Reviewerly/exHarmony huggingface dataset:
HISTORY OF THE DEVELOPMENT OF PROSE WORKS

The article examines the problem of professional training of actors and directors through verbal action in the process of reading a text. Verbal action is a popular concept among many teachers of stage language and acting. The pedagogical education of the individuality of each student in the process of reading the text through verbal influence raises the problem of the relationship between his knowledge and further professional development. The system of progressive study of theoretical concepts of different levels of complexity allows future actors and directors to easily reveal the stylistic nature of the text and develop language techniques based on the optimal level of their development and personal orientation.
User Experience (UX) Matters: What are the Most Desired Skills in the UX Designer and UX Researcher Job Ads

A content analysis study (N = 200) was conducted to examine the most desired skills required in UX designers and UX researchers job ads on the LinkedIn platform. Results showed the visual interface design skill is the most needed design skill for UX designers. For UX researchers, the research skills of usability lab studies, moderated remote usability studies, usability benchmarking, and interviews are most needed. Information Technology &amp; Service and Computer &amp; Network Security are industries that have the highest need in UX designers and UX researchers. The study suggests higher education institutes especially mass communications programs may need to consider adopting the UX concept and skills into its teaching agenda.
MULTILINGUAL LEARNABILITY AND REACTION TIME IN ONLINE SLAVIC INTERCOMPREHENSION EXPERIMENTS

Receptive multilingualism is a multidimensional and multifactorial phenomenon that crucially depends on the mutual intelligibility of closely related languages.As a strategy, it predominantly capitalizes upon a dynamic integration of linguistic, communicative, contextual, and socio-cognitive aspects.Relevant linguistic determinants (especially linguistic distances) along with recognizable extra-linguistic influences (such as attitude and exposure) have recently enjoyed increased attention in the research community.In our online (web-based) intercomprehension experiments, we have observed learning effects that appear to be empirically associated with individual cognitive skills.For this study, we tested 185 Russian subjects in a written word recognition task which essentially involved cognate guessing in Belarusian, Bulgarian, Macedonian, Serbian, and Ukrainian.The subjects had to translate the stimuli presented online into their native language, i.e.Russian.To reveal implicit multilingual learnability, we correlate the obtained intercomprehension scores with the detected reaction times, taking into consideration the potential influence of the experiment rank on the reaction time too.
THE ANALYSIS OF E-LEARNING SUCCESS BY USING DELONE AND MCLEAN SUCCESS MODEL (CASE STUDY: PERTAMINA UNIVERSITY)

Education is a crucial thing and highly concerned all over the world. As one of the educational institutions, the university has currently applied many information systems because of several obstacles and problems. With the fast development of information and communication technology, the learning process also has improved, known as e-learning. Pertamina University is a private university located in Jakarta, which has six faculties and 15 study programs. Since its inception in 2016, Pertamina University has applied e-learning to its students. Based on the conceptual models developed by DeLone &amp; McLean, this research aims to examine the success of the implementation of the e-learning system in Pertamina University with six variables, which are information quality, system quality, service quality, use, user satisfaction, and net benefit. The results of the study using 610 samples showed that the information quality variable did not affect the user satisfaction variable, which means that the quality of information on e-learning needed to be improved again to get a better response to user satisfaction.
A Comparative Study of RTOP and Chinese Classical Classroom Teaching Evaluation Tools

The new round of basic education curriculum reform in China recently will inevitably bring about the reform of classroom teaching. To find a method of testing the reformed classroom teaching effect so that it follows the new curriculum reform is a problem that needs to be solved urgently. On the basis of examining the evaluation concept and application of the "Reformed Classroom Teaching Observation Protocol (RTOP)" originated in the United States, we test the appropriateness of RTOP in China's classroom teaching evaluation environment from both qualitative and quantitative perspectives, with good results. By comparing the advantages and disadvantages of RTOP and China's "Toshiba Cup Scoring Table", it is found that RTOP can provide guidance for the transformation of classroom teaching evaluation concepts and the development of evaluation tools in the context of China's new curriculum reform.
Review of Articles Related to Mixed Reality in Education

