LEADER 02712nam 2200577 450 001 9910788153603321 005 20170925180041.0 010 $a1-4985-0098-6 010 $a0-7391-9736-3 035 $a(CKB)2670000000602358 035 $a(SSID)ssj0001459444 035 $a(PQKBManifestationID)12567726 035 $a(PQKBTitleCode)TC0001459444 035 $a(PQKBWorkID)11457011 035 $a(PQKB)11713076 035 $a(MiAaPQ)EBC1992055 035 $a(EXLCZ)992670000000602358 100 $a20141204h20152015 uy| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMexicano and Latino politics and the quest for self-determination $ewhat needs to be done /$fArmando Navarro 210 1$aLanham, Maryland :$cLexington Books,$d[2015] 210 4$dİ2015 215 $a1 online resource (605 pages) 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a1-336-20988-7 311 $a0-7391-9735-5 320 $aIncludes bibliographical references and index. 327 $aMexicanos political experience in Aztla?n : a historical narrative of a conquered, occupied, and colonized people -- Re-Mexicanizacio?n of Aztla?n and Latinoiziacio?n or "browning" of the United States -- Mexicanos and Latinos in the United States in the twenty-first century : under a state of siege and state of crisis -- Profile of internal colonial Mexicano/Latino politics : a people in a leadership, organizational, and electoral crisis -- 2013 Latino immigration reform debacle -- Triad crisis : country, world, and global capitalism in turmoil -- Aztla?n's politics of a nation-within-a-nation : quest for self-determination and reform -- Global secessionist contagion : the politics of separatism -- Aztla?n's Mexicano historical antecedents of separatism : struggles for self-determination -- Aztla?n's polit. 606 $aMexican Americans$xPolitics and government 606 $aHispanic Americans$xPolitics and government 606 $aMexican Americans$xEthnic identity 606 $aHispanic Americans$xEthnic identity 606 $aAztla?n 615 0$aMexican Americans$xPolitics and government. 615 0$aHispanic Americans$xPolitics and government. 615 0$aMexican Americans$xEthnic identity. 615 0$aHispanic Americans$xEthnic identity. 615 0$aAztla?n. 676 $a973/.046872 700 $aNavarro$b Armando$f1941-$01478807 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910788153603321 996 $aMexicano and Latino politics and the quest for self-determination$93709583 997 $aUNINA LEADER 05435nam 22007575 450 001 996466438303316 005 20200703172048.0 010 $a3-319-71501-1 024 7 $a10.1007/978-3-319-71501-8 035 $a(CKB)4340000000223578 035 $a(DE-He213)978-3-319-71501-8 035 $a(MiAaPQ)EBC6296472 035 $a(MiAaPQ)EBC5578244 035 $a(Au-PeEL)EBL5578244 035 $a(OCoLC)1017971199 035 $a(PPN)221251766 035 $a(EXLCZ)994340000000223578 100 $a20171121d2017 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSecurity, Privacy, and Applied Cryptography Engineering$b[electronic resource] $e7th International Conference, SPACE 2017, Goa, India, December 13-17, 2017, Proceedings /$fedited by Sk Subidh Ali, Jean-Luc Danger, Thomas Eisenbarth 205 $a1st ed. 2017. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017. 215 $a1 online resource (XXIV, 295 p. 55 illus.) 225 1 $aSecurity and Cryptology ;$v10662 311 $a3-319-71500-3 320 $aIncludes bibliographical references and index. 