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This study examines the role of financial development (FD) in enhancing the growth effect of foreign direct investment (FDI) in emerging and developing Asia from 1996 to 2019.

The study exploits the new broad-based Financial Development Index of the International Monetary Fund (IMF) and adopts panel smooth transition regression (PSTR) to perform alternative empirical models for a multidimensional analysis of the FD threshold effect in the growth–FDI nexus.

The results show two thresholds of FD mediating the nonlinear effect of FDI on growth. FD beyond a certain level will enhance the growth effect of FDI, but very high levels of FD will not induce foreign investment to benefit economic growth in emerging and developing Asian economies. The impact of financial institutions on the FDI–growth link is stronger than that of financial markets. Besides, FDI’s effect on growth has an inverted-U shape conditional on financial depth, whereas it is positively associated with the accessibility and efficiency of the financial system.

These results suggest policy implications for emerging and developing Asian countries, emphasizing the other side of “too much finance” and the potential for improvement in the access to and efficiency of the financial system to boost the effects of FDI and FD in the growth of these economies.

The study is the first multifaceted investigation into the influence of FD on the growth effect of FDI. Beyond the previous empirical evidence showing only the impact of credit from banking sector, this study shows different mediating effects of different financial sectors and three dimensions of financing (depth, access and efficiency). The study suggests essential implications for the region in adjusting long-run policies to enhance the FDI–FD–growth link.

The purpose of this study is to examine the effect of foreign direct investment (FDI) on economic growth contingent on the development level of the local financial system in emerging and developing Asia during the period 1996–2017.

The study adopts the threshold approach, namely the panel smooth transition regression (PSTR) model, for the annual data collection of 18 emerging and developing Asian countries in 22 years. The authors analyze the alternative PSTR models on different proxies of financial development (FD).

The results show new findings of two distinct thresholds of FD in the FDI–growth nexus. The growth-enhancing effect of FDI is realized only when the FD lies between the two threshold values. Notably, at very high levels of FD, the beneficial effect of FDI on growth is vanishing.

The authors provide new insights into the growth effect of FDI and the role of FD. The estimated nonlinear effect of FDI on growth and the thresholds of FD can be benchmarks for emerging and developing Asia in assessment of their situations. The results suggest important implications to the region in setting the long-run policies to boost the effect of FDI on economic growth.

The purpose of this paper is to propose an automatic pattern matching template generating method for the automatic optical inspection system in TFT LCD assembly and positioning process, to improve the conventional image technology. Besides, focusing on integrating the image system with the existing control system, the double aligner mark searching time is decreased to reduce the working time of the integrated system.

The improved pattern matching method of genetic algorithm was adopted, including setting for template image selecting, encoding, calculating fitness function, pattern matching, template generating and genetic algorithm steps. The predetermined pixels were selected from the target template based on the minimum difference to the block image to be tested by utilizing the genetic algorithm, and the other pixels which have not been selected were neglected.

The selected pixels were encoded for recording by sequence mode, and then the target template and the image to be tested were compared based on the calculated fitness function. This method has the advantages of using the fitness function to reduce the searching time, with the help of genetic algorithm to find the optimal target template, and saving memory space by recording target template based on the sequence mode.

The genetic algorithm used in this study is a kind of optimal tool free from gradient data. As long as the fitness function and after continuous iteration are determined, the optimal solution can be found out, and then the optimal target template can be generated.

This system uses fitness function to reduce the pattern matching time. Plural pixels are preset inside the target template, and its fitness function value is calculated. When the target template is compared with the image to be tested, only the fitness function value (also the difference of the plural pixels) is calculated and compared.

The remaining pixels are neglected, so that the searching time can be reduced greatly. The sequence mode is used to save the required memory space for recording target template. Since sequence mode is adopted to record the information of selected pixels, lots of required memory space for recording target template information will be saved.