Reviewerly/exHarmony huggingface dataset:
A Preliminary Attempt to Evaluate Machine Translations of Ukiyo-e Metadata Records

Providing multilingual metadata records for digital objects is a way expanding access to digital cultural collections. Recent advancements in deep learning techniques have made machine translation (MT) more accurate. Therefore, we evaluate the performance of three well-known MT systems (i.e., Google Translate, Microsoft Translator, and DeepL Translator) in translating metadata records of ukiyo-e images from Japanese to English. We evaluate the quality of their translations with an automatic evaluation metric BLEU. The evaluation results show that DeepL Translator is better at translating ukiyo-e metadata records than Google Translate or Microsoft Translator, with Microsoft Translator performing the worst.
Effects of Gestural Exaggeration to User Experience in Virtual Reality

In real life, people use facial expressions, bodily gestures, and tone variations to convey information more clearly and dramatically. Such multimodal communication is effective, but also requires significant mental and physical efforts on the part of the communicator. In virtual reality (VR), such efforts can be much relieved not only automatically but also in a much more amplified way, which would not possible in real life. In this paper, we investigate the effects of exaggeration and highlighting of gestures when communicating in VR. The exaggeration and highlighting method we consider is enlarging and exaggerating of the gestural body parts. We conduct a comparative experiment in which a VR user tries to understand an avatar conveying a short passage or describing a concept word only in gestures with the avatar’s gesturing body parts appropriately enlarged (or not). Our experiment has shown that there was not only the expected communication efficacy depending on the type of content to be conveyed, there was also a significant influence to the level of concentration, immersion and even presence.
Randomness Analysis on Lightweight Block Cipher, PRESENT

Lightweight cryptography is an area of current research conducted by academicians and cryptographic experts to ensure the security of data in limited-resource devices such as RFID tags, medical and health care devices and sensor networks.One of the lightweight algorithms built is the PRESENT algorithm.To this day, PRESENT has been a reference for lightweight block cipher algorithms and is incorporated into Lightweight Cryptography Standard ISO/IEC 29192-2.The capacity to act as a random number generator is one of the key requirements when designing an algorithm.Thus, this study aims to examine the capabilities of the PRESENT algorithm as a random number generator.By using the NIST Statistical Test Suite, a randomness analysis is performed on the PRESENT algorithm.A total of six data categories i.e., Strict Key Avalanche, Strict Plaintext Avalanche, High-Density Key, Low-Density Key, Low-Density Plaintext and High-Density Plaintext were applied to generate 100 input sequences for each algorithm.From the analysis, the outputs generated from the PRESENT algorithm are essentially non-random based on the 1% significance level.
Algorithmic Primitives for Quantum-Assisted Quantum Control

We discuss two primitive algorithms to evaluate overlaps and transition matrix time series, which are used to construct a variety of quantum-assisted quantum control algorithms implementable on NISQ devices. Unlike previous approaches, our method bypasses tomographically complete measurements and instead relies solely on single qubit measurements. We analyse circuit complexity of composed algorithms and sources of noise arising from Trotterization and measurement errors.
Discussion on Teaching of C language about Freshmen in Xuzhou University of Technology

With the increment in the term of enrollment size and type, the large difference among students has brought challenges to the teaching work. A new round of worldwide scientific and technological revolution and industrial transformation are booming. Advanced manufacturing industry, industrial Internet and other industries has become the important cornerstone of the new industrial revolution. Based on analysis of freshman students, this paper proposes several teaching methods about C language in order to enhance the quality of teaching.
Priming Neural Machine Translation

Priming is a well known and studied psychology phenomenon based on the prior presentation of one stimulus (cue) to influence the processing of a response. In this paper, we propose a framework to mimic the process of priming in the context of neural machine translation (NMT). We evaluate the effect of using similar translations as priming cues on the NMT network. We propose a method to inject priming cues into the NMT networkand compare our framework to other mechanisms that perform micro-adaptation during inference. Overall, experiments conducted in a multi-domain setting confirm that adding priming cues in the NMT decoder can go a long way towards improving the translation accuracy.Besides, we show the suitability of our framework to gather valuable information for an NMT network from monolingual resources.
FOREIGN LANGUAGE TEXTBOOK FOR INTERDISCIPLINARY RESEARCH PROJECTS IN FACE-TO-FACE AND REMOTE LEARNING

