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Articles 1 - 6 of 6
Full-Text Articles in Physical Sciences and Mathematics
Neural Network Prediction Of Electromagnetic Field Strength In Hybrid Micro-Grid System, Ahmed Haidar, Ibrahim Ahmed, Ahmed Abdalla
Neural Network Prediction Of Electromagnetic Field Strength In Hybrid Micro-Grid System, Ahmed Haidar, Ibrahim Ahmed, Ahmed Abdalla
Dr Ahmed Mohamed Ahmed Haidar
Location of any Hybrid Micro-Grid System requires efficiently prediction of the electromagnetic field strength. This study proposes a novel Electromagnetic Field Strength (EFS) predication based on Probabilistic Neural Network (PNN). Learning data sets have been generated using Electromagnetic Transients Program EMTP. The PNN model has three input nodes representing the Switching Distance, Busbar Interference Voltage and Current waveforms, the output node representing the EFS. Testing datasets have deliberately been chosen outside the region of the learning datasets so as to check the performance of the neural network. The results indicate that the proposed technique can be used successfully to detect …
Computing Resource Prediction For Mapreduce Applications Using Decision Tree, Jing Piao, Jun Yan
Computing Resource Prediction For Mapreduce Applications Using Decision Tree, Jing Piao, Jun Yan
Dr Jun Yan
The cloud computing paradigm offer users access to computing resource in a pay-as-you-go manner. However, to both cloud computing vendors and users, it is a challenge to predict how much resource is needed to run an application in a cloud at a required level of quality. This research focuses on developing a model to predict the computing resource consumption of MapReduce applications in the cloud computing environment. Based on the Classified and Regression Tree (CART), the proposed approach derives knowledge of the relationship among the application features, quality of service, and amount of computing resource, from a small training. The …
Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin
Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin
Associate Professor Yan-Xia Lin
No abstract provided.
The Probability Distribution Of Distance Tss-Tls Is Organism Characteristic And Can Be Used For Promoter Prediction, Yun Dai, Ren Zhang, Yan-Xia Lin
The Probability Distribution Of Distance Tss-Tls Is Organism Characteristic And Can Be Used For Promoter Prediction, Yun Dai, Ren Zhang, Yan-Xia Lin
Associate Professor Yan-Xia Lin
Transcription is a complicated process which involves the interactions of promoter cis-elements with multiple trans-protein factors. The specific interactions rely not only on the specific sequence recognition between the cis- and trans-factors but also on certain spatial arrangement of the factors in a complex. The relative positioning of involved cis-elements provides the framework for such a spatial arrangement. The distance distribution between gene transcription and translation start sites (TSS-TLS) is the subject of the present study to test an assumption that over evolution, the TSS-TLS distance becomes a distinct character for a given organism. Four representative organisms (Escherichia cloi, Saccharomyces …
On Spatial Prediction Of Soil Properties In The Presence Of A Spatial Trend: The Empirical Best Linear Unbiased Predictor (E-Blup) With Reml, R Lark, B Cullis, S Welham
On Spatial Prediction Of Soil Properties In The Presence Of A Spatial Trend: The Empirical Best Linear Unbiased Predictor (E-Blup) With Reml, R Lark, B Cullis, S Welham
Professor Brian Cullis
Geostatistical estimates of a soil property by kriging are equivalent to the best linear unbiased predictions (BLUPs). Universal kriging is BLUP with a fixed-effect model that is some linear function of spatial coordinates, or more generally a linear function of some other secondary predictor variable when it is called kriging with external drift. A problem in universal kriging is to find a spatial variance model for the random variation, since empirical variograms estimated from the data by method-of-moments will be affected by both the random variation and that variation represented by the fixed effects. The geostatistical model of spatial variation …
Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin
Improving Promoter Prediction For The Nnpp2.2 Algorithm: A Case Study Using Escherichia Coli Dna Sequences, Ren Zhang, Alexandra Burden, Yan-Xia Lin
Alexandra Burden, Lecturer, School of Mathematics and Applied Statistics, Faculty of Informatics
No abstract provided.