Many structured data-fitting applications require the solution of an optimization problem involving a sum over a potentially large number of measurements. Incremental gradient algorithms offer inexpensive iterations by sampling a subset of the terms in the sum; these methods can make great progress initially, but often slow as they approach a solution. In contrast, full-gradient methods achieve...

In the subgraph querying problem, given a query graph and a dataset of graphs, we want to locate which graphs in the dataset contain the query and/or find all its occurrences. Over the years, numerous methods, fragmented in 2 categories, were proposed to tackle the problem. In the first category, methods follow the filter-then-verify (FTV) paradigm where an index is used to filter out graphs th...

background and aim: in vitro studies have revealed a direct association between resin content and cytotoxicity of resin composites; but implantation studies in this regard are sparse. this study investigates the relationship between filler content of composite resins and biocompatibility. materials and methods: this study was conducted using 18 male wistar rats (180-200g), 1 nano-hybrid (prime-...

In this paper, we investigate how the seemingly chaotic behavior of stock markets could be well represented using neural network, TS fuzzy system and hierarchical TS fuzzy techniques. To demonstrate the different techniques, we considered Nasdaq−100 index of Nasdaq Stock Market and the S&P CNX NIFTY stock index. We analyzed 7 year’s Nasdaq 100 main index values and 4 year’s NIFTY index values. ...

In this paper we provide a brief review of recent advances in computational methods for hyperspectral image analysis with emphasis in hybrid approaches. Hyperspectral imagery acquisition and hyperspectral analysis are growing elds. The analysis of hyperspectral images will have an increasing impact in several application areas, i.e., Earth observation, planetology, food industry, quality proces...

Hybrid methods of using evolutionary algorithms with a local search method are often used in the context of singleobjective real-world optimization. In this paper, we discuss a couple of hybrid methods for multi-objective realworld optimization. In the posteriori approach, the obtained non-dominated solutions of a multi-objective evolutionary algorithm (MOEA) run are modified using a local sear...

A heuristic algorithm is proposed to solve a routing problem that integrates a fixed route service with a demand responsive. The main aim of the integration is to have higher productivity and/or less cost while not significantly reducing the customer service level. The primary application for such a system is a dial-a-ride service. The heuristic, which is tested using real data from a transit a...

Introduction The yeast two-hybrid system is a powerful assay for protein-protein interactions 1. As described elsewhere in this volume, several versions of the twohybrid system have been developed. Most versions have the following features. The two proteins to be tested for interaction are expressed as hybrids in the nucleus of a yeast cell. One of the proteins is fused to the DNA binding domai...

We propose two recommendation methods, based on the appropriate normalization of already existing similarity measures, and on the convex combination of the recommendation scores derived from similarity between users and between objects. We validate the proposed measures on three data sets, and we compare the performance of our methods to other recommendation systems recently proposed in the lit...

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology...