Minimum mean running time function generation using read only memory /

Vita.

Top Ten Box Office Blockbusters of All Time

‘Top Ten Box Office Blockbusters in Dollars’, is an ongoing series of works that represent the production budgets and worldwide gross profits of the top ten grossing films of all time. By displaying this data on top of the full running time of each blockbuster, the viewer’s attention is drawn back and forth between the amassing dollar figures, and the original film’s highly polished presentation. In doing so, the work aims to provide a new opportunity to enjoy these immensely popular films with a new sense of value. The exhibition was selected for the Artistic Program at MetroArts, Brisbane in 2010

Two-level k-means clustering algorithm for k-tau relationship establishment and linear-time classification

Partitional clustering algorithms, which partition the dataset into a pre-defined number of clusters, can be broadly classified into two types: algorithms which explicitly take the number of clusters as input and algorithms that take the expected size of a cluster as input. In this paper, we propose a variant of the k-means algorithm and prove that it is more efficient than standard k-means algorithms. An important contribution of this paper is the establishment of a relation between the number of clusters and the size of the clusters in a dataset through the analysis of our algorithm. We also demonstrate that the integration of this algorithm as a pre-processing step in classification algorithms reduces their running-time complexity.

Decentralised minimal-time dynamic consensus

This paper considers a group of agents that aim to reach an agreement on individually received time-varying signals by local communication. In contrast to static network averaging problem, the consensus considered in this paper is reached in a dynamic sense. A discrete-time dynamic average consensus protocol can be designed to allow all the agents tracking the average of their reference inputs asymptotically. We propose a minimal-time dynamic consensus algorithm, which only utilises a minimal number of local observations of a randomly picked node in a network to compute the final consensus signal. Our results illustrate that with memory and computational ability, the running time of distributed averaging algorithms can be indeed improved dramatically as suggested by Olshevsky and Tsitsiklis. © 2012 AACC American Automatic Control Council).

Assigning real-time tasks on heterogeneous multiprocessors with two unrelated types of processors

A preliminary version of this paper appeared in Proceedings of the 31st IEEE Real-Time Systems Symposium, 2010, pp. 239–248.

Efficient schedulability tests for real-time embedded systems with urgent routines

Task scheduling is one of the key mechanisms to ensure timeliness in embedded real-time systems. Such systems have often the need to execute not only application tasks but also some urgent routines (e.g. error-detection actions, consistency checkers, interrupt handlers) with minimum latency. Although fixed-priority schedulers such as Rate-Monotonic (RM) are in line with this need, they usually make a low processor utilization available to the system. Moreover, this availability usually decreases with the number of considered tasks. If dynamic-priority schedulers such as Earliest Deadline First (EDF) are applied instead, high system utilization can be guaranteed but the minimum latency for executing urgent routines may not be ensured. In this paper we describe a scheduling model according to which urgent routines are executed at the highest priority level and all other system tasks are scheduled by EDF. We show that the guaranteed processor utilization for the assumed scheduling model is at least as high as the one provided by RM for two tasks, namely 2(2√−1). Seven polynomial time tests for checking the system timeliness are derived and proved correct. The proposed tests are compared against each other and to an exact but exponential running time test.

C programs for solving the time-dependent Gross-Pitaevskii equation in a fully anisotropic trap

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Using state-space techniques to represent frequency dependent single-phase lines directly in time domain

This paper proposes to use a state-space technique to represent a frequency dependent line for simulating electromagnetic transients directly in time domain. The distributed nature of the line is represented by a multiple 1t section network made up of the lumped parameters and the frequency dependence of the per unit longitudinal parameters is matched by using a rational function. The rational function is represented by its equivalent circuit with passive elements. This passive circuit is then inserted in each 1t circuit of the cascade that represents the line. Because the system is very sparse, it is possible to use a sparsity technique to store only nonzero elements of this matrix for saving space and running time. The model was used to simulate the energization process of a 10 km length single-phase line. ©2008 IEEE.

Three time-based scale formulations for the two-stage lot sizing and scheduling in process industries

In this paper, we propose three novel mathematical models for the two-stage lot-sizing and scheduling problems present in many process industries. The problem shares a continuous or quasi-continuous production feature upstream and a discrete manufacturing feature downstream, which must be synchronized. Different time-based scale representations are discussed. The first formulation encompasses a discrete-time representation. The second one is a hybrid continuous-discrete model. The last formulation is based on a continuous-time model representation. Computational tests with state-of-the-art MIP solver show that the discrete-time representation provides better feasible solutions in short running time. On the other hand, the hybrid model achieves better solutions for longer computational times and was able to prove optimality more often. The continuous-type model is the most flexible of the three for incorporating additional operational requirements, at a cost of having the worst computational performance. Journal of the Operational Research Society (2012) 63, 1613-1630. doi:10.1057/jors.2011.159 published online 7 March 2012

Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.

