Reviewerly/exHarmony huggingface dataset:
The Effects of Covid-19 on Science Education: A Thematic Review of International Research

The health emergency caused by the COVID-19 pandemic has transformed and decisively affected the entire education system, which has resulted in an urgent need to adapt it to an online scenario. Science education is an area that has been highly affected by and, as a consequence, science teachers were forced to make an extra effort to create virtual learning environments accessible for all students. This study offers a systematic review to synthesize how the COVID-19 pandemic has influenced science teachers’ educational practices and adaptations. To this end, Web of Science, ERIC and Scopus databases used to explore the virtual educational practices, e.g., teaching-learning processes, during the pandemic. The purpose of this study is to analyze the main bibliographic characteristics of the collected literature (research purpose, methodological design, geographical and temporal distribution, central themes) via thematic analysis. The findings offered a synthesis of studies that explain innovative practices, tools, and strategies that were very useful for teachers and students in the STEM area. We believe that future lines of research should be oriented towards broadening the analysis of different pedagogical approaches developed in the teaching of STEM areas during the health crisis by COVID-19. This could be useful for guiding professional and educational actions.
DECENTRALIZED ELECTRONIC VOTING USING SMART CONTRACTS (DEV-SC)

For a citizen, voting is the fundamental tool to bring change in the country for good governance, through electing suitable candidates or a party to give them the power to govern. There are many forms of elections be it in the democratic or monarch systems. Each way, the vote has the power to elect the next people’s representatives. For a long time, paper-based voting was the only system being used globally for years; after the dot-com bubble, many countries emerged with electronic voting. But the problems such as security, transparency, and integrity of elections and the voting process are still under question. The issue with paper-based voting was accessibility, voter turns around and tallies, electronic voting has its own advantages and disadvantages such as a single point of failure, trustful systems, and loopholes to forge the electronic voting systems to alter the outcomes. To solve the problems related to the electronic voting process security, integrity, and transparency, an advanced approach is required to adopt. With the advancement of technologies, 4th industry revolution technologies give us Blockchain, Distributed Ledger and Smart Contract types of technologies which may be beneficial to solve the current problems in electronic voting systems. In this paper, we proposed a research-based case study to implement Decentralized Electronic Voting using Smart Contracts (DEV-SC) to solve security, transparency, and integrity-related problems available in the electronic voting process. This will ensure and enhance the voting process easily, trustable, and verifiable.
Empirical Evaluation of Fixed and Single-Axis Tracking Photovoltaic System: Case of ASHRAE Solar Radiation Modelling for Medina, Saudi Arabia

The main problem in studying the feasibility of solar systems is the enormous gap between theory and experimental radiation intensity, so to get accurate results there is a need for studying energy production in the site of the system empirically. In this study, the energy production of both fixed PV panel system and the system with single-axis tracking were empirically evaluated in Medina, Saudi Arabia. The two systems had the same 270 Wp PV panel. The fixed system was tilted by 23.5 degrees, and the single-axis tracker was tilted by 26 degrees. Both systems had an azimuth angle of zero degrees. A closedloop three-points controller was used to control the tracker with 120 degrees rotation range. The two systems operated simultaneously in July, and the data were collected for 14 days. The empirical results showed that the tracker increased the generated energy by 48.5% during the testing period. As a comparing method, a modified ASHRAE model was used to estimate the increase in the panel's energy output with and without the single-axis tracker, and RMSE and MBE were calculated. It's been found that the experimental energy generation is 10%, 5% less than the estimation of the modified model for the fixed system and the tracking system, respectively. Finally, based on the analysis, it's been estimated that the singleaxis tracker will increase the generated energy by 22.5% yearly in Medina.
Thoreau’s Econational Poetics

Drawing on Henry David Thoreau’s botanical sketches, translation notebooks, and essays on migrant dwelling, this article reads Thoreau’s ecology in the context of his engagements with Asian literature. According to Thoreau, poetry relinquishes independent subject-agency like plants, is regenerative like air, and resists stabilized meaning like celestial bodies. The article proposes an econational method of engaging with global literature that is developed through Thoreau’s theories of texts as unstable oikoi (oikos being the root of eco) and nations as contingent communities. I argue that his poetics models the relations between texts and readers as open-ended networks rather than linear appropriations, and thus stands in contrast to transnational writing that preserves localized identities in the processes of exchange.
Discussion on the Resources Construction and Service of University Library in the Era of Internet plus

