Reviewerly/exHarmony huggingface dataset:
FEATURES OF FORMING OF NATURALLY-SCIENTIFIC COMPETENCE OF STUDENTS OF BASIC SCHOOL ON BASIS OF INTEGRATED TECHNOLOGY OF STUDIES

In the article the given tasks are for the students of 5th classes, maintenance of that represents intersubject integration of natural disciplines. Exposed features of technology of the integrated studies in the conditions of transition of students from initial school to the gymnasium, taking into account the features of adaptation of schoolchildren and dominant technologies the students of 1th - 4th classes studied after that. Realization of row of principles, that come forward for introduction in the future at school of STEM- educations among that, is shown: personality going near the bread-winners of education; the following is forming of necessary ability and skills on all constituents and levels of education; the integrated going is near realization of naturally-mathematical education; the bread-winners of education - skills of work have a motive to forming and development of «flexible skills» in a group, communication; use of technologies of developing and problem studies. It is shown in the article, as work gets organized with all students of class, including with children with the special educational necessities. It is conditioned by that during organization of studies in 5th classes it is necessary to take into account on the requirements of new Ukrainian school, that after initial school in gymnasia will continue studies also to put those, that need an increase pedagogical attention. It is shown, as studies of mathematics can have a practical orientation and be related to other objects, life, prepare students to the capture practical abilities and skills, to give possibility to the students to demonstrate the financial literacy. Considered basic types of tasks of practical character and integrated maintenance, that it is expedient to use for the study of mathematics in 5th classes in accordance with the requirements of new Ukrainian school. It is presented in the article, as tasks from mathematics by regional maintenance, tasks from planning of budget of family, task of ethnology and engineering maintenance can be combination with other educational disciplines. Among them such educational objects, as natural history, that is basis for the study of physics, technology, Ukrainian literature, history. It is shown the authors of publication, as on the basis of offer tasks and own researches to form for student’s ability independently classified geometrical figures, to develop observation for schoolchildren, to extend their world view.
Web quests as a means of forming digital competence of schoolchildren

One of the main tasks of the modern school is the formation of a person with a sufficient level of digital competence. The formation of digital competence of schoolchildren will be facilitated by the inclusion of modern information and communication technologies in training as a subject of study, a means of interaction between participants in the educational process, a means of solving educational problems and planning educational activities. The use of a web quest at informatics lessons or for organizing independent work of students allows you to create conditions for the use of information and communication technologies in all the indicated aspects. The article describes an example of developing a web quest on the theme "Possibilities of the Python programming language in working with positional number systems" for students of 8th grade. This example made it possible to formulate general requirements for the structure of the web quest, for the information resource developed to accompany the web quest, for the forms of organizing the interaction of participants in the educational process, for ways of presenting the results of the work of students, for assessment procedures.
Scalable Pythagorean Mean based Incident Detection in Smart Transportation Systems

Modern smart cities need smart transportation solutions to quickly detect various traffic emergencies and incidents in the city to avoid cascading traffic disruptions. To materialize this, roadside units and ambient transportation sensors are being deployed to collect speed data that enables the monitoring of traffic conditions on each road segment. In this paper, we first propose a scalable data-driven anomaly-based traffic incident detection framework for a city-scale smart transportation system. Specifically, we propose an incremental region growing approximation algorithm for optimal Spatio-temporal clustering of road segments and their data; such that road segments are strategically divided into highly correlated clusters. The highly correlated clusters enable identifying a Pythagorean Mean-based invariant as an anomaly detection metric that is highly stable under no incidents but shows a deviation in the presence of incidents. We learn the bounds of the invariants in a robust manner such that anomaly detection can generalize to unseen events, even when learning from real noisy data. Second, using cluster-level detection, we propose a folded Gaussian classifier to pinpoint the particular segment in a cluster where the incident happened in an automated manner. We perform extensive experimental validation using mobility data collected from four cities in Tennessee, compare with the state-of-the-art ML methods, to prove that our method can detect incidents within each cluster in real-time and outperforms known ML methods.
Towards Building Autonomous Data Services on Azure

