Thematische Bibliographien / Parameters of network

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Auswahl der wissenschaftlichen Literatur zum Thema „Parameters of network“

Autor: Grafiati

Veröffentlicht am 28. Juni 2021

Zuletzt aktualisiert am 3. Februar 2022

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Zeitschriftenartikel zum Thema "Parameters of network"

PELLEGRINI, Lilla, Monica LEBA und Alexandru IOVANOVICI. „CHARACTERIZATION OF URBAN TRANSPORTATION NETWORKS USING NETWORK MOTIFS“. Acta Electrotechnica et Informatica 20, Nr. 4 (21.01.2020): 3–9. http://dx.doi.org/10.15546/aeei-2020-0019.

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We use tools and techniques specific to the field of complex networks analysis for the identification and extraction of key parameters which define ”good” patterns and practices for designing public transportation networks. Using network motifs we analyze a set of 18 cities using public data sets regarding the topology of network and discuss each of the identified motifs using the concepts and tools of urban planning.

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Romanov, Oleksandr, Ivan Saychenko, Anton Marinov und Serhii Skolets. „RESEARCH OF SDN NETWORK PERFORMANCE PARAMETERS USING MININET NETWORK EMULATOR“. Information and Telecommunication Sciences, Nr. 1 (29.06.2021): 24–32. http://dx.doi.org/10.20535/2411-2976.12021.24-32.

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Background. The implementation of the new modern services on existing networks requires replacement or modernization of the old equipment. This negatively affects the efficiency of providing users with new types of services and their cost. Therefore, the issues/tasks of implementing SDN technology in the construction of networks are in the center of attention of representatives of science-research organizations and telecom operators. SDN networks have the advantages of flexible scaling of the system without replacing existing server and network equipment, eliminating operator dependence on specific vendor solutions, and rapid implementation of the new network technologies and services. To determine the numerical values of indicators of the functioning of SDN networks and check their compliance with the requirements, it is proposed to use in working process simulation modelling. For these goals, the Open Networking Foundation consortium developed the Mininet network emulator, the elements of that are published publicly. The formation of the simulation model and the procedure for determining the performance indicators of the SDN network that uses Mininet has a number of features that are considered in the work. Objective. The purpose of the article is to build a simulation model based on the Mininet network emulator and to determine the performance indicators of SDN networks of various structures/topologies. Methods. Creation of a SDN network segment for testing process of its functioning in the overload mode of various communication routes. Results. The Mininet network emulator allows simulating SDN networks of a rather complex structure, change the performance of network branches and the amount of load in communication routes, to create a network-wide overload mode. During the simulation, it is possible to determine a number of indicators of network performance, such as the RTT (Round Trip Time) parameter for each route of communication, the bandwidth of branches and routes of communication, the amount of delay on network elements, loading of OpenFlow Switch ports/interfaces, network elements with the highest delay, the number of served and lost packets. Conclusions. Use of the Mininet network emulator is a fairly convenient tool for determining the performance indicators of SDN networks. However, there are also some problems. First of all, setting up the system's operability requires writing programs to ensure the interaction among standard elements from the Mininet library. Secondone, is when congestion occurs in the communication routes, the Floodlight Controller does not automatically balance traffic along the work-around route. This task has to be solved manually by making changes to the OpenFlow Switch routing tables. Keywords: Software Defined Networking; SDN; Mininet; OpenFlow; Floodlight Controller; OpenFlowSwitch; NFV; virtualization.

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Zhou, Yang. „Research on Network Control Based on QoS of the Network“. Advanced Materials Research 989-994 (Juli 2014): 4265–68. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4265.

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With the technology improvement of computer communication and multimedia coding, real time communication such as audio and video is introduced to networks and become a dominant way of communication.In the control of network, the optimization problem of the network controller based on network Quality of service (QoS) is a very important problem in the research of network control. Considering the influence of network quality—of service (QoS) on the control performance,a system model combining the network parameters and the control parameters is established for networked control systems (NCSs). Based on this, the condition dependent on the network parameters and control parameters is presented for the existence of guaranteed cost controllers.LMI).Within the scope of QoS perturbation,the designed controller can not only make the system as hypnotically stable but also guarantee that the system performance index is not greater than the upper bound.

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LIU, WEI-YI, und KUN YUE. „BAYESIAN NETWORK WITH INTERVAL PROBABILITY PARAMETERS“. International Journal on Artificial Intelligence Tools 20, Nr. 05 (Oktober 2011): 911–39. http://dx.doi.org/10.1142/s0218213011000449.

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Interval data are widely used in real applications to represent the values of quantities in uncertain situations. However, the implied probabilistic causal relationships among interval-valued variables with interval data cannot be represented and inferred by general Bayesian networks with point-based probability parameters. Thus, it is desired to extend the general Bayesian network with effective mechanisms of representation, learning and inference of probabilistic causal relationships implied in interval data. In this paper, we define the interval probabilities, the bound-limited weak conditional interval probabilities and the probabilistic description, as well as the multiplication rules. Furthermore, we propose the method for learning the Bayesian network structure from interval data and the algorithm for corresponding approximate inferences. Experimental results show that our methods are feasible, and we conclude that the Bayesian network with interval probability parameters is the expansion of the general Bayesian network.

