LEADER 03061nam 22005893u 450 001 9910787324203321 005 20230124190941.0 010 $a1-61200-166-1 035 $a(CKB)2670000000402330 035 $a(EBL)1334569 035 $a(OCoLC)855504448 035 $a(SSID)ssj0001368836 035 $a(PQKBManifestationID)12517067 035 $a(PQKBTitleCode)TC0001368836 035 $a(PQKBWorkID)11289045 035 $a(PQKB)11578395 035 $a(MiAaPQ)EBC1334569 035 $a(EXLCZ)992670000000402330 100 $a20151012d2013|||| u|| | 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSpecial Operations in the American Revolution$b[electronic resource] 210 $cCasemate$d2013 215 $a1 online resource (423 p.) 300 $aDescription based upon print version of record. 311 $a1-61200-165-3 327 $a""Cover""; ""Title Page""; ""Copyright""; ""Contents""; ""Dedication""; ""Prologue""; ""1: The Capture of Fort Ticonderoga""; ""2: The New Providence Raid""; ""3: Knowltona???s Rangers""; ""4: Whitcomba???s Rangers""; ""5: John Paul Jonesa??? Raids on Britaina???s Coast""; ""6: Partisan Warfare in the Northern Theater""; ""7: The Rise of Partisan Warfare in the Southern Theater""; ""8: The Whaleboat Wars""; ""9: George Rogers Clarka???s March to Vincennes""; ""Epilogue""; ""Endnotes""; ""Bibliography""; ""Index"" 330 $aWhen the American Revolution began, the colonial troops had little hope of matching His Majesty's highly trained, experienced British and German legions in confrontational battle. Indeed, Washington's army suffered defeat after defeat in the first few years of the war, fighting bravely but mainly trading space for time. However, the Americans did have a trump, in a reservoir of tough, self-reliant frontier fighters, who were brave beyond compare, and entirely willing to contest the King's men with unconventional tactics.In this book, renowned author, and former U.S. Army Colonel, Robert Tonset 606 $aUnited States -- Biography -- Juvenile literature 606 $aSpecial operations (Military science)$xHistory$y18th century$zUnited States 606 $aRegions & Countries - Americas$2HILCC 606 $aHistory & Archaeology$2HILCC 606 $aUnited States - General$2HILCC 607 $aUnited States$xHistory$yRevolution, 1775-1783$xCampaigns 607 $aUnited States$xHistory$yRevolution, 1775-1783$xAmerican forces 615 4$aUnited States -- Biography -- Juvenile literature. 615 0$aSpecial operations (Military science)$xHistory 615 7$aRegions & Countries - Americas 615 7$aHistory & Archaeology 615 7$aUnited States - General 676 $a973.33 700 $aTonsetic$b Robert$01581333 801 0$bAU-PeEL 801 1$bAU-PeEL 801 2$bAU-PeEL 906 $aBOOK 912 $a9910787324203321 996 $aSpecial Operations in the American Revolution$93862816 997 $aUNINA LEADER 06328nam 22008055 450 001 9910838288603321 005 20240313123658.0 010 $a9783031539664 010 $a3031539664 024 7 $a10.1007/978-3-031-53966-4 035 $a(MiAaPQ)EBC31161637 035 $a(Au-PeEL)EBL31161637 035 $a(DE-He213)978-3-031-53966-4 035 $a(CKB)30378469200041 035 $a(OCoLC)1422232142 035 $a(EXLCZ)9930378469200041 100 $a20240214d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning, Optimization, and Data Science $e9th International Conference, LOD 2023, Grasmere, UK, September 22?26, 2023, Revised Selected Papers, Part II /$fedited by Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos M. Pardalos, Renato Umeton 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (503 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v14506 311 08$a9783031539657 311 08$a3031539656 327 $aIntegrated Human-AI Forecasting for Preventive Maintenance Task Duration Estimation -- Exploring Image Transformations with Diffusion Models: A Survey of Applications and Implementation Code -- Geolocation Risk Scores for Credit Scoring Models -- Social Media Analysis: The Relationship between Private Investors and Stock Price -- Deep learning model of two-phase fluid transport through fractured media: a real-world case study -- A Proximal Algorithm for Network Slimming -- Diversity in deep generative models and generative AI -- Improving Portfolio Performance Using a Novel Method for Predicting Financial Regimes -- kolopoly: Case Study on Large Action Spaces in Reinforcement