Managing Quality Properties of Web Service Compositions

Web services from different partners can be combined to applications that realize a more complex business goal. Such applications built as Web service compositions define how interactions between Web services take place in order to implement the business logic. Web service compositions not only have to provide the desired functionality but also have to comply with certain Quality of Service (QoS) levels. Maximizing the users' satisfaction, also reflected as Quality of Experience (QoE), is a primary goal to be achieved in a Service-Oriented Architecture (SOA). Unfortunately, in a dynamic environment like SOA unforeseen situations might appear like services not being available or not responding in the desired time frame. In such situations, appropriate actions need to be triggered in order to avoid the violation of QoS and QoE constraints. In this thesis, proper solutions are developed to manage Web services and Web service compositions with regard to QoS and QoE requirements. The Business Process Rules Language (BPRules) was developed to manage Web service compositions when undesired QoS or QoE values are detected. BPRules provides a rich set of management actions that may be triggered for controlling the service composition and for improving its quality behavior. Regarding the quality properties, BPRules allows to distinguish between the QoS values as they are promised by the service providers, QoE values that were assigned by end-users, the monitored QoS as measured by our BPR framework, and the predicted QoS and QoE values. BPRules facilitates the specification of certain user groups characterized by different context properties and allows triggering a personalized, context-aware service selection tailored for the specified user groups. In a service market where a multitude of services with the same functionality and different quality values are available, the right services need to be selected for realizing the service composition. We developed new and efficient heuristic algorithms that are applied to choose high quality services for the composition. BPRules offers the possibility to integrate multiple service selection algorithms. The selection algorithms are applicable also for non-linear objective functions and constraints. The BPR framework includes new approaches for context-aware service selection and quality property predictions. We consider the location information of users and services as context dimension for the prediction of response time and throughput. The BPR framework combines all new features and contributions to a comprehensive management solution. Furthermore, it facilitates flexible monitoring of QoS properties without having to modify the description of the service composition. We show how the different modules of the BPR framework work together in order to execute the management rules. We evaluate how our selection algorithms outperform a genetic algorithm from related research. The evaluation reveals how context data can be used for a personalized prediction of response time and throughput.

The effect of selective decontamination of the digestive tract on mortality in multiple trauma patients: a multicenter randomized controlled trial

Objective: Evaluation of selective decontamination of the digestive tract (SDD) on late mortality in ventilated trauma patients in an intensive care unit (ICU). Methods: A multicenter, randomized controlled trial was undertaken in 401 trauma patients with Hospital Trauma Index-Injury Severity Score of 16 or higher. Patients were randomized to control (n = 200) or SDD (n = 201), using polymyxin E, tobramycin, and amphotericin B in throat and gut throughout ICU treatment combined with cefotaxime for 4 days. Primary endpoint was late mortality excluding early death from hemorrhage or craniocerebral injury. Secondary endpoints were infection and organ dysfunction. Results: Mortality was 20.9% with SDD and 22.0% in controls. Overall late mortality was 15.3% (57/372) as 29 patients died from cerebral injury, 16 SDD and 13 control. The odds ratio (95% confidence intervals) of late mortality for SDD relative to control was 0.75 (0.40-1.37), corresponding to estimates of 13.4% SDD and 17.2% control. The overall infection rate was reduced in the test group (48.8% vs. 61.0%). SDD reduced lower airway infections (30.9% vs. 50.0%) and bloodstream infections due to aerobic Gram-negative bacilli (2.5% vs. 7.5%). No difference in organ dysfunction was found. Concluson: This study demonstrates that SDD significantly reduces infection in multiple trauma, although this RCT in 401 patients was underpowered to detect a mortality benefit.

Search space pruning and global optimisation of Multiple Gravity Assist spacecraft trajectories

We introduce and describe the Multiple Gravity Assist problem, a global optimisation problem that is of great interest in the design of spacecraft and their trajectories. We discuss its formalization and we show, in one particular problem instance, the performance of selected state of the art heuristic global optimisation algorithms. A deterministic search space pruning algorithm is then developed and its polynomial time and space complexity derived. The algorithm is shown to achieve search space reductions of greater than six orders of magnitude, thus reducing significantly the complexity of the subsequent optimisation.