With the development of technology, there have been developments in the field of education as in every field. Among these developments, it can be said that the most important developments regarding educational environments are reality technologies. These technologies can be divided into three categories as virtual reality, augmented reality and mixed reality. Since mixed reality, one of these technologies, is a combination of virtual and augmented reality, it is thought that studies in this field will contribute to studies in other realities. In this study, the articles using mixed reality technologies were systematically examined. After the examination, the articles were evaluated and classified according to the criteria determined. With the study, the distributions of the articles on mixed reality in the field of education between years 2016-2020 in the Web of Science database were found according to the determined criteria and inferences were made about these distributions. As a result of the study, it was concluded that most of the articles were published in 2020 and 2018. In addition to this result, it was determined that quantitative articles were much more than qualitative articles. It was seen that experimental-applied study was mainly chosen as the type of article. Science was found to be the most preferred learning area. It was seen that the undergraduate level was the most chosen sample level. It was determined that the questionnaire was the most chosen data collection tool. Finally, it was concluded that “50-99” and “0-24” are the most selected sample ranges in mixed reality research in education.
Improving Coronavirus Disease Tracking in Malaysian Health System

This paper proposes Covid-19 Tracing System (CTS) acts as a portal for the health center to update and track their patients' contacts and collect data for further analysis. All of the content is handpicked, filtered, and selected to the best of our ability by assigned individuals (mostly medical staff) to ensure that sources are credible and free of hoaxes for the public's benefit. This application likewise means to assemble information for the top to the bottom investigation (for example, time arrangement to screen the development, in-house patients) and synchronization with a contact following application, for instance, MySejahtera that was created and set up by the Malaysian government and utilized from one side of the country to the other. For simplicity of clients' understanding using Graphic visualizations and dashboards are incorporated.
Learning Faithful Representations of Causal Graphs

Learning contextual text embeddings that represent causal graphs has been useful in improving the performance of downstream tasks like causal treatment effect estimation.However, existing causal embeddings which are trained to predict direct causal links, fail to capture other indirect causal links of the graph, thus leading to spurious correlations in downstream tasks.In this paper, we define the faithfulness property of contextual embeddings to capture geometric distance-based properties of directed acyclic causal graphs.By incorporating these faithfulness properties, we learn text embeddings that are 31.3%more faithful to human validated causal graphs with about 800K and 200K causal links and achieve 21.1% better Precision-Recall AUC in a link prediction fine-tuning task.Further, in a crowdsourced causal question-answering task on Yahoo!Answers with questions of the form "What causes X?", our faithful embeddings achieved a precision of the first ranked answer (P@1) of 41.07%, outperforming the existing baseline by 10.2%.
Risk Minimization for Zero-shot Sequence Labeling

Zero-shot sequence labeling aims to build a sequence labeler without human-annotated datasets.One straightforward approach is utilizing existing systems (source models) to generate pseudo-labeled datasets and train a target sequence labeler accordingly.However, due to the gap between the source and the target languages/domains, this approach may fail to recover the true labels.In this paper, we propose a novel unified framework for zero-shot sequence labeling with minimum risk training and design a new decomposable risk function that models the relations between the predicted labels from the source models and the true labels.By making the risk function trainable, we draw a connection between minimum risk training and latent variable model learning.We propose a unified learning algorithm based on the expectation maximization (EM) algorithm.We extensively evaluate our proposed approaches on cross-lingual/domain sequence labeling tasks over twenty-one datasets.The results show that our approaches outperform state-of-the-art baseline systems.
Using Machine Learning to Predict Chat Difficulty

This study aims to evaluate the effectiveness and potential utility of using machine learning and natural language processing techniques to develop models that can reliably predict the relative difficulty of incoming chat reference questions. Using a relatively large sample size of chat transcripts (N = 15,690), an empirical experimental design was used to test and evaluate 640 unique models. Results showed the predictive power of observed modeling processes to be highly statistically significant. These findings have implications for how library service managers may seek to develop and refine reference services using advanced analytical methods.
The Power of Literal Equivalence in Model Counting

The past two decades have seen the significant improvements of the scalability of practical model counters, which have been quite influential in many applications from artificial intelligence to formal verification. While most of exact counters fall into two categories, search-based and compilation-based, Huang and Darwiche's remarkable observation ties these two categories: the trace of a search-based exact model counter corresponds to a Decision-DNNF formula. Taking advantage of literal equivalences, this paper designs an efficient model counting technique such that its trace is a generalization of Decision-DNNF formula. We first propose a generalization of Decision-DNNF, called CCDD, to capture literal equivalences, then show that CCDD supports model counting in linear time, and finally design a model counter, called ExactMC, whose trace corresponds to CCDD. We perform an extensive experimental evaluation over a comprehensive set of benchmarks and conduct performance comparison of ExactMC vis-a-vis the state of the art counters, c2d, Dsharp, miniC2D, D4, ADDMC, and Ganak. Our empirical evaluation demonstrates ExactMC can solve 885 instances while the prior state of the art could solve only 843 instances, representing a significant improvement of 42 instances.
Dialogic Literary Circles as a Methodological Strategy for the training of students in Early Childhood Education Degree

