Reviewerly/exHarmony huggingface dataset:
A Deep Generative Approach to Native Language Identification

Native language identification (NLI) -identifying the native language (L1) of a person based on his/her writing in the second language (L2) -is useful for a variety of purposes, including marketing, security, and educational applications.From a traditional machine learning perspective, NLI is usually framed as a multi-class classification task, where numerous designed features are combined in order to achieve state-of-the-art results.We introduce a deep generative language modelling (LM) approach to NLI, which consists in fine-tuning a GPT-2 model separately on texts written by the authors with the same L1, and assigning a label to an unseen text based on the minimum LM loss with respect to one of these fine-tuned GPT-2 models.Our method outperforms traditional machine learning approaches and currently achieves the best results on the benchmark NLI datasets.
The relationship between the academic achievement of computerized tests and traditional tests of Business College students. An empirical study

The study aims to investigate the relationship between the academic achievement of computerized tests and traditional pen and paper exams of Business College students at the University of Jordan- Aqaba branch as well as relate differences results to students` gender.&#x0D; The study sample comprised 136 students of a compulsory course at the Business Faculty. A computerized mid-term test was held while the final one was traditional. The results of the two tests were compared where the other general factors affecting students` academic achievement, namely ( the same students, course subject, course subject lecturer) were set. The tests marks were sampled as percentage to the test mark so as to delete the denominator difference of marks where the mid-term mark is out of 30 while the final test is out of 50.&#x0D; The SPSS was used to compare the results of the two tests. Results were related to students gender, whether gender-related differences are found. The study concluded that there is no statistical significant relationship between the academic achievement of computerized tests and traditional ones (paper and pen) held at the Business College in The University of Jordan- Aqaba branch.&#x0D; The results also indicated that the academic achievement differences resulting from computerized tests have to do with the student gender variable in favour of male students.
A Confidence-Guided Technique for Tracking Time-Varying Features

Application scientists often employ feature tracking algorithms to capture the temporal evolution of various features in their simulation data. However, as the complexity of the scientific features is increasing with the advanced simulation modeling techniques, quantification of reliability of the feature tracking algorithms is becoming important. One of the desired requirements for any robust feature tracking algorithm is to estimate its confidence during each tracking step so that the results obtained can be interpreted without any ambiguity. To address this, we develop a confidence-guided feature tracking algorithm that allows reliable tracking of user-selected features and presents the tracking dynamics using a graph-based visualization along with the spatial visualization of the tracked feature. The efficacy of the proposed method is demonstrated by applying it to two scientific datasets containing different types of time-varying features.
Relationship Modeling between Digital Literacy, The Use of e-Resources and Reading Culture of Students at STMIK Sumedang using PLS-SEM

In this paper a relationship model between digital literacy, the use of eresources and reading culture of students at STMIK Sumedang is studied.The goal of study is to determine influence of digital literacy on the use of e-resources and reading culture of students, and the influence of the use of e-resources on reading culture of students.The modeling used Partial Least Square-Structural Equation Modeling (PLS-SEM).Parameters of the model are estimated by Ordinary Least Square Method with PLS-SEM Algorithm.This study took data from 256 questionnaires of students at STMIK Sumedang.The results showed that digital literacy significantly influence the use of e-resources and reading culture of students with the total effects are 0.529 and 0.223.Meanwhile the use of e-resources does not significantly influence the reading culture of students with the total effect is 0.187.
MOBILITY AND REDISTRIBUTION OF MAJOR ELEMENTS IN WEATHERED PROFILE DEVELOPED ON PEGMATITE AT KITIBI-IWOYE, SOUTHWESTERN NIGERIA

