Reviewerly/exHarmony huggingface dataset:
Application of online and offline blended teaching mode in higher vocational English teaching

With the rapid development of the economy and society, the development process of the education industry is also continuing to accelerate.The teaching mode has also changed a lot compared to the past.Nowadays, the hybrid teaching strategy of online and offline has gradually received widespread attention, and has further connotation in the context of the development of the new era.Because the online and offline hybrid teaching mode can fully reflect the autonomy of students, and fully integrate the past classroom teaching and online teaching platform, it can effectively solve the situation that English teaching in vocational colleges and universities is relatively long and inefficient, and can also provide new information reference for the improvement of future teaching mode.Based on this, this paper mainly studies the practical application of online and offline hybrid teaching mode in the process of high school English teaching, hoping to promote the smooth progress of higher vocational English teaching activities.
An Interactive Query Differential Privacy Protection Model Based on Big Data Analysis

The problem of information leakage is becoming more and more serious, and how to effectively protect the security of personal privacy information has become an urgent problem at present. To this end, this paper proposes an interactive query differential privacy protection model based on big data analysis. The model is based on the irrelevance processing of differential privacy association rules to find out the hidden association information among trajectory data sets. The model uses the shared prefix method to de-compress the trajectory dataset deeply. The model constructs prefix trees to clarify useful information and remove redundant trajectory data. The model constructs a parallel gradient descent matrix decomposition algorithm based on the low-rank mechanism and alternating direction multiplier method to remove the load matrix built from the initial results and decompose the corresponding irrelevant load matrix. The model then takes reasonable values according to the user authority level to limit the privacy budget maximum. The model uses Laplace’s principle to add the determined reasonable noise to the differential privacy trajectory data, reduce and delete the irrelevant attribute trajectory data, and finally feed the query results to the user. Through simulation and comparison experiments, we conclude that the proposed model can make the privacy information available to the highest degree and minimize the success probability of stealers, and thus the differential privacy track data can be protected to the best effect.
Analyzing Digital Education using Neutrosophic Sets

Digital learning is a broad umbrella of any form of learning incorporating novel digital technology aspects in teaching and assessment to facilitate learning and engage students. Most education settings have moved from face–to–face to e-learning platforms worldwide ever since the beginning of the COVID-19 pandemic. Assessment of the efficiency of digital learning is essential, and assessment criteria may take several forms. Digital learning effectiveness assessment has received a significant amount of attention and work; nevertheless, a generalized quantitative evaluation model that considers the inter-affected link among criteria and the uncertainty of personal perception simultaneously is still absent. In this study, the hybrid MCDM model that was suggested handles the independent relations of assessment criteria with factor analysis, and it addresses the dependency relations of assessment via the use of AHP. The AHP and neutrosophic integral approaches are used for the purpose of creating synthetic usefulness in line with the environment of subjective perception. This quantitative research study explores students’ readiness to continue utilizing e-learning while measuring satisfaction levels with the e-learning system among higher education students in the Gulf area. Moreover, students’ behavior intention is measured here. Descriptive analysis was opted to achieve the aim of the study. Data analysis demonstrated that higher education students showed medium to high readiness levels towards e-learning and were identified with a medium level of satisfaction with the e-learning system. Moreover, students demonstrated a high intent to utilize the e-learning platform in case of offering parallel e-learning courses in the future.
Differentially Private Clustering Algorithm for Mixed Data

Inspired by the current practice where mixed data is the norm instead of exceptions and the privacy concerns on data management, we propose a differentially private mixed data clustering (DPMC) algorithm considering the cluster analysis on both numerical and categorical data. First, we design an adaptive privacy budget allocation method to analyze the loss due to added noise, thus determining the number of iterations and the privacy budget given accuracy and dataset characteristics. Next, we develop an optimization method based on consistency inference for categorical attributes, in order to improve the clustering performance. Finally, comparative experiments have been carried out using four real-world datasets. The results demonstrate significant improvement in balancing between privacy protection and performance.
A Hybrid Secure Two-Party Protocol for Vertical Federated Learning

