Reviewerly/exHarmony huggingface dataset:
Cybercrime and Cybercriminals

The rising expansion and diversification in the cybercrime arena have become difficult obstacles in order both to understand the extent of embedded risks and to define efficient policies of prevention for corporations, institutions, and agencies. The present study represents a comprehensive review of the origin, typologies, and developments of cybercrime and hacker subculture. This chapter confronts the issues by describing and discussing different criteria of classification in the field and by providing a broad list of definitions and an analysis of the cybercrime practices. A conceptual taxonomy of cybercrime is described as well. Common categories include the digital device is the target to commit the crime, the digital device is used as a tool to perpetrate the felony, or a digital device is an incidental condition to the execution of a crime. The authors complete their study by analyzing lessons learned and future actions that can be undertaken to tackle cybercrime and harden cybersecurity at all levels.
Improving the Mechanisms for Coordination and System Management in Interaction between Government Agencies and Educational Institutions of Higher Education in relation to Activities aimed at Attracting Foreign Citizens

The authors studied a number of projects and concepts aimed at increasing interest in the Russian education system among foreign students, as well as the functions of state structures involved in their implementation. Analyzing existing programs, the authors pay special attention to the activities of Rossotrudnichestvo. In conclusion, a number of measures are proposed aimed at developing the coordination of the work of state structures and educational institutions to attract foreign students. In the context of globalization and the active introduction of digital technologies in all spheres of society, the institution of cooperation between educational institutions of higher education and state authorities, specialized state organizations in the field of attracting foreign citizens to study at Russian universities also depends on the features of remote work and digitalization processes. The paper analyzes the main directions of the use of individual digital technologies in these respects. The main directions for increasing the presence of Russian educational organizations in the global Internet space and increasing the effectiveness of marketing digital strategies are considered.
Cyber Security Education in the Fourth Industrial Revolution

It is critical that cyber education curriculum considers the growing cyber technologies and which aspects of these technologies need to be aligned with the fourth industrial revolution. This chapter seeks to present a comprehensive analysis of the current level of cyber security education in South Africa. It will also track the current trends of cyber security education in the country as well as examining any challenges being experienced including any knowledge gaps. In the end, the chapter proposes recommendations for consideration in strengthening cybersecurity education in the country in to achieve advanced cyber security responses, capable of mitigating any cyber security threats. Offering quality cyber security education is important in preparing the next generation cyber security practitioners, who are highly competent and capable of developing innovative solutions in response to the growing global demand of cyber technologies. The chapter ends by proposing specific strategies that can guide towards this ideal in the context of the fourth industrial revolution.
Action Recognition

Appearance and pose of human actions vary significantly in different views, making multiview action recognition a very challenging task. To address this problem, it is crucial to learn view-invariant features from multiview action data that are robust to view variations. In this chapter, we first describe an approach by using deep learning networks to learn view-specific and view-shared features. The former captures unique dynamics in each view, and the latter encodes common patterns across views. We describe a sample-affinity matrix (SAM) to accurately balance information transfer within the samples of multiple views, for the purpose of limiting information transfer across samples. SAM enables us to learn more informative shared features that are robust to view variations. Furthermore, we encourage incoherence between the two types of features in order to decrease information redundancy and increase discriminability in them. The discriminative power of the learned features is further enhanced by encouraging features in the same categories to be geometrically closer. Robust view-invariant features are finally learned by stacking several layers of features. This approach is evaluated on two multiview datasets, and shows superior performance over state-of-the-art approaches. This chapter further introduces a hybrid convolutional-recursive neural network (HCRNN) to learn compositional features for action recognition from depth cameras. HCRNN captures rich motion, structure and context information, including local adjacent body parts as well as long-range body parts. HCRNN extracts robust features by stacking two layers, the 3D convolutional neural network (3D-CNN) and the 3D recursive neural network (3D-RNN). We use 3D-CNN to capture motion and structure information in local neighborhoods, and use 3D-RNN to compose high-order features for action recognition. Multiple 3D-RNNs are employed to improve the discriminability and robustness of the learned features. We organize the two components as a deep model, and train HCRNN in an unsupervised fashion without network tuning. Results on two RGB-D action datasets show that our method achieves state-of-the-art performance.
Copyright Distinctions in Educational Technology

