Reviewerly/exHarmony huggingface dataset:
Research on Application of Artificial Intelligence Technology in Document Management System

With the continuous popularization of information technology, document management system function upgrade is imperative. This paper analyzes the basic flow of paper archives electronization, studies the basic method of restoring paper archives electronically by using OCR technology, analyzes the flow of document management, designs the framework of intelligent management system, and probes into the mode of using intelligent service of documents, in order to improve the quality and efficiency of document management.
Preparing students to study in distance education

In the modern world, distance education occupies an important place in the system of postgraduate and vocational education. Distance education provides favorable conditions for the implementation of a system of continuous vocational education, and provides an opportunity to acquire knowledge in the most convenient place for students. Distance education creates conditions for effective improvement of the level of their education, regardless of the age and social status of the student. In the form of distance learning, the most important conditions for effective functioning are to ensure an objective assessment of the quality of education, as well as preliminary training of students. A significant part of the study time with distance learning, students are engaged in independent work. This, in turn, requires high-quality educational and methodological literature adapted to distance learning and a high level of self-organization of students to carry out educational activities.
Theoretical foundations of students’ preparation for professional activity in higher educational institutions

The purpose of the article is to improve the quality and efficiency of education in the world, to pay special attention to the widespread use of pedagogical approaches in the processes of supporting students’ education, rapid changes in the socio-economic sphere, to eliminate the problems of improving the education system, and at the same time to identify the possibilities of using innovative technologies in education. The issues of forming the necessary professional competencies on the basis of building an innovative model of technological processes for training future personnel and improving the content as a result of applying didactic, experimental, model, didactic, methodological, and socio-psychological approaches were discussed.
Seamless Virtual Object Transitions: Enhancing User Experience in Cross-Device Augmented Reality Environments

The integration of augmented reality (AR) headsets and projector displays has the potential to enhance shared experiences in various fields. However, the seamless transition of virtual objects between these devices remains a challenge. In this paper, we present a combined cross-device system that evaluates user experience based on different virtual object transition methods during both passive and active interactions. We hypothesize that certain transition techniques may result in confusion, discomfort, or disorientation, while others can improve immersion and ease of use. Our study comprises a virtual zoo scenario, where participants observe and interact with virtual alpacas, providing insights into their experiences with the different transition methods. The results reveal the impact of the content type and size on transitions between devices. We explain how to minimize confusion and discomfort while maximizing immersion and ease of use. Based on our findings, we propose future research directions to further refine cross-device interaction techniques, with the goal of creating more immersive, accessible, and user-friendly experiences in diverse applications, such as education, entertainment, and professional settings.
Traceable and Privacy-Preserving Authentication Scheme for Energy Trading in V2G Networks

With the rapid popularization of electric vehicles (EVs) in modern society, vehicle-to-grid (V2G) has been widely concerned as an emerging technology. However, various privacy and security issues arise frequently in the energy interaction between EVs and the smart grid (SG), such as the lack of secure authentication and disclosure of EVs’ identity. Although many crypto-based schemes are proposed to achieve secure authentication of V2G networks, they rely on certification authority (CA) or private key generator (PKG). In response to this problem, some certificateless signature-based schemes have been proposed. Nevertheless, most of them are not suitable for V2G networks due to the high computational cost and communication overhead, and they do not consider the problem of tracking illegal signatures. Therefore, we propose a traceable and privacy-preserving authentication scheme with supporting batch verification for energy trading in V2G networks. We use the method of binary tree level traversal to quickly track EVs with illegal signatures, which can reduce computational resources. Besides, the proposed scheme is easier to be deployed in real world because of avoiding the problems of key escrow and certificate management. Finally, we conduct a comprehensive security analysis and performance evaluation regarding our scheme. We prove that our proposed scheme is secure under the random oracle model (ROM), and the experimental results illustrate that the proposed scheme has less computational cost and communication overhead as compared to the existing schemes.
Shallow Camera Pipeline for Night Photography Enhancement

Enhancing night photography images is a challenging task that requires advanced processing techniques. While CNN-based methods have shown promising results, their high computational requirements and limited interpretability can pose challenges. To address these limitations, we propose a camera pipeline for rendering visually pleasing photographs in low-light conditions. Our approach is characterized by a shallow structure, explainable steps, and a low parameter count, resulting in computationally efficient processing. We compared the proposed pipeline with recent CNN-based state-of-the-art approaches for low-light image enhancement, showing that our approach produces more aesthetically pleasing results. The psycho-visual comparisons conducted in this work show how our proposed solution is preferred with respect to the other methods (in about 44% of the cases our solution has been chosen, compared to only about 15% of the cases for the state-of-the-art best method).
Resource-efficient quantum key distribution with using integrated silicon photonics