Geochemical studies of weathering profiles around Kitibi-Iwoye revealed redistribution of elements from parental pegmatite to the regolith. Geological mapping showed that the pegmatite intrudes diorite and migmatite gneiss. Weathered samples from B-horizon were air-dried, pulverised and analysed using X-ray Fluorescence Spectrometry (XRF) in the Department of Geological Sciences, University of Cape Town, South Africa. Chemical Index of Alteration (CIA), Weathering Index of Parker (WIP), Mass balance calculation and Al2O3 – CaO+Na2O – K2O (A–CN–K) ternary plot were employed to determine elemental mobility and distribution caused by weathering. SiO₂ (74.2 and 43.4 wt %), CaO (0.43 and 0.03 wt. %), Na2O (7.14 and 0.04 wt. %), K2O (1.90 and 0.67 wt. %), MnO (0.11 and 0.03 wt. %) and P2O5 (0.20 and 0.05wt. %) displayed depletion from parent rock to the regolith respectively. But Al₂O₃ (15.5 wt. % and 33.5 wt. %), Fe2O3 (0.39 and 3.40 wt. %), TiO2 (0.04 and 0.35 wt. %) and MgO (0.08 and 0.11 wt. %) showed enrichment from parent rock to the regolith respectively. Fe₂O₃ (3.19) is the most enriched whereas Na2O (-99.8), CaO (-98.9), P2O5 (-95.3), K2O (-89.5), SiO2 (-81.9), MgO (-73.1), MnO (-64.5) and Al2O3 (-23.6) are progressively depleted. Mean CIA value of 97.8 revealed that weathering has almost reached its completion whereas CIA of 62.1 for the pegmatite suggested that the parent rock is at incipient stage of weathering. Pegmatite had a WIP of 110.5 whereas the weathered samples with WIP ranging from 2.66, 3.88, 6.03, 6.23, 6.92, 8.08, 9.08, 9.76 and 14.6 respectively showed decreasing trend of weathering. This study confirmed contrasting behaviour of CIA and WIP. A-CN-K diagram suggested strongly weathered samples plotted at the apex of Al2O3 field whereas pegmatite plots along the A-CN line.
Deep Anomaly Detection via Morphological Transformations

The goal of deep anomaly detection is to identify abnormal data by utilizing a deep neural network trained by a normal training dataset. In general, industrial visual anomaly detection problems distinguish normal and abnormal data through small morphological differences, such as cracks and stains. Nevertheless, most existing algorithms focus on capturing not morphological features, but semantic features of normal data. Therefore, they yield poor performance on real-world visual inspection, even though they show their superiority in simulations with representative image classification datasets. To solve this problem, we propose a novel deep anomaly detection method that encourages understanding of salient morphological features of normal data. The main idea behind our algorithm is to train a multi-class model to classify between dozens of morphological transformations applied to all the given data. To this end, the proposed algorithm utilizes a self-supervised learning strategy, which makes unsupervised learning straightforward. Additionally, we present a kernel size loss to enhance the proposed neural networks&rsquo; morphological feature representation power. This objective function is defined as the loss between predicted kernel size and label kernel size via morphologically transformed images with the label kernel. In all experiments on the industrial dataset, the proposed method demonstrates superior performance. For instance, in the MVTec anomaly detection task, our model achieved an area under the receiver operating characteristic (AUROC) value of 72.92%, which is 8.74% higher than the semantic-feature-based deep anomaly detection.
THE AWARENESS AND USE OF SAUDI DIGITAL LIBRARY AMONG THE FACULTY MEMBERS OF VARIOUS COLLEGE LIBRARIES IN KSA

Digital Libraries play a major role as centers of learning and institutions of information dissemination. The study aims at investigating the awareness and use of Saudi digital library (SDL) among the faculty members of various college libraries in Saudi Arabia. A questionnaire method was used to identify the awareness of Saudi digital library services, their views on SDL services and their satisfaction levels about e resources and on line database. A simple random sampling method was used. Descriptive statistics like mean, standard deviation, average have been used to analyze the data using the SPSS 22 software. Hypothesis testing was done by using Chi-square test. The data was collected through structured questionnaire. The study was confined to faculty members of various university in Saudi Arabia.
Research of technical state of electric motors based on petri nets

In this work, the possibility of using Petri nets when monitoring the technical condition and diagnostics of electric motors is considered. Based on the use of fuzzy temporary Petri nets, a mathematical model of the process diagnostic has been developed. The control of the technical conditions of the electric motor in the model is done based on the cluster analysis. The description of the diagnostic process is carried out using a set of events, states, transitions, input and output functions, markers, parameters of time delays. Figs.: 3. Tabl.: 1. Refs.: 15 titles.Keywords: Petri net; technical condition; diagnostic process; electric motor; mathematical model.
Cloud Storage Protection Scheme Based on Fully Homomorphic Encryption

Cloud computing allows enterprises and individuals to have a less physical infrastructure of software and hardware. Nevertheless, there are some concerns regarding privacy protection which may turn out to be a strong barrier. Traditional encryption schemes have been used to encrypt the data before sending them to the cloud. However, the private key has to be provided to the server before any calculations on the data. To solve this security problem, this paper proposes a fully homomorphic encryption scheme for securing cloud data at rest. The scheme is based on prime modular operation, its security depends on factoring multiple large prime numbers (p1, p2,...pn) up to n, which is formed from very large prime numbers up to hundreds of digits as this is an open problem in mathematics. In addition, the elements of the secret key are derived from a series of mathematical operations and the calculation of an Euler coefficient within the modular of integers. Furthermore, it adds the complexity of noise to the plaintext using the number of users of the Cloud Service Provider. Moreover, its randomness is evaluated by the National Institute of Standards and Technology statistical tests, and the results demonstrating that the best statistical performance was obtained with this algorithm.
Linguistics Characteristics of Social Network

