ABSTRACT:
We describe the Data Protection and Privacy Relationships Model (DAPPREMO), which is based on high mathematics and the set theory, considering that the data protection and privacy regulation and Ethics principles in those domains belong to a set. DAPPREMO is a new and innovative solution to adopt a model in any data protection and privacy activities. We theorize that DAPPREMO is an innovative approach to have a broad overview of all the objects related to a specific case or more cases from a data protection and privacy perspective. DAPPREMO is the result of a multidisciplinary approach by combining the legal view based both on the existing laws on privacy and the protection of natural persons with regard to the processing of personal data and mathematics. We describe DAPPREMO as a solution for a multidisciplinary approach to address any data protection and privacy issue.

ABSTRACT:
The global pandemic and subsequent quarantine measures and restrictions have posed an array of challenges to the structure and procedure of education workflow. Foreign Languages Acquisition and Linguistic Education assessment are fundamentally interdisciplinary processes, informed by the nature of linguistic content and types of communicative and professional activities. Cross-sectorial factors of societal change, that provide the backdrop for an interdisciplinary skillset critical transformation, crucial for the COVID-19 emergency educational framework, are considered. The study is based on identification of various interdisciplinary competency principles, derivative of 21st century skills for university staff members and projected digital literacy requirements. It is determined how in the situation of the COVID-19 pandemic lockdown all elements of the Final Qualification Assessment at Borys Grinchenko Kyiv University, Ukraine, for European and Oriental Languages programs have been relegated to the digital, remote or hybrid format with the use of ICT tools and skills that comprise an interdisciplinary realm of Foreign Languages acquisition and assessment. Every step of the procedure adaptation to digital format required accelerated development of interdisciplinary skills of all participants and officials and cross-sectorial activities, otherwise not carried out through assessment of Foreign Languages programs.

ABSTRACT:
The effect of contact between cells on forming orientation of cells under the shear flow field has been investigated in vitro. To create a Couette type of the shear flow, the culture medium was sandwiched with a constant gap between parallel walls: a lower stationary culture disk, and an upper rotating disk. The wall shear stress (2 Pa) on the lower culture disk was controlled by the rotating speed of the upper disk. Myoblasts (C2C12: mouse myoblast cell line) were used in the test. After cultivation without flow for 24 hours for adhesion of cells on the lower plate, the constant wall shear stress was continuously applied on cells for 7 days in the incubator. The behavior of each cell was traced at the time-lapse images observed by an inverted phase contrast microscope placed in an incubator. The experimental results quantitatively show that increase of the contact region between cells affects forming perpendicular orientation of cells against the main flow direction.

ABSTRACT:
This study is a meta-cognitive discussion about whether non-English scientists know about the existence of computer tools – such as monolingual, bilingual and multilingual electronic dictionaries, CAT [Computer Assisted Translation] tools - and whether they know how to use them in order to communicate their inter-disciplinary research internationally. It also discusses what is at stake when concepts such as inter-scientificity (i.e. “bar”, with 17 different terms in Greek) and reverse inter-scientificity (i.e. “πρόγραμμα” [: program] with at least 6 different terms in English) emerge. Then the author of this study claims that only human mind/intelligence (nous) - with the aid artificial intelligence (computer –CAT tools) and through different mental/cognitive processes (noesis) can establish certain criteria in choosing appropriate terms and expressions, so that an inter-disciplinary research can be communicated properly and thus (international) scientific communication can be achieved effectively. Finally, the author of the present study proposes that Higher Education Institutions [HEIs] in North America (the USA and Canada) and Europe should get involved in educating and training both their large number of international students and staff administrative and academic), if a proper international inter-disciplinary communication is to be attained.