Modern cloud has turned data services into easily accessible commodities. With just a few clicks, users are now able to access a catalog of data processing systems for a wide range of tasks. How- ever, the cloud brings in both complexity and opportunity. While cloud users can quickly start an application by using various data services, it can be difficult to configure and optimize these services to gain the most value from them. For cloud providers, managing every aspect of an ever-increasing set of data services, while meeting customer SLAs and minimizing operational cost is becoming more challenging. Cloud technology enables the collection of significant amounts of workload traces and system telemetry. With the progress in data science (DS) and machine learning (ML), it is feasible and desirable to utilize a data-driven, ML-based approach to automate various aspects of data services, resulting in the creation of autonomous data services. This paper presents our perspectives and insights on creating autonomous data services on Azure. It also covers the future endeavors we plan to undertake and unresolved issues that still need attention.
Pengaruh Motivasi Belajar Terhadap Minat Belajar Peserta Didik Kelas VI Mata Pelajaran Agama Islam di Sekolah Dasar Negeri 14 Sendoyan Bungor Kecamatan Sejangkung Kabupaten Sambas

This study aims to find out: (1) Learning Motivation in Class VI Students at Sendoyan Bungor 14 State Elementary School, Sejangkung District, Sambas Regency, 2020/2021 Academic Year. (2) Interest in learning in class VI students at Sendoyan Bungor 14 State Elementary School, Sejangkung District, Sambas Regency, for the 2020/2021 academic year. (3) The significant effect of learning motivation on learning interest of class VI students at Sendoyan Bungor 14 State Elementary School, Sejangkung District, Sambas Regency, 2020/2021 Academic Year. This research is a quantitative research with an associative approach. The subjects of this study were all grade VI students of SD Negeri 14 Sendoyan Bungor, Sejangkung District, Sambas Regency for the 2020/2021 academic year, a total of 35 students. Data collection techniques using questionnaires and documentation. Data analysis techniques used simple regression analysis to answer the first and second research and multiple regression analysis to answer the third research question. The results of this study indicate that: (1) There is a positive and significant influence on learning motivation in class VI students at SD Negeri 14 Sendoyan Bungor, Sejangkung District, Sambas Regency, for the 2020/2021 academic year of 22.4% with a significance value of 0.007 &lt;0. 05 and Fcount of 8.388. (2) There is a positive and significant effect of interest in learning in grade VI students at SD Negeri 14 Sendoyan Bungor, Sejangkung District, Sambas Regency for the 2020/2021 academic year of 18.4% with a significance value of 0.016 &lt;0.05 and Fcount of 6.545. (3) There is a significant influence between learning motivation on learning interest of class VI students at SD Negeri 14 Sendoyan Bungor, Sejangkung District, Sambas Regency for the 2020/2021 academic year of 31% with a significance value of 0.006 &lt;0.05 and Fcount of 6.279.
MODERN APPROACHES TO DEFINING SPEECH GENRES

This article focuses on modern linguistics and its new promising direction, the anthropocentric theory of speech genres (TSG). The author of the article examines the importance of the theory of speech genres in the context of virtual communication and its impact on social content. The necessity of a multidimensional approach to the study of speech genres in modern genology and the virtual nature of social networks, their unstructured nature, pluralism and fragmentation are emphasized. It is concluded that the modern speech genre and the virtual speech genre are an information and communication environment based on written communication and using a wide range of linguistic means. The importance of distinguishing between speech genres on the web cannot be overstated, as it helps ensure effective communication and understanding among Internet users. Speech genres are varieties of texts or speech that have their own characteristics, style, and purpose. They are used to convey information, express thoughts, entertain, or create an emotional atmosphere. In the online space, recognizing speech genres has several crucial aspects: communication efficiency, avoiding misinterpretation, enhancing credibility, facilitating effective information seeking. In conclusion, the identifying speech genres on the web is of utmost importance as it enables effective communication, helps users find relevant content, prevents misinterpretation, enhances credibility, and fosters trust. By understanding and utilizing the appropriate speech genres, both content creators and consumers can engage in meaningful and productive online interactions.
Development of an Agile Requirements Risk Prioritization Method: A Design Science Research Study

The practice of information systems development (ISD) has changed during the past two decades from very structured approaches to agile ISD methods.However, in the literature many methods available for managing requirements-related risks follow a structured approach to ISD.Few, if any, available methods offer solutions that prioritize requirements risks for agile ISD projects based on recognizing requirements-related risks and patterns in order to mitigate these.To fill this gap in the literature, we apply the design science research methodology to develop an agile requirements risk prioritization method together with industry experts (n=54) in Finland and New Zealand in a multi-year study.The method was developed by applying contingency theory, and our study makes an artifactual contribution to the literature.The method helps practitioners prioritize the overall requirements-related risks for ISD projects.
Applying the group discussion method in vocational educational institutions on the example of computer subjects

