Disponibilidade de boro e correlação com propriedades dos solos do estado do Rio de Janeiro

Com o objetivo de verificar as relações entre o boro (B) extraível e os teores de argila, carbono (C) e pH, foram determinados os conteúdos de B disponível em 103 amostras do horizonte superficial de solos do Estado do Rio de Janeiro, por colorimetria utilizando azomethina-H, após extração com água quente. Os teores de B variaram de 1,31 a 4,50 mg kg-1 de solo, com média de 2,43 + 0,67 mg kg-1. Os valores de correlação encontrados foram r = 0,29** no que tange a B e C orgânico, e r = 0,27** no tocante a B e argila. O maior valor de correlação foi verificado entre B e pH (r = -0,41**). Os conteúdos de argila e C orgânico influenciaram na disponibilidade de B

Steady State RF Fingerprinting for Identity Verification: One Class Classifier Versus Customized Ensemble

Mobile phone proliferation and increasing broadband penetration presents the possibility of placing small cellular base stations within homes to act as local access points. This can potentially lead to a very large increase in authentication requests hitting the centralized authentication infrastructure unless access is mediated at a lower protocol level. A study was carried out to examine the effectiveness of using Support Vector Machines to accurately identify if a mobile phone should be allowed access to a local cellular base station using differences imbued upon the signal as it passes through the analogue stages of its radio transmitter. Whilst allowing prohibited transmitters to gain access at the local level is undesirable and costly, denying service to a permitted transmitter is simply unacceptable. Two different learning approaches were employed, the first using One Class Classifiers (OCCs) and the second using customized ensemble classifiers. OCCs were found to perform poorly, with a true positive (TP) rate of only 50% (where TP refers to correctly identifying a permitted transmitter) and a true negative (TN) rate of 98% (where TN refers to correctly identifying a prohibited transmitter). The customized ensemble classifier approach was found to considerably outperform the OCCs with a 97% TP rate and an 80% TN rate