Wound problems following hip arthroplasty before and after the introduction of a direct thrombin inhibitor for thromboprophylaxis

NICE guidelines have stated that patients undergoing elective hip surgery are at increased risk for venous thromboembolic events (VTE) following surgery and have recommended thromboprophylaxis for 28-35 days1, 2. However the studies looking at the new direct thrombin inhibitors have only looked at major bleeding. We prospectively looked at wound discharge in patients who underwent hip arthroplasty and were given dabigatran postoperatively between March 2010 and April 2010 (n=56). We retrospectively compared these results to a matched group of patients who underwent similar operations six months earlier when all patients were given dalteparin routinely postoperatively until discharge, and discharged home on 150mg aspirin daily for 6 weeks (n=67). Wound discharge after 5 days was significantly higher in the patients taking dabigatran (32% dabigatran n=18, 10% dalteparin n=17, p=0.003) and our rate of delayed discharges due to wound discharge significantly increased from 7% in the dalteparin group (n=5) to 27% for dabigatran (n=15, p=0.004). Patients who received dabigatran were more than five times as likely to return to theatre with a wound complication as those who received dalteparin (7% dabigatran n=4, vs. 1% dalteparin n=1), however, this was not statistically significant (p=0.18). The significantly higher wound discharge and return to theatre rates demonstrated in this study have meant that we have changed our practice to administering dalteparin until the wound is dry and then starting dabigatran. Our study demonstrates the need for further clinical studies regarding wound discharge and dabigatran.

Clustering of web users using the tensor decomposed models

We propose to use the Tensor Space Modeling (TSM) to represent and analyze the user’s web log data that consists of multiple interests and spans across multiple dimensions. Further we propose to use the decomposition factors of the Tensors for clustering the users based on similarity of search behaviour. Preliminary results show that the proposed method outperforms the traditional Vector Space Model (VSM) based clustering.

Understanding business process models : the costs and benefits of structuredness

Previous research has put forward a number of properties of business process models that have an impact on their understandability. Two such properties are compactness and(block-)structuredness. What has not been sufficiently appreciated at this point is that these desirable properties may be at odds with one another. This paper presents the results of a two-pronged study aimed at exploring the trade-off between compactness and structuredness of process models. The first prong of the study is a comparative analysis of the complexity of a set of unstructured process models from industrial practice and of their corresponding structured versions. The second prong is an experiment wherein a cohort of students was exposed to semantically equivalent unstructured and structured process models. The key finding is that structuredness is not an absolute desideratum vis-a-vis for process model understandability. Instead, subtle trade-offs between structuredness and other model properties are at play.

