Reviewerly/exHarmony huggingface dataset:
Formation model for university teachers’ monitoring skills

The problem relevance that we are studying is attributable to the need to create educational process monitoring at universities and the insufficient development of theoretical, scientific and methodological features of forming teachers’ monitoring skills in the course of their educational activities. The major aim of the study is to build a model for the formation of teachers’ monitoring skills of and its implementation into the universities’ educational process in Kazakhstan. The research methods include modeling which will allow to study this issue as a process of meaningful acquisition of university monitoring skills by teachers. The research results in this article represent a model for the formation of university teachers’ monitoring skills, show the properties of monitoring skills; develop a mechanism for introducing this model into practice. The practical significance of this article is that the model is aimed at adapting teachers to modern circumstances of professional activity in the educational sphere and is concentrated upon developing scientific and methodological support for education quality monitoring.
GEOCHEMISTRY AND PETROGENESIS OF THE CALC-ALKALINE GRANITOIDS FROM THE NORTHERN ARABIAN–NUBIAN SHIELD. A CASE STUDY FROM WADI EL-AKHDER GRANITOIDS, SOUTHERN SINAI, EGYPT

I-type granitoids emplaced during pre-collision stages of the Neoproterozoic Pan-African Orogeny, are widely distributed in the southern Sinai Peninsula and constituting 30% of the basement outcrops.Petrological, geochemical, and mineral chemistry data are presented for the I-type, Wadi El-Akhder granitic suite (AGR), in order to determine their origin and geotectonic implications.The tonalitegranodiorites of Wadi El-Akhder have geochemical characteristics of medium-K calc-alkaline, metaluminous to mildly peraluminous granitoids formed in an island-arc environment, which are conformable with well-known Egyptian older granitoids rocks (G 1 ).They have low Al 2 O 3 , FeO*, MgO, MnO, CaO, TiO 2 , Sr, Ba, and V contents, but possess high contents of Na 2 O, K 2 O, Nb, Zr, Th, and Rb.The studied AGR are generally characterized by enrichment of LILE and LREE and depletion of HFSE relative to N-MORB values, and follow assimilation and fractional crystallization (AFC) trends indicative of extensive crustal contamination of magma derived from a mantle source.The studied granitic rocks show high CaO/Na 2 O ratios (0.82-1.54) being decrease from tonalite to granodiorites, whereas they have also high Al 2 O 3 /TiO 2 ratios (16.69-27.61)increasing toward the granodiorites.These features indicate that emplacement of the granitoid were strongly affected by magma mixing of felsic and mafic melts.The chemical characteristics of the AGR are remarkably similar to those of subduction-related granitoids from the Arabian-Nubian Shield (ANS).
A systematic review on the effectiveness of virtual reality cognitive training (VRCT) and computer‐based cognitive training (CBCT) for individuals with mild cognitive impairment (MCI)

Technological advancement and enhanced education level of aging population demand more effective and evidence-based cognitive trainings. Besides conventional computer-based cognitive training (CBCT), immersive virtual reality cognitive training (VRCT) has been gaining popularity over the last decade.The overall aim of this study is to assess the effectiveness on VRCT and CBCT in five specific cognitive domains [i.e. global cognitive function (GCF), memory (Mem), executive function (EF), language (Lang) and visuospatial skills (VS)] of individuals with mild cognitive impairment. The specific objectives were to: a) identify advantages and limitations of VRCT and CBCT; b) observe and report the trend of cognitive trainings; and c) suggest future research directions.Systematic review was performed on 320 studies were yielded from five electronic databases. 18 randomized controlled trials met the PRISMA criteria, with 10 related to VRCT and 8 related to CBCT. Random-effect model was used in determining the main effect of cognitive training in 5 specific cognitive domains.VRCT provided the largest effect size on VS and Lang while the smallest on EF. CBCT provided the largest effect size on Mem and Lang while the smallest on EF. VRCT and CBCT generate an opposite effect on VS. VRCT outweighs CBCT in treatment effectiveness of GCF, EF, Lang and VS. More immersive-and-interactive experiences in VRCT may help individuals with MCI better engage in real-life experiences which supports skills generalization and reduces external distractions. CBCT tends to improve Mem but no definite conclusions can be made. Further investigation with more stringent research design and specific protocol are required to reach consensus about the optimum intervention regime.
Cybersecurity Law for Consumer Online Vaccine Sales

