Relevant bibliographies by topics / Classification of network devices

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  1. Dissertations / Theses

Academic literature on the topic 'Classification of network devices'

Author: Grafiati
Published: 28 June 2021
Last updated: 14 February 2022

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Dissertations / Theses on the topic "Classification of network devices"

1

Eis, Pavel. "Datová sada pro klasifikaci síťových zařízení pomocí strojového učení." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445543.

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Automatic classification of devices in computer network can be used for detection of anomalies in a network and also it enables application of security policies per device type. The key to creating a device classifier is a quality data set, the public availability of which is low and the creation of a new data set is difficult. The aim of this work is to create a tool, that will enable automated annotation of the data set of network devices and to create a classifier of network devices that uses only basic data from network flows. The result of this work is a modular tool providing automated a
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Sleem, Lama. "Design and implementation of lightweight and secure cryptographic algorithms for embedded devices." Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCD018.

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Nous vivons actuellement dans une ère avec sans cesse de nouveaux appareils technologiques (smartphone, réseaux de capteurs sans fil, aux caméras haute résolution, etc). En partant des médias sociaux, en passant par des caméras de surveillance très puissantes, et sans oublier la surveillance de la santé en temps réel, on constate qu'une grande quantité de données est stockée dans le cloud et les serveurs. Cela représente un grand défi de stockage et de transmission, en particulier dans les plates-formes aux ressources limitées qui sont caractérisées par : (a) des capacités de calcul limitées,
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Erlandsson, Niklas. "Utilizing machine learning in wildlife camera traps for automatic classification of animal species : An application of machine learning on edge devices." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-104952.

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A rapid global decline in biodiversity has been observed in the past few decades, especially in large vertebrates and the habitats supporting these animal populations. This widely accepted fact has made it very important to understand how animals respond to modern ecological threats and to understand the ecosystems functions. The motion activated camera (also known as a camera trap) is a common tool for research in this field, being well-suited for non-invasive observation of wildlife. The images captured by camera traps in biological studies need to be classified to extract information, a tra
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Luckhardt, Christoph [Verfasser]. "Development of thermo-analytical prediction and classification models for food in thermal devices using a multi sensor system and artificial neural networks / Christoph Luckhardt." Kassel : Universitätsbibliothek Kassel, 2013. http://d-nb.info/1043361863/34.

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Akarapu, Deepika. "Object Identification Using Mobile Device for Visually Impaired Person." University of Dayton / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1628092619349812.

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Wolf, Robert, Niko Joram, Stefan Schumann, and Frank Ellinger. "Dual-band impedance transformation networks for integrated power amplifiers." Cambridge University Press, 2016. https://tud.qucosa.de/id/qucosa%3A70680.

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This paper shows that the two most common impedance transformation networks for power amplifiers (PAs) can be designed to achieve optimum transformation at two frequencies. Hence, a larger bandwidth for the required impedance transformation ratio is achieved. A design procedure is proposed, which takes imperfections like losses into account. Furthermore, an analysis method is presented to estimate the maximum uncompressed output power of a PA with respect to frequency. Based on these results, a fully integrated PA with a dual-band impedance transformation network is designed and its functional
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Kühnert, Wolfram. "Dynamic Devices Network Architecture." [S.l. : s.n.], 2003. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10952962.

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Alexander, David. "A Network Metadata Infrastructure for Locating Network Devices." Ohio University / OhioLINK, 2004. http://www.ohiolink.edu/etd/view.cgi?ohiou1088176648.

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Zenteno, Efrain. "Vector Measurements for Wireless Network Devices." Licentiate thesis, KTH, Signalbehandling, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-111863.

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Wireless networks are an iconic technology of today’s modern era, theyare present in our daily activities as can be exemplified by cellular communications,wi-fi, bluetooth, and others. Vector measurements play an importantrole in the design, simulation, and testing of wireless networks and are usedto characterize key devices operating in the radio interface, such as amplifiers,filters, and mixers.Accurate characterization is the key for improving the capacity and efficiencyof wireless networks. As the demand for network capacity continuouslyincreases, the accuracy of vector measurements must a
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Omer, Mahgoub Saied Khalid. "Network Latency Estimation Leveraging Network Path Classification." Thesis, KTH, Network Systems Laboratory (NS Lab), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229955.

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With the development of the Internet, new network services with strict network latency requirements have been made possible. These services are implemented as distributed systems deployed across multiple geographical locations. To provide low response time, these services require knowledge about the current network latency. Unfortunately, network latency among geo-distributed sites often change, thus distributed services rely on continuous network latency measurements. One goal of such measurements is to differentiate between momentary latency spikes from relatively long-term latency changes.
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