Reviewerly/exHarmony huggingface dataset:
Development of Instructional Games Model Based Learning Media in Class V Elementary School Science Learning

PENGEMBANGAN MEDIA PEMBELAJARAN BERBASIS MODEL INSTRUCTIONAL GAMES PADA PEMBELAJARAN IPA KELAS V SEKOLAH DASARABSTRACTThis study aims to produce interactive learning media based on instructional games models in science learning in grade V elementary schools that meet very valid and valid criteria. This type of research is research and development (Research and Development). The research model used is the 4-D type, namely define, design, develop, and disseminate. In this study, it only reached the develop stage due to time constraints. This research was conducted in the even semester of the 2019/2020 school year. The research instrument includes a validation sheet. Interactive learning media based on instructional games models in science learning are validated by 1 media expert in display aspects and 2 experts or teachers in the content aspect. Based on the results of the study, the development of instructional games based on instructional games in science learning in grade V SD produced interactive media that met valid criteria with a percentage of 82.5% from the display aspect, 95% from the content aspect and 95% from the content aspect by the class teacher. So, it can be concluded that interactive learning media based on the instructional games model fulfills very valid criteria to be used as a science learning medium in grade V in elementary schools.Kata kunci : model instructional games, pembelajaran IPA
Cyber Threats and Attack Vectors during COVID-19

The ongoing world pandemic caused by COVID19 has had a significant impact on cyber incidents and has led to a sharp increase in cybercrime activity. The shift of a large proportion of users to remote work has increased their use of ICT systems. The inadequate observance of cyber-hygiene norms and low awareness has turned large parts of users into vulnerable groups, and the cybercriminals benefited from it. Cybercriminals started phishing campaigns using social engineering and COVID19 related issues. They have created fake online resources and content with the aim to infect users and spread malware. During the pandemic, phishing attacks increased significantly and became dominant. Cybercriminals use e-mail as the main source of malware, they also actively create fake online resources and applications that are as close as possible to real sought-after and up-to-date content. Not only the activity of cybercriminals for financial gain was revealed as one of the motives of cyber-attacks, but political purposes play a big part in it also. The number of attacks increased in all sectors, including governments, industry, healthcare, service providers, critical infrastructure, and consumers. The current trend in cyber-attacks has highlighted the importance of cybersecurity in modern challenges and business processes, across all areas. The level of user awareness and adherence to proper rules of cyber hygiene was manifested as an important and critical link. Because only at the technical level, even in the presence of cybersecurity controls, the user is a vulnerable and important group in the whole security chain.
UPAYA MENINGKATKAN HASIL BELAJAR SISWA DENGAN MENGGUNAKAN MODEL PEMBELAJARAN PROBLEM BASED LEARNING PADA PADA MATA PELAJARAN MATEMATIKA KELAS IV SDN 106788 PURWODADI KECAMATAN SUNGGAL KABUPATEN DELI SERDANG TAHUN PEMBELAJARAN 2018/2019

This study aims to increase student learning outcomes on mathematics subjects in the material measuring angles with standard units by applying the Problem Based Learning learning model at SDN 106788 PURWODADI, Sunggal District, Deli Serdang Regency. This type of research is Classroom Action Research. The subjects of this study were students of class IV-B, which amounted to 29 students consisting of 11 male students and 18 female students. This research was conducted in two cycles. Data from the results of this study were obtained from tests of student learning outcomes and observations.Based on the results of the study, it was shown that there was an increase in the learning outcomes of material students measuring angles with simple aircraft standard units by applying the Problem Based Learning learning model. This can be seen from improving student learning outcomes every cycle. In the pre-test of student learning outcomes carried out before the application of learning there were 4 students (32%) completed learning while 17 students (68%) had not yet finished with a grade point average of 50.93. In cycle 1 completeness of student learning outcomes there were 17 students (72%) completed in 8 students (28%) not yet completed with an average value of 70.4. The results of teacher observation amounted to 67.27% with a good category while the observations of students amounted to 64% with sufficient categories. Student learning outcomes have increased to 23 students (92%) completed 2 students (8%) have not been completed while the average value of 86.4. Teacher observation results have increased by 92.72% with very good categories while student observations amounted to 92% with very good categories. By looking at the percentage of learning outcomes and observations it can be concluded that the Application of Problem Based Learning Learning Models can improve student learning outcomes.
Closing the loop between mission design and navigation analysis

