Reviewerly/exHarmony huggingface dataset:
ON THE FORMATION OF METHODOLOGICAL COMPETENCE OF STUDENTS OF PHILOLOGY

The article is devoted to the formation of methodological competence of students of Philology.We created modern basis for the essence of the category "content of training", the inalienable part of which is the choice of philologists training content".The aim of this article was to show how to change the content of training for the students of Philology and construction of content of foreign languages training as one of the main controllable factors.Having reviewed studies of many scientists we came to the conclusion that in the definition of this notion much depends on the approach chosen, the subject group of the students and many other factors.Methodological competence is a constituent of professional competence like red rose is a constituent of flowers group of Flora.In the narrow meaning "methodological competence" is understood as content analysis, in the wide meaning the notion understanding depends on the approach.If the approach is competence-oriented the essence of the category is considered to be competence (combination of skills, attitudes and knowledge), which marks are programs content, thus key competencies are concerned with methodological culture of students of philology.If it is activity approach, competence is the key category and speech acts are the essence of speech activities, which marks are levels of communication, thus key competencies are concerned with content of knowledge and teaching and translation competency.The modern approach should integrate the best in them on a new spiral of research and be the unity of these two.The formation of intuition in chosen situations may become crucial in the formation of it.Then methodological competency and professional competency are the essence of the category and the key competencies of the students of philology should be based on the concrete choice of the content of learning so that the factors that influence it will become controllable.
NUMERACY SKILLS EMPOWERMENT FROM PRESCHOOL

The development of numerical abilities was examined in 59 children aged 5 years divided into three groups: one control group (n = 15) and two experimental groups (pencil-and-paper mathematical training: n = 29: computerized mathematical training: n = 15).The participants were assessed both before and after a battery of validated tests assessing numerical abilities (BIN test) and fluid intelligence (CPM test).The three groups showed similar values in the pre-test assessment regarding these two dimensions.A gain between post-test and pre-test scores was calculated; this result underlines significant differences between experimental groups and the control group in the four areas evaluated by the BIN test.This study shows the efficacy of both computer-assisted and pencil-and-paper training in enriching numerical intelligence; pencil-and-paper mathematical training seems to be more effective in some areas.This aspect leads us to reflect about this result and to deepen the research with subsequent experiments.
Coordinating epistemic frames in informal physics: Agency, support, and technology

Informal physics environments present opportunities for youth to voluntarily engage with physics in a collaborative space.However, individual children's educational backgrounds, expectations, and motivations impact their engagement with the group learning activities and educational tools in informal physics learning.We initiate an investigation into the variables of agency, support, and technology that contribute to children's dynamic epistemic framing of a virtually simulated learning environment within an afterschool physics environment.Specifically, we consider the use of PhET interactive simulations in the PISEC afterschool physics program by middle-school students and their college-aged mentors.We analyzed video of a group of three learners and their mentor as they use a simulation and transition into a physical experiment based on the simulation.We analyzed each individual's actions and vocalizations to identify their framing using a two-dimensional framing axis.Further, we determined when these frames appeared to be aligned or misaligned between group members during the activity, transitions between alignment and misalignment, and investigated what malleable factors (e.g.technology use, mentor pedagogy, program structures) are contributing to these shifts in alignment.Initial analysis shows malleable factors such as UE pedagogy and environment affordances (e.g.technology, spatial orientation), as well as their intersection with non-malleable factors (e.g.youth social motivations) for future investigation.
The Correlation Between Adjective Mastery And Students’ Writing Descriptive Text At SMA Swasta Persiapan Stabat

The objective of study is investigated correlation between adjective mastery and students’ writing descriptive text of the tenth grade students of SMA Swasta Persiapan Stabat. The study is a correlation research. It is aimed at finding out whether there is any significant correlation between the adjective mastery and students’ ability in writing descriptive text. The population is 244 and the sample is 44 which took by lottery technique. The data analysis used Product Moment formula. It can be concluded that there is a significant correlation between the adjective mastery and writing descriptive text ability of the 2017/2018 tenth year students of SMA Swasta Persiapan Stabat. This is proved from the analysis that the coefficient correlation between the students’ adjective mastery and writing descriptive text ability is 0.78. Compared with the degree of correlation, it is categorized as a strong and significant correlation. Therefore, the hypothesis of the study is accepted.
Video classification detection technique for spatial and temporal motion identification using pathway system

