http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Machine Learning and Intelligent Communications
4th International Conference, MLICOM 2019, Nanjing, China, August 24-25, 2019, Proceedings
XVI, 795 p. 366 illus., 259 illus. in color. online resource.
This volume constitutes the refereed post-conference proceedings of the Fourth International Conference on Machine Learning and Intelligent Communications, MLICOM 2019, held in Nanjing, China, in August 2019. The 65 revised full papers were carefully selected from 114 submissions. The papers are organized thematically in machine learning, intelligent positioning and navigation, intelligent multimedia processing and security, wireless mobile network and security, cognitive radio and intelligent networking, IoT, intelligent satellite communications and networking, green communication and intelligent networking, ad-hoc and sensor networks, resource allocation in wireless and cloud networks, signal processing in wireless and optical communications, and intelligent cooperative communications and networking.
Wireless Networks -- High-Dimensional Data Anomaly Detection Framework Based on Feature Extraction of Elastic Network -- A Drone Formation Transformation Approach -- The principle and design of Separate fingerprint identification system LTE antenna port number detection algorithm based on channel estimation and piecewise linear regression -- Topology Sensing in Wireless Networks by Leveraging Symmetrical Connectivity -- Multi-destination two-hop untrusted AF relay networks with destination-aided cooperative jamming -- Secrecy Sum Rate for Two-way Untrusted Relay in SCMA Networks -- Improving complex network controllability via link prediction -- Communications -- Rectangular waveguide design optimization by sequential nonlinear programming and genetic algorithm -- Noise Reduction in Network Embedding -- Indoor localization Based on Centroid Constraints of AP Quadrilateral Networks -- Partially Overlapping Channel Selection in Jamming Environment: A Hierarchical Learning Approach -- A Q-Learning-based Channel Selection and Data Scheduling Approach for High-frequency Communications in Jamming Environment -- RFID Indoor Location Based on Optimized Generalized Regression Neural Network -- Beacon in the Air: Optimizing Data Delivery for Wireless -- Energy Powered UAVs -- Power Optimization in Wireless Powered based Mobile -- Edge Computing -- Big Data and Internet of Things -- Predicting Socio-economic Levels of Individuals via App -- Usage Records -- Multiple Task Assignment for Cooperating Homogeneous -- Unmanned Aerial Vehicles -- Design of Overall Framework of Self-Service Big Data -- Governance for Power Grid -- Data cleaning Based on Multi-sensor Spatiotemporal Correlation -- Distributed Hierarchical Fault Diagnosis Based on Sparse Auto-encoder and Random Forest -- A Data Quality Improvement Method Based on the Greedy Algorithm -- Research of Lightweight Encryption Algorithm Based on AES and Chaotic Sequences for Narrow-Band Internet of Things -- Energy Efficiency Maximization for Green Cognitive Internet of Things with Energy Harvesting -- Smart Internet of Things -- A smart wearable device for preventing indoor electric shock hazards -- A VLP approach based on a single LED lamp -- A Method of Calculating the Semantic Similarity between English and Chinese Concepts -- A Bicycle-borne Sensor Node for Monitoring Air Pollution based on NB-IoT -- Power Beacons Deployment in Wireless Powered Communication with Truncated Poisson Cluster Process -- Mobile Edge Computing-Enabled Resource Allocation for Ultra-Reliable and Low-Latency Communications -- A Bayesian Method for Link Prediction with Considering Path Information -- Identifying sources of random walk-based epidemic spreading in networks -- Design of intelligent lighting system for office workplace based on ZigBee Technology -- Machine Learning -- Active Sampling Based on MMD for Model Adaptation -- Optimal Dwell Time for Frequency Hopping in a Stackelberg Game with a Smart Jammer -- An Active Noise Correction Graph Embedding Method -- Applications of Machine Learning -- Trajectory Data for Demand Analysis -- Reinforcement Learning for HEVC Screen Content Intra.
edited by Xiangping Bryce Zhai, Bing Chen, Kun Zhu.
Information Systems and Communication Service
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 294