Reviewerly/exHarmony huggingface dataset:
Teacher-Student Interaction Styles In The Electronic Environment Of Foreign Language Instruction

The paper considers the problem of teacher-student interaction styles in the process of online foreign language teaching at a university. Taking into account the inevitable integration of online classes into education and the aim to enhance the students’ innovative potential the authors set the goal to determine and describe the efficient communication styles for a teacher to interact with students in the electronic environment. Literature review and theoretical analysis allowed the authors to specify in detail characteristics of authoritarian, democratic and laissez-faire styles, which are applicable to online English as a Foreign Language (EFL) instruction. The characteristics are based on the four criteria: determining the components of online learning process, organizing online group activities, giving the online feedback, making online assessment. Using the given characteristics, a questionnaire was created to group students’ preferences into three categories. To obtain necessary data about students’ preferences related to online teacher-student interaction styles a survey was conducted among the students of National Research University of Electronic Technology (MIET), Moscow, Zelenograd, Russian Federation. The results of the survey show that students tend to prefer a democratic EFL teacher to communicate with online. Modern students are eager to participate actively in the education process organized in the electronic environment. To take into consideration their point of view and, therefore, to make the process of online EFL learning more effective, the authors recommend that the teachers maintain the so-called “subject-subject” or partnership relation with their students.
Analyzing the Interruption and Overlapping of the Debate between Trish Regan and Liu Xin

A debate is a reference to each other using a certain reason to state their views on things or problems, to expose the contradictions, and finally get the common understanding and opinions. Debate is a kind of verbal communication based on the premise of speculation, which is interactive and confrontational. In a conversation between two or more people, only one person speaks at the same time. There is no pre-determined conversion method, and the turn-taking is skillful. The interruption and overlapping are common in turn-taking. This paper aims to analyze the interruption and overlapping in the TV debate between Trish Regan and Liu Xin.
Finding Answers in a Text Document

Have you ever wanted to find the answer by looking at a paper? Nowadays, we can do that using the latest AI model. NLP techniques are improved drastically over the last years. With the latest transformer models, we can even find answers to questions in a text document. In this chapter, we will learn how to develop an iOS app that is powered with this technology. The smart application will be able to find and highlight the answer in a given document and also speak the answer using text-to-speech. You will be introduced to the state-of-the-art NLP model of 2018 called BERT. A question-answering app will be developed to learn how to use this model in iOS.
МЕТАМОДЕРНИЗМ И ДРУГИЕ КОНЦЕПЦИИ КУЛЬТУРЫ ПОСЛЕ ПОСТМОДЕРНИЗМА В КОНТЕКСТЕ МУЗЫКОВЕДЕНИЯ

In recent decades they talk a lot about the end of the postmodernism: they offer ideas of didgimodernism, cosmodernism and other. In this article author considers different conceptions from the position of musicology. The conception of metamodernism look most fruitful for music analyze: it talk about return of affect, oscillation, post-irony and search of new vertical.
Exploring Artist Gender Bias in Music Recommendation.

Music Recommender Systems (mRS) are designed to give personalised and meaningful recommendations of items (i.e. songs, playlists or artists) to a user base, thereby reflecting and further complementing individual users' specific music preferences. Whilst accuracy metrics have been widely applied to evaluate recommendations in mRS literature, evaluating a user's item utility from other impact-oriented perspectives, including their potential for discrimination, is still a novel evaluation practice in the music domain. In this work, we center our attention on a specific phenomenon for which we want to estimate if mRS may exacerbate its impact: gender bias. Our work presents an exploratory study, analyzing the extent to which commonly deployed state of the art Collaborative Filtering(CF) algorithms may act to further increase or decrease artist gender bias. To assess group biases introduced by CF, we deploy a recently proposed metric of bias disparity on two listening event datasets: the LFM-1b dataset, and the earlier constructed Celma's dataset. Our work traces the causes of disparity to variations in input gender distributions and user-item preferences, highlighting the effect such configurations can have on user's gender bias after recommendation generation.
Pengembangan bahan ajar gamifikasi pada relasi dan himpunan

The purpose of this study was to determine whether the development of gamification teaching materials in relation and function materials for class VIII students is appropriate and attractive for use in junior high schools. The test subjects in this study were students of class VII SMP in Kalianda. This research method is Research and Development (R&D), which uses the ADDIE development model. The results of the study were: the material expert's assessment gave an average percentage of 87% which was categorized as very feasible, the media expert gave a score with an average percentage of 86.75% which was categorized as suitable for use. In the small group trial, an average of 3.49 was obtained with the very attractive category. In the field trial, an average of 3.44 was obtained with the very interesting category. So it can be concluded that this gamification teaching material is categorized as very interesting and suitable for use in mathematics learning in junior high schools.
Constructing an electronic speckle pattern interferometry system for visualizing operational deflection shapes

