Reviewerly/exHarmony huggingface dataset:
Towards Improving Open Student Answer Assessment using Pretrained Transformers

The transfer learning pretraining-finetuning paradigm has revolutionized the natural language processing field yielding state-of the art results in several subfields such as text classification and question answering. However, little work has been done investigating pretrained language models for the open student answer assessment task. In this paper, we fine tune pretrained T5, BERT, RoBERTa, DistilBERT, ALBERT and XLNet models on the DT-Grade dataset which contains freely generated (or open) student answers together with judgment of their correctness. The experimental results demonstrated the effectiveness of these models based on the transfer learning pretraining-finetuning paradigm for open student answer assessment. An improvement of 8%-15% in accuracy was obtained over previous methods. Particularly, a T5 based method led to state-of-the-art results with an accuracy and F1 score of 0.88.
Bibliometric Analysis of Cyber Threat and Cyber Attack Literature: Exploring the Higher Education Context

In nearly all procedures involving students and faculty, higher education organizations make substantial use of computers and the internet. Little is known on the progress and development of literature on cyber threats and cyber attacks in this sector. This chapter fills this gap by examining the trends of literature on cyber threats and cyber attacks focusing on the higher education. Bibliometric analysis through Scopus database was employed to offer research ideas and trigger debates. Analyzed parameters include the number of document types, publications, authorship, citation, and subject areas, as well as the topographical dispersion of published research. The earliest publication could be seen in the year 2003, and since then 606 papers were published. The majority of publications were conference papers but merely 8.42% of those were open access. The results indicate that publications hit a plateau in 2018, with English becoming the main publication language. The most prominent country that has contributed to the literature is the United States. Nonetheless, the majority of the publications were contained by the subject area of Computer Science, hence it is relatively challenging to trace the progress in education context. This chapter presents a groundwork providing insights for others to probe into the topic further.
Research on Knowledge Distillation of Generative Adversarial Networks

The compression of Generative Adversarial Networks (GANs) has been an emerging study in recent years. However, conventional compression methods can hardly be applied to GANs due to the training process and optimization target of GANs are different from the traditional classification detection network. Inspired by the recent success of knowledge distillation, we condense the recent researches on them applied to particular GANs, i.e. WGAN and CGAN for special tasks into two strategies: Soft Target Only Strategy (STOS) and Inherited Hard Target Strategy (IHTS), and propose an novel Random Hard Target Strategy, namely RHTS. In RHTS, we take the student network generator loss as the hard target of knowledge distillation when the discriminator is fixed, and the output of the teacher network generator as the soft target to distill GANs. The experiments on image datasets (MNIST, CIFAR-10), and structured-data datasets (Australian Credit Approval dataset, Credit Approval Data Set) show that STOS and IHTS are effective, and RHTS is the best. Such results are further proved on WGAN, WGAN-GP and LSGAN in order to demonstrate the better generalization ability of the strategies. Besides, the RHTS improve the stability of the GAN training process, where the performance and stability confirm the rationality of our design.
Three-party reference frame independent quantum key distribution protocol*

We present a three-party reference frame independent quantum key distribution protocol which can be implemented without any alignment of reference frames between the sender and the receiver. The protocol exploits entangled states to establish a secret key among three communicating parties. We derive the asymptotic key rate for the proposed protocol against collective attacks and perform a finite-size key security analysis against general attacks in the presence of statistical fluctuations. We investigate the impact of reference frame misalignment on the stability of our protocol, and we obtain a transmission distance of 180 km, 200 km, and 230 km for rotation of reference frames β = π /6, β = π /8 and β = 0, respectively. Remarkably, our results demonstrate that our proposed protocol is not heavily affected by an increase in misalignment of reference frames as the achievable transmission distances are still comparable to the case where there is no misalignment in reference frames (when β = 0). We also simulate the performance of our protocol for a fixed number of signals. Our results demonstrate that the protocol can achieve an effective key generation rate over a transmission distance of about 120 km with realistic 10 7 finite data signals and approximately achieve 195 km with 10 9 signals. Moreover, our proposed protocol is robust against noise in the quantum channel and achieves a threshold error rate of 22.7%.
RETRACTED: Image processing technology in American football teaching

Based on the development and advantages of digital image processing technology, this paper introduces its application in American football teaching. Aiming at the characteristics of image processing technology and practicality, the deep learning is introduced into the American football teaching process. Combining the characteristics of electronic information subject and years of teaching experience, the teaching mode and practice of American football are discussed. This lets students analyze and solve practical problems, promote students' deep understanding of knowledge, flexibly grasp the use of knowledge, and enhance their ability to innovate. The multi-processing technology of motion video image based on the analysis and evaluation of non-interference technology has been widely used and developed in the field of modern sports. It has an important help and support for improving the athletic ability of elite athletes. The practice has won the support and recognition of the majority of coaches and athletes.
Evaluating User Acceptance using WebXR for an Augmented Reality Information System

