Reviewerly/exHarmony huggingface dataset:
Research on the Role of Corrective Feedback in Teaching of Chinese as a Second Language: A Systematic Review and Meta-Analysis

The study adopts a systematic review and metaanalysis approach to summarize the qualitative research on corrective feedback and to discuss the application and effect of corrective feedback under different conditions in Teaching Chinese as a Second Language in the classroom setting. Data mining was conducted from 2006 to 2020 based on the database of CNKI and Google Scholar and analyzed by a systematic review and meta-analysis. There are a total of 20 articles, 18 master's degree thesis and 2 journal papers were involved based on the selection criteria. The use distribution and correction effect of different feedback methods are integrated. The correlation of another five factors (error type, teaching link, language proficiency, research setting, individual factors of teachers and students) was established. Several conclusions were drawn: (a)Error types, teaching links, language proficiency and research setting will all affect the utilization rate and repair rate of corrective feedback, and their influence decreases successively. (b)The response rate and self-repair rate of implicit feedback are higher than that of explicit feedback. (c)Prompts (especially metalinguistic clues and elicitation) is most conducive to learners’ self-correction, so as to promote their Chinese acquisition. (d)The utilization rate of recast is the highest, but its repair rate is much lower. (e)The utilization rate of repetition is the lowest, but response and repair rate is high. (f)The feedback rate to clarification is high but the rate of correction is low. (g) Metalinguistic clues are most likely to trigger learners’ anxiety, while recast can effectively reduce anxiety.
Improving Few-Shot Text-to-SQL with Meta Self-Training via Column Specificity

The few-shot problem is an urgent challenge for single-table text-to-SQL. Existing methods ignore the potential value of unlabeled data, and merely rely on a coarse-grained Meta-Learning (ML) algorithm that neglects the differences of column contributions to the optimization object. This paper proposes a Meta Self-Training text-to-SQL (MST-SQL) method to solve the problem. Specifically, MST-SQL is based on column-wise HydraNet and adopts self-training as an effective mechanism to learn from readily available unlabeled samples. During each epoch of training, it first predicts pseudo-labels for unlabeled samples and then leverages them to update the parameters. A fine-grained ML algorithm is used in updating, which weighs the contribution of columns by their specificity, in order to further improve the generalizability. Extensive experimental results on both open-domain and domain-specific benchmarks reveal that our MST-SQL has significant advantages in few-shot scenarios, and is also competitive in standard supervised settings.
SOCIAL SELF-DETERMINATION OF A SECONDARY SCHOOL STUDENT IN THE CONTEXT OF HUMANIZATION OF THE EDUCATIONAL PROCESS

We regard the social self-determination of senior secondary school students as the basis for their education as citizens of Latvia and citizens of Europe. This underpins the need to actualize the problem of social self-determination. The aim of the research is to determine the essence and structure of social self-determination of senior secondary school students and to identify the conditions for the development of social self-determination in secondary school students in the process of education. Research methods include observation, questionnaire, survey, comparison, experiment, and mathematical statistics. Research results are the following:- as a result of the study, there was determined the content and structure of social self-determination as a systemic personal formation, representing the relationship of two components: citizenship and intercultural identity; - the conditions for the development of social self-determination have been identified, including the humanization of the educational process based on a certain system of moral values and beliefs; - the key strategy for organizing the educational process has been suggested: changing the content of education by introducing a cultural component, which would contribute to a change in all structural components, from the goal to the result; - this implies a change in the procedural aspect of education: the organization of a personal cultural dialogue; the dialogue is regarded as the basis for communication in the pedagogical process; - the key values of secondary school students were determined in the process of a fact-finding experiment.
Multi-Objective Optimization Method for Task Scheduling and Resource Allocation in Cloud Environment

In the cloud environment, the process of task scheduling and resource allocation plays a vital role in cloud resource management. The unpredictable and uncertain behaviour of the task arrival rate poses significant challenges in the effective allocation of resources. An efficient scheduling technique is essential to avoid under or overutilization of resources. In order to increase the performance of scheduling and allocation, this paper presents multi-objective optimization method for optimal resource allocation and task scheduling based on a three-stage strategy. In the first stage, a description of tasks and virtual machines is prepared. At stage two, tasks are classified and labelled based on the resource demand and execution time. Finally, the modified-Grey Wolf optimization algorithm is used for the allocation and scheduling of tasks for a disparate scenario. The experimental results proved that the proposed method reduced the makespan time and cost with an improved utilization rate.
Scale Invariance, Power Laws, and Regular Variation

