04689nam 2200625 450 991013128880332120230807215548.01-118-91588-71-118-91587-9(CKB)3710000000413219(SSID)ssj0001481451(PQKBManifestationID)11842001(PQKBTitleCode)TC0001481451(PQKBWorkID)11502652(PQKB)10785680(DLC) 2015015961(MiAaPQ)EBC2044677(Au-PeEL)EBL2044677(CaPaEBR)ebr11053023(CaONFJC)MIL786040(OCoLC)909142688(EXLCZ)99371000000041321920150519h20152015 uy 0engurcnu||||||||txtccrBioShock and philosophy irrational game, rational book /edited by Luke CuddyChichester, England :Wiley Blackwell,2015.©20151 online resource (161 pages)Blackwell Philosophy and Pop Culture SeriesIncludes index.1-118-91589-5 1-118-91586-0 Includes bibliographical references at the end of each chapters and index.Machine generated contents note: Hacking Into This Book (Introduction) Luke Cuddy Level 1 Research Bonus: Increased Wisdom Capacity 1: BioShock's Meta-Narrative: What BioShock Teaches the Gamer about Gaming Collin Pointon 2: The Value of Art in BioShock: Ayn Rand, Emotion, and Choice Jason Rose 3: SHODAN vs. The Many--or--Mind vs. The Body Robert M. Mentyka 4: "The Cage is Somber:" A Feminist Understanding of Elizabeth Catlyn Origitano Tears, Time, and Reality 5: Rapture in a Physical World: Did Andrew Ryan Choose the Impossible? James Cook 6: Would You Kindly Bring us the Girl and Wipe Away the Debt: Free Will and Moral Responsibility in BioShock Infinite Oliver Laas 7: BioShock as Plato's Cave Roger Travis 8: BioShock Infinite and Transworld Individuality: Identity Across Space and Time Charles Joshua Horn 9: Shockingly Limited: Escaping Columbia's God of Necessity Scott Squires and James McBain The "Union" and the Sodom Below 10: "The Bindings are There as a Safeguard:" Sovereignty and Political Decisions in BioShock Infinite Rick Elmore 11: Propaganda, Lies, and Bullshit in BioShock's Rapture Rachel McKinnon 12: The Vox Populi Group, Marx, and Equal Rights for All Tyler DeHaven and Chris Hendrickson The Circus of Values 13: Infinite Lighthouses, Infinite Stories: BioShock and the Aesthetics of Video Game Storytelling Laszlo Kajtar 14: Have You Ever Been To Rapture? BioShock as an Introduction to Phenomenology Stefan Schevelier 15: "Evolve today!" Human Enhancement Technologies in the BioShock Universe Simon Ledder 16: Vending Machine Values: Buying Beauty and Morality in BioShock Michael J. Muniz ."Considered a sign of the 'coming of age' of video games as an artistic medium, the award-winning BioShock franchise covers vast philosophical ground. BioShock and Philosophy: Irrational Game, Rational Book presents expert reflections by philosophers (and Bioshock connoisseurs) on this critically acclaimed and immersive fan-favorite. Reveals the philosophical questions raised through the artistic complexity, compelling characters and absorbing plots of this ground-breaking first-person shooter (FPS) Explores what BioShock teaches the gamer about gaming, and the aesthetics of video game storytelling Addresses a wide array of topics including Marxism, propaganda, human enhancement technologies, political decision-making, free will, morality, feminism, transworld individuality, and vending machines in the dystopian society of Rapture Considers visionary game developer Ken Levine's depiction of Ayn Rand's philosophy, as well as the theories of Aristotle, de Beauvoir, Dewey, Leibniz, Marx, Plato, and others from the Hall of Philosophical Heroes"--Provided by publisher."Presents expert reflections by philosophers (and connoisseurs) on BioShock, the critically acclaimed and immersive video game"--Provided by publisher.Blackwell philosophy and popculture series.Video gamesPhilosophyVideo gamesDesignVideo gamesPhilosophy.Video gamesDesign.794.8/1536PHI000000bisacshCuddy Luke1980-MiAaPQMiAaPQMiAaPQBOOK9910131288803321BioShock and philosophy2212152UNINA10983nam 2200505 450 99650347110331620240110174148.03-031-21743-8(MiAaPQ)EBC7153768(Au-PeEL)EBL7153768(CKB)25616793000041(PPN)268355622(EXLCZ)992561679300004120230417d2022 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierIntelligent information and database systemsPart I 14th Asian Conference, ACIIDS 2022, Ho Chi Minh City, Vietnam, November 28-30, 2022, proceeding /Ngoc Thanh Nguyen [and five others]Cham, Switzerland :Springer,[2022]©20221 online resource (743 pages)Lecture Notes in Computer SciencePrint version: Nguyen, Ngoc Thanh Intelligent Information and Database Systems Cham : Springer International Publishing AG,c2023 9783031217425 Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Advanced Data Mining Techniques and Applications -- Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption -- 1 