Dipeshkumar R. Sonaviya^*, Bhaven N. Tandel

Sound & Vibration, Vol.55, No.1, pp. 57-68, 2021, DOI:10.32604/sv.2021.010715 - 19 January 2021

Abstract Road traffic noise pollution has been recognized as a serious issue which affects human health as well as affects urban regions. Noise maps are very beneficial to identify the impact of noise pollution. A noise mapping study performed to study the propagation of noise in tier-II city along with field measurements. The noise maps are developed using a computer simulation model (SoundPLAN essential 4.0 software). The noise prediction models like U.K’s CoRTN, Germany’s RLS-90, and their modified versions, which can be used for homogenous road traffic conditions, cannot be successfully applied in heterogeneous road traffic… More >

Mohammad Aldossary^*

Computer Systems Science and Engineering, Vol.36, No.2, pp. 353-368, 2021, DOI:10.32604/csse.2021.014974 - 05 January 2021

Abstract With the expansion of cloud computing, optimizing the energy efficiency and cost of the cloud paradigm is considered significantly important, since it directly affects providers’ revenue and customers’ payment. Thus, providing prediction information of the cloud services can be very beneficial for the service providers, as they need to carefully predict their business growths and efficiently manage their resources. To optimize the use of cloud services, predictive mechanisms can be applied to improve resource utilization and reduce energy-related costs. However, such mechanisms need to be provided with energy awareness not only at the level of More >

Satoshi Minamoto*, Takuya Kadohira, Kaita Ito, Makoto Watanabe, Masahiko Demura

The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.2, pp. 136-136, 2019, DOI:10.32604/icces.2019.05447

Abstract The Materials Integration (MI) System is a domestically developed system in the “Cross-ministerial Strategic Innovation Promotion Program” to analyze structural materials performance. The performance on structural materials having complicated inputs/outputs would be solved with the combination of different scientific programs or data from experiment. One of the merits of constructing a combined model (here we call workflow) is that calculations are performed and the data would be stored in the system automatically.
Furthermore, we developed a web application (“MIREA”: MI REgression Analyzer) that enables us to build high versatile prediction models based on machine learning… More >

Pierre I. Karakiewicz^1,2, Felix K.-H. Chun^2,3, Alberto Briganti², Paul Perrotte¹, Michael McCormack¹, François Bénard¹, Luc Valiquette¹, Markus Graefen³, Fred Saad¹

Canadian Journal of Urology, Vol.13, Suppl.2, pp. 18-25, 2006

Abstract Introduction: Several nomograms have been developed to predict PCa related outcomes. Neural networks represent an alternative.
Methods: We provide a descriptive and an analytic comparison of nomograms and neural networks, with focus on PCa detection.
Results: Our results indicate that nomograms have several advantages that distinguish them from neural networks. These are both quantitative and qualitative.
Conclusion: In the field of PCa detection, nomograms appear to outweigh the benefits of neural networks. However, the neural network methodology represents a valid alternative, which should not be underestimated. More >