Weak conformance of process models with respect to data objects

Process models specify behavioral aspects by describing ordering constraints between tasks which must be accomplished to achieve envisioned goals. Tasks usually exchange information by means of data objects, i.e., by writing information to and reading information from data objects. A data object can be characterized by its states and allowed state transitions. In this paper, we propose a notion which checks conformance of a process model with respect to data objects that its tasks access. This new notion can be used to tell whether in every execution of a process model each time a task needs to access a data object in a particular state, it is ensured that the data object is in the expected state or can reach the expected state and, hence, the process model can achieve its goals.

Structuring acyclic process models

This paper addresses the problem of transforming a process model with an arbitrary topology into an equivalent well-structured process model. While this problem has received significant attention, there is still no full characterization of the class of unstructured process models that can be transformed into well-structured ones, nor an automated method to structure any process model that belongs to this class. This paper fills this gap in the context of acyclic process models. The paper defines a necessary and sufficient condition for an unstructured process model to have an equivalent structured model under fully concurrent bisimulation, as well as a complete structuring method.

Unveiling hidden unstructured regions in process models

Process models define allowed process execution scenarios. The models are usually depicted as directed graphs, with gateway nodes regulating the control flow routing logic and with edges specifying the execution order constraints between tasks. While arbitrarily structured control flow patterns in process models complicate model analysis, they also permit creativity and full expressiveness when capturing non-trivial process scenarios. This paper gives a classification of arbitrarily structured process models based on the hierarchical process model decomposition technique. We identify a structural class of models consisting of block structured patterns which, when combined, define complex execution scenarios spanning across the individual patterns. We show that complex behavior can be localized by examining structural relations of loops in hidden unstructured regions of control flow. The correctness of the behavior of process models within these regions can be validated in linear time. These observations allow us to suggest techniques for transforming hidden unstructured regions into block-structured ones.

The triconnected abstraction of process models

Companies use business process models to represent their working procedures in order to deploy services to markets, to analyze them, and to improve upon them. Competitive markets necessitate complex procedures, which lead to large process specifications with sophisticated structures. Real world process models can often incorporate hundreds of modeling constructs. While a large degree of detail complicates the comprehension of the processes, it is essential to many analysis tasks. This paper presents a technique to abstract, i.e., to simplify process models. Given a detailed model, we introduce abstraction rules which generalize process fragments in order to bring the model to a higher abstraction level. The approach is suited for the abstraction of large process specifications in order to aid model comprehension as well as decomposing problems of process model analysis. The work is based on process structure trees that have recently been introduced to the field of business process management.

Time- vs. frequency-domain identification of parametric radiation force models for marine structures at zero speed

The dynamics describing the motion response of a marine structure in waves can be represented within a linear framework by the Cummins Equation. This equation contains a convolution term that represents the component of the radiation forces associated with fluid memory effects. Several methods have been proposed in the literature for the identification of parametric models to approximate and replace this convolution term. This replacement can facilitate the model implementation in simulators and the analysis of motion control designs. Some of the reported identification methods consider the problem in the time domain while other methods consider the problem in the frequency domain. This paper compares the application of these identification methods. The comparison is based not only on the quality of the estimated models, but also on the ease of implementation, ease of use, and the flexibility of the identification method to incorporate prior information related to the model being identified. To illustrate the main points arising from the comparison, a particular example based on the coupled vertical motion of a modern containership vessel is presented.

Hybrid frequency–time domain models for dynamic response analysis of marine structures

Time-domain models of marine structures based on frequency domain data are usually built upon the Cummins equation. This type of model is a vector integro-differential equation which involves convolution terms. These convolution terms are not convenient for analysis and design of motion control systems. In addition, these models are not efficient with respect to simulation time, and ease of implementation in standard simulation packages. For these reasons, different methods have been proposed in the literature as approximate alternative representations of the convolutions. Because the convolution is a linear operation, different approaches can be followed to obtain an approximately equivalent linear system in the form of either transfer function or state-space models. This process involves the use of system identification, and several options are available depending on how the identification problem is posed. This raises the question whether one method is better than the others. This paper therefore has three objectives. The first objective is to revisit some of the methods for replacing the convolutions, which have been reported in different areas of analysis of marine systems: hydrodynamics, wave energy conversion, and motion control systems. The second objective is to compare the different methods in terms of complexity and performance. For this purpose, a model for the response in the vertical plane of a modern containership is considered. The third objective is to describe the implementation of the resulting model in the standard simulation environment Matlab/Simulink.

