Reviewerly/exHarmony huggingface dataset:
Design activity in physical education classes pedagogical diagnostic system

This article is devoted to give concepts to students about physical qualities in higher educational institutions using innovative technologies. The questions of modern methods of teaching movements are revealed, the classification and meaning are revealed. The issues of teaching the subject of Timo feedback using pedagogical technologies are considered. Designing a lesson includes requirements, design principles, an algorithm, has certain features, is of particular importance for the organization and results of the activities of the participants in the educational process. The article deals with the issues of the influence of physical qualities on the body of students.
The Applications of Object Migration Automaton (OMA)-Memetic Algorithm for Solving NP-Hard Problems

In this chapter, to evaluate the efficiency of the object migration automaton (OMA)-memetic algorithm (OMA-MA), it has been used for designing memetic algorithms to solve the equipartitioning problem (EPP), the graph isomorphism problem (GIP), and the assignment of cells to switches problem in cellular mobile network (ACTSP). The results of computer experimentations have shown that all the OMA-MAs outperform the others in terms of quality of solution and rate of convergence.
Multi Aspect Sentiment of Beauty Product Reviews using SVM and Semantic Similarity

Beauty products are an important requirement for people, especially women. But, not all beauty products give the expected results. A review in the form of opinion can help the consumers to know the overview of the product. The reviews were analyzed using a multi-aspect-based approach to determine the aspects of the beauty category based on the reviews written on femaledaily.com. First, the review goes through the preprocessing stage to make it easier to be processed, and then it used the Support Vector Machine (SVM) method with the addition of Semantic Similarity and TF-IDF weighting. From the test result using semantic, get an accuracy of 93% on the price aspect, 92% on the packaging aspect, and 86% on the scent aspect.
INVESTIGATION ON COMBINATORIAL ASYMMETRIC KEY CRYPTOSYSTEM AND HASH BASED MULTIFACTOR AUTHENTICATION TECHNIQUES FOR SECURED DATA COMMUNICATION IN WIRELESS SENSOR NETWORK

Wireless sensor network security pulls in considerations of numerous specialists around the globe. Security is utilized with attributes of authentication, uprightness, protection, nonrepudiation and privacy. The security benefits in WSN need to ensure the data imparted over network and assets from the assaults. Security and authentication during information communication are testing one in WSN. For secure communication in WSN, cryptographic and steganographic techniques are utilized. The information are sent or gotten to by any hub in network after authentication measure to keep from unapproved clients to get to the data. Our exploration clarifies Investigation on Combinatorial Asymmetric Key Cryptosystem and Hash Based Multifactor Authentication Techniques.
Wingardium Leviosa Wand / Sharifah Nur Atiqah Wan Akil

Wingardium Leviosa wand is a magical wand which is a new product idea which create from a common problem that society having to deal in their daily life nowadays. This report will provide a detailed road map on how to convert the ideas and vision into real, functioning, profitable and viable product. Today, the world is grappling with an invisible, deadly enemy, which can kill human being in just a blink of eyes. The existence of shocking smallest creature in universe which is coronavirus (Covid-19) has electrifying the worldwide. As the coronavirus pandemic has stretched around the world, it time to contribute our sweat, tears and blood to produce products that is useful to be use in this critical time. Wingardium Leviosa Wand is a unique product that made up of aluminium which is known to be one of eco- friendly materials. This product is focusing on giving communities a fresh, new, healthy and a better life by protecting people from harmful, dangerous and an invisible creature such as bacteria and viruses. Other than that, this wand also acts as strong shield to the consumer, that no single microorganisms able to pass through them.
COVID-19 Precaution Technique By Real Time Face Mask Detector Using Machine Learning

This paper will detail how our machine vision/deep learning pipeline will be applied in our two-phase COVID-19 face mask detector. Following that, we'll go over the dataset that will be used to train our custom face mask detector. will then teach you how to use Keras and TensorFlow to train a face mask detector on our dataset with a Python script. This Python script will be used to train a face mask detector and then the effects will be reviewed. Given the qualified COVID-19 face mask detector, we will go on to introduce two more Python scripts for detecting face masks in real-time video streams. We'll conclude this article by looking at the findings of our face mask detector. I will even make some extra recommendations for change.During a coronavirus infection, nearly everyone wears a mask to help deter the transmission of the COVID19 virus. In certain contexts, such as group access control, face access control, facial attendance, facial security checks at train stations, and so on, this almost renders traditional facial recognition technology ineffective. As a result, it is critical to enhance the identification accuracy of emerging facial recognition technologies on masked faces. The majority of current advanced facial recognition techniques are focused on deep learning and include a vast number of face samples.
Experiencias en el uso de la Tecnología Educativa en el período Covid-19 en la Universidad de Oriente

