Reviewerly/exHarmony huggingface dataset:
Fundamental Data Security Technologies

In this chapter, we introduce the fundamental technologies for achieving blockchain-based data security in HCN. First, we discuss basic crypto technologies from notations to hash functions. Second, we investigate basic blockchain technologies, with three exemplary blockchains, including Bitcoin, Ethereum, and Hyperledger Fabric. This will help us understand the working and design principles for blockchain-based applications. Third, we present state-of-the-art privacy-enhancing technologies for blockchain, including various constructions of the widely used zero-knowledge proof and anonymous credential techniques. Finally, we discuss computation models for blockchain and show how verifiable computations from cryptography or trusted hardware can boost blockchain efficiency and privacy.
Transparent Data Query in HCN

Data query enables a data user to quickly find and retrieve data according to the user-specified keywords, range, or other query metrics. Data query plays a vital role in supporting many data-intensive applications in future networks. As data are generated and distributed at heterogeneous network entities, data query is often conducted by a third party that is out of the trust domain of the query user. In this chapter, we investigate transparent data query services for HCN. First, we identify the necessity for transparent VNF query and slice configuration across different network resource providers and propose a blockchain-based verifiable query scheme for NFV-enabled network management. Second, we integrate SNARG-based on/off-chain computation model to achieve succinct storage of a query dictionary and efficient verifications of query results. At the same time, we further investigate the random access memory (RAM) issue of SNARG-based solution that causes inefficient proving overheads. To address the efficiency challenge, we design a two-level SNARG system that conducts a key query to reduce search space for a full query. From pre-computed authenticators and a Merkle tree, we design a dictionary pruning scheme to efficiently generate an aggregated authenticator for the verifications in the SNARG system for the full query. We analyze the security properties of each component in the proposed scheme to achieve verifiable data query on the blockchain. We conduct extensive experiments with a consortium network to demonstrate the on/off-chain efficiency of the proposed scheme. With our proposed dictionary pruning strategy, off-chain proof generation overheads can be significantly reduced.
Fair Data Marketing in HCN

In data marketing, a data owner can sell his/her data to a data buyer for profit considerations. The data buyer can utilize the data for various data-intensive applications, such as AI-assisted network management in HCN. With data privacy laws taking effect, it is essential to preserve the rights of data owners including data access control and identity privacy. At the same time, fair payment for the data owner and honest data delivery for the data buyer are also critical for the development of data marketing. In this chapter, we propose a blockchain–cloud data marketing scheme that complies with privacy regulations and preserves marketing fairness. First, we adopt a hybrid marketing model that utilizes the cloud server as a powerful data storage unit and the blockchain as a reliable controller of data marketing. By doing so, on-chain storage and computation costs are significantly reduced by only recording critical data marketing operations rather than the large volume of data. Second, we design succinct commitments of data marketing operations for data owners, data buyers, and the cloud server with efficient on-chain verifications. Through financial incentives and accountability enforcement, the proposed scheme achieves fair data marketing even with a rational off-chain cloud server. Third, we tailor the designs of multi-message PS signature and the threshold cryptograph for distributed management of data owners’ anonymous credentials. Specifically, distributed credential issuance and threshold identity tracing are realized without a single certificate authority. We conduct thorough security analysis and extensive experiments on a consortium blockchain network with different settings, which demonstrates that the proposed marketing scheme achieves the security goals and is practical for implementation.
Introduction

Future communication network is envisioned to be highly heterogeneous with various stakeholders from different trust domains, including mobile operators, technological vendors, etc. As service requirements and user dynamics become more dynamic, artificial intelligence (AI)-assisted network management is a promising approach to increase service satisfaction and reduce operational costs. However, the AI-assisted approach puts stringent demand on data volume and quality, which requires new data security approaches across the trust boundaries of network stakeholders. In this chapter, we first review the features of future heterogeneous communication networks (HCN) to highlight the need of an advanced network architecture with data-driven network management methods. To manage data lifecycle events and preserve data security among heterogeneous network stakeholders, we introduce blockchain-based data management (DM) for HCN. We then present the design challenges in balancing privacy, efficiency, and fairness in DM with the decentralization nature of the blockchain and discuss three representative data security approaches: reliable data provenance, transparent data query, and fair data marketing. Finally, we provide the aim of the monograph and the overview the main contents of the following chapters.
Pseudometric spaces: From minimality to maximality in the groups of combinatorial self-similarities