Copyright law is the most recognizable form of intellectual property in the world and perhaps the most misunderstood in educational technology. This is not surprising due to the current climate of uncertainty and financial austerity in higher education. Universities in the United Kingdom in particular are facing significant challenges. Brexit brings uncertainty for treatment of European students in the UK for research collaborations with Europe and for British partnerships across Europe.
Evaluation

Evaluation is the process of placing value or worth on student performance and is based upon data from student assessment. Teachers evaluate whenever they assign grades to students. Because grades carry with them certain connotations, some teachers recommend that letter grades be replaced with other types of measurements or descriptive narratives. These replacement evaluative systems also have their difficulties. In the end, there is no perfect way to assign grades, but a solid foundation in the meaning of grades can help teachers to develop a system that is effective for their own instructional and assessment styles.
Video Captioning Via Two-stage Attention Model and Generative Adversarial Network

Video captioning plays an important role in video retrieval and personalized recommendations with the rapid rise of short videos. In the process of video captioning, the accuracy of caption generation may be affected by the existence of irrelevant visual content. To address this problem, a two-stage attention model is proposed, including object-level attention and frame-level attention. The object-level attention first focuses on the salient objects in each frame and then the frame-level attention adaptively attends to the frame most relevant to the caption. In addition, because of the exposure bias problem in recurrent neural network (RNN)-based sequence generation, generative adversarial network (GAN) and reinforcement learning (RL) algorithm are combined to make the generated caption more accurate and natural. For the discriminator in the GAN framework, we take both the generated caption and the video features as input, then a new reward function is proposed to update the parameters of generator. The experiments on two benchmark datasets, MSVD and MSR-VTT, have shown the effectiveness of our proposed method.
A Visual Co-occurrence Driven Recommender System

Advancements in vision and mobile technologies made the availability of millions of images every day. Typically, image recommendation systems find the most similar objects for a given image based on the object present in that image. However, existing works do not focus on recommending one or more objects that complete an image. Such objects make the image content-rich as well as complement it. In this paper, we introduce recommending new objects that can increase the image's completeness so that the image becomes more content-rich. We also present a recommendation system framework to recommend new objects based on the chances of their co-occurrence with existing objects in an image. We create a weighted co-occurrence graph from a set of objects on which the model is implemented and use graph centrality measures to generate recommendations. The experimental results demonstrate the viability of the proposed approach.
New Tools, Gadgets, and Devices in Libraries

The internet explosions, proliferation of online resources and the advent of free and open access resources in the last two decades provided the much needed impetus for libraries to inject new energy into providing quality service delivery of its services. More and more applications and databases are being provided to the libraries as mobile products. This chapter that focuses on new tools, gadgets, and devices in the libraries; summarizes, to some extent and expatiate to a large extent, the various new tools, devices and gadgets operational and adaptable to various aspects of librarianship and sections of the librarians. After an exploration of how these devices and tools work, and the different types, the author provided a comparison of current popular products, followed by a look at some of the new tools, gadgets and devices that we have available (toand around us). With the awareness that we are in the midst of an ongoing information revolution, the internet and personal computing are key components of this transition,and has tremendous potential to transform library services. In this chapter, all tools/devices and gadgets therefore, will be analyzed with an eye towards the future, cost-effectiveness, performance and functionality.
Why Is Reading Important?

The aim to write this article is to figure out the reasons why we should read, and giving all the advantages of itself. Moreover, social benefits of reading have been discussed by the author. To conclude with, research has been analyzed to get better development of the reading, importance, and benefits of it have been investigated.
Image Recognition of Human Faces based on BP Neural Network and Particle Swarm Optimization

With the development of artificial intelligence and machine learning, BP neural network has been widely studied in the realm of face recognition. To address the problems that it is sensitive to initial weights and thresholds, easily fall into local minimum, and have slow learning rates. This paper uses an adaptive mutation particle swarm optimization to improve BP networks, and the network used is compared with a single BP network in the ORL database for comparison experiments. Finally, the experimental results demonstrate that the algorithm has faster learning rate and higher recognition rate.
Design of Intelligent Proofreading System Based on Artificial Intelligence

With rapidly developing of computer technologies, English translation based on artificial intelligence has gradually become one of the research directions. Limited to the factors of algorithms as well as matching degree, some problems still bottleneck English translation. To develop an intelligent system for English translation, the author proposed a computer intelligent proofreading model and further developed it. The system can directly integrate additional annotations with input text at the word level, including language markers or automatically generated word classes. Experiments on English translation show that this proofreading model has good performance in automatic scoring and more grammatical coherence. Finally, the author discussed the technological design of this proofreading system from the aspects of hardware and software.
Research on the Construction of Mass Entrepreneurship and Innovation Practice Curriculum System for English Majors in Colleges and Universities under the Background of internet plus