The research has the purpose of analyzing the experience of the students of the first course of the Early Childhood Education Degree on the methodology of the Dialogic Literary Circles.The aim is to examine the variables that influence the academic performance of the future teacher, as well as the conditions that have an impact on their teaching-learning process, including Dialogical Literary Circles.A qualitative methodology has been used, from a phenomenological perspective.The Dialogic Literary Circles were implemented in the subject of "General Didactics" in the Early Childhood Education Degree during the year 2019-2010.The study is aimed at 230 students, of which 90 of them have agreed to participate in the discussion groups (9 groups of 10 people each) to collect the data.A script has been developed to direct the students' discourse and find out their perception of this methodological strategy.A content analysis was carried out with the information obtained, helping us from the Nvivo 12 program.Were obtained very positive results on the implications of this methodological strategy for the training of the university student.The students consider that through the Dialogic Literary Circles they have acquired pedagogical knowledge, but also this strategy has led them to value the collaborative work, the respect for the opinions of their peers, has encouraged reading and expanded vocabulary, besides developing communication and oral expression skills.Therefore, conclude that it is an active methodology, very pertinent to put it into practice at university, since it encourages in the initial training of teachers to be professionals with the skills required in today's society.
Adaptive Beam Search Decoding for Discrete Keyphrase Generation

Keyphrase Generation compresses a document into some highly-summative phrases, which is an important task in natural language processing. Most state-of-the-art adopt greedy search or beam search decoding methods. These two decoding methods generate a large number of duplicated keyphrases and are time-consuming. Moreover, beam search only predicts a fixed number of keyphrases for different documents. In this paper, we propose an adaptive generation model-AdaGM, which is mainly inspired by the importance of the first words in keyphrase generation. In AdaGM, a novel reset state training mechanism is proposed to maximize the difference in the predicted first words. To ensure the discreteness and get an appropriate number of keyphrases according to the content of the document adaptively, we equip beam search with a highly effective filter mechanism. Experiments on five public datasets demonstrate the proposed model can generate marginally less duplicated and more accurate keyphrases. The codes of AdaGM are available at: https://github.com/huangxiaolist/adaGM.
[A Gaussian mixture-hidden Markov model of human visual behavior].

Vision is an important way for human beings to interact with the outside world and obtain information. In order to research human visual behavior under different conditions, this paper uses a Gaussian mixture-hidden Markov model (GMM-HMM) to model the scanpath, and proposes a new model optimization method, time-shifting segmentation (TSS). The TSS method can highlight the characteristics of the time dimension in the scanpath, improve the pattern recognition results, and enhance the stability of the model. In this paper, a linear discriminant analysis (LDA) method is used for multi-dimensional feature pattern recognition to evaluates the rationality and the accuracy of the proposed model. Four sets of comparative trials were carried out for the model evaluation. The first group applied the GMM-HMM to model the scanpath, and the average accuracy of the classification could reach 0.507, which is greater than the opportunity probability of three classification (0.333). The second set of trial applied TSS method, and the mean accuracy of classification was raised to 0.610. The third group combined GMM-HMM with TSS method, and the mean accuracy of classification reached 0.602, which was more stable than the second model. Finally, comparing the model analysis results with the saccade amplitude (SA) characteristics analysis results, the modeling analysis method is much better than the basic information analysis method. Via analyzing the characteristics of three types of tasks, the results show that the free viewing task have higher specificity value and a higher sensitivity to the cued object search task. In summary, the application of GMM-HMM model has a good performance in scanpath pattern recognition, and the introduction of TSS method can enhance the difference of scanpath characteristics. Especially for the recognition of the scanpath of search-type tasks, the model has better advantages. And it also provides a new solution for a single state eye movement sequence.视觉是人类与外界交互并获取信息的重要方式。为了研究在不同条件下人类的视觉行为，本文采用了混合高斯-隐马尔可夫模型（GMM-HMM）对扫视过程中的眼动路径进行建模，并提出了一种新的模型优化方法——时移分段法（TSS）。TSS 方法可突出眼动序列中时间维度的特征，提升模式识别结果，增强模型稳定性。本研究对多维特征模式识别采用了线性判别分析（LDA）方法，以评价各模型的合理性及识别的准确性。全文共进行了四组对比试验，第一组应用了 GMM-HMM 模型对眼动路径进行建模分类，三分类准确率均值可达到 0.507，大于三分类机会概率（0.333）；第二组试验应用 TSS 方法，分类准确率均值提高至 0.610；第三组将 GMM-HMM 与 TSS 结合，分类准确率均值达到 0.602，且相较于第二组模型更稳定；最后，将模型分析结果与眼跳（SA）等特征分析结果进行比较，建模分析方法远好于基础信息分析方法。同时，通过对三类任务特性分析，结果显示，自由查看任务特异性较高，而对象搜寻任务的敏感度较高。综上所述，GMM-HMM 模型应用在眼动模式识别领域有较好的特征提取效果，引入 TSS 方法可以加强眼动特征差异，尤其对搜寻类任务的眼动路径识别有更好的优势，也为单一状态眼动序列提供了新的解决方案。.
Pelatihan Mendeley Sebagai Manajemen Referensi bagi Mahasiswa

