Reviewerly/exHarmony huggingface dataset:
Pooled Sample Testing with Clustering (For Efficient COVID-19 Screening)

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Challenges and Working Solutions in Agile Adaptation: Experiences from the Industry.

Science Foundation Ireland 10/CE/I1855, 13/RC/20194 European Regional Development Fund 113E528
Peer Review Jurnal Nasional Terakreditasi Sinta 2 Illocutionary Acts in Religious Discourse: The Pragmatics of Nouman Ali Khan’s Speeches

This present inquiry is designed to investigate the use of illocutionary acts in Nouman Ali Khan’s speeches and analysing the functions of the types of illocutionary acts from the speeches. The method applied was the descriptive qualitative method to conduct the research. The data were collected by using the textual analysis and open coding from three speeches by Nouman Ali Khan in a seminar titled “When Muslims Works Together” at the Islamic Association of North Texas (IANT). They are classified into some categories based on Searle’s theory. The finding of this study showed that (1) there are four types of illocutionary acts; representatives, directives, commissives, and expressives, (2) the illocutionary representatives is the most frequent types of illocutionary act appeared in the speeches, i.e., 306 utterances or 63.22% with five functions; informing, stating, describing, reminding and concluding, (3) then, the second most frequently types of illocutionary act appeared in the speeches was the illocutionary directives, i.e., 144 utterances or 29.75% with five functions; suggesting, commanding, inviting, forbidding and questioning, (4) the illocutionary commissives occurred in 22 utterances or 4.55% with two functions; promising and warning., (5) the illocutionary expressives is found in 12 utterances or 2.48% with two functions; praising and expressing hope or wish, and (6) lastly, the declaratives types was not identified in the speeches as it requires specific circumstances.
Distance education of students

The aim of the study is to reveal the typical social and psychological opportunities and limitations of distance learning via the Internet. The study of scientific-methodical and pedagogical literature on the problem of social and psychological opportunities and limitations in distance learning in higher education institutions were used. The article presents the views of scholars on the theoretical aspects of social and psychological opportunities and limitations of distance education of university students. Different aspects of students' attitude to distance learning in the conditions of coronavirus pandemic spreading have been described based on a survey of humanities students. Based on the results of the research, three groups of opportunities and limitations of distance education of students ― pedagogical, information-technological, and psychological ― as well as their content have been identified.
Maintenance des bases de connaissances à l'aide de contraintes

Knowledge bases are huge collections of primarily encyclopedic facts. They are widely used in entity recognition, structured search, question answering, and other tasks. These knowledge bases have to be curated, and this is a crucial but costly task. In this thesis, we are concerned with curating knowledge bases automatically using constraints. Our first contribution aims at discovering constraints automatically. We improve standard rule mining approaches by using (in-)completeness meta-information. We show that this information can increase the quality of the learned rules significantly. Our second contribution is the creation of a knowledge base, YAGO 4, where we statically enforce a set of constraints by removing the facts that do not comply with them. Our last contribution is a method to correct constraint violations automatically. Our method uses the edit history of the knowledge base to see how users corrected violations in the past, in order to propose corrections for the present.
STIL - Simultaneous Slot Filling, Translation, Intent Classification, and Language Identification: Initial Results using mBART on MultiATIS++

Slot-filling, Translation, Intent classification, and Language identification, or STIL, is a newly-proposed task for multilingual Natural Language Understanding (NLU). By performing simultaneous slot filling and translation into a single output language (English in this case), some portion of downstream system components can be monolingual, reducing development and maintenance cost. Results are given using the multilingual BART model (Liu et al., 2020) fine-tuned on 7 languages using the MultiATIS++ dataset. When no translation is performed, mBART’s performance is comparable to the current state of the art system (Cross-Lingual BERT by Xu et al. (2020)) for the languages tested, with better average intent classification accuracy (96.07% versus 95.50%) but worse average slot F1 (89.87% versus 90.81%). When simultaneous translation is performed, average intent classification accuracy degrades by only 1.7% relative and average slot F1 degrades by only 1.2% relative.
WEB OF SCIENCE JOURNAL EVALUATION PROCESS: EVOLUTION OF CRITERIA

