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Predicting numeric ratings for Google apps using text features and ensemble learning
Umer, Muhammad,Ashraf, Imran,Mehmood, Arif,Ullah, Saleem,Choi, Gyu Sang Electronics and Telecommunications Research Instit 2021 ETRI Journal Vol.43 No.1
Application (app) ratings are feedback provided voluntarily by users and serve as important evaluation criteria for apps. However, these ratings can often be biased owing to insufficient or missing votes. Additionally, significant differences have been observed between numeric ratings and user reviews. This study aims to predict the numeric ratings of Google apps using machine learning classifiers. It exploits numeric app ratings provided by users as training data and returns authentic mobile app ratings by analyzing user reviews. An ensemble learning model is proposed for this purpose that considers term frequency/inverse document frequency (TF/IDF) features. Three TF/IDF features, including unigrams, bigrams, and trigrams, were used. The dataset was scraped from the Google Play store, extracting data from 14 different app categories. Biased and unbiased user ratings were discriminated using TextBlob analysis to formulate the ground truth, from which the classifier prediction accuracy was then evaluated. The results demonstrate the high potential for machine learning-based classifiers to predict authentic numeric ratings based on actual user reviews.
CO_2 geological storage: A review on present and future prospects
Umer Zahid,한종훈,임영섭,Jaeheum Jung 한국화학공학회 2011 Korean Journal of Chemical Engineering Vol.28 No.3
CO_2 can be stored in geological media for hundreds to thousands of years depending on the location and trapping mechanism(s) involved. A saline aquifer presents the largest capacity available for CO_2 storage among all geological storage options. Two main methodologies proposed by the Department of Energy, US (DOE) and carbon sequestration leadership forum (CSLF) are used for capacity estimation of geological locations for CO_2 storage. A study conducted by Global CCS Institute in 2010 identified 80 large scale integrated projects which will prove to be a huge step in building confidence and commercialization of storage projects in the near future. Use of reliable monitoring tools and accurate simulation software is a must for safe and cost-effective CO_2 storage.
Vibration Control of a Nuclear Fuel Rod Maneuvering Under Water
Umer Hameed Shah,Mingxu Piao,Gyoung-Hahn Kim,Keum-Shik Hong 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10
This paper addresses the vibration control problem of a fuel transport system (FTS) in a nuclear power plant. The FTS transports the fuel rods in the nuclear reactor to desired locations within the fuel building. The fuel rods must be transported under water to avoid radiation leaks into the environment. It has been observed that a quick maneuver of the trolley can cause vibrations that can damage the structure of the fuel rods, due to the hydrodynamic force exerted by the surrounding fluid. In this study, a distributed parameter model of the FTS, using the extended Hamilton’s principle, is developed. The developed model is verified with experiments. A velocity command is designed, as an open-loop control, to transport the fuel rods in quick time to the target locations with minimal vibrations. The residual vibrations of the fuel rod are controlled while considering the effects of the hydrodynamic force imposed by the surrounding water. Simulation and experimental results show that the proposed velocity command transports the fuel rods to the target location quickly resulting in a significant decrease in the rod’s vibrations.