Development of a support vector machine-based navigation system for driving a mobile robot through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features. Such features are then submitted to a support vector machine in order to find out the most appropriate route. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route. © 2012 IEEE.

Cardiopulmonary bypass: development of John Gibbon's heart-lung machine

To provide a brief review of the development of cardiopulmonary bypass. A review of the literature on the development of extracorporeal circulation techniques, their essential role in cardiovascular surgery, and the complications associated with their use, including hemolysis and inflammation. The advancement of extracorporeal circulation techniques has played an essential role in minimizing the complications of cardiopulmonary bypass, which can range from various degrees of tissue injury to multiple organ dysfunction syndrome. Investigators have long researched the ways in which cardiopulmonary bypass may insult the human body. Potential solutions arose and laid the groundwork for development of safer postoperative care strategies. Steady progress has been made in cardiopulmonary bypass in the decades since it was first conceived of by Gibbon. Despite the constant evolution of cardiopulmonary bypass techniques and attempts to minimize their complications, it is still essential that clinicians respect the particularities of each patient's physiological function.

Traffic soil compaction of an oxisol related to soybean development and yield

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

Analytical method for the design of a machine with aligned and skewed permanent magnets

This work aims to present the design and the evaluation of a standard multi-pole machine with permanent magnets inserted in the rotor by two different geometrical forms: aligned and skewed magnets. The design (new analytical method) was based on a standard 250 W three phase 12-pole induction motor (squirrel cage rotor type), beginning with the original stator constructive data to calculate the magnetic flux density to determine the permanent magnets. In the development of the work, a simple and modular rotor was built reusing the original 12-pole stator (concentrated windings). The machine was evaluated in a laboratory for the purpose of checking the quantity and quality of energy produced with the machine operating as a generator and its start, torque, and performance working as a motor. In conclusion, the modular skewed magnet is an option for electrical machines, for the generation of a reasonable quality, in the context of decentralized generation and a motor with high torque and low energetic consumption.

α-SiAION: Development and machining test on gray cast iron

The α-SiAlON ceramic cutting tool insert is developed. Silicon nitride and additives powders are pressed and sintered in the form of cutting tool inserts at temperature of 1900 °C. The physics and mechanical properties of the inserts like green density, weight loss, relative density, hardness and fracture toughness are evaluated. Machining studies are conducted on grey cast iron workpiece to evaluate the performance of α-SiAlON ceramic cutting tool. In the paper the cutting tool used in higher speed showed an improvement in the tribological interaction between the cutting tools and the grey cast iron workpiece resulted in a significant reduction of flank wear and roughness, because of better accommodation and the presence of the graphite in gray cast iron. The above results are discussed in terms of their affect at machining parameters on gray cast iron.

A case study of concurrent engineering application on the development of parts for the white goods industry in Brazil

This classical way to manage product development processes for massive production seems to be changing: high pressure for cost reduction, higher quality standards, markets reaching for innovation lead to the necessity of new tools for development control. Into this, and learning from the automotive and aerospace industries factories from other segments are starting to understand and apply manufacturing and assembly oriented projects to ease the task of generate goods and from this obtain at least a part of the expected results. This paper is intended to demonstrate the applicability of the concepts of Concurrent Engineering and DFM/DFA (Design for Manufacturing and Assembly) in the development of products and parts for the White Goods industry in Brazil (major appliances as refrigerators, cookers and washing machines), showing one case concerning the development and releasing of a component. Finally is demonstrated in a short term how was reached a solution that could provide cost savings and reduction on the time to delivery using those techniques.

Development of ceramic cutting tools for future application on dry machining

Advanced ceramic materials constitute a mature technology with a very broad base of current and potential applications and a growing list of material compositions. Within the advanced ceramics category, silicon nitride based ceramics are wear-resistant, corrosion-resistant and lightweight materials, and are superior to many materials with regard to stability in high-temperature environments. Because of this combination the silicon nitride ceramics have an especially high potential to resolve a wide number of machining problems in the industries. Presently the Si3N4 ceramic cutting tool inserts are developed using additives powders that are pressed and sintered in the form of a cutting tool insert at a temperature of 1850 °C using pressureless sintering. The microstructure of the material was observed and analyzed using XRD, SEM, and the mechanical response of this array microstructure was characterized for hardness Vickers and fracture toughness. The results show that Si3N4/20 wt.% (AlN and Y 2O3) gives the best balance between hardness Vickers and fracture toughness. The Si3N4/15 wt.% (AlN and Y 2O3) composition allows the production of a very fine-grained microstructure with low decreasing of the fracture toughness and increased hardness Vickers. These ceramic cutting tools present adequate characteristics for future application on dry machining. © (2010) Trans Tech Publications.

Development of an instrumentation system embedded on FPGA for real time measurement of mechanical vibrations in rotating machinery

The real-time monitoring of events in an industrial plant is vital, to monitor the actual conditions of operation of the machinery responsible for the manufacturing process. A predictive maintenance program includes condition monitoring of the rotating machinery, to anticipate possible conditions of failure. To increase the operational reliability it is thus necessary an efficient tool to analyze and monitor the equipments, in real-time, and enabling the detection of e.g. incipient faults in bearings. To fulfill these requirements some innovations have become frequent, namely the inclusion of vibration sensors or stator current sensors. These innovations enable the development of new design methodologies that take into account the ease of future modifications, upgrades, and replacement of the monitored machine, as well as expansion of the monitoring system. This paper presents the development, implementation and testing of an instrument for vibration monitoring, as a possible solution to embed in industrial environment. The digital control system is based on an FPGA, and its configuration with an open hardware design tool is described. Special focus is given to the area of fault detection in rolling bearings. © 2012 IEEE.

