A Multi-Level Framework for Validation of Ontology-Driven and Community-Based Web Services Composition

2012 ◽  
Vol 3 (1) ◽  
pp. 58-72
Author(s):  
Nacéra Bennacer ◽  
Guy Vidal-Naquet
Keyword(s):  
Web Services ◽  
Description Logic ◽  
A Priori ◽  
Search Space ◽  
Community Based ◽  
Execution Plan ◽  
Multi Level ◽  
Priori Information ◽  
Dynamic Execution ◽  
Execution Order

This paper proposes an Ontology-driven and Community-based Web Services (OCWS) framework which aims at automating discovery, composition and execution of web services. The purpose is to validate and to execute a user’s request built from the composition of a set of OCWS descriptions and a set of user constraints. The defined framework separates clearly the OCWS external descriptions from internal realistic implementations of e-services. It identifies three levels: the knowledge level, the community level and e-services level and uses different participant agents deployed in a distributed architecture. First, the reasoner agent uses a description logic extended for actions in order to reason about: (i) consistency of the pre-conditions and post-conditions of OCWS descriptions and the user constraints with ontologies semantics, (ii) consistency of the workflow matching assertions and the execution dependency graph. Then the execution plan model is generated automatically to be run by the composer agents using the dynamic execution plan algorithm (DEPA), according to the workflow matching and the established execution order. The community composer agents invoke the appropriate e-services and ensure that the non functional constraints are satisfied. DEPA algorithm works dynamically without a priori information about e-services states and has interesting properties such as taking into account the non-determinism of e-services and reducing the search space.

scholarly journals QoS Based Discovery and Service Provider System

2019 ◽  
pp. 197-204
Author(s):  
Ramesh Kumar ◽  
Lavanya V ◽  
Karthika R ◽  
Harshini B
Keyword(s):  
Web Services ◽  
A Priori ◽  
Search Space ◽  
Added Value ◽  
Layer By Layer ◽  
Semantic Matching ◽  
Semantic Approach ◽  
Service Patterns ◽  
Numeric Estimation ◽  
Multiple Services

We propose a two-step, context-based semantic approach to the problem of matching and ranking Web services for possible service composition. Semantic understanding of Web services may provide added value by identifying new possibilities for compositions of services and context-based semantic. The semantic matching ranking approach is unique since it provides the Web service designer with an explicit numeric estimation of the extent to which a possible composition. This process consists of multiple services that can be executed in sequence or in a parallel process. Given a service request, a set of candidates (available services and service patterns) is dynamically generated layer by layer from inputs to outputs of this request. For each layer, the algorithm traverses a priori search space which is a set of service patterns from historical solutions, then it searches available services from the repositories. That means each layer contains all services and service patterns that can be executed with a set of outputs provided by previous layers. The search process terminates until all the outputs of a request are obtained.

Parallel Interval Algorithm for the Parameter Identification of Linear Elastomechanical Systems

1995 ◽  
Author(s):  
Michael Oeljeklaus ◽  
H. Günther Natke
Keyword(s):  
Parameter Identification ◽  
Measurement Errors ◽  
Degrees Of Freedom ◽  
A Priori ◽  
Search Space ◽  
Information Measurement ◽  
Large Structures ◽  
Speed Up ◽  
Parallel Iterative ◽  
Priori Information

Abstract An interval analytical approach to parameter identification in the frequency domain of mathematical models for linear elasto-mechanical systems is described. A priori information, measurement errors and — if possible — unmeasurable degrees of freedom are modelled in terms of intervals. A parallel iterative update method — based on the interval analytical Gauss-Seidel method — is used to reduce the volume of the parameter search space initially given. The search for the global minimum of the WLS objective function using output residuals is performed on the reduced parameter space in a last step1. Subsystem identification and sub-model synthesis are used in the case of realistic models with a large number of degrees of freedom. Parallelization of the algorithm with respect to subsystems is applied in the case of large structures to reduce the amount of memory and to speed-up the computation. Test results for some simulations for a test structure are given in order to illustrate the method.

scholarly journals An Information-Motivated Exploration Agent to Locate Stationary Persons with Wireless Transmitters in Unknown Environments

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7695
Author(s):  
Daniel Barry ◽  
Andreas Willig ◽  
Graeme Woodward
Keyword(s):  
Information Gain ◽  
Search Algorithm ◽  
A Priori ◽  
Search Space ◽  
Wireless Transmitters ◽  
Multiple Sensors ◽  
Single Target ◽  
Information Exploration ◽  
Speed Up ◽  
Priori Information

Unmanned Aerial Vehicles (UAVs) show promise in a variety of applications and recently were explored in the area of Search and Rescue (SAR) for finding victims. In this paper we consider the problem of finding multiple unknown stationary transmitters in a discrete simulated unknown environment, where the goal is to locate all transmitters in as short a time as possible. Existing solutions in the UAV search space typically search for a single target, assume a simple environment, assume target properties are known or have other unrealistic assumptions. We simulate large, complex environments with limited a priori information about the environment and transmitter properties. We propose a Bayesian search algorithm, Information Exploration Behaviour (IEB), that maximizes predicted information gain at each search step, incorporating information from multiple sensors whilst making minimal assumptions about the scenario. This search method is inspired by the information theory concept of empowerment. Our algorithm shows significant speed-up compared to baseline algorithms, being orders of magnitude faster than a random agent and 10 times faster than a lawnmower strategy, even in complex scenarios. The IEB agent is able to make use of received transmitter signals from unknown sources and incorporate both an exploration and search strategy.

