Reviewerly/exHarmony huggingface dataset:
Systematic Review of BYOD Cyber Forensic Ecosystem

Since the inception of Bring Your Own device (BYOD) a series of the study conducted in various segments of BYOD. The exponential growth of the adoption of BYOD technology increased the demand for research. As a result, academic researchers created a good amount of abstracts with new techniques and methods. This study article offers a systematic study of existing techniques and development on the BYOD cybersecurity ecosystem. The primary goal of this systematic review is to identify the existing research specifically on BYOD Cyber forensic ecosystem and grouping the techniques developed in various areas and summarized the findings. Post analyzing 8519 articles this study identifies the potential 18 research which contributes to enhancing the cybersecurity forensic ecosystem. Limitations of existing research are also identified which organizations need to mitigate to build a cyber secured Forensic BYOD environment. Finally concluded that BYOD Cyber secured ecosystem is indeed needed for the organization for enabling BYOD services so that due to the impact of cyberattacks in the BYOD environment business ecosystem does not get fragmented.
ADAPTIVE SECURE AND DYNAMIC ENCRYPTED CLOUD DATA USING ELLIPTIC CURVE CRYPTOGRAPHY

Cloud computing is technology based on the internet. Computing actually took place on a computer that is not the one currently being used, mostly remote. Data obtained during this process is stored by remote servers and processed by them. Cloud encryption is required because, when it is distributed via the Internet and other computer networks, its main purpose is to safeguard and protect sensitive information. Providers of cloud storage encrypt data and transfer the user’s encryption keys. When required, these keys are used to securely decrypt data. Many studies have argued a variety of cryptographic techniques to preserve the privacy and security of user data stored in the cloud. In this paper, to encrypt the data, an effective privacy protection scheme called Elliptic Curve Cryptography (ECC) is proposed. Uploading encrypted files and indexes to a cloud server will reduce the computing cost of encryption and decryption. It will then allow users to use the hash conflict feature to create trap door and send it to the cloud service provider to search for matched ciphertext. Experiments show that, by using this process, files can be encrypted, decrypted, and retrieved more easily compared to conventional methods. It can also maintain data protection and decrease the overhead for communication.
Retraction: Administered Machine Learning Models for Covid-19 Future Forecasting (J. Phys.: Conf. Ser. 1916 012157)

This article (and all articles in the proceedings volume relating to the same conference) has been retracted by IOP Publishing following an extensive investigation in line with the COPE guidelines. This investigation has uncovered evidence of systematic manipulation of the publication process and considerable citation manipulation. IOP Publishing respectfully requests that readers consider all work within this volume potentially unreliable, as the volume has not been through a credible peer review process. IOP Publishing regrets that our usual quality checks did not identify these issues before publication, and have since put additional measures in place to try to prevent these issues from reoccurring. IOP Publishing wishes to credit anonymous whistleblowers and the Problematic Paper Screener [1] for bringing some of the above issues to our attention, prompting us to investigate further. [1] Cabanac G, Labbé C and Magazinov A 2021 arXiv: 2107.06751v1 Retraction published: 23 February 2022
The educational component “Teaching methodology of social and health-care educational sector” under quarantine restrictions

The article reveals the theoretical and practical aspects of the organization of blended learning of future primary school teachers under quarantine caused by COVID-19. On the example of the educational component “Teaching methodology of social and health-care educational sector” the article describes the peculiarities of organizing the educational process in blended format, namely providing examples of tasks that allow to form civic and social competencies of first-level higher education students under the conditions of new time challenges. The article focuses on the specificities of working in the virtual learning environment Moodle, summarizes own teaching experience of training of educational component “Teaching methodology of social and health-care educational sector”. The author's method of structuring and content of the educational component is proposed, which is reflected in the textbook. The necessity of using digital tools Canva, Padlet, Coggle for organizing group work of students during blended learning under quarantine conditions caused by COVID-19 is considered and also the samples of tasks to be completed by future primary school teachers are given. The article presents the results of a survey of applicants for the first level of higher education program 013 Primary Education, which show that students have a generally positive attitude to using digital tools Canva, Padlet, Coggle, as it positively influences the formation of their professional competence and the formation of their own methodological system. The author's method suggested in this article is incomplete and is continually being improved in accordance with time challenges.
ORGANIZATION OF STEM LESSON ON “MAKING A SMART EPOXY NIGHT LIGHT” TO DEVELOP CREATIVE AND PROBLEM-SOLVING CAPABILITY FOR HIGH SCHOOL STUDENTS

