Reviewerly/exHarmony huggingface dataset:
PURPOSE MODEL - Visual Method for Mutual Understanding in Co-creation Projects

This paper develops a new visual communication method for mutual understanding in Co-creation projects, the Purpose Model, and discusses its effectiveness. To create the tool, 30 cases of Co-creation projects were investigated and four elements of sustainable and better Co-creation projects were extracted. We also summarized seven items used in several tools for visualizing stakeholders used in the areas of project management and service design. Following these elements as well, a new model is proposed to visualize Co-creation and promote mutual understanding among concerned persons. The features of this style are that it focuses on the ‘common purpose’, which is important for Co-creation projects, and that it can be used for fixed-point observation by writing in the same format, including changes from the initial, ambiguous stage. In the process of devising the Purpose Model, the needs for communication tools in projects involving multiple stakeholders were identified, while disseminating the information on SNS and providing toolkits and web tools as open source. As examples of use in actual projects, I introduce the use of the tool in the kick-off of a Living Laboratory for public-private-academic collaboration in a smart city, and its use in communication within and between teams in a commercial facility involving citizens in a redevelopment project.
Innovative Thinking About Human-Computer Interaction in Interactive Narrative Games

Research on game interaction has been popular in recent years. Interactive narrative games are a branch of role-playing game games. In order to give interactive narrative games a stronger sense of immersion and a more diverse experience, the study of their interaction methods is essential. In this paper, we start from the development experience of interactive narrative games and categorize the existing game interaction methods into eight types: visual, auditory, tactile, gesture, expression, virtual reality, augmented reality, and intentional interaction according to the existing applications. And on this basis, based on the interaction design principles proposed by Donald Norman and the acceptance aesthetics theory proposed by Hans Robert Jauss, the interaction methods of future interactive narrative games are explored. Finally, the trend of interaction development and innovation of interactive narrative games is summarized as five points: the compounding of interaction medium, the naturalization of interaction behavior, the receptive innovation of interactive aesthetics, the warning innovation of interaction ethics, and the development of dual-universe integration of interaction experience.
The Effectiveness of Communicative Language Teaching towards Students’ Ability in Essay Writing

This study discusses the effectiveness of using Communicative Language Teaching in essay writing. The research method used experimental quantitative method. The design of research was a quasi-experimental research using a one group pretest-posttest model. Written test was an instrument that was applied in research to obtain research data. In analyzing the data, the steps taken consisted of 1) counting mean of pretest and posttest, 2) counting standard deviation of the pretest and posttest, 3) counting normality of the pretest and posttest, 4) counting the homogeneity of the pretest and posttest, and 5) testing the hypothesis. The result of the study shown that the using of Communicative Language Teaching was effective to be implemented in essay writing. This is proved by the value of tcount &gt; ttable = 4.30&gt; 1.70329. That means Ha is accepted and Ho is rejected. In this case, all students are more enjoyable in learning essay writing in class and they are motivated to improve their skill especially in writing essay
Exhibition activity as a pedagogical factor in the formation of the personality of culture

The article presents the conceptual essence exhibition activities of art education institutions in addressing issues of aesthetic education of a person of culture; pedagogical views on the problem are highlighted, the phenomenon of exhibition activities of participants in the educational process of art education institutions; characteristics of creative assets exhibitions demonstrated by participants of educational process as well as the role of exhibition work in creating cultural and artistic space as an effective factor of aesthetic education of a person of culture are considered. The author indicated priority tasks of exhibition activities of educational institutions of different levels in the field of multicultural space and in the life of modern society, a number of issues related to methodological support and system solution of a complex of tasks arising within the exhibition process under current conditions of education based on methodology of the scientific theory of pedagogical management are identified.
A Pilot Study: Can Using QR Codes Increase Student Participation in Large Classroom Settings?

In large classes, students report feeling a lack of personalization and ownership for learning course material.Students can feel disengaged from the learning process, thus a greater risk of failing to seek clarification of misunderstood concepts.Given that 35-50% of persons have an introverted temperament, it is important to provide an equitable learning environment to support all students' learning.The purpose of this pilot project was to determine if the use of a QR code to ask questions would improve student engagement both during class and after class time for a first and third semester prelicensure nursing students.Post QR code survey using a 1-10 Like rt scale showed a mean satisfaction score of 8.63 for 1st semester and 7.79 for 3rd semester students.90.7% of first semester and 76.9% of third semester students felt having access to the QR code enabled them to ask more questions.
IMPROVING THE MOOD AND WELL-BEING OF MUSIC STUDENTS THROUGH MUSIC THERAPY

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 8471-8478ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.2229Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
FOSTERING CROSS-CULTURAL UNDERSTANDING THROUGH TECHNOLOGY-LED EDUCATIONAL PRACTICES:PERSPECTIVES FROM GREEK TEACHERS

