Reviewerly/exHarmony huggingface dataset:
TEACHING EXTENSIVE LISTENING DEVELOPING RECOUNT PARAGRAPH WRITING

This study aimed to facilitate students in an integrated learning approach to meet the purpose of teaching and learning. This listening–writing integrated teaching data was a survey research designe, to identify the intention, preference and benefit of students. The study aimed also to identify the case of theoritical proposition and the field practice. The data was taken from 58 English education study program students of 4th semest, those who were in the treatment of the teaching approach. Students’ responses to the questionnaires was in order to answer 2 research questions: what are students intentions, preferencec, and the benefits, and other suggestions of students toward the teaching approach. The data of research provided in approaching of Likert’s scale in the renge of 1 (strongly agree) to 5 (strongly disagree). However the questionnaires were designed more in positive view points towards the implementation rather than in negativesites. The questionnaire data was analysed using descriptive statistical operaion to see the average number of students’ responses and the frequency toward each of three points. By data analysis, the result shows that, 30 student (51,7%) strongly agree, 25 students (43,1% agree) 2 student 3,4% neutral, 1 student (1,7%) disagree to the intention. There were also 20 students ) 34,5% strongly agree, 33 (56% agree), 5 (8,6% neutral and none disagree for preferences, while, 12 (20,7% strongly agree, 41 students (70,7%) agree, 5 students (8,6%) neutral and none dis/or strongly agree with the benefit. Even in a quite strong data, but there were also great number of studsent complain in their hand writing note data. The complains are in the cases that (a) writing is difficult so, it should not be in parallel with listening, (b) writng created boringness, and their proportion of changing this (integrated) approach. From the two data, the possible conclussion is that there was benefit for the integrated listening-writing but a fully and detail explanation should have than become the consern on the awarenes of student
Technical overview of the U.S. Geological Survey Earth Mapping Resources Initiative (Earth MRI)

First posted November 2, 2020 For additional information, contact: Earth MRI Science CoordinatorMineral Resources ProgramU.S. Geological Survey913 National Center12201 Sunrise Valley DriveReston, VA 20192 The Earth Mapping Resources Initiative (Earth MRI) was developed by the U.S. Geological Survey in response to a Federal directive calling on various Federal agencies to address potential vulnerabilities in the Nation’s supply of critical mineral resources. The primary purpose of this initiative is to identify potentially mineralized areas containing critical minerals by gathering new basic geologic data about the United States and its territories and to make these data publicly available through the Earth MRI web portal (https://usgs.gov/earthmri). The gathering of data is accomplished through geophysical surveys, geologic mapping, and the collection of topographical (light detection and ranging, or lidar) data. In addition to identifying areas permissive for hosting critical minerals, the new data collected are likely to be helpful in addressing other societal needs as well, such as by helping to locate groundwater resources, providing information needed to mitigate effects of natural hazards, and identifying locations of the mineral resources useful for restoring and rebuilding aging infrastructure in the United States.
University Staff Teaching Activity As A Factor Of Forming Students' Creative Activity

The article presents the results of the research held by 30 Vietnamese teachers and 60 Vietnamese students of Hanoi Pedagogical University in Vietnam and Russian University of Peoples' Friendship of Russia in the field of forming creative activity of students in the learning process.Q-methodology was applied to identify the factors influencing formation of creative activity of students.Collecting materials and processing of statistical data were carried out using a web application-Ken-Q Analysis version 1.0.6.The uniqueness of this study lies in the comparative analysis of both the views of teachers and students on the factors of creative activity formation.The result of the study showed that teaching is a key factor in forming creative activity of students.The factor of teaching activity was chosen as a key one not only by the teachers themselves, but also by the students.The analysis of surveys of teachers and students showed similar results.Both showed a high level of agreement or disagreement with the following statements: "Teaching creates motivation for students' creativity" (20: +5); "Teacher is ready to support creative activity of students during classes" (18: +5); "Teacher is a paradigm example of creativity" (31: +4); "Style of leadership in management and organization of teachers' classes" (40: +4); "Teacher carries out supervision, meeting different needs of the students in the group" (26: +4); "Teacher and students establish positive relationship in the learning process" (29: +4); "When evaluating learning outcomes, teachers appreciate new, unique and useful products" (11: +3); and other.
Multiple-instance Learning based on Bernoulli Mixture Model