Augmented Reality has a long history and has seen major technical advantages in the last years. With WebXR, a new web standard, Mobile Augmented Reality (MAR) applications are now available in the web browser. With our work, we implemented an Augmented Reality Information System and conducted a case study to evaluate the user acceptance of such an application build with WebXR. Our results indicate that the user acceptance regarding web-based MAR applications for our specific use case seems to be given. With our proposed architecture we also lay the foundation for other AR information systems.
DIGITAL DISCOURSE OF CONSTRUCTING A THEORETICAL IMAGE OF THE EDUCATION PHENOMENON

Digitalization has embraced all aspects and institutions of modern society, including education. The widespread introduction of new information technologies in Russia; the change of formats for the presentation of educational information, as well as methods of broadcasting educational materials; the transformation of the role and priorities of academic disciplines; the emergence of online / offline access to methodological resources have already become a reality. There is an information-technological synthesis of tradition and innovations in the educational environment. The scientific and educational space «responds»to this digital challenge in education with diverse researchers» reflections. These theoretical interpretations are aimed mainly at the consideration of certain aspects of digital education, for example, distance learning, open education, massive online courses, e-learning environment. In fact, we can state the fragmentary theoretical context regarding the phenomenon of education in the digital age. The author proposes methodological tools, on the one hand generalizing the array of theorizations of the phenomenon of education, including the digital context; on the other hand, allowing constructing a theoretical image of the education phenomenon, reflecting the main attributive characteristics of the latter in digital reality. Under the theoretical image of the education phenomenon, in the most general form, is meant a theoretical construct that serves as a synthesizing representative of real and / or potential theorizations of the education phenomenon, and acts, on the one hand, as a link between the researcher with his methodological preferences and heterogeneous theoretical ideas about the phenomenon of education; on the other hand, as a basis necessary and sufficient for the interpretation of the education phenomenon in the context of a certain type of scientific rationality. It is argued that this method of cognition of the education phenomenon in its theorizations (through the construction of theoretical images), allows you to fix the most significant attribute characteristics of the phenomenon under study, phasing out the concomitant ones.
Research on 3D Reconstruction Method Based on Temporal Fourier Transform Profilometry

Fourier Transform Profilometry (FTP) and Phase Measurement Profilometry (PMP) are 3D surface measurement techniques that have been widely used, however, FTP has some defects, such as high requirement for space carrier frequency of projection fringe and easy loss of high-frequency components of measured object. High precision measurement based on PMP is difficult to realize dynamic measurement. However, Temporal Fourier Transform Profilometry (TFTP) can realize high-precision 3D reconstruction of dynamic objects. Therefore, this paper deeply explores the implementation process of TFTP method, it is proved that this method can retain the high-frequency components of the measured object to realize 3D surface reconstruction under the condition of low space carrier frequency projection. In addition, this paper discusses the influence of relevant parameters on the results of 3D reconstruction, and compares FTP method and TFTP method. On this basis, a measuring system is proposed, which is simple to construct and operate, and can quickly reconstruct the 3D shape of objects.
Digital Technologies in Russian Corporate Citizenship Initiatives

COVID-19 pandemic forced social structures from business, governmental and nongovernmental sectors to integrate digital technologies to their activities. Lockdown of Spring, 2020 in Russia led to transfer business structures their socially responsible initiatives, interaction with target audiences and stakeholders to digital communication platforms and applications.Digitalization and global initiatives in sustainable development created a new common language to communicate with each other – the global standards for sustainability reporting (GRI Standards). We may observe the transformation of corporate social responsibility approach of business actors to corporate social sustainability one, thus, businesses exhibit themselves as corporate citizens through their communication and activities (Tulchinsky, 2012; Kanaeva, 2014; Blagov, 2015; Kosorukov, 2017, 2019, etc.).The Russian corporations COVID-19 case (X5 Retail Group, United Metallurgical Company, Gazpromneft’, Severstal’, Nornikel) demonstrated that the vision of business organization through corporate citizenship approach and communication strategy supported by active digital communication instruments and platforms development helps to overcome crisis situation for all social partners.
Highly Efficient Protection of Biometric Face Samples with Selective JPEG2000 Encryption

