Reviewerly/exHarmony huggingface dataset:
Research on chaotic features of a flow field over a plunging airfoil based on dynamic mode decomposition

Periodic motion of a plunging airfoil causes continuous changes in the surrounding flow field.The time-dependent thrust coefficient depends entirely on unsteady characteristics of the flow field.On the contrary, the time-dependent thrust coefficient may also reflect the unsteady characteristics of the corresponding flow field.With the fast Fourier transform (FFT) and dynamic mode decomposition (DMD), unsteady aerodynamic forces can be correlated with the flow field characteristics in the frequency domain.In the present paper, DMD is performed to analyze the unsteady characteristics of the flow field around a plunging NACA0012 airfoil at the Reynolds number of 20 000.
Development of electronic digital signature algorithms with compound modules and their cryptanalysis

This article proposes options of electronic digital signature algorithms, the cryptographic strength of which is based on the complexity of computing a discrete logarithm in a finite field and the complexity of solving a problem of decomposing a sufficiently large odd number to prime factors, on the hash function used, as well as their cryptanalysis.Unlike existing electronic digital signature algorithms (RSA, El-Gamal) in the proposed new electronic digital signature algorithm signature generation process – s, is carried out using a private parameter - ϕ(N).
Research on Key Technologies of Industrial Internet Data Security

Abstract At present, industrial Internet data is facing a severe security situation in storage, transmission, and use. This paper proposes data security management and security protection strategies by studying the data security risks and status quo of industrial Internet platforms. Among them, the security management strategy includes data classification and classification, data security assessment and data security threat emergency management. The security protection strategy deploys industrial data security protection from the technical aspects of collection, storage, transmission, processing, sharing, and deletion, providing a reference for further strengthening the industrial Internet data security.
Machine extraction of polymer data from tables using XML versions of scientific articles

In this study, we examined machine extraction of polymer data from tables in scientific articles. The extraction system consists of five processes: table extraction, data formatting, polymer name recognition, property specifier identification, and data extraction. Tables were first extracted in plain text. XML versions of scientific articles were used, and the tabular forms were accurately extracted, even for complicated tables, such as multi-column, multi-row, and merged tables. Polymer name recognition was performed using a named entity recognizer created by deep neural network learning of polymer names. The preparation cost of the training data was reduced using a rule-based algorithm. The target polymer properties in this study were glass transition temperature (Tg), melting temperature (Tm), and decomposition temperature (Td), and the specifiers were identified using partial string matching. Through these five processes, 2,181 data points for Tg, 1,526 for Tm, and 2,316 for Td were extracted from approximately 18,000 scientific articles published by Elsevier. Nearly half of them were extracted from complicated tables. The F-scores for the extraction were 0.871, 0.870, and 0.841, respectively. These results indicate that the extraction system created in this study can rapidly and accurately collect large amounts of polymer data from tables in scientific literature.
Evolved auxiliary controller with applications to aerospace

Purpose To guarantee the asymptotic stability of discrete-time nonlinear systems, this paper aims to propose an evolved bat algorithm fuzzy neural network (NN) controller algorithm. Design/methodology/approach In evolved fuzzy NN modeling, the NN model and linear differential inclusion representation are established for the arbitrary nonlinear dynamics. The control problems of the Fisher equation and a temperature cooling fin for high-speed aerospace vehicles will be described and demonstrated. The signal auxiliary controlled system is represented for the nonlinear parabolic partial differential equation (PDE) systems and the criterion of stability is derived via the Lyapunov function in terms of linear matrix inequalities. Findings This representation is constructed by sector nonlinearity, which converts the nonlinear model to a multiple rule base for the linear model and a new sufficient condition to guarantee the asymptotic stability. Originality/value This study also injects high frequency as an auxiliary and the control performance to stabilize the nonlinear high-speed aerospace vehicle system.
Consecutive Missing Data Recovery Method Based on Long-Short Term Memory Network

This paper describes a consecutive missing data recovery method based on long-short term memory (LSTM) network. The supposed method is fully data-driven and does not depend on system topology and parameters. It exploits the deep learning technique to address missing phasor measurement unit (PMU) data, utilizing the characteristics of LSTM suitable for processing and predicting time series. Simulation results show that, under various PMU missing conditions, the proposed method can maintain a competitively high accuracy.
The Interaction Between Perceived Risk, Attitude, and Intention to Use: An Empirical Study on Bitcoin as a Crypto Currency

