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The purpose of this paper is to propose a novel quality of service (QoS)‐aware service composition approach, called SEQOIA, capable of defining at run‐time a service composition plan meeting both functional and non‐functional constraints and optimizing the overall quality of service.

SEQOIA is a semantic‐driven QoS‐aware dynamic composition approach leveraging on an integer linear programming technique (ILP). It exploits the expressiveness of an ontology‐based service profile model handling structural and semantic properties of service descriptions. It represents the service composition problem as a set of functional and non‐functional constraints and an objective function.

The authors developed a proof of concept implementing SEQOIA, as well as an alternative composition solution based on state‐of‐the‐art AI planning and ILP techniques. Results of testing activities show that SEQOIA performs better than the alternative solution over a limited set of candidate services. This behaviour was expected, as SEQOIA guarantees to find the service composition providing the optimal QoS value, while the alternative approach does not provide this guarantee, as it handles separately the specification of the functional service composition flow and the QoS‐based service selection step.

SEQOIA leverages on semantic annotations in order to make service composition feasible by coping with syntactic and structural differences typically existing across different, even similar, service implementations. To ease the adoption of SEQOIA in real enterprise scenarios, the authors chose to leverage on an XML‐based message model of services interfaces (including but not strictly requiring the use of WSDL).

The purpose of this paper is to formally verify the composition of web services to reduce inconsistencies in software architectures.

In order to check the web services composition, the authors use a model‐driven engineering (MDE)‐based approach and to achieve the formalization of web service composition in ACME and check the consistency of this composition, the authors introduce the pattern mediation to formalize web services composition with the ADL ACME, using the concept of architectural style of ACME. Subsequently, a scenario shows how this style can be used in ACMEStudio to detect inconsistencies. The example shows a web travel organization application.

The authors ensure reliability defined through non‐functional properties. To do so, use ACME was used to check assembling consistency of web service composition. In a second part, a SWC2ACME tool was designed and implemented to check if the web services meta‐model conforms to ACME model.

The paper describes a framework which has proven to be useful to ensure a safe design and execution of software architectures, specifically web services composition.

This paper aims to characterize the mineral composition of Martian surfaces based on Thermal Emission Spectrometer (TES; Mars Global Surveyor) as measured in the infrared thermal range. It presents modeling and interpreting of TES spectral data from selected Martian regions from which the atmospheric influences had been removed using radiative transfer algorithm and deconvolution algorithm. The spectra from the dark area of Cimmeria Terra and the bright Isidis Planitia were developed in Philip Christensen’s and Joshua Bandfield’s publications, where these spectra were subjected to spectral deconvolution to estimate the mineral composition of the Martian surface. The results of the analyses of these spectra were used for the modeling of dusty and non-dusty surface of Mars. As an additional source, the mineral compositions of Polish basalts and mafic rocks were used for these surfaces as well as for modeling Martian meteorites Shergottites, Nakhlites and Chassignites. Finally, the spectra for the modeling of the Hellas region were obtained from the Planetary Fourier Spectrometer (PFS) – (Mars Express) and the mineralogical compositions of basalts from the southern part of Poland were used for this purpose. The Hellas region was modeled also using simulated Martian soil samples Phyllosilicatic Mars Regolith Simulant and Sulfatic Mars Regolith Simulant, showing as a result that the composition of this selected area has a high content of sulfates. Linear spectral combination was chosen as the best modeling method. The modeling was performed using PFSLook software written in the Space Research Centre of the Polish Academy of Sciences. Additional measurements were made with an infrared spectrometer in thermal infrared spectroscopy, for comparison with the measurements of PFS and TES. The research uses a kind of modeling that successfully matches mineralogical composition to the measured spectrum from the surface of Mars, which is the main goal of the publication. This method is used for areas where sample collection is not yet possible. The areas have been chosen based on public availability of the data.

The infrared spectra of the Martian surface were modeled by applying the linear combination of the spectra of selected minerals, which then are normalized against the measured surface area with previously separated atmosphere. The minerals for modeling are selected based on the expected composition of the Martian rocks, such as basalt. The software used for this purpose was PFSLook, a program written in C++ at the Space Research Centre of the Polish Academy of Sciences, which is based on adding the spectra of minerals in the relevant percentage, resulting in a final spectrum containing 100 per cent of the minerals.

The results of this work confirmed that there is a relationship between the modeled, altered and unaltered, basaltic surface and the measured spectrum from Martian instruments. Spectral deconvolution makes it possible to interpret the measured spectra from areas that are potentially difficult to explore or to choose interesting areas to explore on site. The method is described for mid-infrared because of software availability, but it can be successfully applied to shortwave spectra in near-infrared (NIR) band for data from the currently functioning Martian spectroscopes.

This work is the only one attempting modeling the spectra of the surface of Mars with a separated atmosphere and to determine the mineralogical composition.

Team composition research considers how configurations (e.g., team-level diversity) of team members’ attributes (e.g., personality, values, demographics) influence important outcomes. Our chapter describes key issues in understanding and effectively managing team composition over time.

