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1

Constraint networks: Techniques and algorithms. Hoboken, NJ: ISTE/John Wiley, 2009.

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2

Yokoo, Makoto. Distributed Constraint Satisfaction: Foundations of Cooperation in Multi-agent Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001.

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3

Khan, Altaf Hamid. Feedforward neural networks with constrained weights. [s.l.]: typescript, 1996.

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4

Chandramouli, Shyam Sundar. Network Resource Allocation Under Fairness Constraints. [New York, N.Y.?]: [publisher not identified], 2014.

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5

Liu, Kun, Emilia Fridman y Yuanqing Xia. Networked Control Under Communication Constraints. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4230-5.

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6

Zhang, Wen-An, Bo Chen, Haiyu Song y Li Yu. Distributed Fusion Estimation for Sensor Networks with Communication Constraints. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0795-8.

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7

Beate, Lohnert, ed. Social networks: Potentials and constraints : indications from South Africa. Saarbrücken: Verlag für Entwicklungspolitik, 2007.

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8

Liu, Qinyuan, Zidong Wang y Xiao He. Stochastic Control and Filtering over Constrained Communication Networks. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00157-5.

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9

O'Young, D. L. Constrained heat exchanger network : targeting and design. Manchester: UMIST, 1989.

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10

Domenico, Delli Gatti y National Bureau of Economic Research., eds. Financially constrained fluctuations in an evolving network economy. Cambridge, MA: National Bureau of Economic Research, 2008.

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11

Tambouratzis, Tatiani. A neural network implementation of the constraint propagation paradigm in vision. Uxbridge: Brunel University, 1991.

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12

Yüksel, Serdar. Stochastic Networked Control Systems: Stabilization and Optimization under Information Constraints. New York, NY: Springer New York, 2013.

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13

SOA with REST: Principles, patterns & constraints. Upper Saddle River, NJ: Prentice Hall, 2012.

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14

Stapko, Timothy John. Practical embedded security: Building secure resource-constrained systems. Amsterdam: Elsevier/Newnes, 2008.

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15

Pang, Zhong-Hua, Guo-Ping Liu, Donghua Zhou y Dehui Sun. Networked Predictive Control of Systems with Communication Constraints and Cyber Attacks. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-0520-7.

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16

Balakrishnan, Anantaram. Using a hop-constrained model to generate alternative communication network designs. Cambridge, Mass: Sloan School of Management, Massachusetts Institute of Technology, 1990.

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17

Back to monopoly: Opportunities and constraints for public and corporate networks in post-unification Germany. Aldershot, Hants, England: Brookfield, Vt., USA, 1996.

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18

Tetreault, Pierre. An investigation of possible constraints for the definition of the 1988 North American Height Network. Mississauga, Ont: University of Toronto, Erindale Campus, Survey Science, 1987.

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19

Abich, Geancarlo, Luciano Ost y Ricardo Reis. Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Constrained IoT Edge Devices. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-18599-1.

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20

Tennina, Stefano. IEEE 802.15.4 and ZigBee as Enabling Technologies for Low-Power Wireless Systems with Quality-of-Service Constraints. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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21

Social capital and institutional constraints: A comparative analysis of China, Taiwan and the US. Abingdon, Oxon: Routledge, 2012.

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22

Lecoutre, Christophe. Constraint Networks. Wiley & Sons, Incorporated, John, 2010.

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23

Lecoutre, Christophe. Constraint Networks: Targeting Simplicity for Techniques and Algorithms. Wiley & Sons, Incorporated, John, 2013.

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24

Lecoutre, Christophe. Constraint Networks: Targeting Simplicity for Techniques and Algorithms. Wiley & Sons, Incorporated, John, 2013.

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25

Lecoutre, Christophe. Constraint Networks: Targeting Simplicity for Techniques and Algorithms. Wiley & Sons, Incorporated, John, 2010.

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26

Systems Biology: Constraint-Based Reconstruction and Analysis. Cambridge University Press, 2015.

