Relevant bibliographies by topics / Federated systems

Academic literature on the topic 'Federated systems'

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Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Federated systems"

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Conrad, S., W. Hasselbring, U. Hohenstein, R. D. Kutsche, M. Roantree, G. Saake, and F. Saltor. "Engineering federated information systems." ACM SIGMOD Record 28, no. 3 (September 1999): 9–11. http://dx.doi.org/10.1145/333607.333608.

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Li, Yanbin, Yue Li, Huanliang Xu, and Shougang Ren. "An Adaptive Communication-Efficient Federated Learning to Resist Gradient-Based Reconstruction Attacks." Security and Communication Networks 2021 (April 22, 2021): 1–16. http://dx.doi.org/10.1155/2021/9919030.

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The widely deployed devices in Internet of Things (IoT) have opened up a large amount of IoT data. Recently, federated learning emerges as a promising solution aiming to protect user privacy on IoT devices by training a globally shared model. However, the devices in the complex IoT environments pose great challenge to federate learning, which is vulnerable to gradient-based reconstruction attacks. In this paper, we discuss the relationships between the security of federated learning model and optimization technologies of decreasing communication overhead comprehensively. To promote the efficiency and security, we propose a defence strategy of federated learning which is suitable to resource-constrained IoT devices. The adaptive communication strategy is to adjust the frequency and parameter compression by analysing the training loss to ensure the security of the model. The experiments show the efficiency of our proposed method to decrease communication overhead, while preventing privacy data leakage.
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Jajodia, Sushil, and Duminda Wijesekera. "Security in Federated Database Systems." Information Security Technical Report 6, no. 2 (June 2001): 69–79. http://dx.doi.org/10.1016/s1363-4127(01)00208-4.

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Lyu, Weiwei, Xianghong Cheng, and Jinling Wang. "Adaptive Federated IMM Filter for AUV Integrated Navigation Systems." Sensors 20, no. 23 (November 28, 2020): 6806. http://dx.doi.org/10.3390/s20236806.

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High accuracy and reliable navigation in the underwater environment is very critical for the operations of autonomous underwater vehicles (AUVs). This paper proposes an adaptive federated interacting multiple model (IMM) filter, which combines adaptive federated filter and IMM algorithm for AUV in complex underwater environments. Based on the performance of each local system, the information sharing coefficient of the adaptive federated IMM filter is adaptively determined. Meanwhile, the adaptive federated IMM filter designs different models for each local system. When the external disturbances change, the model of each local system can switch in real-time. Furthermore, an AUV integrated navigation system model is constructed, which includes the dynamic model of the system error and the measurement models of strapdown inertial navigation system/Doppler velocity log (SINS/DVL) and SINS/terrain aided navigation (SINS/TAN). The integrated navigation experiments demonstrate that the proposed filter can dramatically improve the accuracy and reliability of the integrated navigation system. Additionally, it has obvious advantages compared with the federated Kalman filter and the adaptive federated Kalman filter.
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Shokouhi, Milad, and Luo Si. "Federated Search." Foundations and Trends® in Information Retrieval 5, no. 1 (2011): 1–102. http://dx.doi.org/10.1561/1500000010.

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L’Amrani, Hasnae, Younès EL Bouzekri EL Idrissi, and Rachida Ajhoun. "Identity Management Systems: Techno-Semantic Interoperability for Heterogeneous Federated Systems." Computer and Information Science 11, no. 3 (July 29, 2018): 102. http://dx.doi.org/10.5539/cis.v11n3p102.

