Reviewerly/exHarmony huggingface dataset:
Equivalence Levels of Literary Corpus Translation Using a Freeware Analysis Toolkit

Machine translation has the potential to make huge contributions to translation industries, but it seems, for now, that machine translation equivalence has led to a crucial point for literary translation by using machine translation because of the problem of the equivalence itself. This paper, therefore, aimed to see the equivalence degree of literary translation resulted by machine translation, i.e., freeware toolkit AntConc 3.5.0 software 2019. The data were collected from English-Indonesian J.K. Rowling's Harry Potter and The Order of The Phoenix novel by using the software to find the equivalent translation. The collected data were analyzed qualitatively based on the strategy of translation equivalent level proposed by Mona Baker (1992). The analyzed data revealed that the equivalent level of the software mostly occurred in a word level, above word level, and grammatical level. The software was likely difficult to find a textual level and a pragmatic level of translation equivalence because they required a context and still needed human involvement as part of a greater creative project of translation which were not done by the machine translation. After all, Antconc 3.5.0 as Computer Assisted Tool (CAT) brought a huge contribution to translation industry, helped to analyze large corpora particularly to find the degree of translation equivalence in word and above word level.
Generalized method to validate social distancing using median angle proximity methodology

Social distancing in industries as well as all public places due to the breakdown of pandemic of COVID-19 is currently of global interest. An advanced global solution for social distancing monitoring among the group of people in real time using computer vision and deep learning is proposed. A state of art method, Median angle proximity method is proposed on the coordinates obtained from the YOLOv3 (You only look once) algorithm to determine the predefined threshold resulting in the social distancing violating bounding boxes. The violating bounding boxes are then saved as single images using deep sort method. All the parts of the work are done using opensource programming language. The work has met all the requirements planned and is considered to be ready for deployment in real time with an average accuracy of 85%
Poster: Blockchain Application Feasibility in Telehealth for DSCSA Compliance

Interest in blockchain applications for supply chain management is on the rise. Recent regulatory relief enabling telehealth expansion across the United States, coupled with drug tracking requirements mandated by the Drug Supply Chain Security Act (DSCSA), necessitates an evidence-based understanding of feasible blockchain applications for the DSCSA-compliant tracking of drugs prescribed to remote patients who use personal devices to access telehealth. The purpose of this project is twofold: first, to identify use cases for DSCSA-compliant blockchain applications for telehealth and second, to formulate stakeholder recommendations with regard to policy and technical issues surrounding the current regulatory framework for blockchain applications in health care.
Communicative Language Ability and HOT or LOT of English National Final Examination Test Items

&lt;p&gt;This article aimed to observe and analyzed English national final examination test items for senior high school. This research identified and determined the variation of the test items’ level of questions, analyzed the number of higher order thinking and lower order thinking of the test items and analyzed the communicative language ability that exist in the tests items. This study was conducted through qualitative research focusing on the content analysis method. The data source used in this study was document of English National Examination including the transcript of the listening tests. The data taken from document of English National Examination were all English test items of UN for SMA 2014. The writer took documents of English UN for SMA including the cassette of its listening section from SMA Negeri 1 Rao, Pasaman Regency West Sumatera. The test items were observed, classified, analyzed, and then the results were interpreted and drew the conclusion. This study was done by analyzing the test items document due to the levels of questions and communicative language ability, after all the types was identified and written down, they were used as the basis to make inferences and draw the conclusion.&lt;/p&gt;
Collaborative Learning Network for Scene Text Detection

Text detection in the wild has been a popular research topic, and previous approaches to scene text detection have achieved promising performances across various benchmarks. In general, these methods use a large number of labels with precise character positions as training data. However, accurate annotation of large amounts of training data is a challenge. On the other hand, image-level annotation can be quickly obtained from rich media in a tag retrieval manner. Therefore it is essential to investigate how to improve the performance of strongly supervised text detection models through image-level annotation data. In this work, we propose a training framework for collaborative learning of a weakly supervised text classification network and a strongly supervised text detection network. The collaborative learning of the two sub-task networks is achieved by constraining the consistency of the two networks at the perceptual level. Experiments on standard data set ICDAR2015 show that the framework can significantly improve the performance of the strongly supervised text detection network by training using image-level annotation data.
The Effect of Qigong Exercise on the Teacher’s Work Stress Level

