Reviewerly/exHarmony huggingface dataset:
PENGARUH MULTIMEDIA PEMBELAJARAN MATEMATIKA BERBASIS GOOGLE SITES TERHADAP MOTIVASI BELAJAR

In this study, researchers used Pre-Experimental Design with the form of One Group Pretest-Posttest Design. the sample in this study were 32 students of class XI TITL at SMK Negeri 2 Pontianak. the data collection technique in this study was an indirect communication technique using a questionnaire. The learning motivation of students who do not use multimedia martematics learning based on google sites has an average percentage of 71% (high). The learning motivation of students who use multimedia learning martematics based on google sites has an average percentage of 82% (very high). The effect of using multimedia learning martematics based on google sites on the learning motivation of class XI students at SMK Negeri 2 Pontianak is evidenced by the results of the Wilcoxon test whose probability value or Sig. 2 tailed of 0.000 &lt;0.05 and an effect size value of 1.021 which shows an increase in learning motivation in the large category. Thus it can be concluded that the use of multimedia learning martematics based on google sites has a major effect on student learning motivation.
TERMINOLOGY OF MODERN MACHINE TRANSLATION THEORY

The article examines the terms that are most commonly used to describe machine translation. All the terms presented in this article are used in scientific and journalistic works depending on the process of producing a translation. The main factor is the participation of a human translator in the process. The article is focused on the terms used in Ukrainian and English terminology. Modern computer and linguistic terminology have no general term to describe machine translation as a phenomenon and this problem is partly related to the systems that generate it. The twenty-first century has witnessed a rapid development of computer technologies, including the spread of the Internet, which has led to the emergence of new interdisciplinary and applied fields of science, such as computer linguistics and a new field in translation studies which is related to machine translation. Machine translation was firstly done on computers that were not so multifunctional as modern computers. Nowadays machine translation applications such as Google Translate, SYSTRAN, DeepL Translate have been developed and are now available to everyone – to translators and to people of any other specialization and profession. Despite the rapid development of translation studies and computer technology, the terminological problem of machine translation theory has been ongoing since the beginning. Both Ukrainian and English terminology use one of the presented in this article terms as a general term. For example, Ukrainian terminology most commonly uses the term machine translation while English terminology uses the term computer-aided translation as a general term. The problem is that it depends on the researcher and on the century or decade when a specific term was used. No term mentioned in this article is regarded as wrong or unusable, specifically if it describes human translator involvement in the process. The developing process of translation studies and computer technologies is ongoing so is the terminology. The article pays attention to all the terms, both in Ukrainian and English, and gives information about the establishing process of machine translation terminology, which shows the use of a particular term nowadays, and establishes the links between modern terminology of machine translation and the development process of the terms since the beginning. The aim of this article is to analyze all possible options and propose a general term to be used in Ukrainian language for machine translation as a phenomenon. Analyzing terms that are commonly used in parallel to refer to machine translation itself and the systems that generate it will help to determine which one is best to use in scientific research.
Vivaldi Violin Concerto "Four Seasons" -- Spring music analysis

Vivaldi is an important composer and outstanding violinist of the Baroque period. The violin concerto "The Four Seasons" is one of his most famous works. This paper makes a detailed analysis of the first theme of "Four Seasons" in "Spring", leading readers to stay in the green spring and feel the relaxed and happy melody of music.
Eksperimental'noe issledovanie prototipa sverkhprovodyashchego sigma-neyrona dlya adiabaticheskikh neyronnykh setey

The artificial neuron proposed earlier for use in superconducting neural networks is experimentally studied. The fabricated sample is a single-junction interferometer, part of the circuit of which is shunted by an additional inductance, which is also used to generate an output signal. A technological process has been developed and tested to fabricate a neuron in the form of a multilayer thin-film structure over a thick superconducting screen. The transfer function of the fabricated sample, which contains sigmoid and linear components, is experimentally measured. A theoretical model is developed to describe the relation between input and output signals in a practical superconducting neuron. The derived equations are shown to approximate experimental curves at a high level of accuracy. The linear component of the transfer function is shown to be related to the direct transmission of an input signal to a measuring circuit. Possible ways for improving the design of the sigma neuron are considered.
A Trusted Execution Environment Architecture for Big Data Computing Platform Based on TPCM

This paper proposes a method for implementing a trusted execution environment for a computing platform based on Trusted Platform Control Module (TPCM). The method is based on a dual-architecture, which maintains the original design of the device and introduces TPCM as root of trust to measure the trustworthiness of the platform's execution environment. With the integration of control implementation, this method can fundamentally address the issue of untrustworthiness in the platform's execution environment. By ensuring the trustworthiness and integrity of the boot environment, the method dynamically checks and confirms the boot and execution environment in real-time through the implanted TPCM trusted agent, ultimately achieving a full lifecycle trustworthy measurement and protection of the execution environment for big data computing platforms.
Physical Layer Authentication Based on Transformer

