421 research outputs found

    Dynamics of one-dimensional electron systems

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    We investigate the separation of spin and charge in interacting one-dimensional fermion systems. Density matrix renormalisation group (DMRG) simulations on the Hubbard model in the time domain show this phenomenon explicitely in a transport scenario. The separation of internal degrees of freedom and charge even remains when extending the problem to SU(3) fermions. Additionally, identifying signatures for spinon and holon are found for the momentum-dependent spectral function in a magnetic field

    Dimensionality reduction and sparse representations in computer vision

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    The proliferation of camera equipped devices, such as netbooks, smartphones and game stations, has led to a significant increase in the production of visual content. This visual information could be used for understanding the environment and offering a natural interface between the users and their surroundings. However, the massive amounts of data and the high computational cost associated with them, encumbers the transfer of sophisticated vision algorithms to real life systems, especially ones that exhibit resource limitations such as restrictions in available memory, processing power and bandwidth. One approach for tackling these issues is to generate compact and descriptive representations of image data by exploiting inherent redundancies. We propose the investigation of dimensionality reduction and sparse representations in order to accomplish this task. In dimensionality reduction, the aim is to reduce the dimensions of the space where image data reside in order to allow resource constrained systems to handle them and, ideally, provide a more insightful description. This goal is achieved by exploiting the inherent redundancies that many classes of images, such as faces under different illumination conditions and objects from different viewpoints, exhibit. We explore the description of natural images by low dimensional non-linear models called image manifolds and investigate the performance of computer vision tasks such as recognition and classification using these low dimensional models. In addition to dimensionality reduction, we study a novel approach in representing images as a sparse linear combination of dictionary examples. We investigate how sparse image representations can be used for a variety of tasks including low level image modeling and higher level semantic information extraction. Using tools from dimensionality reduction and sparse representation, we propose the application of these methods in three hierarchical image layers, namely low-level features, mid-level structures and high-level attributes. Low level features are image descriptors that can be extracted directly from the raw image pixels and include pixel intensities, histograms, and gradients. In the first part of this work, we explore how various techniques in dimensionality reduction, ranging from traditional image compression to the recently proposed Random Projections method, affect the performance of computer vision algorithms such as face detection and face recognition. In addition, we discuss a method that is able to increase the spatial resolution of a single image, without using any training examples, according to the sparse representations framework. In the second part, we explore mid-level structures, including image manifolds and sparse models, produced by abstracting information from low-level features and offer compact modeling of high dimensional data. We propose novel techniques for generating more descriptive image representations and investigate their application in face recognition and object tracking. In the third part of this work, we propose the investigation of a novel framework for representing the semantic contents of images. This framework employs high level semantic attributes that aim to bridge the gap between the visual information of an image and its textual description by utilizing low level features and mid level structures. This innovative paradigm offers revolutionary possibilities including recognizing the category of an object from purely textual information without providing any explicit visual example

    Layer 2 Path Selection Protocol for Wireless Mesh Networks with Smart Antennas

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    In this thesis the possibilities of smart antenna systems in wireless mesh networks are examined. With respect to the individual smart antenna tradeoffs, a routing protocol (Modified HWMP, MHWMP) for IEEE 802.11s mesh networks is presented, that exploits the full range of benefits provided by smart antennas: MHWMP actively switches between the PHY-layer transmission/reception modes (multiplexing, beamforming and diversity) according to the wireless channel conditions. Spatial multiplexing and beamforming are used for unicast data transmissions, while antenna diversity is employed for efficient broadcasts. To adapt to the directional channel environment and to take full benefit of the PHY capabilities, a respective MAC scheme is employed. The presented protocol is tested in extensive simulation and the results are examined.:1 Introduction 2 Wireless Mesh Networks 3 IEEE 802.11s 4 Smart Antenna Concepts 5 State of the Art: Wireless Mesh Networks with Smart Antennas 6 New Concepts 7 System Model 8 Results and Discussion 9 Conclusion and Future Wor