Abstract The group of combinatorial self-similarities of a pseudometric space <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mrow> <m:mo>(</m:mo> <m:mrow> <m:mi>X</m:mi> <m:mo>,</m:mo> <m:mi>d</m:mi> </m:mrow> <m:mo>)</m:mo> </m:mrow> </m:math> \left(X,d) is the maximal subgroup of the symmetric group <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi mathvariant="normal">Sym</m:mi> <m:mrow> <m:mo>(</m:mo> <m:mrow> <m:mi>X</m:mi> </m:mrow> <m:mo>)</m:mo> </m:mrow> </m:math> {\rm{Sym}}\left(X) whose elements preserve the four-point equality <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi>d</m:mi> <m:mrow> <m:mo>(</m:mo> <m:mrow> <m:mi>x</m:mi> <m:mo>,</m:mo> <m:mi>y</m:mi> </m:mrow> <m:mo>)</m:mo> </m:mrow> <m:mo>=</m:mo> <m:mi>d</m:mi> <m:mrow> <m:mo>(</m:mo> <m:mrow> <m:mi>u</m:mi> <m:mo>,</m:mo> <m:mi>v</m:mi> </m:mrow> <m:mo>)</m:mo> </m:mrow> </m:math> d\left(x,y)=d\left(u,v) . Let us denote by <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi class="MJX-tex-caligraphic" mathvariant="script">ℐP</m:mi> </m:math> {\mathcal{ {\mathcal I} P}} the class of all pseudometric spaces <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mrow> <m:mo>(</m:mo> <m:mrow> <m:mi>X</m:mi> <m:mo>,</m:mo> <m:mi>d</m:mi> </m:mrow> <m:mo>)</m:mo> </m:mrow> </m:math> \left(X,d) for which every combinatorial self-similarity <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi mathvariant="normal">Φ</m:mi> <m:mo>:</m:mo> <m:mi>X</m:mi> <m:mo>→</m:mo> <m:mi>X</m:mi> </m:math> \Phi :X\to X satisfies the equality <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi>d</m:mi> <m:mrow> <m:mo>(</m:mo> <m:mrow> <m:mi>x</m:mi> <m:mo>,</m:mo> <m:mi mathvariant="normal">Φ</m:mi> <m:mrow> <m:mo>(</m:mo> <m:mrow> <m:mi>x</m:mi> </m:mrow> <m:mo>)</m:mo> </m:mrow> </m:mrow> <m:mo>)</m:mo> </m:mrow> <m:mo>=</m:mo> <m:mn>0</m:mn> <m:mo>,</m:mo> </m:math> d\left(x,\Phi \left(x))=0, but all permutations of metric reflection of <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mrow> <m:mo>(</m:mo> <m:mrow> <m:mi>X</m:mi> <m:mo>,</m:mo> <m:mi>d</m:mi> </m:mrow> <m:mo>)</m:mo> </m:mrow> </m:math> \left(X,d) are combinatorial self-similarities of this reflection. The structure of <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi class="MJX-tex-caligraphic" mathvariant="script">ℐP</m:mi> </m:math> {\mathcal{ {\mathcal I} P}} -spaces is fully described.
Norms and rules for developing a foreign language teaching strategy at institutions of higher education

This article discusses the norms and rules for developing a foreign language teaching strategy at institutions of higher education. The author highlights the key stages of strategy development, from analysing students’ needs and identifying language levels to integrating technology, promoting independent learning and supporting teachers. The article provides specific recommendations and tools for optimising the process of language teaching in the university environment to ensure the successful development of students’ language skills.
NFT Culture: A New Era

It is observed that there are several artists who are developing marvelous products but their product needs international exposure. These artists have limited market if they are going to promote and sell product. Moreover the there is lack of premium customer in rural areas. Thus artist who lives in rural area does not get proper incentive and significance. NFT is the only way to provide such artist global market where such artists may promote their art work. With the advent of blockchain technology NFT creation and marketing has been increased. Thus there are several international; market place such as Opensea and Young parrot that allows creation of NFT over Matic, Satoshi core, Ethereum and BNB smart chain. 9NFTMANIA proposed a lifestyle that is named as NFT culture. In these culture greetings, invitations, certificates, membership card would be made in form of NFT. In this way secure transfer of digital asset could be made and this NFT would have particular value. Even if a person wants to thank someone or want to say good morning then he should transfer NFT to other person's wallet. Moreover the supply of such greeting NFT would be limited thus there remains expectation of raise in price. On other hand holder of NFT would be able to access premium web services when web 3.0 mechanisms are applied to verify NFT holder in Metaverse.
Virtual Reality in Destination Marketing: The Why, the Who and the When

