Confidence Intervals for Policy Reforms in Behavioural Tax Microsimulation Modelling

This paper addresses the need for a measure of the uncertainty that is associated with the results calculated through tax policy behavioural microsimulation modelling. Deriving the analytical measure would be extremely complicated, therefore, a simulated approach is proposed which generates a pseudo sampling distribution of aggregate measures based on the sampling distribution of the estimated labour supply parameters. This approach, which is very computer intensive, is compared to a more time-efficient approach where the functional form of the sampling distribution is assumed to be normal. The results show that in many instances the results from the two approaches are quite similar. The exception is when aggregate measures for minor types of payments, involving relatively small groups of the population, are examined.

Application of Pre-fabricated Concrete Elements (PCE) in construction projects in Iran

Abstract: In recent decades, construction waste has become a serious environmental problem in many large cities around the globe. The construction sector in Tehran/Iran produced 50,000 tonnes of waste each day in 2010. Furthermore the growing young population, changing lifestyles and rising demand for housing increases the construction material consumption, hence generating more waste. Two main materials are used to construct buildings in Iran: steel and concrete. Various studies have exposed that use of PCE significantly decrease in the amount of waste production. This study aims to explore advantages, barriers, and potential improvement activities on PCE in Iran based on interviews and a questionnaire survey. Moreover, the three methods of concrete construction that are used in the Iranian, namely in-situ concrete, ready-mixed concrete and PCE have been examined. A case study in Tehran was used to illustrate the concrete waste generation and financial issues of these three concrete work methods. The results of questionnaires illustrate that the main advantages of applying PCE in Iran areon-site concrete waste reduction; improve environmental performance; and shorten project time. Moreover, the most significant hindrances are higher project costs; lack of legislation and regulations; limited manufacturers; and limited products. The findingsof the case study indicate that use of PCE has the most cost and the least on-site concrete waste than the other two methods. Finally, the most mentioned recommendation for improving use of PCE in Iran were governmental incentives for using PCE; and education and training

A model for spectroscopic food sample analysis using data sonification

Abstract: In this paper, we propose a method to generate an audio output based on spectroscopy data in order to discriminate two classes of data, based on the features of our spectral dataset. To do this, we first perform spectral pre-processing, and then extract features, followed by machine learning, for dimensionality reduction. The features are then mapped to the parameters of a sound synthesiser, as part of the audio processing, so as to generate audio samples in order to compute statistical results and identify important descriptors for the classification of the dataset. To optimise the process, we compare Amplitude Modulation (AM) and Frequency Modulation (FM) synthesis, as applied to two real-life datasets to evaluate the performance of sonification as a method for discriminating data. FM synthesis provides a higher subjective classification accuracy as compared with to AM synthesis. We then further compare the dimensionality reduction method of Principal Component Analysis (PCA) and Linear Discriminant Analysis in order to optimise our sonification algorithm. The results of classification accuracy using FM synthesis as the sound synthesiser and PCA as the dimensionality reduction method yields a mean classification accuracies of 93.81% and 88.57% for the coffee dataset and the fruit puree dataset respectively, and indicate that this spectroscopic analysis model is able to provide relevant information on the spectral data, and most importantly, is able to discriminate accurately between the two spectra and thus provides a complementary tool to supplement current methods

Investigation into the potential of rubberised concrete products

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