Introduction -- 1.1 Recent Work on Textual Stream Clustering -- 2 Distance Based Clustering with Automatic Threshold Determination (textClust) -- 2.1 Automatic Tresholding During the Online Phase -- 2.2 Algorithm Specification -- 3 Experiments -- 3.1 Benchmarking Datasets -- 3.2 Experimental Setup -- 3.3 Evaluation Metrics -- 3.4 Experimental Results -- 4 Discussion and Future Work -- References -- Using GPUs to Speed Up Genetic-Fuzzy Data Mining with Evaluation on All Large Itemsets -- 1 Introduction -- 2 Related Work -- 3 Components of the Proposed Algorithm -- 3.1 Chromosome Representation -- 3.2 Population Initialization -- 3.3 Fitness Function and Selection -- 3.4 Genetic Operators and Termination -- 4 The Proposed GFM-GPU-LAll Optimization Algorithm -- 5 Experimental Evaluations -- 6 Conclusions and Future Work -- References -- Efficient Classification with Counterfactual Reasoning and Active Learning -- 1 Introduction -- 2 Related Works -- 3 Framework -- 3.1 Problem Definition -- 3.2 Proposed Method CCRAL -- 4 Experiments and Discussions -- 4.1 Datasets -- 4.2 Baselines and Evaluation -- 4.3 Results -- 5 Conclusion -- References -- Visual Localization Based on Deep Learning - Take Southern Branch of the National Palace Museum for Example -- 1 Introduction -- 2 Related Work -- 2.1 Convolutional Neural Network -- 2.2 Visual Localization Based on Deep Learning -- 3 Proposed Method -- 3.1 Network Architecture -- 3.2 Loss Function -- 4 Experiments -- 4.1 Pretrained Model -- 4.2 Normalization -- 4.3 Loss Function -- 5 Conclusion and Future Work -- References.SimCPSR: Simple Contrastive Learning for Paper Submission Recommendation System -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Contrastive Learning -- 3.2 Modeling -- 3.3 Evaluation Metrics -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Datasets -- 4.3 Training Details -- 4.4 Results -- 5 Conclusion and Further Works -- References -- Frequent Closed Subgraph Mining: A Multi-thread Approach -- 1 Introduction -- 2 Related Work -- 3 Definitions -- 4 Proposed Method -- 5 Experimental Results -- 6 Conclusion and Future Work -- References -- Decision Support and Control Systems -- Complement Naive Bayes Classifier for Sentiment Analysis of Internet Movie Database -- 1 Introduction -- 2 Related Work -- 2.1 Sentiment Analysis (SA) -- 2.2 Complement Naïve Bayes Classifier -- 2.3 Analysis Metrics -- 3 Methodology -- 3.1 Research Workflow -- 3.2 Internet Movie Database (IMDB) -- 4 Experiment and Result -- 4.1 Experiment Results -- 5 Conclusions -- References -- Portfolio Investments in the Forex Market -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 The Investing Process -- 4 Numerical Experiments -- 5 Conclusions -- References -- Detecting True and Declarative Facial Emotions by Changes in Nonlinear Dynamics of Eye Movements -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussions -- 5 Conclusions -- References -- Impact of Radiomap Interpolation on Accuracy of Fingerprinting Algorithms -- 1 Introduction -- 2 Related Work -- 2.1 Fingerprinting Localization -- 2.2 Dynamic Radiomap -- 2.3 Interpolation Algorithms -- 3 Experimental Scenario and Achieved Results -- 4 Conclusions -- References -- Rough Set Rules (RSR) Predominantly Based on Cognitive Tests Can Predict Alzheimer's Related Dementia -- 1 Introduction -- 2 Methods -- 2.1 Theoretical Basis -- 3 Results -- 3.1 Statistical Results.3.2 RSR for Reference of Model1 Group -- 3.3 RSR for Reference of Model2 Group -- 4 Discussion -- References -- Experiments with Solving Mountain Car Problem Using State Discretization and Q-Learning -- 1 Introduction -- 2 Related Works -- 3 Modeling the Mountain Car Problem -- 3.1 Physics of the Mountain Car Problem -- 3.2 Model Exploration Using Random Walk and Numerical Simulation -- 4 Optimal Control Using State Discretization and Q-Learning -- 4.1 Q-Learning and SARSA Algorithms -- 4.2 State Discretization -- 4.3 Experimental Results -- 5 Conclusions and Future Work -- References -- A Stable Method for Detecting Driver Maneuvers Using a Rule Classifier -- 1 Introduction -- 2 Data Logging -- 2.1 Data Stream Forming -- 2.2 Data Collection -- 3 Evaluation of the Model -- 4 Conclusions and Further Work -- References -- Deep Learning Models -- Using Deep Transformer Based Models to Predict Ozone Levels -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Baseline Models -- 3.2 Performance Evaluation Metrics -- 4 Problem Description and Our Model -- 4.1 Problem Description -- 4.2 Deep Transformer Based Models -- 4.3 MLP and LSTM Networks -- 5 Experiments -- 5.1 Comparison Between