Virtual Reality in Destination Marketing: The Why, The Who and The When. Virtual reality (VR) is one of the fastest growing areas in information and communication technologies. Starting with the 1990s, the technology has also been successfully employed in tourism. Among other purposes, VR is used in tourism to provide a more effective marketing of a destination than classical means such as (paper) brochures. While the literature on the use of VR in destination marketing has been steadily growing, it is still scarce and fragmented. The main objective of this study is to better understand how could VR be used to improve the marketing of tourism destinations. To gather data for this study an experiment was used: participants were invited to take an online virtual tour of a very popular landmark in Paris, and then fill out a questionnaire in order to share their experience. The data from the 89 questionnaires collected were then processed using SPSS. The results have shown that almost all of our respondents were satisfied with their VR experience. Moreover, the VR experiment has improved the users’ image of and satisfaction with the destination. This, in turn, has positively influenced their intention to visit or re-visit the destination and to recommend it to others. The study also found that some socio-demographic groups (female, older than 25 years) may be more suitable targets for destination marketing using VR than others. Finally, we learned that, although the use of VR is effective for destination marketing both before and after tourists visit the site, the technology may be more useful in improving the image of the destination when applied before the physical visit. Keywords: virtual reality, virtual tourism, destination marketing, destination image, user satisfaction.
Small Scale Models of Solar Tracking Systems

Increasing the efficiency of photovoltaic panels using solar tracking systems is a current topic. The use of solar tracking systems is a solution, especially in low power applications. The paper presents two types of solar tracking systems, one based on astronomical data, and the other based on tracking the point of maximum illumination. Both systems are made on small scale for educational purposes. These systems can be used for the analysis of methods, principles and particularities in order to use them in practical applications. For the two experimental models of solar tracking made, the hardware and software structure are presented. To orient the photovoltaic panels in the two directions (East-West, respectively South-North) DC motors or stepper motors are used. One motor is used for each axis of rotation. Both structures have the control part composed of a microcontroller development system. This control method has the advantage that can significantly reduce the number of electronic components as well as the cost of designing and building of equipment. For the solar tracking system based on astronomical data, a remote monitoring and control system has been achieved. It uses a friendly graphic interface made on PC with the help of Visual Basic software. Both models were tested and the experimental results showed correct operation according to the imposed protocol. Finally, an energy efficiency analysis was done and it was found that the PV panel that uses the tracking systems produces 35% more energy compared to a fixed PV panel.
Decoding the impact of emotions: machine learning insights on user interests in social networks

This study investigates the correlation that exists between users' emotional states and their expressed interests in the context of social network. By utilizing cutting-edge machine learning methods, we set out to reveal the connections that underpin user behavior. Saudi Arabia is among the nations with the highest usage of X (previously Twitter). Several studies used the analysis of English tweets to determine the topic of interest and whether the user is passive or active. Studies that examined user interaction to ascertain interest have been conducted with reference to Arabic tweets. There are, however, few studies that track how an external factor, like emotions, affects interest over time. To investigate the relationship between interest and emotion, we used two models of supervised algorithms: Support Vector Machines (SVM) and Naïve Bayes. Once the topic of interests and emotions were classified, we discovered that the topic of interest had a higher accuracy than the emotion classifier because it had been applied to a sample of dataset. Furthermore, the SVM outperformed Naïve Bayes in terms of accuracy for classifying both topics of interest and emotions. Finally, the result indicates that the interests for specific user change over time according to the emotions.
A Study of Interaction Design for E-learning System Based on Distributed Asynchronous Communication

This paper discusses insufficient teacher-student communication in online courses for asynchronous computer programming. In such an online course, communication between students and teachers is significantly reduced compared with that in offline courses. Hence, teachers seldom receive questions and feedback from students because in asynchronous online learning, questions are mostly asked through email, chat, and forum. This makes it difficult for students to describe the questions clearly, resulting in a decrease in students’ motivation to ask questions. Furthermore, it is difficult for teachers to statistically analyze the collected questions to improve the quality of the learning materials. In this study, we designed an online learning system according to the learning habits in computer science, which allows students to ask questions without too much description and to review more easily. In addition, teachers are provided with tools for statistical analysis.
AR-C&amp;P: A Tangible Programming for Children Based Augmented Reality

Augmented Reality (AR) technology enables continuous visual feedback and varied digital scenes on the real world. This paper presents AR-C&P, an AR-based tangible programming tool for young children. It allows children to create AR maze map with low-cost materials and plan the route by constructing tangible program sequences. Meanwhile, a variety of real-time visual feedback from the screen will be superimposed on the real scenes of the whole process. AR-C&P is intuitive and intriguing which could enrich children’s creating experience, develops their cognitive developmental skills and helps children learn fundamental programming concepts. We conducted two experiments. The first experiment reveals the relationship between task completion and cognitive developmental skills. The second experiment reveals the effect of AR on learning programming.
Driven by Extrinsic and Intrinsic Factors: Understanding Students’ Acceptance of Augmented Reality Learning Applications