The development of information technology in the world has progressed so rapidly to get information, insights, products and needs in everyday life through the internet, everyone from all over the world accesses the site to conduct transactions online.Buying and selling opportunities using e-commerce/online buying and selling media which is a liaison between business actors and consumers, so that the agreement or agreement made is through online.Vaccines are biological elements that have certain characteristics and require special handling in the vaccine chain since they are produced at the factory until they are used in service units. Deviations from existing provisions can result in damage to the vaccine thereby reducing or even eliminating the potential that can lead to nonimmunity. The vaccine cold chain is a procedure used to keep the vaccine at a certain temperature that has been set so that it still has good potential starting from the manufacture of the vaccine to the time of administration. based on Law Number 19 of 2016 concerning Amendments to Law Number 11 of 2008 concerning Information and Electronic Transactions and Law No.
Equipping Higher Education Students with Digital Skills for the Post-Pandemic World

The Covid-19 pandemic has led to a digital transformation in global higher education because universities were forced to close, and higher education students faced interrupted education processes. Currently, online learning in higher education is a new phenomenon, and the pandemic has highlighted the importance of digital skills for higher education students for both new distance teaching and learning methods and the new labor market. The longer universities remain closed, the more higher education students will lose their future, resulting in a permanent loss of digital skills for the post-pandemic world. Accordingly, this study presents the current situation of higher education students relative to the pre-pandemic period and offers recommendations about the importance of equipping them with digital skills. In this context, this study overviews the level of digital skills of higher education students by synthesizing and comparing current data from reliable international institutions and provides an overall assessment.
Clustering by Hybrid K-Harmonic Means and Biogeography Based Optimization Algorithm for Medical Data

In today trendy world hybrid based optimized data clustering is unique and imperative clustering tool in the area of data mining, which is dynamic research of actual creation problems. The oldest and furthermost commonly used popular clustering technique is the K-means(KM) algorithm, which is very complex and for the initialization of the cluster centroid and it will easily go for premature converge. This initialization problem of K-means can be evaded by built in boost function of K-Harmonic Means, which is centroid based clustering algorithm and also unresponsive for collection of initial partition clustering , but it can easily go for pre-matured conjunction in local optima. To avoid this convergence problem, this proposed algorithm uses Boosting K-harmonic means(KHM) algorithm with BBO to produce more precise, robust, better clustering solution in few number of iterations, evade conning in local optima and simply convergence to relate with Harmonic Means, BBO algorithms. Biogeography based algorithm works with the concept of emigration and immigration of inhabitants from one location to another location, Which has high computation cost. For avoiding this high computation cost in this hybrid optimization technique Biogeography-Based Optimization (BBO) is integrated with K-Harmonic means algorithm to produce optimum and effective clustering solution with faster convergence. BBO is universal optimization methods to solve utmost of the optimization problem, which is an production based generation of evolutionary algorithm (EA)that augments a function by stochastically and repeatedly improving the clustering solution of quality, or fitness function. The experimental results of this paper shown as the projected method is very resourceful and faster to afford better clustering solution in less number of repetitions for medical data.
Syntactic Interpretations and Normal Forms

This chapter introduces some techniques that are useful for the simplification of formulas of first-order logic: the reduction to relational symbol sets is explained, the use of definitions in theories is clarified, and the prenex normal form and the Skolem normal form for first-order formulas are presented.
Physics News

Physik in unserer ZeitVolume 52, Issue 6 p. 269-269 Treffpunkt Forschung Physics News First published: 02 November 2021 https://doi.org/10.1002/piuz.202170607Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume52, Issue6November 2021Pages 269-269 RelatedInformation
Developing English for Front Office Learning Materials

This study aims to develop English language materials of front office for second semester students of the eleventh grade at SMK N 2 Singaraja. This study adopts the Design and Development (D&amp;D) which is guided by data collection through six instruments, namely questionnaires for teacher and front office staff, Google form for teachers and students, checklist for students, and checklist for expert judges. There are three stages that the researcher takes to complete this study, namely designing, developing, and evaluating the quality of the teaching materials (product) so that it can be categorized as a good material. The result is that there are four topics developed by the researcher, namely (1) Renewal of reservations, (2) Cancellation of reservations, (3) Handling of group reservations orally and in writing, and (4) Handling of individual reservations orally and in writing.
Near Duplicate Image Detection Using Image Net Model

