Reviewerly/exHarmony huggingface dataset:
THEORETICAL FRAMEWORK FOR TEACHERS SELF- ASSESSMENT TO TEACH 21ST CENTURY SKILLS

The context of educational reforms taking place in many countries gives special relevance, as the curriculum enters the 21st century skills or so-called transversal skills. It is necessary to ascertain how successful the teaching of these skills is already so that the school management together with teachers develop evidence-based or data-driven professional development solutions. The aim of the research is to create a theoretical framework and corresponding self-assessment tools, how the teacher can assess for himself to what extent he has succeeded in achieving the competence to teach students in the 21st century skills required to achieve the goals set by the school in the context of the ongoing education reform in the country. For the self-assessment of teachers’ competencies, performance appraisal is used, comparing to what extent does teaching in a particular case correspond to good practice using performance level descriptors as tools - a set of teachers' learning progressions and tests. The developed set of teachers' professional learning progressions is based on data-based and field-tested analytical descriptions of performance levels from expert work. It includes 17 progressions developed within the framework of categories and criteria, the practical testing of which in school practice is planned in the authors' further research.
CYBER VULNERABILITY IN LIGHT OF ONLINE LEARNING REALITY

Presently, as Covid 19 has caused most of educational processes to move online, cybersecurity and data protection is rapidly gaining importance in all educational institutions, and most of the academia became more vulnerable to cyberattacks. This article sheds some light on how communities of higher education institutions perceive increased online threats, what measures they take to protect themselves against cybercrime, whether they practice good security hygiene. This paper presents and analyses results of a survey conducted at higher education institutions (universities, colleges) into perception of cybersecurity, online culture and hygiene during the present times of remote education.
Using Knowledge Graphs to Plausibly Infer Missing Associations in EMR Data

Electronic Medical Records (EMRs) are increasingly being deployed at primary points of care and clinics for digital record keeping, increasing productivity and improving communication. In practice, however, there still exists an often incomplete picture of patient profiles, not only because of disconnected EMR systems but also due to incomplete EMR data entry – often caused by clinician time constraints and lack of data entry restrictions. To complete a patient’s partial EMR data, we plausibly infer missing causal associations between medical EMR concepts, such as diagnoses and treatments, for situations that lack sufficient raw data to enable machine learning methods. We follow a knowledge-based approach, where we leverage open medical knowledge sources such as SNOMED-CT and ICD, combined with knowledge-based reasoning with explainable inferences, to infer clinical encounter information from incomplete medical records. To bootstrap this process, we apply a semantic Extract-Transform-Load process to convert an EMR database into an enriched domain-specific Knowledge Graph.
File Spooler and Copy System for Fast Data Transfer

CERN (derived from Conseil européen pour la recherche nucléaire) is a European research organization in nuclear physics, which has particle accelerators and other infrastructures necessary for high-energy physics research.
Web Application Development for Inferential Statistics using R Shiny

The rapid development of world technology has a major influence in the world of education and can be used to support learning activities.Regarding the rapid advancement of computers, statistics learning can be done with many online computer simulations.Computer simulation and visualization in supporting statistics learning is necessary to design program well.This can increase interest, motivation and understanding in learning statistics both theory and application, so it is not boring.Many frameworks can be used to build website-based applications; one of them is the Shiny Web Framework.Shiny is a package of the R programming language that makes the users easily build web-based applications.By using R-shiny, the users are not required to master R program because it has friendly and interactive web-based menus.Therefore, R-shiny is very good as a complement in statistic learning that the users are able to focus more on statistical concepts without being limited their ability to master statistical software.
On the State of Genre/Form Vocabulary: A Quantitative Analysis of LCGFT Data in WorldCat

The purpose of this paper is to report on a quantitative analysis of the LCGFT vocabulary within a large set of MARC bibliographic data retrieved from the OCLC WorldCat database. The study aimed to provide a detailed analysis of the outcomes of the LCGFT project, which was launched by the Library of Congress (LC) in 2007. Findings point to a moderate increase in LCGFT use over time; however, the vocabulary has not been applied to the fullest extent possible in WorldCat. Further, adoption has been inconsistent between the various LCGFT disciplines. These and other findings discussed here suggest that retrospective application of the vocabulary using automated means should be investigated by catalogers and other technical services librarians. Indeed, as the data used for the analysis show somewhat uneven application of LCGFT, and with nearly half a billion records in WorldCat, it remains a certainty that much of LCGFT’s full potentials for genre/form access and retrieval will remain untapped until innovative solutions are introduced to further increase overall vocabulary usage in bibliographic databases.
Microcontroller based Autistic Child Monitoring System in Bangladesh

