on one can cause undesirable biases.This work presents an overview of the effects of class imbalance on classification models in Alzheimer's detection utilizing voxel based-morphometry (VBM).MRI scans are processed by FreeSurfer where cerebral volumetric and thickness are taken as feature vectors.The effcts of class imbalances on multiple machine learning models were compared to one another.Furthermore, different biomarkers were studied for their effect on different metrics of trained models.The classification models were trained to detect the following categories: Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal controls (NC).SVM, KNN, MLP, Random Forest, etc. algorithms were evaluated for the prediction analysis.It was observed that class imbalance did not produce any significant effects on the disease classification process.
Modern trends in the development of the sectoral system of international scientific and educational cooperation

The Yearbook contains articles of a general theoretical, historical and applied nature concerning Russian education and science.The activities of world-class scientific and educational centers and the sectoral system of international scientific and educational cooperation, various problems of Russian educational organizations, including those related to their optimization, trends in socialization and professional orientation of young people are covered.A number of articles are devoted to international education and training of foreign students in Russia, the use and study of the Russian language in schools and universities of foreign countries.The Yearbook is written for employees of Russian educational and scientific organizations, students and graduate students of sociological and pedagogical faculties, as well as to anyone interested in trends in the development of domestic and international education and science.
ПЕДАГОГИЧЕСКАЯ ПРОФИЛАКТИКА ЯЗЫКОВОЙ ИННОВАЦИОННОЙ ДЕЯТЕЛЬНОСТИ

In recent years, scientific and technological innovation has rapidly penetrated the educational space in the course of reforms in our education system. However, regardless of whether it is open or secretive or passive or active intentional or without intent, various psychological barriers impede innovative changes in the psychological barriers that manifest themselves in the innovative pedagogical process and the problem of overcoming them.
Russian Paraphrasers: Paraphrase with Transformers

This paper studies the generation methods for paraphrasing in the Russian language. There are several transformer-based models (Russian and multilingual) trained on a collected corpus of paraphrases. We compare different models, contrast the quality of paraphrases using different ranking methods and apply paraphrasing methods in the context of augmentation procedure for different tasks. The contributions of the work are the combined paraphrasing dataset, fine-tuned generated models for Russian paraphrasing task and additionally the open source tool for simple usage of the paraphrasers.
PMA LibGuides: Image Guide: Free Image Sources

A guide to finding and using images in the museum collections and elsewhere. Tips for finding free images on web.
Automatic Detection of Stellate Lesions in Digital Mammograms Using Multi-scale SIFT

This paper presents a novel automatic mammography recognition approach used to develop computer-aided diagnostic systems that require a robust method to assist the radiologist in identifying and recognizing speculations from a multitude of lines corresponding to the normal fibrous breast tissue. Following this rationale, this paper introduces a novel approach for detecting the speculated lesions in digital mammograms based on multi-scale SIFT (scale-invariant feature transform) orientations. The proposed method starts by estimating a set of key points that best represent the image mammography in a scale space. We then benefit from SIFT algorithm to locally characterize each key point by assigning a consistent orientation. Thereafter, a set of three features are extracted for each pixel in the image mammogram based on these orientations. The extracted features are fed into BDT (binary decision tree) in order to perform per pixel classification and decide whether the pixel is normal or abnormal. We evaluate the proposed system on BCDR (breast cancer digital repository) database and the experimental results show that our method is accurate with 97.95% recognition rate, while it is robust to illumination changes, rotation and scale variations.
What does BERT Learn from Arabic Machine Reading Comprehension Datasets

In machine reading comprehension tasks, a model must extract an answer from the available context given a question and a passage. Recently, transformer-based pre-trained language models have achieved state-of-the-art performance in several natural language processing tasks. However, it is unclear whether such performance reflects true language understanding. In this paper, we propose adversarial examples to probe an Arabic pre-trained language model (AraBERT), leading to a significant performance drop over four Arabic machine reading comprehension datasets. We present a layer-wise analysis for the transformer’s hidden states to offer insights into how AraBERT reasons to derive an answer. The experiments indicate that AraBERT relies on superficial cues and keyword matching rather than text understanding. Furthermore, hidden state visualization demonstrates that prediction errors can be recognized from vector representations in earlier layers.
Regulating Initial Coin Offerings and Cryptocurrencies: A Comparison of Different Approaches in Nine Jurisdictions Worldwide