Ocular characteristics of anisometropia

Animal models of refractive error development have demonstrated that visual experience influences ocular growth. In a variety of species, axial anisometropia (i.e. a difference in the length of the two eyes) can be induced through unilateral occlusion, image degradation or optical manipulation. In humans, anisometropia may occur in isolation or in association with amblyopia, strabismus or unilateral pathology. Non-amblyopic myopic anisometropia represents an interesting anomaly of ocular growth, since the two eyes within one visual system have grown to different endpoints. These experiments have investigated a range of biometric, optical and mechanical properties of anisometropic eyes (with and without amblyopia) with the aim of improving our current understanding of asymmetric refractive error development. In the first experiment, the interocular symmetry in 34 non-amblyopic myopic anisometropes (31 Asian, 3 Caucasian) was examined during relaxed accommodation. A high degree of symmetry was observed between the fellow eyes for a range of optical, biometric and biomechanical measurements. When the magnitude of anisometropia exceeded 1.75 D, the more myopic eye was almost always the sighting dominant eye. Further analysis of the optical and biometric properties of the dominant and non-dominant eyes was conducted to determine any related factors but no significant interocular differences were observed with respect to best-corrected visual acuity, corneal or total ocular aberrations during relaxed accommodation. Given the high degree of symmetry observed between the fellow eyes during distance viewing in the first experiment and the strong association previously reported between near work and myopia development, the aim of the second experiment was to investigate the symmetry between the fellow eyes of the same 34 myopic anisometropes following a period of near work. Symmetrical changes in corneal and total ocular aberrations were observed following a short reading task (10 minutes, 2.5 D accommodation demand) which was attributed to the high degree of interocular symmetry for measures of anterior eye morphology, and corneal biomechanics. These changes were related to eyelid shape and position during downward gaze, but gave no clear indication of factors associated with near work that might cause asymmetric eye growth within an individual. Since the influence of near work on eye growth is likely to be most obvious during, rather than following near tasks, in the third experiment the interocular symmetry of the optical and biometric changes was examined during accommodation for 11 myopic anisometropes. The changes in anterior eye biometrics associated with accommodation were again similar between the eyes, resulting in symmetrical changes in the optical characteristics. However, the more myopic eyes exhibited slightly greater amounts of axial elongation during accommodation which may be related to the force exerted by the ciliary muscle. This small asymmetry in axial elongation we observed between the eyes may be due to interocular differences in posterior eye structure, given that the accommodative response was equal between eyes. Using ocular coherence tomography a reduced average choroidal thickness was observed in the more myopic eyes compared to the less myopic eyes of these subjects. The interocular difference in choroidal thickness was correlated with the magnitude of spherical equivalent and axial anisometropia. The symmetry in optics and biometrics between fellow eyes which have undergone significantly different visual development (i.e. anisometropic subjects with amblyopia) is also of interest with respect to refractive error development. In the final experiment the influence of altered visual experience upon corneal and ocular higher-order aberrations was investigated in 21 amblyopic subjects (8 refractive, 11 strabismic and 2 form deprivation). Significant differences in aberrations were observed between the fellow eyes, which varied according to the type of amblyopia. Refractive amblyopes displayed significantly higher levels of 4th order corneal aberrations (spherical aberration and secondary astigmatism) in the amblyopic eye compared to the fellow non-amblyopic eye. Strabismic amblyopes exhibited significantly higher levels of trefoil, a third order aberration, in the amblyopic eye for both corneal and total ocular aberrations. The results of this experiment suggest that asymmetric visual experience during development is associated with asymmetries in higher-order aberrations, proportional to the magnitude of anisometropia and dependent upon the amblyogenic factor. This suggests a direct link between the development of higher-order optical characteristics of the human eye and visual feedback. The results from these experiments have shown that a high degree of symmetry exists between the fellow eyes of non-amblyopic myopic anisometropes for a range of biomechanical, biometric and optical parameters for different levels of accommodation and following near work. While a single specific optical or biomechanical factor that is consistently associated with asymmetric refractive error development has not been identified, the findings from these studies suggest that further research into the association between ocular dominance, choroidal thickness and higher-order aberrations with anisometropia may improve our understanding of refractive error development.

Adaptive cache aware multiprocessor scheduling framework

Computer resource allocation represents a significant challenge particularly for multiprocessor systems, which consist of shared computing resources to be allocated among co-runner processes and threads. While an efficient resource allocation would result in a highly efficient and stable overall multiprocessor system and individual thread performance, ineffective poor resource allocation causes significant performance bottlenecks even for the system with high computing resources. This thesis proposes a cache aware adaptive closed loop scheduling framework as an efficient resource allocation strategy for the highly dynamic resource management problem, which requires instant estimation of highly uncertain and unpredictable resource patterns. Many different approaches to this highly dynamic resource allocation problem have been developed but neither the dynamic nature nor the time-varying and uncertain characteristics of the resource allocation problem is well considered. These approaches facilitate either static and dynamic optimization methods or advanced scheduling algorithms such as the Proportional Fair (PFair) scheduling algorithm. Some of these approaches, which consider the dynamic nature of multiprocessor systems, apply only a basic closed loop system; hence, they fail to take the time-varying and uncertainty of the system into account. Therefore, further research into the multiprocessor resource allocation is required. Our closed loop cache aware adaptive scheduling framework takes the resource availability and the resource usage patterns into account by measuring time-varying factors such as cache miss counts, stalls and instruction counts. More specifically, the cache usage pattern of the thread is identified using QR recursive least square algorithm (RLS) and cache miss count time series statistics. For the identified cache resource dynamics, our closed loop cache aware adaptive scheduling framework enforces instruction fairness for the threads. Fairness in the context of our research project is defined as a resource allocation equity, which reduces corunner thread dependence in a shared resource environment. In this way, instruction count degradation due to shared cache resource conflicts is overcome. In this respect, our closed loop cache aware adaptive scheduling framework contributes to the research field in two major and three minor aspects. The two major contributions lead to the cache aware scheduling system. The first major contribution is the development of the execution fairness algorithm, which degrades the co-runner cache impact on the thread performance. The second contribution is the development of relevant mathematical models, such as thread execution pattern and cache access pattern models, which in fact formulate the execution fairness algorithm in terms of mathematical quantities. Following the development of the cache aware scheduling system, our adaptive self-tuning control framework is constructed to add an adaptive closed loop aspect to the cache aware scheduling system. This control framework in fact consists of two main components: the parameter estimator, and the controller design module. The first minor contribution is the development of the parameter estimators; the QR Recursive Least Square(RLS) algorithm is applied into our closed loop cache aware adaptive scheduling framework to estimate highly uncertain and time-varying cache resource patterns of threads. The second minor contribution is the designing of a controller design module; the algebraic controller design algorithm, Pole Placement, is utilized to design the relevant controller, which is able to provide desired timevarying control action. The adaptive self-tuning control framework and cache aware scheduling system in fact constitute our final framework, closed loop cache aware adaptive scheduling framework. The third minor contribution is to validate this cache aware adaptive closed loop scheduling framework efficiency in overwhelming the co-runner cache dependency. The timeseries statistical counters are developed for M-Sim Multi-Core Simulator; and the theoretical findings and mathematical formulations are applied as MATLAB m-file software codes. In this way, the overall framework is tested and experiment outcomes are analyzed. According to our experiment outcomes, it is concluded that our closed loop cache aware adaptive scheduling framework successfully drives co-runner cache dependent thread instruction count to co-runner independent instruction count with an error margin up to 25% in case cache is highly utilized. In addition, thread cache access pattern is also estimated with 75% accuracy.