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The identity management domain is a huge research domain. The federated systems proved on theirs legibility to solve a several digital identity issues. However, the problem of interoperability between federations is the researcher first issue. The researchers final goal is creating a federation of federations which is a large meta-system composed of several different federation systems. The previous researchers’ technical interoperability approach solved a part of the above-mentioned issue. However, there are some-others problems in the communication process between federated systems. In this work, the researcher target the semantic interoperability as a solution to solve the exchange of attribute issue among heterogeneous federated systems, because there is a significant need of managing the users’ attributes coming from different federations. Therefore, the researcher proposed a semantic layer to enhance the previous technical approach with the aim to guarantee the exchange of attribute that has the same semantic signification but a different representation, all that based on a mapping and matching between different anthologies. This approach will be applied to the academic domain as the researcher application domain.
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L'Amrani, Hasnae, Younès El Bouzekri El Idrissi, and Rachida Ajhoun. "Technical Interoperability to Solve Cross-Domain Issues Among Federation Systems." International Journal of Smart Security Technologies 7, no. 1 (January 2020): 21–40. http://dx.doi.org/10.4018/ijsst.2020010102.

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Digital identity management with the metamorphosis of web services enforces new security challenges. A set of identity management systems exists to deal with these identities, alongside the goal of improving user experience and gain secure access. Nowadays, one faces a large number of heterogeneous identity management approaches. This study treated several identity management systems. The federated system makes proof of it eligibility for the identity management. Thus, the researcher interest is on the federated model. Since it consists of the distribution of digital identity between different security domains. The base of security domains is a trust agreement between the entities in communication. Federated identity management faces the problem of interoperability between heterogeneous federated systems. This study is an approach of a technical interoperability between the federations. The authors propose an approach that will permit inter-operation and exchange identity information among heterogeneous federations.
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Lübke, Daniel, and Jorge Marx Gómez. "Developing and Customizing Federated ERP Systems." International Journal of Enterprise Information Systems 5, no. 3 (July 2009): 47–59. http://dx.doi.org/10.4018/jeis.2009070104.

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Conrad, S., B. Eaglestone, W. Hasselbring, M. Roantree, M. Schöhoff, M. Strässler, M. Vermeer, and F. Saltor. "Research issues in federated database systems." ACM SIGMOD Record 26, no. 4 (December 1997): 54–56. http://dx.doi.org/10.1145/271074.271089.

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Thuraisingham, Bhavani. "Security issues for federated database systems." Computers & Security 13, no. 6 (1994): 509–25. http://dx.doi.org/10.1016/0167-4048(91)90139-5.

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Dissertations / Theses on the topic "Federated systems"

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Fernandez, George, and gfernandez@rmit edu au. "A federated approach to enterprise integration." Swinburne University of Technology, 2006. http://adt.lib.swin.edu.au./public/adt-VSWT20060502.113336.

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In order to remain competitive, the integration of their information systems is an imperative for many large organisations. Applications that originally have been developed independently are now required to interoperate to support new or different functions of the enterprise. Although the mechanisms for application interoperation exist provided by the technology, due to the sheer number and complexity of the running systems, integration solutions � centralised or distributed�appropriate at the local level do not translate successfully to the whole enterprise. Centralised integration approaches often satisfy only some of the integration requirements, they are very expensive, and are fraught with danger since they imply an �all or nothing� approach. Distributed approaches, on the other hand, suffer from complexity and scalability problems as the number of system interfaces to be implemented and the number of execution-time invocations grows with the number of component applications. This dissertation makes a contribution to the field of Enterprise Application Integration (EAI) within the framework of distributed systems technology. Based on real-life case studies experience, we present here a federated approach that controls the size and complexity of the integration effort by reusing existing systems as much as possible and reducing the number of interacting applications. Only selected local elements are exposed to the organisational milieu, and a consistent supporting infrastructure is provided to make systems interactions possible. Our approach provides a flexible and scalable strategy to enterprise integration, avoiding the shortcomings of traditional approaches. We respect existing organisational structures, and demonstrate how appropriate federation infrastructure and protocols enable the interoperation of existing systems. The three main facets of enterprise knowledge are systematically incorporated into the integration effort: a) by the use of domain ontologies to support data integration; b) by the development of a methodology to include business rules; and c) by the development of FEW, a federated workflow model to implement the business processes of the organisation.
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Nizamani, Hyder Ali. "Modelling architectures of federated identity management systems." Thesis, University of Leicester, 2012. http://hdl.handle.net/2381/10180.

