Distribution-Based Categorization of Classifier Transfer Learning

Transfer Learning (TL) aims to transfer knowledge acquired in one problem, the source problem, onto another problem, the target problem, dispensing with the bottom-up construction of the target model. Due to its relevance, TL has gained significant interest in the Machine Learning community since it paves the way to devise intelligent learning models that can easily be tailored to many different applications. As it is natural in a fast evolving area, a wide variety of TL methods, settings and nomenclature have been proposed so far. However, a wide range of works have been reporting different names for the same concepts. This concept and terminology mixture contribute however to obscure the TL field, hindering its proper consideration. In this paper we present a review of the literature on the majority of classification TL methods, and also a distribution-based categorization of TL with a common nomenclature suitable to classification problems. Under this perspective three main TL categories are presented, discussed and illustrated with examples

Marketing mix and new product diffusion models

In this paper we analyze the relationship between the marketing mix and new product diffusion models. The goal is to obtain a general new product diffusion model that incorporates the classic 4Ps model of the Marketing Mix: Product, Price, Place, Promotion. An empirical study was conducted using mobile broadband adoption data in Japan.info:eu-repo/semantics/publishedVersio

Ionic liquids and deep eutectic solvents for application in pharmaceutics

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Stacked Denoising Autoencoders and Transfer Learning for Immunogold Particles Detection and Recognition

In this paper we present a system for the detection of immunogold particles and a Transfer Learning (TL) framework for the recognition of these immunogold particles. Immunogold particles are part of a high-magnification method for the selective localization of biological molecules at the subcellular level only visible through Electron Microscopy. The number of immunogold particles in the cell walls allows the assessment of the differences in their compositions providing a tool to analise the quality of different plants. For its quantization one requires a laborious manual labeling (or annotation) of images containing hundreds of particles. The system that is proposed in this paper can leverage significantly the burden of this manual task. For particle detection we use a LoG filter coupled with a SDA. In order to improve the recognition, we also study the applicability of TL settings for immunogold recognition. TL reuses the learning model of a source problem on other datasets (target problems) containing particles of different sizes. The proposed system was developed to solve a particular problem on maize cells, namely to determine the composition of cell wall ingrowths in endosperm transfer cells. This novel dataset as well as the code for reproducing our experiments is made publicly available. We determined that the LoG detector alone attained more than 84\% of accuracy with the F-measure. Developing immunogold recognition with TL also provided superior performance when compared with the baseline models augmenting the accuracy rates by 10\%

Determination of polybrominated diphenyl ethers in water at ng/L level by a simple DLLME-GC-(EI) MS method

Dispersive liquid-liquid microextraction (DLLME) is an extraction procedure gaining popularity in the recent years due to the easiness of operation, high enrichment factors, low cost and low consumption of organic solvents. This extraction method, prior to gas chromatography with mass spectrometry detection (GC-MS), was optimized for the determination of polybrominated diphenyl ethers (PBDEs) in aqueous samples. These were extracted with chlorobenzene (extraction solvent) and acetonitrile (dispersive solvent), allowing an enrichment factor of about 470 for BDE-100. The calibration curve for BDE-100 was linear in the range of 0.005-10 mu g/L, with an average reproducibility of 12% (RSD, %). The LOD, calculated by the signal-tonoise ratio, was 0.5 ng/L for BDE-100 and the recovery ranged from 91-107% for all spiked samples. Relative expanded uncertainty was concentration-dependent, reaching high values near the limit of quantification and decreasing until 14% for concentrations higher than 1 mu g/L of BDE-100. The dispersive liquid-liquid microextraction combined with gas chromatography with mass spectrometry detection (DLLME-GC-MS) method could be successfully applied to the determination of other PBDEs in water samples

Ensaios triaxiais cíclicos na caracterização mecânica de agregados britados: metodologias AASHTO e CEN

Os agregados britados de granulometria extensa continuam a ser frequentemente utilizados nas camadas não ligadas de pavimentos rodoviários Portugueses, nomeadamente em sub-base e base granulares. O comportamento destes materiais naquele tipo de camadas, apesar de alguns estudos já realizados nesse sentido, não se encontra ainda suficientemente caracterizado, sobretudo por razões que se prendem com a heterogeneidade dos maciços donde são provenientes. Sendo estes materiais de especial importância para a tecnologia de pavimentos Portuguesa e por forma a tentar contribuir para um mais aprofundado conhecimento dos mesmos foram desenvolvidas duas teses de Doutoramento, na Universidade de Coimbra e no Instituto Superior Técnico, que, utilizando diferentes metodologias de ensaio, tiveram como principal objectivo a caracterização mecânica e a elaboração de modelos típicos de comportamento para materiais britados não tratados. Basicamente, em ambos os trabalhos procedeu-se, para além da caracterização geotécnica, à caracterização do comportamento mecânico do material em laboratório, recorrendo a ensaios triaxiais cíclicos, realizados segundo dois procedimentos distintos. Nesta comunicação apresentam-se os resultados encontrados, nomeadamente no que respeita à modelação dos resultados dos ensaios triaxiais cíclicos, segundo as duas metodologias de ensaio, incluindo o modelo que, segundo os trabalhos, melhor traduz o comportamento mecânico daqueles materiais portugueses. Por fim, faz-se uma breve comparação entre as duas metodologias de ensaio e avalia-se a sua influência no módulo resiliente dos materiais

Perfluorodecalin/hydrocarbon systems prediction and correlation of liquid-liquid equilibrium data

Experimental binary, ternary and quaternary liquid-liquid equilibrium data for systems containing perfluorodecaline (PFD) and some hydrocarbons were determined. Binary NRTL, UNIQUAC and UNIFAC parameters were obtained, from the binary, the ternary and the quaternary experimental data: for the calculation of parameters from binary data a Newton-Raphson technique was used and the parameters so obtainedfor each temperature (T)-were linearly correlated with T and 1/T. Predicted binary, ternary and quaternary data were then compared with the experimental results; a Nelder-Mead method was used for the calculation of the binary parameters from ternary tie-line data. UNIFAC group parameters for the interaction CH2/CF2 and CH=CH2/CF2 were obtained. Attempts were made, and are discussed, to: correlate UNIFAC parameters with the number of carbon atoms and temperature; obtain a set of NRTL and UNIQUAC parameters yielding the overall best fit for the systems under consideration

Liquid-liquid equilibria of systems containing perfluoromethylcyclohexane

Liquidliquid equilibria for the quaternary system perfluoromethylcyclohexane (PFMCH)1-heptenen-heptanen-hexane at 288.15 K and for the ternary systems PFMCH1-heptenen-heptane, PFMCH1-heptenen-hexane and PFMCHn-heptanen-hexane at 279.15 K and 288.15 K are reported. The experimental results are compared with predicted values calculated using the NRTL and the UNIQUAC models