Abstract
Electric power network stability analysis requires that all system components are represented by their models. Usually, detailed data about system components such as generators, transformers and transmission lines are available. In this case accurate models can be derived from the network devices. However, corresponding data for individual loads are not always available, which makes the modelling of loads an important area of research studies. In this paper it is studied and analysed the effect of the composite load models in the dynamic voltage stability of an electric power network. The composite load models comprise residential, commercial and industrial loads. A severe contingency situation was simulated. The automatic voltage regulators of the generating units, the turbine speed governors, and the under load tap changers models were taken into account. The simulation results were obtained using the EUROSTAG software package. Finally, some conclusions that provide a better understanding of the dynamic voltage stability are pointed out.

Abstract

Abstract
One of the most well known successes of Inductive Logic Programming (ILP) is on Structure-Activity Relationship (SAR) problems. In such problems, ILP has proved several times to be capable of constructing expert comprehensible models that hell) to explain the activity of chemical compounds based on their structure and properties. However, despite its successes on SAR problems, ILP has severe scalability problems that prevent its application oil larger datasets. In this paper we present LogCHEM, an ILP based tool for discriminative interactive mining of chemical fragments. LogCHEM tackles ILP's scalability issues in the context of SAR applications. We show that LogCHEM benefits from the flexibility of ILP both by its ability to quickly extend the original mining model, and by its ability, to interface with external tools. Furthermore, We demonstrate that LogCHEM can be used to mine effectively large chemoinformatics datasets, namely, several datasets from EPA's DSSTox database and on a dataset based on the DTP AIDS anti-viral screen.

Abstract
Endoscopic capsule is a recent medical technology with important clinical benefits but suffering from a practical handicap: long exam annotation times. This paper proposes and compares two approaches (Bayesian and support vector machines) that can be used to segment the gastrointestinal tract into its four major topographic areas, allowing the automatic estimation of the clinically relevant gastric and intestinal sections and corresponding transit times. According to medical specialists, this can reduce exam annotation times by up to 12% (15 min). This automatic tool has been integrated into our CapView annotation software that is currently being used by three medical institutions.

Abstract
The automotive suspension plays a crucial role in vehicle safety and driving comfort. One of the most important components in vehicle suspensions is the damper (or shock absorber). Because there is no precise method to perform shock absorber test within the vehicle, an embedded autonomous system, powered by the energy harvested from the shock absorber itself, capable of monitoring shock absorber parameters and transmitting these values throughout a wireless interface to the vehicle central diagnostic unit, is presented. Such a device will permit the shock absorber condition assessment under vehicle operation, which to our best knowledge is considered a breakthrough in vehicle safety. © 2008 IEEE.

Abstract
This article studies several Fractional Order Control algorithms used for joint control of a hexapod robot. Both Pade and series approximations to the fractional derivative are considered for the control algorithm. The walking performance is evaluated through two indices: The mean absolute density of energy used per unit distance travelled, and the control effort. A set of simulation experiments reveals the influence of the different approximations upon the proposed indices. The results show that the fractional proportional and derivative algorithm, implemented using the Pade approximation with a small number of terms, gives the best results.