Reviewerly/exHarmony huggingface dataset:
Self-Assessment and Pre-Service Teachers’ Self-Regulated Learning in a School Organisation Course in Hybrid Learning

<p align="left">The lack of autonomy of university students is a current problem in higher education, being considered a skill that students must acquire. To meet the objectives of higher education, students, especially those enrolled in bachelor’s degree programmes, must be assisted in achieving a greater capacity for self-regulation, for which teachers must find an effective balance between guidance and self-regulated learning. We worked with 39 undergraduate students of the Bachelor’s Degree in Early Childhood Education programme at the University of Salamanca (Spain) who were enrolled in a subject about school organisation, in the context of a hybrid learning mode due to the COVID-19 crisis. The pre-service teachers measured their progress weekly and self-assessed their performance in implementing the subject group work using a digitised rating scale through a questionnaire. The results showed that the students who best self-regulated their learning were more realistic in their self-assessment of their work, although they were not the highest achievers in some cases in terms of the final assessment of the assignment. In addition, the students valued the experience as positive, noting particularly that using the digital questionnaire to reflect on the quality of their work had helped them to improve the final assignment. Based on the results, teachers in the university where the study was implemented are considering continuing this practice and even applying it to other subjects, such as the Final Degree Project, where students have a more autonomous role in their learning and where good self-regulation can have very positive results.
Improving aspect-based neural sentiment classification with lexicon enhancement, attention regularization and sentiment induction

Abstract Deep neural networks as an end-to-end approach lack robustness from an application point of view, as it is very difficult to fix an obvious problem without retraining the model, for example, when a model consistently predicts positive when seeing the word “ terrible. ” Meanwhile, it is less stressed that the commonly used attention mechanism is likely to “over-fit” by being overly sparse, so that some key positions in the input sequence could be overlooked by the network. To address these problems, we proposed a lexicon-enhanced attention LSTM model in 2019, named ATLX. In this paper, we describe extended experiments and analysis of the ATLX model. And, we also try to further improve the aspect-based sentiment analysis system by combining a vector-based sentiment domain adaptation method.
Improved Watermark Criteria Through Mark image

With many applications using digital multimedia technologies, the need to protect digital multimedia data from hackers is emphasized. Copyright holders are concerned about protecting any kind of unlawful duplication of their information. With all these kinds of problems, technology development is very important. Digital watermarks are an important requirement to protect multimedia data. There are important criteria to measure the success of a watermarking process, it is confidentiality, capacity and reliability. In this paper, the logo mark was relied upon to achieve these criteria to a high degree by taking advantage of the symmetry characteristic of the logo image, Which is often used this type of logo images. Symmetry reduces the size of the embedded data, reduces the location of the embedded within the image, and increases confidentiality by encrypting less data in various ways.
THE LEVEL OF DEVELOPMENT OF STUDENTS’ DIGITAL COMPETENCIES IN THE COMMUNICATION DOMAIN

Our time is the time of rapid changes in all walks of life. The fastest changing segment is that of digital technologies. As the development of digital technologies is a current and continuous process, it is expected that in time these technologies will become completely integrated into the school practice. Therefore, it is important to observe if the students are ready and to what extent they are equipped to apply digital tools in education. Furthermore, it is necessary to establish whether students possess digital competencies which will become necessary if one wishes to keep up with the teaching process and complete school assignments or if students´ digital competencies are related to spending leisure time on content that is unrelated to school assignments. The paper researches digital competencies of secondary school students in the communication domain. We strived to establish the level of students´ digital competencies necessary to communicate through digital technologies, and differences in the level of students´ digital competencies bearing in mind their academic achievements, sex, and form. The results of the conducted research indicate that the largest number of students have mastered the basic and intermediate levels of digital competencies in the communication domain, but one cannot disregard the number of students who are advanced users in this domain. When it comes to differences in participants’ responses in terms of research variables, it has been established that there are statistically significant differences concerning sex and academic achievement, while there are no established statistical differences in regard to their form.
A semi-automatic motion-constrained Graph Cut algorithm for Pedestrian Detection in thermal surveillance videos

