Data collection mechanism is a crucial factor for the performance of intrusion detection system (IDS). Simple random sampling and Stratified random sampling techniques of statistics are introduced to the procedure of data collection for IDS, and formulas used to calculate the sample size of packets based on these sampling techniques are presented. The implementation of packets sampling is provi...

a better understanding of rangeland vegetation cover and its variation in different years basedon wetness and droughtiness fluctuations is a great importance. economical priority setting ofrangelands is based on variations in rainfall and drought patterns, because it yields to bettercharacterization of vegetative cover. yet a comprehensive and continuous monitoring ofvegetative cover of rangela...

Although the random forest classification procedure works well in datasets with many features, when the number of features is huge and the percentage of truly informative features is small, such as with DNA microarray data, its performance tends to decline significantly. In such instances, the procedure can be improved by reducing the contribution of trees whose nodes are populated by non-infor...

I describe a simple procedure for investigating the convergence properties of Markov Chain Monte Carlo sampling schemes. The procedure employs multiple runs from a sampler, using the same random deviates for each run. When the sample paths from all sequences converge, it is argued that approximate equilibrium conditions hold. The procedure also provides a simple diagnostic for detecting modes i...

The purpose of this study is to determine whether sampling procedure affected children’s inferences about populations or samples or both. In two experiments children learned to predict the color of a toy from its shape. In the first experiment a deceptive or honest teacher sampled the toys, while the second contrasted random and non-random sampling (using a magnetic wand to select from a popula...