Internet plus mobile technology provides the foundation for the arrival of the era of the media. The learning styles of teachers and students in universities are no longer confined to libraries and classrooms, but also have more choices such as mobile phone and tablet computer. The Internet plus era brings new opportunities and challenges to university libraries. It requires that the libraries of colleges and universities should make changes in technology and content on the one hand, and renew ideas in the same way. It is a rare opportunity to leap over development. In this interactive context, the library industry needs to think deeply about how to integrate with the Internet and realize the increment of readers in the form of innovation. The Internet plus user internet behavior is analyzed in this paper. The problems in the resource construction and service of university libraries are summarized. The innovation of University Libraries in the era of Internet plus and effective measures for optimizing the resources of University Libraries in the era of Internet plus are discussed, in order to make the university libraries develop more rapidly in the changing era.
Improving Intent Detection Accuracy Through Token Level Labeling

Intent detection is traditionally modeled as a sequence classification task where the role of the models is to map the users' utterances to their class. In this paper, however, we show that the classification accuracy can be improved with the use of token level intent annotations and introducing new annotation guidelines for labeling sentences in the intent detection task. What is more, we introduce a method for training the network to predict joint sentence level and token level annotations. We also test the effects of different annotation schemes (BIO, binary, sentence intent) on the model’s accuracy.
An Examination of the Statistical Laws of Semantic Change in Clinical Notes.

Natural language is continually changing. Given the prevalence of unstructured, free-text clinical notes in the healthcare domain, understanding the aspects of this change is of critical importance to clinical Natural Language Processing (NLP) systems. In this study, we examine two previously described semantic change laws based on word frequency and polysemy, and analyze how they apply to the clinical domain. We also explore a new facet of change: whether domain-specific clinical terms exhibit different change patterns compared to general-purpose English. Using a corpus spanning eighteen years of clinical notes, we find that the previously described laws of semantic change hold for our data set. We also find that domain-specific biomedical terms change faster compared to general English words.
Psychology in AI Stance

This review discusses the role of psychology in the development in the sector of artificial intelligence. Cognitive science bestows the scientific basis for advancement in the realm of artificial intelligence. Gleaning a high-tech machine that can think, learn, reason, experience, and can function autarchic bereft of supervision is one of the pivotal grails in all of computer science. Studies posit that higher education in psychology can smooth the path for reasoning about general issues. With a prodigiously autarchic, learning, reasoning, the artificially intelligent system comes with a need to possess hardware and software that transcribes processes and subsystems that subsist within a human brain including intuitive and emotional concepts. The idea of interweaving these two immense realms: the complexities of psychology and vitality of artificial intelligence has gained escalation in recent times. This review focuses on how computer implementation and psychological tools bring enhancement in the field of artificial intelligence.
Hidden Cosets and Applications to Unclonable Cryptography.

In 2012, Aaronson and Christiano introduced the idea of hidden subspace states to build public-key quantum money [STOC ’12]. Since then, this idea has been applied to realize several other cryptographic primitives which enjoy some form of unclonability.
Applying the Information Bottleneck Principle to Prosodic Representation Learning

This paper describes a novel design of a neural network-based speech generation model for learning prosodic representation.The problem of representation learning is formulated according to the information bottleneck (IB) principle. A modified VQ-VAE quantized layer is incorporated in the speech generation model to control the IB capacity and adjust the balance between reconstruction power and disentangle capability of the learned representation. The proposed model is able to learn word-level prosodic representations from speech data. With an optimized IB capacity, the learned representations not only are adequate to reconstruct the original speech but also can be used to transfer the prosody onto different textual content. Extensive results of the objective and subjective evaluation are presented to demonstrate the effect of IB capacity control, the effectiveness, and potential usage of the learned prosodic representation in controllable neural speech generation.
Discreet Interactive Wallpaper Concepts Study

In this paper, we address the design of discreet interactive wallpapers. We chart the initial user perceptions with a simulation-based user study (n = 14), where we evaluate different concepts specifically designed for electrochromic ink, ranging from ambient information delivery to gamification. Our research contributes background knowledge for designers and practitioners working with interactive environments.
Contrastive Explanations for Explaining Model Adaptations