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27

Palsson, Bernhard O. Systems Biology: Constraint-Based Reconstruction and Analysis. Cambridge University Press, 2015.

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28

Coolen, A. C. C., A. Annibale y E. S. Roberts. Ensembles with hard constraints. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0005.

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This chapter introduces random graph ensembles involving hard constraints such as setting a fixed total number of links or fixed degree sequence, including properties of the partition function. It continues on from the previous chapter’s investigation of ensembles with soft-constrained numbers of two-stars (two-step paths) and soft-constrained total number of triangles, but now combined with a hard constraint on the total number of links. This illustrates phase transitions in a mixed-constrained ensemble – which in this case is shown to be a condensation transition, where the network becomes clumped. This is investigated in detail using techniques from statistical mechanics and also looking at the averaged eigenvalue spectrum of the ensemble. These phase transition phenomena have important implications for the design of graph generation algorithms. Although hard constraints can (by force) impose required values of observables, difficult-to-reconcile constraints can lead to graphs being generated with unexpected and unphysical overall topologies.
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29

FitzGerald, David Scott. Refuge beyond Reach. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190874155.001.0001.

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The core of the asylum regime is the principle of non-refoulement that prohibits governments from sending refugees back to their persecutors. Governments attempt to evade this legal obligation to which they have explicitly agreed by manipulating territoriality. A remote control strategy of “extraterritorialization” pushes border control functions hundreds or even thousands of kilometers beyond the state’s territory. Simultaneously, states restrict access to asylum and other rights enjoyed by virtue of presence on a state’s territory, by making micro-distinctions down to the meter at the borderline in a process of “hyper-territorialization.” This study analyzes remote controls since the 1930s in Palestine, North America, Europe, and Australia to identify the origins of different forms of remote control, explain how they work together as a system of control, and establish the conditions that enable or constrain them in practice. It argues that foreign policy issue linkages and transnational advocacy networks promoting a humanitarian norm that is less susceptible to the legal manipulation of territoriality constrains remote controls more than the law itself. The degree of constraint varies widely by the technique of remote control.
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30

Erkut, Erhan R. Distance constrained multi-facility tree network location problems with extensions to planar networks. 1986.

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31

Erl, Thomas, Raj Balasubramanian, Cesare Pautasso y Benjamin Carlyle. SOA with REST Principles, Patterns and Constraints for Building Enterprise Solutions with REST (paperback). Pearson Higher Education & Professional Group, 2017.

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32

Chaudhry, Sohail Siddique. Network location problems with distance constraints. 1985.

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33

Ziegelmann, Dr Mark. Constrained Shortest Paths and Related Problems: Constrained Network Optimization. VDM Verlag Dr. Müller, 2010.

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34

Time-constrained communication in multiple access networks. 1985.

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35

Bianconi, Ginestra. Synchronization, Non-linear Dynamics and Control. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0015.

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This chapter is entirely devoted to characterizing non-linear dynamics on multilayer networks. Special attention is given to recent results on the stability of synchronization that extend the Master Stability Function approach to the multilayer networks scenario. Discontinous synchronization transitions on multiplex networks recently reported in the literature are also discussed, and their application discussed in the context of brain networks. This chapter also presents an overview of the major results regarding pattern formation in multilayer networks, and the proposed characterization of multivariate time series using multiplex visibility graphs. Finally, the chapter discusses several approaches for multiplex network control where the dynamical state of a multiplex network needs to be controlled by eternal signals placed on replica nodes satisfying some structural constraints.
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36

Yu, Li, Bo Chen, Wen-An Zhang y Haiyu Song. Distributed Fusion Estimation for Sensor Networks with Communication Constraints. Springer, 2018.

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37

Modiano, Eytan, Murtaza Zafer y Randal Berry. Energy-Efficient Scheduling under Delay Constraints for Wireless Networks. Springer International Publishing AG, 2012.

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38

Energy-Efficient Scheduling under Delay Constraints for Wireless Networks. Morgan & Claypool Publishers, 2012.

