This paper proposes a buffered dual-access-mode cache to reduce power consumption for highly-associative caches in modern embedded systems. The proposed scheme consists of a MRU (most recently used) buffer table and a single cache structure to implement two accessing modes, phased mode and way-prediction mode. The proposed scheme shows better access time and lower power consumption than two pop...

Artificial neural network was considered in previous studies for prediction of engine performance and emissions. ICA methodology was inspired in order to optimize the weights of multilayer perceptron (MLP) of artificial neural network so that closer estimation of output results can be achieved. Current paper aimed at prediction of engine power, soot, NOx, CO2, O2, and temperature with the ai...

We introduce Branch Predictor Prediction (BPP) as a power-aware branch prediction technique for high performance processors. Our predictor reduces branch prediction power dissipation by selectively turning on and off two of the three tables used in the combined branch predictor. BPP relies on a small buffer that stores the addresses and the sub-predictors used by the most recent branches execut...

Being able to predict self-generated sensory consequences is an important feature of normal brain functioning. In the auditory domain, self-generated sounds lead to smaller brain responses compared to externally generated sounds. Here we investigated the role of brain oscillations underlying this effect. With magnetoencephalography, we show that self-generated sounds are associated with increas...

Wind power prediction accuracy is important for assessing the security and economy when wind power is connected to the grid, and wind speed is the key factor. This article presents a future four hours prediction scheme that combined chaos phase space reconstruction with NWP method. Historical wind speed data are reconstructed as phase space vectors, which are used as the first input part of pre...

Genetic Analysis Workshop 18 provided a platform for evaluating genomic prediction power based on single-nucleotide polymorphisms from single-nucleotide polymorphism array data and sequencing data. Also, Genetic Analysis Workshop 18 provided a diverse pedigree structure to be explored in prediction. In this study, we attempted to combine pedigree information with single-nucleotide polymorphism ...

The development of the smart grid has resulted in new requirements for fault prediction of power transformers. This paper presents an entropy-based Bagging (E-Bagging) method for prediction of characteristic parameters related to power transformers faults. A parameter of comprehensive information entropy of sample data is brought forward to improve the resampling process of the E-Bagging method...

Power generation industry is the key industry of carbon dioxide (CO2) emission in China. Assessing its future CO2 emissions is of great significance to the formulation and implementation of energy saving and emission reduction policies. Based on the Stochastic Impacts by Regression on Population, Affluence and Technology model (STIRPAT), the influencing factors analysis model of CO2 emission of...