This paper proposes a new rule-based language for programming heterogeneous sensor actuator networks. Rules are declarative statements which are evaluated using sensor readings spanning multiple sources. We combine our declarative rules system with the notion of frequency based operation and communication to allow a compiler to emit a work schedule optimized for minimal power consumption. Combi...

quantitative valuations of observed heterosis for 11 traits of 15 f1 hybrids generated by half diallel crosses of six diverse rice cultivars (domsefid, hashemi and binam, three iranian local cultivars; dorfak, kadous and ir30, three improved cultivars), were made in this study. fifteen f1 hybrids and their parents were evaluated in a randomized complete block design with three replications at t...

in order to produce new hybrids and evaluate the general and specific combining ability of sunflower inbred lines and restorers, four inbred lines and six restorers were selected in 2004. twenty-four f1 hybrids were derived in 2004 and evaluated on a rcbd design with three replications in 2005. the results of variance analysis showed that treatments were significantly different for all traits e...

Existing statistical approaches to natural language problems are very coarse approximations to the true complexity of language processing. As such, no single technique will be best for all problem instances. Many researchers are examining ensemble methods that combine the output of multiple modules to create more accurate solutions. This paper examines three merging rules for combining probabil...

This research focuses on the development of a rule-based intelligent equipment trouble-shooting and maintenance platform using JAVA Expert System Shell (JESS) technology. A prototype system is designed and developed combining rule-based knowledge system and inference engine to support real-time collaborative equipment maintenance across geographical boundary. The main modules of the system incl...

In rule learning, rules are typically induced in two phases, rule refinement and rule selection. It was recently argued that the usage of two separate heuristics for each phase—in particular using the so-called inverted heuristic in the refinement phase—produces longer rules with comparable classification accuracy. In this paper we test the utility of inverted heuristics in the context of subgr...

In this paper a high performance face recognition system, based on different data fusion techniques combining the decisions obtained from the probability distribution functions (PDF) based face recognition system in different colour channels, is introduced. The PDFs of the equalized and segmented face images are used as statistical feature vectors for the recognition of faces by minimizing the ...

The challenges of the Semantic Web endeavour in knowledge representation and reasoning prompted a wealth of research in combining description logic (DL) as ontology languages (e.g. OWL) with logic programming for rule-based reasoning. General issues of combining and integrating formalisms have to be faced such as the type of combination, conceptual simplicity and tractability. Even though const...

This paper presents the translation technologies of Portuguese to Chinese machine translation system, PCT Assistente a hybrid translation model integrated with example-based and rule-based translation paradigms to counterbalance the intrinsic weakness of these approaches by combining the strong features of another. In the example-based model, translation examples are annotated under the schema ...

This paper investigates different ways of combining feature selection with bagging and rule extraction in predictive modeling. Experiments on a large number of data sets from the medicinal chemistry domain, using standard algorithms implemented in the Weka data mining workbench, show that feature selection can lead to significantly improved predictive performance. When combining feature selecti...