Abstract Multiple-instance learning (MIL) is a form of weakly supervised learning. Its instances are arranged in groups (called bags), and labels are provided for the entire bag after training. The classic MIL method represents examples with pre-calculated features, and the classification process is also cumbersome. In this paper, we use neural networks to extract features, parameterize all transformations, and use Bernoulli mixture model to construct MIL models for baggage tags, using simpler network structures and more accurately solving these problems. Experiments show that our results can be competitive with the classical MIL algorithm on the MINST dataset.
Design of Educational Process from the Point of View of Management Humanitology

The old management system crisis and the involvement of new social sectors into participation in management encourage us to study the humanitarian foundations of managing the higher education system. This article discusses the issues of managerial humanitology and the content of special education, and the ratio of civil and professional elements in the formation of a managerial worldview. A feature of contemporary Russian higher education is the highest level of its fundamental natural and humanitarian component. Furthermore, the development of the higher education system in historical retrospective also indicates its humanistic character, which is laid down by Christianity and the Russian Orthodox Church. Naturally, today highly qualified specialists are needed to successfully implement socio-economic reforms in the country, able to understand and implement them properly. In this regard, the higher education system plays a unique role, since higher education, being a social institution, is responsible not only for the inheritance, accumulation, and reproduction of scientific and specialized knowledge but also for the formation and transfer of cultural values and norms of behavior.
Generation of Checkered Pattern Images by Iterative Calculation Using Prewitt Filter with Expanded Window Size

We propose a nonphotorealistic rendering method for generating checkered pattern images from photographic images. The proposed method is executed by iterative calculation using a Prewitt filter with an expanded window size and can automatically generate checkered patterns according to changes in edges and shade of photographic images. To verify the effectiveness of the proposed method, an experiment was conducted using various photographic images. An additional experiment was conducted to visually confirm the checkered pattern images generated by changing the iteration number, window size, and parameter to emphasize the checkered patterns.
PENERAPAN METODE ADABOOST UNTUK MENGOPTIMASI PREDIKSI PENYAKIT STROKE DENGAN ALGORITMA NAÏVE BAYES

Stroke is the deadliest disease in the world. Creating injury to this nervous system because of this requires special attention in its treatment. The development of the Industrial Revolution Era 4.0 technology and health science can collaborate to become something beneficial by using machine learning. Currently the benefits are used in predicting several diseases to be anticipated. In particular, stroke using adaboost optimization with naïve Bayes which can provide an accuracy of 0.986 has an Excellent classification diagnosis with 70/30 split data. The previous accuracy without using optimization is 0.976. The result of this accuracy is used by health experts in making good decisions in the field of nursing and medicine. In order to speed up the results of diagnosis to stroke patients.
Data Mining Implementation Using Naïve Bayes Algorithm and Decision Tree J48 In Determining Concentration Selection

Computerization of society has substantially improved the ability to generate and collect data from a variety of sources. A large amount of data has flooded almost every aspect of people's lives. AMIK HASS Bandung has an Informatic Management Study Program consisting of three areas of concentration that can be selected by students in the fourth semester including Computerized Accounting, Computer Administration, and Multimedia. The determination of concentration selection should be precise based on past data, so the academic section must have a pattern or rule to predict concentration selection. In this work, the data mining techniques were using Naive Bayes and Decision Tree J48 using WEKA tools. The data set used in this study was 111 with a split test percentage mode of 75% used as training data as the model formation and 25% as test data to be tested against both models that had been established. The highest accuracy result obtained on Naive Bayes which is obtaining a 71.4% score consisting of 20 instances that were properly clarified from 28 training data. While Decision Tree J48 has a lower accuracy of 64.3% consisting of 18 instances that are properly clarified from 28 training data. In Decision Tree J48 there are 4 patterns or rules formed to determine concentration selection so that the academic section can assist students in determining concentration selection.
Design a solar power air conditioning system for the engineering building at Mutah University

Jordan like the other non-oil countries, spend significant amount of its budget on importing foreign energy. Also, the power demand increases due to, the population growth, in addition to hosting high number of refugees, from neighboring countries, and the enhancement of the citizen life style. The objective of this study, is to define the cooling load requirement, for the engineering building, at Mutah University, in order to analyze suitable cooling system, to cater the required cooling load. Energy analysis carried out, using the climate variables tabulated data, and Cooling Load Temperature Difference (CLTD), and Cooling Load Factor (CLF). The required power, to drive the cooling system was defined. Climate data shows that the average temperature was 33.2 °C, 32 °C and 33.3 °C in 2015, 2016 and 2017, respectively. The maximum temperatures was 38 °C registered in 2015. In this study the implementation of renewable energy, was considered by analyzing the viability of using, photovoltaic system, to provide power for the cooling system. Two options, to provide power for the system analyzed, the first option is supply the power from the grid, and the second option is, to supply the required power using photovoltaic power plant. The results show that, the cooling load of the building is 560 kW, and the required electrical power, to operate the cooling system is 224 kW electrical power. In addition, the results show that, the cost of power from PV system is, 40 % less than the cost of power from grid for the first 10 years. In addition, the payback period for the designed system is 5 years.
How I Stopped Worrying and Learned to Love the Usage Data

