Reviewerly/exHarmony huggingface dataset:
NATIVE ENGLISH TEACHERS IN EFL SPEAKING CLASSES: DEPICTING THEIR STRATEGIES TO TEACH VIETNAMESE STUDENTS

The aims of this research are; (1) to know the strategies used by native English teachers to teach speaking to the students of Vietnam National University of Agriculture, (2) to describe how the strategies contributed to the students speaking skills, and (3) to explain the problems faced by native English teachers in EFL speaking classes. This research is descriptive research with a qualitative approach. The data were collected through classroom observation, interviews, and documentation. It presents the result of the study in the form of a descriptive explanation. The findings of this research are the strategies used by native English teachers to teach speaking to the students of Vietnam National University of Agriculture, namely (a) group discussion, (b) role play, (c) brainstorming, (d) storytelling, (e) story completion, (f) describing picture, (g) game (guessing the word), (h) using target language/interview. Based on those strategies, the results show that the strategies help students to improve their speaking skills, vocabulary, and confidence. Also, it can help students to solve problems, increase sensitivity, think critically, and express their ideas. Furthermore, the findings of the problems faced by native English teachers in speaking class are (a) pronunciation, (b) lack of confidence, (c) lack of ending sounds, (d) no vocabulary and grammar.
Correction to: Sequence stratigraphy of subsurface upper Eocene-lower Oligocene deposits, Dahomey Basin, southwestern Nigeria: palynological and palynofacies approach

A Correction to this paper has been published: 10.1007/s12517-021-07693-0
Teaching computers to understand our language

Are you up to anything this weekend?'This sentence provides a simple example of how different contexts can alter a sentence's intended meaning.If you are asked this by a colleague or teacher, they are likely just making small talk.However, if you are asked this by a friend, they might be seeking to find out whether you have any free time to socialise with them.As social animals, we naturally understand and interpret subtle differences like this, which occur during hundreds of our interactions every day.But, this concept of understanding the subtleties of language is very difficult to instil in computers.Professor Yulan He is a computer scientist at the University of Warwick, working in the field of natural language processing.She is training artificial intelligence (AI) to overcome this challenge through sophisticated reading comprehension exercises."Language understanding is extremely difficult for computers due to the variety, ambiguity, subtlety and expressiveness of human languages," she says.She is drawing information from a multitude of sources to provide a knowledge base that computer models can 'learn' from, and contribute to, to build the models' understanding of how we use language.
Neotectonic-related landforms in the Campos do Jordão Plateau, Southeast Brazil

The Campos do Jordão Plateau, situated in the Serra da Mantiqueira – western flank of the Continental Rift of Southeastern Brazil, presents several morphological features that are indicative of neotectonic activity. This paper presents a morphotectonic map of the southeastern front of the plateau (scale 1:25,000), based on detailed photointerpretation, with structural data obtained during field surveys and also supported by morphometric analysis. The map illustrates morphotectonic features (triangular and trapezoidal facets, rectilinear escarpments, low drainage divides, shutter ridges and drainage captures) and their relationship with brittle structures and lithotypes. Triangular and trapezoidal facets and rectilinear escarpments are commonly associated with normal faults, whereas low divides and shutter ridges are associated with strike-slip ones. The map provides insights into the neotectonic activity and its influence on the landforms in southeast Brazil.
Analisis dan Perancangan Simulasi Enkripsi dan Dekripsi pada Algoritma Steganografi untuk Penyisipan Pesan Text pada Image menggunakan Metode Least Significant Bit (LSB) Berbasis Cryptool2

Security and confidentiality of data is the central aspect of an information system so that it can only be accessed by the owner of the information or interested user. In sending data, without the existence of a technique of concealing important information, it will be very easy for people who do not have access rights/interests to know the contents of the information. Steganography is the art and science of hiding secret messages in other messages so that the contents of the secret message cannot be traced. In this study, steganography technic is implemented by using the Least Significant Bit (LSB) method, modifying less significant bits or the last bit in one byte of data by using text messages as a storage medium. The purpose of this study was to analyze and design an encryption and decryption simulation for the insertion of text messages in an image by using the steganography algorithm using the Least Significant Bit (LSB) method, so that it would secure the text messages sent by the sender to the receiver by inserting the text message into an image both in the format * .jpg, * .bmp and * .png. The software will be used to simulate steganography using free program (Open Source) Cryptool2 in order to describe the concepts of cryptography and cryptanalysis. Keywords: Steganography, Least Significant Bit (LSB), Cryptool2
Jakarta Composite Index Model Before and During COVID-19 Using CNN-LSTM

