Synthesis and Optimization of Reversible Circuits - A Survey

Reversible logic circuits have been historically motivated by theoretical research in low-power electronics as well as practical improvement of bit-manipulation transforms in cryptography and computer graphics. Recently, reversible circuits have attracted interest as components of quantum algorithms, as well as in photonic and nano-computing technologies where some switching devices offer no signal gain. Research in generating reversible logic distinguishes between circuit synthesis, post-synthesis optimization, and technology mapping. In this survey, we review algorithmic paradigms --- search-based, cycle-based, transformation-based, and BDD-based --- as well as specific algorithms for reversible synthesis, both exact and heuristic. We conclude the survey by outlining key open challenges in synthesis of reversible and quantum logic, as well as most common misconceptions.Comment: 34 pages, 15 figures, 2 table

Knowledge formalization in experience feedback processes : an ontology-based approach

Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving themissions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable

EXPERIMENTAL PREDICTION AND OPTIMIZATION OF MATERIAL REMOVAL RATE DURING HARD TURNING OF AUSTENITIC 304L STAINLESS STEEL

This work involves a predictive model for material removal rate (MRR). It investigates the influence of machining process parameters such as cutting speed, feed rate and depth of cut on the material removal rate (output parameter) during hard turning of AISI 304L austenitic stainless steel (0.03 wt. % C (max)). A total of 27 experiments were conducted using a MORISEIKI SL-253B CNC machine with cemented carbide cutting tool under three different spindle speeds (1000, 1200, 1400rev/min), feed rates (0.05, 0.10, 0.15mm/rev) and depths of cut (0.4, 0.8, 1.2mm). The machining parameter settings were determined using the Taguchi experimental design method. The Taguchi method and relationship between MRR and input parameters were arrived at through MINITAB16 software package. The optimum machining parameters combination was obtained by using larger-the-better analysis of signal-to-noise (S/N) ratio. The optimal cutting condition is at spindle speed level 2 (1200 rpm); feed rate at level 3 (0.15mm/rev) and Depth of cut at level 3 (1.2 mm) which gave an optimum MRR of 77.80243mm3/min. The S/N ratio response table, main effect plots and the relationship between cutting parameters and the MRR was obtained. A mathematical model was developed using multiple regression analysis to predict MRR during hard turning of AISI 304L austenitic stainless steel. The level of importance and performance characteristics of the machining parameters on MRR was determined by using analysis of variance (ANOVA). From the results, the feed rate had the most significant effects on the MRR followed by depth of cut.The spindle speed has the least effect on MRR. It was also revealed that the predicted results found a good correlation with the experimental results as the regression line fits well for both results data at 95% confidence interval.Keywords: Machining; material removal; optimizatio

Geotechnical Response Models for Steel Compliant Riser in Deepwater Clays

The touchdown zone (TDZ) often proves to be a spot where cyclic bending stresses are the largest and is therefore a critical location for fatigue. Catenary steel compliant pipelines or risers (SCRs) are subject of much ongoing research, particularly with respect to their fatigue life, which is strongly influenced by seabed soil conditions in the TDZ. This chapter reviews the recent publications that might have an impact on the SCR-seabed interaction. The review starts by looking at the SCR general arrangement. Thereafter, the focus moves to the review of the recent research that studied the interactions between deepwater SCRs and the seabed. In addition, the review went over the analysis techniques of the SCR, including the modelling philosophy and models for geotechnical response. The research gap and the need for future research are identified

NOTICE: A Framework for Non-functional Testing of Compilers

International audience—Generally, compiler users apply different optimizations to generate efficient code with respect to non-functional properties such as energy consumption, execution time, etc. However, due to the huge number of optimizations provided by modern compilers, finding the best optimization sequence for a specific objective and a given program is more and more challenging. This paper proposes NOTICE, a component-based framework for non-functional testing of compilers through the monitoring of generated code in a controlled sand-boxing environment. We evaluate the effectiveness of our approach by verifying the optimizations performed by the GCC compiler. Our experimental results show that our approach is able to auto-tune compilers according to user requirements and construct optimizations that yield to better performance results than standard optimization levels. We also demonstrate that NOTICE can be used to automatically construct optimization levels that represent optimal trade-offs between multiple non-functional properties such as execution time and resource usage requirements