The demand for cost-efficient forest aboveground biomass (AGB) prediction methods is growing worldwide. The National Land Survey of Finland (NLS) began collecting airborne laser scanning (ALS) data throughout Finland in 2008 to provide a new high-detailed terrain elevation model. Similar data sets are being collected in an increasing number of countries worldwide. These data sets offer great po...

The influence of long-range residue interactions on defining secondary structure in a protein has long been discussed and is often cited as the current limitation to accurate secondary structure prediction. There are several experimental examples where a local sequence alone is not sufficient to determine its secondary structure, but a comprehensive survey on a large data set has not yet been d...

In this paper we present mechanisms that improve the accuracy and performance of history-based branch prediction. By studying the characteristics of the decision structures present in high-level languages, two mechanisms are proposed that reduce the number of wrong predictions made by a branch target buer (BTB). Execution-driven modeling is used to evaluate the improvement in branch prediction ...

The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR) me...

Branch prediction is a key mechanism used to achieve high performance on multiple issue, deeply pipelined processors. By predicting the branch outcome at the instruction fetch stage of the pipeline, superscalar processors are better able to exploit Instruction Level Parallelism (ILP) by providing a larger window of instructions. However, when a branch is mispredicted, instructions from the misp...

MOTIVATION With complex traits and diseases having potential genetic contributions of thousands of genetic factors, and with current genotyping arrays consisting of millions of single nucleotide polymorphisms (SNPs), powerful high-dimensional statistical techniques are needed to comprehensively model the genetic variance. Machine learning techniques have many advantages including lack of parame...

Results are the most important factor in competitive sports. If we can scientifically predict race results, it is bound to become a research focus of the sports competitions. In this paper, we use the gray prediction method and neural network theory to establish two prediction results model. Numerical experiments show that the model has high prediction accuracy.

â  using of prediction models is one of the methods of financial performance prediction. financial ratios are employed as predictive variable in prediction models. the main purpose of this study is to compare the incremental information content of accrual and cash ratios for prediction and evaluation of the financial performance of business entities by data mining models. in align with research...