327 $aOn the (in)Security of ChaCha20 Against Physical Attacks -- An Industrial Outlook on Challenges of Hardware Security in Digital Economy -- How to Digitally Construct and Validate TRNG and PUF Primitives Which Are Based on Physical Phenomenon -- Cache Attacks: From Cloud to Mobile -- May the Fourth Be with You: A Microarchitectural Side Channel Attack on Several Real-World Applications of Curve25519 -- The Crisis of Standardizing DRM: The Case of W3C Encrypted Media Extensions -- Parameter Choices for LWE -- Efficient Side Channel Testing of Cryptographic Devices Using TVLA -- IoT Insecurity - Innovation and Incentives in Industry -- Hardware enabled cryptography: Physically Unclonable Functions and Random Numbers as Roots of Trust -- Tackling the Time-Defence: An Instruction Count Based Microarchitectural Side-channel Attack on Block Ciphers -- Hey Doc, Is This Normal?: Exploring Android Permissions in the Post Marshmallow Era -- Efficient Software Implementation of Laddering Algorithms over Binary Elliptic Curves -- Analysis of Diagonal Constants in Salsa -- Practical Fault Attacks on Minalpher: How to Recover Key with Minimum Faults -- eSPF: A Family of Format-Preserving Encryption Algorithms Using MDS Matrices -- Similarity Based Interactive Private Information Retrieval -- A Secure and Efficient Implementation of the Quotient Digital Signature Algorithm (qDSA) -- Variable-Length Bit Mapping and Error Correcting Codes for Higher-Order Alphabet PUFs -- Mutual Friend Attack Prevention in Social Network Data Publishing -- Short Integrated PKE+PEKS in Standard Model -- Differential Fault Attack on Grain v1, ACORN v3 and Lizard -- Certain observations on ACORN v3 and the Implications to TMDTO Attacks -- Efficient Implementation of Private License Plate Matching Protocols. . 330 $aThis book constitutes the refereed proceedings of the 7th International Conference on Security, Privacy, and Applied Cryptography Engineering, SPACE 2017, held in Goa, India, in December 2017. The 13 revised full papers presented together with 1 short paper, 7 invited talks, and 4 tutorials were carefully reviewed and selected from 49 initial submissions. This annual event is devoted to various aspects of security, privacy, applied cryptography, and cryptographic engineering. This is indeed a very challenging field, requiring the expertise from diverse domains, ranging from mathematics to solid-state circuit design. 410 0$aSecurity and Cryptology ;$v10662 606 $aData protection 606 $aComputer security 606 $aData encryption (Computer science) 606 $aCoding theory 606 $aInformation theory 606 $aComputer communication systems 606 $aSecurity$3https://scigraph.springernature.com/ontologies/product-market-codes/I28000 606 $aSystems and Data Security$3https://scigraph.springernature.com/ontologies/product-market-codes/I28060 606 $aCryptology$3https://scigraph.springernature.com/ontologies/product-market-codes/I28020 606 $aCoding and Information Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/I15041 606 $aComputer Communication Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/I13022 615 0$aData protection. 615 0$aComputer security. 615 0$aData encryption (Computer science). 615 0$aCoding theory. 615 0$aInformation theory. 615 0$aComputer communication systems. 615 14$aSecurity. 615 24$aSystems and Data Security. 615 24$aCryptology. 615 24$aCoding and Information Theory. 615 24$aComputer Communication Networks. 