Animated pedagogical agents are lifelike animated characters that facilitate the learning process. This paper describes Adele, a pedagogical agent that is designed to work with Web-based educational simulations. The Adele architecture implements key pedagogical functions: presentation, student monitoring and feedback, probing questions, hints, and explanations. These capabilities are coupled with an animated persona that supports continuous multi-modal interaction with a student. The architecture supports client-side execution in a Web browser environment, and is able to inter-operate with simulations created by off-the-shelf authoring tools.
Skin lesion segmentation is a crucial but challenging task in computer-aided diagnosis of skin images. This work aims to propose a skin cancer detection model, which includes two major phases: Feature extraction and Classification. Initially, feature extraction takes place, where the Gray-Level Co-Occurrence Matrix (GLCM) features and Gray Level Run-Length Matrix (GLRM) features are extracted from the input image. These extracted features are subjected to the classification process, where Optimized Neural Network (NN) is exploited for classifying the skin lesion. In addition, to attain more enhanced output, the weights of NN is tuned finely using Cuckoo-Grey Wolf based Optimization (CGWO). Finally, the superiority of the adopted scheme is analyzed by determining both the positive as well as negative measures through the comparison over several conventional methods.
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