Análise e implementação de um algoritmo de busca dispersa para o planejamento da expansão de sistemas de transmissão

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Novas aplicações de metaheurísticas na solução do problema de planejamento da expansão do sistema de transmissão de energia elétrica

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Eficácia do programa de remediação fonológica em escolares com dificuldades de aprenizagem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Desenvolvimento e implementação de modelos para simulação de dados SNPs

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Desenvolvimento e aplicação de um software cristalográfico com protocolo de acesso a um banco de dados distribuído

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Planejamento de experimentos em blocos aplicado às propriedades mecânicas de arames de aço para molas

The purpose of this article is to demonstrate an application of the design of block experiments via analysis and multiple linear regression in the investigation of a steel thermal treatment process with multiple responses. The study aimed to design statistical models to predict the mechanical properties in SAE 9254 draw steel wires, with diameters of 2.00 mm and 6.50 mm, after quench hardening and tempering. For this purpose, process input variables (wire diameter, processing speed, tempering temperature and polymer concentration) were investigated regarding their influence on the material tensile strength, yield point and hardness. The results revealed that the mechanical properties of the steel wire are significantly influenced by the selected variables, and analysis of variance (ANOVA) was employed to validate the design of the statistical models. Multiple linear regression allowed for an appropriate representation of the process, and graphical analysis was found to be very useful in displaying the behavior of the multiple responses.

Impaired acuity of the approximate number system in 22q11.2 microdeletion syndrome

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelagem e otimização por metodologia de superfícies de resposta: um estudo em arames de aço SAE 9254 para molas automobilísticas

Pós-graduação em Engenharia Mecânica - FEG

Correlação entre habilidades cognitivo-linguísticas em escolares com dificuldades de aprendizagem

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Desempenho de escolares com e sem transtorno de aprendizagem em leitura, escrita, consciência fonológica, velocidade de processamento e memória de trabalho fonológica

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

O aprimoramento de um software de estúdio virtual por meio de técnicas de matting digital e registro de objetos virtuais

A virtual studio system can use technologies as augmented reality and digital matting to decrease production costs at the same time it provides the same resources of a conventional studio. With this, it’s possible for the current studios, with low cost and using conventional devices, to create productions with greater image quality and effects. Some difficulties are recurrent in virtual studio applications that use augmented reality and digital matting. The virtual objects registration in augmented reality techniques suffer from problems caused by optical distortions in the camera, errors in the marker tracking system, lack of calibration on the equipments or on the environment (lighting, for example), or even by delays in the virtual objects display. On the other hand, the digital matting’s main problem is the real-time execution to preview the scene, which must have optimized processing speed at the same time while maintain the best image quality possible. Taking the given context into consideration, this work aims to give continuity to a virtual studio system called ARStudio, by enhancing digital matting, virtual objects registration and introducing a segmentation based on depth map, yet adding better control over functionalities previously implemented

Contrast Sensitivity Mediated by Inferred Magno- and Parvocellular Pathways in Type 2 Diabetics with and without Nonproliferative Retinopathy

PURPOSE. To evaluate achromatic contrast sensitivity (CS) with magnocellular-(M) and parvocellular-(P) probing stimuli in type 2 diabetics, with (DR) or without (NDR) nonproliferative retinopathy. METHODS. Inferred M-and P-dominated responses were assessed with a modified version of the steady-/pulsed-pedestal paradigm (SP/PP) applied in 26 NDR (11 male; mean age, 55 +/- 9 years; disease duration, 5 +/- 4 years); 19 DR (6 male; mean age, 58 +/- 7 years; disease duration = 9 +/- 6 years); and 18 controls (CTRL; 12 male; mean age, 55 +/- 10 years). Thresholds were measured with pedestals at 7, 12, and 19 cd/m(2), and increment durations of 17 and 133 ms. The thresholds from the two stimulus durations were used to estimate critical durations (Tc) for each data set. RESULTS. Both DR and NDR patients had significant reduction in CS in both SP and PP paradigms in relation to CTRL (Kruskal-Wallis, P < 0.01). Patients` critical duration estimates for either paradigm were not significantly different from CTRL. CONCLUSIONS. The significant reduction of CS in both paradigms is consistent with losses of CS in both M and P pathways. The CS losses were not accompanied by losses in temporal processing speed in either diabetic group. Significant CS loss in the group without retinopathy reinforces the notion that neural changes associated with the cellular and functional visual loss may play an important role in the etiology of diabetic visual impairment. In addition, the results show that the SP/PP paradigm provides an additional tool for detection and characterization of the early functional damage due to diabetes. (Invest Ophthalmol Vis Sci. 2011; 52:1151-1155) DOI:10.1167/iovs.09-3705

