Big Data, Cloud Computing, and Data Science Engineering / edited by Roger Lee.

Include References And Indexes

Robust Optimization Model for Designing Emerging Cloud-Fog Networks -- Multi-task Deep Reinforcement Learning with Evolutionary Algorithm and Policy Gradients Method in 3D Control Tasks -- Learning Neural Circuit by AC Operation and Frequency Signal Output -- IoTDoc: A Docker-Container based Architecture of IoT-enabled cloud system -- A Survival Analysis-Based Prioritization of Code CheckerWarning: A Case Study using PMD -- Elevator Monitoring System to Guide User's Behavior by Visualizing the State 0f Crowdedness -- Choice Behavior Analysis of Internet Access Services Using Supervised Learning Models -- Norm-referenced Criteria for Strength of the Upper limbs for the Korean High School Baseball Players Using Computer Assisted Isokinetic Equipment -- A Feature Point Extraction and Comparison Method through Representative Frame Extraction and Distortion Correction for 360 Degree Realistic Contents -- Dimension Reduction by Word Clustering with Semantic Distance -- Word-Emotion Lexicon for Myanmar Language -- Release from the Curse of High Dimensional Data Analysis -- Evaluation of Inertial Sensor Configurations for Wearable Gait Analysis -- Index.

This edited book presents the scientific outcomes of the 4th IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2019) which was held on May 29-31, 2019 in Honolulu, Hawaii. The aim of the conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Presenting 15 of the conference's most promising papers, the book discusses all aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them.