Reviewerly/exHarmony huggingface dataset:
Cloud Security Game Theory Scoring From Predation Models In Simulation

Abstract Cloud economics results from amassing computation resources while being able to distribute workload in space and time. The backbone of this ability is virtualization, which abstracts the host hardware, sharing virtual machines. This means of interface is also a primary vehicle and target for attackers. The counter-measures to this threat consider the costs and benefits to the cloud’s essential functions. Where the future development of the cloud is also considered, this competition between attackers and victims is analogous to those modeled in extended game theory. Yet, the attacker and victim costs and benefits, expressed as utility measures necessary for game-theory methods, are elusive quantities. This paper establishes such a game as a predator-prey contest played out on a data-center environment. A set of contestant parameters are applied at the threshold of a viable model to the recognizable boundaries. Measurement of system health is extracted in relief with individual cost, benefit, and risk. An examination of metrics capable of validating extended interaction is developed. This establishes a baseline model for more elaborate expression of security in cloud economics.
Stand-alone obstacle avoidance controller for image-based navigation

In this paper we present a stand-alone reactive avoidance controller inspired by the spirals described by insects during their flights.Unlike state-of-the-art obstacle avoidance methods, it only focuses on circumventing hazardous elements and can be coupled to navigation controllers working in different state space, such as the image one.We describe the obstacle avoidance problem by following a set of spirals, the spiral parameters computation to deal with convex/concave obstacles, and the spiral following controller design.Finally, a set of simulations obtained with ROS/Gazebo show the efficiency of the proposed approach to navigate in a cluttered environment.
Making an investment decision in the cryptocurrency market

This article is devoted to the formation of a methodological basis for assessing the investment attractiveness of cryptocurrencies. The paper studies the main investment strategies with cryptocurrencies, and developed a methodological approach to making an investment decision in the crypto-currency market, which includes an assessment of the investment attractiveness of a digital financial asset. The scientific article presents an assessment of the investment attractiveness of the two most popular cryptocurrencies - Bitcoin and Ethereum.
GOR, the Group of Revolutionary Objects: Praxis and Research

GOR stands for Groupe des Objets Revolutionaires, or, in English, the Group of Revolutionary Objects. This group was founded by Filipe Pais, Julie Brugier and Olivain Porry in 2018, in reaction to two major planetary concerns: the climate crisis and techno-solutionism. GOR, in response, opens a fictional design space for debate and aesthetic manifestations, wherein objects and machines are given autonomy, and the possibility of disobeying whilst challenging human decisions. This article is a statement about GOR’s motivations, practice and research, written by two of the group members. In addition to further introducing the GOR manifesto and the forces which have given rise to it, it reviews its artistic practices and actions conducted during art residencies and group exhibitions; it identifies two examples of how the GOR design space can yield interesting clues in research, introducing the notion of super-object and an artistic framework named COCO2.
The Application of Personalized Recommendation System in the Cross-Regional Promotion of Provincial Intangible Cultural Heritage

With the accelerated trend of globalization and modernization, many provincial intangible cultural heritages (PICH) are in danger of being lost. In the context of Internet technology, the use of digital multimedia for personalized recommendation is an effective way to promote the transmission of intangible cultural heritage. However, traditional recommendation systems tend to treat different members as homogeneous objects, ignoring the relationship between members’ professional backgrounds and the inherent properties of items, and cannot truly solve the problem of conflicting preferences in the integration process. In view of this, this paper proposes a group recommendation system based on nonnegative matrix decomposition. First, the group rating information is decomposed into a user matrix and item matrix by nonnegative matrix decomposition. Then, the item affiliation matrix and member expertise matrix are calculated by using the affiliation and expertise weights for the two matrices, respectively, and the contribution degree of each member to different item ratings is obtained from them. Finally, the group preference model is constructed by weighted fusion of members’ preferences based on their contribution degrees, and different recommendation lists are generated for different user preferences. The experimental results prove that this system has high recommendation accuracy in cross-regional promotion of PICH.
Development of a Mobile Application for Flag Identification based on Artificial Neural Networks

Machine learning, and more specifically its subfield known as deep learning, have been driving new disruptive technologies and recent accomplishments in various industries. This paper applies to some extent the same technology to develop a mobile application for educational purposes, that allows one to identify unknown flags with the help of artificial intelligence. For the application to be functional and effective, a custom dataset had to be created and processed in various ways in order to provide a collection of data that resembles data from the real world. The collection would then be used as the input data for constructing the model, which is developed within the framework TensorFlow. Once the model was developed, it was implemented as part of a mobile application programmed with Flutter. The functionality of the mobile application and the model’s accuracy are then put to the test against over a hundred new images the model has not seen previously or been trained on. The result of this evaluation could be considered an estimate of the readiness and usability of the application in a real-world scenario.
Modeling Vulnerability Discovery Process in Major Cryptocurrencies