This article presents a semi-automatic algorithm that can detect pedestrians from the background in thermal infrared images. The proposed method is based on the powerful Graph Cut optimisation algorithm which produces exact solutions for binary labelling problems. An additional term is incorporated into the energy formulation to bias the detection framework towards pedestrians. Therefore, the proposed method obtains reliable and robust results through user-selected seeds and the inclusion of motion constraints. An additional advantage is that it enables the algorithm to generalise well across different databases. The effectiveness of our method is demonstrated on four public databases and compared with several methods proposed in the literature and the state-of-the-art. The method obtained an average precision of 98.92% and an average recall of 99.25% across the four databases considered and outperformed methods which made use of the same databases.
Sentiment Classification of Educational Tourism Reviews Based on Parallel CNN and LSTM with Attention Mechanism

With the rapid development of the Internet and tourism, the Internet has been widely used in the tourism industry. Tourism enterprises and tourists use the Internet to publish and obtain travel-related information. Educational tourism is a new type of tourism activity. As a combination of “tourism + education,” it has gradually attracted the attention of tourists. With its convenience, fast speed, and low barrier, tourism text data provide great convenience for tourists’ sentiment calculation and have become one of the main sources of big data for tourism. However, the reviews of educational tourism have a lot of redundant information and complex sentence patterns, leading to a relatively low classification accuracy of the existing sentiment analysis algorithms. In order to effectively obtain the implicit semantic information of short text reviews for sentiment orientation recognition, a sentiment classification model for educational tourism online reviews based on parallel CNN and LSTM with multichannel attention mechanism is proposed. Firstly, Word2Vec technique is used, and based on noise word filtering, the feature words of educational tourism reviews are extracted to preprocess the input data set. Then, parallel CNN and LSTM are used to extract text local information and contextual features, and a multichannel attention mechanism is used to extract the attention values from the LSTM output. Finally, the output information of the multichannel attention mechanism is fused to effectively extract text features and focus on important words. The experimental results show that compared with other advanced methods, the proposed algorithm achieves improvements in terms of precision, recall, and F1 value and improves the AUC performance. It will help the educational tourism bases to carry out targeted development and construction in response to tourists feedback, enhance the sense of gain and happiness of tourists in educational tourism activities, improve tourism experience, and promote the rapid development of high-quality educational tourism.
Analysis of the Effects of Digital Technology on the Algerian Economy

This study aims to study the reality and prospects of the digital economy in Algeria through annual reports and statistics that present the usefulness of digitalisation in Algerian economic sectors. Using an analytical study, we conclude that the economic sector had not experienced remarkable development in terms of digitalisation, except for a few activities in a few sectors such as health, industry and services that have experienced a gradual evolution to new information and communication technologies, which have brought added value in Algeria.
Improvements on Non-Interactive Zero-Knowledge Proof Systems Related to Quadratic Residuosity Languages

Non-interactive zero-knowledge (NIZK) proof systems are very useful for statement verification without interaction in cryptography ; they entail just one message, called the proof, that convinces the verifier of the truth of the statement without leaking any extra information. Many NIZK proof systems are related to quadratic residuosity languages and follow three main steps. First, the prover and the verifier sample a common reference string (CRS) in some particular form. Second, the prover proves that n is a Blum integer ( BL , n = p 1 t 1 · p 2 t 2 , where p 1 and p 2 are different primes both congruent to 3 modulo 4, and t 1 and t 2 are odd). Third, various statements (e.g., NQR n , OR n , AND n , T ( k , t ) , and 3 SAT ) can be proven by the prover based on the properties of BL . In this study, we improve the NIZK proof system for n ∈ BL based on the special distribution of the square roots modulo n and embed this proof in the third step. Moreover, we show that the CRS can be sampled more efficiently using the improved process.
A framework for belief revision under restrictions

Abstract Traditional belief revision usually considers generic logic formulas, whilst in practical applications some formulas might even be inappropriate for beliefs. For instance, the formula $p \wedge q$ is syntactically consistent and is also an acceptable belief when there are no restrictions, but it might become unacceptable under restrictions in some context. If we assume that p represents ‘manufacturing product A ’ and q represents ‘manufacturing product B ’, an example of such a context would be the knowledge that there are not enough resources to manufacture them both and, hence, $p \wedge q$ would not be an acceptable belief. In this article, we propose a generic framework for belief revision under restrictions. We consider restrictions of either fixed or dynamic nature, and devise several postulates to characterize the behaviour of changing beliefs when new evidence emerges or the restriction changes. Moreover, we show that there is a representation theorem for each type of restriction. Finally, we discuss belief revision of qualitative spatio-temporal information under restrictions as an application of this new framework.
Development of an Augmented Reality Training Environment Construction System Using Puzzle-Like Programming in a Real Environment