Introduction: As internet and communication technologies are getting developed, the commercial transaction is becoming more electronic. This change also brings new approaches to new payment mechanisms like emergence of crypto currencies. They are virtual and digital currencies which can only be used in electronic environment but they are increasingly treated as a new payment and investment tool. Nevertheless, their use has not spread into the general public, yet. At this point, it will better to take the complex nature of the crypto currencies into consideration because it may still lead to some risks for people and the type of the risks perceived by consumers may influence their attitudes toward and intention to use crypto currencies.Aim: Accordingly, this study attempts to examine the interaction between perceived risk, attitudes toward and intention to use crypto currencies within the context of Bitcoin, as the first crypto currency.Method: This study was designed as a causal research. The sample of the study was reached by using convenience sampling method and data were collected with survey. The compiled data were tested with Structural Equation Model.Findings: A statistically significant and negative relationship was found between perceived financial, time and psychological risk and attitudes toward the use of Bitcoin, and a statistically significant and positive relationship was found between attitudes toward and intention to use Bitcoin. The findings of the study are expected to contribute to both relevant literature and practice by explaining the financial behavior of the individuals within the context of perceived risk theory.
The effects of cognitive load on query reformulation: mental demand, temporal demand and frustration

Purpose This study explores the effects of cognitive load on the propensity to reformulate queries during information seeking on the web. Design/methodology/approach This study employs an experimental design to analyze the effect of manipulations of cognitive load on the propensity for query reformulation between experimental and control groups. In total, three affective components that contribute to cognitive load were manipulated: mental demand, temporal demand and frustration. Findings A significant difference in the propensity of query reformulation behavior was found between searchers exposed to cognitive load manipulations and searchers who were not exposed. Those exposed to cognitive load manipulations made half as many search query reformulations as searchers not exposed. Furthermore, the National Aeronautical and Space Administration Task Load Index (NASA-TLX) cognitive load scores of searchers who were exposed to the three cognitive load manipulations were higher than those of searchers who were not exposed indicating that the manipulation was effective. Query reformulation behavior did not differ across task types. Originality/value The findings suggest that a dual-task method and NASA-TLX assessment serve as good indicators of cognitive load. Because the findings show that cognitive load hinders a searcher's interaction with information search tools, this study provides empirical support for reducing cognitive load when designing information systems or user interfaces.
Blockchain and its Application in Non-Fungible Tokens

Blockchain has always been considered as the solution to almost every problem that our world experiences in any form of transaction, one of its booming applications is non-fungible tokens. With increasing use of cryptocurrencies, and new assets that one can buy using it, non-fungible tokens are in the buzz, and through this journal we are trying to help people and upcoming generations understand non-fungible tokens and the variety of areas in which it can be used.
Medical image security authentication method based on wavelet reconstruction and fractal dimension

In this article, based on wavelet reconstruction and fractal dimension, a medical image authentication method is implemented. According to the local and global methods, the regularity of the mutation structure in the carrier information is analyzed through a measurement defined in the medical image transformation domain. To eliminate the redundancy of the reconstructed data, the fractal dimension is used to reduce the attributes of the reconstructed wavelet coefficients. According to the singularity of the fractal dimension of the block information, the key features are extracted and the fractal feature is constructed as the authentication feature of the images. The experimental results show that the authentication scheme has good robustness against attacks, such as JPEG compression, multiplicative noise, salt and pepper noise, Gaussian noise, image rotation, scaling attack, sharpening, clipping attack, median filtering, contrast enhancement, and brightness enhancement.
Workload classification in multi-vm cloud environment using deep neural network model

In this competitive world, everyone needs to be prepared for future risks and emergency conditions. In a multi-cloud environment users can easily shift from one cloud to another cloud because of the available data and application transfer technologies. Therefore a strong forecast system is mandatory for such conditions and to stop user migration to other clouds. Virtual Machine (VM) plays an important role in effective resource management and cost reduction in cloud infrastructure. Workload prediction in multi-VM is very useful to handle uncertain situations. In this paper, we propose a promising workload prediction technique that can handle the workload from multiple virtual machines. It has a pre-processing and feature selection engine that handles direct data from these virtual machines and the model is strong enough in classifying data based on historical workloads. This classification enables extra knowledge for the cloud vendor to optimize resource usage. This strategy can be used for producing an alarm whenever there is continuously high utilization of resources in the future. Here, our prediction methodology is experimented with a popular real-world Grid Workload Archive (GWA) dataset and it achieves more than 85% prediction accuracy for CPU, Memory and Disk Utilization.
Effects of a handlebar on standing VR locomotion

