Reviewerly/exHarmony huggingface dataset:
STUDENTS’ DIFFICULTIES IN WRITING RECOUNT TEXT THROUGH PROJECT BASED LEARNING

English language lessons have become compulsory secondary schools. Especially, in era of globalization writing is very important The purpose of this study is to investigate students' difficulties in writing recount text through Project Based Learning. This study used descriptive qualitative research. The data was gathered through questionaire. The questionnaire were administered to eight grade students of SMPN 3 Batujajar in the academic year of 2019/2020. The questionnaires consist of 5 statements related to aspects of writing. The data was analyzed descriptively.The result showed that most of students got difficulties in writing related to five aspect of writing, such as content (23,33%), grammar or language use (56,67%), organization (36,67%), mechanic (43,33%), and vocabulary (26,67%).
The Research on developing Cardboard game development tool

Due to the technological development of the head-mounted device, the user can experience the world of virtual reality, and the experience of the immersive experience combined with the gameplay of the game can provide a new experience for the player. Google Cardboard is cheap and easy to use, providing a simpler method to experience VR games. Cardboard VR games make game design more difficult due to the functional limitations of the device, so there are fewer related games. However, it is easier to play such games. If you can design a good game, there will be good market value. When students make this kind of hard-to-design game, if their pressure on programming can be reduced, students can focus on game design to design better games. This research develops development tools for Cardboard games to provide game designers arising the quality of the games they develop.
LibGuides: Master of Education in Early Childhood Education: Home

Early childhood education is a branch of education theory that relates to the teaching of children from birth up to the age of eight.
Punctuation model (14-09-2020)

A python package that punctuates Icelandic text. The input data is unpunctuated text and punctuated text is returned. The user can choose between two punctuation models, a BERT-based Transformer and a bidirectional RNN ([Punctuator 2](www.github.com/ottokart/punctuator2)) in Tensorflow 2.
Information and communication technology as a basic pillar of the e-training process: View a collection of examples and experiences

This study aims at theoretical analysis, one of the most important and latest topics, Which is particularly important as it relates to the most important keys to success, and a source of the most important sources of sustainable competitive advantage. The subject of electronic training for human resources,  Which knows some of the lack of business management literature, despite its great importance, We have tried through this treatment to link the variable and its main pillars  To denounce the importance of technology and the need to establish it To move towards electronic training as a substitute for traditionalism. We have also presented a set of leading examples of e-training All of which rely on information and communication technology as a backbone of the theoretical analysis of the subject.
LibGuides: Referencing Software: Home

Introduction to using this Coventry University Guide to Referencing in Harvard style website
COVID-19 Advertorials Accentuating Fright and Xenophobia in Ecosystem: An Eco-linguistic Approach to SFL

This present study explores manipulation of language of COVID-19 advertorials to achieve specific goal of fear and xenophobia among people through ecolinguistic study of five advertorials published on COVID-19 on five global websites. To the best of author’s knowledge, no research has been conducted on advertorials of different websites in this COVID-19 language context. The purpose of this research is to investigate and apply M.A.K. Halliday’s  3 semantic meta-functions proposed in Systemic Functional Linguistics (henceforth SFL) on corona advertorials from ecolinguistic perspective. Collection of 5 corona advertorials was gathered as data from 5 different websites. Only one corona advertorial from each website was built. Ecolinguistic analysis of Halliday’s 3 meta-function was adopted as analytical framework to analyse elements of fear and xenophobia in the language of COVID-19 advertorials. Present research employed qualitative, descriptive method containing observation. Results revealed that 3 meta-functions of ecolinguistic SFL can be used in shedding light on use of language in these advertorials to sustain and invigorate a global narrative of fright and xenophobia. Findings showed that language of COVID-19 advertorials accentuates elements of fright and xenophobia in ecosystem. Results of current study will deliver a guideline of didactic inferences for future researchers in the field.
Variasi Kalimat dan Jenis Klausa pada Karangan Deskripsi Siswa Kelas VII di SMP N 1 Cepogo, Boyolali

