Reviewerly/exHarmony huggingface dataset:
Subquadratic Overparameterization for Shallow Neural Networks

Overparameterization refers to the important phenomenon where the width of a neural network is chosen such that learning algorithms can provably attain zero loss in nonconvex training. The existing theory establishes such global convergence using various initialization strategies, training modifications, and width scalings. In particular, the state-of-the-art results require the width to scale quadratically with the number of training data under standard initialization strategies used in practice for best generalization performance. In contrast, the most recent results obtain linear scaling either with requiring initializations that lead to the lazy-training, or training only a single layer. In this work, we provide an analytical framework that allows us to adopt standard initialization strategies, possibly avoid lazy training, and train all layers simultaneously in basic shallow neural networks while attaining a desirable subquadratic scaling on the network width. We achieve the desiderata via Polyak-Lojasiewicz condition, smoothness, and standard assumptions on data, and use tools from random matrix theory.
Bitcoin and The Merchant of Venice: Literary Narrative As an Alternative to Reductive Digital Technology and Economics

Bitcoin, which appeared for the purpose of solving the problems concerning the traditional currency, rather brought about a new problem that we are experiencing for the first time. This paper attempts to rethink the problem of Bitcoin by summoning one of Shakespeare’s narratives, The Merchant of Venice. First, we will look at the problem of money and trust in the capitalist system, and examine the possibility of literary narratives as an alternative to reductive economics and digital technology. Then, it will reinterpret the Bitcoin technical white paper of Satoshi from a narrative perspective and reveal the utopian fiction within. Finally, while reading Bitcoin anew through the literary narrative of The Merchant of Venice, this paper probe a way in which a literary work constructs an irreducible perspective by combining the macroscopic technological/economic point of view and the microscopic human point of view.
Voice User Interfaces

Welcome to the incredible world of voice user interfaces (VUIs). You are embarking on a fantastic voyage of discovery. Are you new to VUI? Do you have a little bit of Python under your belt? Do you want to learn how to design and build innovative, custom, data-driven Alexa skills for your home and business? Have you already published your first dice rolling skill? Are you an experienced Alexa skill builder and want to integrate Alexa with online APIs (Application Program Interfaces), rich data sources, and powerful applications? If you answered “Yes,” then this book will show you how to analyze, build, test, and deploy data-driven Alexa skills. You will learn how to use the tools, techniques, and code so that you quickly level up, first building a simple calculator skill, on up to the final project, where you will create a FinTech (Financial Technology) skill that uses APIs to tell you your personal net worth.
Sentiment Analysis of Beauty Product Reviews Using the K-Nearest Neighbor (KNN) and TF-IDF Methods with Chi-Square Feature Selection

The rise of beauty products in recent times can make consumers hesitate to choose a beauty product, especially for women. Beauty product reviews have become a very valuable source of information for consumers in making decisions to purchase a product in improving their products and marketing strategies. The process of sentiment analysis on negative and positive beauty product reviews will be classified one by one. Therefore, in this study, sentiment analysis was applied to the beauty product review data using the K-Nearest Neighbor (KNN) method to find the best k in the case of this study. The dataset used will be pre-processed with case folding, noise removal, tokenization, stemming, stopword removal, and slang words, for feature extraction using Term Frequency Inverse Document Frequency (TF-IDF) to calculate the weight of a word in the document, and The feature selection method uses Chi-Square which aims to select the features needed to increase the accuracy value. In this study, the best accuracy value was 71% of the data classified using KNN with a k value of 50 and the model on feature selection with 76 features.
Reconstruction for Powerful Graph Representations