Electronic speckle pattern interferometry (ESPI) is an effective optical method for visualizing operational deflection shapes of vibrating objects. The time-averaged ESPI method is used to show how an object vibrates when driven sinusoidally. We describe the construction of our system, which we built using standard optical components. Such a system is appropriate for both research and educational purposes. We will discuss the lessons learned by constructing several ESPI systems.
Knowledge Graph Anonymization using Semantic Anatomization.

As the usage of RDF-based Knowledge Graphs is going mainstream, it becomes necessary for organizations and companies to consider the privacy preservation of the data they are managing and possibly sharing. This is generally performed by anonymization techniques such as triple suppression and generalization. Nevertheless, these techniques have the drawback of reducing the utility of the released datasets. This paper presents semantic anatomization, a novel anonymization technique, that retains all quasi-identifier and sensitive values in the RDF graph. Due to an aggregating mechanism and the exploitation of the semantics contained in ontologies, this technique preserves data correlation and supports high quality analysis from anonymized graphs. We demonstrate the potential of semantic anatomization on large graphs generated from our own extension of the well-established Lehigh university benchmark.
The Effect of Online Gamification Learning on Students' Motivation and Students' Writing Descriptive Text

Online gamification learning is an imaginative methodology that expects to build manufacturing clients' commitment and motivation. The inspiration driving this assessment was to investigate the impacts of the utilization of online gamification learning on students’ motivation and students' writing descriptive text. The study was conducted at MTs. Mambaus Sholihin Gresik in class VIII I. To know whether online gamification learning is effective, the researcher utilized a pre-experimental method in which the information was tried by a statistical formula of t-test. The consequence of the exploration is the mean of the pre-test was 66.3810 and the mean of the post-test was 80.2143. The questionnaire appeared that students who agree with the method of online gamification learning have motivated and helped them in writing descriptive text. It can be concluded that the students' motivation and students’ accomplishment in writing descriptive text is improved when they are educated by online gamification learning.
Eye movements during the reading of narrative and poetic texts.

Video stream: https://vimeo.com/358415199&#x0D; Despite a wealth of studies using eye tracking to investigate mental processes during vision or reading, the investigation of oculomotor activity during natural reading of longer texts –be it newspaper articles, narratives or poetry– is still an exception in this field (as evidenced by the program of ECEM 2017 in Wuppertal). Following up on our symposium at ECEM 2017, here we bring together eye movement research on natural text reading to report recent progress in a coordinated way sharing data, experiences and software skills in this highly complex subfield. More specifically, in this symposium we will address several challenges faced by an eye tracking perspective on the reading of longer texts which involve a surplus of intervening variables and novel methods to analyze the data. In particular, the following issues will be addressed:&#x0D; - Which text-analytical and statistical methods are best to deal with the myriad of surface and affective semantic features potentially influencing eye movements during reading of ‘natural’ texts?&#x0D; - What are the pros and cons of using machine learning assisted predictive modeling as an alternative to the standard GLM/LMM frameworks?&#x0D; - Which kind of theoretical models can deal with the level of complexity offered by reading longer natural texts?&#x0D;
CNN-Based Image Style Transfer and Its Applications

Convolutional neural network is a variant of deep neural network. It is widely used to extract image features and used in image classification, image generation and style transfer. In the style transfer task, we can extract the content from one picture through the convolutional neural network, extract the style from another picture, and generate a new picture by the combination. In this paper, we show the general steps of image style transfer based on convolutional neural networks through a specific example, and discuss the future possible applications.
Designing with Sound to Reduce Motion Sickness in VR

Motion sickness has been a significant obstacle for the development of Virtual Reality technology since the beginning of its existence. Research has shown that audio can be used to reduce motion si ...
LibGuides: Digital Learning Guide: Maintain Communication

This guide was created as part of emergency planning in case we need to close school for weeks at a time
How to Integrate Chinese Culture into College English Teaching under the Belt and Road Initiative