Models -- 5.2 Hyperparameters Optimisation -- 6 Conclusions and Future Work -- References -- An Ensemble Based Deep Learning Framework to Detect and Deceive XSS and SQL Injection Attacks -- 1 Introduction -- 1.1 Background Study -- 2 Proposed Detection and Deception Technique -- 2.1 Data Preparation and Feature Selection -- 2.2 Using the Ensemble Based Deep Learning Classifiers -- 2.3 State Maintenance Module -- 2.4 Deception Module to Lure/Engage Attackers -- 3 Discussion, Performance Analysis and Testing -- 3.1 Comparative Analysis -- 4 Conclusion and Future Work -- References -- An Image Pixel Interval Power (IPIP) Method Using Deep Learning Classification Models.1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 4 Experiments and Results -- 4.1 Datasets -- 4.2 Baseline Method -- 4.3 Training Setup -- 4.4 Evaluation Metrics -- 4.5 Experimental Results and Discussions -- 5 Conclusion -- References -- Meta-learning and Personalization Layer in Federated Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 4 Numerical Experiments -- 5 Results and Discussion -- 6 Conclusion -- A Experimental Details -- A.1 Model Architecture -- A.2 Hyper-parameters Searching -- References -- ETop3PPE: EPOCh's Top-Three Prediction Probability Ensemble Method for Deep Learning Classification Models -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Training Setup -- 4.3 Evaluation Metrics -- 4.4 Experiment Results and Discussions -- 5 Conclusions -- References -- Embedding Model with Attention over Convolution Kernels and Dynamic Mapping Matrix for Link Prediction -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Dynamic Convolution -- 3.2 TransD Model -- 4 The Proposed Model -- 5 Experiments and Result Analysis -- 5.1 Benchmark Datasets -- 5.2 Experimental Setup -- 5.3 Results -- 6 Conclusion and Future Research Directions -- References -- Employing Generative Adversarial Network in COVID-19 Diagnosis -- 1 Introduction -- 2 Proposed Framework -- 2.1 Data Augmentation -- 2.2 Transfer Learning -- 3 Experimental Evaluation -- 3.1 Using GAN to Generate Synthetic Images -- 3.2 Transfer Learning -- 4 Conclusion -- References -- SDG-Meter: A Deep Learning Based Tool for Automatic Text Classification of the Sustainable Development Goals -- 1 Introduction -- 2 State-of-the-Art -- 3 Multi-labeled Text Classification with BERT -- 3.1 BERT: Bidirectional Encoder Representations from Transformers -- 3.2 SDG-Meter Tool -- 4 Experimentation.4.1 Dataset -- 4.2 Test and Results -- 5 Conclusion -- References -- The Combination of Background Subtraction and Convolutional Neural Network for Product Recognition -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Background Subtraction and Skin Removal -- 3.2 Product Classification -- 3.3 Product Tracking and Counting -- 4 Experiment -- 4.1 Experimental Setup -- 4.2 Training Classifier -- 4.3 Result and Discussion -- 5 Conclusions -- References -- Strategy and Feasibility Study for the Construction of High Resolution Images Adversarial Against Convolutional Neural Networks -- 1 Introduction -- 1.1 Attacks in the R Domain -- 1.2 Three Challenges Faced by Attacks in the H Domain -- 1.3 Our Contribution: A Strategy and a Feasibility Study -- 2 CNNs and the Target Scenario -- 2.1 The Target Scenario -- 2.2 The Target Scenario Lifted to HR Images -- 3 Attack Strategy for the Target Scenario on HR Images -- 3.1 Construction of Adversarial Images in H -- 3.2 Indicators: The Loss Function L and L2-distances -- 4 Feasibility Study -- 4.1 The Evolutionary Algorithm EAtarget,C -- 4.2 Running the Strategy to Get Adversarial Images with the EA -- 4.3 Visual Quality -- 5 Conclusion -- References -- Using Deep Learning to Detect Anomalies in Traffic Flow -- 1 Introduction -- 2 Problem Description -- 2.1 Data -- 2.2 Scenarios -- 3 Auto-encoder Models -- 3.1 CNN Auto-encoder Model -- 3.2 BiLSTM Auto-encoder Model -- 4 Experiments -- 4.1 Basic Scenario -- 4.2 Guided Scenario -- 5 Conclusions and Future Work -- References -- A Deep Convolution Generative Adversarial Network for the Production of Images of Human Faces -- 1 Introduction -- 2 A Recall of the Genarative Adversial Networks (GAN) -- 3 Related Works Concerning the Variants of GANs -- 3.1 Architecture-Variant -- 3.2 Loss-Variant.4 Deep Convolutional GAN: A Method Adopted for Human Faces Images Producing.Lecture notes in computer science.Artificial intelligenceCongressesDatabase managementCongressesArtificial intelligenceDatabase management006.3Nguyen Ngoc Thanh(Computer scientist),MiAaPQMiAaPQMiAaPQBOOK996503471103316Intelligent Information and Database Systems1902355UNISA