An environment for knowledge discovery in biology

This paper describes a data mining environment for knowledge discovery in bioinformatics applications. The system has a generic kernel that implements the mining functions to be applied to input primary databases, with a warehouse architecture, of biomedical information. Both supervised and unsupervised classification can be implemented within the kernel and applied to data extracted from the primary database, with the results being suitably stored in a complex object database for knowledge discovery. The kernel also includes a specific high-performance library that allows designing and applying the mining functions in parallel machines. The experimental results obtained by the application of the kernel functions are reported. © 2003 Elsevier Ltd. All rights reserved.

On the specific filtration mechanism of a mesoporous silica membrane, prepared with non-connecting parallel pores

We report the singular filtration properties of an ultrafiltration membrane made with mesoporous silica that exhibits cylindrical pores aligned mostly normal to the support. This membrane supported on tubular commercial macroporous alumina supports was prepared by the interfacial growth mechanism between stable silica-surfactant hybrid micelles made of the association of silica oligomers with polyethyleneoxide-based (PEO) surfactants and sodium fluoride, a well-known silica condensation catalyst [Boissière et al., An ultrafiltration membrane made with mesoporous MSU-X silica, Chem. Mater. 15 (2003) 460-463]. It appears that the combined effect of the silica nature of the membrane, whose surface charge can be easily adjusted by changing the pH and the non-connected cylindrical shape of the pores provides a new behavior in the retention properties, as proved by the filtration of polyoxyethylene polymers (PEO) with different molecular weights. Depending on the filtration conditions, a rejection rate of 80% and a steep cut-off at 2000 Da can be obtained or, on the reverse, polymers three times bigger than the pore diameter can diffuse through the membrane. This new filtration mechanism, which opens up new modes of separation modes, is explained in the light of both topology of the porous network and pH-dependent interactions between PEO polymers and silica porous media. © 2004 Elsevier B.V. All rights reserved.

Eigenvalue analyses of two parallel lines using a single real transformation matrix

For a typical non-symmetrical system with two parallel three phase transmission lines, modal transformation is applied using some examples of single real transformation matrices. These examples are applied searching an adequate single real transformation matrix to two parallel three phase transmission line systems. The analyses are started with the eigenvector and eigenvalue studies, using Clarke's transformation or linear combinations of Clarke's elements. The Z C and parameters are analyzed for the case that presents the smallest errors between the exact eigenvalues and the single real transformation matrix application results. The single real transformation determined for this case is based on Clarke's matrix and its main characteristic is the use of a unique homopolar reference. So, the homopolar mode becomes a connector mode between the two three-phase circuits of the analyzed system. ©2005 IEEE.

Effect of dentinal surface preparation on bond strength of self-etching adhesive systems

The aim of this study was to evaluate the effects of dentin surface treatments on the tensile bond strength (TBS) of the self-etching primer Clearfil SE Bond (CSE) and the one-step self-etching One-Up Bond F (OUB). The exposed flat dentin surfaces of twenty-four sound third molars were prepared with diamond bur at high-speed, carbide bur at low-speed or wet ground with #600 grit SiC paper. The adhesive systems were applied to the dentin surfaces and light-cured according to the manufacturers' instructions. A 6-mm high composite crown was incrementally built-up and each increment was light-cured for 40 seconds. After being stored in water (37°C/24 h), the samples were serially sectioned parallel to the long axis, forming beams (n = 20) with a cross-sectional area of approximately 0.8 mm 2. The specimens were tested in a Universal Testing Machine at 0.5 mm/min. The cross-sectional area was measured and the results (MPa) were analyzed by two-way ANOVA and Tukey Test (p < 0.05). Overall, the groups treated with CSE exhibited the highest TBS for all surface treatments. Dentin surfaces prepared with carbide bur at low speed reduced TBS in the CSE group; however, OUB was not affected by surface treatments. The effect of surface abrasive methods on TBS was material-dependent.

Life with a hemodialysis machine

The aim of the present study was to describe the experience of patients undergoing haemodialysis starting from their own perception. A qualitative perspective using Merleau Ponty's Existential Phenomenology was considered to be the most appropriate methodology for this study. Fifteen patients were interviewed in a haemodialysis unit at a Brazilian teaching hospital. Interviews were based on the question 'What does the experience of living with a haemodialysis machine mean?' Convergences in speeches were grouped into three categories: the machine, improvement in quality of life, reflection on patients' experience. These findings show the existential reality patients experience. A haemodialysis machine dictates their lives: they have to accept strict rules controlled by a team of healthcare providers. They realize it has to be so and there is no way out. It is the only way to get some relief from the symptoms of the disease. The feeling is mostly acceptance of the condition. Healthcare providers' dedication is recognized. Some participants complain bout painful procedures, others deny them, others fantasize the reality. An essential piece of information is the lack of future perspectives; few patients mentioned the possibility of a transplant or the possibility of carrying out their own care. The study may contribute in outlining new perspectives for nurses to understand the needs of patients undergoing haemodialysis. An approach accepting patients' views will probably bring awareness to patients as to the possibilities of helping with their own treatment.