Emergency drills and drills against terrorism have been held at nuclear facilities. Shortcomings of these drills are that the numbers of emergency scenarios and roles are limited because many workers must participate in them simultaneously. The times during which all employees can participate simultaneously are limited. As a means of solving these problems, augmented reality (AR) training has been increasingly adopted in recent years, but difficulties of creating contents and the inadequate degrees of freedom in the created contents are becoming problematic. For this study, we developed an AR training environment construction system for users to create scenarios easily by simply assembling and placing blocks representing scenario components in a real-world environment. To realize the construction system, we also developed the “Program Block,” which enables users to create scenarios in a puzzle-like style. The system can create and simulate various scenarios involving interaction between trainees and a real-world environment. To evaluate the ease of system usage and flexibility for scenario creation, a subjective experiment was conducted at a nuclear facility. Results indicate that users can construct an AR training environment easily.
Fostering communication and collaboration through regenerative design games

This paper explores how regenerative design games might foster the communication and collaboration skills needed to scaffold transitions to just and sustainable futures. It explores three design games, each co-designed with different people, for different intents and purposes but each with the shared aim to build people’s capacity for regeneration, open communication, and effective collaboration. Framed by critical pragmatism and performed through co-design, the paper discusses the role of games in explorations of uncertain futures and highlights the important role played by care practices in co-design processes.
Protecting the integrity of relational database by watermarking technique

The paper proposed a watermarked scheme used to protect integrity for relational databases. In this schema, watermark is created from attributes in the database and embedded in some properties of the relational database. After embedding the watermarkin relational database, the use value of the attributes does not change. The paper proves the correctness of the proposed watermarked scheme.
Application of optical measurement techniques during various stages of pregnancy

Optical measurement techniques have evolved since the mid-2000's due to the advancement in computer processing and digital camera sensors. These techniques allow for the digitization of full three-dimensional (3D) surfaces and provide time-domain surface information data with high details not previously possible with more traditional measurement techniques. A variety of industries are using these technologies with a focus on high accuracy industrial applications including aerospace and automotive. This paper introduces optical measurements techniques used to provide quantifiable data and visual information of a woman's abdomen during various stages of pregnancy. Two non-invasive techniques are used for this study including structured light (SL) scanning and digital image correlation (DIC). An overview of these techniques, the process for data collection, results of the data, and opportunities for future studies are presented in this paper. The structured light scanning was used to capture a 3D surface of the woman's abdomen at four to six week intervals starting at week 15 of maternity and ending six days prior to birth. The results quantify growth during each stage of pregnancy along with full surface data in addition to postnatal results. The DIC data was collected during week 30 when the baby was very active in the womb and external deformations on the woman's abdomen were observed visually. The results from these studies were not intended to be a formal medical study but to provide feasibility of the SL and DIC process during the stages of pregnancy and encourage unique uses of otherwise industrial measurements.
Solutions to attract investment in Western mountainous districts of Nghe An Province

Although investment activities in the western mountainous region of Nghe An Province in recent years have not commensurated with the regional resources, they have made a significant contribution to the local socio-economic development of the local region. The article analyzes investment projects in the western highland districts of Nghe An Province in the period from 2016 to 2019, in order to identify the causes and to propose feasible solutions. Through the analysis of secondary data extracted from the Department of Planning and Investment of Nghe An Province, it can be seen that the number of investment projects and the scale of capital invested in the western region of Nghe An Province are too modest compared to their potential. After finding out the causes, the authors propose a number of solutions, which focus on improving infrastructure, the state management of investment activities and investment promotion to attract more investment projects to this area
A survey of software architectural change detection and categorization techniques

