Reviewerly/exHarmony huggingface dataset:
Student Characteristics

Higher Education AbstractsVolume 56, Issue 4 p. 377-377 STUDENT CHARACTERISTICS Student Characteristics First published: 08 January 2022 https://doi.org/10.1111/hea.41_12178Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume56, Issue4October 2021Pages 377-377 RelatedInformation
Small Quantum-safe Design Approach for Long-term Safety in Cloud Environments

Cloud services will have a high priority in IT and parts of digitisation in the following years. Furthermore, other areas such as medicine, agriculture, Industry 4.0 use cloud services for collecting, processing, and primarily storing data and combine this with smart IoT devices. In addition to high availability and ensuring efficiency without downtime, data security is the most important in those cloud environments. Therefore, enabling traffic encryption between sensors and cloud computing to achieve the authentication and integrity of saved data is expected. And established cryptographic algorithms, like the symmetric scheme or the asymmetric Public-Key technique Rivest-Shamir-Adleman (RSA), guaranteed the security of the data in the pre-quantum computer age. However, some cryptographic algorithms are vulnerable because of emerging quantum computing and are defined as potentially broken. It is, therefore, desirable to explore the use of post-quantum cryptography to ensure data security. This paper shows an approach to keep long-term data quantum-safe with a block cipher suite.
The Transfer Phenomena of Air Pollutants Emitted from Power Station and Generators in Nasiriyah City and the Effect of Meteorological Parameters on its Dispersion by Using Fixed Box Model

Abstract The study aims to use the fixed box model to calculate the spread of pollutants (CO2, SO2, NOX, particulate) resulting from the burning of fuel used to produce electrical energy in the Nasiriyah city and to know the way they spread in the city through being affected by the wind speed and compare the results calculated from the model with the results measured by the lancom4 device. The results showed that the main pollutants for the air in Nasiriyah was emitted from burning the fuel used for the production of electric power, and the results showed that the concentration of pollutants (CO2, SO2, NOX) was much higher inside the city when compared with the upstream direction of the winds due to its increase with the movement of winds and its entry into the city. Through the application of the fixed box model and when comparing the calculated results through the model with the results measured by the lancom4 device, the error rate was (4 %, 2%, 2%, 5%) for pollutants (CO2, SO2, NOX, particulate) respectively, it was also observed that the highest emission rate of pollutants was result from using heavy fuel (fuel oil) and the lowest emission was from light oil (Dry gas). We noted the spread of pollutants and dilution in the atmosphere increases with the increase in wind speed, excluding for particles mater.
String Theory

SummaryIn the last chapter, we described the history of the universe starting at 10−10 s after the Big Bang. In order to physically describe the real starting point, the Big Bang, we still have to get a grip on these first 10−10 s! As explained above, there is so far no established theory for this very early phase in the universe. We could boldly assume that the same physical laws continue to hold in the early phase. But it is not quite that simple, because there is a fundamental problem with this argument: the established physical theories fail in the very early universe and in particular cannot provide a consistent description of the Big Bang. Let us first briefly explain this problem.
Using of R parameter in a Massey-Omura protocol on elliptic curves

Modern cryptography is based both on the classical areas of arithmetic and algebra, such as modular arithmetic, finite field theory, and on the most modern sections, including the theory and applications of elliptic curves, and anti-jamming coding. However, the development of computer technology leads to an increase in the stability of cryptosystems, that is, the length of keys. In this article, a method for increasing stability using parametric algebra without increasing the key length is illustrated by the example of the Messi-Omura algorithm based on an elliptic curve.
Beyond $L_{p}$ Norms: Delving Deeper into Robustness to Physical Image Transformations

With the increasing adoption of deep learning in computer vision-based applications, it becomes critical to achieve robustness to real-world image transformations, such as geometric, photometric, and weather changes, even in the presence of an adversary. However, earlier work has focused on only a few transformations, such as image translation, rotation, or coloring. We close this gap by analyzing and improving robustness against twenty-four different physical transformations. First, we demonstrate that adversarial attacks based on each physical transformation significantly reduce the accuracy of deep neural networks. Next, we achieve robustness against these attacks based on adversarial training, where we show that single-step data augmentation significantly improves robustness against these attacks. We also demonstrate the generalization of robustness to these types of attacks, where robustness achieved against one attack also generalizes to some other attack vectors. Finally, we show that using an ensemble-based robust training approach, robustness against multiple attacks can be achieved simultaneously by a single network. In particular, our proposed method improves the aggregate robustness, against twenty-four different attacks, from 21.4&#x0025; to 50.0&#x0025; on the ImageNet dataset.
Implementation of Emerging Technologies in Pandemic Situations: Contact Tracing vs. Privacy in Canada