Formulation of the problem. The article considers the problem of applying the group discussion method in vocational educational institutions on the example of computer subjects. There is a problem of developing students’ critical analysis of the information content and instilling the communication skills, promoting the professional training of students and teachers for the positive and responsible use of infor- mation and communication technology, and services. The purpose of the article. To consider the main peculiarities of the applying of group discussion methods in the educational process of vocational institutions on the example of computer subjects. The main results of the study. The modern learning process is analyzed, which provides for one of the important tasks to significantly expand the forms of learning activities of students. The characteristics of teaching methods are given. The theoretical foundations of the educational process are highlighted, which should be constructed as communication, interaction, exchange of initiatives of its participants. This is the way the educational process is organized using group, interactive (interaction-based) teaching methods – discussions, role-playing, and simulation games. The focus is on the group discussion as the most prevalent method. The main task of the group discussion is revealed: to identify the existing diversity of participants’ points of view on any problem and a comprehensive analysis of each of them on the example of computer topics. It has been proved that the organized training and education, carried out within the framework of a particular pedagogical system, has a certain organizational design, diﬀering by the quantitative coverage of students, the ratio of collective and individual forms of organization of students’ activities, the degree of their self-activity and the specifics of the educational process management by the teacher. The practical example describes the stages of conducting a discussion lesson, which contributes to the development of basic communication skills of students, develops their thinking and speaking, while they master the public speaking skills and evidence-based argument, increases their interest in computer topics. We oﬀer the author’s lesson plan for vocational institutions on the topic “Book and computer in the information society: pros and cons”. Conclusions. It is concluded that discussion is one of the most difficult types of interactive lessons. Students should not only have an understanding of the main interpretations of essential IT problems, but also express their own opinions on various issues. Discussion of these questions is impossible without gaining experience in dialogue and discussion.
The Business of Extracting Knowledge from Academic Publications

Markus Strasser (@mkstra write a fascinating article entitled "The Business of Extracting Knowledge from Academic Publications". I spent months working on domain-specific search engines and knowledge discovery apps for biomedicine and eventually figured that synthesizing "insights" or building knowledge graphs by machine-reading the academic literature (papers) is *barely useful* :https://t.co/eciOg30Odc— Markus Strasser (@mkstra) December 7,
Methodology of studying values and meanings of teacher education: hermeneutical approach

The hermeneutical approach as a traditional one for philosophy and philology, but quite new for educational science, can complement axiological approach in studying value-semantic aspects of teacher education. Pedagogic hermeneutics is a developing direction of humanitarian culture studies, based on comprehension of pedagogic reality’s objects, presented in form of a text and studied with help of a text, taking into account social and individual experience. At the same time, the text is interpreted in hermeneutics both literally and broadly, in the second case as a text can be taken any sign system, including pedagogic processes, systems, phenomena, relationships and other objects accessible to potential comprehension and interpretation by a researcher. This article provides justification for use of the hermeneutical approach as a methodology for studying values of teacher education. The author highlights a set of principles of pedagogic hermeneutics – the hermeneutic circle, information pre-understanding, dialogue understanding, text contextuality, superior understanding. Hermeneutical methods of studying the teacher education values which go back to philosophical or philological knowledge (terminological analysis, intellectual dialogue with the text’s author, diachronic analysis of the text, metaphorisation and demetaphorisation) concretise those principles. A mechanism of hermeneutical methodology, its driving forces, term base and main provisions of the hermeneutical approach in relation to studying teacher education are presented.
Steganographic embedding of information in SVG images on a WEB page

This study suggests a steganographic algorithm for embedding data in SVG images integrated into html code. The algorithm uses a composite key that includes an embed key, an encryption key, and a replacement table. The basic principle of embedding is to add style classes to an SVG image. These classes do not affect the picture in the browser. The message is encoded as the names of the classes to be added. Class names are formed based on a symmetric encryption algorithm and a replacement table. One class name contains 9 bits of information. A style set is generated for each added class. The new styles do not affect the appearance of the picture. Style settings are defined either based on default values or based on existing classes. Embed labels are added to tags with embedded data. The labels are calculated based on the hash functions from the string from the embedding key and the block number. Embedded data is randomly distributed over the code of an html page with SVG images. This arrangement makes it difficult to analyze the page when hacking the system. Embedded information is detected by sequential analysis of page code and search for embed marks. The sender of the message must have a permission to edit the web page. The recipient retrieves the message in page code view. An analysis of possible attacks on the proposed system has been carried out. Hacking of the system is possible only by direct overhauling. The system is resilient with the correct choice of hash function and encryption algorithm. The proposed steganographic embedding method is effective for html pages containing a fairly large number of SVG images.
Analysis and System Construction of ALSTM-LSTM Model-based Sports Jumping Rope Movement