The purpose of this study are: (1) Describe the variation of sentences in the essay description of grade VII students in SMP N 1 Cepogo. (2) Identifying the type of clause in the essay description of grade VII students in SMP N 1 Cepogo. This type of research is a qualitative descriptive study. The data source in this study is the work of the description text of grade VII students of SMP N 1 Cepogo, Boyolali. This research data in the form of words, phrases, clauses and sentences contained in the student description text. The research method used is descriptive qualitative data collection techniques refer to and note, and data analysistechniques using the method of covering the basic techniques or for direct elements (BUL) and advanced techniques. The results showed that the use of sentences in each paragraph in the text description written by students of SMP N 1Cepogo, Boyolali varied. Sentence variations used in writing paragraphs in the description text include: (a) 15 paragraph variations of sequence sentences, there are 40 regular sequence sentences and 19 inversion sentences, (b) 15 paragraph variations of active-passive sentences, there are 29 active sentences and 25 passive sentences, (3) 2 paragraph variations of intonation sentences, there are 4news sentences, 1 command sentence and 1 question sentence, and (d) 6 paragraph variations of long-short sentences, there are 6 long sentences and 15 short sentences. The results of research on the types of clauses used by students of SMP N 1 Cepogo, Boyolali in writing long sentences in the description text include, (a) 8 free clauses, (b) 4 bound clauses, and (c) 3 verbal clauses.
New Lossless Random Grids Progressive Secret Sharing Based on XOR for Binary-Image

Random grids-based visual secret sharing is an important methodology without pixel expansion and codebook. However, random grids-based VSS for general access structure (GAS) had the drawbacks of low visual quality. In this paper, we developed a lossless random grids-based progressive VSS to improve Prasetyo's Scheme utilizing three shared image indices and XOR operation to construct share images.
The unreasonable effectiveness of Neural Models in Language Decoding

This tutorial will provide an in-depth look at the experiments, jointly carried out by KantanMT and eBay during 2018, to determine which Neural Model delivers the best translation performance for eBay Customer Service content. It will lay out the timeline, process and mechanisms used to customise Neural MT models and how these were used in conjunction with Human Based evaluations to determine which approach to Neural MT provided the best translation outcomes.The tutorial will cover the following topics and methods:- Structural differences in Neural Networks and how they assist the language decoding process – RNN, CNN and TNN will be covered in detailed.- Customisation of Neural MT using the KantanMT Platform- Using MQM Framework for the evaluation and comparison of Translation Outputs and comparison to Human Translation- Collation and analysis of experimental findings in reaching our decision to standardise on Transformer type networks.Participants of the tutorial will get a clear understanding of Neural Model types and the differences, it will also cover how to customise these models and then how to set up a controlled experiment to determine translation performance.
ProPaCoL-Net: A Novel Recursive Stereo Image SR Network with Progressive Parallax Coherency Learning

Recently, stereo cameras have been widely packed in smart phones and autonomous vehicles thanks to low cost and smallsized packages. Nevertheless, acquiring high resolution (HR) stereo images is still a challenging problem. While the traditional stereo image processing tasks have mainly focused on stereo matching, stereo super-resolution (SR) has drawn less attention which is necessitated for HR images. Some deep learning based stereo image SR works have recently shown promising results. However, they have not fully exploited binocular parallax in SR, which may lead to unrealistic visual perception. In this paper, we present a novel and computationally efficient convolutional neural network (CNN) based deep SR network for stereo images by learning parallax coherency between the left and right SR images, which is called ProPaCoL-Net. The proposed ProPaCoL-Net progressively learns parallax coherency via a novel recursive parallax coherency (RPC) module with shared parameters. The RPC module is effectively designed to extract parallax information in prior for the left image SR from its right view input images and vice versa. Furthermore, we propose a parallax coherency loss to reliably train the ProPaCoL-Net. From extensive experiments, the ProPaCoL-Net shows to outperform the very recent state-of-the-art method with average 1.15 dB higher in PSNR.
Active Word Learning through Self-supervision

Models of cross-situational word learning typically characterize the learner as a passive observer, but a language learning child can actively participate in verbal and non-verbal communication. We present a computational study of crosssituational word learning to investigate whether a curious word learner who actively influences linguistic input in each context has an advantage over a passive learner. Our computational model learns to map words to objects in real images by selfsupervision through simulating both word comprehension and production. We examine different curiosity measures as guiding input selection, and analyze the relative impact of each method. Our results suggest that active learning leads to higher overall performance, and a formulation of curiosity which relies both on subjective novelty and plasticity yields the best performance and learning stability.
TELEMEDICINA NA PANDEMIA COVID-19

The Covid-19 pandemic declared by the WHO in March 2020 is a highly contagious disease, with predominantly respiratory symptoms caused by the new coronavirus (SARS-CoV-2). There is no specific therapy. Preventive measures are the main strategy to contain the spread of the disease, which includes social distancing, self-isolation and quarantine, in addition to hygiene measures and the use of facial masks. In this context, telemedicine has been used to bridge the gap between doctors and patients. Health services had to implement infrastructure, care processes and remote patient guidance, as well as the improvement of  actions in teleducation.Keywords: Telemedicine, Telehealth, Covid-19, Coronavirus.
IQ Test Expert System for Selecting Candidates for New Students