676 $a005.82 702 $aAli$b Sk Subidh$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aDanger$b Jean-Luc$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aEisenbarth$b Thomas$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466438303316 996 $aSecurity, privacy, and applied cryptography engineering$92065794 997 $aUNISA LEADER 10786nam 22004933 450 001 996601561103316 005 20240601060245.0 010 $a981-9723-03-5 035 $a(MiAaPQ)EBC31356869 035 $a(Au-PeEL)EBL31356869 035 $a(CKB)32169881100041 035 $a(EXLCZ)9932169881100041 100 $a20240601d2024 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aWeb and Big Data $e7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6-8, 2023, Proceedings, Part I 205 $a1st ed. 210 1$aSingapore :$cSpringer Singapore Pte. Limited,$d2024. 210 4$dİ2024. 215 $a1 online resource (533 pages) 225 1 $aLecture Notes in Computer Science Series ;$vv.14331 311 $a981-9723-02-7 327 $aIntro -- Preface -- Organization -- Contents - Part I -- A BERT-Based Semantic Enhanced Model for COVID-19 Fake News Detection -- 1 Introduction -- 2 Related Work -- 2.1 COVID-19 Fake News Collection -- 2.2 COVID-19 Fake News Detection -- 2.3 BERT Model -- 3 Methodology -- 3.1 Dataset -- 3.2 Problem Statement -- 3.3 Text Representation Learning -- 3.4 Topic Generation -- 3.5 Classifier Design -- 4 Experimental Results and Parameter Analysis -- 4.1 Experimental Results -- 4.2 Parameter Analysis -- 5 Conclusion -- References -- Mining Frequent Geo-Subgraphs in a Knowledge Graph -- 1 Introduction -- 2 Problem Definition -- 3 Frequent Geo-Subgraph Mining -- 4 Optimizations -- 4.1 Arc Consistency Based Candidate Generation -- 4.2 Image Vertex Reusage -- 4.3 Geo-Grid Based Vertex Ordering -- 5 Experimental Study -- 5.1 Setup -- 5.2 Performance Evaluations -- 6 Related Work -- 7 Conclusion -- References -- Locality Sensitive Hashing for Data Placement to Optimize Parallel Subgraph Query Evaluation -- 1 Introduction -- 2 Background -- 2.1 Preliminaries -- 2.2 Parallel Execution Model -- 3 Locality Sensitive Hashing for Data Placement -- 3.1 Vertex Similarity -- 3.2 Vertex MinHash -- 4 System Implementation -- 5 Experiments -- 5.1 Experimental Setting -- 5.2 Effect of Our Proposed Techniques -- 5.3 Comparison with Other Parallel Subgraph Query Systems -- 5.4 Data Placement Performance -- 6 Related Work -- 7 Conclusion -- References -- DUTD: A Deeper Understanding of Trajectory Data for User Identity Linkage -- 1 Introduction -- 2 Related Work -- 3 Preliminary -- 4 Proposed Model -- 4.1 Grid Feature Extractor -- 4.2 Tranformer-Based Encoder -- 4.3 Matcher -- 5 Experiment -- 5.1 Datasets -- 5.2 Baselines -- 5.3 Parameter Setting and Evaluation Metrics -- 5.4 Performance Comparison -- 5.5 Ablation Study -- 6 Conclusion -- References. 327 $aLarge-Scale Rank Aggregation from Multiple Data Sources Based D3MOPSO Method -- 1 Introduction -- 2 Related Work -- 3 Definitions and Problem Formulation -- 4 Proposed Method -- 4.1 Strategy on Encoding Scheme and Multi-directional Search -- 4.2 Particle Swarm Initialization -- 4.3 Definition of Discrete Position and Velocity -- 4.4 Discrete Particle Statue Updating -- 4.5 Framework of the Proposed Algorithm -- 4.6 Complexity Analysis -- 5 Experimental Studies -- 5.1 Comparison Algorithms -- 5.2 Experimental Settings -- 5.3 Evaluation Metrics -- 5.4 The Results -- 6 Conclusion -- References -- Hierarchically Delegatable and Revocable Access Control for Large-Scale IoT Devices with Tradability Based on Blockchain -- 1 Introduction -- 2 Building Blocks -- 2.1 Blockchain and Ethereum -- 2.2 Digital Signature -- 2.3 BIP-32 Standard -- 3 System Assumption and Requirements -- 3.1 System Entities -- 3.2 System Assumption -- 3.3 System Requirements -- 4 The Proposed Framework -- 