Electronic Construction Collaboration System – Phase III, December 2011

This phase of the electronic collaboration project involved two major efforts: 1) implementation of AEC Sync (formerly known as Attolist), a web-based project management system (WPMS), on the Broadway Viaduct Bridge Project and the Iowa Falls Arch Bridge Project and 2) development of a web-based project management system for bridge and highway construction projects with less than $10 million in contract value. During the previous phase of this project (fiscal year 2010), the research team helped with the implementation process for AEC Sync and collected feedback from the Broadway Viaduct project team members before the start of the project. During the 2011 fiscal year, the research team collected the post-project surveys from the Broadway Viaduct project members and compared them to the pre-project survey results. The results of the AEC Sync implementation on the Broadway project were positive. The project members were satisfied with the performance of the AEC Sync software and how it facilitated document management and its transparency. In addition, the research team distributed, collected, and analyzed the pre-project surveys for the Iowa Falls Arch Bridge Project. The implementation of AEC Sync for the Iowa Falls Arch Bridge Project appears to also be positive, based on the pre-project surveys. The fourth phase of this electronic collaboration project involves the identification and implementation of a WPMS solution for smaller bridge and highway projects. The workflow for the shop drawing approval process for sign truss projects was documented and used to identify possible WPMS solutions. After testing and evaluating several WPMS solutions, Microsoft SharePoint Foundation’s site pages were selected to be pilot-tested on sign truss projects. Due to the limitation on the SharePoint license that the Iowa Department of Transportation (DOT) has, a file transfer protocol (FTP) site will be developed alongside this site to allow contractors to upload shop drawings to the Iowa DOT. The SharePoint site pages are expected to be ready for implementation during the 2012 calendar year

A survey of QoS-aware web service composition techniques

Web service composition can be briefly described as the process of aggregating services with disparate functionalities into a new composite service in order to meet increasingly complex needs of users. Service composition process has been accurate on dealing with services having disparate functionalities, however, over the years the number of web services in particular that exhibit similar functionalities and varying Quality of Service (QoS) has significantly increased. As such, the problem becomes how to select appropriate web services such that the QoS of the resulting composite service is maximized or, in some cases, minimized. This constitutes an NP-hard problem as it is complicated and difficult to solve. In this paper, a discussion of concepts of web service composition and a holistic review of current service composition techniques proposed in literature is presented. Our review spans several publications in the field that can serve as a road map for future research

Integrating information and knowledge for enterprise innovation

It has widely been accepted that enterprise integration, can be a source of socio-technical and cultural problems within organisations wishing to provide a focussed end-to-end business service. This can cause possible “straitjacketing” of business process architectures, thus suppressing responsive business re-engineering and competitive advantage for some companies. Accordingly, the current typology and emergent forms of Enterprise Resource Planning (ERP) and Enterprise Application Integration (EAI) technologies are set in the context of understanding information and knowledge integration philosophies. As such, key influences and trends in emerging IS integration choices, for end-to-end, cost-effective and flexible knowledge integration, are examined. As touch points across and outside organisations proliferate, via work-flow and relationship management-driven value innovation, aspects of knowledge refinement and knowledge integration pose challenges to maximising the potential of innovation and sustainable success, within enterprises. This is in terms of the increasing propensity for data fragmentation and the lack of effective information management, in the light of information overload. Furthermore, the nature of IS mediation which is inherent within decision making and workflow-based business processes, provides the basis for evaluation of the effects of information and knowledge integration. Hence, the authors propose a conceptual, holistic evaluation framework which encompasses these ideas. It is thus argued that such trends, and their implications regarding enterprise IS integration to engender sustainable competitive advantage, require fundamental re-thinking

Integrating Taxonomies into Theory-Based Digital Health Interventions for Behavior Change: A Holistic Framework

Digital health interventions have been emerging in the last decade. Due to their interdisciplinary nature, digital health interventions are guided and influenced by theories (e.g., behavioral theories, behavior change technologies, persuasive technology) from different research communities. However, digital health interventions are always coded using various taxonomies and reported in insufficient perspectives. The inconsistency and incomprehensiveness will bring difficulty for conducting systematic reviews and sharing contributions among communities. Based on existing related work, therefore, we propose a holistic framework that embeds behavioral theories, behavior change technique (BCT) taxonomy, and persuasive system design (PSD) principles. Including four development steps, two toolboxes, and one workflow, our framework aims to guide digital health intervention developers to design, evaluate, and report their work in a formative and comprehensive way

Task Runtime Prediction in Scientific Workflows Using an Online Incremental Learning Approach

Many algorithms in workflow scheduling and resource provisioning rely on the performance estimation of tasks to produce a scheduling plan. A profiler that is capable of modeling the execution of tasks and predicting their runtime accurately, therefore, becomes an essential part of any Workflow Management System (WMS). With the emergence of multi-tenant Workflow as a Service (WaaS) platforms that use clouds for deploying scientific workflows, task runtime prediction becomes more challenging because it requires the processing of a significant amount of data in a near real-time scenario while dealing with the performance variability of cloud resources. Hence, relying on methods such as profiling tasks' execution data using basic statistical description (e.g., mean, standard deviation) or batch offline regression techniques to estimate the runtime may not be suitable for such environments. In this paper, we propose an online incremental learning approach to predict the runtime of tasks in scientific workflows in clouds. To improve the performance of the predictions, we harness fine-grained resources monitoring data in the form of time-series records of CPU utilization, memory usage, and I/O activities that are reflecting the unique characteristics of a task's execution. We compare our solution to a state-of-the-art approach that exploits the resources monitoring data based on regression machine learning technique. From our experiments, the proposed strategy improves the performance, in terms of the error, up to 29.89%, compared to the state-of-the-art solutions.Comment: Accepted for presentation at main conference track of 11th IEEE/ACM International Conference on Utility and Cloud Computin