Federated learning (FL) is a promising distributed machine learning technique for solving the privacy leakage problem in machine learning training process. Multiple parties collaborate to train a machine learning model, while the data is kept locally, so as to achieve privacy-preservation of users. However, some studies have shown that an attacker can infer some sensitive information from the interacted data, even if the raw data is not available. It is necessary to adopt some privacy-preserving techniques such as secure multi-party computation and homomorphic encryption to prevent the above problem. Most existing solutions have focused on FL over horizontally partitioned data but ignore the research on FL over vertically partitioned data. In this paper, we present a vertical federated learning scheme with enhanced privacy preservation. Split learning is used to enable cooperative neural network training between multiple parties with vertically partitioned datasets, and a hybrid secure two-party computation protocol is adopted for protecting users’ privacy. The experimental results demonstrate the feasibility of our scheme.
Body Temperature and Oxygen Level Detection System

A device comprising an oximeter and a module for detecting body temperature has been designed so that a person can readily check his or her health in crucial situations. This was accomplished by programming Arduino to output values measured by sensors such as the MAX30102 (Particle Sensor) and GY-906-BCC (Infrared Sensor). We’ve all been dealing with a global pandemic for the past year. As a result, there have been numerous coronavirus discoveries. The COVID-19 virus primarily affects an individual’s respiratory system, lowering the patient’s oxygen levels, and it causes a rise in body temperature. This approach can be quite valuable in such situations and can aid in the regular monitoring of an individual’s health.
Syntactic priming in the L2 neural language model

In recent years, the increasing abilities of neural (-network) language models (NLMs) have led to examining their representation of syntactic structures. To assess the linguistic knowledge that NLMs acquire, researchers have leveraged the traditional syntactic priming paradigm to investigate the potentials of NLMs in learning abstract structural information. In this study, we concentrated on investigating the extent to which the L2 NLM is sensitive to syntactic priming in psycholinguistic. Following Sinclair et al. (2022), we adopted a novel metric with which we controled various linguistic factors. Based on this adoption, we implemented the L2 NLM trained on the L2 corpus and explored which factors influence the strength of priming effects. In so doing, we discovered that the L2 NLM is also sensitive to various linguistic factors but displays irregular syntactic priming performances depending on experiments with different types of controlled materials.
Encompassing argumentation by Relevance Theory

This paper aims to make a pragmatic account of encompassing argumentation by a communicative theory such as Relevance Theory (RT). While communication can be viewed as a discourse in which communicators share their intentions with each other, argumentation is a process of vindicating something in a systematized and logical way, which consists of one or more claims, and presents one or more grounds for supporting them. In general, a speaker conveys his intention to a hearer for the purpose of making an influence in the hearer’s mind. With reference to this point, there have been two relevant pragmatic theories such as RT and Argumentation Theory (AT). Judging from the pragmatic point of view, argumentation can be viewed as a part of communication; thus, it is possible to assume that RT could effectively encompass argumentation. This paper argues that although RT has focuses more on examining the process of communication than how argumentation is performed, by extending the range of its application, it can integrate AT and successfully cover the domain of argumentation as well.
A study on the effect of synchronous hybrid learning (SHL) in a college English course: A comparison of face-to-face learners and online learners

This study aims to investigate whether and how the synchronous hybrid learning (SHL) environment impacted face-to-face group (F2FG) and non-face-to-face group (NF2FG) differently in terms of their academic achievement and learning satisfaction. The results were as follows: First, while test scores increased with both groups, only the F2FG showed a statistically significant improvement. Second, survey results revealed that the two groups differed in the degrees and areas of satisfaction. The F2FG gave higher satisfaction scores than their counterparts in teacher-learner interaction, class participation, and class effectiveness whereas overall attitudes toward SHL were more positive with the NF2G. Lastly, the participants cited the relative ease of concentration (F2FG) and not being restricted by location (NF2FG) as the strengths of SHL. As shortcomings, they pointed out the instructor’s attention being constantly divided between the two groups of learners and occasional delays in communication due to technical glitches.
A linguistic feature analysis of English abstracts of articles on English linguistics by Korean and American scholars

