Environmental impact of castor oil catalytic transfer hydrogenation

In the vegetable oil chemical industry, hydrogenation is one of the most important processes. An alternative method for vegetable oil hydrogenation is the use of catalytic transfer hydrogenation (CTH), which can utilize organic molecules as hydrogen donors at ambient pressure. These alternative processes should be optimized in relation to the variables required for a good conversion and impacts should also be known to be minimized. An assessment of the environmental impact of laboratory scale chemical processes is an important tool to improve the technological aspects of a process (increased yields, reduced production times, lower costs) and it can also lead to the creation of a cleaner technology. Using the Leopold Matrix, we have succeeded in developing a more efficient and cleaner process for the CTH of castor oil using Raney Ni as a catalyst and cyclohexene or isopropanol as a hydrogen donor solvent. The results of the technical and environmental assessments showed that the extent of conversion for the unsaturation reaction was high (>99 %), and the environmental impact of the process could be significantly reduced to create a cleaner technology. It was found, after process optimization, that the remaining environmental impacts were negative (67.48 %), local (78.95 %), temporary (95.33 %), direct (80.12 %), and reversible (95.32 %).     

Data-parallel,volumerendering algorithms

In this presentation, we consider the image-composition scheme for parallel volume rendering in which each processor is assigned a portion of the volume. A processor renders its data by using any existing volume-rendering algorithm. We describe one such parallel algorithm that also takes advantage of vector-processing capabilities. The resulting images from all processors are then combined (composited) in visibility order to form the final image. The major advantage of this approach is that, as viewing and shading parameters change, only 2D partial images, and not 3D volume data, are communicated among processors. Through experimental results and performance analysis, we show that our parallel algorithm is amenable to extremely efficient implementations on distributed memory, multiple instruction-multiple data (MIMD), vector-processor architectures. This algorithm is also very suitable for hardware implementation based on image composition architectures. It supports various volume-rendering algorithms, and it can be extended to provide load-balanced execution.     

Steering Image Generation with Wavelet Based Perceptual Metric

It is often the case that images generated by image synthesis algorithms are judged by visual examination. The user resorts to an iterative refinement process of inspection and rendering until a satisfactory image is obtained. In this paper we propose quantitative metrics to compare images that arise from an image synthesis algorithm. The intent is to be able to guide the refinement process inherent in image synthesis. The Mean-Square-Error (MSE) has been traditionally employed to guide this process. However, it is not a viable metric for image synthesis control. We propose the use of a wavelet based perceptual metric which incorporates the frequency response of the Human Visual System. A useful aspect of the wavelet based metric is its ability to selectively measure the changes to structures of different sizes and scales in specific locations. Also, by resorting to the use of wavelets of various degrees of regularity, one can seek different levels of smoothness in an image. It is rare that such level of control can be obtained from a metric other than a wavelet based metric. We show the usefulness of our metric by examining its effectiveness in providing insights for common operations of an image synthesis algorithm (e.g., blurring). We also provide some examples of its use in rendering algorithms frequently used in graphics.     

Action dependencies in privacy-preserving multi-agent planning

Collaborative privacy-preserving planning (CPPP) is a multi-agent planning task in which agents need to achieve a common set of goals without revealing certain private information. In many CPPP algorithms, the individual agents reason about a projection of the multi-agent problem onto a single-agent classical planning problem. For example, an agent can plan as if it controls the public actions of other agents, ignoring any private preconditions and effects theses actions may have, and use the cost of this plan as a heuristic estimate of the cost of the full, multi-agent plan. Using such a projection, however, ignores some dependencies between agents’ public actions. In particular, it does not contain dependencies between public actions of other agents caused by their private facts. We propose a projection in which these private dependencies are maintained. The benefit of our dependency-preserving projection is demonstrated by using it to produce high-level plans in a new privacy-preserving planner, and as a heuristic for guiding forward search privacy-preserving algorithms. Both are able to solve more benchmark problems than any other state-of-the-art privacy-preserving planner. This more informed projection does not explicitly expose any private fact, action, or precondition. In addition, we show that even if an adversary agent knows that an agent has some private objects of a given type (e.g., trucks), it cannot infer the number of such private objects that the agent controls. This introduces a novel form of strong privacy, which we call object-cardinality privacy, that is motivated by real-world requirements.     

