Reviewerly/exHarmony huggingface dataset:
SECTION #4. VIRTUAL EDUCATIONAL ENVIRONMENT IN THE SYSTEM OF PROFESSIONAL FOREIGN LANGUAGE TRAINING 4.2 EDUCATION OF PATRIOTISM IN INTERNATIONAL STUDENTS THROUGH GAMIFICATION

The article outlines the relevance of patriotic education-teaching of future specialists in international relations, substantiates the emergence of new modernized, rethought forms and methods of work in the context of patriotic education-teaching. The scientific understanding of patriotism education based on the model of humanistic oriented developmental education through subject-subject and socio-pedagogical strategy is revealed. The possibilities for implementing these strategies through the use of gamification tools during practical foreign language classes as a space for creating effective conditions for the education of a citizen-patriot are substantiated. Gamification is characterized as one of the key trends in European education of the 21st century. The purpose of the article is to reveal the potential possibilities of gamification in the process of educating and teaching the patriotism of future specialists in international relations, to identify advantages and possible risks, to expand teachers' ideas about the possibilities and resource potential of gamification in education. The advantages of gamification as a means of patriotic education-teaching are described, the optimality of using this tool in working with students of international relations is revealed, the peculiarities of the implementation of gamification in this age period are revealed, the task of gamification in the context of patriotic education-teaching is outlined. The novelty of the research consists of the introduction into the practice of higher education institutions of patriotic education-teaching by means of gamification during practical foreign language classes. The functions of gamification aimed at the development and formation of personality are characterized. Emphasis is placed on the fact that the use of gamification elements no way replaces learning or education, but acts as another methodical tool for working with students of international relations in the context of patriotic education-teaching. The risks that may arise in the process of implementing gamification elements are outlined, the aspects that are important to consider when gamifying the process of educating and teaching patriotism of future international relations specialists are revealed in order to avoid risks.The conclusions confirm that in the patriotic education-teaching of future specialists in international relations, this methodological toolkit has a number of advantages and helps to make the educational process more effective.
Alleviating Representational Shift for Continual Fine-tuning

We study a practical setting of continual learning: fine-tuning on a pre-trained model continually. Previous work has found that, when training on new tasks, the features (penultimate layer representations) of previous data will change, called representational shift. Besides the shift of features, we reveal that the intermediate layers' representational shift (IRS) also matters since it disrupts batch normalization, which is another crucial cause of catastrophic forgetting. Motivated by this, we propose ConFiT, a fine-tuning method incorporating two components, cross-convolution batch normalization (Xconv BN) and hierarchical fine-tuning. Xconv BN maintains pre-convolution running means instead of post-convolution, and recovers post-convolution ones before testing, which corrects the inaccurate estimates of means under IRS. Hierarchical fine-tuning leverages a multi-stage strategy to fine-tune the pre-trained network, preventing massive changes in Conv layers and thus alleviating IRS. Experimental results on four datasets show that our method remarkably outperforms several state-of-the-art methods with lower storage overhead.
Federated Learning of Molecular Properties with Graph Neural Networks in a Heterogeneous Setting

Chemistry research has both high material and computational costs to conduct experiments. Institutions thus consider chemical data to be valuable and there have been few efforts to construct large public datasets for machine learning. Another challenge is that different intuitions are interested in different classes of molecules, creating heterogeneous data that cannot be easily joined by conventional distributed training. In this work, we introduce federated heterogeneous molecular learning to address these challenges. Federated learning allows end-users to build a global model collaboratively while keeping the training data distributed over isolated clients. Due to the lack of related research, we first simulate a heterogeneous federated learning benchmark (FedChem) by jointly performing scaffold splitting and latent Dirichlet allocation on existing datasets for heterogeneously distributed client data. Our results on FedChem show that significant learning challenges arise when working with heterogeneous molecules across clients. We then propose a method to alleviate the problem, namely Federated Learning by Instance reweighTing (FLIT(+)). FLIT(+) can align the local training across heterogeneous clients by improving the performance for uncertain samples. Comprehensive experiments conducted on our new benchmark FedChem validate the advantages of this method over other federated learning schemes. FedChem should enable a new type of collaboration for improving AI in chemistry that mitigates concerns about valuable chemical data.
The Status Quo of the Utilization of e-Learning Environment in the Ministry of Education in Jordan and Improvement Requirements

