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  • 1
    Keywords: Artificial intelligence. ; Application software. ; Algorithms. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (771 pages)
    Edition: 1st ed.
    ISBN: 9783319320342
    Series Statement: Lecture Notes in Computer Science Series ; v.9648
    DDC: 006.3
    Language: English
    Note: Intro -- Preface -- Organization -- Contents -- Data Mining and Knowledge Discovery -- Screening a Case Base for Stroke Disease Detection -- Abstract -- 1 Introduction -- 2 Knowledge Representation and Reasoning -- 3 A Case Study -- 4 Case Based Reasoning -- 5 Conclusions -- Acknowledgments -- References -- SemSynX: Flexible Similarity Analysis of XML Data via Semantic and Syntactic Heterogeneity/Homogeneity Detection -- 1 Introduction -- 1.1 On the Innovativeness of the SemSynX Proposal -- 2 Running Example -- 3 The SemSynX Approach -- 3.1 XML Data Similarity Analysis in SemSynX -- 4 Experimental Results -- 5 Conclusions and Future Work -- References -- Towards Automatic Composition of Multicomponent Predictive Systems -- 1 Introduction -- 2 Related Work -- 3 MCPS Description -- 4 Contribution to Auto-WEKA -- 5 Methodology -- 6 Results and Discussion -- 7 Conclusion and Future Work -- References -- LiCord: Language Independent Content Word Finder -- 1 Introduction -- 2 Related Work -- 3 LiCord: Proposed Framework -- 3.1 NGram Constructor -- 3.2 Function Word Decider -- 3.3 Feature Value Calculator -- 3.4 Classifier Learner -- 4 Experiment -- 4.1 Experiment 1 -- 4.2 Experiment 2 -- 5 Conclusion -- References -- Mining Correlated High-Utility Itemsets Using the Bond Measure -- 1 Introduction -- 2 Preliminaries and Related Work -- 3 The FCHM Algorithm -- 4 Experimental Study -- 5 Conclusion -- References -- An HMM-Based Multi-view Co-training Framework for Single-View Text Corpora -- 1 Introduction -- 2 View Generation -- 3 Co-training with HMM View -- 4 Experiments -- 5 Results -- 6 Conclusions -- References -- Does Sentiment Analysis Help in Bayesian Spam Filtering? -- 1 Introduction -- 2 Related Work -- 2.1 Spam Filtering Techniques -- 2.2 Sentiment Analysis -- 3 Improving Spam Filtering Using Sentiment Analysis -- 3.1 Bayesian Spam Filtering. , 3.2 Sentiment Analysis -- 4 Experimental Results -- 4.1 Bayesian Spam Filtering Experiment -- 4.2 Sentiment Analysis -- 5 Conclusions -- References -- A Context-Aware Keyboard Generator for Smartphone Using Random Forest and Rule-Based System -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Adaptive Keyboard Generator -- 3.1 Data Collection -- 3.2 Data Analysis -- 3.3 User Behavior Pattern Recognition -- 3.4 GUI Generation -- 4 Experimental Results -- 5 Concluding Remarks -- Acknowledgements -- References -- Privacy Preserving Data Mining for Deliberative Consultations -- 1 Introduction -- 2 Privacy Preserving Data Mining for Deliberative Consultations - Literature Review -- 2.1 Levels of Privacy Preserving -- 2.2 Types of Data Partitioning in Privacy Preserving Data Mining -- 2.3 Methods of Data Modification in Privacy Preserving Data Mining -- 2.4 Privacy Preserving Techniques -- 3 Usability of Privacy Preserving Techniques in Deliberative Consultations -- 4 Conclusions and Future Work -- References -- Feature Selection Using Approximate Multivariate Markov Blankets -- 1 Introduction -- 2 Theoretical Foundations -- 2.1 Bivariate Approach for Feature Redundancy -- 2.2 Multivariate Approach -- 3 Data -- 3.1 Synthetic Datasets -- 3.2 UCI Datasets -- 4 Experiments and Results -- 4.1 Synthetic Datasets -- 4.2 UCI Datasets -- 5 Conclusions and Future Works -- References -- Student Performance Prediction Applying Missing Data Imputation in Electrical Engineering Studies Degree -- Abstract -- 1 Introduction -- 2 Case of Study -- 3 The Used Data Imputation Techniques -- 3.1 The MICE Algorithm -- 3.2 The AAA Algorithm -- 3.3 Models Validation -- 4 Results -- 5 Conclusions -- Acknowledgments -- References -- Accuracy Increase on Evolving Product Unit Neural Networks via Feature Subset Selection -- 1 Introduction -- 2 Methodology. , 2.1 Product Unit Neural Networks and Training Procedure -- 2.2 Experimental Design Distribution -- 2.3 Feature Selection -- 3 Proposal Description -- 4 Experimentation -- 5 Results -- 5.1 Results Applying EDD and EDDFS -- 5.2 Results Obtained with State-of-the-art Classifiers -- 6 Conclusions -- References -- Time Series -- Rainfall Prediction: A Deep Learning Approach -- 1 Introduction -- 2 Related Work -- 3 Data Preparation -- 4 Proposed Architecture -- 5 Experiments -- 5.1 Optimizing the Proposed Network Architecture -- 5.2 Evaluation of the Proposed Network -- 6 Conclusions and Future Work -- References -- Time Series Representation by a Novel Hybrid Segmentation Algorithm -- 1 Introduction -- 2 Hybrid Segmentation Algorithm -- 2.1 Summary of the Algorithm -- 2.2 Genetic Algorithm -- 2.3 Local Search -- 3 Experimental Results and Discussion -- 3.1 Time Series Analysed -- 3.2 Experimental Setting -- 3.3 Discussion -- 4 Conclusions -- References -- A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Time Series Forecasting Based on Nearest Neighbours -- 3.2 Algorithm Implementation for Apache Spark -- 4 Results -- 4.1 Datasets Description -- 4.2 Design of Experiments -- 4.3 Electricity Consumption Big Data Time Series Forecasting -- 5 Conclusions -- References -- Active Learning Classifier for Streaming Data -- 1 Introduction and Related Works -- 2 Active Learning Classifier for Data Stream -- 3 Experiments -- 3.1 Goals -- 3.2 Results -- 3.3 Discussion -- 4 Conclusions -- References -- Bio-inspired Models and Evolutionary Computation -- Application of Genetic Algorithms and Heuristic Techniques for the Identification and Classification of the Information Used by a Recipe Recommender -- 1 Introduction -- 2 Specification of the Proposed Genetic Algorithm. , 2.1 Codification -- 2.2 Starting Generation -- 2.3 GA Operators -- 2.4 Fitness Function -- 2.5 Getting the New Generation -- 2.6 Results -- 3 Heuristics -- 4 Conclusions -- References -- A New Visualization Tool in Many-Objective Optimization Problems -- 1 Introduction -- 2 Related Work -- 3 Proposed Tool -- 3.1 Overview Step -- 3.2 Detail Step -- 4 Experimental Results -- 5 Conclusion -- References -- A Novel Adaptive Genetic Algorithm for Mobility Management in Cellular Networks -- 1 Introduction -- 2 Basic Concepts -- 2.1 The Genetic Algorithm -- 2.2 Adaptation Within Evolutionary Algorithms -- 2.3 Studied Adaptation Strategies -- 2.4 Mobility Management in Cellular Networks -- 3 The Proposed Approach -- 3.1 Initialisation -- 3.2 Selection -- 3.3 Reproduction -- 3.4 Evaluation and Replacement -- 4 Experimental Results and Analysis -- 4.1 Numerical Results -- 4.2 Discussion and Interpretation -- 5 Conclusions -- References -- Bio-Inspired Algorithms and Preferences for Multi-objective Problems -- 1 Introduction -- 2 Foundations -- 3 Interactive Algorithms -- 3.1 CI-NSGA-II -- 3.2 CI-SMS-EMOA -- 3.3 CI-SPEA2 -- 4 Performance Indicators -- 4.1 Referential Cluster Variance Indicator -- 4.2 Hull Volume Indicator -- 5 Experimental Results -- 6 Final Remarks -- References -- Assessment of Multi-Objective Optimization Algorithms for Parametric Identification of a Li-Ion Battery Model -- 1 Introduction -- 2 Semi-physical Model for Li-Ion Battery -- 3 Multi-Objective Approach for Semi-physical Models -- 4 Experimental Results -- 4.1 Experimental Setup and Electronic Instrumentation -- 4.2 Statistical Experimental Design -- 4.3 Numerical Results and Discussion -- 5 Conclusion -- References -- Comparing ACO Approaches in Epilepsy Seizures -- 1 Introduction -- 2 FRBC Learning Metaheuristics for ECI -- 2.1 Pittsburg Learning of Generalized FRBC Models. , 2.2 Ant-Miner+ for Learning FRBCs with Michigan Style -- 3 Experimentation and Results -- 3.1 Materials and Methods -- 3.2 Evaluating the Effect of the Partitioning in the ACO Pittsburg Learning and Ant-Miner+ Michigan Approach -- 4 Conclusions and Future Work -- References -- Estimating the Maximum Power Delivered by Concentrating Photovoltaics Technology Through Atmospheric Conditions Using a Differential Evolution Approach -- 1 Introduction -- 2 CPV Technology -- 2.1 Study of Influential Atmospheric Conditions on the Electric Performance of CPV Modules -- 2.2 The Use of SMR and APE Indexes to Characterise the DNI Spectral Distribution -- 3 Experimental Study -- 4 Conclusions -- References -- A Hybrid Bio-inspired ELECTRE Approach for Decision Making in Purchasing Agricultural Equipment -- Abstract -- 1 Introduction -- 2 Agricultural Decision Making and Related Work -- 3 A Hybrid Bio-Inspired ELECTRE Model -- 3.1 Multiple Criteria Decision Making ELECTRE I Model -- 3.2 Application of Bio-Inspired Ranking Method -- 4 Choosing and Decision Making for Agricultural Equipment -- 4.1 Data Collection - Combine Harvester -- 5 Experimental Results -- 5.1 Experimental Results - Combine Harvester -- 5.2 Complete Ranking PROMETHEE II Method - Experimental Results -- 5.3 Discussion on Experimental Results -- 5.4 Experimental Results - Purchasing Irrigation Equipment -- 6 Conclusion and Future Work -- Acknowledgments -- References -- Learning Algorithms -- Evaluating the Difficulty of Instances of the Travelling Salesman Problem in the Nearby of the Optimal Solution Based on Random Walk Exploration -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Travelling Salesman Problem and Instances -- 3.2 Experimental Setup -- 4 Analysis -- 4.1 How Far from the Optimal Fitness? -- 4.2 Area as Metric -- 4.3 Comparison with the Phase Transition Parameter for TSP. , 5 Conclusions and Future Work.
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Journal of chemical ecology 14 (1988), S. 825-838 
    ISSN: 1573-1561
    Keywords: Solenopsis invicta ; Hymenoptera ; Formicidae ; imported fire ant ; Dufour's gland ; trail pheromone ; pheromone ; (Z,E)-a-farnesene ; sesquiterpene
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Chemistry and Pharmacology
    Notes: Abstract TheSolenopsis invicta trail pheromone is synthesized by the Dufour's gland and is released through the sting apparatus. The recruitment subcategory of theS. invicta trail pheromone was shown to be composed of a mixture of the orientation pheromone, (Z,E)-α-farnesene and an unidentified homosesquiterpene consisting of three rings and one double bond (C-1). C-1 is present in worker Dufour's glands at only 75 pg per worker equivalent. This is the first report that demonstrates that different exocrine products from the same gland control different subcategories of behavior related to mass recruitment.
    Type of Medium: Electronic Resource
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