Deep Learning is a subset of artificial intelligence and machine learning, which is the development of multiple layered neural networks.There are many sectors that deep learning can be applied to such as computer vision, natural languages processing, and even time series data forecasting.One of the deep learning algorithms that have depth in forecasting time series data is CNN-LSTM.CNN-LSTM (Convolutional Neural Network -Long Sort Term Memory) is a deep learning algorithm that uses a convolution layer to automate data extraction and an LSTM layer to learn data patterns by paying attention to the order in the data.In this study, CNN-LSTM was used to model the JCI (Jakarta Composite Index) before the COVID-19 period and during the COVID-19 period.JCI data was taken from December 1, 2018 to June 1, 2021.JCI data was split into data training, data validation, and data testing.Based on the analysis, the MAPE value was 1.4% for the JCI test data before COVID-19 and 0.5% for the JCI test data during COVID-19.From the MAPE value, it can be said that CNN-LSTM has excellent forecasting capabilities for JCI data before and during COVID-19.
Metacognitive strategies of primary school students

&#x0D; &#x0D; &#x0D; The present study was to determine the level of use of the metacognitive strategies of the students of the fifth and sixth grade of the primary level. The research was developed in the quantitative approach, it was of a basic type, with a non-experimental cross-sectional design, of a descriptive level. The sample consisted of 80 students from the V cycle (fifth and sixth grade) of primary school. The sampling used was intentional non- probabilistic for convenience. To measure the study variable Metacognitive strategies, the survey technique was applied and the 33-item questionnaire with a Likert-type scale was used for data collection. Cronbach's alpha statistic was used for the reliability of the instrument, obtaining 0.805 reliability. The results of the research determined that the variable Metacognitive strategies are used by students in their learning in 62.50% considered at a regular level, 21.25% considered at a low level and 16.25% considered at a low level. good level, reaching the conclusion that metacognitive strategies should be encouraged and developed in students in order to improve learning, where they themselves are capable of self- assessment and self-criticism of their own learning.&#x0D; &#x0D; &#x0D;
Statistical Methods and Nonlinear Dynamics for Analyzing Brain Activity. Theoretical and Experimental Aspects

In this paper, we propose statistical methods and nonlinear dynamics for analyzing brain activity in epileptic patients, using the PhysioNet database. Thus, the analysis by statistical methods (the time variation of the standard deviation of the component signals of the electroencephalogram, the time variation of the signal variance, the time variation of the skewness, the time variation of the kurtosis, the construction of the recurrence maps corresponding to both normal functioning of the brain, as well as of the pre-crisis period, respectively of the crisis, the evolution in time of the spatial–temporal entropy, the variations of the Lyapunov coefficients, etc.) allows us to determine not only the epilepsy time based on a specific strange attractor but also that the entry into the epileptic seizure can be determined at least twenty minutes in advance. Finally, utilyzing elements of nonlinear dynamics and chaos, one builds in the states space certain attractors corresponding to a wide “class” of signals of encephalographic type. These classes dictate the normal or the abnormal functioning (the epileptic one) of the brain so that a possible classification of the types of epilepsy can be given.
THE IMPORTANCE OF THE ROLE OF THE FAMILY AS A SOCIO-CULTURAL EDUCATIONAL ENVIRONMENT IN THE HISTORY OF ARMENIAN PEDAGOGICAL THOUGHT

The article discusses the role of the family as a socio-cultural educational environment in the history of Armenian pedagogical thought. In particular, reference was made to M. Mashtots’s, M. Khorenatsi’s, M. Taghiadyan’s, Kh. Abovyan’s, Raffi’s, I. Harutyunyan's and G. Hakobyan's observations and opinions on the issues of educational, social functions of the family, providing a comfortable environment for the child.
A Novel Kernelized Fuzzy Clustering Algorithm for Data Classification

Data are expanding day by day, clustering plays a main role in handling the data and to discover knowledge from it. Most of the clustering approaches deal with the linear separable problems. To deal with the nonlinear separable problems, we introduce the concept of kernel function in fuzzy clustering. In Kernelized fuzzy clustering approach the kernel function defines the non- linear transformation that projects the data from the original space where the data are can be more separable. The proposed approach uses kernel methods to project data from the original space to a high dimensional feature space where data can be separable linearly. We performed the test on the real world datasets which shows that our proposed kernel based clustering method gives better accuracy as compared to the fuzzy clustering method.
A Study of ICT-Based Learning in Elementary School Mathematics Learning Concepts During the COVID-19 Pandemic

