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Articoli di riviste sul tema "Multi-Level Networks"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 2 febbraio 2022

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1

Брусков, А. А. "Failure propagation in interdependent multi-level networks." Informacionno-technologicheskij vestnik, no. 2(28) (June 17, 2021): 76–90. http://dx.doi.org/10.21499/2409-1650-2021-28-2-76-90.

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В этой работе разрабатываются новый подход и алгоритмические инструменты для моделирования и анализа живучести сетей с разнородными узлами, а также рассматривается их применение в космических сетях. Космические сети позволяют совместно использовать ресурсы космических аппаратов на орбите, такие как хранение, обработка и обмен данными. Каждый космический аппарат в сети может иметь различный состав и функциональность подсистем, что приводит к неоднородности узлов. Большинство традиционных анализов живучести сетей предполагают однородность узлов и в результате не подходят для анализа космических

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Raghunath, M. T., and Abhiram Ranade. "Designing Interconnection Networks for Multi-level Packaging." VLSI Design 2, no. 4 (1995): 375–88. http://dx.doi.org/10.1155/1995/57617.

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A central problem in building large scale parallel machines is the design of the interconnection network. Interconnection network design is largely constrained by packaging technology. We start with a generic set of packaging restrictions and evaluate different network organizations under a random traffic model. Our results indicate that customizing the network topology to the packaging constraints is useful. Some of the general principles that arise out of this study are: 1) Making the networks denser at the lower levels of the packaging hierarchy has a significant positive impact on global c

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3

PAPAEFSTATHIOU, IOANNIS. "LOW LEVEL HARDWARE COMPRESSION FOR MULTI-GIGABIT NETWORKS." Journal of Circuits, Systems and Computers 13, no. 06 (2004): 1307–19. http://dx.doi.org/10.1142/s0218126604001969.

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As it has already been proved, link layer compression is very effective when used in packet networks. In particular, packet compression is especially useful when encryption is applied to the network packets. Encrypting the packets causes the data to be random in nature, and thus no compression can be applied after it. It is believed that low level encryption will be applied to the vast majority of Internet Protocol (IP) networks in the near future, and thus a large number of very sophisticated encryption devices have already been manufactured. Based on these facts, we claim that hardware devic

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4

Zappa, Paola, and Garry Robins. "Organizational learning across multi-level networks." Social Networks 44 (January 2016): 295–306. http://dx.doi.org/10.1016/j.socnet.2015.03.003.

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5

Liu, Pengju, Hongzhi Zhang, Wei Lian, and Wangmeng Zuo. "Multi-Level Wavelet Convolutional Neural Networks." IEEE Access 7 (2019): 74973–85. http://dx.doi.org/10.1109/access.2019.2921451.

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6

Park, Seejeen, and Seunghoo Lim. "Are Networks Flat or Vertical?: Developing a Multi-Level Multi-Dimension Network Model." Public Organization Review 18, no. 2 (2017): 223–43. http://dx.doi.org/10.1007/s11115-017-0377-3.

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7

Conway, Max, Claudio Angione, and Pietro Liò. "Iterative Multi Level Calibration of Metabolic Networks." Current Bioinformatics 11, no. 1 (2016): 93–105. http://dx.doi.org/10.2174/1574893611666151203222505.

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8

Papadopoulos, Yannis. "taking stock of multi-level governance networks." European Political Science 4, no. 3 (2005): 316–27. http://dx.doi.org/10.1057/palgrave.eps.2210032.

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9

Madhuri, K., G. Hari Priya, P. Seshu Babu, and K. R. R. Mohan Rao. "Multi-Level Modleach for Wireless Sensor Networks." Indian Journal of Science and Technology 10, no. 25 (2017): 1–5. http://dx.doi.org/10.17485/ijst/2017/v10i25/110666.

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10

Yu, Dongfei, Jianlong Fu, Xinmei Tian, and Tao Mei. "Multi-source Multi-level Attention Networks for Visual Question Answering." ACM Transactions on Multimedia Computing, Communications, and Applications 15, no. 2s (2019): 1–20. http://dx.doi.org/10.1145/3316767.

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11

Cai, Guoyong, Guangrui Lyu, Yuming Lin, and Yimin Wen. "Multi-level Deep Correlative Networks for Multi-modal Sentiment Analysis." Chinese Journal of Electronics 29, no. 6 (2020): 1025–38. http://dx.doi.org/10.1049/cje.2020.09.003.