The use of Educational Technology has its main levels of application in the media and in Information and Communication Technology, at the Higher Education level it is specified in the use of materials, resources and didactic means and more generally, the use of information and communication technologies in university teaching, that is, in the design, development and evaluation of distance education programs and courses (EaD), the internet in face-to-face teaching and the establishment of a half-close virtual of learning. The objective of this work is to show the experiences of the use of educational technology as a support for face-to-face teaching and as a scenario for EaD, in addition to its application in the research and extension components. The activities and actions used to obtain the results achieved are described and the level of impact in the current moments of higher Superior education.
IMPLEMENTASI LOAD BALANCING SISTEM CLUSTER SERVER PADA WEB SERVER UNTUK JAMINAN KETERSEDIAAN LAYANAN TINGGI

Website services have become especially important thing and are the primary need of everyone’s information needs. This High information needs require website services to be reliable so that it doesn’t disrupt it’s user. Problems often happened in the website services when the infrastructure supporting it was having system failure, such as power shortage, natural disaster, hardware failure, and internet network problem etc. To increase website services’ system reliability and optimal service, infrastructure system that support server cluster schema is needed. The objective of infrastructure system that support server cluster schema is to increase website services’ system reliability and minimize downtime. Server cluster allow website services to look undisturbed on the user’s view even though there are some problems happening in the main server such as power shortage, because the website services is being serve by backup server using failover function. Infrastructure’s requirement for implementation of cluster server system at least needs to be double from the main system used, so that when the main system had hardware or software problems the backup system can serve website services just as good as the main system. It is hoped that website services will always available and the services is undisturbed even though there are problems in the infrastructure.
Neural-network's way to refine keystroke-information for high quality classification purposes

A user’s typing manner defines identity of a user because typing rhythm of every user is always unique due to its link with behavior, style and mental attitude of user. On account of this, keystroke-feature creates a behavioral biometric recognition system. But timing based typing information can be deceptive also if information is shared by user half-heartedly. In this work neural-network-based classifier systematically investigates, presence of less significance in given dataset. Entries of few users are identified and eliminated from the data set, having relatively large misclassification errors. These entries are result of negative participation of some users during data collection process and during authentication process these entries may deteriorate performance-accuracy. This paper consists of different sets of password-entries based timings (of users) to be observed while classification procedure. Afterwards z–score normalization is applied to compare and analyze results of classification on original dataset and on reduced dataset.
Neural Lyapunov Redesign.

Learning controllers merely based on a performance metric has been proven effective in many physical and non-physical tasks in both control theory and reinforcement learning. However, in practice, the controller must guarantee some notion of safety to ensure that it does not harm either the agent or the environment. Stability is a crucial notion of safety, whose violation can certainly cause unsafe behaviors. Lyapunov functions are effective tools to assess stability in nonlinear dynamical systems. In this paper, we combine an improving Lyapunov function with automatic controller synthesis in an iterative fashion to obtain control policies with large safe regions. We propose a two-player collaborative algorithm that alternates between estimating a Lyapunov function and deriving a controller that gradually enlarges the stability region of the closed-loop system. We provide theoretical results on the class of systems that can be treated with the proposed algorithm and empirically evaluate the effectiveness of our method using an exemplary dynamical system.
Probabilistic Programming Bots in Intuitive Physics Game Play

Recent findings suggest that humans deploy cognitive mechanism of physics simulation engines to simulate the physics of objects. We propose a framework for bots to deploy probabilistic programming tools for interacting with intuitive physics environments. The framework employs a physics simulation in a probabilistic way to infer about moves performed by an agent in a setting governed by Newtonian laws of motion. However, methods of probabilistic programs can be slow in such setting due to their need to generate many samples. We complement the model with a model-free approach to aid the sampling procedures in becoming more efficient through learning from experience during game playing. We present an approach where combining model-free approaches (a convolutional neural network in our model) and model-based approaches (probabilistic physics simulation) is able to achieve what neither could alone. This way the model outperforms an all model-free or all model-based approach. We discuss a case study showing empirical results of the performance of the model on the game of Flappy Bird.
Distilling the Knowledge from Normalizing Flows

Normalizing flows are a powerful class of generative models demonstrating strong performance in several speech and vision problems. In contrast to other generative models, normalizing flows are latent variable models with tractable likelihoods and allow for stable training. However, they have to be carefully designed to represent invertible functions with efficient Jacobian determinant calculation. In practice, these requirements lead to overparameterized and sophisticated architectures that are inferior to alternative feed-forward models in terms of inference time and memory consumption. In this work, we investigate whether one can distill flow-based models into more efficient alternatives. We provide a positive answer to this question by proposing a simple distillation approach and demonstrating its effectiveness on state-of-the-art conditional flow-based models for image super-resolution and speech synthesis.
Complex-Valued Vectors for Word Representation