Under the background of internet plus, in order to better keep up with the development of the times, this paper first analyzes the mass entrepreneurship and innovation practice courses for college English majors. By using the B/S framework of Internet technology, and aiming at the problems existing in the mass entrepreneurship and innovation practice course for English majors, this paper constructs a system with the functions of curriculum setting and evaluation guarantee, which emphasizes the idea of strengthening the combination of mass entrepreneurship and innovation consciousness and practice course. It not only improves the system of mass entrepreneurship and innovation practice courses for English majors in colleges and universities, but also improves the high-quality teaching effect of students’ mass entrepreneurship and innovation practice courses.
Enhancing Privacy Through DMMA: Decision-Making Method for Authentication

Attribute-Based Authentication (ABA) is becoming more prevalent in everyday interactions. In this paper, we propose the Decision-Making Method for Authentication (DMMA) to address the privacy concerns in ABA. The need for DMMA is supported through multiple observations. First, in practice, the indistinguishability of crypto-proof-based assertions (that are posessed by different users) fails with non-zero probability. This explains why cryptographic means alone are insufficient to provide a substantial level of unlinkability in ABA systems with n users. Second, each user in ABA possesses multiple credentials: they can be used interchangeably to get access to the service(s) which is provided by a relying party (RP). DMMA addresses the challenge of interchangeable usage. As an initial step, we synthesized the criterion of unlinkability: it is based on the definitions of international standard ISO 27551 as well as the information theoretic measure of conditional entropy. We then use that criterion to formalize the task of authentication as a non-cooperative coordination game. In this game, players (targets of the attack) maximize their utilities by using their assertions interchangeably. The experiment demonstrates that a number of equilibria with substantially higher unlinkability can be achieved. Unlinkability vary depending on: i) the information (and its trustworthiness) about the moves of the other players in the game; ii) the statistical distribution of user attributes. DMMA demonstrates how users may be provided recommendations over the optimal selection of assertions for ABA. These recommendations can have a practical impact if DMMA is implemented as a feature within Digital Credential Wallets (DCWs).
Impacts, Sustanability and Resilience on the Egyptian Tourism and Hospitality Industry after the Russian Airplane crash in 2015.

The Russian airplane crash in 2015 has severely affected the tourism industry in Egypt. The present article is focused on the impacts of economic, political, and social impacts on Egyptian tourism after this crisis. The present study aimed at dealing with the crisis to mitigate the consequences and allow the companies to make the best use of it to restore their business. The present article has also discussed the crisis impacts on the financial situation of company A which is one of the top five hospitality companies in Egypt. Crisis management and investments in human resources were the most effective strategies to overcome the harsh consequences of the crisis on tourism sector. The present study data is based on the Egyptian ministry of tourism figures, internet, articles, and international channels reports aimed to explain how the political, social, and economic events had a negative impact on the hotel industry in Egypt.
Intellectual Property Challenges in Digital Library Environments

Intellectual property poses a major challenge to digital libraries. This is because access to information in digital libraries is limited by laws, licenses and technology adopted by intellectual property owners. Similarly, intellectual property renders it difficult for digital libraries to make orphan works discoverable and accessible. Furthermore, intellectual property fragments copyright ownership, making it difficult for digital libraries to obtain the right clearance on content. To cope with these challenges, digital libraries have embraced the open access movement which allows reading, copying, downloading and sharing of digital content as long as the creators of the works are cited and acknowledged. Besides, digital libraries offer access to digital works produced under creative commons licenses. These licenses give the copyright owners the liberty to modify the copyright of their works to give room for sharing, use, and building upon the work.
A Case Study on Digital Currency with a Special Reference to India

Digital Currency means any currency that is mainly managed, stored and exchanged on digital devices like computer, smartphone, etc. Digital Currency is a type of currency that has no physical form and only exists in digital form and includes virtual money and crypto currency. Digital Currency is also known as digital money or cyber cash and can be used to purchase goods and services but can also be restricted to certain online communities such as gaming, or social networks. In this paper we will study the actual meaning of digital currencies in the modern world with a special reference to current status of digital currency in India. The current study has been casual, exploratory and empirical in nature and the data needed for research work has been collected by using both direct and indirect method of data collection.
Unsupervised feature selection based on robust self-representative dictionary pair learning with application to aluminum electrolysis

