Medical and Biological Image Analysis

Today, technology and information communication are deeply embedded in our life. Information is present and used in many forms: electronic documents, audio, videos, photos, etc. Recent advances in technology, particularly in the computer industry and communication, have motivated organisations to replace their traditional manually stored and exchanged records with computer systems and digital documents for secure storage and smooth transmission. Medical and biological image processing is a numerical method and technique for modifying a digital image to improve or extract information. The main stages of image processing are

Computational Modeling of Airborne Noise Demonstrated Via Benchmarks, Supersonic Jet, and Railway Barrier

In the last several years, there has been a growing demand for mobility to cope with the increasing population. All kinds of transportation have responded to this demand by expanding their networks and introducing new ideas. Rail transportation introduced the idea of high-speed trains and air transportation introduced the idea of high-speed civil transport (HSCT). In this expanding world, the noise legislation is felt to inhibit these plans. Accurate computational methods for noise prediction are in great demand. In the current research, two computational methods are developed to predict noise propagation in air. The first method is based on the finite differencing technique on generalized curvilinear coordinates and it is used to solve linear and nonlinear Euler equations. The dispersion-relation-preserving scheme is adopted for spatial discretization. For temporal integration, either the dispersion-relation-preserving scheme or the low-dispersion-and-dissipation Runge-Kutta scheme is used. Both characteristic and asymptotic nonreflective boundary conditions are studied. Ghost points are employed to satisfy the wall boundary condition. A number of benchmark problems are solved to validate different components of the present method. These include initial pulse in free space, initial pulse reflected from a flat or curved wall, time-periodic train of waves reflected from a flat wall, and oscillatory sink flow. The computed results are compared with the analytical solutions and good agreements are obtained. Using the method developed, the noise of Mach 2.1, perfectly expanded, two-dimensional supersonic jet is computed. The Reynolds-averaged Navier-Stokes equations are solved for the jet mean flow. The instability waves, which are used to excite the jet, are obtained from the solution of the compressible Rayleigh equation. Then, the linearized Euler equations are solved for jet noise. To improve computational efficiency, flow-adapted grid and a multi-block time integration technique are developed. The computations are compared with the experimental results for both the mean flow and the jet noise. Good agreement is obtained. The method proved to be fast and efficient. The second computational method is based on the boundary element technique. The Helmholtz equation is solved for the sound field around a railway noise barrier. Linear elements are used to discretize the barrier surface. Frequency-dependent grids are employed for efficiency. The train noise is represented by a point source located above the nearest rail. The source parameters are estimated from a typical field measurement of train noise spectrum. Both elevated and ground-level train decks are considered. The performance of the noise barrier at low and high frequencies is investigated. Moreover, A-weighted sound pressure levels are calculated. The computed results are successfully compared with field measurements

Mechanical properties of carbon black/poly (ε-caprolactone)-based tissue scaffolds

Carbon black (CB) spherical particles were added to poly(ε-caprolactone) (PCL) polymer to produce strong synthetic tissue scaffolds for biomedical applications. The objective of this paper is to study the mechanical behavior of CB/PCL-based nanocomposites using experimental tests, multi-scale numerical approaches, and analytical models. The mechanical properties of CB/PCL scaffolds were characterized using thermal mechanical analysis and results show a significant increase of the elastic modulus with increasing nanofiller concentration up to 7 wt%. Conversely, finite element computations were performed using a simulated microstructure, and a numerical model based on the representative volume element (RVE) was generated. Thereafter, Young's moduli were computed using a 3D numerical homogenization technique. The approach takes into consideration CB particles’ diameters, as well as their random distribution and agglomerations into PCL. Experimental results were compared with data obtained using numerical approaches and analytical models. Consistency in the results was observed, especially in the case of lower CB fractions

Evaluation of Orifice Flow Meter Accuracy under Pulsation Conditions

Orifice meter is a flow measuring device which is widely used in various industrial applications. Although the device gives accurate measurement during steady flow, measurement errors related to square root and sampling errors are unavoidable if pulsations exist. This research investigatesand improves the performance of an orifice plate flow meter under pulsation effects. A simple model for the pulsating flow through an orifice meter is presented. Square root error (SRE) is estimated. Sampling errors (SE) are reduced by proper selection of the averaging tim

Signature-Free Asynchronous Binary Byzantine Consensus with t<<n/3, O(n²) Messages, and O(1) Expected Time