Graph neural networks (GNNs) have limited expressive power, failing to represent many graph classes correctly. While more expressive graph representation learning (GRL) alternatives can distinguish some of these classes, they are significantly harder to implement, may not scale well, and have not been shown to outperform well-tuned GNNs in real-world tasks. Thus, devising simple, scalable, and expressive GRL architectures that also achieve real-world improvements remains an open challenge. In this work, we show the extent to which graph reconstruction -- reconstructing a graph from its subgraphs -- can mitigate the theoretical and practical problems currently faced by GRL architectures. First, we leverage graph reconstruction to build two new classes of expressive graph representations. Secondly, we show how graph reconstruction boosts the expressive power of any GNN architecture while being a (provably) powerful inductive bias for invariances to vertex removals. Empirically, we show how reconstruction can boost GNN's expressive power -- while maintaining its invariance to permutations of the vertices -- by solving seven graph property tasks not solvable by the original GNN. Further, we demonstrate how it boosts state-of-the-art GNN's performance across nine real-world benchmark datasets.
Safe and secure

Cybersecurity is a serious problem for all computers and digital systems. In healthcare, patient safety is paramount, but in the wider world security has a higher profile than safety. Both have problems caused by poor programming and all the design and development processes that precede actual coding.
DISTANT LEARNING ESL

Distance Learning is an online-based program that gives students additional practice outside the classroom and helps decrease the amount of time it takes inside the classroom to study for the HSE test or to improve English language skills. МЕТОДИКА ВИКЛАДАННЯ У ВИЩІЙ ШКОЛ І 146 Випуск І (81), 2021 Distance education, as a form of education that enables and promotes development of autonomous life-long learning skill, necessary to keep up with rapid changes and development in today’s society, is a concept definitely worth considering. Teaching a foreign language in a distance education system is very challenging, primarily in terms of overcoming the main gap – lack of direct contact between teachers and learners. This paper focuses on the aspect of teaching materials used for ESL in a distance learning system. To ensure the implementation of basic educational programs with high efficiency, the implementation of appropriate reforms in distance and innovative learning, which meet all modern requirements, is a very important process in the development of education. The development of distance learning courses will be useful to ensure equal access to educational opportunities for all students, especially for workers, or for those who study in parallel in other universities in Ukraine or abroad. Private educational organizations and government agencies around the world support the use and development of distance learning by accumulating pedagogical and methodological experience for further development. Distance learning technologies represent many new opportunities for teaching foreign languages, which allow further expanding the range of teaching methods, just as language laboratories, television and computers have increased the standard classroom. It is important to review these distance-learning options to distinguish their ability levels, as these systems have different limitations on the learning process. For example, one-way systems that use only presentations have been criticized for not providing anything other than a video distribution system that could be reproduced by sending 10 videos to students. The lack of direct bilateral interaction, which characterizes many distance education programs, is contrary to the goals of foreign language teaching. However, using this interaction, distance technologies can maintain the integrity of foreign language teaching. Learning strategies that encourage student-teacher dialogue and student autonomy in distance learning situations should be included in learning.
Development of Innovation Systems in Bioinformatics Using Blockchain Platforms

It is reasonable to use digital technologies to organize and support an innovation system that simplify and promote interactions between innovation activity participants by performing a situational analysis of big volumes of structured and unstructured data on innovation activity subjects in the regions. The aim of the article is to substantiate the essence, peculiarities and features of integrating blockchain platforms with Big Data intelligent analytics for regional innovation development. The study was carried out as based on materials describing the development of this concept both in the whole world and its spread in the Russian economy.
Implementasi Sistem Informasi Enterprise Pendaftaran dan Registrasi Siswa di Sekolah Menengah Kejuruan Swasta Kabupaten Bandung

Implementation of Enterprise Information System Registration and Registration of new Students is a business process in Vocational High School Education, the need for dynamic data collection is a problem that must be solved by unified modelling languange (UML) scheme, a system that can be flexible and responsive. Data integration needs are the ultimate goal of an information system to be able to process data, both for its own needs and to display information to the relevant part in terms of user and data needs for other information systems. In addition, the results of the admission selection of new students are more accurate and prospective students are accepted in accordance with the expected results.
"Achievements and Future Prospects of Japanese Language Education in Korea : Based on the Narrative Analysis of the President of the Korea Association of Japanese Education (KAJE)(20th Anniversary Period: 2019-20)"