The proposal of the “Belt and Road” Initiative plays an important role in promoting economic prosperity and regional economic cooperation among countries along the route, strengthening civilization exchanges, and promoting the development of world economy and trade. As a universal language in the world, English is very important for promoting cultural exchanges between countries. Therefore, China is paying more and more attention to the development of college English teaching. This article explains the necessity of integrating Chinese culture into English teaching in colleges and universities under the background of the “Belt and Road” initiative, analyzes the current situation of Chinese culture in college English teaching, and explores the integration of Chinese teaching into Chinese culture to develop Chinese culture and cultivate diverse and high-quality English talents for the country.
Python Foundations: Data Science for All

The Python Foundations seminar emphasizes a hands-on approach and is designed to reach a diverse student population to provide them with the entry-level programming skills required in data science. The creation of the seminar materials has been funded by a three-year federal grant and has followed a systematic approach to enhance the student learning experience and raise student awareness of data science. The seminar materials—structured in three parts: pre-seminar, live seminar, and post-seminar—are licensed under the Creative Commons Attribution-ShareAlike 4.0 International license to encourage adoption by any institution. To foster interest in the seminar, students have the possibility to earn a digital badge attesting to their newly acquired skills.
Hybrid image denoising based on region division

This paper proposes an efficient hybrid framework for image denoising, in which the advantages of different denoising methods are effectively incorporated by using the region prior knowledge. In detail, the input noisy image is first divided into a large number of overlapping patches followed by extraction of Speed Up Robust Feature (SURF), and then the noisy patches are classified into two categories based on Twin Support Vector Machine (TWSVM). The texture patches are enhanced via Gradient Histogram Preservation (GHP) while flat patches can be re-established using Block Matching Three-Dimensional Filtering (BM3D). Finally, the re-established images can be acquired by fusing the processing results of the two kinds of patches. To evaluate the effectiveness of the presented method, we conduct experiments on standard image datasets and compare the performance with other outstanding denoising approaches. Experimental results show that the presented method achieves better results, especially in containing textures and edges compared with existing image denoising methods.
Towards the design of an assurance framework for increasing security and privacy in Connected Vehicles

Intelligent transport systems (ITS) play a key role in our daily activities. ITS development over the last decades has been based on the rapid evolution of information and communication technologies (ICT), which include processing capabilities, availability of hardware and communication technologies. However, as the development of ITS services increases so does the users' awareness regarding the degree of trust that they demonstrate on adopting this kind of services. This has brought to light several security and privacy concerns that ITS analysts should consider when designing and implementing various IT related services. This paper identifies how risk analysis can interact with security and privacy requirements' engineering world, in order to provide a holistic approach for reasoning about security and privacy in such complex environments like ITS systems.
PENERAPAN METODE PIPOLANDO PADA PEMBELAJARAN PENGENALAN KONSEP BILANGAN ANGKA ANAK USIA DINI

One aspect of early childhood development that needs to be developed is cognitive abilities. One of the cognitive development that must be possessed by children is to understand the concept of numbers. The purpose of the ability to recognize the concept of numbers is to find out the basics of learning numbers so that in time the child will be better prepared to follow numeracy learning at the next level which is more complex. Numbers in everyday life, the knowledge of numbers has been introduced to children from an early age in the right way.This study was entitled The Application of the PIPOLANDO (Ping, Poro lan Sudo) Method in Learning to Introduce the Concept of Early Childhood Numbers. This research used qualitative research, type field research (field research), with a qualitative descriptive approach. The purpose of this study was to determine the process of applying the PIPOLANDO method (Ping, Poro lan Sudo), in learning the introduction of the concept of early childhood numbers in group A PAUD.TK QILPI Al Wahab Sungelebak.The results of this study indicated the application of PIPOLANDO in learning activities to introduce the concept of numbers in group A QILPI Kindergarten Al Wahab Sungelebak Karanggeneng Lamongan was done through several activities: a) starting with the initial activity of reading classically PIPOLANDO visual aids, and then b) individual activities in the class , where one by one, the children were asked to read PIPOLANDO material books by the teacher. T hrough the application of the PIPOLANDO method it can be said that children experienced good development in recognizing the concept of numbers. This was shown by data from a total of 25 students there, almost all children had developed very well. As for the lack of application of the PIPOLANDO method, it took a long time to master the learning targets during the learning process.
Cuneiform Clay Tablets Texts Elicitation Using Modified Wavelet Transform, Discrete Cosine Transform & Cuckoo Algorithm