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Today’s dynamic and scalable collaborative systems demand not only to deal with functional but also some non-functional (e.g., security) requirements. For a secure inter-organisational collaboration scenario, Federated Identity Management systems (FIMs) provide a suitable mechanism to deal with access control. FIMs enable users of an organisation to access resources (or services) of the other trusted organisations in a secure and seamless way. More precisely, FIMs allow cross-domain user authentication to enable access control across organisations under the concept known as Circle of Trust (CoT). Patterns of FIMs emerged as recurring CoT scenarios due to the fact that each of these patterns has different security requirements. More importantly, organisations may join up or leave the CoT during the development life-cycle. Such a change in a FIM system may have an impact on its security requirements. Therefore, it is important to formally describe architectural and reconfiguration aspects of FIMs by considering their patterns. To this purpose, we propose • two UML models for FIMs where one model uses the standard UML notations to describe architectural aspects of FIMs while the other uses the UML profile in [33] to describe those aspects of FIMs together with their reconfigurations • a formal model for FIMs in ADR (Architectural Design Rewriting) to characterise their patterns by describing an architectural style together with style-preserving reconfigurations. We also study the adequacy of UML to describe architectural aspects of systems and compare it with ADR. Our comparison develops through the modelling of architectural and reconfiguration aspects of FIMs. In ADR, these aspects of FIMs are suitably represented through style-consistent (graphical) designs in terms of ADR productions. On the other hand, UML has limitations in expressing constraints over complex associations; also, UML seems to provide unsatisfactory support for presenting architectural styles in a general way. Overall, our investigation shows that UML has some drawbacks due to the complexity of diagrams, their proliferation, and the lack of a precise semantics that consistently relates them. ADR gives precise and simpler specifications for architectural design.
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Dzikiewicz, Joseph. "Cyrano : a meta model for federated database systems /." Diss., This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-11082006-133632/.

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Sayar, Ahmet. "High performance, federated, service-oriented geographic information systems." [Bloomington, Ind.] : Indiana University, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3344771.

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Thesis (Ph.D.)--Indiana University, Dept. of Computer Science, 2009.
Title from PDF t.p. (viewed on Oct. 8, 2009). Source: Dissertation Abstracts International, Volume: 70-02, Section: B, page: 1135. Adviser: Geoffrey C. Fox.
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Gupta, Ankush M. "Cross-engine query execution in federated database systems." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106013.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 47-48).
Duggan et al.have created a reference implementation of the BigDAWG system: a new architecture for future Big Data applications, guided by the philosophy that "one size does not fit all." Such applications not only call for large-scale analytics, but also for real-time streaming support, smaller analytics at interactive speeds, data visualization, and cross-storage-system queries. The importance and effectiveness of such a system has been demonstrated in a hospital application using data from an intensive care unit (ICU). In this report, we implement and evaluate a concrete version of a cross-system Query Executor and its interface with a cross-system Query Planner. In particular, we focus on cross-engine shuffle joins within the BigDAWG system.
by Ankush M. Gupta.
M. Eng.
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Smith, Arthur M. D. "A Study on Federated Learning Systems in Healthcare." Youngstown State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1629188090536169.

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Carlsson, Robert. "Privacy-Preserved Federated Learning : A survey of applicable machine learning algorithms in a federated environment." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-424383.

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There is a potential in the field of medicine and finance of doing collaborative machine learning. These areas gather data which can be used for developing machine learning models that could predict all from sickness in patients to acts of economical crime like fraud. The problem that exists is that the data collected is mostly of confidential nature and should be handled with precaution. This makes the standard way of doing machine learning - gather data at one centralized server - unwanted to achieve. The safety of the data have to be taken into account. In this project we will explore the Federated learning approach of ”bringing the code to the data, instead of data to the code”. It is a decentralized way of doing machine learning where models are trained on connected devices and data is never shared. Keeping the data privacypreserved.
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Ince, Levent. "The role of expert systems in federated distributed multi-database systems/." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA377679.

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D'Silva, Albert A. Allwyn. "Dynamic evolution of integrated schemas for federated objectbase systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ32090.pdf.