In this paper we introduce the idea of an author about the use of slang language for the period of (16th -20th) century, while other give the use of slang language in the social network and the purpose of the said and the name giving to it. Also the factors that affect the variety of language which will reflect also on the language used in the internet . Hence a new linguistic expression was rising with the name of internet linguistic. We give also some popular internet slangs and its advantages also the emoticons and its different use between males and fameless and prefer to use the capitalize letters. This study also shows the effect of virtual communication on the individuals. We conclude that analytically the internet slang is a specific variety of language and characteristics according to the kind of output, also commonly used than speech, like feedback, emoticons, multiple conversations, hypertext links, persistence, and multiple authorship. Moreover it challenged the cooperative and politeness principles, relevance theory, humor, economy, and tolerance, it express the social identity, rather than illiteracy or the character limit of message services.
Evaluating an Aspect Extraction Method for Opinion Mining in the Portuguese Language

The opinion issued by consumers of products and services has become increasingly valued, both by other consumers and by companies. The automatic interpretation of review texts to generate information is of paramount importance. With opinion mining at the aspect level, it is possible to extract and summarize opinions about different components of a product or service. This paper evaluates the behavior of a method for extracting aspects using natural language processing tools for the Portuguese language. The aim is to investigate the maturity of the tools for Portuguese compared to the already consolidated tools for the English language. The evaluation was carried out in three datasets from two different domains with original texts in Portuguese and their translations into English, and vice versa, and the results indicate that there is no difference between languages.
Trust framework for online products and services using grain level comparison: A solution to boot-strapping problem

Abstract Service-oriented architecture has changed the way that web applications are designed. Today users are more inclined towards online products and services to save time, energy, and cost. However existing frameworks for online purchasing have certain drawbacks and one of the foremost is ‘trust’. Hence the struggle is to build such a system trust that offers commendations to the customer for the products and services even with inadequate resources; consequently building customer’s trust upon the vender as well as the system. Current systems available only utilize trust by providing product features and comparison using the rating system. However, a problem occurs when a “Bootstrapping issue” is raised, i.e., if a new company emerges in the market then the existing system cannot generate a trust rating for it; the same goes for the new product. Such a problem can cause an uncertain situation for the customer to; a) whether go for the existing product or b) the new product of a new company. In this article, we propose a system trust using a novel framework, which can solve the problem of bootstrapping using a ‘grain level approach’. By providing a high level of granularity, the details of the product’s specs and features will be much in-depth, which will offer the customer an enhanced platform to examine and compare the product amongst several other similar products and ultimately coming to a decision to purchase it by trusting it. As a result, the decision-making power of the customers will be strengthened and the system’s trust will be extended.
Bibliometric mapping of research on continuing education

The paper analyzes an array of scientific publications on continuing education over the past 45 years using the method of bibliometric mapping. We consider as units of analysis both (1) the collaborations of authors, organizations, and countries participating in scientific research on continuing education, as well as (2) keywords as indicators of thematic areas in the stream of publications on continuing education. We characterize the scientometric indicators of scientific directions in research on continuing education. Our analysis shows the high positive dynamics of publication productivity and the dominance of two main scientific areas in continuing education research: medicine (healthcare) and education itself. Our analysis also reveals a weak transcollaborative connection between (1) the authors of scientific research on continuing education and (2) the formation of groups of authors for conducting single studies. We further notice an expansion of the terminological (and, as a consequence, problemological) content of studies on continuing education towards interdisciplinary communication and the use of information technologies.
The Effectiveness of a Parenting Enhancement Program for Care Workers in Child Care Facilities

The purpose of this study is to construct a parenting function strengthening program and to examine its effectiveness in order to raise the self-confidence of the parenting function and to help parents with parenting stress and the emotional regulation ability in child care facilities. Thirty care workers were randomly assigned to an intervention (n = 15) group and a control group (n = 15). Care workers in the intervention group participated in six weekly program sessions of strengthening the parenting function. The control group did not have any intervention. The questionnaire consisted of the needs and assessment of the parenting efficacy, parenting stress and emotion regulation ability for the purpose of verifying the effectiveness of the intervention program. All of the factors were evaluated by self-report measures. After termination of the program, differences between pretest and posttest were analyzed for parenting efficacy, parenting stress, and emotional regulation ability. As a result, the level of parenting efficacy and emotional regulation ability of the instructor of the intervention group improved positively and the parenting stress decreased. In the control group, parenting efficacy was changed positively, but there was no change in parenting stress and emotion regulation ability. This study confirms that there is a positive change in the ability of the parenting program for enhancing the child rearing ability and the psychological stability of care workers.
Unsupervised Multi-Document Abstractive Summarization Using Recursive Neural Network with Attention Mechanism

