Vol. 36 · No. 6

An approach of generation of tiled code with an arbitrary order of loops within tiles is presented. It is based on the transitive closure of the program dependence graph and derived via a combination of the Polyhedral and Iteration Space Slicing frameworks. The approach is explained by means of a working example. Details of an implementation of the approach in the TRACO compiler are outlined. Increasing tiled program performance due to loop permutation within tiles is illustrated on real-life programs from the NAS Parallel Benchmark suite. An analysis of speed-up and scalability of parallel tiled code with loop permutation is presented.

Topic strength is an important hotspot in topic research. The evolution of topic strength not only indicates emerging new topics, but also helps us to determine whether a topic will produce some fluctuation of topic strength over time. Thus, topic strength analysis can provide significant findings in public opinion monitoring and user personalization. In this paper, we present an LDA-based topic strength analysis approach. We take topic quality into our topic strength consideration by combining local LDA and global LDA. For empirical studies, we use three data sets in real applications: film critic data of ``A Chinese Odyssey'' in Douban Movies, corruption news data in Sina News, and public paper data. Compared to existing approaches, experimental results show that our proposed approach can obtain better results of topic strength analysis in detecting the time of event topic occurrences and distinguishing different types of topics, and it can be used to monitor the occurrences of public opinions and the changes of public concerns.

In this paper, we present SEMAG - a novel semantic-agent learning recommendation mechanism which utilizes the advantages of instructional Semantic Web rules and multi-agent technology, in order to build a competitive and interactive learning environment. Specifically, the recommendation-making process is contingent upon chapter-quiz results, as usual; but it also checks the students' understanding at topic-levels, through personalized questions generated instantly and dynamically by a knowledge-based algorithm. The learning space is spread to the social network, with the aim of increasing the interaction between students and the intelligent tutoring system. A field experiment was conducted in which the results indicated that the experimental group gained significant achievements, and thus it supports the use of SEMAG.

Cloud computing becomes increasingly popular for hosting all kinds of applications not only due to their ability to support dynamic provisioning of virtualized resources to handle workload fluctuations but also because of the usage based on pricing. This results in the adoption of data centers which store, process and present the data in a seamless, efficient and easy way. Furthermore, it also consumes an enormous amount of electrical energy, then leads to high using cost and carbon dioxide emission. Therefore, we need a Green computing solution that can not only minimize the using costs and reduce the environment impact but also improve the performance. Dynamic consolidation of Virtual Machines (VMs), using live migration of the VMs and switching idle servers to sleep mode or shutdown, optimizes the energy consumption. We propose an adaptive underloading detection method of hosts, VMs migration selecting method and heuristic algorithm for dynamic consolidation of VMs based on the analysis of the historical data. Through extensive simulation based on random data and real workload data, we show that our method and algorithm observably reduce energy consumption and allow the system to meet the Service Level Agreements (SLAs).

In order to improve the execution time and clustering quality of sequence clustering algorithm in large-scale dynamic dataset, a novel algorithm RPCAISC (Representative Points and Cluster Attributes Based Incremental Sequence Clustering) was presented. In this paper, density factor is defined. The primary representative point that has a density factor less than the prescribed threshold will be deleted directly. New representative points can be reselected from non-representative points. Moreover, the representative points of each cluster are modeled using the K-nearest neighbor method. The definition of the relevant degree (RD) between clusters was also proposed. The RD is computed by comprehensively considering the correlations of objects within a cluster and between different clusters. Then, whether the two clusters need to merge is determined. Additionally, the cluster attributes of the initial clustering are retained with this process. By calculating the matching degree between the incremental sequence and the existing cluster attributes, dynamic sequence clustering can be achieved. The theoretic experimental results and analysis prove that RPCAISC has better correct rate of clustering results and execution efficiency.

The semantics of programs written in some languages is concerned with the interpretation in various types of models. The purpose of structural operational semantics is to describe how a computation is performed. This method is one of the most popular semantic methods in the community of software engineers. It describes program behavior in the form of state changes caused by the execution of elementary steps. This feature predestinates the usage of the structural operational semantics for implementation of programming languages and also for verification purposes. Another semantic method, denotational semantics, defines changes of states by functions. In this paper a new approach to semantics is presented: behavior of programs, i.e., changes of states are modeled in the category of states. The morphisms category expresses elementary execution steps and the program execution is an oriented path in the category, i.e. composition of morphisms. Our categorical model is constructed for a simple procedural language that contains all basic van Dijkstra's constructs. We enriched our approach also with procedures forming a collection of categories interconnected by functors. This method enables the repeated call of procedures, nesting of procedure calls and recursive calls. Moreover, it allows to illustrate and accentuate dynamics of the program execution. The simplicity of this method does not exclude its mathematical exactness.

Though quasi-classical description logic (QCDL) can tolerate the inconsistency of description logic in reasoning, a knowledge base in QCDL possibly has no model. In this paper, we investigate the satisfiability of QCDL, namely, QC-coherency and QC-consistency and develop a tableau calculus, as a formal proof, to determine whether a knowledge base in QCDL is QC-consistent. To do so, we repair the standard tableau for DL by introducing several new expansion rules and defining a new closeness condition. Finally, we prove that this calculus is sound and complete. Based on this calculus, we implement an OWL paraconsistent reasoner called QC-OWL. Preliminary experiments show that QC-OWL is highly efficient in checking QC-consistency.

The main objective of this paper is to present a possibility of high quality a posteriori error evaluation based on reference solutions obtained by means of the new multipoint meshless finite difference method. Due to its higher order approximation, the multipoint results may be used as improved reference solution instead of the true analytical one to estimate the errors. Several types of a posteriori error estimators which can be used to evaluate the calculation error are described here. The results of selected numerical benchmarks are considered.

The Web has become a tremendously huge data source hidden under linked documents. A significant number of Web documents include HTML tables generated dynamically from relational databases. Often, there is no direct public access to the databases themselves. On the other hand, RDF (Resource Description Framework) gives an efficient mechanism to represent directly data on the Web based on a Web-scalable architecture for identification and interpretation of terms. This leads to the concept of Linked Data on the Web. To allow direct access to data on the Web as Linked Data, we propose in this paper an approach to transform HTML tables into RDF triples. It consists of three main phases: refining, pre-treatment and mapping. The whole process is assisted by a domain ontology and the WordNet lexical database. A tool called Htab2RDF has been implemented. Experiments have been carried out to evaluate and show efficiency of the proposed approach.

Raytracers that allow the spatially explicit calculation of the fate of light beams in a 3D scene allow the consideration of shading, reflected and transmitted light in functional-structural plant models (FSPM). However, the spectrum of visible light also has an effect on cellular and growth processes. This recently created the interest to extend this modelling paradigm allowing the representation of detailed spectra instead of monochromatic or white light and to extend existing FSPM platforms accordingly. In this study a raytracer is presented which supports the full spectrum of light and which can be used to compute spectra from arbitrary light sources and their transformation at the organ level by absorption, reflection and transmission in a virtual canopy. The raytracer was implemented as an extension of the FSPM platform GroIMP.