The current situation in the world caused by the COVID-19 pandemic imposes a number of new requirements in all spheres of life including the sphere of education. Professors and students of higher educational establishments were set a challenge to switch the educational process to remote learning in short order. The challenge created some difficulties, such as the need to choose the most appropriate and effective educational platform, adapt the material under study to digital form maintaining high quality of presenting information. Thus, in the contemporary world it is very important not only to master skills in the area of the professional career, but what is vital, is the ability to combine tasks from various scientific areas, to work as a team with other specialists and to be able to adapt and find solutions to different problems as quickly as possible. These are the skills and abilities that students acquire while working on interdisciplinary projects in a foreign language. Such interdisciplinary projects have been realised in the Institute of Radioelectronics and Information Technologies at Ural Federal University for several years so far. The results of their realization are excellent. Ural Federal University rates interdisciplinary projects as ones with the highest priority. We suggest that using information and communication technologies in the educational process at higher educational establishments represents one of the most important requirements not only at the time of virus pandemic but also in everyday life of each and every graduate. That is why the textbook which helps to form and develop competences necessary for the realization of interdisciplinary projects in a foreign language is of top value taking into account the fact that the textbook can be used not only for face-to-face learning, but also for remote learning in the digital form. So we created a textbook entitled «How to master scientific skills in English». The textbook is targeted at the formation as well as the development of all the four types of speech activities, such as speaking, listening, reading and writing. Besides the textbook «How to master scientific skills in English» is helpful in the development of a foreign language communicative research competence which the students gain in the realization of a project work in different spheres. The results of the research include the analysis of the textbook testing under the condition of face-to-face and remote learning with the students of the Institute of Radioelectronics and Information Technologies at Ural Federal University and the analysis of surveys of the students on the basis of performance under the condition of face-to-face and remote learning.
Text and Speech Alignment Methods for Speech Translation Corpora Creation : Augmenting English LibriVox Recordings with Italian Textual Translations

The recent uprise of end-to-end speech translation models requires a new generation of parallel corpora, composed of a large amount of source language speech utterances aligned with their target la ...
Building a Memory Map to Reconstruct an Urban Memory: The Case of the Beijing City Gates

Memory research has become a hot topic in the field of digital humanities (DH). DH methods and tools can help to realize the intellectualization and visualization of urban memory. This paper uses the knowledge map (KM) approach to organize, process, and mine archives and documentation data related to urban memory in order to build a map for the reorganization and reconstruction of urban memory. Thus, it proposes a three-tiered “concept-instance-resource” conceptual model. Furthermore, it takes the Beijing city gates as a case to test the effectiveness of this conceptual model. We believe this study provides a good exploration of the use of DH methods and tools in memory practice.
A Q-values Sharing Framework for Multiagent Reinforcement Learning under Budget Constraint

In teacher-student framework, a more experienced agent (teacher) helps accelerate the learning of another agent (student) by suggesting actions to take in certain states. In cooperative multiagent reinforcement learning (MARL), where agents need to cooperate with one another, a student may fail to cooperate well with others even by following the teachers' suggested actions, as the polices of all agents are ever changing before convergence. When the number of times that agents communicate with one another is limited (i.e., there is budget constraint), the advising strategy that uses actions as advices may not be good enough. We propose a partaker-sharer advising framework (PSAF) for cooperative MARL agents learning with budget constraint. In PSAF, each Q-learner can decide when to ask for Q-values and share its Q-values. We perform experiments in three typical multiagent learning problems. Evaluation results show that our approach PSAF outperforms existing advising methods under both unlimited and limited budget, and we give an analysis of the impact of advising actions and sharing Q-values on agents' learning.
A Grid-Point Detection Method based on U-Net for a Structured Light System

Accurate detection of the feature points of the projected pattern plays an extremely important role in one-shot 3D reconstruction systems, especially for the ones using a grid pattern. To solve this problem, this paper proposes a grid-point detection method based on U-net. A specific dataset is designed that includes the images captured with the two-shot imaging method and the ones acquired with the one-shot imaging method. Among them, the images in the first group after labeled as the ground truth images and the images captured at the same pose with the oneshot method are cut into small patches with the size of 64x64 pixels then feed to the training set. The remaining of the images in the second group is the test set. The experimental results show that our method can achieve a better detecting performance with higher accuracy in comparison with the previous methods.
PyRos: A State Channel-Based Access Control System for a Public Blockchain Network

