Reviewerly/exHarmony huggingface dataset:
Towards Non-task-specific Distillation of BERT via Sentence Representation Approximation

Recently, BERT has become an essential ingredient of various NLP deep models due to its effectiveness and universal-usability. However, the online deployment of BERT is often blocked by its large-scale parameters and high computational cost. There are plenty of studies showing that the knowledge distillation is efficient in transferring the knowledge from BERT into the model with a smaller size of parameters. Nevertheless, current BERT distillation approaches mainly focus on task-specified distillation, such methodologies lead to the loss of the general semantic knowledge of BERT for universal-usability. In this paper, we propose a sentence representation approximating oriented distillation framework that can distill the pre-trained BERT into a simple LSTM based model without specifying tasks. Consistent with BERT, our distilled model is able to perform transfer learning via fine-tuning to adapt to any sentence-level downstream task. Besides, our model can further cooperate with task-specific distillation procedures. The experimental results on multiple NLP tasks from the GLUE benchmark show that our approach outperforms other task-specific distillation methods or even much larger models, i.e., ELMO, with efficiency well-improved.
Fractal Dimension Generalization Measure

Developing a robust generalization measure for the performance of machine learning models is an important and challenging task. A lot of recent research in the area focuses on the model decision boundary when predicting generalization. In this paper, as part of the "Predicting Generalization in Deep Learning" competition, we analyse the complexity of decision boundaries using the concept of fractal dimension and develop a generalization measure based on that technique.
MALE STUDENTS’ READING COMPREHENSION DIFFICULTIES

The purpose of this research is to find out the factors that influence male students' reading comprehension difficulties on Procedure text at X Class of Madrasah Aliyah Khairul Ummah Islamic Boarding School Batu Gajah. The researcher used Descriptive Analysis Research. In this research, researcher wants to describe the factors that influence male students' reading comprehension difficulties on procedure text at X class of Madrasah Aliyah Khairul Ummah Islamic Boarding School Batu Gajah. This research used the formulation total percentage of the result Internal factors and External factors. Internal factors that are Intelligence got 71%, readiness got 48% and interest 75%. The most internal factor that influence male students’ reading comprehension difficulties on procedure text at the first grade is interest. The external factors that are Family got 20%, school got 26%, and society got 35%. The most eksternal factor that influence male students’ reading comprehension difficulties on procedure text is society.
METODE TPR (TOTAL PHYSICAL RESPONSE) DALAM PEMBELAJARAN BAHASA INGGRIS PADA ANAK USIA DINI

This literature study reviews about the use of TPR (Total Physical Response) method in early childhood English learning. TPR method is considered as one of the most suitable method for introducing and teaching English as foreign language to early childhood. This method is designed according to the early childhood development stages and how to they learn language. Teaching English using this method tries to teach English through physical movement. This method uses a comprehensive approach that emphasizes more on early childhood’s listening skills, speaking, and physical movement. O the other words, this method is built based on the coordination of speech/language and physical movement. Using this method, teacher introduces English vocabularies in the form of commands that are able to do by the children’s movement. In teaching English using this method, teacher also can use real object, realia, poster, picture, and flashcard. Furthermore, this method can be combined with other teaching methods, such as: games, song and movement, storytelling, etc. There are some benefits using this method on teaching English as a foreign language to early childhood.
ДІЯЛЬНІСТЬ КОНЦЕРТМЕЙСТЕРА В НАВЧАЛЬНОМУ ПРОЦЕСІ ЗАКЛАДІВ ВИЩОЇ ОСВІТИ

The purpose of the article is to clarify tasks and specifics of the accompanist’s modern training activity at higher education institutions. We have used the following methods to achieve the goal. The analogue method is to identify difficulties in the work of the accompanist. The retrospective method is to understand the profession of accompanist. The personalisation method shows the great accompanists’ contribution to the development of this profession. The hermeneutic method grants the work with primary sources of information, their selection and systematisation. The syncretic method is to highlight the features of accompaniment art and all its components. The scientific novelty of the article is to determine the key features of the accompanist’s work at present; summarise the theoretical and practical experience of famous researchers and the article’s author who is a representative of this profession; to provide look-back analysis of the complexities and advantages of the accompanist’s profession during the 20th – early 21st centuries. Conclusions. We have clarified the tasks and specifics of the accompanist’s activity in the modern educational process at the higher education institutions. Using the previous data of scientific works of known scientists and accompanist’s cases we have covered the most difficult technologies of work of the accompanist. The article focuses mostly on the professional training and level of the artistic culture of the accompanist, the ability to work with vocalists, deep understanding of the music piece, which encourages the vocalist to work together, know the musical and poetic text of the vocal work perfectly, work on articulation, beat and rhythm, use means of musical expression, artistic performance, vocal breathing – all the components that affect the result of the collaboration between the vocalist and the accompanist.
The University of Tokyo’s Submissions to the WAT 2020 Shared Task

