Use of Ontologies as Representation Support of Workflows Oriented to Administrative Management

One of the applications of workflow systems is the management of administrative processes characterized by the transmission of information elements among users of an organization. Tasks contained in these processes are carried out by users responsible for confirming, modifying or adding information throughout. These processes need to be defined in workflow management systems in which all the elements are perfectly identified and are easily adaptable to changes that may arise in the sequences of tasks, in the users involved or in the data transmitted from one task to another. For this kind of processes is easier to reuse those represented in ontologies. On one hand, existing ontologies for representing some domain elements can be reused. At the same time, ontologies have an excellent expressive capacity to define tasks, their relationships and the flow control among them with precision. This paper proposes a complete model, together with the necessary software tools, for tackling this issue.

Efficient simulation of tissue-like P systems by transition cell-like P systems

In the framework of P systems, it is known that the construction of exponential number of objects in polynomial time is not enough to efficiently solve NP-complete problems. Nonetheless, it could be sufficient to create an exponential number of membranes in polynomial time. Working with P systems whose membrane structure does not increase in size, it is known that it is not possible to solve computationally hard problems (unless P = NP), basically due to the impossibility of constructing exponential number of membranes, in polynomial time, using only evolution, communication and dissolution rules. In this paper we show how a family of recognizer tissue P systems with symport/antiport rules which solves a decision problem can be efficiently simulated by a family of basic recognizer P systems solving the same problem. This simulation allows us to transfer the result about the limitations in computational power, from the model of basic cell-like P systems to this kind of tissue-like P systems.     

Empirical Comparisons of X‐bar Charts when Control Limits are Estimated

A control chart is a very common tool used to monitor the quality of business processes. An estimator of the process variability is generally considered to obtain the control limits of a chart when parameters of the process are unknown. Assuming Monte Carlo simulations, this paper first compares the efficiency of the various estimators of the process variability. Two empirical measures used to analyze the performance of control charts are defined. Results derived from various empirical studies reveal the existence of a linear relationship between the performance of the various estimators of the process variability and the performance of charts. The various Monte Carlo simulations are conducted under the assumption that the process is in both situations of in‐control and out‐of‐control. Copyright © 2015 John Wiley & Sons, Ltd.     

Effects of heating in air and chlorine atmosphere on the crystalline structure of pure Ta2O5 or mixed with carbon

Structure changes undergone by pure amorphous hydrated tantalum oxide mixed with different types of carbon when heated in air or chlorine atmospheres were monitored by X-ray diffraction (XRD) and scanning electronic microscopy (SEM). Heating in air of pure Ta2O5 causes the appearance of the hexagonal structure -Ta2O5 at 973 K and the ortho-rhombic structure -Ta2O5 at 1173 K. Heating in chlorine atmosphere markedly lowers the temperature at which transformation to the orthorhombic phase occurs. This effect is attributed to recrystallization of tantalum oxide from tantalum chloride and oxygen, both in gaseous phase, formed in a previous chlorination step of the amorphous oxide. When the thermal treatment is performed in chlorine atmosphere the presence of carbon permits the detection of the hexagonal form at 753 K; this temperature varies with the type of carbon and the oxide : carbon ration. © 1998 Kluwer Academic Publishers     

An integrated domain analysis approach for teleoperated systems

Teleoperated systems for ship hull maintenance (TOS) are robotic systems for ship maintenance tasks, such as cleaning or painting a ship’s hull. The product line paradigm has recently been applied to TOS, and a TOS reference architecture has thus been designed. However, TOS requirements specifications have not been developed in any rigorous way with reuse in mind. We therefore believe that an opportunity exists to increase the abstraction level at which stakeholders can reason about this product line. This paper reports an experience in which this TOS domain was analyzed, including the lessons learned in the construction and use of the TOS domain model. The experience is based on the application of extensions of well-known domain analysis techniques, together with the use of quality attribute templates traced to a feature model to deal with non-functional issues. A qualitative research method (action research) was used to carry out the experience.     

A multivariable control scheme in a two-stage anaerobic digestion system described by partial differential equations

This paper deals with the design and application of a nonlinear multivariable controller in an anaerobic digestion system (AD) carried out in two interconnected fixed bed bioreactors. The proposed control scheme is derived from a mathematical model of the AD system described by a set of partial differential equations and consists of an estimator and two nonlinear control laws. The first law is developed to regulate the volatile fatty acids in the first bioreactor while the second aims at maintaining the chemical oxygen demand at predetermined set-points in the second bioreactor. The performance of the control algorithm is evaluated via numerical simulations in the face of load disturbances, parameter kinetic uncertainties and set-point changes. Stability and convergence properties of the proposed control scheme are also addressed in this paper.     

Applying intelligent agents and semantic web services in eGovernment environments

The increasing volume of eGovernment‐related services is demanding new approaches for service integration and interoperability in this domain. Semantic web (SW) technologies and applications can leverage the potential of eGovernment service integration and discovery, thus tackling the problems of semantic heterogeneity characterizing eGovernment information sources and the different levels of interoperability. eGovernment services will therefore be semantically described in the foreseeable future. In an environment with semantically annotated services, software agents are essential as the entities responsible for exploiting the semantic content in order to automate some tasks, and so enhance the user's experience. In this paper, we present a framework that provides a seamless integration of semantic web services and intelligent agents technologies by making use of ontologies to facilitate their interoperation. The proposed framework can assist in the development of powerful and flexible distributed systems in complex, dynamic, heterogeneous, unpredictable and open environments. Our approach is backed up by a proof‐of‐concept implementation, where the breakthrough of integrating disparate eGovernment services has been tested.     

Interactive Ray Tracing of Large Models Using Voxel Hierarchies

We propose an efficient approach for interactive visualization of massive models with CPU ray tracing. A voxel‐based hierarchical level‐of‐detail (LOD) framework is employed to minimize rendering time and required system memory. In a pre‐processing phase, a compressed out‐of‐core data structure is constructed, which contains the original primitives of the model and the LOD voxels, organized into a kd‐tree. During rendering, data is loaded asynchronously to ensure a smooth inspection of the model regardless of the available I/O bandwidth. With our technique, we are able to explore data sets consisting of hundreds of millions of triangles in real‐time on a desktop PC with a quad‐core CPU.     

On the differential benchmarking of promotional efficiency with machine learning modelling (II): Practical applications

The assessment of promotional sales with models constructed by machine learning techniques is arousing interest due, among other reasons, to the current economic situation leading to a more complex environment of simultaneous and concurrent promotional activities. An operative model diagnosis procedure was previously proposed in the companion paper, which can be readily used both for agile decision making on the architecture and implementation details of the machine learning algorithms, and for differential benchmarking among models. In this paper, a detailed example of model analysis is presented for two representative databases with different promotional behaviour, namely, a non-seasonal category (milk) and a heavily seasonal category (beer). The performance of four well-known machine learning techniques with increasing complexity is analyzed in detail here. In particular, k-Nearest Neighbours, General Regression Neural Networks, Multilayer Perceptron (MLP), and Support Vector Machines (SVM), are differentially compared. Present paper evaluates these techniques along the experiments described for both categories when applying the methodological findings obtained in the companion paper. We conclude that some elements included in the architecture are not essential for a good performance of the machine learning promotional models, such as the semiparametric nature of the kernel in SVM models, whereas other can be strongly dependent of the database, such as the convenience of multiple output models in MLP regression schemes. Additionally, the specificity of the behaviour of certain categories and product ranges determines the need to establish suitable and specific procedures for a better prediction and feature extraction.