Context-aware workflow management in eHealth applications

Although recent studies have suggested the feasibility of integrating workflow and rule technology in a Clinical Decision Support System (CDSS), their implementation has not been verified yet. This paper proposes a knowledge engine which integrates workflow and rule engine as a tool for interpretation and execution of computer interpretable clinical guidelines. The objective of this paper is to validate its feasibility in two perspectives: clinical knowledge coverage and execution performance. The two open source engines which were selected and integrated were chosen due to their reliability and consistency. Implementation of workflow and rule engine integration has shown that the integrated knowledge engine (uBrain) is an effective CDSS for the execution of clinical guidelines.

Purpose – Most literature on workflow (WF) adaptation considered the control flow correctness like absence of dead lock, live-lock, etc. during adaptation. The data aspect of WF adaptation like data flow, database schema changes and their correctness are less studied. When the WF schema is modified, their data flow and the database schema changes. The existing approaches used for adapting these data changes in the underlying database schema are time consuming and/or affect the old data persistence. The purpose of this paper is to concern the dynamic adaptation of the WF schema and implementing its data changes in the existing database schema. Design/methodology/approach – A conceptual framework developed to adapt on-the-fly, the concomitant data changes during WF adaptation. The framework consists a set of data schema compliance criteria (DSC) which identify the data changes that can be directly accommodated in the existing database schema. Data adaptation algorithm (DAA) is developed to handle the data changes that does not conform to the DSC in the existing database schema. Findings – In this approach the existing database schema is dynamically evolved without re-creating it, after WF schema adaptation. Therefore the WF schema changes can be implemented on-the-fly without stopping the running system. It also ensures the persistence of old data residing in the existing database. Originality/value – A novel approach developed to adapt the data changes in the existing database schema, without requiring recreation or migration the data. This automated consistency checking of data attribute changes in the database schema and implement them dynamically.

The proliferation of service-oriented architectures in the last decade has brought forward an important class of sophisticated distributed applications that are founded on the idea of composing multiple simple services into a complex, coherent whole. Such applications spanning multiple service invocations can be most effectively realized by means of workflows. When it comes to high performance workflow execution, distribution (outscaling) of services is a key concept and also a very straightforward advantage of the workflow paradigm. Concretely, both the constituent services of the workflow and the system that manages their invocations have to be distributed across an environment of computational devices. In a wide spectrum of applications, that entail heterogeneity of the encompassed computational devices, e.g., modern emergency management, invocations of optimal service instances in conjunction to their reliability are fundamental prerequisites of distributed workflow management. At the center of this thesis is a formal model that defines the distributed (i.e., scalable) execution of workflows. To extend this model for reliability in a novel way, which does not affect the scalability of execution, the Safety-Ring system service is presented. The idea behind Safety-Ring is to offer recovery for a wide range of node failures, which host active services of running workflows. To this end, the Safety-Ring provides a scalable, reliable, and consistent data store that is used for the storage of workflow execution state. The novel failure-recovery mechanism features effective reliability such that can be applied on the nodes that host the Safety-Ring service themselves, thus we say the Safety-Ring is self-healing. To apply the reliable (and distributed) execution model, enhanced by Safety-Ring, to heterogeneous node environments, that are predominantly composed of mobile de- vices, this thesis presents the Compass data access protocol. In providing scalable data lookup for its maintained data, the Safety-Ring assumes network runtime characteristics which are rather stable, and thus Safety-Ring implicitly optimizes for the number of queried nodes. Especially in mobile applications, where node network connectivity dynamically changes, data access protocols should aim at reducing the overall data lookup latency, rather than the number of queried nodes. Compass introduces latency optimal paths to each node, which dynamically adapt to changing network characteristics. The scalable data lookup of Safety-Ring is not affected. In case distributed execution of workflows spans services of continuous (stateful) type, their reliability is decoupled from the Safety-Ring. Since such service types are predominantly featured by devices of limited resources, novel approaches to resource conservative recovery of failures for continuous services have to be provided. This thesis builds on proven recovery techniques, such as passive-standby, so as to enhance them for redundancy of the continuous state and thus improve the overall reliability of the system. In doing so the redundancy of state is enforced by means of a lightweight, in terms of network overhead, consistency protocol which allows for its application in resource limited node environments. In order to improve the execution performance of distributed workflows, in terms of throughput, this thesis offers a novel concept to services distribution. At the heart of our approach lie decentralized controllers that autonomously perform dynamic reconfiguration of the execution environment in terms of available services. This primarily affects the Safety-Ring service and all application services. Thereby, the goals of the controllers are to prevent workflow execution bottlenecks and unnecessary service deployments that waste resources. Since the controllers are equipped at any node in the system and can affect any other node of the system we say that the distributed workflow execution model is self-optimizing. Finally, all the presented concepts are implemented within the context of the OSIRIS distributed workflow engine and quantitatively evaluated in a series of experiments. The results of experiments confirm the benefits of our concepts for the distributed workflow execution model.

