Remotely sensed indicators of habitat heterogeneity: Use of synthetic aperture radar in mapping vegetation structure and bird habitat

An integrated remote sensing/field ecology project linked the use of synthetic aperture radar (SAR) and aerial photography to studies of landscape spatial heterogeneity and bird community ecology. P-, L-, and C-band SAR data, collected over a section of Kakadu National Park in Australia's Northern Territory during the Joint NASA/Australia DC-8 data acquisition campaign, were analyzed in light of field data integrating vegetation structure and floristics with bird abundances across a heterogeneous study site. Results indicate that SAR data are able to discern structural differences relevant to bird habitat quality within floristically homogeneous stands, while multispectral sensors successfully identified floristic differences among habitat types. Simplifying indices of bird diversity showed ambiguous changes across the site; however, the abundances of individual species were observed to change significantly across both floristic and structural gradients. These results suggest that efforts to map bird diversity should focus on species-specific habitat relationships and that some measure of vegetation structure is needed to understand bird habitat. The approach employed here advances the use of SAR data in the three-dimensional mapping of animal habitats from remotely sensed data, and extends current capabilities for mapping and modeling large-scale patterns in the distribution of biological diversity.     

Compact Mathematical Formulation for Graph Partitioning

The graph partitioning problem consists of dividing the vertices of a graph into clusters, such that the weight of the edges crossing between clusters is minimized. We present a new compact mathematical formulation of this problem, based on the use of binary representation for the index of clusters assigned to vertices. This new formulation is almost minimal in terms of the number of variables and constraints and of the density of the constraint matrix. Its linear relaxation brings a very fast computational resolution, compared with the standard one.Experiments were conducted on classical large benchmark graphs designed for comparing heuristic methods. On one hand, these experiments show that the new formulation is surprisingly less time efficient than expected on general k-partitioning problems. On the other hand, the new formulation applied on bisection problems allows to obtain the optimum solution for about ten instances, where only best upper bounds were previously known.     

Conversion of Full-Scale Wet Scrubbers to Biotrickling Filters for H2S Control at Publicly Owned Treatment Works

Until recently, biological treatment of odors in biofilters or biotrickling filters was thought to require a longer gas contact time than chemical scrubbing, hence bioreactors for air treatment required a larger footprint. This paper discusses the conversion of chemical scrubbers to biological trickling filters. Initially, research was conducted with a laboratory-scale biotrickling filter. An effective open-pore polyurethane packing material was identified and H2S biotreatment performance was quantified. Key technical issues in determining the general suitability of converting wet scrubbers to biotrickling filters were identified, and a generic ten-step conversion procedure was developed. Following the laboratory research, five full-scale chemical scrubbers treating odorous air at the Sanitation District of Orange County, Calif., were converted to biotrickling filters. The original airflow rate was maintained, resulting in a gas contact time as low as 1.6–3.1?s. The converted biotrickling filters demonstrated an excellent capability for treating high H2S concentrations to concentrations below regulatory limits. This study shows outstanding potential for converting chemical scrubbers to biotrickling filters at publicly owned treatment works.     

Towards Pseudonymous e-Commerce

The lack of privacy is one of the main reasons that limits trust in e-commerce. Current e-commerce practice enforces a customer to disclose her identity to the e-shop and the use of credit cards makes it straightforward for an e-shop to know the real identity of its customers. Although there are some payment systems based on untraceable tokens, they are not as widely used as credit cards. Furthermore, even without buying anything, a customer is already disclosing some information about who or where she may be by just connecting to the e-shop's web server and leaving behind an IP-address. In this paper, we present novel components that enable secure pseudonymous e-commerce. On the one hand, these components allow a customer to browse through an e-shop, select goods, and pay the goods with her credit card such that neither the e-shop operator nor the credit card issuer nor an eavesdropper is able to get any information about the customer's identity. On the other hand, it is guaranteed that none of the involved parties is able to act dishonestly during the credit card payment. Such a system could greatly enhance trust in e-commerce since it overcomes the customers' privacy concerns.     

