Abstract
Similarly to other standard versions of the Maximum Principle, recently derived necessary conditions of optimality involving Hamiltonian Inclusions are satisfied by a degenerate set of multipliers when applied to problems to which the initial state is fixed and it is in the boundary of the state constraint set. In such case, the necessary conditions do not provide useful information to select minimizers. A constraint qualification under which nondegenerate necessary conditions based on a "standard" maximum principle was previously defined. In this paper we show that when the "velocity set" is convex the same constraint qualification permits nondegenerate necessary conditions involving Hamiltonian Inclusions. This is of relevance since it covers problems in which the set of multipliers produced by Hamiltonian Inclusion conditions is smaller than those generated by "standard" Maximum Principles. Furthermore, we show that the constraint qualification can be strengthened so that normality can be established.

Abstract
A silicon soil moisture sensor, based in the dual-probe heat-pulse (DPHP) method, was modeled, simulated and tested for achieving, with low-cost, accurate and reliable measurements. This method is based on the application of a heat pulse during a fixed interval of time. The maximum rise in temperature (DeltaT(M)) is monitored by the measurement probe, placed at a certain distance of the heater source. A low-cost high-performance and small temperature sensor (a dynamic V-pTAT generator) was designed and fabricated to be placed into the probe which have 0.912 mm inner diameter and 20 mm long. If one considers the range of water contents, ratio of water mass to dry soil mass, in a typical agricultural soil (0.05-0.35 m(3) M-3), the average sensitivity of the dual probe is about 1.95 degreesC per unit change (m(3) M-3) in water content for q = 400 Jm(-1).

Abstract

Abstract
This paper describes a wireless RF CMOS interface for soil moisture measurements. The interface basically comprises a Delta-Sigma (DeltaSigma) modulator for acquiring an external sensor signal, and a RF section where data is transmitted to a local processing unit. The DeltaSigma modulator is a single-bit, second-order modulator and it is implemented using switched-capacitors techniques in a fully-differential topology. With a sampling frequency of 423.75 kHz and an oversampling ratio (OSR) of 256, the modulator achieves a dynamic range of 98.7 dB (16.1 bit). The output of the modulator is applied to a counter, as a first-order decimation filter, and the result is stored. Prior to transmission, data is encoded as a pulse width modulated signal and assembled in a frame containing preamble and checksum control fields. This frame is then transmitted through a power amplifier operating at 433.92 MHz in class-E mode. To evaluate the DeltaSigma modulator performance, the bitstream was acquired and transferred to a personal computer to perform digital filtering and decimation using MATLAB. The soil moisture sensor is based on dual-probe heat-pulse (DPHP) method and is implemented by using an integrated temperature sensor and a heater. After applying a heat-pulse for a fixed period of time, the temperature rise, that is a function of soil moisture, generates a differential voltage that is amplified and applied to the mixed-signal interface input. The described interface can also be used with other kinds of environmental sensors in a wireless sensors network. The CMOS mixed-signal interface has been implemented in a single-chip using a standard CMOS 0.7 mum process (AMI C07M-A, n-well, 2 metals and 1 poly).

Abstract
One of the major problems that actual logic programming systems have to address is whether and how to prune undesirable parts of the search space. A region of the search space would definitely be undesirable if it can only repeat previously found solutions, or if it is well-known that the whole computation will fail. Or it may be the case that we are interested in a subset of solutions. In this work we discuss how the BEAM addresses pruning issues. The BEAM is an implementation of David Warren's Extended Andorra Model. Because the BEAM relies on a very flexible execution mechanism, all cases of pruning discussed above should be considered. We show that all these different forms of pruning can be supported, and study their impact in applications.

Abstract