Classification of petroleum well drilling operations using Support Vector Machine (SVM)

During the petroleum well drilling operation many mechanical and hydraulic parameters are monitored by an instrumentation system installed in the rig called a mud-logging system. These sensors, distributed in the rig, monitor different operation parameters such as weight on the hook and drillstring rotation. These measurements are known as mud-logging records and allow the online following of all the drilling process with well monitoring purposes. However, in most of the cases, these data are stored without taking advantage of all their potential. On the other hand, to make use of the mud-logging data, an analysis and interpretationt is required. That is not an easy task because of the large volume of information involved. This paper presents a Support Vector Machine (SVM) used to automatically classify the drilling operation stages through the analysis of some mud-logging parameters. In order to validate the results of SVM technique, it was compared to a classification elaborated by a Petroleum Engineering expert. © 2006 IEEE.

Estimation of electrical machine speed using sensorless technology and neural networks

The use of sensorless technologies is an increasing tendency on industrial drivers for electrical machines. The estimation of electrical and mechanical parameters involved with the electrical machine control is used very frequently in order to avoid measurement of all variables related to this process. The cost reduction may also be considered in industrial drivers, besides the increasing robustness of the system, as an advantage of the use of sensorless technologies. This work proposes the use of a recurrent artificial neural network to estimate the speed of induction motor for sensorless control schemes using one single current sensor. Simulation and experimental results are presented to validate the proposed approach. ©2008 IEEE.

Analysis of electric torque in single machine-infinite bus system using phase shifters

ResumoThe main idea of this work is based on the analysis of the electric torque through the acting of the PS in the power system, provided of a control for the compensation degree (PSC). A linear model of the single machine-infinite bus system is used with a PS installed (SMIB/PS system). The variable that represents the presence of PS in the net is associated to the phase displacement introduced in the terminal voltage of the synchronous machine by PS. For the input signals of the PSC are evaluated variations of the angular speed of the rotor, the current magnitude and the active power through the line where the PS is located. The simulations are accomplished to analyze the influence of the PS in the torque formation (synchronizing and damping), of the SMIB/PS system. The analysis are developed in the time and frequency domain.

Evaluation of a new intraoral paralleling device for creating guiding planes: A pilot study

Aim: The aim of the study was to assess the accuracy of a new intraoral paralleling device for creating proximal guiding planes for removable partial dental prostheses. Methods and Materials: Thirty gypsum casts were divided into two groups in which the proximal surfaces of selected teeth were prepared using either a surveying device (Group 1) or the new ParalAB paralleling device (Group 2). In each cast guiding planes were prepared on the distal surface of the maxillary left canine (A), on the mesial and distal surfaces of the maxillary left second molar (B and C), and on the distal surface of the maxillary right canine (D). Each prepared surface formed an angle related to the occlusal plane that was measured five times and averaged by one operator using a tridimensional coordinate machine. Results: The mean guiding plane angles (± standard deviation) for the prepared surfaces were A=91.82° (±0.48°, B=90.47° (±0.47°, C=90.21° (±0.76°, and D=90.50° (±0.73°) for the dental surveyor (Group 1) and A=92.18° (±0.87°), B=90.90° (±0.85°), C=90.07° (±0.92°), and D=90.66° (±0.76°) for the ParalAB paralleling device (Group 2). A two-way ANOVA, Tukey's, and Levène's tests (at p<0.05) revealed statistically significant differences among surfaces prepared by both groups and that one surface Conclusions: The ParalAB device was able to prepare parallel surfaces and despite significant difference between groups, the ParalAB presented a small deviation from absolute parallelism and can be considered a valid method to transfer guide plans in the fabrication of removable partial dentures. Clinical Significance: The preparation of suitable guiding planes on abutment teeth during the fabrication of removable partial dentures is dependent on the ability of the operator and requires considerable chair time. When multiple teeth are involved, achieving parallelism between abutment surfaces can be technically challenging, especially in posterior regions of the mouth. The ParalAB prototype intraoral paralleling device can aid the clinician during the preparation of accurate guiding planes with a minimum degree of occlusal divergence. © 2010 Seer Publishing LLC.

Optimized dynamic response of parallel operation of two single phase inverters based on evolutionary theory

In this work it is proposed an optimized dynamic response of parallel operation of two single-phase inverters with no control communication. The optimization aims the tuning of the slopes of P-ω and Q-V curves so that the system is stable, damped and minimum settling time. The slopes are tuned using an algorithm based on evolutionary theory. Simulation and experimental results are presented to prove the feasibility of the proposed approach. © 2010 IEEE.

Precipitates segmentation from scanning electron microscope images through machine learning techniques

The presence of precipitates in metallic materials affects its durability, resistance and mechanical properties. Hence, its automatic identification by image processing and machine learning techniques may lead to reliable and efficient assessments on the materials. In this paper, we introduce four widely used supervised pattern recognition techniques to accomplish metallic precipitates segmentation in scanning electron microscope images from dissimilar welding on a Hastelloy C-276 alloy: Support Vector Machines, Optimum-Path Forest, Self Organizing Maps and a Bayesian classifier. Experimental results demonstrated that all classifiers achieved similar recognition rates with good results validated by an expert in metallographic image analysis. © 2011 Springer-Verlag Berlin Heidelberg.

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.