The recent studies on English abstracts have been analyzed focusing on the rhetorical move structure and some linguistic features of MA theses and PhD dissertations. However, little research has been conducted to explore the linguistic features of English research articles. This study aims to investigate the linguistic features in English abstracts between Korean non-native speakers of English (NNS) and native speakers of English (NS). A corpus consisting of 100 abstracts (50 abstracts each) is analyzed at the word, phrase, sentence and discourse levels. The results show that i) English native speakers have a higher TTR than non-native speakers on lexical diversity and density, which means the former uses more various lexical items than the latter, ii) on the phrase level, high frequent n-grams occur in the introductory part of the abstracts of non-native speakers and in the conclusion part of the native speakers, and iii) on the sentence level and above, all the scores of text readability are higher in NS texts than NNS ones, which means the latter texts are more difficult to understand than the forner.
An authoring tool for task-oriented dialogue scenarios design in EFL context

Computer-based conversational environments have been advocated as a promising approach for providing virtual, yet realistic opportunities for communication practice to second language learners. However, the high authoring costs of such environments continue to prevent their widespread diffusion and adoption. Furthermore, there is a limited set of authoring interfaces dedicated to making the creation of dialogue scenarios in the context of language learning easier. In this research, we present a dialogue scenario authoring system that could aid the rapid implementation of desirable dialogue scenarios, lowering the barrier to dialogue scenario authoring for non-programmers or even educators. To that end, we built a pseudo-versatile dialogue scenario authoring interface that enables the automatic generation of services-related dialogue scenarios by leveraging the common underlying structure of services (restaurant, hotel, travel planning, etc.) that appear to share a certain degree of similarity at the task level. Here, we describe the proposed system’s features and present the findings of an experimental evaluation study that suggests the usefulness of our approach to facilitating dialogue scenarios designed by people with no prior experience authoring dialogue systems components. According to an evaluation of the tool by a second language teaching expert, the proposed system might also foster second language teaching and learning by allowing both educators and learners to participate in the design of dialogue scenarios that are adapted to different levels of learners.
Popularity-Based BERT for Product Recommendation

Daily, a large number of ratings and reviews are shared on various social media platforms and websites. Manufacturers wish to create a user recommender system that can discover possible target customers fast and effectively. Different recommendation models are used by online e-commerce platforms like Amazon and Flipkart to deliver different choices to different users. We gathered data of user reviews on Amazon electronic devices for this study. As a result, this research uses review data with ranking (rating) labels on Amazon's electronic items to fine-tune and carry out fine-tuning the bidirectional encoder representations from transformers (BERT) model. We have built a recommendation system that allows recommending products to users/customers related to past product ratings. This study proposes a popularity-based recommender for recommending electronic devices/products to relevant potential consumers. To predict ratings, the proposed recommender system uses fine-tuned BERT. The popularity-based approach looks for products that are currently trending or popular among users, then recommends them to clients right away. In this study, we have recommended popular products to the users/customers which are frequently rated/reviewed by different users.
An analysis of business English textbooks based on the revised 2015 national curriculum

This study examined whether the business English textbooks used in vocational high schools followed the revised 2015 national curriculum and were abided by its teaching and learning principles. In this study, three business English textbooks were analyzed both quantitatively and qualitatively. First, in terms of skills, all of the coursebooks covered writing the most while treating speaking minimally. This unbalanced coverage of skills went against the curriculum’s goal which pursues communication-oriented business English education. Among three textbooks, one rigorously followed the curriculum while the other two did not. However, the in-depth analysis based on the teaching and learning principles stipulated in the curriculum showed that the textbook that strictly adhered to the curriculum did not offer engaging activities, which can promote students’ communicative competence in a business setting. Pedagogical suggestions were discussed.
COMMUNITY RELATIONS MANAGEMENT IN CONTEMPORARY CORPORATE HOUSES

Modern organizations receive land, labor, capital, investors, distributors, consumers, image builders, events managers and other facilitators of organizational development. They are required to establish and maintain a mutually beneficial relationship with the communities since they are at the receiving end. Community relationship management is an important activity undertaken by the modern organizations. These organizations must cultivate civic responsibility and repay their gratitude to the local community. Community involvement is necessary to foster a sense of community teamwork for the sustainable development of the organization. A comprehensive community relations program enhances the visibility of organizations and brings the community closer to the organizational mainstream. Good community relations programs generate series of advantages to the organizations. New business opportunities also crop up on the basis of effective community relations programmes implemented by the modern organizations. The salient features of community relations management are primarily discussed in this paper on the basis of qualitative research methodology.
Impact of Expanding Coal Industry on the Regional Environment in an Indian Coal-Belt - A Case Study from Jharkhand, India

