We present significant improvements to a practical algorithm for the point-to-point shortest path problem on road networks that combines A∗ search, landmark-based lower bounds, and reach-based pruning. Through reach-aware landmarks, better use of cache, and improved algorithms for reach computation, we make preprocessing and queries faster while reducing the overall space requirements. On the r...

A constant-work-space algorithm has read-only access to an input array and may use only O(1) additional words of O(log n) bits, where n is the input size. We show how to triangulate a plane straight-line graph with n vertices in O(n) time and constant workspace. We also consider the problem of preprocessing a simple n-gon P for shortest path queries, where P is given by the ordered sequence of ...

The paper investigates local preprocessing of sensor data by autonomous agents. Means of artificial intelligence are applied to facilitate a rich and comprehensive preprocessing in order to reduce the amount of communication in spite of reasonable configuration costs. Scenarios for applications are presented, from which requirements are derived. After a short discussion of related approaches, a...

State-of-the-art algorithms for industrial instances of MaxSAT problem rely on iterative calls to a SAT solver. Preprocessing is crucial for the acceleration of SAT solving, and the key preprocessing techniques rely on the application of resolution and subsumption elimination. Additionally, satisfiability-preserving clause elimination procedures are often used. Since MaxSAT computation typicall...

In this study, we present a preprocessing method for quadrupole time-of-flight (Q-TOF) tandem mass spectra to increase the accuracy of database searching for peptide (protein) identification. Based on the natural isotopic information inherent in tandem mass spectra, we construct a decision tree after feature selection to classify the noise and ion peaks in tandem spectra. Furthermore, we recogn...

This paper describes the system developed by the Serendio team for the SemEval-2013 Task 2 competition (Task A). We use a lexicon based approach for discovering sentiments. Our lexicon is built from the Serendio taxonomy. The Serendio taxonomy consists of positive, negative, negation, stop words and phrases. A typical tweet contains word variations, emoticons, hashtags etc. We use preprocessing...

Medical image preprocessing and segmentation are very important in medical area. This paper deal with the implementation of simple algorithm for detection of skin cancer also and infected area. Skin cancer are the most common cancer in human. Skin cancer are curable cancer after early detection. In hospital doctor used a biopsy (a laboratory medical procedure). There are many different type of ...

In this paper we present sQueezeBF, an effective preprocessor for QBFs that combines various techniques for eliminating variables and/or clauses. In particular sQueezeBF combines (i) variable elimination by Q-resolution and equality reduction, and (ii) clause simplification via subsumption and self-subsumption resolution. The experimental analysis shows that sQueezeBF can produce significant re...

Preprocessing algorithms can dramatically improve the performance of even the most efficient SAT solvers on many problem instances [8]. Such algorithms simplify the formula by various means, including the deduction of necessary assignments, the addition of implied clauses, the deletion of redundant clauses, and the identification of equivalent literals. A number of preprocessors have been made ...

Techniques for the preprocessing of (not-necessarily convex) quadratic programs are discussed. Most of the procedures extend known ones from the linear to quadratic cases, but a few new preprocessing techniques are introduced. The implementation aspects are also discussed. Numerical results are finally presented to indicate the potential of the resulting code, both for linear and quadratic prob...