The economics of renewable energy expansion in rural Sub-Saharan Africa

Accelerating development in Sub-Saharan Africa will require massive expansion of access to electricity—currently reaching only about one third of households. This paper explores how essential economic development might be reconciled with the need to keep carbon emissions in check. We develop a geographically explicit framework and use spatial modeling and cost estimates from recent engineering studies to determine where stand-alone renewable energy generation is a cost effective alternative to centralized grid supply. Our results suggest that decentralized renewable energy will likely play an important role in expanding rural energy access. However, it will be the lowest cost option for a minority of households in Africa, even when likely cost reductions over the next 20 years are considered. Decentralized renewables are competitive mostly in remote and rural areas, while grid connected supply dominates denser areas where the majority of households reside. These findings underscore the need to decarbonize the fuel mix for centralized power generation as it expands in Africa.     

Effect of gallium grading in Cu(In,Ga)Se2 solar-cell absorbers produced by multi-stage coevaporation

We investigate Cu(In,Ga)Se₂ thin films grown in multi-stage coevaporation processes and solar cells fabricated from such absorbers. Despite some interdiffusion during film growth, Ga/(Ga+In) gradients defined via evaporation-profile variations in the process are to a good part retained in the finished film. This indicates that the bandgap can be engineered in this type of process by varying the evaporation profiles, and consequently also that unintended profile variations should be noted and avoided. With front-side gradients the topmost part of many grains seems to be affected by a higher density of lattice defects due to the strong change of gallium content under copper-poor growth conditions. Electrically, both back-side gradients and moderate front-side gradients are shown to yield an improvement of device efficiency. If a front-side gradient is too wide, though, it causes strong voltage-dependent collection and the fill factor is severely reduced.     

Classifying vocational training markets

The German educational system is characterized by a large sector of dual vocational training, which facilitates integration into the labour market. This system creates a specific training market for school leavers, which is characterized by strong regional disparities. These differences as well as their consequences have not been systematically analysed in previous research. In a theory-guided analysis this paper examines empirically which structural ‘handicaps’ affect regional transition rates from school to training and how regional training markets may be classified according to these structural factors. To this end, a new method is applied which combines regression and cluster analysis to avoid arbitrariness in the selection of classification variables. It generates a well-interpretable classification of vocational education markets, which is of broad use in research and labour market policy. The method may be applied to solve a broad variety of similar research problems in regional science.     

Systematic literature review of the objectives,techniques, kinds,and architectures of models at runtime

In the context of software development, models provide an abstract representation of a software system or a part of it. In the software development process, they are primarily used for documentation and communication purposes in analysis, design, and implementation activities. Model-Driven Engineering (MDE) further increases the importance of models, as in MDE models are not only used for documentation and communication, but as central artefacts of the software development process. Various recent research approaches take the idea of using models as central artefacts one step further by using models at runtime to cope with dynamic aspects of ever-changing software and its environment. In this article, we analyze the usage of models at runtime in the existing research literature using the Systematic Literature Review (SLR) research method. The main goals of our SLR are building a common classification and surveying the existing approaches in terms of objectives, techniques, architectures, and kinds of models used in these approaches. The contribution of this article is to provide an overview and classification of current research approaches using models at runtime and to identify research areas not covered by models at runtime so far.     

Analytical read back signal modeling in magnetic recording

An analytical model for the read back signal is derived for perpendicular and longitudinal magnetic recording. The model captures the contribution of a single bit rather than the contribution of a bit transition which makes it applicable to patterned media as well as continuous media. It is based on the law of Biot?CSavart and separates the contribution of the magnetic media from the head sensitivity function.     

Counting critical formations on the circle: algebraic–geometric and Morse-theoretic bounds

In this work, we analyze the critical points of potential functions on the torus arising in decentralized formation shape control of multiagent systems on the unit circle. A rotation symmetry of the potential function allows to reduce the analysis to a reduced function on a lower-dimensional torus. We show that these reduced potential functions are generically Morse functions. Lower bounds on the number of critical points of the reduced potential are obtained by Morse-theoretic arguments. For trees, precise information on the number of critical points is obtained. We use algebraic–geometric methods to determine upper bounds on the number of critical points of the reduced potentials. Our approach is applicable both to standard formation control potential functions and potential functions arising from the Kuramoto model of coupled oscillators with identical natural frequencies.     