Teachers are a population at risk of experiencing work stress due to excessive workloads.This condition requires management so that it does not affect work productivity and health.This study aims to identify the effect of qigong exercise on the teacher's work stress level.This research method is Pre-Experimental with one group of pre and post-test design.This research used a purposive sampling technique.The respondents were not allowed to do other relaxation therapies.Qigong exercise was done three times for 50 minutes per session in a week.The instruments were questionnaires of work stress level.The test was the Wilcoxon Signed Rank Test.This study passed the ethical test.The median value in preintervention was 51.00 and the value in post-intervention was 45.00.There is the effect of qigong exercise on the teacher's work stress with a p-value of 0.011 (<0.05).Qigong exercise can reduce work stress by reducing the secretion of the hormone cortisol.The exercise needs to be practiced regularly at least three times for 50 minutes per session in a week to obtain an optimal result in reducing workstress.
Fraud Detection in NFC-Enabled Mobile Payments: A Comparative Analysis

Near field communication (NFC) is a short-range wireless communication technology that bestows contactless payments. Mobile Commerce is an amplification of electronic commerce and makes use of a mobile device to conduct a payment transaction. The growing popularity of mobile banking has led to an increase in fraudulent payment transactions thus resulting in financial losses. Therefore, the state-of-the-art solutions is required to detect and prevent fraud in mobile payments. This paper presents a comparative analysis of various fraud detection techniques for NFC-enabled mobile payments and evaluates each technique based on certain parameters.
Del aprendizaje tradicional al aprendizaje invertido como continuidad del proceso educativo en contexto de COVID-19 / From traditional learning to Flipped learning as a continuity of the educational process in the context of COVID-19

This health crisis that impacts the entire world has caused an enormous opportunity in teaching to rethink the way in which the teaching process is conceived and exercised, to reflect on where and how it is taught and to improve both dimensions of educational practice when it is resumed the presence. Many teachers and students had to relearn a new way of accessing knowledge and interacting in cyberspace. The objective of this work is to present the experience of using the inverted learning method in the continuity of the subject Introduction to Computer Science II, taught to first-year students in Faculty 3 belonging to the University of Computer Sciences, in the current context of COVID-19. In this process, support spaces were generated for the students, didactic materials and other results were obtained, such as comprehensive attention to the educational needs of the group and of each student in particular.
Chaotic True Random Number Generator for Secure Communication Applications

This work is proposed chaotic true random number generator (TRNG) based on chaotic PWM sequence generator. The chaos CMOS circuit presents here is the chaotic sequence generator. The main components of the chaotic PWM circuit is chaotic sequence generator for chaotic triangular waveforms. The chaotic TRNG was designed by using 0.18μm CMOS process. The full system is prose to be a implementation of IoT secure data communication system using chaotic security.
Impacts of Climate Variability on Sustainable Agriculture in Imo State, Nigeria

Rainfall and Temperature are important factors in agriculture especially in Nigeria where rain-fed agriculture is practiced extensively and agriculture contributes to food security and provides employment for urban and rural dwellers. Therefore, climate variability represents a major danger to agriculture by modifying the rainfall and temperature pattern, thereby resulting to a big peril in the sustainability of agriculture. This is the reason all countries of the world are concerned about the effects of climate variability on agriculture. This work therefore, examined the impact of climate variability on rainfall and temperature in Imo State, South Eastern Nigeria. The rainfall and temperature data were gotten from Nigerian Meteorological Agency (NIMET) for a period of 30 years which was analyzed by using descriptive statistics, decadal distribution, trend graph anomalies and 5 year moving average. The analysis showed increasing trend pattern in yearly maximum, minimum temperature and decrease in annual rainfall, The third order polynomial trend shows a decrease in the anomaly of annual mean rainfall (y = -0.0002x4) and a persistent increase in the mean temperature anomaly especially in the second decade (1996-2007).The discoveries show that there is a notable variability in temperature and rainfall pattern which revealed an increase in temperature and decrease in annual rainfall. This calls for serious attention as people in this part of Nigeria critically depend on rainfall for agricultural practices.It is recommended that government should support the agricultural sector by providing mechanized farming systems such as irrigation and drilling of water borehole in farm sites for agriculture, especially for the rural farmers and create awareness to the farmers on recent trends in climate issues to achieve sustainable agriculture.
Postgraduates’ attitude towards postgraduate education and scientific and lecturing activity

Analyzed is the problem, connected with the fact, that scientific community has long been concerned about effectiveness of the system of postgraduate education. It has changed a lot in recent years. Today’s PhD graduates do not have enough classical training; they need to acquire a broader set of skills required for their future research activity beyond the academy. In this regard, PhD graduates have not considered their employment in the scientific field as a whole since the 2000s. Thus some areas of training programs have been massed, which has led to the depreciation of the academic degree. Since 2014, the Russian postgraduate training system has been functioning as the third level of higher education being the integration of educational and research components. Changes have led to the fact that doctoral programs have become more pedagogically oriented, preparing the future candidate of Sciences to work in higher and secondary education. At the moment, the graduation level is approximately 12% of the total number of graduate doctorate students. The percentage of doctoral graduates’ completion has continued to decline steadily since 2014. The article deals with the postgraduates` attitudes towards postgraduate education and scientific and teaching activity.
Aeromagnetic map of Burney and the surrounding area, northeastern California

