Free-Form Sketching of Self-Occluding Objects

When 3D objects occlude each other or self-occlude, their drawings typically consist of a set of contours that might partially overlap or self-overlap. The authors' method infers the hidden parts of contours and creates a smooth 3D shape matching those contours by solving a set of optimization problems     

Minimal Unroll Factor for Code Generation of Software Pipelining

We address the problem of generating compact code from software pipelined loops. Although software pipelining is a powerful technique to extract fine-grain parallelism, it generates lifetime intervals spanning multiple loop iterations. These intervals require periodic register allocation (also called variable expansion), which in turn yields a code generation challenge. We are looking for the minimal unrolling factor enabling the periodic register allocation of software pipelined kernels. This challenge is generally addressed through one of: (1) hardware support in the form of rotating register files, which solve the unrolling problem but are expensive in hardware; (2) register renaming by inserting register moves, which increase the number of operations in the loop, and may damage the schedule of the software pipeline and reduce throughput; (3) post-pass loop unrolling that does not compromise throughput but often leads to impractical code growth. The latter approach relies on the proof that MAXLIVE registers (maximal number of values simultaneously alive) are sufficient for periodic register allocation (Eisenbeis et al. in PACT ’95: Proceedings of the IFIP WG10.3 working conference on Parallel Architectures and Compilation Techniques, pages 264–267, Manchester, UK, 1995; Hendren et al. in CC ’92: Proceedings of the 4th International Conference on Compiler Construction, pages 176–191, London, UK, 1992). However, the best existing heuristic for controlling this code growth—modulo variable expansion (Lam in SIGPLAN Not 23(7):318–328, 1988)—may not apply the correct amount of loop unrolling to guarantee that MAXLIVE registers are enough, which may result in register spills Eisenbeis et al. in PACT ’95: Proceedings of the IFIP WG10.3 working conference on Parallel Architectures and Compilation Techniques, pages 264–267, Manchester, UK, 1995. This paper presents our research results on the open problem of minimal loop unrolling, allowing a software-only code generation that does not trade the optimality of the initiation interval (II) for the compactness of the generated code. Our novel idea is to use the remaining free registers after periodic register allocation to relax the constraints on register reuse. The problem of minimal loop unrolling arises either before or after software pipelining, either with a single or with multiple register types (classes). We provide a formal problem definition for each scenario, and we propose and study a dedicated algorithm for each problem. Our solutions are implemented within an industrial-strength compiler for a VLIW embedded processor from STMicroelectronics, and validated on multiple benchmarks suites.     

High-dimensional MRI data analysis using a large-scale manifold learning approach

A novel manifold learning approach is presented to efficiently identify low-dimensional structures embedded in high-dimensional MRI data sets. These low-dimensional structures, known as manifolds, are used in this study for predicting brain tumor progression. The data sets consist of a series of high-dimensional MRI scans for four patients with tumor and progressed regions identified. We attempt to classify tumor, progressed and normal tissues in low-dimensional space. We also attempt to verify if a progression manifold exists—the bridge between tumor and normal manifolds. By identifying and mapping the bridge manifold back to MRI image space, this method has the potential to predict tumor progression. This could be greatly beneficial for patient management. Preliminary results have supported our hypothesis: normal and tumor manifolds are well separated in a low-dimensional space. Also, the progressed manifold is found to lie roughly between the normal and tumor manifolds.     

Sensor fault reconstruction and observability for unknown inputs,with an application to wastewater treatment plants

In this article, we propose a general methodology for identifying and reconstructing sensor faults on dynamical processes. This methodology is issued from the general identification theory developed in the previous papers (Busvelle, E., and Gauthier, J.-P. (2003), ‘On Determining Unknown Functions in Differential Systems, with an Application to Biological Reactor’, ESAIM: Control, Optimisation and Calculus of Variations, 9, 509–553; Busvelle, E., and Gauthier, J.-P. (2004), ‘New Results on Identifiability of Nonlinear Systems’, in 2nd Symposium on Systems, Structure and Control, Oaxaca, Mexico; Busvelle, E., and Gauthier, J.-P. (2005), ‘Observation and Identification Tools for Non Linear Systems. Application to a Fluid Catalytic Cracker’, International Journal of Control, 78, 208–234): in fact, this identification theory also provides a general framework for the problem of ‘observability with unknown inputs’. Indeed, many problems of fault detection can be formulated as such observability problems, the (eventually additive) faults being just considered as unknown inputs. Our application to ‘sensor fault detection’ for wastewater treatment plants (WWTP) constitutes an ideal academic context to apply the theory: first, in this 3-5 case (3 sensors, 5 states), the theory applies generically and, second, any system is naturally under the ‘observability canonical form’ required to apply the basic high-gain observer from Gauthier and Kupka (Gauthier, J.-P., and Kupka, I. (1994), ‘Observability and Observers for Nonlinear Systems’, SIAM Journal on Control, 32, 975–994). A simulation study on the Bleesbrük WWTP is proposed to show the effectiveness of this approach.     

Evaluation of uncertainties in sewer condition assessment

Closed Circuit Television Inspection is used since decades as industry standard for sewer system inspection and structural performance evaluation. In current practice, inspection data are helpful to support asset management decisions. However, the quality and uncertainty of sewer condition assessment is rarely questioned. This article presents a methodology to determine the probability to underestimate, overestimate or accurately estimate the real condition of a pipe using visual inspection. The approach is based on the analysis of double inspections of the same sewer pipes and has been tested using the extensive data-set of the city of Braunschweig in Germany. Results indicate that the probability to inspect correctly a pipe in poor condition is close to 80%. The probability to overestimate the condition of a pipe in bad condition (false negative) is 20% whereas the probability to underestimate the condition of a pipe in good condition (false positive) is 15%. Finally, sewer condition evaluation can be used to assess the general condition of the network with an excellent accuracy probably because the respective effects of false positive and false negative are buffered.     

Ady2p is essential for the acetate permease activity in the yeast Saccharomyces cerevisiae

To identify new genes involved in acetate uptake in Saccharomyces cerevisiae, an analysis of the gene expression profiles of cells shifted from glucose to acetic acid was performed. The gene expression reprogramming of yeast adapting to a poor non-fermentable carbon source was observed, including dramatic metabolic changes, global activation of translation machinery, mitochondria biogenesis and the induction of known or putative transporters. Among them, the gene ADY2/YCR010c was identified as a new key element for acetate transport, being homologous to the Yarrowia lipolytica GPR1 gene, which has a role in acetic acid sensitivity. Disruption of ADY2 in S. cerevisiae abolished the active transport of acetate. Microarray analyses of ady2Delta strains showed that this gene is not a critical regulator of acetate response and that its role is directly connected to acetate transport. Ady2p is predicted to be a membrane protein and is a valuable acetate transporter candidate.     

Intelligent gripper technology for the handling of carbon fiber material

Nowadays, the serial production of Carbon Fiber-Reinforced Polymers remains a challenge for the industry. Their production and application have been limited by the intensive manual work required to produce them and the resulting elevated manufacturing costs. Moreover, the production handling tasks are fulfilled to a limited extent by the gripping systems currently available in the market. The delicate process and specific material requirements of these polymers compromise the feasibility and use of automated gripper systems. An innovative solution for the automated material handling of carbon fiber textiles developed by the wbk Institute for Production Science in cooperation with J. Schmalz GmbH will be presented in this paper. The main focus of this study deals with measuring principles to increase energy efficiency, process reliability and adaptability of a gripping system using low pressure grippers. This study presents suitable solutions for the implementation of low pressure grippers in a production environment.