784 research outputs found

    Additive Spanners and Distance Oracles in Quadratic Time

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    Let G be an unweighted, undirected graph. An additive k-spanner of G is a subgraph H that approximates all distances between pairs of nodes up to an additive error of +k, that is, it satisfies d_H(u,v) <= d_G(u,v)+k for all nodes u,v, where d is the shortest path distance. We give a deterministic algorithm that constructs an additive O(1)-spanner with O(n^(4/3)) edges in O(n^2) time. This should be compared with the randomized Monte Carlo algorithm by Woodruff [ICALP 2010] giving an additive 6-spanner with O(n^(4/3)log^3 n) edges in expected time O(n^2 log^2 n). An (alpha,beta)-approximate distance oracle for G is a data structure that supports the following distance queries between pairs of nodes in G. Given two nodes u, v it can in constant time compute a distance estimate d\u27 that satisfies d <= d\u27 <= alpha d + beta where d is the distance between u and v in G. Sommer [ICALP 2016] gave a randomized Monte Carlo (2,1)-distance oracle of size O(n^(5/3) polylog n) in expected time O(n^2 polylog n). As an application of the additive O(1)-spanner we improve the construction by Sommer [ICALP 2016] and give a Las Vegas (2,1)-distance oracle of size O(n^(5/3)) in time O(n^2). This also implies an algorithm that in O(n^2) time gives approximate distance for all pairs of nodes in G improving on the O(n^2 log n) algorithm by Baswana and Kavitha [SICOMP 2010]

    ARCH-COMP20 Category Report: Hybrid Systems with Piecewise Constant Dynamics and Bounded Model Checking

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    This report presents the results of a friendly competition for formal verification of continuous and hybrid systems with piecewise constant dynamics. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in 2020. In this fourth edition, five tools have been applied to solve six different benchmark problems in the category for piecewise constant dynamics: BACH, PHAVerLite, PHAVer/SX, TROPICAL, and XSpeed. Compared to last year, we combine the HBMC and HPWC categories of ARCH-COMP 2019 to a new category PCDB (hybrid systems with Piecewise Constant bounds on the Dynamics (HPCD) and Bounded model checking (BMC) of HPCD systems). The result is a snapshot of the current landscape of tools and the types of benchmarks they are particularly suited for. Due to the diversity of problems, we are not ranking tools, yet the presented results probably provide the most complete assessment of tools for the safety verification of continuous and hybrid systems with piecewise constant dynamics up to this date

    Confidential Consortium Framework: Secure Multiparty Applications with Confidentiality, Integrity, and High Availability

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    Confidentiality, integrity protection, and high availability, abbreviated to CIA, are essential properties for trustworthy data systems. The rise of cloud computing and the growing demand for multiparty applications however means that building modern CIA systems is more challenging than ever. In response, we present the Confidential Consortium Framework (CCF), a general-purpose foundation for developing secure stateful CIA applications. CCF combines centralized compute with decentralized trust, supporting deployment on untrusted cloud infrastructure and transparent governance by mutually untrusted parties. CCF leverages hardware-based trusted execution environments for remotely verifiable confidentiality and code integrity. This is coupled with state machine replication backed by an auditable immutable ledger for data integrity and high availability. CCF enables each service to bring its own application logic, custom multiparty governance model, and deployment scenario, decoupling the operators of nodes from the consortium that governs them. CCF is open-source and available now at https://github.com/microsoft/CCF.Comment: 16 pages, 9 figures. To appear in the Proceedings of the VLDB Endowment, Volume 1

    Survey of local algorithms

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    A local algorithm is a distributed algorithm that runs in constant time, independently of the size of the network. Being highly scalable and fault-tolerant, such algorithms are ideal in the operation of large-scale distributed systems. Furthermore, even though the model of local algorithms is very limited, in recent years we have seen many positive results for non-trivial problems. This work surveys the state-of-the-art in the field, covering impossibility results, deterministic local algorithms, randomised local algorithms, and local algorithms for geometric graphs.Peer reviewe

    Automatic Screening and Classification of Diabetic Retinopathy Eye Fundus Image

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    Diabetic Retinopathy (DR) is a disorder of the retinal vasculature. It develops to some degree in nearly all patients with long-standing diabetes mellitus and can result in blindness. Screening of DR is essential for both early detection and early treatment. This thesis aims to investigate automatic methods for diabetic retinopathy detection and subsequently develop an effective system for the detection and screening of diabetic retinopathy. The presented diabetic retinopathy research involves three development stages. Firstly, the thesis presents the development of a preliminary classification and screening system for diabetic retinopathy using eye fundus images. The research will then focus on the detection of the earliest signs of diabetic retinopathy, which are the microaneurysms. The detection of microaneurysms at an early stage is vital and is the first step in preventing diabetic retinopathy. Finally, the thesis will present decision support systems for the detection of diabetic retinopathy and maculopathy in eye fundus images. The detection of maculopathy, which are yellow lesions near the macula, is essential as it will eventually cause the loss of vision if the affected macula is not treated in time. An accurate retinal screening, therefore, is required to assist the retinal screeners to classify the retinal images effectively. Highly efficient and accurate image processing techniques must thus be used in order to produce an effective screening of diabetic retinopathy. In addition to the proposed diabetic retinopathy detection systems, this thesis will present a new dataset, and will highlight the dataset collection, the expert diagnosis process and the advantages of the new dataset, compared to other public eye fundus images datasets available. The new dataset will be useful to researchers and practitioners working in the retinal imaging area and would widely encourage comparative studies in the field of diabetic retinopathy research. It is envisaged that the proposed decision support system for clinical screening would greatly contribute to and assist the management and the detection of diabetic retinopathy. It is also hoped that the developed automatic detection techniques will assist clinicians to diagnose diabetic retinopathy at an early stage
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