The Web of Science Core Collection is a highly selective, abstract-indexed scientometric database, which currently includes more than 21 thousand scientific journals of all specialties published in 110 countries. The database contains three specialized indexes: Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), Art and Humanities Citation Index (AHCI) and a multidisciplinary Emerging Source Citation Index (ESCI). Today there are 15 Ukrainian journals included in the SCIE and 68 in the ESCI. Unfortunately, since 2015, no Ukrainian journals have moved from ESCI to specialized indexes; moreover, several Ukrainian journals were excluded for publishing ethics violations. In 2019, the criteria of journal evaluation were updated/clarified. Today there are 28 criteria; 24 of them (quality criteria) are a prerequisite for inclusion into the ESCI. Journals applying to specialized indexes are evaluated according to four additional criteria of influence. The evaluation is carried out by the Clarivate Editorial Board consisting of company employees, who, in addition to professional skills, do not have any conflicts of interest. To initiate the journal evaluation process, the publisher fills out an online form and continues to publish the journal in a timely manner. Evaluation and subsequent indexing of the journal in the Web of Science Core Collection is a free procedure and the criteria are presented in the article.
Neural Machine Translation Using Extracted Context Based on Deep Analysis for the Japanese-English Newswire Task at WAT 2020

This paper describes the system of the NHK-NES team for the WAT 2020 Japanese–English newswire task. There are two main problems in Japanese-English news translation: translation of dropped subjects and compatibility between equivalent translations and English news-style outputs. We address these problems by extracting subjects from the context based on predicate-argument structures and using them as additional inputs, and constructing parallel Japanese-English news sentences equivalently translated from English news sentences. The evaluation results confirm the effectiveness of our context-utilization method.
Maximum energy efficiency on photovoltaic solar panels by using an innovative solar tracker

Abstract The solutions currently used for the acquisition of solar energy are based on fixed mechanical structures, in which the photovoltaic panels are either ground-mounted or building-integrated, positioned on suitable rooftops. Both solutions involve the partial take-over of solar energy, thus a reduced energy efficiency of the photovoltaic installation. The solution proposed by the authors of the paper has an innovative mechanical construction and a mixed mode of operation, which combines the secular way with that of the tracking. The operation of the solar tracker presented in the paper is based on the programming in LabVIEW, with the use of a general module for the acquisition/generation of analogue and digital signals. The design developed by the authors has a simple mechanical construction, and the positioning considers the clock of the PC, so that the initial positioning (at start-up) is done in a simplified manner, regardless of the geographical placement of the tracker. The authors performed experiments in the laboratory and in the field, the results being consistent with the theoretical assumptions.
Curriculum Learning with Diversity for Supervised Computer Vision Tasks

Curriculum learning techniques are a viable solution for improving the accuracy of automatic models, by replacing the traditional random training with an easy-to-hard strategy. However, the standard curriculum methodology does not automatically provide improved results, but it is constrained by multiple elements like the data distribution or the proposed model. In this paper, we introduce a novel curriculum sampling strategy which takes into consideration the diversity of the training data together with the difficulty of the inputs. We determine the difficulty using a state-of-the-art estimator based on the human time required for solving a visual search task. We consider this kind of difficulty metric to be better suited for solving general problems, as it is not based on certain task-dependent elements, but more on the context of each image. We ensure the diversity during training, giving higher priority to elements from less visited classes. We conduct object detection and instance segmentation experiments on Pascal VOC 2007 and Cityscapes data sets, surpassing both the randomly-trained baseline and the standard curriculum approach. We prove that our strategy is very efficient for unbalanced data sets, leading to faster convergence and more accurate results, when other curriculum-based strategies fail.
UMA ANÁLISE COMPARATIVA ENTRE FLUTTER E REACT NATIVE COMO FRAMEWORKS PARA DESENVOLVIMENTO HÍBRIDO DE APLICATIVOS MOBILE: ESTUDO DE CASO VISANDO PRODUTIVIDADE

As mobile applications and smartphones become increasingly popular and accessible to the population, it is normal to have a large demand in the app development field for various sorts of problems. The choice of a good development framework is essential for the creation and maintenance of an application, mostly for a company whose goal is having the lowest cost possible or for developers who wish to have good productivity while developing a project. This article aims to carry out a comparative analysis between the two most popular hybrid mobile development frameworks in the market, focusing on productivity during the development process.
Sistem Referensi Pemilihan Smartphone Android Dengan Metode Fuzzy C-Means dan TOPSIS

Difficulties faced by STMIK Pontianak students while choosing an Android smartphone are the diversity of brands, types, series and specifications makes it hard to choose which is the best. Determine that matches to needs along with an appropriate budget also difficult. This research aims to design a reference system for selecting an Android smartphone to resolve the problem. This system was developed using the Fuzzy C-Means algorithm and TOPSIS. The research method used is survey. Software design uses agile with extreme programming models also White-Box Testing, cluster center testing, and acceptance testing. This research found a method to get an alternative group that matches to the user from existing cluster by Euclidean Distance. This research produces a system that can clustering smartphone data and provide references in the form of alternatives that matches to the user. The test results using White-Box Testing produce all functions running well. Testing the cluster center using MSE gets the central error values ​​C1: 1.8481, C2: 2.5316, and C3: 1.8214. Acceptance tesing results above 70%. Weaknesses in this system do not discuss lifestyle needs in choosing an Android smartphone. The criteria used in this research is still technical and not use non-technical criteria.
ANALYSIS OF INTEGRATION PROCESS IN ENVIRONMENTAL AND TECHNICAL EDUCATION AS A KEY TO FORMATION OF ENVIRONMENTAL WORLD OUTLOOK AMONG ENGINEERING SPECIALISTS

The relevance of the analysis is that the global ecological crisis, in which humanity exists, is a result of the influence of many factors and, first of all, the egocentric, consumer attitude towards the natural environment.The production of material goods has led to the widespread introduction of new technologies, which, in parallel with positive results, have caused a significant negative anthropogenic load on nature and the supercritical exploitation of natural resources by man.But there is another significant reason for the ecological crisis -this is the insufficient level of environmental education and upbringing, in general, the environmental consciousness of the majority of inhabitants on our planet.Despite that, the training of specialists with an appropriate level of environmental knowledge, environmental awareness and worldview on the basis of new criteria for assessing relationship between human society and nature, should become one of the most powerful key factors in solving the extremely acute environmental and socio-economic problems of modern Ukraine.The purpose of the article is to analyze the foundations of the integration process in environmental and technical education, taking into consideration the environmental component in the education of future specialists in Engineering in order to form their ecological worldview.Methodology -the use of the analytical research method as a way of theoretical assimilation of reality and the construction of practical activity.Result.As a result of analysis, the environmental problems in Ukraine as prerequisites for the formation of an environmental outlook among future specialists are considered.Possible approaches to the integration of environmental and technical education are proposed as the basis for the formation of an environmental outlook among engineering specialists.The fundamentals of greening of technical education and the formation of the ecological competence among young specialists are analyzed.
LibGuides: LSC 504:Baby Story Time: Tools for Reading to the Wee Ones.: Reading Guides: Books, Websites, & Magazines

Reading and providing quality programming to your youngest patrons is quite the task: however, with the proper tools, you will be able to provide your wee patrons with many wonderful story time experiences and a lifetime love of reading.
Fostering Cooperative Learning through Reciprocal Reading Methods in German Online Class

Understanding of written texts is one of the important competencies that learners of German as a foreign language must master. Therefore, making students good readers is the main goal in the German middle class, where students must reach level B1. During online learning German there are obstacles in the learning process, especially in learning reading skills for middle-level German classes in the course. Deutsch 3. Students tend to be less active and teachers cannot control it directly because there is no face-to-face process. The results of the questionnaire to students showed that the teaching method used was considered less cooperative and boring. To overcome this problem, an integrated reading method or reciprocal reading is applied. This method (Palinscar and Brown 1984) requires interaction between students through an integrated reading strategy, namely summarizing, questioning, clarifying, predicting, and responding to what they read. The interaction between students increases their activity in class because they have to interact in order to understand the content of the reading that is being discussed. After the application of the reciprocal reading method, online learning reading skills in the Deutsch 3 course experienced significant changes. This is evidenced through the results of research findings which indicate differences in values and motivation between the control class and the experimental class. The post-test results showed that the experimental class experienced a higher increase in scores than the control class. In addition to increasing the value of the experimental class, there was also an increase in motivation as evidenced by the results of student questionnaires
Macroeconomics Fever in times of COVID-19: a Dynamic Stochastic General Equilibrium Model Analysis for Ethiopia

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Research on the Smart Classroom Mode Construction of College English Listening and Speaking under Mobile Internet Mode

The application and popularization of smart classroom teaching mode is the concrete embodiment of the high development of educational informatization. Based on reviewing the relevant studies on the smart classroom at home and abroad, following the characteristics of the mobile Internet era, the paper analyzes the connotation and characteristics of the smart classroom under mobile Internet environment; relying on the relevant language learning theories, it focuses on analyzing and constructing smart classroom teaching mode for college English listening and speaking course: an organic combination of online and offline activities throughout three stages of before, in and after class, with the purpose of providing reference and thinking for English teaching reform under mobile Internet environment and enhancing English teaching effect in an all-round way.
Post-digital practice and spatial specificity of music

