Reviewerly/exHarmony huggingface dataset:
EDUCATION FOR POOR PEOPLE AND VULNERABLE GROUPS. A LOOK FROM ECUADOR

The world is changing rapidly as a result of technological advancement. One of the effects of this transformation is closely related to education. Education is an essential element in achieving growth, development and the improvement of the living conditions of the inhabitants of a country. Quality education, which increases the levels of schooling and knowledge of the population, is an indispensable condition for social development. From this perspective, vulnerability is a social trait that has marked the realities of many countries, but more so in the Latin American context, specifically because of the development impacts that have been implemented from the development of the current knowledge society. This element is the greatest challenge that the educational system has, to implement good, diversified strategies with positive results in the face of the multiple social realities of the country where it includes the possibility of varying, both, the classroom strategies and the didactic forms, but with equivalent learning results. The objective of this article is to make an assessment of the different elements that affect the access to education of the different vulnerable groups and their possibilities of study at present as a result of the COVID-19 pandemic.
The Magic of Summation Sequences: Applied Combinatorics and Graph Theory

Mathematics is a useful basis for motivating self-working card tricks. In this paper, we expand the realm of self-working magic tricks through the examination of a novel type of universal cycle called a Summation Sequence. An analysis of the graph theoretical and combinatorial structure of Summation Sequences reveals, firstly, the existence of operations that preserve the properties of Summation Sequences, and, secondly, a special type of Summation Sequence called a Symmetric Sequence. We apply our most important results to the realm of card magic, where we exploit the properties of Summation Sequences to motivate various card effects.
A Mixed-Precision Binary Neural Network Architecture for Touch Modality Classification

Binary Neural Networks (BNN) have been proposed to address the computational complexity and memory requirements of Convolutional Neural Networks (CNN). However, in most of the applications, BNNs suffer from severe accuracy loss due to the 1-bit quantization. In this paper, a Mixed-Precision Binary Weight Network (MP-BWN) is proposed as a compromise between CNN and BNN. Compared to traditional binary networks, MP-BWN offers better performance with an acceptable increase in the network size. MP-BWN achieves up to 99% reduction in both the number of operations and the network size compared to similar state-of-the-art solutions. When validated on a touch modality classification problem, the MP-BWN surpassed similar existing solutions by achieving a classification accuracy of 77.8%.
Automatic Detection of Human Blood Group with Special Case in Low Resolution Using Image Processing

Blood group identification during emergency situation is very important. At present image processing technology will give the result very quick and it is widely used in medical field. In this paper, we are proposing blood group identification using image processing technology. This method is fast and accurate than the traditional method. Sometimes due to some human careless, detection of human blood could be inaccurate, these errors can be reduced by using image processing technology. By using image processing technology small error in the output can be calculated and human mistakes is reduced. By using This approach, we can determine the blood type quickly and accurately than the manual method.
Using blockchain for trustworthy mobile contact tracing

As the number of COVID-19 cases continues to climb globally, lots of public healthcare safety measures are being proposed. Apart from safety measures such as social distancing, mask wearing and per...
LANDASAN PENGEMBANGAN PEMBELAJARAN

Learning is a process carried out by educators to students so that they can acquire knowledge and knowledge, master knowledge and habits, and shape behavior and skills. Likewise with the development of learning, if a learning development does not have a strong foundation or foundation, the learning development carried out will be easily swayed and will be detrimental to both educators and students. The foundation of learning development can be interpreted as an idea, assumption or principle that is the basis or starting point in the development of learning. This journal discusses the meaning of the foundation of learning development and the application of the basic method of learning development. Poles, tiles, glass, and so on, in a building, will not be able to stand and stick without the foundation.
Применение эллиптических кривых в защите информации

The article is devoted to the study of elliptic curves in cryptography. Particular attention is paid to their advantages over other public-key cryptographic systems, as well as a platform is proposed for the hardware implementation of the elliptic curve in cryptography.
Modeling thermal processes using electrical equivalent circuits in digital twins of technical devices

