This paper presents a model for measuring intellectual capital (IC) within small and medium-sized enterprises (SMEs) in correlation with the key factors for the successful implementation of knowledge management (KM). Most of the existing IC measurement models are intended to cover general aspects. The kernel of these models could be customized/extended to handle more specific aspects, like KM. The focus of this study is the integration between an IC measurement model and the key factors for successful implementing of KM. The paper identifies, analyses and compares IC elements that are relevant for SMEs and how they can be linked with the IC measurement methods for determining if a company is ready for KM. For this purpose, a general IC measurement model is taken as reference for the study.

State of charge (SOC) is the equivalent of a fuel gauge for a battery pack in an electric vehicle. Determining the state of charge is thus particularly important for electric vehicles (EVs), hybrid EVs, or portable devices. The aim of this innovative study is to estimate the SOC of a high-capacity lithium iron phosphate (LiFePO₄) battery cell from an experimental dataset obtained in the University of Oviedo Battery Laboratory using the multivariate adaptive regression splines (MARS) technique. An accurate predictive model able to forecast the SOC in the short term is obtained and it is a first step using the MARS technique to estimate the SOC of batteries. The agreement of the MARS model with the experimental dataset confirmed the goodness of fit for a limited range of SOC (25-90% SOC) and for a simple dynamic data profile [constant-current (CC) constant-voltage charge-CC discharge].