Accuracy estimate and optimization techniques for SimRank computation

The measure of similarity between objects is a very useful tool in many areas of computer science, including information retrieval. SimRank is a simple and intuitive measure of this kind, based on a graph-theoretic model. SimRank is typically computed iteratively, in the spirit of PageRank. However, existing work on SimRank lacks accuracy estimation of iterative computation and has discouraging time complexity. In this paper, we present a technique to estimate the accuracy of computing SimRank iteratively. This technique provides a way to find out the number of iterations required to achieve a desired accuracy when computing SimRank. We also present optimization techniques that improve the computational complexity of the iterative algorithm from O(n ⁴) in the worst case to min(O(nl), O(n ³/ log₂ n)), with n denoting the number of objects, and l denoting the number object-to-object relationships. We also introduce a threshold sieving heuristic and its accuracy estimation that further improves the efficiency of the method. As a practical illustration of our techniques, we computed SimRank scores on a subset of English Wikipedia corpus, consisting of the complete set of articles and category links.     

Scaling the formation of slug bubbles in microfluidic flow-focusing devices

The present study aims at scaling the formation of slug bubbles in flow-focusing microfluidic devices using a high-speed digital camera and a micro particle image velocimetry (μ-PIV) system. Experiments were conducted in two different polymethyl methacrylate square microchannels of respectively 600 × 600 and 400 × 400 μm. N₂ bubbles were generated in glycerol–water mixtures with several concentrations of surfactant sodium dodecyl sulfate. The influence of gas and liquid flow rates, the viscosity of the liquid phase and the width of the microchannel on the bubble size were explored. The bubble size was correlated as a function of the width of the microchannel W _c, the ratio of the gas/liquid flow rates Q _g/Q _l and the liquid Reynolds number. During the pinch-off stage, the variation of the minimum width of the gaseous thread W _m with the remaining time could be scaled as _boxclose_boxclose ()^ - 0.15 (T - t)^1/3 . W_{\text{m}} \propto ({\frac{{Q_{\text{g}} }}{{Q_{\text{l}} }}})^{ - 0.15} (T - t)^{1/3} . The velocity fields in the liquid phase around the thread, determined by μ-PIV measurements, were obtained around a forming bubble to reveal the role of the liquid phase.     

Characterization of renal tumours based on Raman spectra classification

In this study, we propose to evaluate the potential of Raman spectroscopy (RS) to assess renal tumours at surgery. Different classes of Raman renal spectra acquired during a clinical protocol are discriminated using support vector machines classifiers. The influence on the classification scores of various preprocessing steps generally involved in RS are also investigated and evaluated in the particular context of renal tumour characterization. Encouraging results show the interest of RS to evaluate kidney cancer and suggest the potential of this technique as a surgical assistance during partial nephrectomy.     

Reliability versus performance for critical applications

Applications implemented on critical systems are subject to both safety critical and real-time constraints. Classically, applications are specified as precedence task graphs that must be scheduled onto a given target multiprocessor heterogeneous architecture. We propose a new method for simultaneously optimizing two objectives: the execution time and the reliability of the schedule. The problem is decomposed into two successive steps: a spatial allocation during which the reliability is maximized (randomized algorithm), and a scheduling during which the makespan is minimized (list scheduling algorithm). It allows us to produce several trade-off solutions, among which the user can choose the solution that best fits the application’s requirements. Reliability is increased by replicating adequate tasks onto well chosen processors. Our fault model assumes that processors are fail-silent, that they are subject to transient failures, and that the occurrences of failures follow a constant parameter Poisson law. We assess and validate our method by running extensive simulations on both random graphs and actual application graphs. They show that it is competitive, in terms of makespan, compared to existing reference scheduling methods for heterogeneous processors (HEFT), while providing a better reliability.     

Airflow in a slot-ventilated enclosure partially filled with porous boxes: Part I - Measurements and simulations in the clear region

A reduced-scale model and CFD predictions were used to investigate experimentally and numerically the airflow patterns within a ceiling slot-ventilated enclosure partially loaded with vented boxes filled by spherical objects. The experiments were carried out using laser Doppler velocimetry. Airflows around and inside porous boxes were predicted taking into account their aerodynamic interactions. This work is divided into two parts. This paper presents part I and concerns the air velocity characteristics within the jet above the boxes, while Part II deals with the air velocity characteristics inside the boxes. The results highlight the confinement effect due to the enclosure and the influence of load porosity on jet penetration, its development and hence the heterogeneity of ventilation within the enclosure. The numerical predictions obtained with the computational fluid dynamics Fluent package using the RSM turbulence model show reasonable agreement with experimental data. Predicted velocity profiles were generally within an error of 3-30% of the measured velocities.     

A DSS for integrated distribution of empty and full containers

A DSS integrating empty and full containers transshipment operations is presented, addressing the typically unbalanced export/import containers trading problem. The problem is modeled as a network, where nodes represent customers, leasing companies, harbors and warehouses, while arcs represent transportation routes. The underlying mathematical model operates in stages, first prioritizing and adjusting full containers demands considering available empty containers supplies, and then statically optimizing costs. Transportation routes are registered and dynamically controlled, cyclically, for a given time horizon. The DSS is flexible, allowing several parameters to be configured. Experimental examples using randomly generated parameters were conducted to evaluate the effectiveness of the system.     

Betriebliches Identitätsmanagement

Enterprise Identity Management Systems (EIdMS) are an IT-based infrastructure that needs to be integrated in various business processes and related infrastructures. Assessment and preparation of decisions for the introduction need to take the costs, benefits, and the organizational settings into consideration. A variety of methods for the evaluation and decision support of new IT (e. g. EIdMS) are discussed in the literature – however, these are typically based on single dimensions (e. g. financial or technology aspects). This paper proposes a multidimensional decision support framework, based on the Balanced Scorecard concept. The presented approach introduces four perspectives and a related set of initial decision parameters to support decision making. The perspectives are (a) financial/monetary, (b) business processes, (c) supporting processes and (ICT) infrastructure and (d) information security, risks and compliance. Perspectives and adaptable sets of decision parameters also may serve as foundation for software-based decision support instruments.     

A multivariable control scheme in a two-stage anaerobic digestion system described by partial differential equations

This paper deals with the design and application of a nonlinear multivariable controller in an anaerobic digestion system (AD) carried out in two interconnected fixed bed bioreactors. The proposed control scheme is derived from a mathematical model of the AD system described by a set of partial differential equations and consists of an estimator and two nonlinear control laws. The first law is developed to regulate the volatile fatty acids in the first bioreactor while the second aims at maintaining the chemical oxygen demand at predetermined set-points in the second bioreactor. The performance of the control algorithm is evaluated via numerical simulations in the face of load disturbances, parameter kinetic uncertainties and set-point changes. Stability and convergence properties of the proposed control scheme are also addressed in this paper.     

ITEA—interactive trajectories and events analysis: exploring sequences of spatio-temporal events in movement data

Widespread use of GPS and similar technologies makes it possible to collect extensive amounts of trajectory data. These data sets are essential for reasonable decision making in various application domains. Additional information, such as events taking place along a trajectory, makes data analysis challenging, due to data size and complexity. We present an integrated solution for interactive visual analysis and exploration of events along trajectories data. Our approach supports analysis of event sequences at three different levels of abstraction, namely spatial, temporal, and events themselves. Customized views as well as standard views are combined to form a coordinated multiple views system. In addition to trajectories and events, we include on-the-fly derived data in the analysis. We evaluate our integrated solution using the IEEE VAST 2015 Challenge data set. A successful detection and characterization of malicious activity indicate the usefulness and efficiency of the presented approach.