The COVID-19 pandemic required unprecedented efforts to address the emergency situation in public health in all countries around the world. Governments turned their hopes to technology and its potential to offer reliable solutions in controlling the virus. Contact-tracing apps were introduced to assist health officials in tracking down exposures after infected individuals were identified. Despite the benefits, the design of tracking apps was accompanied by many privacy concerns. The objective of this chapter is to survey what strategies of digital contact tracing have been used to control the spread of COVID-19, what are some of the privacy discussions that surround the choices for those strategies and whether those choices are embedded in the legal requirements of privacy protection. The chapter argues that privacy should be a central feature of the conversations surrounding the implementation of contact-tracing technology—every decision-making should always take place within the legal boundaries of privacy protection. The Canadian case serves as a good example because the public policy makers did not respond to the health crisis by compromising privacy rights for the benefit of protecting public health, even if the situation could have favored such decision. The chapter offers an exploratory review of current measures for COVID-19 contact tracing employed in Canada with the aim of analyzing how privacy concerns shaped the Canadian decision-making in adopting particular measures. The chapter concludes that it is in under situations of crisis when a country’s democracy is put to a test—policy makers will fail the test if they aim to achieve legitimate goals through controversial means, especially if those means weaken fundamental human rights. Undermining privacy in the name of protecting public health could have dangerous implications for future public policy making. It could open the door to the abuse of government powers in times of crisis, and once the crisis is over the changes to our privacy rights could become permanent.
THE IMPORTANCE OF THE EMAIL LANGUAGE IN THE MEDIA DISCOURSE

In the modern world of the Internet, at a time when man-made technology is opening the way to all areas of our lives, it is not surprising that a new field of linguistics - the rapid development of Internet linguistics. The Internet language is constantly on the move; it is observed and operates in different types of communication. In the 21st century, the study of the Internet language from a systemic and structural point of view is observed. At present, linguists are focusing on the analysis of different expressions of the new media discourse in the various virtual worlds observed in the communication process. The formation of an anthropocentric scientific paradigm in linguistics leads to the intensification of linguistic trends related to communication problems.Internet linguistics studies the new language style and form created by the Internet. Internet linguistics can be developed in four perspectives: sociolinguistics, pedagogy, stylistics and applied linguistics. When it comes to communication, it is impossible not to remember the term discourse. Electronic discourse and computer-mediated discourse also provide a basis for the interactivity of computer users to keep social communication active.
Cyber incidents connected to financial institutions

The main topic of the paper is the accelerated digital transformation of financial institutions, which, in addition to the advantages, also brings an increased risk of cyber incidents. Cyber incidents can cause systemic damage and, therefore, building a good cyber security system goes beyond individual financial institutions. Based on a comparative analysis of the trend of public awareness about cyber-attacks, the conclusion of this paper is that, unlike developed countries, public awareness in Serbia has no continuous but occasional growth caused by individual events related to cyber-attacks. Designing a national campaign to raise public awareness about cyber security, as well as training and retaining highly qualified personnel, are two recommendations that are self-imposed after the observation and analysis of information on cyber incidents in Serbia.
Video Risk Detection and Localization using Bidirectional LSTM Autoencoder and Faster R-CNN

This work proposes a new unsupervised learning approach to detect and locate the risks "abnormal event" in video scenes using Faster R-CNN and Bidirectional LSTM autoencoder.The approach proposed in this work is carried out in two steps: In the first step, we used a bidirectional LSTM autoencoder to detect the frames containing risks.In the second step, for each frame containing risks, we first used Faster R-CNN to extract all the objects containing in the scene and then for each object detected we check whether it represents a risk or not.In other words, in testing phase, the frames with events deviated from normal features learned in training phase are detected as risk.To locate objects representing risk, only the objects detected by Fast R-CNN deviated from normal feature are classified as risk.Experimental results demonstrate that the proposed method can reliably detect and locate the object representing risk in video sequences.
The Political Economy of Cluster Development Initiatives in Tanzania: Institutional Framework and Emerging Challenges

