Reviewerly/exHarmony huggingface dataset:
Disaster Avoidance in Google Cloud Implementations

One of the great benefits of cloud-based services is its ability to provide easy deployment [8].Then, the right security mindsets and awareness for proper cloud administration will pay off more, to securely utilize these services.However, as all cloud providers will always saythe security of the cloud is their responsibility, the security in the cloud lies with the client users.This saying invariably makes the study of what the users of these cloud services need to know and act on so much important.The focus in this study will be on Google cloud, a user-friendly and cost-saving cloud, which offers good ROI and peace of mind for business users.Google Cloud Platform (GCP) and G Suite (now Google Workspace), are the distinct Google entities that get cloud customers set up completely for the journey to Google Cloud services' adoption [6].
Multivariate analysis and geochemical assessment of heavy metals pollution in surface sediment from euphrates river, Iraq

Heavy metals and physical-chemical parameters in surface sediment were collected from twelve sites in the Euphrates river, Iraq, during October, and November of 2018. The high level of Cd and Pb co ...
Pelatihan Mikrokontroler Dalam Pengenalan Robotika Sebagai Respon Revolusi Industri 4.0 Di SMK Media Informatika Dasana Indah Tengerang

Industry 4.0 fundamentals involve at least 4 thing : interconnection (machines, devices and people are connected), information transparency (data analysis needs), decentralized decisions (effects of interconnection and information transparency) and technical assistance (the purpose of industry 4.0). Collaboration between machines / devices and humans is very important to implement Industry 4.0. In this collaboration, the role of the microcontroller as a connector between machines and humans. Microcontroller Training for Introduction of Robotics as a Response to the Revolution of Industry 4.0 at SMK Media Informatika Dasana Indah Tengerang is aimed for students and teacher so they know about Industry 4.0 and its application in microcontroller programming. Therefore the method of PKM program consists of seminar and workshop. The seminar explained about Industry 4.0 Revolution and the workshop is programming Line Follower which is embedded with Arduino Uno. Result of this PKM program in the form of industry 4.0 revolution seminar combine with microcontroller programming workshop, this combination give bigger impact compared with just given a seminar or just a workshop. The students and teacher who attend this event get additional knowledge about Industry 4.0 and how to program a microcontroller.
DIAGNOSTICS METHOD OF INTERPERSONAL RELATIONS BETWEEN THE CURATOR AND STUDENTS

The method of diagnosing interpersonal interactions of curators and students is designed to study the perception of curators and students in the academic group about themselves and the curator, as well as to study the relationship between curators and students of the group. The method determines the type of attitude to the curator in self-assessment and mutual assessment. The technique is constructed according to the type of Likert scale. The statements in the form of small crafts in Ukrainian folklore are selected for evaluation - proverbs and sayings, which in content are the quintessence of folk ideas about human relations, and in form - concise and easy to understand. In addition, a statement in "metaphorical" form is subjectively easier to evaluate than a direct answer. There are variables that determine the type of attitude to the curator: "Understanding and democracy"; "One step ahead: attentiveness and foresight", "Efficiency, teamwork efficiency". These characteristics reflect various aspects of interpersonal interaction in the academic group, where the curator may pay attention to each of the participants in the educational process, and may be careless and biased; can organize team activities, express their ideas and wishes; predict the likelihood of problematic, conflict situations and manage the process of their resolution, and may, conversely, be passive, inactive, critical of social phenomena and others, provoke conflicts and misunderstandings. The interpersonal interaction of the curator and students is analyzed in a three-dimensional space, which is created by axes: understanding and democracy - misunderstanding and despotism; attentiveness and foresight - inattention and short-sightedness; efficiency, effective teamwork - passivity, unproductive teamwork. The method can be used to assess the behavior of the curator in the assessment of students (from the outside), for self-assessment of the curator and the description of the ideal curator. Depending on the level of diagnosis, the instructions change.
Analysis of Dilithium post-quantum electronic signature resistance to fault attacks

Ю.І. ГОРБЕНКО, канд
Ekstraksi Informasi Semantik dan Spatiotemporal pada Artikel Online Terkait Bencana di Indonesia

