Another Fast and Simple DEM Depression-Filling Algorithm Based on Priority Queue Structure

Some depression cells with heights lower than their surrounding cells may often be found in Grid-based digital elevation models (DEM) dataset due to sampling errors.The depression-filling algorithm presented by Planchon and Darboux works very quickly compared to other published methods.Despite its simplicity and deli-cacy,this algorithm remains difficult to understand due to its three complex subroutines and its recursive execution.Another fast algorithm is presented in this article.The main idea of this new algorithm is as follows:first,the DEM dataset is viewed as an island and the outer space as an ocean;when the ocean level increases,the DEM cells on the island's boundary will be inundated;when a cell is inundated for the first time,its elevation is increased to the ocean level at that moment;after the ocean has inun-dated the entire DEM,all of the depressions are filled.The depression-removing processing is performed using a priority queue.Theoretically,this new algorithm is a fast algorithm despite the fact that it runs more slowly than Planchon and Darboux's method.Its time-complexity in both the worst case and in an average case is O(8nlog 2 (m)),which is close to O(n).The running speed of this algorithm depends mainly on the insertion operation of the priority queue.As shown by the tests,the depres-sion-filling effects of this algorithm are correct and valid,and the overall time consumption of this algorithm is less than twice the time consumed by Planchon & Darboux's method for handling a DEM smaller than 2500×2500 cells.More importantly,this new algorithm is simpler and easier to understand than Planchon and Darboux's method This advantage allows the correct program code to be written quickly.

VIRTUAL WAITING TIMES IN PRIORITY-M/G/1 QUEUES WITH VACARIONS

In this paper exhaustive-service priority-M/G/1 queueing systems with multiple vacations, single vacation and setup times are studied under the nonpreemptive and preemptive resume priority disciplines. For each of the six models analysed, the Laplace-Stieltjes transform of the virtual waiting time Wk(t) at time t of class k is derived by the method of collective marks. A sufficient condition for , where U has the standard normal distribution, is also given.

Stochastic Model for Multiple Classes and Subclasses Simple Documents Processing

The issue of document management has been raised for a long time, especially with the appearance of office automation in the 1980s, which led to dematerialization and Electronic Document Management (EDM). In the same period, workflow management has experienced significant development, but has become more focused on the industry. However, it seems to us that document workflows have not had the same interest for the scientific community. But nowadays, the emergence and supremacy of the Internet in electronic exchanges are leading to a massive dematerialization of documents;which requires a conceptual reconsideration of the organizational framework for the processing of said documents in both public and private administrations. This problem seems open to us and deserves the interest of the scientific community. Indeed, EDM has mainly focused on the storage (referencing) and circulation of documents (traceability). It paid little attention to the overall behavior of the system in processing documents. The purpose of our researches is to model document processing systems. In the previous works, we proposed a general model and its specialization in the case of small documents (any document processed by a single person at a time during its processing life cycle), which represent 70% of documents processed by administrations, according to our study. In this contribution, we extend the model for processing small documents to the case where they are managed in a system comprising document classes organized in subclasses;which is the case for most administrations. We have thus observed that this model is a Markovian ML×K/ML×K/1 queues network. We have analyzed the constraints of this model and deduced certain characteristics and metrics. In fine, the ultimate objective of our work is to design a document workflow management system, integrating a component of global behavior prediction.

ON THE SINGLE SERVER RETRIAL QUEUE WITH PRIORITY SUBSCRIBERS AND SERVER BREAKDOWNS

The author concerned the reliability evaluation as well as queueing analysis of M1, M2/G1, G2/1 retrial queues with two different types of primary customers arriving according to independent Poisson flows. In the case of blocking, the first type of customers can be queued whereas the second type of customers must leave the service area but return after some random period of time to try their luck again. The author assumes that the server is unreliable and it has a service-type dependent, exponentially distributed life time as well as a service-type dependent, generally distributed repair time. The necessary and sufficient condition for the system to be stable is investigated. Using a supplementary variable method, the author obtains a steady-state solution for queueing measures, and the transient as well as the steady-state solutions for reliability measures of interest.

Using a priority queuing approach to improve emergency department performance

Emergency department over-crowding has been a growing problem throughout the world.This paper presents a practical approach to estimate the waiting times for multi-class patients and apply the approach to reduce the waiting time for high priority patients.Patient flows with different levels of acuity are formulated based on the priority queue models.It derives explicit expressions of the wait time for the Markov queue and uses the concept of isomorphism to approximate the wait time in the general queue.Numerical results with simulation experiments are reported to display the accuracy of the approach.A case study from an emergency department indicates that the proposed approach can efficiently prioritize patient flows in decreasing waiting times.The queuing models have two features.First,the approximation applies to the general priority queues and reduces to the exact results of the Markov priority queue.Second,the models requires no iterative algorithm.