Название: Software Engineering in IoT, Big Data, Cloud and Mobile Computing
Автор: Haengkon Kim, Roger Lee
Издательство: Springer
Год: 2021
Страниц: 225
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This edited book presents scientific results of the International Semi-Virtual Workshop on Software Engineering in IoT, Big data, Cloud and Mobile Computing (SE-ICBM 2020) which was held on October 15, 2020, at Soongsil University, Seoul, Korea. The aim of this workshop 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. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.

The workshop organizers selected the best papers from those papers accepted for presentation at the workshop. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 17 of the conference’s most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.

In Chapter “Variability Modeling in Software Product Line: A Systematic Literature Review,” Aman Jaffari, Jihyun Lee and Eunmi Kim introduce the majority of the studies proposed techniques for modeling variability in a separate model rather than modeling variability as an integral part of the development artifact.

In Chapter “The Use of Big Data Analytics to Improve the Supply Chain Performance in Logistics Industry,” Lai Yin Xiang, Ha Jin Hwang, Haeng Kon Kim, Monowar Mahmood and Norazryana Mat Dawi discuss a bigger picture of how the use of big data analytics can improve the supply chain performance in logistics industry. Logistics industry could benefit from the results of this research by understanding the key success factors of big data analytics to improve supply chain performance in logistics industry.

In Chapter “An Implementation of a System for Video Translation Using OCR,” Sun-Myung Hwang and Hee-Gyun Yeom develop an image translator that combines existing OCR technology and translation technology and verify its effectiveness. Before developing, we presented what functions are needed to implement this system and how to implement them, and then tested their performance.