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Wang, Jia Jia, Yong Xiang Zhang, Wei Gong Zhang und Hua Zhang Zhou. „Measuring Parameters of SpaceWire Network“. Advanced Materials Research 159 (Dezember 2010): 522–26. http://dx.doi.org/10.4028/www.scientific.net/amr.159.522.

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SpaceWire is used for on-board satellite networks. It is proposed by the ESA as the basis for future data-handing architectures. It takes an indispensable role for the shortage of bandwidth of bus among data processing. Based on the research of SpaceWire Network, some parameters, such as delay, bit error ratio, bandwidth and throughput, a new scheme of the testing about the parameters of SpaceWire was proposed. Then its implementation technology was analyzed and explained.

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Besfat, Henok M., Zelalem Hailu Gebeyehu und Sudhir K. Routray. „Estimation of Parameters of 5G Network Dimensioning“. International Journal of Electronics, Communications, and Measurement Engineering 10, Nr. 2 (Juli 2021): 15–32. http://dx.doi.org/10.4018/ijecme.2021070102.

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Cellular network traffic increases rapidly, and new services are introduced every year. For proper planning and design of such networks, exact requirements must be known with good accuracy. Dimensioning is an important part of network planning and design. Dimensioning is essential to determine the network requirements. In the coming years, fifth-generation (5G) will be deployed widely. 5G infrastructure is hybrid of wireless and optical components. For 5G network dimensioning, there is a need of a hybrid model. In this paper, the authors develop mathematical expressions for 5G network dimensioning. They use ITU proposed typical 5G network provisions to estimate bandwidth, network capacity, coverage, and capital expenditures. They also establish the correlation between the optical and the wireless parts. The expressions developed in this work can be used for the fast estimation of network coverage. So, this model can play important roles for 5G network planning and design.

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Chechin, G. V. „Select main parameters of Internet traffic exchange network“. Issues of radio electronics 49, Nr. 5 (05.07.2020): 10–16. http://dx.doi.org/10.21778/2218-5453-2020-5-10-16.

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The article considers the urgent problem of mathematical modeling of the Internet traffic exchange network. A mathematical model of an Internet traffic exchange network with an arbitrary number IX (Internet Exchange Point, IX, IXP) in the form of a Queuing network is presented. The model allows you to analyze alternative options for building a traffic exchange network and determine the optimal parameters of its structure: minimize the average delay and select the bandwidth of communication channels, the performance of traffic exchange nodes with restrictions on reliability and cost, and select the topology of the traffic exchange network taking into account the main parameters. Calculation examples are provided for Internet traffic exchange networks with a uniformly growing and substantially uneven loading of channels. We conclude that it is advisable to build networks with several Internet traffic exchange nodes.

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Buranova, M., und R. Latypov. „MPLS Network Parameters Analysis when Changing the Topology“. Proceedings of Telecommunication Universities 5, Nr. 3 (2019): 6–12. http://dx.doi.org/10.31854/1813-324x-2019-5-3-6-12.

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One of the main tasks in network design is to evaluate the probability-time characteristics of the functioning of information and communication networks. Considering that the traffic of modern networks possesses the properties of self-similarity, we observe the difficulties while using the traditional mathematical apparatus of public serve theory. This paper presents us the results of jitter simulation estimating the delay, the probability of traffic loss when traffic processing in MPLS network. It was taken the real multimedia traffic and an on-off flow with a distribution of Pareto periods on and off as the researched flows. As the result, we discovered that when the network load increases or network size increases, jitter usually decreases, while the delay and loss probability increase.

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Ma, Yifang, und Zhiming Zheng. „Extracting principal parameters of complex networks“. International Journal of Modern Physics C 26, Nr. 09 (22.06.2015): 1550103. http://dx.doi.org/10.1142/s012918311550103x.

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The evolution of networks or dynamic systems is controlled by many parameters in high-dimensional space, and it is crucial to extract the reduced and dominant ones in low-dimensional space. Here we consider the network ensemble, introduce a matrix resolvent scale function and apply it to a spectral approach to get the similarity relations between each pair of networks. The concept of Diffusion Maps is used to get the principal parameters, and we point out that the reduced dimensional principal parameters are captured by the low order eigenvectors of the diffusion matrix of the network ensemble. We validate our results by using two classical network ensembles and one dynamical network sequence via a cooperative Achlioptas growth process where an abrupt transition of the structures has been captured by our method. Our method provides a potential access to the pursuit of invisible control parameters of complex systems.

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NITTA, TOHRU. „THE UNIQUENESS THEOREM FOR COMPLEX-VALUED NEURAL NETWORKS WITH THRESHOLD PARAMETERS AND THE REDUNDANCY OF THE PARAMETERS“. International Journal of Neural Systems 18, Nr. 02 (April 2008): 123–34. http://dx.doi.org/10.1142/s0129065708001439.

