A comparative evaluation of open loop and closed loop drug administration strategies in the treatment of AIDS.

In recent years, many researchers in the field of biomedical sciences have made successful use of mathematical models to study, in a quantitative way, a multitude of phenomena such as those found in disease dynamics, control of physiological systems, optimization of drug therapy, economics of the preventive medicine and many other applications. The availability of good dynamic models have been providing means for simulation and design of novel control strategies in the context of biological events. This work concerns a particular model related to HIV infection dynamics which is used to allow a comparative evaluation of schemes for treatment of AIDS patients. The mathematical model adopted in this work was proposed by Nowak & Bangham, 1996 and describes the dynamics of viral concentration in terms of interaction with CD4 cells and the cytotoxic T lymphocytes, which are responsible for the defense of the organism. Two conceptually distinct techniques for drug therapy are analyzed: Open Loop Treatment, where a priori fixed dosage is prescribed and Closed Loop Treatment, where the doses are adjusted according to results obtained by laboratory analysis. Simulation results show that the Closed Loop Scheme can achieve improved quality of the treatment in terms of reduction in the viral load and quantity of administered drugs, but with the inconvenience related to the necessity of frequent and periodic laboratory analysis.

An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology

This paper describes a analog implementation of radial basis neural networks (RBNN) in BiCMOS technology. The RBNN uses a gaussian function obtained through the characteristic of the bipolar differential pair. The gaussian parameters (gain, center and width) is changed with programmable current source. Results obtained with PSPICE software is showed.

Investigations into the use of the finite element method and artificial neural networks in the non-destructive analysis of metallic tubes

This work presents an investigation into the use of the finite element method and artificial neural networks in the identification of defects in industrial plants metallic tubes, due to the aggressive actions of the fluids contained by them, and/or atmospheric agents. The methodology used in this study consists of simulating a very large number of defects in a metallic tube, using the finite element method. Both variations in width and height of the defects are considered. Then, the obtained results are used to generate a set of vectors for the training of a perceptron multilayer artificial neural network. Finally, the obtained neural network is used to classify a group of new defects, simulated by the finite element method, but that do not belong to the original dataset. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

Prototipagem como forma alternativa para realização de cranioplastia com metilmetacrilato: Nota técnica

The prototyping is a method for reconstruction of human body segments by computer software. It has been used in neurosurgery for cranial reproduction in patients allowing the programming of surgical procedures and the production of prosthesis to reconstruct bone failures in the skull. We present two cases of cranioplasty performed with the use of acrylic prosthesis constructed by prototyping. After 10 months of follow-up, they donot present signs of infection and show good aesthetic result. The advantages pointed at the literature for this method (reduction of surgical time, easy technical handle, and good aesthetic result) were confirmed.

Frequency-adjustable positive sequence detector for power conditioning applications

This paper proposes a novel and simple positive sequence detector (PSD), which is inherently self-adjustable to fundamental frequency deviations by means of a software-based PLL (Phase Locked Loop). Since the proposed positive sequence detector is not based on Fortescue's classical decomposition and no special input filtering is needed, its dynamic response may be as fast as one fundamental cycle. The digital PLL ensures that the positive sequence components can be calculated even under distorted waveform conditions and fundamental frequency deviations. For the purpose of validating the proposed models, the positive sequence detector has been implemented in a PC-based Power Quality Monitor and experimental results illustrate its good performance. The PSD algorithm has also been evaluated in the control loop of a Series Active Filter and simulation results demonstrate its effectiveness in a closed-loop system. Moreover, considering single-phase applications, this paper also proposes a general single-phase PLL and a Fundamental Wave Detector (FWD) immune to frequency variations and waveform distortions. © 2005 IEEE.

Scalable distributed virtual environments using multicast application level

Most of architectures proposed for developing Distributed Virtual Environment (DVE) allow limited number of users. To support the development of applications using the internet infrastructure, with hundred or, perhaps, thousands users logged simultaneously on DVE, several techniques for managing resources, such as bandwidth and capability of processing, must be implemented. The strategy presented in this paper combines methods to attain the scalability required, In special the multicast protocol at application level.

Automatic system for thermal damage detection in manufacturing process with Internet monitoring

This work involved the development of a smart system dedicated to surface burning detection in the grinding process through constant monitoring of the process by acoustic emission and electrical power signals. A program in Visual Basic® for Windows® was developed, which collects the signals through an analog-digital converter and further processes them using burning detection algorithms already known. Three other parameters are proposed here and a comparative study carried out. When burning occurs, the newly developed software program sends a control signal warning the operator or interrupting the process, and delivers process information via the Internet. Parallel to this, the user can also interfere in the process via Internet, changing parameters and/or monitoring the grinding process. The findings of a comparative study of the various parameters are also discussed here. Copyright © 2006 by ABCM.

