Reviewerly/exHarmony huggingface dataset:
Intelligent Interfaces and Systems for Human-Computer Interaction

The paper presents a brief review of intelligent interfaces and systems of human-machine interaction. To date, few intelligent interfaces and systems are used in various areas of industry. All the systems of human-machine interaction can be divided into intelligent synthesis and analysis systems. Intelligent synthesis implies the presentation of information from the system to the user. Aiming at presenting information from a person to a system, intelligent analysis is based on state-of-the-art predictive neural networks such as Transformer models with attention mechanisms. Meanwhile, intelligent synthesis is based on generative neural networks designed to generate video, audio and text information for various tasks. The paper briefly describes state-of-the-art methods in this area, as well as provides an overview of existing freely available systems for generating and analyzing uni- and multimodal information. The paper also focuses on recent research results of the Speech and Multimodal Interfaces Laboratory of SPC RAS in this field, as well as presents some methods for solving actual tasks of intelligent analysis.
An Exploratory Study and Prevention Measures of Mob Lynchings: A Case Study of India

Mob lynching is violent human behaviour where people punish someone without a legal trial. Lynching ends with a significant injury or death of a person. In the digital era, almost every piece of news, including the incident of mob lynching, is shared on social media. Once a case of mob lynching is shared on social media, it propagates to a wide range of audiences. This study uses quantitative and qualitative approaches to investigate mob lynching in India and discuss possible prevention measures through social media using two datasets, one collected from Twitter and another from a fact-checking website. The fact-checked data provides an overview of the cause and effect of mob lynching, while the tweets provide the current discussion and user response. The proposed analysis highlights frequent topics discussed on Twitter, user reactions to those posts, and their relation with historic mob lynching incidents. In the end, a prevention measure is proposed using a user study. The result shows that most tweets are of negative sentiment; tweets are more retweeted than likes. The topic modelling shows the tweets are asking for mob lynching and help. There is partial support for prevention measures, and there is a need for literacy, awareness, and strict law to control mob lynching in future.
Study of practical state-preparation error tolerant reference-frame-independent quantum key distribution protocol

Quantum key distribution (QKD) enables the establishment of shared keys between two distant users, Alice and Bob, based on the fundamental principles of quantum mechanics, and it has proven to possess information-theoretic security. In most of QKD systems, Alice and Bob require a shared reference frame, and real-time calibration of the reference frame increases system costs and reduces its performance. Fortunately, the reference-frame-independent QKD protocol has been proposed, overcoming reference-frame drift issues and receiving widespread attention. However, in practical QKD systems, the non-ideal characteristics of realistic devices introduce certain inconsistency between the theory and the practice. In real-world quantum key distribution systems, device imperfections can lead to security vulnerabilities, thereby reducing system security. For example, imperfections in the encoding apparatus at the source end may result in errors in the quantum states. The inherent defects in the detection part may cause after-pulse effects and dead-time effects, thus reducing the key rate. Therefore, in this work, we propose a practical state-preparation error tolerant reference-frame-independent quantum key distribution protocol by taking imperfections in both the source and the detectors into account. Moreover, a three-intensity decoy-state scheme for modeling analysis and numerical simulations is employed. In this protocol, we reduce the influence of state-preparation errors on the key rate by utilizing virtual state methods to precisely estimate the phase-error rate. Furthermore, by characterizing the effects of after-pulses and dead-time on the key rate, our protocol exhibits higher robustness and can effectively address issues related to detector imperfections. This approach can also be extended to other quantum key distribution protocols with higher security levels, such as measurement-device-independent quantum key distribution protocol and twin-field quantum key distribution, further mitigating the influence of device imperfections on practical implementation of QKD system. Therefore, our present work provide important reference value for putting the quantum key distributions into practical application.
What's New in terrainr 0.4.0?

terrainr version 0.4.0 is now on CRAN! This version is a relatively minor updatethat shouldn’t impact most workflows, but makes some changes to improve thelogic and consistency of the package. The rest of this post runs through thechanges you can expect if you update.packages any time soon!&lt;strong&gt;What’s a terrainr?&lt;/strong&gt; terrainr is an R package for theretrieval and visualization of spatial data.
Make Your R Package Easier to Cite

Scientists rarely cite research software they use as part of a research project. As a consequence, the software and the time spent developing and maintaining it becomes an invisible scholarly contribution. Furthermore, this lack of visibility means that incentives to produce high quality, sustainable software are missing. Among many reasons why software is not cited, one is the lack of a clear citation information from package developers.
A Roundup of R Tools for Handling BibTeX