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39

Modiano, Eytan, Murtaza Zafer y Randal Berry. Energy-Efficient Scheduling under Delay Constraints for Wireless Networks. Morgan & Claypool Publishers, 2012.

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40

Yu, Li, Bo Chen, Wen-An Zhang y Haiyu Song. Distributed Fusion Estimation for Sensor Networks with Communication Constraints. Springer London, Limited, 2016.

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41

Yu, Li, Bo Chen, Wen-An Zhang y Haiyu Song. Distributed Fusion Estimation for Sensor Networks with Communication Constraints. Springer, 2016.

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42

Wang, Zidong, Qinyuan Liu y Xiao He. Stochastic Control and Filtering over Constrained Communication Networks. Springer, 2019.

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43

Wang, Zidong, Qinyuan Liu y Xiao He. Stochastic Control and Filtering over Constrained Communication Networks. Springer, 2018.

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44

Fischer, Manuel. Institutions and Policy Networks in Europe. Editado por Jennifer Nicoll Victor, Alexander H. Montgomery y Mark Lubell. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190228217.013.36.

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This chapter reviews the European literature on institutions and policy networks. Institutions provide actors with opportunities and constraints for negotiation and cooperation and thus influence the structure of policy networks. The chapter first presents studies on the influence of country- and sector-level institutions on the structure of policy networks. The respective literature deals with the influence of consensual democracy versus majoritarian democracy, corporatist systems of interest intermediation, multiple levels of governance, degrees of European Union integration, processes of liberalization and democratization, and policy-process-specific venues on policy networks. The chapter then discusses the positions and roles of state actors in policy networks. Due to their formal decision-making power, state actors are either networking targets or play a key role in terms of network integration, brokerage, or network management. The review concludes with a short discussion of commonalities and directions for future research.
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45

Bolouri, Maryam. Network models with generalized upper bound side constraints. 1989.

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46

Cooperative communications for energy constrained wireless networks: Energy efficient communication in sensor networks. LAP Lambert Academic Publishing, 2011.

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47

Tarbouriech, Sophie, Antoine Girard y Laurentiu Hetel. Control Subject to Computational and Communication Constraints: Current Challenges. Springer, 2018.

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48

Tarbouriech, Sophie, Antoine Girard y Laurentiu Hetel. Control Subject to Computational and Communication Constraints: Current Challenges. Springer, 2018.

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49

Coolen, A. C. C., A. Annibale y E. S. Roberts. Applications of random graphs. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0011.

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This chapter reviews graph generation techniques in the context of applications. The first case study is power grids, where proposed strategies to prevent blackouts have been tested on tailored random graphs. The second case study is in social networks. Applications of random graphs to social networks are extremely wide ranging – the particular aspect looked at here is modelling the spread of disease on a social network – and how a particular construction based on projecting from a bipartite graph successfully captures some of the clustering observed in real social networks. The third case study is on null models of food webs, discussing the specific constraints relevant to this application, and the topological features which may contribute to the stability of an ecosystem. The final case study is taken from molecular biology, discussing the importance of unbiased graph sampling when considering if motifs are over-represented in a protein–protein interaction network.
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50

Bruhn, Mark J. Intentionality and Constraint in Conceptual Blending. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190457747.003.0005.

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This chapter proposes a systems-theoretic adjustment to conceptual blending theory with respect to the so-called generic space. In creative conceptualization, the generic space is not an optional by-product of conceptual mappings across previously and otherwise constituted input spaces, but rather their effective cause, and not by selecting for them but by massively constraining against anything not them. As a first approximation of the blend’s targeted or intended meaning, the generic space functions as an indispensable “proto-blend” that sets the parameters and satisfaction conditions for the resulting conceptual network. This underappreciated point is elaborated through case studies of three well-known and increasingly complex creative blends: a sentence-level metaphor (“This surgeon is a butcher!”), an extemporaneous discourse exchange (from the live radio talk show “Loveline”), and a highly iconic lyric poem (Richard Wilbur’s “Piazza di Spagna, Early Morning”).
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