This study aims to identify the reality of e-learning utilization in the schools of the ministry of education in Jordan and improvement requirements from teachers' perspective and their relationship with some variables. In order to achieve the objectives of this study, analysis descriptive method was applied through a questionnaire used as the main tool for collecting information, which consists of (72) paragraphs, it was distributed to (321) teachers (males and females) in the public schools of the Middle Badia/Al-Jeeza governorate. The results show that the real use of e-Learning which is represented through the education system in the ministry of education from the teachers' perspective was average, and they also show that there are no statically significant differences for the degree of e-learning utilization which is presented through the education system at the ministry of education in Jordan due to differences (gender, teaching experience, and academic level). Whereas the study shows statically significant differences for the degree of e-learning utilization which is presented through the education system at the ministry of education in Jordan due to the difference of the school type, and it was for the favor of primary schools. The researchers recommended rethinking the way of e-Learning activating and utilizing in a wider and more appropriate way by those who are responsible for this in the schools of the ministry of education, in order to improve the teaching-learning process and to hold training courses for teachers on use and merge technology in the teaching process.
Entropically secure encryption with faster key expansion

Entropically secure encryption is a way to encrypt a large plaintext with a small key and still have information-theoretic security, thus in a certain sense circumventing Shannon's result that perfect encryption requires the key to be at least as long as the entropy of the plaintext. Entropically secure encryption is not perfect, and it works only if a lower bound is known on the entropy of the plaintext. The typical implementation is to expand the short key to the size of the plaintext, e.g. by multiplication with a public random string, and then use one-time pad encryption. This works in the classical as well as the quantum setting. In this paper, we introduce a new key expansion method that is faster than existing ones. We prove that it achieves the same security. The speed gain is most notable when the key length is a sizeable fraction of the message length. In particular, a factor of 2 is gained in the case of approximate randomization of quantum states.
Iterates of prime producing polynomials and their Galois groups

Let $\F_q$ be a finite field of characteristic $p>0$. We prove that, given $F(t,x)\in \F_q[t][x]$ an irreducible separable monic polynomial in the variable $x$ and a generic monic polynomial $\phi(t)$ in the variable $t$, the polynomial $F(t,\phi)$ is a prime producing polynomial over large finite fields under suitable irreducible specialization. We also prove that $F(t,\phi)$ satisfies Odoni's conjecture, namely the arboreal Galois representation associated to $F(t,\phi)$ is surjective.
Decentralized Stochastic Optimization with Inherent Privacy Protection

Decentralized stochastic optimization is the basic building block of modern collaborative machine learning, distributed estimation and control, and large-scale sensing. Since involved data usually contain sensitive information like user locations, healthcare records and financial transactions, privacy protection has become an increasingly pressing need in the implementation of decentralized stochastic optimization algorithms. In this paper, we propose a decentralized stochastic gradient descent algorithm which is embedded with inherent privacy protection for every participating agent against other participating agents and external eavesdroppers. This proposed algorithm builds in a dynamics based gradient-obfuscation mechanism to enable privacy protection without compromising optimization accuracy, which is in significant difference from differential-privacy based privacy solutions for decentralized optimization that have to trade optimization accuracy for privacy. The dynamics based privacy approach is encryption-free, and hence avoids incurring heavy communication or computation overhead, which is a common problem with encryption based privacy solutions for decentralized stochastic optimization. Besides rigorously characterizing the convergence performance of the proposed decentralized stochastic gradient descent algorithm under both convex objective functions and non-convex objective functions, we also provide rigorous information-theoretic analysis of its strength of privacy protection. Simulation results for a distributed estimation problem as well as numerical experiments for decentralized learning on a benchmark machine learning dataset confirm the effectiveness of the proposed approach.
ProQA: Structural Prompt-based Pre-training for Unified Question Answering

Question Answering (QA) is a longstanding challenge in natural language processing. Existing QA works mostly focus on specific question types, knowledge domains, or reasoning skills. The specialty in QA research hinders systems from modeling commonalities between tasks and generalization for wider applications. To address this issue, we present ProQA, a unified QA paradigm that solves various tasks through a single model. ProQA takes a unified structural prompt as the bridge and improves the QA-centric ability by structural prompt-based pre-training. Through a structurally designed prompt-based input schema, ProQA concurrently models the knowledge generalization for all QA tasks while keeping the knowledge customization for every specific QA task. Furthermore, ProQA is pre-trained with structural prompt-formatted large-scale synthesized corpus, which empowers the model with the commonly-required QA ability. Experimental results on 11 QA benchmarks demonstrate that ProQA consistently boosts performance on both full data fine-tuning, few-shot learning, and zero-shot testing scenarios. Furthermore, ProQA exhibits strong ability in both continual learning and transfer learning by taking the advantages of the structural prompt.
Testing &amp; the Impact of Item Analysis in Improving Students’ Performance in End-of-Year Final Exams