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12

COEN, DAVID, and MARK THATCHER. "Network Governance and Multi-level Delegation: European Networks of Regulatory Agencies." Journal of Public Policy 28, no. 1 (2008): 49–71. http://dx.doi.org/10.1017/s0143814x08000779.

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ABSTRACTEuropean networks of regulators in industries such as telecommunications, securities, energy and transport have been cited as important examples of the growth of network governance in Europe. Using a principal-agent perspective as a starting point, the article examines why a double delegation to networks of regulators has taken place. It looks at how and why the European Commission, national governments and independent regulatory agencies have driven the creation of networks, their institutional character and their implications for regulatory governance in Europe. It argues that proble

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13

Sauvage, Laurent, Tarik Graba, and Thibault Porteboeuf. "Multi-level formal verification." Journal of Cryptographic Engineering 7, no. 1 (2016): 87–95. http://dx.doi.org/10.1007/s13389-016-0144-3.

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14

Khoury, Mehdi, and Seth Bullock. "Multi-Level Resilience." International Journal of Adaptive, Resilient and Autonomic Systems 5, no. 4 (2014): 34–45. http://dx.doi.org/10.4018/ijaras.2014100103.

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From a multi-disciplinary point of view, research on resilience focuses on robustness, recovery, and adaptive capacity. Robustness quantifies how much damage a system can take before it breaks, whereas recovery refers to the ability of a system to recuperate within limits of time and resources, and adaptability requires a system to be able to structurally reorganize throughout time so as to improve its chances of survival when facing disturbances. In this paper, after discussing examples of models of robustness, recovery and adaptability from different scientific disciplines, is a discussion o

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15

Yin, Lijie, and Nasruddin Hassan. "Multi-level encryption algorithm for user-related information across social networks." Open Physics 16, no. 1 (2018): 989–99. http://dx.doi.org/10.1515/phys-2018-0120.

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AbstractThe traditional RSA information encryption algorithm uses one-dimensional chaotic equations to generate pseudo-random sequences that meet the encryption requirements. This encryption method is too simple and the security performance is poor. A multi-level encryption algorithm for user-related information across social networks is proposed, and a user association model across social networks is constructed to obtain user-related information across social networks. This multi-level chaotic encryption algorithm based on neural network is used to select three different chaotic mapping mode

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16

Zhang, Lihe, Xiang Fang, Hongguang Bo, Tiantian Wang, and Huchuan Lu. "Deep multi-level networks with multi-task learning for saliency detection." Neurocomputing 312 (October 2018): 229–38. http://dx.doi.org/10.1016/j.neucom.2018.05.105.

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17

Kolp, Otto. "A mapping of multi-level problems to multi-dimensional crossbar networks." Communications in Applied Numerical Methods 8, no. 9 (1992): 597–607. http://dx.doi.org/10.1002/cnm.1630080907.

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18

Greening, Phil, and Christine Rutherford. "Disruptions and supply networks: a multi‐level, multi‐theoretical relational perspective." International Journal of Logistics Management 22, no. 1 (2011): 104–26. http://dx.doi.org/10.1108/09574091111127570.

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19

Mu, Guo, and Liu. "A Multi-Scale and Multi-Level Spectral-Spatial Feature Fusion Network for Hyperspectral Image Classification." Remote Sensing 12, no. 1 (2020): 125. http://dx.doi.org/10.3390/rs12010125.

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Extracting spatial and spectral features through deep neural networks has become an effective means of classification of hyperspectral images. However, most networks rarely consider the extraction of multi-scale spatial features and cannot fully integrate spatial and spectral features. In order to solve these problems, this paper proposes a multi-scale and multi-level spectral-spatial feature fusion network (MSSN) for hyperspectral image classification. The network uses the original 3D cube as input data and does not need to use feature engineering. In the MSSN, using different scale neighborh

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20

He, Yulin, Won-Sik Yoon ., and Jai-Hoon Kim . "Multi-level Clustering Architecture for Wireless Sensor Networks." Information Technology Journal 5, no. 1 (2005): 188–91. http://dx.doi.org/10.3923/itj.2006.188.191.