Recently, the Augmented Reality (AR) market is growing rapidly, and it has been used in mobile learning environments. This study emphasized the learning experience in AR environments, trying to explain the behavioral intention of users from both extrinsic and intrinsic causes. An extended Technology Acceptance Model was proposed to investigate factors that affect the acceptance of AR among Chinese college students, and all the variables were incorporated into a structural equation modeling. A total of 184 questionnaires were used. Results indicated that the model was supported and could explain 54.1% of the variance in behavioral intention. Both interactivity and interface quality positively affected perceived ease of use and flow. Both perceived usefulness and flow positively affect behavioral intention, and perceived usefulness has a stronger one. However, perceived ease of use showed no significant relationship with behavioral intention. Based on the results, this study gave some advice on AR learning application design.
Theoretical, methodological and conceptual foundations of professional training of the future psychologists

The article reveals the actual problem of higher psychological education in the specialty 053 Psychology. It is related to the pragmatic issue of creating educational and scientific and educational and professional programs. In the conditions of autonomy of a higher education institution, it is necessary for the developers of these programs to have a modern scientific understanding of the peculiarities of competence approach in education, the types of competencies that should be formed in future psychologists, as well as the key concepts on which these educational documents should be based.
Design of a Drone for Urban Application Using a Patented Technology

The present work deals with a design of a drone based on the ThrustPod technology, a patented solution for the vertical take-off and landing fixed wing aircraft in the urban aerial mobility scenario. The ThrustPod is based on extractable thrusters with fixed vertical axis that can be activated only for the vertical flight phases. On the contrary, in cruise conditions the ThrustPod thrusters are retracted inside the fuselage. The proposed solution leads to several advantages, e.g. reduced noise and reduced aerodynamic drag during cruise flight missions with respect to other equivalent aircraft. The proposed solution is designed for a drone to be used as a flying testbed to tune the ThrustPod functions and for aircraft control purposes in the entire flight envelope. The drone preliminary design is carried out using an in-house Matlab code and starting from some defined preliminary mission and aircraft specifications (e.g. wing span, cruise distance, etc.). The code is able to provide an optimal configuration of the drone, in terms of requirements for fuselage dimensions, energy and motors able to satisfy defined requirements with the minimum aircraft weight. The work is concluded with selection of suitable components able to satisfy the preliminary design requirements to manufacture the drone.
From sublime awe to abject cringe: on the embodied processing of AI art

This article urges a reorientation in thinking about AI art (and AI more generally), shifting from the common focus on computational ‘intelligence’ to the embodied, metabolic processing that takes place in our encounters with (moving-image) artworks produced with machine-learning algorithms. Drawing on Merleau-Ponty’s corporeal phenomenology, the article argues that spectators’ bodies act as filters, distilling visual phenomena from a range of extraperceptual facets of these works; in particular, bodies react to invisible algorithmic infrastructures, which, in the case of machine learning algorithms, also operate as filters in their own right. The collision of metabolic and computational microtemporal operations calls forth a number of embodied affects, ranging from sublime awe to disorientation, cringe, and uncanny feelings of relational and environmental entanglement. These themes are explored through the work of four contemporary artists working with AI: Ian Cheng, Refik Anadol, Jon Rafman, and Yvette Granata. In conversation with these artists, the author explores our bodily responses to AI-generated imagery in an attempt to better understand the stakes, as well as the underlying mechanisms, of the new technology’s transformation of our visual culture.
A Keyphrase-Centric Search Engine for Scientific Papers

The ever increasing interest and participation in scientific research and development has been a major contributor towards the exponential increase of textual and multi-modal scientific data on the Web over the past few years. It is imperative for scientists to keep track of the latest development in their respective area of research, but the ever-expanding landscape of research publications makes it quite challenging. Automating the parsing, retrieval, and understanding of this literature through state-of-the-art NLP and IR tools is the need of the hour. The goal of this doctoral work will be to develop new tools singularly for the low-resource scientific domain. We propose to contribute to this field by not only developing deep learning solutions for these tasks, but also providing the NLP and IR community with unique challenging datasets wherever necessary.
Explainability of Text Processing and Retrieval Methods

This tutorial presents explainability of text processing and retrieval methods, an emerging area focused on fostering responsible and trustworthy deployment of machine learning systems in the context of information retrieval. As the field has rapidly evolved in the past 4-5 years, numerous approaches have been proposed that focus on different access modes, stakeholders, and model development stages. This tutorial aims to introduce IR-centric notions, classification, and evaluation styles in explainable information retrieval (ExIR) while focusing on IR-specific tasks such as ranking, text classification, and learning-to-rank systems. We will delve into method families and their adaptations to IR, extensively covering post-hoc methods, axiomatic and probing approaches, and recent advances in interpretability-by-design approaches. We will also discuss ExIR applications for different stakeholders, such as researchers, practitioners, and end-users, in contexts like web search, patent and legal search, and high-stakes decision-making tasks. To facilitate practical understanding, we will provide a hands-on session on applying text processing and ExIR methods, reducing the entry barrier for students, researchers, and practitioners alike. Earlier version of this tutorial has been presented in SIGIR 2023.