Yes / Identifying and explaining the pathophysiology of sepsis, as well as the importance of monitoring for indicators of patient deterioration in sepsis.

Geothermal energy can make an important contribution to the U.S. energy portfolio. Production areas require seismic monitoring tools to develop and monitor production capability. This paper describes modifications made to a prototypical seismic tool to implement improvements that were identified during previous tool applications. These modifications included changing the motor required for mechanical coupling the tool to a bore-hole wall. Additionally, development of a closed-loop process control utilized feedback from the contact force between the coupling arm and bore-hole wall. Employing a feedback circuit automates the tool deployment/anchoring process and reduces reliance on the operator at the surface. The tool components were tested under high temperatures and an integrated system tool test demonstrated successful tool operations. / Master of Science

No / The cure of polydicyclopentadiene conducted by ring-opening metathesis polymerisation in the presence of a Grubbs catalyst was studied using non-invasive Raman spectroscopy. The spectra of the monomer precursor and polymerised product were fully characterised and all stages of polymerisation monitored. Because of the monomer's high reactivity, the cure process is adaptable to reaction injection moulding and reactive rotational moulding. The viscosity of the dicyclopentadiene undergoes a rapid change at the beginning of the polymerisation process and it is critical that the induction time of the viscosity increase is determined and controlled for successful manufacturing. The results from this work show non-invasive Raman spectroscopic monitoring to be an effective method for monitoring the degree of cure, paving the way for possible implementation of the technique as a method of real-time analysis for control and optimisation during reactive processing. Agreement is shown between Raman measurements and ultrasonic time of flight data acquired during the initial induction period of the curing process.

京都大学 / 新制・課程博士 / 博士(経済学) / 甲第25076号 / 経博第683号 / 京都大学大学院経済学研究科経済学専攻 / (主査)教授 関口 格, 准教授 陳 珈惠, 教授 原 千秋 / 学位規則第4条第1項該当 / Doctor of Economics / Kyoto University / DGAM

The purpose of this study was to analyze the experiences of self-monitoring of blood glucose (SMBG) usage of adults with type 2 diabetes mellitus (T2DM) who are not using insulin. The sample consisted of 11 women and 8 men who were Caucasian Americans, 38 to 79 years of age. Data were analyzed using the grounded theory method including open and axial coding and the constant comparative method. The theory of "SMBG as a Cue in T2DM Self-Care" emerged from the data and is composed of four categories (a) Engaging, (b) Checking, (c) Responding, and (d) Establishing a Pattern. Engaging marks the beginning of SMBG. Participants began on the recommendation of their physician and monitored between 2-6 times a day. Participants monitored because of curiosity and over time reduced or kept their initial frequency. Checking occurs when the blood glucose is obtained. Two subcategories emerged: Evaluating and Validating. The main items participants evaluated or validated were the effects of foods in relation to blood glucose levels. Responding involves reacting to SMBG. Two subcategories emerged: Taking Action and Experiencing Emotion. Most actions involved changing foods consumed. Participants described feeling conflicted and "being bad" when not following through with an action. Emotions such as blame and fear were experienced when blood glucose levels were higher than normal, while happiness was experienced with normal levels. Establishing a Pattern occurs when participants decide on how often to monitor. Two subcategories emerged: Using Regularly and Using Sporadically. The pattern developed was based on obtaining "normal" blood glucose patterns or on the absence of ill symptoms of T2DM. Healthcare provider disinterest in SMBG and fingertip pain contributed to a decreased monitoring frequency. Participants described cyclical, iterative episodes of Checking, Responding, and varying their established patterns throughout their experiences with monitoring. Participants discussed the value and struggles of SMBG in a T2DM self-care regimen. The theory of SMBG as a Cue in T2DM Self-Care could be used to guide the development of effective intervention strategies to help individuals with T2DM achieve blood glucose control which, in turn, leads to avoidance of ill symptoms and complications of T2DM.