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21

Choi, Sang-Yong, Ik-Seon Kang, Dae-Hyeok Kim, Bong-Nam Noh, and Yong-Min Kim. "Multi-Level Emulation for Malware Distribution Networks Analysis." Journal of the Korea Institute of Information Security and Cryptology 23, no. 6 (2013): 1121–29. http://dx.doi.org/10.13089/jkiisc.2013.23.6.1121.

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22

Soliman, Hisham. "Multi-level power flow for large networks.(Dept.E)." MEJ. Mansoura Engineering Journal 16, no. 1 (2021): 103–13. http://dx.doi.org/10.21608/bfemu.2021.169282.

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23

Liao, Yong, and Qiong Liu. "Multi-Level and Multi-Scale Feature Aggregation Network for Semantic Segmentation in Vehicle-Mounted Scenes." Sensors 21, no. 9 (2021): 3270. http://dx.doi.org/10.3390/s21093270.

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The main challenges of semantic segmentation in vehicle-mounted scenes are object scale variation and trading off model accuracy and efficiency. Lightweight backbone networks for semantic segmentation usually extract single-scale features layer-by-layer only by using a fixed receptive field. Most modern real-time semantic segmentation networks heavily compromise spatial details when encoding semantics, and sacrifice accuracy for speed. Many improving strategies adopt dilated convolution and add a sub-network, in which either intensive computation or redundant parameters are brought. We propose

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24

Cap, Jan-Patrick, Erik Blaich, Holger Kohl, Ariane von Raesfeld, Rainer Harms, and Markus Will. "Multi level network management – A method for managing inter-organizational innovation networks." Journal of Engineering and Technology Management 51 (January 2019): 21–32. http://dx.doi.org/10.1016/j.jengtecman.2019.02.001.

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25

Li, Xiaoming, Guangquan Xu, Sandhya Armoogum, and Honghao Gao. "Consumers Team Detection Model Based on Trust for Multi-Level." Mobile Information Systems 2019 (February 3, 2019): 1–10. http://dx.doi.org/10.1155/2019/4147859.

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Due to rapid advances in technology, social networks have become important platforms for daily communication, product marketing, and information dissemination. Targeted delivery of social network advertisement can considerably improve the efficacy of the advertisement and maximize the profits from it. In this context, managing the specific audience of a social network advertisement and achieving targeted advertisement delivery have been the ultimate goals of the social network advertising sector. Identifying user groups with similar properties is critical to increasing targeted sales. When bot

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26

Zhang, Qiuyue, and Ran Lu. "A Multi-Attention Network for Aspect-Level Sentiment Analysis." Future Internet 11, no. 7 (2019): 157. http://dx.doi.org/10.3390/fi11070157.

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Aspect-level sentiment analysis (ASA) aims at determining the sentiment polarity of specific aspect term with a given sentence. Recent advances in attention mechanisms suggest that attention models are useful in ASA tasks and can help identify focus words. Or combining attention mechanisms with neural networks are also common methods. However, according to the latest research, they often fail to extract text representations efficiently and to achieve interaction between aspect terms and contexts. In order to solve the complete task of ASA, this paper proposes a Multi-Attention Network (MAN) mo

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27

Huang, Mengke, Zhi Liu, Linwei Ye, Xiaofei Zhou, and Yang Wang. "Saliency detection via multi-level integration and multi-scale fusion neural networks." Neurocomputing 364 (October 2019): 310–21. http://dx.doi.org/10.1016/j.neucom.2019.07.054.

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28

GROEN, AARD J. "KNOWLEDGE INTENSIVE ENTREPRENEURSHIP IN NETWORKS: TOWARDS A MULTI-LEVEL/MULTI DIMENSIONAL APPROACH." Journal of Enterprising Culture 13, no. 01 (2005): 69–88. http://dx.doi.org/10.1142/s0218495805000069.

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29

Fuschini, Franco, Marina Barbiroli, Giovanna Calò, et al. "Multi-Level Analysis of On-Chip Optical Wireless Links." Applied Sciences 10, no. 1 (2019): 196. http://dx.doi.org/10.3390/app10010196.