Real-valued word vectors (RWV) often perform poorly when showing semantic relations such as the ambiguity of the word itself (“spring” can refer to a kind of season or fountain) and the polarity between words (words “love” and “hate” have a high degree of similarity due to their similar distribution). Although dynamic word vectors alleviate these problems, such methods are still lacking interpretability. Inspired by quantum theory, we believe that basic reasons are insufficient modeling ability of RWV and weak abstract ability of language models. To solve the above problems, we propose to use complex-valued word vectors (CWV) for the representation, which can naturally model semantic relations of words. We also design an explicable lexicon-extended quantum probability neural network (LQPNN) based on the theory of quantum measurement to training CWV. Experiments on three datasets of classification demonstrate the effectiveness of our model, which achieves superior performances.
Verifiable Computation over the Helix Tangle

The cryptocurrency platforms such as BitCoin and Ethereum rely on Proof-of-Work (PoW) consensus algorithm. Following the PoW, the nodes that solve the computationally intensive cryptographic puzzle is given the opportunity to create the next block in return for an incentive. Such puzzle-solving nodes are called “mining nodes,” and its owners’ are referred to as miners. Mining nodes are powerful computation platforms with the ability to perform computationally-intensive tasks. Although contemporary PoW computations demand high computation resources, the outcome of the PoW is not practical as the result of the computation is not used for any other applications except securing the blockchain. Using the mining nodes to execute practical algorithms for applications such as artificial intelligence, protein folding, and video processing would increase the effectiveness of the mining nodes while securing the blockchain. However, the distribution of computation tasks and sensitive data among trustless mining nodes leads to security vulnerabilities. Besides, the lack of technologies for verifying the result of the computation performed by the mining nodes makes verifiable computation impractical. In this work, we formulate the verifiable computation problem, discuss the existing work, and propose a novel platform for verifiable computation for the Helix Tangle.
THE IMPORTANCE OF DEVELOPING THE DIALECTICAL THINKING CAPACITY OF STUDENTS AT THE MILITARY SCIENCE ACADEMY IN VIETNAM

Materialistic dialectical thinking is a type of thinking that develops at the highest level of thinking, plays an important role in the process of world perception and human practical activities. In this article, the author focuses on analyzing the importance of developing the dialectical thinking capacity of students at the Military Science Academy in Vietnam in developing the ability to acquire and store Marxism-Leninism scientific knowledge, whose core is the materialistic dialectics, applying worldview, materialistic dialectical methodology in learning, training and scientific research; the capacity to think logically, synthesize existing knowledge, create new knowledge, the capacity to summarize the practice in learning, training and scientific research.&#x0D; &#x0D; &lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0782/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
Identifying the Age Using Face Image Using DWT, LBP, SVM and k-NN

ABSTRACT The research related to identifying the age using face images has become progressively more important, due to the fact it has a multiplicity of potentially helpful applications. In this paper we survey the complete age synthesis or age estimation from face images techniques. Automatic facial age identifying is one of the main issues in pattern recognition which shows the age of human according to her/his facial expressions. Basically, age detection/estimation is a process of identifying the actual (or approximate) age of human. An identifying the age system is usually composed of aging feature extraction and feature classification; both of which are important in order to get better the performance. Facial features are measured one of the important personal behavior. This can be used in numerous applications, like face recognition and age estimation. The importance of these applications lies in numerous areas, like defense applications, law enforcement applications, and attendance systems. Identifying the age is classification of a face image with exact actual age or age group. In this paper, we are going to plan a system to identify the age using face images which is based on Discrete Wavelet Transform (DWT) and Local Binary Pattern (LBP) for feature extraction and Support Vector Machine (SVM) and k-NN (k-nearest neighbor) for classifier. Our planned approach has been developed, tested and trained using the database FG-NET. Keywords: DWT, LBP, SVM, k-NN, Feature extraction, Classification
Rafiqul Huffazh: An Android Application using Quran Automatic Speech Recognition for Assisting Muroja’ah

