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Measures of inequality determine the effectiveness of social and economic policies aimed at reducing inequality and to design effective intervention policies. The purpose of this paper is to focus on poverty reduction and welfare improving impacts of reducing income inequality in the case of Fiji. Using Fiji's Household Income and Expenditure Survey 2002‐2003, a comprehensive analysis is used to measure the level of inequality by household income, quintile income distribution, decomposition of inequality by ethnicity and regional groups, and the household income inequality by source of income.

Several statistical techniques have been applied to investigate the degree of inequality in the household income. These include the Gini coefficient, the Nelson ratio, the concentration index and the Atkinson index. An evaluation by ethnicity, regions and household income sources reflects the level of inequality, and concerns for policies and governance.

The results show that urban households, in particular, experience greater inequalities, in both positive and normative terms. The Indo‐Fijian households experience greater income inequalities than the Fijian households. Decomposition results for the separate factor income components also indicate major sources of inequality. These findings clearly establish that Fiji still has a long way to go in reducing the income gaps between the rich and the poor in both rural and urban households.

The paper is a first study that estimates various measures of inequality in the case of Fiji. The implication of the empirical findings suggests that Fiji is unlikely to achieve its Millennium Development Goal of halving poverty rate by 2015 due to the large income differentials by ethnicity and in the urban‐rural areas.

The purpose of this paper is to predict and control the composition during laser additive manufacturing, since composition control is important for parts manufactured by laser additive manufacturing. Aluminum and steel functionally graded material (FGM) were manufactured by laser metal deposition, and the composition was analyzed by means of spectral analysis simultaneously.

The laser metal deposition process was carried out on a 5 mm thick 316L plate. Spectral line intensity ratio and plasma temperature were chosen as two main spectroscopic diagnosis parameters to predict the compositional variation. Single-trace single-layer experiments and single-trace multi-layer experiments were done, respectively, to test the feasibility of the spectral diagnosis method.

Experiment results showed that with the composition of metal powder changing from steel to aluminum, the spectral intensity ratio of the characteristic spectral line is proportional to the elemental content in the plasma. When the composition of deposition layers changed, the characteristic spectrum line intensity ratio changed obviously. And the linear chemical composition analysis results confirmed the gradient composition variation of the additive manufacturing parts. The results verified the feasibility of composition analysis based on spectral information in the laser additive manufacturing process.

The composition content of aluminum and steel FGM was diagnosed by spectral information during laser metal deposition, and the relationship between spectral intensity and composition was established.