Localising and quantifying damage by means of a multi-chromosome genetic algorithm

This paper presents a structural damage detection methodology based on genetic algorithms and dynamic parameters. Three chromosomes are used to codify an individual in the population. The first and second chromosomes locate and quantify damage, respectively. The third permits the self-adaptation of the genetic parameters. The natural frequencies and mode shapes are used to formulate the objective function. A numerical analysis was performed for several truss structures under different damage scenarios. The results have shown that the methodology can reliably identify damage scenarios using noisy measurements and that it results in only a few misidentified elements. (C) 2012 Civil-Comp Ltd and Elsevier Ltd. All rights reserved.

Personal and Social Performance (PSP) scale for patients with schizophrenia: translation to Portuguese, cross-cultural adaptation and interrater reliability

INTRODUCTION: Schizophrenia is a chronic mental disorder associated with impairment in social functioning. The most widely used scale to measure social functioning is the GAF (Global Assessment of Functioning), but it has the disadvantage of measuring at the same time symptoms and functioning, as described in its anchors. OBJECTIVES:Translation and cultural adaptation of the PSP, proposing a final version in Portuguese for use in Brazil. METHODS: We performed five steps: 1) translation; 2) back translation; 3) formal assessment of semantic equivalence; 4) debriefing; 5) analysis by experts. Interrater reliability (Intraclass correlation, ICC) between two raters was also measured. RESULTS: The final version was applied by two independent investigators in 18 adults with schizophrenia (DSM-IV-TR). The interrater reliability (ICC) was 0.812 (p < 0.001). CONCLUSION: The translation and adaptation of the PSP had an adequate level of semantic equivalence between the Portuguese version and the original English version. There were no difficulties related to understanding the content expressed in the translated texts and terms. Its application was easy and it showed a good interrater reliability. The PSP is a valid instrument for the measurement of personal and social functioning in schizophrenia.

SMAC multi-hop mesh routing protocol using IEEE 802.15.4

This paper discusses some aspects related to Wireless Sensor Networks over the IEEE 802.15.4 standard, and proposes, for the very first time, a mesh network topology with geographic routing integrated to the open Freescale protocol (SMAC - Simple Medium Access Control). For this is proposed the SMAC routing protocol. Before this work the SMAC protocol was suitable to perform one hop communications only. However, with the developed mechanisms, it is possible to use multi-hop communication. Performance results from the implemented protocol are presented and analyzed in order to define important requirements for wireless sensor networks, such as robustness, self-healing property and low latency. (c) 2011 Elsevier Ltd. All rights reserved.

A novel strategy for building interoperable MPI environment in heterogeneous high performance systems

Breakthrough advances in microprocessor technology and efficient power management have altered the course of development of processors with the emergence of multi-core processor technology, in order to bring higher level of processing. The utilization of many-core technology has boosted computing power provided by cluster of workstations or SMPs, providing large computational power at an affordable cost using solely commodity components. Different implementations of message-passing libraries and system softwares (including Operating Systems) are installed in such cluster and multi-cluster computing systems. In order to guarantee correct execution of message-passing parallel applications in a computing environment other than that originally the parallel application was developed, review of the application code is needed. In this paper, a hybrid communication interfacing strategy is proposed, to execute a parallel application in a group of computing nodes belonging to different clusters or multi-clusters (computing systems may be running different operating systems and MPI implementations), interconnected with public or private IP addresses, and responding interchangeably to user execution requests. Experimental results demonstrate the feasibility of this proposed strategy and its effectiveness, through the execution of benchmarking parallel applications.

A multi-objective adaptive immune algorithm for multi-application NoC mapping

Current SoC design trends are characterized by the integration of larger amount of IPs targeting a wide range of application fields. Such multi-application systems are constrained by a set of requirements. In such scenario network-on-chips (NoC) are becoming more important as the on-chip communication structure. Designing an optimal NoC for satisfying the requirements of each individual application requires the specification of a large set of configuration parameters leading to a wide solution space. It has been shown that IP mapping is one of the most critical parameters in NoC design, strongly influencing the SoC performance. IP mapping has been solved for single application systems using single and multi-objective optimization algorithms. In this paper we propose the use of a multi-objective adaptive immune algorithm (M(2)AIA), an evolutionary approach to solve the multi-application NoC mapping problem. Latency and power consumption were adopted as the target multi-objective functions. To compare the efficiency of our approach, our results are compared with those of the genetic and branch and bound multi-objective mapping algorithms. We tested 11 well-known benchmarks, including random and real applications, and combines up to 8 applications at the same SoC. The experimental results showed that the M(2)AIA decreases in average the power consumption and the latency 27.3 and 42.1 % compared to the branch and bound approach and 29.3 and 36.1 % over the genetic approach.