ABSTRACT:
Before 1970 both foreign language and mathematics were hard to learn because the two taught grammar before language. Then a turn took place in foreign language education allowing students to learn it through communication. Mathematics education never had a similar turn, so it is still hard for many. Therefore, this paper asks if it is possible to learn mathematics as communication. We see that three different kinds of mathematics are taught, pre-setcentric, setcentric and post-setcentric. And that the three grand theories disagree as to which to recommend. Being inspired by the fact that children communicate about the physical fact Many with two-dimensional box- and bundle-numbers with units, a curriculum is designed where trigonometry is rooted in a mutual recounting of the three sides in a box halved by its diagonal. So, the answer is: Yes, core mathematics can be learned as communication about boxes since it is directly connected to counting and recounting Many in boxes and bundles.

ABSTRACT:
The term Internet of Things (IoT) refers to a broad class of devices used by business entities as well as consumers to provide or consume a broad array of services. All these devices share their need to connect to the internet to deliver their native functionality. This connection requirement exposes the devices to the cybersecurity threats found on the internet. Existing literature on IoT cybersecurity solution models has shown that different technologies, such as communication technologies, mobile-app based authorization framework, graph-theoretic approach or blockchain technologies, have been majorly proposed to solve IoT security issues. However, these studies only focus on some specific IoT security issues like data theft or security issues on some specific layer across the whole IoT architecture. Therefore, there is a lack of systematic framework to solve IoT cybersecurity issues. This paper presents a framework for assessing such risks. In the qualitative analysis results, the device threats seem more severe than data confidentiality and privacy issues. This surprising finding highlights the significances of security taxonomy because both issues are based on different technical requirements. Our study has important managerial and practical implications for users, managers, and policymakers.

ABSTRACT:
The global situation experienced due to the advance of the covid-19 pandemic and the requirements of social isolation has affected multiple sectors, especially the education sector. In particular, teachers, support workers and university students have taken on a great challenge by recognizing that conditions have changed but learning is not delayed. Therefore, they have seen the need to implement virtual education strategies in a short period of time. For the universities in which face-to-face was the daily learning model, which do not have the necessary infrastructure for the new virtual modality, it has been a threat to the environment as they were forced, under these conditions, to migrate from face-to-face education to non-attendance. face-to-face, emergent way.

That is why this study emphasizes the adverse effects of the social emergency caused by COVID-19 in the university teaching work environment, the appearance of stress and the need for institutions to adopt measures to improve their situation in terms of technology organization, methods and techniques and improve their digital skills in line with emerging global trends and realities, to avoid negative consequences on the mental health of their teachers and students.

ABSTRACT:
This paper focuses on changes in the Media-Political Communications of the Muslim Brotherhood while in power in Egypt in 2012 and 2013. The MB or al-Ikhwan al-Muslimun is regarded as the mother of Islamist movements in the Middle East. During their period in power, the group established its first TV channel Misr25 and launched a daily newspaper al-Hurria wa al- 'Adala. No other studies have researched the communications of the Brotherhood or their approach to media while they were in power.

The Brotherhood’s communications during this period were little more than themes and trends that were communicated from the top down by the group’s leadership to their media outlets, which lacked sufficient independence to do their work based on editorial values alone. This study identifies these themes, analyses them, and places them within the wider context of the literature in historical and regional contexts.

This paper concludes that the Brotherhood’s main aim was to achieve a constitution with an Islamic background regardless of hostility and criticism. The study also shows that the Brotherhood moved towards antagonist discourses as the opposition rallied against them, and underlines the troubled relationship between the Brotherhood and the main actors in Egyptian society, which were the army, the Christians and the secular opposition. The paper uniquely answers questions related to the Brotherhood’s rule in Egypt in 2012 and 2013 through the analysis of its media.