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Networks-on-chip are being regarded as a promising solution to meet the on-going requirement for higher and higher computation capacity. In view of future kilo-cores architectures, electrical wired connections are likely to become inefficient and alternative technologies are being widely investigated. Wireless communications on chip may be therefore leveraged to overcome the bottleneck of physical interconnections. This work deals with wireless networks-on-chip at optical frequencies, which can simplify the network layout and reduce the communication latency, easing the antenna on-chip integra

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30

Kasmi, Ouafae, Amine Baina, and Mostafa Bellafkih. "Multi Level Integrity Management in LTE/LTE-A Networks." Advances in Science, Technology and Engineering Systems Journal 2, no. 3 (2017): 658–68. http://dx.doi.org/10.25046/aj020384.

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31

Liu, Jia-Bao, Mobeen Munir, Amina Yousaf, Asim Naseem, and Khudaija Ayub. "Distance and Adjacency Energies of Multi-Level Wheel Networks." Mathematics 7, no. 1 (2019): 43. http://dx.doi.org/10.3390/math7010043.

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Energies of molecular graphs have various applications in chemistry, polymerization, computer networking and pharmacy. In this paper, we give general closed forms of distance and adjacency energies of generalized wheel networks W n , m . Consequently, we give these results for classical wheel graphs. We also give pictorial dependencies of energies on the involved parameters m ≥ 3 and n .

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32

Arthur, James D. "Partitioned frame networks for multi-level, menu-based interaction." International Journal of Man-Machine Studies 32, no. 6 (1990): 663–72. http://dx.doi.org/10.1016/s0020-7373(05)80106-3.

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33

Börzel, Tanja A., and Karen Heard-Lauréote. "Networks in EU Multi-level Governance: Concepts and Contributions." Journal of Public Policy 29, no. 2 (2009): 135–51. http://dx.doi.org/10.1017/s0143814x09001044.

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AbstractWhile there is broad scholarly agreement that policy-making in the European Union (EU) involves a multitude of public and private actors at different levels of government, there is less agreement whether the EU should be conceptualized as a form of governancebynetworks or governanceinnetworks. This article first examines different concepts of networks. It then sets out multiple functions of networks within the EU policy process. Particular attention is paid to the extent to which networks may provide added value to European integration and improve the quality of governance by effective

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34

Beesley, Lisa. "Multi‐level complexity in the management of knowledge networks." Journal of Knowledge Management 8, no. 3 (2004): 71–100. http://dx.doi.org/10.1108/13673270410541051.

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35

Cao, Jiale, Yanwei Pang, Shengjie Zhao, and Xuelong Li. "High-Level Semantic Networks for Multi-Scale Object Detection." IEEE Transactions on Circuits and Systems for Video Technology 30, no. 10 (2020): 3372–86. http://dx.doi.org/10.1109/tcsvt.2019.2950526.

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36

Durugbo, Christopher. "Collaborative networks: a systematic review and multi-level framework." International Journal of Production Research 54, no. 12 (2015): 3749–76. http://dx.doi.org/10.1080/00207543.2015.1122249.

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37

Tang, Fangcheng, and Youmin Xi. "Exploring dynamic multi-level linkages in inter-organizational networks." Asia Pacific Journal of Management 23, no. 2 (2006): 187–208. http://dx.doi.org/10.1007/s10490-006-7166-9.

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38

Mo, Juan, and Lei Zhang. "Multi-level deep supervised networks for retinal vessel segmentation." International Journal of Computer Assisted Radiology and Surgery 12, no. 12 (2017): 2181–93. http://dx.doi.org/10.1007/s11548-017-1619-0.

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39

Więcek, Dariusz, Igor Michalski, Krzysztof Rzeźniczak, and Dariusz Wypiór. "Multi-RAT Orchestration Method for Heterogeneous Wireless Networks." Applied Sciences 11, no. 18 (2021): 8281. http://dx.doi.org/10.3390/app11188281.

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Currently, energy efficiency (EE) of wireless communication is essential where many wireless networks with different Radio Access Technologies (RATs) coexist together. The RATs can be effectively selected and managed on a higher level to achieve maximum EE and save energy, e.g., save batteries. The approach to wireless traffic steering in mobile networks with a proof-of-concept solution is presented in this paper, owing to the developed high-level multi-RAT (multi-Radio Access Technology) heterogonous network orchestration approach. Based on the high-level network orchestrator, which traces ne

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40

Pirmagomedov, R., and A. A. Ahmed. "Multi-Level Peer-to-Peer Requests Processing in Mobile Networks." Proceedings of Telecommunication Universities 6, no. 2 (2020): 79–86. http://dx.doi.org/10.31854/1813-324x-2020-6-2-79-86.