Indonesia is one country that has a high risk of natural disasters. Ranked in 36 out of 172 countries in disaster index and having 2,372 disaster incidents in 2017, actions need to be taken to minimize the impact of natural disasters. One of it is to do a hazard map modeling. In making hazard maps, several approaches can be used, one of which is the semantic approach to extract disaster information. Therefore, this study aims to develop a system that can be used to extract spatiotemporal and semantic information related to natural disasters in Indonesia. This study uses the NLP method in conducting the information extraction process and carried out using the GATE (General Architecture for Text Engineering) application. In processing Indonesian language articles, it is necessary to develop the plugin because the Indonesian information structure is different from the default information structure in GATE application. The plugin development process is done by using ontology as the basis for determining semantic information. Literature study was carried out related to government regulations that further explained the need for semantic and spatiotemporal information about disaster events. system performance developed produces a precision value of 38% and a recall value of 32%. this is because the system experiences some difficulties in carrying out the information inference process. The reason for low precision rate is because the rules used in the inference process to pair the three types of information still cannot accommodate the variation of information positions in different sentences.
Aplikasi Perbandingan Sistem Perbaikan Citra Digital menggunakan Metode Dekonvolusi Wiener, Lucy Richardson, dan Regularized

In some cases, there is some damage to an image caused by interference during the image capture process. Blurred image damage can be overcome by deconvolution digital image processing. There are various methods to repair the image blur damage, including using the Regularized, Wiener, and Lucy Richardson deconvolution methods. Each blurring image repair method produces a different debluring result of image processing. Image comparison application was built to compare the ability of image restoration results to a Motion Blur image with the algorithms used in deconvolution. Image restoration comparison parameters used include determining the MSE and PSNR values between the test image and the deconvolved image. The results of implementing the comparative application of Motion Blur image improvement to 270 blur simulations consisting of 9 different levels of image blurring, obtained the average PSNR value for Wiener's deconvolution = 59.16dB, Lucy Richardson = 26.92dB and Regularized = 36.94dB.Keywords:Image Restoration; Lucy Richardson; Motion Blur; Regularized; Wiener.
On the Complementary Nature of Knowledge Graph Embedding, Fine Grain Entity Types, and Language Modeling

We demonstrate the complementary natures of neural knowledge graph embedding, finegrain entity type prediction, and neural language modeling.We show that a language model-inspired knowledge graph embedding approach yields both improved knowledge graph embeddings and fine-grain entity type representations.Our work also shows that jointly modeling both structured knowledge tuples and language improves both.
Rancang Bangun Sistem Informasi Akademi: Modul Sistem Absensi Berbasis Mobile dan Web pada Universitas Universal

The academic information system that focuses on the attendance module is a continuation of the manual attendance that imposes the use of attendance papers that are paraphrased by students. Attendance modules at Universal University can be designed utilizing Internet technology and network, where students only use smartphones to scan Quick-Response Code (QR Code) and web-based applications for lecturers to verify attendance. The attendance module is designed using real-time data processing. The software process Model used is the waterfall model and assisted with analysis using Unified Modelling Language (UML). The design of the application uses the PHP programming language for Web applications and Java for mobile applications, as well as databases using MySQL. The result of the design of the build attendance module in the form of a mobile application for use by students who can scan QR Code as attendance, and a Web application to be used by the lecturer as an attendance verification that has scanned QR Code and students who are not present. Attendance is more effective online when compared to manual attendance.
The problem of the formation of subjective-leadership qualities among cadets of military educational organizations of higher education of the troops of the National Guard of the Russian Federation: cognitive and empirical aspect

Introduction. The problem of leadership in scientific research is given a lot of attention. However, this problem remains relevant for a large number of scientific areas. The formation of leadership qualities of a person is interested in the pedagogical composition of power higher educational institutions. Materials and methods. The main methods of research were: analysis of literature on the problem of research, systematization of the data obtained, conducting an empirical study of the influence of various factors on the formation and development of leadership qualities of future officers of the Russian Guard. Results. The article presents the experience of studying the leadership qualities of university cadets of the National Guard troops receiving the specialty of a military psychologist. There is a positive dynamics of leadership qualities throughout the entire period of study at a military university, as one of the most important conditions for readiness for professional activity, and a conclusion was made about the stability of the main management style in the fifth year. Discussion and Conclusions. During the study, it was established that in order to develop the leadership qualities of the future officer of the National Guard troops, it is now necessary to solve the following tasks in the educational process of a military university: development of awareness of his/her purpose as an officer, perseverance in realization of assigned tasks, steady desire to be a leader, self-confidence, readiness to make decisions and take responsibility, consistency, perseverance in realization and fulfillment of assigned tasks, awareness of own strength, faith in achievement of the goal. Keywords: leadership, professionalization, professionally important personal qualities, need for self-development, management style.
Penerapan Media Virus (Visual Rumus) Pada Materi Lingkaran Untuk Meningkatan Hasil Belajar Kelas VI SDN Opo Opo Kec. Krejengan Kab. Probolinggo