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Popfinger, Christopher [Verfasser]. "Enhanced active databases for federated information systems / Christopher Popfinger." München : GRIN Verlag, 2007. http://d-nb.info/1181206952/34.

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Books on the topic "Federated systems"

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Rehman, Muhammad Habib ur, and Mohamed Medhat Gaber, eds. Federated Learning Systems. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70604-3.

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International Workshop on Engineering Federated Information Systems (4th 2001 Berlin, Germany). Engineering federated information systems: Proceedings of the 4th workshop, EFIS 2001, Oct 9-10, 2001, Berlin (Germany). Berlin: Akademische Verlagsgesellschaft Aka, 2001.

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International Workshop on Engineering Federated Information Systems (3rd 2000 Dublin, Ireland). Engineering federated information systems: Proceedings of the 3rd workshop, EFIS 2000, June 19-20, 2000, Dublin (Ireland). Amsterdam: IOS Press, 2000.

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Leney, Alice. A fresh start to recycling in the FSM: Improving container deposit systems in the Federated States of Micronesia. Fiji]: United Nations Development Programme, 2005.

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Dowling, Jim. Distributed Applications and Interoperable Systems: 13th IFIP WG 6.1 International Conference, DAIS 2013, Held as Part of the 8th International Federated Conference on Distributed Computing Techniques, DisCoTec 2013, Florence, Italy, June 3-5, 2013. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Nicola, Rocco. Coordination Models and Languages: 15th International Conference, COORDINATION 2013, Held as Part of the 8th International Federated Conference on Distributed Computing Techniques, DisCoTec 2013, Florence, Italy, June 3-5, 2013. Proceedings. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Workshop on I/O in Parallel and Distributed Systems (4th 1996 Philadelphia, Pa.). Proceedings of the IOPADS, Fourth Annual Workshop on I/O in Parallel and Distributed Systems: Part of the Federated Computing Research Conference, May 27, 1996, Philadelphia, PA. New York: Association for Computing Machinery, 1996.

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Workshop on I/O in Parallel and Distributed Systems (6th 1999 Atlanta, Ga.). Proceedings of the IOPADS, Sixth Workshop on I/O in Parallel and Distributed Systems: Part of FCRC '99 : the ACM Federated Computing Research Conference : May 5, 1999, Atlanta, Georgia. New York: Association for Computing Machinery, 1999.

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Hershey, Rachel Riemann. The Federated GIS: An accessible geographic information system. London: London School of Economics and Political Science, Geographical Information Research Laboratory, 1991.

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M, Davis Jeffrey. Federated States of Micronesia: Reform of the tax system. [Washington, D.C.]: International Monetary Fund, Fiscal Affairs Dept., 1994.

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Book chapters on the topic "Federated systems"

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Dirir, Ahmed Mukhtar, Khaled Salah, and Davor Svetinovic. "Towards Blockchain-Based Fair and Trustworthy Federated Learning Systems." In Federated Learning Systems, 157–71. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70604-3_7.

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Wei, Kang, Jun Li, Chuan Ma, Ming Ding, and H. Vincent Poor. "Differentially Private Federated Learning: Algorithm, Analysis and Optimization." In Federated Learning Systems, 51–78. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70604-3_3.

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Ziller, Alexander, Andrew Trask, Antonio Lopardo, Benjamin Szymkow, Bobby Wagner, Emma Bluemke, Jean-Mickael Nounahon, et al. "PySyft: A Library for Easy Federated Learning." In Federated Learning Systems, 111–39. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70604-3_5.

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Enthoven, David, and Zaid Al-Ars. "An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies." In Federated Learning Systems, 173–96. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70604-3_8.

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Thapa, Chandra, M. A. P. Chamikara, and Seyit A. Camtepe. "Advancements of Federated Learning Towards Privacy Preservation: From Federated Learning to Split Learning." In Federated Learning Systems, 79–109. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70604-3_4.

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Farooq, Ali, Ali Feizollah, and Muhammad Habib ur Rehman. "Federated Learning Research: Trends and Bibliometric Analysis." In Federated Learning Systems, 1–19. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70604-3_1.