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This paper will prove the uniqueness theorem for 3-layered complex-valued neural networks where the threshold parameters of the hidden neurons can take non-zeros. That is, if a 3-layered complex-valued neural network is irreducible, the 3-layered complex-valued neural network that approximates a given complex-valued function is uniquely determined up to a finite group on the transformations of the learnable parameters of the complex-valued neural network.

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Dissertationen zum Thema "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.

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In the upcoming years, industrial enterprises are expected to undergo a major transformation, as the Internet of Things (IoT) reaches widespread adoption. A key enabler behind this transformation, known as Industry 4.0, is the 5th generation of cellular networks (5G). Through privately owned networks, enterprises will be able to utilize the 5G technology to tailor the network to meet their needs in terms of security, reliability, and quality of service. Although much of the technology is currently in place, few efforts have been dedicated to help enterprises understand and optimise the value that this new solution brings. One way of making 5G more accessible is through information visualization of its data. Dashboards are today the widely adopted tool for processing data in organisations. This study aimed at examining the affordances and challenges of information visualization of 5G network data in such a tool, in order to make 5G more accessible. A large number of commercial network management dashboards were reviewed in relation to research on effective dashboard design, and a prototype was developed and evaluated with seven user experience experts. Results from the expert review suggests information visualization clearly aided communication of the five visualized network parameters: throughput, latency, availability, coverage, and devices. However, to fully examine the usefulness of the tool, further research on the tool’s fit in an industry context needs to be conducted.
Inom 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.

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Biswas, Sanjeet Kumar. „Analysis and comparison of network performance with different network parameters“. FIU Digital Commons, 1999. http://digitalcommons.fiu.edu/etd/1703.

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The purpose of this study was to analyze the network performance by observing the effect of varying network size and data link rate on one of the most commonly found network configurations. Computer networks have been growing explosively. Networking is used in every aspect of business, including advertising, production, shipping, planning, billing, and accounting. Communication takes place through networks that form the basis of transfer of information. The number and type of components may vary from network to network depending on several factors such as requirement and actual physical placement of the networks. There is no fixed size of the networks and they can be very small consisting of say five to six nodes or very large consisting of over two thousand nodes. The varying network sizes make it very important to study the network performance so as to be able to predict the functioning and the suitability of the network. The findings demonstrated that the network performance parameters such as global delay, load, router processor utilization, router processor delay, etc. are affected. The findings demonstrated that the network performance parameters such as global delay, load, router processor utilization, router processor delay, etc. are affected significantly due to the increase in the size of the network and that there exists a correlation between the various parameters and the size of the network. These variations are not only dependent on the magnitude of the change in the actual physical area of the network but also on the data link rate used to connect the various components of the network.

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Ikiz, Suheyla. „Performance Parameters Of Wireless Virtual Private Network“. Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607094/index.pdf.

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ABSTRACT PERFORMANCE PARAMETERS OF WIRELESS VIRTUAL PRIVATE NETWORK KZ, Sü
heyla 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.

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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.

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Gustavsson, 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.

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The 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.

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Shaun, Ferdous Jahan. „Multi-Parameters Miniature Sensor for Water Network Management“. Thesis, Paris Est, 2018. http://www.theses.fr/2018PESC1138/document.

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L’eau est une ressource vitale, indispensable à la vie sur terre. A l’instar de nombreuses autres ressources naturelles, l’eau propre à la consommation est soumise à une forte pression à cause de l’impact de l’activité humaine d’une part et de l’augmentation continue de la population mondiale d’autre part. Une pression tellement forte que l’eau propre représente l’un des 17 objectifs de développement durable des Nations Unies. Dans ce contexte, une gestion rationnelle et durable de la ressource s’avère indispensable. Dans ce but, un système intelligent de supervision des réseaux d’eau potable peut s’avérer très utile. Les systèmes existant sont toutefois peu intégrés et compacts, nécessitent souvent une alimentation externe, et restent relativement chers pour un déploiement massif sur les réseaux. La présente thèse s’inscrit dans le cadre d’un projet de recherche européen, PROTEUS, visant à pallier ces différents problèmes en mettant au point un système de mesure pour la supervision de la ressource en eau permettant la mesure de 9 paramètres physico-chimiques, reconfigurable, et énergétiquement autonome. La contribution de la présente thèse à ce projet porte sur la conception et l’optimisation des différents capteurs physiques (conductivité électrique, pression, température et débit) ainsi qu’à leur co-intégration sur une même puce. Le système proposé montre des performances au moins égales à celle de l’état de l’art en ce qui concerne la robustesse, assurée par la redondance de nombreux éléments sensibles, le domaine de sensibilité et la consommation énergétique. Le présent manuscrit est par conséquent construit comme suit : le premier chapitre est une introduction générale à la supervision de grandeurs environnementales et à la puce multi-capteurs. Le second chapitre décrit la structure de la puce multi-capteurs ainsi que les méthodes de fabrication utilisées, avec une attention particulière accordée aux capteurs de pression et de conductivité électrique. Le troisième chapitre porte sur l’utilisation de résistances électriques pour la mesure de diverses grandeurs physiques, notamment la température. Le dernier chapitre s’attarde plus particulièrement sur l’utilisation de ce type de résistances pour la mesure de débit avant de conclure et de proposer des perspectives pour des travaux futurs
Water 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

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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.

