PZT thin film actuated elastic fin micromotor

A piezoelectric elastic fin micromotor based on a PbZr(0.53 )Ti(0.47)O(3) thin film driving a micromachined silicon membrane was fabricated and studied. The stator was characterized by interferometry, and a laser set-up was used to measure the angular velocity and acceleration of the motor. The torque, the output power, and the efficiency of the device were extracted from these measurements. Values up to 1020 rpm and 0.94 muNm were observed for the velocity and the torque, respectively, which would be sufficient for a wristwatch application. The present version exhibited an efficiency of 0.17%, which could theoretically be increased to 4.8%     

Dynamics of voltage polarity reversal as the controlling factor inspace-charge induced breakdown of insulating polymers

Our investigation is focused on the understanding of high-field phenomena in polymers. In highly insulating materials such as polyethylene, space charge has a strong influence on both the short and long term breakdown strengths. The aim of this report is to demonstrate and discuss the importance of the dynamics of voltage polarity reversal at the injecting needle electrode on space charge induced breakdown. Evidence of space charge injection is provided by the observation of local breakdown generated by grounding of the sample after the polarization (so-called `grounding' tree). The effect which is polarity dependent, can be observed only when the sample is short-circuited immediately after charging. Field computation is performed versus injected charge and a critical charge density is derived in order to explain polymer breakdown upon grounding. The time dependence of the effect is explained by space charge relaxation. Polymer degradation under ac voltage is discussed on the basis of this interpretation     

Dynamic Query Operator Scheduling for Wide-Area Remote Access

Distributed databases operating over wide-area networks such as the Internet, must deal with the unpredictable nature of the performance of communication. The response times of accessing remote sources can vary widely due to network congestion, link failure, and other problems. In such an unpredictable environment, the traditional iterator-based query execution model performs poorly. We have developed a class of methods, called query scrambling, for dealing explicitly with the problem of unpredictable response times. Query scrambling dynamically modifies query execution plans on-the-fly in reaction to unexpected delays in data access. In this paper we focus on the dynamic scheduling of query operators in the context of query scrambling. We explore various choices for dynamic scheduling and examine, through a detailed simulation, the effects of these choices. Our experimental environment considers pipelined and non-pipelined join processing in a client with multiple remote data sources and delayed or possibly bursty arrivals of data. Our performance results show that scrambling rescheduling is effective in hiding the impact of delays on query response time for a number of different delay scenarios.     

A Bag of Strings Representation for Image Categorization

This paper presents an architecture well suited for natural images classification or visual object recognition applications. The method proposes to integrate a spatial representation into the well known “bag of local signatures” approach. For this purpose, it combines the power of a string representation which provides an ordered view of local features with the vectorial histogram representation allowing to recognize efficiently and quickly an image by using a machine learning classifier. To reach this goal, we propose to represent an image by a set of strings of local signatures obtained by tracking the detected salient points along image edges. We propose here to conjointly use the Hölder exponents and the direction of minimal regularity of the bidimensional signal singularities to compute a signature describing precisely a region of interest centered on an interest point. As we will see, an alphabet of strings is easily obtained by using a typical self organizing map architecture. As a consequence, a “bag of strings” representation is used, providing a compact representation encoding both local signatures and spatial information. This representation is particularly well suited to train a support vector machine classifier used for the last classification step. This architecture obtains good classification rates on different well known datasets.     

Hybridation of Bayesian networks and evolutionary algorithms for multi-objective optimization in an integrated product design and project management context

A better integration of preliminary product design and project management processes at early steps of system design is nowadays a key industrial issue. Therefore, the aim is to make firms evolve from classical sequential approach (first product design the project design and management) to new integrated approaches. In this paper, a model for integrated product/project optimization is first proposed which allows taking into account simultaneously decisions coming from the product and project managers. However, the resulting model has an important underlying complexity, and a multi-objective optimization technique is required to provide managers with appropriate scenarios in a reasonable amount of time. The proposed approach is based on an original evolutionary algorithm called evolutionary algorithm oriented by knowledge (EAOK). This algorithm is based on the interaction between an adapted evolutionary algorithm and a model of knowledge (MoK) used for giving relevant orientations during the search process. The evolutionary operators of the EA are modified in order to take into account these orientations. The MoK is based on the Bayesian Network formalism and is built both from expert knowledge and from individuals generated by the EA. A learning process permits to update probabilities of the BN from a set of selected individuals. At each cycle of the EA, probabilities contained into the MoK are used to give some bias to the new evolutionary operators. This method ensures both a faster and effective optimization, but it also provides the decision maker with a graphic and interactive model of knowledge linked to the studied project. An experimental platform has been developed to experiment the algorithm and a large campaign of tests permits to compare different strategies as well as the benefits of this novel approach in comparison with a classical EA.     