Maximizing revenue in Grid markets using an economically enhanced resource manager

Traditional resource management has had as its main objective the optimization of throughput, based on parameters such as CPU, memory, and network bandwidth. With the appearance of Grid markets, new variables that determine economic expenditure, benefit and opportunity must be taken into account. The Self-organizing ICT Resource Management (SORMA) project aims at allowing resource owners and consumers to exploit market mechanisms to sell and buy resources across the Grid. SORMA's motivation is to achieve efficient resource utilization by maximizing revenue for resource providers and minimizing the cost of resource consumption within a market environment. An overriding factor in Grid markets is the need to ensure that the desired quality of service levels meet the expectations of market participants. This paper explains the proposed use of an economically enhanced resource manager (EERM) for resource provisioning based on economic models. In particular, this paper describes techniques used by the EERM to support revenue maximization across multiple service level agreements and provides an application scenario to demonstrate its usefulness and effectiveness. Copyright © 2008 John Wiley & Sons, Ltd.

Selection of funding schemes by a borrowing decision model: a Hong Kong case study

In financial decision-making, a number of mathematical models have been developed for financial management in construction. However, optimizing both qualitative and quantitative factors and the semi-structured nature of construction finance optimization problems are key challenges in solving construction finance decisions. The selection of funding schemes by a modified construction loan acquisition model is solved by an adaptive genetic algorithm (AGA) approach. The basic objectives of the model are to optimize the loan and to minimize the interest payments for all projects. Multiple projects being undertaken by a medium-size construction firm in Hong Kong were used as a real case study to demonstrate the application of the model to the borrowing decision problems. A compromise monthly borrowing schedule was finally achieved. The results indicate that Small and Medium Enterprise (SME) Loan Guarantee Scheme (SGS) was first identified as the source of external financing. Selection of sources of funding can then be made to avoid the possibility of financial problems in the firm by classifying qualitative factors into external, interactive and internal types and taking additional qualitative factors including sovereignty, credit ability and networking into consideration. Thus a more accurate, objective and reliable borrowing decision can be provided for the decision-maker to analyse the financial options.

The automatic layout model in the sequencing of construction activities of multi-objective diaphragm wall unit by using self-learning neural network

Foundation construction process has been an important key point in a successful construction engineering. The frequency of using diaphragm wall construction method among many deep excavation construction methods in Taiwan is the highest in the world. The traditional view of managing diaphragm wall unit in the sequencing of construction activities is to establish each phase of the sequencing of construction activities by heuristics. However, it conflicts final phase of engineering construction with unit construction and effects planning construction time. In order to avoid this kind of situation, we use management of science in the study of diaphragm wall unit construction to formulate multi-objective combinational optimization problem. Because the characteristic (belong to NP-Complete problem) of problem mathematic model is multi-objective and combining explosive, it is advised that using the 2-type Self-Learning Neural Network (SLNN) to solve the N=12, 24, 36 of diaphragm wall unit in the sequencing of construction activities program problem. In order to compare the liability of the results, this study will use random researching method in comparison with the SLNN. It is found that the testing result of SLNN is superior to random researching method in whether solution-quality or Solving-efficiency.

A variational method to retrieve the extinction profile in liquid clouds using multiple field-of-view lidar

Liquid clouds play a profound role in the global radiation budget but it is difficult to remotely retrieve their vertical profile. Ordinary narrow field-of-view (FOV) lidars receive a strong return from such clouds but the information is limited to the first few optical depths. Wideangle multiple-FOV lidars can isolate radiation scattered multiple times before returning to the instrument, often penetrating much deeper into the cloud than the singly-scattered signal. These returns potentially contain information on the vertical profile of extinction coefficient, but are challenging to interpret due to the lack of a fast radiative transfer model for simulating them. This paper describes a variational algorithm that incorporates a fast forward model based on the time-dependent two-stream approximation, and its adjoint. Application of the algorithm to simulated data from a hypothetical airborne three-FOV lidar with a maximum footprint width of 600m suggests that this approach should be able to retrieve the extinction structure down to an optical depth of around 6, and total opticaldepth up to at least 35, depending on the maximum lidar FOV. The convergence behavior of Gauss-Newton and quasi-Newton optimization schemes are compared. We then present results from an application of the algorithm to observations of stratocumulus by the 8-FOV airborne “THOR” lidar. It is demonstrated how the averaging kernel can be used to diagnose the effective vertical resolution of the retrieved profile, and therefore the depth to which information on the vertical structure can be recovered. This work enables exploitation of returns from spaceborne lidar and radar subject to multiple scattering more rigorously than previously possible.

