Reviewerly/exHarmony huggingface dataset:
Simulating quantum chaos on a quantum computer

We show that currently available noisy intermediate-scale quantum (NISQ) computers can be used for versatile quantum simulations of chaotic systems. We introduce a novel classical-quantum hybrid approachfor exploring the dynamics of the chaotic quantum kicked top (QKT) on a universal quantum computer. The programmability of this approach allows us to experimentally explore the complete range of QKT chaoticity parameter regimes inaccessible to previous studies. Furthermore, the number of gates in our simulation does not increase with the number of kicks, thus making it possible to study the QKT evolution for arbitrary number of kicks without fidelity loss. Using a publicly accessible NISQ computer (IBMQ), we observe periodicities in the evolution of the 2-qubit QKT, as well as signatures of chaos in the time-averaged 2-qubit entanglement. We also demonstrate a connection between entanglement and delocalization in the 2-qubit QKT, confirming theoretical predictions.
FROM A TO Z (FROM ARGENTINA TO ZAMBIA AND FROM AUDIO TAPES TO ZOOM): EDUCATIONAL TECHNOLOGIES UNDER COVID-19

FROM A TO Z (FROM ARGENTINA TO ZAMBIA AND FROM AUDIO TAPES TO ZOOM): EDUCATIONAL TECHNOLOGIES UNDER COVID-19
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning

Deep learning has proven effective for various application tasks, but its applicability is limited by the reliance on annotated examples. Self-supervised learning has emerged as a promising direction to alleviate the supervision bottleneck, but existing work focuses on leveraging co-occurrences in unlabeled data for task-agnostic representation learning, as exemplified by masked language model pretraining. In this chapter, we explore task-specific self-supervision, which leverages domain knowledge to automatically annotate noisy training examples for end applications, either by introducing labeling functions for annotating individual instances, or by imposing constraints over interdependent label decisions. We first present deep probabilistic logic(DPL), which offers a unifying framework for task-specific self-supervision by composing probabilistic logic with deep learning. DPL represents unknown labels as latent variables and incorporates diverse self-supervision using probabilistic logic to train a deep neural network end-to-end using variational EM. Next, we present self-supervised self-supervision(S4), which adds to DPL the capability to learn new self-supervision automatically. Starting from an initial seed self-supervision, S4 iteratively uses the deep neural network to propose new self supervision. These are either added directly (a form of structured self-training) or verified by a human expert (as in feature-based active learning). Experiments on real-world applications such as biomedical machine reading and various text classification tasks show that task-specific self-supervision can effectively leverage domain expertise and often match the accuracy of supervised methods with a tiny fraction of human effort.
SCAFFOLDING LEARNING WITH MERLIN: MALAYSIAN STUDENTS' PERCEPTIONS OF AN AI CHATBOT

Appears in: EDULEARN21 Proceedings Publication year: 2021Pages: 4260-4265ISBN: 978-84-09-31267-2ISSN: 2340-1117doi: 10.21125/edulearn.2021.0902Conference name: 13th International Conference on Education and New Learning TechnologiesDates: 5-6 July, 2021Location: Online Conference
EDUCATIONAL WEB QUESTS IN MATHEMATICS AS AN ELEMENT OF THE DIGITAL EDUCATIONAL ENVIRONMENT

M. Artyukhina, O. Artyukhin, S. Napalkov, O. AbramovaLobachevsky State University of Nizhny Novgorod (RUSSIAN FEDERATION)
EDUCATION SYSTEM IN THE FAR NORTH DISTRICTS OF THE RUSSIAN FEDERATION: THE CASE OF THE YENISEI DISTRICT, KRASNOYARKIY KRAI

A. Didenko1, V. Kirko 2, G. Savolainen1, A. Lukyanova3, V. Razumovskaya4 1Krasnoyarsk State Pedagogical University named after V.P. Astafyev (RUSSIAN FEDERATION) 2Siberian Federal University, Krasnoyarsk State Pedagogical University named after V.P. Astafiev (RUSSIAN FEDERATION) 3Reshetnev Siberian State University of Science and Technology (RUSSIAN FEDERATION) 4Siberian Federal University (RUSSIAN FEDERATION)
Facial Image Analysis for Identification of Gender: A Machine Learning based Approach

Facial biometrics for gender classification is known to significantly improve the efficiency of person identification in biometric access control models. It not only increases the speed but also improves the accuracy. It reduces the effort of finding a match for a face in the databases to almost a half. The process like any pattern recognition framework needs to extract the useful features. A novel gender identification algorithm is proposed which is based on the facial features of a person. Viola Jones object detection technique is used for face detection from an image, and the relevant facial features are extracted using Topographic Independent Component Analysis. An SVM based classifier is trained using the calculated feature vector to determine whether the person in the image is a male or a female.
Compact Variable-base ECC Scalar Multiplication using Euclidean Addition Chains

