Optimization of silicon solar cell fabrication based on neural network and genetic programming modeling

This study describes techniques for the cascade modeling and the optimization that are required to conduct the simulator-based process optimization of solar cell fabrication. Two modeling approaches, neural networks and genetic programming, are employed to model the crucial relation for the consecutively connected two processes in solar cell fabrication. One model (Model 1) is used to map the five inputs (time, amount of nitrogen and DI water in surface texturing and temperature and time in emitter diffusion) to the two outputs (reflectance and sheet resistance) of the first process. The other model (Model 2) is used to connect the two inputs (reflectance and sheet resistance) to the one output (efficiency) of the second process. After modeling of the two processes, genetic algorithms and particle swarm optimization were applied to search for the optimal recipe. In the first optimization stage, we searched for the optimal reflectance and sheet resistance that can provide the best efficiency in the fabrication process. The optimized reflectance and sheet resistance found by the particle swarm optimization were better than those found by the genetic algorithm. In the second optimization stage, the five input parameters were searched by using the reflectance and sheet resistance values obtained in the first stage. The found five variables such as the texturing time, amount of nitrogen, DI water, diffusion time, and temperature are used as a recipe for the solar cell fabrication. The amount of nitrogen, DI water, and diffusion time in the optimized recipes showed considerable differences according to the modeling approaches. More importantly, repeated applications of particle swarm optimization yielded process conditions with smaller variations, implying greater consistency in recipe generation.     

Distribution-preserving statistical disclosure limitation

One approach to limiting disclosure risk in public-use microdata is to release multiply-imputed, partially synthetic data sets. These are data on actual respondents, but with confidential data replaced by multiply-imputed synthetic values. A mis-specified imputation model can invalidate inferences based on the partially synthetic data, because the imputation model determines the distribution of synthetic values. We present a practical method to generate synthetic values when the imputer has only limited information about the true data generating process. We combine a simple imputation model (such as regression) with density-based transformations that preserve the distribution of the confidential data, up to sampling error, on specified subdomains. We demonstrate through simulations and a large scale application that our approach preserves important statistical properties of the confidential data, including higher moments, with low disclosure risk.     

Silver Bullet Talks with Ed Amoroso

Gary McGraw interviews Ed Amoroso, AT&T's chief information security officer. Their conversation ranged widely, from system design to privacy.     

Vortex dynamics at the superfluid λ-transition

A vortex-ring theory of the superfluid⁴He -transition is extended to include the dynamics of the transition. The response of the vortices to an oscillating superflow is found by solving the Fokker-Planck equation. This allows a calculation of the superfluid relaxation time, which is in agreement with Landau-Khalatnikov theory and with dynamic scaling. At high frequencies the transition becomes broadened, with both the superfluid density and the dissipation remaining finite at and above T. Comparison is made to earlier theories that use high-temperature expansions and renormalization-group expansions. Applications to other subjects such as mutual friction, high-T_c superconductors, and rapidly quenched systems are briefly discussed.     

Fabrication process of open surfaces by robotic fibre placement

Composite materials are being used extensively in many industrial sectors. They offer excellent material properties compared to other structural materials available. However, the traditional fabrication process using manual hand lay-up is time consuming and labour intensive. Therefore, robotic fibre placement has been introduced to overcome these drawbacks. This approach may greatly reduce cycle time and manufacturing costs. This paper describes the overall strategy for the establishment of a flexible robotic fibre placement technique. The fabrication process planning of this new technique is presented. Three different types of fibre placement for open surfaces are discussed. These include simulation-based fibre path generation, fibre steering, and sensory-based contour following methodologies. The system architecture for the process control is also presented.     

Human SMILE-Derived Stromal Lenticule Scaffold for Regenerative Therapy: Review and Perspectives

A transparent cornea is paramount for vision. Corneal opacity is one of the leading causes of blindness. Although conventional corneal transplantation has been successful in recovering patients’ vision, the outcomes are challenged by a global lack of donor tissue availability. Bioengineered corneal tissues are gaining momentum as a new source for corneal wound healing and scar management. Extracellular matrix (ECM)-scaffold-based engineering offers a new perspective on corneal regenerative medicine. Ultrathin stromal laminar tissues obtained from lenticule-based refractive correction procedures, such as SMall Incision Lenticule Extraction (SMILE), are an accessible and novel source of collagen-rich ECM scaffolds with high mechanical strength, biocompatibility, and transparency. After customization (including decellularization), these lenticules can serve as an acellular scaffold niche to repopulate cells, including stromal keratocytes and stem cells, with functional phenotypes. The intrastromal transplantation of these cell/tissue composites can regenerate native-like corneal stromal tissue and restore corneal transparency. This review highlights the current status of ECM-scaffold-based engineering with cells, along with the development of drug and growth factor delivery systems, and elucidates the potential uses of stromal lenticule scaffolds in regenerative therapeutics.     

My personal history in the early explorations of computer graphics

Gary Demos discovered computer graphics while hearing a computer-generated film presentation at CalTech in 1970 by John Whitney Sr. Gary then began working under the direction of Ivan Sutherland in Utah to develop early computer graphics hardware and software. In 1974 Gary and John Whitney Jr. started the “Motion Picture Project” at Information International to produce computer generated simulated scenes for movies (Futureworld, Looker, and Tron) and commercials. These early computer-generated visuals were quite challenging given the level of software and hardware technology available in the 1970’s. In 1981 Gary and John left Information International to form Digital Productions, where they produced effects for the movies Last Starfighter and “2010”, which were both released in 1984. Digital Productions used the Cray XMP computer, together with the Digital Film Printer that they had developed at Information International. Following a hostile takeover by Omibus of Digital Productions in 1986, Whitney/Demos Productions was formed, using a Thinking Machine parallel computer. This paper describes the technical challenges and achievements of this early visual computing.     

Genetic subsets regression

Subset regression procedures have been shown to provide better overall performance than stepwise regression procedures. However, due to the combinatorial nature of evaluating each potential subset, subset regression techniques are costly to use. To resolve this difficulty, the use of a simple genetic algorithm (GA) is proposed to reduce the number of subsets which must be evaluated. Any of a number of popular criteria, including Mallows' C_p, MSE, R², AIC, etc., can be used to drive the search strategy associated with the use of the GA. Several illustrated examples on its use are provided.     

Supporting Scientific Collaboration: Methods, Tools and Concepts

This paper discusses the interrelationship between e-Science and CSCW in terms of key substantive, methodological and conceptual innovations made in both fields. In so doing, we hope to draw out the existing relationship between CSCW and e-Science research, and to map out some key future challenges where the two areas of research may become more closely aligned. In considering what may be required to draw the two more closely together, the paper focuses primarily on investigations that have been undertaken in two dedicated initiatives into e-Science, along with the key issues emerging from these studies.     

Enterprise Performance Management: Making it Work

Abstract

Enterprise performance management (EPM) is the integration of control and improvement methods imbedded with analytics. Its methods include the strategy map, balanced scorecards, costing (including activity based cost management), budgeting, forecasting and resource capacity requirements planning. These methods fuel other core solutions such as customer relationship management (CRM), supply chain management (SCM), risk management, and human capital management systems, as well as lean management and Six Sigma initiatives.