First posted February 11, 2021 For additional information, contact: Director,Geology, Minerals, Energy, & Geophysics Science CenterMenlo Park, CaliforniaU.S. Geological Survey345 Middlefield RoadMenlo Park, CA 94025-3591 An aeromagnetic survey was conducted to improve understanding of the geology and structure in the area around Burney, northeastern California. The new data are a substantial improvement over existing data and reveal a prominent north northwest-trending magnetic grain that allows extension of mapped faults, delineation of plutons within the Mesozoic basement in the northern Sierra Nevada, and linear anomalies that limit the amount of strike-slip offset along various faults in the area.
Report of the ALCTS Electronic Resources Interest Group Meeting. ALCTS Virtual Interest Group Week, June 2020

On Friday, June 12, the ALCTS Electronic Resource Interest Group hosted a session for the ALCTS Virtual Interest Group Week. A total of six presentations were chosen for a series of lightning talks...
VIKOR Model of TBM Construction Risk Prediction for a Long Inclined Shaft in a Coal Mine based on Trapezoidal Vague Set

Accurate warning is realized in this study in order to improve the reliability of the construction risk analysis model of shield machine (tunnel boring machine, TBM) in a long inclined shaft of coal mine.First, the risk factors of TBM construction of a long inclined shaft in coal mine were identified, the index system of secondary risk assessment was established, and the classification standard of risk grade was determined.Then, on the basis of introducing two trapezoidal vague number algorithms, the trapezoidal vague number BM operator and the weighted arithmetic average operator were proposed, respectively, and several conclusions were obtained.The weight vector of the risk index was determined by the deviation maximization method, after which the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) model based on the trapezoidal Vague number was established.Finally, the TBM construction risks of the long inclined shaft (No. 2 test well) in the Taigmiao mining area of Shenhua Group of China was evaluated, and the trends were forecasted by using this model.Results show that: (1) The risk method proposed in this study can effectively depict and deal with uncertain monitoring information.(2) Compared with the results of the scoring method and the utility value method, the rankings of the optimal and the worst risk grades are maintained, and the ranking results obtained by the scoring method and the VIKOR method are also the same.(3) The calculated monitoring results are consistent with the actual safety conditions of the coal mine construction.Conclusions indicate that the model and method are effective and practical in coal mine risk assessment, which can provide a new way for the analysis and prediction of TBM construction risks in a long inclined shaft.
Thanks for Your Help! – The Value of Q&amp;A Websites for Refugee Integration

The huge number of people fleeing their home countries poses a challenge to refugees and host societies.Q&A websites are highly promising in supporting refugee integration, one long-term solution to displacement.In our study, we aim to identify how refugee Q&A websites are used and, as a result, what value they provide to their users with respect to refugee integration.Based on data of the successful Q&A website 'Wefugees', we apply a mixed-methods approach consisting of descriptive statistics, social network analysis, and content analysis.Our results indicate that Q&A websites serve for the provision of information on a broad range of integrational topics and, surprisingly, constitute a one-way support service instead of leading to community building.We are the first to examine Q&A websites in this context and expand literature studying the role of digital services for refugee integration.Our results further provide design implications for refugee Q&A websites.
Evaluasi Usability Pada Aplikasi Pembelajaran Tari Menggunakan System Usability Scale (SUS)

The existence of dance in an area needs to be preserved so that it is not displaced by the entry of foreign cultural arts, The lack of interest of the younger generation in local culture needs to be watched out for because it has an impact on the sustainability of traditional dance. To introduce and motivate the younger generation to learn dance, an Android-based dance learning application has been developed. The purpose of this study was to evaluate the Android-based dance learning application, in the evaluation process involving 20 respondents to provide statements from the aspect of usability using the system usability scale (SUS) method consisting of the testing phase using 10 instruments for assessment, the data processing stage, the result analysis stage, and the result conclusion. The test results obtained a value of 79.37 with grade "B" means that the learning application that has been tested can be declared acceptable in the Acceptability Ranges category and it can be stated that the dance learning application is easy to use and can be used as a learning tools.
Deep Hierarchical App Recommendation with Dynamic Behaviors