With the rapid proliferation of wireless devices, effectively authenticating legitimate users has become a pivotal challenge in wireless communication. Amongst various approaches, physical layer authentication technology based on deep learning has garnered substantial attention from numerous researchers. In this paper, we propose a scheme for implementing physical layer authentication based on the Swin Transformer, utilizing Channel State Information (CSI) to distinguish between legitimate and illegitimate nodes in industrial network systems. In contrast to traditional physical layer authentication methods based on thresholds, the method proposed in this paper eschews the use of thresholds to achieve authentication. Moreover, compared to other methods based on deep neural networks, the introduction of attention mechanisms enables superior learning of wireless channel state features, enhancing model accuracy and reducing computational complexity. The efficacy of this scheme is validated through channel probing results in typical industrial wireless environments provided by the National Institute of Standards and Technology (NIST), which will facilitate the application of deep learning technology to industrial wireless network systems to enhance their security.
Multi-UAVs Cooperative Target Search with Communication Constraint

This paper studies the problem of multi-unmanned aerial vejicles (multi-UAVs) cooperative search under communication constraints. We propose a distributed collaborative search method. In this method, we bulid target probability map for each UAV, and update the maps according to the Bayesian formula and the consensus algorithm. Based on the Shannon entropy and the target probability map, we design the objective function to guide UAVs fly to unexplored areas while keep the consistence of the communication network. Every UAV act as an independent agent, uses distributed model predictive control (DMPC) algorithm and particle swarm optimization (PSO) algorithm to achieve the trajectory optimazation. Finally, we made several simulation experiments to verify the feasibility of our method.
A Privacy Protecting Mechanism in UAV-MEC Network with Blockchain-Enabled Federated Learning

The UAV (unmanned aerial vehicles) network is a promising solution to support real-time applications and services. However, local UAV nodes are prone to privacy disclosure, and base station edge nodes are difficult to effectively identify trusted local UAV nodes and resist malicious attacks. To address the privacy concern, we propose the adaptive nonlinear privacy protection to preserve model gradient in the federated learning training process, overcoming the drawbacks associated with empirically selecting DP(Differential privacy) parameters. Through the model accuracy analysis, it can be seen that the proposed algorithm achieves higher accuracy in privacy protection using adaptive layered contribution factor compared with the privacy protection method based on DP.Experiments show that the proposed algorithm can effectively protect the privacy and security of UAV gradient, and achieve higher accuracy. Under the conditions of 10%, 20% and 30% pollution ratio of data sets, the experiment shows that the proposed algorithm still has strong anti-data poisoning attack ability.
Automated Neural Network Structure Design for Efficient

The creation of suitable and efficient tools for anomaly detection constitutes a crucial aspect of security, applicable not only to industrial networks but also to cyber-physical systems. This article elucidates a framework designed to automate the selection of an optimal deep neural network architecture, thereby expediting the creation and implementation of neural network-based tools. The framework presented here enables a rapid design of an Artificial Neural Network structure without necessitating user intervention. Its efficacy has been showcased through experimentation with the publicly accessible HAI dataset, yielding an accuracy of approximately 0.94 after 10 epochs. Subsequently, a second scenario was performed where a total of 5456 models were generated and trained, with an average time of approximately 9.95 seconds per model.
A Continuous Authentication Scheme for Digital Therapeutics Using Denoising Autoencoder

In healthcare, digital therapeutics provides users with better services in terms of preventing, managing and treating diseases. However, it is a non-trivial task to ensure the security of digital therapeutics. In some scenarios, for example, the wearable biosensors might be used by others or violated by malicious adversaries. When these happen, the patient's treatment might be affected. Investigation shows that conventional one-time login authentication mechanism cannot solve the above problems. Motivated by these observations, in this paper we present a continuous authentication scheme for digital therapeutics using denoising autoencoder. Specifically, it achieves user-transparent re-authentication when users wear the wearable devices. To improve the re-authentication rate, the denoising autoencoder is employed to learn gait features using three-axis acceleration data. To illustrate the practicality, we evaluate the performance of our scheme using public datasets and compare it with that of relevant schemes. The results show that the re-authentication rate of our scheme reaches 92.8%, and it works well no matter users' activities (walking, sitting, running and/or jumping, etc).
Optimization of the random number generator based on InGaAs pi-n photodiode in a homodyne scheme using discrete wavelet analysis

An approach is proposed to optimize the operation of a random number generator based on discrete wavelet analysis. It is shown that controlling the contribution of the scale components of the wavelet transform to the signal can increase the degree of randomness of the generated series of numbers.
The Influence of Workload, Knowledge, Motivation on Medical Record Quality Through Doctor Compliance

Background. Medical records are records and documents containing the patient's identity, examination, treatment, actions and other services that have been provided to patients. Medical records are said to be of high quality if the data and information are complete and can be read by those entitled to it from time to time as a continuous communication tool. Objective: The study aimed to analyze the effect of workload, knowledge and motivation through doctor compliance that can improve the medical record quality. Method: This study uses a quantitative approach with a causal design research using SPSS-Path Analysis. Result: There was no effect of workload on the quality of medical records through doctor's compliance, there was an influence of knowledge on the quality of medical records through doctor's compliance and there was an influence of motivation on the quality of medical records through doctor's compliance. Implication: This study proves that the amount of doctor's compliance is able to mediate the effect of knowledge and motivation which can improve the quality of medical records. Hospital management is expected to be able to motivate doctors to understand changes in the current digitalization era and to improve the level of awareness of doctors to work in an orderly administration.&#x0D; &#x0D; &#x0D; Keywords: Compliance, Knowledge, Medical Record Quality, Motivation, Workload
Intelligent fertigation, pillar of sustainable agriculture

&lt;p&gt;The growing demand for food in the country has required an increase in agricultural production levels and, with it, an increase in irrigation systems. Among the most widespread are central pivot irrigation systems, but their large number and variety make their optimal configuration difficult, generating overexploitation of natural resources such as water and threatening the sustainability of agriculture and the country. For this reason, the objective of this research was to implement software that would allow obtaining the appropriate configuration of this equipment using information on the type of crop, the agro-climatic conditions of the region, and the soil in order to obtain maximum utilization. As a result, an application capable of performing the calculations so that the value of water delivered by the system is closer to the estimated needs for a crop in each of its phases was achieved. To demonstrate this, an experimental study was carried out in field conditions in the agricultural enterprise La Cuba in Ciego de Avila; it showed that, with the use of the software, there was a saving of up to 94.5% of the water previously misused. In addition, the level of liquid provided allows the sowing to be in better conditions to reach its optimum yield. As an added value, the software has a minimalist and intuitive interface, which allows real-time visualization of field information.&lt;/p&gt;
Pseudobrookite from Active Fumaroles of the Tolbachik Volcanic Massif (Kamchatka). Chemistry of Pseudobrookite-Group Minerals and Its Indicator Role

For the first time there is characterized pseudobrookite from deposits of active volcanic fumaroles Arsenatnaya and Yadovitaya of the Tolbachik volcanic massif (Kamchatka). Chemical composition of pseudobrookite-group minerals and isomorphism in these oxides of different origin were studied on the base of 203 analyses (literature data and original analyses of 40 samples) from 44 localities. It is shown that at the near-surface levels pseudobrookite crystallized mainly with composition chemically close to the end-member Fe\(_{2}^{{3 + }}\)TiO5. It is known that lunar rocks contain only minerals of the “ferropseudobrookite” Fe2+Ti2O5 ‒ armalcolite MgTi2O5 series characterized by an intermediate value of the Fe2+:Mg-ratio, the highest Ti content and the absence of Fe3+. Impact minerals and there technogenic analogues are chemically close to Fe2+Ti2O5. Pseudobrookite from Tolbachik fumaroles is characterized by the high Al content (up to 7.1 wt % Al2O3), a stable level of Cu (up to 1.8 wt % CuO) and Sn (up to 1.8 wt % SnO2) admixtures, and, sporadically by the small admixture of Sc (up to 0.3 wt % Sc2O3). Cu and Sn admixtures are indicative features of the pseudobrookite of this genetic type. These elements usually are incorporated into pseudobrookite together, according to the isomorphic scheme Sn4+ + Cu2+ → 2Fe3+, which is revealed for the first time for minerals of this group. Pseudobrookite of Tolbachik fumaroles was formed participating the process of gas–metasomatic alteration of basalt at temperature 500–750 °С. Presumably, Cu and Sn were brought by volcanic gas, while basalt was a source of Ti, Al and Sc; for Fe a source could be mixed.
Ob ustoychivosti aksial'no-simmetrichnykh sostoyaniy v teorii Ginzburga-Landau

The stability of superconducting states with a trapped magnetic flux in a spherical sample is investigated. Superconductors with a finite value of the Ginzburg–Landau parameter are considered (in particular, type I superconductors for which the magnetic field distortion near the sample plays an important role). It is assumed that the sample size is not too large as compared to correlation length ξ(T), and the superconducting state is axially symmetric. The possibility of the existence of states with a trapped flux in zero external field is considered. The results are compared to those for a cylindrical sample.
THE POTENTIAL USE OF QUICK RESPONSE (QR) CODES IN MOBILE BANKING: AN ANALYSIS OF IMPLEMENTATION AND ITS IMPACT ON USER EXPERIENCE