To provide a natural locomotion for a virtual supermarket in a cognitive rehabilitation application we compare three walk in place (WIP) approaches (WIP; WIP + Bar for stability support; WIP + Bar for steering and stability support). We use tracked knee bending with and without a handlebar as a real correspondent to a virtual handlebar of a virtual shopping cart. For steering we use shoulder or handlebar rotation. We present an evaluation of the influence of the physical handlebar as a fixed reference and postural stability aid on cybersickness and user satisfaction. Our preliminary results indicate advantages for steering via a handlebar. Unexpectedly, a bar for postural stability seems to increase cybersickness but still improve user satisfaction compared to WIP only.
Combination RSA with One Time Pad for Enhanced Scheme of Two-Factor Authentication

RSA is a popular asymmetric key algorithm with two keys scheme, a public key for encryption and private key for decryption. RSA has weaknesses in encryption and decryption of data, including slow in the process of encryption and decryption because it uses a lot of number generation. The reason is RSA algorithm can work well and is resistant to attacks such as brute force and statistical attacks. in this paper, it aims to strengthen the scheme by combining RSA with the One Time Pad algorithm so that it will bring up a new design to be used to enhance security on two-factor authentication. Contribution in this paper is to find a new scheme algorithm for an enhanced scheme of RSA. One Time Pad and RSA can combine as well.
Exploring BERT for Aspect Extraction in Portuguese Language

Sentiment Analysis is the computer science field that comprises techniques that aim to automatically extract opinions from texts. Usually, these techniques assign a Sentiment Orientation to the whole document (Document Level Sentiment Analysis). But a document can express sentiment about several aspects of an entity. Methods that extract those aspects, paired with the sentiment about them, operate in the Aspect Level. Aspect-Based Sentiment Analysis approaches can be split into two stages: Aspect Extraction and Aspect Sentiment Classification. The literature presents works mainly focused on reviews about hotels, smartphones, or restaurants. In this work, we present an approach for Aspect Extraction based on Multilingual (Google's) and Portuguese (BERTimbau) BERT pre-trained models. Our experiments show that Aspect Extraction based on BERT pre-trained for Portuguese achieved Balanced Accuracy of up to 93% on a corpus of reviews about the accommodation sector.
Inspiring healthy Food Choices in a Virtual Reality Supermarket by adding a tangible Dimension in the Form of an Augmented Virtuality Smartphone

We want to understand the changing shopping behaviour, influenced by health-targeting nutrition apps on mobile devices. To achieve that, we have built a realistic Virtual Reality (VR) supermarket simulation and addressed core aspects such as handling virtual products, prevention of cybersickness, rounded off with an initial pilot study. On top of that, we built a virtual replica smartphone in VR with nutritionrelated functionality. This has been extended with an Augmented Virtuality (AV) feature, that enables us to track the screen of a participant's own smartphone, hence allowing us to integrate real-world apps and letting the user interact with them during the simulation. To achieve a high-quality tracking, we propose a hybrid approach, utilizing an add-on RGB camera on the VR headset fused with data provided through a WLAN connection in the case of self-made apps. This enables the users to manipulate the simulation from within the smartphone app, introducing a versatile, highly usability-centered controller because they can handle their phone naturally.
Agent-Based Path Prediction Strategy (ABPP) for Navigation Over Dynamic Environment

Probabilistic path planning is major problem in the field of navigation and can be solved by using various navigational methods or technique. Many researchers have designed, developed and implemented the same to solve the mentioned problem. These implemented methods is categorized into classical approaches such as road map technique (RM), Cluster decomposition (CD) and artificial potential field (APF), and inspired approach such as Fuzzy logic (FL), particle swarm optimization (PSO), genetic algorithm (GA), Artificial neural network (ANN), etc. are invented. The selection of path planning algorithm is mostly depends upon the type of environment for which the path has to be generated. This environment is classified as static and dynamic. While considering the environment, all the characteristics related to the environment should be considered. Although the static environment has very less parameters to be considered while implementing the path planning algorithm, in the dynamic environment we need to consider the frames of static environment over the time series to get the best result. In this paper, we proposed an algorithm to predict the path over dynamic environment by considering the future position of the entire obstacle roaming in the environment. The proposed algorithm is based on Agent-based prediction function which will help the algorithm to generate time series obstacle position which in turn will help to generate the probabilistic path over the dynamic environment. We have also shown the probabilistic path generated with the help of mentioned algorithm along with time and path length results generated.
A robust watermark algorithm for copyright protection by using 5-level DWT and two logos