本稿では、韓国における日本語教育の成果と今後の展望について韓国日語教育学会(20周年期：2019～20年)の成果を中心として、「会長」経験者のナラティブ分析を取り入れ、接近して考察しようと試みたものである。世界の日本語教育の潮流の1つである「つながりの日本語教育」とそれを標榜し運営してきた韓国日語教育学会の軌跡について述べ、また、韓国における日本語教育を牽引する使命を持ち、日本語教育という単一分野に特化して発展してきた韓国日語教育学会の動向と今後の日本語教育の展望を考察することを通して、日本語教育全体に対して示唆するところを世に示すことを目的とした。 第11代役員時期＜2019(20周年)学年度～2020学年度＞の特徴として、初の日本人会長、多様な20周年記念行事、韓国日本語教育ネットワーク(NET-JEK)の創設、新たな企画と運営、学術誌評価、コロナ禍における新たな挑戦としてのNINJALチュートリアルと第1回オンライン国際学術大会等が挙げられる。 今後の展望として＜1. 更なる「日本語教育のつながりとひろがり」2. 世界とつながる日本語教育＜国外> 3. 社会とつながる日本語教育＜国内＞ 4. 他分野との融合複合。5. オフライン(対面)とオンライン(非対面)の融合。＞の5点を挙げた。 政治や外交は複雑であるが、人文学の我々は決して分断と対立の力に負けることなく、この2019-20年を転換点として、民間文化交流と学術交流の拡大の力で、日本語教育に上昇気流を呼び戻し、韓国の日本語教育を再生させる動きを、韓国日語教育学会並びに関連団体が力を合わせて作っていくことを願う。
Applied Virtual Reality (Vr) In Education Medicine

It is known that e-learning is the latest method of education at the present time, especially at a time when the student is unable to attend college or school and perform his homework, especially in the circumstances of the Corona pandemic (Covid-19), through lectures and electronic lessons in the form of video.      Electronic platforms where learning takes place at any time and any place and contains modern learning tools through which virtual reality can be applied in education, especially medical and contains three-dimensional models(3D) that are closer to the truth because of the interactive content they contain. The existing two-dimensional ones in the current teaching and this system has been built on the basis of the (ADDIE) model and the use of the following technologies in the system (ASP.NET, CSS, Java script, Html) (SQL-server) for database and (web Gel, bootstrap and JQuery) for virtual reality.
High-precision laser ablation inductively coupled plasma mass spectrometry determination of trace elements in geological glasses by internal standardization

The analysis of trace elements (TE) in geological materials is a valuable tool to understand geological processes, including studies in geochemistry and petrology. Among the methods applied to determine TE, Laser Ablation Inductively Coupled Plasma Mass Spectrometry ­(LA-ICP-MS) detects TE contents in the μg/g and ng/g range. The aim of this paper is to validate, at Laboratório de Geologia Isotópica (LGI) — Centro de Estudos em Petrologia e Geoquímica/Universidade Federal do Rio Grande do Sul (CPGq/UFRGS), a high-precision method for LA-ICP-MS analyses of TE in geological materials. Samples used in this work were reference Max-Planck-Institut für Chemie — Dingwell (MPI-DING) glasses. The method is used in tandem with the Electron Probe Microanalyzer — Wavelength Dispersive X-ray Spectrometer (EPMA-WDS) technique to determine the major and minor elements of the samples and check for homogeneity. Analyses were conducted in a Thermo® Element2 Inductively Coupled Mass Spectrometer (ICP-MS) coupled to a New Wave Research® Neodymium-Doped Yttrium Aluminum Garnet (Nd:YAG) (213nm) laser ablation system. 43Ca and 29Si were used as internal standards (IS). Glitter® software and in-house spreadsheets were utilized for reduction treatments. The results using 29Si as IS present a high degree of fractionation errors compared to the results using 43Ca. Uncertainties caused by matrix interferences and fractionation effects can be corrected applying a correction factor. The obtained results demonstrate an effective recovery of TE content for the analyzed reference materials. Moreover, these silicate glasses proved to be robust to create an internal database of matrix matching standards in routine silicate analyses.
Integrating deep learning to improve text understanding in conversation-based ITS