International audienceThis paper is on broadcast and agreement in asynchronous message-passing systems made up of n processes, and where up to t processes may have a Byzantine Behavior. Its first contribution is a powerful , yet simple, all-to-all broadcast communication abstraction suited to binary values. This abstraction, which copes with up to t < n/3 Byzantine processes, allows each process to broadcast a binary value, and obtain a set of values such that (1) no value broadcast only by Byzantine processes can belong to the set of a correct process, and (2) if the set obtained by a correct process contains a single value v, then the set obtained by any correct process contains v. The second contribution of the paper is a new round-based asynchronous consensus algorithm that copes with up to t < n/3 Byzantine processes. This algorithm is based on the previous binary broadcast abstraction and a weak common coin. In addition of being signature-free and optimal with respect to the value of t, this consensus algorithm has several noteworthy properties: the expected number of rounds to decide is constant; each round is composed of a constant number of communication steps and involves O(n²) messages; each message is composed of a round number plus a constant number of bits. Moreover , the algorithm tolerates message reordering by the adversary (i.e., the Byzantine processes)

Adaptive traffic lights based on traffic flow prediction using machine learning models

Traffic congestion prediction is one of the essential components of intelligent transport systems (ITS). This is due to the rapid growth of population and, consequently, the high number of vehicles in cities. Nowadays, the problem of traffic congestion attracts more and more attention from researchers in the field of ITS. Traffic congestion can be predicted in advance by analyzing traffic flow data. In this article, we used machine learning algorithms such as linear regression, random forest regressor, decision tree regressor, gradient boosting regressor, and K-neighbor regressor to predict traffic flow and reduce traffic congestion at intersections. We used the public roads dataset from the UK national road traffic to test our models. All machine learning algorithms obtained good performance metrics, indicating that they are valid for implementation in smart traffic light systems. Next, we implemented an adaptive traffic light system based on a random forest regressor model, which adjusts the timing of green and red lights depending on the road width, traffic density, types of vehicles, and expected traffic. Simulations of the proposed system show a 30.8% reduction in traffic congestion, thus justifying its effectiveness and the interest of deploying it to regulate the signaling problem in intersections

Influence du pH sur la rétention des révélateurs photographiques hydroquinones par nanofiltration

L’objet de ce travail est d’étudier l’influence du pH sur le taux de rétention lors de la nanofiltration des solutions d’hydroquinone, d’hydroquinone monosulfonate et d’hydroquinone disulfonate seules ou en mélange, qui sont présents dans les bains révélateurs photographiques. Les résultats nous montrent que les taux de rétention et de dissociation de l’hydroquinone sont liés. L’exploitation des courbes de dosage des acides par NaOH conduit à déterminer le pKa pour l’hydroquinone sulfonique acide comme étant égal à 2,82. Les deux acidités de l’hydroquinone disulfonique acide sont caractérisées par pKa1 = 2,28 et pKa2 = 2,44. Quand il n’existe aucune forme ionisée, le taux de rétention reste faible (TR = 10 %). Dès l’apparition d’une ionisation, alors le taux de rétention augmente considérablement (TR = 50 %). A l’apparition de A2-, le taux de rétention subit une nouvelle augmentation (TR = 98 %). Lorsque pH  pKa1 et pH > pKa2, la molécule est ionisée. La rétention est en relation avec la répulsion des charges négatives de la membrane. Les taux de rejet deviennent importants (TR = 90 %). Bien que les taux de rétention de l’hydroquinone, l’hydroquinone sulfonique acide et l’hydroquinone disulfonique acide suivent la même évolution lorsque le composé est seul ou en mélange, on notera un petit décalage entre les courbes du composé en mélange et du composé seul. Nous attribuons ceci aux propriétés chimiques des composés hydroquinones de la solution, à savoir leur mobilité et leur concentration, etc. Une étude relative à l’influence de ces paramètres serait donc envisageable afin de confirmer ces suppositions.Photographic development is the process of transforming the latent images into visible images thanks to a reducer. The principal components of picture development are agents of development, additives, an alkaline substance and an antiscreen. Hydroquinone and its derivatives are the most commonly used agents of development and revealing. Our study aimed to investigate the influence of pH on the retention of hydroquinone, hydroquinone monosulphonate and hydroquinone disulphonate solutions, which are present in the photographic revealing baths after nanofiltration. The results showed that the retention depends on the dissociation state of hydroquinone. In the absence of any ionized form, the retention is weak. As ionization increases, the retention increases considerably. The retention increases further if the A2- form is present. When pH  pKa1 and pH > pKa2, the molecules become ionized, and the retention is affected by repulsion of the negative charges of the membrane. The retention becomes considerable. The retention of hydroquinone, hydroquinone monosulphonate and hydroquinone disulphonate generally follow the same evolution curves when the compound is alone or in a mixture. However a small shift in the curve for compounds in mixtures indicated more retention. We attribute this shift to the chemical properties of the hydroquinone compounds in solution, particularly their mobility and concentration. A further study of influence of these parameters is proposed to confirm these assumptions