When biometric databases grow larger, a security breach or leak can affect millions. In order to protect against such a threat, the use of encryption is a natural choice. However, a biometric identification attempt then requires the decryption of a potential huge database, making a traditional approach potentially unfeasible. The use of selective JPEG2000 encryption can reduce the encryption’s computational load and enable a secure storage of biometric sample data. In this paper we will show that selective encryption of face biometric samples is secure. We analyze various encoding settings of JPEG2000, selective encryption parameters on the "Labeled Faces in the Wild" database and apply several traditional and deep learning based face recognition methods.
Time-invariant discord and steady-state entanglement in engineered non-equilibrium dephasing environments

Abstract We study theoretically the dynamics of quantum and classical correlations in the two-qubit system, locally experiencing a one-sided engineered pure dephasing non-equilibrium environment with an Ohmic class spectrum. The environmental non-equilibrium nature is characterized by random perturbations with non-stationary statistics. Particularly, we investigate the influence of the non-equilibrium feature on the protection of these correlations and, more specifically, its effect on the non-trivial phenomenon of time-invariant discord. Remarkably, we show that in the presence of this engineered non-equilibrium environment, time-invariant discord with a significantly larger magnitude exists for all Ohmic spectral densities, i.e., sub-Ohmic, Ohmic, and super-Ohmic without zero-temperature restriction. Additionally, we also show that our engineered non-equilibrium model provides a promising tool for trapping entanglement in a steady-state with a higher magnitude. Moreover, our proposed model also renders new insights for controlling decoherence through engineering the relative initial phases of the bath modes without performing any artificial operations on the main quantum system.
Conditioning Gaze-Contingent Systems for the Real World: Insights from a Field Study in the Fast Food Industry

Eye tracking can be used to infer what is relevant to a user, and adapt the content and appearance of an application to support the user in their current task. A prerequisite for integrating such adaptive user interfaces into public terminals is robust gaze estimation. Commercial eye trackers are highly accurate, but require prior person-specific calibration and a relatively stable head position. In this paper, we collect data from 26 authentic customers of a fast food restaurant while interacting with a total of 120 products on a self-order terminal. From our observations during the experiment and a qualitative analysis of the collected gaze data, we derive best practice approaches regarding the integration of eye tracking software into self-service systems. We evaluate several implicit calibration strategies that derive the user’s true focus of attention either from the context of the user interface, or from their interaction with the system. Our results show that the original gaze estimates can be visibly improved by taking into account both contextual and interaction-based information.
ParsNER-Social: A Corpus for Named Entity Recognition in Persian Social Media Texts

Named Entity Recognition (NER) is one of the essential prerequisites for many natural language processing tasks. All public corpora for Persian named entity recognition, such as ParsNERCorp and ArmanPersoNERCorpus, are based on the Bijankhan corpus, which is originated from the Hamshahri newspaper in 2004. Correspondingly, most of the published named entity recognition models in Persian are specially tuned for the news data and are not flexible enough to be applied in different text categories, such as social media texts. This study introduces ParsNER-Social, a corpus for training named entity recognition models in the Persian language built from social media sources. This corpus consists of 205,373 tokens and their NER tags, crawled from social media contents, including 10 Telegram channels in 10 different categories. Furthermore, three supervised methods are introduced and trained based on the ParsNER-Social corpus: Two conditional random field models as baseline models and one state-of-the-art deep learning model with six different configurations are evaluated on the proposed dataset. The experiments show that the Mono-Lingual Persian models based on Bidirectional Encoder Representations from Transformers (MLBERT) outperform the other approaches on the ParsNER-Social corpus. Among different Configurations of MLBERT models, the ParsBERT+BERT-TokenClass model obtained an F1-score of 89.65%.
Domain Model Discovery from Textbooks for Computer Programming Intelligent Tutors

We present a novel approach to intro-to-programming domain model discovery from textbooks using an over-generation and ranking strategy. We first extract candidate key phrases from each chapter in a Computer Science textbook focusing on intro-to-programming and then rank those concepts according to a number of metrics such as the standard tf-idf weight used in information retrieval and metrics produced by other text ranking algorithms. Specifically, we conduct our work in the context of developing an intelligent tutoring system for source code comprehension for which a specification of the key programming concepts is needed - the system monitors students' performance on those concepts and scaffolds their learning process until they show mastery of the concepts. Our experiments with programming concept instruction from Java textbooks indicate that the statistical methods such as KP Miner method are quite competitive compared to other more sophisticated methods. Automated discovery of domain models will lead to more scalable Intelligent Tutoring Systems (ITSs) across topics and domains, which is a major challenge that needs to be addressed if ITSs are to be widely used by millions of learners across many domains.
Blended Teaching Reform of Higher Vocational Education Based on Addie Teaching Design Model