The digital environment has transformed how data on library material use is collected and reported, providing librarians with more information about usage but less clarity about how to interpret it. This article discusses current approaches to reporting and assessing library book use, addresses the question of what qualifies as a worthwhile use of library materials, and presents an analysis of four years of COUNTER 4 BR2 ebook reports at a single research institution to explore the reliability of page view-level usage data for collection assessment. It reveals ways assessment theory and practice fail to capture the value of library materials throughout the research lifecycle, and argues for an inclusive view of collections use.
Computational Thinking in der Musikwissenschaft: Jupyter Notebook als Umgebung für Lehre und Forschung

We show that in connection with the digitalization of musicology a special kind of mathematical and logical thinking, i. e. computational thinking/literacy, is in need. Computational thinking is characterized by effective procedures whereas computational literacy includes the implementation of these procedures on machines, i.e. programming. Both are the core of formalization, model building and computer simulation. Furthermore, we point out that “computation” as a central concept for the sciences in the 21st century and its use in cognitive science and the computational sciences make it necessary to reassess the basic assumptions underlying musicological research as science of mind (Geisteswissenschaft). We propose a digital habitat to integrate computational thinking/literacy in musicology and to become acquainted with model building and computer simulation. Jupyter Notebook provides a basis for such a digital habitat. We describe our use of Jupyter Notebook as a teaching environment for computational thinking/literacy.
Sense of Belonging and Job Satisfaction on Employee Performance

The company's ability to develop is influenced by improvements in employee performance.Performance can be measured from various aspects, namely from the inputs, processes, outputs, and outcomes achieved.There are several variables that affect employee performance, including a sense of belonging and job satisfaction.This research aims to find out how much the contribution of each indicator of the variable sense of belonging and job satisfaction will affect employee performance improvement in a multinational company in Banten.The causal relationship between variables was analyzed with Structural Equation Modeling-Partial Least Squares (SEM-PLS).The sampling method used is a simple random sampling with total respondent was 68 employees.The data was obtained through a questionnaire and processed using the SmartPLS.The variables studied included Sense of Belonging, Job Satisfaction and Performance.The research results are targeted to be able to contribute to the company to find the most dominant indicators affecting employee performance improvement, become the basis for companies to determine policies and be a reference for further research in the field of human resource management.The results of this research on manufacturing company's employees in Merak Banten showed that the two exogenous latent variables, Sense of Belonging (X1) and Job Satisfaction (X2) with their indicators affecting endogenous latent variable of Performance (Y) with their indicators significantly.
DISTANCE EDUCATION: PROBLEMS AND ADVANTAGES

The article provides a brief overview of the international scientific-practical conference “Relevant directions of the development of the higher education system: distance education - problems and advantages”, which was held on June 16-17, 2020 in Southern Federal University. The conference was organized by the Center for the Study of Social and Labor Relations and Problems of the Union Movement SFedU, Department of Applied Conflictology and Mediation SFedU, Trade Union Organization of SFedU. The article outlines the main ideas and results reached by the conference participants, as well as provides a generalized idea of the experience of using online learning with its advantages and disadvantages.
Studying Prospective Participants Of Open Online Cources

Active use of open online courses worldwide makes it necessary to study the practice of open education in the context of Russian universities.Due to that, the questions of who is going to become a participant of online courses and how we can describe this person are extremely relevant.The purpose of this paper is to describe results of a study dedicated to revealing characteristics of potential participants of online courses.The study was conducted by surveying undergraduate, post-graduate and continuing education students that have a need in getting a professional degree.In total, 123 respondents were surveyed.It has been revealed that despite rather high Selection of online course for all the groups of respondents was largely defined by developer reputation, platform, content, topic, as well as course workload.As a whole, respondents prefer blended learning approach that imply a combination of face-to-face interaction with online support in a form of a course.Readiness to completely switch to MOOCs was demonstrated only by 9.5 % of undergraduates, 6.3 % of postgraduates and 7.1 % of students of continuing education programs.As the most important obstacles for learning through online courses, the respondents named insufficient development of skills in independent processing of teaching information and in building online communication without direct contact with instructor.In general, further expansion of MOOCs in educational process in universities requires deeper research into characteristics of potential MOOC participants, as well as purposeful training in skills necessary for independent completion of online courses.
IMPROVING STUDENTS’ WRITING SKILL USING A MOBILE LEARNING APPLICATION

