Reviewerly/exHarmony huggingface dataset:
RELATIONSHIP BETWEEN EXTRACURRICULAR ACTIVITIES WITH LEARNING CREATIVITY IN SMP STUDENTS

Extracurricular activities are one way to achieve institutional goals. These activities are carried out outside school hours and are generally in the form of assignments, completed through experiments, or in the form of practice as practice and theory accepted at school. When students carry out extra-curricular activities it means that they are training their learning creativity. By getting used to students practicing their lessons from school, the creative potential they have will also develop. So, in addition to achieving institutional goals, students are also expected to be independent after graduating from school. However, there are still many teachers who do not realize the great benefits of extra-curricular activities so that they are not serious about implementing them. In this study, the authors determined a sample of 10.56% of the total number of students of class VII SMP from 30 students who became respondents. The method used is descriptive method, to obtain data the researcher uses a closed questionnaire and this questionnaire is divided into two, namely the first part to obtain data about extra-curricular activities and the second part to obtain data about student learning creativity. Respondents' answers are rated with the following weights: option a value 4, option b value 3, option c value 2, option d value 1. The data is quantitative and the analysis technique is a statistical analysis of correlations using the Product Moment Statistics formula developed by Pearson. Hypothesis testing is based on a significance level of 5% or by using a confidence level of 95% used the r table (correlation table) with a sample size of 30. Then the calculation results obtained r = 0.9885 and r table correlation = 0.361, which means high correlation.
Review of Workflow Scheduling Algorithms in Cloud Computing

Cloud computing is a parallel and distributed framework computation by the information technology resources and which are further characterized by the demand services through the Internet. The cloud providers also use a typical model such as “pay-as-you-go” to access the network services. Due to its wide popularity, a huge number of applications and organizations are on Cloud platforms. The performance of the Cloud depends on the number of applications run at a given point of time and resources available at Cloud to execute these applications. Hence, improper utilization of computational resources may result in a compromise in the overall performance of the Cloud. This issue becomes critical for real-time applications where performance in form of throughput and response time is of utmost importance. Here comes the role of scheduling algorithms that appropriately plan the task on a given resource. Proper scheduling mechanism can avoid the problem of performance as well as resource utilization. Through this research, various scheduling mechanisms being used for Cloud computing is extensively surveyed and evaluated them based on various parameters such as throughput, latency, makespan, etc for typical task execution and also discuss their benefits and challenges.
Overview Of Various Optimization Techniques For Recommendation System

Artificial intelligence and data science has opened the doors of possibilities to help users for optimizing their search results. Ultimately, the search engines are working for providing the exact results to the user upon search. Over last 5 years, number of internet user in India have increased rapidly with the better internet speed and verity of android options available in market. At the end of 2020, the number of internet users in India is forecasted as 650 million which will be around 50% of Indian population. With huge number of users, it becomes very important to provide the optimised search results. Matching the preferences of users in search results may increase the user satisfaction. Many web services, applications and search engines use recommender system to enhance the user experience. Authors have presented the overview of various techniques implemented in optimization of search results for the recommender system.
Continual learning with neural activation importance

Continual learning is a concept of online learning along with multiple sequential tasks. One of the critical barriers of continual learning is that a network should learn a new task keeping the knowledge of old tasks without access to any data of the old tasks. In this paper, we propose a neuron importance based regularization method for stable continual learning. We propose a comprehensive experimental evaluation framework on existing benchmark data sets to evaluate not just the accuracy of a certain order of continual learning performance also the robustness of the accuracy along with the changes in the order of tasks.
Education: socialization vs individualization

Presented is an attempt to understand the concept of individualization of education. The article analyzes interpretations of this concept, that have emerged in recent years. Identified are elements, on which is focused attention of researchers, namely: individualization of the educational process, and individualization of the student. It is established that reasons, that prevent individualization of learning, are features of organization of educational process, while influence, that conservative nature of institute of education has effect on reducing effectiveness of the process of differentiation and individualization is not noticed. It is revealed that the need for educational system to perform functions of socialization and cultural reproduction sets tasks that at latent level contradict with requirements of individualization. Implementation of these functions is accompanied by formation of logical conformism among students and unification of their identifications that are individually and personally expressed in processes of self-typing. Thus, in order to transform education in accordance with ideas of variation, differentiation and individualization, it is necessary to study the limits of institutional possibilities for individualization of both student and learning process, as well as to explore the possibility of transformation in the context of individualization of institutional nature of the education system itself.
ANALISIS SASTRA ANAK DALAM CERKAK MAJALAH PANJEBAR SEMANGAT EDISI (1 – 53) TAHUN 2016 SERTA RELEVANSINYA SEBAGAI MATERI PEMBELAJARAN APRESIASI SASTRA SISWA SMK (SEBUAH PENDEKATAN SOSIOLOGI SASTRA)

