Spatial data warehouses and spatial OLAP come towards the cloud: design and performance

Cloud computing systems handle large volumes of data by using almost unlimited computational resources, while spatial data warehouses (SDWs) are multidimensional databases that store huge volumes of both spatial data and conventional data. Cloud computing environments have been considered adequate to host voluminous databases, process analytical workloads and deliver database as a service, while spatial online analytical processing (spatial OLAP) queries issued over SDWs are intrinsically analytical. However, hosting a SDW in the cloud and processing spatial OLAP queries over such database impose novel obstacles. In this article, we introduce novel concepts as cloud SDW and spatial OLAP as a service, and afterwards detail the design of novel schemas for cloud SDW and spatial OLAP query processing over cloud SDW. Furthermore, we evaluate the performance to process spatial OLAP queries in cloud SDWs using our own query processor aided by a cloud spatial index. Moreover, we describe the cloud spatial bitmap index to improve the performance to process spatial OLAP queries in cloud SDWs, and assess it through an experimental evaluation. Results derived from our experiments revealed that such index was capable to reduce the query response time from 58.20 up to 98.89 %.     

Linear mixture model applied to Amazonian vegetation classification

Many research projects require accurate delineation of different secondary succession (SS) stages over large regions/subregions of the Amazon basin. However, the complexity of vegetation stand structure, abundant vegetation species, and the smooth transition between different SS stages make vegetation classification difficult when using traditional approaches such as the maximum likelihood classifier (MLC). Most of the time, classification distinguishes only between forest/non-forest. It has been difficult to accurately distinguish stages of SS. In this paper, a linear mixture model (LMM) approach is applied to classify successional and mature forests using Thematic Mapper (TM) imagery in the Rondônia region of the Brazilian Amazon. Three endmembers (i.e., shade, soil, and green vegetation or GV) were identified based on the image itself and a constrained least-squares solution was used to unmix the image. This study indicates that the LMM approach is a promising method for distinguishing successional and mature forests in the Amazon basin using TM data. It improved vegetation classification accuracy over that of the MLC. Initial, intermediate, and advanced successional and mature forests were classified with overall accuracy of 78.2% using a threshold method on the ratio of shade to GV fractions, a 7.4% increase over the MLC. The GV and shade fractions are sensitive to the change of vegetation stand structures and better capture biophysical structure information.     

A computational study of parametric tabu search for 0–1 mixed integer programs

We present a computational study of parametric tabu search for solving 0–1 mixed integer programming (MIP) problems, a generic heuristic for general MIP problems proposed by Glover [Glover F. Parametric tabu-search for mixed integer programs. Computers and Operations Research 2006; 33: 2449–94.]. This approach solves a series of linear programming problems by incorporating branching inequalities as weighted terms in the objective function. New strategies are proposed for uncovering feasible and high-quality solutions and extensive computational tests are performed on instances from the literature.     

Acoustic evaluation and adjustment of an open-plan office through architectural design and noise control

Arranging office space into a single open room offers advantages in terms of easy exchange of information and interaction among coworkers, but reduces privacy and acoustic comfort. Thus, the purpose of this work was to evaluate the acoustic quality of a real open-plan office and to propose changes in the room to improve the acoustic conditioning of this office. The computational model of the office under study was calibrated based on RT and STI measurements. Predictions were made of the RT and STI, which generated the radius of distraction r(D), and the rate of spatial decay of sound pressure levels per distance doubling DL(2) in the real conditions of the office and after modifications of the room. The insertion of dividers between work stations and an increase in the ceiling's sound absorption improved the acoustic conditions in the office under study.     

Studies on SiC, DLC and TiO2 thin films as piezoresistive sensor materials for high temperature application

The use of thin films as sensing elements for microsensor applications has been shown very attractive due to their low-cost fabrication, potential for integration with standard CMOS technologies and possibility of deposition on different substrate types. In particular, piezoresistive sensors based on thin films have been commonly developed because can be easily implemented using microfabrication processes and present the best relation between sensitivity and system complexity, which showing great advantages in term of device integration. In our previous works (Fraga et al. 2010, 2011a), we studied undoped and nitrogen-doped PECVD a-SiC thin films as alternative materials to replace the silicon piezoresistors in strain and pressure sensors for harsh environments. Here, we focused our attention on the piezoresistive properties of sputtered silicon carbide (SiC), diamond-like carbon (DLC) and titanium dioxide (TiO₂) thin films. These materials were evaluated in terms of sensitivity or gauge factor and of the influence of the temperature on this sensitivity, allowing a preliminary analysis of the applicability of these thin films in high temperature piezoresistive sensors.     

Text entry for the Blind on Smartwatches

Universal Access in the Information Society - The interaction challenges presented by touch-screen enabled devices for blind and visually impaired people has been addressed extensively in the...     

Multiple biological sequence alignment in heterogeneous multicore clusters with user-selectable task allocation policies

Multiple Sequence Alignment (MSA) is an important problem in Bioinformatics that aims to align more than two sequences in order to emphasize similarity regions. This problem is known to be NP-Hard, so heuristic methods are used to solve it. DIALIGN-TX is an iterative heuristic method for MSA that generates alignments by concatenating ungapped regions with high similarity. Usually, the first phase of MSA algorithms is parallelized by distributing several independent tasks among the nodes. Even though heterogeneous multicore clusters are becoming very common nowadays, very few task allocation policies were proposed for this type of architecture. This paper proposes an MPI/OpenMP master/slave parallel strategy to run DIALIGN-TX in heterogeneous multicore clusters, with several allocation policies. We show that an appropriate choice of the master node has great impact on the overall system performance. Also, the results obtained in a heterogeneous multicore cluster composed of 4 nodes (30 cores), with real sequence sets show that the execution time can be drastically reduced when the appropriate allocation policy is used.     

Characterizing peers communities and dynamics in a P2P live streaming system

Despite the large number of works devoted to understand P2P live streaming applications, most of them put forth so far rely on characterizing the static view of these systems. In this work, we characterize the SopCast, one of the most important P2P live streaming applications. We focus on its dynamics behavior as well as on the community formation phenomena. Our results show that SopCast presents a low overlay topology diameter and low end-to-end shortest path. In fact, diameter is smaller than 6 hops in almost 90 % of the observation time. More than 96 % of peers’ end-to-end connections present only 3 hops. These values combined may lead to low latencies and a fast streaming diffusion. Second, we show that communities in SopCast are well defined by the streaming data exchange process. Moreover, the SopCast protocol does not group peers according to their Autonomous System. In fact, the probability that a community contains 50 % of its members belonging to the same AS (when we observe the largest AS of our experiments) is lower then 10 %. Peers exchange more data with partners belonging to the same community instead of peers inside the same AS. For the largest AS we have, less than 18 % of peer traffic has been exchanged with another AS partners. Finally, our analysis provides important information to support the future design of more efficient P2P live streaming systems and new protocols that exploit communities’ relationships.