Static Strategies for Worksharing with Unrecoverable Interruptions

One has a large workload that is “divisible”—its constituent work’s granularity can be adjusted arbitrarily—and one has access to p remote worker computers that can assist in computing the workload. How can one best utilize the workers? Complicating this question is the fact that each worker is subject to interruptions (of known likelihood) that kill all work in progress on it. One wishes to orchestrate sharing the workload with the workers in a way that maximizes the expected amount of work completed. Strategies are presented for achieving this goal, by balancing the desire to checkpoint often—thereby decreasing the amount of vulnerable work at any point—vs. the desire to avoid the context-switching required to checkpoint. Schedules must also temper the desire to replicate work, because such replication diminishes the effective remote workforce. The current study demonstrates the accessibility of strategies that provably maximize the expected amount of work when there is only one worker (the case p=1) and, at least in an asymptotic sense, when there are two workers (the case p=2); but the study strongly suggests the intractability of exact maximization for p≥2 computers, as work replication on multiple workers joins checkpointing as a vehicle for decreasing the impact of work-killing interruptions. We respond to that challenge by developing efficient heuristics that employ both checkpointing and work replication as mechanisms for decreasing the impact of work-killing interruptions. The quality of these heuristics, in expected amount of work completed, is assessed through exhaustive simulations that use both idealized models and actual trace data.     

Urban flood risk assessment using sewer flooding databases

Sustainable water management is a global challenge for the 21st century. One key aspect remains protection against urban flooding. The main objective is to ensure or maintain an adequate level of service for all inhabitants. However, level of service is still difficult to assess and the high-risk locations difficult to identify. In this article, we propose a methodology, which (i) allows water managers to measure the service provided by the urban drainage system with regard to protection against urban flooding; and (ii) helps stakeholders to determine effective strategies for improving the service provided. One key aspect of this work is to use a database of sewer flood event records to assess flood risk. Our methodology helps urban water managers to assess the risk of sewer flooding; this approach does not seek to predict flooding but rather to inform decision makers on the current level of risk and on actions which need to be taken to reduce the risk. This work is based on a comprehensive definition of risk, including territorial vulnerability and perceptions of urban water stakeholders. This paper presents the results and the methodological contributions from implementing the methodology on two case studies: the cities of Lyon and Mulhouse.     

Synthesis and structure-activity study of quaternary ammonium functionalized beta-cyclodextrin-carboxymethylcellulose polymers

Carboxymethylcellulose (CMC) and beta-cyclodextrin (beta-CD)-based polymers functionalized with two types of quaternary ammonium compounds (QACs), the alkaquat DMB-451 (N-alkyl (50% C14, 40% C12, 10% C10) dimethylbenzylammonium chloride) (DMD-451) named polymer DMB-451, and FMB 1210-8 (a blend of 32 w% N-alkyl (50% C14, 40% C12, 10% C10) dimethylbenzylammonium chloride and 48 w% of didecyldimethylammonium chloride) named polymer FMB 1210-8, were synthethized and characterized by Fourier transform infrared spectroscopy. The antimicrobial activities of these polymers against Eschericia coli were also evaluated at 25 degrees C in wastewater. The results have indicated that the polymer FMB 1210-8 possesses a high-affinity binding with bacterial cells that induces a rapid disinfection process. Moreover, in the same experimental conditions of disinfection (mixture of 1.0 g of polymer and 100 mL of wastewater), the polymer FMB 1210-8 has a higher antimicrobial efficiency (99.90%) than polymer DMB-451 (92.8%). This phenomenon might be associated to a stronger interaction with bacterial cells due to stronger binding affinity for E. coli cells and greater killing efficiency of the C10 alkyl chains QAC of polymer FMB 1210-8 to disrupt the bacterial cell membrane as compared to N-alkyl (50% C14, 40% C12, 10% C10) dimethylbenzylammonium chloride. Together, these results suggest that the polymer FMB 1210-8 could constitute a good disinfectant against Escherichia coli, which could be advantageously used in wastewater treatments due to the low toxicity of beta-CD and CMC, and moderated toxicity of FMB 1210-8 to human and environment.     

Development and Deployment of an Intelligent Kite Aerial Photography Platform (iKAPP) for Site Surveying and Image Acquisition

Aerial photographs and images are used by a variety of industries, including farming, landscaping, surveying, and agriculture, as well as academic researchers including archaeologists and geologists. Aerial imagery can provide a valuable resource for analyzing sites of interest and gaining information about the structure, layout, and composition of large areas of land that would be unavailable otherwise. Current methods of acquiring aerial images rely on techniques such as satellite imagery, manned aircraft, or more recently unmanned aerial vehicles (UAVs) and micro‐UAV technologies. These solutions, while accurate and reliable, have several drawbacks. Using satellite imagery or UAVs can prove to be very expensive, costing tens of thousands for images. They can also prove to be time‐consuming and in some cases have constraints on use, such as no‐fly zones. In this paper, we present an alternative low‐cost, versatile solution to these methods, an intelligent kite aerial photography platform (iKAPP), for the purpose of acquiring aerial images and monitoring sites of interest. We show how this system provides flexibility in application, and we detail the system's design, mechanical operation, and initial flight experiments for a low‐cost, lightweight, intelligent platform capable of acquiring high‐resolution images. Finally, we demonstrate the system by acquiring images of a local site, showing how the system functions and the quality of images it can capture. The application of the system and its capabilities in terms of capture rates, image quality, and limitations are also presented. The system offers several improvements over traditional KAP systems, including onboard “intelligent” processing and communications. The intelligent aspect of this system stems from the use of self‐image stabilization of the camera, the advantage being that one is able to configure the system to capture large areas of a site automatically, and one can see the site acquisition in real time, all of which are not possible with previous methods of AP. © 2013 Wiley Periodicals, Inc.     

