Abstract
NoSQL databases manage the bulk of data produced by modern Web applications such as social networks. This stems from their ability to partition and spread data to all available nodes, allowing NoSQL systems to scale. Unfortunately, current solutions' scale out is oblivious to the underlying data access patterns, resulting in both highly skewed load across nodes and suboptimal node configurations. In this paper, we first show that judicious placement of HBase partitions taking into account data access patterns can improve overall throughput by 35%. Next, we go beyond current state of the art elastic systems limited to uninformed replica addition and removal by: i) reconfiguring existing replicas according to access patterns and ii) adding replicas specifically configured to the expected access pattern. MeT is a prototype for a Cloud-enabled framework that can be used alone or in conjunction with OpenStack for the automatic and heterogeneous reconfiguration of a HBase deployment. Our evaluation, conducted using the YCSB workload generator and a TPC-C workload, shows that MeT is able to i) autonomously achieve the performance of a manual configured cluster and ii) quickly reconfigure the cluster according to unpredicted workload changes. © 2013 ACM.

Abstract
The Drosophila melanogaster G protein-coupled receptor gene, methuselah (mth), has been described as a novel gene that is less than 10 million years old. Nevertheless, it shows a highly specific expression pattern in embryos, larvae, and adults, and has been implicated in larval development, stress resistance, and in the setting of adult lifespan, among others. Although mth belongs to a gene subfamily with 16 members in D. melanogaster, there is no evidence for functional redundancy in this subfamily. Therefore, it is surprising that a novel gene influences so many traits. Here, we explore the alternative hypothesis that mth is an old gene. Under this hypothesis, in species distantly related to D. melanogaster, there should be a gene with features similar to those of mth. By performing detailed phylogenetic, synteny, protein structure, and gene expression analyses we show that the D. virilis GJ12490 gene is the orthologous of mth in species distantly related to D. melanogaster. We also show that, in D. americana (a species of the virilis group of Drosophila), a common amino acid polymorphism at the GJ12490 orthologous gene is significantly associated with developmental time, size, and lifespan differences. Our results imply that GJ12490 orthologous genes are candidates for developmental time and lifespan differences in Drosophila in general.

Abstract
This paper presents the development of a behavior-based AGV using fuzzy logic. A robot platform and a fuzzy logic controller (FLC) are developed for the embodiment of different behaviors. Experimental results are given to assess the performance of the AGV and to validate the proposed design schemes for its construction and control. © 2013, Springer Science+Business Media Dordrecht.

Abstract
Classification of texture images, especially in cases where the images are subjected to arbitrary rotation and scale changes due to dynamic imaging conditions is a challenging problem in computer vision. This paper proposes a novel methodology to obtain rotation and scale invariant texture features from the images. The feature extraction for a given image involves the calculation of the averages of Gabor filter responses at various scales and orientations. For rotation and scaling of images, these averages indicate the respective shifts in the features. These shifts are normalized by doing summations of Gabor responses across scales and then taking the magnitude of Discrete Fourier Transforms across the resulting features and vice versa thus giving us scale and rotation invariant texture features. The proposed features are used for identifying cancer in the vital stained magnification endoscopy images. Experiments demonstrate the superiority of the proposed feature set over several other state-of-the-art texture feature extraction methods with around 90% classification accuracy for identifying cancer in gastroenterology images.

Abstract
There are several approaches to create the Humanoid robot gait planning. This problem presents a large number of unknown parameters that should be found to make the humanoid robot to walk. Optimization in simulation models can be used to find the gait based on several criteria such as energy minimization, acceleration, step length among the others. The presented paper addresses a comparison between two optimization methods, the Stretched Simulated Annealing and the Genetic Algorithm, that runs in an accurate and stable simulation model. Final results show the comparative study and demonstrate that optimization is a valid gait planning technique.

Abstract