Reviewerly/exHarmony huggingface dataset:
What Is Considered Complete for Visual Recognition?

This is an opinion paper. We hope to deliver a key message that current visual recognition systems are far from complete, i.e., recognizing everything that human can recognize, yet it is very unlikely that the gap can be bridged by continuously increasing human annotations. Based on the observation, we advocate for a new type of pre-training task named learning-by-compression. The computational models (e.g., a deep network) are optimized to represent the visual data using compact features, and the features preserve the ability to recover the original data. Semantic annotations, when available, play the role of weak supervision. An important yet challenging issue is the evaluation of image recovery, where we suggest some design principles and future research directions. We hope our proposal can inspire the community to pursue the compression-recovery tradeoff rather than the accuracy-complexity tradeoff.
Politeness Strategies used by the Students with Regional Multicultural Background

his study aimed to describe the politeness strategy used by the students of Language and Science Faculty in Wijaya Kusuma Surabaya University with different regional multicultural backgrounds. The data in this qualitative study were taken from 20 participants, in which 10 participants were non-Javanese, and 10 participants were Javanese. The data were collected, documented, transcribed, reduced, and coded to make the analysis easier. The analysis was done by following these procedures 1) the data were classified based on the students’ place of origin, types of politeness, and the strategies they used and displayed 2) the data were analyzed using Brown’s and Levinson’s theory of politeness strategies. The finding reveals that both groups of students used negative and positive politeness strategies; however, the types of strategies are different. The non-Javanese students used strategies of apologizing and being pessimistic in negative politeness strategy while the Javanese students used strategies of apologizing, hedging, and giving deference. In positive politeness strategies, the non-Javanese students used strategies of avoiding disagreement, promising, exaggerating, and seeking agreement; meanwhile, the Javanese students used avoiding disagreement, exaggerating, and giving for reason strategies.
ASQ: Automatically Generating Question-Answer Pairs using AMRs

We introduce ASQ, a tool to automatically mine questions and answers from a sentence using the Abstract Meaning Representation (AMR). Previous work has used question-answer pairs to specify the predicate-argument structure of a sentence using natural language, which does not require linguistic expertise or training, and created datasets such as QA-SRL and QAMR, for which the question-answer pair annotations were crowdsourced. Our goal is to build a tool (ASQ) that maps from the traditional meaning representation AMR to a question-answer meaning representation (QMR). This enables construction of QMR datasets automatically in various domains using existing high-quality AMR parsers, and provides an automatic mapping AMR to QMR for ease of understanding by non-experts. A qualitative evaluation of the output generated by ASQ from the AMR 2.0 data shows that the question-answer pairs are natural and valid, and demonstrate good coverage of the content. We run ASQ on the sentences from the QAMR dataset, to observe that the semantic roles in QAMR are also captured by ASQ. We intend to make this tool and the results publicly available for others to use and build upon.
The Neural Representation of Mental Models Across Content Type: A Common Spatial Structure

Mental models provide a cognitive framework that allows for organizing and manipulating information while reasoning about the world. Deductive reasoning with mental models is supported by a frontoparietal network, including regions of anterior prefrontal cortex associated with relational integration, and superior parietal regions associated with spatial cognition. Based in part on this evidence, mental models are often considered spatial representations. However, studies of transitive reasoning often rely on direct perception of stimuli that are inherently spatial in content, leaving open the possibility that the associated neural representations are specific to content that is inherently spatial or concretely perceivable. Here we directly test the hypothesis that the neural representation of mental models generated through transitive reasoning relies on this same frontoparietal network irrespective of the spatial nature of the stimulus content. Specifically, participants generated three distinct mental models through a transitive reasoning task. The content within the three models ranges from expressly visuospatial to entirely abstract. Moreover, all of the mental models participants generated were based on inferred relationships that were never directly observed. Multivariate representational similarity analysis was used to assess the correlation between these to-be-learned mental models and the patterns of neural activity elicited while viewing individual stimuli after training. Patterns representative of the mental models were revealed in both superior parietal lobule and anterior prefrontal cortex. Notably, these neural patterns were highly convergent across stimulus types. These results support the conclusion that, independent of content, relational reasoning using mental models relies on neural mechanisms associated with spatial processing.
Measuring Fine-Grained Domain Relevance of Terms: A Hierarchical Core-Fringe Approach

We propose to measure fine-grained domain relevance - the degree that a term is relevant to a broad (e.g., computer science) or narrow (e.g., deep learning) domain. Such measurement is crucial for many downstream tasks in natural language processing. To handle long-tail terms, we build a core-anchored semantic graph, which uses core terms with rich description information to bridge the vast remaining fringe terms semantically. To support a fine-grained domain without relying on a matching corpus for supervision, we develop hierarchical core-fringe learning, which learns core and fringe terms jointly in a semi-supervised manner contextualized in the hierarchy of the domain. To reduce expensive human efforts, we employ automatic annotation and hierarchical positive-unlabeled learning. Our approach applies to big or small domains, covers head or tail terms, and requires little human effort. Extensive experiments demonstrate that our methods outperform strong baselines and even surpass professional human performance.
Problem Posing Based Learning Approaches of Eighth Grade Students: Implementation of Active Learning Framework Supported by GeoGebra

The aim of this study was to examine the problem-posed learning approaches of eighth grade students in the Active Learning framework supported by GeoGebra. Case study was used in this study. The study group comprised 19 eighth grade students. Interview forms, learning activities, unstructured observations and students' problems posed with GeoGebra software during the intervention were used as data collection tools. Descriptive analysis was used to analyze the data. To investigate students' skills through the stages of the Active Learning Framework, seven activities were developed and applied for each acquisition in triangles with congruence and similarity sub-learning domains. GeoGebra software was introduced to students for three weeks before the intervention and the process continued for ten weeks. As a result of the analysis of the data, Active Learning Framework supported by GeoGebra software was appeared to be an effective approach in improving the skills of students in this context by transferring the problem solving and posing to the learning environment in a systematic way.
СОЦИАЛЬНАЯ РАБОТА С ДЕТЬМИ С ИНВАЛИДНОСТЬЮ

The article exams the latest changes in the field of policy and legislation on the rights of people with disabilities, the potential and opportunities of society aimed at improving the situation of people with disabilities, improving their quality of life, summarize the experience of working with children in domestic and world social rehabilitation practice, considers the problems social and cultural adaptation of children with disabilities, the activities of organizations aimed at providing social protection and support to children with disabilities and their families. There is an increase in attention, to the problem of social integration of people with disabilities into society, and to the problems associated with various difficulty of children with disabilities in everyday life, lack of full access to infrastructure, limited access to education, satisfaction of socio-cultural, sports needs and other demand. Based on the results of sociological research, the main aspects of the activities of specialists in social work in society are considered, recommendations for improving the mechanisms of socio-cultural adaptation of children with disabilities are proposed. The research was carried out within the framework of the OT-F1-100 project Scientific and methodological foundations for improving the system of socio-cultural adaptation of children with disabilities.
The Use of Chain Blocks in the Maintenance of Intellectual Property Rights: استخدام سلسلة الكتل في حفظ حقوق الملكية الفكرية

The present study aimed to identify the reality of the use of blocks series in the process of preserving intellectual property rights, and the study adopted the theoretical documentary approach, and the study relied on books, documents, reports and studies published Internet sites in the 'list, and was addressed to the general framework of the study deals with the introduction, problem and importance To the theoretical side of the study in which the researcher addressed a literary review of more than one aspect of the issue of the series of blocks and intellectual property rights, the researcher concluded at the end of the research to a set of results, the most important of which while the technology of the blockchain can bring innovation in many sectors Despite the enthusiasm for this technology, it should not be considered a "magic bullet." Instead, it should be carefully evaluated according to the objectives of the company sector and its business. The use of electronic systems for a long time, such as banks, insurance companies, etc. There is a difficulty in getting rid of their systems and replace them with a new system do not know the risks of its application and there are no uniform standards.
Imagine a proposal for a personal e-learning environment (PLE) to support the research skills of undergraduate students

The study aimed at identifying the degree of use of undergraduate students in some of the applications of mobile personal learning environments in their academic life, and the opportunities available to these programs and electronic applications when used to support scientific research skills and the most important challenges facing them. The aim was to present a proposed scenario for a training program that aims to employ the use of personal learning environments (PLE) in mobile devices (smart phones, tablets or laptops) to support the scientific research skills and academic skills needed by The study consisted of (154) female students from the Faculty of Applied Medical Sciences. The researcher used a questionnaire consisting of (32) words distributed on three axes after verifying their validity and stability. The researcher also constructed a proposed training program aimed at Use mobile personal learning environments to support scientific research skills. The study concluded with a set of results. In light of this, recommendations were made to activate the use of smart phones and tablets and to encourage students to use them in supporting scientific research skills, dissemination and academic skills. Develop appropriate plans to train students and faculty on what is new in the field of e-learning and mobile education.
Efektivitas Pembelajaran dengan Menggunakan Model Kamus Kata Penggolong Bahasa Mandarin Berbasis Nomina Alfabetis dalam Bahasa Indonesia

