Automatic identification of animals is extremely useful for scientists, providing ways to monitor species and changes in ecological communities. The choice of effective audio features and classification techniques is a challenge on any audio recognition system, especially in bioacoustics that commonly uses several algorithms. This paper presents a novel software architecture that supports multiple feature extraction and classification algorithms to help on the identification of animal species from their recorded sounds. This architecture was implemented by the WASIS software, freely available on the Web.
This paper presents a review of several robotic tools applied to the activity of pruning near power distribution lines. Power utilities prune trees to minimize the tree-caused power outages, because they are the greatest single cause of outages for power utilities in overhead distribution systems. Pruning trees around overhead power lines is considered a dangerous task due to many factors such as the risk of fall, electrical shock, accidents with the pruning tools and insect attack. Therefore robotic systems may provide a significant increase not only in productivity but also may provide a safe environment to perform the task. The article discusses both airborne and ground-based robots. Since most existing works in the literature are related to rural areas, this paper discusses some requirements to enable this kind of technology in urban areas.
This paper presents a new approach for automatic oscillography classification in distribution networks, including the detection of patterns not initially presented to the classifier during training, which are defined as novelties. We performed experiments with coupled novelty detection and multi-class classification, and also in separate stages, using the following classifiers: Gaussian Mixture Models (GMM), K-means clustering (KM), K-nearest neighbors (KNN), Parzen Windows (PW), Support Vector Data Description (SVDD), and multi-class classification based on Support Vector Machines (SVM). Preliminary results for simulated data in the Alternative Transient Program (ATP) demonstrate the ability of the method to identify new classes of events in a dynamic learning environment.
Esta revisão apresenta os princípios de funcionamento de células solares orgânicas (OSCs). Esta classe de dispositivos fotovoltaicos vem sendo amplamente estudada e otimizada para uma futura comercialização devido às suas características optoeletrônicas, obtendo atualmente eficiência de conversão de energia, em laboratório, comparáveis às células solares comerciais inorgânicas. Este trabalho apresenta as características de células solares orgânicas, comparando com as de outras gerações de dispositivos fotovoltaicos bem como um detalhamento dos princípios de funcionamento de OSCs, com ênfase na geração de cargas livres a partir de polímeros conjugados.
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