Children with developmental disorders and their families face major challenges in managing the risk to a disabled child, who may be prone to becoming lost away from their own home. Health and Social care system in Bangladesh has not yet developed the capacity and infrastructure to provide safety services to children with ASD (Autistic Spectrum Disorder). There are no nationwide statistics of Autistic Children in Bangladesh. As per the global prevalence rate, 1 percent of the world population has autism. One in 160 children has an ASD. Since there are 55 million children in Bangladesh below age 14, there may be 550,000 autistic children. As the physically challenged child cannot take care of themselves and no one is there who can keep observation 24-hour like whether the child is getting panic, whether the child is on safety zone or changed his position elsewhere, whether he falls, etc. We have to keep them safe as the number of accidents with children is increasing. Our research study proposed the development of a wearable smart device, which can be a belt, wristwatch or locket. The developed device include a Microcontroller (PIC-16F876A), a global positioning system (GPS), global system for mobile (GSM), and switching unit and the monitoring unit includes sensors and mobile device in parent’s hand with which parents can find the current location of the child by using Google Map. This device ensures 24-hour monitoring and works as an interface between child and parents for emergency response.
Choice Of Reading Materials And Reading Achievement Of Junior High Students

Reading is an important skill that can be used to communicate and understand the academic, business and cultural world. Reading can be a tool for learners’ progress and success in different fields of discipline. This study utilized descriptive-correlational design to examine 41 respondents selected as census or total enumeration using purposive sampling. Findings revealed that majority of the respondents used hard copy reading materials for the past 12 months. There were 22 respondents who used books, 2 who used magazines and 1 respondent used newspaper. Most of the class were in frustration level which is 75. 6%. There was one non-reader. Independent readers were four and instructional were five. There was a significant negative relationship (cc= -0.572 and p-value= 0.001) between choice of reading materials and reading achievement. This suggested that the use of soft copies as reading material is correlated to high reading achievement. The implications may serve as basis for intervention, program, and policy formulation. Teachers need to design interactive reading materials using the 21st Century technologies like soft copies reading materials which can be handy and can be access anytime and anywhere using mobile phones. Reading intervention using technology-based materials may be designed to improve reading achievement of the students. Schools may introduce e-library which may introduce various materials that can be accessed and read in soft copy format. This will also be beneficial to distance learning modality.
Framework Design IoT for Smart Agriculture

West Bandung Regency has a very abundant potential of natural resources, one of which is in agriculture. Agriculture is the use of resources made by humans to produce food and manage their environment. One of problem is the inability of farmers to supervise and take care of crops so that an intelligent agricultural system based on IOT is required. The intelligent agricultural system aims to predict and monitor the problems faced by farmers to increase the productivity of agricultural products. In this study, it proposed a design of intelligent agricultural framework by configuring several sensors that generated data from agricultural land and then the information is presented in the monitoring system for the use of the user to determine the decisions in conducting agricultural activities.
The impact of transformational leadership on the quality of work-life – An applied study in telecommunications companies -The Hashemite Kingdom of Jordan –: تأثير الْقِيَادَة التّحويليّة في جودة حياة العمل – دِرَاسَة تطبيقية على العاملين في شركات الاتصالات - المملكة الأردنية الهاشمية –

This study aims to identify the impact of transformational leadership on the quality of work-life in telecommunications companies operating in the Hashemite Kingdom of Jordan. The researcher has employed the descriptive analytical approach to analyze the study data، the most important results reached in this study are: the overall average answers for the workers on transformational leadership comes high, with an arithmetic average (3.79) , while the quality of work-life has come to a medium degree with an arithmetic average (3.17). The study recommended that leaders in telecommunications companies should be encouraged to continue practicing the transformational leadership style because of its characteristics and practices that have an impact on the effectiveness of the company and taking into account the social and humanitarian aspects of workers.
Unveiling the End-User Viewport Resolution From Encrypted Video Traces

Video streaming is without doubt the most requested Internet service, and main source of pressure on the Internet infrastructure. At the same time, users are no longer satisfied by the Internet’s best effort service, instead, they expect a seamless service of high quality from the side of the network. As result, Internet Service Providers (ISP) engineer their traffic so as to improve their end-users’ experience and avoid economic losses. Content providers from their side, and to enforce customers privacy, have shifted towards end-to-end encryption (e.g., TLS/SSL). Video streaming relies on the dynamic adaptive streaming over HTTP protocol (DASH) which takes into consideration the underlying network conditions (e.g., delay, loss rate, and throughput) and the viewport capacity (e.g., screen resolution) to improve the experience of the end user in the limit of the available network resources. In this work, we propose an experimental framework able to infer fine-grained video flow information such as chunk sizes from encrypted YouTube video traces. We also present a novel technique to separate video and audio chunks from encrypted traces based on Gaussian Mixture Models (GMM). Then, we leverage our dataset to train models able to predict the class of viewport (either <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SD</i> or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HD</i> ) per video session with an average 92% accuracy and 85% F1-score. The prediction of the exact viewport resolution is also possible but shows a lower accuracy than the viewport class.
Towards a Semantic Data Harmonization Federated Infrastructure