With the rapid development of information technology, computer technology and the popularization of network technology, the field of missionary education is rapidly disintegrating.There are a lot of free excellent teaching resources on the qualified network education platform, which is convenient for students to watch and read.Traditional classroom teaching has adapted to the learning habits and needs of young students.Moreover, in Higher Vocational English class, the phenomenon of students playing with mobile phones can not be stopped.A deep reform of English teaching is imperative.In view of this, the author uses Addie teaching design model, according to the current situation of Higher Vocational Students' English learning in Shandong Vocational College of Industry, applies blended learning in College English class in order to stimulate students' interest in learning, solve the difficulties faced by teachers in English teaching, and provide reference for teachers to improve teaching effect.
Analysis of Voice Changes in Anti Forensic Activities Case Study: Voice Changer with Telephone Effect

Voice recordings can be changed in various ways, either intentionally or unintentionally, one of which is by using a voice changer. Reference voice recordings and suspect voice recordings will be more difficult to analyze if suspect voice recordings are changed using a voice changer application under certain effects such as telephone effect. Voice Changer can be one form of activity that can be carried out by anti-forensics, making it difficult for investigators to investigate if the voice recording is changed with telephone effect. This study has two types of recordings, namely the reference voice recording (unknown sample) and suspect voice recording (known sample) that has been changed using a voice changer application with telephone effect. Investigations were carried out based on data results extraction and analysis using pitch, formant, and spectrogram using the Analysis of variance (ANOVA) method and the likelihood ratio method. The results of this study indicate that the application of voice changer can be one form of activity that can be carried out by anti-forensics so that it can be difficult for investigators to conduct investigations on sound recording evidence. This research may help forensic communities, especially investigators to conduct investigations on sound recording.
College-level mathematical modelling with mobile devices

Purpose This work is devoted to increasing the effectiveness of a mathematical modelling lesson with the help of mobile devices. It verifies the authors' hypothesis which states that enabling students to solve mathematical models on mobile devices improves their academic results in the discipline. Design/methodology/approach The paper describes an experiment conducted among 38 college students in an extracurricular mathematical club where they solved mathematical models with the help of their own smartphones. The authors describe the mathematical models assigned to students, analyse their academic performance and gather their opinions. Findings The usage of mobile devices in the mathematical modelling class positively affects students' scores and interest in the subject. The percentage of positive grades among students working on mobile devices is higher than among students working on desktop computers. Originality/value The authors discover that in the context of the college-level mathematical modelling course, mobile devices can be successfully used as an alternative replacement for traditional desktop computers.
Theories and applications of quantum annealing: A literature survey

<p indent="0mm">Quantum annealing (QA) algorithm is a new quantum optimization algorithm based on the classical simulated annealing (SA) algorithm. Unlike classical SA algorithm, which uses the thermal waves to search for the optimal solution, the QA algorithm uses the quantum tunneling effect to allow a quantum to penetrate a potential barrier with a higher energy than itself. Therefore, the algorithm can get rid of the local extreme values and is more likely to approach the global optimal with higher probability. In the literature, the QA algorithm has shown perfect optimization effects on combinatorial optimization problems. In this paper, the basic concepts and application fields of QA algorithm, which is the core principle of D-Wave quantum computer, are systematically reviewed. The applications of QA algorithm in cryptography, traveling salesman problem, graph coloring problem, and traffic path are discussed in detail. In addition, the direction of future research for QA algorithm is explored.
Comparing Static Analysis and Code Smells as Defect Predictors: An Empirical Study

Background. Industrial software increasingly relies on open source software. Therefore, industrial practitioners need to evaluate the quality of a specific open source product they are considering for adoption. Automated tools greatly help assess open source software quality, by reducing the related costs, but do not provide perfectly reliable indications. Indications from tools can be used to restrict and focus manual code inspections, which are typically expensive and time-consuming, only on the code sections most likely to contain faults. Aim. We investigate the extent of the effectiveness of static analysis bug detectors by themselves and in combination with code smell detectors in guiding inspections. Method. We performed an empirical study, in which we used a bug detector (SpotBugs) and a code smell detector (JDeodorant). Results. Our results show that the selected bug detector is precise enough to justify inspecting the code it flags as possibly buggy. Applying the considered code smell detector makes predictions even more precise, but at the price of a rather low recall. Conclusions. Using the considered tools as inspection drivers proved quite useful. The relatively small size of our study does not allow us to draw universally valid conclusions, but our results should be applicable to source code of any kind, although they were obtained from open source code.