This book constitutes refereed proceedings of the Third International Conference on Computer and Communication Engineering, CCCE 2023, held in Stockholm, Sweden, in March 2023.
The 18 full papers presented were carefully reviewed and selected from 36 submissions. The papers are organized in the following topical sections: image analysis and method; network model and function analysis of mobile network; system security estimation and analysis of data network; and AI-based system model and algorithm.

Klappentext

Image analysis and method: Enhanced Acoustic Noise Reduction Techniques for Magnetic Resonance Imaging System.- Rough Rice Grading in the Philippines Using Infrared Thermography.- An Interpretable Hybrid Recommender Based on Graph Convolution to Address Serendipity.- Network Model and Function Analysis of Mobile Network: A Geometry-based Strategic Placement of RISs In millimeter Wave Device to Device Communication.- Obstacle Aware Link Selection for Stable Multicast D2D Communications.- Mobility Aware Path Selection for Millimeterwave 5G Networks in the Presence of Obstacles.- A Probabilistic Analysis of the Delay in RIS Assisted SISO D2D Communication using Chernoff's Bounds.- An Empirical Analysis on Lossless Compression Techniques: Enhancing IoT Security through Deep Learning-based Intrusion Detection.- A Security and Vulnerability Assessment on Android Gambling Applications.- A Compliance Based and Security Assessment of Bring Your Own Device (BYOD) in Organizations.- A Compliance Based and Security Assessment of Bring Your Own Device (BYOD) in Organizations.- AI -based system model and algorithm: Application of Machine Learning in Predicting Crime Links on Specialized Features.- An Empirical Analysis on Lossless Compression Techniques.- An Analysis of the Performance Changes of the Model by Reducing the Input Feature Dimension in Stock Price Forecasting.- A Hybrid Algorithm by Incorporating Neural Network and Metaheuristic Algorithms for Function Approximation and Demand Prediction Estimation.- Deep QA: An Open-Domain Dataset of Deep Questions and Comprehensive Answers.- Tropical Cyclone Analysis and Accumulated Precipitation Predictive Model Using Regression Machine Learning Algorithm.- Mapping Learning Algorithms on Data, A Promising Novel Methodology to Compare Learning Algorithms.

Inhalt
Image analysis and method: Enhanced Acoustic Noise Reduction Techniques for Magnetic Resonance Imaging System.- Rough Rice Grading in the Philippines Using Infrared Thermography.- An Interpretable Hybrid Recommender Based on Graph Convolution to Address Serendipity.- Network Model and Function Analysis of Mobile Network: A Geometry-based Strategic Placement of RISs In millimeter Wave Device to Device Communication.- Obstacle Aware Link Selection for Stable Multicast D2D Communications.- Mobility Aware Path Selection for Millimeterwave 5G Networks in the Presence of Obstacles.- A Probabilistic Analysis of the Delay in RIS Assisted SISO D2D Communication using Chernoff's Bounds.- An Empirical Analysis on Lossless Compression Techniques: Enhancing IoT Security through Deep Learning-based Intrusion Detection.- A Security and Vulnerability Assessment on Android Gambling Applications.- A Compliance Based and Security Assessment of Bring Your Own Device (BYOD) in Organizations.- A Compliance Based and Security Assessment of Bring Your Own Device (BYOD) in Organizations.- AI -based system model and algorithm: Application of Machine Learning in Predicting Crime Links on Specialized Features.- An Empirical Analysis on Lossless Compression Techniques.- An Analysis of the Performance Changes of the Model by Reducing the Input Feature Dimension in Stock Price Forecasting.- A Hybrid Algorithm by Incorporating Neural Network and Metaheuristic Algorithms for Function Approximation and Demand Prediction Estimation.- Deep QA: An Open-Domain Dataset of Deep Questions and Comprehensive Answers.- Tropical Cyclone Analysis and Accumulated Precipitation Predictive Model Using Regression Machine Learning Algorithm.- Mapping Learning Algorithms on Data, A Promising Novel Methodology to Compare Learning Algorithms.