Reviewerly/exHarmony huggingface dataset:
디지털 과학 교과서 읽기 과정에서 나타나는 초등학교 4학년 학생들의 안구운동 분석 - ‘식물의 생활’ 단원을 중심으로 -

The purpose of this study is to analyze the reading processes of students who are in elementary school 4th grade, learning science digital textbook based on eye movement. The participants were divided into upper and lower group based on result of pre and post-test. The students confirmed their understanding of the tasks after they completed all the tasks, they have performed on preliminary and four main tasks. The task performance of eye movements were observed by mobil eye-tracker and the collected data based on participants'' observation time, eye fixation frequency and gaze movement. The main results are as follows. First, Students pay more attention to digital contents than to fixed contents in digital textbooks. It means when students get interested by manipulating themselves with digital contents and learn new information when they read digital textbooks. Second, upper group students can have better attention regardless of the type of learning contents and they also learn to link information with meaning. However, lower group students have less focus on fixed text and highly interactive contents. It means, even a digital contents with mixture of text, voice, and illustrations shows lower attention when they spend lots of time to learn. Lastly, upper group students tended to watch the illustrations and title of it, that shows when students read digital textbooks, they handling language and visual information with a complementary attitude. However, lower group students focused on specific visual information among the elements of digital textbooks and switch over their eyes into other subjects.
RELATO DE CASO: ABORDAGEM DO PACIENTE DPOC E SUAS COMORBIDADES

Objective: to report the case of a patient with chronic obstructive pulmonary disease, diabetes mellitus, heart failure, psoriasis, hypertension and obesity. Method: the information was written by reviewing the medical record, interviewing the patient and reviewing the literature. Final considerations: the case reported and the publications raised bring to light the discussion of the patient's lifestyle and nursing care, given the complexity of chronic obstructive pulmonary disease, in addition to its association with other comorbidities that directly affect quality individual's life span.
LibGuides: Remote Library Services for Online Learning: Multimedia

This guide offers links and answers questions for the online learning shift taking place in response to the COVID-19 outbreak.
Adversarial Learning on the Latent Space for Diverse Dialog Generation

Generating relevant responses in a dialog is challenging, and requires not only proper modeling of context in the conversation but also being able to generate fluent sentences during inference. In this paper, we propose a two-step framework based on generative adversarial nets for generating conditioned responses. Our model first learns a meaningful representation of sentences by autoencoding and then learns to map an input query to the response representation, which is in turn decoded as a response sentence. Both quantitative and qualitative evaluations show that our model generates more fluent, relevant, and diverse responses than existing state-of-the-art methods.
Аспектный анализ данных систематизации документного фонда библиотек и научный ландшафт

The paper discusses the method of aspect analysis of classification indexes of the document collection of libraries. The method allows you to establish links between the Sciences and information flows between them, which determines the landscape of scientific knowledge. The object of analysis is a set of composite classification indexes containing pointers to relevant areas of knowledge as aspects. The proposed approach can be used in scientometric research.
Expanding Search-Based Software Modularization to Enterprise-Level Projects: A Case Study at Adyen

Code quality of software products often degrades while they grow. Counteracting the degradation of code quality or improving it requires immense effort. Tools that reduce this effort are a hot topic in software engineering research. Software Modularization in particular aims to aid in the process of improving the quality of code structure, by finding flaws in code structure and suggesting improvements. Much research has been done in this field, however, most of it is applied on small to medium scale codebases. In addition, the quality of solutions implied by this research is often not properly validated. This thesis aims to apply an existing approach to an enterprise-level codebase, namely that of Adyen, and validating the results with developers experienced with the code. We achieve this by taking a graph-based approach, applying the NSGA-II algorithm, and introducing a new metric called the Estimated Build Cost of module Cache Breaks. We evaluate the approach in two ways. First, we performed a controlled experiment exploring the feasibility of the approach on larger scale codebases. For this experiment, we apply the approach to the Adyen codebase. The results show that the approach is scalable and shows a significant improvement of code quality in terms of the metrics used. We then performed a user study where we explore the feasibility of these results in practice. For this study, solutions generated during the experiment are split up and filtered to form groups with less than 10 changes, which are reviewed by developers that have changed that code recently or are a senior with experience in that specific area of the code. The results show that the algorithm is successful in identifying flaws in the codebase. However, the improvements it suggests are less precise and require future work.
ANALISIS PENENTUAN PUTUS STUDI (DROP OUT) MAHASISWA SEKOLAH PASCASARJANA UNIVERSITAS SUMATERA UTARA MENGGUNAKAN ALGORITMADATA MINING C 4.5

