{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":21,"n_cols":5,"rows_kept":21,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[10,2,10,3],[12,2,12,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNISA996464512603316"]
[null,null,"Titolo",null,"Smart computing and communication : 5th international conference, SmartCom 2020, Paris, France, December 29-31, 2020 : proceedings / / Meikang Qiu (editor)"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"3-030-74717-4"]
[null,null,"Descrizione fisica",null,"1 online resource (304 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science ; ; v.12608"]
[null,null,"Disciplina",null,"004"]
[null,null,"Soggetti",null,"Cloud computing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents -- A Post-processing Trajectory Publication Method Under Differential Privacy -- 1 Introduction -- 2 Preliminaries -- 2.1 Differential Privacy -- 2.2 Data Model -- 2.3 Inconsistency Problem -- 3 Proposed Methods -- 3.1 Differential Privacy Publishing of Trajectory -- 3.2 Constrained Inference -- 4 Evaluation -- 5 Conclusion -- References -- Chinese Clinical Named Entity Recognition Based on Stroke-Level and Radical-Level Features -- 1 Introduction -- 2 Related Work -- 3 Hierarchical Structure of Proposed Model -- 3.1 Embedding Layer -- 3.2 BiLSTM Layer -- 3.3 CRF Layer -- 4 Experiments and Results -- 4.1 Experimental Data and Evaluation Indicators -- 4.2 Model Building and Parameter Setting -- 4.3 Experimental Results -- 5 Conclusion -- References -- Vision-Based Autonomous Driving for Smart City: A Case for End-to-End Learning Utilizing Temporal Information -- 1 Introduction -- 2 Background and Related Works -- 3 Proposed Method: Temporal Conditional Imitation Learning (TCIL) -- 4 Proposed Model: CNN-LSTM Network -- 5 Experiment -- 5.1 Dataset -- 5.2 Training -- 5.3 Evaluation -- 6 Results -- 6.1 Comparison with the State-of-the-Art -- 6.2 Ablation Study -- 7 Conclusion -- References -- A Novel Estimation Method for the State of Charge of Lithium-Ion Battery Using Temporal Convolutional Network Under Multiple Working Conditions -- 1 Introduction -- 2 Our Proposed TCN for SOC Estimation -- 2.1 Causal Convolutions -- 2.2 Dilated Convolutions -- 2.3 Residual Block -- 2.4 Model Overall Structure -- 3 Performance Analysis -- 3.1 Dataset -- 3.2 Experimental Settings -- "]
[{"$nulls":4},"3.3 SOC Estimation at Fixed Ambient Temperatures -- 3.4 SOC Estimation at Varying Ambient Temperatures -- 3.5 Comparative Analysis of Experimental Results -- 4 Conclusion -- References."]
[{"$nulls":4},"Research on Security Methods of Wireless Sensor Networks Based on Internet of Things Technology -- 1 Introduction -- 2 Characteristics of Wireless Sensor Networks -- 3 Several Commonly Used Attack Methods for Wireless Networks -- 4 Main Defense Methods of Wireless Sensor Network -- 5 Summary and Outlook -- 6 Funding Statement -- References -- Research on Multi-channel Pulse Amplitude Analyzer Based on FPGA -- 1 Introduction -- 2 Research Status -- 3 Multi-channel Pulse System Design -- 4 Experimental Results and Analysis -- 4.1 Master Function Timing Test -- 4.2 PWM Chopper Amplitude Modulation Test -- 5 Conclusion and Prospect -- References -- Towards Smart Building: Exploring of Indoor Microclimate Comfort Level Thermal Processes -- 1 Introduction -- 2 Literature Review -- 3 Mathematical Model -- 3.1 Heat Balance Equation on Indoor Environment -- 4 Simulation Results and Discussion -- 5 Conclusion -- References -- Container Memory Live Migration in Wide Area Network -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Key Designs -- 4.1 Dirty Page Tracking -- 4.2 Dirty Page Popularity-Based Migration Algorithm -- 5 System Modules -- 6 Evaluation -- 7 Conclusion -- References -- vRAS: An Efficient Virtualized Resource Allocation Scheme -- 1 Introduction -- 2 Problem Definition -- 3 vRAS -- 3.1 System Structure -- 3.2 vRAS Functionality -- 3.3 Estimation of Resource Requirements -- 3.4 Determination of Resource Allocation Sizes -- 4 Performance Evaluation -- 5 Conclusion -- References -- HOOD: High-Order Orthogonal Decomposition for Tensors -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Method -- 5 Experiments -- 6 Conclusion -- References -- A GMM-Based Anomaly IP Detection Model from Security Logs -- 1 Introduction -- 2 Related Work and Comparison of Existing Methods -- 3 Detection Model."]
