Vol. 32 · No. 2

According to the Object Management Group, a rule is a proposition that is a claim of obligation or of necessity. The concept of rule is usually employed in the context of business process to manage companies operations. While a workflow is an explicit specification of tasks' execution flow, business rules only impose restrictions on the tasks' execution. This provides a great deal of flexibility for the process execution, since the stakeholders are free to choose an execution flow which does not violate the rules. The execution of a task in a process can be seen as the occurrence of an event, which may enable/disable the execution of some other tasks in the process. Event-driven programming is a paradigm in which the program control-flow is determined by the occurrence of events. The capacity to handle processes that are unpredictably non-linear and dynamic makes the event-driven paradigm an effective solution for the implementation of business rules. However, the connection between the business rules and their implementation through event-driven programming has been made in an ad-hoc and unstructured manner. This paper proposes a methodology to tackle such a problem by systematically moving from business rules described in natural language toward a concrete implementation of a business process. We use complex event processing (CEP) to implement the process. CEP relies on the event driven paradigm for monitoring and processing events. The methodology allows for the active participation of business people at all stages of the refinement process. Throughout the paper, we show how our methodology was employed to implement the operations of the World Bank.

The current design and manufacturing semiconductor technologies require to test the products against delay related defects. However, complex acpSOC require low-overhead testability methods to keep the test cost at an acceptable level. Skewed-load tests seem to be the appropriate way to test delay faults in these acpSOC because the test application requires only one storage element per scan cell. Compressed skewed-load test generator based on genetic algorithm is proposed for wrapper-based logic cores of acpSOC. Deterministic population initialization is used to ensure the highest achievable aclTDF coverage for the given wrapper and scan cell order. The developed method performs test data compression by generating test vectors containing already overlapped test vector pairs. The experimental results show high fault coverages, decreased test lengths and better scalability in comparison to recent methods.

This article introduces ME-MLS, an efficient multithreading local search algorithm for solving the multiobjective scheduling problem in heterogeneous computing systems. We consider the minimization of both the makespan and energy consumption objectives. The proposed method follows a fully multiobjective approach, applying a Pareto-based dominance search that is executed in parallel by using several threads. The experimental analysis demonstrates that the new multithreading algorithm outperforms a set of fast and accurate two-phases deterministic heuristics based on the traditional MinMin. The new ME-MLS method is able to achieve significant improvements in both makespan and energy consumption objectives in reduced execution times for a large set of testbed instances, while exhibiting a near linear speedup behavior when using up to 24 threads.

Kernel rootkits pose significant challenges on defensive techniques as they run at the highest privilege level along with the protection systems. Modern architectural approaches such as the NX protection have been used in mitigating attacks, however determined attackers can still bypass these defenses with specifically crafted payloads. In this paper, we propose a virtualized Harvard memory architecture to address the kernel code integrity problem, which virtually separates the code fetch and data access on the kernel code to prevent kernel from code modifications. We have implemented the proposed mechanism in commodity operating system, and the experimental results show that our approach is effective and incurs very low overhead.

In this paper we give a recognition algorithm in O(n(n+m)) time for bipartite chain graphs, and directly calculate the density of such graphs. For their stability number and domination number, we give algorithms comparable to the existing ones. We point out some applications of bipartite chain graphs in chemistry and approach the Minimum Chain Completion problem.

We propose an efficient parallel implementation of the Ramalingam algorithm for dynamic updating the shortest paths subgraph of a directed weighted graph with a sink after deletion of an edge. To this end, a model of associative (content addressable) parallel systems with vertical processing (the STAR-machine) is used. On the STAR-machine, the Ramalingam decremental algorithm for dynamic updating the shortest paths subgraph is represented as the main procedure textsfDeleteArc that uses a group of auxiliary procedures. We provide the textsfDeleteArc procedure along with the auxiliary procedures, prove correctness of these procedures and evaluate the time complexity. We also consider an example of implementing the textsfDeleteArc procedure on the STAR-machine.

We provide a generalization of one-sided (crisp-fuzzy) concept lattices, based on Galois connections. Our approach allows analysis of object-attribute models with different structures for truth values of attributes. Moreover, we prove that this method of creating one-sided concept lattices is the most general one, i.e., with respect to the set of admissible formal contexts, it produces all Galois connections between power sets and the products of complete lattices. Some possible applications of this approach are also included.

Automatic generic document summarization based on unsupervised schemes is a very useful approach because it does not require training data. Although techniques using latent semantic analysis (LSA) and non-negative matrix factorization (NMF) have been applied to determine topics of documents, there are no researches on reduction of matrix and speeding up of computation of the NMF method. In order to achieve this scheme, this paper utilizes the generic impressive expressions from newspapers to extract important sentences as summary. Therefore, it has no stemming processes and no filtering of stop words. Generally, novels are typical documents providing sentimental impression for readers. However, newspapers deliver different impressions for new knowledge because they inform readers about current events, informative articles and diverse features. The proposed method introduces impressive expressions for newspapers and their measurements are applied to the NMF method. From 100 KB text data of experimental results by the proposed method, it turns out that the matrix size reduces by 80

In this article we present a new method for text segmentation. The method relies on the number of lexical chains (LCs) which end in a sentence, which begin in the following sentence and which traverse the two successive sentences. The lexical chains are based on Roget's thesaurus (the 1987 and the 1911 version). We evaluate the method on ten texts from the DUC 2002 conference and on twenty texts from the CAST project corpus, using a manual segmentation as gold standard.

Efficient retrieval of XML elements and documents is essential in the effective application of the XML format. The ranking function BM25F is composed of several document fields with potentially different degrees of importance; these fields are known as selected fields that give substantial improvements over the baseline BM25. The BM25F function has performed well in past evaluations; however, there are issues that require additional attention. In the first instance, which elements should be treated as fields? Secondly, what is an appropriate weight for each field? Previously, document fields were selected manually, and the weight for each chosen field was tuned before being assigned. Two automatic methods are introduced in this paper that enable the extraction of fields in document-centric XML documents and the assignment weights to the selected fields. Our experiments show an improvement of up to 28