The paper describes the development process of the The University of Tokyo’s NMT systems that were submitted to the WAT 2020 Document-level Business Scene Dialogue Translation sub-task. We describe the data processing workflow, NMT system training architectures, and automatic evaluation results. For the WAT 2020 shared task, we submitted 12 systems (both constrained and unconstrained) for English-Japanese and Japanese-English translation directions. The submitted systems were trained using Transformer models and one was a SMT baseline.
Towards a Conceptual Description of Verbs

Abstract Our work is focused on the conceptual description of verbs by employing two main resources – the lexical semantic network WordNet and the conceptual frames from FrameNet. We implement a method for inheritance-based mapping between the two resources by transferring the frame assignments from a hypernym to its hyponyms. We discover that the method performs best for directly related pairs of synsets but deteriorates in assignment at two or more steps. The mapping is then used for enhancing each of the resources by expanding it with new entries and by contributing to the resources’ relational structure.
A New Parameterized Model for Determining Quality of Online Video Service Using Modern H.265/HEVC and VP9 Codecs

This paper describes a new measurement method (VS model) for determining the quality of online video services relying on modern H.265/HEVC and VP9 codecs. The said method has been developed on the basis of VQuad-HD curves (according to ITU-T J.341). This model does not refer to signal analysis, but protocol analysis instead. The parameters used are: type of video codec, encoding rate, transport technique, packet loss and burst size. The method may be implemented quickly and easily, which is one of the great advantages when using this method to measure QoS.
State-dependent Routing Dynamics in Noisy Quantum Computing Devices

Routing plays an important role in programming noisy, intermediate-scale quantum (NISQ) devices, where limited connectivity in the register is overcome by swapping quantum information between locations. However, routing a quantum state using noisy gates introduces non-trivial noise dynamics, and deciding on an optimal route to minimize accumulated error requires estimates of the expected state fidelity. Here we validate a model for state-dependent routing dynamics in a NISQ processor based on correlated binary noise. We develop a composable, state-dependent noise model for CNOT and SWAP operations that can be characterized efficiently using pair-wise experimental measurements, and we compare model predictions with tomographic state reconstructions recovered from a quantum device. These results capture the state-dependent routing dynamics that are needed to guide routing decisions for near-real time operation of NISQ devices.
The Differences between English and Indonesian Lecturer in the Classroom Interaction Based on Sinclair and Coulthard Model

This study was about IRF (Initiation-Response-Feedback) analysis on classroom interaction between English and Indonesian lecturer with students. The aimed of this study were to describe the processes of Initiation-Response-Feedback are employed by the English and Indonesian Lecturers with students in classroom interaction based on Sinclair and Coulthard Model. This research used qualitative research. The data of this study were the utterances that expressed by the English and Indonesian lecturer with students in thelearning process. The source of data was English and Indonesian lecturer with the students in STKIP Budidaya Binjai. The data were collected in five ways by Rymes (2009) observing, recording, transcribing, interviewing and analyzing. The data were analyzed based on Sinclair and Coulthard (1975). The result of this study were English subject, the lecturer initiaton was the highest appear in classroom interaction. The students felt enthusiastic in learning it although they had problem in pronounciation and write words but they want to try to do the task given by the lecturer. Lecturer initiation as the highest appear in classroom interaction. The competition as the technique of teaching that lecturer used in this learning process just made one student of each group that become active in share their opinion. The other students felt ashamed to share their opinion because of afraidness to get bad score from the lecturer
Features of Development of Creative Abilities of Senior Preschoolers in Collective Application

Resume: the article discusses the theoretical aspects of the concept of creative abilities. The author offers the results of an experiment on the formation of creative abilities in a collective application.
Distributed Fusion Estimation for Stochastic Uncertain Systems with Network-Induced Complexity and Multiple Noise

This paper investigates an issue of distributed fusion estimation under network-induced complexity and stochastic parameter uncertainties. First, a novel signal selection method based on event-trigger is developed to handle network-induced packet dropouts as well as packet disorders resulting from random transmission delays, where the ${H_2}/{H_\infty }$ performance of the system is analyzed in different noise environments. In addition, a linear delay compensation strategy is further employed for solving the complexity network-induced problem, which may deteriorate the system performance. Moreover, a weighted fusion scheme is used to integrate multiple resources through an error cross-covariance matrix. Several case studies validate the proposed algorithm and demonstrate satisfactory system performance in target tracking.
Do Open Data Badges Influence Author Behaviour? a Case Study at Springer Nature