The random generation of Euclidean addition chains fits well with a GLV context (Dosso et al., 2018) and provides a method with decent performance despite the growth of the base field required to get the same level of security. The aim of this paper is to reduce the size of the base field required. Combined with an algorithmic improvement, we obtain a reduction of 21% of the memory usage. Hence, our method appears to be one of the most compact scalar multiplication procedure and is particularly suitable for lightweight applications.
RECOMMENDATIONS IN E-LEARNING: IDENTIFYING CURRENT TRENDS WITH AUTOMATED CRAWLING METHODS

Appears in: EDULEARN21 Proceedings Publication year: 2021Pages: 7914-7920ISBN: 978-84-09-31267-2ISSN: 2340-1117doi: 10.21125/edulearn.2021.1615Conference name: 13th International Conference on Education and New Learning TechnologiesDates: 5-6 July, 2021Location: Online Conference
MANAGEMENT OF AN EDUCATIONAL INSTITUTION IN A DIGITAL SOCIETY: NEW REQUIREMENTS FOR LEADERS OF THE EDUCATION SYSTEM

MANAGEMENT OF AN EDUCATIONAL INSTITUTION IN A DIGITAL SOCIETY: NEW REQUIREMENTS FOR LEADERS OF THE EDUCATION SYSTEM
SISTEM INFORMASI BERBASIS WEB PADA TOKO BUKU DI TOKO BATAM

Developments in the field of technology can be used to help work, one of which is by building a web-based information system at a used bookstore in the city of Batam. The sales system in this bookstore is still manual, where buyers have to come to the store to get the desired book. Limitations in terms of product marketing are one of the obstacles in the bookstore. The main problem at this bookstore is the difficulty of buyers when looking for books because of the low stock of books. The data collection method Used on this examine is to apply commentary and interview techniques, where researchers come to the location to make observations to see the existing system in the bookstore and interview the owner to find out the existing problems. The research technique utilized in this study is the System Development Life Cycle (SDLC) method with the waterfall model. By making this online sales system, it can make its easier for sellers to market products, and for buyers to be able to see the available stock of books and choose and buy books without having to come to a bookstore
A User Query-Centered Recommender System from Public Repository

Query-based User Information Categorization and Extraction (QICE) methods allow the classical query extraction with its knowledge obtained from useful resources. Open Data encodes machine-readable user facts from different sources, including third-party, that play a vital role in this QICE. Mining techniques from documents available in free sources and constructing the user text based on the user query with its knowledge and analysis are the core research problems in the public repositories and query understanding tasks such as query pattern analysis and user information requirements. However, the public repositories encode the user information through Wikipedia and web pages which are static, and these do not understand the user requirement perspectives. These static web pages have many quality issues with user query information, such as information extracted, complete data representing, time of query retrieval, and correctness of the information categorized based on the user query. QICE methods are, therefore, facing problem user query variances and type of user query confusability. In this paper, a query recommender system proposes developing a technique for user-query-centered knowledgeable integration and addressing the challenges of knowledge mining of the Twitter social network by extracting the knowledge from query log data. The proposed User-Query Centered Recommender System (UQCRS) is applied to exploit different measures to demonstrate the efficiency of recommendations delivered. The proposed algorithm exhibits an effective result to the search shortcuts issues. And to provide a performance comparison of the proposed system, the comprehensive evaluation is compared with well-known methods and demonstrates the impact of the results.
MPHELL: A fast and robust library with unified and versatile arithmetics for elliptic curves cryptography (extended version)

We propose a new versatile elliptic curves cryptography library based on unified arithmetics and various low-level arithmetics with a focus on protection against simple power analysis and an abstract layer for easy customisations. The implementations are oriented toward industrial applications and embedded devices. The number arithmetic used in the library is partly inherited from GMP with several improvements using adapted Montgomery representation and windowing techniques. We also present an improved AMNS (Adapted Modular Number System) arithmetic with competitive running time. The abstraction layer allows for the integration of external arithmetics (e.g., other libraries or hardware co-processor), general number systems and randomization of arithmetics. The library has the advantage of proposing standard elliptic curves but gives also the possibility to use curves in different settings such as Weierstrass form in co-Z coordinates, Jacobi quartic or Edwards forms (as well as their associated conversions functions). It has been extensively tested on x86-64, ARM 32/64 bits, STM32 architectures and also in real-world applications. We present some comparative elliptic curves signatures timings for different curves without taking into account the specificity of the curves in our library (as opposed to OpenSSL for instance).
A REVIEW OF THE APPLICATION OF AVATAR IN VIRTUAL LEARNING ENVIRONMENT

