P-Tree Structures and Event Horizon: Efficient Event-Set Implementations

This paper describes efficient data structures, namely the Indexed P-tree, Block P-tree, and Indexed-Block P-tree （or/P-tree, BP-tree, and IBP-tree, respectively, for short）, for maintaining future events in a general purpose discrete event simulation system, and studies the performance of their event set algorithms under the event horizon principle. For comparison reasons, some well-known event set algorithms have been selected and studied, that is, the Dynamic-heap and the P-tree algorithms. To gain insight into the performance of the proposed event set algorithms and allow comparisons with the other selected algorithms, they are tested under a wide variety of conditions in an experimental way. The time needed for the execution of the Hold operation is taken as the measure for estimating the average time complexity of the algorithms. The experimental results show that the BP-tree algorithm and the IBP-tree algorithm behave very well with the event set of all the sizes and their performance is almost independent of the stochastic distributions.     

A comparative techno‐economic assessment of three bio‐oil upgrading routes for aviation biofuel production

The aviation industry continues to grow, and consequently, more fuel is needed. With the intention of decarbonising the aviation sector, sustainable routes that have the potential to mitigate emissions, such as biomass fast pyrolysis, can positively contribute to this direction. Within this context, the present study performs a comparative techno‐economic evaluation of aviation biofuel manufacture via the main bio‐oil upgrading pathways, namely, hydroprocessing (HP), gasification followed by Fischer‐Tropsch synthesis (G+FT), and zeolite cracking (ZC). The research constitutes the first endeavour to investigate and compare the feasibility of producing biojet fuel via pyrolysis‐based routes. The presented work provides an inclusive evaluation that comprises process modelling and financial assessment. Based on the simulations, overall energy efficiencies of 48.8%, 45.73%, and 45.38% and jet fuel energy efficiencies of 23.70%, 21.45%, and 20.53% were calculated, while the implementation of a discounted cash flow analysis estimated minimum jet fuel selling prices (MJSPs) of 1.98, 2.32, and 2.21 $/L for the HP, the G+FT, and the ZC, respectively. Sensitivity analysis revealed that the processes are capital and feedstock intensive while an increase to the bio‐oil yield will favour the economic performance of the examined biorefineries. An increase of the plant size from 100 (base case) to 150 dry tonnes per hour of feedstock will decrease the selling prices by approximately 25% for all cases. Monte Carlo simulations exhibited that without establishing and/or maintaining appropriate policy schemes, there is no pragmatic prospect for the examined biorefineries to beat the competition against the prevailing oil infrastructures.     

Practical Product Path Guiding Using Linearly Transformed Cosines

Path tracing is now the standard method used to generate realistic imagery in many domains, e.g., film, special effects, architecture etc. Path guiding has recently emerged as a powerful strategy to counter the notoriously long computation times required to render such images. We present a practical path guiding algorithm that performs product sampling, i.e., samples proportional to the product of the bidirectional scattering distribution function (BSDF) and incoming radiance. We use a spatial-directional subdivision to represent incoming radiance, and introduce the use of Linearly Transformed Cosines (LTCs) to represent the BSDF during path guiding, thus enabling efficient product sampling. Despite the computational efficiency of LTCs, several optimizations are needed to make our method cost effective. In particular, we show how we can use vectorization, precomputation, as well as strategies to optimize multiple importance sampling and Russian roulette to improve performance. We evaluate our method on several scenes, demonstrating consistent improvement in efficiency compared to previous work, especially in scenes with significant glossy inter-reflection.     

A Pipeline Technique for Dynamic Data Transfer on a Multiprocessor Grid

This paper describes a pipeline technique which is used to redistribute data on a multiprocessor grid during runtime. The main purposes of the algorithm are to minimize the data transfer time, prevent congestion on the ports of the receiving processors, and minimize the number of idle processors. One of the key ideas for this algorithm is the creation of processor classes, firstly introduced by Desprez et al. [IEEE Transactions on Parallel and Distributed Systems 9(2):102 (1998).] Based on the idea of classes, we create the pipeline tasks used to organize the redistribution of data. Our experimental results show that this pipeline technique can significantly reduce the amount of time required to complete a dynamic data transfer task.     