Mathematics learning is one of the subjects that is interesting to point out because learning emphasizes providing direct learning experiences for students to find out and do something so that they are able to explore and understand nature scientifically. In understanding the concept of learning Mathematics, sometimes students find it difficult to digest a material. In other words, these students need a learning media that does not rely on imagination alone, but is concrete so that students understand the material taught by the educator more easily. A learning method is needed that involves students directly in the mathematics learning process. Based on the results of this study, it shows that the learning achievement of Mathematics in grade VI SDN Opo - Opo is still not satisfactory. This can result in low student achievement in learning Mathematics. This is due to inaccurate learning media used by educators so that it has an impact on the less attractive learning of MATHEMATICS for students. On the basis of this research, it can be concluded that the Virus media (Visual Formula) can improve the learning achievement of grade VI students at SDN Opo - Opo, Krejengan District, Probolinggo Regency.
Outreach activities at LHCb

The LHCb collaboration has a wide outreach programme covering physics news, detector photos and videos, masterclasses and exhibitions at the CERN site.The presence on social media, and on web in general, is the first line in making the public aware of the experiment activities.At the experimental site, guides are aided by posters and real detector parts to make visitors more involved in the tour.The masterclasses in particle physics include an example of real data analysis at LHCb and are designed to inspire high-school students, the scientists of tomorrow.
Generating Data on Individual Learning Paths for Classification Using Deep Learning Networks

The article considers information about individual learning paths as a set of observations with a large number of features.To reduce the amount of information, it is proposed to classify samples using deep learning networks.Selections are saved either in a relational database or as an ontology.To device training algorithms, a generation of model data instead of real ones, which is currently missing, is proposed.Data are converted from relational tables to ontology using the ANTLR compiler generator.Based on the generated data and qualimetric estimates, the integral characteristics are calculated using a method also proposed in the article.The final results will be a quality assessment of the classification based on deep learning networks.The methods and approaches proposed by the authors are universal and can be used in any higher educational institution to select an algorithm for their qualitative classification.
Correction to: Semi-Supervised Sentiment Analysis of Portuguese Tweets with Random Walk in Feature Sample Networks

Inadvertently the authors of this chapter released it without correcting an error in the title. This has now been corrected and the corrected title reads: “Semi-Supervised Sentiment Analysis of Portuguese Tweets with Random Walk in Feature Sample Networks”.
Entanglement-breaking of quantum dynamical channels

Entanglement is a key issue in the quantum physics which gives rise to resources for achieving tasks that are not possible within the realm of classical physics. Quantum entanglement varies with the evolution of the quantum systems. It is of significance to investigate the entanglement dynamics in terms of quantum channels. We study the entanglement-breaking channels and present the necessary and sufficient conditions for a quantum channel to an entanglement-breaking one for qubit systems. Furthermore, a concept of strong entanglement-breaking channel is introduced. The amendment of entanglement-breaking channels is also studied.
Prediction of Water Use Using Backpropagation Neural Network Method and Particle Swarm Optimization

Clean water production has not been well considered between the balance of water use by the community and the production of clean water that is in accordance with the needs of the community. Prediction of water use in meeting the daily needs of the community is very necessary in order to be able to produce efficient water. This research can help PDAM Kota in Kalimantan to be able to produce clean water in accordance with the use of clean water by the community. The Backpropagation Neural Network method focuses on the recapitulation of water use by the community. For better prediction results, optimization is done with Particle Swarm Optimization (PSO). It is expected that the results in this study can predict community water use in daily activities. The test results showed that the Prediction results had RMSE of 0.040 with parameters for training cycle 600 values, learning rate 0.1 and momentum 0.2, and neuron size was 3 and in particle swarm optimization population size 8, max.of gene 100, inertia weight value 0.3, the value of local best weight 1.0 and global value of best weight 1.0
The right to personal data protection, digital technologies and the pandemic for COVID-19 in Colombia

COVID-19 pandemic has generated additional social and political impacts beyond those strictly related to health, leading countries to, within the context of declared states of emergency, temporarily limit some civil rights and liberties in order to preserve their citizen’s life and health On the other hand, it has accelerated the digital transformation with the development and use of technological tools to complement public health measures Several international organizations have voiced their concern about the violation of the right to personal data protection in this new scenario and have even proposed ethical guidelines to be taken into account This article will analyses the measures that have been implemented in Colombia during COVID-19 pandemic, from the actual perspective of the legal framework of the right to personal data protection, and how its principles and rights may be reinterpreted in the light of these new ethical recommendations Copyright © 2020 Ana Gomez-Cordoba, Sinay Arevalo-Leal, Diana Bernal-Camargo, Daniela Rosero de los Rios
PENGEMBANGAN MODUL PELAKSANAAN KURIKULUM 2013 UNTUK MENINGKATKAN PROFESIONAL GURU ANAK USIA DINI