Developing students' creativity and problem-solving capability is a necessary, important, and long-term goal in high schools. Integrating STEM topics into the high school curriculum through interdisciplinary integration of subjects to solve real-life problems helps learners create practical products with useful application. Thanks to the STEM topics, learners are encouraged to apply their acquired knowledge to solve specific problems in real life, from which many different competencies are formed and developed for students especially problem-solving and creativity. The article presents the impact of applying STEM topics in teaching Chemistry to the development of students' creative and problem-solving abilities, the process of designing STEM topics in teaching Chemistry, the steps to implement the topic, product evaluation criteria, evaluation criteria for component competencies of creativity and problem-solving capability, and the results to develop students' problem-solving and creative capability through experimental teaching activities in high schools. The data obtained from the teacher’s assessment and the students’ selfassessment showed obvious development of students’ creative and problem-solving capability in the experimental class.
Social and pedagogical competence of experts of the social sphere

Participants.The study involved 294
Enhancing Features of Cloud Computing Using Cloud Access Security Brokers to Avoid Data Breaches

Data breaches have gained widespread attention as businesses of all sizes become increasingly reliant on digital data, cloud computing, and workforce mobility. Cloud applications reduce costs and improve productivity. But it is equally important to monitor and protect data in a cloud environment. These are the questions that arise how to deal with lost visibility, unmanaged devices, and careless users. This paper explains how cloud access security brokers (CASBs) extend security to cloud applications, awareness for data breaches, providing visibility, threat protection, access control, and compliance. The key characteristics and benefits of cloud access security brokers (CASBs) are visibility, threat protection, access control and compliance are key components of this paper to extend data loss prevention (DLP). There is need to create the architecture of CABs having feature to deal with all types of Data Breaches. The result of the study provided a secure architecture to fulfill the security needs and tracks the complex connections between enterprise infrastructure and its cloud service provider.
String

The String class in Java is a data type that can hold string literals. String is a reference data type, as are all non-primitive data types. This means that the variable contains an address to an object in the memory and not the object itself. A String object is created in the memory, and the address to the object is returned to the variable. As seen in the following code, string literals are delimited by double quotes:
Levels of Interaction between Aspect and Tense

Chapter 5 describes how all verbs are anchored in the system of positive real numbers R+ by focussing on the meaning of a verb without taking into account its arguments. This makes it possible to distinguish stative from non-stative verbs by assigning to each of them a (mathematical) function determining the value of the eventuality argument ?? of the verb. The next step is then to separate non-stative verbs expressing continuity in R+ from verbs expressing discreteness in N by assigning to the latter a discretizing function mapping from R+ to N. A formal account of aspectual composition from the tenseless bottom to the tensed top S’ makes it possible to distinguish the (ten) factors that are in play on different levels of phrase structure.
FINANCIAL VIABILITY OF CRYPTOCURRENCIES IN PAKISTAN

The globally acknowledged accelerating crypto hype has put a lot of work on researchers and analysts. This new marvel of digital currencies requires a lot of attention, for it to become conventional worldwide. Virtual coins or cryptographic forms of money utilize encryption framework, so called the Block Chain technology, that manage the formation and supply of coins and exchanges must be recognized from a financial examination point of view. Subsequently, it is essential to inspect which social, money related &amp;amp; macroeconomic components decide its cost with a specific end goal to know the degree and outcomes of the economy. This paper aims to study different internal and external factors that affect cryptocurrencies’ prices. A sample of four digital coins with largest market capitalization has been selected. Daily price data from the years 2015 to 2020 of Bitcoin with other altcoins such as Ethereum, Ripple and Litecoin has been taken. Internal factors consist of demand and supply variables and also the attractiveness associated with its increasing hype. Other factors include KSE-100 Index (Karachi Stock Exchange), USD-PKR (Dollar to Pakistani Rupee) exchange rate and oil prices from PSO (Pakistan State Oil). ARDL analysis has been done to study the effect of these factors on the prices of crypto coins. Our analysis shows that circulating supply has a significant effect on Ethereum and Ripple prices in the long run. Attractiveness has been significant on the prices of Ethereum only.
Penggunaan Teknologi Informasi dan Komunikasi (TIK) dalam Knowledge Sharing pada PT. Indonesia Villa Jaya Batam