State monitoring is a fundamental building block for Cloud services. The demand for providing state monitoring as services (MaaS) continues to grow and is evidenced by CloudWatch from Amazon EC2, which allows cloud consumers to pay for monitoring a selection of performance metrics with coarse-grained periodical sampling of runtime states. One of the key challenges for wide deployment of MaaS is to provide better balance among a set of critical quality and performance parameters, such as accuracy, cost, scalability and customizability. This dissertation research is dedicated to innovative research and development of an elastic framework for providing state monitoring as a service (MaaS). We analyze limitations of existing techniques, systematically identify the need and the challenges at different layers of a Cloud monitoring service platform, and develop a suite of distributed monitoring techniques to support for flexible monitoring infrastructure, cost-effective state monitoring and monitoring-enhanced Cloud management. At the monitoring infrastructure layer, we develop techniques to support multi-tenancy of monitoring services by exploring cost sharing between monitoring tasks and safeguarding monitoring resource usage. To provide elasticity in monitoring, we propose techniques to allow the monitoring infrastructure to self-scale with monitoring demand. At the cost-effective state monitoring layer, we devise several new state monitoring functionalities to meet unique functional requirements in Cloud monitoring. Violation likelihood state monitoring explores the benefits of consolidating monitoring workloads by allowing utility-driven monitoring intensity tuning on individual monitoring tasks and identifying correlations between monitoring tasks. Window based state monitoring leverages distributed windows for the best monitoring accuracy and communication efficiency. Reliable state monitoring is robust to both transient and long-lasting communication issues caused by component failures or cross-VM performance interferences. At the monitoring-enhanced Cloud management layer, we devise a novel technique to learn about the performance characteristics of both Cloud infrastructure and Cloud applications from cumulative performance monitoring data to increase the cloud deployment efficiency.

Gemeinsamer Workshop von Universitaetsrechenzentrum und Professur Rechnernetze und verteilte Systeme der Fakultaet fuer Informatik der TU Chemnitz. Service Monitoring ist eine Voraussetzung für zuverlässige Dienste. Ausgehend von einer Einführung in die Techniken des Real-Time Monitoring wird das System "Big Brother" und der Einsatz im Universitätsrechenzentrum der TUC vorgestellt. Abschliesend werden einige Aspekte der Benachrichtigung beim Auftreten kritischer Ereignisse und Zustände diskutiert. bei der Alarmierung

Scalable system monitoring is a fundamental abstraction for large-scale networked systems. The goal of this dissertation is to design and build a scalable monitoring middleware that provides system introspection for large distributed systems and that will facilitate the design, development, and deployment of distributed monitoring applications. This middleware will enable monitoring applications to flexibly control the tradeoff between result precision and communication cost and to improve result accuracy in the face of node failures, network delays, and system reconfigurations. We present PRISM (PRecision-Integrated Scalable Monitoring), a scalable monitoring middleware that provides a global aggregate view of large-scale networked systems and that can serve as a building block for a broad range of distributed monitoring applications by coordinating views of multiple vantage points across the network. To coordinate a global view for system introspection, PRISM faces two key challenges: (1) scalability to large systems and high data volumes and (2) safeguarding accuracy in the face of node and network failures. To address these challenges, we design, implement, and evaluate PRISM, a system that defines precision as a new unified abstraction to enable scalable monitoring. PRISM quantifies (im)precision along a three-dimensional vector: arithmetic imprecision (AI) and temporal imprecision (TI) balance precision against monitoring overhead for scalability while network imprecision (NI) addresses the challenge of providing consistency guarantees despite failures. Our prototype implementation of PRISM addresses the challenge of providing these metrics while scaling to a large number of nodes and attributes by (1) leveraging Distributed Hash Tables (DHTs) to create scalable aggregation trees, (2) self-tuning AI budgets across nodes in a principled, near-optimal manner to shift precision to where it is useful, (3) pipelining TI delays across tree levels to maximize batching of updates, and (4) applying dual-tree prefix aggregation which exploits symmetry in our DHT topology to drastically reduce the cost of the active probing needed to maintain NI. Through extensive simulations and experiments on four large-scale testbeds, we observe that PRISM provides a key substrate for scalable monitoring by (1) reducing monitoring load by up to two orders of magnitude compared to existing approaches, (2) providing a flexible framework to control the tradeoff between accuracy, bandwidth cost, and response latency, (3) characterizing and improving confidence in the accuracy of results in the face of system disruptions, and (4) improving the observed accuracy by up to an order of magnitude despite churn. We have built several monitoring applications on top of PRISM including a distributed heavy hitter detection service, a distributed monitoring service for Internet-scale systems, and a detection service for monitoring distributed-denial-of-service (DDoS) attacks at the source-side in distributed networked systems. Finally, we demonstrate how the unified precision abstraction enables new monitoring applications by presenting experiences from these applications. / text

No description available.

Thesis (M. Sc.)--University of Hong Kong, 1996. / Includes bibliographical references (leaf 42-47).