In Conversation-based intelligent tutoring systems (CbITS), assessing learners' natural language input is a key factor for the system to be effective. When using AutoTutor, a well-known CbITS, asse...
Mind the Gap: Assessing Temporal Generalization in Neural Language Models

Our world is open-ended, non-stationary, and constantly evolving; thus what we talk about and how we talk about it change over time. This inherent dynamic nature of language contrasts with the current static language modelling paradigm, which trains and evaluates models on utterances from overlapping time periods. Despite impressive recent progress, we demonstrate that Transformer-XL language models perform worse in the realistic setup of predicting future utterances from beyond their training period, and that model performance becomes increasingly worse with time. We find that, while increasing model size alone -- a key driver behind recent progress -- does not solve this problem, having models that continually update their knowledge with new information can indeed mitigate this performance degradation over time. Hence, given the compilation of ever-larger language modelling datasets, combined with the growing list of language-model-based NLP applications that require up-to-date factual knowledge about the world, we argue that now is the right time to rethink the static way in which we currently train and evaluate our language models, and develop adaptive language models that can remain up-to-date with respect to our ever-changing and non-stationary world. We publicly release our dynamic, streaming language modelling benchmarks for WMT and arXiv to facilitate language model evaluation that takes temporal dynamics into account.
The new development of plus size women body sizing for sportswear appearance / Nur Awatif Adawiyah Abdul Aziz and Shaliza Mohd Shariff

In this globalization era, the overall look of women's plus size sportswear is one of the issues that is still being faced by plus size ladies today. The sportswear that is produced today makes the plus size women feel excluded from society as they could not fit the current trend due to the body image that they owned. Plus size women usually faced a problem in choosing the right sports attire due to their varying sizes and body shapes. Plus size consists of 7 types of body shapes that have different widths on each part of their body. This group of people constantly faced similar problems in finding the best sportswear that suits their size as the current sports garment in the market does not get high demand in producing plus size workout garments which is much costly compared to the normal sports attire. The research aim is to create plus-size sportswear and the design criteria that could fit the seven types of plus size body shape On this basis, the innovation of plus size sportswear for plus size women will increase their selfconfidence, and the essentials factors of the design will give maximum usage to them which will give a good look to their physical appearance.
Refocusing on Relevance: Personalization in NLG.

Many NLG tasks such as summarization, dialogue response, or open domain question answering, focus primarily on a source text in order to generate a target response. This standard approach falls short, however, when a user’s intent or context of work is not easily recoverable based solely on that source text– a scenario that we argue is more of the rule than the exception. In this work, we argue that NLG systems in general should place a much higher level of emphasis on making use of additional context, and suggest that relevance (as used in Information Retrieval) be thought of as a crucial tool for designing user-oriented text-generating tasks. We further discuss possible harms and hazards around such personalization, and argue that value-sensitive design represents a crucial path forward through these challenges.
Pelatihan Penggunaan Aplikasi SIPGAR Bagi Pemuda DAS di Kota Palangka Raya