The rapid development in the technology of Internet and the increase in the usage of mobile devices, it is very easy for users to capture, communicate and share the images through the networks. The spectacular achievement of convolution neural networks in the area of computer vision, will help us to match the features that are very similar between the images for detecting the duplicate version of the image. In this project we use Image Net model that mainly provide a large database that contains many images of different categories. Flask framework is used in this project, which includes many libraries, modules that helps the web developer to write web application. In this project the user is allowed to upload the image, then the image features will be extracted and fed to the CNN model. The CNN model will calculate the similarity distance between the images that is already present in the database and detect the top four images that are duplicate version of the uploaded image.
Supplemental Material: Assessing the effect of melt extraction from mushy reservoirs on compositions of granitoids: From a global database to a single batholith

&lt;div&gt;Includes database with matched compositions for bulk plutonic rocks and associated minerals; detailed tutorial for using iSpectra®; and more exhaustive set of simulations.&lt;br&gt;&lt;/div&gt;
Quantum Generative Adversarial Networks

Quantum machine learning could be one of the first applications for general-purpose quantum computers in the near future. Given the computational complexity of the quantum spectrum problem, quantum circuits outperform conventional neural networks in terms of expression. The notion of generative adversarial training, in order to form a distinct generative model, is a major recent achievement in classical machine learning. This paper describes a method to implement generative adversarial networks on quantum computer to minimize the loss/error of generator model. The paper implements hybrid-quantum architecture for GAN using the minimax game strategy for loss calculation. As a generator, it uses a quantum circuit, and as a discriminator, it uses a classical neural network. Only one-qubit rotation gates and controlled two-qubit phase gates are used in the parametric quantum circuit in the proposed approach.
Reproducibility in the technical debt domain

Abstract Context It is crucial to understand how reproducible the measurement results in the scientific publications are, as reproducibility is one of the cornerstones of engineering. Objective The goal of this study is to investigate the scientific publications presented at the premier technical debt conferences by understanding how reproducible the reported findings are. Method We conducted a systematic literature review of 135 unique papers published at the “International Workshop on Managing Technical Debt” and the “International Conference on Managing Technical Debt”, the premier scientific conference series on technical debt. Results Only 44 of the investigated 135 papers presented numerical evidence and only 5 papers listed the tools, the availability of the tools, and the version of the tools used. For the rest of the papers additional information would have been needed for the potential reproducibility. One of the published papers even referred to a pornographic site as a source of a toolset for empirical research.
Semantics of First-Order Languages

This chapter is an introduction the to basic semantic concepts of first-order logic: structures, interpretations, the satisfaction relation (a relation between interpretations and formulas) and the consequence relation. By several examples, the reader is made familiar with the formalization (and the question of formalizability) of properties in first-order logic.
Yaatree: A Mobile Application for Transportation Request Focused on People with Disabilities

New technologies have the duty to help in the inclusion of people with disabilities in society. This article shows the design, development and evaluation of an application oriented to the transport of people with a motor disability. The application is developed for Android system, uses Google’s geolocation services, maps and routes generation, in addition, it stores information in Firebase, also has a web interface that allows the validation of new users in mobile application. The results show that the application has a proper construction and a high level of usability. Finally, the long-term objective of the application is to be put into production to effectively help in the transportation of people with motor disabilities in Ecuador.
PALEOECOLOGICAL SIGNIFICANCE OF PALYNOMORPHS FROM PALEONTOLOGICALY-DATED MAASTRICHTIAN–DANIAN DEPOSITS, BIR ABU MINQAR AREA, SOUTH WESTERN DESERT, EGYPT

This study is carried out on the Dakhla Formation deposits at the Bir Abu Minqar section, South Western Desert, Egypt.Maastrichtian/Danian palynofloras have been recovered from the micropaleontology (foraminifera-nannoplankton)-and macropaleontology (bivalvia-ammonites)-dated deposits of the upper Dakhla Formation.Pteridophytic and liverworts spores, pollen of gymanosperms and angiosperms as well as dinoflagellate cysts have been identified.Angiosperm pollen includes typical members of the Late Cretaceous Palmae Province such as Spinizonocolpites echinatus.Presence of palm pollen and hygrophylic pteridophytic spores suggest a prevalence of humid tropical conditions during the deposition of the studied section, with Nypa palm mangroves thriving in the intertidal swamps that bordered the Late Cretaceous shallow sea at the area of the Abu Minqar.
Machine Learning Algorithms in Software Defect Prediction Analysis

