Framework for enterprise systems engineering

This research aimed at developing a research framework for the emerging field of enterprise systems engineering (ESE). The framework consists of an ESE definition, an ESE classification scheme, and an ESE process. This study views an enterprise as a system that creates value for its customers. Thus, developing the framework made use of system theory and IDEF methodologies. This study defined ESE as an engineering discipline that develops and applies systems theory and engineering techniques to specification, analysis, design, and implementation of an enterprise for its life cycle. The proposed ESE classification scheme breaks down an enterprise system into four elements. They are work, resources, decision, and information. Each enterprise element is specified with four system facets: strategy, competency, capacity, and structure. Each element-facet combination is subject to the engineering process of specification, analysis, design, and implementation, to achieve its pre-specified performance with respect to cost, time, quality, and benefit to the enterprise. This framework is intended for identifying research voids in the ESE discipline. It also helps to apply engineering and systems tools to this emerging field. It harnesses the relationships among various enterprise aspects and bridges the gap between engineering and management practices in an enterprise. The proposed ESE process is generic. It consists of a hierarchy of engineering activities presented in an IDEF0 model. Each activity is defined with its input, output, constraints, and mechanisms. The output of an ESE effort can be a partial or whole enterprise system design for its physical, managerial, and/or informational layers. The proposed ESE process is applicable to a new enterprise system design or an engineering change in an existing system. The long-term goal of this study aims at development of a scientific foundation for ESE research and development.

Scheduling medical application workloads on virtualized computing systems

This dissertation presents and evaluates a methodology for scheduling medical application workloads in virtualized computing environments. Such environments are being widely adopted by providers of "cloud computing" services. In the context of provisioning resources for medical applications, such environments allow users to deploy applications on distributed computing resources while keeping their data secure. Furthermore, higher level services that further abstract the infrastructure-related issues can be built on top of such infrastructures. For example, a medical imaging service can allow medical professionals to process their data in the cloud, easing them from the burden of having to deploy and manage these resources themselves. In this work, we focus on issues related to scheduling scientific workloads on virtualized environments. We build upon the knowledge base of traditional parallel job scheduling to address the specific case of medical applications while harnessing the benefits afforded by virtualization technology. To this end, we provide the following contributions: (1) An in-depth analysis of the execution characteristics of the target applications when run in virtualized environments. (2) A performance prediction methodology applicable to the target environment. (3) A scheduling algorithm that harnesses application knowledge and virtualization-related benefits to provide strong scheduling performance and quality of service guarantees. In the process of addressing these pertinent issues for our target user base (i.e. medical professionals and researchers), we provide insight that benefits a large community of scientific application users in industry and academia. Our execution time prediction and scheduling methodologies are implemented and evaluated on a real system running popular scientific applications. We find that we are able to predict the execution time of a number of these applications with an average error of 15%. Our scheduling methodology, which is tested with medical image processing workloads, is compared to that of two baseline scheduling solutions and we find that it outperforms them in terms of both the number of jobs processed and resource utilization by 20–30%, without violating any deadlines. We conclude that our solution is a viable approach to supporting the computational needs of medical users, even if the cloud computing paradigm is not widely adopted in its current form.

Reliability of the Clinical Application of a Mechanical Inclinometer in Measuring Glenohumeral Motion

Objective: Establish intra- and inter-examiner reliability of glenohumeral range of motion (ROM) measures taken by a single-clinician using a mechanical inclinometer. Design: A single-session, repeated-measure, randomized, counterbalanced design. Setting: Athletic Training laboratory. Participants: Ten college-aged volunteers (9 right-hand dominant; 4 males, 6 females; age=23.2±2.4y, mass=73±16kg, height=170±8cm) without shoulder or neck injuries within one year. Interventions: Two Certified Athletic Trainers separately assessed passive glenohumeral (GH) internal (IR) and external (ER) rotation bilaterally. Each clinician secured the inclinometer to each subject’s distal forearm using elastic straps. Clinicians followed standard procedures for assessing ROM, with the participants supine on a standard treatment table with 90° of elbow flexion. A second investigator recorded the angle. Clinicians measured all shoulders once to assess inter-clinician reliability and eight shoulders twice to assess intra-clinician reliability. We used SPSS 14.0 (SPSS Inc., Chicago, IL) to calculate standard error of measure (SEM) and Intraclass Correlation Coefficients (ICC) to evaluate intra- and inter-clinician reliability. Main Outcome Measures: Dependent variables were degrees of IR, ER, glenohumeral internal rotation deficit (GIRD) and total arc of rotation. We calculated GIRD as the bilateral difference in IR (nondominant–dominant) and total arc for each shoulder (IR+ER). Results: Intra-clinician reliability for each examiner was excellent (ICC[1,1] range=0.90-0.96; SEM=2.2°-2.5°) for all measures. Examiners displayed excellent inter-clinician reliability (ICC[2,1] range=0.79-0.97; SEM=1.7°-3.0°) for all measures except nondominant IR which had good reliability(0.72). Conclusions: Results suggest that clinicians can achieve reliable measures of GH rotation and GIRD using a single-clinician technique and an inexpensive, readily available mechanical inclinometer.

Framework for Enterprise Systems Engineering

This research aimed at developing a research framework for the emerging field of enterprise systems engineering (ESE). The framework consists of an ESE definition, an ESE classification scheme, and an ESE process. This study views an enterprise as a system that creates value for its customers. Thus, developing the framework made use of system theory and IDEF methodologies. This study defined ESE as an engineering discipline that develops and applies systems theory and engineering techniques to specification, analysis, design, and implementation of an enterprise for its life cycle. The proposed ESE classification scheme breaks down an enterprise system into four elements. They are work, resources, decision, and information. Each enterprise element is specified with four system facets: strategy, competency, capacity, and structure. Each element-facet combination is subject to the engineering process of specification, analysis, design, and implementation, to achieve its pre-specified performance with respect to cost, time, quality, and benefit to the enterprise. This framework is intended for identifying research voids in the ESE discipline. It also helps to apply engineering and systems tools to this emerging field. It harnesses the relationships among various enterprise aspects and bridges the gap between engineering and management practices in an enterprise. The proposed ESE process is generic. It consists of a hierarchy of engineering activities presented in an IDEF0 model. Each activity is defined with its input, output, constraints, and mechanisms. The output of an ESE effort can be a partial or whole enterprise system design for its physical, managerial, and/or informational layers. The proposed ESE process is applicable to a new enterprise system design or an engineering change in an existing system. The long-term goal of this study aims at development of a scientific foundation for ESE research and development.