Fault identification in distribution lines using intelligent systems and statistical methods

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder. © 2006 IEEE.

Microbial distribution in the root canal system after periapical lesion induction using different methods

The aim of this study was to evaluate the microbial distribution in the root canal system after periapical lesion induction in dogs' teeth using different methods. Fifty-two root canals were assigned to 4 groups (n=13). Groups I and II: root canals were exposed to the oral cavity for 180 days; groups III and IV: root canals were exposed for 7 days and then the coronal openings were sealed for 53 days. The root apices of groups I and III were perforated, while those of groups II and IV remained intact. After the experimental periods, the animals were euthanized and the anatomic pieces containing the roots were processed and stained with the Brown & Brenn method to assess the presence and distribution of microorganisms. The incidence of microorganisms at different sites of the roots and periapical lesions was analyzed statistically by the chi-square test at 5% significance level. All groups presented microorganisms in the entire root canal system. A larger number of microorganisms was observed on the root canal walls, apical delta and dentinal tubules (p<0.05), followed by cementum and cemental resorption areas. In spite of the different periods of exposure to the oral environment, the methods used for induction of periapical periodontitis yielded similar distribution of microorganisms in the root canal system.

Short-term multinodal load forecasting in distribution systems using general regression neural networks

Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, trustable and has a short-time processing. This paper proposes two methodologies based on general regression neural networks for short-term multinodal load forecasting. The first individually forecast the local loads and the second forecast the global load and individually forecast the load participation factors to estimate the local loads. To design the forecasters it wasn't necessary the previous study of the local loads. Tests were made using a New Zealand distribution subsystem and the results obtained are compatible with the ones founded in the specialized literature. © 2011 IEEE.

Influence of microthreads and platform switching on stress distribution in bone using angled abutments

Purpose: To evaluate the stress distribution in peri-implant bone by simulating the effect of an implant with microthreads and platform switching on angled abutments through tridimensional finite element analysis. The postulated hypothesis was that the presence of microthreads and platform switching would reduce the stress concentration in the cortical bone. Methods: Four mathematical models of a central incisor supported by an implant (5.0mm×13mm) were created in which the type of thread surface in the neck portion (microthreaded or smooth) and the diameter of the angled abutment connection (5.0 and 4.1mm) were varied. These models included the RM (regular platform and microthreads), the RS (regular platform and smooth neck surface), the SM (platform switching and microthreads), and the SS (platform switching and smooth neck). The analysis was performed using ANSYS Workbench 10.0 (Swanson Analysis System). An oblique load (100N) was applied to the palatine surface of the central incisor. The bone/implant interface was considered to be perfectly integrated. Values for the maximum (σmax) and minimum (σmin) principal stress, the equivalent von Mises stress (σvM), and the maximum principal elastic strain (e{open}max) for cortical and trabecular bone were obtained. Results: For the cortical bone, the highest σmax (MPa) were observed for the RM (55.1), the RS (51.0), the SM (49.5), and the SS (44.8) models. The highest σvM (MPa) were found for the RM (45.4), the SM (42.1), the RS (38.7), and the SS models (37). The highest values for σmin were found for the RM, SM, RS and SS models. For the trabecular bone, the highest σmax values (MPa) were observed in the RS model (6.55), followed by the RM (6.37), SS (5.6), and SM (5.2) models. Conclusion: The hypothesis that the presence of microthreads and a switching platform would reduce the stress concentration in the cortical bone was partially rejected, mainly because the microthreads increased the stress concentration in cortical bone. Only platform switching reduced the stress in cortical bone. © 2012 Japan Prosthodontic Society.

Stress distribution in implant-supported prosthesis with external and internal implant-abutment connections

Objective. This study aimed to investigate the stress distribution in screwed implant-supported prostheses with different implant-abutment connections by using a photoelastic analysis. Materials and methods. Four photoelastic models were fabricated in PL-2 resin and divided according to the implant-abutment connection (external hexagon (EH) and Morse taper (MT) implants (3.75 × 11.5 mm)) and the number crowns (single and 3-unit piece). Models were positioned in a circular polariscope and 100-N axial and oblique (45) loading were applied in the occlusal surface of the crowns by using a universal testing machine. The stresses were photographically recorded and qualitatively analyzed using software (Adobe Photoshop). Results. Under axial loading, the MT implants exhibited a lower number of fringes for single-unit crowns than EH implants, whereas for a 3-unit piece the MT implants showed a higher number of fringes vs EH implants. The oblique loading increased the number of fringes for all groups. Conclusion. In conclusion, the MT implant-abutment connection reduced the amount of stress in single-unit crowns, for 3-unit piece crowns the amount of stress was lower using an external hexagon connection. The stress pattern was similar for all groups. Oblique loading promoted a higher stress concentration than axial loading. © Informa Healthcare.