We report a demonstration of resource-efficient chip-based BB84 QKD with a silicon-based encoder and decoder. The system enables realizing secure key distribution at a rate of 866 bps over a commercial fiber channel up to 150 km.
Reading Practices of Students in Media Communication System of 21st Century: ‘Book Enthusiasts’ and ‘Digital Adepts’

The article explores the reading practices of contemporary students in the context of the development of digital technologies. The authors interpret the results of sociological research conducted, which reveal students’ attitudes towards various reading practices in the midst of media transformations (surveys, focus groups, analysis of drabbles). The study investigates students’ attitudes towards reading (the value of reading and frequency of engagement), differentiating interests and factors influencing reading activity. The effectiveness of promoting and supporting reading in libraries, universities, the film industry, and opinion leaders is evaluated. The conclusion is drawn that there is no basis for a fundamental distinction between supporters of traditional (book enthusiasts) and digital (digital adepts) reading. Both are fully integrated into the traditional paper and digital book environment. Modern digital and visual communication technologies were found to be the most significant means of encouraging reading for both categories of respondents. The lines of digital inequality are primarily determined by the level of engagement in media communication and the ability to generate creative content. A predominantly passive position of respondents towards reading content online is observed. The conclusion is made about the gap between the declared, recognized, and implemented value of reading.
The Use of Geofencing in Android-Based Mobile Applications for Promotional Ads in Shopping Centers

This paper describes the implementation of geofencing technology in Android-based mobile applications for promotional advertisements based on the user's location. Geofencing is a location-based service that uses GPS, cellular networks, or Wi-Fi to create virtual geographic boundaries around specific locations. This technology enables businesses to send targeted advertisements to mobile users based on their current location. The paper presents the development of an Android-based mobile application that uses geofencing technology to provide location-based promotional advertisements to users. Researchers use one of the big shopping centers in Jakarta as a location object for geofencing technology. The application uses Google Maps and Firebase to create geofences around specific locations, and then sends push notifications to users within the geofenced areas. The implementation also includes a backend system to manage the promotional advertisements and user data. The results show that the implementation of geofencing technology in Android-based mobile applications can provide a more targeted and effective way to deliver promotional advertisements to users.
Research on the Development of On-Site Human Activity Recognition and Supervision Tools Based on Fuzzy Algorithms

This article is aimed at the limitations of human judgment in on-site supervision work for human behavior. It proposes a human activity recognition method based on fuzzy algorithms and develops a corresponding on-site supervision tool. Firstly, a comprehensive fuzzy evaluation model is established to fuzzify and accurately recognize human behavior. Subsequently, considering the on-site conditions and requirements, a portable on-site tool integrated with fuzzy algorithms is developed. This tool can monitor and identify human behavior in real-time, as well as provide auxiliary decision-making and data transmission functions, effectively improving the efficiency and accuracy of on-site supervision work. Finally, experimental results demonstrate that this method and tool exhibit high accuracy and practicality, and can be widely applied in various fields.
Hierarchical Federated Learning for Heterogeneous Features and Distributed Data in IoT Networks

Considering the heterogeneous compositions of Internet of Things (IoT) networks, this paper proposes a hierarchical federated learning (HiFL) framework to exploit both heterogeneous features and distributed data generated therein. In specific, the HiFL framework is a hierarchical architecture that leverages both vertical and horizontal federated learning. Clients that having local data of the same feature are grouped into the same cluster, naturally forming a party; otherwise, they are in different clusters. Parallel training of multiple clusters is handled by cluster heads (i.e., sub-servers), which operate in a horizontal federated learning manner to make use of data samples of the same feature distributed in clients within the same party. Then, a server collects and aggregates the results of parties to update the global model for a decreased training loss. We implement the HiFL system in a parameter server architecture and assess its performance via experiments using the NSL-KDD data set. We first discuss the local results of different parties that only use part of the features based on the analysis of feature importance. Then, we compare our system with fully centralized learning (which violates data locality) and learning based on only local features. Numerical results demonstrate that the proposed HiFL model outperforms the models based on local features, and approaches to the centralized model.
Stages of formation of environmental consciousness in the process of Civil and Patriotic education of students