This study aims to examine the application of technology to mathematics learning at the time of the Covid-19 pandemic.The research method used is comparative analysis research.The variables being compared are Information and communication technologies-based learning media with the contribution of several aspects, namely the total article with the title of the media, user perception, the total material that can be applied, gameplay, graphic design, and features of the application.Utilization of technology that can be used in the learning process without facing real time but has good effectiveness.The learning media are Edmodo, Geogebra, and Knowre Math.This third application helps in learning mathematics as the co-19 pandemic continues so that it does not require face-to-face but learning runs efficiently.
Arterial hypertension and cerebrovascular accidents. epidemiological profile of patients attended between 2013 and 2019 in Joinville, Santa Catarina, Brazil

Introduction: Cerebrovascular accident (CVA) is the second cause of death in the world, and arterial hypertension (AH) is the main risk factor. Objectives: To evaluate the prevalence of AH and the epidemiological profile of patients who suffered CVA, first and recurrent events, registered at JOINVASC, between 2013 and 2019. Methodology: An observational, descriptive, retrospective study, analyzing demographic data and risk factors, in patients that suffered CVA, first or recurrent event, was done. Results: In the study period, 6057 CVA events were registered, 4402(72.6%) patients were classified as hypertensive, (122 were excluded due to incomplete data), 4387 registers were analyzed. In this group, 2149 (51.2%) were male, mean age was 68.4±14.7(18 a 102 years), BMI was 27.5±5.1(14 a 59), 4330(39.9%) with Diabetes, 2559(58.8%) were smokers or ex-smokers, 3174(7.42%) were sedentary, and 504(11.5%) had controlled AH. In the group with recurrent event (1392-31.7%) (52.3%, p&lt;0.001) were females, mean age was (69.4± 11.5) (p&lt;0.002); BMI was lower (p=0.02). There was more cardiopathy (47.6%) (p&lt;0,001) ,smokers or ex-smokers (66.2)(p&lt;.005), diabetes (46.7%) (p&lt;0.001) and deaths (32.3%)(p&lt;0.001), less physical activity (22.0%)(p&lt;0.001), use of antihypertensive drugs was greater (1.52±0,93)(p&lt;0.001),. Logistic regression showed that female sex, BMI, DM, cardiopathy, physical activity, and more anti- hypertension drugs, were significant predictors for recurrence of neurologic event. Discussion: Despite advances in primary health care and prevention campaigns, the prevalence of AH in patients with CVA is high, and still has lowlevels of control, even in patients with recurrent CVA.
Efficient loop-check for multimodal KD45n logic

We introduce sequent calculus for multi-modal logic KD45n which uses efficient loop-check. Efficiency of the used loop-check is obtained by using marked modal operator squarei which is used as an alternative to sequent with histories ([2,3]).We use inference rules with or branches to make all rules invertible or semi-invertible. We showthe maximum height of the constructed derivation tree. Also polynomial space complexity is proved.
Методика дистанционного преподавания и контроля дисциплины «Физическая культура и спорт» в период пандемии COVID-19

The article presents an analysis of the results of research on the methodology of distance learning in the discipline «Physical culture and sport» at the Moscow State University of Technology and Management&nbsp;named after K.G.&nbsp;Razumovsky (PKU) before and after the COVID-19 pandemic. On the base of the obtained data, the author develops practical recommendations to improve the effectiveness of teaching and control in the theoretical course «Theory and methodology of physical culture».
Binary sequences and lattices constructed by discrete logarithms

&lt;abstract&gt;&lt;p&gt;In 1997, Mauduit and Sárközy first introduced the measures of pseudorandomness for binary sequences. Since then, many pseudorandom binary sequences have been constructed and studied. In particular, Gyarmati presented a large family of pseudorandom binary sequences using the discrete logarithms. Ten years later, to satisfy the requirement from many applications in cryptography (e.g., in encrypting "bit-maps'' and watermarking), the definition of binary sequences is extended from one dimension to several dimensions by Hubert, Mauduit and Sárközy. They introduced the measure of pseudorandomness for this kind of several-dimension binary sequence which is called binary lattices. In this paper, large families of pseudorandom binary sequences and binary lattices are constructed by both discrete logarithms and multiplicative inverse modulo $ p $. The upper estimates of their pseudorandom measures are based on estimates of either character sums or mixed exponential sums.&lt;/p&gt;&lt;/abstract&gt;
On the Representation by Bivariate Ridge Functions

We consider the problem of representation of bivariate functions by sums of ridge functions. It is shown that if a function from a certain class of smoothness is represented by the sum of finitely many ridge functions with arbitrary behaviors, then it can be also represented as the sum of ridge functions of the same class of smoothness. As an example, this result is applied to a homogeneous partial differential equation with constant coefficients.
Online Library System to Dr. Richard Pathirana Public Library in Galle area in Sri Lanka

In southern province there are available 2,654,000 of population and 1,063,334 of people who are in Galle district.Also there are 101,159 of people in Galle Municipal Council.At present 225,458 of school children are in Galle district.The members of the Dr.Richard Pathirana Public Library-Galle are 40988 and among these members most consists of students and other consists of adults in according to 2020 statistic of Dr.
The Value of Education in Literature and Relevance for Teaching