Characterization of shaking intensity distribution and seismic assessment of RC buildings for the Kashmir (Pakistan) earthquake of October 2005

This chapter describes the conceptual workflow model of WIDE. The definition of the model has been guided by the need of providing high flexibility in the definition of processes, in the assignment of tasks to agents, and in the definition of the information items associated to the process. Particular attention has been paid to the workflow (WF) modularization and distribution problem, in order to be able to specify WF schemas at different levels of detail, and to be able to distribute the work among different locations. The most original aspects of the WIDE model, however, involve the transactional model and the support for exceptions.

Determinants of Elite Rowing Performance: Implications for Developing Rowers

The representation of a scene at different levels of detail is necessary to achieve real-time rendering. In aerial views, only the part of the scene that is close to the viewing point needs to be displayed with a high level of detail, while more distant parts can be displayed with a low level of detail. However, when a sequence of images is generated and displayed in real-time, the transition between different levels of detail causes noticeable temporal aliasing. In this paper, we propose a method, based on object blending, that visually softens the transition between two levels of Delaunay triangulation. We present an algorithm that establishes, in an off-line process, a correspondence between two given polygonal objects. The correspondence enables on-line blending between two representations of an object, so that one representation (level of detail) progressively evolves into the other.

Loops are the main source of parallelism in scientific programs. Hence, several techniques were developed to detect parallelism in these loops and transform them into parallel forms. In this dissertation, compile time transformations and efficient parallel execution of loops with various type of dependencies are investigated. First, Doacross loops with uniform dependencies are considered for execution on distributed memory parallel machines (multicomputers). Most known Doacross loop execution techniques can be applied efficiently only to shared memory parallel machines. In this thesis, code reordering technique, improvements to partitioning strategies, and finding a balance between communication and parallelism are presented to reduce the execution time of Doacross loops on multicomputers. As with most parallelizing transformation techniques, only single loopnests are considered in the first part of this dissertation. However, parallelizing each loopnest in a program separately, even if an optimal execution can be obtained for each loopnest, may not result in an efficient execution of all the code in the program because of communication overhead across the loops in a multicomputer environment. Hence, across loop data dependence representation and analysis are introduced in this work to improve the parallel execution of the whole code. Our contribution consists of finding and representing data dependencies whose sources and destinations are subspaces of the iteration space mainly common across the loops. This type of dependence information is used in this thesis to improve global iteration space partitioning, automatic generation of communication statements across loops, and index alignment. The final part of this dissertation presents new parallelizing techniques for loops with irregular and complex dependencies. Various data dependence analysis algorithms can be found in the literature even for loops with complex array indexing. However, the improvement in data dependence testing has not been followed by similar amelioration in restructuring transformations for loops with complex dependencies. Such loops are mostly executed in serial mode. Our parallelizing techniques for these loops consists of identifying regions of the iteration space where all iterations can be executed in parallel. The advantages of all the transformations presented in this dissertation are: (1) they significantly reduce the execution time of loops with various types of dependencies as shown in this work using the MasPar machine (2) they can be implemented at compile, time which makes the task of parallel programming easier.

Abstract. This paper presents a geometric approach for modelling tree roots with different Levels of Detail, suitable for analysis of the tree anchoring, potentially occupied underground space, interaction with urban elements and damage produced and taken in the built-in environment. Three types of tree roots are considered to cover several species: tap root, heart shaped root and lateral roots. Shrubs and smaller plants are not considered, however, a similar approach can be considered if the information is available for individual species. The geometrical approach considers the difficulties of modelling the actual roots, which are dynamic and almost opaque to direct observation, proposing generalized versions. For each type of root, different geometric models are considered to capture the overall shape of the root, a simplified block model, and a planar or surface projected version. Lower detail versions are considered as compatibility version for 2D systems while higher detail models are suitable for 3D analysis and visualization. The proposed levels of detail are matched with CityGML Levels of Detail, enabling both analysis and aesthetic views for urban modelling.

