Vector Image Segmentation by Piecewise Continuous Approximation

In this article we present an approach to the segmentation problem by a piecewise approximation of the given image with continuous functions. Unlike the common approach of Mumford and Shah in our formulation of the problem the number of segments is a parameter, which can be estimated. The problem can be stated as: Compute the optimal segmentation with a fixed number of segments, then reduce the number of segments until the segmentation result fulfills a given suitability. This merging algorithm results in a multi-objective optimization, which is not only resolved by a linear combination of the contradicting error functions. To constrain the problem we use a finite dimensional vector space of functions in our approximation and we restrict the shape of the segments. Our approach results in a multi-objective optimization: On the one hand the number of segments is to be minimized, on the other hand the approximation error should also be kept minimal. The approach is sound theoretically and practically: We show that for L ²-images a Pareto-optimal solution exists and can be computed for the discretization of the image efficiently.     

Single string planning problem arising in liner shipping industries: A heuristic approach

We propose an efficient heuristic approach for solving instances of the Single String Planning Problem (SSPP) arising in the liner shipping industry. In the SSPP a Liner Service Provider (LSP) only revises one of its many operational strings, and it is assumed that the other strings are unchangeable. A string is a service route composed of a sequence of port calls—a call is a visit to a port followed by loading/unloading operations made by a vessel. In a string the vessel's round trip terminates at the same port that it started from, and the port calls follow a published itinerary. The SSPP is regularly encountered by all LSPs, and a major part of their seasonal network planning process is devoted to repeatedly solving SSPP for different regions using experts' knowledge. Despite the practical importance of the problem, very little has been written about it in the literature. A revision is carried out in the form of a controlled re-sequencing, insertion and elimination of ports from along the current string, given a set of ports limited to those that exist on the string and a set of potential ones. The outcome determines the required capacity, service level (frequency), call sequence, etc., corresponding to the LSP's seasonal strategy. Exact decomposition methods are limited and can solve only very small size instances—small in terms of the number of ports, vessel classes, vessel number and commodities. In contrast, the proposed heuristic method is an efficient approach for obtaining high quality and practical solutions to real-size instances in significantly less computational time.     

A general heuristic for vehicle routing problems

We present a unified heuristic which is able to solve five different variants of the vehicle routing problem: the vehicle routing problem with time windows (VRPTW), the capacitated vehicle routing problem (CVRP), the multi-depot vehicle routing problem (MDVRP), the site-dependent vehicle routing problem (SDVRP) and the open vehicle routing problem (OVRP).     

Dynamic Programming on the Word RAM

Dynamic programming is one of the fundamental techniques for solving optimization problems. In this paper we propose a general framework which can be used to decrease the time and space complexity of these algorithms with a logarithmic factor. The framework is based on word encoding, i.e. by representing subsolutions as bits in an integer. In this way word parallelism can be used in the evaluation of the dynamic programming recursion. Using this encoding the subset-sum problem can be solved in O( n b/ log b) time and O(b/ log b) space, where n is the number of integers given and b is the target sum. The knapsack problem can be solved in O( n m/ log m) time and O(m/ log m) space, where n is the number of items and m = max{b,z} is the maximum of the capacity b and the optimal solution value z . The problem of finding a path of a given length b in a directed acyclic graph G=(V,E) can be solved in O(|E|b/ log b) time and O(|V|b/ log b) space. Several other examples are given showing the generality of the achieved technique. Extensive computational experiments are provided to demonstrate that the achieved results are not only of theoretical interest but actually lead to algorithms which are up to two orders of magnitude faster than their predecessors. This is a surprising observation as the increase in speed is larger than the word size of the processor.     

Multi-objective and multi-constrained non-additive shortest path problems

Shortest path problems appear as subproblems in numerous optimization problems. In most papers concerning multiple objective shortest path problems, additivity of the objective is a de-facto assumption, but in many real-life situations objectives and criteria, can be non-additive. The purpose of this paper is to give a general framework for dominance tests for problems involving a number of non-additive criteria. These dominance tests can help to eliminate paths in a dynamic programming framework when using multiple objectives. Results on real-life multi-objective problems containing non-additive criteria are reported. We show that in many cases the framework can be used to efficiently reduce the number of generated paths.     

Dynamic Programming on the Word RAM

Abstract. Dynamic programming is one of the fundamental techniques for solving optimization problems. In this paper we propose a general framework which can be used to decrease the time and space complexity of these algorithms with a logarithmic factor. The framework is based on word encoding, i.e. by representing subsolutions as bits in an integer. In this way word parallelism can be used in the evaluation of the dynamic programming recursion. Using this encoding the subset-sum problem can be solved in O( n b/ log b) time and O(b/ log b) space, where n is the number of integers given and b is the target sum. The knapsack problem can be solved in O( n m/ log m) time and O(m/ log m) space, where n is the number of items and m = max{b,z} is the maximum of the capacity b and the optimal solution value z . The problem of finding a path of a given length b in a directed acyclic graph G=(V,E) can be solved in O(|E|b/ log b) time and O(|V|b/ log b) space. Several other examples are given showing the generality of the achieved technique. Extensive computational experiments are provided to demonstrate that the achieved results are not only of theoretical interest but actually lead to algorithms which are up to two orders of magnitude faster than their predecessors. This is a surprising observation as the increase in speed is larger than the word size of the processor.     

