Reviewerly/exHarmony huggingface dataset:
Commentary or Perspective: Opportunities to Leverage the Use of Global Public Health Innovative Research Technology in Combatting Cybercrime

Recently while near my hometown baseball field, I was reminded of the Little League Pledge. Players traditionally recited the pledge prior to the start of a baseball or softball game; two lines particularly stood out to me, they were “I will play fair and strive to win. But, win or lose, I will always do my best.” The first line mentioned got us thinking about the pandemic and rise in cybercrime. Why are there persons willing to partake in cybercrime, taking advantage of the situation the pandemic has created, and not playing fair? Can cybersecurity researchers utilize similar efforts or strategies used by the global public health to combat cybercrimes, during difficult causal situations? This paper will outline a subset of current research taking place concerning cybercrime and COVID-19 through a rapid literature review, bring to light strategies and technologies that can be used to complement the research, and bring a call to action for researchers and practitioners to give this topic greater attention, awareness, and more knowledge and focus.
One-Class Classifiers for Novelties Detection in Electrical Submersible Pumps

Detecting anomalies and fault novelties is of high interest in the industry due to the scarcity of fault examples to train classification systems. In this article two algorithms for anomaly detection, One-Class SVM and Isolation Forest, are successfully used as effective methods for detecting fault novelties in problems of electrical submersible pumps. Faults in submersible electric pumps generate an enormous cost for companies in the oil and gas sector, since the cost of stopping production to change the equipment is excessive, which makes it necessary to identify problems before implementation. Empirical evaluation shows that both one-class classifiers performed satisfactorily, obtaining macro f-measure values of approximately 0.86. For comparison purposes, a Random Forest trained in a conventional binary classification manner is tested and achieved a macro f-measure of 0.95. Results show that the proposed solutions can have practical applications in the classification of problems in electrical submersible pumps, changing the way the oil and gas industry addresses this difficulty.
Comparing Alternative Storage Models for Words Extracted from Legal Texts

The COVID-19 pandemic created new demands for services in the judicial system, requiring the use of a data warehouse (DW). Although there exist approaches that use DW in the judicial domain, few target the pandemic or publicly provide the information extracted from the texts. Following the needs of a legal expert, we have developed the COVID-19 Portal. It extracts documents from the Supreme Federal Court in Brazil to obtain quantitative information on words used in the texts. In this paper, we present the design of a DW, and show the query performance improvement achieved with its implementation. The DW has been developed on Postgres, and its performance is compared with the original implementation on MongoDB Cloud and a local MongoDB database.
Sim-DRS: a similarity-based dynamic resource scheduling algorithm for microservice-based web systems

Microservice-based Web Systems (MWS), which provide a fundamental infrastructure for constructing large-scale cloud-based Web applications, are designed as a set of independent, small and modular microservices implementing individual tasks and communicating with messages. This microservice-based architecture offers great application scalability, but meanwhile incurs complex and reactive autoscaling actions that are performed dynamically and periodically based on current workloads. However, this problem has thus far remained largely unexplored. In this paper, we formulate a problem of Dynamic Resource Scheduling for Microservice-based Web Systems (DRS-MWS) and propose a similarity-based heuristic scheduling algorithm that aims to quickly find viable scheduling schemes by utilizing solutions to similar problems. The performance superiority of the proposed scheduling solution in comparison with three state-of-the-art algorithms is illustrated by experimental results generated through a well-known microservice benchmark on disparate computing nodes in public clouds.
FCOSMask: Fully Convolutional One-Stage Face Mask Wearing Detection Based on MobileNetV3

Wearing masks correctly in public is one major self-prevention method against the worldwide Coronavirus disease 2019 (COVID-19). This paper proposes FCOSMask, a fully convolutional one-stage face mask wearing detector based on the lightweight network, for emergency epidemic control and long-term epidemic prevention work. MobileNetV3 is applied as the backbone network to reduce computational overhead. Thus, complex calculation related to anchor boxes is avoided in the anchor-free method, and Complete Intersection over Union (CIoU) loss is selected as the bounding box regression loss function to speed up model convergence. Experiments show that compared to other anchor-based methods, detection speed of FCOSMask is improved around 3 to 4 times on self-established datasets and mean average precision (mAP) achieves 92.4%, which meets the accuracy and real-time requirements of the face mask wearing detection task in most public areas. Finally, a Web-based face mask wearing system is developed that can support public epidemic prevention and control management.
Distance Work with the Preparation of Future Managers of Physical Culture in the Conditions of a Post-Pandemic Society