We discuss how context shapes team composition. We review empirical research that examined relationships between team composition, and team processes and emergent properties over multiple time points. We review research that examined how composition can be effectively managed over the lifecycle of a team.

Context shapes the nature of team composition itself (e.g., dynamic composition). To the extent that membership change, fluid boundaries, and multiple team membership are present should be accounted for in research and practice. The research we reviewed indicated no, or fleeting effects for surface-level (e.g., demographics) composition on the development of team processes and emergent properties over time, although there were exceptions. Conversely, deep-level composition affected team processes and emergent properties early in a team’s lifespan as well as later. Team composition information can be used in staffing; it can also inform how to best leverage training, leadership, rewards, tasks, and technology to promote team effectiveness.

Teams are the building blocks of contemporary organizations. Understanding and effectively managing team composition over time can increase the likelihood of team.

Our chapter provides novel insights into key issues in understanding and effectively managing team composition over time.

In order to represent, analyze, optimize, and manufacture a component made of multi‐heterogeneous materials for high‐tech applications, a computer model of the heterogeneous component needs to be built first. Heterogeneous materials include composite, functionally graded materials, and heterogeneous materials with a periodic microstructure. Current modeling techniques focus only on capturing the geometric information and cannot satisfy the requirements from modeling the components made of multi‐heterogeneous materials. This paper develops a modeling method, which can be implemented by employing the functions of current CAD graphic software and can obtain the model including both the material information (about its microstructures and constituent composition) and the geometry information without the problems arising from too many data.

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

Service composition phenomenon based on non-scenario aspects are become the latest issues in enterprise software applications of the multi-cloud environment due to the phenomenal increase in a number of Web services. The traditional service composition patterns are hard to support the dynamic, flexible and autonomous service composition in the inter-cloud platform. To address this problem, this paper aims to describe a dynamic service composition framework (SCF) that is enriched with various structural and functional aspects of composition patterns in a cloud computing environment. The proposed methodology helps to integrate various heterogeneous cloud services dynamically to acquire an optimal and novel enterprise solution for delivering the service to the end-users automatically.

SCF and different composition patterns have been used to compose the services present in the inter-cloud architecture of the multi-agent-based system. Further, the proposed dynamic service composition algorithm is illustrated using a hybrid approach, where service are chosen according to various needs of quality of service parameters. Besides, a priority-based service scheduling algorithm is proposed that facilitates the automation of delivering cloud service optimally.

The proposed framework is capable of composing the heterogeneous service and facilitate the structural and functional aspects of service composition process in enterprise cloud-based applications in terms of flexibility, scalability, integrity and dynamicity of the cloud bus. The advantage of the proposed algorithm is that it helps to minimize the execution cost, processing time and get better success rate in delivering the service as per customer’s need.

The novelty of the proposed architecture coordinates cloud participants, automate service discovery pattern, reconfigure scheduled services and focus on aggregating a composite services in inter-cloud environments. Besides, the proposed framework supported several non-functional characteristics such as robustness, flexibility, dynamicity, scalability and reliability of the system.

XML has spread beyond the computer science fields and reached other areas such as, e‐commerce, identification, information storage, instant messaging and others. Data communicated over these domains are now mainly based on XML. Thus, allowing non‐expert programmers to manipulate and control their XML data is essential. The purpose of this paper is to present an XA2C framework intended for both non‐expert and expert programmers and provide them with means to write/draw their XML data manipulation operations.

In the literature, this issue has been dealt with from two perspectives: first, XML alteration/adaptation techniques requiring a certain level of expertise to be implemented and are not unified yet; and second, Mashups, which are not formally defined yet and are not specific to XML data, and XML‐oriented visual languages are based on structural transformations and data extraction mainly and do not allow XML textual data manipulations. The paper discusses existing approaches and the XA2C framework is presented.

The framework is defined based on the dataflow paradigm (visual diagram compositions) while taking advantage of both Mashups and XML‐oriented visual languages by defining a well‐founded modular architecture and an XML‐oriented visual functional composition language based on colored petri nets allowing functional compositions. The framework takes advantage of existing XML alteration/adaptation techniques by defining them as XML‐oriented manipulation functions. A prototype called XA2C is developed and presented here for testing and validating the authors' approach.

This paper presents a detailed description of an XML‐oriented manipulation framework implementing the XML‐oriented composition definition language.

Data service (DS) is a special software service that enables data access in cloud environment and provides a unified data model for cross-origination data integration and data sharing. The purpose of the work is to automatically compose DSs and quickly generate data view to satisfy users' various data requirements (DRs).

The paper proposes an automatic DS composition and view generation approach. DSs are organized into DS dependence graph (DSDG) based on their inherent dependences, and DSs can be automatically composed using the DSDG according to user's DRs. Then, data view will be generated by interpreting the composed DS.

Experimental results with real cross-origination data sets show the proposed approaches have high efficiency and good quality for DS composition and view generation.

The authors propose a DS composition algorithm and a data view generation algorithm according to users' DRs.