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This open access book focuses on robot introspection, which has a direct impact on physical human–robot interaction and long-term autonomy, and which can benefit from autonomous anomaly monitoring and diagnosis, as well as anomaly recovery strategies. In robotics, the ability to reason, solve their own anomalies and proactively enrich owned knowledge is a direct way to improve autonomous behaviors. To this end, the authors start by considering the underlying pattern of multimodal observation during robot manipulation, which can effectively be modeled as a parametric hidden Markov model (HMM). They then adopt a nonparametric Bayesian approach in defining a prior using the hierarchical Dirichlet process (HDP) on the standard HMM parameters, known as the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM). The HDP-HMM can examine an HMM with an unbounded number of possible states and allows flexibility in the complexity of the learned model and the development of reliable and scalable variational inference methods. This book is a valuable reference resource for researchers and designers in the field of robot learning and multimodal perception, as well as for senior undergraduate and graduate university students.

Robotics. --- Automation. --- Statistics . --- Control engineering. --- Mechatronics. --- Machine learning. --- Mathematical models. --- Robotics and Automation. --- Bayesian Inference. --- Control, Robotics, Mechatronics. --- Machine Learning. --- Mathematical Modeling and Industrial Mathematics. --- Models, Mathematical --- Simulation methods --- Learning, Machine --- Artificial intelligence --- Machine theory --- Mechanical engineering --- Microelectronics --- Microelectromechanical systems --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Automatic factories --- Automatic production --- Computer control --- Engineering cybernetics --- Factories --- Industrial engineering --- Mechanization --- Assembly-line methods --- Automatic control --- Automatic machinery --- CAD/CAM systems --- Robotics --- Robotics and Automation --- Bayesian Inference --- Control, Robotics, Mechatronics --- Machine Learning --- Mathematical Modeling and Industrial Mathematics --- Robotic Engineering --- Control, Robotics, Automation --- Collaborative Robot Introspection --- Nonparametric Bayesian Inference --- Anomaly Monitoring and Diagnosis --- Multimodal Perception --- Anomaly Recovery --- Human-robot Collaboration --- Robot Safety and Protection --- Hidden Markov Model --- Robot Autonomous Manipulation --- open access --- Bayesian inference --- Automatic control engineering --- Electronic devices & materials --- Machine learning --- Mathematical modelling --- Maths for engineers --- Statistics. --- Automatic control.

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Genetic Optimization Techniques for Sizing and Management of Modern Power Systems explores the design and management of energy systems using a genetic algorithm as the primary optimization technique. Coverage ranges across topics related to resource estimation and energy systems simulation. Chapters address the integration of distributed generation, the management of electric vehicle charging, and microgrid dimensioning for resilience enhancement with detailed discussion and solutions using parallel genetic algorithms.

Electric power systems --- Management. --- Mathematical models. --- Genetic algorithms.

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Este libro de investigación trata sobre que los momentos de la lectura mejoran la comprensión lectora en los niveles literal, inferencial y crítico de los estudiantes del segundo grado “E” del ciclo avanzado del CEBA “Politécnico Regional del Centro”- Huancayo, es de naturaleza cuantitativa, tipo aplicada, diseño pre experimental, con pre test y pos test en un solo grupo, muestra no probabilística. Se aplicó un pre test para diagnosticar su comprensión de textos, luego una propuesta experimental basada en la estrategia los momentos de la lectura de Isabel Solé y un post test para determinar los efectos. Se demostró estadísticamente que la aplicación de esta estrategia permite mejorar significativamente la comprensión lectora en el nivel literal, inferencial y crítico. Esto se fundamenta porque en el pre test la mayoría de estudiantes alcanzó calificaciones inferiores a 10 (escala vigesimal); pero, en el post test la mayoría superó este promedio en estos niveles. En el calculó se evidenció que existen diferencias significativas entre las puntuaciones del pre y post test de 6,6 puntos p < 0,05.

Education --- Education, Elementary