Due to the spread of the Covid-19 virus, all countries began to introduce quarantine measures, which led to the closure of all higher education institution indefinitely. They were forced to switch to a distance learning process in a short time. The readiness for this process was different, purely technical problems arose - the lack of the Internet, computers, educational materials on the network. And most importantly, the teachers are not ready for distance learning. The IT industry was the first to respond to the needs of teachers and students in physical culture and sports: the power of channels was increased, a large number of services and tools for teaching appeared. For video conferencing, the ZOOM tool turned out to be very popular, a large number of blogs with training recommendations were published on social networks, distance courses were held on the development of training resources and the organization of training. After the weakening of quarantine in the world, it became clear that humanity has entered a new stage of development, where distance learning will play a big role. Therefore, it is important to analyze the results of the distance learning process and determine the priority ways of developing online education in training future managers of physical culture and sports. The article is devoted to the problems of using distance work in the training of future managers of physical culture and sports.
The Relationship of Indonesian Language Learning with the Environment

In the world of education there is a learning process carried out by teachers and students. Without the learning carried out by the teacher, of course students will not gain knowledge and experience about various things. The learning process is basically to develop the activities and creativity of students, through various interactions and learning experiences. However, in practice it is often not realized that there are still many learning activities that are carried out which actually hinder the activity and creativity of students. The learning process in the classroom generally emphasizes the cognitive aspect, so that the mental abilities learned are mostly centered on understanding knowledge and memory materials. In such situations, students are usually required to accept what is considered important by the teacher and memorize it. Teachers generally don't like the learning atmosphere where the students ask a lot of questions outside the context being taught. Seeing such conditions, the activities and creativity of students are hampered or cannot develop optimally.
A new type of intuitionistic fuzzy modal operators over intuitionistic fuzzy pairs

In the paper, two intuitionistic fuzzy modal operators from a new type are introduced over intuitionistic fuzzy pairs. Some of the basic properties of the new operators are formulated and checked.
Peer Review Declaration Form Guidance

On the following page you will find the declaration form. • Please answer each question. • You should submit the form along with the rest of your submission files. • The deadline is the submission date written in your publishing agreement. All conference organisers/editors are required to declare details about their peer review. We will publish the information you provide as part of your proceedings. Peer review declaration All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Double-blind • Conference submission management system: Easy Chair • Number of submissions received: 97 • Number of submissions sent for review: 73 • Number of submissions accepted: 38 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 39.17% • Average number of reviews per paper: 2 • Total number of reviewers involved: 51 • Any additional info on review process : • Contact person for queries : Name : Dr. Nishu Gupta Affiliation: Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Chennai, India Email : nishugupta@ieee.org
Seeing things clearly: Image understanding through hard-attention and reasoning with structured knowledge

In this talk, Jonathan aims to frame the current challenges of explainability and understanding in ML-driven approaches to image processing, and their potential solution through explicit inference techniques. Jonathan works as a senior data scientist at EXPLORE-AI and is a member of the RAIL lab at the University of the Witwatersrand, South Africa. His research is focused on capturing higher-order reasoning behind diagnostic outcomes in radiological investigations using agent-based methods; allowing learning models to better understand and articulate knowledge in a clinical setting.
Full Issue

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 58, Issue 10 p. I-I Full Issue Full Issue First published: 01 December 2021 https://doi.org/10.1111/j.1467-6346.2021.10277.xAboutPDF 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 onFacebookTwitterLinkedInRedditWechat Volume58, Issue10December 2021Pages I-I RelatedInformation
Supplemental Material: Earthquake weather and climate change: Should we stress about the forecast?

Table S1. Onshore UK earthquake catalogue for 1980–2012 with local magnitudes ≥1.5&lt;br&gt;
Socialization of Zoom Application Utilization for Making a Learning Presentation in Video Form

Learning is a process of student interaction with teachers and learning resources in a learning environment. The article clearly states that learning is a process of interaction between teachers (educators) and students (students). During this pandemic, all learning processes are carried out remotely. Because face-to-face learning in class cannot be carried out as a result of the highly contagious corona virus outbreak. The selection of the right learning media must pay attention to and adjust the needs of the subject matter so that the media functions as a tool that can increase understanding and interest in learning. Zooming presentation learning media is one of the newest applications that has a fresh, unique, attractive appearance and has sophistication in zooming in and out and can combine videos, images and animations. With this community service, it is hoped that it can help the problems of teachers at Darul Faizin High School regarding online learning problems. So that this socialization can be a solution in providing learning materials to students.
The Area Method in the Wolfram Language