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The aim of this diploma thesis is to look at the design of network infrastructure in practice. There are individual procedures, brands, standards that must be followed when designing. It includes a brief general overview of terminal elements, cable systems and related matters. In general, methods for measuring optical lines and parameters for measuring metallic networks are described here. The possible complications that accompany it are briefly described in the implementation. The network design methodology is also described here on the example of a specific object. Before the actual handover of the work, the entire infrastructure is analyzed and measured with output protocols within the certification of the entire system together with outputs in the form of a measurement protocol.

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Lux, 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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Synthetic biology endeavors to forward engineer genetic circuits with novel function. A major inspiration for the field has been the enormous success in the engineering of digital electronic circuits over the past half century. This dissertation approaches synthetic biology from the perspective of the engineering design cycle, a concept ubiquitous across many engineering disciplines. First, an analysis of the state of the engineering design cycle in synthetic biology is presented, pointing out the most limiting challenges currently facing the field. Second, a principle commonly used in electronics to weigh the tradeoffs between hardware and software implementations of a function, called co-design, is applied to synthetic biology. Designs to implement a specific logical function in three distinct domains are proposed and their pros and cons weighed. Third, automatic transitioning between an abstract design, its physical implementation, and accurate models of the corresponding system are critical for success in synthetic biology. We present a framework for accomplishing this task and demonstrate how it can be used to explore a design space. A major limitation of the aforementioned approach is that adequate parameter values for the performance of genetic components do not yet exist. Thus far, it has not been possible to uniquely attribute the function of a device to the function of the individual components in a way that enables accurate prediction of the function of new devices assembled from the same components. This lack presents a major challenge to rapid progression through the design cycle. We address this challenge by first collecting high time-resolution fluorescence trajectories of individual cells expressing a fluorescent protein, as well as snapshots of the number of corresponding mRNA molecules per cell. We then leverage the information embedded in the cell-cell variability of the population to extract parameter values for a stochastic model of gene expression more complex than typically used. Such analysis opens the door for models of genetic components that can more reliably predict the function of new combinations of these basic components.
Ph. D.

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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.

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McCloskey, 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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Models of the spread of disease in a population often make the simplifying assumption that the population is homogeneously mixed, or is divided into homogeneously mixed compartments. However, human populations have complex structures formed by social contacts, which can have a significant influence on the rate and pattern of epidemic spread. Contact networks capture this structure by explicitly representing each contact that could possibly lead to a transmission. Contact network models parameterize the structure of these networks, but estimating their parameters from contact data requires extensive, often prohibitive, epidemiological investigation. We developed a method based on approximate Bayesian computation (ABC) for estimating structural parameters of the contact network underlying an observed viral phylogeny. The method combines adaptive sequential Monte Carlo for ABC, Gillespie simulation for propagating epidemics though networks, and a previously developed kernel-based tree similarity score. Our method offers the potential to quantitatively investigate contact network structure from phylogenies derived from viral sequence data, complementing traditional epidemiological methods. We applied our method to the Barabási-Albert network model. This model incorporates the preferential attachment mechanism observed in real world social and sexual networks, whereby individuals with more connections attract new contacts at an elevated rate (“the rich get richer”). Using simulated data, we found that the strength of preferential attachment and the number of infected nodes could often be accurately estimated. However, the mean degree of the network and the total number of nodes appeared to be weakly- or non-identifiable with ABC. Finally, the Barabási-Albert model was fit to eleven real world HIV datasets, and substantial heterogeneity in the parameter estimates was observed. Posterior means for the preferential attachment power were all sub-linear, consistent with literature results. We found that the strength of preferential attachment was higher in injection drug user populations, potentially indicating that high-degree “superspreader” nodes may play a role in epidemics among this risk group. Our results underscore the importance of considering contact structures when investigating viral outbreaks.
Science, Faculty of
Graduate

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Bücher zum Thema "Parameters of network"

Mavaddat, R. Network scattering parameters. Singapore: World Scientific, 1996.

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Network scattering parameters. Singapore: World Scientific, 1996.

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Canada, Atomic Energy of. Generation of Synthetic Fracture Parameters For Crack Network Analysis. S.l: s.n, 1985.

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United 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.

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Tan, 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.

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Lemmon, Michael. Competitively inhibited neural networks for adaptive parameter estimation. Boston: Kluwer Academic, 1991.

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Lemmon, Michael. Competitively Inhibited Neural Networks for Adaptive Parameter Estimation. Boston, MA: Springer US, 1991.

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Lemmon, 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.

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Zuev, Sergey, Ruslan Maleev und 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.