Trade-offs and responsiveness of the single-layer urban canopy parametrization in WRF: an offline evaluation using the MOSCEM optimization algorithm and field observations

For an increasing number of applications, mesoscale modelling systems now aim to better represent urban areas. The complexity of processes resolved by urban parametrization schemes varies with the application. The concept of fitness-for-purpose is therefore critical for both the choice of parametrizations and the way in which the scheme should be evaluated. A systematic and objective model response analysis procedure (Multiobjective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm) is used to assess the fitness of the single-layer urban canopy parametrization implemented in the Weather Research and Forecasting (WRF) model. The scheme is evaluated regarding its ability to simulate observed surface energy fluxes and the sensitivity to input parameters. Recent amendments are described, focussing on features which improve its applicability to numerical weather prediction, such as a reduced and physically more meaningful list of input parameters. The study shows a high sensitivity of the scheme to parameters characterizing roof properties in contrast to a low response to road-related ones. Problems in partitioning of energy between turbulent sensible and latent heat fluxes are also emphasized. Some initial guidelines to prioritize efforts to obtain urban land-cover class characteristics in WRF are provided. Copyright © 2010 Royal Meteorological Society and Crown Copyright.

Urban and agricultural soils: conflicts and trade-offs in the optimization of ecosystem services

On-going human population growth and changing patterns of resource consumption are increasing global demand for ecosystem services, many of which are provided by soils. Some of these ecosystem services are linearly related to the surface area of pervious soil, whereas others show non-linear relationships, making ecosystem service optimization a complex task. As limited land availability creates conflicting demands among various types of land use, a central challenge is how to weigh these conflicting interests and how to achieve the best solutions possible from a perspective of sustainable societal development. These conflicting interests become most apparent in soils that are the most heavily used by humans for specific purposes: urban soils used for green spaces, housing, and other infrastructure and agricultural soils for producing food, fibres and biofuels. We argue that, despite their seemingly divergent uses of land, agricultural and urban soils share common features with regards to interactions between ecosystem services, and that the trade-offs associated with decision-making, while scale- and context-dependent, can be surprisingly similar between the two systems. We propose that the trade-offs within land use types and their soil-related ecosystems services are often disproportional, and quantifying these will enable ecologists and soil scientists to help policy makers optimizing management decisions when confronted with demands for multiple services under limited land availability.

Engineering a plant community to deliver multiple ecosystem services

The sustainable delivery of multiple ecosystem services requires the management of functionally diverse biological communities. In an agricultural context, an emphasis on food production has often led to a loss of biodiversity to the detriment of other ecosystem services such as the maintenance of soil health and pest regulation. In scenarios where multiple species can be grown together, it may be possible to better balance environmental and agronomic services through the targeted selection of companion species. We used the case study of legume-based cover crops to engineer a plant community that delivered the optimal balance of six ecosystem services: early productivity, regrowth following mowing, weed suppression, support of invertebrates, soil fertility building (measured as yield of following crop), and conservation of nutrients in the soil. An experimental species pool of 12 cultivated legume species was screened for a range of functional traits and ecosystem services at five sites across a geographical gradient in the United Kingdom. All possible species combinations were then analyzed, using a process-based model of plant competition, to identify the community that delivered the best balance of services at each site. In our system, low to intermediate levels of species richness (one to four species) that exploited functional contrasts in growth habit and phenology were identified as being optimal. The optimal solution was determined largely by the number of species and functional diversity represented by the starting species pool, emphasizing the importance of the initial selection of species for the screening experiments. The approach of using relationships between functional traits and ecosystem services to design multifunctional biological communities has the potential to inform the design of agricultural systems that better balance agronomic and environmental services and meet the current objective of European agricultural policy to maintain viable food production in the context of the sustainable management of natural resources.

Objective determination of the extratropical transition of tropical cyclones in the Northern Hemisphere

Extratropical transition (ET) has eluded objective identification since the realisation of its existence in the 1970s. Recent advances in numerical, computational models have provided data of higher resolution than previously available. In conjunction with this, an objective characterisation of the structure of a storm has now become widely accepted in the literature. Here we present a method of combining these two advances to provide an objective method for defining ET. The approach involves applying K-means clustering to isolate different life-cycle stages of cyclones and then analysing the progression through these stages. This methodology is then tested by applying it to five recent years from the European Centre of Medium-Range Weather Forecasting operational analyses. It is found that this method is able to determine the general characteristics for ET in the Northern Hemisphere. Between 2008 and 2012, 54% (±7, 32 of 59) of Northern Hemisphere tropical storms are estimated to undergo ET. There is great variability across basins and time of year. To fully capture all the instances of ET is necessary to introduce and characterise multiple pathways through transition. Only one of the three transition types needed has been previously well-studied. A brief description of the alternate types of transitions is given, along with illustrative storms, to assist with further study

Human resource allocation management in multiple projects using sociometric techniques

This article describes a new application of key psychological concepts in the area of Sociometry for the selection of workers within organizations in which projects are developed. The project manager can use a new procedure to determine which individuals should be chosen from a given pool of resources and how to combine them into one or several simultaneous groups/projects in order to assure the highest possible overall work efficiency from the standpoint of social interaction. The optimization process was carried out by means of matrix calculations performed using a computer or even manually, and based on a number of new ratios generated ad-hoc and composed on the basis of indices frequently used in Sociometry.