This research aimed to (1) describe and explain the intrinsic elements contained in the cerkak - cerkak of the Panjebar Semangat magazine on the Edition (1 - 53) in 2016; (2) describe the social condition of the society contained in the cerkak-cerkak of the Panjebar Semangat magazine on the Edition (1 - 53) in 2016; (3) Describe and explain the relevance of the cerkak-cerkak of the Panjebar Semangat magazine on the Edition (1 - 53) in 2016. This was a qualitative research with descriptive qualitative method. The sources of the data in this study were documents and informants. The validity of the data was triangulation theory and the source. The sampling technique used in this research was purposive sampling technique. Technique of collecting data used reading and interviewing techniques. There were 4 Data analysis techniques used in this research, those were domain analysis, taxonomy, component, theme and cultural. Based on the results of the research and discussion written on chapter IV about cerkak analysis, social condition of the society, and the relevance as learning material of literature appreciation subject on high school student, it was concluded that the analysis of 6 cerkak containing child literature element was suitable to read for student.
The Dialectics of the Visual and the Book Culture in the Postmodern Era

The object of research in the present work is the issue of the coexistence of the book and the visual cultures. Contemporary culture, having become informational, has transformed into a society of visual culture. The phenomenon of visual culture of post-industrial society is examined as a specific type of information and as a process. The processes of virtualization of life are becoming the distinctive feature of contemporary informational technologies. Information in the present era is exerting its influence on the user of technologies to a much greater degree as it was the case earlier. But the author does not agree with the negative evaluation of visualization as a replication of the set model of communication which impoverishes human thought. The reasons for this intellectual impoverishment and the lowering of the overall cultural level of the consumer have not been incited by art works of visual culture. These processes are conditioned by the specificity of contemporary mass culture which forms the “midrange” personality. Descriptions and comparisons are given of the model of the sociocultural mechanism of informational impact of art works pertaining to visual and book culture. The attempt is made to answer the question of whether visual culture possesses a systematic predominating status, or whether it must be examined as one of the directions of culture of the informational society. The conclusion is reached about the prospects of coexistence and interpenetration of the visual and the book culture with each other.
Penerapan Algoritma Elias Delta Codes Dalam Kompresi File Teks

File size or large files are not only a problem in terms of storage, but also another problem when communication between computers. Data usage with a larger size will take longer transfer times compared to data that has a smaller size. Therefore to overcome this problem you can use data compression. Seeing the compression of data compression, data compression is needed that can reduce the size of the data, so that it gains the advantage of reducing the use of external storage media space, accelerating the process of transferring data between storage media, data utilization used in this study is the elias delta codes algorithm. Compression is a method used to reduce the bit or data from the original result to a new result. Where this compression will be applied into the algorithm, the elias delta codes algorithm. After getting the results of the compression it will be designed into Microsoft Visual Studio 2008
LibGuides: Primary Sources: Maps and Government Data

This is a research guide to finding primary sources that are accessible through the MSU Duane G. Meyer Library or through the open web.
Ενιαίος Κατάλογος Συνεργατικού Δικτύου Ακαδημαϊκών Βιβλιοθηκών: αποτίμηση από τους επαγγελματίες πληροφόρησης

The present research focuses on the effort of valuation as a reference to librarians' view of new collaborative systems used in the field of librarianship. It is well understood that in modern society, due to the rapid growth of the technology sector over the last few years, the systems used in the field of libraries are evolving and new forms and tools are introduced. The main concern of the present work is to present the data in detail, taking into account the theoretical background of previous research and presentations in order to derive a significant and lucrative result.
The Teachers Activating the Passive English Learners

The objective of this research was to describe the efforts of teacher in activating the passive English learners at SMA Negeri 2 Buton Tengah. The research was conducted at SMA Negeri 2 Buton Tengah, by using a grounded theory and applied qualitative approach. The source of the data was observation, interviewed and documents. The key instrument of this research was the researcher herself. The findings of this research were follows: (1) there are several kinds of passive attitude do in the teaching and learning process, such us: less of motivation, less of interested and the students were lazy (2) there are many teachers’ efforts to activate the passive students to be participate in the teaching and learning process, such us asking to do something, giving motivation, reward, direction, score, and games.
Website-based teleradiology information systems at disaster locations

