Reviewerly/exHarmony huggingface dataset:
Progressive Scrambling for Social Media

Despite research work achieving progress in preserving the privacy of user profiles and visual surveillance, correcting problems in social media have not taken a great step. The reason is the lack of effective modelling, computational algorithms, and resultant evaluations in quantitative research. In this article, the authors take social media into consideration and link users together under the umbrella of social networks so as to exploit a way that the potential problems related to media privacy could be solved. The author's contributions are to propose tensor product-based progressive scrambling approaches for privacy preservation of social media and apply our approaches to the given social media which may encapsulate privacy before being viewed so as to achieve the goal of privacy preservation in anonymity, diverse and closeness. These approaches fully preserve the media information of the scrambled image and make sure it is able to be restored. The results show the proposed privacy persevering approaches are effective and have outstanding performance in media privacy preservation.
An Objective Compliance Analysis of Project Management Process in Main Agile Methodologies with the ISO/IEC 29110 Entry Profile

Software Process Improvement efforts (SPI) are pursued by organizations for improving the overall quality of their software development processes. However, very small entities (VSEs) avoid them by the lack of required financial and other organizational resources. In contrast, VSEs use agile software development methodologies (ASDMs), but these ASDMs do not foster adherence to best scholastic practices promoted by SPI. Furthermore, while a new ISO/IEC standard (29110) has been recently released for VSEs, it was not designed taking account the ASDM approaches. Thus, we investigate the extent of adherence of main ASDMs (two industrial and one academic type) with this new standard. Initial results provide evidence on the strong need to enhance the two industrial ASDMs (XP and SCRUM). In contrast, the academic ASDM (UPEDU) fits the standard very well but it is scarcely used by VSEs. Hence, it is concluded that there is a knowledge gap between the praxis with ASDMs and the recommended scholastic software processes like the ISO/IEC 29110 standard for VSEs.
Methods of developing artistic empathy of future Music teachers in the process of vocal training

The article substantiates the essence, content and method of developing artistic empathy. The purpose of the article is to substantiate the methods of vocal training that are effective in developing the artistic empathy of the future Music teachers. The purpose of the article is realised through the use of methods of theoretical research: analysis, synthesis, generalisation, deduction, induction, extrapolation. The article clarifies the meaning of the concept "empathy" as a psychological process based on penetration into the inner world of a person. Empathy is interpreted as the integration of emotional and cognitive aspects of cognition. The components of empathy in the context of psychological research have been determined. Empathy as a factor in regulating the effectiveness of pedagogical communication has been studied. Empathy acts as a tool for establishing emotional contact. The procedural aspect of empathy in the context of the teacher's activity is considered. The content of artistic empathy is considered as a process of sympathising with artistic phenomena. Artistic empathy is defined as the basis for comprehending an artistic image. In the context of Music teachers’ activities, artistic empathy is defined as a complex personal and professional entity that allows us to identify the emotional state of a person or the emotional portrait of a musical work. The artistic empathy causes a reaction of sympathy, which optimises artistic and pedagogical communication. It is noted that the vocal training of future Music teachers creates a unique platform for the development of artistic empathy. Two vectors of the artistic empathy within the activities of Music Arts teachers have been considered: empathic penetration into the emotional world of a musical work, and empathic penetration into the emotional world of students in the process of artistic and pedagogical communication. A list of effective methods of the vocal training which is aimed at developing art empathy of the future teachers of Musical Arts has been offered: a method of reflexive adjustment, a method of empathic supervision, a method of emotional collections, a method of vocal improvisation.
Modular Reduction

Modular reduction is the computation of x mod m. Such computation is implicit in all modular-arithmetic operations, because it is necessary to ensure that results are within range, even though some intermediate value will most likely might not be. Barrett reduction Reduction Barrett Montgomery reduction Reduction Montgomery The first two sections of the chapter cover two well-known methods for modular reduction that are commonly used in cryptography arithmetic: Montgomery reduction and Barrett reduction . The third section—a short one–is on a method that might be suitable in certain case when an “isolated” reduction—i.e., not a sequence of reductions—is required. And the last section—another short one—is on reduction with respect to certain specific moduli, such as those that are significant because of their inclusion in some cryptography standards; the moduli all have forms that facilitate efficient reduction.
Note linguistiche sul ciclo di Nane Oca