These days, businesses, in both online and offline, have started accepting cryptocurrencies as payment methods.Even in countries like El Salvador, cryptocurrencies are recognized as fiat currencies.Meanwhile, publicly known, but not patched software vulnerabilities are security threats to not only software users but also to our society in general.As the status of cryptocurrencies has gradually increased, the impact of security vulnerabilities related to cryptocurrencies on our society has increased as well.In this paper, we first analyze vulnerabilities from the two major cryptocurrency vendors of Bitcoin and Ethereum in a quantitative manner with the respect to the CVSS, to see how the vulnerabilities are roughly structured in those systems.Then we introduce a modified AML vulnerability discovery model for the vulnerability datasets from the two vendors, after showing the original AML dose not accurately represent the vulnerability discovery trends on the datasets.The analysis shows that the modified model performs better than the original AML model for the vulnerability datasets from the major cryptocurrencies.
SISTEM INFORMASI AKUNTANSI SEBAGAI DETERMINAN KINERJA KEUANGAN PADA PERUSAHAAN JASA KONSTRUKSI DI KOTA MATARAM

This study aims to examine the influence of accounting information system on financial performance on a construction services company in the city of Mataram. This research uses primary data and secondary data, primary data obtained from questionnaires to the respondents, which is the employees who work directly with the accounting information system construction services company in the city of Mataram, while the secondary data obtained from the financial data of the company for 3 years. The sampling technique used is purposive sampling with the sampling results a total of 47 companies. Data were processed using the software smartPLS the latest version 3.3.3. The results of this study indicate that accounting information systems affect the company's financial performance. The success of an accounting information system will provide impact and benefits on the performance of individuals and companies, so that will increase the effectiveness and efficiency of the company. the implications of this study can be used as input by the business of construction services, where the company should also pay attention to the use of accounting information systems that are appropriate and adequate for the company to improve the performance of the company.
use of South African languages by youth on social media

The focus of this article is to discuss new media choices and use of selected South Africanlanguages on social media by youth residing in Limpopo Province, South Africa. The use oflanguage on social media facilitates communication between communicators and use of one’scultural language can ensure that this communication is better. This paper summarises a study ofyouth in Limpopo Province. The purpose of the study was to explore and describe languages usedby youth on social media and identify reasons for the communication engaged in. The researchmethodology used to collect and analyse data was a combination of qualitative and quantitativeapproaches. For the quantitative part of the research, a survey and online observation were usedfor data collection and statistical methods and semiotic analysis used to analyse data. For thequalitative aspects of the study, personal interviews and focus groups were employed for datacollection and thematic analysis used to analyse data. The findings indicated that the majorityof the youth do not prefer to use their African mother tongue languages to communicate onTwitter and Facebook but chat in the English language on those forums. However, the youngpeople prefer to use their African languages when communicating to others on the WhatsAppsocial media platform. Reasons for these choices are stated. The discussion contributes to theacademic debate on the role of language in decolonising higher education, and to debates aboutpromoting the use of African languages.
Methodology to Extract Technical Requirements for Public Services: Electric Vehicle Case for Korean Postal Service

The purpose of this paper is to propose the methodology for extracting the technical requirements of RFPs for general public services that has become more complex and increasingly specialized for service providers, government agencies, technology suppliers with the rapid change in technology in the fourth industrial revolution. This study proposes four step process for extracting technology requirements for a request of proposal based on the quality function development (QFD) concept with the Delphi method: 1) Define public service attributes based on Delphi method, 2) Define the engineering characteristics, 3) Develop HOQ to transform the public service attributes to the engineering characteristics, and 4) Extract technical requirements from the result of HOQ. As an application, the proposed methodology’s feasibility and effectiveness have been demonstrated for generating technical requirements for Korea Post’s adoption of electric vehicles for mail delivery.
Strategic collaboration for technology-supported development and use of multilingual children’s storybooks in Kenya