The area method is a decision procedure for geometry developed by Chou et al. in the 1990's. The method aims to reduce the specified hypothesis to an algebraically verifiable form by applying elimination lemmas. The order in which the lemmas are applied is determined by the stated conjecture and the underlying geometric construction. In this paper we present our implementation of the area method for Euclidean geometry as a stand-alone Mathematica package.
Mediating Role of Social Media on Online Shopping Behavior: Smart-PLS Approach

Consumer behaviour and decisions to buy from online retailers were increasingly influenced and changed by social media. Because of the never-ending advances in information technology, online shopping is becoming more popular. Therefore, this study aimed to examine the mediating effect of social media on online shopping behaviour in Nigeria. A cross-sectional study was used, and a simple random sampling procedure was used to select three hundred and eighty (380) online shoppers. Data were analysed using Structural Equation Modelling –Partial Least Square (SEM-PLS). The analysis revealed that advertising had an insignificant effect on online shopping behaviour with a path coefficient (Beta value = 0.11; t value = 1.743; p= 0.082). There is positive relationship between advertising and social media effect (Beta value = 0.787; t value = 34.556; p= 0.000). the proposed relationship between social media effect and Online Shopping Behaviour (=0.378; t-value =5.735; p =0.000) is supported. In contrast, the projected relationship between Trust and Online Shopping Behaviour is (=0.466; t-value =12.817; p =0.000). Lastly, the result revealed there is a strong correlation between Trust and Online Shopping Behaviour.
Efficiency of the Professional Development of a Teacher in the System of Further Training: Analysis of Educational Teachers’ Needs

The purpose of the study is to determine the optimal type of training in the course of teachers’ professional development and to identify the expected results of this process. A questionnaire survey of secondary school teachers from 3 cities and 25 districts of the Republic of Sakha was conducted. Based on the obtained results and conclusions, the recommendation is made to develop courses with an analytical structure, focused on the organization of advisory support throughout the course, solving cases in the school context, review of strategies suitable for handling the actual learning task. Moreover, this structure is suitable for both online and offline learning courses. Also, a separate course on the development of professional ethics of a teacher in distance and offline learning formats is required. This can be seen as an urgent task of the modern teacher’s activity, which leads to the success of the implementation of state policy in the educational field
Efficient bilingual lexicon extraction from comparable corpora based on formal concepts analysis

Abstract Bilingual corpora are an essential resource used to cross the language barrier in multilingual natural language processing tasks. Among bilingual corpora, comparable corpora have been the subject of many studies as they are both frequent and easily available. In this paper, we propose to make use of formal concept analysis to first construct concept vectors which can be used to enhance comparable corpora through clustering techniques. We then show how one can extract bilingual lexicons of improved quality from these enhanced corpora. We finally show that the bilingual lexicons obtained can complement existing bilingual dictionaries and improve cross-language information retrieval systems.
Spatial Data Visualization in Augmented Reality for Facility Operations and Asset Monitoring in Oil and Gas Industry

Conventional and inadequate facility monitoring and planning commonly addressed severe consequences, including a significant amount of time allocation, which might lead to disruption in public service provision, cost, property damage, injuries, and fatalities. This study aims to answer the challenges in conventional facility monitoring and construction planning in the oil and gas industry by utilizing emerging technology, Augmented Reality (A.R.), and GIS integration. This research presents a new workflow involving site suitability analysis, field data collection, data visualization that integrates GIS capabilities, mobile technology, and A.R. connected seamlessly, called GIS-AR. Based on the results of this study, with approximately 1.6 meters measurement deviation, less operating time (&lt; 10 seconds), and few workers involved (only one person), GIS-AR implementation showed benefits in facility operations, monitoring, and planning in the oil and gas industry. Those values answered the challenges faced by the industry in time management and worker efficiency, at which the cost can be potentially saved up to 98%. The convergence of GIS, web mapping, mobile technology, and A.R. implies the emergence of location-based systems and, in sequence, the diminishing use of traditional analog maps by smartphone users. This convergence supports a new way of spatial data exploration.
ORGANIZATIONAL FORMS (STRUCTURES) OF BLENDED LEARNING AS POWERFUL MEANS OF INFLUENCE ON THE FORMATION OF LEGAL COMPETENCE OF THE FUTURE EDUCATIONAL INSTITUTION MANAGEMENT MANAGERS IN THE CONDITIONS OF THE MAGISTRACY

