2,757 research outputs found

    Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

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    Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

    Multiplex Communities and the Emergence of International Conflict

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    Advances in community detection reveal new insights into multiplex and multilayer networks. Less work, however, investigates the relationship between these communities and outcomes in social systems. We leverage these advances to shed light on the relationship between the cooperative mesostructure of the international system and the onset of interstate conflict. We detect communities based upon weaker signals of affinity expressed in United Nations votes and speeches, as well as stronger signals observed across multiple layers of bilateral cooperation. Communities of diplomatic affinity display an expected negative relationship with conflict onset. Ties in communities based upon observed cooperation, however, display no effect under a standard model specification and a positive relationship with conflict under an alternative specification. These results align with some extant hypotheses but also point to a paucity in our understanding of the relationship between community structure and behavioral outcomes in networks.Comment: arXiv admin note: text overlap with arXiv:1802.0039

    Teaching Truth: Grassroots Reactions to Classroom Censorship Legislation in Georgia

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    Legislation known as “anti-CRT” bills swept across the United States in 2020 designed to eradicate principles of diversity, equity, inclusion, and oftentimes history from school curriculums. This research employs an engaged anthropological framework to explore the reactions and resistance measures employed by grassroots groups in response to the Protect Students First Act in Georgia. Data analysis utilized over 10 hours of participant observation at events during 2022-2023 in the Atlanta Metropolitan area, in-depth interviews with grassroots leaders from Georgia Educators for Equity and Justice Inc. (GAEEJ) and Teach for Freedom Collective, and surveys provided by GAEEJ on the impacts of legislation on teachers and students, activists’ motivations for action, and their strategies of resistance. The study reveals that resistance to this legislation is grounded in participants’ demand for equity and advocacy in schools and takes the form of community-making and capacity-building for successful initiatives against classroom censorship laws

    Youth as E-Citizens: Engaging the Digital Generation

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    "Youth as E-Citizens: Engaging the Digital Generation" provides a groundbreaking overview of Web-based efforts to increase youth civic engagement. Beginning with a close-up examination of website content, the report also examines the organizations and institutions creating that content, and the larger environment in which civic sites function. The full report offers:Case studies of high-profile sites' strategies for launch, visibility and funding; the online response to 9/11; and online youth activism.Discussion of the potential that websites offer to build lasting habits of civic involvement. Current developments in technology, regulation and law that raise urgent questions about the viability of the civic Web.In addition, the project has created an online showcase of top youth civic websites. To see how they use the Internet to facilitate civic involvement and learning, take the Online Tour (http://centerforsocialmedia.org/ecitizens/index.htm)!"Youth as E-Citizens" was initiated by the Center for Media Education. With the closing of the Center in the fall of 2003, the project joined the Center for Social Media. Initial funding for this multi-year research project was provided by the Center for Information and Research on Civic Learning and Engagement (CIRCLE). The Ford Foundation, the Open Society Institute, the Packard Foundation, and the Surdna Foundation also provided critical support

    Complexity and robustness of structures against extreme events

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    Civil structures are designed to support the loads acting on them. At present, the common practitioner considers both ordinary (winds, snow, accidental loads) and extreme events (earthquake, fire), combines the actions in such a way that, once the resistance of the elements is determined, the probability of failure is limited to a prescribed value. The set of events that may interest the structure is known and, therefore, a statistics of the actions is defined a priori. However, other events that are not forecastable may interest the construction. The sources of such events, called “Black Swans” after Taleb, are unknown, as well as their magnitude. For ensuring the integrity of the construction in such situations, which imply large damages, robust measures have to be taken (Chapter 3). Structural engineering is not the only domain in which unexpected events occur. Nature is the realm of contrasts. By means of evolution, living species differentiates, differentiated, in order to survive and reproduce. Various strategies were implemented in order to guarantee a biological robustness. Such mechanisms evoke one fundamental property of systems, the complexity and the connectivity between the components. The interaction between the parts makes the whole system more robust and tolerant to errors and damages (Chapters 1 and 2). Robustness in structures is implemented through classical strategies, which tend to limit the extent of damages through a design based on the consequences (Chapter 4). Being inspired by natural strategies, the idea of complexity in structural engineering is explored. Many issues arise, since a proper definition of this term has not been stated yet (Chapters 5 and 6). The ef- fects of element removal on frame structures, which represent an example of highly connected structural scheme, are investigated. As a result of simple simulations, the trend observed in Nature, which wants the complex systems to be robust to random damages, are spotted in the loaded structural schemes (Chapter 7)

    Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey

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    Adversarial attacks and defenses in machine learning and deep neural network have been gaining significant attention due to the rapidly growing applications of deep learning in the Internet and relevant scenarios. This survey provides a comprehensive overview of the recent advancements in the field of adversarial attack and defense techniques, with a focus on deep neural network-based classification models. Specifically, we conduct a comprehensive classification of recent adversarial attack methods and state-of-the-art adversarial defense techniques based on attack principles, and present them in visually appealing tables and tree diagrams. This is based on a rigorous evaluation of the existing works, including an analysis of their strengths and limitations. We also categorize the methods into counter-attack detection and robustness enhancement, with a specific focus on regularization-based methods for enhancing robustness. New avenues of attack are also explored, including search-based, decision-based, drop-based, and physical-world attacks, and a hierarchical classification of the latest defense methods is provided, highlighting the challenges of balancing training costs with performance, maintaining clean accuracy, overcoming the effect of gradient masking, and ensuring method transferability. At last, the lessons learned and open challenges are summarized with future research opportunities recommended.Comment: 46 pages, 21 figure

    The Eternal Network:The Ends and Becomings of Network Culture

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