In Video classification, the Video scene or the tracking technology, which divides the Video into semantic sections, is an important element for adding insight and searching for metadata for Video. 5 Data augmentation is one of the main methods of addressing the problem of learning to take few shots, but current syntheses are only tackling the detection of crime scene per image when in reality images can contain several movements with respect to crime.
Rancang Bangun Sistem Informasi Penggajian Pegawai Berbasis Web di Madrasah Ibtidaiyah Nurul Huda Kota Tangerang

Madrasah Ibtidaiyah Nurul Huda Kota Tangerang is one of the private schools, but data processing payroll in this schooll was still unintegrated. The ongoing payroll system was still in use of a manual system. The results of this were many obstacles faced by the school in the production of materials such as in payroll contracts, payroll calculations, payroll slips, and drawing up payroll reports. Also, the information presentation was less fast, inexact, inaccurate because current media transmission information consists of purely physical documents. The research method used waterfall method. Waterfall is a model of its development process for the coverage of a system, sequential or linear. The research steps were divided into: analysis, design, coding, testing and maintenance. The system would then be built using synthetic programming language PHP and Mysql as a database. The web-based employee payroll information system was intended to provide advantages in payroll data processing such as payroll process, payroll calculations, payroll slips, and payroll reports, so that manual jobs could be much easier and computerized. The result was derived from this research was development of the web-based employee payroll information system.
Analysis of the Effects of Supraglottal Tract Surgical Procedures in Automatic Speaker Recognition Performance

This article evaluates the impact in the performance of state-of-the-art automatic speaker recognition schemes of three surgical procedures modifying the supraglottal tract structures of speakers. To do so, a new corpus (Cuco) was recorded, containing the speech of 107 speakers before and after surgery. Speakers were divided into four groups depending on the type of surgery: tonsillectomy, functional endoscopy sinus surgery (FESS), septoplasty, and controls. The analyzed speaker recognition schemes were i-vectors, i-vectors with supervised Universal Background Model, i-vectors employing Time-delay Deep Neural Networks and x-vectors. In all cases, probabilistic linear discriminant analysis was employed in the back-end. Results show changes in the speech of patients who underwent tonsillectomy or FESS after surgery in contrast to controls or patients who had a septoplasty, where not significant variations are observed. These changes increase the Equal Error Rate (EER) of the analyzed speaker recognition schemes for the septoplasty and FESS groups when employing enrollment data recorded before the surgery. Moreover, surgery has a similar influence in the speech of female and male speakers with respect to the analyzed schemes. In consequence, results suggest that it is advisable to update the speaker's enrollment speech after three months following supraglottal tract surgery to ensure that the effects of the operation and post-operative recovery period do not influence the performance of the automatic speaker recognition systems.
The existence of a solution of the two-dimensional direct problem of propagation of the action potential along nerve fibers

In this article, we consider a generalized parabolic two-dimensional direct problem of the process of propagation of the action potential along nerve fibers. The problem is reduced to a generalized hyperbolic problem using the Laplace transform. A generalized two-dimensional direct hyperbolic problem is reduced to a regular hyperbolic problem using methods for rectifying characteristics and isolating singularities. Using the piecewise-continuous function, the existence of the solution of the last problem is proved. From the equivalence of problems it follows that there exists a generalized solution of the parabolic problem.
Learning temporal-spatial consistency correlation filter for visual tracking

Discriminant correlation filter-based tracking approaches, which adopt a circular shift operator on the tracking target object (the only accurate positive sample) to obtain training data and rely on the potential sample periodic extension hypothesis that enables model training and detection, can be efficiently accomplished through FFT. However, real background information is not modeled during the total learning process. The background-aware correlation filter (BACF) tracking algorithm uses a binary matrix to acquire real positive and negative samples using a dense sampling method to model the targets appearance. However, the BACF algorithm does not consider temporal and spatial consistency information, and when a target undergoes an abrupt change, the learned correlation filter will drift to the background. To solve this problem, in this paper, we introduce temporal and spatial consistency constraints into the baseline BACF framework and propose a learning temporal-spatial consistency correlation filter (TSCF) tracking algorithm. This enables the correlation filter to learn to adapt to the appearance of mutation between successive frames. The temporal consistency constraint smooths the multi-channel correlation filter in the time series, and the spatial consistency constraint smooths the multi-channel correlation filter in spatial distribution, thus making the energy distribution more uniform of the correlation filter learned. In this paper, the TSCF model has closed solutions and the conjugate gradient descent method is used to approximate the optimal solution of a system of closed solutions. The optimization process can then be transformed into the Fourier domain using cyclic matrix properties to quickly obtain a solution, which effectively reduces the cost of calculating large matrices. In this paper, our TSCF algorithm increases distance precision by 5.5$%$ and raises the AUC by 4.3$%$ compared to the baseline BACF algorithm on the TB100 public database. The distance precision achieves 0.879 and the AUC reaches 0.663 on the TB100 database making use of only hand-crafted features. The TSCF algorithm proposed in this paper can be applied to challenging conditions such as short time occlusion, out-of-plane rotation, in-plane rotation, and so on, thus demonstrating its robustness and effectiveness.
The Cost- Saving Role of Blockchain Technology As a Data Integrity Tool: E-health Scenario