Initial Coin Offerings (ICOs) and cryptocurrencies are applications of blockchain technology that offer many benefits. ICOs are increasingly used by companies for crowdfunding, allowing start- ups to find investors. Cryptocurrencies allow cheap, fast and straightforward international money transfers. However, along with such benefits also come risks, like volatility of cryptocurrency rates, abuse by (cyber)criminals, and other risks and uncertainties for investors. Governments across the globe are struggling with the question whether and how to regulate cryptocurrencies and ICOs. The technologies and applications are similar in different jurisdictions, but the responses of legislators, regulators and supervisory authorities widely differ. In this article, we investigate the regulatory responses to cryptocurrencies and ICOs in nine jurisdictions worldwide. The aim of investigating different approaches towards regulating cryptocurrencies and ICOs is to identify different approaches, to make a comparison between jurisdictions, and to identify potential good or best practices. The nine jurisdictions that are compared in this paper are Australia, Belgium, China, Estonia, Japan, Switzerland, The Netherlands, the United States, and the European Union.It is concluded that all the jurisdictions investigated do have legislation that is applicable to ICOs and cryptocurrencies. However, big differences exist in the extent to which the legislation applies and is regulated by the national supervising authorities. Generally speaking, most legislation of the investigated jurisdictions consists of financial markets legislation (including that of securities), anti-money laundering legislation, and consumer law. The approaches of the countries investigated differ from a negative, forbidding approach (such as in China, which has launched an ICO-ban and is obstructing trade in cryptocurrencies) to a positive and facilitating approach (such as in Australia and Switzerland, where the aim is to promote innovation). Although this paper does not assess which method of regulation of ICOs and cryptocurrencies can ultimately be qualified as best strategy, we conclude that a positive and facilitating approach offers more opportunities for investors and innovative companies. However, this approach requires a clear and detailed legislative and regulatory framework for all parties involved in the establishment, issuing, storing or trading of cryptocurrencies and ICOs. Such a framework should at least provide boundaries with regard to money laundering and other common forms of cybercrime. Moreover, it should provide some sort of consumer/investor protection and clarity when it comes to tax liability. A legislative and regulatory framework that provides all these aspects will prevent abuse and may enable governments to intervene when issues occur.
Historieta para la prevención de enfermedad por coronavirus (COVID-19) en la infancia. Una experiencia de investigación online

Introduction: Since 2019 the faces the COVID-19 disease, which, due to its transmissibility and damage to the human body, became the pandemic of 2020. The socioeconomic effects are registered in most of the planet. From the individual point of view, it also affects psychologically, especially the elderly and children. Objective: to design a cartoon aimed to the child population for the prevention of COVID-19 disease. Method: a qualitative, participatory, art-based research was carried out in online mode, using the WhatsApp Messenger application. Based on the Knowledge Translation Model of Straus, Tetroe and Graham. 21 infants (9 girls and 12 boys) between the ages of 6 to 14 years participated. The work sessions were held in their homes with the collaboration of their families. Results: Cartoon titled Learning about the virus that paralyzed the world which, based on the drawings made by the participants, was structured into three components: children's curiosity, knowledge transmitted by the basic health team and basic messages for the prevention of COVID- 19. Conclusions : the use of social networks, with the participation of infants and families for the construction of knowledge in special circumstances of pandemic such as social isolation, were essential for the development of an educational technology based on artistic expressions that also allowed the transfer of information to a vulnerable population, such as children.
Decision Making for Acceptance of Physics Teachers with the Fuzzy TOPSIS Method

Abstract Teachers are the most important human resource in educating students. At SMP Negeri 3 Palembang there is still a great need for teaching staff, namely professional physics teachers. The professional physics teachers selected are those who really have good potential in educating. Teacher selection has not been represented quantitatively so that it is still based on subjective views and thoughts. This study aims to provide a quantitative employee selection decision-making technique through the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Data obtained through interviews with teachers and HRD to get the weight of the criteria at each stage and implemented in teacher candidates. The results obtained were teacher candidate rankings for each stage of selection, so that the teacher was declared to have passed to the next stage or did not pass and could not continue to the next stage. The value with the lowest ranking and does not meet the special criteria will result in the candidate not passing. From the research results, the use of the fuzzy method can make it easier in subjective assessment, and the TOPSIS fuzzy calculation until the final stage results in 3 passing candidates. Keywords —Teacher Selection Decision Making, Fuzzy TOPSIS, Knockout System in Selection Stages
DarkJargon.net: A Platform for Understanding Underground Conversation with Latent Meaning

An essential part of underground conversation are dark jargon terms. They are benign-looking, but have hidden, sometimes sinister meanings and are used by participants of underground forums for illicit behavior. For example, the dark term "rat" is often used in lieu of "Remote Access Trojan". We present a novel online platform that caters to the understating of underground conversation with latent meaning. Our system enables researchers, law enforcement agents and "white-hat" hackers to gain invaluable insights into underground communication by providing them with a tool to (1) look-up dark jargon terms in a dictionary; (2) explore the usage of dark jargon over time and interpret their meaning; (3) collaborate and contribute their own research findings. Furthermore, we introduce a novel dark jargon interpretation method that leverages masked language modeling of a transformer-based architecture.
Galveston College Library: Distance Education & Online Resources: Find Web Resources

This guide is designed to help online students locate and use the GC Library's online resources.
REKOMENDASI PENINGKATAN KEMATANGAN SISTEM INTERAKSI PEMBELAJARAN DI FASILKOM UNIVERSITAS ESA UNGGUL

eLearning offers many opportunities for improving university’s learning process. However, it isnecessary to understand the maturity of university’s interaction system to assure this technology will notworsen the interaction between the system entities. This research aims to measure the learninginteraction system maturity of Faculty of Computer Science Universitas Esa Unggul (Fasilkom) andpropose recommendations for improving its maturity level. We modify the eLearning Maturity Model(eMM) in accordance with the characteristic of Fasilkom learning environment to get more genericmodel of learning system, with or without the technology. The result shows there are two main aspectsthat need to be improved at Fasilkom UEU learning system: (a) Academic Organization andManagement, and (b) Curriculum and Learning Content Planning and Development.