Data integration is an increasing need in medical informatics projects like the EU Precise4Q project, in which multidisciplinary semantically and syntactically heterogeneous data across several institutions needs to be integrated. Besides, data sharing agreements often allow a virtual data integration only, because data cannot leave the source repository. We propose a data harmonization infrastructure in which data is virtually integrated by sharing a semantically rich common data representation that allows their homogeneous querying. This common data model integrates content from well-known biomedical ontologies like SNOMED CT by using the BTL2 upper level ontology, and is imported into a graph database. We successfully integrated three datasets and made some test queries showing the feasibility of the approach.
Citizens’ Readiness to Use Electronic Voting System in Oyo State, Nigeria

The right to vote, which is identified as one of the fundamental human rights, encourages civic consciousness through political participation. Elections in Nigeria have been found to record low turnout, which has been partly attributed to problems identified with the traditional voting system used in the county. This study investigated the perception of Oyo state citizens about e-voting system, as well as their readiness to use the system. Descriptive survey research design was adopted. Questionnaire data was collected from 390 respondents, while 20 respondents were also interviewed. Questionnaire data were analysed using the Statistical Package for Social Sciences and presented using descriptive statistics in form of frequency, percentage, mean and standard deviation. The interview data was analysed using Nvivo software, version 10. Findings reveal that citizens perceived the current voting system as stressful and not transparent, and that e-voting system would be better than the present voting system because of the advantages associated with technology use. The citizens are ready to use e-voting system, if adopted by Nigerian government. The study recommends that Nigerian government could adopt and implement e-voting system to reduce the huge financial expenses associated with conduct of elections, as well as some other challenges that have been associated with elections in Nigeria.
Specifications for the Routine Implementation of Federated Learning in Hospitals Networks

We collected user needs to define a process for setting up Federated Learning in a network of hospitals. We identified seven steps: consortium definition, architecture implementation, clinical study definition, data collection, initialization, model training and results sharing. This process adapts certain steps from the classical centralized multicenter framework and brings new opportunities for interaction thanks to the architecture of the Federated Learning algorithms. It is open for completion to cover a variety of scenarios.
Defining a Reference Architecture for Transformed Health Ecosystems

The paper discusses requirements and solutions for design and management of transformed health ecosystems. After introducing related definitions with reference to the transformation of health to P5 medicine, basics on systems, knowledge representation and management as well as system development processes and their formal representation/modelling from the perspectives of systems theory, theory of knowledge, languages and grammars are considered in some detail. As result, the ISO 23903 reference architecture is shortly introduced and compared with other existing approaches and standards.
RESEARCH OF ROBOTIC SYSTEMS CONTROL METHODS USING MOTION RECOGNITION TOOLS, MACHINE LEARNING AND SKELETALIZATION ALGORITHMS

The aim of the research is to develop possible control methods of robotic systems based on the usability of motion detection equipment, skeletalization algorithms and robotic systems, integrating them into the existing test bench by performing compatibility tests. The article reviews the possible motion detection systems, establishing the criteria of applicability in the control of robotic systems, describes the experimental research plan, research stand, discusses the research results and presents summarized conclusions and suggestions for the integration of research results into the educational process.
Decision Support System for Service Quality Using SMART and Fuzzy ServQual Methods

The Regional Technical Implementation Unit of the Tresna Werdha Social Home for the Elderly of Natar South Lampung does not yet have a systematic calculation, which can be a parameter of the quality level of each service. This study develops a system to solve the problem of the calculation gap between perceptions and expectations in determining the quality level of each service, namely the Decision Support System using the Simple Multi-Attribute Rating Technique Method (SMART) and Fuzzy Service Quality. The results showed that the SMART method obtained an accuracy rate of 85.71%, 75.00% Precision, 100% Recall, and 100% Specificity, while the Fuzzy Service Quality method obtained an accuracy rate of 71.43%, 66.67% Precision, 66.67% Recall, and 75.00% Specificity. So that the Simple Multi-Attribute Rating Technique Method (SMART Method) is superior, so it is more appropriate to solve the problem of decision-making on the level of service quality at the Regional Technical Implementation Unit of the Tresna Werdha Elderly Social Home, Natar South Lampung.
Health risk assessment of heavy metals contamination in sediments of the River Nile, Damietta Branch using Mathematical Models