This study aims to describe and explain the value of education in literature and how relevant it is for teaching. The method used in this research is descriptive qualitative. Descriptions and explanations lead to circumstances, phenomena and are not limited to data collection but analysis and interpretation of these data. The data collection technique used in this study is a non-interactive technique. Non-interactive data collection techniques by doing intensive reading of the novel and taking notes actively with the method of content analysis. The object of research is literature, namely the Novel Sang Nyai 1 by Budi Sardjono. The approach used by the researcher is an objective approach that emphasizes literature. With this approach, researchers will easily find data as a description related to the value of education and its relevance in teaching. The results showed that the value of education in the literature of Sang Nyai 1 by Budi Sardjono in the form of irrationality, tolerance, and discipline. The irrationality of the characters Kesi and Kang Petruk has a close relationship in instilling educational values through literature. The value of tolerance education shows tolerance for other people and the natural environment. Kang Petruk was assigned by Kiai Sapu Jagad to preserve nature. The value of education in the form of discipline, both personally and socially, is implicitly explained to be interpreted by the reader. The relevance of the value of education in literature for teaching is that literature is the right and good medium to transfer the value of education to students, both at the school and university levels. Through literature, in the novel Sang Nyai 1 by Budi Sardjono, there are educational values in the form of irrationality, tolerance, and discipline. These three educational values are expected to contribute to the teaching of Indonesian at both the school and university levels..
Marbel Application for Multicultural Based Language Learning During the Covid-19 Pandemic

This research is a case study that investigates and compares teachers' perceptions of using the Marbel application for multicultural-based language learning to two experienced elementary school teachers, especially on language skills, namely speaking skills and students' reading skills. Based on the results of the study, it was found that Marbel Budaya Nusantara in multicultural-based language learning could improve students' speaking and reading skills. The Marbel application also prepares teachers, students and parents to meet the demands of online learning. Thus the Marbel Budaya Nusantara application can be used as a multicultural-based language learning medium. This Marbel online educational game is very relevant and useful in improving the quality and quality of education during the pandemic COVID-19.
Exploration on the Cultivation of Innovative Applied Talents in Local Universities under the Background of Industry-Education Integration

Local colleges and universities should focus on serving regional industries and local economic development, as training base for applied talents with innovative spirit. The fusion of industry and education proposes new guidelines to construct school-enterprise collaborative education platform and integration of industrial chain and academic chain. By using the fusion of industry and education to enhance higher education quality for local colleges and universities, Dezhou University construct the competency-based talent cultivation mechanism from the aspects of reforming the talent training scheme, optimizing the specialty and curriculum system, adopting diversified innovation and entrepreneurship courses, promoting the practice teaching, building platforms for practice and innovation, training "double-skilled" teachers and establishing safeguard measures for talents training. Thus providing guidance and demonstration for the cultivation of applied talents with innovative spirits in local colleges and universities.
An Improved Adaptive Filter by IT2FLS as Tumor MRI Detector

Brain tumor edge identification framework has been of incredible guide to the human doctors.This paper presents an examination investigation of two of the best edge discovery techniques.The two strategies are the Interval Type-2 Fuzzy Logic System (IT2FLS) and the versatile channel.The examination is led utilizing MATLAB.These edge locators are tried on pictures included with 0.001 white Gaussian commotion and salt and pepper clamor.The planned calculation is an improved versatile channel with IT2FLS.This produces more clear and more splendid edges when contrasted with regular techniques results found in the writing.
Hybrid End-to-End Architecture for Hindi Speech Recognition System

Traditional automatic speech recognition (ASR) systems are based on statistical models like hidden Markov model–Gaussian mixture model (HMM-GMM). Deep neural network (DNN)-based ASR systems have a complex structure containing modules like lexicon, acoustic, and language models. Each module has their limitations, and the combined form greatly reduce the performance. Recently, end-to-end ASR models greatly reduce this limitation by introducing single deep network architecture without any additional language resource. Connectionist temporal classification (CTC), attention mechanism, and hybrid CTC/attention mechanism are the three major types of end-to-end models. These end-to-end models require a massive amount of training data to work fine. The training data is not available for the majority of Indian languages. Hindi is one of them. This work is part of the Hindi speech challenge ( https://sites.google.com/view/asr-challenge ) conducted by IIT, Madras, in September 2020. In this paper, we trained the end-to-end ASR system using the Hindi dataset. We found hybrid CTC/attention model with $$\lambda =0.5$$ performs better compare to other models. The training of the end-to-end ASR model has been done without an additional language model.