Abstract
Recent developed button heat pulse probes (BHPP) demonstrated a great potential for soil water content measurements. This new probe compared to conventional heat pulse probes (HPP), does not use needles, and measurement accuracy is significantly improved. This new design, with the possibility to assembly the probe and electronics in the same package, with low-cost, and with less power consumption compared to conventional HPP, make it suitable to be connected to wireless data acquisition systems in precision agriculture. The probe was tested in agar to demonstrate the potential advantages of the button heat pulse sensor for soil water content measurements. It was possible to have an 0.5 °C temperature rise with only 156mW of power consumption, a ten times power reduction in heat-pulse soil water content measurements. These tests showed the potential use of the button heat pulse sensor for the determination of soil water content. © 2010 IEEE.

Abstract
In this paper we present a software tool to be used in residential/household generic power circuitry analysis and simulation, under non-linear loads. This tool can both be used by electrical engineers and by students of electrical engineering. It has an easy-to-use, friendly interface, and can be used to teach design techniques or as a laboratory tool to study the applicability of known methods to real world practical situations. Also, the users may supply their own data. The simulated results are very close to the measured ones.

Abstract
The main aim of this paper is to analyze the behavior of the three-phase squirrel cage induction motor under different voltage fluctuation levels. To achieve this goal several simulations were performed using the EMTP/ATP tool. Here we present how mechanical torque, speed and efficiency parameters varied with different levels of voltage fluctuation and modeling frequencies. As it was expected, the induction motor is sensitive to voltage fluctuations within certain amplitude levels and frequencies. Also, the speed is more affected by low frequencies and high amplitudes of voltage fluctuations, while the torque and efficiency are more affected by middle and high frequencies and amplitudes. ©2010 IEEE.

Abstract
Despite the benefits of precision agriculture and precision viticulture production systems, its adoption rate in the Portuguese Douro Demarcated Region remains low. One of the most demanding tasks in wine making is harvesting. Even for humans, the environment makes grape detection difficult, especially when the grapes and leaves have a similar color, which is generally the case for white grapes. In this paper, we propose a system for the detection and location, in the natural environment, of bunches of grapes in color images. The system is also able to distinguish between white and red grapes, at the same time, it calculates the location of the bunch stem. The proposed system achieved 97% and 91% correct classifications for red and white grapes, respectively.

Abstract
The rate of adoption of Precision Agriculture and Precision Viticulture production systems in the Douro Demarcated Region remains low. We believe that one way to raise it is to address challenging real-world problems whose solution offers a clear benefit to the viticulturist. For example, one of the most demanding tasks in wine making is harvesting. Even for humans, the detection of grapes in their natural environment is not always easy. White grapes are particularly difficult to detect, since their color is similar to that of the leafs. Here we present a low cost system for the detection of white grapes in natural environment color images. The system also calculates the probable location of the bunch stem and achieves 91% of correct classifications.

Abstract
Despite the benefits of precision agriculture and precision viticulture production systems, its rate of adoption in the Portuguese Douro Demarcated Region remains low. We believe that one way to raise it is to address challenging real-world problems whose solution offers a clear benefit to the viticulturist. For example, one of the most demanding tasks in wine making is harvesting. Even for humans, the environment makes grape detection difficult, especially when the grapes and leaves have a similar color, which is generally the case for white grapes. In this paper, we propose a system for the detection and location, in the natural environment, of bunches of grapes in color images. This system is able to distinguish between white and red grapes, and at the same time, it calculates the location of the bunch stem. The system achieved 97% and 91% correct classifications for red and white grapes, respectively.