This study was conducted to evaluate heavy metals pollution in sediments of the Nile River-Damietta Branch using mathematical models of heavy metal indices (enrichment factor (EF), contamination factor (CF), pollution load index (PLI), degree of contamination (DC) and geo-accumulation index (I geo )).The results showed that the concentrations of heavy metals in sediment samples, followed the order of Fe> Zn> Pb> Co> Ni> Cu> Mg.The EF for each heavy metal element was calculated relative to the background values after normalization with the Fe element.According to the mean values of EFs, the descending order of heavy metals enrichment in the sediments was: Cd >Fe> Pb > Co > Zn > Ni > Cu (greater to lower).Cd was considered to poses significant to very high enrichment along with the different stations along the study area.In addition, it recorded very high contamination (7.41±0.71)and I geo mean value (6.50 ± 1.32) along the study area.PLI values varied between 0.813 and 2.331 along the study area with a mean value of 1.338 ± 0.477.This result showed a considerable degree of contamination (mean value =16.442 ± 7.136) along the branch.However, stations 3, 5, 9 and 10 recorded a very high degree of contamination with values (30.901, 33.867, 56.932 and 48.536), respectively.HI values of heavy metal order was: Cd (239.63)> Pb (72.65) > Co (34.732) > Ni (14.457) > Zn (5.952) > Cu (4.719) > Fe (2.896).With respect to human health, Ni, Pb, Cd, Fe, Zn, Cu, and Co were identified as potential contaminants.whereas, Pb, Cd and Cu are classified as non-carcinogenic by Agency for Toxic Substances and Disease Registry.
Multiobjective evolutionary flight planning of autonomous unmanned aerial vehicles for exploration and surveillance

This article presents a multiobjective evolutionary approach for computing flight plans for a fleet of unmanned aerial vehicles to perform exploration and surveillance missions. The static off-line planning subproblem is addressed, which is useful to determine initial flight routes to maximize the explored area and the surveillance of points of interest in the zone. A specific flight planning solution is developed, to be applied in low-cost commercial Bebop 2. The experimental analysis is performed in realistic instances of the surveillance problem. Results indicate that the proposed multiobjective evolutionary algorithm is able to compute accurate flight plans, significantly outperforming a previous evolutionary method applying the linear aggregation approach.
Research on power prediction of photovoltaic power station based on similar hour and LM-BP neural network

Aiming to solve the problem of low precision of traditional photovoltaic power forecast method under abrupt weather conditions. In this paper, a high-precision photovoltaic power prediction method based on similarity time and LM-BP neural network is proposed. Firstly, the factors affecting the output power of photovoltaic power station are analyzed, and the short-term output power model of photovoltaic power station is established based on similar day and LM-BP neural network. Then, from the perspective of model training efficiency and prediction accuracy, the deficiencies in the short-term power prediction of photovoltaic power stations based on similar days and LM-BP algorithm are analyzed. Secondly, the prediction model of LM-BP neural network based on similar hours is established. Finally, Jiaxing photovoltaic power station is taken as an example for simulation verification. The simulation results show that the proposed method has high accuracy in predicting photovoltaic power under abrupt weather conditions.
Gaussian quantum states can be disentangled using symplectic rotations

We show that every Gaussian mixed quantum state can be disentangled by conjugation with a passive symplectic transformation, that is a metaplectic operator associated with a symplectic rotation. The main tools we use are the Werner-Wolf condition on covariance matrices and the symplectic covariance of Weyl quantization. Our result therefore complements a recent study by Lami, Serafini, and Adesso.
CHANGING FOREIGN LANGUAGE TEACHING STANDARDS AS A CONDITION FOR UNIVERSITY GRADUATES' EMPLOYABILITY

The main aim of the study is to substantiate a new foreign language teaching standard in the universities of Russia closing the gap between the standards and the modern job market demands. In order to achieve this aim it is necessary to define the vector of the changes and correlate them with the bachelor and master students’ requirements. The main changes which the modern labor market is undergoing are the emergence of new related professions, blurring borders between professions, difficulties defining narrow vocational standards. The study hypothesizes that foreign language teaching standards should be transformed towards greater interdisciplinarity and development of soft skills rather than a merely linguistic component in the course. The main methods of research, namely analyzing literature on the soft skills in demand with employers, polls of bachelors and masters on the need and possibility to develop soft skills in the ELT classroom, allowed identifying the soft skills which are in greater demand in terms of employability in the modern job market and received a positive feedback from the respondents – communicative competence, learnability, critical and creative thinking, collaboration skills. A similar poll was conducted among the graduates of the CAAS MSU working in various spheres. The study resulted in developing the new foreign language teaching standard which encompasses teaching two European languages, instructing with the help of interdisciplinary materials and forming soft skills on all the stages of foreign language acquisition.