Academic literature on the topic 'Parameters of network'
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Journal articles on the topic "Parameters of network"
PELLEGRINI, Lilla, Monica LEBA, and Alexandru IOVANOVICI. "CHARACTERIZATION OF URBAN TRANSPORTATION NETWORKS USING NETWORK MOTIFS." Acta Electrotechnica et Informatica 20, no. 4 (January 21, 2020): 3–9. http://dx.doi.org/10.15546/aeei-2020-0019.
Full textRomanov, Oleksandr, Ivan Saychenko, Anton Marinov, and Serhii Skolets. "RESEARCH OF SDN NETWORK PERFORMANCE PARAMETERS USING MININET NETWORK EMULATOR." Information and Telecommunication Sciences, no. 1 (June 29, 2021): 24–32. http://dx.doi.org/10.20535/2411-2976.12021.24-32.
Full textZhou, Yang. "Research on Network Control Based on QoS of the Network." Advanced Materials Research 989-994 (July 2014): 4265–68. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4265.
Full textLIU, WEI-YI, and KUN YUE. "BAYESIAN NETWORK WITH INTERVAL PROBABILITY PARAMETERS." International Journal on Artificial Intelligence Tools 20, no. 05 (October 2011): 911–39. http://dx.doi.org/10.1142/s0218213011000449.
Full textWang, Jia Jia, Yong Xiang Zhang, Wei Gong Zhang, and Hua Zhang Zhou. "Measuring Parameters of SpaceWire Network." Advanced Materials Research 159 (December 2010): 522–26. http://dx.doi.org/10.4028/www.scientific.net/amr.159.522.
Full textBesfat, Henok M., Zelalem Hailu Gebeyehu, and Sudhir K. Routray. "Estimation of Parameters of 5G Network Dimensioning." International Journal of Electronics, Communications, and Measurement Engineering 10, no. 2 (July 2021): 15–32. http://dx.doi.org/10.4018/ijecme.2021070102.
Full textChechin, G. V. "Select main parameters of Internet traffic exchange network." Issues of radio electronics 49, no. 5 (July 5, 2020): 10–16. http://dx.doi.org/10.21778/2218-5453-2020-5-10-16.
Full textBuranova, M., and R. Latypov. "MPLS Network Parameters Analysis when Changing the Topology." Proceedings of Telecommunication Universities 5, no. 3 (2019): 6–12. http://dx.doi.org/10.31854/1813-324x-2019-5-3-6-12.
Full textMa, Yifang, and Zhiming Zheng. "Extracting principal parameters of complex networks." International Journal of Modern Physics C 26, no. 09 (June 22, 2015): 1550103. http://dx.doi.org/10.1142/s012918311550103x.
Full textNITTA, TOHRU. "THE UNIQUENESS THEOREM FOR COMPLEX-VALUED NEURAL NETWORKS WITH THRESHOLD PARAMETERS AND THE REDUNDANCY OF THE PARAMETERS." International Journal of Neural Systems 18, no. 02 (April 2008): 123–34. http://dx.doi.org/10.1142/s0129065708001439.
Full textDissertations / Theses on the topic "Parameters of network"
Åkesson, Emma. "Information visualization of network parameters in private cellular network solutions." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280858.