Indonesia is a disaster-prone country, be it social, natural, and non-natural disasters. Disasters are usually associated with mass casualties, where health services are an important factor in preventing death, disability, and disease events. Therefore a special health information system in the event of a disaster is needed. One form of health information system is a teleradiology information system used for remote diagnostic imaging. The purpose of this study is the creation of a website-based teleradiology information system at the disaster location as an easy way to interpret radiological images. This type of research uses the Research and Development (R&D) approach of the Borg and Gall method. The sample in this study was 1 radiologist, 2 radiology admins, and 3 radiographers. Expert validation was carried out on the teleradiology information system website design and respondent validation was carried out on website quality and user satisfaction. The result of this research is the teleradiology information system website called INRASTER has fulfilled the three main components of teleradiology for disaster. On the results of statistics on the relationship between website quality and user satisfaction variables, the Sig. (2-tailed) < 0.05 which means there is a significant relationship between website quality and user satisfaction. This research concludes that the teleradiology information system website (INRASTER) can be used to facilitate the interpretation of radiological images so that this website can be used during disasters, especially in Indonesian regions.
Research Guides: RPW 2610W A Hands-On History of the American Research University - Loss, Meadows: Search Tips

Library research guide for RPW2610W A Hands-On History of the American Research University. Tips for searching the library catalog, Special Collections Collections Guides, and databases.
Modern Approaches to Quality Assurance of Teacher Training

The article deals with the problem of modern approaches to teacher training in the context of its quality assurance. The concept of ‘innovation’ is defined and the system of classification is introduced on the grounds of the analysis of scientific and pedagogical resources. Ensuring qualitative education means innovative processes of pedagogical practice development, as well as purposeful managerial influence on the system of professional training, significant corrections of its content and way of performance of pedagogical intuitions, i.e. educational system transferring to perform on new grounds. Organizational innovations happening in the organization of the educational process of higher education institutions are analyzed alongside content innovations reflected in the content of teacher training (new educational programmes, introduction of new disciplines, modern courses, integration of subjects, development of methodologies, etc.). Technological innovations include introducing new teaching forms and methods, assessment approaches (testing, rating); use of modern information technologies in the process of teacher training. Building professional competency, individual and professional qualities, the capacity to work and live in an innovative pace is exclusively important for future teachers. Effective forms and methods of teaching future teachers are introduced.
EVALUASI IMPLEMENTASI PROGRAM BANTUAN OPERASIONAL SEKOLAH PADA SATUAN PENDIDIKAN SEKOLAH DASAR NEGERI TAHUN 2019-2020 DI KECAMATAN LUBUK BASUNG

Evaluation Policy implementation is a process to see how the process of implementing a policy has been implemented or to see whether the process of implementing a policy has been implemented in accordance with predetermined technical or implementation instructions. One of the programs from the government is the BOS program. The background of the BOS program was the increase in fuel prices which resulted in a decrease in people's purchasing power which had a negative impact on poor people's access to Nine Years of Basic Education. This study finds out about the evaluation of the implementation of the school operational assistance program in the state primary school education unit 2019-2020 in Lubuk Basung sub-district. This research uses implementation evaluation theory according to Grindle. This research uses a qualitative approach with a descriptive type. The selection of informants was carried out by using purposive sampling technique. Meanwhile, data analysis was carried out ethically and emotionally. Based on the results of the research that has been carried out, the researcher draws the conclusion that the evaluation of the implementation of the school operational assistance program in the 2019-2020 public elementary school education unit in Lubuk Basung sub-district has been carried out well even
Research guides: LibrarySearch Tips: Reading Results

A guide to the University of Toronto Libraries' LibrarySearch platform How to understand a list of search results
A Structural Equation Model for Happiness Among Elementary Students

This research examines the relationship of happiness, self-esteem, school adjustmentand peer trust as a descriptive correlation study.The data collected from PSKC (Panel Study on Korean Children) panel survey of 2017 were analyzed using statistical program of SPSS 18.0. Several Descriptive statistics, Pearson Product Moment Correlations and Multiple Regression were used. The participants in this study were 757 males (51.0%) and 727 females (49.0%). The mean age was 9.39 years old. The structural model developed on the basis of causal correlations between peer trust, school adjustment, self-esteem and happiness was verified. It also examined that the elementary students’ school adjustment partially mediates the association between peer trust and happiness. This confirmed again that school adjustment is an important factor in the happiness of elementary school students. Based on these conclusions, it is suggested that educational activities or home environments that provide school-age children with an opportunity to explore themselves are necessary
Attention R-CNN for Accident Detection.