ABSTRACT:
The instructional delivery methods in many Ghanaian tertiary institutions are characterized by rigid curricula with little or no classroom discussions and interaction. These practices restrict creativity and transformation as students are separated from inquiry and only perform the role of listening, memorizing, and repeating the thoughts and ideas teachers narrate. Students lack exposure to learning environments that are conducive to cultivate critical thinking skills and develop critical consciousness. This qualitative case study explored how problem-posing education informs the instructional delivery methods in a Ghanaian university. The study focused on problem-posing education, a principle of Paulo Freire’s critical pedagogy as the framework for the study. The study purposefully selected 11 participants (two faculty members, eight students, and one administrative staff) who provided substantial data and deeper meaning and understanding of the phenomenon. The data revealed that problem-posing education informs the institution’s instructional delivery methods through problem-based curricula content, entrepreneurial skill development, and feedback/partnership opportunities. The study’s findings indicate that problem-posing education advocates cognition and transformative learning.

ABSTRACT:
Social inequality has become a challenging social phenomenon in many advanced countries. Individuals are affected by social divisions of race, gender, economic, cultural, and political structures. Among these social divisions, income and power inequality have become the major political preoccupation in most developed countries. In the United States, income disparity between the upper and middle classes has been increasing for several decades. While the top 1% earners who contributed to 10% of the U.S. national income in 1980 increased to 20% in 2016, the bottom 50% earners who contributed to 20% of national income in 1980 decreased to 13% in 2016. There have been several interpretations of this phenomenon but from a globalization point of view. This study, therefore, explores the phenomenon of economic and power inequality from a globalization standpoint. Using intersectionality as the theoretical framework, this paper explores how various social constructs intersect in a globalized economy to create income and power disparities. The author adopts a systematic literature review approach to identify gaps, contradictions, inconsistencies, interpretations, and connections in the literature relative to the phenomenon being explored. The findings will add to the scholarly literature on socioeconomic inequality and provide meaningful recommendations to improve U.S. social policies.

ABSTRACT:
Image classification is widely used in many fields. Traditional metric learning based classification methods always maximize between-class distances and minimize within-class distances based on features calculated from each individual. Different from traditional methods, this paper takes each class as a distribution and try to maximize the distances among different distributions using information geometry. In order to minimize the distance among individuals within a class, the paper assumes that each class follows a joint Gaussian distribution and takes an exploratory study on the relation between a within-class distance and the determinant of the covariance matrix of the distribution. It is found that under some assumptions, the average within-class distance among the same class is proportional to the standard deviation (for a random variable) or the product of standard deviations of each feature (for a random vector). As a result, the standard deviation (for a random variable) or the determinant of the covariance matrix (for a random vector) is used to substitute the within-class distance in the metric learning. The proposed method thereinafter saves a lot of computational cost. The method is then applied to person re-identification, which is a very important application in a 5G time, such as smart city. To our surprise, the proposed method is very competitive compared with many state-of-the-art methods while saving the computational cost in the learning stage. Experimental results demonstrate the effectiveness of the proposed method.

ABSTRACT:
Deep Learning (DP) models have been successfully applied to detect and predict failures in rotating machines. However, these models are often based on the supervised learning paradigm and require annotated data with operational status labels (e.g. normal or failure). Furthermore, machine measurement data is not commonly labeled by industry because of the manual and specialized effort that they require. In situations where labels are nonexistent or cannot be developed, unsupervised machine learning has been successfully applied for pattern recognition in large and multivariate datasets. Thus, instead of experts labeling a large amount of structured and/or non-structured data instances (also referred to as Big Data), unsupervised machine learning allows the annotation of the dataset from the few underlying interesting patterns detected. Therefore, we evaluate the performance of six unsupervised learning algorithms for the identification of anomalous patterns from a turbogenerator installed and operating in an oil and gas platform. The algorithms were C-AMDATS, Luminol Bitmap, SAX-REPEAT, k-NN, Bootstrap, and Robust Random Cut Forest. The evaluation performance was quantitatively calculated with seven classification metrics. The C-AMDATS algorithm was able to effectively and better detect the anomalous patterns, and it presented an accuracy of 99%, which leverages the further development of supervised DL models.