The IQ test information system at the Taman Siswa Lubukpakam Private High School is still done by selling, after the which Recapitulation is done manually, the obstacle is that the school has Difficulties in delivering information on the results of IQ tests that are slow and not timely , and in the calculation of the IQ test results that require a long time, the resulting in slow work.The making of this system uses the methodology of field researchers, interviews and observations. This requires some Data Including student data. Data Reviews These are expected to be the basis of making this application system in order to present the required information quickly intervening and accurately. IQ tests in the determination and consideration of class Unmatched in schools are usually done manually and the make enough time to find out the IQ results in Determining prospective new students at school, besides calculating the IQ test results Because it is quite complicated, then to Facilitate the school in carrying out the IQ test to Determine the prospective new students required the existence of a computer-based application and to build applications that will be used by the web programming language. The results of the evaluation of the application that was built were very helpful and accelerated the school in Determining the selection of classrooms that adjusted Reviews their abilities and civilized the use of computers among students. then to Facilitate the school in carrying out the IQ Test to Determine the prospective new students required the existence of a computer-based application and to build applications that will be used by the Web programming language. The results of the evaluation of the application that was built were very helpful and accelerated the school in Determining the selection of classrooms that adjusted Reviews their abilities and civilized the use of computers among students. then to Facilitate the school in carrying out the IQ Test to Determine the prospective new students required the existence of a computer-based application and to build applications that will be used by the Web programming language. The results of the evaluation of the application that was built were very helpful and accelerated the school in Determining the selection of classrooms that adjusted Reviews their abilities and civilized the use of computers among students
Estrategias de Aprendizaje: Inteligencias Múltiples y Estrategias Didácticas

This article has as a main objective to: Identify how multiple intelligences and didactic strategies intervene in learning strategies. The data obtained is organized in a concentration matrix and is given statistical treatment to explore results where a 90 Alpha Cronbach is obtained. Besides, information is processed in the statistical analysis: Percentages and frequencies, comparative with T student test and integrational with factorial analysis. As main results it stands out that: Starting from the use, handling and development of multiple intelligences such as naturalistic, bodily-kinesthetic, logical mathematical along with didactic strategies such as team building, individual work, exchange of ideas, participation, visual aids, study of chaos, and to arouse curiosity impacts in students and motivates them to do analysis, comprehensive lecture and work collaboratively, all of this combined encourages students to be more autodidactic.
The future strong motion national seismic networks in Central America designed for earthquake early warning.

&amp;lt;p&amp;gt;The national seismic networks in Central America have been developing network-based early warning since 2016 for Nicaragua, 2018 for El Salvador and 2019 for Costa Rica. This effort is part of a project with the Swiss Seismological Service (ETH Zurich) including funds for accelerograph deployment. At each network, delay for first earthquake parameter estimations have been significantly reduced by optimizing data acquisition, metadata quality, and configuration of the EEW algorithms implemented in SeisComP3, i.e. Virtual Seismologist and the Finite fault rupture Detector. Issues remain with significant numbers of deployed instrumentation that for a variety of reasons, do not optimally contribute to the EEW systems. Building on our experience so far, we design national network upgrades that will optimize the earthquake early warning performance in the Central America region, mitigating the current issues with velocimeter clipping during large events, datalogger delays, and incomplete network coverage. The new instruments have been selected after testing all available EEW-capable accelerographs natively compatible with SeisComP3 including class A force balance accelerometers as well as MEMs. To justify our instrument selection, we summarize the performance of these different instruments. We model and discuss reference maps for performance expectations, and present planned instrument vaults. Our primary focus is on minimizing first alert times but we also wish to accentuate the broad value of the network upgrade for seismological monitoring showing changes in the magnitude of completeness in the region. We demonstrate the value of the network upgrade for earthquake early warning with real-time processing simulation using synthetic data for the maximum magnitude earthquake expected for the Central America subduction zone.&amp;lt;/p&amp;gt;
Research Guides: Dissertations or Theses in SOAR at USI: Licensing Your Work

Information about submitting your electronic thesis or dissertation (ETD) in the Scholarly Open Access Repository (SOAR) at USI.
Efficiency in transmitting information through chaotic signals

The chaotic signal is a relatively new field in communication systems. Motivation derives from the advantages offered by chaotic signals, such as spread spectrum, robustness in multipath environments and resistance to jamming. Chaotic signals are non-periodic, broadband, and difficult to predict and to reconstruct; they may be generated by mathematical map functions, electronic circuits or laser optics. Their properties coincide with requirements for signals used in communication systems, in particular for secure communication systems. The study in this paper is focused on one of the methods, proposed to send binary messages by chaotic signals- the chaos shift keying (CSK) approach. Each symbol to be transmitted is coded as a discrete chaotic signal, which is generated by a chaotic map. The symbols are detected at the receiver by coherent detection technique. The purpose in this paper is to present the error probability of a coherent CSK digital system under the influence of additive white Gaussian noise (AWGN), assuming ideal synchronization at the receiver. The solution for the error probability has been derived, in terms of the signal-to-noise power ratio.
Research Guides: Dissertations or Theses in SOAR at USI: Access Restrictions (Embargoes)