This research uses a research and development approach. The study aimed to develop early childhood teacher modules in developing learning devices following the conditions of the local area. Data collection techniques using questionnaires and Focus Group Discussion. Data analysis techniques using descriptive analysis and t-test. The research samples were early childhood teachers in Ternate city and early childhood education experts. The 2013 Early Childhood Education curriculum provides an opportunity for schools to develop learning models following the local context. Child learning starts from around the house and school so it is not uprooted from its cultural roots. In this curriculum, teachers are required to be able to develop their learning tools that are appropriate but on the other hand, there is a lack of books or modules that can be a guide in developing these learning devices. Based on this, the teacher module was developed as a practical guide in developing learning devices. Based on the results of the study, data from early childhood teacher modules was effectively used to improve the ability of teachers to develop learning devices. It is recommended that early childhood teachers in the urban area of Ternate be able to use this module to develop learning.
VOICE IDENTIFICATION BASED ON THE I-VECTOR AND DEEP NEURAL NETWORKS USING SHORT UTTERANCES

Text-independent voice recognition of the user using short sentences is a very difficult task due to the large spread and inconsistency of the content between short sentences, in order to improve user recognition by voice, it is planned to highlight several sets of distinguishing features that contain more information related to the voice. The results show that the i-vector DNN system is superior to the GMM i-vector system for various durations. However, the characteristics of both systems deteriorate significantly as the duration of the sentences decreases. To solve this problem, we propose two new nonlinear mapping methods that train DNN models to map i-vectors extracted from short sentences to their corresponding i-vectors of long sentences.
A LOOK AT THE CONTEMPORARY CHALLENGES IN THE PREPARATION OF A FUTURE TEACHER OF MATHEMATICS

The article considers and reviews the monograph of I.A. Akulenko "Competence-oriented meth-odological preparation of the future mathematics teacher of profile school (theoretical aspect)". The peer-reviewed monograph presents the scientific foundations of the theory of competence-oriented methodological training of the future teacher of mathematics of the profile school. The specifics of the work of the teacher of mathematics of the profile school are shown. The analysis of his methodi-cal activity in the educational process in mathematics is made. The conclusion about the necessity and possibility of improving the system of methodical preparation of the future teacher for work in the conditions of profile differen-tiation of teaching mathematics in the profile school is motivated. The methodical system of competence-oriented methodical preparation of the future teacher of mathemat-ics of profile school is designed.
Geochemical Characteristics of Amphibolites in Parts of Iseyin-Oyan Schist Belt, Southwestern Nigeria

Amphibolite is an important lithologic unit of the Nigerian basement complex that are commonly intercalated within metasedimentary sequences. Disseminated grains of sulphide minerals and base metal deposits are reported to occur in amphibolites and some other lithologies in other schist belts of Nigeria apart from the Iseyin-Oyan schist belt. Detailed geochemical study of amphibolitic rocks in this schist belt is scarce in literature, whereas none exist for the area under study, thus, this study is aimed at delineating the amphibolites within the Iseyin-Oyan schist belt around Itasa area with detail appraisal of their petrography and geochemical characteristics. A geologic field mapping was undertaken, and fresh representative amphibolite samples were obtained. Petrographic and geochemical studies of the samples were carried out with a view to understand their nature and petrogenetic characteristics. Geochemical data were elucidated using diverse geochemical discrimination diagrams. The amphibolites occur as lenses of small to large rocky boulders trending NNE-SSW and are essentially basal to quartz mica schist. Modal compositions revealed that they are dominantly composed of hornblende and plagioclase. XRD and mineral chemistry revealed that the plagioclase ranged from andesine to anorthite while hornblende is mainly magnesiohornblende. Geochemical data and discrimination diagrams revealed that the amphibolites are formed from basaltic to basaltic-andesite protolith that are of tholeiitic nature and had suffered crustal contamination. Tectonic discrimination diagrams indicated that the rocks were emplaced in the Mid Ocean Ridge but had been affected by collision due to Pan African Orogenic tectonic event.
Beyond the EM algorithm: constrained optimization methods for latent class model

Latent class model (LCM), which is a finite mixture of different categorical distributions, is one of the most widely used models in statistics and machine learning fields. Because of its noncontinuous nature and flexibility in shape, researchers in areas such as marketing and social sciences also frequently use LCM to gain insights from their data. One likelihood-based method, the expectation–maximization (EM) algorithm, is often used to obtain the model estimators. However, the EM algorithm is well-known for its notoriously slow convergence. In this research, we explore alternative likelihood-based methods that can potential remedy the slow convergence of the EM algorithm. More specifically, we regard likelihood-based approach as a constrained nonlinear optimization problem, and apply quasi-Newton type methods to solve them. We examine two different constrained optimization methods to maximize the log-likelihood function. We present simulation study results to show that the proposed methods not only converge in less iterations than the EM algorithm but also produce more accurate model estimators.