This research presents a contribution to the field of optimisation under uncertainty by proposing a nonlinear navigation analysis approach under both aleatoric and epistemic uncertainty. The navigation analysis is framed as a sequential filtering problem with an alternation of uncertainty propagation arcs and orbit determination instances. The state distribution is modelled as a mixture of kernels where the mixture weights are interval-valued to model the epistemic component. Specific techniques are discussed for Gaussian mixtures in particular. The uncertainty propagation step is solved by using Gaussian Hermite quadrature rules to compute the propagated means and covariances. The observation update is efficiently solved with a combination of variational inference and importance sampling, and a routine is developed to compute the posterior interval-valued weights. Given the distribution representation, lower and upper expectations of a generic quantity of interest are the solutions of linear programming problems and, therefore, are inexpensive to compute. The developed navigation analysis is finally applied to the robust quantification of the probability of impact of Europa Clipper with Jupiter’s moon Europa during one of its close flybys.
Stimulus generalizability of performance feedback training on metacognitive accuracy of visual working memory

In any moment, the quality and the quantity of information represented in visual working memory (VWM) is severely limited. Additionally, individuals tend to overestimate the accuracy of representations held in VWM, leading to confident-but-inaccurate responses (e.g., Adam & Vogel, 2017). Since it is difficult to improve the capacity of VWM, we instead aimed to improve the accuracy of metacognitive assessments of VWM representations. In the first experiment, participants remembered an array of simple objects (e.g., coloured squares or oriented lines) over a one second retention interval. Using a whole-report method (e.g., Adam & Vogel, 2016), participants then reported the colour or orientation of each object along with the confidence of their report. Importantly, performance feedback was given for each response to promote confident-and-accurate responses while discouraging confident-but-inaccurate responses. More precisely, confident-and-accurate responses led to larger reward points than not-so-confident-but-accurate responses, while confident-but-inaccurate responses resulted in larger penalty points than not-so-confident-and-inaccurate responses. Results demonstrated that in both younger and older adults, our feedback improved metacognitive accuracy for VWM representations, leading to a significant reduction of confident-but-inaccurate responses. Furthermore, this improvement was observed even after the performance feedback was removed. Interestingly, this training effect was more immediate and larger in magnitude when compared to a control experiment without feedback (Experiment 2). In Experiment 3, the training effect was found to generalize to an untrained stimulus. That is, when participants were given feedback training on one type of stimulus (e.g., colour) and then tested on the untrained stimulus (e.g., oriented lines), their metacognitive accuracy for the untrained stimulus was higher than before training. Therefore, we demonstrate that not only does feedback training improve metacognitive accuracy, but this training effect also generalizes to an untrained stimulus.
Integrating elements of data science into high-school teaching: Naïve Bayes-classification algorithm and programming in Python

Probability theory and mathematical statistics are traditionally one of the most difficult chapters of mathematics to teach. One of the authors, Péter Princz has experience in teaching various topics via computer programming of the problem at hand as a class activity. The proposed method is to involve programming as a didactic tool in hard-to-teach topics. The intended goal in this case is to implement a naïve Bayes-classifier algorithm in Python and demonstrate the machine-learning capabilities of it by applying it to a real-world dataset of edible or poisonous mushrooms. The students would implement the algorithm in a playful and interactive way. The proposed incremental development process aligns well with the spirit of Tamás Varga who considered computers as modern tools of experimental problem solving as early as in the 1960s.&#x0D; Subject Classification: 97D40, 97D50, 97K50, 97K99, 97M60, 97P40, 97P50, 97U50
Labor Movement of the Gunsan Region in the First Half of the 1920s - Focusing on the ‘Gunsan Labor Federation’ and Port Loading Labor Movement -

