Massively parallel Lucas Kanade optical flow for real-time video processing applications

This paper deals with dense optical flow estimation from the perspective of the trade-off between quality of the estimated flow and computational cost which is required by real-world applications. We propose a fast and robust local method, denoted by eFOLKI, and describe its implementation on GPU. It leads to very high performance even on large image formats such as 4 K (3,840 × 2,160) resolution. In order to assess the interest of eFOLKI, we first present a comparative study with currently available GPU codes, including local and global methods, on a large set of data with ground truth. eFOLKI appears significantly faster while providing quite accurate and highly robust estimated flows. We then show, on four real-time video processing applications based on optical flow, that eFOLKI reaches the requirements both in terms of estimated flows quality and of processing rate.     

QoS aggregation for service orchestrations based on workflow pattern rules and MCDM method: evaluation at design time and runtime

Service consumers satisfaction is considered today as one of the main concern to be ensured by service providers, especially with the spread of concurrency and the increase of functionally equivalent services. This satisfaction is closely related to quality of service (QoS) perceived by service consumers. In this context, we propose an approach to determine the satisfaction degree corresponding to the QoS of service-based applications, with regard to service consumers’ QoS expectations. Our approach is based on a preference model, which is built only on the basis of service consumer’s provided information. This preference model is also based on the 2-additive Choquet operator that takes into account preferential dependencies. In this paper, we target both design time and runtime aggregation of QoS of service-based applications.     

The vehicle routing problem with restricted mixing of deliveries and pickups

The vehicle routing problem with deliveries and pickups is one of the main problems within reverse logistics. This paper focuses on an important assumption that divides the literature on the topic, namely the restriction that all deliveries must be completed before pickups can be made. A generalised model is presented, together with a mathematical formulation and its resolution. The latter is carried out by adopting a suitable implementation of the reactive tabu search metaheuristic. Results show that significant savings can be achieved by allowing a mixture of delivery and pickup loads on-board and yet not incurring delays and driver inconvenience.     

Active XML-based Web data integration

Today, the Web is the largest source of information worldwide. There is currently a strong trend for decision-making applications such as Data Warehousing (DW) and Business Intelligence (BI) to move onto the Web, especially in the cloud. Integrating data into DW/BI applications is a critical and time-consuming task. To make better decisions in DW/BI applications, next generation data integration poses new requirements to data integration systems, over those posed by traditional data integration. In this paper, we propose a generic, metadata-based, service-oriented, and event-driven approach for integrating Web data timely and autonomously. Beside handling data heterogeneity, distribution and interoperability, our approach satisfies near real-time requirements and realize active data integration. For this sake, we design and develop a framework that utilizes Web standards (e.g., XML and Web services) for tackling data heterogeneity, distribution and interoperability issues. Moreover, our framework utilizes Active XML (AXML) to warehouse passive data as well as services to integrate active and dynamic data on-the-fly. AXML embedded services and changes detection services ensure near real-time data integration. Furthermore, the idea of integrating Web data actively and autonomously revolves around mining events logged by the data integration environment. Therefore, we propose an incremental XML-based algorithm for mining association rules from logged events. Then, we define active rules dynamically upon mined data to automate and reactivate integration tasks. Finally, as a proof of concept, we implement a framework prototype as a Web application using open-source tools.     

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.