One of the promising areas of digitalization of the economy today is associated with the concept of digital twins of technical systems. Digital twins based on simulation models of technical devices, which are calibrated according to the results of experimental studies on a real-time device are of great interest. Such models allow us to conduct preventive analysis of the operation consequences of these devices in various modes. Thus, a problem occurs to develop parametrically coupled models of physical processes of various natures that underlie the principles of operation of these devices. Currently, for these purposes, simulation software packages are used. MatLab Simulink software is the most popular one. However, not all such software packages provide tools to work with chain models of all physical processes that are of the user interest. Thus, the purpose of this article is to develop methods to construct digital twins of technical devices using models of arbitrary physical processes (in particular, thermal) based on electrical equivalent circuits. It unifies the task of modeling processes based on circuit theory. To develop the method to construct digital twins, the authors have applied the phenomenon of isomorphism of equations of physical processes based on the theory of circuits that is based on the theory of ordinary differential equations. The simulation has been carried out in the MatLab Simulink environment using the SimScape library for modeling physical processes. Assumptions typical for circuit theory are made during simulation. A method has been developed to construct simulation models based on the use of electrical equivalent circuits of physical processes of an arbitrary nature. In contrast to existing approaches, where the analogy method is used to simulate one of the processes of the researcher interest, it is proposed to develop a single integrated model of all physical processes underlying the operation of this class of devices. It will reduce the level of requirements for simulation systems by limiting the requested functionality of these systems to electrical circuits only. The proposed method can be used as the basis for the development of digital twins of technical devices that allow simulating their operation in arbitrary modes, considering a variety of related factors of different physical nature.
A Lattice-Based Anonymous Authentication for Privacy Protection of Medical Data

With the process of informatization of medical institutions, the issue of protecting patients’ personal privacy information has also attracted more and more attention. At the same time, the development of quantum computers has also caused people’s attention post-quantum encryption algorithms. Lattice-based cryptography is a typical post-quantum encryption algorithm. In order to protect the privacy of medical information in the quantum computer environment, a medical information collection model that resists quantum attacks is proposed in this paper. The model is based on lattice-based anonymous identity authentication scheme. The lattice-based anonymous authentication scheme proposed in this paper has proved its security in the random oracle model.
Extended Abstract: Facies Mapping of the Utica Shale, Point Pleasant, and Trenton/Lexington Formations in Northeastern Ohio

Abstract The Ordovician Utica shale play is a major oil and gas producing interval in the Appalachian Basin. The Utica shale play can be found as far as New York and Canada into Indiana and Kentucky. The Utica shale play consists of the Utica shale, Point Pleasant Formation, and Trenton/Lexington limestones. The shallow marine fossiliferous limestones of the Trenton and shallow marine shaly limestones of the Lexington are overlain by an interbedded shale and limestone of the Point Pleasant Formation, which grade into the deeper marine interbedded shales and limey shales of the Utica. Previous research of the play covers multiple states. Geochemical and petro-physical data has been conducted for the play with little to no research being done on using litho-facies and electro-facies to understand the relationship of total organic content (TOC) to density or other factors. The data collected from lithofacies and electrofacies are correlated with production to better understand the driving mechanisms for the Utica shale play. The use of Kline Por 3 (#6434) core and petrophysical logs provided by the Ohio Geological Survey and Department of Natural Resources from the research area, are the data for the litho-facies and electro-facies. The use of a computer program called Geologic Analysis via Maximum Likelihood System (GAMLS) will create well to well cross sections. This will take well logs and separate the lithologies into groups based on the different combinations of petrophysical data. This will provide a model for the identified lithofacies and electrofacies patterns and/or trends in northeastern Ohio (Fig. 1).
Open Scholarly Metrics for the Journal of Open Source Software

The Journal of Open Source Software (JOSS) is a developer friendly, open access journal for research software packages published as open source software. JOSS started publishing in 2016, and has published more than 1,500 articles so far. After five years and that many articles, it is time to have a closer look at how JOSS content is reused.
Learning together in a global pandemic: practices and principles for teaching and assessing online in uncertain times

The higher education sector has been massively disrupted by COVID-19. The technological changes of the past two decades have enabled a ‘blended learning’ approach. Nonetheless, most academics were not prepared to become fully online teachers with very short notice (nor were most students prepared to learn online) in 2020. Our aim was to investigate and document changes in teaching from the perspective of teaching academics in the initial semester impacted by the COVID-19 global pandemic. To that end, we surveyed and interviewed a range of colleagues in three national contexts to create brief case studies from different disciplines, with different class sizes, and from teachers with differing years of experience in teaching (on campus and online)
Real-time face mask detection on edge IoT devices