The purpose of feature selection is to remove the irrelevant and redundant features, and find the compact representation of the original features with good generalization ability in the high-dimensional data. In practical applications, a large number of high-dimensional data lead to the curse of dimensionality. Besides, the real data are much more complex, which is characterized by redundant, less labeled data and containing noise and outliers. To eliminate these unfavourable factors, an unsupervised feature selection method based on robust self-representative dictionary pair learning is proposed and applied to classification. The method does not require data labels, and uses representation coefficients to model the clustering structure and data distribution. The synthetical dictionary is used for data reconstruction, and the analytical dictionary is designed to analytically code data and assign probabilities to data features. Then, sparse regularization constraint is applied to the analytical dictionary to ensure robustness against noise and outliers in the data. Meanwhile, a regularized self-representative weight strategy is proposed, which uses the self-representative weight matrix to enhance the significance of important features. The effectiveness of the proposed method is verified by experiments on the benchmark datasets and the anode current data in aluminum electrolysis.
String Unification

In this chapter, we discuss grand unified theories (GUTs) from the $$\mathrm {E}_8\times \mathrm {E}_{8}^{\prime }$$ heterotic string and present the resultant phenomenological implications. We take concrete example a flipped SU(5) model on $$\mathbb {Z}_{\mathrm {12-I}}$$ orbifold. In Chaps. 7 – 12 , we discussed in length the theoretical framework for orbifolded superstrings.
The Challenge of Adequately Defining Technical Risk

Chapter 2 investigates the risk and compliance conundrum as fundamental principles that better inform the governance of cyber security in organizations. Public cloud computing examples are used to highlight the deficiencies of legacy risk assessment methods but also to provide a stark warning about using compliance mapping approaches instead of considered security control implementations. Ultimately using blanket compliance frameworks does not necessarily influence, but rather conversely, creates a vacuum that does not drill deep enough into the controls needed to safeguard cloud environments; this is particularly relevant since public cloud systems are connected to and accessed via the internet and therefore exposed to external threats. This chapter explores the use of threat modelling to contextualize risks more accurately in order to mitigate them more effectively.
Research and Application of Virtual Sample Generation Method Based on Conditional Generative Adversarial Network

In the chemical production process, due to certain physical limitations and high measurement costs, it is sometimes difficult to obtain plenty of data points to improve the accuracy of the prediction model. To solve this problem, this paper proposes a novel virtual sample generation method to reasonably expand training sets, aiming to promote accuracy of prediction model. First, the outliers of the original samples are found by local outlier factor. Then, iterative midpoint interpolation is performed on each outlier to obtain a new sample x with a more uniform distribution, so as to fill the scarce area as much as possible. Second, the corresponding output of these new virtual samples are generated by a generative model based on conditional generative adversarial network. To observe the effectiveness of the proposed method, we used standard function dataset and purified terephthalic acid (PTA) production dataset for verification. Experimental results show that our method effectively improves the accuracy of the prediction model.
Social Media Applications as Effective Service Delivery Tools for Librarians

In a bid to satisfy the growing needs of library users, the social media hype has gradually crept into the library profession with a wide variety of social media applications such as Facebook, MySpace, Flickr, LinkedIn, Twitter, YouTube, Skype, Library Thing, Ning, and so on being common tools for carrying out routine tasks within the library community. This chapter will provide an overview of social media applications and identify those that are commonly used in libraries in Nigeria as well as explore the reasons for using social media applications in libraries and how they are employed in performing sundry library routines. The chapter will also examine the future role of librarians with respect to the current realities as presented by these social media applications as well as the opportunities and the challenges of using social media applications in libraries. Recommendations and future trends in the use of social media applications will also be highlighted.
Evaluation of the Attack Effect Based on Improved Grey Clustering Model

There are a lot of uncertainties and incomplete information problems on network attack. It is of great value to access the effect of the attack in the current network attack and defense. This paper examines the characteristics of network attacks, there are problems with traditional clustering that index attribution is not clear and the cross of clustering interval. A two-stage grey synthetic clustering evaluation model based on center-point triangular whitenization weight function was proposed for the attack effect. The authors studied the feasibility of applying this model to the evaluation of network attack effect. Finally, an example is given, which showed the model could evaluate the effect of the denial-of-service attack precisely. It is also shown that the model is viable to evaluate the attack effect.