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Kumar, Yogesh, and Ruchi Singla. "Federated Learning Systems for Healthcare: Perspective and Recent Progress." In Federated Learning Systems, 141–56. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70604-3_6.

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Briggs, Christopher, Zhong Fan, and Peter Andras. "A Review of Privacy-Preserving Federated Learning for the Internet-of-Things." In Federated Learning Systems, 21–50. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70604-3_2.

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Yang, Liu, Ben Tan, Vincent W. Zheng, Kai Chen, and Qiang Yang. "Federated Recommendation Systems." In Lecture Notes in Computer Science, 225–39. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63076-8_16.

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Papahristos, S., and W. A. Gray. "Federated case environment." In Advanced Information Systems Engineering, 461–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/3-540-54059-8_99.

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Conference papers on the topic "Federated systems"

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Qiang, Yang. "Federated Recommendation Systems." In 2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019. http://dx.doi.org/10.1109/bigdata47090.2019.9005952.

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Biran, Yahav, George Collins, Syed Azam, and Joel Dubow. "Federated Cloud computing as System of Systems." In 2017 International Conference on Computing, Networking and Communications (ICNC). IEEE, 2017. http://dx.doi.org/10.1109/iccnc.2017.7876217.

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Wei, Xiguang, Quan Li, Yang Liu, Han Yu, Tianjian Chen, and Qiang Yang. "Multi-Agent Visualization for Explaining Federated Learning." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/960.

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As an alternative decentralized training approach, Federated Learning enables distributed agents to collaboratively learn a machine learning model while keeping personal/private information on local devices. However, one significant issue of this framework is the lack of transparency, thus obscuring understanding of the working mechanism of Federated Learning systems. This paper proposes a multi-agent visualization system that illustrates what is Federated Learning and how it supports multi-agents coordination. To be specific, it allows users to participate in the Federated Learning empowered multi-agent coordination. The input and output of Federated Learning are visualized simultaneously, which provides an intuitive explanation of Federated Learning for users in order to help them gain deeper understanding of the technology.
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Catuogno, Luigi, and Clemente Galdi. "Interoperability between Federated Authentication Systems." In 2014 Eighth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS). IEEE, 2014. http://dx.doi.org/10.1109/imis.2014.71.

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De Capitani di Vimercati, Sabrina, and Pierangela Samarati. "Access control in federated systems." In the 1996 workshop. New York, New York, USA: ACM Press, 1996. http://dx.doi.org/10.1145/304851.304871.

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Zhang, Hongyi, Jan Bosch, and Helena Holmstrom Olsson. "Federated Learning Systems: Architecture Alternatives." In 2020 27th Asia-Pacific Software Engineering Conference (APSEC). IEEE, 2020. http://dx.doi.org/10.1109/apsec51365.2020.00047.

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Levin, Anna, Konstantin Dorfman, and Sylvain Afchain. "Diving into federated network." In SYSTOR'17: International Systems and Storage Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3078468.3078494.

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Levin, Anna, and Philippe Massonet. "Enabling federated cloud networking." In SYSTOR 2015: International Conference on Systems and Storage. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2757667.2778189.

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Kewley, Robert, James Cook, Niki Goerger, Dale Henderson, and Edward Teague. "Federated simulations for systems of systems integration." In 2008 Winter Simulation Conference (WSC). IEEE, 2008. http://dx.doi.org/10.1109/wsc.2008.4736181.

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Su, Tianqi, Meiqi Wang, and Zhongfeng Wang. "Federated Regularization Learning: an Accurate and Safe Method for Federated Learning." In 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS). IEEE, 2021. http://dx.doi.org/10.1109/aicas51828.2021.9458510.

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Reports on the topic "Federated systems"

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Lentini, J., C. Everhart, D. Ellard, R. Tewari, and M. Naik. Requirements for Federated File Systems. RFC Editor, January 2010. http://dx.doi.org/10.17487/rfc5716.

