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2Published 2020Table of Contents: “...S-MEDUTA: Combining Balanced Scorecard with simulation and MCDA techniques for the evaluation of the strategic performance of an Emergency Department -- An Architecture For Cooperative Mobile Health Applications -- An Educational Scenario for the Learning of the Conic Section: Studying the Ellipse with the Use of Digital Tools and Elements of Differentiated Instruction and Cognitive Neurosciences 45 -- Antibody clustering using a machine learning pipeline that fuses genetic, structural and physicochemical properties -- Neuroeducation and computer programming. A review -- Towards Analyzing Next Generation Sequencing Algorithms -- WOL Ecosystem: Secure remote power-state control of computer(s) over the internet for telemedicine purposes and dementia patients -- Epidemics Fuzzy Decision-Making Applications and Fuzzy Genetic Algorithms Efficiency Enhancement -- Multivariate data analysis and machine learning for prediction of MCI-to-AD conversion -- A Deep Learning Approach for Human Action Recognition using Skeletal Information -- Artificial Neural Networks in Computer Aided Drug Design. ...”
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4Published 2022Table of Contents: “...Mariachi master-apprentice program: familia during the COVID-19 pandemic /...”
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7by Kubat, MiroslavTable of Contents: “...Cover -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- Acknowledgment -- 1 Core AI: Problem Solving and Automated Reasoning -- 1.1 Early Milestones -- 1.2 Problem Solving -- 1.3 Automated Reasoning -- 1.4 Structure and Method -- 2 Blind Search -- 2.1 Motivation and Terminology -- 2.2 Depth-First and Breadth-First Search -- 2.3 Practical Considerations -- 2.4 Aspects of Search Performance -- 2.5 Iterative Deepening (and Broadening) -- 2.6 Practice Makes Perfect -- 2.7 Concluding Remarks -- 3 Heuristic Search and Annealing -- 3.1 Hill Climbing and Best-First Search -- 3.2 Practical Aspects of Evaluation Functions -- 3.3 A-Star and IDA-Star -- 3.4 Simulated Annealing -- 3.5 Role of Background Knowledge -- 3.6 Continuous Domains -- 3.7 Practice Makes Perfect -- 3.8 Concluding Remarks -- 4 Adversary Search -- 4.1 Typical Problems -- 4.2 Baseline Mini-Max -- 4.3 Heuristic Mini-Max -- 4.4 Alpha-Beta Pruning -- 4.5 Additional Game-Programming Techniques -- 4.6 Practice Makes Perfect -- 4.7 Concluding Remarks -- 5 Planning -- 5.1 Toy Blocks -- 5.2 Available Actions -- 5.3 Planning with STRIPS -- 5.4 Numeric Example -- 5.5 Advanced Applications of AI Planning -- 5.6 Practice Makes Perfect -- 5.7 Concluding Remarks -- 6 Genetic Algorithm -- 6.1 General Schema -- 6.2 Imperfect Copies and Survival -- 6.3 Alternative GA Operators -- 6.4 Potential Problems -- 6.5 Advanced Variations -- 6.6 GA and the Knapsack Problem -- 6.7 GA and the Prisoner?...”
Published 2023
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