Many decision making systems deployed in the real world are not static - a phenomenon known as model adaptation takes place over time. The need for transparency and interpretability of AI-based decision models is widely accepted and thus have been worked on extensively. Usually, explanation methods assume a static system that has to be explained. Explaining non-static systems is still an open research question, which poses the challenge how to explain model adaptations. In this contribution, we propose and (empirically) evaluate a framework for explaining model adaptations by contrastive explanations. We also propose a method for automatically finding regions in data space that are affected by a given model adaptation and thus should be explained.
Benchmarking the Robustness of Instance Segmentation Models

This article presents a comprehensive evaluation of instance segmentation models with respect to real-world image corruptions as well as out-of-domain image collections, e.g., images captured by a different set-up than the training dataset. The out-of-domain image evaluation shows the generalization capability of models, an essential aspect of real-world applications, and an extensively studied topic of domain adaptation. These presented robustness and generalization evaluations are important when designing instance segmentation models for real-world applications and picking an off-the-shelf pretrained model to directly use for the task at hand. Specifically, this benchmark study includes state-of-the-art network architectures, network backbones, normalization layers, models trained starting from scratch versus pretrained networks, and the effect of multitask training on robustness and generalization. Through this study, we gain several insights. For example, we find that group normalization (GN) enhances the robustness of networks across corruptions where the image contents stay the same but corruptions are added on top. On the other hand, batch normalization (BN) improves the generalization of the models across different datasets where statistics of image features change. We also find that single-stage detectors do not generalize well to larger image resolutions than their training size. On the other hand, multistage detectors can easily be used on images of different sizes. We hope that our comprehensive study will motivate the development of more robust and reliable instance segmentation models.
Blockchain Technology for 6G Communication Networks

The limits of 5g networks that have been recognized with the continued deployment of 5g networks prompted the exploratory research into the sixth generation of wireless communications technologies (6G). This chapter first presents the reader a clear introduction to the subject, by providing an overview of this technology in terms of its fundamental components and the relationships between them. Second, the link between cryptography and blockchain technology is made clearer by reviewing some of the techniques used in this technology, together with its implementation in the blockchain environment. Moreover, the chapter discusses a very important aspect of the subject, namely the consensus mechanism, by which the parties reach an agreement on the data to be published in the network. Also, it examines some of the main challenges facing the 6G networks, together with some of the blockchain-based solutions in both infrastructure and application levels. Finally, the chapter concludes by highlighting the challenges of open research in today’s blockchain technology.
On the ability of monolingual models to learn language-agnostic representations.

Pretrained multilingual models have become a de facto default approach for zero-shot cross-lingual transfer. Previous work has shown that these models are able to achieve cross-lingual representations when pretrained on two or more languages with shared parameters. In this work, we provide evidence that a model can achieve language-agnostic representations even when pretrained on a single language. That is, we find that monolingual models pretrained and finetuned on different languages achieve competitive performance compared to the ones that use the same target language. Surprisingly, the models show a similar performance on a same task regardless of the pretraining language. For example, models pretrained on distant languages such as German and Portuguese perform similarly on English tasks.
Application of Digital Technology in Electronic Music Instrument Design

The characteristics of electronic musical instruments determine that their development is inseparable from the development of electronic technology. At the end of the 20th century, computer technology began to profoundly affect the work progress of sound design. From analog sound signal synthesis in the late World War II, to digital control of analog sound signal synthesis in the 1980s, then came to today’s pure digital synthesis. The design of electronic musical instruments has fully entered the digital times. This article mainly reviews the history of the development of electronic technology and electronic musical instruments, explores its development trajectory, and proposes new ideas of electronic musical instruments’ digital technology design in its future development by combining with the actual work cases of the author’s.
Medical Data Analytics for Secure Multi-party-primarily based Cloud Computing utilizing Homomorphic Encryption