Purpose: This article aimed to examine the political economy of Cluster Development Initiatives on the institutional framework for CDIs in Tanzania context basing on the contractual arrangements of key actors, policy strategies, collaboration and institutional challenges under the guidance of the new institutional economic theory. Design/Methodology/Approach: The research used a cross-sectional design with a mixed approach through simple random sampling techniques to obtain 150 SMEs owners in the cluster of the regions of Singida, Mbeya and Morogoro. Interview, observation, survey and review of documents were used to get the required information. The quantitative and qualitative information were analyzed by descriptive statistics, ANOVA as well as analysis of the themes consecutively. Findings: It was found that the contractual arrangements of key actors were based on funding, training, technical expertise and linking clusters to various stakeholders. The difference in collaboration was not significant as well as significant with P value = 0.097and P value = 0.000 across regions and clusters respectively. Low government commitment, inadequate funding and low collaboration among cluster members were the major institutional challenges as there was inadequate political and institutional support to realize the intended objectives. Research limitation: The study focused on SMEs in clusters in the regions of Singida, Mbeya and Morogoro in Tanzania where CDIs were largely implemented. Practical Implication: The knowledge advanced by this study will help CDIs implementers and other stakeholders on the nature of political and institutional support, the collaboration of key stakeholders and the major institutional challenges. Social Implication: The knowledge advanced by this study will help policymakers to adjust SME development policies to provide special attention to CDIs issues as well as strengthen project capacity write up to attract funds. Originality/Value: The novelty of this study is on informing about the political economy of Cluster Development Initiatives particularly on the contractual arrangements of key actors, policy strategies, collaboration and institutional challenges under the guidance of the new institutional economic theory in Tanzania.
Maximal Sub-prevalent Co-location Patterns

In this chapter, we introduce star participation instances to measure the prevalence of co-location patterns such that spatially correlated instances which cannot form cliques will also be properly considered. Then we propose a new concept called sub-prevalent co-location patterns (SPCP) based on the star participation instances. Furthermore, two efficient algorithms—the prefix-tree-based algorithm (PTBA) and the partition-based algorithm (PBA)—are proposed to mine all the maximal sub-prevalent co-location patterns (MSPCPs) in a spatial data set.
Fully abstract models for effectful λ-calculi via category-theoretic logical relations

We present a construction which, under suitable assumptions, takes a model of Moggi’s computational λ-calculus with sum types, effect operations and primitives, and yields a model that is adequate and fully abstract. The construction, which uses the theory of fibrations, categorical glueing, ⊤⊤-lifting, and ⊤⊤-closure, takes inspiration from O’Hearn &amp; Riecke’s fully abstract model for PCF. Our construction can be applied in the category of sets and functions, as well as the category of diffeological spaces and smooth maps and the category of quasi-Borel spaces, which have been studied as semantics for differentiable and probabilistic programming.
A Novel Side-Information for Unsupervised Cluster Ensemble

Many clustering and cluster ensemble models have been proposed recently and have not addressed two concerns; when a single model is executed multiple times on a dataset, it predicts various labels for each data object; however, these various labels have a small correctness ratio due to the randomness in generating values in each implementation. Further, detecting which the correct label from these diverse answers is complicated, specifically when the unsupervised model works on a real-world application and needs to deliver a single correct label to the user. In this work considered these two issues by proposing a novel unsupervised constraints termed Inherited Constraints (IC) that behaves as semi-supervised constraints generation. Moreover, execute the IC needs a cluster model to utilize; thus, we proposed an unsupervised cluster ensemble model by integrating the Density Peaks cluster ensemble framework (DPE) and IC to improve the performance. This model is termed DPEIC. Further, we proposed a model termed Answer Settlements (AS) to detect a single correct label for each data object from the diverse answers obtained by DPEIC after utilized multiple times to consider the most duplicated labels as the correct ones. We compare DPEIC-AS with several state-of-the-arts to validate the strengths of this work. The experimental results indicate that DPEIC-AS outperforms the compared models at a different rate, ranging from 3% to 93%. Also, The AS assisted two state-of-the-arts methods to detect the correct labels with the highest possibilities from diverse answers.
TxT: Crossmodal End-to-End Learning with Transformers