The digital economy of health and its global proliferation have led to the use of health information systems in the daily health services delivery to patients. Consequently, there is a development of web-based electronic healthcare aimed at providing electronic health services in real-time. In this way, through the implementation of the concept of electronic health, there is an exchange of health information among all stakeholders of the health organization, all with the aim of monitoring the health status of patients, timely intervention and adequate allocation of medical resources. Processing and sharing a large amount of health data in real time, with the constant need to maintain a high level of interoperability and scalability of network infrastructure, requires the highest possible level of security in accessing data, in order to reduce the misuse of health data. By using blockchain technology, the risk of misusing health information, asymmetry of information and the risk of increasing transaction costs are reduced in a very short time. Blockchain is a robust mathematical algorithm that can provide maximum security of the transaction using cryptographic methods. This type of technology is based on a distributed database that contains encrypted data that can not be changed or disturbed. For this reason, the application of this technology as a data integration tool is increasingly reflected in the electronic business of health organizations - electronic healthcare. Blockchain technology is especially used in information-intensive electronic healthcare records and medical applications, which ultimately results in reduced costs of providing health services, especially when it comes to system maintenance and security costs, interoperability and data redundancy. According to above-mentioned cost-saving role of blockchain technology in processing, sharing and analyzing healthcare data, in this paper, there will be more to say about the positive economic impact of blockchain technology on electronic healthcare, especially in the case of Estonia. This European country is a pioneer in creating, implementing and using the e-Health concept as an integral part of health information system through its healthcare system, in order to increase efficiency of healthcare services.&#x0D; Keywords: Blockchain technology, data integrity, e-Health, health economics
Adaptive Smoothness Constraint Image Multilevel Fuzzy Enhancement Algorithm

For the problems of poor enhancement effect and long time consuming of the traditional algorithm, an adaptive smoothness constraint image multilevel fuzzy enhancement algorithm based on secondary color-to-grayscale conversion is proposed.By using fuzzy set theory and generalized fuzzy set theory, a new linear generalized fuzzy operator transformation is carried out to obtain a new linear generalized fuzzy operator.By using linear generalized membership transformation and inverse transformation, secondary color-to-grayscale conversion of adaptive smoothness constraint image is performed.Combined with generalized fuzzy operator, the region contrast fuzzy enhancement of adaptive smoothness constraint image is realized, and image multilevel fuzzy enhancement is realized.Experimental results show that the fuzzy degree of the image is reduced by the improved algorithm, and the clarity of the adaptive smoothness constraint image is improved effectively.The time consuming is short, and it has some advantages.
Detect Slitheen by analyzing the browsing behaviors and forcing retransmission

Previous studies on decoy routing did not consider the impact of content delivery networks (CDN). The CDN are widely used by popular websites which should not be ignored. In this paper, we take the first step to study the problem of applying the decoy routing in the CDN. In detail, we take Slitheen, which is one of the most advanced decoy routing techniques as our research object, and design the detection attacks from the following aspects: replacing the CDN edge servers; analyzing retransmission latency; comparing ciphertexts; analyzing the page loading duration. If Slitheen exposes its users to the censor, they will be in great danger in some repressive regimes. In order to reinforce Slitheen, we propose attack plans from the perspective of the attacker. To the best knowledge of the authors, our work is the first research on decoy routing in the CDN. By simulations, we demonstrate the feasibility of our detection scheme. We show that using our attack methods, the packet-sending frequency, the retransmission delay, and the page loading durations of Slitheen sessions are all obviously different from regular ones.
Comparison of the Effect of Scientific and Conventional Learning on the Creativity and Learning Outcomes of Phyisical Education Student