This research presented educational tests in a detailed way. Tests, their types, classifications and functionswere briefly discussed. Special focus was given to multiple-choice questions. The special design of this type of questions was explained and illustrated because it is the most important component of objective tests. The paper also presented a classification of tests that is based on their form and method of teaching. It concluded by stating four criteria of a good test. In addition, a recommendation to conduct further studies in this regard due to the huge importance of tests in general and their close connection to improving students’ performance was also given. The paper provided suggestions for further studies in analyzing the quality of test items.
Penerapan Teknologi Augmented Reality Pada Pembelajaran Sistem Saraf Bagian Otak

Brain is a part of the nervous system. The Nervous system has characteristics of abstract and complicated matter, because it deals with complex physical and chemical mechanisms. Therefore something is needed that can help to simplify this matter like application Augmented Reality (AR) technology. The application of AR technology to the learning of the nervous system on the brain is an android-based application that provides 3D illustrations of the brain and nerve cells so that students can see it directly and interact with the object. Method that used on development this AR application is Multimedia Development Life Cycle. Softwares that used in buildong this application are CorelDraw, Vuforia, Unity, and Visual Studio Code. The results obtained is an AR application for learning the nervous system on the brain. The tests was carried out on several students with alpha testing and beta testing methods. Based on the tests this AR application has been running well according to its function
An Empirical Study of College English Smart Teaching Driven by Intelligent Technology

With the continuous integration of artificial intelligence technology and foreign language education, the entire educational ecology, including traditional foreign language education concepts, education models, management structures and governance systems, is undergoing profound changes. This study uses the Rain Classroom Smart Teaching Platform for online-and-offline foreign language teaching, providing a virtual intelligent learning environment for learners. This pedagogy supports the construction of a learning community through the establishment of an online learning space, which seamlessly connects different learning scenarios and forms a multi-way interactive relationship between teachers and students. The questionnaire survey showed that students were more satisfied with this hybrid smart teaching module (88. 78) and were significantly more motivated to learn English (87. 6). The results of the pre- and post-tests conducted before and after the teaching experiment showed a significant increase in students’ scores ( p&lt;. 05), confirming the effectiveness of the teaching model. This study has implications for the practice of EFL teaching in higher education.
Artificial Intelligence Applied to Breast Cancer Classification

One in eight women is likely to develop breast cancer at some stage in her life, with a 12.5% average risk rate of developing breast cancer. Early detection and treatment are of vital importance to ensure the patient's survival. Currently, mammography is the main diagnostic study to identify breast cancer. However, since mammography requires a human, medical radiologist, to make a diagnosis, it is prone to errors. Recently, deep learning techniques have proven to be a suitable tool for breast cancer classification and detection. Therefore, this research proposes an algorithm based on convolutional neural networks (CNN) for screening classification of cancer in mammography images. The evaluation results of the proposed algorithm respect state-of-the-art algorithms demonstrate competitive accuracy results of up to 99% and the fastest training time. Therefore, our algorithm is well suitable for automatic breast cancer detection using the public All-MIAS database.
Universität Bonn Holding ISBN::978-83-67405-11-9

Universität Bonn Holding: The mindsponge and BMF analytics for innovative thinking in social sciences and humanities. Berlin, Germany: De Gruyter. ISBN (PDF): 978-83-67405-11-9; ISBN (hardcover): 978-83-67405-10-2. doi:10.2478/9788367405119.
Implementation of Augmented Reality (AR) in Malaysian Education System

The post-globalization world is witnessing the rapid development of technology.Revolution of industry 4.0 that hit the world encourages the use of various technologies and gadgets by all sectors or industries including education.Education system all around the globe excited to implement new technologies with the aims of enhancing students' focus, interest and comprehension throughout the teaching and learning sessions.Recently, the Augmented Reality (AR) technology attracts more intention and increasingly mastered by the educators to use the technology during teaching and learning sessions.AR innovation optimized the sophistication of social medias as an effective teaching medium.The use of this technology indicates great potential to produce more creative, innovative and competitive generation.
The Development and Perception of Trainee Teachers towards Smartphone Based Free Fall Measurement Kit Using Arduino