Evaluation of three methods for retrospective correction of vignetting on medical microscopy images utilizing two open source software tools

Correction of vignetting on images obtained by a digital camera mounted on a microscope is essential before applying image analysis. The aim of this study is to evaluate three methods for retrospective correction of vignetting on medical microscopy images and compare them with a prospective correction method. One digital image from four different tissues was used and a vignetting effect was applied on each of these images. The resulted vignetted image was replicated four times and in each replica a different method for vignetting correction was applied with fiji and gimp software tools. The highest peak signal-to-noise ratio from the comparison of each method to the original image was obtained from the prospective method in all tissues. The morphological filtering method provided the highest peak signal-to-noise ratio value amongst the retrospective methods. The prospective method is suggested as the method of choice for correction of vignetting and if it is not applicable, then the morphological filtering may be suggested as the retrospective alternative method.     

Supervisory control and reactive synthesis: a comparative introduction

This paper presents an introduction to and a formal connection between synthesis problems for discrete event systems that have been considered, largely separately, in the two research communities of supervisory control in control engineering and reactive synthesis in computer science. By making this connection mathematically precise in a paper that attempts to be as self-contained as possible, we wish to introduce these two research areas to non-expert readers and at the same time to highlight how they can be bridged in the context of classical synthesis problems. After presenting general introductions to supervisory control theory and reactive synthesis, we provide a novel reduction of the basic supervisory control problem, non-blocking case, to a problem of reactive synthesis with plants and with a maximal permissiveness requirement. The reduction is for fully-observed systems that are controlled by a single supervisor/controller. It complements prior work that has explored problems at the interface of supervisory control and reactive synthesis. The formal bridge constructed in this paper should be a source of inspiration for new lines of investigation that will leverage the power of the synthesis techniques that have been developed in these two areas.     

The Refinement Calculus of Reactive Systems Toolset

International Journal on Software Tools for Technology Transfer - We present the Refinement Calculus of Reactive Systems Toolset, an environment for compositional formal modeling and reasoning...     

A graph-based model for malware detection and classification using system-call groups

In this paper we present a graph-based model that, utilizing relations between groups of System-calls, detects whether an unknown software sample is malicious or benign, and classifies a malicious software to one of a set of known malware families. More precisely, we utilize the System-call Dependency Graphs (or, for short, ScD-graphs), obtained by traces captured through dynamic taint analysis. We design our model to be resistant against strong mutations applying our detection and classification techniques on a weighted directed graph, namely Group Relation Graph, or Gr-graph for short, resulting from ScD-graph after grouping disjoint subsets of its vertices. For the detection process, we propose the \(\Delta \)-similarity metric, and for the process of classification, we propose the SaMe-similarity and NP-similarity metrics consisting the SaMe-NP similarity. Finally, we evaluate our model for malware detection and classification showing its potentials against malicious software measuring its detection rates and classification accuracy.     

ETHYLENE OXIDATION ON SILVER CATALYSTS: EFFECT OF ETHYLENE OXIDE AND OF EXTERNAL TRANSFER LIMITATIONS

Ethylene oxidation to ethylene oxide and to carbon dioxide over silver catalysts was studied in a CSTR. The effects of two factors on the catalyst performance were examined. The first was the presence of excess ethylene oxide in the feed. A kinetic model was introduced which assumed that ethylene and ethylene oxide compete for the same sites on the catalyst surface. This model provided reasonable quantitative agreement with kinetic and potentiometric measurements. The second factor that was studied was the presence of external heat and mass transfer limitations. It was found that such limitations cause a significant decrease of the selectivity to ethylene oxide. This decrease is a result of the temperature difference between the catalyst surface and the bulk of the gas phase and of the fact that the activation energy of ethylene combustion is greater than that of ethylene epoxidation. The contribution of other factors such as inhibition by CO₂ or possible incomplete mixing in the reactor is shown to be insignificant.