Knowledge management has been applied in various organizations. The implementation of knowledge management will not work if there is no process of knowledge sharing. Knowledge sharing is the key to an organization's success. To facilitate knowledge sharing, it can use information assistance. The existence of information technology can be an enabler in the process of knowledge sharing. PT. Indonesia Villa Jaya is a company of production field. This company is one of the companies that already did knowledge sharing activities. Knowledge sharing activities include routine meetings, training, watching together, and many other activities. Knowledge sharing activities in this company are also inseparable from the role of information technology. However, this time, the use of information technology in this company has not been maximized that there are still many complaints from employees regarding the use of information technology for knowledge sharing. This study aims to determine the description of the use of information technology for knowledge sharing. The information technology that will be discussed from this research are ICT tools, ICT infrastructure, and ICT know-how. This is a quantitative research. The population of this research is the employees of PT. Indonesia Villa Jaya, with questionnaire collection methods and census sampling techniques, and data analysis techniques with descriptive analysis. The results of this study indicate that the use of information technology for knowledge sharing at PT Indonesia Villa Jaya is at a good level. ICT Infrastructure has the highest value for information technology variables that support knowledge sharing.
Features of programming training of future teachers of informatics

Problem and goal. The problem of identifying approaches to training in programming of future teachers of informatics in the context of technologization of modern society is considered. The aim is to determine the features of teaching programming to informatics students of pedagogical universities, as well as the formation of a system of programming languages for teaching future teachers of informatics. Methodology. To solve this problem, a range of research methods was used: analysis of regulatory documents that determine the priority tasks of education and of research and scientific and methodological publications of foreign and domestic scientists, as well as training experience in programming of informatics students of pedagogical universities; reflection of the content of the knowledge gained; identification of approaches to teaching programming for future teachers of informatics. Results. An analysis of the experience of programming teaching to students of pedagogical universities was carried out, including the personal experience of teachers, which made it possible to identify such relevant in modern conditions approaches to teaching future teachers of informatics programming as fundamental and multilevel; specifics of teaching programming, taking into account the professional and pedagogical orientation of the training of future teachers of informatics, are determined; a multilevel system of programming languages for teaching future teachers of informatics is proposed. Conclusion . In the context of the dynamically developing field of information technology and the growing interest in programming, it is important to provide school education with teachers of informatics who have competencies in the field of programming, ready to teach modern programming languages to schoolchildren.
Virtual Reality as Participant

As virtual reality is implemented into military pilot training programs, it poses questions and challenges for instructors and instructional designers who create and facilitate virtual reality-driven courses. This chapter explores virtual reality as a technical participant in student learning, using an introductory course on flying offered at the United States Air Force Academy (undergraduate, freshmen) as an example. This introductory course includes assigned readings, brief classroom instruction, and virtual flying time. A majority of class time is spent in an immersive virtual reality flying scenario. The purpose of this chapter is to inform various stakeholders, particularly course or instructional designers, about virtual reality as an interactive participant in student learning and about the role key characteristics of virtual reality may play in instructional design. Additionally, this chapter offers instructional design considerations for creating a course or lesson primarily around immersive virtual reality experiences.
Art education on big data and digital platforms base of higher education institutions

The study aimed to identify Big Data components and the role of the digital platform used for art education. In addition, the aim can be considered a definition of participants' role in the educational process in a broad application of Big Data and digital platforms. In conducting the research, a comprehensive approach was actively used, as well as descriptive methods, qualitative and quantitative ways of monitoring. We used questionnaires to get the necessary information, studied the essential literary sources, collected and analyzed data, and summarized the results. After summarizing the information obtained, it became clear that the Big Data use and digital platforms for art education allowed the transfer of the classical educational process to digital media and created the necessary environment for intellectualizing the educational process. In the future, it is worth considering and searching for options on how to get rid of the gaps in the use of information technology for art education. Relevant issues can be viewed as the problems of security, confidentiality, ethical component, compatibility, data storage, and processing problems, and the acute experienced personnel shortage.
Incorporating Lévy Flight to Distribution-Based Discrete Particle Swarm Optimization