Our website is based on Markdown content rendered with Hugo.Markdown content is in some cases knit from R Markdown, but with less functionality than if one rendered R Markdown to html as in the blogdown default.In particular, we cannot use the usual BibTex + CSL + Pandoc-citeproc dance to handle a bibliography.Thankfully, using the rOpenSci package RefManageR, we can still make our own bibliography from a BibTeX file without formatting reference
Miscellaneous Wisdom about R Markdown &amp; Hugo Gained from Work on our Website

Whilst working on the blog guide, Stefanie Butland and I consolidated knowledge we had already gained, but it was also the opportunity to up our Rmd/Hugo technical game.Our website uses Hugo but not blogdown&lt;sup&gt;1&lt;/sup&gt; to render posts: every post is based on an .md file that is either written directly or knit from an .Rmd file.We wanted to provide clear guidance for both options, and to stick to the well-documented Hugo way of e.g. inserting fi
We cleaned our website URLs with R!

Last year we reported on the joy of using commonmark and xml2 to parseMarkdown content, like the source of this website built withHugo, in particular to extractlinks,at the time merely to count them. How about we go a bit further and usethe same approach to find links to be fixed?
Teacher and Student Attendance System at Noor Faqih Usman Foundation Based on RFID Integrated with Raspberry Pi

In educational institutions, tracking attendance is crucial for ensuring effective administration and student engagement. This abstract presents the development of a Teacher and Student Attendance System at the Noor Faqih Usman Foundation, leveraging Radio Frequency Identification (RFID) technology integrated with Raspberry Pi. The proposed system aims to automate the attendance recording process, streamline administrative tasks, and enhance the overall efficiency of attendance management. This can create gaps in the development of data manipulation, data frameworks, and rigid systems. The purpose of this study was to create an RFID-Based Teacher and Student Attendance System integrated with Raspberry Pi. This study was conducted using a quantitative method of study and development study. This RFID-based attendance technology will later replace the role of paper to record the attendance of teachers and students using cards/keychains to make it easier to report attendance; data can be stored in digital form such as Excel, can be accessed via wireless smartphones, interested parties can monitor through the website, and the educational institution will be touched by at least technology. The results showed that the system was able to control the attendance process and succeeded well.
SENA: Similarity-Based Error-Checking of Neural Activations

In this work, we propose SENA, a run-time monitor focused on detecting unreliable predictions from machine learning (ML) classifiers. The main idea is that instead of trying to detect when an image is out-of-distribution (OOD), which will not always result in a wrong output, we focus on detecting if the prediction from the ML model is not reliable, which will most of the time result in a wrong output, independently of whether it is in-distribution (ID) or OOD. The verification is done by checking the similarity between the neural activations of an incoming input and a set of representative neural activations recorded during training. SENA uses information from true-positive and false-negative examples collected during training to verify if a prediction is reliable or not. Our approach achieves results comparable to state-of-the-art solutions without requiring any prior OOD information and without hyperparameter tuning. Besides, the code is publicly available for easy reproducibility at https://github.com/raulsenaferreira/SENA.
A call for a research agenda on fair NLP for Portuguese

Diverse areas widely apply artificial intelligence and natural language processing (NLP) tools to their contexts. However, these algorithms present ethical issues, such as biased and discriminatory decisions. For example, representation biases in NLP can result in discriminatory behavior towards race and gender. Works have been addressing this issue and seeking to build fair NLP solutions, however they mainly focus on Anglo-Saxon languages. This work aims to challenge the scientific community in order to stimulate and motivate further research in the fair NLP specifically for the Portuguese language. To achieve this, a literature review was conducted to identify existing research efforts and indicate future directions.
From Database Repairs to Causality in Databases and Beyond

We describe some recent approaches to score-based explanations for query answers in databases. The focus is on work done by the author and collaborators. Special emphasis is placed on the use of counterfactual reasoning for score specification and computation. Several examples that illustrate the flexibility of these methods are shown.
A web-based human liver atlas

The liver is the largest solid organ in the body that can be anatomically divided into segments. We present in this work a web-based subject-specific human liver atlas based on the Couinaud segments simulated from portal venous (PV) perfusion zones, hepatic arterial (HA) and hepatic venous (HV) trees, as well as biliary drainage. The purpose of the atlas is to provide the modelling community with freely accessible 3D hepatic structures for in silico simulations, which are of tremendous value in yielding novel insights in hepatic circulation, drug transport and clearance.
Urban China and COVID-19: how Chinese cities responded to the pandemic

