Volume 1, Issue 3

With the advent of multi-core computer systems, real-time (RT) scheduling on multiprocessors (MPs) is gaining more and more practical relevance. Basic algorithms developed in the 1970s or earlier are strongly influential on state-of-the-art preemptive hard real-time scheduling algorithms. These relationships will be revealed and visualized by four genealogies. Here, the two classification dimensions prioritization dynamics and migration dynamics serve as a framework for the systematization. Finally, such genealogical reconstructions could even lead to the discovery of new algorithms. An extra look will be devoted to the group of fully dynamic scheduling algorithms with full migration in which algorithms can reach full utilization, neglecting scheduling and context switching overheads. The important question for a set of RT scheduling algorithms serving as a basis for more sophisticated ones will be dealt with.

With recent advances in imaging techniques, huge quantities of domain-specific images, such as medical or geospatial images, are produced and stored daily in computer-based image repositories. Size of databases and limited time at hand makes manual evaluation and annotation by domain experts difficult. In such cases computer based methods can be used to enrich the process of decision making while eliciting previously unknown information. For example, in the medical domain, query by image methods can be used by medical experts for differential diagnosis by displaying previously evaluated cases that contain similar visual patterns. Also, less experienced practitioners can benefit from query-by-semantic methods in training processes, especially for difficult-to-interpret cases with multiple pathologies. In this article we develop a methodology for ranking medical images using customized mixture models. The regions of interest are determined using Dirichlet process to determine natural groupings of images in a content-based feature space. These natural groupings of images are then evaluated for relevance to mixtures of associative semantic mappings. We evaluate and compare the performance of our method on two medical datasets using mean average precision and precision-recall charts.

In this paper we investigate image browsing as an interactive method for visualizing line graphs. We have compared two interfaces that both presented exactly identically looking tables, but while one version was an overview+detail interface, the other one was a distortion-oriented interface of bifocal type. We expected there to be no difference in task completion times, and found none in our first statistical evaluation. Users preferred the static overview+detail interface to the distortion-oriented, which was motivated by complaints about the changed appearance of the distortion-oriented table. The empirical results were compared to theoretical results obtained using Fitts’ law, which showed a difference in task completion time for a certain task type. A second statistical analysis included only data from task type for which a difference could be expected. The new results supported the theoretical model, saying that users were faster with the overview+detail interface. In this paper we discuss problems with image browsing tests, and suggest some ideas for future research topics and designs.

The goal of this article is to provide a rigorous conceptual framework for defining the concepts of dependability and resilience. Since the seventies, the terms dependability and resilience have been used in nearly all the scientific and technological fields related to Information and Communication systems. The introduction and use of these concepts in all these fields makes it difficult to have a common and precise definition. Having such a definition is nevertheless mandatory for the software and systems engineering research community that create development processes, languages and tools to support the engineering of products that would be required to be dependable or resilient. For this, we introduce an abstract and generic terminology defined mathematically to be used when speaking about dependability and resiliency. We also provide some abstract semantic descriptions to these terminological elements. This formal framework is defined from a software engineering perspective, which means that we define its components such that they are useful for the development or improvement of analysis, architectural design, detailed design, implementation, verification and maintenance phases. To this aim, we provide the necessary elements in accordance with a model driven engineering perspective that enable the definition of a new modelling language for dependable and resilient systems.

Image fusion is the method of combining relevant information from two or more images into a single image resulting in an image that is more informative than the initial inputs. Methods for fusion include discrete wavelet transform, Laplacian pyramid based transform, curvelet based transform etc. These methods demonstrate the best performance in spatial and spectral quality of the fused image compared to other spatial methods of fusion. In particular, wavelet transform has good time-frequency characteristics. However, this characteristic cannot be extended easily to two or more dimensions with separable wavelet experiencing limited directivity when spanning a one-dimensional wavelet. This paper introduces the second generation curvelet transform and uses it to fuse images together. This method is compared against the others previously described to show that useful information can be extracted from source and fused images resulting in the production of fused images which offer clear, detailed information.

Specular reflections are not wanted in images because they can really reduce the performance of image processing techniques. This is particularly true for medical images and especially for colposcopic images. There are several methods in the literature allowing to extract specular reflections, but only a few methods can perform an automatic extraction. In this paper, we propose a new method to extract and to restore specularities automatically. This method is based on Dichromatic Reflection Model (DRM) and multi-resolution inpainting technique (MIT). The DRM approach will retrieve specularities while the MIT technique re-establish colors in bright zones using local information. The proposed method achieves good results and does not need any a priori knowledge. The efficiency of this method for colposcopic images has been demonstrated through a collaboration with the oncology center of Marrakech University Hospital.

DoS attacks can vary in type, depending on many different criteria, as well as their countermeasures. Detailed taxonomy can help distinguish all possible types and be used for better understanding of the situation. This study reviews existing DoS attack and DoS attack countermeasure classifications and offers new classification schemes. The proposed DoS attack taxonomy has a new attack characteristic, which describes how bug exploitation can be used for DoS attack execution, as well as new possible values for resource depletion attack and the ways of agent army formation. We also clarify methods for DoS effect achievement and position them in the DoS taxonomy hierarchy. While for DoS attack countermeasure taxonomy we combine ideas from existing taxonomies and compose a three criteria hierarchy with average detailing level. All criteria and categories are described, and seven DoS attack and seven DoS attack countermeasure taxonomies are analysed to obtain their characteristics. Some research is also done to show their application capabilities.