Text summarization is an active field of research with a goal to provide short and meaningful gists from large amount of text documents. Extractive text summarization methods have been extensively studied where text is extracted from the documents to build summaries. There are various type of multi document ranging from different formats to domains and topics. With the recent advancement in technology and use of neural networks for text generation, interest for research in abstractive text summarization has increased significantly. The use of graph based methods which handle semantic information has shown significant results. When given a set of documents of English text files, we make use of abstractive method and predicate argument structures to retrieve necessary text information and pass it through a neural network for text generation. Recurrent neural networks are a subtype of recursive neural networks which try to predict the next sequence based on the current state and considering the information from previous states. The use of neural networks allows generation of summaries for long text sentences as well. This paper implements a semantic based filtering approach using a similarity matrix while keeping all stop-words. The similarity is calculated using semantic concepts and Jiang–Conrath similarity and making use of a recurrent neural network with an attention mechanism to generate summary. ROUGE score is used for measuring accuracy, precision and recall scores.
The Semantics of Historical Knowledge. Labelling Strategies for Interdisciplinary and Digital Research in History.

This short paper aims at introducing some labelling concepts developed and used by the authors. Indeed, developing a conceptual framework for interdisciplinary research in history is a much-needed strategy in order to ensure that historians use all vestiges from the past regardless their origin or support for the construction of historical discourse. Fixing the semantics of historical knowledge is the first unavoidable step to build a new scenario in which NLP tasks enable more efficient data gathering and exploitation.
SISTEM INFORMASI LAYANAN DIGITAL PUSKESMAS BERBASIS ANDROID

The very rapid development of information technology has proven to play an important role in the accelerated development of information both in the world of industry, government and the world of health, so that it can support the performance of increasing the efficiency, effectiveness and productivity of all elements of society, especially in the world of health, both public and private institutions. or individually or individually, which can encourage the realization of a developed and prosperous society. The health sector is one of the important sectors of development that has the potential to be integrated with the presence of technology. Public health center Bayur Lor. Cilamaya Kulon, Karawang Regency is one of the developing health service centers. The number of patients that continues to increase every day causes new problems in the process of seeking information about patients, the number of patients, the number of visits, total income, and data on existing drug supplies. Because based on the existing problems, the Public health center Bayur Lor. Cilamaya Kulon, Karawang Regency, needs to take advantage of information technology, which can overcome the problems faced, so that public health services can be improved for the realization of the vision and mission of the Public health center Bayur Lor. Cilamaya Kulon. Looking at some of the existing problems, researchers use the waterfall method in making an information system. Applications made in this study are based on android. To facilitate the mention of this application, namely Android-based LAGILEMAS (Public health center Digital Service).&#x0D;
RANCC: Rationalizing Neural Networks via Concept Clustering

We propose a new self-explainable model for Natural Language Processing (NLP) text classification tasks.Our approach constructs explanations concurrently with the formulation of classification predictions.To do so, we extract a rationale from the text, then use it to predict a concept of interest as the final prediction.We provide three types of explanations: 1) rationale extraction, 2) a measure of feature importance, and 3) clustering of concepts.In addition, we show how our model can be compressed without applying complicated compression techniques.We experimentally demonstrate our explainability approach on a number of well-known text classification datasets.
PENGARUH MULTIMEDIA INTERAKTIF TERHADAP MOTIVASI BELAJAR SISWA PELAJARAN PAI

This study discusses the Effect of Interactive Multimedia Learning on Student Learning Motivation in PAI Subjects at SMK NU Darul Hikam Karanggeneng Lamongan Academic Year 2019/2020. This research is motivated by the presence of interactive multimedia learning media now very helpful in increasing student motivation and broad knowledge. This research answers the problem formulation 1) How is interactive multimedia learning in PAI subjects? 2) What is the motivation for student learning on PAI subjects? 3) What is the effect of interactive multimedia learning on students' motivation in PAI subjects at SMK NU Darul Hikam Karanggeneng Lamongan in the 2019/2020? To answer the problem formulation, this research uses quantitative methods, this method uses saturated samples, because this study was conducted for all students, amounting to 54 multimedia majors at SMK NU Darul Hikam Karanggeneng Lamongan. From the results of calculations with a simple linear regression formula obtained a significance value of 0,000 where the number is smaller than the Cronbach alpha value of 0.05. Thus, it can be concluded that interactive multimedia learning can affect student motivation in PAI subjects at SMK NU Darul Hikam Karanggeneng Lamongan.