Abstract Solar activity affects the heliosphere in different ways. Variations particles and radiation that impact Earth’s atmosphere, climate, human activities often disruptive Consequently, ability to forecast solar across temporal scales is gaining increasing significance. In this study, we present predictions for cycle 25 of three indicators: core-to-wing ratio Mg II at 280 nm, radio flux 10...

This paper uses minute-by-minute British electricity demand observations to evaluate methods for prediction from 10 to 30 minutes ahead. Such very short lead times are important for the real-time scheduling of electricity generation. We consider methods designed to capture both the intraday and the intraweek seasonal cycles in the data, including ARIMA modelling, an adaptation of Holt-Winters e...

In today’s competitive market, production costs, lead time and optimal machine utilization are crucial values for companies. Since machine or process breakdowns severely limit their effectiveness, methods are needed to predict products’ life expectancy. Furthermore, continuous assessment and prediction of product’s performance could also enable a collaborative product life-cycle management in w...

although more than 98% of the human genome is transcribed, most of these transcripts are not translated into proteins. rather, they are considered as non-coding rnas. micrornas (mirnas) are very short non-coding rnas approximately 22 nucleotides in length which regulate many key processes of cells such as growth, proliferation, differentiation, cell cycle, apoptosis (programmed cell death) and ...

Abstract. The terrestrial carbon cycle plays a critical role in modulating the interactions of climate with Earth system, but different models often make vastly predictions its behavior. Efforts to reduce model uncertainty have commonly focused on structure, namely by introducing additional processes and increasing structural complexity. However, extent which increased complexity can directly i...

This paper introduces a new hardware-based machine learning building block – called Learning Classifier Table (LCT) – for the run-time reliability, performance and power optimization of future generations of Systems-on-Chip. LCT inherits concepts from the reinforcement learning techniques found in Learning Classifier Systems. Prediction weighted LCT rule evaluation is implemented on a clock cyc...

Cycle time optimization could be one of the great challenges in business process management. Although there is much research on this subject, task similarities have been paid little attention. In this paper, a new approach is proposed to optimize cycle time by minimizing entropy of work lists in resource allocation while keeping workloads balanced. The idea of the entropy of work lists comes fr...