Particle swarm optimization (PSO) has been extended and shown to perform well on discrete optimization. Some of the extended PSOs handle continuous parameters of probability distributions over variable values of candidate solutions instead of directly handling discrete variables. These distribution-based discrete PSOs (DDPSOs) sample a variable value from a probability distribution for each variable to generate a candidate solution. This procedure can be considered as a kind of random local search centering on an intended solution, which has the highest generation probability. It has drawbacks the step size increases proportionally and the probability of producing solutions close to the intended solution decreases exponentially in high-dimensional problems. This paper proposes a novel sampling method (NS) to control the step size for DDPSO and determined the step sizes according to Lévy distribution in a similar way to Lévy flight. NS is applied to three representative DDPSOs, and they were compared in integer and categorical versions of function optimization problems and NK landscape problems. The results show NS improves the efficiency and robustness of all the DDPSO variants. In addition, NS was tested on feature selection experiments and was achieved superior results compared to some evolutionary algorithms designed for feature selection.
Using Geochemical Data to Understand Geological Processes H. Rollinson and V. Pease Cambridge University Press. pp346. Paperback price £49.99. ISBN 978-1-108-74584-0 https://doi.org/10.1017/9781108777834

Using Geochemical Data to Understand Geological Processes H. Rollinson and V. Pease Cambridge University Press. pp346. Paperback price £49.99. ISBN 978-1-108-74584-0 https://doi.org/10.1017/9781108777834 - Volume 85 Issue 5
A Comparative Analysis of the Student Motivation in Light of Glynn and Kobal-la (2006) Five Factors Model at a Higher level

It was a comparative analysis of students' motivation in light of Glynn and Kobal-la (2006) five factors model at a higher level. Objectives were to assess the level of students' motivation and differences in the students' motivation on the basis of gender/age/university.The population was 9615 students of public universities of Islamabad. By using a convenient sampling technique, 260 students were selected. The tool was developed by Mubeen and Reid (2014), in light of the G AND K model. The data was analyzed by using Cronbach alpha reliability, intersection correlation, t-test, and ANOVA. The majority of respondents were above Average level of motivation. A significant difference between male and female students related to all the factors of motivation, and females were found better than male students. However, age-wise, no significant difference was found related to motivation. Overall, Air University students were found better than other universities. It is recommended that teachers and management need to plan group work for students not only involved but also engage them in positive competitions. There is a need to develop a sense of responsibility. Teachers need to set achievable goals as well for students to encourage task completion
Multi-scale automated detection of active faults from precisely relocated earthquake catalogs

Machine Learning (ML) and Digital Twins (DT) are at the heart of today’s different industries, ranging from advanced manufacturing to biomedical systems to resilient ecosystems, civil infrastructures, smart cities, and healthcare. They have become indispensable for solving complex problems in science, engineering, and technology development. The purpose of the MMLDT-CSET 2021 conference is to facilitate the transition of ML and DT from fundamental research to mainstream fields and technologies through advanced data science, mechanistic methods, and computational technologies. This 3-day conference features technical tracks of emerging ML-DT fields and applications, special public lectures, short courses, and demonstrations. The conference will be held in a hybrid format, featuring both on-site and virtual sessions.
Security

You have learned many of the most important security aspects of Azure API Management already. However, there is at least one aspect remaining that you need to understand, authentication. In this chapter, you will learn to authenticate a client with a backend web service using both HTTP basic authentication and OAuth 2.0. At the end of this chapter, you will learn about two additional security aspects that are important to understand when working with Azure API Management.
Joint learning of latent representation and global similarity for multi-view image clustering

Multi-view subspace clustering aims to divide a set of multi-source data into several groups according to their underlying subspace structure. However, the similarity matrix which is learned by most existing methods, can not well characterize data themselves more comprehensively in original data space and the global similarity the multi-view data. In this paper, we propose to jointly learn the shared latent representation by different views and the similarity matrix in a unified model. Our model can learn the shared latent representation of multi-view data from the latent space and the similarity matrix from the shared latent representation simultaneously. Experimental results on four benchmark datasets demonstrate that our method outperforms other existing competitive multi-view clustering methods.
Information-theoretic feature selection based on the Weight of the New Classification Information

Many objective functions of feature selection methods are positively correlated with the amount of the new classification information and negatively correlated with the amount of redundant information. However, a critical issue in these methods is they ignore the magnitude of the negative correlation of redundant information. So, we proposed a new method from another perspective to measure redundancy between features, and employ the Weight of the New Classification Information (WNCI) to ensure features are related with class label when selected feature is given. Finally, we tested the classification accuracy of the proposed method and compared with five other methods on eighteen data sets. Then the experiment results show that the new proposed method performs better than these other methods in terms of classification accuracy.