QoS-aware optimal and automated semantic web service composition with user’s constraints

Automated semantic web service composition is one of the critical research challenges of service-oriented computing, since it allows users to create an application simply by specifying the inputs that the application requires, the outputs it should produce, and any constraints it should respect. The composition problem has been handled using a variety of techniques, from artificial intelligence planning to optimization algorithms. However no approach so far has focused on handling three composition dimensions simultaneously, producing solutions that are: (1) fully functional (i.e., fully executable) by using a mechanism of semantic matching between the services involved in the solutions, (2) are optimized according to non-functional quality-of-service (QoS) measurements, and (3) respect global QoS constraints. This paper presents a novel approach based on a Harmony Search algorithm that addresses these three dimensions simultaneously through a fitness function, to select the optimal or near-optimal solution in semantic web service composition. In our approach, the search space is modeled as a planning-graph structure which encodes all the possible composition solutions for a given user request. To improve the selection process we have compared the original Harmony Search algorithm with its recently developed variants Improved Harmony Search (IHS) algorithm and Global Best Harmony Search (GHS) algorithm. An experimentation of the approach conducted with an extended version of the Web Service Challenge 2009 dataset showed that: (1) our approach is efficient and effective to extract the optimal or near-optimal composition in diverse scenarios; and (2) both variants IHS and GHS algorithms have brought improvements in terms of fitness and execution time.     

Spectral definition of the macro-algae Ulva curvata in the back-barrier bays of the Eastern Shore of Virginia,USA

We have developed methods to determine the visible (VIS) to near-infrared (NIR) spectral properties of thalli and epiphytes of bloom-forming and green macrophyte Ulva curvata in back-barrier lagoons in Virginia, USA. A 2% increase in NIR thalli reflectance from winter to summer (ca. 9.5%) matched the drop in summer NIR transmittance (ca. 90%). In contrast, summer and winter VIS reflectance (reaching 6%) were nearly identical while winter transmittance (ca. 85%) was 10–20% higher. NIR absorption remained at 5% but VIS absorption increased by 10–20% from winter to summer. Replicate consistency substantiated the high transmittance difference indicating thallus composition changed from summer to winter. Epiphytes increased thallus reflectance (<ca. 4%) and decreased transmittance (<ca. 10%) and exhibited broadband VIS and NIR absorptions in summer and selective peaks in winter. A simulation coupling water extinction with thallus reflectance and transmittance found seven submerged thalli maximized the surface reflectance enhancement (ca. 2.5%).     

Flat-plate techniques for measuring reflectance of macro-algae (Ulva curvata)

We tested the consistency and accuracy of flat-plate spectral measurements (400–1000 nm) of the marine macrophyte Ulva curvata. With sequential addition of Ulva thallus layers, the reflectance progressively increased from 6% to 9% with six thalli in the visible (VIS) and from 5% to 19% with ten thalli in the near infrared (NIR). This progressive increase was simulated by a mathematical calculation based on an Ulva thallus diffuse reflectance weighted by a transmittance power series. Experimental and simulated reflectance differences that were particularly high in the NIR most likely resulted from residual water and layering structure unevenness in the experimental progression. High spectral overlap existed between fouled and non-fouled Ulva mats and the coexistent lagoon mud in the VIS, whereas in the NIR, spectral contrast was retained but substantially dampened by fouling.     

Monte Carlo Estimation of a Joint Density Using Malliavin Calculus, and Application to American Options

We use the Malliavin integration by parts formula in order to provide a family of representations of the joint density (which does not involve Dirac measures) of (X_θ, X _{θ + δ}), where X is a d-dimensional Markov diffusion (d ≥ 1), θ > 0 and δ > 0. Following Bouchard et al. (2004), the different representations are determined by a pair of localizing functions. We discuss the problem of variance reduction within the family of separable localizing functions: We characterize a pair of exponential functions as the unique integrated-variance minimizer among this class of separable localizing functions. We test our method on the d-dimensional Brownian motion and provide an application to the problem of American options valuation by the quantization tree method introduced by Bally et al. (2002). MSC 1991 Subject Classifications: Primary 60H07 65C05, secondary 49-00     

Skin Lesion Segmentation and Classification Using Conventional and Deep Learning Based Framework

Background: In medical image analysis, the diagnosis of skin lesions remains a challenging task. Skin lesion is a common type of skin cancer that exists worldwide. Dermoscopy is one of the latest technologies used for the diagnosis of skin cancer. Challenges: Many computerized methods have been introduced in the literature to classify skin cancers. However, challenges remain such as imbalanced datasets, low contrast lesions, and the extraction of irrelevant or redundant features. Proposed Work: In this study, a new technique is proposed based on the conventional and deep learning framework. The proposed framework consists of two major tasks: lesion segmentation and classification. In the lesion segmentation task, contrast is initially improved by the fusion of two filtering techniques and then performed a color transformation to color lesion area color discrimination. Subsequently, the best channel is selected and the lesion map is computed, which is further converted into a binary form using a thresholding function. In the lesion classification task, two pre-trained CNN models were modified and trained using transfer learning. Deep features were extracted from both models and fused using canonical correlation analysis. During the fusion process, a few redundant features were also added, lowering classification accuracy. A new technique called maximum entropy score-based selection (MESbS) is proposed as a solution to this issue. The features selected through this approach are fed into a cubic support vector machine (C-SVM) for the final classification. Results: The experimental process was conducted on two datasets: ISIC 2017 and HAM10000. The ISIC 2017 dataset was used for the lesion segmentation task, whereas the HAM10000 dataset was used for the classification task. The achieved accuracy for both datasets was 95.6% and 96.7%, respectively, which was higher than the existing techniques.     