Effects of smoking cessation and reduction in asthmatics.

The present study examined the effect of smoking reduction and cessation on asthma regulation and biomarkers of exposure to cigarette smoke. In a prospective open design, we allocated 220 asthmatics among three groups: (a) Smoking reduction (reducers), with the aim of smoking fewer than seven cigarettes per day, (b) complete smoking cessation (abstainers), or (c) continuation of usual smoking (continuing smokers). Subjects used nicotine chewing gum or an oral nicotine inhaler to promote reduction and cessation. We monitored changes in the biomarkers carbon monoxide, cotinine, and thiocyanate, and in peak flow, medicine use, bronchial reactivity, and asthma symptoms. The analysis used the three outcome groups, regardless of original allocation to treatment groups. At 4 months, analysis of abstainers (n = 27), reducers (n = 33), and continuing smokers (n = 50) showed marked, statistically significant decreases in expired carbon monoxide of 17 ppm (abstainers) and 15 ppm (reducers); in plasma cotinine of 124 ng/ml (abstainers) and 122 ng/ml (reducers); and in plasma thiocyanate of 5.03 ng/ml (abstainers) and 3.74 ng/m (reducers). For abstainers, we observed improvements in the asthma-specific quality-of-life score, and reductions in self-reported day and night use of rescue beta2-agonists, in doses of inhaled corticosteroids, in daytime asthma symptoms, and in bronchial hyperreactivity. For reducers, smaller improvements occurred for night use of rescue beta2-agonists, doses of inhaled corticosteroids, and bronchial hyperreactivity. Smoking cessation resulted in a marked decrease in three biomarkers of cigarette smoke inhalation and improved asthma regulation, whereas smoking reduction had a less pronounced effect on biomarkers and only a small effect on asthma regulation.     

Plasma Treatment of Polyacetal-Copolymer, Polycarbonate, Polybutylene terephthalate and Nylon 6, 6 Surfaces to Improve the Adhesion of Ink

Polyacetal-copolymer (POMB), polycarbonate (PC), polybutylene terephthalate (PBT), and nylon 6, 6 (PA6, 6) have been treated in an electron cyclotron resonance (ECR) plasma chamber to improve their adhesion properties towards ink. The chemical composition, the surface free energy, and the macroscopic adhesion have been studied by X-ray photoelectron spectroscopy (XPS), contact angle measurements, cross-cut tests, and the Scotch Tape test. Their dependence on the neutral gas, the treatment time, the pressure, and the ageing in air have been investigated. The XPS results reveal that the plasma treatment allows one to clean the surface and, if reactive gases are used, to incorporate new chemical species. The static and dynamic contact angles decrease with the plasma treatment and continue to decrease after contact with air. Very slow hydrophobic recovery is visible in the advancing contact angle, whereas the receding contact angle remains non-measurable even after more than a week of air exposure. Lower pressures and longer treatment times (120 s) lead to better macroscopic adhesion and reproducibility. For optimal treatment conditions (0.5 Pa, 120s N₂ plasma treatment time), the improvement of the adhesion remains excellent after seven days exposure of the sample in air.     

Is there a health benefit of reduced tobacco consumption? A systematic review.

This review presents the available evidence on the health effects of reduced smoking. Smoking reduction was defined as reduction of the daily intake of tobacco without quitting. Only published papers were reviewed. Case reports and studies without a thorough definition of smoking reduction or health outcome were excluded. We searched in personal databases, BioMail Medline Search, Medline, the Cochrane Database of Systematic Reviews, and EMBASE. We followed the QUORUM standards for systematic reviews, and both authors read and discussed all publications. A total of 25 studies (31 publications) were identified: 8 articles reported on effects on the cardiovascular system; 11 on the airways; 7 on carcinogens, DNA damage, and lung cancer; 3 on birth weight; and 4 on other health effects. Some papers assessed more than one outcome. In most studies, reduction was defined as less than 50% of baseline tobacco consumption. Most of the studies were small, with the populations selected and short follow-up periods. The limited data suggest that a substantial reduction in smoking improves several cardiovascular risk factors and respiratory symptoms. In addition, smoking reduction is associated with a 25% decline in biomarkers and incidence of lung cancer and a small, mostly nonsignificant, increase in birth weight. There seem to be no substantial beneficial effects on lung function. The evidence on other health effects and mortality is too limited to draw conclusions. A substantial reduction in smoking seems to have a small health benefit, but more studies are needed to determine the long-term effects of smoking reduction.