During the Covid-19 pandemic, health factors in the form of maintaining physical fitness are very important. There are many ways to keep your body in shape. The most effective way to maintain physical fitness during the current covid-19 pandemic is to comply with health protocols and get used to exercising so that the body is always in a fit condition. Exercise can be used as an alternative to keep the body fit. Another important thing besides exercising during the current pandemic is checking physical fitness regularly and independently. One way that can be used is the SIPGAR application. An application published by the Ministry of Health of the Republic of Indonesia to check a person's physical fitness independently via Android. The purpose of this activity is that participants get education about physical fitness and can do tests independently through the operation of the SIPGAR application. The method used in this activity is training. The training was conducted for 5 times, with different participants and places. The total number of participants who attended the training was 42 people. Based on the results of the training, there were several problems experienced by the participants including not all participants were able to download applications on the play store and register an account. This is because each participant's cellphone has different specifications. The solution is that participants who successfully register help their friends to register, while still using the identity of the participant who cannot register. After successful registration, then login using their respective cellphones. After the implementation of this activity the youth felt happy, this was because they already had new skills in operating the SIPGAR application. According to the participants, SIPGAR is an application that is easy and accurate to measure a person's physical fitness, besides that the test can also be carried out anywhere and does not require a special place, the most important thing is that the distance reached is 1600 meters. So that the participants will be able to check their physical fitness regularly and independently easily. Another hope that the participants want is training on other applications to support their skills in operating applications regarding self-health checks independently
Funcionamiento ejecutivo en estudiantes de Educación Física: Particularidades en contextos virtualizados por la pandemia

espanolEl objetivo es conocer y establecer algunas distinciones acerca de como se desempenaban en sus aprendizajes los estudiantes de educacion fisica antes de la pandemia y ahora en la virtualidad. Se profundizo en las funciones ejecutivas. Se trabajo con 46 estudiantes que cursan Psicologia Educacional en Educacion Fisica, de la Universidad Nacional de Rio Cuarto, Cordoba, Argentina. Se utilizo una version adaptada de EFECO (Ramos-Galarza et al., 2016). Los resultados evidencian tendencias de peor manejo en tiempos de pandemia respecto al monitoreo, inhibicion, flexibilidad cognitiva, control emocional, iniciativa y memoria de trabajo. En la virtualidad aparecen dificultades de atencion, organizacion, conectividad, vinculos, estados de animo, angustia y sueno. EnglishThe objective is to know and establish some distinctions about how physical education students performed in their learning before the pandemic and now in virtuality. Executive functions were studied. We worked with 46 students who are studying Educational Psychology in Physical Education, from the National University of Rio Cuarto, Cordoba, Argentina. An adapted version of EFECO was used (Ramos-Galarza et al., 2016). The results show trends of worse management in times of pandemic regarding monitoring, inhibition, cognitive flexibility, emotional control, initiative, and working memory. In virtuality, difficulties with attention, organization, connectivity, bonds, moods, anguish, and sleep are shown.
A Web Scale Entity Extraction System

Understanding the semantic meaning of content on the web through the lens of entities and concepts has many practical advantages. However, when building large-scale entity extraction systems, practitioners are facing unique challenges involving finding the best ways to leverage the scale and variety of data available on internet platforms. We present learnings from our efforts in building an entity extraction system for multiple document types at large scale using multi-modal Transformers. We empirically demonstrate the effectiveness of multi-lingual, multi-task and cross-document type learning. We also discuss the label collection schemes that help to minimize the amount of noise in the collected data.
Reading Brain in the Digital Age: An Experience of Philippine High School

The study aims to ascertain the significant relationship of digital reading profile and reading comprehension, and digital reading behavior and reading comprehension of Grade 7 students of Elpidio Quirino High School. The results will be obtained through the three phases of the study: digital reading profile and digital reading behavior survey, reading comprehension tests, and focus group discussion. The findings of the study show that the participants read more academic resources online or offline as opposed to the results from the qualitative data in which it shows that they preferred Wattpad, also respondents tend to use cellphone in reading digital materials. Based on the comparison made, the result shows no significant relationship. From the findings, due to its portability, cellphone is the commonly used device and Wattpad is the most commonly read digital reading material. It can be concluded that digital reading has no effect on the reading brain of the students. Based on the conclusions, it is suggested that through the inevitable emergence of technology, proper utilization and the collaboration of parents and teacher is vital to promote genuine love for reading.
Building a Messaging App with MERN

Welcome to your third MERN project, where you build an awesome messaging app using the MERN framework. The back end is hosted in Heroku, and the front-end site is hosted in Firebase.