EVALUATING TRANSIT SYSTEMS IN A UNIVERSITY ENVIRONMENT THE CLEMSON UNIVERSITY CASE STUDY

With the economy in a slow recovery, enrollment in higher education is increasing. This means that universities across the country must accommodate these new students, their vehicles, and local transportation needs. Campus setting and ambiance is a treasured quality on a university campus resulting in the approval of additional surface lots and parking garages being difficult or restricted. To combat the increased number of single occupancy vehicles, universities are developing and encouraging the use of multimodal transportation by providing pedestrian, bicycle, and public transportation facilities along with providing users with the information necessary to make the optimal modal choice (Boyles, 2006). This research developed a framework to evaluate transit in the context of mobility currently on a university campus. The framework includes a process that any university can utilize to evaluate its current and future transit efficiency levels and identify solutions through an integrated process of planning, operations, and performance monitoring. Clemson University\u27s campus in Clemson, South Carolina serves as a case study for the test application of this process. This study evaluates Clemson University\u27s performance in providing adequate transportation options to the university community in comparison with similar universities. Customer satisfaction surveys are used to determine deficiencies from the user\u27s perspective. Traffic simulations and a matrix alternative analysis have evaluated several alternatives developed through integrating the results of transit capacity surveys, user surveys, and considerations for pedestrian and bicycle traffic to create seamless operations and optimal function of all transportation modes available. The case study presented in this thesis can serve as a guide to university campuses beginning to have significant mobility problems. It also provides an insight into the institutional or organizational structures that facilitate efficient, high-quality transportation services, which can guide universities to pursue structural or policy changes to improve mobility. Although the process is tailored for small &ndash or medium &ndash sized universities outside of urban areas, the evaluation framework can be customized for use at any university regardless of its size or location

Evaluating e-Government services from a citizens' prespective: A reference process model

Evaluating and optimizing e-government services is imperative for governments especially due to the capacity of e-services to transform public administrations and assist the interactions of governments with citizens, businesses and other government agencies. Existing widely applied evaluation approaches neglect to incorporate citizens’ satisfaction measures. Several citizen satisfaction models and indicators have been suggested in academia; however a reference process model that can assist practitioners to apply these performance measures is missing. In this paper we draw upon the evaluation approach proposed by the EU funded project CEES and propose a reference process model that captures re-usable practices for e-government evaluation from a citizens’ perspective. The novelty of the proposed approach is that using DEA for evaluating the e-services the assessment results in suggestions for strategic improvement of the e-services.EU FP7 Marie Curie People Project “CEES - Citizen oriented Evaluation of E-Government Systems” (reference IAPP-2008-230658

CONFPROFITT: A CONFIGURATION-AWARE PERFORMANCE PROFILING, TESTING, AND TUNING FRAMEWORK

Modern computer software systems are complicated. Developers can change the behavior of the software system through software configurations. The large number of configuration option and their interactions make the task of software tuning, testing, and debugging very challenging. Performance is one of the key aspects of non-functional qualities, where performance bugs can cause significant performance degradation and lead to poor user experience. However, performance bugs are difficult to expose, primarily because detecting them requires specific inputs, as well as specific configurations. While researchers have developed techniques to analyze, quantify, detect, and fix performance bugs, many of these techniques are not effective in highly-configurable systems. To improve the non-functional qualities of configurable software systems, testing engineers need to be able to understand the performance influence of configuration options, adjust the performance of a system under different configurations, and detect configuration-related performance bugs. This research will provide an automated framework that allows engineers to effectively analyze performance-influence configuration options, detect performance bugs in highly-configurable software systems, and adjust configuration options to achieve higher long-term performance gains. To understand real-world performance bugs in highly-configurable software systems, we first perform a performance bug characteristics study from three large-scale opensource projects. Many researchers have studied the characteristics of performance bugs from the bug report but few have reported what the experience is when trying to replicate confirmed performance bugs from the perspective of non-domain experts such as researchers. This study is meant to report the challenges and potential workaround to replicate confirmed performance bugs. We also want to share a performance benchmark to provide real-world performance bugs to evaluate future performance testing techniques. Inspired by our performance bug study, we propose a performance profiling approach that can help developers to understand how configuration options and their interactions can influence the performance of a system. The approach uses a combination of dynamic analysis and machine learning techniques, together with configuration sampling techniques, to profile the program execution, analyze configuration options relevant to performance. Next, the framework leverages natural language processing and information retrieval techniques to automatically generate test inputs and configurations to expose performance bugs. Finally, the framework combines reinforcement learning and dynamic state reduction techniques to guide subject application towards achieving higher long-term performance gains

Context-driven progressive enhancement of mobile web applications: a multicriteria decision-making approach

Personal computing has become all about mobile and embedded devices. As a result, the adoption rate of smartphones is rapidly increasing and this trend has set a need for mobile applications to be available at anytime, anywhere and on any device. Despite the obvious advantages of such immersive mobile applications, software developers are increasingly facing the challenges related to device fragmentation. Current application development solutions are insufficiently prepared for handling the enormous variety of software platforms and hardware characteristics covering the mobile eco-system. As a result, maintaining a viable balance between development costs and market coverage has turned out to be a challenging issue when developing mobile applications. This article proposes a context-aware software platform for the development and delivery of self-adaptive mobile applications over the Web. An adaptive application composition approach is introduced, capable of autonomously bypassing context-related fragmentation issues. This goal is achieved by incorporating and validating the concept of fine-grained progressive application enhancements based on a multicriteria decision-making strategy

COBRA framework to evaluate e-government services: A citizen-centric perspective

E-government services involve many stakeholders who have different objectives that can have an impact on success. Among these stakeholders, citizens are the primary stakeholders of government activities. Accordingly, their satisfaction plays an important role in e-government success. Although several models have been proposed to assess the success of e-government services through measuring users' satisfaction levels, they fail to provide a comprehensive evaluation model. This study provides an insight and critical analysis of the extant literature to identify the most critical factors and their manifested variables for user satisfaction in the provision of e-government services. The various manifested variables are then grouped into a new quantitative analysis framework consisting of four main constructs: cost; benefit; risk and opportunity (COBRA) by analogy to the well-known SWOT qualitative analysis framework. The COBRA measurement scale is developed, tested, refined and validated on a sample group of e-government service users in Turkey. A structured equation model is used to establish relationships among the identified constructs, associated variables and users' satisfaction. The results confirm that COBRA framework is a useful approach for evaluating the success of e-government services from citizens' perspective and it can be generalised to other perspectives and measurement contexts. Crown Copyright © 2014.PIAP-GA-2008-230658) from the European Union Framework Program and another grant (NPRP 09-1023-5-158) from the Qatar National Research Fund (amember of Qatar Foundation

Decision-focussed resource modelling for design decision support

Resource management including resource allocation, levelling, configuration and monitoring has been recognised as critical to design decision making. It has received increasing research interests in recent years. Different definitions, models and systems have been developed and published in literature. One common issue with existing research is that the resource modelling has focussed on the information view of resources. A few acknowledged the importance of resource capability to design management, but none has addressed the evaluation analysis of resource fitness to effectively support design decisions. This paper proposes a decision-focused resource model framework that addresses the combination of resource evaluation with resource information from multiple perspectives. A resource management system constructed on the resource model framework can provide functions for design engineers to efficiently search and retrieve the best fit resources (based on the evaluation results) to meet decision requirements. Thus, the system has the potential to provide improved decision making performance compared with existing resource management systems

Layered evaluation of interactive adaptive systems : framework and formative methods

Peer reviewedPostprin