The essay focuses on the language of Nane Oca’s cycle of novels, studied in its evolution from the first book to the very recent Lato oscuro . Mainly, three aspects are taken into account: 1) literary entries; 2) syntactic patterns; 3) lexical compounds. The analysis of each aspect tries to show how in the language of Nane Oca forms derived from the literary tradition (used to give a characteristic epic tone to the work) are originally combined with completely new solutions. As the literary component decreases, the presence of the dialect, which Scabia uses more openly, becomes stronger over time.
Smart Learning With Seamless Activities

The new vision for self-directed, motivated, adaptive, resource-enriched, and technology-embedded smart higher education has promoted smart learning with mobile-assisted seamless activities to learn across time and locations, individual and collective, from one scenario to another including formal and informal learning through smart mobile devices. Methodologically, the collective and ubiquitous leaning for student-centered learning is examined qualitatively with empirical data of how smart education are enhancing students' individual and collaborative learning, rather than focusing on using only technological devices. Theoretically, the analysis is based on the concept of mobile-assisted seamless learning activities, MSL, grounded in six dimensions of actual learning. The findings display that smart learning with mobile-assisted seamless mediated learning activities improves with the design of before-, in-, and after-class stages with a focus on contextual, adapted, and self-directed seamless learning activities to promote the students' capabilities to learn, collaborate, and critically solve problems in different situations and contexts.
Video Text Detection

In Chap. 3, for a given video, text frames are detected based on edge features and mutual nearest neighbor symmetry. This chapter deals with the text detection in text frames by introducing cognitive science-based approaches. For text detection, Delaunay triangulation [1] and histogram-oriented moments [2] approaches are explored.
Readability

We can increase the accessibility of scientific writing to L2 readers by improving readability of the texts. Existing concepts and guidelines provide some help with this, but fall short when applied to communicating science topics to L2 readers. This chapter discusses readability, as well as other attempts at making English accessible to global readers.
A Trend Analysis of Mobile Learning

The aim of this study is to determine current tendencies regarding mobile learning in published research between 2010 and 2015. In this study, 221 articles collected from the Web of Science Core Collection database with SSCI index were examined by using the content analysis technique. In the analyses, eight criteria were used, namely; research technique, sampling size, sampling level, learning domain, topical domain, data collecting tool, data analysis method and mobile application development approach. The results suggest that the main tendencies under these categories were experimental method; sample sizes of 31-100 people; higher education students; humanities and social sciences domain; learner outcomes topical domain; mixed data collecting tools; mixed analysis methods; and native mobile application development approach.
Efficient Fault Tolerance on Cloud Environments

With mission critical web applications and resources being hosted on cloud environments, and cloud services growing fast, the need for having greater level of service assurance regarding fault tolerance for availability and reliability has increased. The high priority now is ensuring a fault tolerant environment that can keep the systems up and running. To minimize the impact of downtime or accessibility failure due to systems, network devices or hardware, the expectations are that such failures need to be anticipated and handled proactively in fast, intelligent way. This article discusses the fault tolerance system for cloud computing environments, analyzes whether this is effective for Cloud environments.
Pandemonium

This chapter explores the impact of the COVID-19 pandemic and how California UC Links programs adapted and transformed undergraduate and K-12 program activities in response to the deepening COVID-19 crisis. The authors review challenges faced by programs and how they leveraged and strengthened existing partnerships to engage K-12 participants. Emerging responses to the ever-changing context of the pandemic are also explored, and the authors focus on re-envisioning the UC Links undergraduate course and school- and community-based activities. Innovative activities that UC Links programs and their partners designed and piloted in the Spring and Summer quarters of 2020 are explored, including distributing resources, creating mediated hands-on activities, producing mediated virtual activities, and bridging after- and in-school activities. Learnings from virtual summer programs and Fall 2020 collaborative activities are summarized as context for both understanding and co-constructing future activities developed in response to shelter-in-place conditions.
The Rise of the Virtual Human

Virtual Humans are here to stay. From the voice in your satNav to Apple's “Siri”, we are accustomed to engaging in some level of conversation with our technology, and it is rapidly becoming apparent that natural language interfaces have potential in a wide range of applications. Whilst audio-only communication has its place, most natural conversations take place face to face, and believable embodiment of virtual humans is the necessary next step for them to be fully integrated into our lives. Much progress has been made in the creation of relatable characters for film, but real-time facial animation presents a unique set of design challenges. This chapter examines the role of the virtual human, its history, and approaches to design and creation. It looks at ways in which they can be brought to life, interacting, assisting and learning. It concludes with a view into popular culture and perceptions of the future, where fact and fiction meet.
Diaphragm valve is enhanced to meet regulations for drinking water