Model-based diagnosis techniques for Internet delay diagnosis with dynamic routing

In this paper we propose a model-based approach to diagnose latencies in computer networks. We formalize this problem as a model-based diagnosis (MBD) problem and propose a range of methods to solve it. Three solution approaches are proposed: a conflict-directed approach, a constraint satisfaction approach and a linear programming approach. We discuss the pros and cons of these approaches and describe which approaches are suited to handle which network routing policies. In particular we handle this work networks with static routing policies, where there exists a static route between every pair of end-users, as well as two common types of dynamic routing policies, where information between a pair of end users may pass via more than a single route. The performance of the proposed approaches is demonstrated experimentally on two domains: the standard NS2 network simulator and on parts of the Internet topology obtained from the Route Views project. Both able to find diagnoses fast for network models with 1,000 nodes.     

Mining closed patterns in relational,graph and network data

Recent theoretical insights have led to the introduction of efficient algorithms for mining closed item-sets. This paper investigates potential generalizations of this paradigm to mine closed patterns in relational, graph and network databases. Several semantics and associated definitions for closed patterns in relational data have been introduced in previous work, but the differences among these and the implications of the choice of semantics was not clear. The paper investigates these implications in the context of generalizing the LCM algorithm, an algorithm for enumerating closed item-sets. LCM is attractive since its run time is linear in the number of closed patterns and since it does not need to store the patterns output in order to avoid duplicates, further reducing memory signature and run time. Our investigation shows that the choice of semantics has a dramatic effect on the properties of closed patterns and as a result, in some settings a generalization of the LCM algorithm is not possible. On the other hand, we provide a full generalization of LCM for the semantic setting that has been previously used by the Claudien system.     

On Polarization-Induced Zero Temperature Spin Wave Damping in Dilute 3He

We have observed spin waves in dilute ³ He, spin polarized by a ⁴ He circulating dilution refrigerator. The maximum polarization is a factor 5 higher than the equilibrium polarization in the magnetic field of 10.54 T at temperatures between 10 and 20 mK. The measured spin wave damping is about a factor 4 lower than the damping expected from previous spin echo experiments in ³ He- ⁴ He mixtures, which confirmed the prediction of polarization-induced spin wave damping at zero temperature in Fermi liquids. Our experiment shows that the existence of polarization-induced spin wave damping remains an open question.     

Template-Based Volume Viewing

We present an efficient three-phase algorithm for volume viewing that is based on exploiting coherency between rays in parallel projection. The algorithm starts by building a ray-template and determining a special plane for projection - the base-plane. Parallel rays are cast into the volume from within the projected region of the volume on the base-plane, by repeating the sequence of steps specified in the ray-template. We carefully choose the type of line to be employed and the way the template is being placed on the base-plane in order to assure uniform sampling of the volume by the discrete rays. We conclude by describing an optimized software implementation of our algorithm and reporting its performance.     

Learning Function-Free Horn Expressions

The problem of learning universally quantified function free first order Horn expressions is studied. Several models of learning from equivalence and membership queries are considered, including the model where interpretations are examples (Learning from Interpretations), the model where clauses are examples (Learning from Entailment), models where extensional or intentional background knowledge is given to the learner (as done in Inductive Logic Programming), and the model where the reasoning performance of the learner rather than identification is of interest (Learning to Reason). We present learning algorithms for all these tasks for the class of universally quantified function free Horn expressions. The algorithms are polynomial in the number of predicate symbols in the language and the number of clauses in the target Horn expression but exponential in the arity of predicates and the number of universally quantified variables. We also provide lower bounds for these tasks by way of characterising the VC-dimension of this class of expressions. The exponential dependence on the number of variables is the main gap between the lower and upper bounds.