A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements

The accurate identification of the nitrogen content in plants is extremely important since it involves economic aspects and environmental impacts, Several experimental tests have been carried out to obtain characteristics and parameters associated with the health of plants and its growing. The nitrogen content identification in plants involves a lot of non-linear parameters and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought SPAD index using artificial neural networks (ANN). The network acts as identifier of relationships among, crop varieties, fertilizer treatments, type of leaf and nitrogen content in the plants (target). So, nitrogen content can be generalized and estimated and from an input parameter set. This approach can form the basis for development of an accurate real time system to predict nitrogen content in plants.

Influence of the type of vehicle and limit of obturation on apical and periapical tissue response in dogs' teeth after root canal filling with mineral trioxide aggregate

The purpose of this study was to investigate the influence of the type of vehicle (distilled water or propyleneglycol) on the response of apical tissues of dogs' teeth after root canal filling with mineral trioxide aggregate (MTA) at two different limits. Forty roots of incisors and premolars of two adult dogs were used. After pulpectomy, the root canals were prepared biomechanically, and the roots had the apical cemental barrier penetrated with a #15 K-file and widened to a #25 K-file. The root canals were assigned to four groups according to the vehicle used for MTA (ProRoot-MTA; Tulsa Dental, Tulsa, OK) preparation and the limit of root canal filling: group 1, filling with MTA/distilled water to the limit of the cemental canal; group 2, overfilling with MTA/distilled water, group 3, filling with MTA/propyleneglycol to the limit of the cemental canal; and group 4, overfilling with MTAlpropyleneglycol. The animals were killed by anesthetic overdose 90 days after endodontic treatment and the anatomic pieces were prepared for histomorphological analysis. The sections were stained with hematoxylin and eosin and Brown and Brenn techniques. The results showed that MTA pastes prepared with either distilled water or propyleneglycol as vehicles had similar biological behavior (p > 0.05); root fillings placed at the cemental canal limit showed better results than the overfillings (p = 0.01), and MTA/propyleneglycol paste was more easily placed into the root canals than MTA/distilled water paste.

Design of a reconfigurable pseudorandom number generator for use in intelligent systems

This paper deals with the design of a network-on-chip reconfigurable pseudorandom number generation unit that can map and execute meta-heuristic algorithms in hardware. The unit can be configured to implement one of the following five linear generator algorithms: a multiplicative congruential, a mixed congruential, a standard multiple recursive, a mixed multiple recursive, and a multiply-with-carry. The generation unit can be used both as a pseudorandom and a message passing-based server, which is able to produce pseudorandom numbers on demand, sending them to the network-on-chip blocks that originate the service request. The generator architecture has been mapped to a field programmable gate array, and showed that millions of numbers in 32-, 64-, 96-, or 128-bit formats can be produced in tens of milliseconds. (C) 2011 Elsevier B.V. All rights reserved.

Influences of the load centre of gravity on heavy vehicle acceleration

The aim of this paper is to analyse the influence of the load centre of gravity on heavy vehicle acceleration. This analysis is done through a method in which a vehicle centre of gravity map is used. A model for the driving force is presented for bus, truck and tractor-semi trailer combinations. The proposed model takes into consideration the resistance forces (drag, rolling resistance, translation and rotation acceleration, climbing resistance) and the 4 X 2 traction system. The positions of the vehicle centre of gravity as a function of the position of the load centre of gravity are determined. The vehicle acceleration is calculated based on the position of the load centre of gravity. This study analyses the acceleration of one of the Mercedes-Benz do Brasil tractor-semitrailer vehicle. A comparison of the acceleration for different maximum adhesion coefficients and ramps are presented, showing new results. An example showing the variations of the load centre of gravity position with the acceleration time and distance is provided. The load centre of gravity position is important for vehicle safety and the efficiency and economy in the transportation of the load.

Reducing the gap between mobile and intelligent software agents

This paper presents an approach to integrate an artificial intelligence (AI) technique, concretely rule-based processing, into mobile agents. In particular, it focuses on the aspects of designing and implementing an appropriate inference engine of small size to reduce migration costs. The main goal is combine two lines of agent research, First, the engineering oriented approach on mobile agent architectures, and, second, the AI related approach on inference engines driven by rules expressed in a restricted subset of first-order predicate logic (FOPL). In addition to size reduction, the main functions of this type of engine were isolated, generalized and implemented as dynamic components, making possible not only their migration with the agent, but also their dynamic migration and loading on demand. A set of classes for representing and exchanging knowledge between rule-based systems was also proposed.

An intelligent system for pavement management

This paper describes a method for the evaluation of pavement condition through artificial neural networks using the MLP backpropagation technique. Two of the most used procedures for detecting the pavement conditions were applied: the overall severity index and the irregularity index. Tests with the model demonstrated that the simulation with the neural network gives better results than the procedures recommended by the highway officials. This network may also be applied for the construction of a graphic computer environment.