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When considering the main trends in the development of modern autonomous objects (aircraft, combat vehicles, motor vehicles, floating vehicles, agricultural machines, etc.) in recent decades, two key areas can be identified. The first direction is associated with the improvement of traditional designs of autonomous objects (AO) with an internal combustion engine (ICE) or a gas turbine engine (GTD). The second direction is connected with the creation of new types of joint-stock companies, namely electric joint-stock companies( EAO), joint-stock companies with combined power plants (AOKEU). The energy efficiency is largely determined by the power of the generator set and the battery, which is given to the electrical network in various driving modes. Most of the existing methods for calculating power supply systems use the average values of disturbing factors (generator speed, current of electric energy consumers, voltage in the on-board network) when choosing the characteristics of the generator set and the battery. At the same time, it is obvious that when operating a motor vehicle, these parameters change depending on the driving mode. Modern methods of selecting the main parameters and characteristics of the power supply system do not provide for modeling its interaction with the power unit start-up system of a motor vehicle in operation due to the lack of a systematic approach. The choice of a generator set and a battery, as well as the concept of the synthesis of the power supply system is a problem studied in the monograph. For all those interested in electrical engineering and electronics.

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Patan, Maciej. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Buchteile zum Thema "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.

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Ghatak, 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.

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Almond, Russell G., Robert J. Mislevy, Linda S. Steinberg, Duanli Yan und 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.

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Yonemura, Tomoko, Yoshikazu Hanatani, Taichi Isogai, Kenji Ohkuma und 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.

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Sumongkayothin, Karin, Pakpoom Rachtrachoo, Arnuphap Yupuech und 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.

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Colbourn, C., und 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.

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Kumar, B. Naveen, und 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.

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Tozzo, Veronica, und 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.

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Tschiatschek, Sebastian, Peter Reinprecht, Manfred Mücke und 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.

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Badrieh, 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.

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Konferenzberichte zum Thema "Parameters of network"

Hummel, Robert A., Joshua A. Taylor und 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.

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We address the early design of complex, large-scale systems by viewing them as random networks and optimizing structure over their generative parameters. In this approach, we do not seek specific topologies, but rather classes of near-optimal networks which correspond to desirable statistical behavior, while also allowing flexibility to accommodate unmodeled constraints. Functionally, we perform the optimization of generative parameters on small networks (e.g., one hundred nodes) and use the results to design large networks (e.g., one thousand or more nodes). This approach is a computationally feasible forward design path for large-scale systems. A numerical example is given in which a network’s degree distribution is optimized for combined robustness and cost in a cascading failure scenario; the work has direct application to distributed communication systems.

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Filho, Milton B. Do Coutto, Julio C. Stacchini de Souza und 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.

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Embrechts, Mark J., Aaron L. Schweizerhof, Mark Bushman und 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.

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This research involves the development and validation of neural network models for several engine parameters for a turbofan engine. The investigation encompasses data collection, data translation, development of the neural network models, and testing. The data used to train and validate the neural network models was acquired from state of the art models as well as flight tests. During this study, different neural network architectures and training algorithms are exercised and evaluated for a turbofan engine operating at steady-state conditions. In addition, studies are performed to optimize the neural network architecture and resolution of data used for training. The resulting models are thoroughly validated using data for approximately sixty thousand flight conditions. The neural network models trained and tested with data acquired from state of the art models are capable of predicting their respective parameters with a maximum of 5.3 percent error. A neural network model created with a small set of flight test data and validated with a slightly larger set of data resulted in a maximum error of 4.6 percent.

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Cika, Petr, Stepan Grabovsky, Vaclav Zeman und 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.

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Kulkarni, Samrat, Beth Polonsky und 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.

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Kulkarni, Samrat, Mohamed El-Sayed, Paul Gagen und 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.

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Kumar, Manish, und 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.

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Design of an efficient fuzzy logic controller involves the optimization of parameters of fuzzy sets and proper choice of rule base. There are several techniques reported in recent literature that use neural network architecture and genetic algorithms to learn and optimize a fuzzy logic controller. This paper presents methodologies to learn and optimize fuzzy logic controller parameters that use learning capabilities of neural network. Concepts of model predictive control (MPC) have been used to obtain optimal signal to train the neural network via backpropagation. The strategies developed have been applied to control an inverted pendulum and results have been compared for two different fuzzy logic controllers developed with the help of neural networks. The first neural network emulates a PD controller, while the second controller is developed based on MPC. The proposed approach can be applied to learn fuzzy logic controller parameter online via the use of dynamic backpropagation. The results show that the Neuro-Fuzzy approaches were able to learn rule base and identify membership function parameters accurately.

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Lluna, Eduardo, A. Edith Navarro, Diego Ramírez und 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.

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Devarakonda, Kanchan, Sotirios G. Ziavras und 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.

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Cooper, Colin, Tomasz Radzik und 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.

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Berichte der Organisationen zum Thema "Parameters of network"

Shenker, S., und J. Wroclawski. General Characterization Parameters for Integrated Service Network Elements. RFC Editor, September 1997. http://dx.doi.org/10.17487/rfc2215.

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Al-Qadi, Imad, Egemen Okte, Aravind Ramakrishnan, Qingwen Zhou und Watheq Sayeh. Truck-Platoonable Pavement Sections in Illinois’ Network. Illinois Center for Transportation, Februar 2021. http://dx.doi.org/10.36501/0197-9191/21-002.