The objectives of this service activity are: 1) To increase the knowledge of the participants, namely students, the importance of the Mendeley application as a reference management of library resources in research. 2) To improve the ability of the participants, namely students, to be able to operate the Mendeley application properly and correctly. The stages of work carried out by the implementing team in this community service program are providing training and providing assistance in managing reference sources of libraries in scientific works and being able to operate the Mendeley application properly and correctly. This activity was attended by 7th (seven) students of the Faculty of Economics, majoring in Accounting, UNG, who were preparing proposals and theses. The expected result of this service program is that it can improve the skills of students as young researchers to manage references to library sources or citations so that the writings in scientific works are presented properly and correctly in accordance with the procedures for writing scientific papers that are applied.
Random Forests for Opponent Hand Estimation in Gin Rummy

We demonstrate an AI agent for the card game of Gin Rummy. The agent uses simple heuristics in conjunction with a model that predicts the probability of each card's being in the opponent's hand. To estimate the probabilities for cards' being in the opponent's hand, we generate a dataset of Gin Rummy games using self-play, and train a random forest on the game information states. We explore the random forest classifier we trained and study the correspondence between its outputs and intuitively correct outputs. Our agent wins 61% of games against a baseline heuristic agent that does not use opponent hand estimation.
New Synonyms Extraction Model Based on a Novel Terms Weighting Scheme

The traditional statistical approach in synonyms extraction is time-consuming. It is necessary to develop a new method to improve the efficiency and accuracy. This research presents a new method in synonyms extraction called Noun Based Distinctive Verbs (NBDV) that replaces the traditional tf-idf weighting scheme with a new weighting scheme called the Orbit Weighing Scheme (OWS). The OWS links the nouns to their semantic space by examining the singular verbs in each context. The new method was compared with important models in the field such as the Skip-Gram, the Continuous Bag of Words, and the GloVe model. The NBDV model was manipulated over the Arabic and English languages and the results showed 47% Recall and 51% Precision in the dictionary-based evaluation and 57.5% Precision in the human experts’ evaluation. Comparing with the synonyms extraction based on tf.idf, the NBDV obtained 11% higher recall and 10% higher precision. Regarding the efficiency, we found that on average, the synonyms extraction of a single noun requires the process of 186 verbs and in 63% of the runs; the number of singular verbs was less than 200. It is concluded that the developed method is efficient and processes the single run in linear time.
DIGITAL DATA PROCESSING BASED ON WAVELET TRANSFORMS

The paper focuses on the main theoretical principles and properties of wavelet transforms. The problem of digital data processing based on wavelet transforms is considered. The analysis and processing of signals and functions that are non-stationary in time and inhomogeneous in space are presented. The authors propose methods of progressive coefficients’ values that combine wavelet decomposition and quantization, the main purpose of which is to convey the most important piece of information about a signal.
IoT BASED HOUSING AREA PORTAL WITH NODEMCU, WEB AND ANDROID APPLICATIONS

The access time of using the portal in certain blocks in a residential area can be a problem for some residents. Another problem that arises is if the officer holding the portal key is not in place. The purpose of this study is to create a system to regulate access rights to a particular block within a residential area so that the opening and closing of the portal can be done at any time by residents in the intended area. There are several blocks of this system, namely the NodeMCU controller block, ESP32CAM, Android applications, and web applications that are built using the PHP and MySQL programming languages. NodeMCU is used as the main controller to manage servo motors, send and receive data to and from the server, receive input related to open and close portals from the android application. The web application is used to register users, view the portal usage log, and verify the login process of the application. This system has been running well based on the results of tests that have been carried out, where the registration process, login, opening and closing portals, log usage is in accordance with the objectives to be achieved.&#x0D; Index Terms—Portal; NodeMCU; ESP32CAM; Android; Web Application