Technique for application of hi-bright LED in automobile industry through intelligent systems

The advantages offered by the electronic component LED (Light Emitting Diode) have caused a quick and wide application of this device in replacement of incandescent lights. However, in its combined application, the relationship between the design variables and the desired effect or result is very complex and it becomes difficult to model by conventional techniques. This work consists of the development of a technique, through artificial neural networks, to make possible to obtain the luminous intensity values of brake lights using LEDs from design data.

An intelligent system to real time rainfall prediction using radar data

This work presents a new approach for rainfall measurements making use of weather radar data for real time application to the radar systems operated by institute of Meteorological Research (IPMET) - UNESP - Bauru - SP-Brazil. Several real time adjustment techniques has been presented being most of them based on surface rain-gauge network. However, some of these methods do not regard the effect of the integration area, time integration and distance rainfall-radar. In this paper, artificial neural networks have been applied for generate a radar reflectivity-rain relationships which regard all effects described above. To evaluate prediction procedure, cross validation was performed using data from IPMET weather Doppler radar and rain-gauge network under the radar umbrella. The preliminary results were acceptable for rainfalls prediction. The small errors observed result from the spatial density and the time resolution of the rain-gauges networks used to calibrate the radar.

Development of intelligent systems for well drilling and petroleum production

Domains where knowledge representation is too complex to be described analytically and in a deterministic way is very common in the petroleum industry, particularly in the field of exploration and production. In these domains, applications of artificial intelligence techniques are very suitable, especially in cases where the preservation of corporate and technical knowledge is important. The Laboratory for Research on Artificial Intelligence Applied to Petroleum Engineering (LIAP) at Unicamp, has, during the last 10 years, dedicated research efforts to build intelligent systems in well drilling and petroleum production fields. In the following sections, recent advances in intelligent systems, under development in the research laboratory, are described. (C) 2001 Published by Elsevier B.V. B.V.

Vehicle influence on calcium hydroxide pastes diffusion in human and bovine teeth

The purpose of this study was to compare the pH and calcium ion liberation after use of calcium hydroxide pastes with different paste vehicles in human or bovine teeth. Ninety-two single-rooted human and bovine roots were used. The roots were instrumented and an external cavity preparation was performed. The roots were divided in to human and bovine groups. Each group was subdivided into four subgroups (SB) according to the vehicle:SB1, detergent; SB2, saline; SB3, polyethylenoglycol + camphorated paramonochlorophenol (Calen PMCC) and SB4, polyethylenoglycol + furacyn paramonochlorophenol (FPMC). Specimens were immersed into saline solution at 37 degrees C and after 7 and 14 days pH and calcium ion measurements were made. The results were analyzed by ANOVA and Tukey tests (P < 0.05). There was no statistical difference between bovine and human teeth in the pH analysis (P < 0.05), but bovine teeth provided larger calcium ion liberation than human teeth. Calen PMCC was statistically more effective for pH increase and calcium ion liberation in all analyses, followed by FPMC and saline. Detergent showed the lowest pH alterations and calcium ion liberation. The period of 14 days showed more calcium ionic liberation than the 7-day period.

H-2 and H-infinity - norm control of intelligent structures using LMI techniques

Linear Matrix Inequalities (LMIs) is a powerful too] that has been used in many areas ranging from control engineering to system identification and structural design. There are many factors that make LMI appealing. One is the fact that a lot of design specifications and constrains can be formulated as LMIs [1]. Once formulated in terms of LMIs a problem can be solved efficiently by convex optimization algorithms. The basic idea of the LMI method is to formulate a given problem as an optimization problem with linear objective function and linear matrix inequalities constrains. An intelligent structure involves distributed sensors and actuators and a control law to apply localized actions, in order to minimize or reduce the response at selected conditions. The objective of this work is to implement techniques of control based on LMIs applied to smart structures.

Urban Traffic Control and Monitoring - An Approach for the Brazilian Intelligent Cities Project

This paper describes an urban traffic control system which aims at contributing to a more efficient traffic management system in the cities of Brazil. It uses fuzzy sets, case-based reasoning, and genetic algorithms to handle dynamic and unpredictable traffic scenarios, as well as uncertain, incomplete, and inconsistent information. The system is composed by one supervisor and several controller agents, which cooperate with each other to improve the system's results through Artificial Intelligence Techniques.

Towards an intelligent graphical interface for linear programming modelling

The increase of computing power of the microcomputers has stimulated the building of direct manipulation interfaces that allow graphical representation of Linear Programming (LP) models. This work discusses the components of such a graphical interface as the basis for a system to assist users in the process of formulating LP problems. In essence, this work proposes a methodology which considers the modelling task as divided into three stages which are specification of the Data Model, the Conceptual Model and the LP Model. The necessity for using Artificial Intelligence techniques in the problem conceptualisation and to help the model formulation task is illustrated.