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Lentini, J., and R. Tewari. Administration Protocol for Federated File Systems. Edited by C. Lever. RFC Editor, March 2015. http://dx.doi.org/10.17487/rfc7533.

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Lentini, J., and R. Tewari. Namespace Database (NSDB) Protocol for Federated File Systems. Edited by C. Lever. RFC Editor, March 2015. http://dx.doi.org/10.17487/rfc7532.

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African Open Science Platform Part 1: Landscape Study. Academy of Science of South Africa (ASSAf), 2019. http://dx.doi.org/10.17159/assaf.2019/0047.

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This report maps the African landscape of Open Science – with a focus on Open Data as a sub-set of Open Science. Data to inform the landscape study were collected through a variety of methods, including surveys, desk research, engagement with a community of practice, networking with stakeholders, participation in conferences, case study presentations, and workshops hosted. Although the majority of African countries (35 of 54) demonstrates commitment to science through its investment in research and development (R&D), academies of science, ministries of science and technology, policies, recognition of research, and participation in the Science Granting Councils Initiative (SGCI), the following countries demonstrate the highest commitment and political willingness to invest in science: Botswana, Ethiopia, Kenya, Senegal, South Africa, Tanzania, and Uganda. In addition to existing policies in Science, Technology and Innovation (STI), the following countries have made progress towards Open Data policies: Botswana, Kenya, Madagascar, Mauritius, South Africa and Uganda. Only two African countries (Kenya and South Africa) at this stage contribute 0.8% of its GDP (Gross Domestic Product) to R&D (Research and Development), which is the closest to the AU’s (African Union’s) suggested 1%. Countries such as Lesotho and Madagascar ranked as 0%, while the R&D expenditure for 24 African countries is unknown. In addition to this, science globally has become fully dependent on stable ICT (Information and Communication Technologies) infrastructure, which includes connectivity/bandwidth, high performance computing facilities and data services. This is especially applicable since countries globally are finding themselves in the midst of the 4th Industrial Revolution (4IR), which is not only “about” data, but which “is” data. According to an article1 by Alan Marcus (2015) (Senior Director, Head of Information Technology and Telecommunications Industries, World Economic Forum), “At its core, data represents a post-industrial opportunity. Its uses have unprecedented complexity, velocity and global reach. As digital communications become ubiquitous, data will rule in a world where nearly everyone and everything is connected in real time. That will require a highly reliable, secure and available infrastructure at its core, and innovation at the edge.” Every industry is affected as part of this revolution – also science. An important component of the digital transformation is “trust” – people must be able to trust that governments and all other industries (including the science sector), adequately handle and protect their data. This requires accountability on a global level, and digital industries must embrace the change and go for a higher standard of protection. “This will reassure consumers and citizens, benefitting the whole digital economy”, says Marcus. A stable and secure information and communication technologies (ICT) infrastructure – currently provided by the National Research and Education Networks (NRENs) – is key to advance collaboration in science. The AfricaConnect2 project (AfricaConnect (2012–2014) and AfricaConnect2 (2016–2018)) through establishing connectivity between National Research and Education Networks (NRENs), is planning to roll out AfricaConnect3 by the end of 2019. The concern however is that selected African governments (with the exception of a few countries such as South Africa, Mozambique, Ethiopia and others) have low awareness of the impact the Internet has today on all societal levels, how much ICT (and the 4th Industrial Revolution) have affected research, and the added value an NREN can bring to higher education and research in addressing the respective needs, which is far more complex than simply providing connectivity. Apart from more commitment and investment in R&D, African governments – to become and remain part of the 4th Industrial Revolution – have no option other than to acknowledge and commit to the role NRENs play in advancing science towards addressing the SDG (Sustainable Development Goals). For successful collaboration and direction, it is fundamental that policies within one country are aligned with one another. Alignment on continental level is crucial for the future Pan-African African Open Science Platform to be successful. Both the HIPSSA ((Harmonization of ICT Policies in Sub-Saharan Africa)3 project and WATRA (the West Africa Telecommunications Regulators Assembly)4, have made progress towards the regulation of the telecom