A new state space approach is proposed to model the time-dependence in an extreme value process. The generalized extreme value distribution is extended to incorporate the time-dependence using a state space representation where the state variables either follow an autoregressive (AR) process or a moving average (MA) process with innovations arising from a Gumbel distribution. Using a Bayesian a...

We consider a two-phase method for computing the complete set of efficient solutions of the biobjective minimum spanning tree problem. The first phase computes the extreme efficient solutions by expanding the convex hull of the feasible space. The second phase repeatedly applies a k-best minimum spanning tree algorithm to find all nonextreme efficient solutions. We report results of our computa...

Extreme ultraviolet lithography is one of the modern lithography tools for high-volume manufacturing with 22 nm resolution and beyond. But critical challenges exist to the design and fabrication of large-scale and highly efficient diffraction transmission gratings, significantly reducing the feature sizes down to 22 nm and beyond. To achieve such a grating, the surface flatness, the line edge r...

Biological creatures with unique surface wettability have long served as a source of inspiration for scientists and engineers. More specifically, materials exhibiting extreme wetting properties, such as superhydrophilic and superhydrophobic surfaces, have attracted considerable attention because of their potential use in various applications, such as self-cleaning fabrics, anti-fog windows, ant...

The performance of many efficient algorithms critically depends on the tuning of their parameters, which on turn depends on the problem at hand, e.g., the performance of Evolutionary Algorithms critically depends on the judicious setting of the operator rates. The Adaptive Operator Selection (AOS) heuristic that is proposed here rewards each operator based on the extreme value of the fitness im...

Abstract A common approach to modelling extreme values is to consider the excesses above a high threshold as realisations of a non-homogeneous Poisson process. While this method offers the advantage of modelling using threshold-invariant extreme value parameters, the dependence between these parameters makes estimation more difficult. We present a novel approach for Bayesian estimation of the P...

Peripheral populations are those situated at the distribution margins of a species and are often subjected to more extreme abiotic and biotic conditions than those at the core. Here, we hypothesized that shorter repeat length and fewer heteroplasmic mitochondrial DNA (mtDNA) copies, which are associated with more efficient mitochondrial function, may be related to improved survival under extrem...

In many areas of medicine, security, and life sciences, we want to allocate limited resources to different sources in order to detect extreme values. In this paper, we study an efficient way to allocate these resources sequentially under limited feedback. While sequential design of experiments is well studied in bandit theory, the most commonly optimized property is the regret with respect to t...

Extreme values are often correlated over time, for example, in a financial time series, and these values carry various risks. Max-stable processes such as maxima of moving maxima (M3) processes have been recently considered in the literature to describe timedependent dynamics, which have been difficult to estimate. This paper first proposes a feasible and efficient Bayesian estimation method fo...