Environmental sustainability of coal industry is a major concern considering the trends of its exponential effect on the region and towards climate change. The study examines the land use/land cover changes using spatio temporal datasets of the years 2000 and 2020 in Dhanbad district which comes under the major coal-belt of India. The study shows the impact of expanding industries on the environment depicting a remarkable decrease in vegetation (18.89%), increase in built-up land (14.32%) and coalfields (0.9%) exhibiting massive deforestation activities. The study focuses on the increase in emissions from coal mining activities including GHGs, SOx, PMs, etc. over the years and their harmful impacts on the region. The sustainability evaluation of the coalfields of the study area is done through 15 predetermined indicators, suggesting the urgency and need of actions for sustainable functioning of coal mining industry in order to limit global warming to below 2 °C as suggested in the Paris Agreement-2016. The study also lays stress on the changing economic pattern of the region as an effect of increasing industrialization and changes in the land use.
Latency and Prevention of Fraud in Labor Legal Relations

The following measures can be proposed to prevent and detect labor fraud. They can be divided into two groups: informational and control. Informational measures provide for informing about the labor fraud in the media. Though there is not enough information about labor fraud nowadays, the potential victim is warned about the very possibility of such fraud. Management measures are directly aimed at identifying labor fraud. To detect and prevent labor fraud, the employer should have a more careful control over how wages are calculated and how the employee performs the work. If the organization is not large or an individual entrepreneur has up to 100 employees, the employer or the head of the HR department can directly control whether there is embezzlement through fraud. If the organization is large with a large number of structural divisions and a large number of employees, a special control department can be created for internal, personal or economic security. This department should consist of lawyers, economists, accountants, specialists in economic and information security, as well as a specialist in personnel. Its objective will be to identify theft by fraud in the field of labor relations. It does not imply total control on the part of the employer, but if there are grounds to believe that theft may be committed through labor fraud, a more careful control will be appropriate and expedient, and the employer just needs to be more vigilant. All actions on the part of the employer exercising control must comply with the applicable law. Thus, only proper and reasonable oversight by the employer can prevent and detect labor fraud.
Formation of the information culture of the individual in project and research activities

The article is devoted to the problem of finding an effective methodology for the formation of the value bases of the college students’ information culture of education in the design and research activities. The article presents a theoretical analysis of the experience of forming the value foundations of the information culture of the individual. The authors identify the stages of the process of formation of the value bases of the information culture of students in the organization of secondary vocational education. The article presents a description of experimental work, in the core of which there is design methodology’s and research activities’ modernisation with an emphasis on the formation of the value foundations of the information culture of the individual. The paper describes the author's diagnostic tools for assessing the dynamics of the formation of the value bases of the information culture of the individual according to the practice-activity criterion. The analysis of the results indicates the positive dynamics of the formation of the information culture value foundations. It is concluded that the presented results of the empirical study, as well as the secondary mathematical and statistical processing of the results by the chi-square method, confirm the effectiveness of the described work on the formation of the value foundations of the information culture of students of secondary vocational education.
Complex numbers in the school course of Mathematics and in the perspective model of the final exam

The article is devoted to the use of the concept of a complex number in a school Mathematics course. Until recently, the topic of complex numbers had not been included in the state final exam, however studied in classes with in-depth study of mathematics. In connection with the introduction of tasks related to this concept into the prospective model of the unified state exam, it is now becoming topical. The article primarily touches upon the analysis of the presentation of material in school textbooks, in particular the concept of a complex number. Then there are several examples of problem solving, which was presented in a promising model of the unified state exam in Mathematics, using both analytical and geometric interpretation of a complex number. In addition, various approaches to solving the problem are shown, both algebraic (estimation method) and geometric (finding the altitude in a triangle, similarity method, methods of analytical geometry) methods, as well as methods of mathematical analysis (finding the largest or smallest value using the derivative). The article also contains some methodological recommendations for preparing on this topic and a system of tasks that can be offered both to teachers in preparing for the exam, and to pupils to consolidate the skill of solving tasks of this type.