305 research outputs found

    Multi-Hazard Assessment of Seismic and Scour Effects on Rural Bridges with Unknown Foundations

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    This chapter proposes a probabilistic framework for assessing seismic and scour effects on existing river-crossing bridge structures. The emphasis is on bridge structures in rural areas, for which it has been recognized that a large number of rural bridges have unknown foundation types and further are subject to both flooding-induced scour and seismic damage. With a review of the US-based rural bridges, this chapter presents a probabilistic framework for bridge performance assessment. Using a representative rural bridge model, the fragility results for the bridge reveal that scour tends to be beneficial in reducing structural damage at slight to moderate seismic intensities and to be detrimental in increasing collapse potential at high-level intensities. The demand hazard curves further quantify probabilistically the occurrence of local damage and global collapse, and systematically reveal the complex effects of scour as a hydraulic hazard on bridge structures

    Digital Photograph Analysis for Measuring Percent Plant Cover in the Arctic

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    Long-term satellite remote sensing data, when properly calibrated and validated against ground monitoring, could provide valuable data sets for assessing climate change impacts on ecosystems, wildlife, and other important aspects of life in the Arctic. Percent plant cover is ideal for seasonal and long-term ground monitoring because it can be observed non-destructively and is closely related to other key ecosystem variables, such as biomass and leaf area index (LAI). Accurately measuring percent plant cover in the Arctic, however, has been a challenge. Advances in digital photography and imageprocessing techniques have provided the potential to measure vegetation cover accurately. In this paper we report an adapted method for quantifying percent plant cover based on plot digital photograph classification (PDPC). In this digital image analysis, the red, green, and blue image channels and the intensity, hue, and saturation image channels were used together to ensure more accurate cover measurement and labeling of plant species. We evaluated the accuracy of the PDPC method and two other techniques, visual estimate and digital grid overlay, by testing against artificial plots with known percent cover, by comparing with destructively measured LAI, and by comparing results of the three methods. Our evaluation indicates that the PDPC method is the most accurate. In addition, PDPC has the advantages of being objective, quick in the field, and suitable for measuring percent plant cover in the Arctic at the level of functional types or species groups.Lorsqu'elles sont bien calibrées et qu'elles sont validées contre le dépistage terrestre, les données résultant de la télédétection satellitaire à long terme pourraient fournir d'importants ensembles de données en vue de l'évaluation des incidences du changement climatique sur les écosystèmes, la faune et d'autres aspects-clés de la vie dans l'Arctique. Le pourcentage de couverture végétale est idéal pour le dépistage saisonnier et le dépistage terrestre à long terme parce qu'il peut être observé sans qu'il n'y ait de destruction et parce qu'il est étroitement lié à d'autres variables-clés se rapportant aux écosystèmes, comme la biomasse et l'indice de surface foliaire (ISF). Toutefois, dans l'Arctique, la mesure exacte du pourcentage de couverture végétale représente un défi. Les progrès réalisés dans les domaines de la photographie numérique et des techniques de traitement d'images fournissent la possibilité de mesurer la couverture végétale avec précision. Dans cette communication, nous faisons état d'une méthode adaptée permettant de quantifier le pourcentage de couverture végétale en fonction de la classification de photographies numériques de parcelles. Dans le cadre de l'analyse d'images numériques, les canaux rouges, verts et bleus des images ainsi que les canaux d'intensité, de tonalité et de saturation des images ont été utilisés pour donner lieu à la mesure plus exacte de la couverture végétale et à l'étiquetage des espèces végétales. Nous avons évalué l'exactitude de la méthode de classification de photographies numériques de parcelles de même que celle de deux autres techniques, soit l'estimation visuelle et la superposition de grilles numériques en faisant des essais à la lumière de parcelles artificielles dont le pourcentage de couverture végétale était connu et en les comparant avec des ISF mesurés de manière destructive, puis en comparant les résultats des trois méthodes. Selon notre évaluation, la méthode consistant en la classification de photographies numériques de parcelles PDPC est la plus précise. La classification de photographies numériques de parcelles a également l'avantage d'être objective, d'être rapide sur le terrain et de se prêter à la mesure du pourcentage de couverture végétale dans l'Arctique en ce qui a trait aux types fonctionnels ou aux groupements d'espèces

    Decentralized Asset Custody Scheme with Security against Rational Adversary

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    Asset custody is a core financial service in which the custodian holds in-safekeeping assets on behalf of the client. Although traditional custody service is typically endorsed by centralized authorities, decentralized custody scheme has become technically feasible since the emergence of digital assets, and furthermore, it is greatly needed by new applications such as blockchain and DeFi (Decentralized Finance). In this work, we propose a framework of decentralized asset custody scheme that is able to support a large number of custodians and safely hold customer assets of multiple times the value of the total security deposit. The proposed custody scheme distributes custodians and assets into many custodian groups via combinatorial designs, where each group fully controls the assigned assets. Since every custodian group is small, the overhead cost is significantly reduced. The liveness is also improved because even a single alive group would be able to process transactions. The security of this custody scheme is guaranteed under the rational adversary model, such that any adversary corrupting a bounded fraction of custodians cannot move assets more than the security deposit paid. We further analyze the security and performance of our constructions from both theoretical and experimental sides and give explicit examples with concrete numbers and figures for a better understanding of our results

    On Tightness of the Tsaknakis-Spirakis Algorithm for Approximate Nash Equilibrium

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    Finding the minimum approximate ratio for Nash equilibrium of bi-matrix games has derived a series of studies, started with 3/4, followed by 1/2, 0.38 and 0.36, finally the best approximate ratio of 0.3393 by Tsaknakis and Spirakis (TS algorithm for short). Efforts to improve the results remain not successful in the past 14 years. This work makes the first progress to show that the bound of 0.3393 is indeed tight for the TS algorithm. Next, we characterize all possible tight game instances for the TS algorithm. It allows us to conduct extensive experiments to study the nature of the TS algorithm and to compare it with other algorithms. We find that this lower bound is not smoothed for the TS algorithm in that any perturbation on the initial point may deviate away from this tight bound approximate solution. Other approximate algorithms such as Fictitious Play and Regret Matching also find better approximate solutions. However, the new distributed algorithm for approximate Nash equilibrium by Czumaj et al. performs consistently at the same bound of 0.3393. This proves our lower bound instances generated against the TS algorithm can serve as a benchmark in design and analysis of approximate Nash equilibrium algorithms

    Coordinated Dynamic Bidding in Repeated Second-Price Auctions with Budgets

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    In online ad markets, a rising number of advertisers are employing bidding agencies to participate in ad auctions. These agencies are specialized in designing online algorithms and bidding on behalf of their clients. Typically, an agency usually has information on multiple advertisers, so she can potentially coordinate bids to help her clients achieve higher utilities than those under independent bidding. In this paper, we study coordinated online bidding algorithms in repeated second-price auctions with budgets. We propose algorithms that guarantee every client a higher utility than the best she can get under independent bidding. We show that these algorithms achieve maximal coalition welfare and discuss bidders' incentives to misreport their budgets, in symmetric cases. Our proofs combine the techniques of online learning and equilibrium analysis, overcoming the difficulty of competing with a multi-dimensional benchmark. The performance of our algorithms is further evaluated by experiments on both synthetic and real data. To the best of our knowledge, we are the first to consider bidder coordination in online repeated auctions with constraints.Comment: 43 pages, 12 figure
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