Generating Rare Association Rules Using the Minimal Rare Itemsets Family

Rare association rules correspond to rare, or infrequent, itemsets, as opposed to frequent ones that are targeted by conventional pattern miners. Rare rules reflect regularities of local, rather than global, scope that can nevertheless provide valuable insights to an expert, especially in areas such as genetics and medical diagnosis where some specific deviations/illnesses occur only in a small number of cases. The work presented here is motivated by the long-standing open question of efficiently mining strong rare rules, i.e., rules with high confidence and low support. We also propose an efficient solution for finding the set of minimal rare itemsets. This set serves as a basis for generating rare association rules.     

A Declarative Approach to Network Device Configuration Correctness

Configuration Logic (CL) is a formal language that allows a network engineer to express constraints in terms of the actual parameters found in the configuration of network devices. We present an efficient algorithm that can automatically check a pool of devices for conformance to a set of CL constraints; moreover, this algorithm can point to the part of the configuration responsible for the error when a constraint is violated. Contrary to other validation approaches that require dumping the configuration of the whole network to a central location in order to be verified, we also present an algorithm that analyzes the correct formulas and greatly helps reduce the amount of data that need to be transferred to that central location, pushing as much of the evaluation of the formula locally on each device. The procedure is also backwards-compatible, in such a way that a device that does not (or only partially) supports a local evaluation may simply return a subset or all of its configuration. These capabilities have been integrated into a network management tool called ValidMaker.     

Interleaved Ultrawideband Antenna Arrays Based on Optimized Polyfractal Tree Structures

There is considerable interest in interleaving multiple phased array antennas into a single common aperture system. Current phased array antenna technology is limited to narrowband operation, leading to the appearance of grating lobes and strong mutual coupling effects when they are incorporated into the design of a common aperture system. To overcome this obstacle, a new class of arrays, called polyfractal arrays, has been introduced that possess natural wideband properties well suited for large-scale genetic algorithm optimizations. These arrays also possess recursive beamforming properties and an autopolyploidy-based chromosome expansion that can dramatically accelerate the convergence of a genetic algorithm. In addition, a robust Pareto optimization can be applied to reduce the peak sidelobe levels at several frequencies throughout the intended operating band, leading to ultrawideband antenna array designs. Because of their lack of grating lobes, these polyfractal arrays are ideal building blocks for interleaved antenna array systems. This paper develops these concepts, first creating ultrawideband array designs based on polyfractal geometries and then interleaving these designs into a common aperture system. Several examples of interleaved systems are discussed, with one two-array system possessing a peak sidelobe level of nearly -18 dB with no grating lobes over a 20:1 bandwidth with either of the component array mainbeams steered independently up to 60deg from broadside.     

A fast compound algorithm for mining generators,closed itemsets,and computing links between equivalence classes

In pattern mining and association rule mining, there is a variety of algorithms for mining frequent closed itemsets (FCIs) and frequent generators (FGs), whereas a smaller part further involves the precedence relation between FCIs. The interplay of these three constructs and their joint computation have been studied within the formal concept analysis (FCA) field yet none of the proposed algorithms is scalable. In frequent pattern mining, at least one suite of efficient algorithms has been designed that exploits basically the same ideas and follows the same overall computational schema. Based on an in-depth analysis of the aforementioned interplay that is rooted in a fundamental duality from hypergraph theory, we propose a new schema that should enable for a more parsimonious computation. We exemplify the new schema in the design of Snow-Touch, a concrete FCI/FG/precedence miner that reuses an existing algorithm, Charm, for mining FCIs, and completes it with two original methods for mining FGs and precedence, respectively. The performance of Snow-Touch and of its closest competitor, Charm-L, were experimentally compared using a large variety of datasets. The outcome of the experimental study suggests that our method outperforms Charm-L on dense data while on sparse one the trend is reversed. Furthermore, we demonstrate the usefulness of our method and the new schema through an application to the analysis of a genome dataset. The initial results reported here confirm the capacity of the method to focus on significant associations.     

Metamaterials Based on Polyvinyl Alcohol with Metal or Metal Oxide Particles: Synthesis and Study by Nondestructive Physical Methods

Theoretical Foundations of Chemical Engineering - Methods for the synthesis of polymer hydrogel–metal metamaterials based on polyvinyl alcohol and reduced Cu, Ag, Co, and Fe (or magnetite...     

Robust feedback stabilization of underwater robotic vehicles

The controlled motion of an underwater vehicle is very likely to be affected by arbitrary disturbances with considerable magnitudes. In this paper, we develop a simple approach for optimal robust control design of underwater robotic vehicles having decentralized input-output structure. Our design method is based on an explicit condition on the control input matrix which has been found to be necessary and sufficient for a decentralized control system to be robust against arbitrary, but otherwise, bounded disturbances. That makes it possible to get optimal trade-off relations between the bounds of disturbances, the system output accuracy, and the control force limits. For the robust control design purpose, we apply decentralized sliding-mode control the stability of which can be easily verified using Lyapunov theory. In order to show the effectiveness of the design method, the controlled planar motion of an underwater robotic vehicle is taken as an illustrative example.     

A graph approach to generate all possible regression submodels

A regression graph to enumerate and evaluate all possible subset regression models is introduced. The graph is a generalization of a regression tree. All the spanning trees of the graph are minimum spanning trees and provide an optimal computational procedure for generating all possible submodels. Each minimum spanning tree has a different structure and characteristics. An adaptation of a branch-and-bound algorithm which computes the best-subset models using the regression graph framework is proposed. Experimental results and comparison with an existing method based on a regression tree are presented and discussed.