The problems of patriotic education and civic formation of young people are the most urgent at the present stage of development of our society and need their comprehensive understanding and comprehensive solution. Therefore, the education system, including higher education, is designed to ensure the continuity of generations, the preservation and development of a sense of respect for the nature of the native land, the education of patriots of Russia both through the educational process and through various forms of extracurricular educational activities of an ecological nature. The work on attracting students to the environmental problem is an integral part of civic and patriotic education. The purpose of patriotic education is to create and root in society the foundations of patriotism as a value, as well as the formation and development of the most important socially significant personal qualities and the ability to manifest them in the creative process in the interests of society and the state.
GWO-BP-AdaBoost: Enhancing Classification Performance of BP Neural Networks Through GWO-Based Optimization and AdaBoost Integration

This paper proposes a method based on the Grey Wolf Optimizer (GWO) to automatically search and quickly determine the number of hidden nodes in a single-hidden-layer Back Propagation (BP) neural network, as well as the number of training iterations. This method aims to address the difficulties and suboptimal selection of the hidden layer node count and training iterations in BP neural network, which often lead to unstable predictive performance and unsatisfactory classification results. By optimizing the structure and training process of the BP neural network, the proposed approach enhances its classification capability. In addition, by employing the Adaptive Boosting (AdaBoost) algorithm to combine multiple weak classifiers, which are GWO-BP neural networks, a GWO-BP-AdaBoost strong classifier model is constructed to further enhance the classification performance of the BP neural network. Experimental results demonstrate that the classification ability of the BP neural network is enhanced through optimization using the GWO algorithm. Moreover, the subsequently established GWO-BP-AdaBoost classification model exhibits further improvement in classification ability compared to the GWO-BP neural network. The GWO-BP- AdaBoost classification model effectively classifies the dataset with high accuracy and excellent classification performance.
Blockchain-Based Applications for Disrupting and Accelerating Innovation in Organizations and Society

Blockchain-based applications are already being used for countless applications that support new goals in organizations and society at large. In this chapter, the authors will survey existing blockchain-based applications according to four quadrants: economic; social; environmental; and governmental/organizational transparency. The chapter also details several cases, spanning one or more of the identified quadrants, namely solutions for food products traceability, sustainability and circular economy, product dematerialization (NFTs and Digital Twins), cryptocurrencies, and others.
Aggregating Data

Databases store data. That’s obvious, but the data itself is pretty inert—you save it, you retrieve it, and you sometimes change it. That’s OK for some things, but sometimes you want the data to work a little harder.
Permodelan Sistem Penjualan Mobil Bekas Menggunakan Web Engineering

The main purpose of this study is to improve accessibility and convenience for potential buyers in finding, comparing, and buying used cars. This application should be designed with an intuitive and responsive user interface, so that users can make transactions easily using web engineering methods. Based on the results of the recapitulation of the 7 test criteria that have been carried out, the results of the number of answers from respondents are obtained which have a value of 100% in accordance with testing the functionality of the system using blackbox testing.
RingSFL: An Adaptive Federated Learning System for Heterogeneous Clients

Federated learning (FL) has the ability to protect user privacy during cooperative training. However, vanilla FL lacks adaptation to heterogeneous clients and suffers from privacy leakage. This proposal demonstrates the prototype system of RingSFL, which integrates FL with a model split mechanism for client heterogeneity and data privacy preservation. RingSFL forms a ring topology among clients. Instead of local training, the model is split and trained across clients in a pre-defined direction. By properly setting the propagation lengths, the training efficiency is significantly enhanced. Additionally, since the local models are blended, the privacy risks is mitigated.
Cryptocurrency mining with quantum computers

We devised a quantum-computer compatible proof-of-work cryptographic algorithm and verified it on superconducting quantum processors. The algorithm enables a noticeable speedup when executed on quantum hardware while it is still verifiable on classical computers.
Characterization of the Polarization Fluctuations in Gain-Switched Vertical-Cavity Surface-Emitting Lasers for Quantum Random-Number Generation

We characterize a quantum random number generator based on the excitation of the linearly polarized modes of a gain-switched vertical-cavity surface-emitting laser. We find good agreement between our experiments and simulations.
Penerapan Extreme Programming Pada Sistem Informasi Keuangan Sekolah Berbasis Website

