Robustness Considerations Research Articles

Design Rules and Failure Modes of DMFC Stack Development

Fuel cell is regarded as a next generation power source for portable electronics as well as military applications due to significantly higher energy density compared to that of a battery. The key issues in developing DMFC systems for portable applications are volume and weight. In this paper, we describe three design rules to optimize the stack design, such as a flow field design, in consideration of volume, weight, robustness, and efficiency. In addition, the stack development history and two fatal failure modes are reported to aid in designing robust and reliable DMFC stacks.

Robustness Teaching By Inverted Pendulum Designed by Coefficient Diagram Method

Inverted pendulum is very effective tool in control education. A low cost inverted pendulum was presented in ACE94 (Manabe, 1994). This system was later presented in several workshops in various universities, and several students wrote master's thesis on the subject. With these experiences, it was later found that the system is a very good example of robust control design. Robust control design has developed over various mathematical concepts and tools. However practical robust control should be more technology oriented rather than theory. This paper will focus on various robustness considerations in the design of the low-cost inverted pendulum in order to clarify true meaning of robust control design

Robust Multi‐response Parameter Design based on RSM

This paper discusses multi‐response robust parameter design problems based on response surface method. Most research effort on multi‐response parameter design problem focuses much on finding out optimal parameters based on certain criteria or objectives. Research shows that optimal solution in terms of some criteria may not be robust. To achieve robust solution we should consider how sensitive the solution is when the factors change around it. A comparative study of methods for multi‐response robust parameter design is conducted. Solution with consideration of robustness and optimality is proposed with applications of the example.

METAPHYSICS AND THE REDEMPTION OF SACRIFICE: ON RENÉ GIRARD AND CHARLES WILLIAMS

René Girard is something of a Janus for philosophers and theologians interested in the question of sacrifice. On the one hand, few thinkers in any century have made such a compelling case for the importance and centrality of sacrifice within all human culture. On the other hand, Girard has steadfastly insisted that sacrifice be understood in exclusively anthropological terms thus foreclosing the metaphysical and theological questions that prima facie seem to attend any robust consideration of sacrifice. In this essay, I seek to move beyond this Girardian impasse by supplementing Girard's late‐thought with a more robust metaphysics of sacrifice as found in the work of the novelist, literary critic, and theologian, Charles Williams (one of the Oxford ‘Inklings’ and a close companion of C.S. Lewis). To begin with, I first explain Girard's understanding of the mimetic mechanism and the sacrificial origins of human culture. I then consider a number of the criticisms with which he has been charged, especially the accusation of methodological reductionism. I explore the way that Girard's late work has responded to a number of these criticisms but argue that Girard's responses fail to diffuse the charges. By way of conclusion, I suggest that Girard's insights can be saved when supplemented with the kind of relational metaphysics found in Williams' most perfectly realized novel, Descent into Hell. Rather than dispensing with ontology in favour of praxis, Williams transforms the profoundly Girardian themes of mediated desire, the doppelganger, mimetic rivalry, ritual, and the function of sacrifice by placing them in the context of what he calls the metaphysics of ‘co‐inherence.’ This allows Williams to provide a far more positive account of both mimesis and sacrifice (even in its substitutionary mode) than Girard, not just non‐retaliation but the actual bearing of one another's deepest burdens in communion, prayer, and love.

Robustness considerations in selecting efficient two-color microarray designs

The main goal of microarray experiments is to select a small subset of genes that are differentially expressed among competing mRNA samples. For a given set of such mRNA samples, it is possible to consider a number of two-color cDNA microarray designs with a fixed number of arrays. Appropriate criteria can be used to select an efficient design from such a set of alternative experimental designs. In practice, however, microarray expression data often contain missing observations and the most efficient design (with complete observations) for a specific setup may not be efficient in the presence of missing observations. In this article, we propose two criteria to address the robustness of microarray designs against missing observations. We demonstrate the simultaneous use of efficiency and robustness criteria to select good microarray designs for both one-factor and multi-factor experiments.

