Bicycle Touring Infrastructure: An Architectural Proposal for Sustainable Bicycle Tourism

Thesis (Master's)--University of Washington, 2016-06

GIS-Based Suitability Analysis and Planning of Green Infrastructure: A Case of the PPCOD, Capitol Hill

Thesis (Master's)--University of Washington, 2016-06

RFID technology to support environmentally sustainable supply chain management

RFID is one of the contemporary technologies that has the potential to enable improved data gathering and cross-companies integration, and thus achieve cost efficiency. However, RFID has not yet become primary approach to collect data from the supply chain activities. This is partly due to (relative) high cost of implementation, partly due to technical deficiencies, as well as cross-company systems integration issues. This paper discusses a potential application area for RFID technology, which is environmentally sustainable supply chain management. The paper discusses the current practices in green supply chain management, and proposes possible applications of RFID enabling green supply chain management. The paper also proposes an idea of ad hoc RFID systems which are rapidly deployable and require minimal, if at all, pre-existing infrastructure. © 2010 IEEE.

Adaptive SOA Infrastructure Based on Variability Management

In order to exploit the adaptability of a SOA infrastructure, it becomes necessary to provide platform mechanisms that support a mapping of the variability in the applications to the variability provided by the infrastructure. The approach focuses on the configuration of the needed infrastructure mechanisms including support for the derivation of the infrastructure variability model.

Information systems to support decision-making in *construction owner organizations: A data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, non-integrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. ^ A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. ^ One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects. ^

Assessment of policies for innovative financing in infrastructure systems

Infrastructure systems are drivers of the economy in the nation. A dollar spent on infrastructure development yields roughly double the initial spending in ultimate economic output in the short term; and over a twenty-year period, and generalized ‘public investment’ produces an aggregated $3.21 of economic activity per $1.00 spent [1]. Thus, formulation of policies pertaining to infrastructure investment and development is of significance affecting the social and economic wellbeing of the nation. The aim of this policy brief is to evaluate innovative financing in infrastructure systems from two different perspectives: (1) through consideration of the current condition of infrastructure in the U.S., the current trends in public spending, and the emerging innovative financing tools; (2) through evaluation of the roles and interactions of different agencies in the creation and the diffusion of innovative financing tools. Then using the example of transportation financing, the policy brief provides an assessment of policy landscapes which could lead to the closure of infrastructure financing gap in the U.S and proposes strategies for citizen involvement to gain public support of innovative financing.

Information systems to support decision-making in construction owner organizations : a data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, nonintegrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects.

Financing infrastructure development : time to unshackle the bonds?

The authors would like to thank the RICS for their financial support of the project and the numerous respondents who gave so freely of their time. Part of the research was supported by a grant from the Hong Kong-Scotland Partners in Post-Doctoral Research Scheme sponsored by the Research Grants Council of Hong Kong and the Scottish Government (S-HKU701/13).

A Framework to Support the Sharing and Reuse of Computable Phenotype Definitions Across Health Care Delivery and Clinical Research Applications.

INTRODUCTION: The ability to reproducibly identify clinically equivalent patient populations is critical to the vision of learning health care systems that implement and evaluate evidence-based treatments. The use of common or semantically equivalent phenotype definitions across research and health care use cases will support this aim. Currently, there is no single consolidated repository for computable phenotype definitions, making it difficult to find all definitions that already exist, and also hindering the sharing of definitions between user groups. METHOD: Drawing from our experience in an academic medical center that supports a number of multisite research projects and quality improvement studies, we articulate a framework that will support the sharing of phenotype definitions across research and health care use cases, and highlight gaps and areas that need attention and collaborative solutions. FRAMEWORK: An infrastructure for re-using computable phenotype definitions and sharing experience across health care delivery and clinical research applications includes: access to a collection of existing phenotype definitions, information to evaluate their appropriateness for particular applications, a knowledge base of implementation guidance, supporting tools that are user-friendly and intuitive, and a willingness to use them. NEXT STEPS: We encourage prospective researchers and health administrators to re-use existing EHR-based condition definitions where appropriate and share their results with others to support a national culture of learning health care. There are a number of federally funded resources to support these activities, and research sponsors should encourage their use.