Planning and scheduling teams of skilled workers

Solving problems that mix planning and scheduling are often seen as a challenge. Discrete time-based scheduling, along with complex side constraints, does not mix well with the more flexible nature of the planning model. This is demonstrated in our experiments when trying to solve a problem where we must assemble teams of skilled workers to perform jobs that require these skills, break up these teams and then assemble new ones to perform more jobs. The mixing of the planning part (grouping workers into teams) and the scheduling part (creating a schedule for each worker), along with some difficult side constraints and a large problem size (800 workers, 2,000 jobs over one month) combine to contribute to the challenge of finding good solutions for this problem.     

Communicating between the kernel and user‐space in Linux using Netlink sockets

When developing Linux kernel features, it is a good practice to expose the necessary details to user‐space to enable extensibility. This allows the development of new features and sophisticated configurations from user‐space. Generally, software developers have to face the task of looking for a good way to communicate between the kernel and user‐space in Linux. This tutorial introduces you to Netlink sockets, a flexible and extensible messaging system that provides communication between kernel and user‐space. We provide the fundamental guidelines for practitioners who wish to develop Netlink‐based interfaces. Copyright © 2010 John Wiley & Sons, Ltd.     

Analysis reuse exploiting taxonomical information and belief assignment in industrial problem solving

To take into account the experience feedback on solving complex problems in business is deemed as a way to improve the quality of products and processes. Only a few academic works, however, are concerned with the representation and the instrumentation of experience feedback systems. We propose, in this paper, a model of experiences and mechanisms to use these experiences. More specifically, we wish to encourage the reuse of already performed expert analysis to propose a priori analysis in the solving of a new problem. The proposal is based on a representation in the context of the experience of using a conceptual marker and an explicit representation of the analysis incorporating expert opinions and the fusion of these opinions. The experience feedback models and inference mechanisms are integrated in a commercial support tool for problem solving methodologies. The results obtained to this point have already led to the definition of the role of “Rex Manager” with principles of sustainable management for continuous improvement of industrial processes in companies.     

Information quality measurement of medical encoding support based on usability

Medical encoding support systems for diagnoses and medical procedures are an emerging technology that begins to play a key role in billing, reimbursement, and health policies decisions. A significant problem to exploit these systems is how to measure the appropriateness of any automatically generated list of codes, in terms of fitness for use, i.e. their quality. Until now, only information retrieval performance measurements have been applied to estimate the accuracy of codes lists as quality indicator. Such measurements do not give the value of codes lists for practical medical encoding, and cannot be used to globally compare the quality of multiple codes lists. This paper defines and validates a new encoding information quality measure that addresses the problem of measuring medical codes lists quality. It is based on a usability study of how expert coders and physicians apply computer-assisted medical encoding. The proposed measure, named ADN, evaluates codes Accuracy, Dispersion and Noise, and is adapted to the variable length and content of generated codes lists, coping with limitations of previous measures. According to the ADN measure, the information quality of a codes list is fully represented by a single point, within a suitably constrained feature space. Using one scheme, our approach is reliable to measure and compare the information quality of hundreds of codes lists, showing their practical value for medical encoding. Its pertinence is demonstrated by simulation and application to real data corresponding to 502 inpatient stays in four clinic departments. Results are compared to the consensus of three expert coders who also coded this anonymized database of discharge summaries, and to five information retrieval measures. Information quality assessment applying the ADN measure showed the degree of encoding-support system variability from one clinic department to another, providing a global evaluation of quality measurement trends.