Sensorless fault tolerant control for induction motors

In this paper, a sensorless fault tolerant controller for induction motors is developed. In the proposed approach, a robust controller based on backstepping strategy is designed in order to compensate for both the load torque disturbance and the rotor resistance variation caused by the broken rotor bars faults. The proposed approach needs neither fault detection and isolation schemes nor controller re-design. Moreover, to avoid the use of speed and flux sensors, a second order sliding mode observer is introduced to estimate the flux and the speed. The observer converges in a finite time and leads to good estimates of the flux and the speed even in the presence of the rotor resistance variation and the load torque disturbance. Since the observer converges in the finite time, the stability of the closed-loop system (controller with observer) is shown in two steps. First, the boundedness of the closed-loop system trajectories before the convergence of the observer is proved. Second, the convergence of the closed-loop system trajectories is proved after the convergence of the observer. To highlight the efficiency and applicability of the proposed control scheme, simulation and experimental results are conducted for a 1.5 kW induction motor.     

Topology and thickness optimization of laminated composites including manufacturing constraints

This paper presents a gradient based optimization method for large-scale topology and thickness optimization of fiber reinforced monolithic laminated composite structures including certain manufacturing constraints to attain industrial relevance. This facilitates application of predefined fiber mats and reduces the risk of failure such as delamination and matrix cracking problems. The method concerns simultaneous determination of the optimum thickness and fiber orientation throughout a laminated structure with fixed outer geometry. The laminate thickness may vary as an integer number of plies, and possible fiber orientations are limited to a finite set. The conceptual combinatorial problem is relaxed to a continuous problem and solved on basis of interpolation schemes with penalization through the so-called Discrete Material Optimization method, explicitly including manufacturing constraints as a large number of sparse linear constraints. The methodology is demonstrated on several numerical examples.     

Interactive topology optimization on hand-held devices

This paper presents an interactive topology optimization application designed for hand-held devices running iOS or Android. The TopOpt app solves the 2D minimum compliance problem with interactive control of load and support positions as well as volume fraction. Thus, it is possible to change the problem settings on the fly and watch the design evolve to a new optimum in real time. The use of an interactive app makes it extremely simple to learn and understand the influence of load-directions, support conditions and volume fraction. The topology optimization kernel is written in C# and the graphical user interface is developed using the game engine Unity3D. The underlying code is inspired by the publicly available 88 and 99 line Matlab codes for topology optimization but does not utilize any low-level linear algebra routines such as BLAS or LAPACK. The TopOpt App can be downloaded on iOS devices from the Apple App Store, at Google Play for the Android platform, and a web-version can be run from www.topopt.dtu.dk.     

Little effect of transfer technique instruction and physical fitness training in reducing low back pain among nurses: a cluster randomised intervention study

The aim of this study was to evaluate the effect of a transfer technique education programme (TT) alone or in combination with physical fitness training (TTPT) compared with a control group, who followed their usual routine. Eleven clinical hospital wards were cluster randomised to either intervention (six wards) or to control (five wards). The intervention cluster was individually randomised to TT (55 nurses) and TTPT (50 nurses), control (76 nurses). The transfer technique programme was a 4-d course of train-the-trainers to teach transfer technique to their colleagues. The physical training consisted of supervised physical fitness training 1 h twice per week for 8 weeks. Implementing transfer technique alone or in combination with physical fitness training among a hospital nursing staff did not, when compared to a control group, show any statistical differences according to self-reported low back pain (LBP), pain level, disability and sick leave at a 12-month follow-up. However, the individual randomised intervention subgroup (transfer technique/physical training) significantly improved the LBP-disability (p = 0.001). Although weakened by a high withdrawal rate, teaching transfer technique to nurses in a hospital setting needs to be thoroughly considered. Other priorities such as physical training may be taken into consideration. The current study supports the findings of other studies that introducing transfer technique alone has no effect in targeting LBP. However, physical training seems to have an influence in minimising the LBP consequences and may be important in the discussion of how to prevent LBP or the recurrence of LBP among nursing personnel.     

Binary-image comparison with local-dissimilarity quantification

In this paper, we present a method for binary image comparison. For binary images, intensity information is poor and shape extraction is often difficult. Therefore binary images have to be compared without using feature extraction. Due to the fact that different scene patterns can be present in the images, we propose a modified Hausdorff distance (HD) locally measured in an adaptive way. The resulting set of measures is richer than a single global measure. The local HD measures result in a local-dissimilarity map (LDMap) including the dissimilarity spatial layout. A classification of the images in function of their similarity is carried out on the LDMaps using a support vector machine. The proposed method is tested on a medieval illustration database and compared with other methods to show its efficiency.