This chapter examines three major strategies used by city governments in China to contain COVID-19 lockdowns, the grid governance system, and digital surveillance. Although some of these measures have also been used in other countries, the ways in which they are implemented in China spotlight the territorial logic of urban governance in the country. The enforcement of these measures strictly trails administrative jurisdictions, and largely depends on the pre-existing territorial institutions and authorities. China’s experience offers several lessons for other countries. It demonstrates the importance of empowering municipal institutions and coordinating central-local responses, but also the consequence of disengaging citizens and encroaching upon citizen rights.
A Lévy Flight-Inspired Random Walk Algorithm for Continuous Fitness Landscape Analysis

Heuristic algorithms are effective methods for solving complex optimization problems. The optimal algorithm selection for a specific optimization problem is a challenging task. Fitness landscape analysis (FLA) is used to understand the optimization problem's characteristics and help select the optimal algorithm. A random walk algorithm is an essential technique for FLA in continuous search space. However, most currently proposed random walk algorithms suffer from unbalanced sampling points. This article proposes a Lévy flight-based random walk (LRW) algorithm to address this problem. The Lévy flight is used to generate the proposed random walk algorithm's variable step size and direction. Some tests show that the proposed LRW algorithm performs better in the uniformity of sampling points. Besides, the authors analyze the fitness landscape of the CEC2017 benchmark functions using the proposed LRW algorithm. The experimental results indicate that the proposed LRW algorithm can better obtain the structural features of the landscape and has better stability than several other RW algorithms.
Exploring Parents' Perceptions Toward Early Childhood English Language Education in Jakarta

This study investigates parents' perceptions of early childhood English language education in Jakarta, Indonesia. With an increasing emphasis on English proficiency in a globalized world, understanding parental attitudes toward introducing English early age is essential. This research employed a mixed-methods approach, utilizing a survey questionnaire to gather insights from 52 parents, consisting of 40 mothers and 12 fathers, whose children were between 3 to 6 years old. The survey revealed that 92% of parents agreed that early English education enhances language development, 88% believed it provides a competitive edge, 83% considered it crucial for opportunities, and 74% saw its potential to boost cognitive skills. In-depth interviews were conducted with 16 participants, selected through purposive sampling, to delve deeper into parental perceptions, providing further insight. The findings underscore parents' collective recognition of the positive impact of early English education on language development and cognitive skills, presenting a valuable resource for parents seeking informed decisions about their children's early language learning journey. The study offers input for educators, policymakers, and curriculum designers aiming to create effective early English programs resonating with parental perspectives.
A study of " Bei-sentence" in crime news headlines in the new media context

New media play an important role in news communication, and in order to attract readers' attention, they often use quilt sentences in crime news headlines frequently, and such usage has triggered extensive discussions. In the context of linguistics, a combination of quantitative and qualitative analysis is used to study the structural features, semantic features and predicate components of the Bei-sentence in crime news headlines, which can explore the use of the Bei-sentence and related linguistic features in crime news headlines in the new media context. In addition, the linguistic features and functions of the Bei-sentence have a significant impact on the meaning expression and readers' emotion of the headlines. The improper use of new media language may cause secondary harm to victims and also undermine the justice of social news. The new research perspective of combining social phenomena with linguistic theories helps to deeply understand the characteristics of crime news headlines in the new media context and helps to improve readers' media literacy.
The reform of informatization of college curriculum teaching based on the integration of science and education

Aiming at the phenomenon of the students' education of science universities in our country attaching more importance to scientific research than teaching in the aspects of scientific research and teaching, scientific research and talents cultivation, the transformation of scientific research achievements rather than talent cultivation, centering on the fundamental task of "establishing morality and educating people" and based on the integration concept of science and education, this paper analyzes the problems existing in the students' theory and technology course teaching on mine fire prevention. From the aspects of "optimizing curriculum system to stimulate scientific research thinking", "scientific research platform to serve practical teaching", "knowledge sharing to deepen understanding and application", "innovation competition to integrate knowledge learning and practical innovation" and "university-enterprise joint cultivation of comprehensive ability", we explored the first-class talent training mode, and explored a set of crisscrossing curriculum training mode of science and education integration and collaborative education. It provides reference and reference ideas for personnel training in relevant colleges and universities.
Research on Smart Service Innovation of University Libraries in the "Internet plus" Environment