[{"$nulls":4},"3.1 Algorithm Background Knowledge Introduction -- 3.2 Detection Model -- 4 Test Results -- 4.1 Data Set -- 4.2 Test Results -- 5 Conclusion -- References -- Intelligent Textbooks Based on Image Recognition Technology -- 1 Introduction -- 2 Related Work -- 3 Architecture -- 3.1 SSM Framework -- 3.2 Perceptual Hash Algorithm -- 3.3 OpenCV's Template Matching Algorithm -- 4 Implementation and Results -- 4.1 System Analysis -- 4.2 Implementation of iOS Client -- 5 Conclusion -- Reference -- Visual Analytics for Basketball Star Card Market-Under the Background of the NBA Restart -- 1 Introduction -- 2 Data Description -- 2.1 Sample Selection -- 2.2 Data Crawling -- 2.3 Data Cleaning and Reorganization -- 3 Empirical Analysis -- 3.1 Price Distribution -- 3.2 Transaction Volume of Star Cards at Different Times -- 3.3 Price Trends and Reasons for Fluctuations -- 3.4 Price Rising Period -- 3.5 Price Down Period -- 4 Conclusion -- References -- An Effective Seafile Dockerfile for Raspberry Pi to Make Docker YAML Files for Treehouses -- 1 Introduction -- 2 Background Technology -- 2.1 Treehouses -- 2.2 Services.Sh -- 3 Docker Image Building -- 4 Starting the Seafile Container -- 5 Automate the Initiation of a Seafile Container -- 6 Debugging Technique -- 7 Conclusion -- References -- Design of a Hardware Accelerator for Zero-Knowledge Proof in Blockchains -- 1 Introduction -- 2 Groth16's Calculation Steps and Software Implementation -- 2.1 Calculation Steps of Groth16 Algorithm -- 2.2 The Method of Software Implementation -- 3 Hardware Design and Implementation -- 3.1 FFT Units -- 3.2 ECP Units -- 3.3 MAC Units -- 4 Results and Analysis -- 5 Conclusion -- References -- Energy-Efficient Optimization Design for UAV-Assisted Wireless Powered MEC "]
[{"$nulls":4},"Systems -- 1 Introduction -- 2 System Model and Problem Formulation -- 2.1 Energy Consumption Based on Working Pattern."]
[{"$nulls":4},"2.2 Problem Formulation -- 3 Proposed Solution -- 3.1 Charging Resources Allocation Optimization -- 3.2 IoTDs Associations Optimization -- 3.3 Working Mode Decisions Optimization -- 4 Experimental Results and Analysis -- 5 Conclusion -- References -- Privacy-Preserving Accelerated Clustering for Data Encrypted by Different Keys -- 1 Introduction -- 2 Preliminaries -- 2.1 k-Means Clustering -- 2.2 Avoiding Divisions -- 3 Model Description -- 3.1 System Model -- 3.2 Threat Model -- 4 Our Scheme -- 4.1 Secure Distance Computation -- 4.2 Secure Comparison -- 4.3 Privacy Preserving Accelerated Clustering -- 4.4 Security Analysis -- 5 Experimental Evaluation -- 6 Conclusions -- References -- Blockchain Technology in Automobile Insurance Claim Systems Research -- 1 Introduction -- 2 Related Work Research -- 3 Key Technology Contrast -- 3.1 Public or Permissioned -- 3.2 Node Selection and Consensus Algorithm -- 3.3 Encryption Algorithm -- 3.4 The Data Analysis -- 4 Challenges for Blockchain -- 4.1 Throughput and Scalability -- 4.2 User Privacy Issues -- 4.3 Smart Contract -- 5 Prospects -- 6 Conclusions -- References -- Birds Classification Based on Deep Transfer Learning -- 1 Introduction -- 1.1 Research Background -- 1.2 Frame of the Thesis -- 2 Work Foundation -- 2.1 Convolutional Neural Network -- 2.2 ResNeXt -- 2.3 Deep Transfer Learning -- 2.4 Model Fine-Tuning -- 3 Algorithm -- 4 Experimental Design -- 4.1 Data Set -- 4.2 Experimental Environment -- 4.3 Experimental Procedure -- 5 Analysis of Experimental Results -- 6 Conclusion -- References -- Research on Security Consensus Algorithm Based on Blockchain -- 1 Introduction -- 2 Introduction of Several Consensus Algorithms -- 2.1 CFT Consensus Algorithms -- 2.2 BFT Consensus Algorithms -- 3 Comparison of Consensus Algorithm Performance -- 4 Summary and Outlook -- References."]
[{"$nulls":4},"Design of Intelligent Detection and Alarm System for Accident Anti-collision Based on ARM Technology -- 1 Introduction -- 2 Research Status at Home and Abroad -- 3 Related Technology Introduction -- 3.1 Melis Window Introduction -- 3.2 Melis Message Mechanism -- 4 Anti-collision System Software Design -- 4.1 System Main Program -- 4.2 G-Sensor Control Design -- 4.3 Anti-collision Design -- 4.4 Anti-collision System Test Analysis -- 5 Summary and Outlook -- References -- Resisting Adversarial Examples via Wavelet Extension and Denoising -- 1 Introduction -- 2 Research Background -- 2.1 Adversarial Attacks -- 2.2 Defense Strategies -- 3 Methodology -- 3.1 Overview -- 3.2 Wavelet Extension -- 3.3 Wavelet Denoising -- 4 Evaluations -- 4.1 Experimental Settings and Implementations -- 4.2 Black-Box Scenario -- 4.3 White-Box Scenario -- 5 Conclusion -- References -- Privacy-Preserving Computing Framework for Encrypted Data Under Multiple Keys -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Additively Homomorphic Encryption (AHE) -- 3.2 AHE Under Multiple Keys -- 3.3 AHE Supports One Multiplication -- 3.4 AHE Supports One Multiplication Under Multiple Keys -- 4 Model Description -- 4.1 System Model -- 4.2 Threat Model -- 5 Privacy Preserving Computing Framework -- 5.1 Secure Addition Protocol (SA) -- 5.2 Secure Multiplication Protocol (SM) -- 5.3 Secure Exponentiation Protocol (SE) -- 6 Security Analysis -- 7 Experimental Evaluation -- 7.1 Performance of Our Scheme -- 7.2 Comparison with Existing Schemes -- 8 Conclusions -- References -- Deep Reinforcement Learning Based on Spatial-Temporal Context for IoT Video Sensors Object Tracking -- 1 Introduction -- 2 Related Works -- 2.1 Visual Object Tracking -- 2.2 Deep Reinforcement Learning -- 3 The Existing Popularity About Deep "]
[{"$nulls":4},"RL and STC Tracker (DRST) -- 3.1 Framework of DRST."]
[{"$nulls":4},"3.2 DRST Networks."]