Programming deformity forecast assumes a vital job in keeping up great programming and decreasing the expense of programming improvement. It encourages venture directors to assign time and assets to desert inclined modules through early imperfection identification. Programming imperfection expectation is a paired characterization issue which arranges modules of programming into both of the 2 classifications: Defect– inclined and not-deformity inclined modules. Misclassifying imperfection inclined modules as not-deformity inclined modules prompts a higher misclassification cost than misclassifying not-imperfection inclined modules as deformity inclined ones. The machine learning calculation utilized in this paper is a blend of Cost-Sensitive Variance Score (CSVS), Cost-Sensitive Laplace Score (CSLS) and Cost-Sensitive Constraint Score (CSCS). The proposed Algorithm is assessed and indicates better execution and low misclassification cost when contrasted and the 3 algorithms executed independently.
ON THE ACCURACY OF POSITIONING OF MOBILE ROBOT'S WALKING PROPULSION DEVICES

The problems of the influence of the choice of the kinematic scheme of the walking mechanism on the positioning accuracy of its foot with the same small positioning errors are considered. The relationships between the laws of changing the coordinates of the foot of the walking mechanism as a material point and the change in the position of the output elements of the motors of the drives of the orthogonal mover and the mover with a parallel chain of drives are established.
DarkNet Traffic Classification Pipeline with Feature Selection and Conditional GAN-based Class Balancing

DarkNet is an encrypted collection of internet sites that host criminal activities and hidden services. These privatized networks keep the internet activity anonymous and almost untraceable. DarkNet traffic classification aids in enhancing the security of any network through detection of threats or risks to any network of systems. In this paper, the standard CIC-Darknet2020 dataset used contained instances of benign and DarkNet traffic to a network. Feature importance analysis is performed using Chi-Squared statistical score on the dataset to aid in feature selection. The imbalance of the classes is then handled by performing oversampling using Conditional Generative Adversarial Networks. The multi-class classification of the traffic encryption type is performed using Random Forest classifier. This pipeline performs with a F1-Score of 97.87 for traffic encryption classification.
Design of an Enterprise Financial Risk Management System Based on Big Data Mining

To enhance the real-time management and control capabilities of enterprises for relevant financial risk behaviors to greatly improve the economic profitability of the enterprises themselves, a corporate financial risk management system based on big data mining is designed. Use the Hadoop architecture to provide the ZooKeeper management structure and the connection elements required by the Mesos host to complete the hardware execution environment of the risk management system based on big data mining. On this basis, we define organizational system design principles, management program design principles, and guarantee system design principles, complete the construction of the software execution environment of the management system, and combine the structure of related hardware equipment to achieve a smooth enterprise financial risk management system based on big data mining applications. The comparative experimental results show that, compared with the ERM framework management system, the big data mining management system can effectively control the financial risky behavior of the enterprise, and it has a stronger effect on improving the economic profitability of the enterprise itself.
Vector Model of the Youth Professional Self-Determination in the Context of Multidisciplinary University

Today’s education is struggling to respond to the challenges of a changing world. The skills and knowledge, traditionally taught at educational institutions, rapidly become obsolete. This raises a question about organizing career guidance work, as a system of professional, psychological and educational guidance of a person on the path towards self-determination. Universities should be involved not only in providing the learners with high quality educational services, but also in developing a flexible and innovative model that could impact on professional self-determination at all levels of university education, from the emergence of interest in profession to additional professional training. Given that, the development of multidimensional vector model of the youth professional self- determination in the context of multidisciplinary university is gaining increasing importance.
Implementation of Imla Online Learning

Facing the era of globalization and technological developments lately, the world is faced with a fast flow of information. Therefore, the importanceof information technology and the internet in various fields of life, including the worldof education. This study aims to describe the implementation of imla online learning. This research uses descriptive qualitative research. The object of this research is the student the students of Hasanka boarding school Palangka Raya. This research technique uses observation and interviews. The results showed that the implementation of imla online learning could improve students’ ability to write Arabic. Judging from the learning that has been applied with the progress of each meeting, where students can write correctly or not make mistakes. Judging from the results of the research that there has been an increase in students, let online-based learning continue to be carried out, because with the online learning of imla ‘this makes people who want to learn very easy to obtain, then it will also have a positive impact on smartphone users who is on the rise at this time.
Thoreau's "Life without Principle" and the Art of Living and Getting a Living

Often seen as an anti-work crank, Henry David Thoreau was, in reality, an astute philosopher of work who devised a philosophy that envisioned the beneficial role work plays in the well-lived life. His essay "Life without Principle" is a jeremiad that laments the ways that materialism corrupts work, and calls upon his readers to repent and turn to a life of self-culture guided by moral and spiritual values. Salvation of work comes from a life lived with principle that makes work pleasurable for the worker, moral in its execution, and beneficial to the common good.