FOSTERING CROSS-CULTURAL UNDERSTANDING THROUGH TECHNOLOGY-LED EDUCATIONAL PRACTICES:PERSPECTIVES FROM GREEK TEACHERS
MAXIMISING THE POTENTIAL OF LABORATORIES TO DELIVER TRANSFORMATIVE ACTIVE LEARNING OPPORTUNITIES VIA EFFECTIVE USE OF LEARNING MANAGEMENT SYSTEMS

MAXIMISING THE POTENTIAL OF LABORATORIES TO DELIVER TRANSFORMATIVE ACTIVE LEARNING OPPORTUNITIES VIA EFFECTIVE USE OF LEARNING MANAGEMENT SYSTEMS
SOFTWARE PROJECT MANAGEMENT EDUCATION DURING THE COVID-19 PANDEMIC: AN EXPERIENCE REPORT OF EMERGENCY REMOTE EDUCATION

SOFTWARE PROJECT MANAGEMENT EDUCATION DURING THE COVID-19 PANDEMIC: AN EXPERIENCE REPORT OF EMERGENCY REMOTE EDUCATION
THE VIRTUAL READING CHALLENGE: AN EDUCATIONAL TOOL TO PROMOTE READING AND PEER COOPERATION

Appears in: EDULEARN23 Proceedings Publication year: 2023Pages: 7644-7652ISBN: 978-84-09-52151-7ISSN: 2340-1117doi: 10.21125/edulearn.2023.1985Conference name: 15th International Conference on Education and New Learning TechnologiesDates: 3-5 July, 2023Location: Palma, Spain
Blockchain Security Mechanism Design Based on Chinese Cryptosystem SM2 Algorithm

The cryptographic system is the foundation of blockchain security mechanisms. This paper constructs a blockchain security mechanism based on the Chinese national cryptographic SM2 algorithm, involving the generation of public–private key pairs and the signing of block information using key pairs. However, the original SM2 algorithm has a high computational complexity, which cannot meet the requirements of low on-chain delay in blockchain applications. To solve this problem, this paper optimizes the SM2 digital signature algorithm. The scalar multiplication operation in the digital signature algorithm has a large computational complexity, which affects the efficiency of a digital signature. To reduce its computational complexity, this paper improves the traditional window non-adjacent form (w-NAF) algorithm for the scalar multiplication operation and proposes a low computational complexity Fw-NAF algorithm based on the prime number precomputation window, which greatly reduces its computational complexity.
Construction of Intelligent Classroom of Distance Music Teaching under Modern Information Technology

People began to emphasize music education gradually.Music teaching can cultivate a person's quality and sense of beauty.Therefore, it is of great significance to develop music teaching, which is conducive to better learning music.High quality music teaching can achieve better teaching results, so developing music teaching is something that contemporary people need to seriously study.In the traditional music teaching, music teaching ignored the aesthetic characteristics of music, and only single tuned theoretical knowledge, which made the quality of music teaching poor.This paper aimed to study the construction of distance music teaching intelligent classroom under modern information technology (IT).By studying how to integrate the wisdom classroom into teaching, an innovative remote intelligent classroom mode of music teaching was constructed.In this experiment, five classes were selected from the traditional teaching school and the remote intelligent classroom music teaching school under the modern IT for the examination of each subject.The results of the experiment were that in the vocal music test, instrumental music test, solfeggio test, ear training test and written music knowledge test, the average score of the vocal music test of the five classes under the music teaching of the remote intelligent classroom under the modern IT was 82.4, and the average score of the vocal music test of each class in the traditional music teaching was 72.2.The average score of instrumental music test of the five classes under the music teaching of the remote intelligent classroom under the modern IT was 82.2, and the average score of instrumental music test of each class in the traditional music teaching was 71.The average score of the five classes' solfeggio examination under the music teaching of the remote intelligent classroom under the modern IT was 82.8, and the average score of each class's solfeggio examination under the traditional music teaching was 73.2.The average score of the ear training test of the five classes under the music teaching of the remote intelligent classroom under the modern IT was 82.4, and the average score of the ear training test of each class in the traditional music teaching was 72.8.The average score of the written examination of music knowledge in the five classes under the music teaching of the remote intelligent classroom under modern IT was 84.4, and the average score of the written examination of music knowledge in each class of traditional music teaching was 73.6.It can be seen from
Denoising of COVID-19 CT and chest X-ray images using deep learning techniques for various noises using single image