Extending Science Gateway Frameworks to Support Big Data Applications in the Cloud

Cloud computing offers massive scalability and elasticity required by many scien-tific and commercial applications. Combining the computational and data handling capabilities of clouds with parallel processing also has the potential to tackle Big Data problems efficiently. Science gateway frameworks and workflow systems enable application developers to implement complex applications and make these available for end-users via simple graphical user interfaces. The integration of such frameworks with Big Data processing tools on the cloud opens new oppor-tunities for application developers. This paper investigates how workflow sys-tems and science gateways can be extended with Big Data processing capabilities. A generic approach based on infrastructure aware workflows is suggested and a proof of concept is implemented based on the WS-PGRADE/gUSE science gateway framework and its integration with the Hadoop parallel data processing solution based on the MapReduce paradigm in the cloud. The provided analysis demonstrates that the methods described to integrate Big Data processing with workflows and science gateways work well in different cloud infrastructures and application scenarios, and can be used to create massively parallel applications for scientific analysis of Big Data.

Data Science Seminar: Generic Big Data Processing for Advancing Situation Awareness and Decision-Support

The generation of heterogeneous big data sources with ever increasing volumes, velocities and veracities over the he last few years has inspired the data science and research community to address the challenge of extracting knowledge form big data. Such a wealth of generated data across the board can be intelligently exploited to advance our knowledge about our environment, public health, critical infrastructure and security. In recent years we have developed generic approaches to process such big data at multiple levels for advancing decision-support. It specifically concerns data processing with semantic harmonisation, low level fusion, analytics, knowledge modelling with high level fusion and reasoning. Such approaches will be introduced and presented in context of the TRIDEC project results on critical oil and gas industry drilling operations and also the ongoing large eVacuate project on critical crowd behaviour detection in confined spaces.

Revealing Cultural Ecosystem Services through Instagram Images : The Potential of Social Media Volunteered Geographic Information for Urban Green Infrastructure Planning and Governance

With the prevalence of smartphones, new ways of engaging citizens and stakeholders in urban planning and govern-ance are emerging. The technologies in smartphones allow citizens to act as sensors of their environment, producing and sharing rich spatial data useful for new types of collaborative governance set-ups. Data derived from Volunteered Geographic Information (VGI) can support accessible, transparent, democratic, inclusive, and locally-based governance situations of interest to planners, citizens, politicians, and scientists. However, there are still uncertainties about how to actually conduct this in practice. This study explores how social media VGI can be used to document spatial tendencies regarding citizens’ uses and perceptions of urban nature with relevance for urban green space governance. Via the hashtag #sharingcph, created by the City of Copenhagen in 2014, VGI data consisting of geo-referenced images were collected from Instagram, categorised according to their content and analysed according to their spatial distribution patterns. The results show specific spatial distributions of the images and main hotspots. Many possibilities and much potential of using VGI for generating, sharing, visualising and communicating knowledge about citizens’ spatial uses and preferences exist, but as a tool to support scientific and democratic interaction, VGI data is challenged by practical, technical and ethical concerns. More research is needed in order to better understand the usefulness and application of this rich data source to governance.