Reasoning over multiple modalities, e.g. in Visual Question Answering (VQA), requires an alignment of semantic concepts across domains. Despite the widespread success of end-to-end learning, today’s multimodal pipelines by and large leverage pre-extracted, fixed features from object detectors, typically Faster R-CNN, as representations of the visual world. The obvious downside is that the visual representation is not specifically tuned to the multimodal task at hand. At the same time, while transformer-based object detectors have gained popularity, they have not been employed in today’s multimodal pipelines. We address both shortcomings with TxT, a transformer-based crossmodal pipeline that enables fine-tuning both language and visual components on the downstream task in a fully end-to-end manner. We overcome existing limitations of transformer-based detectors for multimodal reasoning regarding the integration of global context and their scalability. Our transformer-based multimodal model achieves considerable gains from end-to-end learning for multimodal question answering.
On Building a Vulnerability Dataset with Static Information from the Source Code

Software vulnerabilities are weaknesses in software systems that can have serious consequences when exploited. Examples of side effects include unauthorized authentication, data breaches, and financial losses. Due to the nature of the software industry, companies are increasingly pressured to deploy software as quickly as possible, leading to a large number of undetected software vulnerabilities. Static code analysis, with the support of Static Analysis Tools (SATs), can generate security alerts that highlight potential vulnerabilities in an application's source code. Software Metrics (SMs) have also been used to predict software vulnerabilities, usually with the support of Machine Learning (ML) classification algorithms. Several datasets are available to support the development of improved software vulnerability detection techniques. However, they suffer from the same issues: they are either outdated or use a single type of information. In this paper, we present a methodology for collecting software vulnerabilities from known vulnerability databases and enhancing them with static information (namely SAT alerts and SMs). The proposed methodology aims to define a mechanism capable of more easily updating the collected data.
Readable, Serious, Traditional: Investigating Scholarly Perceptions of the Visual Design and Reading Experiences of Academic Journals

Academic journals are not known for the quality of their visual designs or the reading experiences they provide, despite being fundamental to the dissemination of research and knowledge in most disciplines. Journals are produced by and for scholars and are considered currency within academic culture; however, little is known about how visual design affects a journal’s perceived prestige or reading experience. This paper discusses a survey conducted to investigate reader perceptions of academic journals across disciplines. We used quantitative and qualitative responses to understand reader practices and preferences as they pertain to format and visual design. Across disciplines, issues related to access, prestige, readability, and academic culture were said to influence reading experience. Survey respondents indicated a desire for improved reading experiences, especially on digital platforms. The article concludes with a discussion about how publishers and editors may confront these issues and consider the diverse needs of their readers.
Planning under Sustainable Processes

The article presents the models used in the planning of production with unstable technology. This issue is becoming increasingly important for universities in connection with the transition of the Ministry of Science and Higher Education to the new principle of planning a state order for specialists, when the admission figures in the state assignment turn into release figures. For successful work in these conditions, universities are forced to change their system of planning for the training of specialists. The considered models are a proven tool for determining the size of the contingent and the necessary resources, which must be launched into the educational process in order to fulfill the state order by a given deadline.
AN APPROACH TOWARD STANDARDIZATION OF EMR WITH EFFICIENT ACCESSIBILITY OF DATA ON DEMAND

Among the most often discussed topics in the healthcare industry are medical terminology standardization and the establishment of a centralized electronic medical record (EMR). There is a wide range of information in patient master records and treatment statistics records, as well as a dynamic data structure. Over time, the number of records has increased at a rapid rate, resulting in a large volume of data that necessitated the implementation of a structured data base management system. Even while data science and analytics have the potential to alleviate the problem of data management, the lack of confidence in cloud-based data storage may become a big issue in the future. For improved storage management, these records may be preserved, and they may be replicated over different clouds or maintained in a distributed way for increased security and reliability. Medical data generated by wearable medical devices or portable devices used by home care patients, on the other hand, may be connected to several cloud servers in order to improve accessibility and security. For data accessibility and security, the proposed system will build a generic medical record management system that will be deployed across various clouds. It will also design a Body Area Network (BAN) architecture that will be connected to a distributed cloud