    Applying Formal Methods to Networking: Theory, Techniques and Applications

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    Despite its great importance, modern network infrastructure is remarkable for the lack of rigor in its engineering. The Internet which began as a research experiment was never designed to handle the users and applications it hosts today. The lack of formalization of the Internet architecture meant limited abstractions and modularity, especially for the control and management planes, thus requiring for every new need a new protocol built from scratch. This led to an unwieldy ossified Internet architecture resistant to any attempts at formal verification, and an Internet culture where expediency and pragmatism are favored over formal correctness. Fortunately, recent work in the space of clean slate Internet design---especially, the software defined networking (SDN) paradigm---offers the Internet community another chance to develop the right kind of architecture and abstractions. This has also led to a great resurgence in interest of applying formal methods to specification, verification, and synthesis of networking protocols and applications. In this paper, we present a self-contained tutorial of the formidable amount of work that has been done in formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial

    Application-driven data processing in wireless sensor networks

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    Wireless sensor networks (WSNs) are composed of spatially distributed, low-cost, low-power, resource-constrained devices using sensors and actuators to cooperatively monitor and operate into the environment. These systems are being used in a wide range of applications. The design and implementation of an effective WSN requires dealing with several challenges involving multiple disciplines, such as wireless communications and networking, software engineering, embedded systems and signal processing. Besides, the technical solutions found to these issues are closely interconnected and determine the capability of the system to successfully fulfill the requirements posed by each application domain. The large and heterogeneous amount of data collected in a WSN need to be efficiently processed in order to improve the end-user comprehension and control of the observed phenomena. The thesis focuses on a) the development of centralized and distributed data processing methods optimized for the requirements and characteristics of the considered application domains, and b) the design and implementation of suitable system architectures and protocols with respect to critical application-specific parameters. The thesis comprehends a summary and nine publications, equally divided over three different application domains, i.e. wireless automation, structural health monitoring (SHM) and indoor situation awareness (InSitA). In the first one, a wireless joystick control system for human adaptive mechatronics is developed. Also, the effect of packet losses on the performance of a wireless control system is analyzed and validated with an unstable process. A remotely reconfigurable, time synchronized wireless system for SHM enables a precise estimation of the modal properties of the monitored structure. Furthermore, structural damages are detected and localized through a distributed data processing method based on the Goertzel algorithm. In the context of InSitA, the short-time, low quality acoustic signals collected by the nodes composing the network are processed in order to estimate the number of people located in the monitored indoor environment. In a second phase, text- and language-independent speaker identification is performed. Finally, device-free localization and tracking of the movements of people inside the monitored indoor environment is achieved by means of distributed processing of the radio signal strength indicator (RSSI) signals. The results presented in the thesis demonstrate the adaptability of WSNs to different application domains and the importance of an optimal co-design of the system architecture and data processing methods

