Design of a state observer using decay rate LMI constraints for fault detection in mechanical systems

Nowadays, one of the most important concerns for many companies is to maintain the operation of their systems without sudden equipment break down. Because of this, new techniques for fault detection and location in mechanical systems subject to dynamic loads have been developed. This paper studies of the influence of the decay rate in the design of state observers using LMI for fault detection in mechanical systems. This influence is analyzed by the performance index proposed by Huh and Stein for the condition of a state observer. An example is presented to illustrate the methodology discussed.

Characterization of texture in image of skin lesions by support vector machine

Due to the increased incidence of skin cancer, computational methods based on intelligent approaches have been developed to aid dermatologists in the diagnosis of skin lesions. This paper proposes a method to classify texture in images, since it is an important feature for the successfully identification of skin lesions. For this is defined a feature vector, with the fractal dimension of images through the box-counting method (BCM), which is used with a SVM to classify the texture of the lesions in to non-irregular or irregular. With the proposed solution, we could obtain an accuracy of 72.84%. © 2012 AISTI.

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 assessment of the quality of sugar using electronic tongue and machine learning algorithms

The correct classification of sugar according to its physico-chemical characteristics directly influences the value of the product and its acceptance by the market. This study shows that using an electronic tongue system along with established techniques of supervised learning leads to the correct classification of sugar samples according to their qualities. In this paper, we offer two new real, public and non-encoded sugar datasets whose attributes were automatically collected using an electronic tongue, with and without pH controlling. Moreover, we compare the performance achieved by several established machine learning methods. Our experiments were diligently designed to ensure statistically sound results and they indicate that k-nearest neighbors method outperforms other evaluated classifiers and, hence, it can be used as a good baseline for further comparison. © 2012 IEEE.

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.

Bond strength of adhesive systems with different solvents to dry and wet dentin

Aim: This study evaluates bond strength between dentin and composite using adhesives with different solvents to dry and wet dentin. Materials and methods: Ninety bovine incisors were used; the vestibular surfaces were worn by the exposure of an area with a diameter of 4 mm of dentin. The specimens were divided into 6 groups, according to the type of adhesive used and hydratation stals: Group SB-wet: Single Bond 2 in wet dentin, Group SBdry: Single Bond 2 in dry dentin, Group SL-wet: Solobond M in wet dentin, Group SL-dry: Solobond M in dentin dry. Group XPwet: XP Bond in wet dentin, Group XP-dry: XP Bond in dentin dry. They were cut to obtain specimens in the shape of stick with 1 × 1 mm and subjected to microtensile test in universal testing machine with a cross speed of 1mm/min. The data were analyzed with ANOVA and Tukey's tests (5%). Results: ANOVA showed significant differences for surface treatment and interaction, but no difference was found for adhesive factor. The Tukey's test showed that the samples with wet dentin shown higher values of bond strength. Conclusion: The adhesive did not influence in the bond strength. The groups with wet dentin showed higher values of bond strength than groups with dry dentin.

Influence of CVD diamond tips and Er:YAG laser irradiation on bonding of different adhesive systems to dentin

Aim: The aim of this study was to compare the microtensile bond strength of three adhesive systems, using different methods of dentin preparation. Materials and methods: A hundred and eight bovine teeth were used. The dentin from buccal face was exposed and prepared with three different methods, divided in 3 groups: Group 1 (DT)- diamond tip on a high-speed handpiece; Group 2 (CVD)-CVD tip on a ultrasonic handpiece; Group 3 (LA)-Er: YAG laser. The teeth were divided into 3 subgroups, according adhesive systems used: Subgroup 1-Adper Single Bond Plus/3M ESPE (SB) total-etch adhesive; Subgroup 2-Adper Scotchbond SE/3M ESPE (AS) selfetching adhesive; Subgroup 3-Clearfil SE Bond/Kuraray (CS) selfetching adhesive. Blocks of composite (Filtek Z250-3M ESPE) 4 mm high were built up and specimens were stored in deionized water for 24 hours at 37°C. Serial mesiodistal and buccolingual cuts were made and stick-like specimens were obtained, with transversal section of 1.0 mm2. The samples were submitted to microtensile test at 1 mm/min and load of 10 kg in a universal testing machine. Data (MPa) were subjected to ANOVA and Tukey's tests (p < 0.05). Results and conclusion: Surface treatment with Diamond or CVD tips associated with Clearfil SE Bond adhesive produced significantly lower bond strength values compared to other groups. Surface treatment with Er: YAG laser associated with Single Bond Plus or Clearfil SE Bond adhesives and surface treatment with CVD tip associated with Adper Scotchbond SE adhesive produced significantly lower bond strength values compared to surface treatment with diamond or CVD tips associated with Single Bond Plus or Adper Scotchbond SE adhesives. Clinical significance: Interactions between laser and the CVD tip technologies and the different adhesive systems can produce a satisfactory bonding strength result, so that these associations may be beneficial and enhance the clinical outcomes.

An approach to implement data fusion techniques in wireless sensor networks using genetic machine learning algorithms

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks. © 2013 Elsevier B.V. All rights reserved.

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.

Aspectos ergonômicos em colhedoras de cana-de-açúcar: ruído, distribuição dos comandos e avaliação ponderada de conforto

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Desenvolvimento ontogenético de estruturas sensoriais em Macrobrachium rosenbergii (De Man 1879) (Crustacea, Palaemonidae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Economic efficiency of two baling systems for sugarcane straw

In recent years, harvesting process of sugarcane is changing itself, passing through semi-mechanized for mechanized system, who, currently predominate in Sao Paulo state, Brazil. Mechanized harvesting consists in a sequence of operations which includes cutting the pointer and chopping the stalk. The straw is a harvesting residue, and it stays in the ground, piling up above soil, with a possible prejudice for crop yield. An economic way to retract this straw is using mechanized processing for bailing it, involving hay balers, which are imported to Brazil and their use require regularly field conditions of work. Those balers could produce square or round bales, which can be sold to energy generation. This study aims to estimate economic efficiency indicators of round and square systems for sugarcane straw, establishing a relationship between baling costs and the incoming generated from those bales. Based on data set, round baling system was 26% more efficient than square baling system, and that round baler has a lower purchase price and a higher compress ratio of biomass, allowing a greater potential for power generation, turning it a more advantageous in a possible marketing for bales produced. (C) 2014 Elsevier B.V. All rights reserved.

