The serpentine leafminer, Liriomyza trifolii (Burgess) (Agromyzidae) has, during the past 8 years, become an increasingly important pest on tomatoes, the second most important vegetable crop in South Africa. In some areas where weekly chemical applications are made on the basis of a threshold level of 0.25 mines per plant, it is feared that this pest has become resistant. In the present study, examination of the effect of various levels of infestation on growth and yield of tomatoes showed that neither growth nor yield were negatively affected by infestation levels of up to 1092 and 468 mines per plant in a glasshouse and field trial, respectively. A comparison of yield on control plants with 1–50, 51–100 and > 100 mines per plant (field trial) indicated that low L. trifolii infestations of 1–50 mines/plant in fact increased the yield by c. 60%. The phenology of L. trifolii feeding (before or during and after flowering) had no effect on yield and the effect of herbivory by L. trifolii was not obscured by any relationship between fruit production and growth of the tomato plants. These results were confirmed by a field trial and it is thus clear that even the threshold level being applied in the USA (four mines per three terminal leaflets per plant) is unrealistically low. Low correlations between number of mines per plant and percentage of pinnae or leaves infected indicated that assessing levels of infection by counting mines could not be replaced by the easier counting of pinnae or leaves infected.
Trusted platform modules (TPMs) can provide a variety of security functionalities. However, the TPM specification is highly complex and the deployment of TPM-based solutions is a difficult and delicate task. In this paper we propose the use of security patterns to specify TPM-based security solutions. The refined notion of security patterns developed in the SERENITY research project allows us to produce precise specifications of TPM-based solutions for particular security goals. This approach makes TPM technology available to system engineers without in-depth knowledge of trusted computing specifications.
In production lines, buffers function as a means to decouple stations, which reduce the effect that station failures and varying process times have on the complete line's throughput. However, adding larger buffers can be costly, for example, in the automotive industry where it results in increased working capital. This manuscript addresses the buffer allocation problem (BAP), seeking the smallest total buffer size while meeting a prescribed throughput by employing a simulation-based optimisation approach. A Tabu Search algorithm searches the solution space for the optimal buffer configuration while a discrete event simulation model evaluates each configuration, accounting for the machine (un)reliability. Since the multiple simulations add a sizeable computational burden, our approach introduces a novel neighbourhood search mechanism, which borrows from the Theory of Constrains. Solving test sets available in the literature suggest that this approach is 18 times faster than prior Adaptive Tabu Search approaches for small problems, and more than five times faster for medium-sized problems.
In the automotive industry, a Body in White (BIW) refers to the first step, the basic structure, in the production of a vehicle. Once a BIW production line has been built, the (maximum) capacity is fixed and throughput is therefore limited by the equipment specified during the design phase. The main metric used to inform the production line design is the Net Ideal Cycle Time (NICT). Unfortunately, the state of practice to estimate the NICT is a basic heuristic that does not account for production variation. In this paper, we challenge the current estimation approach by proposing an alternative that assumes actual production to follow a Weibull distribution. The proposed model is derived and estimated from empirical data. The results suggest that BIW production lines have traditionally been designed with too low a capacity, resulting in planned throughput rarely being achieved. On the other hand, increasing the design capacity implies a higher initial investment. In this paper it is demonstrated that the higher investment required is offset by reduced losses, resulting in more reliable planning and returns.
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