The specificity of space aesthetics in virtual music is analyzed in the article, we consider the basic features of Homo Virtualis as a unity formed by effect of accessible Infinite and apperception of mostly affective-bodily experience. Hermeneutic potential of Homo Virtualis is provided by uniformed coding of sound qualities inside the digital continuum, transformed shapes of conceptual art. Sound performance of the open is embodied not only through the allusions of Ambient but refined post-digital aesthetics, aesthetics of ‘failure’, methods of ‘glitch’. Implementing philosophical and aesthetical tools we investigate ideology and practice of virtual music-making. Digital artists experience is considered via microsound technology, tele-immersion, as a version of post-digital with orientation on a myth of nature. It is shown that evocation of music and sound unity of Homo Virtualis reveal/bring to life ancient views about magic of the soundscape. Simultaneously, through ontological self-sufficiency of τέχνη in online music the fact that post-digital aesthetics belongs to the digital appears in hypostasis from aesthetical music being into impersonal media-message. Mutual representation of the truth and mystification which is specific to art is transforming into performed myth of involvement. Virtual music causes speculations on essence and limits of music
Hatching Egg Image Segmentation Based on Dense Blocks and the Hierarchical Sampling of Pixels

Fertility detection of hatching eggs is crucial in the manufacturing of vaccines. For hatching egg images, the segmentation results of blood vessels, cracks and air chambers are important for detecting the fertility of hatching eggs. In this paper, we propose an image segmentation method based on dense blocks and the hierarchical sampling of pixels. Dense blocks are used instead of the traditional layer-by-layer structure to improve efficiency and model robustness. The hierarchical sampling of pixels uses small batch sampling to add diversity during batch updates, which can accelerate learning. The sampled features are sparsely arranged and classified using an Multi-layer Perceptron(MLP), which can introduce complex nonlinear predictors and improve accuracy. The experimental results show that the MIoU reaches 90.5%. The proposed method can significantly improve the segmentation performance.
SEQUENCE-TO-SEQUENCE LEARNING FOR MOTION-AWARE CLAIM GENERATION

The goal of this research is to generate a motion-aware claim using a deep neural network approach: sequence-to-sequence learning method. A motion-aware claim is a sentence that is logically correlated to the motion while preserving its grammatical structure. Our proposed model generates a motion-aware claim in a form of one sentence and takes motion as the input also in a form of one sentence. We use a publicly available argumentation mining dataset that contains annotated motion and claim data. In this research, we propose a novel approach for argument generation by employing a scheduled sampling strategy to make the model converge faster. The BLEU scores and questionnaire are used to quantitatively assess the model. Our best model achieves 0.175 ± 0.088 BLEU-4 score. Based on the questionnaire results, we can also derive a conclusion that it is hard for the respondents to differentiate between the human-made and the model-generated arguments.
Self-served campaign management tool for contextual advertising

Advertising is an essential way of communicating value to the audience. Adlede does this with context in focus when finding articles with right content to the right campaigns. To know if matching a ...
DESIGNING THE DEVELOPMENT PROGRAM OF AN EDUCATIONAL ORGANIZATION AS AN ANTI-CRISIS STRATEGY

Despite the overall instability and unpredictability of the modern world and to be precise Russian educational system, the importance of having an insight into the perspectives and future directions of a particular educational organization cannot be doubted. That is why it is vital to explore the topic of choosing the right organizational priorities in short and long run and instruments to incorporate them into the task force.
The Future AI in Healthcare: A Tsunami of False Alarms or a Product of Experts?

Recent significant increases in affordable and accessible computational power and data storage have enabled machine learning to provide almost unbelievable classification and prediction performances compared to well-trained humans. There have been some promising (but limited) results in the complex healthcare landscape, particularly in imaging. This promise has led some individuals to leap to the conclusion that we will solve an ever-increasing number of problems in human health and medicine by applying `artificial intelligence' to `big (medical) data'. The scientific literature has been inundated with algorithms, outstripping our ability to review them effectively. Unfortunately, I argue that most, if not all of these publications or commercial algorithms make several fundamental errors. I argue that because everyone (and therefore every algorithm) has blind spots, there are multiple `best' algorithms, each of which excels on different types of patients or in different contexts. Consequently, we should vote many algorithms together, weighted by their overall performance, their independence from each other, and a set of features that define the context (i.e., the features that maximally discriminate between the situations when one algorithm outperforms another). This approach not only provides a better performing classifier or predictor but provides confidence intervals so that a clinician can judge how to respond to an alert. Moreover, I argue that a sufficient number of (mostly) independent algorithms that address the same problem can be generated through a large international competition/challenge, lasting many months and define the conditions for a successful event. Finally, I propose introducing the requirement for major grantees to run challenges in the final year of funding to maximize the value of research and select a new generation of grantees.