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Truck platooning has many benefits over traditional truck mobility. Literature shows that platooning improves safety and reduces fuel consumption between 5% and 15% based on platoon configuration. In Illinois, trucks carry more than 50% of freight tonnage and constitute 25% of the traffic on interstates. Deployment of truck platooning within interstate highways would result in significant fuel savings, but may have a direct impact on flexible pavement performance. The channelization of the platoon and reduced rest time between consecutive loads would accelerate the damage accumulation at the channelized position. Ultimately, this would lead to pavement service life reduction and a subsequent increase in maintenance and rehabilitation costs. Therefore, the main objective of this project is to quantify the effects of platooning on flexible pavements and provide guidelines for the state of Illinois by considering the aforementioned factors. Although the benefits of platooning are quantifiable, not every truck route is platoonable. For efficient platooning, trucks need to travel at a constant high speed for extended distances. The integrity of the platoon should be preserved because interfering vehicles would compromise the platooning benefits and road safety. An introduced high-level approach considers the volume/capacity of a roadway and the expected number of highway exit and entry conflicts. Using these parameters, each roadway section is assigned a level of platoonability, ranging from one to five—with five being the highest. A framework was developed to analyze the Illinois highway network. It was found that 89% of the network highway is platoonable under average capacity conditions.

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Henderson, Tim, Vincent Santucci, Tim Connors und Justin Tweet. National Park Service geologic type section inventory: Klamath Inventory & Monitoring Network. National Park Service, Juli 2021. http://dx.doi.org/10.36967/nrr-2286915.

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A fundamental responsibility of the National Park Service (NPS) is to ensure that park resources are preserved, protected, and managed in consideration of the resources themselves and for the benefit and enjoyment by the public. Through the inventory, monitoring, and study of park resources, we gain a greater understanding of the scope, significance, distribution, and management issues associated with these resources and their use. This baseline of natural resource information is available to inform park managers, scientists, stakeholders, and the public about the conditions of these resources and the factors or activities which may threaten or influence their stability. There are several different categories of geologic or stratigraphic units (supergroup, group, formation, member, bed) which represent a hierarchical system of classification. The mapping of stratigraphic units involves the evaluation of lithologies, bedding properties, thickness, geographic distribution, and other factors. If a new mappable geologic unit is identified, it may be described and named through a rigorously defined process that is standardized and codified by the professional geologic community (North American Commission on Stratigraphic Nomenclature 2005). In most instances when a new geologic unit such as a formation is described and named in the scientific literature, a specific and well-exposed section of the unit is designated as the type section or type locality (see Definitions). The type section is an important reference section for a named geologic unit which presents a relatively complete and representative profile. The type or reference section is important both historically and scientifically, and should be protected and conserved for researchers to study and evaluate in the future. Therefore, this inventory of geologic type sections in NPS areas is an important effort in documenting these locations in order that NPS staff recognize and protect these areas for future studies. The documentation of all geologic type sections throughout the 423 units of the NPS is an ambitious undertaking. The strategy for this project is to select a subset of parks to begin research for the occurrence of geologic type sections within particular parks. The focus adopted for completing the baseline inventories throughout the NPS was centered on the 32 inventory and monitoring networks (I&M) established during the late 1990s. The I&M networks are clusters of parks within a defined geographic area based on the ecoregions of North America (Fenneman 1946; Bailey 1976; Omernik 1987). These networks share similar physical resources (geology, hydrology, climate), biological resources (flora, fauna), and ecological characteristics. Specialists familiar with the resources and ecological parameters of the network, and associated parks, work with park staff to support network level activities (inventory, monitoring, research, data management). Adopting a network-based approach to inventories worked well when the NPS undertook paleontological resource inventories for the 32 I&M networks. The network approach is also being applied to the inventory for the geologic type sections in the NPS. The planning team from the NPS Geologic Resources Division who proposed and designed this inventory selected the Greater Yellowstone Inventory and Monitoring Network (GRYN) as the pilot network for initiating this project. Through the research undertaken to identify the geologic type sections within the parks of the GRYN methodologies for data mining and reporting on these resources were established. Methodologies and reporting adopted for the GRYN have been used in the development of this type section inventory for the Klamath Inventory & Monitoring Network. The goal of this project is to consolidate information pertaining to geologic type sections which occur within NPS-administered areas, in order that this information is available throughout the NPS to inform park managers...

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Henderson, Tim, Mincent Santucci, Tim Connors und 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.