Kinematic models for manoeuvring and seakeeping of marine vessels

The motion of marine vessels has traditionally been studied using two different approaches: manoeuvring and seakeeping. These two approaches use different reference frames and coordinate systems to describe the motion. This paper derives the kinematic models that characterize the transformation of motion variables (position, velocity, accelerations) and forces between the different coordinate systems used in these theories. The derivations hereby presented are done in terms of the formalism adopted in robotics. The advantage of this formulation is the use of matrix notation and operations. As an application, the transformation of linear equations of motion used in seakeeping into body-fixed coordinates is considered for both zero and forward speed.

Painting anatase (TiO2) nanocrystals on long nanofibers to prepare photocatalysts with large active surface for dye degradation and organic synthesis

Anatase TiO2 nanocrystals were painted on H-titanate nanofibers by using an aqueous solution of titanyl sulfate. The anatase nanocrystals were bonded solidly onto the titanate fibers through formation of coherent interfaces at which the oxygen atoms were shared by the nanocrystals and the fiber. This approach allowed us to create large anatase surfaces on the nanofibers, which are active in photocatalytic reactions. This method was also applied successfully to coat anatase nanocrystals on surfaces of fly ash and layered clay. The painted nanofibers exhibited a much higher catalytic activity for the photocatalytic degradation of sulforhodamine B and the selective oxidation of benzylamine to the corresponding imine (with a product selectivity >99%) under UV irradiation than both the parent H-titanate nanofibers and a commercial TiO2 powder, P25. We found that gold nanoparticles supported on H-titanate nanofibers showed no catalytic activity for the reduction of nitrobenzene to azoxybenzene, whereas the gold nanoparticles supported on the painted nanofibers and P25 could efficiently reduce nitrobenzene to azoxybenzene as the sole product under visible light irradiation. These results were different from those from the reduction on the gold nanoparticles photocatalyst on ZrO2, in which the azoxybenzene was the intermediate and converted to azobenzene quickly. Evidently, the support materials significantly affect the product selectivity of the nitrobenzene reduction. Finally, the new photocatalysts could be easily dispersed into and separated from a liquid because of their fibril morphology, which is an important advantage for practical applications.

Rapid identification of cytochrome P450cam variants by in vivo screening of active site libraries

The selection of cytochrome P450 enzymes from large variant libraries, and the subsequent use of these enzymes in preparative scale biotransformations, remains a formidable challenge due to the complexities of the associated electron transport systems. Here, a powerful approach for the generation and screening of P450cam libraries for new function is presented that is both flexible and robust. A targeted library was generated wherein only the P450cam active-site amino acids Y96 and F98 were fully randomized and biotransformations, using a novel P450cam whole-cell system, were screened by GC–MS for the hydroxylation of diphenylmethane. One in 50 of the reactions screened, including 16 different variants, produced 4-hydroxydiphenylmethane with up to 92% conversion observed in the case of the Y96A variant. These results demonstrate a primary example of the screening of P450cam libraries in a format that is compatible with extension to preparative scale reactions.

Active control of car suspension systems using IDA-PBC

This paper considers the design of active control for car suspension systems using a particular form of energy-based control called Interconnection-and-Damping-Assignment Passivity-Based Control (IDA-PBC). This approach allows one to shape the kinetic and potential energy as well as modify the power flow among different components of the system by changing the interconnection and dissipative structure in a meaningful way. Different controller parameterisations are considered to design a class of controllers for active suspension systems.