Chapter Contents: Abstract 6.1 IoT devices and object detection 6.1.1 IoT devices and object detection 6.1.2 Real-time object detection on edge IoT devices 6.1.3 A generic detection algorithm 6.2 Literature survey 6.3 Traditional feature extraction techniques 6.3.1 Histogram of oriented gradients (HOG) 6.3.2 Scale invariant feature transform (SIFT) 6.3.3 Speeded up robust features (SURF) 6.4 Traditional detection methods 6.4.1 Histogram of oriented gradients with support vector machines (HOG+SVM) 6.5 Traditional face detection techniques 6.5.1 Viola–Jones Haar cascade method 6.5.1.1 Problems with face detection 6.5.1.2 Tradeoff between speed and accuracy 6.5.1.3 Working principle of Viola–Jones method 6.6 Face mask detection 6.7 Deep learning for object detection 6.7.1 Convolutional neural networks (CNNs) 6.7.2 Object detection using deep learning 6.7.3 Faster RCNN for object detection 6.7.4 Enhancing faster RCNN with MobileNet 6.8 Internet and deep learning 6.8.1 Client–server architecture 6.9 Edge IoT architecture 6.10 Implementing an edge IoT architecture 6.10.1 Dynamic web pages 6.10.2 Backend using Node.js 6.10.3 MongoDB as database 6.11 Discussion 6.12 Conclusion References
Augmenting Cities and Architecture with immersive Technologies: Conference Workshop Proceedings

Augmented reality (AR) has many domains it can be applied to, such as collaboration, heads up display navigation and operating heavy machinery. Recently, AR has shown promise at engaging communities and enhancing individual experiences within cities. While science fiction has depicted future cities imbued with holograms, recent work has shown that AR can have more engaging applications, in areas like community engagement, personalised digital signage, and visualisation. On a consumer level, AR is most common on smartphones, particularly after the release of ARKit and ARCore - improving the functionality. Smartphone AR apps have primarily consisted of location-aware smartphone augmented reality (AR) apps, like Pokemon Go – bringing people outside and having ripple effects on the physical space through physical signage. Smart glasses are also becoming more accessible and enable the possibility to naturally integrate virtual content into our daily lives. While immersive technologies are advancing and gradually becoming accessible, further understanding is needed of their application and the potential benefits they bring to cities, communities, and individuals. This also brings up the question of how the virtual and physical spaces co-exist creating an augmented space. This year we narrowed the focus from the broader cities to how such immersive technologies (like AR and VR) can be used to improve people’s wellbeing within a city environment (such as taking someone to another world, gamifying the city, or playfully reminding people to take the stairs). For this workshop it was more important than ever to consider people’s wellbeing in cities as global pandemics and environmental issues change the way people operate in cities. This workshop has been run at MAB 2018 and ISMAR 2019, where it has received attendees from a range of different backgrounds. Many interesting insights have been brought up during the workshop around security, privacy, and use cases. After ISMAR, we guest edited a focus section in a special issue of IxDA (Interaction Design and Architectures Journal).
Chapter 1. The Mobile Revolution

Chapter 1 of Library Technology Reports (vol. 57, no. 2), “Mobile Technology in Libraries,” presents a brief overview of the mobile revolution that has taken place in the past twenty years. It covers the technology involved, current statistics focused on mobile technology growth, how mobile technology has changed business practices, emerging trends with mobile technology, and how mobile technology is affecting today’s library.
Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices

We propose the use of the vector-valued distance to compute distances and extract geometric information from the manifold of symmetric positive definite matrices (SPD), and develop gyrovector calculus, constructing analogs of vector space operations in this curved space. We implement these operations and showcase their versatility in the tasks of knowledge graph completion, item recommendation, and question answering. In experiments, the SPD models outperform their equivalents in Euclidean and hyperbolic space. The vector-valued distance allows us to visualize embeddings, showing that the models learn to disentangle representations of positive samples from negative ones.
ANALYZE NONLINEAR CONSTRAINTS NONNEGATIVE MATRIX FACTORIZATION

Processing of data with large dimensions has been a hot topic in recent decades. Various techniques have been proposed to execute the desired information or structure. Non- Negative Matrix Factorization-based on non-negatives data has become one of the favorite methods for shrinking dimensions. The main strength of this approach is the non-negative object, the object modeled by a combination of some basic non-negative parts so as to provide a physical interpretation of the object construction. NMF methods include the use of text mining, pattern recognition, and bioinformatics. The mathematical formulation for NMF did not appear as a convex optimization problem, and various types of model mathematics have been proposed to solve the problem Framework for Alternative Nonnegative Least Square.(ANLS) Are coordinates of the block formulation approaches that have been proven reliable theoretically and empirically efficient. This dissertation proposes a new algorithm to solve NMF based on the framework ANLS. This algorithm is put forward primary pivot methods to least squares problem with not – negative constraints which can overcome the limitations of the active set method. The proposed algorithm explores the reduced gradient method is a method that efficiently blocks the central pivot in the context of NMF. These algorithms also own ANLS convergence properties of the framework can be developed for the formulations and NMF with other constraints.
Chaos Algorithm of Electrical Control System Based on Neural Network Technology