Literacy is critical to achieving the 17 United Nations Sustainable Development Goals butmany countries have not achieved globally desirable literacy levels. In this paper I describe acollaborative strategy that the South African Institute for Distance Education (SAIDE) adoptedto implement the African Storybook (ASb) in sub-Saharan Africa in response to the shortageof multilingual literacy resources. The paper focuses on Kenya, drawing on my experience asthe ASb Partner Development Coordinator and from ASb partner reports. One of the findingsis that nationwide literacy programmes may not meet specific literacy needs of children fromhard-to-reach communities. Other innovative and unique initiatives need to intervene througha collaborative bottom-up approach. I conclude with some lessons learned, achievements andchallenges.
Structural and functional model of the successful person training in USA colleges and universities

The purpose of the article is to study the training of a successful person in the colleges and universities of the USA as a holistic process and to create a structural and functional model. The methods of retrospective analysis, systematization and generalization, abstraction and specification, modeling and graphic visualization are applied. A structural and functional model of successful person training in colleges and universities of the USA has been created. The focus groups of this process have been defined, in which the work is aimed at applicants, first-year students, second-fourth years students and a special category - students of the last year and graduates, as a significant part of students do not complete their studies on time. Examples of effective use of models and strategies of student training by American institutions of higher education are given. Five stages of successful person training in American institutions of higher education are proposed. It is summarized that the created structural and functional model is the basis for creating a strategy for the development of an educational institution and will contribute to the high-quality organization of the training of specialists in colleges and universities.
Design of Precise Estimation Algorithm for Sports Pose Based on Multifeature Fusion

The estimation time and estimation precision of motion pose samples are problematic for the pose estimation algorithm of sports movements. This paper proposes a multifeature fusion-based algorithm for accurate posture estimation. The human rod model is constructed after analyzing the human pose estimation technology. Using the Kalman filter method, the degree of freedom and range of motion of the major joints of the human body were determined. The eight-star model was used to extract the sports posture features, and the weighted average method was used to process the grayscale images of sports. Using the multifeature fusion method, the extracted multisource feature vector information is thoroughly analyzed and processed, and a new group of fusion feature vectors is created. Using a mixture Gaussian distribution model, the posture estimation of an athlete’s body is accomplished. Experimental results indicate that when the amount of sports pose sample data is 900 GB, the accurate estimation time of the proposed method is 5.3 s, and its accuracy is 100 percent. Improve the estimation accuracy of samples of sports posture.
Sharing unreviewed research data: Problems and prospects

This paper highlights the results of the survey of Ukrainian scientists on the exchange of unreviewed research data with other scientists, and their motivation to use and disseminate unreviewed research data. By “research data” we mean both processed (summarized in the form of text data, tables, figures, infographics, etc.) and unprocessed information collected by researchers due to experiments, observations, simulations, through surveys or in other ways, or generated from available information. A questionnaire was distributed in different Facebook groups for scientists (“Ukrainian Scientific Journals” “Ukrainian Scientists Worldwide”, “Pseudoscience News in Ukraine”, “Scientific Conferences and Publications”, “Academic Virtue and Plagiarism”, “Higher School and Science of Ukraine: Disintegration or Blossoming?”, “Ukrainian cuisine of scientific publications”) and through university networks. Results from 736 respondents demonstrated awareness and attitudes about data sharing, advantages, and disadvantages of data sharing for scientists. Most of the respondents don’t trust the results of scientific research published in sources other than peer-reviewed scientific journals. Only 34.7 % of the respondents use to publish their unreviewed research data. The reasons that can stop scientists from sharing research data are the following: problems with copyright protection, luck of time, fear to lose publishing opportunities, contradictions with the requirements of the journals, risk of misinterpretation, risk of losing leadership in the field of research, ethical norms violations, prejudice. Researchers, especially those who work at universities, highlighted lack of time for data sharing, because they teach and supervise students, conduct research, have administrative activities, participate in community services. Among the reasons for data sharing the scientists noted cooperation, formation of reputation, increasing the likelihood of being quoted, feedback from the scientific community, development of science, saving results to use in the future, etc. 30.9 % of the respondents indicated that they do not find anything that could motivate them to share research data. Meanwhile about 78.0 % of respondents are sure, that they need trainings in the field of data sharing.
Typology of competence characteristics of pupils with intellectual disabilities