An introduction to the class of regularly varying distributions and the important properties of this class, including scale invariance. Examples of applying regularly varying distributions to branching processes are included.
Image steganography based on LSB using various scanning methods in spatial domain

Data security plays a vital role in the field of Information Technology. Cryptography and Steganography methods are widely used to enforce security efficiently. In Spatial Domain, many steganography methods are available such as LSB, PVD etc. These existing methods always suffer from the quality, security trade off. In this paper, we proposed an enhanced LSB method to deal with such tradeoffs. The proposed method achieves the goal by employing variable embedding patterns and the results with optimized PSNR, MSE and entropy values evidently show that the quality and security are well balanced by the proposed method.
DISTANCE EDUCATION AS AN ALTERNATIVE FORM OF LEARNING IN A PANDEMIC CONDITION

The aim of the research is to analyze the relationship between the success and frequency of the distance learning server Moodle using in the study of medical students, as well as to assess the features and identify major problems in training during COVID-19 pandemic. The results of 200 medical students total success have been analyzed. Students’ education achievement was assessed as a factor in determining the training success in the context of relationship with the number of Moodle distance learning server visits. Two subgroups have been analyzed (100 people in each) depending on the departments: сlinical discipline (propaedeutics of іnternal medicine) and theoretical (biochemistry). Statistical analysis of students’ activity in Moodle system revealed high correlation between the frequency of the platform visits and students’ educational success at the Department of Propaedeutics of Internal Medicine. A similar pattern is observed in the analysis of the correlation between the use of Moodle and learning outcomes in theoretical disciplines by the example of Bioorganic and biological chemistry and clinical biochemistry department. Thus, in order to prevent the spread of acute respiratory disease COVID-19, an distance education elements should be implemented; the using of the Moodle platform helps to increase medical student’s educational success.
Facial Expression Recognition in Real Time Using Swarm Intelligence and Deep Learning Model

The human face manifests many different emotions and leads to certain actions as per their intentions. The determination of human intensions by analyzing their facial expressions can serve the society to preserve tranquil habitats in different aspects, such as detection of autism and depression; helping to understand dumb, deaf, and bedridden humans; mental state analysis; suspicious people detection; online student assessment; and more. Moreover, Society 5.0–centered advanced applications can be created with a focus to preserve human happiness and technological growth. The implementation of a facial expression recognition system helps to accomplish the goal of Society 5.0 by incorporating the mentioned convenience. This chapter aims to develop an autonomous facial expression recognition (AFER) system in real time for the classification of expressions. The classification model is a hybrid approach of deep convolutional and recurrent neural networks, which is experimented in real time for 36 humans (24 males and 12 females) ages 20–35. The feature components are extracted using the hybrid Gabor filter and local binary pattern. The selection process exploits the modified swarm intelligence approach of an improved quantum-inspired gravitational search algorithm. The AFER system is trained with the JAFFE, KDEF, RaFD databases, and some Indian expression images. The trained system is tested for front pose and movement of face to the yaw angles −30 and +30 degrees. The results are determined in terms of recall, precision, f-measure, recognition rate, and accuracy measures. Also, the results are evaluated for the existing AFER system, and a comparison is conducted. The comparative analysis indicates the significant performance of the proposed AFER system compared to existing systems.
Analysis and Countermeasure Research of Modern English Teaching Problems Based on Data Mining Technology

In order to improve the effect of English teaching reform, this paper combines data mining technology to analyze the modern English teaching process and formulate corresponding strategies. Moreover, this paper uses the parameter covariance moment drop as a performance indicator to evaluate the data points in the sample set and obtain the preliminary clustering of the data points. At the same time, this paper adjusts the initial accumulation of data points, including merging and deleting clusters, and this paper assigns missing data points and corrects data points that are incorrectly clustered. In addition, this paper adopts the LSVM method to segment the interval and constructs the system structure on the basis of this data analysis. Through the simulation teaching research, we can see that the problem analysis and countermeasure research system of modern English teaching based on data mining technology proposed in this paper meet the needs of modern English teaching reform.
Towards a Feasible Hand Gesture Recognition System as Sterile Non-contact Interface in the Operating Room with 3D Convolutional Neural Network