Computer technology's maturity has enabled intelligent and interactive sports training.Jumping rope test in secondary school faces difficulties due to bulky testing equipment and inefficient data measurement.An ALSTM-LSTM model based on visual human posture estimation is proposed for motion system analysis.Joint pose features are fused through LSTM, and the attention mechanism assigns weights to feature sequences to achieve motion recognition, considering the data's multidimensional and hierarchical nature.The model's precision value is 95.83.Its average accuracy is much higher than LSTM, ML-KNN, and RSN models.Additionally, the model has 95.2% accuracy in localizing jump rope stance movements with low data consumption.The model can improve the accuracy of the analysis of the jump rope sport's posture based on the characteristics of human movement, and inspire new technical tools for teaching instruction.
Using Standard Deviation with Analogy-Based Estimation for Improved Software Effort Prediction

Software effort estimation is one of the most difficult tasks in software development whereas predictability is also of equal importance for strategic management.Accurate prediction of the actual cost that will be incurred in software development can be very beneficial for the strategic management.This study discusses the latest trends in software estimation focusing on analogy-based techniques to show how they have improved the accuracy for software effort estimation.It applies the standard deviation technique to the expected value of analogy-based estimates to improve accuracy.In more than 60 percent cases the applied technique of this study helped in improving the accuracy of software estimation by reducing the Magnitude of Relative Error (MRE).The technique is simple and it calculates the expected value of cost or time and then uses different confidence levels which help in making more accurate commitments to the customers.
Improved 3D Rotation-based Geometric Data Perturbation Based on Medical Data Preservation in Big Data

With the rise in technology, a huge volume of data is being processed using data mining, especially in the healthcare sector.Usually, medical data consist of a lot of personal data, and third parties utilize it for the data mining process.Perturbation in health care data highly aids in preventing intruders from utilizing the patient's privacy.One of the challenges in data perturbation is managing data utility and privacy protection.Medical data mining has certain special properties compared with other data mining fields.Hence, in this work, the machine learning (ML) based perturbation approach is introduced to provide more privacy to healthcare data.Here, clustering and IGDP-3DR processes are applied to improve healthcare privacy preservation.Initially, the dataset is pre-processed using data normalization.Then, the dimensionality is reduced by SVD with PCA (singular value decomposition with Principal component analysis).Then, the clustering process is performed by IFCM (Improved Fuzzy C means).The high-dimensional data are divided into several segments by IFCM, and every partition is set as a cluster.Then, improved Geometric Data Perturbation (IGDP) is used to perturb the clustered data.IGDP is a combination of GDP with 3D rotation (3DR).Finally, the perturbed data are classified using a machine learning (ML) classifier -kernel Support Vector Machine-Horse Herd Optimization (KSVM-HHO) to classify the perturbed data and ensure better accuracy.The overall evaluation of the proposed KSVM-HHO is carried out in the Python platform.The performance of the IGDP-KSVM-HHO is compared over the two benchmark datasets, Wisconsin prognostic breast cancer (WBC) and Pima Indians Diabetes (PID) dataset.For the WBC dataset, the proposed method obtains an overall accuracy of 98.08% perturbed data, and for the PID dataset, the proposed method obtains an overall accuracy of 98.04%.
Data Sharing using PDPA-Compliant Blockchain Architecture in Malaysia

Data privacy is undoubtedly the biggest concern for the modern society.Data privacy is also becoming a key policy in data protection regulations.Organizations assemble massive amount of personal data of the users for monetary and political purposes.These data can be sold for commercial purpose without the prior knowledge or permission from the respective data owners.This can be mitigated by having blockchain to provide a much-needed transparency.However, blockchain's own transparency becomes its own disadvantage when data owners want to be completely anonymous.Blockchain's transparent nature will be conflicting with nonlinkability.Since the data in blockchain is publicly viewable, any personal data or private transactions being processed through blockchain will be exposed to every node in the network.Hence, blockchain implementations also must comply with privacy acts such as Personal Data Protection Act (PDPA) to have privacy by design and by default.Hence, this paper proposes a PDPAcompliant blockchain architecture for data trading that provides complete control of data and anonymity to the users.A prototype is created using various tools to implement the proposed architecture.This study presents anonymous data sharing for users, data access, data delete features to verify the correctness of the proposed architecture.