Free fall motion is one of the topics that is always considered challenging for Physics Students. The lack of teaching aids concerning this topic is also why students are less exposed to the free fall concept. Thus, this study aims to develop a Free Fall Kit as a teaching aid for the Physics Form Four under the subtopic Free Fall Movement. This kit is developed using an Arduino microcontroller where the result of gravitational acceleration will be displayed on the smartphone through the Bluetooth module. This study also aims to test the trainee teacher’s perceptions of majoring in physics at Universiti Pendidikan Sultan Idris towards the Free Fall Kit. The validity study was conducted with three experts among the physics lecturers at the Sultan Idris University of Education. These validity data were analyzed using the Percentage of Consent. The validity value obtained showed a high value where the total percentage of validity agreement from the three experts was 98.3% for face validity and 93.3% for content validity. This study uses a descriptive method to assess the instrument reliability and respondents perceptions of the developed kits. The data obtained showed that Cronbach’s Alpha value is 0.97, while an average mean score is 3.82 and an average standard deviation value is 0.28, indicating that the level of reliability and perception is at a high level of agreement among the respondents. In conclusion, the Free Fall Kit has a good perception among trainee teachers at Universiti Pendidikan Sultan Idris and has achieved the objectives of this research. The implication is that the Free Fall Kit can be an alternative teaching aid for teachers to teach the subtopic of free fall motion to determine the value of gravitational acceleration.
Communication Strategy Approaches in A Facebook Live Sinar Harian Talk Broadcast

This study investigates the communication strategies (CS) used by the host and guests in a live talk broadcast on Facebook.The aim of the study is to identify and analysed how the respondents compensate for their insufficient linguistic repertoire and enhance their online discussions via the use of the CS in the live talk broadcast.The data was derived from the Facebook Live Sinar Harian talk broadcast on live video streaming on 14 January 2020.Due to the nature of the qualitative research method applied to this study, document content analysis was used.Thematic analysis revealed guest's employment of an array of CS when interacting during the talk show which includes nine prominent communication strategies used by the host and invited guests in the program, such as abbreviations, denial, questioning, repetition, referral, interruptions, delay, literal translation, and language exchange.
Impact of Distance Learning on the English Language Learning Process

Interaction plays a critical role in processing data utilized for language learning. The outcome of a learning system depends on the learner's level of knowledge of a second foreign language (L2). The study uses a primary qualitative approach, working with data from primary sources in the form of open-ended questions. The use of primary research methods in this study was important because it allowed for a better understanding of the impact of distance education on English language learning (concerning Arab learners). This study used the main qualitative research methods and the case study method as a research tool because this method allows qualitative data to be collected, investigated, and calculated combined. In addition, the open-ended questions allowed participants to share their experiences of the impact of distance education on English language learning (applied to Arabic learners). The results of the qualitative research also revealed the challenges teachers face when innovating in online foreign language teaching, including, but not limited to, difficulties related to broadband access, accessibility, LMS connectivity issues, and appropriate assessment tools. The study results also showed that teachers would like more in-service training and preparation courses on the effective use of innovations and the application of unique applications in online teaching.
Critical Reading of Walden from the Perspective of Chinese and Western Cultures

Chinese traditional thoughts have a great influence on Western literature and American Transcendentalism. Given Sino-western culture differences and Thoreau’s language limitations, by making a comparative analysis of Confucianism-Taoism implied in the essay and Thoreau’s transcendentalism, this paper aims to understand and interpret objectively and realistically elements of Chinese traditional culture in Walden so as to further think about how to maintain the cultural consciousness and cultural confidence of Chinese traditional culture. To start with the interpretation of the writing background of Walden and the author's personal identities, critical reading of Walden from different perspectives of Chinese and Western cultures is of great significance for the interpretation of the essence of Chinese and Western cultures, which contributes to guiding positive world views, outlooks on life and values, and better appreciating Chinese traditional culture and transcendentalism involved in Walden.
Designing Frameworks for Reliability in Deep Learning Systems

There has been a great amount of progress in deep learning models in the last decade. Such models are most accurate when applied to test data drawn from the same distribution as their training set. However, in practice, the data confronting models in real-world settings rarely match the training distribution. This study explores the use of co-design approaches for developing reliable design frameworks for deep learning systems. It aims to raise awareness on how to develop reliable ML models within the context of recommender systems. While much work needs to be done in this field, the study provides suggestions and practical tips for how to develop reliable ML models such as in the case of recommender systems