To determine the dropout of the study (droup out) University of Sumatera Utara graduate school students, the author tries to help determine the dropout of the study by using an algorithm in data mining, the C.4.5 algorithm. Data of University of Sumatera Utara graduate school students are processed in tabular form so that a decision tree can be obtained to be explored and then developed again. After the decision tree is obtained, data analysis is done using SPSS (Statistical Product and Service) software and RapidMine software is used to display the decision results. The results obtained are obtained a rule model that can show the relationship rules of existing variables, determine the variables that influence the determination of study dropouts at the University of Sumatera Utara graduate students and be able to predict study dropouts at the University of Sumatera Utara Postgraduate Studies ie the study drop out prediction if the GPA 8 and Study Load <36 SKS.
A Study on Exploring the Implications of Category Theory in Traditional Chinese Education Philosophy

In today"s era of the Fourth Industrial Revolution, the purpose is to explore what categories of traditional Chinese education philosophy can be applied in the educational field. We hope that the study of the categorical theory of traditional Chinese educational philosophy will provide a clue to overcoming the chaos of the categorical theory of educational philosophy that we are currently experiencing. The category of ancient educational philosophy in China is single. But the majority are paired. Ancient educators in China studied educational laws and put particular emphasis on dialectical relations between categories when they set up a theoretical system with this, combining educational experience. Inspired by the philosophy of "History," they critically synthesized the educational categories presented in the history, and clarified the value of dialectical features and methodologies by making the category system more complete and systematic. The category of ancient education philosophy in China not only has the characteristic of combining body theory, ethics, cognition and discipline, but also has acquired the capacity and power of educational thought and continued to come up with new things in knowledge and knowledge, thus accumulating the experience of development to this day.
Personalized knowledge point recommendation system based on course knowledge graph

Abstract Existing class education lacks analysis of students’ learning data, which can not reasonably evaluate students’ mastery of knowledge points and locate students’ learning path in real time, nor effectively recommend the required knowledge points for students. In order to solve the above problems, a personalized knowledge point recommendation system model (KG-PKP) combined with the knowledge graph of the course is proposed. By using accuracy, answer-time and answer-types in answer records, evaluation equations which to judge students’ mastery of knowledge points can be constructed. We can extract the knowledge points in answer records and map them into the course knowledge graph. Personalized knowledge points for students can be recommended by using the semantic hierarchical relationship and sequence of knowledge points in the knowledge graph. The comparative experiment proves the validity and interpretability of the model.
Meteorological probabilistic models for power system adequacy and resiliency assessment

The consequence of increasing the use of large amount of renewable non programmable generation capability (wind and PV systems) as well as extreme weather events or, more in general, changing environmental conditions, will have significant impacts on future power systems, in particular on the power system adequacy and on the resiliency assessment. Climate change has changed and will continue to affect both the energy demand and the available generation capacity. For instance, high demand for extreme heat or cold phenomena can determine the presence of critical operating conditions from the point of view of power system adequacy. Meteorological variables, therefore, are essential inputs to study key dimensions that must be kept under close observation to correctly manage the power systems. In this context, the aim of this paper is to propose models to generate profiles of the main meteorological variables (irradiance, wind speed, ambient temperature) considering their interdependence, suitable for adequacy and resilience analysis. In this paper, two models are proposed for the generation of the hourly daily radiation profiles based on statistical data: one is based on data probability distributions and the other on the clear sky solar radiation. Moreover, since climatic variables are interdependent, to generate the hourly temperature profiles a model based on the irradiance profile and the monthly mean daily minimum and maximum hourly temperatures is developed. The temperature is generated starting from the measured data and from irradiance data generated using the two approaches here proposed. Then, the persistence of low and high temperature situations and number of consecutive clear and cloudy days considering measured and simulated data is analysed.
COMMUNICATION OF LEADERSHIP AND TEAM

This article is devoted to the study of the relationship, mutual influence of team building and team leadership established by the author of the article, the competencies of leaders in the field of team building, leadership styles, including with regard to the process of forming and maintaining teams, are established that the process of creating an effective team is an integral part of the leader’s daily activities.
Privacy by Design: Analysis of Capacitive Proximity Sensing as System of Choice for Driver Vehicle Interfaces