Virtual education environment based on avatar provides learners with immersive learning experience. Avatar is to realize the interaction between learners and computer interface，which can improve the learning effect and stimulate learners' potential by enhancing learners' presence. With the popularization and development of virtual reality technology (VR for short), virtual education environment based on VR is increasingly advanced. In order to explore the impact of avatars on education in virtual educational environments, a literature review was conducted to determine the representation, application status, advantages, challenges and future educational potential of avatars in educational contexts.In this paper, 26 high-impact journals were selected to conduct a literature review using 42 papers in the past 10 years (2010-2020) that applied avatar-based virtual teaching environment to teaching. The author uses qualitative and complementary description methods to analyze the content of the paper, and constructs a coding and analysis framework from the aspects of representation, applied disciplines, teaching effects, and research deficiencies.The results show that, virtual avatars are designed mainly from the aspects of personalized appearance, behavior, action, person perspective, gender and age, which are divided into five possible presentations: demonstrative, experiential, diagnostic, role-playing and constructional. Avatars are mainly used in science, medicine, pedagogy and interdisciplinary studies, among which they are most widely used in the medical field, such as virtual teaching experiments and pre-service training. Constructivism Learning Theory, collaborative learning and Situated learning have been widely used in avatar-based virtual education environments. The avatar-based virtual learning environment visualizes difficult content, which not only improves learners' learning effect and learning attitude, but also improves learners' presence and effective participation in learning. Students interact through avatars, which promotes learners' ability to interact and collaborate.The integration of avatars and education still has some problems, such as high cost, difficult technology, unreasonable design of teaching process and ethics. But avatar-based virtual worlds offer unique educational experiences, and by solving the above problems, avatars still have great educational potential. Future research should not only improve the usability of avatars, but also focus on the integration of avatar-based virtual world with a wider range of disciplines, so as to explore more effective teaching methods, instructional design processes and teaching quality evaluation dimensions. For educators and researchers of virtual education environments, this study provides a relatively comprehensive explanation of the combination of avatar-based virtual education environments and specific disciplines, and makes a systematic analysis and induction based on this, which has rarely been studied before.
A Study and analysis of attacks by exploiting the source code against computer systems

An avalanche of threats from malicious used information and communication technologies (ICT) ‎in political, military, economic and social affairs led to a deep awareness of the fact that new ‎technologies may pose additional risks to international peace and safety. Thus, the problem of ‎international information security, that is, the state of the spread of information among the ‎countries of the world, with which excludes the possibility of violation of the rights of the ‎individual and users in various state agencies and in all fields of knowledge. In the field of ‎knowledge, as well as destructive and illegal impact on elements of the national critical ‎information infrastructure, became an integral part of international security as a system of ‎international relations based on the observance by all states of generally recognized principles and ‎norms of international law and excluding the solution of controversial questions and ‎disagreements between them through force or threat of force, in general. Thus, the principles of ‎international security providing for promoting peaceful coexistence, being ensuring equal security ‎for all states, the creation of effective guarantees in the military, political, economic and ‎humanitarian spheres, preventing the race of nuclear and space weapons, respect for the sovereign ‎rights of every people, fair political settlement of international crises and regional conflicts ‎certainly include the creation of a system of international information security. At the same time, ‎under the IIB system, designed for countering threats to strategic stability and ensuring equal ‎partnership in the global digital environment, we understand the totality international and ‎national norms and institutions, chief among which are the UN Regulated activities of various ‎actors worldwide.‎
Application of augmented reality technology in factory equipment inspection: Taking Microsoft HoloLens 2 as an example

Modern science and technology are gradually advancing, and as factory instruments become more and more sophisticated, their maintenance is relatively difficult. When the equipment fails, the maintenance personnel may need to carry the paper manual to read and record in addition to the inspection and repair in person. The paper may be stained during the process, which is quite inconvenient. Microsoft HoloLens 2 is a pair of smart-glasses with excellent mixed reality technology. It allows users to communicate with gestures or voice in augmented reality and provides development tools for companies to create interactive content. In this study, the Unity engine is used to receive sensor data on equipment, and Vuforia is used to visualize the data. Finally, Microsoft HoloLens 2 is used to present the data to the end user. It aims to integrate equipment information through mixed reality technology to make it easier for maintenance personnel to perform maintenance, or the personnel without maintenance experience can also maintain the equipment in a simple way.
Raw Differentiable Architecture Search for Speech Deepfake and Spoofing Detection