scholarly journals Adaptive Randomness: A New Population Initialization Method

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Weifeng Pan ◽  
Kangshun Li ◽  
Muchou Wang ◽  
Jing Wang ◽  
Bo Jiang
Keyword(s):  
A Priori ◽  
Optimization Methods ◽  
Search Space ◽  
Population Based ◽  
Convergence Speed ◽  
Initial Population ◽  
Wide Range ◽  
Priori Information ◽  
Better Than

Population initialization is a crucial task in population-based optimization methods, which can affect the convergence speed and also the quality of the final solutions. Generally, if no a priori information about the solutions is available, the initial population is often selected randomly using random numbers. This paper presents a new initialization method by applying the concept of adaptive randomness (AR) to distribute the individuals as spaced out as possible over the search space. To verify the performance of AR, a comprehensive set of 34 benchmark functions with a wide range of dimensions is utilized. Conducted experiments demonstrate that AR-based population initialization performs better than other population initialization methods such as random population initialization, opposition-based population initialization, and generalized opposition-based population initialization in the convergence speed and the quality of the final solutions. Further, the influences of the problem dimensionality, the new control parameter, and the number of trial individuals are also investigated.

Multi-Level Web Service Clustering to Bootstrap the Web Service Discovery and Selection

2019 ◽  
pp. 44-68
Author(s):  
Banage T. G. S. Kumara ◽  
Incheon Paik ◽  
Koswatte R. C. Koswatte
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Composition ◽  
Service Discovery ◽  
Value Added ◽  
Search Space ◽  
Clustering Approach ◽  
Multi Level ◽  
Service Clustering ◽  
Service Discovery And Selection

Existing technologies for web services have been extended to give the value-added customized services to users through the service composition. Service composition consists of four major stages: planning, discovery, selection, and execution. However, with the proliferation of web services, service discovery and selection are becoming challenging and time-consuming tasks. Organizing services into similar clusters is a very efficient approach. Existing clustering approaches have problems that include discovering semantic characteristics, loss of semantic information, and a shortage of high-quality ontologies. Thus, the authors proposed hybrid term similarity-based clustering approach in their previous work. Further, the current clustering approaches do not consider the sub-clusters within a cluster. In this chapter, the authors propose a multi-level clustering approach to prune the search space further in discovery process. Empirical study of the prototyping system has proved the effectiveness of the proposed multi-level clustering approach.

Innovative Approach to Information Search by Example of a Patent Analysis of an Important Substitution Plan

2020 ◽  
pp. 143-157
Author(s):  
Maria A. Milkova
Keyword(s):  
Information Search ◽  
Topic Modeling ◽  
Cognitive Biases ◽  
A Priori ◽  
Import Substitution ◽  
Innovative Approach ◽  
Iterative Search ◽  
Comprehensive Picture ◽  
Priori Information ◽  
Selection Of

Nowadays the process of information accumulation is so rapid that the concept of the usual iterative search requires revision. Being in the world of oversaturated information in order to comprehensively cover and analyze the problem under study, it is necessary to make high demands on the search methods. An innovative approach to search should flexibly take into account the large amount of already accumulated knowledge and a priori requirements for results. The results, in turn, should immediately provide a roadmap of the direction being studied with the possibility of as much detail as possible. The approach to search based on topic modeling, the so-called topic search, allows you to take into account all these requirements and thereby streamline the nature of working with information, increase the efficiency of knowledge production, avoid cognitive biases in the perception of information, which is important both on micro and macro level. In order to demonstrate an example of applying topic search, the article considers the task of analyzing an import substitution program based on patent data. The program includes plans for 22 industries and contains more than 1,500 products and technologies for the proposed import substitution. The use of patent search based on topic modeling allows to search immediately by the blocks of a priori information – terms of industrial plans for import substitution and at the output get a selection of relevant documents for each of the industries. This approach allows not only to provide a comprehensive picture of the effectiveness of the program as a whole, but also to visually obtain more detailed information about which groups of products and technologies have been patented.

scholarly journals Computational Method for Wavefront Sensing Based on Transport-Of-Intensity Equation

Photonics ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 177
Author(s):  
Iliya Gritsenko ◽  
Michael Kovalev ◽  
George Krasin ◽  
Matvey Konoplyov ◽  
Nikita Stsepuro
Keyword(s):  
A Priori ◽  
Spherical Wave ◽  
Computational Method ◽  
Optical Systems ◽  
Radius Of Curvature ◽  
Imaging Method ◽  
Wavefront Sensing ◽  
Phase Imaging ◽  
Transport Of Intensity Equation ◽  
Priori Information

Recently the transport-of-intensity equation as a phase imaging method turned out as an effective microscopy method that does not require the use of high-resolution optical systems and a priori information about the object. In this paper we propose a mathematical model that adapts the transport-of-intensity equation for the purpose of wavefront sensing of the given light wave. The analysis of the influence of the longitudinal displacement z and the step between intensity distributions measurements on the error in determining the wavefront radius of curvature of a spherical wave is carried out. The proposed method is compared with the traditional Shack–Hartmann method and the method based on computer-generated Fourier holograms. Numerical simulation showed that the proposed method allows measurement of the wavefront radius of curvature with radius of 40 mm and with accuracy of ~200 μm.

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