In the "Internet plus" era, the rapid development and popularization of information technology have brought unprecedented opportunities and challenges to libraries. The construction of university libraries, as an important support for teaching and research in universities, faces the problem of how to better utilize internet technology to provide smart library services. The traditional library service can no longer meet the needs of users, so it is necessary to improve the service quality and efficiency of university libraries with the help of intelligent services under the "Internet plus" environment. I hope to improve the quality of university education, promote teaching reform and innovation, cultivate students' comprehensive qualities, enhance the core competitiveness of university libraries, and enhance the comprehensive strength of universities through research and practice of intelligent services in university libraries.
Adaptation of First-Year Students to Study at a Pedagogical University within the Framework of Educational Practice

&lt;p&gt;The article is devoted to the urgent problem of adaptation of first&amp;ndash;year students - future physics teachers to university education. The relevance is confirmed by the fact that it is based on the law &amp;ldquo;On Education in the Russian Federation&amp;rdquo;, which, among other things, states the need to achieve a high quality of education without compromising the health of students. The concept of &amp;ldquo;adaptation of students&amp;rdquo;, factors and a set of problems of a first&amp;ndash;year student are considered. The components of adaptation in the educational process in teaching physics are presented: psychological and social, health-preserving, ergonomic, content-procedural &amp;mdash; on which we can work to a greater extent at the Department of Physics and Methods of Teaching Physics. The results of the survey and diagnostics made it possible to identify the difficulties experienced by future physics teachers in the first year of study, which makes it possible to create conditions for the adaptation of first-year students to the university format of educational and cognitive activity. Recommendations for organizing the process of adaptation of first&amp;ndash;year students &amp;mdash; future teachers of physics &amp;mdash; to study at a university within the framework of educational practice are highlighted.&lt;/p&gt;
Assessing the Competencies of the Educational Module for Future Teachers of Primary General Education: Design and Implementation

&lt;p&gt;The article presents a solution to the problem of designing means for assessing professional competencies in future teachers of primary general education according to the module of educational activities of the Core of Higher Pedagogical Education. The authors substantiate the process of designing assessment tools by teachers on the basis of competency-based and modular approaches to the content of teacher education based on the conceptual approaches presented in the studies of A.A. Verbitsky, A.V. Khutorsky, N.N. Narbekov, M.A. Bezborodova, O.A. Kozyreva, A.V. Novikov. Information-analytical, planning-prognostic, organizational-executive, control-diagnostic, regulatory-corrective stages of designing evaluation tools are presented. The content and planned results of the teacher&amp;rsquo;s activity are revealed in the course of designing evaluation tools for the psychological and pedagogical training of bachelors students in the profile &amp;ldquo;Primary education&amp;rdquo;. The prospects of the study are to determine the levels of formation of the competencies of the module of educational activity in future primary school teachers based on the creation of competency-oriented professional tasks.&lt;/p&gt;
Adaptive Propagation Network Based on Multi-scale Information Fusion

Graph Neural Networks (GNNs) have achieved remarkable success in many aspects, but they still suffer from certain limitations, such as over-smoothing with increasing layer depth, sensitivity to topological perturbations, and inability to be applied to heterophilic graphs. So this paper proposes a Multi-scale Information Fusion Adaptive Propagation Network (MAPNET) to overcome these limitations. First, a new graph data augmentation method is designed, which deletes unimportant edges and introduces KNN graphs to perturb the graph structure, and adds the graph regularization terms to improve the model’s robustness and generalization; second, a multi-scale information fusion adaptive propagation process is designed to enhance the diversity of neighborhoods to alleviate the over-smoothing problem; finally, the edge weights are extended to the negative values to adapt to the heterophilic graphs. Experimental results show that MAPNET partially solves the over-smoothing problem in GNNs. The model outperforms recent models in both semi-supervised and fully supervised node classification tasks on multiple datasets, and has better generalization performance and robustness.
Application of Data Encryption in Chinese Named Entity Recognition

Recently, with the continuous development of deep learning, there has been a significant improvement in the performance of named entity recognition tasks. However, privacy and confidentiality concerns in specific fields, such as biomedical and military, limit the availability of data for training deep neural networks. To address the issues of data leakage and the disclosure of sensitive data in these domains, we propose an encryption learning framework. For the first time, we employ multiple encryption algorithms to encrypt the training data in the named entity recognition task, training the deep neural network with the encrypted data. Our experiments, conducted on six Chinese datasets, including three self-constructed datasets, demonstrate that the encryption method achieves satisfactory results. In fact, the performance of some models trained with encrypted data even surpasses that of the unencrypted method, highlighting the effectiveness of the introduced encryption method and partially resolving the problem of data leakage.