Since the annulment of Presidential Instruction No. 14/1967, which prohibits the celebration of Chinese New Year and Chinese culture in Indonesia, there has been a gradual increase in Indonesian interest in Chinese culture, including learning Mandarin. And with the increasingly tight trade relations between China and Indonesia, the need for human resources who can communicate well, especially oral communication, increases. Mandarin learners in Indonesia are not limited to those who came from Chinese ethnic, but also come from non-Chinese ethnicities. The need for literacy materials for learning Mandarin is getting higher, this is needed to help the process of learning Mandarin language. This research used quantitative research methods with questionnaire data collection techniques. Respondents of this study were undergraduate students of Chinese Literature at Maranatha Christian University Bandung, class of 2019/2020. This study aims to determine the effectiveness of learning Chinese noun classifier words by using a Chinese noun classifier dictionary model based on alphabetical nouns in Indonesian.
Application of Deep Self-Attention in Knowledge Tracing

The development of intelligent tutoring system has greatly influenced the way students learn and practice, which increases their learning efficiency. The intelligent tutoring system must model learners' mastery of the knowledge before providing feedback and advices to learners, so one class of algorithm called "knowledge tracing" is surely important. This paper proposed Deep Self-Attentive Knowledge Tracing (DSAKT) based on the data of PTA, an online assessment system used by students in many universities in China, to help these students learn more efficiently. Experimentation on the data of PTA shows that DSAKT outperforms the other models for knowledge tracing an improvement of AUC by 2.1% on average, and this model also has a good performance on the ASSIST dataset.
Конструктивно-инструментальные основания концепции включающего общества

The article presents an instrumental and philosophical approach to the philosophy of education, to its areas related to inclusive education. It is shown that the demonstration of the features of the philosophy and special methods of inclusion is a significant moment in the integral construction of the" inclusive " society. It is considered that in the space of a special social group there is a process of joint purposeful activity of subjects with the PLO, their training and education in the framework of the implementation of practical tasks for the organization of the effective functioning of the" inclusive " society.
Automated Dynamic Concurrency Analysis for Go

The concurrency features of the Go language have proven versatile in the development of a number of concurrency systems. However, correctness methods to address challenges in Go concurrency debugging have not received much attention. In this work, we present an automatic dynamic tracing mechanism that efficiently captures and helps analyze the whole-program concurrency model. Using an enhancement to the built-in tracer package of Go and a framework that collects dynamic traces from application execution, we enable thorough post-mortem analysis for concurrency debugging. Preliminary results about the effectiveness and scalability (up to more than 2K goroutines) of our proposed dynamic tracing for concurrent debugging are presented. We discuss the future direction for exploiting dynamic tracing towards accelerating concurrent bug exposure.
Educación a distancia ante la emergencia sanitaria por COVID-19. Condiciones, procesos y perspectivas de estudiantes normalistas

This article presents the results of a mixed empirical study with a cross-sectional design, of a descriptive type, the purpose of which is to know the conditions, processes and student perceptions regarding distance education with the use of digital media carried out in the situation of confinement due to the pandemic of COVID-19. 208 undergraduate students in several majors in high school teaching participated. A questionnaire with open-ended and multiple-choice questions was used. Based on the findings, it is noted that the digital divide is present in an important way; the learners that are “digital natives” present opportunities for improvement in the use of digital media for study and work purposes. The shift to distance mode had a predominantly adverse effect; however, in several cases, it represented an opportunity for personal and professional development. The distance work experience is mostly valued as “not great” (40.5%) and “good” (33%), and the attention given to particular situations that affected student achievement as “good” (53%) and “not great” (22%). The article’s main proposals for improvement are: a) on the part of teachers more and better communication with the learners, commitment and organization of work, as well as sensitivity to understand situations that exceed student possibilities; b) at the institutional level, training in the use of digital media for teachers and students, and unification of the type of work platform. Student commitments focus on greater enthusiasm and responsibility for work.
Pengembangan Sistem Informasi Inventori Barang Berbasis Website Menggunakan Model Rapid