German valves and pumps manufacturer KSB SE &amp; Co KGaA reports that its subsidiary SISTO Armaturen SA is launching its SISTO-16TWA valve type series for drinking water applications with new materials for wetted components.
One-Group t-Test for the Mean

This chapter explains how to use one of the most popular and most helpful statistical tests in environmental science research: the one-group t-test for the mean. This test compares the mean of your data set against the hypothesized population mean for your data to determine if the difference between these two values is “large enough” to be considered a “significant difference.” The formula is presented, explained, and a practical example is given using your calculator. Seven steps are outlined for using this formula to test specific hypotheses about your data. These steps build on the hypothesis-testing steps you learned in Chap. 3 of this book. You will also learn how to find the absolute value of a number, how to find the critical value of t in the table given in Appendix E of this book, and how to state both the result and conclusion of your statistical test. In addition, the difference between the 95% confidence interval about the mean (Chap. 3) and the one-group t-test is explained. Three practice problems are given at the end of the chapter to test your Excel skills, and the answers to these problems appear in Appendix A of this book. An additional practice problem is presented in the Practice Test given in Appendix B along with its answer in Appendix C of this book.
Bilingual reference production

We investigate reference production in bilingual children. Based on Kibrik (2011), we analyze the production of referring expressions in discourse in terms of activation of a referent. We propose a novel approach, which calculates activation by taking into account different activation-lending factors and their respective weight. This allows us to compare the activation encoded by referring expressions across languages and groups of speakers, and to run correlational analyses with the speakers’ cognitive profiles. In particular, the study addresses the correlation between activation and lexical processing among bilinguals, based on the distribution of referring expressions in narratives by 20 German-Greek bilingual children, compared to their monolingual peers. We found that bilingual pronouns correspond to a lower activation than monolingual ones. Speed of lexical retrieval is a predictor of the bilingual performance. Our model of analysis accounts for how reference production varies across individuals and which cognitive mechanisms underlie this variation.
Practical data analysis of PAD classroom in College English Intensive Reading Teaching

PAD classroom model is a classroom teaching model proposed and proved effective in practice in recent years. It is very suitable for a variety of courses. There are some problems in the current college English intensive reading course, resulting in the poor results of English teaching. English teachers need to seek new classroom teaching methods to stimulate classroom vitality and improve teaching quality. PAD classroom model is a good innovative way of English intensive reading course. This paper discusses the benefits of PAD classroom to college English teaching, selects 50 freshmen to experiment with traditional English teaching methods and PAD teaching methods, analyzes the changes brought by PAD teaching mode to students' English performance from the result data, and explores the changes that PAD can bring to today's teaching system. From the experimental data, PAD classroom can improve students' academic performance by about 10%, which is a very effective teaching method.
Investigation Management

Accident investigations increase the knowledge of the investigator in a way that is generalisable beyond the particular circumstances investigated. They drive improvements in safety. Incidents are often a rehearsal for an accident, and their investigation provides statistical information about the frequency and severity of operational events. Incident reports may also identify new hazards. This chapter considers the nature of, and process for, an incident or accident investigation for a Data-Centric System. It identifies how evidence management supports investigation management.
A Pet Detection System Based on YOLOv4

With the increasing development of artificial intelligence, it brings an opportunity to use advanced intelligent technology to solve real pet problems. And it has important practical significance to solve a series of issues such as pet photography and public transportation pet detection in a faster and more efficient way. By studying the application of deep convolutional neural networks in pet detection tasks, a complete system for pet detection is designed. The entire system uses the YOLOv4 algorithm as the basic algorithm for object detection. After completing the process of data collection, data expansion and data labeling, completing the algorithm training and optimization process, quantitatively analyzing the final system detection effect and testing the robustness and generalization of the system, a system for cat and dog detection with a mean average precision of 95.71% is finally obtained. Experiments show that the designed detection system can use the deep convolutional neural network to automatically, quickly and accurately detect pets.
Memetic Algorithms

Memetic algorithms enable robots to engage in memetic learning, – that is, the transmission of cultural ideas or symbols from one robot mind to another, enabling robots to learn social values by performing intelligent imitation. This chapter introduces a formal definition of memetic algorithms and further identifies a minimum set of functional requirements a robot must meet in order to process memetic algorithms and perform memetic learning. Additionally, this chapter formalizes how robot memes can be manipulated and communicated in problem solving based on the novel concept of an “intelligent meme.” A disaster relief scenario involving robots is used as an example to ground the formalisms developed in this chapter.
Vulnerable Learners’ Experiences on Drug Abuse in Zimbabwean Rural Schools: A Literature Review Perspective