Chaos is a common physical phenomenon in electrical control systems. The chaotic movement has high flexibility and sensitivity to the initial value, ergonomics and randomness of the movement trajectory. When maximizing and optimizing the design of the system, we can consider making full use of the chaotic ergonomics as the restraint of system maximization and optimization, to prevent the entire system from being trapped into a local minimum when it falls into search. The main reason for chaos optimization is to use chaotic variables to search for data within a certain range according to its availability and regularity, so that the search for chaotic variables exceeds the local minimum, and finally achieves the global maximum excellent. System optimization based on chaos theory is developing into a new global optimization method. In this paper, the chaotic algorithm of electrical control system based on neural network technology is researched. On the basis of related data, the chaotic phenomenon is generally understood, and then the characteristics of chaos are summarized on the basis, and then the chaos of electrical control system is explained. The discrimination method has laid the groundwork for the following experiments. Finally, the chaos algorithm of the electrical control system based on neural network technology is optimized. According to the experimental results, the optimized algorithm is nearly 10 s faster than the original algorithm. It can be seen that the optimized algorithm has better performance than the unoptimized algorithm.
The Minimum Edit Arborescence Problem and Its Use in Compressing Graph Collections

The inference of minimum spanning arborescences within a set of objects is a general problem which translates into numerous application-specific unsupervised learning tasks. We introduce a unified and generic structure called edit arborescence that relies on edit paths between data in a collection, as well as the Minimum Edit Arborescence Problem, which asks for an edit arborescence that minimizes the sum of costs of its inner edit paths. Through the use of suitable cost functions, this generic framework allows to model a variety of problems. In particular, we show that by introducing encoding size preserving edit costs, it can be used as an efficient method for compressing collections of labeled graphs. Experiments on various graph datasets, with comparisons to standard compression tools, show the potential of our method.
APLIKASI KOTAK SARAN MAHASISWA BERBASIS ANDROID PADA STMIK KRISTEN NEUMANN INDONESIA MEDAN

Good service quality in a university is one of the things expected by students. With the suggestionbox provided by STMIK Kristen Neumann Indonesia is one form to improve good service, butminimal students use the suggestion box because the criticisms and suggestions do not getimmediate response from the leadership, because the suggestion box is a one-way media. With theexisting problems and to take advantage of developments in information technology, the authorsbuild an Android-based student suggestion box application that can be directly responded by theleadership.
Riflessioni sulla vulnerabilità e resilienza attraverso una proposta filmica: una esperienza di didattica a distanza condotta in forma interattiva

Introduction The reorganization of someone’s way of life, the ability to transform a painful or simply stressful event a process of learning and growing following a traumatic event, involves two fundamental subjects: vulnerability and resilience. The aim of this study is to describe students’ experiences related to the issues of resilience and vulnerability order to explore the reflections stimulated by the use of films. Following the Covid-19 pandemic, an elective educational proposal for the Bachelor of Science program Nursing at the University of Turin, that has been realized since 2014, but was conducted 2020 the form of distance learning.Materials and Methods: We analyze, through the method of content analysis, the students’ experiences expressed after a narrative mandate and a reflective exercise. Personal experiences about disability have been harvested before watching the film. The opinions about resilience and vulnerability are later analyzed, using the film tool as a stimulus for personal reflection. Results: There are three themes which the qualitative analysis converge: the experience before someone’s disability, the reflections on resilience through the proposal and filmic learning tool, care strategies and resilience the proposed film. The distance learning modality was appreciated by the students who felt a more direct relationship with the expert patient, greater interactivity and more intense emotional dimension compared to the editions conducted the presence, even if they lived in the solitude of their workstations.Conclusions: The online event, with the film as a tool and the contribution of the expert patient, has been useful dealing with issues such as vulnerability and resilience order to recognize the potential benefits and assistance focused on the patient’s needs and problems.
Practical Aspect of Privacy-Preserving Data Publishing in Process Mining.

Process mining techniques such as process discovery and conformance checking provide insights into actual processes by analyzing event data that are widely available in information systems. These data are very valuable, but often contain sensitive information, and process analysts need to balance confidentiality and utility. Privacy issues in process mining are recently receiving more attention from researchers which should be complemented by a tool to integrate the solutions and make them available in the real world. In this paper, we introduce a Python-based infrastructure implementing state-of-the-art privacy preservation techniques in process mining. The infrastructure provides a hierarchy of usages from single techniques to the collection of techniques, integrated as web-based tools. Our infrastructure manages both standard and non-standard event data resulting from privacy preservation techniques. It also stores explicit privacy metadata to track the modifications applied to protect sensitive data.