Compacted Probabilistic Visual Target Classification With Committee Decision in Wireless Multimedia Sensor Networks

This paper focuses on the compacted probabilistic binary visual classification for human targets in highly constrained wireless multimedia sensor network (WMSN). With consideration of robustness and accuracy, Gaussian process classifier (GPC) is used for classifier learning, since it can provide a Bayesian framework to automatically determine the optimal or near optimal kernel hyper-parameters. For decreasing computing complexity, feature compaction are carried out before learning, which are implemented by integer lifting wavelet transform (ILWT) and rough set. Then, the individual decisions of multiple nodes are combined by committee decision for improving the robustness and accuracy. Experimental results verify that GPC with committee decision can effectively carry out binary human target classification in WMSN. Importantly, GPC outperforms support vector machine, especially when committee decision is used. Furthermore, ILWT and rough set can offer compact representation of effective features, which can decrease the learning time and increase the learning accuracy.

Nonlinear Set Observation for Consistency-Based Diagnosis Using Implicit Interval Methods

The consideration of robustness and sensitivity is one of the main issues in the design of diagnosis methods. It is important to avoid false alarms which can be caused by uncertainties such as disturbed measurements or imprecise system models while, at the same time, no actual fault should be missed. One possibility to deal with such uncertainties is to use set-valued observers in a consistency-based fault diagnosis algorithm. This allows to eliminate false alarms by precluding models that are inconsistent with the measurements.We present a consistency-based diagnosis algorithm using an implicit interval method for state set observation of nonlinear continuous-time systems. The proposed state-set observer guarantees to enclose the set of system states that is consistent with the model and the measurements including uncertainties. Using this implicit observer concept in combination with a previously described diagnosis algorithm results in tighter state sets and therefore better diagnosis results. For an inverted pendulum as a benchmark system, diagnosis results using the new observer are presented and compared with previous results.Additionally, we discuss some modifications of the diagnosis algorithm that significantly reduce the computational effort required for fault detection.

Incredible Worlds, Credible Results

Robert Sugden argues that robustness analysis cannot play an epistemic role in grounding model-world relationships because the procedure is only a matter of comparing models with each other. We posit that this argument is based on a view of models as being surrogate systems in too literal a sense. In contrast, the epistemic importance of robustness analysis is easy to explicate if modelling is viewed as extended cognition, as inference from assumptions to conclusions. Robustness analysis is about assessing the reliability of our extended inferences, and when our confidence in these inferences changes, so does our confidence in the results. Furthermore, we argue that Sugden’s inductive account relies tacitly on robustness considerations.

Filtering in Oz: Australia's Foray into Internet Censorship

Australia's decision to implement Internet censorship using technological means creates a natural experiment: the first Western democracy to mandate filtering legislatively, and to retrofit it to a decentralized network architecture. But are the proposed restrictions legitimate? The new restraints derive from the Labor Party's pro-filtering electoral campaign, though coalition government gives minority politicians considerable influence over policy. The country has a well-defined statutory censorship system for on-line and off-line material that may, however, be undercut by relying on foreign and third-party lists of sites to be blocked. While Australia is open about its filtering goals, the government's transparency about what content is to be blocked is poor. Initial tests show that how effective censorship is at filtering prohibited content - and only that content - will vary based on what method the country's ISPs use. Though Australia's decisionmakers are formally accountable to citizens, efforts to silence dissenters, outsourcing of blocking decisions, and filtering's inevitable transfer of power to technicians undercut accountability. The paper argues Australia represents a shift by Western democracies towards legitimating Internet filtering and away from robust consideration of the alternatives available to combat undesirable information.

Robust portfolio selection based on a multi-stage scenario tree

The aim of this paper is to apply the concept of robust optimization introduced by Bel-Tal and Nemirovski to the portfolio selection problems based on multi-stage scenario trees. The objective of our portfolio selection is to maximize an expected utility function value (or equivalently, to minimize an expected disutility function value) as in a classical stochastic programming problem, except that we allow for ambiguities to exist in the probability distributions along the scenario tree. We show that such a problem can be formulated as a finite convex program in the conic form, on which general convex optimization techniques can be applied. In particular, if there is no short-selling, and the disutility function takes the form of semi-variance downside risk, and all the parameter ambiguity sets are ellipsoidal, then the problem becomes a second order cone program, thus tractable. We use SeDuMi to solve the resulting robust portfolio selection problem, and the simulation results show that the robust consideration helps to reduce the variability of the optimal values caused by the parameter ambiguity.