The onset of COVID-19 pandemic had a great impact on the health, economy and livelihood of so many lives around the world. Early identification of positive cases and isolation followed by treatment is very crucial in order to receive prompt treatment and prevent the virus from spreading further. Chest X-ray (CXR) and Computed Tomography (CT) are widespread and cost-effective medical imaging radiographic tools which are presently used for diagnosing the covid-19 quickly. A crucial step towards establishing a quick COVID-19 pre-diagnosis and reducing the workload on medical professionals is the use of deep learning algorithms to identify positive CXR and CT pictures of infected individuals. However, the CXR images have complicated edge structures and rich texture details that are sensitive to noise, which can interfere with the machines and doctors diagnosis. This paper presents two state-of-art denoising techniques, Noise2Noise(N2N) and Noise2Void(N2V),to eliminate the noises that were added to COVID-19 chest x-ray scan image and CT medical image modalities by additive Gaussian noise, Speckle noise, and salt-and-pepper noise. These two techniques do not require a pair of noisy and clean photos; instead, they denoise a single noisy image. Based on the study, Noise2Void performs well in removing Gaussian, Speckle, and salt-and-pepper noise from CXR image modalities. Similarly, Noise2Noise performance is good to remove only Gaussian noise in CT images. In the case of Speckle and salt and pepper noise in CT images. Noise2void gives better quality images with better PSNR and SSIM. The results are measured quantitatively and qualitatively using Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure(SSIM). In this paper, we experiment two learning based methods to de-noise images with high noise. The proposed method is beneficial for applications involving images that are highly prone to noise.
ROR and Organizational Identifier Interoperability in Publishing Systems

The Research Organization Registry (ROR) is a global, community-led registry of open persistent identifiers for research organizations.Scholarly publishers already know the advantages of standardizing internal customer information with organization identifiers, but there are an increasing number of reasons for publishers to share organization data with other systems.ROR, a free and open CC0 dataset with a no-cost REST API, makes it easy for systems to exchange organization data for any and all purposes.
Performance analysis of Reinforcement Learning for Miner Selection in Blockchain

Blockchain is an emerging technology in the industry and business applications because of its characteristics such as tamper-proof, decentralized, immutable, transparent, and secure. Though it has several advantages, it still suffers from main challenges like privacy and scalability. Scalability is defined in terms of throughput, capacity, and response time. The response time includes the time of adding the block to the Blockchain. It consists of the miner's time who adds the block to the blockchain. The paper proposes a reinforcement learning method to improve the scalability of blockchain systems. The proposed methodology discusses the performance analysis of the reinforcement learning algorithm to select the miners for block mining.
MSD: Mixing Signed Digit Representations for Hardware-efficient DNN Acceleration on FPGA with Heterogeneous Resources

By quantizing weights with different precision for different parts of a network, mixed-precision quantization promises to reduce the hardware cost and improve the speed of deep neural network (DNN) accelerators that typically operate with a fixed quantization scheme. However, the additional control needed, and the decreased hardware efficiency arising from multi-precision operations have made mixed-precision quantization schemes challenging to deploy in practice. In this paper, a practical mixed-precision quantization framework called MSD that leverages the heterogeneous computing resources on FPGA to perform bit-serial and bit-parallel operations simultaneously is presented. MSD combines the use of a custom restricted signed digit (RSD) representation, which utilizes a limited number of effectual bits, and the conventional 2's complement representation to quantize DNN weights. Depending on the availability of fine-grained and coarse-grained resources, MSD encodes a subset of weights with RSD to allow highly efficient bit-serial multiply-accumulate implementation using LUT resources. Furthermore, the number of effectual bits used in RSD is optimized to match the bit-serial hardware latency to the bit-parallel operation on the coarse-grained resources to ensure the highest run-time utilization of all on-chip resources. Experiments show that MSD achieved a 1.36× speedup on the ResNet-18 model over the state-of-the-art, and a remarkable 4.91% higher accuracy on MobileNet-V2.
Distributionally Robust Kalman Filtering for INS/GPS Tightly Coupled Integration With Model Uncertainty and Measurement Outlier

The Kalman filter (KF) has been widely used in INS/GPS tightly coupled integration system. However, KFs are prone to divergence when the INS/GPS tightly coupled integration suffers from model uncertainties, measurement outliers caused by sensor errors, or changes in hostile environment. Existing studies can hardly address all of these conditions. In this paper, to ensure accurate and robust positioning performance for the INS/GPS tightly coupled integration under uncertainties and outliers, an improved distributionally robust Kalman filter (DRKF) based on Wasserstein and moment-based ambiguity set is proposed. To this end, the state least favorable conditional prior distribution is obtained using the Wasserstein metric, and the moment-based ambiguity set is adopted to describe the distribution of the measurement noise. Furthermore, we use a novel saturation mechanism to suppress outliers, and this ensures robust bounded-error state estimation in presence of outliers. Experimental results demonstrate that the proposed algorithm can effectively deal with the model uncertainties and measurement outliers for the INS/GPS navigation system, with higher estimation accuracy and stronger robustness as compared to most relevant methods.
A Modern Approach of Swarm Intelligence Analysis in Big Data