Blockchain is a technology that enables the implementation of a decentralized system by replacing the role of the centralized entity with the consensus of participants in the system to solve the problem of subordination to the centralized entity. Blockchain technology is being considered for application in numerous fields; however, the scalability limitation of a public blockchain has led many researchers to consider private blockchains, which reduce the security of the system while improving scalability. A state channel represents a leading approach among several scalability solutions, intended to address public blockchain scalability challenges while ensuring the security of the blockchain network. Participants in the channel perform the process of updating the state of the channel outside the blockchain. This process can proceed very quickly because it does not require the consensus of the blockchain network, but still, like on-chain, it can guarantee features such as irreversibility. In this paper, we propose the PyRos protocol, an access control system that supports the trading and sharing of data between individuals on a public blockchain based on the state channel. As far as we know, the research using the off-chain state channel for access control has not been proposed yet, so PyRos is a new approach in this field. In PyRos, user-defined access control policies are stored off-chain, and policy updates are always rapid regardless of the performance of the blockchain network. Moreover, PyRos provides means to prevent malicious participants from arbitrarily using the channel’s previous state while resolving constraints due to scalability problems, along with privacy guarantees for the transaction content. To evaluate the efficiency and security of PyRos, we provide qualitative analysis of security requirements and analysis in terms of the performance of public blockchain platforms.
Secure Sourcing of COTS Products: A Critical Missing Element in Software Engineering Education

The aim of this paper is to publicize both the challenge and potential solution for the integration of secure supply chain risk management content into conventional software engineering programs. Specifically, software engineering programs typically do not teach how to ensure that the code produced and sold in commercial off-the-shelf (COTS) products hasn't been compromised through the sourcing process. We propose four instructional modules and topics based on established principles that can form the basis of a comprehensive course to address secure sourcing of COTS products.
Learning Sampling Distributions for Efficient High-Dimensional Motion Planning.

Robot motion planning involves computing a sequence of valid robot configurations that take the robot from its initial state to a goal state. Solving a motion planning problem optimally using analytical methods is proven to be PSPACE-Hard. Sampling-based approaches have tried to approximate the optimal solution efficiently. Generally, sampling-based planners use uniform samplers to cover the entire state space. In this paper, we propose a deep-learning-based framework that identifies robot configurations in the environment that are important to solve the given motion planning problem. These states are used to bias the sampling distribution in order to reduce the planning time. Our approach works with a unified network and generates domain-dependent network parameters based on the environment and the robot. We evaluate our approach with Learn and Link planner in three different settings. Results show significant improvement in motion planning times when compared with current sampling-based motion planners.
PLANNING, MANAGING AND LEADING THE DIGITAL TRANSFORMATION OF SCHOOLS

The Digital Maturity Framework for Schools in Croatia has been designed as a part of the e-Schools pilot project that is part of the “e-Schools: a comprehensive informatisation of school operation processes and teaching processes aimed at the creation of digitally mature schools for the 21st century”. It is based on the European Framework for Digitally Competent Educational Organisations. The School Digital Maturity Framework is structured in 5 characteristic areas of the Croatian education system: Planning, Management and Leadership, ICT (Information and Communications Technology) in Learning and Teaching, Development of Digital Competencies, ICT Culture and ICT Infrastructure. According to the 2016-2018 Digital Maturity Evaluation, schools have the lowest level of digital maturity in the areas of Planning, Management and Leadership. Therefore, it can be assumed that majority of schools are not ready for the upcoming digital transformation challenges. The purpose of this paper is to determine which core individual competencies defined by the information constructs, Knowledge, Skills and Abilities, significantly set the degree of school management digital maturity. Thereby, the primary objective was to create a new information construct Experience and to explore the correlation between relationships of two constructs. Principals of primary schools in the Republic of Croatia were selected as the research sample (860). The survey was conducted using a questionnaire method that contains original metrics of the influencing factors Knowledge, Skills, Abilities and Experience on the basis of which the information model was designed. By descripting the information model, it is possible to determine the impact of a particular construct on the school digital maturity in the area of planning, management and leadership. Therefore, this paper represents a contribution to the information and communication sciences field and opens initiatives for further interdisciplinary research related to the development of an original methodology for conceptualizing the management of school’s digital transformation.
Teaching Distributed Requirements Engineering: Simulation of an Offshoring Project with Geographically Separated Teams