4.1 High-Level Overview -- 4.2 IoT Device Registration -- 4.3 Ownership Transfer/Trading of IoT Device -- 4.4 (Hierarchical) Delegation of Access Control -- 4.5 Access an IoT Device -- 4.6 Revocation -- 5 Experimental Results -- 6 Security Analysis -- 7 Conclusions -- References -- Distributed Deep Learning for Big Remote Sensing Data Processing on Apache Spark: Geological Remote Sensing Interpretation as a Case Study -- 1 Introduction -- 2 Related Works -- 2.1 Distributed Deep Learning's Development Status -- 2.2 DDL-Based Remote Sensing Data Processing -- 3 Distributed Deep Learning Frameworks -- 3.1 MLlib -- 3.2 SparkTorch and TensorflowOnSpark -- 3.3 DeepLearning4Java -- 3.4 BigDL -- 3.5 Horovod -- 4 D-AMSDFNet: Distributed Deep Learning-Based AMSDFNet for Geological Remote Sensing Interpretation -- 4.1 AMSDFNet -- 4.2 Design of Distributed AMSDFNet -- 5 Experiments. 327 $a5.1 Settings -- 5.2 Analysis of Experimental Results -- 6 Conclusions -- References -- Graph-Enforced Neural Network for Attributed Graph Clustering -- 1 Introduction -- 2 Related Works -- 3 Notations and Problem Formulation -- 4 Degradation Analysis -- 4.1 Intra-cluster Estrangement -- 4.2 Attribute Similarity Neglection -- 4.3 Blurred Cluster Boundaries -- 5 The Proposed Method -- 5.1 Multi-task Learning Framework -- 5.2 High-Order Structural Proximity Enforcement -- 5.3 Attribute Similarity Enforcement -- 5.4 Cluster Boundary Enforcement -- 5.5 Joint Objective Optimization -- 6 Experiments -- 6.1 Experiment Settings -- 6.2 Performance Comparison -- 6.3 Efficiency Comparison -- 6.4 Ablation Study -- 6.5 Hyperparameter Sensitivity Analysis -- 7 Conclusion -- References -- MacGAN: A Moment-Actor-Critic Reinforcement Learning-Based Generative Adversarial Network for Molecular Generation -- 1 Introduction -- 2 Related Work -- 3 MacGAN Overview -- 3.1 GAN -- 3.2 Autoregressive GAN for SMILES Strings -- 3.3 Moment Reward -- 4 Experiment -- 4.1 Dataset -- 4.2 Evaluation Measures -- 4.3 Desired Chemical Properties -- 4.4 Model Setup -- 4.5 Experimental Results -- 5 Conclusion -- References -- Multi-modal Graph Convolutional Network for Knowledge Graph Entity Alignment -- 1 Introduction -- 2 Related Work -- 2.1 Entity Alignment -- 2.2 Multi-modal Knowledge Graph -- 3 Methodology -- 3.1 Definition and Model Overview -- 3.2 Multi-modal Pre-trained Embedding -- 3.3 Multi-modal Enhancement Embedding Mechanism -- 3.4 Objective -- 4 Experiments -- 4.1 Datasets -- 4.2 Experimental Settings -- 4.3 Baselines -- 4.4 Main Results -- 4.5 Ablation Study -- 4.6 Parameter Analysis -- 5 Conclusion and Future Work -- References -- Subgraph Federated Learning with Global Graph Reconstruction -- 1 Introduction -- 2 Related Work -- 2.1 Subgraph Federated Learning (SFL). 327 $a2.2 Graph Structure Learning (GSL) -- 2.3 Split Learning -- 3 Problem Setting -- 4 Methodology -- 4.1 Framework Overview -- 4.2 Local Pre-training -- 4.3 The Local Graph Learning Module -- 4.4 The Global Graph Structure Learning Module -- 4.5 Objective and Training Procedure -- 5 Experiment -- 5.1 Experimental Setups -- 5.2 Comparison with State-of-the-art Methods (RQ1) -- 5.3 Ablation Study (RQ2) -- 5.4 Sensitivity Analysis (RQ3) -- 6 Conclusion -- References -- SEGCN: Structural Enhancement Graph Clustering Network -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Notations -- 3.2 Topology Enhancement Module -- 3.3 Improved Attention-Driven Graph