Full textInom de kommande åren förväntas industriföretag genomgå en stor transformation, i samband med att sakernas internet (engelskans Internet of Things, IoT) når utbredd användning. En viktig möjliggörare bakom denna transformation, känd som Industri 4.0, är den 5:e generationens mobilnät (5G). Genom privatägda mobilnät kommer företag att kunna använda 5G teknologin till att skräddarsy sina nätverk för att tillgodose de egna behoven gällande säkerhet, tillförlitlighet och kvalitet. Trots att mycket av 5G teknologin redan är på plats, har få ansträngningar gjorts för att hjälpa företag förstå och optimera värdet som denna nya lösning medför. Ett sätt som kan göra 5G mer lättförståeligt är genom informationsvisualisering av dess data. Dashboards är idag det mest använda verktyget för att bearbeta data i organisationer. Denna studie ämnade därför att undersöka fördelarna och nackdelarna med informationsvisualisering av data från ett privat 5G-nät i ett sådant verktyg. Ett stort antal kommersiella dashboards för nätverksprestationshantering granskades i förhållande till forskning inom området för effektiv design av dashboards, och en prototyp utvecklades och utvärderades med sju experter inom användarupplevelse. Resultaten från expertgranskningen tyder på att användningen av informationsvisualisering klart hjälpte i kommunikationen av de fem visualiserade nätverksparametrarna: genomströmning, svarstid, tillgänglighet, täckning och uppkopplade enheter. Däremot krävs ytterligare forskning kring verktygets roll i industriell kontext för att kunna göra en fullständig granskning av verktygets användbarhet.
Biswas, Sanjeet Kumar. "Analysis and comparison of network performance with different network parameters." FIU Digital Commons, 1999. http://digitalcommons.fiu.edu/etd/1703.
Full textIkiz, Suheyla. "Performance Parameters Of Wireless Virtual Private Network." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607094/index.pdf.
Full textheyla Ms.c, Department of Information Systems Supervisor: Assoc. Prof. Dr. Nazife Baykal Co-Supervisor: Assist. Prof. Dr. Yusuf Murat Erten January 2006, 78 pages As the use of PC&rsquo
s and handheld devices increase, it expected that wireless communication would also grow. One of the major concerns in wireless communication is the security. Virtual Private Network (VPN) is the most secure solution that ensures three main aspect of security: authentication, accountability and encryption can use in wireless networks. Most VPNs have built on IP Security Protocol (IPSec) to support end-to-end secure data transmission. IPSec is a wellunderstood and widely used mechanism for wired network communication. Because, wireless networks have limited bandwidth and wireless devices have limited power and less capable CPU, the performance of the networks when VPN&rsquo
s are used is an important research area. We have investigated the use of VPNs in wireless LANs to provide end &ndash
to &ndash
end security. We have selected IPSec as the VPN protocol and investigated the effects of using IPSec on the throughput, packet loss, and delay of the wireless LANs. For this purpose, we have set up a test bed and based, our results on the actual measurements obtained from the experiments performed using the test bed. v The wireless LAN we have used is an 802.11g network and the results show that the performance of the network is adversely affected when VPN&rsquo
s are used but the degradation is not as bad as expected.
Ramaisa, Motlalepula. "Inferring congestion from delay and loss characteristics using parameters of the three-parameter Weibull distribution." Diss., Pretoria : [s.n.], 2005. http://upetd.up.ac.za/thesis/available/etd-08282007-112036.
Full textGustavsson, Jonas. "Automated Performance Optimization of GSM/EDGE Network Parameters." Thesis, Linköping University, Linköping University, Communication Systems, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-52565.
Full textThe GSM network technology has been developed and improved during several years which have led to an increased complexity. The complexity results in more network parameters and together with different scenarios and situations they form a complex set of configurations. The definition of the network parameters is generally a manual process using static values during test execution. This practice can be costly, difficult and laborious and as the network complexity continues to increase, this problem will continue to grow.This thesis presents an implementation of an automated performance optimization algorithm that utilizes genetic algorithms for optimizing the network parameters. The implementation has been used for proving that the concept of automated optimization is working and most of the work has been carried out in order to use it in practice. The implementation has been applied to the Link Quality Control algorithm and the Improved ACK/NACK feature, which is an apart of GSM EDGE Evolution.
