Assessment of the types of public building maintenance contracts in Saudi Arabia

The study revealed that Fixed Price, Cost Plus and Purchased Labour contracts are the top three maintenance contracts adopted whilst Unit Price, Cost Plus A Percentage Fee contracts are alternatives used in the Kingdom. Some other types of maintenance contract were thought to be inappropriate by ministry departments.     

Greedy hot-potato routing on the two-dimensional mesh

Summary We propose hot-potato (or, deflection) packet routing algorithms on the two-dimensional mesh. The algorithms are strongly greedy in the sense that they attempt to send packets in good directions whenever possible. Furthermore, the routing operations are simple and independent of the time that has elapsed. The first algorithm gives the best evacuation time known for delivering all the packets to their destinations. A batch ofk packets with maximal source-to-destination distanced _max is delivered in 2(k-1)+d _max. The second algorithm improves this bound tok+d _max when all packets are destined to the same node. This also implies a new bound for the multitarget case, which is the first to take into account the number of in-edges of a node. The third algorithm is designed for routing permutations with source-to-destination distance at most three, in which case the algorithm terminates in at most seven steps. We also show a lower bound of five steps for this problem. Ishai Ben-Aroya received the B.A. and M.Sc. in computer science from the Technion (Israel Institute of Technology). He is currently working with Microsoft Israel R&D group. His main interests include Routing Algorithms, Cryptography and Computer Security. Tamar Eilam received the B.A. degree in Computer Science from the Technion IIL in 1995, and is currently studying towards her M.A. degree. Assaf Schuster received his B.A., M.A. and Ph.D. degrees in Computer Science from the Hebrew University of Jerusalem (the last one in 1991). He is currently a lecturer at the Technion IIL. His main interests include Networks and Routing Algorithms, Parallel and Distributed Computation, Optical Computation and Communication, Dynamically Reconfiguring Networks, and Greedy Hot Potato Routing.This work was supported in part by the French-Israeli grant for cooperation in Computer Science, and by a grant from the Israeli Ministry of Science. An extended abstract appeared in proc. 2nd European Symposium on Algorithms, September 1994     

Computation of nonlinear functionals in particle methods

We consider the numerical computation of nonlinear functionals of distribution functions approximated by point measures. Two methods are described and estimates for the speed of convergence as the number of points tends to infinity are given. Moreover, numerical results for the entropy functional are presented.     

A Semi-Lagrangian Method for 3-D Fokker Planck Equations for Stochastic Dynamical Systems on the Sphere

In this paper, we consider stochastic dynamical systems on the sphere and the associated Fokker–Planck equations. A semi-Lagrangian method combined with a Finite Volume discretization of the sphere is presented to solve the Fokker–Planck equation. The method is applied to a typical problem in fiber dynamics and textile production. The numerical results are compared to explicit solutions and Monte-Carlo solutions.     

Fusing distributional and experiential information for measuring semantic relatedness

Models of semantic relatedness have usually focused on language-based distributional information without taking into account “experiential data” concerning the embodied sensorial source of the represented concepts. In this paper, we present an integrative cognitive model of semantic relatedness. The model – semantic family resemblance – uses a variation of the co-product as a mathematical structure that guides the fusion of distributional and experiential information. Our algorithm provides superior results in a set expansion task and a significant correlation with two benchmarks of human rated word-pair similarity datasets.     

Improving the SMAC atmospheric correction code by analysis of Meteosat Second Generation NDVI and surface reflectance data

In order to obtain high quality data, the correction of atmospheric perturbations acting upon land surface reflectance measurements recorded by a space-based sensor is an important topic within remote sensing. For many years the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer model and the Simplified Method for Atmospheric Correction (SMAC) codes have been used for this atmospheric correction, but previous studies have shown that in a number of situations the quality of correction provided by the SMAC is low. This paper describes a method designed to improve the quality of the SMAC atmospheric correction algorithm through a slight increase in its computational complexity. Data gathered from the SEVIRI aboard Meteosat Second Generation (MSG) is used to validate the additions to SMAC, both by comparison to simulated data corrected using the highly accurate 6S method and by comparison to in-situ and 6S corrected SEVIRI data gathered for two field sites in Africa. The additions to the SMAC are found to greatly increase the quality of atmospheric correction performed, as well as broaden the range of atmospheric conditions under which the SMAC can be applied. When examining the Normalised Difference Vegetation Index (NDVI), the relative difference between SMAC and in-situ values decreases by 1.5% with the improvements in place. Similarly, the mean relative difference between SMAC and 6S reflectance values decreases by a mean of 13, 14.5 and 8.5% for Channels 1, 2 and 3 respectively. Furthermore, the processing speed of the SMAC is found to remain largely unaffected, with only a small increase in the time taken to process a full SEVIRI scene. Whilst the method described within this paper is only applicable to SEVIRI data, a similar approach can be applied to other data sources than SEVIRI, and should result in a similar accuracy improvement no matter which instrument supplies the original data.     

Shrinking‐horizon dynamic programming

We describe a heuristic control policy for a general finite‐horizon stochastic control problem, which can be used when the current process disturbance is not conditionally independent of the previous disturbances, given the current state. At each time step, we approximate the distribution of future disturbances (conditioned on what has been observed) by a product distribution with the same marginals. We then carry out dynamic programming (DP), using this modified future disturbance distribution, to find an optimal policy, and in particular, the optimal current action. We then execute only the optimal current action. At the next step, we update the conditional distribution, and repeat the process, this time with a horizon reduced by one step. (This explains the name ‘shrinking‐horizon dynamic programming’). We explain how the method can be thought of as an extension of model predictive control, and illustrate our method on two variations on a revenue management problem. Copyright © 2010 John Wiley & Sons, Ltd.     

Scheduling a maintenance activity and due-window assignment on a single machine

We study a single machine scheduling and due-window assignment problem. In addition to the traditional decisions regarding sequencing the jobs and scheduling the due-window, we allow an option for performing a maintenance activity. This activity requires a fixed time interval during which the machine is turned off and no production is performed. On the other hand, after the maintenance time, the machine becomes more efficient, as reflected in the new shortened job processing times. The objective is to schedule the jobs, the due-window and the maintenance activity, so as to minimize the total cost consisting of earliness, tardiness, and due-window starting time and size. We introduce an efficient (polynomial time) solution for this problem.     

Meshfree method for fluctuating hydrodynamics

In the current study a meshfree Lagrangian particle method for the Landau–Lifshitz Navier–Stokes (LLNS) equations is developed. The LLNS equations incorporate thermal fluctuation into macroscopic hydrodynamics by the addition of white noise fluxes whose magnitudes are set by a fluctuation–dissipation theorem. The study focuses on capturing the correct variance and correlations computed at equilibrium flows, which are compared with available theoretical values. Moreover, a numerical test for the random walk of standing shock wave has been considered for capturing the shock location.     

A Technology Readiness Level scale for iron and steel industries

The Technology Readiness Level (TRL) scale is one of the most popular maturity assessment techniques used by industrial firms worldwide. However, it is not a panacea that will work for every firm or every industry in its original form. Consequently, for the scale to be truly useful, it has to be adapted to fit the unique features of different firms and industries. In this article, we propose a revised and domain-specific TRL scale for evaluating technology maturity in iron and steel industries. This revised scale takes into account the idiosyncrasies of such firms, for example, product/process interdependencies, scaling problems, the reliance on pilot and demonstration experiments, and the fact that input and output materials are ingredients rather than components. The revised TRL scale helps managers to assess technology maturity and reduce risk by delivering better project and technology evaluations and providing a ‘common language’.