Long-evans rats acquire operant self-administration of 20% ethanol without sucrose fading

A major obstacle in the development of new medications for the treatment of alcohol use disorders (AUDs) has been the lack of preclinical, oral ethanol consumption paradigms that elicit high consumption. We have previously shown that rats exposed to 20% ethanol intermittently in a two-bottle choice paradigm will consume two times more ethanol than those given continuous access without the use of water deprivation or sucrose fading (5-6 g/kg every 24 h vs 2-3 g/kg every 24 h, respectively). In this study, we have adapted the model to an operant self-administration paradigm. Long-Evans rats were given access to 20% ethanol in overnight sessions on one of two schedules: (1) intermittent (Monday, Wednesday, and Friday) or (2) daily (Monday through Friday). With the progression of the overnight sessions, both groups showed a steady escalation in drinking (3-6 g/kg every 14 h) without the use of a sucrose-fading procedure. Following the acquisition phase, the 20% ethanol groups consumed significantly more ethanol than did animals trained to consume 10% ethanol with a sucrose fade (1.5 vs 0.7 g/kg every 30 min) and reached significantly higher blood ethanol concentrations. In addition, training history (20% ethanol vs 10% ethanol with sucrose fade) had a significant effect on the subsequent self-administration of higher concentrations of ethanol. Administration of the pharmacological stressor yohimbine following extinction caused a significant reinstatement of ethanol-seeking behavior. Both 20% ethanol models show promise and are amenable to the study of maintenance, motivation, and reinstatement. Furthermore, training animals to lever press for ethanol without the use of sucrose fading removes a potential confound from self-administration studies. © 2010 Nature Publishing Group All rights reserved.

Evaluation of modal analysis techniques using physical models to detect osseointegration of implants in transfemoral amputees

Non-invasive vibration analysis has been used extensively to monitor the progression of dental implant healing and stabilization. It is now being considered as a method to monitor femoral implants in transfemoral amputees. This paper evaluates two modal analysis excitation methods and investigates their capabilities in detecting changes at the interface between the implant and the bone that occur during osseointegration. Excitation of bone-implant physical models with the electromagnetic shaker provided higher coherence values and a greater number of modes over the same frequency range when compared to the impact hammer. Differences were detected in the natural frequencies and fundamental mode shape of the model when the fit of the implant was altered in the bone. The ability to detect changes in the model dynamic properties demonstrates the potential of modal analysis in this application and warrants further investigation.

A Study of XML models for data mining : representations, methods, and issues

With the increasing number of XML documents in varied domains, it has become essential to identify ways of finding interesting information from these documents. Data mining techniques were used to derive this interesting information. Mining on XML documents is impacted by its model due to the semi-structured nature of these documents. Hence, in this chapter we present an overview of the various models of XML documents, how these models were used for mining and some of the issues and challenges in these models. In addition, this chapter also provides some insights into the future models of XML documents for effectively capturing the two important features namely structure and content of XML documents for mining.

