Ping Ji

TL;DR: In this paper, the authors compared the performance of Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) on the same set of container port data for the world's largest container ports and compared the results obtained.

TL;DR: This paper presents a comprehensive survey of the recent advances in activity recognition with smartphones' sensors, starting with the basic concepts such as sensors, activity types, etc and reviewing the core data mining techniques behind the main stream activity recognition algorithms.

TL;DR: In this paper, the authors apply DEA windows analysis to a sample of the world’s major container ports in order to deduce their relative efficiency, concluding that existing programming methods for estimating efficiency are inadequate in capturing the long-term increased efficiency and competitiveness that accrue from significant investments.

TL;DR: Two hybrid genetic algorithms (HGAs) are developed and it is proved that the performance of H GA2 is superior to that of HGA1 in terms of the total delivery time.

TL;DR: In this paper, the authors present the pros and cons of port privatization and provide an empirical examination of the relationship between privatization and relative efficiency within the container port industry, concluding with the rejection of the hypothesis that greater private sector involvement in the container ports sector irrevocably leads to improved efficiency.