Imaging mass spectrometry is an innovative technique that combines high-resolution microscopic imaging tools with analytical capabilities of spectrometry. It is a powerful tool to determine the spatial distribution of chemical compounds on complex surfaces, for example, for microscale analysis of cells and tissue in biological samples. The result is a large spectral datacube: a three-dimensional (3D) dataset in which surface position and mass spectral distribution are represented. Analysts try to discover ‘features’: correlations in spectral profiles with a recognizable spatial distribution. Techniques for feature extraction and visualization are developed to improve the exploratory analysis of spectral datacubes. The topic of this work is the design and implementation of feature extraction and visualization techniques in high-resolution imaging spectrometry data. Principal Component Analysis (PCA) is interactively used as a governing approach for feature detection. A wide range of visualization techniques are implemented based on extracted features. The thesis is organized as follows. In Chapter 2 (Spectral analysis: a survey), we provide a brief background survey on spectral analysis. The analysis in the proposed approach is divided into three stages: data acquisition, feature extraction and feature visualization. For each stage, a detailed description of currently applied methods is given. The methods most appropriate for this qualitative approach of analysis are chosen as a specific subset. PCA in combination with a binning function is most suited for extracting features from imaging mass spectral data. Both methods increase the signal-to-noise ratio and reduce the amount of data from imaging mass spectrometry. Chapter 3 (PCA-based feature extraction) compares the quality of three different PCA-based methods for detecting and extracting features from spectral datacubes. We discuss preprocessing of mass spectral data, PCA, additional rotational optimization by VARIMAX, and the PARAFAC method for factor regression. The results are compared quantitatively and qualitatively, together with some performance characteristics. For the quantitative comparison, we used a RMSE metric to compare the methods with ground truth spectra under various noise conditions. For the qualitative comparison, we used three criteria to judge the quality of features in the resulting visualizations. These criteria were applied to interpret the visualizations of features. In Chapter 4 (Feature-based registration), a robust method for automatic featurebased registration is developed. The reduction of uncorrelated noise provided by PCA allows high-resolution imaging mass spectrometry datasets to be automatically aligned and combined for high-resolution analysis of large areas. The results clearly show that the entropy-weighted, mean squared error landscape of chemically matched component images can be used to automatically align high-resolution imaging mass spectrometry datasets. Several spectral datacubes are combined to provide better detection and extraction of features. In Chapter 5 (Feature visualization), a visualization technique is described that utilizes principal components to create transfer functions for volume rendering of a spectral datacube. Two types of spectral datacubes are visualized in 3D by direct volume rendering with these transfer functions to control opacity and highlight extracted features. This enables us to visualize the link between the spectral and spatial characteristics of a feature within the spectral datacube. Applications demonstrate the additional value of these visualizations. Chapter 6 (Feature zooming) presents a technique for spectral and/or spatial zooming of extracted features. This technique is especially useful for spatially extended datasets. The combined spectral datasets are too large in size to be explored and visualized using commonly feature extraction and visualization techniques. Analysts are able to select important features or deselect unimportant features for further analysis on different levels of detail. Moreover, features with unwanted artifacts can be removed to reduce noise. Chapter 7 (High-resolution feature visualization) provides an approach to parametrically visualize features in 3D and at the highest resolution possible. Three parameters control the spectral contribution, the level of detail and the level of density on which an extracted feature is represented. This visualization has feature shapes with well-defined borders and provides more insight into the influences of noise on a mass spectral measurement. It is possible to distinguish different peaks according to their difference in density and spatial position, which would not be possible in a separate spectral or spatial view. An application shows how resulting features are visualized and interpreted. The developed tools generate new possibilities to handle, explore, and visualize the large imaging mass spectrometry datasets. A sensitive, selective, and robust approach for feature extraction enables detection and classification of features in different proteomics applications. Multiple feature shapes with high-resolution characteristics can be compared and examined on different levels of detail. These visualizations can provide more detailed molecular insight in the biochemistry of surfaces and improve classification of peptides and proteins.