A people-to-people recommendation system using Tensor Space Models

Existing recommendation systems often recommend products to users by capturing the item-to-item and user-to-user similarity measures. These types of recommendation systems become inefficient in people-to-people networks for people to people recommendation that require two way relationship. Also, existing recommendation methods use traditional two dimensional models to find inter relationships between alike users and items. It is not efficient enough to model the people-to-people network with two-dimensional models as the latent correlations between the people and their attributes are not utilized. In this paper, we propose a novel tensor decomposition-based recommendation method for recommending people-to-people based on users profiles and their interactions. The people-to-people network data is multi-dimensional data which when modeled using vector based methods tend to result in information loss as they capture either the interactions or the attributes of the users but not both the information. This paper utilizes tensor models that have the ability to correlate and find latent relationships between similar users based on both information, user interactions and user attributes, in order to generate recommendations. Empirical analysis is conducted on a real-life online dating dataset. As demonstrated in results, the use of tensor modeling and decomposition has enabled the identification of latent correlations between people based on their attributes and interactions in the network and quality recommendations have been derived using the 'alike' users concept.

Models of collective cell motion for cell populations with different aspect ratio : diffusion, proliferation and travelling waves

Continuum, partial differential equation models are often used to describe the collective motion of cell populations, with various types of motility represented by the choice of diffusion coefficient, and cell proliferation captured by the source terms. Previously, the choice of diffusion coefficient has been largely arbitrary, with the decision to choose a particular linear or nonlinear form generally based on calibration arguments rather than making any physical connection with the underlying individual-level properties of the cell motility mechanism. In this work we provide a new link between individual-level models, which account for important cell properties such as varying cell shape and volume exclusion, and population-level partial differential equation models. We work in an exclusion process framework, considering aligned, elongated cells that may occupy more than one lattice site, in order to represent populations of agents with different sizes. Three different idealizations of the individual-level mechanism are proposed, and these are connected to three different partial differential equations, each with a different diffusion coefficient; one linear, one nonlinear and degenerate and one nonlinear and nondegenerate. We test the ability of these three models to predict the population level response of a cell spreading problem for both proliferative and nonproliferative cases. We also explore the potential of our models to predict long time travelling wave invasion rates and extend our results to two dimensional spreading and invasion. Our results show that each model can accurately predict density data for nonproliferative systems, but that only one does so for proliferative systems. Hence great care must be taken to predict density data for with varying cell shape.

Thresholds for error probability measures of business process models

The quality of conceptual business process models is highly relevant for the design of corresponding information systems. In particular, a precise measurement of model characteristics can be beneficial from a business perspective, helping to save costs thanks to early error detection. This is just as true from a software engineering point of view. In this latter case, models facilitate stakeholder communication and software system design. Research has investigated several proposals as regards measures for business process models, from a rather correlational perspective. This is helpful for understanding, for example size and complexity as general driving forces of error probability. Yet, design decisions usually have to build on thresholds, which can reliably indicate that a certain counter-action has to be taken. This cannot be achieved only by providing measures; it requires a systematic identification of effective and meaningful thresholds. In this paper, we derive thresholds for a set of structural measures for predicting errors in conceptual process models. To this end, we use a collection of 2,000 business process models from practice as a means of determining thresholds, applying an adaptation of the ROC curves method. Furthermore, an extensive validation of the derived thresholds was conducted by using 429 EPC models from an Australian financial institution. Finally, significant thresholds were adapted to refine existing modeling guidelines in a quantitative way.

User behaviour modelling in a multi-dimensional environment for personalization and recommendation