Offshoring software development projects are often conducted with a client and a requirements engineering team in one country and development teams in another country. The geographical distance, time zone differences, language and cultural differences can introduce significant challenges to the elicitation and communication of software requirements. In this paper, a cooperation between two universities in Japan and Germany to teach students distributed software requirements engineering is described. An international software development project was simulated, with the requirements engineering team in Japan and the development teams in Germany. This research highlights a unique aspect rarely explored in software engineering education. Instead of equally distributing team members in each country, one requirements engineering team consulted with clients on site in Japan while the development of the software prototype was outsourced to four engineering teams in Germany. Students cooperated remotely using cloud computing tools to perform requirements engineering and to develop a prototype of a laboratory scheduling and management system. Real-time communication was limited to one 90 minute class session per week. Student opinions were surveyed at the beginning and at the end of the semester to evaluate their learning processes. Results of these surveys show significant changes in students' estimations of the relative importance of different challenges to conducting distributed requirements engineering.
Formation of Public Consciousness and Digital Culture of Students in the System of Continuous Pedagogical Education

The article deals with the problem of analyzing trends in the formation of public consciousness and digital culture of students in the system of continuous teacher education. The conclusions are based on the fact that symbolic interactionism (information theory), socio-psychological centrality are based on the level of importance of certain ideas or self-conceit, the degree of interactivity in the implementation of acquired communicative and role models of student behavior. Moderate support for the theories of identity and symbolic interactionism was revealed, since the identity of the "other" was not much in the focus of research analysis. Identification aspects are related to the relationship between concepts, and interactive commitment is related to the psychological centrality of the student's personality, but not to the identification of the "other". Self-esteem is a Central element of the psychological centrality of the individual, if it is important for her. It is shown that identities can be stable and unstable, since they are associated with a person's social environment. Instability is associated with the student's desire to make social, religious, and cultural changes in their own lives, that is, with the desire to master and join new cultural values. The level of a person's self-esteem depends on the identification combination of socio-psychological (external and internal) aspects and conditions of their existence.
Analysis of Web Server Logs of Websites Using Different Web Mining Tools

Lots of information can be extracted from data collected by the server logs of the website. This information is very useful for the development and security purpose of the web site. There are lots of open source and proprietary tools available for analysis of weblog data. In this paper, we have compared the results obtained from the analysis of web log files of two websites. One website related to the government department used for the posting of teachers through counselling and others are old server logs of NASA. We have taken two entirely different types of websites for comprehensive analysis. We have used WebLog Expert, Webalizer, AWStats, Analog Stats and Google Analytics for analysis of weblog data. Results and patterns obtained from analysis compared in terms of general statistics, activity statistics, access statistics, visitors information, Browsers, Referrers and errors.
Difficulties and Suggestions of Online Education Reform and Development under the Background of COVID-19 Prevention and Control

The outbreak of COVID-19 at the beginning of 2020 makes China's online education system face unprecedented challenges. There has been a long-term controversy on online education in academic circles. The large-scale online teaching carried out during the period of COVID-19 has further enlarged this dispute. The difference lies in the different views on the nature of education and the quality of education. The changes of knowledge carriers and media in the information age have led to great changes in the connotation, structure, production mode, presentation mode and transmission mode of knowledge. These changes will inevitably lead to changes in learning and education. Online education is the inevitable embodiment of these changes. This is the underlying logic of vigorously developing online education and promoting educational reform. The development of online education should not be aimed at replacing the offline classroom, but should meet the urgent needs of the times and reality, and achieve the higher goal of promoting educational reform and building a learning society. In the post COVID-19 era, offline teaching should keep up with online teaching, adopt "double line teaching mode" and "online and offline exchange teaching system", so as to create a "new normal" of hybrid teaching.
An Encryption and Decryption Algorithm Based on Random Dynamic Hash and Bits Scrambling

This paper proposes a stream cipher algorithm. Its main principle is conducting the binary random dynamic hash with the help of key. At the same time of calculating the hash mapping address of plaintext, change the value of plaintext through bits scrambling, and then map it to the ciphertext space. This encryption method has strong randomness, and the design of hash functions and bits scrambling is flexible and diverse, which can constitute a set of encryption and decryption methods. After testing, the code evenness of the ciphertext obtained using this method is higher than that of the traditional method under some extreme conditions..