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IoT has enabled the rapid growth of smart remote healthcare applications. These IoT-based remote healthcare applications deliver fast and preventive medical services to patients at risk or with chronic diseases. However, ensuring data security and patient privacy while exchanging sensitive medical data among medical IoT devices is still a significant concern in remote healthcare applications. Altered or corrupted medical data may cause wrong treatment and create grave health issues for patients. Moreover, current remote medical applications' efficiency and response time need to be addressed and improved. Considering the need for secure and efficient patient care, this paper proposes a lightweight Blockchain-based and Fog-enabled remote patient monitoring system that provides a high level of security and efficient response time. Simulation results and security analysis show that the proposed lightweight blockchain architecture fits the resource-constrained IoT devices well and is secure against attacks. Moreover, the augmentation of Fog computing improved the responsiveness of the remote patient monitoring system by 40%., Comment: 32 pages, 13 figures, 5 tables, accepted by Elsevier "Internet of Things; Engineering Cyber Physical Human Systems" journal on January 9, 2023

The proliferation of resource-constrained devices has become prevalent across various digital applications, including smart homes, smart healthcare, and smart transportation, among others. However, the integration of these devices brings many security issues. To address these concerns, Blockchain technology has been widely adopted due to its robust security characteristics, including immutability, cryptography, and distributed consensus. However, implementing blockchain within these networks is highly challenging due to the limited resources of the employed devices and the resource-intensive requirements of the blockchain. To overcome these challenges, a multitude of researchers have proposed lightweight blockchain solutions specifically designed for resource-constrained networks. In this paper, we present a taxonomy of lightweight blockchain solutions proposed in the literature. More precisely, we identify five areas within the "lightweight" concept, namely, blockchain architecture, device authentication, cryptography model, consensus algorithm, and storage method. We discuss the various methods employed in each "lightweight" category, highlighting existing gaps and identifying areas for improvement. Our review highlights the missing points in existing systems and paves the way to building a complete lightweight blockchain solution for networks of resource-constrained devices., Comment: 77 pages, 10 figures, final version accepted by Internet of Things Journal, Elsevier

This paper will discuss a Virtual Exchange (VE) between the University of Michigan (USA) and the High Institute of Technological Studies of Béja (Tunisia) that took place between October and December 2019. Students from Tunisia and USA were enrolled in two entrepreneurship courses in their respective universities and joined together to work in groups on an innovative project on 'creating a prototype for a seawater farm in the region of Khniss' to be presented at the end of the semester. As this project was student-centered, the main focus was to show its impact on the students through their testimonials on what challenges they encountered and what benefits they gained from this experience at an academic and personal level. These testimonials showed that despite differences in intercultural communication competencies between American and Tunisian students and the use of English as a lingua franca, students gained valuable skills in team communication, collaboration, and coordination in a large team spread over two continents. Students taught each other and learned from each other while working toward solving a social and environmental problem the world is struggling with. Another light was shed on the impact of this VE on the instructors, the pedagogy adopted to conduct the project, as well as the contribution of the instructional support staff. Moving from a directive to a student-driven approach was rewarding for the Tunisian instructor who learned how to push students out of their comfort zone, dive into uncertain areas, and ask questions rather than accepting the norms. On his part the American instructor learned that it is possible to create meaningful, unconventional student-led projects across languages, cultures, and geography as long as the teams (students and faculty) are excited and committed to the project. He also learned that students get inspired to be brave, thoughtful, and resourceful when they can witness what effective professional collaboration by faculty looks like. [For the complete volume, "Virtual Exchange: Towards Digital Equity in Internationalisation," see ED614868.]

Cybersecurity is an inherent characteristic that should be addressed before the large deployment of smart city applications. Recently, Blockchain appears as a promising technology to provide several cybersecurity aspects of smart city applications. This paper provides a comprehensive review of the existing blockchain-based solutions for the cybersecurity of the main smart city applications, namely smart healthcare, smart transportation, smart agriculture, supply chain management, smart grid, and smart homes. We describe the existing solutions and we discuss their merits and limits. Moreover, we define the security requirements of each smart city application and we give a mapping of the studied solutions to these defined requirements. Additionally, future directions are given. We believe that the present survey is a good starting point for every researcher in the fields of cybersecurity, blockchain, and smart cities., Comment: 65 pages, 6 figures, 37 tables

This case study reports a Virtual Exchange (VE) between students at Cracow University of Economics (Poland) enrolled in business courses and students from the High Institute of Technological Studies of Béja (Tunisia) enrolled in an entrepreneurship course. The main aim of the project was to enhance students' awareness of similarities and differences between the Polish and the Tunisian entrepreneurial ecosystems. The goals also included improving language skills, Information and Communication Technology (ICT) literacy, teamwork, and increasing their self-confidence. The chapter describes the schedule of the project, tasks that students accomplished, and the technological and communication tools that were used. Finally, the study includes conclusions and suggestions for future initiatives. [For the complete volume, "Designing and Implementing Virtual Exchange -- A Collection of Case Studies," see ED609252.]

Pretrained contextualized text representation models learn an effective representation of a natural language to make it machine understandable. After the breakthrough of the attention mechanism, a new generation of pretrained models have been proposed achieving good performances since the introduction of the Transformer. Bidirectional Encoder Representations from Transformers (BERT) has become the state-of-the-art model for language understanding. Despite their success, most of the available models have been trained on Indo-European languages however similar research for under-represented languages and dialects remains sparse. In this paper, we investigate the feasibility of training monolingual Transformer-based language models for under represented languages, with a specific focus on the Tunisian dialect. We evaluate our language model on sentiment analysis task, dialect identification task and reading comprehension question-answering task. We show that the use of noisy web crawled data instead of structured data (Wikipedia, articles, etc.) is more convenient for such non-standardized language. Moreover, results indicate that a relatively small web crawled dataset leads to performances that are as good as those obtained using larger datasets. Finally, our best performing TunBERT model reaches or improves the state-of-the-art in all three downstream tasks. We release the TunBERT pretrained model and the datasets used for fine-tuning.

The Multiple Travelling Salesman Problem (MTSP) is among the most interesting combinatorial optimization problems because it is widely adopted in real-life applications, including robotics, transportation, networking, etc. Although the importance of this optimization problem, there is no survey dedicated to reviewing recent MTSP contributions. In this paper, we aim to fill this gap by providing a comprehensive review of existing studies on MTSP. In this survey, we focus on MTSP's recent contributions to both classical vehicles/robots and unmanned aerial vehicles. We highlight the approaches applied to solve the MTSP as well as its application domains. We analyze the MTSP variants and propose a taxonomy and a classification of recent studies.