Local ICA for multivariate statistical fault diagnosis in systems with unknown signal and error distributions

Based on a noncausal data structure, this article develops a statistical‐based monitoring scheme for diagnosing abnormal situations in complex systems. The recorded variables are assumed to exhibit Gaussian and non‐Gaussian signal components, which are monitored using the statistical local approach. For diagnosing abnormal conditions, the paper introduces a regression‐based technique that allows estimating the fault contribution from abnormal operating conditions. Application studies involving a simulation example and the analysis of recorded data from an industrial melter process demonstrate that the proposed diagnosis scheme is more sensitive in analyzing incipient fault conditions than existing approaches discussed in the literature. © 2011 American Institute of Chemical Engineers AIChE J, 58: 2357–2372, 2012     

Quantization analysis and enhancement of a VLSI gradient-based motion estimation architecture

Despite more than 40 years of research, motion estimation is still considered an emerging field, a field especially relevant today because of its vast utility for real-world applications. Currently, even the best bio-inspired algorithms lack certain characteristics that are readily found, for example, naturally in, say, mammals. Furthermore, the vast computational resources required are not usually affordable in real-time application. We present here a useful framework for building bio-inspired systems in real-time environments, reducing computational complexity. A complete quantization study of neuromorphic robust optical flow architecture is performed, using properties found in the cortical motion pathway. This architecture is designed for VLSI systems. An extensive analysis is performed to avoid compromising the viability and the robustness of the final system. A set of simulations and techniques that can be helpful for designing real-time artificial vision embedded systems and, specifically, gradient-based optical flow systems is shown. This work includes the final error results, resource usage, and performance data.     

Improvements of constraint programming and hybrid methods for scheduling of tests on vehicle prototypes

In the automotive industry, a manufacturer must perform several hundreds of tests on prototypes of a vehicle before starting its mass production. Tests must be allocated to suitable prototypes and ordered to satisfy temporal constraints and various kinds of test dependencies. The manufacturer aims to minimize the number of prototypes required. We present improvements of constraint programming (CP) and hybrid approaches to effectively solve random instances from an existing benchmark. CP mostly achieves better solutions than the previous heuristic technique and genetic algorithm. We also provide customized search schemes to enhance the performance of general search algorithms. The hybrid approach applies mixed integer linear programming (MILP) to solve the planning part and CP to find the complete schedule. We consider several logical principles such that the MILP model can accurately estimate the prototype demand, while its size particularly for large instances does not exceed memory capacity. Moreover, the robustness is alleviated when we allow CP to partially change the allocation obtained from the MILP model. The hybrid method can contribute to optimal solutions in some instances.     

Lipase‐catalyzed transesterification to remove saturated MAG from biodiesel

Saturated MAG (SMG) are known to be present in FAME intended to be used as biodiesel. These SMG can strongly affect the properties of biofuels such as the cloud point (CP), and they have been implicated in engine failure due to filter plugging. It is shown here that lipase G from Penicillium camemberti can be efficiently used for the transesterification of SMG to fatty acid methyl ester and glycerol even in the presence of the bulk biodiesel. Thus, in samples of commercial biodiesel to which glycerol monostearate (GMS) and glycerol monopalmitate (GMP) had been added, their levels were enzymatically reduced from 2% (w/v) to 0.22% (w/v) for GMP and 0.14% (w/v) for GMS as confirmed by GC‐MS analysis. Practical applications: SMG present in biodiesel can have a pronounced negative effect on the CP, and/or filterability and in‐field performance of the fuel. The lipase‐catalyzed transesterification shown in this paper enables a significant reduction in the amount of SMG, leading to superior biodiesel quality.