Reviewerly/exHarmony huggingface dataset:
Personal Orientation of Educational Activities as a Basis for the Development of Professional Orientation of Students of Pedagogical Specialties

This article is devoted to the development of professional orientation of students of pedagogical specialties. Based on the works of I.S. Yakimanskoy, E.V. Bondarevskaya, A.A. Melik-Pashayeva, I.N. Semenova, V.K. Zaretsky and other researchers, the authors clarified the principles of personal orientation of educational activities that contribute to the development of the professional orientation of students of pedagogical specialties at the university. The article also presents the author's complex of pedagogical conditions ensuring the development of the professional orientation of students of pedagogical specialties in a higher educational institution. The complex includes the following components: identification and formation of value orientations of students of pedagogical specialties; creating in higher education educational environment that promotes self-realization of the individual; accounting of students' subject experience; development of pedagogical abilities of future teachers; development of professional skills of university teachers as the basis for the formation of professional orientation of students of pedagogical specialties. The article also describes the results of experimental work, which confirmed the effectiveness of the developed complex of pedagogical conditions that ensure the development of the professional orientation of students of pedagogical specialties in a higher educational institution on the basis of personal orientation of educational activities.
Joint Training for Learning Cross-lingual Embeddings with Sub-word Information without Parallel Corpora

In this paper, we propose a novel method for learning cross-lingual word embeddings, that incorporates sub-word information during training, and is able to learn high-quality embeddings from modest amounts of monolingual data and a bilingual lexicon. This method could be particularly well-suited to learning cross-lingual embeddings for lower-resource, morphologically-rich languages, enabling knowledge to be transferred from rich- to lower-resource languages. We evaluate our proposed approach simulating lower-resource languages for bilingual lexicon induction, monolingual word similarity, and document classification. Our results indicate that incorporating sub-word information indeed leads to improvements, and in the case of document classification, performance better than, or on par with, strong benchmark approaches.
학교문화예술교육 정책의 변천과정과 개선방안 연구 - 학교 무용 예술강사 지원사업 중심으로

The purpose of this study is to review the introduction and changes of the project for the support of a school dance arts instructor, and to suggest ways to improve the school dance arts lecture support project in the transition period. In addition to related academic materials, there are policy research reports, business presentation materials, business result reports, workshop materials, and forum materials that were used in order to grasp the concrete aspects of the school culture art education policy. The results of this study are as follows: First, in terms of administrative and financial aspects, it appeared that there was a budget shortage in the school arts instructor support project and an unstable working environment system for the art instructor. Accordingly, it was suggested to avoid short-term event-oriented business and secure a stable time for the art instructor and to arrange them consistently. Second, it is suggested to use the cooperation method of ensuring independent space and operating a dance education program suitable for the curriculum in terms of educational environment and facilities. Third, in terms of support for the activities of the school dance arts instructor, ways to improve treatment, promote morale, and develop various dance education programs are suggested. Fourth, in terms of manpower training and retraining, the study proposes a method to establish a dance philosophy of a the preceding dance arts instructor, to expand the training period of a new instructor, to secure the expertise of the existing art instructor, and to strengthen capacity.
The Digital Student : Beyond the Boundaries of the Body

The Digital Student: Beyond the Boundaries of the BodyEva Alerby & Niclas EkbergResearch topic and aimIn the Nordic countries, as in many other countries in the world, there has been a massive ...
Calibration tests beyond classification

Most supervised machine learning tasks are subject to irreducible prediction errors. Probabilistic predictive models address this limitation by providing probability distributions that represent a belief over plausible targets, rather than point estimates. Such models can be a valuable tool in decision-making under uncertainty, provided that the model output is meaningful and interpretable. Calibrated models guarantee that the probabilistic predictions are neither over- nor under-confident. In the machine learning literature, different measures and statistical tests have been proposed and studied for evaluating the calibration of classification models. For regression problems, however, research has been focused on a weaker condition of calibration based on predicted quantiles for real-valued targets. In this paper, we propose the first framework that unifies calibration evaluation and tests for probabilistic predictive models. It applies to any such model, including classification and regression models of arbitrary dimension. Furthermore, the framework generalizes existing measures and provides a more intuitive reformulation of a recently proposed framework for calibration in multi-class classification.
On the Dynamics and Computed Torque Control of an Asymmetric Four-Limb Parallel Schonflies Motion Generator

In this paper, the application of cloud computing in the field of robotics is described. Dual robots are assigned the job of picking up objects lying on the floor and to keep them in the given spaces. In the co-operative environment both the robots try to follow their route of shortest path till such situations arise when either the object or the space has been exhausted. Then the robot searches for the next nearest object or space or the remaining object or space and act accordingly.
Zero-Knowledge Agent Trained for the Game of Risk

Recent developments in deep reinforcement learning applied to abstract strategy games such as Go, chess and Hex have sparked an interest within military planning. This Master thesis explores if it ...
Semi-Supervised Cleansing of Web Argument Corpora.