This thesis has taken a look at the labor movement in the Gunsan region after 1910 to the end of 1925 with the focus on the activities of Port Loading Labor Movement and Gunsan Labor Federation.BR The ‘Gunsan Labor Cooperative Association’ with the grain traders and local accommodations leading the way organized the laborers at the port works in the ports that were referred to as the miscellaneous workers force up to the point in a way of growing into the largest labor union in Gunsan. The ‘Gunsan Labor Association’ of Cho Yong-gwan who was a socialist for the Seoul Faction has significant implication in that the innovative labor union was organized around the laborers by abolishing the foreman-oriented system. And, the ‘Gunsan Labor Federation’ was the first local-based labor federation that organized by the innovative and conservative labor unions in unity. In addition, with the steady growth of the innovative forces, the Gunsan Railway Labor Association was organized as a leading innovative labor union.BR However, as shown conclusively by the conflict of the Gunsan Labor Cooperative Association and Gunsan Labor Association, the conflicts between the leaders of innovative and conservative labor unions around the workload between the labor unions in the same work field were emerged in confrontations. This was even more complicated deployment by integrating with the internal struggles of nationwide socialist factions.
LibGuides: UUNI100 Student FYE Infographic Project Guide: Infographic Design and Creation

The third major assignment for UUNI 100 is to create an FYE Infographic. This guide will assist you through the process. See some examples of formats, learn best practices for creating an infographic, and select an information creation tool. Also, consider additional content that it is permissible to add to make your infographic more eye-catching.
THE RUSSIAN LANGUAGE PIPELINE IN THE LIMA MULTILINGUAL ANALYZER

In this paper we describe the implementation of Russian language pipeline in LIMA multilingual analyzer and the results obtained in GramEval-2020 shared task. LIMA is a modular pipeline that implements rule-based and machine learning analysis components. Russian language pipeline includes deep neural networks based modules for tokenization, sentence segmentation, part of speech tagging, lemmatization and dependency parsing. Part of speech tags, feature tags and dependency trees conform to Universal Dependencies rules.
On the Sub-Gaussianity of the $r$-Correlograms

In this article, we show that the centered relay correlation function is a sub-Gaussian random variable. This is done by a careful analysis of its Laplace transform and by estimating the sub-Gaussian standard of the $r$-correlograms.
ANALISIS MOTIVASI DAN HASIL BELAJAR MATEMATIKA TERHADAP PEMBELAJARAN DARING PADA PESERTA DIDIK KELAS VII SMPN 5 KOTABARU

This study aims to determine the motivation and learning outcomes of students in class VII SMPN 5 Kotabaru after the application of online learning. The method used in this research is descriptive research with a qualitative approach that utilizes qualitative data and is described descriptively. Descriptive research aims to create a systematic, factual and accurate description, description of the facts, properties and relationship between the phenomena be`ing investigated. The results showed that the learning motivation of class VII students at SMPN 5 Kotabaru was categorized as high with an average score of 77% ant the learning outcomes of grade VII students at SMPN 5 Kotabaru after online learning could be categorized as good with an average 69,17. Motivations to learn is not the main factor in determining learning outcomes, but learning motivation is important for increasing optimal learning outcomes.&#x0D; &#x0D; Keywords: Learning Motivation, Mathematics Learning Outcomes, Online Learning.
Reseña del Seminario "Destreza, didáctica y descubrimiento con GeoGreba"