This paper addresses accident detection where we not only detect objects with classes, but also recognize their characteristic properties. More specifically, we aim at simultaneously detecting object class bounding boxes on roads and recognizing their status such as safe, dangerous, or crashed. To achieve this goal, we construct a new dataset and propose a baseline method for benchmarking the task of accident detection. We design an accident detection network, called Attention R-CNN, which consists of two streams: one is for object detection with classes and one for characteristic property computation. As an attention mechanism capturing contextual information in the scene, we integrate global contexts exploited from the scene into the stream for object detection. This introduced attention mechanism enables us to recognize object characteristic properties. Extensive experiments on the newly constructed dataset demonstrate the effectiveness of our proposed network. The dataset and source code are publicly available on our project page. 1 https://sites.google.com/view/ltnghia/research/accident-detection
Compositional Generalization via Parsing Tree Annotation

Humans can understand a novel sentence by parsing it into known components like phrases and clauses. To achieve human-level artificial intelligence, compositional generalization tasks are suggested and used to assess machine learning models. Among those tasks, the SCAN tasks are challenging for the standard deep learning models, such as RNN sequence-to-sequence models and Transformers, that show great success across many natural language processing tasks. Even though a long line of deep learning research has developed memory augmented neural networks aimed at the SCAN tasks, their generalities remain questionable for more complex and realistic applications where the standard seq2seq models dominate. Hence, one needs to propose a method that helps the standard models to discover compositional rules. To this end, we propose a data augmentation technique using paring trees. Our technique annotates targets by inserting a new delimiter token in between them according to their parsing trees. For the training stage, the technique needs prior knowledge about the targets' semantic or syntactic compositionality. On the other hand, for the test stage, the technique uses no such knowledge. Experiments show that our technique enables the standard models to achieve compositional generalization on the SCAN tasks. Furthermore, we validate our technique on a synthetic task and confirm the standard models' strong performance gains without using prior knowledge about semantic compositionality. As one way to infuse parsing tree information into sequences, our technique can be used for tasks with structured targets like program code generation tasks.
O método Quadripolar e a sua aplicação em trabalhos científicos

This article presents a study on the use and exploitation of the quadripolar method in the context of master's and doctoral studies mainly in Information Science. To this end, studies conducted in Portugal and Brazil between 2006 and 2019 were surveyed. In the field of Information Science, whose object information is taken as a phenomenon, therefore with greater complexity and scope, namely social, a methodological approach that deals with this complexity is required. Thus, the quadripolar method is a viable option that assists in the approach of phenomena associated with information, its use and exploitation, in the context of Information Science. The Quadripolar Method proposes a multidisciplinary approach in which it combines both the qualitative and quantitative approaches, proposing a dynamic research instrument, based on the result of the interaction between four poles: epistemological; theoretical; technical and morphological. This approach allows the double study of the problem in question, both in its context and as a representative of a common class of similar problems.
Federated Learning of Electronic Health Records Improves Mortality Prediction in Patients Hospitalized with COVID-19.

BACKGROUND: Machine learning (ML) models require large datasets which may be siloed across different healthcare institutions. Current ML studies focusing on coronavirus disease 2019 (COVID-19) are limited to single hospital data which limits model generalizability. OBJECTIVE: Using federated learning, a ML technique that avoids locally aggregating raw clinical data across multiple institutions, we predict mortality within seven days in hospitalized COVID-19 patients. METHODS: Patient data was collected from Electronic Health Records (EHRs) from five hospitals within the Mount Sinai Health System (MSHS). Logistic Regression with L1 regularization (LASSO) and Multilayer Perceptron (MLP) models were trained using local data at each site, a pooled model with combined data from all five sites, and a federated model that only shared parameters with a central aggregator. RESULTS: LASSO-federated outperformed LASSO-local at three hospitals, and MLP-federated performed better than MLP-local at all five hospitals as measured by area under the receiver-operating characteristic (AUC-ROC). LASSO-pooled outperformed LASSO-federated at all hospitals, and MLP-federated outperformed MLP-pooled at two hospitals. CONCLUSIONS: Federated learning shows promise in COVID-19 EHR data to develop robust predictive models without compromising patient privacy.