Debate portals and similar web platforms constitute one of the main text sources in computational argumentation research and its applications. While the corpora built upon these sources are rich of argumentatively relevant content and structure, they also include text that is irrelevant, or even detrimental, to their purpose. In this paper, we present a precision-oriented approach to detecting such irrelevant text in a semi-supervised way. Given a few seed examples, the approach automatically learns basic lexical patterns of relevance and irrelevance and then incrementally bootstraps new patterns from sentences matching the patterns. In the existing args.me corpus with 400k argumentative texts, our approach detects almost 87k irrelevant sentences, at a precision of 0.97 according to manual evaluation. With low effort, the approach can be adapted to other web argument corpora, providing a generic way to improve corpus quality.
Constrained Weight Optimization for Learning without Activation Normalization

Weight Normalization (WN) is an essential building block in deep learning. However, even state-of-the-art WN methods need to be combined with activation normalization methods, such as Batch Normalization (BN), to provide the same classification accuracy as BN. In this paper, we aim to circumvent this issue with a weight normalization approach that can be used on its own to provide a classification accuracy competitive to BN. Our approach mimics three fundamental properties of BN, namely, keeping the norm of the weights constant, setting the mean of the weights to zero, and simulating stochastic perturbations due to batch sampling bias. Unlike most of the existing WN methods that rely on "reparametrization", our method directly optimizes the weights with proper constraints and thus can circumvent its serious drawback, gradient explosion. Moreover, we propose an efficient and easy-to-implement algorithm to solve our constrained optimization problem without sacrificing its benefits. The results of classification experiments on three popular benchmark datasets demonstrate that our method is highly competitive with or even better than the state-of-the-art normalization methods.
Machine Learning Basics

Nowadays, artificial intelligence (AI) is one of the most fascinating fields of computer science in addition to blockchain and quantum computing. Hype since the mid-2000s in the industrial community has led to large amounts of investments for AI startups. Globally leading technology companies such as Apple, Google, Facebook, and Microsoft, just to name a few, are quickly acquiring talented AI startups from all over the world to accelerate AI research and, in turn, improve their own products.
A Resilience and Innovative Personal Potential of Students

Aim and problem. The article is devoted to the problem of the correlation between the resilience and the innovative personal potential on the example of a student sample. The authors describe resilience as a dynamic system of individual psychological qualities, life meanings and personal relations, which determine the specifics of its response to changing conditions. Methodology. An empirical study was carried out on a sample of students of the Novosibirsk State Technical University (N = 164) using the psychological tests of a resilience by M. Ungar and A. V. Makhnach, test of an innovative personal potential by Yu. A. Vlasenko, V. K. Kalin, test of a self-esteem of an innovative traits by N. M. Lebedeva, A. N. Tatarko. Results of research. Correlation analysis using Spearman’s Rs criterion showed the correlation between the integral indicator of an innovative personal potential with the general level of a resilience, relational resilience (test ARM), self-efficacy, coping and adaptation (A. V. Makhnach’s test), as well as the presence of many correlations between a resilience and innovative qualities. As a result of the regression analysis, it was found that the innovative personal potential of university students depends on the general level of a resilience and coping and adaptation skills, and the self-perception of innovativeness depends on the general level of a resilience. In a conclusion authors confirm the correlation between the resilience and the innovative personal potential of students.
Generating handwritten digits with generative adversarial networks

In Chapter 9, we delved into the generative and creative side of deep learning. There, we used two recurrent neural networks to forecast and generate classical-looking passages of text. But text data, or generally speaking, sequential data, is not the only thing that these neural networks can create. Images are possible too.
MENINGKATKAN EFEKTIFITAS HASIL BELAJAR SISWA MELALUI SISTEM PENDIDIKAN 4 JAM PEMBELAJARAN PADA JENJANG SMA