Learning -- Alternating mixed-integer programming and neural network training for approximating stochastic two-stage problems -- Heaviest and densest subgraph computation for binary classification. A case study -- SMBOX: A Scalable and Efficient Method for Sequential Model-Based Parameter Optimization -- Accelerated Graph Integration with Approximation of Combining Parameters -- Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non- Visual Environments: A Comparison -- A hybrid steady-state genetic algorithm for the minimum conflict spanning tree problem -- Reinforcement learning for multi-neighborhood local search in combinatorial optimization -- Evaluation of Selected Autoencoders in the Context of End-User Experience Management -- Application of multi-agent reinforcement learning to the dynamic scheduling problem in manufacturing systems -- Solving Mixed Influence Diagrams by Reinforcement Learning -- Multi-Scale Heat Kernel Graph Network for Graph Classification -- Accelerating Random Orthogonal Search for Global Optimization using Crossover -- A Multiclass Robust Twin Parametric Margin Support Vector Machine with an Application toVehicles Emissions -- LSTM noise robustness: a case study for heavy vehicles -- Ensemble Clustering for Boundary Detection in High-Dimensional Data -- Learning Graph Configuration Spaces with Graph Embedding in Engineering Domains -- Towards an Interpretable Functional Image-Based Classifier: Dimensionality -- Reduction of High-Density Di use Optical Tomography Data -- On Ensemble Learning for Mental Workload Classification -- Decision-making over compact preference structures -- User-Like Bots for Cognitive Automation: A Survey -- On Channel Selection for EEG-based Mental Workload Classification -- What Song Am I Thinking Of -- Path-Weights and Layer-Wise Relevance Propagation for Explainability of ANNs with fMRI Data -- Sensitivity Analysis for Feature Importance in Predicting Alzheimer?s Disease -- A Radically New Theory of how the Brain Represents and Computes with Probabilities. 330 $aThis book constitutes the refereed proceedings of the 9th International Conference on Machine Learning, Optimization, and Data Science, LOD 2023, which took place in Grasmere, UK, in September 2023. The 72 full papers included in this book were carefully reviewed and selected from 119 submissions. The proceedings also contain 9 papers from and the Third Symposium on Artificial Intelligence and Neuroscience, ACAIN 2023. The contributions focus on the state of the art and the latest advances in the integration of machine learning, deep learning, nonlinear optimization and data science to provide and support the scientific and technological foundations for interpretable, explainable and trustworthy AI. . 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v14506 606 $aInformation technology$xManagement 606 $aComputer networks 606 $aElectronic digital computers$xEvaluation 606 $aComputer systems 606 $aArtificial intelligence 606 $aMachine learning 606 $aComputer Application in Administrative Data Processing 606 $aComputer Communication Networks 606 $aSystem Performance and Evaluation 606 $aComputer System Implementation 606 $aArtificial Intelligence 606 $aMachine Learning 615 0$aInformation technology$xManagement. 615 0$aComputer networks. 615 0$aElectronic digital computers$xEvaluation. 615 0$aComputer systems. 615 0$aArtificial intelligence. 615 0$aMachine learning. 615 14$aComputer Application in Administrative Data Processing. 615 24$aComputer Communication Networks. 615 24$aSystem Performance and Evaluation. 615 24$aComputer System Implementation. 615 24$aArtificial Intelligence. 615 24$aMachine Learning. 676 $a005.3 700 $aNicosia$b Giuseppe$0241374 701 $aOjha$b Varun$01726448 701 $aLa Malfa$b Emanuele$01726449 701 $aLa Malfa$b Gabriele$01726450 701 $aPardalos$b Panos M$0318341 701 $aUmeton$b Renato$01726451 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910838288603321 996 $aMachine Learning, Optimization, and Data Science$94132119 997 $aUNINA