Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil

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

Abordagem da ergonomia para análise da acessibilidade a hóspedes com deficiência visual em hotéis: soluções de inclusão de pessoas cegas e com baixa visão

This study evaluates the level of accessibility for people with visual impairment (blindness and low vision) hotels in the city of Natal-RN, Brazil, and provides principles, guidelines and means of projective make hotels accessible, to promote comfort, autonomy and security of these people. We used a qualitative research methodology and quantitative trait descriptive, analytical and interpretive. Was taken as a base for field studies Ergonomic Analysis of Work, beginning with a study of the demands of accessibility of hotels and analyzing the modeling activity in these establishments through the application of interactional and observational techniques, such as film, photographic records, conversational actions and observation protocols. A protocol was developed and applied to evaluate the compliance of accessibility of hotels in the face of Brazilian technical standard NBR 9050 (2004). We used methods of Cognitive Task Analysis (CTA) associated with simulated activities to identify the processes of decision making and analyzing the observables of the activities performed by people with visual impairment (POS). Interviews were conducted with people who are blind and low vision in various cities in order to meet accessibility difficulties they faced in hotels and recommendations for improvement that they indicate. The mapping results showed that of 16 hotels 4 and 5 star studied in Natal-RN, reached only 7% of the 50 items of the protocol, while none of them reached 70% of the items. About the results obtained in simulated activities and analyzed from the ATC, we saw that the hotel where it was performed this step shows a need to adequately address the guests with visual impairments

Odometria visual baseada em técnicas de structure from motion

Visual Odometry is the process that estimates camera position and orientation based solely on images and in features (projections of visual landmarks present in the scene) extraced from them. With the increasing advance of Computer Vision algorithms and computer processing power, the subarea known as Structure from Motion (SFM) started to supply mathematical tools composing localization systems for robotics and Augmented Reality applications, in contrast with its initial purpose of being used in inherently offline solutions aiming 3D reconstruction and image based modelling. In that way, this work proposes a pipeline to obtain relative position featuring a previously calibrated camera as positional sensor and based entirely on models and algorithms from SFM. Techniques usually applied in camera localization systems such as Kalman filters and particle filters are not used, making unnecessary additional information like probabilistic models for camera state transition. Experiments assessing both 3D reconstruction quality and camera position estimated by the system were performed, in which image sequences captured in reallistic scenarios were processed and compared to localization data gathered from a mobile robotic platform

Implementação de um sistema embarcado aplicado ao controle de pressão arterial

Hypertension is a dangerous disease that can cause serious harm to a patient health. In some situations the necessity to control this pressure is even greater, as in surgical procedures and post-surgical patients. To decrease the chances of a complication, it is necessary to reduce blood pressure as soon as possible. Continuous infusion of vasodilators drugs, such as sodium nitroprusside (SNP), rapidly decreased blood pressure in most patients, avoiding major problems. Maintaining the desired blood pressure requires constant monitoring of arterial blood pressure and frequently adjusting the drug infusion rate. Manual control of arterial blood pressure by clinical personnel is very demanding, time consuming and, as a result, sometimes of poor quality. Thus, the aim of this work is the design and implementation of a database of tuned controllers based on patients models, in order to find a suitable PID to be embedded in a Programmable Integrated Circuit (PIC), which has a smaller cost, smaller size and lower power consumption. For best results in controlling the blood pressure and choosing the adequate controller, tuning algorithms, system identification techniques and Smith predictor are used. This work also introduces a monitoring system to assist in detecting anomalies and optimize the process of patient care.

Acelerando algoritmos de baixo nível em visão robótica com hardware reconfigurável

A challenge that remains in the robotics field is how to make a robot to react in real time to visual stimulus. Traditional computer vision algorithms used to overcome this problem are still very expensive taking too long when using common computer processors. Very simple algorithms like image filtering or even mathematical morphology operations may take too long. Researchers have implemented image processing algorithms in high parallelism hardware devices in order to cut down the time spent in the algorithms processing, with good results. By using hardware implemented image processing techniques and a platform oriented system that uses the Nios II Processor we propose an approach that uses the hardware processing and event based programming to simplify the vision based systems while at the same time accelerating some parts of the used algorithms

Contribuições a técnicas de agrupamento e visualização de dados multivariados utilizando mapas auto-organizáveis

Self-organizing maps (SOM) are artificial neural networks widely used in the data mining field, mainly because they constitute a dimensionality reduction technique given the fixed grid of neurons associated with the network. In order to properly the partition and visualize the SOM network, the various methods available in the literature must be applied in a post-processing stage, that consists of inferring, through its neurons, relevant characteristics of the data set. In general, such processing applied to the network neurons, instead of the entire database, reduces the computational costs due to vector quantization. This work proposes a post-processing of the SOM neurons in the input and output spaces, combining visualization techniques with algorithms based on gravitational forces and the search for the shortest path with the greatest reward. Such methods take into account the connection strength between neighbouring neurons and characteristics of pattern density and distances among neurons, both associated with the position that the neurons occupy in the data space after training the network. Thus, the goal consists of defining more clearly the arrangement of the clusters present in the data. Experiments were carried out so as to evaluate the proposed methods using various artificially generated data sets, as well as real world data sets. The results obtained were compared with those from a number of well-known methods existent in the literature

Aquatic weed automatic classification using machine learning techniques

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

Use of Primary Sludge from Pulp and Paper Mills for Nanocomposites

Cellulose nanocrystals have been evaluated as reinforcement material in polymeric matrices due to their potential to improve the mechanical, optical, and dielectric properties of these matrixes. This work describes how high pressure defibrillation and chemical purification affect the sludge fiber morphology from micro to nanoscale. Microscopy techniques and X-ray diffraction were used to study the structure and properties of the prepared nanofibers and composites. Microscopic studies showed that the used individualization processes lead to a unique morphology of interconnected web-like structure of sludge fibers. The nanofibers are bundles of cellulose fibers having widths (5 to 30 nm) and estimated lengths of several micrometers.