Remote phenology: Applying machine learning to detect phenological patterns in a cerrado savanna

Plant phenology has gained importance in the context of global change research, stimulating the development of new technologies for phenological observation. Digital cameras have been successfully used as multi-channel imaging sensors, providing measures of leaf color change information (RGB channels), or leafing phenological changes in plants. We monitored leaf-changing patterns of a cerrado-savanna vegetation by taken daily digital images. We extract RGB channels from digital images and correlated with phenological changes. Our first goals were: (1) to test if the color change information is able to characterize the phenological pattern of a group of species; and (2) to test if individuals from the same functional group may be automatically identified using digital images. In this paper, we present a machine learning approach to detect phenological patterns in the digital images. Our preliminary results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; and (2) different plant species present a different behavior with respect to the color change information. Based on those results, we suggest that individuals from the same functional group might be identified using digital images, and introduce a new tool to help phenology experts in the species identification and location on-the-ground. ©2012 IEEE.

The Development of a Universal In Silico Predictor of Protein-Protein Interactions

Protein-protein interactions (PPIs) are essential for understanding the function of biological systems and have been characterized using a vast array of experimental techniques. These techniques detect only a small proportion of all PPIs and are labor intensive and time consuming. Therefore, the development of computational methods capable of predicting PPIs accelerates the pace of discovery of new interactions. This paper reports a machine learning-based prediction model, the Universal In Silico Predictor of Protein-Protein Interactions (UNISPPI), which is a decision tree model that can reliably predict PPIs for all species (including proteins from parasite-host associations) using only 20 combinations of amino acids frequencies from interacting and non-interacting proteins as learning features. UNISPPI was able to correctly classify 79.4% and 72.6% of experimentally supported interactions and non-interacting protein pairs, respectively, from an independent test set. Moreover, UNISPPI suggests that the frequencies of the amino acids asparagine, cysteine and isoleucine are important features for distinguishing between interacting and non-interacting protein pairs. We envisage that UNISPPI can be a useful tool for prioritizing interactions for experimental validation. © 2013 Valente et al.

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

Machine vision to identify broiler breeder behavior

Animal behavioral parameters can be used to assess welfare status in commercial broiler breeders. Behavioral parameters can be monitored with a variety of sensing devices, for instance, the use of video cameras allows comprehensive assessment of animal behavioral expressions. Nevertheless, the development of efficient methods and algorithms to continuously identify and differentiate animal behavior patterns is needed. The objective this study was to provide a methodology to identify hen white broiler breeder behavior using combined techniques of image processing and computer vision. These techniques were applied to differentiate body shapes from a sequence of frames as the birds expressed their behaviors. The method was comprised of four stages: (1) identification of body positions and their relationship with typical behaviors. For this stage, the number of frames required to identify each behavior was determined; (2) collection of image samples, with the isolation of the birds that expressed a behavior of interest; (3) image processing and analysis using a filter developed to separate white birds from the dark background; and finally (4) construction and validation of a behavioral classification tree, using the software tool Weka (model 148). The constructed tree was structured in 8 levels and 27 leaves, and it was validated using two modes: the set training mode with an overall rate of success of 96.7%, and the cross validation mode with an overall rate of success of 70.3%. The results presented here confirmed the feasibility of the method developed to identify white broiler breeder behavior for a particular group of study. Nevertheless, more improvements in the method can be made in order to increase the validation overall rate of success. (C) 2013 Elsevier B.V. All rights reserved.

Incubation temperature manipulation during fetal development reduces adiposity of broiler hatchlings

Broilers are known as an efficient source of lean meat. Genetic selection resulted in broiler strains with large body size and fast growth, but a concomitant increase in fat deposition also occurred. Other than reducing nutrient intake, there is a lack of alternative methods to control body fat composition of broilers. The present study assessed whether incubation temperature (machine temperatures: 36ºC, 37.5ºC, and 39ºC; eggshell temperatures: 37.4 ± 0.08°C, 37.8 ± 0.15ºC, and 38.8 ± 0.33°C, respectively.) from d 13 affects broiler hatchling fat deposition. We analyzed adipocyte hypertrophy and proliferation in 3 body regions; weight and chemical composition of yolk-free chicks and yolk sacs; and serum lipid profile. Increased incubation temperature reduced abdominal and cervical adipocyte size. Independently of temperature, cervical adipocytes were smaller and showed higher proliferation than adipocytes in the abdominal and thigh regions. Smaller cervical adipocytes were observed in birds from eggs incubated at 36ºC and 39ºC. With regard to weight and composition of chicks, ash content as a percentage of dry matter was the only variable affected by temperature; it was higher in chicks from eggs incubated at 36ºC than at 39ºC and showed no significant difference between chicks incubated at 39ºC and 37.5ºC. Absolute and relative weights of yolk sacs were higher from eggs incubated at 39ºC than at 36ºC, and these two treatments did not differ from the 37.5ºC control. Absolute measures of yolk sac lipids, moisture, dry matter, and crude protein content were lower in chicks from eggs incubated at 36ºC, and no significant differences were found for these variables between chicks from eggs incubated at 37.5ºC and 39ºC. Hatchlings from eggs incubated at 36°C had significantly higher cholesterol levels than chicks incubated at the other 2 temperatures, but no additional effects on blood lipids were detected. Incubation temperature manipulation during fetal development altered cervical and abdominal adipocyte size in broiler hatchlings and could become a tool in hatcheries to manipulate chick quality, although further studies are needed to evaluate its long-term effects.