Clustering Network with Global Structure Dynamic Fusion Module -- 3.4 Optimization Objective Function -- 4 Experiment -- 4.1 Benchmark Datasets -- 4.2 Experimental Setup and Evaluation -- 4.3 Clustering Results -- 4.4 Ablation Studies -- 4.5 Visualization Results -- 5 Conclusion -- References -- Designing a Knowledge Graph System for Digital Twin to Assess Urban Flood Risk -- 1 Introduction -- 2 Related Work -- 3 Preliminary -- 4 The Proposed UrbanFloodKG System -- 4.1 System Overview -- 4.2 Data Layer -- 4.3 Graph Layer -- 4.4 Algorithm Layer -- 4.5 Digital Twin Layer -- 5 Experiment and Discussion -- 5.1 Dataset and Environment -- 5.2 Link Prediction Analysis -- 5.3 Node Classification Analysis -- 6 Conclusion -- References -- TASML: Two-Stage Adaptive Semi-supervised Meta-learning for Few-Shot Learning -- 1 Introduction -- 2 Related Work -- 2.1 Brain-Inspired Model for Visual Object Recognition -- 2.2 Meta-learning for Few-Shot Learning -- 3 Methodology -- 3.1 Preliminary -- 3.2 The Two-Stage Semi-supervised Meta-learning Framework -- 3.3 Unsupervised Visual Representation Learning -- 3.4 Gradient-Based Meta-learning for Few-Shot Learning -- 3.5 Global Context-Aware Module -- 4 Experiments. 327 $a4.1 Few-Shot Image Classification -- 4.2 Ablation Study -- 4.3 Visualization -- 5 Conclusion -- References -- An Empirical Study of Attention Networks for Semantic Segmentation -- 1 Introduction -- 2 Related Work -- 2.1 Enrich Contextual Information Based Methods -- 2.2 Reduce Computation Complexity Based Methods -- 3 Experiment -- 3.1 Datasets -- 3.2 Implementation Details -- 4 Analysis -- 5 Conclusions and Future Works -- References -- Epidemic Source Identification Based on Infection Graph Learning -- 1 Introduction -- 2 Preliminaries -- 2.1 Problem Description -- 2.2 Propagation Model -- 3 Related Work -- 4 Our Model -- 4.1 Architecture -- 4.2 Input Generation -- 4.3 GCN Layer -- 4.4 Graph Embedding Layer -- 4.5 Output Layer -- 4.6 Loss Function -- 4.7 Model Complexity -- 5 Experiment -- 5.1 Datasets and Baselines -- 5.2 Evaluation Metrics -- 5.3 Experimental Setting -- 5.4 Source Identification Performance -- 5.5 Ablation Study -- 5.6 Impact of Parameters -- 5.7 Model Efficiency -- 6 Conclusion and Future Work -- References -- Joint Training Graph Neural Network for the Bidding Project Title Short Text Classification -- 1 Introduction -- 2 Related Work -- 2.1 Text Classification -- 2.2 Short Text Classification -- 3 Method -- 3.1 Extracting Contextual Information -- 3.2 Graph Structure Construction -- 3.3 Feature Caching and Replacement -- 3.4 Graph Convolution Operation -- 3.5 Classification -- 4 Experiment -- 4.1 Datasets -- 4.2 Data Processing -- 4.3 Baseline Models -- 4.4 Experimental Settings -- 4.5 Results -- 4.6 Parameter Analysis -- 5 Conclusion -- References -- Hierarchical Retrieval of Ancient Chinese Character Images Based on Region Saliency and Skeleton Matching -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 Visual Feature Extraction -- 3.2 Regional Channel Screening -- 3.3 Saliency Joint Weighting Method. 327 $a3.4 Shape Fine Matching Based on Skeleton Context. 410 0$aLecture Notes in Computer Science Series 700 $aSong$b Xiangyu$01737421 701 $aFeng$b Ruyi$01737422 701 $aChen$b Yunliang$01737423 701 $aLi$b Jianxin$01737424 701 $aMin$b Geyong$01422753 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996601561103316 996 $aWeb and Big Data$94159223 997 $aUNISA