Within a company, data processing is very important for a company to take place. But many companies do not have good data processing. There are still many things that cause data processing errors. Including in PT. Indojaya Multi works, data processing in this company including poor data processing so that there are still many errors that have occurred. Pt. Indojaya Mukti Karya is one of the companies established in Indonesia that provides goods and serves the implementation of the project that is shiny floor. Therefore, we try to develop data processing in the company to be better and efficient. In order to avoid mistakes that have occurred, for that we develop an Inventory system that has several features such as goods forms, clients, suppliers, warehouses and QR codes. In its application this information system is created using the programming language html, css, java script, php and database. And so this information system aims to minimize data processing errors in the company.
Adversarial Attack Driven Data Augmentation for Accurate And Robust Medical Image Segmentation

Segmentation is considered to be a very crucial task in medical image analysis. This task has been easier since deep learning models have taken over with its high performing behavior. However, deep learning models dependency on large data proves it to be an obstacle in medical image analysis because of insufficient data samples. Several data augmentation techniques have been used to mitigate this problem. We propose a new augmentation method by introducing adversarial learning attack techniques, specifically Fast Gradient Sign Method (FGSM). Furthermore, We have also introduced the concept of Inverse FGSM (InvFGSM), which works in the opposite manner of FGSM for the data augmentation. This two approaches worked together to improve the segmentation accuracy, as well as helped the model to gain robustness against adversarial attacks. The overall analysis of experiments indicates a novel use of adversarial machine learning along with robustness enhancement.
Semi-Supervised Few-Shot Classification with Deep Invertible Hybrid Models

In this paper, we propose a deep invertible hybrid model which integrates discriminative and generative learning at a latent space level for semi-supervised few-shot classification. Various tasks for classifying new species from image data can be modeled as a semi-supervised few-shot classification, which assumes a labeled and unlabeled training examples and a small support set of the target classes. Predicting target classes with a few support examples per class makes the learning task difficult for existing semi-supervised classification methods, including selftraining, which iteratively estimates class labels of unlabeled training examples to learn a classifier for the training classes. To exploit unlabeled training examples effectively, we adopt as the objective function the composite likelihood, which integrates discriminative and generative learning and suits better with deep neural networks than the parameter coupling prior, the other popular integrated learning approach. In our proposed model, the discriminative and generative models are respectively Prototypical Networks, which have shown excellent performance in various kinds of few-shot learning, and Normalizing Flow a deep invertible model which returns the exact marginal likelihood unlike the other three major methods, i.e., VAE, GAN, and autoregressive model. Our main originality lies in our integration of these components at a latent space level, which is effective in preventing overfitting. Experiments using mini-ImageNet and VGG-Face datasets show that our method outperforms selftraining based Prototypical Networks.
Importancia de las competencias digitales en los alumnos de nivel medio superior

Digital skills are of great importance in the development of individuals to face the technological challenges that arise every day. With the confinement of students in their homes due to the emergence of COVID-19, is important the need to apply the digital skills of both students and teachers, to continue the educational process. There are five fundamental areas of digital competences according to the European Framework of Digital Competences, developed by the Joint Research Centre (JRC), which include 21 competencies that individuals must develop with respect to the use of information and communication technologies (Tics). A questionnaire was applied to high school students from the Escuela de Bachilleres Diurna de Pánuco, Veracruz, to identify the level of digital skills that students have, which would allow support in the development of their online classes. This article describes the results of the instrument applied in each of the areas where digital skills are classified.
Algebraic methods in difference sets and bent functions

We provide some applications of a polynomial criterion for difference sets. These include counting the difference sets with specified parameters in terms of Hilbert functions, in particular a count of bent functions. We also consider the question about the bentness of certain Boolean functions introduced by Carlet when the $\mathcal{C}$-condition introduced by him doesn't hold.
A Classification Framework of Identifying Major Documents With Search Engine Suggestions and Unsupervised Subtopic Clustering

This paper addresses the problem of automatic recognition of out-of-topic documents from a small set of similar documents that are expected to be on some common topic. The objective is to remove documents of noise from a set. A topic model based classification framework is proposed for the task of discovering out-of-topic documents. This paper introduces a new concept of annotated {\it search engine suggests}, where this paper takes whichever search queries were used to search for a page as representations of content in that page. This paper adopted word embedding to create distributed representation of words and documents, and perform similarity comparison on search engine suggests. It is shown that search engine suggests can be highly accurate semantic representations of textual content and demonstrate that our document analysis algorithm using such representation for relevance measure gives satisfactory performance in terms of in-topic content filtering compared to the baseline technique of topic probability ranking.