Operating surgeons are constrained when interacting with computer systems as they traditionally utilize hand-held devices such as keyboard and mouse. Studies have previously proposed and shown the use of hand gestures is an efficient, touchless way of interfacing with such systems to maintain a sterile field. In this paper, we propose a Deep Computer Vision-based Hand Gesture Recognition framework to facilitate the interaction. We trained a 3D Convolutional Neural Network with a very large scale dataset to classify hand gestures robustly. This network became the core component of a prototype application requiring intraoperative navigation of medical images of a patient. Usability evaluation with surgeons demonstrates the application would work and a hand gesture lexicon that is germane to Medical Image Navigation was defined. By completing one cycle of usability engineering, we prove the feasibility of using the proposed framework inside the Operating Room.
Automated Cancer Diagnostics via Analysis of Optical and Chemical Images by Deep and Shallow Learning

Optical microscopy has long been the gold standard to analyse tissue samples for the diagnostics of various diseases, such as cancer. The current diagnostic workflow is time-consuming and labour-intensive, and manual annotation by a qualified pathologist is needed. With the ever-increasing number of tissue blocks and the complexity of molecular diagnostics, new approaches have been developed as complimentary or alternative solutions for the current workflow, such as digital pathology and mass spectrometry imaging (MSI). This study compares the performance of a digital pathology workflow using deep learning for tissue recognition and an MSI approach utilising shallow learning to annotate formalin-fixed and paraffin-embedded (FFPE) breast cancer tissue microarrays (TMAs). Results show that both deep learning algorithms based on conventional optical images and MSI-based shallow learning can provide automated diagnostics with F1-scores higher than 90%, with the latter intrinsically built on biochemical information that can be used for further analysis.
The impact of the liberalist educational doctrine on the higher education in Russia

Problem and Purpose. The paper deals with different views on the problem of recessionary processes in the Russian higher education. The authors consider the significant impact of the educational doctrine of neoliberalism to be a significant reason for the systemic crisis of the higher education in modern Russia. The purpose of the article is to analyse the main ideological postulates of neoliberalism that address education directly and turn it into an integral part of the global economy. Materials and methods. The research materials are represented by scientific publications of Russian and foreign authors, including pedagogical and socio-political periodicals, conference materials, monographs, Internet resources. The following methods were used: source study, comparative description, comparative and linguistic analysis. Research findings. The authors note the large-scale active penetration of neoliberal ideology into the sphere of education. Particular attention is paid to the analysis of attractiveness of “human capital” and “lifelong learning” ideologemes in neoliberal interpretation, which in fact turn out to be the mechanisms for devaluation of spiritual meaning of education and its commodification. The article presents critical arguments in respect of the strengthening neoliberal position present in the activities of Russian universities: involvement in competition, signs of “academic commerce”, commodification of scientific and educational products, bureaucratisation. It is emphasised that, in the context of the structure of university education according to the business process model, students are offered the position of educational services consumer, which is hypocritically decorated as training of “cognitarians” – creative leaders of the “knowledge economy” era, but in fact – narrow specialists with a set of competences that require constant updating. Conclusion and resume. The study has shown that the problem of higher education crisis is actively discussed by the scientific and pedagogical community in the West and in Russia; the influence of economic and political processes on the traditional foundations of university education is tangibly realised. However, the search for solution to the relevant problems will take place in different directions: the West focuses more on the political leverage of transformation, while the Russian education is aimed at development within its methodological guidelines. The withdrawal from the crisis and overcoming the influence of the educational doctrine of neoliberalism is possible only through the establishment of a new ideology in Russia.
Cybersecurity Management for Incident Response

In information technology, security is the protection of information assets through the use of technology, processes and training.There will always be situations of attack on software systems but the software must continue to work properly under such potential risks.The security process assumes and is required to provide three important elements: integrity, authentication, and availability.Security is a set of processes and techniques implemented to protect private information in electronic or printed format against modification, destruction or unauthorized access.This paper discusses effective management of cybersecurity for incident response.
Virtual classroom management solutions for COVID–19 related anxiety issues