GSM-nätsteknologin har utvecklats och förbättrats under lång tid, vilket har lett till en ökad komplexitet. Denna ökade komplexitet har resulterat i fler nätverksparameterar, tillstånd och standarder. Tillsammans utgör de en komplex uppsättning av olika konfigurationer. Dessa nätverksparameterar har hittills huvudsakligen bestämts med hjälp av en manuell optimeringsprocess. Detta tillvägagångssätt är både dyrt, svårt och tidskrävande och allt eftersom komplexiteten av GSM-näten ökar kommer problemet att bli större.Detta examensarbete presenterar en implementering av en algoritm för automatiserad optimering av prestanda som huvudsakligen använder sig av genetiska algoritmer för att optimera värdet av nätverksparametrarna. Implementeringen har använts för att påvisa att konceptet med en automatiserad optimering fungerar och det mesta av arbetet har utförts för att kunna använda detta i praktiken. Implementeringen har tillämpats på Link Quality Control-algoritmen och Improved ACK/NACK-funktionaliteten, vilket är en del av GSM EDGE Evolution.
Shaun, Ferdous Jahan. "Multi-Parameters Miniature Sensor for Water Network Management." Thesis, Paris Est, 2018. http://www.theses.fr/2018PESC1138/document.
Full textWater is a vital element for every living being on the earth. Like many other dwindling natural resources, clean water faces a strong pressure because of human activity and the rapid growth of global population. The situation is so critical that clean water has been identified as one of the seventeenth sustainable development goals of the United Nations. Under these conditions, a sustainable management of water resources is necessary. For this purpose, a smart solution for water networks monitoring can be very helpful. However, commercially available solutions lack compactness, self-powering capabilities cost competitiveness, necessary to enable the large rollout over water networks. The present thesis takes place in the framework of a European research project, PROTEUS, which addresses these different problems by designing and fabricating a multi-parameter sensor chip (MPSC) for water resources monitoring. The MPSC enables the measurement of 9 physical and chemical parameters, is reconfigurable and self-powered. The present thesis addresses more precisely physical sensors, their design, optimization and co-integration on the MPSC. The developed device exhibits state of the art or larger performances with regard to its redundancy, turn-down ratio and power consumption. The present manuscript is split into two main parts: Part-I and Part-II. Part-I deals with non-thermal aspects of the MPSC, the pressure and conductivity sensor for instance, as well as the fabrication process of the whole device (Chapter 1 and 2). The background of environmental monitoring is presented in Chapter 1 along with the State of Art review. Chapter 2 describes fabrication methods of the MPSC. Preliminary characterization results of non-thermal sensors are also reported in this chapter. Chapter 3 and 4, included in Part-II, deal with thermal sensors (temperature and flow-rate). Chapter 3 describes the many possible uses of electric resistances for sensing applications. Finally, in chapter four, we focus on flowrate sensors before concluding and making a few suggestions for future works
Tobolka, Lukáš. "Problematika návrhu síťové infrastruktury." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442356.
Full textLux, Matthew William. "Estimation of gene network parameters from imaging cytometry data." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/23082.
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Karayaka, Hayrettin Bora. "Neural network modeling and estimation of synchronous machine parameters /." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488195633519029.
Full textMcCloskey, Rosemary Martha. "Phylogenetic estimation of contact network parameters with approximate Bayesian computation." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/58663.
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Graduate
Books on the topic "Parameters of network"
Mavaddat, R. Network scattering parameters. Singapore: World Scientific, 1996.
Find full textNetwork scattering parameters. Singapore: World Scientific, 1996.
Find full textCanada, Atomic Energy of. Generation of Synthetic Fracture Parameters For Crack Network Analysis. S.l: s.n, 1985.
Find full textUnited Nations. Economic Commission for Europe. Transport Division. Inventory of main standards and parameters of the E waterway network "Blue Book". New York: United Nations, 2012.
Find full textTan, Xiao-nan. Systolic calculation of parameters for optimal routing in a type of shuffle-exchange network. Toronto: University of Toronto, Computer Systems Research Institute, 1986.
Find full textLemmon, Michael. Competitively inhibited neural networks for adaptive parameter estimation. Boston: Kluwer Academic, 1991.
Find full textLemmon, Michael. Competitively Inhibited Neural Networks for Adaptive Parameter Estimation. Boston, MA: Springer US, 1991.
Find full textLemmon, Michael. Competitively Inhibited Neural Networks for Adaptive Parameter Estimation. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-4044-1.