Sensitivity Analysis for Scheduling Problems

This paper represents a first attempt at a systematic study of sensitivity analysis for scheduling problems. Because schedules contain both combinatorial and temporal structures, scheduling problems present unique issues for sensitivity analysis. Some of the issues that we discuss have not been considered before. Others, while studied before, have not been explored in the context of scheduling. The applicability of these issues is illustrated using well-known scheduling models. We provide fast methods to determine when a previously optimal schedule remains optimal. Other methods restore an optimal schedule after a parameter change. The value of studying the sensitivity of an optimal sequence instead of the sensitivity of an optimal schedule is demonstrated. We show that, for some problems, sensitivity analysis results depend on the positions of jobs with changed parameters. We identify scheduling problems where performing additional or different computations during optimization facilitates sensitivity analysis. To improve the robustness of an optimal schedule, selection among multiple optimal schedules is considered. We discuss which types of sensitivity analysis questions are intractable because the scheduling problem itself is intractable. We also study how heuristic error bounds vary when the data of a scheduling problem is continuously modified. Although we focus on scheduling problems, several of the issues we discuss and our classification scheme can be extended to other optimization problems.     

Nonlinear averaging theorems, and the determination of parameter convergence rates in adaptive control

The paper presents nonlinear averaging theorems for two-time scale systems, where the dynamics of the fast system are allowed to vary with the slow system. The results are applied to the Narendra-Valavani adaptive control algorithm, and estimates of the parameter convergence rates are obtained which do not rely on a linearization of the system around the equilibrium, and therefore are valid in a larger region in the parameter space.     

Representing Animations by Principal Components

In this paper, we present a representation for three-dimensional geometric animation sequences. Different from standard key-frame techniques, this approach is based on the determination of principal animation components and decouples the animation from the underlying geometry. The new representation supports progressive animation compression with spatial, as well as temporal, level-of-detail and high compression ratios. The distinction of animation and geometry allows for mapping animations onto other objects.     

Microwave radiation as heating method in the synthesis of titanium dioxide nanoparticles from hexafluorotitanate-organic salts

Nanocrystalline anatase was obtained from ionic liquid-like precursors containing hexafluorotitanate-organic salts and less than 25 wt.% of water, and using boric acid as fluoride scavenger. Two alternative heating methods were explored using either a conventional oven or a domestic microwave apparatus. A significant reduction in the reaction time from 24 h to only few minutes was obtained using the microwave route. The as-prepared materials were characterized by X-ray diffraction, transmission electron microscopy, nitrogen sorption analysis, and attenuated total reflectance Fourier transformed infrared, X-ray photoelectronic and Raman spectroscopes. The convenience of using the microwave heating option was a function of the organic cation present in the precursor. Thus, organic ammonium cations containing only hydrocarbon substituents, such as diethylammonium, phenylammonium and benzyltrimethylammonium led to the precipitation of nanocrystalline anatase powder with high specific surface area (up to 120 m² g⁻¹) in a short processing time (1-3 min). Otherwise, alcohol and carboxylate functionalized cations decomposed under microwave treatment. Moreover, the choice of the organic cation allowed tuning several properties of the end material, such as particle size and pore morphology.     

A robust bus evacuation model with delayed scenario information

Due to natural or man-made disasters, the evacuation of a whole region or city may become necessary. Apart from private traffic, the emergency services also need to consider transit-dependent evacuees which have to be transported from collection points to secure shelters outside the endangered region with the help of a bus fleet. We consider a simplified version of the arising bus evacuation problem (BEP), which is a vehicle scheduling problem that aims at minimizing the network clearance time, i.e., the time needed until the last person is brought to safety. In this paper, we consider an adjustable robust formulation without recourse for the BEP, the robust bus evacuation problem (RBEP), in which the exact numbers of evacuees are not known in advance. Instead, a set of likely scenarios is known. After some reckoning time, this uncertainty is eliminated and planners are given exact figures. The problem is to decide for each bus, if it is better to send it right away—using uncertain information on the evacuees—or to wait until the the scenario becomes known. We present a mixed-integer linear programming formulation for the RBEP and discuss solution approaches; in particular, we present a tabu search framework for finding heuristic solutions of acceptable quality within short computation time. In computational experiments using both randomly generated instances and the real-world scenario of evacuating the city of Kaiserslautern, Germany, we compare our solution approaches.