Data collection is beneficial. Therefore, automotive manufacturers start including data collection services. At the same time, manufacturers install cameras for human machine interfaces in vehicles. But those systems may disclose further information than needed for gesture recognition. Thus, they may cause privacy issues. The law (GDPR) enforces privacy by default and design. Research often states that capacitive proximity sensing is better to serve privacy by design than cameras. Furthermore, it is unclear if customers value privacy preserving features. Nonetheless, manufacturers value the customer’s voice. Therefore, several vehicular human machine interface systems, with camera or capacitive proximity sensing, are analyzed. Especially concerning gesture recognition, capacitive proximity sensing systems provide similar features like camera-based systems. The analysis is based on the GDPR privacy definition. Due to the analysis, it is revealed that capacitive proximity sensing systems have less privacy concerns causing features. Subsequently, three hypotheses are formulated to capture the customer’s voice. Due to analysis results, it is questionable if gesture recognition systems, which utilize cameras, are compliant with privacy by design. Especially since well-known systems like capacitive proximity sensing are available. A survey concerning the hypotheses will give further insights in future work.
CHARACTERISTICS OF PATRIOTIC EDUCATION ORGANISATION THROUGOUT EXTRACURRICULAR ACTIVITIES FOR YOUNGER ADOLESCENTS

The article presents the results of a study related to the characteristics of the younger adolescents’ patriotic education throughout extracurricular activities. On the basis of system-activity approach and the concept of existential pedagogy, the author provides a definition of patriotic education as a purposeful interaction of the subjects in the pedagogical process, which results in learning about the system of phenomena in the world around us and the formation of personality, revealing moral feelings and transforming reality for the development of society and country. The concept of "patriotic education objectification" is defined as the relationship of joint activities for organizing educational events and students’ personality transformation as subjects forming the value of identity. The study reveals that the formation of certain levels of patriotism in younger teenagers is affected by the following objective conditions: school integration, family and social traditions, emphasis on external and internal elements and subject interaction in the implementation of extracurricular activities as pedagogical events.
Virtual Machine Software in Computer Network Security Teaching

The development of network makes its security more and more important, but there are many problems in the teaching of network security. Network security has become an important guarantee of network construction. Mastering the technical ability of network security has become the necessary quality of computer and network professionals. Based on this, this paper studies the application of virtual machine software in the teaching of computer network security. Through questionnaire survey, this paper understands the current situation of computer network security course in Colleges and universities, and summarizes the problems existing in the current college computer network security course. Among them, 22.1% of the problems are caused by the fear of system security risks in the teaching process, and the students’ operation practice content is relatively high The reason of less is 19.3%, and the problem caused by the limitation of university equipment resources accounts for 18.6%, and so on. Therefore, the use of virtual machine technology in computer network security in Colleges and universities can effectively solve the problems.
Concept Hierarchy Network based Information Retrieval for Restaurant Recommendation Dialogue

Information recommendation using UGC (User Generated Contents) systems has been paid much attention recently. Explainability and reliability are important for users easy to interpret the search results of a recommendation system. This paper proposes a hierarchical concept network that represents inferences based on evaluation criteria for recommendation in order to satisfy explainable recommendation. Futhermore, we also achieve reliable recommendation by restricting knowledge sources in generating the links between concept categories. We evaluate that our proposal method can generate explainable and reliable search results in some examples of restaurant information recommendation.
STRATEGI PEMBERITAAN DETIK.COM DALAM PENYEBARAN BERITA VIRAL DI WEBSITE WWW.DETIK.COM

Detik.com is an online news portal that prioritizes speed with accurate, credible, balanced and trusted news content. In this study, discussing the detik.com reporting strategy in spreading viral news on the website www.detik.com. The purpose of this research is to find out how the news strategy carried out by detik.com in spreading viral news on the website www.detik.com. This study uses qualitative methods and descriptive research types. Primary data were obtained from in-depth interviews with one Key informant and one informant, while secondary data was obtained through documentation and literature study. The key informant in this study was the Managing Editor, and the informant in this study was the journalist DetikNews.The theory that is relevant to this research is the POAC theory from George R Terry. And the concept of this research is news strategy, news dissemination, and website. The results of this study indicate that the detik.com reporting strategy in spreading viral news on the www.detik.com website is: holding meetings, reporting to the field, conducting a selection strategy for many developing issues, by verifying data and writing strategies by journalists covering in the field, write based on available facts.
GRAPH BASED TEMPORAL AGGREGATION FOR VIDEO RETRIEVAL

Large scale video retrieval is a field of study with a lot of ongoing research. The work that has been done in this fieldeither uses image queries from within the video dataset or iterates through videos frame by frame. These approaches arenot
Detecting Non-Natural Objects in a Natural Environment using Generative Adversarial Networks with Stereo Data