The development, main contributions and ideas arising at the Seminario Destreza, didactica y descubrimiento con GeoGebra, that took place at the Center for Mathematical Meetings, CIEM, of Castro-Urdiales, Cantabria, Spain, on December 22-24, 2019, are commented in this summary. The meeting was sponsored by the Federacion Espanola de Sociedades de Profesores de Matematicas (FESPM) and the Instituto GeoGebra de Cantabria (IGC). Three aspects of the use of GeoGebra in Spanish schools were addressed at the seminar: the skills involved in the design andd creation of GeoGebra constructions, the didactical considerations involved in the use of GeoGebra in the classroom, and the ways in which students develop mathematical competencies when using the program. Issues relatied to Evaulation were specially considered.
Evaluation of Denoising Filters Based on Edge Locations

This paper presents a method to evaluate denoising filters based on edge locations in their denoised images. Image quality assessment has often been performed by using structural similarity (SSIM). However, SSIM does not provide clearly the geometric accuracy of features in denoised images. Thus, in this paper, a method to localize edge locations with subpixel accuracy based on adaptive weighting of gradients is used for obtaining the subpixel locations of edges in ground truth image, noisy images, and denoised images. Then, this paper proposes a method to evaluate the geometric accuracy of edge locations based on root mean squares error (RMSE) and jaggedness with reference to ground truth locations. Jaggedness is a measure proposed in this study to measure the stability of the distribution of edge locations. Tested denoising filters are anisotropic diffusion (AF), bilateral filter, guided filter, weighted guided filter, weighted mean of patches filter, and smoothing filter (SF). SF is a simple filter that smooths images by applying a Gaussian blurring to a noisy image. Experiments were performed with a set of simulated images and natural images. The experimental results show that AF and SF recovered edge locations more accurately than the other tested filters in terms of SSIM, RMSE, and jaggedness and that SF produced better results than AF in terms of jaggedness.
Linear Histogram Adjustment for Image Enhancement

Tone curves are one of the simplest techniques for image enhancement. Specified as a function, a tone curve is a transformation that maps pixel levels of an input image to new output levels. Tone curves are the basis of many contrast enhancement algorithms, including Contrast Limited Histogram Equalisation (CLHE), which derives a tone curve from a modification of the image histogram. While these methods can provide good enhancement, they are generally non-linear. In this paper we show the surprising result that a tone curve generated by the non-linear CLHE method (and HE) can be calculated by applying a linear transform to the histogram of the input image. Experiments validate our method.
LibGuides: Free Cataloging Resources: Learning

A collection of free cataloging resources for New Mexico libraries, librarians and library staff Learn how to catalog library materials
Challenges of knowledge graph evolution from an NLP perspective

Knowledge graphs often express static facts, but concepts and entities change over time. In this position paper, we propose challenges that arise from the perspective of combining NLP and KG evolution in the digital humanities domain based on preliminary experiments.
Development of Learning Media for Word Square in Class V Science Subjects in Elementary Schools

DEVELOPMENT OF WORD SQUARE LEARNING MEDIA IN SCIENCE SUBJECT IN GRADEV IN ELEMENTARY SCHOOLS Mona Rahmadhanti¹, Hendra Hidayat¹,Daswarman¹ Elementary School Teacher Education Study Program Faculty of Teacher Training and Education Bung Hatta University e-mail :mrahmadhanti@gmail.com ABSTRAK This study aims to produce a word square learning media in science learning class V theme 5ecosystem component 1 learning ecosystem component 1 for grade V elementary school thatmeet very valid criteria. This type of research is research and development ( research anddevelopment). The research model used is ADD, namely analysis, design, and development. Inthis study, it only reached the development stage due to time constraints. This research wasconducted only until validation to material and media experts due to conditions. The researchinstrument includes a validation sheet. The word square learning media in science learning isvalidated by four people, of which two lecturers and two senior teacher are divided into onematerial expert and tree media expert. Based on the results of research on the development ofword square learning media for grade V elementary school students using the Aiken V formula,it fulfills very valid criteria with a value of 0,93 from the material aspect, 0,88 from the firstmedia aspect, 0,88 from the second media expert, and the third media expert is 0,90. So, it can beconcluded that the word square learning media fulfills the very valid criteria to be used as ascience learning medium in grade V in elementary school. Keywords : Development, Science Learning Media, Word Square Media
Where Is the Best Place To Buy A Cell Phone