Integrating software testing and run-time checking in an assertion verification framework

We have designed and implemented a framework that unifies unit testing and run-time verification (as well as static verification and static debugging). A key contribution of our approach is that a unified assertion language is used for all of these tasks. We first propose methods for compiling runtime checks for (parts of) assertions which cannot be verified at compile-time via program transformation. This transformation allows checking preconditions and postconditions, including conditional postconditions, properties at arbitrary program points, and certain computational properties. The implemented transformation includes several optimizations to reduce run-time overhead. We also propose a minimal addition to the assertion language which allows defining unit tests to be run in order to detect possible violations of the (partial) specifications expressed by the assertions. This language can express for example the input data for performing the unit tests or the number of times that the unit tests should be repeated. We have implemented the framework within the Ciao/CiaoPP system and effectively applied it to the verification of ISO-prolog compliance and to the detection of different types of bugs in the Ciao system source code. Several experimental results are presented that ¡Ilústrate different trade-offs among program size, running time, or levéis of verbosity of the messages shown to the user.

Using combined static analysis and profiling for logic program execution time estimation

Predicting statically the running time of programs has many applications ranging from task scheduling in parallel execution to proving the ability of a program to meet strict time constraints. A starting point in order to attack this problem is to infer the computational complexity of such programs (or fragments thereof). This is one of the reasons why the development of static analysis techniques for inferring cost-related properties of programs (usually upper and/or lower bounds of actual costs) has received considerable attention.

Integrating software testing and run-time checking in an assertion verification framework.

We have designed and implemented a framework that unifies unit testing and run-time verification (as well as static verification and static debugging). A key contribution of our approach is that a unified assertion language is used for all of these tasks. We first propose methods for compiling runtime checks for (parts of) assertions which cannot be verified at compile-time via program transformation. This transformation allows checking preconditions and postconditions, including conditional postconditions, properties at arbitrary program points, and certain computational properties. The implemented transformation includes several optimizations to reduce run-time overhead. We also propose a minimal addition to the assertion language which allows defining unit tests to be run in order to detect possible violations of the (partial) specifications expressed by the assertions. This language can express for example the input data for performing the unit tests or the number of times that the unit tests should be repeated. We have implemented the framework within the Ciao/CiaoPP system and effectively applied it to the verification of ISO-prolog compliance and to the detection of different types of bugs in the Ciao system source code. Several experimental results are presented that illustrate different trade-offs among program size, running time, or levels of verbosity of the messages shown to the user.

Night time performance of a storage integrated solar thermophotovoltaic (SISTPV) system

Energy storage at low maintenance cost is one of the key challenges for generating electricity from the solar energy. This paper presents the theoretical analysis (verified by CFD) of the night time performance of a recently proposed conceptual system that integrates thermal storage (via phase change materials) and thermophotovoltaics for power generation. These storage integrated solar thermophotovoltaic (SISTPV) systems are attractive owing to their simple design (no moving parts) and modularity compared to conventional Concentrated Solar Power (CSP) technologies. Importantly, the ability of high temperature operation of these systems allows the use of silicon (melting point of 1680 K) as the phase change material (PCM). Silicon's very high latent heat of fusion of 1800 kJ/kg and low cost ($1.70/kg), makes it an ideal heat storage medium enabling for an extremely high storage energy density and low weight modular systems. In this paper, the night time operation of the SISTPV system optimised for steady state is analysed. The results indicate that for any given PCM length, a combination of small taper ratio and large inlet hole-to-absorber area ratio are essential to increase the operation time and the average power produced during the night time. Additionally, the overall results show that there is a trade-off between running time and the average power produced during the night time. Average night time power densities as high as 30 W/cm(2) are possible if the system is designed with a small PCM length (10 cm) to operate just a few hours after sun-set, but running times longer than 72 h (3 days) are possible for larger lengths (50 cm) at the expense of a lower average power density of about 14 W/cm(2). In both cases the steady state system efficiency has been predicted to be about 30%. This makes SISTPV systems to be a versatile solution that can be adapted for operation in a broad range of locations with different climate conditions, even being used off-grid and in space applications.

Quadratic Time Computable Instances of MaxMin and MinMax Area Triangulations of Convex Polygons

We consider the problems of finding two optimal triangulations of a convex polygon: MaxMin area and MinMax area. These are the triangulations that maximize the area of the smallest area triangle in a triangulation, and respectively minimize the area of the largest area triangle in a triangulation, over all possible triangulations. The problem was originally solved by Klincsek by dynamic programming in cubic time [2]. Later, Keil and Vassilev devised an algorithm that runs in O(n^2 log n) time [1]. In this paper we describe new geometric findings on the structure of MaxMin and MinMax Area triangulations of convex polygons in two dimensions and their algorithmic implications. We improve the algorithm’s running time to quadratic for large classes of convex polygons. We also present experimental results on MaxMin area triangulation.