This thesis investigates the use of Generative Adversarial Networks (GANs) for detecting images containing non-natural objects in natural environments and if the introduction of stereo data can imp ...
Research on the Cultivation Mode of University Student Maker Space Based on the Network Platform under the Background of School-Enterprise Cooperation

Abstract With the upsurge of “mass entrepreneurship and innovation” and the maturity of computer technology, the innovation and entrepreneurship education of colleges and universities has been given a new historical mission. How to promote the cultivation of applied talents and improve the ability of college students to innovate and create has become an urgent problem to be solved. With the gradual spread of the maker culture, the cultivation of college students’ thinking and the exploration of the maker space model have gradually become the breakthrough of reform. This paper explores the operation mode of Maker Space in the second classroom of college students based on the network platform and the feasibility of cultivating the culture of Maker in the campus. Based on the experience of cooperation between schools and enterprises in recent years, this paper proposes the cultivation of college students’ creator space under the school-enterprise cooperation mode. Mode of operation.
Deep F-Measure Maximization for End-to-End Speech Understanding

Spoken language understanding (SLU) datasets, like many other machine learning datasets, usually suffer from the label imbalance problem. Label imbalance usually causes the learned model to replicate similar biases at the output which raises the issue of unfairness to the minority classes in the dataset. In this work, we approach the fairness problem by maximizing the F-measure instead of accuracy in neural network model training. We propose a differentiable approximation to the F-measure and train the network with this objective using standard backpropagation. We perform experiments on two standard fairness datasets, Adult, and Communities and Crime, and also on speech-to-intent detection on the ATIS dataset and speech-to-image concept classification on the Speech-COCO dataset. In all four of these tasks, F-measure maximization results in improved micro-F1 scores, with absolute improvements of up to 8% absolute, as compared to models trained with the cross-entropy loss function. In the two multi-class SLU tasks, the proposed approach significantly improves class coverage, i.e., the number of classes with positive recall.
Filíocht Nua: New Poetry

Filíocht Nua: New Poetry Thomas Kinsella street game for the over 15s Take a broad and empty face,Insert a pair of artful eyesHigh in cunning, short on shame,Mean mouth, loose lips. Remove the normal human mind,Substitute a swollen self,Oversized but incomplete; Austere. Subnormal. Neatly dressed. * Form a circle,Throw the hatchet.Run for coverIf he catch it. Hide and seek. Close your eyesAnd say your prayers.Bare your necksAnd start counting. I grew up in Inchicore in the 1930s. The children enjoyed themselves out in the street with simple street games. The games grew rougher with their years. By age fifteen we were in rival street gangs and the games grew rougher still. [End Page 104] Copyright © 2020 The University of St. Thomas
On the effectiveness of GAN generated cardiac MRIs for segmentation.

In this work, we propose a Variational Autoencoder (VAE) - Generative Adversarial Networks (GAN) model that can produce highly realistic MRI together with its pixel accurate groundtruth for the application of cine-MR image cardiac segmentation. On one side of our model is a Variational Autoencoder (VAE) trained to learn the latent representations of cardiac shapes. On the other side is a GAN that uses SPatially-Adaptive (DE)Normalization (SPADE) modules to generate realistic MR images tailored to a given anatomical map. At test time, the sampling of the VAE latent space allows to generate an arbitrary large number of cardiac shapes, which are fed to the GAN that subsequently generates MR images whose cardiac structure fits that of the cardiac shapes. In other words, our system can generate a large volume of realistic yet labeled cardiac MR images. We show that segmentation with CNNs trained with our synthetic annotated images gets competitive results compared to traditional techniques. We also show that combining data augmentation with our GAN-generated images lead to an improvement in the Dice score of up to 12 percent while allowing for better generalization capabilities on other datasets.
Readiness of additional vocational education teachers for pre-retirement age citizens education within Worldskills competition standards

The paper deals with the problem of vocational education teachers' readiness for training pre-retirement age citizens. With the introduction of the state program "Older Generation", aimed to improve the skills or mastering the new competence of pre-retirement age citizens, training centers for this contingent are actively opening up. The training is conducted by teachers of educational institutions of the secondary vocational education system. Training programs according to Worldskills standards within the framework of the championship movement "Skills of the Wise" provide an opportunity for people aged 50+ to upgrade their skills or to master a new competency on the basis of the existing one. The authors aim to identify the level of andragogical competence of a teacher of vocational education. The research is based on empirical methods such as comparative analysis, generalizations, observation, questionnaires, and experiment. The research results show that the education of older people cannot be based on general recommendations, and requires the use of certain methodological approaches in teaching methods.