This study analyzes the potential for using Quick Response (QR) Codes in mobile banking services and their impact on user experience and the development of digital banking services. Focusing on the QR Code Indonesian Standard (QRIS) provided by Bank Indonesia, this research explains how QRIS enables efficient and safe non-cash transactions. Statistical data related to the growth of users and merchants adopting QRIS is used to illustrate the adoption of this technology. A quantitative descriptive approach was used to analyze secondary data that describes the growth of QRIS users and traders. In addition, decision-making theory is used to analyze the factors that influence the decisions of users and business people in adopting QR Codes. Research findings show that digital financial literacy, transaction security, and ease of use are important factors in influencing QRIS adoption. Based on the analysis, it is recommended that digital financial literacy, increasing transaction security, socializing the benefits of QRIS, and cross-sector collaboration be strengthened. In addition, there is a need for continuous evaluation and continuous innovation in digital banking services to optimize the adoption of QR Code technology.
FACING SECURITY CHALLENGES IN DIGITAL MARKETING AND HOW TO OVERCOME THEM

Digital marketing has become a critical component of modern business strategy, but it has also raised new challenges regarding cybersecurity. This research aims to investigate security challenges in digital marketing and the efforts made to overcome them. The research method used is a quantitative descriptive approach with secondary data collection. Data collected includes industry reports, articles, and previous studies related to cybersecurity in digital marketing. This data is analyzed to identify patterns and trends related to security threats and the strategies used by companies to deal with them. The research results show that digital marketing is faced with various security risks, such as data leaks, cyber-attacks, and fraud. Efforts to overcome these challenges include the use of advanced security technology, employee training on security awareness, and collaboration with third parties who are experts in the field of cybersecurity. This research provides an in-depth understanding of security in digital marketing and provides recommendations for companies to improve their security systems.
Existence of sequences satisfying bilinear type recurrence relations

We study sequences $\left\{A_n\right\}_{n=-\infty}^{+\infty}$ of elements of an arbitrary field $\mathbb{F}$ that satisfy decompositions of the form $A_{m+n} A_{m-n}=a_1(m) b_1(n)+a_2(m) b_2(n)$, $A_{m+n+1} A_{m-n}=\tilde a_1(m) \tilde b_1(n)+\tilde a_2(m) \tilde b_2(n)$, where $a_1,a_2,b_1,b_2\colon \mathbb{Z}\to\mathbb{F}$. We prove some results concerning the existence and uniqueness of such sequences. The results are used to construct analogs of the Diffie-Hellman and ElGamal cryptographic algorithms. The discrete logarithm problem is considered in the group $(S,+)$, where the set $S$ consists of quadruples $S(n)=(A_{n-1},A_n, A_{n+1}, A_{n+2})$, $n\in\mathbb{Z}$, and $S(n)+S(m)=S(n+m)$.
Feasibility of data transmission under attack: from isolated toughness variant perspective

The graph model is an appreciable tool for data transmission network, where the feasibility of data transmission in site attack circumstances can be described by fractional critical graphs, and the vulnerability of networks can be measured by isolation toughness variant. This paper considers both the stability of the network and the feasibility of data transmission when the sites are destroyed, and determines the isolated toughness variant bound for fractional (a, b, n)-critical graphs, where the parameter n represents the number of damaged sites at a certain moment. A counterexample proves the sharpness of the given isolated toughness variant bound. The main theoretical conclusion provides an equilibrium between performance and cost in network topology designing.
Constructions and invariants of optimal codes in the Lee metric

We propose concatenated and switching methods for the construction of single-error-correcting perfect and diameter codes in the Lee metric. We analyze ranks and kernels of diameter perfect codes obtained by the switching construction.
Il participio nella <i>peroratio </i>di Col 4,2-6: valore sintattico e funzione retorica

This article concludes the analysis of the participle in the Letter to the Colossians (see LA 62 [2012] 153-172 and LA 63 [2013] 293-317). In particular, we focus on the syntactic and semantic value of the participle, and on its rhetorical function in the brief peroratio (Col 4:2-6). In this pars rhetorica this verbal mood is at the service of the recapitulation of the points of speech (summary), and the emotional aspect upon the audience (pathos). The use of its aspectual and temporal dimensions shows an emphatic amplified style of the Letter to the Colossians. The long syntactic phrases (in particular, 4:2-4) seem well-constructed and held together by the presence of the participle. By using the participle, Paul better defines and describes the prayer of the Colossians (prayer of the thanksgiving and intercession/request), and their conduct in Christ with particular regard towards those outside, and their speech.