Full Day school is an education system that carries out a full-day learning process that starts from 6:45 until 3:00. Behind the advantages of the 2013 curriculum that allows productive students to study in school for a long time. The system also has a weakness that is quite influential on students that is not effective in providing rest time for the brain. The system might cause students to become bored, tired and feel burdened because they have to study for the duration of that long. This study aims to discuss how the planned forms of innovation provide solutions to the ineffectiveness of the education system in the 2013 curriculum and about how the 4-hour learning innovation system in one day as a form of the effectiveness of learning outcomes. This system has a disadvantage that is quite influential on students that is not effective in providing rest time for the brain. The system might cause students to become bored and feel burdened because they have to study for the duration of that long. The research method used is descriptive qualitative by examining several data sources and analyzing and comparing existing innovations with previous research. The development of this innovation is that it can reduce the burden of students' minds from the 2013 curriculum education system by using a 4-hour learning design to focus students on learning some subjects they want to master, it is supported by holding reflections on student learning outcomes so that teachers can evaluate how development learners learn from the teaching and learning process that has taken place.
A Corpus-based Study on the Keyword of Airline Safety English: Focused on Safety Report Published by IATA

The purpose of this study is to suggest the implications for ESP learners based on Corpus by constructing and analyzing the Airline’s Safety Report published by IATA. Linguistic corpus for ESP study has been researched a lot, as it was frequently applied to English education. Listing the high-frequent vocabulary is essential for ESP learners. So it could be an efficient approach to introduce contents for ESP-related discipline. Therefore, annual safety reports for the last 5 years have been collected to make a list and extracted from corpus program called AntConc 3.5.8. The total number of word types from text was 7820 while 301,914 token numbers were shown. First of all, top 50 vocabulary list was extracted according to the order of high frequency. Secondly, lexical bundle list was extracted with 2, 3 and 4 words. Lastly, the concordance list of vocabulary ‘risk’ and ‘safety’ was checked. Through the results of this research, developed lists could be used as a useful tool for those who are studying in Aviation service major at college in the ESP classes or who is about to fly under the training at airlines. Compared to the importance and interest in aviation safety, this study presented a list of major vocabulary based on a language data analysis program in a situation where there was almost no research on related Airline Safety English.
Drift anticipation with forgetting to improve evolving fuzzy system

Working with a non-stationary stream of data requires for the analysis system to evolve its model (the parameters as well as the structure) over time. In particular, concept drifts can occur, which makes it necessary to forget knowledge that has become obsolete. However, the forgetting is subjected to the stability-plasticity dilemma, that is, increasing forgetting improve reactivity of adapting to the new data while reducing the robustness of the system. Based on a set of inference rules, Evolving Fuzzy Systems - EFS - have proven to be effective in solving the data stream learning problem. However tackling the stability-plasticity dilemma is still an open question. This paper proposes a coherent method to integrate forgetting in Evolving Fuzzy System, based on the recently introduced notion of concept drift anticipation. The forgetting is applied with two methods: an exponential forgetting of the premise part and a deferred directional forgetting of the conclusion part of EFS to preserve the coherence between both parts. The originality of the approach consists in applying the forgetting only in the anticipation module and in keeping the EFS (called principal system) learned without any forgetting. Then, when a drift is detected in the stream, a selection mechanism is proposed to replace the obsolete parameters of the principal system with more suitable parameters of the anticipation module. An evaluation of the proposed methods is carried out on benchmark online datasets, with a comparison with state-of-the-art online classifiers (Learn++.NSE, PENsemble, pclass) as well as with the original system using different forgetting strategies.
Improved fast phase unwrapping algorithm based on parallel acceleration

Aiming at the shortcoming of low serial operational efficiency in the quality-map-guided phase-unwrapping algorithm proposed by Miguel, an improved algorithm for parallel merging of multiple low-reliability blocks is pro-posed. Under the condition that the original algorithm design idea is satisfied, the unwrapping path is redefined as the largest reliable edge of the block. In addition, based on the non-continuous characteristic of the unwrapping path of the original algorithm, a low-reliability block out-of-order merging strategy is proposed to make multiple merging tasks can be performed simultaneously. The improved algorithm uses a multi-threaded software architecture. The main thread is responsible for looping through the unprocessed blocks to check whether they meet the requirements of merging, and the child threads receive and perform the merge tasks. The experimental results show that the improved method is completely consistent with the processing results of the original algorithm, and the parallel improvement strategy can effectively use the computer's multi-core resources, so that the operational efficiency of the phase unwrapping algorithm is improved by more than 50%.
IMPOLITENESS COMMENTING ON INSTAGRAM ”KEKEYI”