The COVID-19 pandemic has brought immeasurable changes in almost every aspect of our lives and education is no exception. Following social distancing policies, the vast majority of educational institutions across the globe have shifted their academic structure from traditional face-to-face classes to online classes through a video conferencing software ‘Zoom’ as a synchronous method of instructions. Besides the fact that a complete diversion of classes toward online education has brought hope to many students to continue their education amid this time of the pandemic, there are many drawbacks to online learning, including online learning anxiety, that keep many students from achieving their learning goals. This study is designed to investigate Korean university students’ attitude toward online learning in general and their feelings of anxiety (if any) in particular when using video conferencing software ‘Zoom’. This mixed method study was conducted in two universities in Korea. Participants (n=132) were both male (n=61, 46.2%) and female (n=71, 53.8%) undergraduate students enrolled in the English linguistics department. The hypothesis stated that students with different socio-economic backgrounds have different attitudes towards online learning, which affects their feelings of anxiety for online learning. Quantitative data was collected in the form of survey questions, and interviews were conducted with randomly selected students (n=13) to obtain qualitative data. The findings suggest a few pedagogical implications for both teachers and students that include interventions and support by the experts to feel less isolated in online classes, and provision of a more user-friendly platform to be connected with teachers and peers.
THE VERBAL CREATIVITY OF PRESCHOOLERS AS A PEDAGOGICAL PROBLEM

The article has considered and analyzed psychological and pedagogical approaches to the problem of children’s creativity, especially children of preschool age. We have shown the views of scientists on the concept of “verbal creativity of preschool children”, which is understood as a twofold process of accumulation of impressions in the process of pedagogical activity and their creative processing into the language of verbal signs. Psychological and pedagogical principles of verbal creativity of preschool children have been revealed. The author of the article has highlighted pedagogical conditions for the development of children’s verbal creativity.The purpose of the study is to conduct a theoretical analysis of psychological and pedagogical research on the problem of verbal creativity of preschool children and to identify pedagogical conditions for its development. Research methods – theoretical analysis of the literature on psychology, pedagogy, comparison and classification of materials on the research problem, method of theoretical constructions.Based on theoretical analysis, it has been established that for active and successful participation of preschool children in verbal creativity children have to require a psychological platform in the form of developed imagination, creative thinking, figurative perception, speech in all its aspects. The structure of the process of development of verbal creativity in preschool childhood includes three stages: preparatory (accumulation of experience), the actual process of verbal creativity and the final (analysis of the results).The implementation of pedagogical conditions for the development of verbal creativity of preschoolers requires more careful consideration of the problem of preparing a specialist for the development of verbal creativity of children, which we have seen as prospects for further research.&#x0D; Keywords: creativity; children’s creativity; verbal creativity; speech development; artistic perception; poetic hearing; preschooler; conditions for the development of verbal creativity.
VIOLENT SPEECH DETECH IN VIDEOS USING NATURAL LANGUAGE PROCESSING

The increasing expansion of Internet users has resulted in unwanted cyber concerns such as cyberbullying, hate speech, and a slew of others. This paper deals with the reviewing of different techniques used to detect hate speech by many scholars and researchers. Hate speech occurs when an individual or a group of individuals attack or use derogatory or discriminatory words towards a group of people based on characteristics such as origin, sexuality, ethnicity, religious background, socioeconomic status, race, gender, and other factors. When such action takes place on social networking sites, blogs, creative material, and other forms of online media, it is referred to as Online Hate speech [1]. Hate speech appears to be an explosive kind of communication that uses misunderstandings to promote a hate ideology. Hate speech targets a variety of protected characteristics, such as gender, religion, color, and disability.[2]. Hence it becomes to monitor every post and try to filter out hate speech spreading posts. Concerning this aspect, many techniques have been published using different aspects of machine learning and deep learning. Several attempts to categorize hate speech using machine learning have been performed, with this one focusing on the use of rudimentary NLP feature engineering approaches
An Analysis of the Use of Code Switching in the Students' Conversation

&lt;p&gt;&lt;span lang="EN-US"&gt;This present study aims to analyze the use of code switching in English conversation. This study focuses on the types of code switching that are often used by students in English conversation. The present study employed qualitative descriptive method. The participants were two first semester students of the English education program at Wiralodra Indramayu University. Before making observations, the writer first provided a conversation topic to make it easier to analyze the types of code switching used by students when speaking English. In this step, the writer observed the participants’ conversation using a recording device, then analyzed the results of these observations and conducted interview with students to find out the contributing factors of using code switching in their English conversation. The results of study point out that the first student uses the types of code-switching of inter sentential, intra sentential, and tag switching, while the second student uses the types of inter sentential and intra sentential code switching. Several contributing factors in doing the code switching are identified as nervousness, lack of vocabulary, and forgetting when speaking. Moreover, it is also defined that the use of code switching when speaking English is aimed to facilitate the participants’ conversational fluency&lt;/span&gt;&lt;/p&gt;