China 
Africa 
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Applications and Architectures for Chaotic ICs: An Introduction
Published in M.P. Kennedy, R. Rovatti, G. Setti, Chaotic Electronics in Telecommunications, 2018
Angel Rodriguez-Vázquez, Manuel Delgado-Restituto, Rocío del Rio, Belén Pérez-Verdú
Another important distinction between both approaches arises from their suitability for VLSI implementations. Random signal generators based on the intrinsic noise of electronic devices presents three serious drawbacks for VLSI. First, very low power signals are obtained, thus requiring the use of large gain amplifiers. Second, it may produce spurious correlation in cases where multiple sources are needed. Third, appropriate sources may not be well suited for on-chip implementation in a given technology, thereby forcing the designer to consider off-chip components. On the other hand, the use a linear feedback shift registers is ideally suited for the VLSI generation of random signals, because of their structural simplicity, easy programmability and fast operation (current GaAs technologies allow digital processing well beyond the GHz range). Moreover, a single LFSR has the ability of generating multiple, arbitrarily shifted, linear maximal bit streams by tapping the outputs of selected memory stages and feeding the tapped responses through a set of exclusive-OR gates [63]. Thus, the LFSR approach offers the possibility of implementing multiple uncorrelated random sources with very small area overhead.
Introduction
Published in Jack J. Barry, Information Communication Technology and Poverty Alleviation, 2018
Finally, concluding this section on the causal claims in the literature, it is worth noting that a continuing difficulty faced by studies addressing whether or not ICTs are “actually” contributing to poverty is that many of the determinants of the digital divide are also determinants of poverty. Endogeneity and spurious correlation have proven difficult for large-n analysis to maneuver around with this topic. For instance, academic studies have found that there are many factors influencing the digital divide: disparities in income (Pohjola 2003); human capital (Dewan, Ganley, and Kraemer 2005); enforcement of regulations—state capacity issues (Guillen and Saurez 2005); and socio-political features (Beilok and Demitrova 2003). In fact, income is reported to explain around 90 percent of the variance in the digital divide in terms of access, both between countries and within them (Corrales and Westhoff 2006: 138). It is also clear from the literature that ICTs have the potential to help people move out of poverty, especially through causal mechanisms of enhancing different aspects of human development (e.g., education, health information—see Sachs 2005) and by providing new forms of information/communication exchange (e.g., mobile banking— Menon 2011). Also geographic/infrastructure concerns remain relevant, as does economic concentration, and emerging risks due to IT (the latter is a major claim of the World Bank’s Digital Dividends (2016)). Studies need to take these factors into account, however I posit that they should also consider the interactive impact of governance to understand the impact of ICTs on poverty. Hopefully, from the section above we can see the puzzle to solve emerge due to the extensive contradictory findings in the literature of the impact of ICTs, particularly the internet and mobile phones, on poverty over the last 25 years. Before concluding this chapter, the following section further addresses the important concept of the digital divide and how this book relates to it.
The influence of local market and household factors on aflatoxin presence in maize and symptoms of its exposure to children in Guatemala
Published in International Journal of Environmental Health Research, 2020
Lee E. Voth-Gaeddert, Matthew Stoker, Olga R. Torres, Daniel B. Oerther
Maize Storage and Post-Harvest Practices had statistically significant correlations with Observed Fungus. Maize Storage was negatively correlated with Observed Fungus suggesting that among households with improved storage practices, fungus was observed more often in the maize. This was counter to the original hypothesis. Potential explanations include; 1) an intricate relationship between the material used for maize storage and different types of species of fungal growth or 2) spurious correlation. Improved post-harvest practices for maize was correlated with a lower prevalence in observations of fungus among households, supporting the original hypothesis. Hell et al have reported correlations between several types of improved post-harvest practices and a reduction in aflatoxin presence (Hell et al. 2008). The three post-harvest practices used as indicators for this latent variable included the drying time of maize, the drying surface used, and the mechanisms used to remove maize kernels from the cob. These have been a focus for USAID in Central America and Sub-Saharan Africa.
Infrastructure investment and economic performance
Published in Journal of Mega Infrastructure & Sustainable Development, 2019
Although rates of return from infrastructure projects may be significant, they were inevitably exaggerated by early studies because of the high positive correlation with overall economic activity per se. Analysts must control for what econometricians call ‘severe simultaneity bias’ and ‘spurious correlation’. Once this has been done returns are considerably reduced, and this is even before environmental impacts and broader sustainability concerns are addressed. Put more simply, the benefits from infrastructure projects for society as a whole may indeed be significant in good times, but may provide little by way of economic comfort and protection when times are bad. Policy therefore needs to be more considered and informed, with investment decisions prioritised accordingly. Unfortunately, political systems across the globe invariably prioritise spending on infrastructure, be it by sector and/or spatially, for electoral advantage rather than the maximisation of community welfare. Whilst very few economists would argue that ‘good infrastructure’ (however this may be defined) does not enhance a country’s economic potential, it is more often than not the political process that leads to poor decision making in project selection and implementation, be it either to court short-term popularity in search of political favour, or acceptance and approval of inefficiencies and inequalities driven by political ideology rather than economic and sustainability imperatives.
A Conjugate Model for Dimensional Analysis
Published in Technometrics, 2018
Although practical successes of implementing DA in statistical problems prove DA to be a useful reduction methodology, the studies on appropriate statistical models customized to post-DA variables remain absent. As shown in the previous section, the potential issues in modeling would generate false inferences and predictions, if DA is treated as merely a preprocessing tool. In this section, we propose a DA conjugate family and an additive power-law model to resolve the issues. In this framework, it can be shown that the dimensional constraints can be represented by a set of linear constraints on the parameters, leading to a model that is (i) invariant to choices of basis quantities, (ii) easy to test dimensional constraints, and (iii) free from spurious correlation.