This study aims to find the impoliteness strategies in the commenting of Instagram. The source of the data is taken from Instagram account “Kekeyi” a beauty vlogger who viral because of her uniqueness “using water balloon as sponge” and her controversy in social media. These situation make her get Bullying from her followers. The harassment and impolite language cannot be avoided in the commenting of Kekeyi’s Instagram. By identifying and analyzing of all the data, the writer found that there are three strategies of impoliteness language used by the followers. They are bald on record, positive impoliteness and negative impoliteness. Based on the data, the writer also found that positive impoliteness as the dominant strategy used by her followers. The use of the three strategies seems as the way of her follower to show their disappointment toward what Kekeyi did in her posting and caption were not what they expected. Studying of language impoliteness is very important to avoid verbal bullying in social media.
Peningkatan Hasil Belajar Model Inkuiri Terbimbing Materi Pertumbuhan dan Perkembangan di SMP Negeri 17 Palembang

The purpose of this study is to see an increase in learning outcomes in the material growth and development in class VIII Junior High School Number 17 Palembang. This research is a quantitative research using quasi-experimental method design (Quasi Experimental). The design of this study used a preliminary test design and a final test. Based on the average value of the final class test using the Guided Inquiry learning model that is 76.90 is greater than the average value of the class using the lecture method that is 63.70. Then the analysis of the results of the t test calculation is obtained (t-count 6.777 while df (free degree) is 57.983, the significance is 0.000. So 6.777&gt; 1.671 means Ha is accepted because the t-value is greater than the t-table value. And the probability is smaller than 0.05 values the significance is 0.05. So it can be concluded that learning using the Guided Inquiry learning model there is an increase in learning outcomes in the growth and development material of VIII grade students of Junior High School Number 17 Palembang.
Subject Guides: Kanopy: How Do I Access Kanopy Off Campus?

This guide is used to assist City Tech users on accessing and requesting videos through the library's subscription to Kanopy.
E-SAMPAH BERBASIS MOBILE SEBAGAI MEDIA PENGELOLAAN SAMPAH

Waste is identical to dirty, the source of flood, the source of disease, the source of pollution and various other sources of problems. Every day, the amount of waste is not decreasing but is piling up and is directly proportional to the population growth and economy of the city of Pekalongan. The application of information technology combined with a populist economic approach by involving the community and existing groups/communities, will certainly have a positive impact and provide multiple benefits, namely for the Pekalongan city government and for the community/groups communities involved. There are several benefits gained by the Pekalongan city government, such as: assisted in dealing with the problem of waste which is still constrained by the limited garbage collection area, the number of garbage officers, the number of garbage transport vehicles and the number of waste processing equipment; assisted in opening up new jobs/sources of income for the community; and helped to change the culture of the community in treating waste and littering habits. While the benefits for the community/groups/communities involved are in increasing the income derived from waste. The e-waste application has a good business prospect, because this application can be utilized by city/regional governments in Indonesia in managing waste while providing multiple benefits, namely for the city / regional government and for the people involved. Keywords: Waste Bank, Waste, E-Waste
Quality Estimation for Machine Translation with Multi-granularity Interaction

Quality estimation (QE) for machine translation is the task of evaluating the translation system quality without reference translations. By using the existing translation quality estimation methods, researchers mostly focus on how to extract better features but ignore the translation oriented interaction. In this paper, we propose a QE model for machine translation that integrates multi-granularity interaction on the word and sentence level. On sthe word level, each word of the target language sentence interacts with each word of the source language sentence and yields the similarity, and the $$L_\infty $$ and entropy of the similarity distribution are employed as the word-level interaction score. On the sentence level, the similarity between the source and the target language translation is calculated to indicate the overall translation quality. Finally, we combine the word-level features and the sentence-level features with different weights. We perform thorough experiments with detailed studies and analyses on the English-German dataset in the WMT19 sentence-level QE task, demonstrating the effectiveness of our method.