Compatibilization of regenerated low density polyethylene/poly(vinyl chloride) blends

The aim of this work is to study the valorization of regenerated low density polyethylene (rLDPE) by blending with PVC in the presence of chlorinated polyethylene (CPE) as compatibilizer. For this purpose, four rLDPE samples coming from neat or dirty wastes were used. They were obtained after milling, washing, and extrusion in a conventional recycling plant. They were first characterized in terms of physicochemical (density, melt flow index, water absorption, and level of oxidation by Fourier transform infrared spectroscopy) and mechanical (tensile and shore D hardness) properties. The effect of the ratio of PVC on these physical and mechanical properties was then investigated. These binary blends exhibited lower properties than those of the separated polymers. The addition of CPE to the binary blend with weight proportion of 50/50 leads to a substantial improvement of the considered properties which is due to a better interfacial adhesion between rLDPE and PVC as evidenced by the analysis of the morphology of the blends by scanning electron microscopy. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Interaction of Two Unequal Turbulent Jets with Different Temperature

This paper examines the control and heat transfer process of the mixing of a strong jet and a weak jet. The control of the jet diffusion may be required in many devices such as cooling systems, combustors, gas turbines, heating or cooling surfaces, cooling problem techniques, mixing flows, etc. A steady three‐dimensional problem is solved by the finite volume method using RANS modeling. The validation confirms that both RSM and k‐ε realizable models predict more accurately this flow configuration than the standard k‐ε model. A parametric study is conducted on the basis of ratios of the momentum of the two jets. Due to the Coanda effect, the deviation of the weak jet has been highlighted for several momentum ratios. In the fully developed flow region, after the confluence point, the structure of a single jet flow is recovered. However, the point of maximum velocity is shifted toward the side of the strong jet. For a given velocities ratio of 0.25, the temperatures ratio between the two jets is checked. The location of maximum temperature of the jet is almost constant for diverse values of 0.8 ≤ λ_T ≤ 1. The location of the point of maximum temperature varies linearly according to λ_T.     

Heat transfer enhancement in a parabolic trough solar receiver using longitudinal fins and nanofluids

In this paper,we present a three dimensional numerical investigation of heat transfer in a parabolic trough collector receiver with longitudinal fins using different kinds of nanofluid,with an operational temperature of 573 K and nanoparticle concentration of 1% in volume.The outer surface of the absorber receives a non-uniform heat flux,which is obtained by using the Monte Carlo ray tracing technique.The numerical results are contrasted with empirical results available in the open literature.A significant improvement of heat transfer is derived when the Reynolds number varies in the range 2.57×104≤ Re≤ 2.57×105,the tube-side Nusselt number increases from 1.3 to 1.8 times,also the metallic nanoparticles improve heat transfer greatly than other nanoparticles,combining both mechanisms provides better heat transfer and higher thermo-hydraulic performance.     

Risk assessment of Bt crops on the non‐target plant‐associated insects and soil organisms

Transgenic plants containing Bacillus thuringiensis (Bt) genes are being cultivated worldwide to express toxic insecticidal proteins. However, the commercial utilisation of Bt crops greatly highlights biosafety issues worldwide. Therefore, assessing the risks caused by genetically modified crops prior to their commercial cultivation is a critical issue to be addressed. In agricultural biotechnology, the goal of safety assessment is not just to identify the safety of a genetically modified (GM) plant, rather to demonstrate its impact on the ecosystem. Various experimental studies have been made worldwide during the last 20 years to investigate the risks and fears associated with non‐target organisms (NTOs). The NTOs include beneficial insects, natural pest controllers, rhizobacteria, growth promoting microbes, pollinators, soil dwellers, aquatic and terrestrial vertebrates, mammals and humans. To highlight all the possible risks associated with different GM events, information has been gathered from a total of 76 articles, regarding non‐target plant and soil inhabiting organisms, and summarised in the form of the current review article. No significant harmful impact has been reported in any case study related to approved GM events, although critical risk assessments are still needed before commercialisation of these crops. © 2016 Society of Chemical Industry     

Investigation of pro-oxidant agents’ effects on the ageing of polypropylene bags

ABSTRACT

In this work, the effects of calcium, aluminium and zinc stearates as pro-oxidant agents on the degradation of polypropylene (PP) bags were studied under natural weathering of Mediterranean climate. Samples were taken off periodically and characterised. Tensile properties, structural modifications, morphological and thermal properties were investigated. All the considered properties were affected by the presence of the three pro-oxidant agents. The pro-oxidants can be classified as follows: Zinc stearate > Calcium stearate>Aluminium stearate.