Cloud computing has emerged as a vibrant part of today's modern world, providing computer services such as data storage, managing and processing via the internet. For the most part, cloud applications emphasize a multi-tenant structure to provide support for several customers in a single instance. A multi-tenancy situation involving the allocation of resources in cloud storage and the risks associated with it, in which confidentiality or integrity may be compromised. Homomorphic encryption is one such technique which guarantees to franchise in safeguarding information under cryptographic domain. The proposed modified Algebra Homomorphic Encryption scheme based on updated ElGamal (AHEE) encryption scheme is designed in such a way that the cloud administrators do not obtain any information about the medical data. This scheme is quantitatively evaluated using metrics such as encryption time and decryption time. The experimental results using UCI Machine Learning Repository ECG data set show that the proposed scheme achieved shorter encryption time of 6.61 ms and decryption time of 5.94 ms and also analyze this secured datum using big data analytics.
Design and Implementation of Electronic Voting Using KECCAK256 Algorithm on Ethereum Network

Electronic voting (e-voting) is an electronic method of voting. This voting method ensures that it is easier to vote and encourages more people to vote while also eradicating hooliganism and violence that impede several elections in many countries. It is a transparent form of voting if it has not been hacked; Unique Identification of India thus, the need for Ethereum and blockchain network in the e-voting system. The transactions on blockchain is evenly distributed ensuring that it is decentralized, meaning there is no specific database where data is stored, hence ensuring tight security. This paper seeks to therefore develop an e-voting system based on Ethereum by using the KECCAK256 algorithm by creating a voting scheme that is transparent, reliable, visible, and easy access to the election process starting from registration phase to the results phase. In developing this system, we made use of react js for building the user interface of the system, node js for the executing the JavaScript code outside of the web browser, and solidity was used for programming the smart contract. The system was successfully tested on Ganache which was the local blockchain used in implementing the system, and Google Chrome was the user interface where the user could access to vote and MetaMask which was used for accessing the Ethereum platform where authentication and authorization take place. The performance of the system on comparing it to other existing systems showed that the system was above average.
Multi-Dimensional Sport Physique Evaluation and Ranking for Healthcare Based on TOPSIS

Typically, through monitoring, collecting, integrating, and analyzing the sport scores of individuals, we can know about the sport physique of the individuals in a real-time manner, so as to further guarantee a high-quality health level of people. However, in the abovementioned sport scores-based sport physique monitoring scenario, two major challenges are raised. First, the collected sport scores for sport physique monitoring are often multi-dimensional, which makes it hard to evaluate the sport physique of individuals fairly and reasonably. Moreover, the multiple dimensions of sport scores are often of different weights or significances, which raise a challenging task to objectively evaluate the sport physique of an individual. Considering these challenges, a novel multi-dimensional sport physique evaluation and ranking method, named MSPER, is proposed in this research work for better healthcare for individuals, which is based on the TOPSIS theory. At last, a case study is presented to show the concrete procedure of MSPER method.
Increasing Frequency Resolution in EEG Studies based on Covariation Analysis

The paper discusses the application of the method of co-variance analysis of noisy signals using the example of an electroencephalogram to increase the frequency resolution in relation to the phenomena of electrical activity of the brain. The method is focused primarily on signals presented in digital form. The possibility of increasing the frequency resolution in comparison with the method of Fourier transform and wavelet transform is shown.
QR Code and Useful Applications in Libraries

This article deals with QR code and useful applications in libraries as a emerging technology in the present scenario of libraries hand trend access resources with simple a scan of a code are known as a treasure house of knowledge by having its high quality and rich information resources which are freely provided for academic user community. It is also covers how to generate as well as as decode QR code through various online available that are free and easy to use. This article also explains the all possible implementation of QR code in library services with a briefing of all its advantages as well as limitations.
Russian Experience in Organizing Fully Remote Software Development: an Industry Study of 2021

The pandemic and the COVID-economy continue to have a significant impact on the development of industries of the "new economy". We might see it in the acceleration of digitalization, visualization of work processes and the predominance of communications in electronic channels. The transition to fully remote development and support of software under the influence of the COVID factor not just changed the IT industry, but established a new standard of organization of the software production. This article presents the results of study that covered various aspects of fully remote software development in Russian companies, including VTB, Yandex, Sbertech, and others. More than 20 experts representing their development teams have identified the main approaches to ensuring the motivation and involvement of engineers and to ensuring favorable conditions for their professional growth. The study also identifies the prospects for the evolution of the fully remote software development as a new industry standard. The results of the study are accompanied by the brief conclusions, the main idea of which is the need to quickly understand a new trend in software development and the usage of this factor in the competitive struggle (hiring specialists, organizing teams, organizational development).