Software architecture is defined as the structural construction, design decisions implementation, evolution and knowledge sharing mechanisms of a system. Software architecture documentation help architects with decision making, guide developers during implementation, and preserve architectural decisions so that future caretakers are able to better understand an architect’s solution. Many modern-day software development teams are focusing more on architectural consistency of software design to better cope with the cost-time-efforts, continuous integration, software glitches, security backdoors, regulatory inspections, human values, and so on. Therefore, in order to better reflect the software design challenges, the development teams review the architectural design either on a regular basis or after completing certain milestones or releases. However, many studies have focused on architectural change detection and classification as the essential steps for reviewing design, discovering architectural tactics and knowledge, analyzing software stability, tracing and auditing software development history, recovering design decisions, generating design summary, and so on. In this paper, we survey state-of-the-art architectural change detection and categorization techniques and identify future research directions. To the best of our knowledge, our survey is the first comprehensive report on this area. However, in this survey, we compare available techniques using various quality attributes relevant to software architecture for different implementation levels and types. Moreover, our analysis shows that there is a lack of lightweight techniques (in terms of human intervention, algorithmic complexity, and frequency of usage) feasible to process hundreds and thousands of change revisions of a project. We also realize that rigorous focuses are required for capturing the design decision associativity of the architectural change detection techniques for practical use in the design review process. However, our survey on architectural change classification shows that existing automatic change classification techniques are not promising enough to use for real-world scenarios and reliable post analysis of causes of architectural change is not possible without manual intervention. There is also a lack of empirical data to construct an architectural change taxonomy, and further exploration in this direction would add much value to architectural change management. • Survey on software architectural change detection and classification. • Analysis from various perspectives. • Quickly find SOTA for future research plans. • Beneficial for change management & documentation.
Core Competitiveness of Graduates Majoring in Environmental Design under the Background of “Rural Revitalization + New Liberal Arts”: Cultivation Situation and Renewal Path

Under the background of the great changes that have not been seen in a century and the COVID-19 raging, the CPC Central Committee and the State Council always put the purpose of being realistic and pragmatic and ensure people’s livelihood in a prominent position, attached great importance to the employment of college graduates, listed it as the top priority of employment, and required relevant government departments at all levels to do a good job in ensuring people’s livelihood. Facing the specific reality of the difficult employment of college graduates, professional teachers must be realistic and understand the situation: that is, they must recognize what the core competitiveness of graduates majoring in environmental design is, why is it important and how to improve it, so as to further implement the task of talent training in Colleges and Universities in the new era, innovate the path of talent training and complete the mission of teaching and educating people.
Social media as new effervescent tool for higher education post Covid-19

All Industries and Business People are running behind social media as today’s customers, their suppliers, all prospective employees, and all stakeholders also found on these media platforms. Popular Social media platforms, such as Google Hangout, Twitter, Instagram, Facebook, and LinkedIn, are internet-based applications that build on the societal needs with strong technological foundations for Group communications and exchanges seamlessly. New generation technology-based eLearning platforms are incorporating these social media applications into learning environments also. Thus, they are challenging the status quo of traditional learning modes by using the latest technology innovations, including Social media.cSocial media is about building relationships with improved 24 x 7 communications and more interactively and excitingly learning from others. Hence, it can be used in the learning process to build and grow peer-to-peer interactions and improve peer learning, 24 x 7 Student support and help. “Peer to Peer learning” is a very imperative factor in any teaching and learning process. Information and awareness collected using social media by people can provide useful perceptions about various matters more than the traditional pedagogy with brick-andmortar structure. It can also be used for peer evaluations and determine one’s performance in the group study. The usage of social media has been growing in everybody’s life, and learning should not be an exception for the same. Some years back, it was considered bad to use social media, but today everybody is looking from another side. Universities and Institutions with their vibrant faculty/staff teams are adapting these changing needs of the new paradigm shift in Learning Settings and becoming primary adopters. Initial adopters have the early lead and reasonable advantage also. Today’s most prevalent social networks are Facebook, Twitter, and LinkedIn, used by the majority of people when you consider social media. The true social media experience is much larger than it is explored by many. These platforms can involve and engage students using Smartphone apps by developing interactive Android Apps, which can be used anytime and anywhere by the students. This research provides a comprehensive literature review of such tech-savvy University and Institution approaches and their value proposition for being competitive in this Digital Era using these Online and Social Media Platforms successfully to find out attractions and capabilities available in these media platforms.