Reviewerly/exHarmony huggingface dataset:
EFL STUDENTS’ PERCEPTION ON USING QUIZIZZ APPLICATION: A SURVEY STUDY

The aim of this study was to find out students' perception on the use of the Quizizz application in learning English at Junior High School in Riau. This present study employed a quantitative survey method with data taken from a questionnaire. The number of samples in this study were 50 students using purposive sampling. A structured item questionnaire was used as the instrument. The results showed that Quizizz application is easy to use. The students were happy in studying, had motivation and interest in learning English. Using Quizizz is more practical than doing exercises on paper, it also helps students to review the lessons, and reduce anxiety while doing exams. It can be concluded that students' perceptions were good on the use of the Quizizz application
SELF-REGULATED LEARNING BEHAVIORS LEVELS IN READING SUBJECT THROUGH E-LEARNING AT UNIVERSITY OF PGRI SUMATERA BARAT

AbstractThis study aims to determine levels of regulated learning behavior of English students in reading subject through e-learning at PGRI University, West Sumatra. Problems that occur in distance education students include lack of motivation and procrastination, interference from technology, work and family, as well as the tendency to use reactive methods rather than proactive methods. In this study, the researcher used a descriptive research in quantitative approach. Researchers collected data using the Online Self-Regulated Learning Scale (OSLQ). There were 44 students who participated in this study. Researcher distributed the questionnaire using link of google form. It consisted of 24 questions where the questions were divided into six levels of self regulated learning behaviors, goal setting (setting up the learning goals), environment structuring (deciding the place for study with minimum distraction), time management (setting up time consuming on each learning activity), help seeking (asking for assistence from tutors, peers or the expert of the area concern), self-evaluation (self-reflected the personal performance with the learning goal and achievements), and metacognition (knowledge of controlling cognitive activities). Keywords: levels, regulated learning behavior, e-learning
Research on accident prevention based on data center inspection robot

Currently, the Southwest Regional Data Center Inspection Robot checks for hidden dangers or associated hidden dangers using traditional approaches (such as empirical method and permutation and combination method), which makes it difficult to properly identify hidden dangers. Many hidden dangers cannot be identified solely by the cognition and rules and regulations of the data center's on-site operation and maintenance personnel because the time and space distribution of hidden dangers is not clear, and the hidden dangers have characteristics of concealment and randomness. As a result, how to effectively use the inspection robot's back-end platform to collect basic data, combine historical fault hidden dangers records, and use the correlation mining method to find the correlation between different hidden dangers, allowing you to check the hidden dangers in the data center and achieve the goal of accident prevention.
A priori selected spline–wavelet basis for option pricing under Black–Scholes and Merton model

The paper deals with option pricing under the classical Black-Scholes model and a more sophisticated Merton jump– diffusion model, which allows jumps in the underlying asset price. The Merton model is represented by non–stationary integro– differential equations. Due to the integral term, standard methods are not very efficient because they lead to full discretization matrices. The Black–Scholes model can be considered a particular case of the Merton model, which does not contain the integral term. In the paper, a method is proposed, which is a combination of the Crank–Nicolson scheme and the wavelet–Galerkin method using adaptive quadratic spline wavelet basis selected a priori. This enables to significantly decrease the number of basis functions and size of matrices and vectors involved in computation compared to standard non–adaptive wavelet–Galerkin methods. Furthermore, the proposed wavelet–based method leads to sparse discretization matrices with uniformly bounded condition numbers.
Maple Conference 2021 Mathematical Art and Creative Works Exhibit

The report from the curator on the first Maple Art and Creative Works Exhibit that took place as part of the2021 Maple Conference
A Software Development Kit and Translation Layer for Executing Intel 8080 Assembler on a Quantum Computer (August 2022)