Initialization for robust inverse synthesis of phase-shifting masks in optical projection lithography

The continuous shrinkage of minimum feature size in integrated circuit (IC) fabrication incurs more and more serious distortion in the optical projection lithography process, generating circuit patterns that deviate significantly from the desired ones. Conventional resolution enhancement techniques (RETs) are facing critical challenges in compensating such increasingly severe distortion. In this paper, we adopt the approach of inverse lithography in the mask design, which is a branch of design methodology to treat it as an inverse mathematical problem. We focus on using pixel-based algorithms to design alternating phase-shifting masks with minimally distorted output, with the goal that the patterns generated should have high contrast and low dose sensitivity. This is achieved with a dynamic-programming-based initialization scheme to pre-assign phases to the layout when alternating phase-shifting masks are used. Pattern fidelity and worst case slopes are shown to improve with this initialization scheme, which are important for robustness considerations.

Robust data imputation

Single imputation methods have been wide-discussed topics among researchers in the field of bioinformatics. One major shortcoming of methods proposed until now is the lack of robustness considerations. Like all data, gene expression data can possess outlying values. The presence of these outliers could have negative effects on the imputated values for the missing values. Afterwards, the outcome of any statistical analysis on the completed data could lead to incorrect conclusions. Therefore it is important to consider the possibility of outliers in the data set, and to evaluate how imputation techniques will handle these values. In this paper, a simulation study is performed to test existing techniques for data imputation in case outlying values are present in the data. To overcome some shortcomings of the existing imputation techniques, a new robust imputation method that can deal with the presence of outliers in the data is introduced. In addition, the robust imputation procedure cleans the data for further statistical analysis. Moreover, this method can be easily extended towards a multiple imputation approach by which the uncertainty of the imputed values is emphasised. Finally, a classification example illustrates the lack of robustness of some existing imputation methods and shows the advantage of the multiple imputation approach of the new robust imputation technique.

Passivity-based control of linear switched reluctance motors with robustness consideration

A robust passivity-based control (PBC) algorithm is proposed for the position tracking system of a linear switched reluctance motor (LSRM). By using the modelling analysis of the drive system, a full-order nonlinear controlled model is first developed. Then, on the basis of the state error equation, the proposed robust PBC algorithm is derived from the view points of energy dissipation, control stability and algorithm robustness. The resultant design provides a total structural solution for the control law with the winding excitation scheme integrated into the algorithm. The proposed algorithm guarantees global stability of the whole servo system. It can also overcome the inherent nonlinear characteristics of the system and make the whole system robust to uncertainties and bounded disturbances. Both simulations and experimental implementations are carried out on the proposed LSRM drive system to investigate the performance of the proposed algorithm. The results show that the experimental and the simulation outputs match very well. The proposed algorithm is effective for the high precision position tracking of the LSRM, with high robustness to the system uncertainties and bounded disturbances.

Interests and Neonates: There Is More to the Story than We Explicitly Acknowledge

Although there are many different moral arguments concerning the use of Best Interests in neonatal decision-making, there seems in practice a firm commitment to application of the concept. And yet, there is still little reflection given by practitioners about what employing a Best Interest determination means in infant care. The following lays out a comprehensive taxonomy of interest-sources in order to provide for more robust considerations of what constitutes best interests of/for neonates.

CRISTA: A New Paradigm for Low-Power, Variation-Tolerant, and Adaptive Circuit Synthesis Using Critical Path Isolation

Design considerations for robustness with respect to variations and low-power operations typically impose contradictory design requirements. Low-power design techniques such as voltage scaling, dual- , etc., can have a large negative impact on parametric yield. In this paper, we propose a novel paradigm for low-power variation-tolerant circuit design called critical path isolation for timing adaptiveness (CRISTA), which allows aggressive voltage scaling. The principal idea includes the following: 1) isolate and predict the set of possible paths that may become critical under process variations; 2) ensure that they are activated rarely; and 3) avoid possible delay failures in the critical paths by dynamically switching to two-cycle operation (assuming all standard operations are single cycle), when they are activated. This allows us to operate the circuit at reduced supply voltage while achieving the required yield. Simulation results on a set of benchmark circuits with Berkeley-predictive-technology-model [BPTM 70 nm: Berkeley predictive technology model] 70-nm devices that show an average of 60% improvement in power with small overhead in performance and 18% overhead in die area compared to conventional design. We also present two applications of the proposed methodology that include the following: 1) pipeline design for low power and 2) temperature-adaptive circuit design.