Full textZuev, Sergey, Ruslan Maleev, and Aleksandr Chernov. Energy efficiency of electrical equipment systems of autonomous objects. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1740252.
Full textPatan, Maciej. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Find full textBook chapters on the topic "Parameters of network"
Chowdhury, Dhiman Deb. "Timing Parameters." In NextGen Network Synchronization, 17–32. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71179-5_2.
Full textGhatak, Abhijit. "Initialization of Network Parameters." In Deep Learning with R, 87–102. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-5850-0_4.
Full textAlmond, Russell G., Robert J. Mislevy, Linda S. Steinberg, Duanli Yan, and David M. Williamson. "Parameters for Bayesian Network Models." In Bayesian Networks in Educational Assessment, 241–78. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2125-6_8.
Full textYonemura, Tomoko, Yoshikazu Hanatani, Taichi Isogai, Kenji Ohkuma, and Hirofumi Muratani. "Generating Parameters for Algebraic Torus-Based Cryptosystems." In Cryptology and Network Security, 156–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17619-7_12.
Full textSumongkayothin, Karin, Pakpoom Rachtrachoo, Arnuphap Yupuech, and Kasidit Siriporn. "OVERSCAN: OAuth 2.0 Scanner for Missing Parameters." In Network and System Security, 221–33. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36938-5_13.
Full textColbourn, C., and E. Litvak. "Bounding network parameters by approximating graphs." In DIMACS Series in Discrete Mathematics and Theoretical Computer Science, 91–104. Providence, Rhode Island: American Mathematical Society, 1991. http://dx.doi.org/10.1090/dimacs/005/06.
Full textKumar, B. Naveen, and P. V. Kumar. "Learning Parameters for Hybrid Bayesian Network." In International Conference on Mobile Computing and Sustainable Informatics, 255–60. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49795-8_25.
Full textTozzo, Veronica, and Annalisa Barla. "Multi-parameters Model Selection for Network Inference." In Complex Networks and Their Applications VIII, 566–77. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36687-2_47.
Full textTschiatschek, Sebastian, Peter Reinprecht, Manfred Mücke, and Franz Pernkopf. "Bayesian Network Classifiers with Reduced Precision Parameters." In Machine Learning and Knowledge Discovery in Databases, 74–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33460-3_10.
Full textBadrieh, Fuad. "Multi-Port Network: Z- and Y-Parameters." In Spectral, Convolution and Numerical Techniques in Circuit Theory, 811–28. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-71437-0_42.
Full textConference papers on the topic "Parameters of network"
Hummel, Robert A., Joshua A. Taylor, and Franz S. Hover. "Numerical Optimization of Generative Network Parameters." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-39262.
Full textFilho, Milton B. Do Coutto, Julio C. Stacchini de Souza, and Edwin B. M. Meza. "Correcting electrical network parameters." In Energy Society General Meeting (PES). IEEE, 2009. http://dx.doi.org/10.1109/pes.2009.5275400.
Full textEmbrechts, Mark J., Aaron L. Schweizerhof, Mark Bushman, and Mike H. Sabatella. "Neural Network Modeling of Turbofan Parameters." In ASME Turbo Expo 2000: Power for Land, Sea, and Air. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/2000-gt-0036.
Full textCika, Petr, Stepan Grabovsky, Vaclav Zeman, and Vlastimil Clupek. "Network Emulator of Transmission Parameters of Data Networks." In 2018 10th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). IEEE, 2018. http://dx.doi.org/10.1109/icumt.2018.8631254.
Full textKulkarni, Samrat, Beth Polonsky, and Mohamed El-Sayed. "FTTH Network Economics: Key Parameters Impacting Technology Decisions." In 2008 13th International Telecommunications Network Strategy and Planning Symposium (NETWORKS). IEEE, 2008. http://dx.doi.org/10.1109/netwks.2008.4763668.