Many app recommendation models have been proposed to provide mobile users with the apps that meet their individual needs. However, three main drawbacks limit their performance: (1) Neglect the dynamic change of user preferences in a short time; (2) Singly use either the machining learning or the deep learning method, which cannot learn discrete features or continuous features very well; (3) Directly deal with all apps without considering their hierarchical features. To overcome the above drawbacks, this paper proposes a Dynamic behavior-based age Hierarchy Model (DHM for short). To be specific, we integrate the Boosting Tree and Neural Network, combine the static data as basis and the dynamic behaviors as refinement, and update dynamic behaviors in time to improve the accuracy of personalized app recommendation. Then, this paper proposes a User Hierarchy based personalized App recommendation Model (UHAM for short), it exploits the user attribute layering method to make hierarchical recommendation for users in different age groups, which further enhance the efficiency. We conduct extensive experiments with a real app dataset, and the results validate the effectiveness of our model.
Impact of Probing-Prompting Learning Model towards Students’ Writing Speech Script Ability

The aim of the research was to explore whether the probing/prompting learning model influenced Indonesian English as a Foreign Language students’ ability to perform a speech. The method used in this research was an experimental method with random cluster sampling of students from an Indonesian English as a Foreign Language school ­– Medang Gili Senior High. There were two 10th grade classes of 22 and 25 students. The results of the lottery performed on the available classes established X-B class as the experimental group and X-A class as the control group. Results of the script-writing test indicated that the average score was 79 out of 100 (with the lowest score of 65 and the highest score of 90) and the median and mode were 80.2 and 81.5, respectively. The ability to write scripts using expository models for speeches was tested among the control class. Another test prompted the use of probing prompting. The results of the hypothesis testing (t test) showed a significant level of 0.05, indicating the significant influence of using probing-prompting learning model (5.00 is greater than t table 2.026), so H0 was rejected and H1 was accepted. Ultimately, the use of probing/prompting learning models had a demonstrably positive impact on tenth graders’ abilities to write speeches during the 2019-2020 academic year.
The Reality of Using E-Learning in Arab Schools in Israel from the Parents' Point of View

This study aimed at identifying the reality of using e-learning in Arab schools in Israel from the parents' point of view. A total of eighty eight (88) questionnaires were distributed through e- mail and Whats App application, and one eighty two (82) were completed and returned . The questionnaire consisted of (44) items divided into two fields (the reality of using of electronic curricula, and the reality of electronic technical facilities), and questionnaire applied to a random sample consisted of (82) parents, during the first academic semester 2020/2021. The study findings showed that the reality of using electronic curricula in Arab schools in Israel from the parents' point of view came in medium degree. Also the findings showed that the reality of the electronic technical facilities used in Arab schools in Israel from the parents' point of view came in medium degree. Keywords: E-Learning, Arab Schools, Israel, Parents. DOI: 10.7176/IKM/11-1-04 Publication date: January 31 st 2021
Cyber Security Situational Awareness Jointly Utilizing Ball K-Means and RBF Neural Networks

Low accuracy and slow speed of predictions for cyber security situational awareness. This paper proposes a network security situational awareness model based on accelerated accurate k-means radial basis function (RBF) neural network, the model uses the ball k-means clustering algorithm to cluster the input samples, to get the nodes of the hidden layer of the RBF neural network, speeding up the selection of the initial center point of the RBF neural network, and optimize the parameters of the RBF neural network structure. Finally, use the training data set to train the neural network, using the test data set to test the accuracy of this neural network structure, the results show that this method has a greater improvement in training speed and accuracy than other neural networks.
Regularization model based on transmission constraint

Aiming at the problems of blocking and artifacts in traditional dark channel prior dehazing algorithms, an image dehazing algorithm based on dark channel priors is proposed. First, the transmission is corrected once according to the characteristics of the dark channel of the image to solve the block effect caused by the underestimation of the transmission. Secondly, in order to overcome the problem of blurring of details, this paper proposes a regularized model based on transmission correction to optimize transmission twice to overcome the artifact problem in traditional dehazing algorithms. In addition, the Alternating Direction Method of Multipliers (ADMM) is used to solve the new model. Finally, the atmospheric scattering model is used to restore the image. Numerical experimental results show that the proposed method is significantly better than the traditional image dehazing algorithm. Taking the $480\times 540$ Boat image as an example, the PSNR and SSIM value of the method in the article are improved by 1. 8dB and 0. 56dB on average. The algorithm proposed in the article solves the blocking effect while eliminating the haze, and eliminates the artifacts of the image. It is significantly better than the traditional dehazing algorithm in terms of visual effects and objective evaluation indicators.