Low-level laser therapy (LLLT) in human progressive-intensity running: effects on exercise performance, skeletal muscle status, and oxidative stress

The aim of this work was to evaluate the effects of low-level laser therapy (LLLT) on exercise performance, oxidative stress, and muscle status in humans. A randomized double-blind placebo-controlled crossover trial was performed with 22 untrained male volunteers. LLLT (810 nm, 200 mW, 30 J in each site, 30 s of irradiation in each site) using a multi-diode cluster (with five spots - 6 J from each spot) at 12 sites of each lower limb (six in quadriceps, four in hamstrings, and two in gastrocnemius) was performed 5 min before a standardized progressive-intensity running protocol on a motor-drive treadmill until exhaustion. We analyzed exercise performance (VO(2 max), time to exhaustion, aerobic threshold and anaerobic threshold), levels of oxidative damage to lipids and proteins, the activities of the antioxidant enzymes superoxide dismutase (SOD) and catalase (CAT), and the markers of muscle damage creatine kinase (CK) and lactate dehydrogenase (LDH). Compared to placebo, active LLLT significantly increased exercise performance (VO(2 max) p = 0.01; time to exhaustion, p = 0.04) without changing the aerobic and anaerobic thresholds. LLLT also decreased post-exercise lipid (p = 0.0001) and protein (p = 0.0230) damages, as well as the activities of SOD (p = 0.0034), CK (p = 0.0001) and LDH (p = 0.0001) enzymes. LLLT application was not able to modulate CAT activity. The use of LLLT before progressive-intensity running exercise increases exercise performance, decreases exercise-induced oxidative stress and muscle damage, suggesting that the modulation of the redox system by LLLT could be related to the delay in skeletal muscle fatigue observed after the use of LLLT.

Incorporating label dependency into the binary relevance framework for multi-label classification

In multi-label classification, examples can be associated with multiple labels simultaneously. The task of learning from multi-label data can be addressed by methods that transform the multi-label classification problem into several single-label classification problems. The binary relevance approach is one of these methods, where the multi-label learning task is decomposed into several independent binary classification problems, one for each label in the set of labels, and the final labels for each example are determined by aggregating the predictions from all binary classifiers. However, this approach fails to consider any dependency among the labels. Aiming to accurately predict label combinations, in this paper we propose a simple approach that enables the binary classifiers to discover existing label dependency by themselves. An experimental study using decision trees, a kernel method as well as Naive Bayes as base-learning techniques shows the potential of the proposed approach to improve the multi-label classification performance.

MR-Radix: a multi-relational data mining algorithm

Abstract Background Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.

Contribuições da Psicologia Histórico-Cultural para a formação e atuação do psicólogo em contexto de Educação Inclusiva

Este texto objetiva discutir contribuições da Psicologia Histórico-Cultural para a formação e a atuação do psicólogo junto à educação, num contexto de Educação Inclusiva. Destacam-se os fundamentos e princípios da educação para pessoas com deficiência, bem como postulados da teoria de Vigotski referentes à formação e à atuação dos psicólogos. Considera-se que a perspectiva teórica elaborada pelo autor soviético contribui por: destacar a transitoriedade dos eventos e fenômenos; atrelar o mundo das ideias, valores e representações à vida objetiva e à prática social; relacionar propostas educacionais a um dado projeto de sociedade; defender a possibilidade do desvendamento da constituição social do psiquismo e da possível intervenção sobre a mesma; requisitar uma condição de desenvolvimento humano sobre o patamar do homem cultural e livre. Por fim, destaca-se o fato de que a Educação Inclusiva deve se referir ao processo de apropriação e usufruto das produções humanas mais complexas, elaboradas nas diferentes áreas da vida e do conhecimento.