One of the major obstacles to the adoption of quantum computing is the requirement to define quantum circuits at the quantum gate level. Many programmers are familiar with high-level or low-level programming languages but not quantum gates nor the low-level quantum logic required to derive useful results from quantum computers. The steep learning curve involved when progressing from quantum gates to complex simulations such as Shor's algorithm has proven too much for many developers. The purpose of this paper and the software presented within, addresses this challenge by providing a Software Development Kit (SDK), translation layer, emulator and a framework of techniques for executing Intel 8080/Z80 assembler on a quantum computer, i.e. all salient points of CPU execution, logic, arithmetic and bitwise manipulation will be executed on the quantum computer using quantum circuits. This provides a novel means of displaying the equivalency and interoperability of quantum and classical computers. Developers and researchers can use the SDK to write code in Intel 8080/Z80 assembler which is executed locally via traditional emulation and remotely on a quantum computer in parallel. The emulator features side-by-side code execution with visibility of the running quantum circuit and re-usable/overridable methods. This enables programmers to learn, reuse and contrast techniques for performing any traditional CPU based technique/instruction on a quantum computer; e.g. a programmer may know how to multiply and perform checks on a classical CPU but is not able to perform the same tasks in a quantum implementation, this SDK allows the programmer to pick and choose the methods they would like to use to fulfil their requirements. The SDK makes use of open-source software, specifically Python and Qiskit for the emulation, translation, API calls and execution of user supplied code or binaries.
SimH: A Novel Representation Learning Model With Activation and Projection Mechanisms for COVID-19 Knowledge Bases

The emergence of coronavirus disease 2019 (COVID-19) has had a significant impact on healthcare and the economy. With representation learning applied in constructing COVID-19 knowledge graphs, abundant COVID-19-related knowledge collected by clinicians and scientists all over the world can be utilized to deepen their understanding of the mechanism and related biological functions of the disease. However, most existing representation learning models cannot deal well with COVID-19 knowledge graph due to its low-connected star-like structure and various complex nonlinear relationships. Besides, lacking reliable negative triplets is also a difficult problem, yet to be adequately resolved. In this article, we propose a novel representation learning model called translation on hyperplanes with an activation operation and similar semantic sampling (SimH) for COVID-19 knowledge graphs. In our proposed SimH, an activation operation is designed to provide additional interaction features for low-in-degree entities. Then the hyperplane projection technique is introduced to the distance-based scoring function so that those complex nonlinear relationships can be modeled with lower complexity maintained in comparison with other nonlinear models. Moreover, a negative triplet sampling method that adaptively replaces entities with similar semantics is introduced to generate reliable negative triplets. To verify the effectiveness of SimH, extensive experiments are conducted on the COVID-19-Concepts dataset. The experimental results show that our SimH model achieves significant improvements in prediction and classification accuracy over existing knowledge representation learning models.
Solving constrained problems with dynamic objective functions

Many practical decision-making problems involve changing data and parameters with time. Solving such problems requires a custom-designed algorithm that can efficiently handle the repeatedly changing problem, in fact, its changing search space. In this paper, we consider constrained optimisation problems where the coefficients of the objective function change. We propose a framework that adaptively deals with linear and nonlinear components by satisfying the constraints within a limited time. Furthermore, we introduce a new mechanism to identify the sensitivity of variables, determine the rate of changes in the coefficients of the decision variables, and propose a heuristic to update the population efficiently after every change. The experimental results demonstrate that the proposed approach is able to obtain better solutions than those without having these new components.
A large family of sequences with low correlation

In this paper, for a prime <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$p$</tex> and positive integers <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n, m, e$</tex> , and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$t$</tex> such that <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n=2me$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$t=\lfloor\frac{m}{2}\rfloor$</tex> , a new large family <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{S}$</tex> of p-ary sequences of period <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$p^{n}-1$</tex> with low correlation is constructed. It is shown that <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{S}$</tex> has maximum correlation magnitude <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$1+p^{\frac{n}{2}+2te-e}$</tex> , family size <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$p^{nt}$</tex> and maximal linear span <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(t+1)n$</tex> . Furthermore, based on the theory of quadratic forms over finite fields, all exact correlation values between sequences in <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{S}$</tex> are determined when <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$p = 2$</tex> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">.</sup>
Justifying parameters for the automatic servo control system of a rotary plate vacuum pump in the milking machine