The results of interviews and observations conducted with schools every financial activity such as making budget plans, making financial reports, recording expenditure data in schools still uses the Microsoft Excel application. Based on these problems, a system is needed that can overcome problems in school financial recording using extreme programming methods. Extreme Programming (XP) is an approach or software development model that tries to simplify the various stages in the development process so that it becomes more adaptive and flexible. This goal is to produce a School Financial Information System with the Extreme Programming method. The overall result of technology acceptance model (TAM) testing for information system success amounted to 96.67% with criteria that are very good for the application of school financial information system design.
PERFIL CLÍNICO DE PACIENTES INSERIDOS EM UM PROGRAMA DE REABILITAÇÃO PÓS-COVID-19

Introduction: After the incubation period of the SARS-CoV-2 virus, which causes Covid-19, some symptoms may last for months or years, such as respiratory and peripheral muscle weakness. Objectives: To seek and identify the profile of individuals who were affected by Covid-19 and who had complications and a decrease in their lung and functional capacities, quality of life and peripheral muscle strength, after hospital discharge or home isolation. Methodology: Individuals who contracted Covid-19 and who sought the Extension Project Physical Therapy Assistance to Post-Covid-19 Patients participated in the study. Assessment data were collected using tests, questionnaires and scales. Results: The profile of 30 individuals was identified, who had mild, moderate and severe cases. In addition to the collected comorbidities, fatigue was the predominant symptom in this population. Conclusion: Participants showed changes in aspects related to quality of life, in addition to changes in sleep, fatigue, breathing capacity and handgrip strength.
Research on the Application of Mobile Internet Education Ecosystem in Teaching

With the in-depth development of "Internet plus", the shortcomings and deficiencies in the traditional education and teaching model have become increasingly prominent, which has been unable to meet the requirements of teachers and students for real-time, continuity and convenience of knowledge teaching and learning in the new era. In this context, the application of mobile Internet technology in education and teaching has become increasingly popular, and education and teaching began to be free from the constraints of teaching time and space. The mobile internet education ecosystem has emerged. The main purpose of this article is to study the application of the mobile internet education ecosystem in teaching. Firstly, it elaborates on the connotation and application advantages of the mobile internet education ecosystem, and then points out the path to build a mobile internet education ecosystem. By fully utilizing the convenience of the network and fragmented teaching practices, students can supplement and learn knowledge anytime and anywhere.
Improvement of Presence in Live Music Videos and Alleviation of Discomfort of Viewers by Zooming Operation

People can enjoy watching live performances without visiting live venues thanks to the development of live music streaming services on the Internet. However, such live music videos, especially those recorded by amateur band members, lack a sense of presence. Therefore, in the previous study, the authors proposed a method to improve the sense of presence in live music videos by performing zooming on the video frames. It achieved enhancing the sense of presence. However, it also increased the discomfort of the viewers. This is because the zooming was performed not on a music performer but in the center of the screen, resulting in an unnatural experience for the viewer. Therefore, in this paper, a new zooming method, which effectively emphasizes the music performer with intense movement, is proposed, introducing the concept of the “Main Spot”. The evaluation results through an experiment verified that the proposed method improved the sense of presence in live music videos and alleviated the discomfort of the viewers.
Solar Radiation and Weather Analysis of Meteorological Satellite Data by Tensor Decomposition

In this study, the data obtained from meteorological satellites were analyzed using tensor decomposition. The data used in this paper are meteorological image data observed by the Himawari-8 satellite and solar radiation data generated from Himawari Standard Data. First, we applied Higher-Order Singular Value Decomposition (HOSVD), a type of tensor decomposition, to the original image data and analyzed the features of the data, called the core tensor, obtained from the decomposition. As a result, it was found that the maximum value of the core tensor element is related to the cloud cover in the observed area. We then applied Multidimensional Principal Component Analysis (MPCA), an extension of principal component analysis computed using HOSVD, to the solar radiation data and analyzed the Principal Components (PC) obtained from MPCA. We also found that the PC with the highest contribution rate is related to the solar radiation in the entire observation area. The resulting PC score was compared to actual weather data. From the result, it was confirmed that the temporal transition of the amount of solar radiation in this area can be expressed almost correctly by using the PC score.