Optimization of Backward Giant Circle Technique on the Asymmetric Bars

The release window for a given dismount from the asymmetric bars is the period of time within which release results in a successful dismount. Larger release windows are likely to be associated with more consistent performance because they allow a greater margin for error in timing the release. A computer simulation model was used to investigate optimum technique for maximizing release windows in asymmetric bars dismounts. The model comprised four rigid segments with the elastic properties of the gymnast and bar modeled using damped linear springs. Model parameters were optimized to obtain a close match between simulated and actual performances of three gymnasts in terms of rotation angle (1.5 degrees ), bar displacement (0.014 m), and release velocities (<1%). Three optimizations to maximize the release window were carried out for each gymnast involving no perturbations, 10-ms perturbations, and 20-ms perturbations in the timing of the shoulder and hip joint movements preceding release. It was found that the optimizations robust to 20-ms perturbations produced release windows similar to those of the actual performances whereas the windows for the unperturbed optimizations were up to twice as large. It is concluded that robustness considerations must be included in optimization studies in order to obtain realistic results and that elite performances are likely to be robust to timing perturbations of the order of 20 ms.

Near-Duplicate Keyframe Identification With Interest Point Matching and Pattern Learning

This paper proposes a new approach for near-duplicate keyframe (NDK) identification by matching, filtering and learning of local interest points (LIPs) with PCA-SIFT descriptors. The issues in matching reliability, filtering efficiency and learning flexibility are novelly exploited to delve into the potential of LIP-based retrieval and detection. In matching, we propose a one-to-one symmetric matching (OOS) algorithm which is found to be highly reliable for NDK identification, due to its capability in excluding false LIP matches compared with other matching strategies. For rapid filtering, we address two issues: speed efficiency and search effectiveness, to support OOS with a new index structure called LIP-IS. By exploring the properties of PCA-SIFT, the filtering capability and speed of LIP-IS are asymptotically estimated and compared to locality sensitive hashing (LSH). Owing to the robustness consideration, the matching of LIPs across keyframes forms vivid patterns that are utilized for discriminative learning and detection with support vector machines. Experimental results on TRECVID-2003 corpus show that our proposed approach outperforms other popular methods including the techniques with LSH in terms of retrieval and detection effectiveness. In addition, the proposed LIP-IS successfully speeds up OOS for more than ten times and possesses several avorable properties compared to LSH.

IMC based Robust PID design: Tuning guidelines and automatic tuning

This communication addresses the problem of tuning a PID controller for step response. The tuning is based upon a First Order Plus Time Delay (FOPTD) model and aims to achieve a step response specification while taking into account robustness considerations. The industrial ISA-PID formulation is chosen. A tuning rule is derived first where the four parameters of the ISA-PID are determined by means of two new parameters: one parameter is related to the desired closed-loop time constant and the other one to the robustness level. On a second step, these two parameters are set to a fixed value in order to get a simple and automatic rule that directly gives the controller parameters in terms of the process model parameters. The proposed automatic tuning rule is compared with other known tunings.

Robust-Optimal Fiscal Policy

This paper introduces a concern for model misspecification in a Lucas-Stokey optimal fiscal policy setting. The representative household in this economy is endowed with the knowledge of a reference model for the government spending process but acknowledges that this model is potentially misspecified. The paper shows how this concern for misspecification affects the competitive equilibrium pricing of state contingent bonds and how this in turn affects the calculation of present value budget constraints. The paper shows how the Ramsey problem and optimal solutions are affected by the size of potential misspecifications entertained. The implications for optimal maturity structure for non-contingent debt are analysed, paying particular attention to how the pricing of these assets is affected by robustness considerations. A linear quadratic specification serves to implement numerically the economy under study.

Operational Experience of an IT-SOFC / Battery Hybrid System for Automotive Applications

Testing of a 300 W stack, supplied by Versa Power Systems Ltd., and a sodium - metal chloride (ZEBRA) battery has been performed with a view to assessing the feasibility of combining an intermediate temperature solid oxide fuel cell with a high temperature battery for automotive traction applications. Field testing of a self-compressed stack is demonstrated including consideration of the mechanical robustness of the technology. The battery system, comprising novel cell technology, is tested under pulse discharge and standard driving cycle conditions. Based on modeling studies previously performed, the performance results obtained and the reliability of the respective technologies, development of a full-scale prototype is considered viable and ultimately commercially relevant.