Muroja’ah is reciting Quran verse (ayat) in order to recall the verses that have been memorized. This activity is necessary for people who memorizes Quran (in whole or in part). Muroja'ah is better performed in front of a teacher or companion in order to obtain feedbacks and evaluations, but some people might not be able to find one due to some reasons. A mobile application using Automatic Speech Recognition (ASR) to recognize Quran recitation can be used as an alternative to replace a teacher’s or companion’s role in assisting muroja’ah. Currently, some Quran mobile applications using ASR are available, but none of these is suitable to be used for assisting muroja’ah. Therefore, a new mobile application using ASR for assisting muroja’ah - named Rafiqul Huffazh - is developed in this project. The main feature of Rafiqul Huffazh is to transcribe Quran recitation of user memorization, evaluate the transcription based on the type of error defined and calculate the user score in performing muroja’ah. The application back-end used to transcribe Quran recitation is also developed in this project. The application has passed all the functional testing. Usability testing has also been done and it is concluded that the application interaction is considered suitable for assisting muroja'ah, however its appearance and interaction need further development in order to be more user friendly.
A multi-cloud environment for teaching relational database services

In today's business world, it has become standard practice to use cloud computing to host data and application alike. Instead of equipping with server rooms with expensive yet soon becoming outdate...
Decentralized Multi-Authority ABE for DNFs from LWE.

We construct the first decentralized multi-authority attribute-based encryption (\(\mathsf {MA}\text {-}\mathsf {ABE}\)) scheme for a non-trivial class of access policies whose security is based (in the random oracle model) solely on the Learning With Errors (LWE) assumption. The supported access policies are ones described by \(\mathsf {DNF}\) formulas. All previous constructions of \(\mathsf {MA}\text {-}\mathsf {ABE}\) schemes supporting any non-trivial class of access policies were proven secure (in the random oracle model) assuming various assumptions on bilinear maps.
Brief Idea on Indexing and Citation

This paper gives an idea about indexing and citation from its history to the merits of Citing and Indexing through review of articles published. Indexing is a way to optimize the performance of a database by minimizing the number of disk accesses required when a query is processed. Citation is the Index of presence of another work. Recent literature has been reviewed to help the scholars understand the importance of Indexing and Citation. This paper would simply the meaning and uses of Indexing and Citation. Core Literature review from secondary data sources available such as Journal articles, articles published in websites and internet are taken for briefing about the idea of indexing and Citation. The pattern of Indexing and Citation from early 1500's to recent time has been studied. Indexing started with printing era as in the earlier days no books were identical. Printing was the first form of Indexing. Citation has helped reader to track down the sources one used by citing them accurately in your paper by way of footnotes, a bibliography or reference list. This paper will help the researchers to understand the importance of using Indexing and citation.
The return of Eratosthenes: Secure Generation of RSA Moduli using Distributed Sieving.

Secure multiparty generation of an RSA biprime is a challenging task, which increasingly receives attention, due to the numerous privacy-preserving applications that require it. In this work, we construct a new protocol for the RSA biprime generation task, secure against a malicious adversary, who can corrupt any subset of protocol participants. Our protocol is designed with generic multiparty computation (MPC), making it both platform-independent and allowing for weaker security models to be assumed (e.g., honest majority), should the application scenario require it. By carefully postponing the check of possible inconsistencies in the shares provided by malicious adversaries, we achieve noteworthy efficiency improvements. Concretely, we are able to produce additive sharings of the prime candidates, from multiplicative sharings via a semi-honest multiplication, without degrading the overall (active) security of our protocol. This is the core of our sieving technique, increasing the probability of our protocol sampling a biprime. Similarly, we perform the first biprimality test, requiring several repetitions, without checking input share consistency, and perform the more costly consistency check only in case of success of the Jacobi symbol based biprimality test. Moreover, we propose a protocol to convert an additive sharing over a ring, into an additive sharing over the integers. Besides being a necessary sub-protocol for the RSA biprime generation, this conversion protocol is of independent interest. The cost analysis of our protocol demonstrated that our approach improves the current state-of-the-art (Chen et al.-Crypto 2020), in terms of communication efficiency. Concretely, for the two-party case with malicious security, and primes of 2048bits, our protocol improves communication by a factor of ~37.
Information Support of Scientific and Methodological Guidance of Scientific Research in the Field of Linguistics in the Russian Academy of Sciences

It is proposed to create an information and reference system containing complete and comprehensive information about the scientific and scholarly results achieved by the RAS institutions, scientific departments and researchers in the field of linguistics. The reference system should provide information support for high-quality scientific and methodological guidance from the relevant branch of the Russian Academy of Sciences. The classification of information objects describing scientific and scholarly results includes both traditional forms of writing (publications, reports, dissertations) and the new digital ones (linguistic databases, websites, corpora, accounts, etc.). The preliminary results of creating such a system are described. The functions of the help system are listed. The updated version of the section “Linguistics” of the State rubricator of scientific and technical information is offered.