End-to-end approaches to anti-spoofing, especially those which operate directly upon the raw signal, are starting to be competitive with their more traditional counterparts. Until recently, all such approaches consider only the learning of network parameters; the network architecture is still hand crafted. This too, however, can also be learned. Described in this paper is our attempt to learn automatically the network architecture of a speech deepfake and spoofing detection solution, while jointly optimising other network components and parameters, such as the first convolutional layer which operates on raw signal inputs. The resulting raw differentiable architecture search system delivers a tandem detection cost function score of 0.0517 for the ASVspoof 2019 logical access database, a result which is among the best single-system results reported to date.
Application of Kernel Hypothesis Testing on Set-valued Data

We present a general framework for kernel hypothesis testing on distributions of sets of individual examples. Sets may represent many common data sources such as groups of observations in time series, collections of words in text or a batch of images of a given phenomenon. This observation pattern, however, differs from the common assumptions required for hypothesis testing: each set differs in size, may have differing levels of noise, and also may incorporate nuisance variability, irrelevant for the analysis of the phenomenon of interest; all features that bias test decisions if not accounted for. In this paper, we propose to interpret sets as independent samples from a collection of latent probability distributions, and introduce kernel two-sample and independence tests in this latent space of distributions. We prove the consistency of these tests and observe them to outperform in a wide range of synthetic and real data experiments, where previously heuristics were needed for feature extraction and testing.
Analisis Fatwa Air Sisa Kumbahan Dari Sumber Mutanajjis

Technology advances nowadays give a huge impact to the human welfare.In particular related to treatment of sewage water tecnology that can be converted to more valuable treated wastewater to be used in plant fertilizer and drinking water. While the sewage sedimentation produces bioeffluent, biosolid and biogas as a new energy sources. Despite having a variety of uses, there is question related islamic rule in using treatment water from sewage, is permissible to utilise because they came from mutanajjid water and mustakmal or used water. Therefore, this article is focus on analysing of fatwas on sewage treatment water particularly in changing from mutanajjis water to used water or pure water. This research is qualitative that will using methodology of colleting data by analysing documents of approved fatwas. The findings of study indicate as treated waste water is characterized as pure water. It is because transformation process to eliminate excrement and change it to pure water. Therefore, it can be used as plant watering and drinking water as long as it is not harmful because it has returned to the original nature of water.
Sistem Pakar Troubleshooting Kerusakan Hardware Laptop Dengan Metode Backward Chaining Berbasis Android

Laptop is a very helpful device for human work. Almost all fields use laptops to complete human work. Expert system technology that serves as a substitute for someone who is an expert in their field. Expert systems arise because of problems in a specific specific field, where users want a solution to the problem solved by approaching expert ways in solving problems. There are several methods in expert systems. This study will discuss the Expert System for Troubleshooting Hardware Damage on Laptops, and the inference method used is Backward chaining. Tracking is based on data or facts and then leads to conclusions in the form of conclusions about symptoms of laptop damage or problems that attack the laptop. The system that has been built is tested by comparing the suitability of the system output with the results of expert diagnoses. The test results from 15 case data obtained an accuracy rate of 86.6%. With these accuracy results, it shows that the system is able to help the role of experts
Sentiment Analysis Using Hybrid Feature Extraction for Hotel Reviews

Interpersonal interaction destinations have become well known and normal spots for sharing wide scope of feelings through short messages. These feelings incorporate satisfaction, pity, tension, dread, and so forth. Breaking down short messages helps in recognizing the conclusion communicated by the group. Feeling analysis on hotel audits recognizes the generally speaking sentimentor assessment communicated by a commentator towards an inn. Numerous specialists are dealing with pruning the notion investigation model that obviously recognizes a positive audit and a negative survey. In the proposed work, we show that the utilization of hybrid highlights acquired by linking Machine Learning highlights (TF-IDF) with Lexicon highlights (TextBlob) gives better outcomes both as far as exactness and intricacyare concerned.The proposed model unmistakably separates between a positive audit and negative survey. Since understanding the setting of the surveys assumes a significant part in grouping, utilizing hybrid highlights, helps in catching the setting of the hotel audits and thus expands the precision of order.
The First Language Interference toward Students’ English Speaking as Foreign Language

This research aims at analyzing the first language interference toward students’ English speaking as foreign language made by sixth semester students in course design subject, such as phonological interference (pronunciation), grammatical (morphological and lexical), and lexical interference (vocabulary), and the factors that caused interference of the first language. This research is descriptive qualitative. The findings of the research explained that students made three types of interference categorized as phonological interference such as pronounce the word incorrectly (vowel, diphthong, consonan, and allophonic variation), grammatical interference such as in morphological (singular-plural agreement) and syntactical (subject-verb agreement, phrase, comparative adjective, possessive adjective, and parallel structure), and lexical interference such as in vocabulary (combining between Indonesian and the English language). The data showed that students often make error in phonological aspect. The factors that caused first language interference are lack of knowledge, Indonesian transfer, and lack of vocabularies of foreign language that mastered by students or respondents.