    Automated and intelligent hacking detection system

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    Dissertação de mestrado integrado em Informatics EngineeringThe Controller Area Network (CAN) is the backbone of automotive networking, connecting many Electronic ControlUnits (ECUs) that control virtually every vehicle function from fuel injection to parking sensors. It possesses,however, no security functionality such as message encryption or authentication by default. Attackers can easily inject or modify packets in the network, causing vehicle malfunction and endangering the driver and passengers. There is an increasing number of ECUs in modern vehicles, primarily driven by the consumer’s expectation of more features and comfort in their vehicles as well as ever-stricter government regulations on efficiency and emissions. Combined with vehicle connectivity to the exterior via Bluetooth, Wi-Fi, or cellular, this raises the risk of attacks. Traditional networks, such as Internet Protocol (IP), typically have an Intrusion Detection System (IDS) analysing traffic and signalling when an attack occurs. The system here proposed is an adaptation of the traditional IDS into the CAN bus using a One Class Support Vector Machine (OCSVM) trained with live, attack-free traffic. The system is capable of reliably detecting a variety of attacks, both known and unknown, without needing to understand payload syntax, which is largely proprietary and vehicle/model dependent. This allows it to be installed in any vehicle in a plug-and-play fashion while maintaining a large degree of accuracy with very few false positives.A Controller Area Network (CAN) é a principal tecnologia de comunicação interna automóvel, ligando muitas Electronic Control Units (ECUs) que controlam virtualmente todas as funções do veículo desde injeção de combustível até aos sensores de estacionamento. No entanto, não possui por defeito funcionalidades de segurança como cifragem ou autenticação. É possível aos atacantes facilmente injetarem ou modificarem pacotes na rede causando estragos e colocando em perigo tanto o condutor como os passageiros. Existe um número cada vez maior de ECUs nos veículos modernos, impulsionado principalmente pelas expectativas do consumidores quanto ao aumento do conforto nos seus veículos, e pelos cada vez mais exigentes regulamentos de eficiência e emissões. Isto, associada à conexão ao exterior através de tecnologias como o Bluetooth, Wi-Fi, ou redes móveis, aumenta o risco de ataques. Redes tradicionais, como a rede Internet Protocol (IP), tipicamente possuem um Intrusion Detection Systems (IDSs) que analiza o tráfego e assinala a presença de um ataque. O sistema aqui proposto é uma adaptação do IDS tradicional à rede CAN utilizando uma One Class Support Vector Machine (OCSVM) treinada com tráfego real e livre de ataques. O sistema é capaz de detetar com fiabilidade uma variedade de ataques, tanto conhecidos como desconhecidos, sem a necessidade de entender a sintaxe do campo de dados das mensagens, que é maioritariamente proprietária. Isto permite ao sistema ser instalado em qualquer veículo num modo plug-and-play enquanto mantém um elevado nível de desempenho com muito poucos falsos positivos

    Feasibility of a Cognitive Extension to Existing 802.11b Wireless Devices

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    Cognitive radio presents a means of altering the communication method of a wireless device based on channel conditions and the intended receiving device. However, the design of such a radio is very complicated as it must consider the possibility of multiple forms of modulation, differing transmit frequencies and symbol rates, and the accompany changes to other training procedures such as synchronization. This work proposes that in some cases a simpler, more cost-effective approach can be taken, that builds upon the architecture of existing wireless devices forming a new radio with cognitive capabilities. This approach allows the base device to perform all baseband and MAC-related functions with minimal or no negative effects due to the extension. As changes in modulation type are much more complex, the analysis in this work is restricted to systems wanting to intelligently alter their transmit frequency or power, such as the 802.22 standard. Because of the extensive investment that has already been made in 802.11 technology, 802.11b chipsets and APs are very inexpensive. Therefore a frequency conversion extension was designed and tested as the fixed architecture to enable signal conversion of an 802.11b signal. Cognitive functionalities could be added with little modification to the proposed design in this work.The overall goal of this work is to achieve throughput and packet loss results comparable to the base design at the converted frequency of approximately 1.7 GHz. The successful conversion with a fixed design proves the concept feasible, as the only additional requirement is to interface a cognitive subsystem with a configurable architecture employing the same design as the fixed architecture. The nodes under test were isolated in an anechoic chamber to prevent interference from nearby networks. A program called IxChariot is used to experimentally conduct network performance tests to confirm that the extended device operates nearly identically to a normal 802.11b radio. Tests were performed for one-hop and two-hop scenarios collecting throughput and packet loss statistics. A number of undesirable effects such as increased switching delay time are also examined as well as their impact on the MAC and physical layer of the base device. The results of testing established the feasibility of a cognitive extension with no perceivable throughput/packet loss degradation for reasonable switching delays. Analysis of poor switching delay performance and 802.11g is also presented to illustrate the additional design constraints these challenges present
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