Smartphones have conquered the world in a little over two decades, and today, our lives are unimaginable without them. You can buy them at every corner ...
Website optimization for mobile devices

The results of a research on the optimization of the site of the Central Scientific Agricultural Library for mobile devices are presented. A historical overview of the development of ‘mobile’ sites is given, various approaches to their creation are discussed. Specifications of various mobile devices, their features, methods for determining the fact of switching a user from a mobile version to a version for a personal computer and means for determining the characteristics of a particular device are analyzed. The changes in the process of adaptation for mobile devices of various sections of the library's website are revealed: the main site, search interfaces of databases, reference books, encyclopedias, and electronic libraries.
Peningkatan keterampilan menulis narasi melalui model pembelajaran cooperative integrated reading and composition pada mata pelajaran bahasa indonesia

The purpose of this research is to improve narrative writing skill through Cooperative Integrated Reading and Composition (CIRC) learning model on students fifth class of Laweyan No. 54 Surakarta Public Elementary School academic year 2018/2019. The form of  research is a classroom action research, conducted for two cycles with the planning, implementation, observation, and reflection on each cycle. Data collection techniques are using interviews, observations, tests, and documentation. Data validity technique is using triangulation. Data analysis techniques is interactive analysis  model that includes data reduction, data display, and conclusion rawing verification. The result of research showed that using CIRC learning model can improve narrative writing skill. The average score of each aspect of the students' narrative writing skills has increased, from 11.47 at the pretest, then after the action by applying CIRC to 13.56 in the first cycle, 80.11 in the second cycle and including the skilled category. The conclusion of this research is the narrative writing skills of fifth grade students of Public Elementary School Laweyan No. 54 Surakarta academic year 2018/2019 increases through the application of Cooperative Integrated Reading and Composition (CIRC) learning models. Keywords : Narrative text, writing skill, Cooperative Integrated Reading and Composition (CIRC).
Repeated Record Ordering for Constrained Size Clustering

One of the main techniques used in data mining is data clustering, which has many applications in computer science, biology and social sciences. Constrained clustering is a type of clustering in which side information provided by the user is incorporated into current clustering algorithms. One of the well researched constrained clustering algorithms is called microaggregation. In a microaggregation technique, the algorithm divides the dataset into groups containing at least members, where is a user-defined parameter. The main application of microaggregation is in Statistical Disclosure Control (SDC) for privacy preserving data publishing. A microaggregation algorithm is qualified based on the sum of within-group squared error, . Unfortunately, it has been proven that the optimal microaggregation problem is NP-Hard in general, but the special univariate case can be solved optimally in polynomial time. Many heuristics exist for the general case of the problem that are founded on the univariate case. These techniques order multivariate records in a sequence. This paper proposes a novel method for record ordering. Starting from a conventional clustering algorithm, the proposed method repeatedly puts multivariate records into a sequence and then clusters them again. The process is repeated until no improvement is achieved. Extensive experiments have been conducted in this research to confirm the effectiveness of the proposed method for different parameters and datasets.
Possible attempts to identify e-mail header of the sender for academic qualification fraud

This research aims to contribute to forensic counteractive measures that can identify and track the people who use e-mail for diploma mills. The authors had adopted e-mail forensic process to acquire, extract, analyse, and interpret data. The scope of this research included the empirical analysis from the experimental e-mails' headers using forensic tools and manual approach based on the request for comments (RFCs) as the primary guidelines. The study found that the commercial tool extracted headers less often than the free alternatives. E-mail sent from desktops provided the computer name and ISP of the sender. However, typical and anonymous e-mails can only trace back to the original mail servers. Although tools could provide investigators with ease and convenience, data acquisition and validation need to be done manually. This research is not the ad hoc mechanism, but it can be implemented in other criminal investigations or related endeavours.