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A fundamental responsibility of the National Park Service is to ensure that park resources are preserved, protected, and managed in consideration of the resources themselves and for the benefit and enjoyment by the public. Through the inventory, monitoring, and study of park resources, we gain a greater understanding of the scope, significance, distribution, and management issues associated with these resources and their use. This baseline of natural resource information is available to inform park managers, scientists, stakeholders, and the public about the conditions of these resources and the factors or activities which may threaten or influence their stability. There are several different categories of geologic or stratigraphic units (supergroup, group, formation, member, bed) which represent a hierarchical system of classification. The mapping of stratigraphic units involves the evaluation of lithologies, bedding properties, thickness, geographic distribution, and other factors. If a new mappable geologic unit is identified, it may be described and named through a rigorously defined process that is standardized and codified by the professional geologic community (North American Commission on Stratigraphic Nomenclature 2005). In most instances when a new geologic unit such as a formation is described and named in the scientific literature, a specific and well-exposed section of the unit is designated as the type section or type locality (see Definitions). The type section is an important reference section for a named geologic unit which presents a relatively complete and representative profile for this unit. The type or reference section is important both historically and scientifically, and should be recorded such that other researchers may evaluate it in the future. Therefore, this inventory of geologic type sections in NPS areas is an important effort in documenting these locations in order that NPS staff recognize and protect these areas for future studies. The documentation of all geologic type sections throughout the 423 units of the NPS is an ambitious undertaking. The strategy for this project is to select a subset of parks to begin research for the occurrence of geologic type sections within particular parks. The focus adopted for completing the baseline inventories throughout the NPS was centered on the 32 inventory and monitoring networks (I&M) established during the late 1990s. The I&M networks are clusters of parks within a defined geographic area based on the ecoregions of North America (Fenneman 1946; Bailey 1976; Omernik 1987). These networks share similar physical resources (geology, hydrology, climate), biological resources (flora, fauna), and ecological characteristics. Specialists familiar with the resources and ecological parameters of the network, and associated parks, work with park staff to support network level activities (inventory, monitoring, research, data management). Adopting a network-based approach to inventories worked well when the NPS undertook paleontological resource inventories for the 32 I&M networks. The network approach is also being applied to the inventory for the geologic type sections in the NPS. The planning team from the NPS Geologic Resources Division who proposed and designed this inventory selected the Greater Yellowstone Inventory and Monitoring Network (GRYN) as the pilot network for initiating this project. Through the research undertaken to identify the geologic type sections within the parks of the GRYN, methodologies for data mining and reporting on these resources was established. Methodologies and reporting adopted for the GRYN have been used in the development of this type section inventory for the Chihuahuan Desert Inventory & Monitoring Network. The goal of this project is to consolidate information pertaining to geologic type sections which occur within NPS-administered areas, in order that this information is available throughout the NPS...

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Makedonska, Nataliia, Edward Michael Kwicklis, Jeffrey De'Haven Hyman und 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), Mai 2020. http://dx.doi.org/10.2172/1623419.

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Henderson, Tim, Vincent Santucci, Tim Connors und 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.

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A fundamental responsibility of the National Park Service (NPS) is to ensure that park resources are preserved, protected, and managed in consideration of the resources themselves and for the benefit and enjoyment by the public. Through the inventory, monitoring, and study of park resources, we gain a greater understanding of the scope, significance, distribution, and management issues associated with these resources and their use. This baseline of natural resource information is available to inform park managers, scientists, stakeholders, and the public about the conditions of these resources and the factors or activities which may threaten or influence their stability. There are several different categories of geologic or stratigraphic units (supergroup, group, formation, member, bed) which represent a hierarchical system of classification. The mapping of stratigraphic units involves the evaluation of lithologies, bedding properties, thickness, geographic distribution, and other factors. If a new mappable geologic unit is identified, it may be described and named through a rigorously defined process that is standardized and codified by the professional geologic community (North American Commission on Stratigraphic Nomenclature 2005). In most instances when a new geologic unit such as a formation is described and named in the scientific literature, a specific and well-exposed section of the unit is designated as the type section or type locality (see Definitions). The type section is an important reference section for a named geologic unit which presents a relatively complete and representative profile. The type or reference section is important both historically and scientifically, and should be available for other researchers to evaluate in the future. Therefore, this inventory of geologic type sections in NPS areas is an important effort in documenting these locations in order that NPS staff recognize and protect these areas for future studies. The documentation of all geologic type sections throughout the 423 units of the NPS is an ambitious undertaking. The strategy for this project is to select a subset of parks to begin research for the occurrence of geologic type sections within particular parks. The focus adopted for completing the baseline inventories throughout the NPS was centered on the 32 inventory and monitoring networks (I&M) established during the late 1990s. The I&M networks are clusters of parks within a defined geographic area based on the ecoregions of North America (Fenneman 1946; Bailey 1976; Omernik 1987). These networks share similar physical resources (geology, hydrology, climate), biological resources (flora, fauna), and ecological characteristics. Specialists familiar with the resources and ecological parameters of the network, and associated parks, work with park staff to support network level activities (inventory, monitoring, research, data management). Adopting a network-based approach to inventories worked well when the NPS undertook paleontological resource inventories for the 32 I&M networks. The network approach is also being applied to the inventory for the geologic type sections in the NPS. The planning team from the NPS Geologic Resources Division who proposed and designed this inventory selected the Greater Yellowstone Inventory and Monitoring Network (GRYN) as the pilot network for initiating this project. Through the research undertaken to identify the geologic type sections within the parks of the GRYN methodologies for data mining and reporting on these resources was established. Methodologies and reporting adopted for the GRYN have been used in the development of this type section inventory for the Northern Colorado Plateau Inventory & Monitoring Network. The goal of this project is to consolidate information pertaining to geologic type sections which occur within NPS-administered areas, in order that this information is available throughout the NPS...