&#x0D; Digital badges have previously been shown to incentivise journal authors to share their data openly. In this paper we introduce an Open data badging project at the Springer Nature journal BMC Microbiology. The development of the Open data badge is described, as well as the challenges of developing standard badging criteria and ensuring authorsâ€™ awareness of the badges. Next steps for the badging project are outlined, which are based on the experiences of the team assessing the badges, the number of badges awarded at the journal to date, and the results of an author survey.&#x0D;
Upaya Meningkatkan Kemampuan Guru Mengembangkan Sumber dan Media Belajar dengan Diskusi Model Think Pair and Share di SD Negeri 3 Glagahwangi Polanharjo Klaten Semester II Tahun Pelajaran 2017/2018

The general objective of the research is to find out how the discussion of think pair and share models is implemented in order to increase the active involvement and ability of teachers in developing learning resources and media. This type of research is School Action Research (PTS). The research subjects were 8 teachers. Data collection techniques using questionnaires, assignments, documentation and observation. Data analysis techniques use data reduction, data presentation and conclusions. The results of the study concluded that: (1) Discussion of think pair and share models gave an opportunity for each discussion participant (teacher) to work alone or collaborate by exchanging ideas and experiences, so that the discussion participants (teachers) interact intensively. (2) Discussion of think pair and share models can increase the activity of discussion participants (teachers) during the activity process. From the beginning until the end of the activity, the teacher involved is actively involved in each stage of the activity. (3) Discussion of the think pair and share model can improve the ability of teachers to develop learning resources and media, after they have done dikdusi or exchanged ideas and experiences with fellow teachers.
ICMSC: Intra- and Cross-modality Semantic Consistency for Unsupervised Domain Adaptation on Hip Joint Bone Segmentation

Unsupervised domain adaptation (UDA) for cross-modality medical image segmentation has shown great progress by domain-invariant feature learning or image appearance translation. Adapted feature learning usually cannot detect domain shifts at the pixel level and is not able to achieve good results in dense semantic segmentation tasks. Image appearance translation, e.g. CycleGAN, translates images into different styles with good appearance, despite its population, its semantic consistency is hardly to maintain and results in poor cross-modality segmentation. In this paper, we propose intra- and cross-modality semantic consistency (ICMSC) for UDA and our key insight is that the segmentation of synthesised images in different styles should be consistent. Specifically, our model consists of an image translation module and a domain-specific segmentation module. The image translation module is a standard CycleGAN, while the segmentation module contains two domain-specific segmentation networks. The intra-modality semantic consistency (IMSC) forces the reconstructed image after a cycle to be segmented in the same way as the original input image, while the cross-modality semantic consistency (CMSC) encourages the synthesized images after translation to be segmented exactly the same as before translation. Comprehensive experimental results on cross-modality hip joint bone segmentation show the effectiveness of our proposed method, which achieves an average DICE of 81.61% on the acetabulum and 88.16% on the proximal femur, outperforming other state-of-the-art methods. It is worth to note that without UDA, a model trained on CT for hip joint bone segmentation is non-transferable to MRI and has almost zero-DICE segmentation.
AN ANALYSIS OF AN INNOVATION E-LEARNING ON MODERN PLATFORM

The development of technology has resulted in many innovations, one of which is in the field of education. Innovation in the field of education today apparently uses online learning systems, online tutoring course is one of the learning systems that make students or else easier to access knowledge anytime and anywhere. One of the E-learning innovations in online learning is an application called Ruangguru. Online study or online tutoring from Ruangguru is the highest number of students who have registered in Indonesia. Education in these days was no longer centered upon a back and forth between student and teacher; todays took on a more networked approach and student having their own direct connection for gain knowledge or information. This encouraged the development of a more personalized way of learning where a student’s independence and various way to gain knowledge. This study aims to analyze innovation e-learning on modern platforms in the development of learning medium Ruangguru.
ВІЗУАЛЬНА КУЛЬТУРА ЯК ЧИННИК ФОРМУВАННЯ ІННОВАЦІЙНИХ ТЕХНОЛОГІЙ НАВЧАННЯ: ДОСВІД КИЇВСЬКОГО НАЦІОНАЛЬНОГО УНІВЕРСИТЕТУ КУЛЬТУРИ І МИСТЕЦТВ