Swarm intelligence is one of the most modern and less discovered artificial intelligence types. Until now it has been proven that the most comprehensive method to solve complex problems is using behaviours of swarms. Big data analysis plays a beneficial role in decision making, education domain, innovations, and healthcare in this digitally growing world. To synchronize and make decisions by analysing such a big amount of data may not be possible by the traditional methods. Traditional model-based methods may fail because of problem varieties such as volume, dynamic changes, noise, and so forth. Because of the above varieties, the traditional data processing approach will become inefficient. On the basis of the combination of swarm intelligence and data mining techniques, we can have better understanding of big data analytics, so utilizing swarm intelligence to analyse big data will give massive results. By utilizing existing information about this domain, more efficient algorithm can be designed to solve real-life problems.
Study on the Influence of Modern Information Technology on Student Management in Higher Vocational Colleges

In recent years, with the expanding scale of higher vocational colleges, the difficulty of higher vocational college student management and complexity also rising, the traditional student management mode and method has been difficult to meet the demand of the development of higher vocational colleges, should be more with the role of modern information technology and advantages, improve the higher vocational college student management quality and efficiency.The rapid development of information technology has made it widely used in the field of education, and also has an important impact on the student management of higher vocational colleges, promoted the innovation of the working methods of student management, and also improved the level and effectiveness of student management.Based on this, this paper analyzes the influence of modern information technology on student management in higher vocational colleges, and explores the innovative strategies of student management in higher vocational colleges under the background of information.The development of information technology has promoted great changes in people's production and life, and has also had an important impact on the field of education.In recent years, as the higher vocational college student management difficulty and the complexity of promotion, the higher vocational college student management is facing great challenges, with the help of information technology innovation in higher vocational college student management methods and enhance the level of higher vocational college student management and results has become an inevitable trend, which makes the modern information technology for higher vocational college student management influence more significant. The Influence of Modern Information Technology on the Student Management in Higher Vocational CollegesIn order to improve the level and effectiveness of student management in higher vocational colleges, information technology has been widely used.With the help of the advantages of modern
FPGA-Based Architectures &amp;amp; DAQ Pathways for Distributed ML Systems

existing operations-critical functions of the BLM system. This paper will focus on the evolution of the architectures, which provided the high-frequency, low-latency collection of synchronized data streams to make real-time inferences. The ML models, used for learning both local and global machine signatures and producing high quality inferences based on raw BLM loss measurements, will only be discussed at a high-level.
Information Literacy in Learning Academic Writing

Nowadays information literacy is an indispensable competence as information is ubiquitous and overwhelming.This competence is required in all spheres and should be constantly improved.The article aims to pinpoint the opportunities of integrating information literacy into academic writing as the latter is one of the fundamental skills that students acquire and develop throughout most of the university courses.To achieve the goal the authors reviewed various interpretations of the term "information literacy" stated by different researchers, designed and realised assignments aimed at integrating information literacy and academic writing, carried out a preliminary analysis of the results obtained, and formulated perspectives for further research.The results proved that academic writing can not be taught without information literacy and their integration leads to a synergetic effect on the instruction.Information literacy is an integral part of bachelor, master, and PhD courses.It can be implemented in all educational forms, namely, individual, pair, group, and class activities.One of the fruitful prospects for further research is designing courses and programmes for teachers to involve them in more active information literacy integration into the educational process.
Direct and indirect evidence of compression of word lengths. Zipf’s law of abbreviation revisited

Zipf’s law of abbreviation, the tendency of more frequent words to be shorter, is one of the most solid candidates for a linguistic universal, in the sense that it has the potential for being exceptionless or with a number of exceptions that is vanishingly small compared to the number of languages on Earth. Since Zipf’s pioneering research, this law has been viewed as a manifestation of a universal principle of communication, i.e. the minimization of word lengths, to reduce the effort of communication. Here we revisit the concordance of written language with the law of abbreviation. Crucially, we provide wider evidence that the law holds also in speech (when word length is measured in time), in particular in 46 languages from 14 linguistic families. Agreement with the law of abbreviation provides indirect evidence of compression of languages via the theoretical argument that the law of abbreviation is a prediction of optimal coding. Motivated by the need of direct evidence of compression, we derive a simple formula for a random baseline indicating that word lengths are systematically below chance, across linguistic families and writing systems, and independently of the unit of measurement (length in characters or duration in time). Our work paves the way to measure and compare the degree of optimality of word lengths in languages.