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Pettit, Chris, und D. Wilson. A physics-informed neural network for sound propagation in the atmospheric boundary layer. Engineer Research and Development Center (U.S.), Juni 2021. http://dx.doi.org/10.21079/11681/41034.

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We describe what we believe is the first effort to develop a physics-informed neural network (PINN) to predict sound propagation through the atmospheric boundary layer. PINN is a recent innovation in the application of deep learning to simulate physics. The motivation is to combine the strengths of data-driven models and physics models, thereby producing a regularized surrogate model using less data than a purely data-driven model. In a PINN, the data-driven loss function is augmented with penalty terms for deviations from the underlying physics, e.g., a governing equation or a boundary condition. Training data are obtained from Crank-Nicholson solutions of the parabolic equation with homogeneous ground impedance and Monin-Obukhov similarity theory for the effective sound speed in the moving atmosphere. Training data are random samples from an ensemble of solutions for combinations of parameters governing the impedance and the effective sound speed. PINN output is processed to produce realizations of transmission loss that look much like the Crank-Nicholson solutions. We describe the framework for implementing PINN for outdoor sound, and we outline practical matters related to network architecture, the size of the training set, the physics-informed loss function, and challenge of managing the spatial complexity of the complex pressure.

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Rouil, Richard, Antonio Izquierdo, Camillo Gentile, David Griffith und Nada Golmie. Nationwide Public Safety Broadband Network Deployment: Network Parameter Sensitivity Analysis. National Institute of Standards and Technology, Februar 2015. http://dx.doi.org/10.6028/nist.ir.8039.

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Farhi, Edward, und Hartmut Neven. Classification with Quantum Neural Networks on Near Term Processors. Web of Open Science, Dezember 2020. http://dx.doi.org/10.37686/qrl.v1i2.80.

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We introduce a quantum neural network, QNN, that can represent labeled data, classical or quantum, and be trained by supervised learning. The quantum circuit consists of a sequence of parameter dependent unitary transformations which acts on an input quantum state. For binary classification a single Pauli operator is measured on a designated readout qubit. The measured output is the quantum neural network’s predictor of the binary label of the input state. We show through classical simulation that parameters can be found that allow the QNN to learn to correctly distinguish the two data sets. We then discuss presenting the data as quantum superpositions of computational basis states corresponding to different label values. Here we show through simulation that learning is possible. We consider using our QNN to learn the label of a general quantum state. By example we show that this can be done. Our work is exploratory and relies on the classical simulation of small quantum systems. The QNN proposed here was designed with near-term quantum processors in mind. Therefore it will be possible to run this QNN on a near term gate model quantum computer where its power can be explored beyond what can be explored with simulation.

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Bowles, David, Michael Williams, Hope Dodd, Lloyd Morrison, Janice Hinsey, Tyler Cribbs, Gareth Rowell, Michael DeBacker, Jennifer Haack-Gaynor und 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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The Heartland Inventory and Monitoring Network (HTLN) is a component of the National Park Service’s (NPS) strategy to improve park management through greater reliance on scientific information. The purposes of this program are to design and implement long-term ecological monitoring and provide information for park managers to evaluate the integrity of park ecosystems and better understand ecosystem processes. Concerns over declining surface water quality have led to the development of various monitoring approaches to assess stream water quality. Freshwater streams in network parks are threatened by numerous stressors, most of which originate outside park boundaries. Stream condition and ecosystem health are dependent on processes occurring in the entire watershed as well as riparian and floodplain areas; therefore, they cannot be manipulated independently of this interrelationship. Land use activities—such as timber management, landfills, grazing, confined animal feeding operations, urbanization, stream channelization, removal of riparian vegetation and gravel, and mineral and metals mining—threaten stream quality. Accordingly, the framework for this aquatic monitoring is directed towards maintaining the ecological integrity of the streams in those parks. Invertebrates are an important tool for understanding and detecting changes in ecosystem integrity, and they can be used to reflect cumulative impacts that cannot otherwise be detected through traditional water quality monitoring. The broad diversity of invertebrate species occurring in aquatic systems similarly demonstrates a broad range of responses to different environmental stressors. Benthic invertebrates are sensitive to the wide variety of impacts that influence Ozark streams. Benthic invertebrate community structure can be quantified to reflect stream integrity in several ways, including the absence of pollution sensitive taxa, dominance by a particular taxon combined with low overall taxa richness, or appreciable shifts in community composition relative to reference condition. Furthermore, changes in the diversity and community structure of benthic invertebrates are relatively simple to communicate to resource managers and the public. To assess the natural and anthropo-genic processes influencing invertebrate communities, this protocol has been designed to incorporate the spatial relationship of benthic invertebrates with their local habitat including substrate size and embeddedness, and water quality parameters (temperature, dissolved oxygen, pH, specific conductance, and turbidity). Rigid quality control and quality assurance are used to ensure maximum data integrity. Detailed standard operating procedures (SOPs) and supporting information are associated with this protocol.

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