The scientific task to improve energy efficiency and ensure the process of vacuum regime stabilization in the operation of milking machines has been solved. A mathematical model of the process of functioning of the servo control system of a rotary plate vacuum pump was built; the numerical modeling of its workflow was carried out. This paper reports the results of experimental studies on the influence of the regime parameters of the rotary plate vacuum pump on the efficiency of its operation, as well as the results of experimental research on the servo control system for the rotary plate vacuum pump. The operational process of the rotary plate vacuum pump HB-1200 for a milking machine was investigated. The influence of mode parameters (rotor speed n and vacuum pressure P) on the performance of the vacuum pump, Qa, vacuum pressure fluctuation, ΔP, and the power consumption of the vacuum pump drive, Np, has been determined. The servo control system of the rotary plate vacuum pump was experimentally investigated based on the developed algorithms of its operation. In a generally accepted algorithm, vacuum fluctuation increases with increasing an airflow rate: at ΔQa=45 l/min – ΔP=2.3 kPa; at ΔQa=90 l/min – ΔP=4.6 kPa; at ΔQa=135 l/min – ΔP=6.4 kPa. Unlike the generally accepted one, the developed algorithm enables a stable vacuum mode with the largest vacuum fluctuation being ΔP=2.4 kPa. For the first time, the functional dependence of the influence of the regime parameters of the rotary plate vacuum pump with its automatic servo control system on the stability of the vacuum regime of a milk-vacuum system in the milking machine was established. The results can be applied when improving milking machines in terms of ensuring the stabilization process of the vacuum regime.
Sistem Pakar dalam Mendiagnosis Gizi Buruk pada Balita dengan Menggunakan Metode CBR

Limited information makes people have little knowledge of the early symptoms of Malnutrition in Toddlers. This disease must be treated quickly from an early age otherwise it will not get worse. This study aims to accurately diagnose the symptoms to provide fast, precise and accurate information in classifying the types of Malnutrition in Toddlers. This research is an expert system using Case Based Reasoning (CBR) method. The CBR method makes decisions from new cases based on solutions from previous cases. The data processed were 22 symptoms and 8 types of disease for 22 cases. The accuracy results are very good by being able to identify all types of malnutrition. So that this research can be used as a recommendation in speed to identify malnutrition in toddlers quickly.
Natural language processing: Understanding the current landscape

We spoke with two researchers in Natural Language Processing (NLP) to understand their perspective on the current landscape of NLP - the challenges, successes, and implications of the technology today.
CHAPTER 4.3. USE OF DIGITAL TECHNOLOGIES IN THE EDUCATIONAL PROCESS MODERN EDUCATIONAL INSTITUTION

The introduction of cloud computing into the modern world is a necessary condition for the progressive development of the society. The results of the research, conducted in 2018 by Gartner, IDG and Right Scale, prove that cloud-computing use has become a widespread practice around the world. According to the Right Scale survey, publicly available cloud infrastructures are in the lead in terms of implementation: 81% of companies choose a multi-cloud strategy that uses up to five clouds on average. The hybrid strategy, which is a combination of public and private cloud infrastructures, is followed by 51% of respondents, and 75% of organizations use private clouds. Increasing competition between cloud service providers promotes greater availability of services and helps to expand the capabilities of analytics and integration of cloud computing into various areas of public practice. Global changes in social interaction and communication, growing need for social isolation, caused by the COVID-19 pandemic conditions, actualize the search for optimal ways of indirect interaction, communication, and learning. Piece intelligence, cyber-army, and chat-bots for the collection of information - only a few innovative tools, to which the Ukrainian order is pushed into the cyberspace at the hour of the russian war. In this war, information has become out of control, but ahead of it - innovative technologies for combat action can be unsafe.
Need of cyber security education in modern times

Though with the emergence of Internet that certainly has positively impacted people's lives, as so many of us use social media on internet as a platform for self-expression, to incite discussions, or to become known, but there are negative issues too that have arisen related to its use.Cases like cyberbully, online fraud, racial abuse, pornography and gambling have increased tremendously due to the lack of awareness among Internet users that many end up being victims to these acts.Sometimes people want to be the primary source of information, of sharing a topic, that they overlook the fact stating authentication to the shared information.Today usage of the internet is not just limited to adults, but in this era of technology and multimedia, knowledge of cybersecurity is also important for children.Still, the level of awareness among Internet users is quite low or moderate.Therefore, if proper measures are taken to cultivate knowledge and awareness among Internet users from their early age, i.e., young children, this issue of cyber safety can be understood in a better way.Since now with covid 19 online education has become the new trend, young children specially need to be educated to operate in a safe manner in cyberspace and to protect themselves in the process.The aim of this paper is to sightsee why cyber safety education is so critical for modern learners and how they can understand the risks associated with being active in cyberspace, to have knowledge and understanding about the strategies that stakeholders can use to promote cyber security education in schools.In this paper, few strategies are discussed as how cyber security education can be implemented in schools.
An Sentiment Analysis Model of Online Product Reviews Based on Deep Learning