On the basis of the analysis of theoretical sources on this problem, this article clarifies: 1) ideas of leading scientists on the content of the basic concepts of research (legal competence, blended learning, etc.) and components of blended learning; 2) the ways of formation of legal competence of the future educational institution management managers in the conditions of the magistracy are defined.&#x0D; The specifics of organizational forms (structures) of blended learning as a powerful means of influence on the formation of legal competence of the future educational institution management managers in the conditions of the magistracy are discussed.&#x0D; It is the organizational forms (structures) of blended learning that should be the basis for creating a blended learning environment in the formation of legal competence of future managers in the management of educational institutions in the master's program.
Application of Disruptive Technologies on Environmental Health: An overview of artificial intelligence, blockchain and internet of things

Environmental monitoring technology is a critical component in assisting and ensuring environmental management success. The development patterns of disruptive technologies for environmental monitoring should be studied and anticipated in order to aid in the promotion of India's environmental monitoring and protection. The primary objective is to examine previous research on disruptive technology and its current environmental applications, as well as to determine the degree of connection between the chosen variables, using the Vos Viewer Software, which is being used in this study. A discussion of the existing environmental impacts associated with artificial intelligence (AI), blockchain, and the Internet of Things (IoT), as well as new advancements in these fields, is presented in this article. As a result of the research, the difficulties and possibilities presented by the stated technologies on the entire Indian environmental monitoring network have been highlighted that can be useful for researchers and government for future advancement in environmental health. (*The paper was presented at the 2nd Conference on Business Data Analytics: Innovation in emerging trends in management data analytics. Apeejay School of Management, Dwarka, Delhi, India. November 2021)
A Robust Display Delay Compensation Technique Considering User’s Head Motion Direction for Cloud XR

Conventionally, it has been difficult to realize both photorealistic and geometrically consistent 3DCG rendering on head mounted displays (HMDs), due to the trade-off between rendering quality and low motion-to-photon latency (M2PL). In order to solve this problem, we propose a novel rendering framework, where the server renders RGB-D images of a 3D model with the optimally arranged rendering viewpoints, and the client HMD realizes geometric compensation of M2PL by employing depth image based rendering (DIBR). Experiments with real smart glasses show that the proposed method can display binocular images closer to the ground truth than the conventional approaches.
Pandemics, Delays, and Pure Data: on ‘afterlives’ (2020), for Flute and Live Electronics and Visuals

The essay addresses creative and technical aspects of the piece ‘afterlives’ (2020), for flute and live electronics and visuals. Composed and premiered in the context of the COVID-19 pandemic, the composition employs audiovisual processes based on different audiovisual techniques: phase-vocoders, buffer-based granulations, Ambisonics spatialization, and variable delay of video streams. The resulting sounds and images allude to typical situations of social interaction via video conferencing applications. ‘Afterlives’ relies on an interplay between current, almost-current, and past moments of the audiovisual streams, which dephase the performer’s images and sounds. I have avoided, in text, delving deeper into the Pure Data abstractions and or into the musical analysis of my composition. The main purpose of the text is rather to present compositional/technical elements of ‘afterlives’ and discuss how they enable new experiences of time.
BIBLIOMETRIC ANALYSIS OF PUBLICATIONS OF SCIENTISTS IN OPEN ACCESS JOURNALS AS A TOOL TO INCREASE THE PUBLISHING ACTIVITY OF THE UNIVERSITY

Objective. The study is aimed at increasing the publishing activity and better presentation of scientific results of Admiral Makarov National University of Shipbuilding by expanding scientific publications in open access logs. Chronological frameworks of the studied scientific articles – 2017–2021. Methods. In order to obtain relevant empirical data, the authors of the research analyzed publications of the Admiral Makarov National University of Shipbuilding scientists in open access logs using products and services of scientometric database Scopus. The algorithm of "step-by-step" actions in the Scopus database was considered in relation to: the determination of the most relevant topics; formation of the circles for the most cited publications; determining the representation level of publications made by the University scientists in the Scopus database on the topic of the study. Results. During the study, the authors showed that complete and objective evaluation in the effectiveness of scientific activity of the institution is possible only with the analysis of open resources of scientific information; the percentage of publications in the open access of Admiral Makarov National University of Shipbuilding authors-scientists is growing: in five years, the number of scientific articles of open access has increased twice; the most popular publication model is GoldAPC; there are the most cited publications in foreign editions that relate to the first and second quartile. Conclusions. The authors firstly conducted a bibliometric study of scientists’ publications in open access journals as a tool for raising the publishing activity of the university on the basis of products and services of the Scopus scientometric database. The research materials can be used to further increase of publishing activity both for individual scientists and institutions as a whole.