Writing is claimed to be the most difficult skill for second language and foreign language learners. Thus, it needs an effective model of teaching to improve the students’ writing skill. This study aims to describe the use of a mobile learning application Busuu to improve students’ writing skill. This is a classroom action research (CAR) that was conducted into two cycles. Each cycle consisted two meetings and involved four steps namely planning, action, observation and reflection. The data were collected by using technique of observation, test, and interview. The subject of the research was fourteen students of Widya Kartika University. The result showed that there was an improvement in students’ writing skill. It can be seen from the result of writing test in each cycle which was improved. Mean score of the students’ writing in cycle 1 was 61.14 and the mean score of the students’ writing was 71.42 in cycle 2. In addition, the results of the interview showed that the students had a positive attitude toward the implementation of mobile learning application Busuu in the activities of learning writing.
[Discussion on Key Issues of Geochemical Monitoring of Soil Heavy Metal in Xiong'an New District].

To build a soil environmental quality monitoring network and collect the systematic soil geochemical data of heavy metals before and after the construction of Xiong'an New District(XND), long-term variations in soil heavy metal levels during the XND construction were monitored based on the land quality geochemical survey monitoring data and the geochemical distribution of heavy metals. Parameters such as sampling density, sampling quantity, and sampling period were estimated to construct the geochemical monitoring network, which provides a reference for the future long-term monitoring of soil heavy metal geochemistry in XND. The results indicate that variations in the amount of heavy metals As, Cd, Cu, Hg, and Pb are greater than 36%, while the nugget coefficients of Cd, Cu, and Pb are greater than 75% because of the superposition of manmade sources on the high natural background levels. At the 95% and 90% confidence levels, while the allowable error Δ of the sample mean value is 5%, 10%, and 15% and heavy metals as As, Cd, Cu, Hg,Ni, Pb and Zn is monitored in soil environmental quality monitoring network, the proper numbers in the study area are 1077, 270, 120 and 767, 192, 86, respectively. The minimum detectable change(MDC)of each heavy metal species is between 0.0025 and 2.54 mg ·kg-1. Soil heavy metal monitoring requires different revisit intervals under different annual change rates, but in the study area, revisit intervals of soil monitoring are approximately two years under the current conditions of constant annual change rates.
AN IMPROVED MOVING OBJECTS DETECTION ALGORITHM IN VIDEO SEQUENCES

Context. The implementation of video analytics functions in video surveillance systems makes it possible to increase the efficiency of these systems. One of the functions of these intelligent video surveillance systems is to detect dynamic objects in the surveillance sectors of video surveillance cameras. Existing methods of background subtractoin and object recognition have important disadvantages that limit their application in practice: under low contrast algorithms can not select an object from the background; some moving objects can be recognized as a background, algorithms critical to lighting conditions, and so on. Therefore, an important task is to develop and improve methods for detecting dynamic objects in video sequences.Objective. The research is devoted to the development of an improved method for detecting dynamic objects in video sequences.Method. For moving objects detection in video sequences we used background subtraction methods based on pixel-by-pixel analysis of frames using elements of the expert systems theory.Results. In this paper, we propose an improved method for detecting dynamic objects in video sequences, which is based on the ViBe algorithm. The proposed approach differs from original the using of U*V*W* color model, using double threshold levels and some elements of theory expert systems for removal of vaguenesses in pixel classification (Dempster-Shafer theory) and dynamic method for updating background pixel models. Proposed algorithm include following stages: initialization of the background model (for each pixel with known parameters, the number of previous values in the current frame is stored); foreground detection; the next step is a calculation amounts of points, that belong to the foreground and to the background. For removal of vaguenesses in pixel classification we used some elements of Dempster-Shafer theory. After initialization of the background model and foreground detection next stage is updating background model. For this we used a three-level constructed neighborhood of the studied pixel and used of the even distribution of random values is into each of three levels.Conclusions. Experimental research of the improved algorithm in comparing to original ViBe conducted with the use of test frames from a set of CDNET in the various variants of environment and with the different variants of discriminability. The consolidated results specify on the improvement of results of an offer method as compared to original ViBe on the average on 6,7%.