Handling information overload online, from the user's point of view is a big challenge, especially when the number of websites is growing rapidly due to growth in e-commerce and other related activities. Personalization based on user needs is the key to solving the problem of information overload. Personalization methods help in identifying relevant information, which may be liked by a user. User profile and object profile are the important elements of a personalization system. When creating user and object profiles, most of the existing methods adopt two-dimensional similarity methods based on vector or matrix models in order to find inter-user and inter-object similarity. Moreover, for recommending similar objects to users, personalization systems use the users-users, items-items and users-items similarity measures. In most cases similarity measures such as Euclidian, Manhattan, cosine and many others based on vector or matrix methods are used to find the similarities. Web logs are high-dimensional datasets, consisting of multiple users, multiple searches with many attributes to each. Two-dimensional data analysis methods may often overlook latent relationships that may exist between users and items. In contrast to other studies, this thesis utilises tensors, the high-dimensional data models, to build user and object profiles and to find the inter-relationships between users-users and users-items. To create an improved personalized Web system, this thesis proposes to build three types of profiles: individual user, group users and object profiles utilising decomposition factors of tensor data models. A hybrid recommendation approach utilising group profiles (forming the basis of a collaborative filtering method) and object profiles (forming the basis of a content-based method) in conjunction with individual user profiles (forming the basis of a model based approach) is proposed for making effective recommendations. A tensor-based clustering method is proposed that utilises the outcomes of popular tensor decomposition techniques such as PARAFAC, Tucker and HOSVD to group similar instances. An individual user profile, showing the user's highest interest, is represented by the top dimension values, extracted from the component matrix obtained after tensor decomposition. A group profile, showing similar users and their highest interest, is built by clustering similar users based on tensor decomposed values. A group profile is represented by the top association rules (containing various unique object combinations) that are derived from the searches made by the users of the cluster. An object profile is created to represent similar objects clustered on the basis of their similarity of features. Depending on the category of a user (known, anonymous or frequent visitor to the website), any of the profiles or their combinations is used for making personalized recommendations. A ranking algorithm is also proposed that utilizes the personalized information to order and rank the recommendations. The proposed methodology is evaluated on data collected from a real life car website. Empirical analysis confirms the effectiveness of recommendations made by the proposed approach over other collaborative filtering and content-based recommendation approaches based on two-dimensional data analysis methods.

Flexible high voltage pulsed power supply for plasma applications

Demands for delivering high instantaneous power in a compressed form (pulse shape) have widely increased during recent decades. The flexible shapes with variable pulse specifications offered by pulsed power have made it a practical and effective supply method for an extensive range of applications. In particular, the release of basic subatomic particles (i.e. electron, proton and neutron) in an atom (ionization process) and the synthesizing of molecules to form ions or other molecules are among those reactions that necessitate large amount of instantaneous power. In addition to the decomposition process, there have recently been requests for pulsed power in other areas such as in the combination of molecules (i.e. fusion, material joining), gessoes radiations (i.e. electron beams, laser, and radar), explosions (i.e. concrete recycling), wastewater, exhausted gas, and material surface treatments. These pulses are widely employed in the silent discharge process in all types of materials (including gas, fluid and solid); in some cases, to form the plasma and consequently accelerate the associated process. Due to this fast growing demand for pulsed power in industrial and environmental applications, the exigency of having more efficient and flexible pulse modulators is now receiving greater consideration. Sensitive applications, such as plasma fusion and laser guns also require more precisely produced repetitive pulses with a higher quality. Many research studies are being conducted in different areas that need a flexible pulse modulator to vary pulse features to investigate the influence of these variations on the application. In addition, there is the need to prevent the waste of a considerable amount of energy caused by the arc phenomena that frequently occur after the plasma process. The control over power flow during the supply process is a critical skill that enables the pulse supply to halt the supply process at any stage. Different pulse modulators which utilise different accumulation techniques including Marx Generators (MG), Magnetic Pulse Compressors (MPC), Pulse Forming Networks (PFN) and Multistage Blumlein Lines (MBL) are currently employed to supply a wide range of applications. Gas/Magnetic switching technologies (such as spark gap and hydrogen thyratron) have conventionally been used as switching devices in pulse modulator structures because of their high voltage ratings and considerably low rising times. However, they also suffer from serious drawbacks such as, their low efficiency, reliability and repetition rate, and also their short life span. Being bulky, heavy and expensive are the other disadvantages associated with these devices. Recently developed solid-state switching technology is an appropriate substitution for these switching devices due to the benefits they bring to the pulse supplies. Besides being compact, efficient, reasonable and reliable, and having a long life span, their high frequency switching skill allows repetitive operation of pulsed power supply. The main concerns in using solid-state transistors are the voltage rating and the rising time of available switches that, in some cases, cannot satisfy the application’s requirements. However, there are several power electronics configurations and techniques that make solid-state utilisation feasible for high voltage pulse generation. Therefore, the design and development of novel methods and topologies with higher efficiency and flexibility for pulsed power generators have been considered as the main scope of this research work. This aim is pursued through several innovative proposals that can be classified under the following two principal objectives. • To innovate and develop novel solid-state based topologies for pulsed power generation • To improve available technologies that have the potential to accommodate solid-state technology by revising, reconfiguring and adjusting their structure and control algorithms. The quest to distinguish novel topologies for a proper pulsed power production was begun with a deep and through review of conventional pulse generators and useful power electronics topologies. As a result of this study, it appears that efficiency and flexibility are the most significant demands of plasma applications that have not been met by state-of-the-art methods. Many solid-state based configurations were considered and simulated in order to evaluate their potential to be utilised in the pulsed power area. Parts of this literature review are documented in Chapter 1 of this thesis. Current source topologies demonstrate valuable advantages in supplying the loads with capacitive characteristics such as plasma applications. To investigate the influence of switching transients associated with solid-state devices on rise time of pulses, simulation based studies have been undertaken. A variable current source is considered to pump different current levels to a capacitive load, and it was evident that dissimilar dv/dts are produced at the output. Thereby, transient effects on pulse rising time are denied regarding the evidence acquired from this examination. A detailed report of this study is given in Chapter 6 of this thesis. This study inspired the design of a solid-state based topology that take advantage of both current and voltage sources. A series of switch-resistor-capacitor units at the output splits the produced voltage to lower levels, so it can be shared by the switches. A smart but complicated switching strategy is also designed to discharge the residual energy after each supply cycle. To prevent reverse power flow and to reduce the complexity of the control algorithm in this system, the resistors in common paths of units are substituted with diode rectifiers (switch-diode-capacitor). This modification not only gives the feasibility of stopping the load supply process to the supplier at any stage (and consequently saving energy), but also enables the converter to operate in a two-stroke mode with asymmetrical capacitors. The components’ determination and exchanging energy calculations are accomplished with respect to application specifications and demands. Both topologies were simply modelled and simulation studies have been carried out with the simplified models. Experimental assessments were also executed on implemented hardware and the approaches verified the initial analysis. Reports on details of both converters are thoroughly discussed in Chapters 2 and 3 of the thesis. Conventional MGs have been recently modified to use solid-state transistors (i.e. Insulated gate bipolar transistors) instead of magnetic/gas switching devices. Resistive insulators previously used in their structures are substituted by diode rectifiers to adjust MGs for a proper voltage sharing. However, despite utilizing solid-state technology in MGs configurations, further design and control amendments can still be made to achieve an improved performance with fewer components. Considering a number of charging techniques, resonant phenomenon is adopted in a proposal to charge the capacitors. In addition to charging the capacitors at twice the input voltage, triggering switches at the moment at which the conducted current through switches is zero significantly reduces the switching losses. Another configuration is also introduced in this research for Marx topology based on commutation circuits that use a current source to charge the capacitors. According to this design, diode-capacitor units, each including two Marx stages, are connected in cascade through solid-state devices and aggregate the voltages across the capacitors to produce a high voltage pulse. The polarity of voltage across one capacitor in each unit is reversed in an intermediate mode by connecting the commutation circuit to the capacitor. The insulation of input side from load side is provided in this topology by disconnecting the load from the current source during the supply process. Furthermore, the number of required fast switching devices in both designs is reduced to half of the number used in a conventional MG; they are replaced with slower switches (such as Thyristors) that need simpler driving modules. In addition, the contributing switches in discharging paths are decreased to half; this decrease leads to a reduction in conduction losses. Associated models are simulated, and hardware tests are performed to verify the validity of proposed topologies. Chapters 4, 5 and 7 of the thesis present all relevant analysis and approaches according to these topologies.