The Sumerian was one of the most famous Ancient Iraqi civilization which dates is go back to five thousand years B.c. The Sumerians established the first urban cities in ancient history. One of their most important productions in that period was the invention of the cuneiform system.   This represented a fundamental turning point in the history of that civilization, the cuneiform writing is documented on the surface of clay tablets, and these tablets represent the primary source and essential database for researchers in archeology and ancient linguistics. The interpretation of Sumerian manuscripts is affected by a variety of challenges, clay is a material subject to change due to environmental factors, and it can be corroded, damaged and affected by moisture and improper preservation methods, which leads to the loss of information documented on it. This article offers a method of obtaining the cuneiform script. The current model uses multiple techniques, such as the Discrete Transform Wavelet, Discrete Transform Cosine (DCT) and Cuckoo Search Algorithm (CS). Our method gives an easy, reliable and efficient direction to refine the cuneiform symbolism.Keywords-Discrete Wavelet Transform (DWT), Discrete cosine transform (DCT), Cuckoo Search Algorithm (CS), Image Enhancement and Cuneiform Tablets.
Youth Communities Interaction in the Scientific Environment

Russian scientific schools, as special phenomenon, which formation is a consequence of the cultural and historical development of country, cannot develop in isolation: close interaction between researchers of all levels and ages is necessary. In the conditions of the development of the information society and the emerging knowledge society, not only the involvement of young people in science, but also the interpersonal interaction of young scientists who are representatives of various scientific schools and professional communities is of particular relevance.
On Optimal Surface Voting for Automatic Fault Attribute Refinement and Some Strategies for Improvement

Summary Fault-highlighting attribute has been an essential source of information in practice that can help reveal important subsurface structural features and expedite the entire interpretation process, especially in large exploration areas. We revisit the recently proposed optimal surface voting workflow that can be used to refine any input fault-highlighting attribute to unprecedented resolution and present three strategies for improvement including probabilistic seed point selection, uniformly distributed window size, and iterative voting. These modifications rely on statistical concepts and in principle, can reduce users’ bias in key parameter selection, which is previously present in the original workflow. Our preliminary results have suggested that our approach can further enhance major (large-scaled) fault trends, while suppressing small-scaled features that may not be associated with actual faults in the input attribute.
Triplet erasing-based data augmentation for person re-identification

Occlusion is a fundamental but challenging problem in person re-identification. Previous work like random erasing randomly selects a rectangle region in an image and erases its pixels with random values without considering the correlation between images when triplet loss is employed. To address the problem, we propose an end-to-end approach called triplet erasing-based data augmentation for person re-identification (ReID). We apply this approach to train a convolutional neural network (CNN) with two branches. Local distance branch determines the location of the part that needs to be erased in the image, and then triplet erasing branch erases a rectangle region in the determined part. By generating a variety of occlusion samples, triplet erasing improves the robustness of the model against occlusion. Triplet erasing can increase the distance between the positive sample pairs and decrease the distance between the negative sample pairs, thereby improving the generalisation ability of the network.
'HEDGING' AND GENDER IN PARTICIPATORY DESIGN

There has been much dispute over the role 'hedging'equivocation in expressing opinions -plays in group conversation as well as the impact of gender on a range of processes including Participatory Design; (Holmes, 1986, Dixon and Foster, 1997, Stokoe and Smithson, 2001, Stokoe and Weatheral, 2002, Brulé, E. and Spiel, K. (2019),).This paper addresses these issues by analysing gender differences and hedging in an Innovation Participatory Design workshop focused around the creation and combination of ideas for app development.Discussions were transcribed and analysed; 'hedging' terms seemed an interesting theme for analysis, but no statistical significance was found to prove that 'hedging' was gender-biased.This initial, exploratory, short paper reflects on this finding; on the contrast with research that has found gender differences (Holmes, 1986); on the importance of supplementing statistical with contextual forms of analysis; and what effect or implications this may have on the process of Participatory Design, by acknowledging the importance of giving voice and parity, and trying to facilitate group dynamics that properly reflect the views of all participants.
No Feature Is An Island: Adaptive Collaborations Between Features Improve Adversarial Robustness

To classify images, neural networks extract features from raw inputs and then sum them up with fixed weights via the fully connected layer. However, the weights are fixed despite the input types. Such fixed prior limits networks' flexibility in adjusting feature reliance, which in turn enables attackers to flip networks' predictions by corrupting the most brittle features whose value would change drastically by minor perturbations. Inspired by the analysis, we replace the original fixed fully connected layer by dynamically calculating the posterior weight for each feature according to the input and connections between them. Also, a counterfactual baseline is integrated to precisely characterize the credit of each feature's contribution to the robustness and generality of the model. We empirically demonstrate that the proposed algorithm improves both standard and robust error against several strong attacks across various major benchmarks. Finally, we theoretically prove the minimal structure requirement for our framework to improve adversarial robustness in a fairly simple and natural setting.