Probability and story-telling : normative and descriptive models of juridical proof

The operation of the law rests on the selection of an account of the facts. Whether this involves prediction or postdiction, it is not possible to achieve certainty. Any attempt to model the operation of the law completely will therefore raise questions of how to model the process of proof. In the selection of a model a crucial question will be whether the model is to be used normatively or descriptively. Focussing on postdiction, this paper presents and contrasts the mathematical model with the story model. The former carries the normative stamp of scientific approval, whereas the latter has been developed by experimental psychologists to describe how humans reason. Neil Cohen's attempt to use a mathematical model descriptively provides an illustration of the dangers in not clearly setting this parameter of the modelling process. It should be kept in mind that the labels 'normative' and 'descriptive' are not eternal. The mathematical model has its normative limits, beyond which we may need to critically assess models with descriptive origins.

A gene encoding a new cold-active lipase from an Antarctic isolate of Penicillium expansum

Cold-active lipases are of significant interest as biocatalysts in industrial processes. We have identified a lipase that displayed activity towards long carbon-chain-p-nitrophenyl substrates (C12–C18) at 25 °C from the culture supernatant of an Antarctic Penicillium expansum strain assigned P. expansum SM3. Zymography revealed a protein band of around 30 kDa with activity towards olive oil. DNA fragments of a lipase gene designated as lipPE were isolated from the genomic DNA of P. expansum SM3 by genomic walking PCR. Subsequently, the complete genomic lipPE gene was amplified using gene-specific primers designed from the 5′- and 3′-regions. Reverse transcription PCR was used to amplify the lipPE cDNA. The deduced amino acid sequence consisted of 285 residues that included a predicted signal peptide. Three peptides identified by LC/MS/MS analysis of the proteins in the culture supernatant of P. expansum were also present in the deduced amino acid sequence of the lipPE gene suggesting that this gene encoded the lipase identified by initial zymogram activity analysis. Full analysis of the nucleotide and the deduced amino acid sequences indicated that the lipPE gene encodes a novel P. expansum lipase. The lipPE gene was expressed in E. coli for further characterization of the enzyme with a view of assessing its suitability for industrial applications.

Enzyme activities and biotechnological applications of cold-active microfungi

Fungi are eukaryotic organisms and considered to be less adaptable to extreme environments when compared to bacteria. While there are no thermophilic microfungi in a strict sense, some fungi have adapted to life in the cold. Cold-active microfungi have been isolated from the Antarctic and their enzyme activities explored with a view to finding new candidates for industrial use. On another front, environmental pollution by petroleum products in the Antarctic has led to a search for, and the subsequent discovery of, fungal isolates capable of degrading hydrocarbons. The work has paved the way to developing a bioremedial approach to containing this type of contamination in cold climates. Here we discuss our efforts to map the capability of Antarctic microfungi to degrade oil and also introduce a novel cold-active fungal lipase enzyme.

Parameter estimation of thrust models of uninhabited airborne systems

This paper presents a method for the estimation of thrust model parameters of uninhabited airborne systems using specific flight tests. Particular tests are proposed to simplify the estimation. The proposed estimation method is based on three steps. The first step uses a regression model in which the thrust is assumed constant. This allows us to obtain biased initial estimates of the aerodynamic coeficients of the surge model. In the second step, a robust nonlinear state estimator is implemented using the initial parameter estimates, and the model is augmented by considering the thrust as random walk. In the third step, the estimate of the thrust obtained by the observer is used to fit a polynomial model in terms of the propeller advanced ratio. We consider a numerical example based on Monte-Carlo simulations to quantify the sampling properties of the proposed estimator given realistic flight conditions.

Damping structure selection in nonlinear ship manoeuvring models

This paper presents the application of a statistical method for model structure selection of lift-drag and viscous damping components in ship manoeuvring models. The damping model is posed as a family of linear stochastic models, which is postulated based on previous work in the literature. Then a nested test of hypothesis problem is considered. The testing reduces to a recursive comparison of two competing models, for which optimal tests in the Neyman sense exist. The method yields a preferred model structure and its initial parameter estimates. Alternatively, the method can give a reduced set of likely models. Using simulated data we study how the selection method performs when there is both uncorrelated and correlated noise in the measurements. The first case is related to instrumentation noise, whereas the second case is related to spurious wave-induced motion often present during sea trials. We then consider the model structure selection of a modern high-speed trimaran ferry from full scale trial data.