The effect of overweight/obesity on cognitive function in euthymic individuals with bipolar disorder

Background. - Persistent impairment in cognitive function has been described in euthymic individuals with bipolar disorder. Collective work indicates that obesity is associated with reduced cognitive function in otherwise healthy individuals. This sub-group post-hoc analysis preliminarily explores and examines the association between overweight/obesity and cognitive function in euthymic individuals with bipolar disorder. Methods. - Euthymic adults with DSM-IV-TR-defined bipolar I or II disorder were enrolled. Subjects included in this post-hoc analysis (n = 67) were divided into two groups (normal weight, body mass index [BMI] of 18.5-24.9 kg/m(2); overweight/obese, BMI >= 25.0 kg/m(2)). Demographic and clinical information were obtained at screening. At baseline, study participants completed a comprehensive cognitive battery to assess premorbid IQ, verbal learning and memory, attention and psychomotor processing speed, executive function, general intellectual abilities, recollection and habit memory, as well as self-perceptions of cognitive failures. Results. - BMI was negatively correlated with attention and psychomotor processing speed as measured by the Digit Symbol Substitution Test (P < 0.01). Overweight and obese bipolar individuals had a significantly lower score on the Verbal Fluency Test when compared to normal weight subjects (P < 0.05). For all other measures of cognitive function, non-significant trends suggesting a negative association with BMI were observed, with the exception of measures of executive function (i.e. Trail Making Test B) and recollection memory (i.e. process-dissociation task). Conclusion. - Notwithstanding the post-hoc methodology and relatively small sample size, the results of this study suggest a possible negative effect of overweight/obesity on cognitive function in euthymic individuals with bipolar disorder. Taken together, these data provide the impetus for more rigorous evaluation of the mediational role of overweight/obesity (and other medical co-morbidity) on cognitive function in psychiatric populations. (C) 2011 Elsevier Masson SAS. All rights reserved.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.

Neuropsychological problems after paediatric stroke: two year follow-up of Swiss children

AIM: The aim of this study was to obtain information about neurological and cognitive outcome for a population-based group of children after paediatric ischaemic stroke. METHODS: Data from the Swiss neuropaediatric stroke registry (SNPSR), from 1.1.2000 to 1.7.2002, including children (AIS 1) and neonates (AIS 2). At 18-24 months after a stroke, a follow-up examination was performed including a history, neurological and neuropsychological assessment. RESULTS: 33/48 children (22 AIS 1, 11 AIS 2) participated in the study. Neurological outcome was good in 16/33. After childhood stroke mean IQ levels were normal (94), but 6 children had IQ < 85 (50-82) and neuropsychological problems were present in 75%. Performance IQ (93) was reduced compared to verbal IQ (101, p = 0.121) due to problems in the domain of processing speed (89.5); auditory short-term memory was especially affected. Effects on school career were common. Outcome was worse in children after right-sided infarction. Children suffering from stroke in mid-childhood had the best prognosis. There was no clear relationship between outcome and localisation of the lesion. After neonatal stroke 7/11 children showed normal development and epilepsy indicated a worse prognosis in the remaining 4. CONCLUSION: After paediatric stroke neuropsychological problems are present in about 75% of children. Younger age at stroke as well as an emergence of epilepsy were predictors for worse prognosis.