The purpose of the article is to characterise the essence of visual culture and determine its impact on audio visualisation and analyse the proof of its application in higher education institutions. The article also analyses the case of the Kyiv National University of Culture and Arts in introducing innovative technologies in the educational process. The research methodology is based on the use of historical and theoretical analysis of pedagogical, philosophical, and art studies sources on the issue under study. Comparative and systematic approaches have helped to define visual culture as a factor in change and innovation shaping in the education system. The scientific novelty consists in studying the features of implementing the latest forms in the educational process, which are caused by changes in cultural priorities. Conclusions. The article proves that visual culture, becoming an integral part of modern society, a universal communicator, incentive of activity, a form of Contemporary Art, a means of education, plays a significant role in the formation of public opinion and active subjectification of various forms of social activity. Therefore, the urgent need for higher educational institutions is the use of leading pedagogical technologies. One of these technologies is audio visualisation, which is considered one of the most effective and motivating means to interact with the world of science. Therefore, its involvement and competent use in the educational process is not only a time requirement, and also a complex but necessary process. We believe that the University has gained considerable practical experience in using digital tools thanks to the use of modern digital technologies, interactive tools of educational gamification, the options of Google Classroom, conducting workshops and video conferences in a state of lockdown, managed to combine traditional and innovative technologies successfully; modern software tools, information resources and interaction of participants in the educational process.
KGWE - A customizable editor for OWL ontologies

Regarding ontology editors, it is observed that there are several gaps left by the main tools available on the web for editing and viewing ontologies. The proposal for this work is to provide more efficient and effective editing interfaces, providing a practical tool that improves the visualizing OWL graphs.
Faster R-CNN model learning on synthetic images

Machine learning requires a human description of the data. The manual dataset description is very time consuming. In this article was examined how the model learns from artificially created images, with the least human participation in describing the data. It was checked how the model learned on artificially produced images with augmentations and progressive image size. The model has achieve up to 3.35 higher mean average precision on syntetic dataset in the training with increasing images resolution. Augmentations improved the quality of detection on real photos. The production of artificially generated training data has a great impact on the acceleration of prepare training, because it does not require as much human resources as normal learning process.
IMAGE QUALITY ENHANCEMENT OF SCANNED PHOTOS:COMPARISON OF DEEP LEARNING TECHNIQUES

Currently, millions of photos are captured daily, and several factors can influence the quality of an image, causing distortions.Research has shown that there are several ways to remove defects from images.This study aims to comparatively analyze the potential of Deep Learning techniques to improve scanned images with shadow, glare, crumpled paper, external lightning, change of perspective and wave distortion defects.Based on a review of the literature on recent deep learning architectures, we have selected three, which were trained and refined to improve the quality of the images.The results indicate that the nets were able to attenuate and remove some defects.On this basis, these initial experiments demonstrate that deep learning models are promising for the studied defects.
Development of a Universal Pictographic Language Keyboard

The paradigm of communication between people is changing along with global changes in the modern world. This process is related to the integration of technology into everyday life and represents an expansion of the signs and symbolic environment in the field of communication: more and more new images are appearing designed to mark the attributes of the modern world. Pictorial form of communication is a simplified, cost-effective means of communication. That is why it is widely used in education, rehabilitation, navigation systems of public spaces, web and human interaction with cyberphysical systems. However, modern pictographic systems are fragmented and poorly systematized in a constant race for compliance with the requirements of the modern world. They are almost not investigated in their practical application and are limited in their expressive possibilities. This article is devoted to the description of the initial stage of empirical research of pictographic language LoCoS and the stages of development of an alternative keyboard for communication based on it. The conclusion is made about the possibility of the existence of a universal pictographic language on the basis of its semantic and technological improvement.
Person Re-identification with Adversarial Triplet Embedding

Person re-identification is an important task and has widespread applications in video surveillance for public security. In the past few years, deep learning network with triplet loss has become popular for this problem. However, the triplet loss usually suffers from poor local optimal and relies heavily on the strategy of hard example mining. In this paper, we propose to address this problem with a new deep metric learning method called Adversarial Triplet Embedding (ATE), in which we simultaneously generate adversarial triplets and discriminative feature embedding in an unified framework. In particular, adversarial triplets are generated by introducing adversarial perturbations into the training process. This adversarial game is converted into a minimax problem so as to have an optimal solution from the theoretical view. Extensive experiments on several benchmark datasets demonstrate the effectiveness of the approach against the state-of-the-art literature.