Digital monitoring of broiler breeder behavior for assessment of thermal welfare

The assessment of welfare issues has been a challenge for poultry producers, and lately welfare standards needs to be reached in order to agree with international market demand. This research proposes the use of continuous behavior monitoring in order to contribute for assessing welfare. A software was developed using the language Clarium. The software managed the recording of data as well as the data searching in the database Firebird. Both software and the observational methodology were tested in a trial conducted inside an environmental chamber, using three genetics of broiler breeders. Behavioral pattern was recorded and correlated to ambient thermal and aerial variation. Monitoring video cameras were placed on the roof facing the used for registering the bird's behavior. From video camera images were recorded during the total period when the ambient was bright, and for analyzing the video images a sample of 15min observation in the morning and 15 min in the afternoon was used, adding up to 30 min daily observation. A specific model so-called behavior was developed inside the software for counting specific behavior and its frequency of occurrence, as well as its duration. Electronic identification was recorded for 24h period. Behavioral video recording images was related to the data recorded using electronic identification.. Statistical analysis of data allowed to identify behavioral differences related to the change in thermal environment, and ultimately indicating thermal stress and departure from welfare conditions.

Influence of the facial pattern on ANB, AF-BF, and Wits appraisal.

AIM: To assess the correlation between Wits and AF-BF appraisals with the ANB angle, and verify the influence of the facial type on these appraisals. METHODS: Lateral cephalometric radiographs from 118 untreated individuals were separated into 3 groups according to the facial pattern (brachyfacial, mesofacial, and dolichofacial). The radiographs were digitized and submitted to ANB angle and Wits and AF-BF appraisals on computer software. All radiographs were retraced for intraobserver and interobserver error tests. RESULTS: The Student's t test demonstrated no statistically significant differences on the intraobserver's test (P > .05). There were statistically significant differences in the readings of Wits values of the 3 groups and for AF-BF values in the brachyfacial and mesofacial groups (P <.05). The multiple linear regression tests demonstrated high correlation between ANB and AF-BF for the 3 groups (r2, 0.768). The same result was found for ANB and Wits (r2, 0.624). CONCLUSION: Facial pattern does not have an influence on the correlation between ANB and AF-BF nor between ANB and Wits, but it does influence the measurements of ANB, AF-BF, and Wits.

A development process proposal for the ERP5 system

Modeling ERP software means capturing the information necessary for supporting enterprise management. This modeling process goes down through different abstraction layers, from enterprise modeling to code generation. Thus ERP is the kind of system where enterprise engineering undoubtedly has, or should have, a strong influence. For the case of Free/Open Source ERP, the lack of proper modeling methods and tools can jeopardize the advantage brought by source code availability. Therefore, the aim of this paper is to present a development process proposal for the Open Source ERP5 system. The proposed development process aims to cover different abstraction levels, taking into account well established standards and common practices, as well as platform issues. Its main goal is to provide an adaptable meta-process to ERP5 adopters. © 2006 IEEE.

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.

A genetic neuro-model reference adaptive controller for petroleum wells drilling operations

Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.

Modelagem numérica da superfície na geração da planialtimetra segundo dados de quatro equipamentos topogríficos

The aim of this present work was to compare planialtimetric charts obtained from different risings using two different theodolite types, a total station, and a precision level, used as control. Using a total station, an area was marked with clear variations of relief, following a grid, with a distance of 20 meters among stakes. After that, the stakes were read by the total station and two theodolites of different precisions. The geometric leveling was done by a precision level. The data were input in the DataGeosis software and the numerical modelling of the land was made with mesh of maximum rigidity, generating planialtimetric representation for each rising. It was verified, through comparison of the four representations that little variations occur in relation to the control. The closest representation of the control was the planialtimetry based on the data from the total station, in which the representations obtained from the theodolites were identical among themselves. It was concluded that in the process of obtaining detailed planialtimetry of small areas, submitted to the grid, it was not necessary to use composed geometric leveling, reducing work to the exclusive use of a total station or conventional theodolite.

Implantação do pilar ruju Botucatu na UNESP para integração ao Sistema Geodésico Brasileiro

The objective of this work was to implant a geodesic pillar in the campus of Botucatu (Rubião Júnior) of the São Paulo State University (UNESP), using active stations of the Brazilian Net of Continuous Monitoring (RBMC) as reference, aiming at inclusion in the Brazilian Geodesic System (BGS). In the planning of the trace, some aspects of the pillar optimization were considered: the field evaluation, the equipment Receiver GPS Topcon Hiper GGD and the net RBMC were used to trace the height, and the Topcon Tools 6.04 version software was use for the data processing, the ambiguity solution, as well as the treatment of injunctions during the column adjustment. The obtained results allowed the implantation of a more accurate pillar then 1ppm compatible to the RBMC net, meeting the specification of IBGE.

Implementation of filters for image pre-processing for leaf analyses in plantations

In this work an image pre-processing module has been developed to extract quantitative information from plantation images with various degrees of infestation. Four filters comprise this module: the first one acts on smoothness of the image, the second one removes image background enhancing plants leaves, the third filter removes isolated dots not removed by the previous filter, and the fourth one is used to highlight leaves' edges. At first the filters were tested with MATLAB, for a quick visual feedback of the filters' behavior. Then the filters were implemented in the C programming language. At last, the module as been coded in VHDL for the implementation on a Stratix II family FPGA. Tests were run and the results are shown in this paper. © 2008 Springer-Verlag Berlin Heidelberg.