Paracoccidioidomycosis-related mortality trend, state of Sao Paulo, Brazil: a study using multiple causes of death

Objective. To investigate mortality in which paracoccidioidomycosis appears on any line or part of the death certificate. Method. Mortality data for 1985-2005 were obtained from the multiple cause-of-death database maintained by the Sao Paulo State Data Analysis System (SEADE). Standardized mortality coefficients were calculated for paracoccidioidomycosis as the underlying cause-of-death and as an associated cause-of-death, as well as for the total number of times paracoccidioidomycosis was mentioned on the death certificates. Results. During this 21-year period, there were 1950 deaths related to paracoccidioidomycosis; the disease was the underlying cause-of-death in 1 164 cases (59.69%) and an associated cause-of-death in 786 (40.31%). Between 1985 and 2005 records show a 59.8% decline in the mortality coefficient due to paracoccidioidomycosis as the underlying cause and a 53.0% decline in the mortality as associated cause. The largest number of deaths occurred among men, in the older age groups, and among rural workers, with an upward trend in winter months. The main causes associated with paracoccidioidomycosis as the underlying cause-of-death were pulmonary fibrosis, chronic lower respiratory tract diseases, and pneumonias. Malignant neoplasms and AIDS were the main underlying causes when paracoccidioidomycosis was an associated cause-of-death. The decision tables had to be adapted for the automated processing of causes of death in death certificates where paracoccidioidomycosis was mentioned. Conclusions. Using the multiple cause-of-death method together with the traditional underlying cause-of-death approach provides a new angle on research aimed at broadening our understanding of the natural history of paracoccidioidomycosis.

Is bird incidence in Atlantic forest fragments influenced by landscape patterns at multiple scales?

The degree to which habitat fragmentation affects bird incidence is species specific and may depend on varying spatial scales. Selecting the correct scale of measurement is essential to appropriately assess the effects of habitat fragmentation on bird occurrence. Our objective was to determine which spatial scale of landscape measurement best describes the incidence of three bird species (Pyriglena leucoptera, Xiphorhynchus fuscus and Chiroxiphia caudata) in the fragmented Brazilian Atlantic forest and test if multi-scalar models perform better than single-scalar ones. Bird incidence was assessed in 80 forest fragments. The surrounding landscape structure was described with four indices measured at four spatial scales (400-, 600-, 800- and 1,000-m buffers around the sample points). The explanatory power of each scale in predicting bird incidence was assessed using logistic regression, bootstrapped with 1,000 repetitions. The best results varied between species (1,000-m radius for P. leucoptera; 800-m for X. fuscus and 600-m for C. caudata), probably due to their distinct feeding habits and foraging strategies. Multi-scale models always resulted in better predictions than single-scale models, suggesting that different aspects of the landscape structure are related to different ecological processes influencing bird incidence. In particular, our results suggest that local extinction and (re)colonisation processes might simultaneously act at different scales. Thus, single-scale models may not be good enough to properly describe complex pattern-process relationships. Selecting variables at multiple ecologically relevant scales is a reasonable procedure to optimise the accuracy of species incidence models.

Heuristics for the one-dimensional cutting stock problem with limited multiple stock lengths

This paper deals with the classical one-dimensional integer cutting stock problem, which consists of cutting a set of available stock lengths in order to produce smaller ordered items. This process is carried out in order to optimize a given objective function (e.g., minimizing waste). Our study deals with a case in which there are several stock lengths available in limited quantities. Moreover, we have focused on problems of low demand. Some heuristic methods are proposed in order to obtain an integer solution and compared with others. The heuristic methods are empirically analyzed by solving a set of randomly generated instances and a set of instances from the literature. Concerning the latter. most of the optimal solutions of these instances are known, therefore it was possible to compare the solutions. The proposed methods presented very small objective function value gaps. (C) 2008 Elsevier Ltd. All rights reserved.