Mobility in vehicular networks with multiple access points to the infrastructure

Nowadays there is a huge evolution in the technological world and in the wireless networks. The electronic devices have more capabilities and resources over the years, which makes the users more and more demanding. The necessity of being connected to the global world leads to the arising of wireless access points in the cities to provide internet access to the people in order to keep the constant interaction with the world. Vehicular networks arise to support safety related applications and to improve the traffic flow in the roads; however, nowadays they are also used to provide entertainment to the users present in the vehicles. The best way to increase the utilization of the vehicular networks is to give to the users what they want: a constant connection to the internet. Despite of all the advances in the vehicular networks, there were several issues to be solved. The presence of dedicated infrastructure to vehicular networks is not wide yet, which leads to the need of using the available Wi-Fi hotspots and the cellular networks as access networks. In order to make all the management of the mobility process and to keep the user’s connection and session active, a mobility protocol is needed. Taking into account the huge number of access points present at the range of a vehicle for example in a city, it will be beneficial to take advantage of all available resources in order to improve all the vehicular network, either to the users and to the operators. The concept of multihoming allows to take advantage of all available resources with multiple simultaneous connections. This dissertation has as objectives the integration of a mobility protocol, the Network-Proxy Mobile IPv6 protocol, with a host-multihoming per packet solution in order to increase the performance of the network by using more resources simultaneously, the support of multi-hop communications, either in IPv6 or IPv4, the capability of providing internet access to the users of the network, and the integration of the developed protocol in the vehicular environment, with the WAVE, Wi-Fi and cellular technologies. The performed tests focused on the multihoming features implemented on this dissertation, and on the IPv4 network access for the normal users. The obtained results show that the multihoming addition to the mobility protocol improves the network performance and provides a better resource management. Also, the results show the correct operation of the developed protocol in a vehicular environment.

Explora: Infrastructure for Scaling Up Software Visualisation to Corpora

Visualisation provides good support for software analysis. It copes with the intangible nature of software by providing concrete representations of it. By reducing the complexity of software, visualisations are especially useful when dealing with large amounts of code. One domain that usually deals with large amounts of source code data is empirical analysis. Although there are many tools for analysis and visualisation, they do not cope well software corpora. In this paper we present Explora, an infrastructure that is specifically targeted at visualising corpora. We report on early results when conducting a sample analysis on Smalltalk and Java corpora.

A Microdata Analysis Approach to Transport Infrastructure Maintenance

Maintenance of transport infrastructure assets is widely advocated as the key in minimizing current and future costs of the transportation network. While effective maintenance decisions are often a result of engineering skills and practical knowledge, efficient decisions must also account for the net result over an asset's life-cycle. One essential aspect in the long term perspective of transport infrastructure maintenance is to proactively estimate maintenance needs. In dealing with immediate maintenance actions, support tools that can prioritize potential maintenance candidates are important to obtain an efficient maintenance strategy. This dissertation consists of five individual research papers presenting a microdata analysis approach to transport infrastructure maintenance. Microdata analysis is a multidisciplinary field in which large quantities of data is collected, analyzed, and interpreted to improve decision-making. Increased access to transport infrastructure data enables a deeper understanding of causal effects and a possibility to make predictions of future outcomes. The microdata analysis approach covers the complete process from data collection to actual decisions and is therefore well suited for the task of improving efficiency in transport infrastructure maintenance. Statistical modeling was the selected analysis method in this dissertation and provided solutions to the different problems presented in each of the five papers. In Paper I, a time-to-event model was used to estimate remaining road pavement lifetimes in Sweden. In Paper II, an extension of the model in Paper I assessed the impact of latent variables on road lifetimes; displaying the sections in a road network that are weaker due to e.g. subsoil conditions or undetected heavy traffic. The study in Paper III incorporated a probabilistic parametric distribution as a representation of road lifetimes into an equation for the marginal cost of road wear. Differentiated road wear marginal costs for heavy and light vehicles are an important information basis for decisions regarding vehicle miles traveled (VMT) taxation policies. In Paper IV, a distribution based clustering method was used to distinguish between road segments that are deteriorating and road segments that have a stationary road condition. Within railway networks, temporary speed restrictions are often imposed because of maintenance and must be addressed in order to keep punctuality. The study in Paper V evaluated the empirical effect on running time of speed restrictions on a Norwegian railway line using a generalized linear mixed model.