Searches for new physics using the t(t)over-bar invariant mass distribution in pp collisions at root s=8 TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Disturbance detection for optimal database storage in electrical distribution systems using artificial immune systems with negative selection

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

Estimation of Submerged Aquatic Vegetation Height and Distribution in Nova Avanhandava Reservoir (São Paulo State, Brazil) Using Bio-Optical Modeling

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Stress distribution in delayed replanted teeth splinted with different orthodontic wires: a three-dimensional finite element analysis

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

The influence of the alveolar ridge shape on the stress distribution in a free-end saddle removable partial denture supported by implant

The alveolar ridge shape plays an important role in predicting the demand on the support tooth and alveolar bone in the removable partial denture (RPD) treatment. However, these data are unclear when the RPD is associated with implants. This study evaluated the influence of the alveolar ridge shape on the stress distribution of a free-end saddle RPD partially supported by implant using 2-dimensioanl finite element analysis (FEA). Four mathematical models (M) of a mandibular hemiarch simulating various alveolar ridge shapes (1-distal desceding, 2- concave, 3-horizontal and 4-distal ascending) were built. Tooth 33 was placed as the abutment. Two RPDs, one supported by tooth and fibromucosa (MB) and other one supported by tooth and implant (MC) were simulated. MA was the control (no RPD). The load (50N) were applied simultaneously on each cusp. Appropriate boundary conditions were assigned on the border of alveolar bone. Ansys 10.0 software was used to calculate the stress fields and the von Mises equivalent stress criteria (σvM) was applied to analyze the results. The distal ascending shape showed the highest σvM for cortical and medullar bone. The alveolar ridge shape had little effect on changing the σvM based on the same prosthesis, mainly around the abutment tooth.

Estimation of deposit and spray distribution in hydro sensible paper and morning glory plant

Herbicides application success depends, besides product correct choice, the observation of environmental conditions and application quality. The work aimed to quantify the effects of surfactant addition in spraying solution, in natural and artificial targets, associated to different nozzle boom angles in relation to application offset, by using distinct evaluation methods. Two experiments were conducted at NuPAM-FCA/UNESP, Botucatu County, São Paulo State, constituted by ten treatments, in factorial scheme 2 × 5, corresponding to two spraying solutions conditions (absence or presence of Aterbane BRTM (0.25% v/v) adjuvant) and five angles of spray nozzle in relation to offset application (-30°, -15°, 90°, +15° and +30°). In Ipomea grandifolia leaves, the distribution and drops deposition of a tracer solution were evaluated by using scores visual and spectrophotometer process. In hydro sensible papers, volumetric medium diameter (VMD), density (cm2 ) and drops medium diameter, covered area (%) and application fees (L ha-1) were evaluated through e-SprinkleTM software. Aterbane BRTM (0.25% v/v) presence or absence, associated or no, to spray nozzles offset did not provide significant differences in I. grandifolia spray deposition. The use of artificial targets presented applicative technical limitations in relation to the use of natural ones as study matrix. Deposit and distribution variables esteem distinct behaviours, independent of target nature.

Efficient Placement of Fault Indicators in an Actual Distribution System Using Evolutionary Computing

This paper proposes an evolutionary computing strategy to solve the problem of fault indicator (FI) placement in primary distribution feeders. More specifically, a genetic algorithm (GA) is employed to search for an efficient configuration of FIs, located at the best positions on the main feeder of a real-life distribution system. Thus, the problem is modeled as one of optimization, aimed at improving the distribution reliability indices, while, at the same time, finding the least expensive solution. Based on actual data, the results confirm the efficiency of the GA approach to the FI placement problem.

Estimating the monthly pCO2 distribution in the North Atlantic using a self-organizing neural network

[EN] Here we present monthly, basin-wide maps of the partial pressure of carbon dioxide (pCO2) for the North Atlantic on a latitude by longitude grid for years 2004 through 2006 inclusive. The maps have been computed using a neural network technique which reconstructs the non-linear relationships between three biogeochemical parameters and marine pCO2. A self organizing map (SOM) neural network has been trained using 389 000 triplets of the SeaWiFSMODIS chlorophyll-a concentration, the NCEP/NCAR reanalysis sea surface temperature, and the FOAM mixed layer depth. The trained SOM was labelled with 137 000 underway pCO2 measurements collected in situ during 2004, 2005 and 2006 in the North Atlantic, spanning the range of 208 to 437atm. The root mean square error (RMSE) of the neural network fit to the data is 11.6?atm, which equals to just above 3 per cent of an average pCO2 value in the in situ dataset. The seasonal pCO2 cycle as well as estimates of the interannual variability in the major biogeochemical provinces are presented and discussed. High resolution combined with basin-wide coverage makes the maps a useful tool for several applications such as the monitoring of basin-wide air-sea CO2 fluxes or improvement of seasonal and interannual marine CO2 cycles in future model predictions. The method itself is a valuable alternative to traditional statistical modelling techniques used in geosciences.

Parallel modeling of the electric field distribution in the brain

The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.