Full textKulkarni, Samrat, Mohamed El-Sayed, Paul Gagen, and Beth Polonsky. "FTTH network economics: Key parameters impacting technology decisions." In 2008 13th International Telecommunications Network Strategy and Planning Symposium (NETWORKS). IEEE, 2008. http://dx.doi.org/10.1109/netwks.2008.6231299.
Full textKumar, Manish, and Devendra P. Garg. "Neural Network Based Intelligent Learning of Fuzzy Logic Controller Parameters." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59589.
Full textLluna, Eduardo, A. Edith Navarro, Diego Ramírez, and Silvia Casans. "Sensor Network to Measure Electric Parameters." In 2010 Fourth International Conference on Sensor Technologies and Applications (SENSORCOMM). IEEE, 2010. http://dx.doi.org/10.1109/sensorcomm.2010.81.
Full textDevarakonda, Kanchan, Sotirios G. Ziavras, and Roberto Rojas-Cessa. "Measuring Network Parameters with Hardware Support." In 2007 International Conference on Networking and Services. IEEE, 2007. http://dx.doi.org/10.1109/icns.2007.80.
Full textCooper, Colin, Tomasz Radzik, and Yiannis Siantos. "Estimating network parameters using random walks." In 2012 Fourth International Conference on Computational Aspects of Social Networks (CASoN). IEEE, 2012. http://dx.doi.org/10.1109/cason.2012.6412374.
Full textReports on the topic "Parameters of network"
Shenker, S., and J. Wroclawski. General Characterization Parameters for Integrated Service Network Elements. RFC Editor, September 1997. http://dx.doi.org/10.17487/rfc2215.
Full textAl-Qadi, Imad, Egemen Okte, Aravind Ramakrishnan, Qingwen Zhou, and Watheq Sayeh. Truck-Platoonable Pavement Sections in Illinois’ Network. Illinois Center for Transportation, February 2021. http://dx.doi.org/10.36501/0197-9191/21-002.
Full textHenderson, Tim, Vincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: Klamath Inventory & Monitoring Network. National Park Service, July 2021. http://dx.doi.org/10.36967/nrr-2286915.
Full textHenderson, Tim, Mincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: Chihuahuan Desert Inventory & Monitoring Network. National Park Service, April 2021. http://dx.doi.org/10.36967/nrr-2285306.
Full textMakedonska, Nataliia, Edward Michael Kwicklis, Jeffrey De'Haven Hyman, and Suzanne Michelle Bourret. Discrete Fracture Network Modeling to Estimate Upscaled Parameters for the Topopah Spring, Lava Flow, and Tiva Canyon Aquifers at Pahute Mesa, Nevada National Security Site. Office of Scientific and Technical Information (OSTI), May 2020. http://dx.doi.org/10.2172/1623419.
Full textHenderson, Tim, Vincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: Northern Colorado Plateau Inventory & Monitoring Network. National Park Service, April 2021. http://dx.doi.org/10.36967/nrr-2285337.
Full textPettit, Chris, and D. Wilson. A physics-informed neural network for sound propagation in the atmospheric boundary layer. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/41034.
Full textRouil, Richard, Antonio Izquierdo, Camillo Gentile, David Griffith, and Nada Golmie. Nationwide Public Safety Broadband Network Deployment: Network Parameter Sensitivity Analysis. National Institute of Standards and Technology, February 2015. http://dx.doi.org/10.6028/nist.ir.8039.
Full textFarhi, Edward, and Hartmut Neven. Classification with Quantum Neural Networks on Near Term Processors. Web of Open Science, December 2020. http://dx.doi.org/10.37686/qrl.v1i2.80.
Full textBowles, David, Michael Williams, Hope Dodd, Lloyd Morrison, Janice Hinsey, Tyler Cribbs, Gareth Rowell, Michael DeBacker, Jennifer Haack-Gaynor, and Jeffrey Williams. Protocol for monitoring aquatic invertebrates of small streams in the Heartland Inventory & Monitoring Network: Version 2.1. National Park Service, April 2021. http://dx.doi.org/10.36967/nrr-2284622.
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