: In Zimbabwean rural schools, drug abuse is observed to be on the increase trend. It is in this context that this paper delved into experiences that are encountered by vulnerable learners abusing drug in rural schools. Accordingly, it targeted at how this social phobic has become entrenched in learners’ way of being and the plausible antidotes to this drawback. In this regard, a framework derived from social constructionist and symbolic interactionist standpoints provided the lens through which the researchers perceived the issue under investigation. The researchers used literature review in the generation and analysis of learners’ lived experiences with regards to the issue under study from different sources. The researchers used the narration of information from commissioned reports, newspaper articles and empirical findings. From consulted sources, the researchers noted that there is widespread drug abuse in most rural schools through the influence of the institution linked dynamics, age issues, life stress, peer group pressure, obtainability of ready money and ease of access to drugs. With respect to these findings, the researchers concluded that drug abuse by learners in rural schools in Zimbabwe was from literature perspective mostly due to multi-pronged influences. Hence the researchers recommended that key interested parties such as Government, Non- Governmental Organizations, parents, teachers and policymakers should consistently implement and monitor strategies such as peer counselling to mitigate the drug abuse among rural learners.
Gray Adversarial Attack Algorithm based on Multi-Scale Grid Search

Adversarial attack is an important research direction of neural network security, and the black-box attack in the unknown model is an important application scenario of adversarial attack. The adversarial samples generated by existing black-box attack algorithms often have drastic hue changes, are easy to be perceived by human eyes, and the algorithm computational efficiency is generally low. Therefore, this paper proposes a multi-scale grid search for the image gray attack strategy, performing perturbations of different intensity on image areas of different scales, and then makes the generated sample hue change more natural. Experiments show that the performance of the method is better than the baseline algorithm, and greatly improves the attack efficiency, increasing the neural network query number over 50% comparing with the fastest baseline algorithm.
Design and Implementation of Natural Scene Text Recognition System Based on Deep Learning

With the popularization and rapid development of information technology such as modern multimedia and mobile Internet, people have more and more ways to obtain natural landscape images. How to collect and extract necessary information from rich images becomes more and more important. With the current popularization and development of technologies such as artificial intelligence and deep machine learning, the application requirements for effectively obtaining text resources are also expanding rapidly. This paper aims to study the design and implementation of a natural scene text recognition system based on deep learning. Based on the analysis of system functional requirements, system non-functional requirements and text detection methods, each functional module of the system is designed in detail, and finally in SVT. The performance of the algorithm in this article is analyzed on the public data set, and the test results are compared with the existing algorithms. The test results show that the method and recognition results used in this paper are significantly higher than other methods, and the text recognition results have reached a very high accuracy.
The application of Korean language and slang corpus based on big data technology in teaching

In the context of informatization and big data, corpora based on foreign language teaching and application are developing rapidly. This paper introduces and analyzes the construction of the teaching corpus in the context of big data, and uses big data application technology to construct the Korean colloquial corpus, and studies how to use the constructed corpus to provide teaching methods for the teaching and research of Korean colloquialism. Provides a new way of thinking for Korean language educators.
Cloud Migration

Having dealt with security it is now time to introduce a decision-related concept: cloud migration. The objective of this chapter is to introduce the fundamentals of cloud migration. By the end of the chapter the reader should understand the migration process, different migration strategies, and the taxonomy of applications, such as cloud-enabled, cloud-optimized, and cloud-native applications, according to the migration strategies.
Improving Access to Higher Education With UDL and Switch Access Technology

This chapter presents an in-depth case study of the creative use of a mobile technology system by a diverse learner who is also one of the authors of the chapter. This learner is blind, has significant fine and gross motor impairment, and speaks in a whisper that is not understood by today's speech recognition technology. The learner's inclusion as an author is, in itself, a testimony to the empowerment the mobile communication system has brought to his life, which in turn has allowed him to be an active participant in the design of a learning environment based on Universal Design for Learning (UDL) principles. More specifically, the chapter details the ongoing development of a system for making math content more accessible not only to the individual learner who is the focus of the case study, but to other learners who struggle with higher level math content in higher education.