332 research outputs found
Hadoop Performance Analysis Model with Deep Data Locality
Background: Hadoop has become the base framework on the big data system via the simple concept that moving computation is cheaper than moving data. Hadoop increases a data locality in the Hadoop Distributed File System (HDFS) to improve the performance of the system. The network traffic among nodes in the big data system is reduced by increasing a data-local on the machine. Traditional research increased the data-local on one of the MapReduce stages to increase the Hadoop performance. However, there is currently no mathematical performance model for the data locality on the Hadoop. Methods: This study made the Hadoop performance analysis model with data locality for analyzing the entire process of MapReduce. In this paper, the data locality concept on the map stage and shuffle stage was explained. Also, this research showed how to apply the Hadoop performance analysis model to increase the performance of the Hadoop system by making the deep data locality. Results: This research proved the deep data locality for increasing performance of Hadoop via three tests, such as, a simulation base test, a cloud test and a physical test. According to the test, the authors improved the Hadoop system by over 34% by using the deep data locality. Conclusions: The deep data locality improved the Hadoop performance by reducing the data movement in HDFS
A Consumer Level Simulation Model For Demand Response Analysis On Smart Grid
With the growing awareness of the need for Smart Grid, various countries are taking initiatives for developing Smart Grid.
However, there is limited research on utilizing Smart Grid for Demand-Response (DR).
This study advances the current system of DR by creating a Smart Grid Simulator that allows an intuitive demand response analysis.
The simulator demonstrates that substantial amount of electric power can be reduced efficiently by selective demand control over Smart Grid.
The graphical interface allows generating the electrical usage data and displays both individual and aggregate usage data over time.
This research employs U.S. census data for accurate estimate of family and life style as electric power usage is simulated by taking various inputs including the number of houses, family size, work and life patterns, etc.
This study explores potential Privacy issues in Smart Grid and suggests data anonymization as a viable solution for preventing them.
Moreover, this study proposes directions for future research on electric devices control using Smart Grid Simulator
A validation study on the insertion depth ranges of the five phase points by using musculoskeletal ultrasound: A pilot study
SummaryObjectivesWe conducted preliminary research to validate the insertion depth ranges of the five phase points by using ultrasonography.Design and settingThe insertion depth ranges of the five phase points were investigated by reviewing acupuncture and moxibustion literature. The following lengths were measured in centimetres in order to substitute B-cun values with centimetre values: the distance from the cubital crease to the palmar crease, from the inferior border of the medial tibia condyle to the medial malleolus, and from the popliteal crease to the prominence of the lateral malleolus. The five phase points were represented by pen marks on the skin, per the World Health Organization acupuncture point specifications. The anatomical structures of the five phase points within the insertion depth ranges were observed using colour Doppler ultrasound.ResultsThe five phase points for which the insertion depth ranges needed to be modified were LU11, HT9, PC9, LI1, LI2, SI1, SI2, TE1, ST45, BL66, GB44, SP1, SP2, LR1, and BL67. The five phase points that required careful insertion of acupuncture needles were LU8, LU9, LU10, LI5, ST36, ST41, SP3, HT4, HT7, HT8, SI3, SI8, BL40, KI2, KI3, KI10, KI27, GB34, GB38, LR3, and LR4.ConclusionThis preliminary study provided evidence on the insertion depths in acupuncture treatment. To generate more concrete evidence regarding insertion depths, further research should be conducted in a participant group with more diverse body mass index (BMI) values by using acupoint-specific ultrasonography transducers that can measure the acupoints properly
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