The purpose is to develop a typology of competence characteristics of pupils with intellectual disabilities as a measure of a child’s integration into educational activity. The following methods were applied: retrospective analysis and generalization; empirical measurement of relevant parameters of the research subject by means of valid and proprietary methods; k-means clustering, mathematical methods for data processing. The experiment participants: the total number (n=114) of the children from the first to the fifth grades: the pupils with intellectual disabilities (Group 1: n=57; 50.0%) and the pupils with normal development (Group 2: n=57; 50.0%). Key differences were found in the following competences of the research participants: intellectual-cognitive, emotional-motivational and social. It was established that deficiency of cognitive and adaptive skills, violation of social norms and limited communication prevail in the children with intellectual disabilities. Three types of competence characteristics in the pupils with intellectual disabilities in education were determined: Operational-Reproductive (ORT), Limited-Practical (LPT), Limited-Fixed (LFT). The prospect is to create a conceptual model and correction-development program for the formation of key competences of pupils with intellectual disabilities.
Learning english through YouTube as a self-development factor for future officers

The aim of the article was to assess the effectiveness of learning English through YouTube as a factor in improving the future officers’ language skills. The study involved the following methods: survey, pedagogical experiment, Score-Rating System of Performance Control; Scale of Assessing the Need to Achieve the Goal by Yu. M. Orlov; Adapted Method of T. I. Ilina — Examining Motivation to Study in a higher educational institution (HEI); Diagnosis of the Level of Reflexivity Development by A. V. Karpov. The dynamics of change in the level of foreign language competence is very insignificant for students in the traditional form of education (control group), and it applies only to levels A1 (-8%) and A2 (+8%), that is, the lowest of the represented ones. Learning through the proposed model helps increase student involvement in foreign language learning, which is reflected in the increased number of completed assignments. The quality of education is growing, which is reflected in the increased level of student performance.
Research on Application of Intelligent Corpus Annotation of Entity Extraction with Construction of Knowledge Graph

The purpose of this paper is to solve the problem of big data and small samples caused by the high manual annotation cost of a military corpus. The deep learning algorithm of entity extraction in the military field was organically combined with the method of bootstrapping loop iteration to complete a study on the application of intelligent corpus annotation of military field entities. With the experimental research showing that using a small number of military field entity corpus annotations for RoBERTa pretraining word vectors and BiLSTM-CRF models and based on the bootstrapping algorithm idea to complete 3 rounds of loop iterations and 10 rounds of cross-validation joint-voting model iterations, the best entity extraction model evaluation F value reached up to 91.5%. Finally, the 60M intelligent corpus annotation application testing was completed using the best model of iteration of this round, with a total of 178,177 sentences of military field corpus intelligently labeled, the number of entities that should be labeled reaching 417,734. Therefore, this is an efficient way of construction and evaluation of intelligent corpus annotation model in the military entity extraction field. The findings of this paper provide an effective way of how to complete the labeled corpus. The research serves as a first step for future research, for example, the construction of knowledge graphs and military intelligent Q&amp;A.
Effectiveness of Semantics Feature Analysis on EFL Primary Learners’ Word Awareness

The correlation between the thematic and lexical units is a fundamental stage in language development. Understanding vocabulary from any text and category is essential in school subjects and daily life. Therefore, the current study aims at examining and analyzing the effect of semantic feature analysis (henceforth, SFA) strategy on the word awareness of EFL primary learners. The present study participants are twenty-three learners with language delay (LD), who are learning English as a second language at Da Vinci International School and Smart Kurd Private School, Duhok city, Kurdistan Region of Iraq. Furthermore, to achieve the research aims, a qualitative methodology was used, whereby students were observed, and data was collected through two main tasks, a matrix chart with and without graphical representation. The results showed that students faced fewer difficulties when identifying the physical features of lexical items in both matrixes. By contrast, the participants tended to find location features as the most difficult category. The study has also revealed that SFA with graphic representation is greatly effective in terms of vocabulary learning and retention. Moreover, this study is valuable as it investigated the effectiveness of SFA on primary learners’ word awareness. It contributes largely to children's language development in terms of lexicon enrichment, comprehension, and content retention.
Safeguarding Malay’s Folktale Through Interactive Online Art Exhibition

: Folktale is the oral tradition passed down from various generations through storytelling, writing, performing and visual presentation. It represents the culture and identity of a society. People in Malaysia recognize the value of folktales to convey messages in reprimands, advice, and satire. However, folktales are increasingly forgotten by today's generation. This descriptive study is based on ‘Sang Kancil’, a classic literary manuscript by Dewan Bahasa dan Pustaka in 2015. This study focused on ‘The Mousedeer Counting Crocodiles’ tale in the form of drawings. These were presented in the online art exhibition using the Artsteps application. The development of the online art exhibition was referred to Graham Wallas' Model of the Four Stages of Creativity which are (i) Preparation, (ii). Incubation, (iii) Illumination, and (iv) Verification. The use of the online art exhibition is a way to promote folktales using technology to entice the current generation towards the age-old heritage.