At the present, coding sequence (CDS) has been discovered and larger CDS is being revealed frequently. Approaches and related tools have also been developed and upgraded concurrently, especially for phylogenetic tree analysis. This paper proposes an integrated automatic Taverna workflow for the phylogenetic tree inferring analysis using public access web services at European Bioinformatics Institute (EMBL-EBI) and Swiss Institute of Bioinformatics (SIB), and our own deployed local web services. The workflow input is a set of CDS in the Fasta format. The workflow supports 1,000 to 20,000 numbers in bootstrapping replication. The workflow performs the tree inferring such as Parsimony (PARS), Distance Matrix - Neighbor Joining (DIST-NJ), and Maximum Likelihood (ML) algorithms of EMBOSS PHYLIPNEW package based on our proposed Multiple Sequence Alignment (MSA) similarity score. The local web services are implemented and deployed into two types using the Soaplab2 and Apache Axis2 deployment. There are SOAP and Java Web Service (JWS) providing WSDL endpoints to Taverna Workbench, a workflow manager. The workflow has been validated, the performance has been measured, and its results have been verified. Our workflow's execution time is less than ten minutes for inferring a tree with 10,000 replicates of the bootstrapping numbers. This paper proposes a new integrated automatic workflow which will be beneficial to the bioinformaticians with an intermediate level of knowledge and experiences. All local services have been deployed at our portal http://bioservices.sci.psu.ac.th.

Java bytecodes can be executed with the following three methods: a Java interpreter running on a particular machine interprets bytecodes; a Just-in-Time (JIT) compiler translates bytecodes to the native primitives of the particular machine and the machine executes the translated codes; and a Java processor executes bytecodes directly. The first two methods require no special hardware support for the execution of Java bytecodes and are widely used currently. The last method requires an embedded Java processor, picoJavaI or picoJavaII for instance. The picoJavaI and picoJavaII are simple pipelined processors with no ILP (instruction level parallelism) and TLP (thread level parallelism) supports. A so-called MAJC (microprocessor architecture for Java computing) design can exploit ILP and TLP by using a modified VLIW (very long instruction word) architecture and vertical multithreading technique, but it has its own instruction set and cannot execute Java bytecodes directly. In this paper, we investigate a processor architecture which can directly execute Java bytecodes meanwhile can exploit Java ILP and TLP simultaneously. The proposed processor consists of multiple slots implementing horizontal multithreading and multiple functional units shared by all threads executed in parallel. Our architectural simulation results show that the Java processor could achieve an average 20 IPC (instructions per cycle), or 7.33 EIPC (effective IPC), with 8 slots and a 4-instruction scheduling window for each slot. We also check other configurations and give the utilization of functional units as well as the performance improvement with various kinds of working loads.

Dynamic hierarchical triangulation of a clustered data stream

In virtual reality simulations the speed of rendering is vitally important. One of the techniques for controlling the frame rate is the assignment of different levels of detail for each object within a scene. The most well-known level of detail assignment algorithms are the Funkhouser[1] algorithm and the algorithm where the level of detail is assigned with respect to the distance of the object from the viewer.We propose an algorithm based on an analogy to a market system where each object does not have an assigned level of detail but has the ownership of a certain amount of time which is can use to be rendered with. The optimization of the levels of detail then becomes a simplistic trading process where objects with large amounts of time that they don't need will trade with objects who have need of extra time.The new algorithm has been implemented to run on the DIVE[2] virtual environment system. This system was then used to perform experiments with the aim of comparing the performance of the algorithm against the other two methods mentioned above.

Mobile devices are very common these days. It is rare to meet a person that does not own a mobile phone. In the past these devices were mainly used for voice calls. This changed however with the introduction of the so called smart-phones. Their powerful processors and large displays allowed a large number of new applications. Today these devices are used to check e-mails, surf the Internet or other applications that mainly use data-transmissions instead of voice calls. Today mobile standards like HSPA+ or LTE are therefore designed to provide very high data-rates. However these data-rates can only be achieved when the signal quality between mobile and base-station allows it. Since signal quality depends on a number of factors like distance to the base-station, shadowing and multipath fading, simulators for mobile communication are usually very complex. This complexity leads to long run times, which is not always acceptable. This work will start by introducing a simulation model for mobile data-transmission, which is derived from existing work and specifications. This model will then be used to evaluate a number of heuristics, which will be introduced in the remainder of the document. These heuristics will simulate mobile communication over larger time scales, and will therefore perform faster.