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The evolution of the Internet of Things application dictates new, more stringent requirements for the speed of transmission and processing of information. To reduce latency, peripheral multi-service access computing is gaining in popularity. This approach allows users to process data closer to their location. However, such solutions may not take into account the specifics of applications based on peer-to-peer user requests (P2P). Subject of study. The article explores the processing time of P2P requests in mobile networks. Method. The applied methodology includes methods of mathematical and si

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41

Lacatus, Corina. "Human rights networks and regulatory stewardship: An analysis of a multi-level network of human rights commissions in the United Kingdom." British Journal of Politics and International Relations 20, no. 4 (2018): 809–26. http://dx.doi.org/10.1177/1369148118798529.

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Regulatory networks are increasingly important actors in multi-level systems of human rights governance. Yet we know little about the role that domestic networks play as intermediaries or about the strategies they use to integrate sub-national human rights institutions to ensure compliance at the local level. We draw on the theoretical literature on orchestration to conceptualise network governance and propose a new intermediary for the human rights governance, the multi-level network, which operates inside one country. We apply this theoretical model to the case of a multi-level network opera

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42

Choi, Myung Geol, Eunjung Ju, Jung-Woo Chang, Jehee Lee, and Young J. Kim. "Linkless Octree Using Multi-Level Perfect Hashing." Computer Graphics Forum 28, no. 7 (2009): 1773–80. http://dx.doi.org/10.1111/j.1467-8659.2009.01554.x.

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43

Gançarski, Pierre, and Cédric Wemmert. "Collaborative multi-step mono-level multi-strategy classification." Multimedia Tools and Applications 35, no. 1 (2007): 1–27. http://dx.doi.org/10.1007/s11042-007-0115-x.

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44

Durresi, Arjan, Ping Zhang, Mimoza Durresi, and Leonard Barolli. "Architecture for Mobile Heterogeneous Multi Domain Networks." Mobile Information Systems 6, no. 1 (2010): 49–63. http://dx.doi.org/10.1155/2010/907109.

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Multi domain networks can be used in several scenarios including military, enterprize networks, emergency networks and many other cases. In such networks, each domain might be under its own administration. Therefore, the cooperation among domains is conditioned by individual domain policies regarding sharing information, such as network topology, connectivity, mobility, security, various service availability and so on. We propose a new architecture for Heterogeneous Multi Domain (HMD) networks, in which one the operations are subject to specific domain policies. We propose a hierarchical archi

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Xie, Yu, Chuanyu Yao, Maoguo Gong, Cheng Chen, and A. K. Qin. "Graph convolutional networks with multi-level coarsening for graph classification." Knowledge-Based Systems 194 (April 2020): 105578. http://dx.doi.org/10.1016/j.knosys.2020.105578.

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Zhang, Weiyu, Bin Wu, and Yang Liu. "Cluster-level trust prediction based on multi-modal social networks." Neurocomputing 210 (October 2016): 206–16. http://dx.doi.org/10.1016/j.neucom.2016.01.108.

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Qiang, Yan, Juanjuan Zhao, Yongxing Liu, and Xiaolong Zhang. "A Multi-Level Data Fusion Algorithm for Wireless Sensor Networks." Sensor Letters 12, no. 1 (2014): 123–28. http://dx.doi.org/10.1166/sl.2014.3235.

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Hosseinabadi, Mina Taheri, and Nirwan Ansari. "Multi-Power-Level Energy Saving Management for Passive Optical Networks." Journal of Optical Communications and Networking 6, no. 11 (2014): 965. http://dx.doi.org/10.1364/jocn.6.000965.

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Choumane, Ali, and Ali Harkous. "Multi-level fuzzy overlapping community detection algorithm for weighted networks." International Journal of Data Science 4, no. 4 (2019): 351. http://dx.doi.org/10.1504/ijds.2019.10026918.

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Choumane, Ali, and Ali Harkous. "Multi-level fuzzy overlapping community detection algorithm for weighted networks." International Journal of Data Science 4, no. 4 (2019): 351. http://dx.doi.org/10.1504/ijds.2019.105259.

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