A deductive system for proving workflow models from operational procedures

Many modern business environments employ software to automate the delivery of workflows; whereas, workflow design and generation remains a laborious technical task for domain specialists. Several differ- ent approaches have been proposed for deriving workflow models. Some approaches rely on process data mining approaches, whereas others have proposed derivations of workflow models from operational struc- tures, domain specific knowledge or workflow model compositions from knowledge-bases. Many approaches draw on principles from automatic planning, but conceptual in context and lack mathematical justification. In this paper we present a mathematical framework for deducing tasks in workflow models from plans in mechanistic or strongly controlled work environments, with a focus around automatic plan generations. In addition, we prove an associative composition operator that permits crisp hierarchical task compositions for workflow models through a set of mathematical deduction rules. The result is a logical framework that can be used to prove tasks in workflow hierarchies from operational information about work processes and machine configurations in controlled or mechanistic work environments.

Managing large collections of business process models - Current techniques and challenges

Nowadays, business process management is an important approach for managing organizations from an operational perspective. As a consequence, it is common to see organizations develop collections of hundreds or even thousands of business process models. Such large collections of process models bring new challenges and provide new opportunities, as the knowledge that they encapsulate requires to be properly managed. Therefore, a variety of techniques for managing large collections of business process models is being developed. The goal of this paper is to provide an overview of the management techniques that currently exist, as well as the open research challenges that they pose.