&lt;span&gt;Recent growth and development of internet and multimedia technologies have made it significant to upload data; however, in this situation, the protection of intellectual property rights has become a critical issue. Digital media, including videos, audios, and images are readily distributed, reproduced, and manipulated over these networks that will be lost copyright. Also, the development of various data manipulation tools like PDF converter and Photoshop Editor has resulted in digital data copyright issues. So, a digital watermarking technique has emerged as an efficient technique of protecting intellectual property rights by providing digital data copyright authentication and protection. In this technique, a watermarked document was integrated into electronic data to prevent unauthorized access. In this paper, A robust watermark algorithm based on a 5-level DWT and Two Log was proposed to enhance the copyright protection of images in unsecured media. Our lab results validate that our algorithm scheme is robust and forceful against several sets of attacks, and high quality watermarked image was achieved, where the algorithm was assessed by computation of many evaluation metrics such as PSNR, SNR, MAE, and RMSE.&lt;/span&gt;
The Technology of Military Knowledge Graph Construction Based on Multiple Open Data Sources

In the process of military informatization, there is data isolation, lack of associated organizations, and the problem that data is difficult to use effectively. To solve the above problems, a military knowledge graph construction technology based on open source and multiple data is proposed. Firstly, the military application advantages of knowledge graph are analyzed. Then, based on the internet multi-source data, the military knowledge graph is constructed, and the key process of constructing the military knowledge graph is described in detail. Finally, the knowledge graph construction process is completed. The key technologies in the paper are briefly introduced to provide reference for the application of knowledge graph technology in the military field. Keywords open data; knowledge graph; data fusio; graph construction.
A novel error correction protocol for continuous variable quantum key distribution

Reconciliation is a key element of continuous-variable quantum key distribution (CV-QKD) protocols, affecting both the complexity and performance of the entire system. During the reconciliation protocol, error correction is typically performed using low-density parity-check (LDPC) codes with a single decoding attempt. In this paper, we propose a modification to a conventional reconciliation protocol used in four-state protocol CV-QKD systems called the multiple decoding attempts (MDA) protocol. MDA uses multiple decoding attempts with LDPC codes, each attempt having fewer decoding iteration than the conventional protocol. Between each decoding attempt we propose to reveal information bits, which effectively lowers the code rate. MDA is shown to outperform the conventional protocol in regards to the secret key rate (SKR). A 10% decrease in frame error rate and an 8.5% increase in SKR are reported in this paper. A simple early termination for the LDPC decoder is also proposed and implemented. With early termination, MDA has decoding complexity similar to the conventional protocol while having an improved SKR.
Digital Twin as A Mixed Reality Platform for Art Exhibition Curation

We present a digital twin-based Mixed Reality platform for arts curators. Despite the rising presence of exhibitions in varying digital formats, the virtual engagement of arts curators has been nearly disabled. To replicate and enhance the professional capability of arts curators in the virtual realm, our system integrates a digital twin art space and 3D authoring techniques, aided with spatial and semantic metadata. Our user evaluation proves the system's usability, and its capacity to support curatorial activities. With this, we aim to provide a groundwork to similar systems that also extend arts curator's creativity and outreach beyond time and space.
Barriers of teacher training in the implementation of distance learning technologies in modern education

The article is devoted to the problems of using distance educational technologies, which are barriers in the educational process. The authors investigate the possibilities of taking into account the technical features of the functioning of distance learning technologies and e-learning in the legislation, as well the conditions and problems of using distance learning technologies and e-learning in the educational process. The relevance of the problem is in improving the training of teachers for professional activities in the context of modern tendency in the informatization of education. Professional training is based on the inclusion of innovative activities in the educational process of a pedagogical university aimed at organizing creative informational interaction of students and teachers in the process of mastering e-learning technologies. In accordance with the new amendments in the Federal Law “About Education” the problem of including distance educational technologies in schools actualizes. In the article the directions of teachers’ professional training for distance learning are defined, the main forms of teachers' professional training in the field of distance educational technologies at the stage of training at a pedagogical university and advanced training are listed as well. But there are barriers that impede the use of distance learning technologies and e-learning in the educational process. The difference between distance educational technologies and electronic education is whether there is a direct cooperation between the teacher and the student or not. If it is carried out and with using information technology, technical means, we are talking about e-learning. If the interaction is mediated - through the Internet, then this is distance learning. An educational organization has the right to use one or both forms of educational program implementation. It is important to prepare future teachers for the use of distance learning technologies in professional activities in the global process of informatization and digitalization of education.