The reliability mathematical model of load-sharing parallel systems based on fatigue cumulative damage

Conventional reliability models for parallel systems are not applicable for the analysis of parallel systems with load transfer and sharing. In this short communication, firstly, the dependent failures of parallel systems are analyzed, and the reliability model of load-sharing parallel system is presented based on Miner cumulative damage theory and the full probability formula. Secondly, the parallel system reliability is calculated by Monte Carlo simulation when the component life follows the Weibull distribution. The research result shows that the proposed reliability mathematical model could analyze and evaluate the reliability of parallel systems in the presence of load transfer.

Human interfaces to structured documents

This research investigates some of the reasons for the reported difficulties experienced by writers when using editing software designed for structured documents. The overall objective was to determine if there are aspects of the software interfaces which militate against optimal document construction by writers who are not computer experts, and to suggest possible remedies. Studies were undertaken to explore the nature and extent of the difficulties, and to identify which components of the software interfaces are involved. A model of a revised user interface was tested, and some possible adaptations to the interface are proposed which may help overcome the difficulties. The methodology comprised: 1. identification and description of the nature of a ‘structured document’ and what distinguishes it from other types of document used on computers; 2. isolation of the requirements of users of such documents, and the construction a set of personas which describe them; 3. evaluation of other work on the interaction between humans and computers, specifically in software for creating and editing structured documents; 4. estimation of the levels of adoption of the available software for editing structured documents and the reactions of existing users to it, with specific reference to difficulties encountered in using it; 5. examination of the software and identification of any mismatches between the expectations of users and the facilities provided by the software; 6. assessment of any physical or psychological factors in the reported difficulties experienced, and to determine what (if any) changes to the software might affect these. The conclusions are that seven of the twelve modifications tested could contribute to an improvement in usability, effectiveness, and efficiency when writing structured text (new document selection; adding new sections and new lists; identifying key information typographically; the creation of cross-references and bibliographic references; and the inclusion of parts of other documents). The remaining five were seen as more applicable to editing existing material than authoring new text (adding new elements; splitting and joining elements [before and after]; and moving block text).

Dynamic classifiers for neonatal brain monitoring

Brain injury due to lack of oxygen or impaired blood flow around the time of birth, may cause long term neurological dysfunction or death in severe cases. The treatments need to be initiated as soon as possible and tailored according to the nature of the injury to achieve best outcomes. The Electroencephalogram (EEG) currently provides the best insight into neurological activities. However, its interpretation presents formidable challenge for the neurophsiologists. Moreover, such expertise is not widely available particularly around the clock in a typical busy Neonatal Intensive Care Unit (NICU). Therefore, an automated computerized system for detecting and grading the severity of brain injuries could be of great help for medical staff to diagnose and then initiate on-time treatments. In this study, automated systems for detection of neonatal seizures and grading the severity of Hypoxic-Ischemic Encephalopathy (HIE) using EEG and Heart Rate (HR) signals are presented. It is well known that there is a lot of contextual and temporal information present in the EEG and HR signals if examined at longer time scale. The systems developed in the past, exploited this information either at very early stage of the system without any intelligent block or at very later stage where presence of such information is much reduced. This work has particularly focused on the development of a system that can incorporate the contextual information at the middle (classifier) level. This is achieved by using dynamic classifiers that are able to process the sequences of feature vectors rather than only one feature vector at a time.

Impact of single parameter changes on Ceph cloud storage performance

In a general purpose cloud system efficiencies are yet to be had from supporting diverse applications and their requirements within a storage system used for a private cloud. Supporting such diverse requirements poses a significant challenge in a storage system that supports fine grained configuration on a variety of parameters. This paper uses the Ceph distributed file system, and in particular its global parameters, to show how a single changed parameter can effect the performance for a range of access patterns when tested with an OpenStack cloud system.