Raising the Dead; Extending Evolutionary Algorithms with a Case-based Memory

In dynamically changing environments, the performance of a standard evolutionary algorithm deteriorates. This is due to the fact that the population, which is considered to contain the history of the evolutionary process, does not contain enough information to allow the algorithm to react adequately to changes in the fitness landscape. Therefore, we added a simple, global case-based memory to the process to keep track of interesting historical events. Through the introduction of this memory and a storing and replacement scheme we were able to improve the reaction capabilities of an evolutionary algorithm with a periodically changing fitness function

INSULATION DEFECT LOCALIZATION THROUGH PARTIAL DISCHARGE MEASUREMENTS AND NUMERICAL CLASSIFICATION

In this paper, PD signals are analyzed to localize defects in insulation systems. The task of automatic defect localization with respect to electrodes has a wide range of industrial applications. In fact, depending on the apparatus type, risk assessment is remarkably affected by defect location with respect to the electrodes. In this study, various parameters are first extracted from PD distributions, and statistical analysis is performed to select the most significant parameters concerning localization. Then, the localization process is carried out through numerical classification. Three different classification methods are compared to find the best approach for this application. Comparing a k-nearest neighbour classifier, a probabilistic neural network and a support vector machine (SVM) based classifier, the best results are gained with SVM, although the former two are simpler to implement and easier to tune. SVM based classification has not been applied in PD analysis before this approach

Silver-Film Ion-Exchanged Single-Mode Waveguides in Er Doped Phosphate Glass

NRC publication: Ye

Enhancing Unobtrusive Home Technology Systems with a Virtual Assistant for Mood and Social Monitoring

As the global population ages, there is a growing need for support in daily activities among older individuals. Information and Communication Technologies (ICT) have the potential to ease caregiver responsibilities and worries and enhance the independence of older individuals. The objective of this study is to enrich traditional indoor monitoring systems, which mainly focus on safety and functional aspects, with features that consider both the needs of the caregivers and those of the monitored person. A triangulation of methods approach is employed, utilizing personas, surveys, and interviews to identify both parties’ specific needs and preferences and guide the selection of suitable technologies. Results recognize the importance of addressing the mood and social needs of the monitored persons and consider the barriers that hinder the installation of such systems due to privacy and independence concerns. A general framework is presented, which extends traditional monitoring systems to incorporate these additional needs