2,682 research outputs found

    CHATBOT APPLICATION AS SUPPORT TOOL FOR THE LEARNING PROCESS OF BASIC CONCEPTS OF TELECOMMUNICATIONS AND WIRELESS NETWORKS

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    There are several applications for Chatbots in education, as well as their contributions to mentoring in the learning process. Bots can assist teachers with staying up to date on new standards and evaluation methodologies. Bots can assist students in understanding tough subjects in a way that makes it appear as if they are being taught by another person. Chatbots serve as virtual assistants in the educational setting, improving efficiency or answering frequently asked questions. In this case, we work on the premise of investigating the potential of Chatbots as analytical tools for analyzing preferred types of learning material in a mobile learning environment, which leads to the acquisition of a proper level of knowledge on the topics of telecommunication and wireless networks

    An innovative approach for enhancing capacity utilization in point-to-point voice over internet protocol calls

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    Voice over internet protocol (VoIP) calls are increasingly transported over computer-based networking due to several factors, such as low call rates. However, point-to-point (P-P) calls, as a division of VoIP, are encountering a capacity utilization issue. The main reason for that is the giant packet header, especially when compared to the runt P-P calls packet payload. Therefore, this research article introduced a method to solve the liability of the giant packet header of the P-P calls. The introduced method is named voice segment compaction (VSC). The VSC method employs the unneeded P-P calls packet header elements to carry the voice packet payload. This, in turn, reduces the size of the voice payload and improves network capacity utilization. The preliminary results demonstrated the importance of the introduced VSC method, while network capacity improved by up to 38.33%

    La traduzione specializzata all’opera per una piccola impresa in espansione: la mia esperienza di internazionalizzazione in cinese di Bioretics© S.r.l.

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    Global markets are currently immersed in two all-encompassing and unstoppable processes: internationalization and globalization. While the former pushes companies to look beyond the borders of their country of origin to forge relationships with foreign trading partners, the latter fosters the standardization in all countries, by reducing spatiotemporal distances and breaking down geographical, political, economic and socio-cultural barriers. In recent decades, another domain has appeared to propel these unifying drives: Artificial Intelligence, together with its high technologies aiming to implement human cognitive abilities in machinery. The “Language Toolkit – Le lingue straniere al servizio dell’internazionalizzazione dell’impresa” project, promoted by the Department of Interpreting and Translation (Forlì Campus) in collaboration with the Romagna Chamber of Commerce (Forlì-Cesena and Rimini), seeks to help Italian SMEs make their way into the global market. It is precisely within this project that this dissertation has been conceived. Indeed, its purpose is to present the translation and localization project from English into Chinese of a series of texts produced by Bioretics© S.r.l.: an investor deck, the company website and part of the installation and use manual of the Aliquis© framework software, its flagship product. This dissertation is structured as follows: Chapter 1 presents the project and the company in detail; Chapter 2 outlines the internationalization and globalization processes and the Artificial Intelligence market both in Italy and in China; Chapter 3 provides the theoretical foundations for every aspect related to Specialized Translation, including website localization; Chapter 4 describes the resources and tools used to perform the translations; Chapter 5 proposes an analysis of the source texts; Chapter 6 is a commentary on translation strategies and choices

    Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges and Future Directions

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    Sixth-generation (6G) networks anticipate intelligently supporting a wide range of smart services and innovative applications. Such a context urges a heavy usage of Machine Learning (ML) techniques, particularly Deep Learning (DL), to foster innovation and ease the deployment of intelligent network functions/operations, which are able to fulfill the various requirements of the envisioned 6G services. Specifically, collaborative ML/DL consists of deploying a set of distributed agents that collaboratively train learning models without sharing their data, thus improving data privacy and reducing the time/communication overhead. This work provides a comprehensive study on how collaborative learning can be effectively deployed over 6G wireless networks. In particular, our study focuses on Split Federated Learning (SFL), a technique recently emerged promising better performance compared with existing collaborative learning approaches. We first provide an overview of three emerging collaborative learning paradigms, including federated learning, split learning, and split federated learning, as well as of 6G networks along with their main vision and timeline of key developments. We then highlight the need for split federated learning towards the upcoming 6G networks in every aspect, including 6G technologies (e.g., intelligent physical layer, intelligent edge computing, zero-touch network management, intelligent resource management) and 6G use cases (e.g., smart grid 2.0, Industry 5.0, connected and autonomous systems). Furthermore, we review existing datasets along with frameworks that can help in implementing SFL for 6G networks. We finally identify key technical challenges, open issues, and future research directions related to SFL-enabled 6G networks

    Assessing the Feasibility of Wireless Networks for Managed Automated Driving (MAD): A Spotlight on Communication Technology

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    The primary objective of this research is to develop a comprehensive understanding of the interplay between Signal-to-noise ratio (SNR) and Packet error rate (PER) and their implications on the overall performance of wireless communication systems. This thesis focuses to implement wireless communication between the remote infrastructureand vehicle using the User Datagram Protocol (UDP), with focus on the physical, data link layer

    Інформаційні технології: теорія і практика: Тези доповідей VІ-ї Всеукраїнської науково-практичної інтернет-конференції здобувачів вищої освіти і молодих учених, 2023 р., м. Харків) [Електронний ресурс]

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    У збірнику представлені тези доповідей V Всеукраїнської Інтернетконференції здобувачів вищої освіти і молодих учених, яка мала відбутися 17-18 березня 2022 р. в Національному університеті «Запорізька політехніка», але через військову агресію російської федерації була проведена 10 червня 2022 р. в онлайн форматі. Конференція присвячується до 100-річчя Харківського національного університету міського господарства ім. О.Бекетова. Розглянуто результати досліджень та перспективи розвитку інформаційних технологій. Збірник призначений для науково-технічних підприємств, викладачів вищих навчальних закладів, докторантів, аспірантів і студентів.Зібрані тези доповідей VІ-ї Всеукраїнської інтернет-конференції здобувачів вищої освіти і молодих учених серед студентів, викладачів, науковців, молодих учених і аспірантів. Наукове видання відображає широкий спектр тематики наукових досліджень авторів
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