sector, and in particular of bottlenecks which curb the development of competition among ISPs. A study under HIPSSA identified potential bottlenecks in access at an affordable price to the international capacity of submarine cables and suggested means and tools used by regulators to remedy them. Work on the recommended measures and making them operational continues in collaboration with WATRA. In addition to sufficient bandwidth and connectivity, high-performance computing facilities and services in support of data sharing are also required. The South African National Integrated Cyberinfrastructure System5 (NICIS) has made great progress in planning and setting up a cyberinfrastructure ecosystem in support of collaborative science and data sharing. The regional Southern African Development Community6 (SADC) Cyber-infrastructure Framework provides a valuable roadmap towards high-speed Internet, developing human capacity and skills in ICT technologies, high- performance computing and more. The following countries have been identified as having high-performance computing facilities, some as a result of the Square Kilometre Array7 (SKA) partnership: Botswana, Ghana, Kenya, Madagascar, Mozambique, Mauritius, Namibia, South Africa, Tunisia, and Zambia. More and more NRENs – especially the Level 6 NRENs 8 (Algeria, Egypt, Kenya, South Africa, and recently Zambia) – are exploring offering additional services; also in support of data sharing and transfer. The following NRENs already allow for running data-intensive applications and sharing of high-end computing assets, bio-modelling and computation on high-performance/ supercomputers: KENET (Kenya), TENET (South Africa), RENU (Uganda), ZAMREN (Zambia), EUN (Egypt) and ARN (Algeria). Fifteen higher education training institutions from eight African countries (Botswana, Benin, Kenya, Nigeria, Rwanda, South Africa, Sudan, and Tanzania) have been identified as offering formal courses on data science. In addition to formal degrees, a number of international short courses have been developed and free international online courses are also available as an option to build capacity and integrate as part of curricula. The small number of higher education or research intensive institutions offering data science is however insufficient, and there is a desperate need for more training in data science. The CODATA-RDA Schools of Research Data Science aim at addressing the continental need for foundational data skills across all disciplines, along with training conducted by The Carpentries 9 programme (specifically Data Carpentry 10 ). Thus far, CODATA-RDA schools in collaboration with AOSP, integrating content from Data Carpentry, were presented in Rwanda (in 2018), and during17-29 June 2019, in Ethiopia. Awareness regarding Open Science (including Open Data) is evident through the 12 Open Science-related Open Access/Open Data/Open Science declarations and agreements endorsed or signed by African governments; 200 Open Access journals from Africa registered on the Directory of Open Access Journals (DOAJ); 174 Open Access institutional research repositories registered on openDOAR (Directory of Open Access Repositories); 33 Open Access/Open Science policies registered on ROARMAP (Registry of Open Access Repository Mandates and Policies); 24 data repositories registered with the Registry of Data Repositories (re3data.org) (although the pilot project identified 66 research data repositories); and one data repository assigned the CoreTrustSeal. Although this is a start, far more needs to be done to align African data curation and research practices with global standards. Funding to conduct research remains a challenge. African researchers mostly fund their own research, and there are little incentives for them to make their research and accompanying data sets openly accessible. Funding and peer recognition, along with an enabling research environment conducive for research, are regarded as major incentives. The landscape report concludes with a number of concerns towards sharing research data openly, as well as challenges in terms of Open Data policy, ICT infrastructure supportive of data sharing, capacity building, lack of skills, and the need for incentives. Although great progress has been made in terms of Open Science and Open Data practices, more awareness needs to be created and further advocacy efforts are required for buy-in from African governments. A federated African Open Science Platform (AOSP) will not only encourage more collaboration among researchers in addressing the SDGs, but it will also benefit the many stakeholders identified as part of the pilot phase. The time is now, for governments in Africa, to acknowledge the important role of science in general, but specifically Open Science and Open Data, through developing and aligning the relevant policies, investing in an ICT infrastructure conducive for data sharing through committing funding to making NRENs financially sustainable, incentivising open research practices by scientists, and creating opportunities for more scientists and stakeholders across all disciplines to be trained in data management.
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