Photoelastic Analysis of Stress Distribution With Different Implant Systems

The aim of this study was to evaluate stress distribution with different implant systems through photoelasticity. Five models were fabricated with photoelastic resin PL-2. Each model was composed of a block of photoelastic resin (10 x 40 x 45 mm) with an implant and a healing abutment: model 1, internal hexagon implant (4.0 X 10 mm; Conect AR, Conexao, Sao Paulo, Brazil); model 2, Morse taper/internal octagon implant (4.1 x 10 mm; Standard, Straumann ITI, Andover, Mass); model 3, Morse taper implant (4.0 x 10 mm; AR Morse, Conexao); model 4, locking taper implant (4.0 x 11 mm; Bicon, Boston, Mass); model 5, external hexagon implant (4.0 x 10 mm; Master Screw, Conexao). Axial and oblique load (45) of 150 N were applied by a universal testing machine (EMIC-DL 3000), and a circular polariscope was used to visualize the stress. The results were photographed and analyzed qualitatively using Adobe Photoshop software. For the axial load, the greatest stress concentration was exhibited in the cervical and apical thirds. However, the highest number of isochromatic fringes was observed in the implant apex and in the cervical adjacent to the load direction in all models for the oblique load. Model 2 (Morse taper, internal octagon, Straumann ITI) presented the lowest stress concentration, while model 5 (external hexagon, Master Screw, Conexao) exhibited the greatest stress. It was concluded that Morse taper implants presented a more favorable stress distribution among the test groups. The external hexagon implant showed the highest stress concentration. Oblique load generated the highest stress in all models analyzed.

Influence of Nd:YAG Laser on the Bond Strength of Self-etching and Conventional Adhesive Systems to Dental Hard Tissues

Purpose: The aim of this study was to investigate the influence of Nd:YAG laser on the shear bond strength to enamel and dentin of total and self-etch adhesives when the laser was applied over the adhesives, before they were photopolymerized, in an attempt to create a new bonding layer by dentin-adhesive melting.Material and Methods: One-hundred twenty bovine incisors were ground to obtain flat surfaces. Specimens were divided into two substrate groups (n=60): substrate E (enamel) and substrate D (dentin). Each substrate group was subdivided into four groups (n=15), according to the surface treatment accomplished: X (Xeno III self-etching adhesive, control), XL (Xeno III + laser Nd:YAG irradiation at 140 mJ/10 Hz for 60 seconds + photopolymerization, experimental), S (acid etching + Single Bond conventional adhesive, Control), and SL (acid etching + Single Bond + laser Nd:YAG at 140 mJ/10 Hz for 60 seconds + photopolymerization, experimental). The bonding area was delimited with 3-mm-diameter adhesive tape for the bonding procedures. Cylinders of composite were fabricated on the bonding area using a Teflon matrix. The teeth were stored in water at 37 degrees C/48 h and submitted to shear testing at a crosshead speed of 0.5 mm/min in a universal testing machine. Results were analyzed with three-way analysis of variance (ANOVA; substrate, adhesive, and treatment) and Tukey tests (alpha=0.05). ANOVA revealed significant differences for the substrate, adhesive system, and type of treatment: lased or unlased (p<0.05). The mean shear bond strength values (MPa) for the enamel groups were X=20.2 +/- 5.61, XL=23.6 +/- 4.92, S=20.8 +/- 4.55, SL=22.1 +/- 5.14 and for the dentin groups were X=14.1 +/- 7.51, XL=22.2 +/- 6.45, S=11.2 +/- 5.77, SL=15.9 +/- 3.61. For dentin, Xeno III self-etch adhesive showed significantly higher shear bond strength compared with Single Bond total-etch adhesive; Nd:YAG laser irradiation showed significantly higher shear bond strength compared with control (unlased).Conclusion: Nd:YAG laser application prior to photopolymerization of adhesive systems significantly increased the bond strength to dentin.

First all-sky search for continuous gravitational waves from unknown sources in binary systems

We present the first results of an all-sky search for continuous gravitational waves from unknown spinning neutron stars in binary systems using LIGO and Virgo data. Using a specially developed analysis program, the TwoSpect algorithm, the search was carried out on data from the sixth LIGO science run and the second and third Virgo science runs. The search covers a range of frequencies from 20 Hz to 520 Hz, a range of orbital periods from 2 to similar to 2,254 h and a frequency-and period-dependent range of frequency modulation depths from 0.277 to 100 mHz. This corresponds to a range of projected semimajor axes of the orbit from similar to 0.6 x 10(-3) ls to similar to 6,500 ls assuming the orbit of the binary is circular. While no plausible candidate gravitational wave events survive the pipeline, upper limits are set on the analyzed data. The most sensitive 95% confidence upper limit obtained on gravitational wave strain is 2.3 x 10(-24) at 217 Hz, assuming the source waves are circularly polarized. Although this search has been optimized for circular binary orbits, the upper limits obtained remain valid for orbital eccentricities as large as 0.9. In addition, upper limits are placed on continuous gravitational wave emission from the low-mass x-ray binary Scorpius X-1 between 20 Hz and 57.25 Hz.