In order to improve the accuracy of sentiment classification of online product reviews, a model for sentiment analysis of unbalanced reviews is proposed. Firstly, the LDA model is used to balance the original review text set, and then the word vector model and convolution neural network are combined to construct the review text vectorization feature extraction process to obtain the word feature vector, which is used as the input matrix of the balanced review set. Finally, the BiLSTM algorithm is used for sentiment classification to obtain product reviews of positive and negative sentiment categories. The results show that LDA sampling unbalance processing method is a high accuracy unbalanced text processing method. BiLSTM algorithm has better effect of sentiment classification than other deep learning algorithms. CNN-BiLSTM model based on LDA unbalance processing obtains the optimal model performance evaluation index value in the comparative experiment of different sentiment classification models, which verifies the advantages and effectiveness of the model and effectively realizes sentiment analysis on unbalanced review texts.
The Effectiveness of Extensive Reading Book (Local Wisdom Based) to Support English Subject at Tanjungpura University

This study aims to develop extensive reading materials based on local wisdom to support English courses at Tanjungpura University. The ADDIE model was used in the development of reading materials in this study. This study's data sources include validation sheets from English material experts, instructional design experts, media and graphic design experts, and small group evaluations of students taking English courses. The method used for data collection is a questionnaire, while the instrument used in collecting accurate data is a Likert scale. The analysis used is a descriptive qualitative analysis and quantitative descriptive analysis. The research results have been developed into extensive reading materials based on local wisdom to support English courses. The study results show that the value of 98.4% was obtained in the validation carried out by material experts, instructional design experts as 86.1%, media or graphic design experts as 92.8%, and 86% based on the results of small group trials. The numbers mean that the developed reading book is suitable for supporting English courses with minor revision.
Cloud Improvement Model of Niche Width and Its Application in Tram Evaluation

Niche theory is one of the most important theories and tools in ecology. Niche width is a concept used to measure the position and role of an individual or population in a biological community. However, in the measurement of niche width, due to the unique characteristics of ecosystems, evaluators often give information based on subjective judgment to describe the status of ecological factors. Natural language is used to describe the state of ecological factors, and all the observed values come from the subjective judgment of the language value of the evaluator and have fuzziness and randomness at the same time. To achieve scientific and reasonable decision evaluation, it is necessary to comprehensively consider the fuzziness and randomness of complex systems. The cloud model is used to improve the niche width model, aimed at solving ecological factors under natural language information assignment and niche width evaluation. It is applied to measure tram niche width, which is the typical ecological factor value assignment using natural language thinking.
Assessment and Mitigation of Information Security Policy in Budgeting System using KAMI Index 4.1

This Threats to information resources require information security management policies in every agency. The Information Security Index (KAMI Index) is one of the methods developed by the Ministry of Communication and Information Technology, used to evaluate the maturity level, completeness of ISO/IEC 27001:2013 implementation and information security readyness. As a national zakat institution, XYZ Organization has utilized information technology in several systems, including the budgeting system. However, the information security index has never been measured. This condition may result in the risk of threats to information security, so it is necessary to measure. The Budgeting System needs to be measured using KAMI Index 4.1. The assessment criteria are carried out on seven categories to know how the quality of the information security policy is. The results of this assessment, XYZ organization gets an electronic system score is 17, governance 75, risk management 30, framework 31, asset management 37, ICT 38, securing third party involvement 40%, service security 20%, personal data protection 27% so the total score of 5 categories is 211 or at level I+ to II. This organization has started implement the framework at early stage and has not met the initial requirements for ISO/IEC 27001:2013 certification.
FORECASTING AND SEARCHING FOR GOLD MINERALIZATION WITHIN THE AMGUEMO-KANCHALAN METALLOGENIC ZONE (CHUKOTKA)

Despite the existence of a well-known set of the forecast and search criteria, only three gold and silver epithermal deposits were discovered on the territory of the Amguem-Kanchalan metallogenic zone, which has significant resource potential. The resource base of the enterprises developing them is extremely limited. The aim of the study is to clarify the regional and local conditions for localization of epithermal gold-silver mineralization, forecasting and searching for promising structures and areas of its manifestation within the AmGuemo-Kanchalan metallogenic zone. The airborne geological studies of the territory were carried out. The proposed areas potential for gold mineralization are identified. Recommendations for conducting search and evaluation work are given.