Information about submitting your electronic thesis or dissertation (ETD) in the Scholarly Open Access Repository (SOAR) at USI.
The Use of the Synergistic Approach When Conducting Studies In Biology

The article deals with the application of synergetics in various sciences, including Biology. Synergyplays an important role in ensuring the development of the individual as a biological and intellectualsubject. Synergetics helps to understand the processes of self-organization of human activity, the orderingof his actions. Properties considered in synergetics-autonomy and self-regulation allows us to drawcertain parallels between cybernetic laws and the laws of synergetics.The synergetic approach, its ideas and main strategies can help autonomy, self-education of theindividual, development of personal qualities. Conducting classes in Biology using synergetic methodsis characterized by a variety of methods and their diversity, in contrast to traditional training andconducting classes. The authors are currently using the synergetic method when conducting severalclasses in Biology. In addition, synergetics has recently become one of the new interdisciplinaryresearch areas in science that are of interest to the educational and scientific community around theworld. It is provided an example in the article and summarizes the innovative experience of conductingBiology classes using a synergetic approach on the basis of gymnasium No. 176 in Almatyfor 8th grade students. The content of the classes included integrated sections of the renewed Biologyprogram.Key words: synergetics, pedagogy, natural sciences, educational process, traditional approach.
UIC launches the OpenRail brand – UIC Communications

UIC is launching the OpenRail brand in order to gather together and promote open source projects in the railway sector and foster the use of proofs of concept (POCs) and software developed within…
Blur kernel region estimation and space variant restoration based on weighted L1 norm measure

先进的图像盲复原方法主要体现在模糊核估计的准确性和快速性两方面。针对目前图像复原方法存在信息冗余和有效信息利用不足所引起的模糊核估计耗时长和不精确等问题，我们提出了加权 \begin{document}$ {L}_{1} $\end{document} 范数测度的模糊核区域估计及空可变复原方法。首先提取退化图像的多尺度形态学梯度，抑制噪声对图像有用信息的干扰；然后定义利于模糊核估计的梯度加权 \begin{document}$ {L}_{1} $\end{document} 范数测度，解决小结构区域和细纹理区域导致的模糊核求解不精确问题，提取利于模糊核估计的区域；最后利用区域模糊核的相似性区分图像退化的空不变性和空变性，分别采用空不变和空变复原方法对退化图像进行复原。在反卷积阶段，采用FFTW进行傅里叶变换计算，较大地提升了复原速度。大量实验结果表明，提出的算法仅用单帧图像就能够快速有效地复原图像。
A DEVS Based Methodological Framework for Reinforcement Learning Agent Training

Reinforcement Learning has become one of the fastest growing fields of artificial intelligence due to the successful application of its techniques into several domains. In this way, the integration of intelligent agents based on Reinforcement Learning into information systems is a current reality. However, the way in which they learn requires a simulation model of the process that must be controlled to obtain large volumes of risk-free information. In this work, a methodological framework to support the training of Reinforcement Learning agents using DEVS is proposed. This framework provides the steps and elements required to implement RL Agents with the purpose of accelerating the agent learning and reducing training costs. Also, it allows modeling the dynamics of complex systems in a modular and hierarchical way, favoring the reuse of simulation components, since it is based on DEVS formalims fundamentals.
Detecting gaps in deep learning models used for mask process modeling

Deep neural networks (DNN) have shown excellent performance in classification and regression problems in multiple fields. Recent work has demonstrated the use of deep learning techniques for modeling mask processes (MILAN) where it greatly reduces the time and effort to build an accurate model [1]. Models used in semiconductor fabrication have rigorous requirements about generalization and users need to be aware of potential gaps in the model. It is therefore imperative that we can detect when a deep learning process model is not able to generalize on unseen data. We discuss an approach to solve this problem using variational autoencoders [2] in this paper. Variational autoencoders (VAE) are generative models that compute a probability distribution for describing an observation in the latent space of the model [3]. Therefore, any input to the model can be described in terms of probability distributions of its latent variables. We leverage this property of VAEs to augment MILAN models to determine their robustness. We also present results of the latent space distribution on unseen data when the deep learning model fails to generalize. The results show that our approach provides us with an ability to indicate vulnerabilities in deep neural network models used for mask manufacture proposed.