This study aims to determine and describe the Comparison of the Effects of Scientific and ConventionalLearning on the Creativity and Learning Outcomes of High School Physical Education Students.This research is an experiment through a test instrument technique for learning outcomes and a questionnaire for creativity, with anava 2 x 2 research design.The number of samples was 71 people for the scientific learning group and 57 people for the conventional learning group and the sampling technique using cluster random sampling.Before conducting the analysis of variance (anava), first conduct the analysis requirements, namely the normality test and homogeneity test.Furthermore, the two-way Anava test was used at the α significance level of 0.05 and continued with the Scheffe test at the significance level α = 0.05.The results showed that there were differences in the influence of conventional learning and scientific learning on creativity and physical education learning outcomes and the interaction between the effects of conventional learning and scientific learning on creativity and physical education learning outcomes.
Pre-service English Teachers` Views on Digital Literacy Competences in Language Teaching

Teaching in digital era allows the pre-service teachers to build their digital literacy to run digital teaching effectively and efficiently.Digital literacy on language teaching is the ability to select, evaluate, operate and apply digital media and digital tools in teaching and learning process.This current study aimed at investigating the pre-service English teachers` views on digital literacy competences in language teaching.Survey research was conducted to gather the data and 67 pre-service English teachers were as the participants.The data taken from questionnaire were analyzed through percentage analysis.The finding indicated that the pre-service English teachers were in average digital literacy competences, 84% of them were familiar with social media, 87 % of them argue that digital literacy competences as one of important things in digital teaching, 70% of them were familiar with digital media for EFL teaching.As the conclusion, the pre-service English teachers still need the professional training to upgrade their digital literacy competences and face the digital teaching.
Multi-Label Classification using an Ontology

During these last few years, the problem of multilabel classification (ML) has been studied in several domains, such as text categorization.Multi-label classification is a main challenging task because each instance can be assigned to multiple classes simultaneously.This paper studies the problem of Multi-label classification in the context of web pages categorization.The categories are defined in an ontology.Among the weakness of the multi-label classification methods, exist the number of positive and negative examples used to build the training dataset of a specific label.So the challenge comes from the huge number of labels combinations that grows exponentially.In this paper, we present an ontology-based Multilabel classification which exploit dependence between the labels.In addition, our approach uses the ontology to take into account relationships between labels and to give the selection of positive and negative examples in the learning phase.In the prediction phase, if a label is not predicted, the ontology is used to prune the set of descendant labels.The results of experimental evaluation show the effectiveness of our approaches.
THE CHARACTER DEVELOPMENT OF ‘BEN’ IN GIFTED HANDS: THE BEN CARSON'S STORY THROUGH ERIKSON'S PSYCHOSOCIAL THEORY

This study aims to identify and provide a description of the development of the main character in the film Gifted Hands: The Ben Carson Story by Thomas Carter based on the approach of textual literary psychology through qualitative descriptive techniques, namely listening, observing, and copy-writing. Erikson's theory of psychological development, which reviews the development of the character influenced by those who are nearby becoming the focal point of the discussion - in terms of dialogue, action-reaction, and the situation depicted in the film. The findings in this study are four stages of character development from eight stages, namely school age, adolescence, early adulthood, and adulthood, at each stage, there are two elements namely dystonic (disruptive) and syntonic (harmony).
An Exploratory Study of Hierarchical Fuzzy Systems Approach in A Recommendation System

Recommendation system, also known as a recommender system, is a tool to help the user in providing asuggestion of a specific dilemma. Recently, the interest in developing a recommendation system in manyfields has increased. Fuzzy Logic system (FLSs) is one of the approaches that can be used to model therecommendation systems as it can deal with uncertainty and imprecise information. However, one of thefundamental issues in FLS is the problem of the curse of dimensionality. That is, the number of rules inFLSs is increasing exponentially with the number of input variables. One effective way to overcome thisproblem is by using Hierarchical Fuzzy System (HFSs). This paper aims to explore the use of HFSs forRecommendation system. Specifically, we are interested in exploring and comparing the HFS and FLS forthe Career path recommendation system (CPRS) based on four key criteria, namely topology, the numberof rules, the rules structures and interpretability. The findings suggested that the HFS has advantagesover FLS towards improving the interpretability models, in the context of a recommendation systemexample. This study contributes to providing an insight into the development of interpretable HFSs in theRecommendation systems.&#x0D; Keywords: Fuzzy Logic Systems, Hierarchical Fuzzy Systems, Recommendation Systems