Organizational and direct support maintenance manual : automated data processing system AN/MYQ-4A (NSN 7010-01-158-5397).

"13 May 1985"--[Vol. 2].

An Effective Method for Constructing Data Structures Solving an Array Maintenance Problem

In this paper a constructive method of data structures solving an array maintenance problem is offered. These data structures are defined in terms of a family of digraphs which have previously been defined, representing solutions for this problem. We present as well a prototype of the method in Haskell.

Should weight loss and maintenance programmes be designed differently for men? : A systematic review of long-term randomised controlled trials presenting data for men and women: The ROMEO project

Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved. Acknowledgements This review is one of a series of systematic reviews for the ROMEO project (Review Of MEn and Obesity), funded by the National Institute for Health Research, Health Technology Assessment Programme (NIHR HTA Project 09/127/01; Systematic reviews and integrated report on the quantitative and qualitative evidence base for the management of obesity in men http://www.hta.ac.uk/2545). The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the Department of Health. HERU, HSRU and NMAHP are funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. The authors accept full responsibility for this publication. We would also like to thank the Men's Health Forums of Scotland, Ireland, England and Wales: Tim Street, Paula Carroll, Colin Fowler and David Wilkins. We also thank Kate Jolly for further information about the Lighten Up trial.

Should weight loss and maintenance programmes be designed differently for men? : A systematic review of long-term randomised controlled trials presenting data for men and women: The ROMEO project

Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved. Acknowledgements This review is one of a series of systematic reviews for the ROMEO project (Review Of MEn and Obesity), funded by the National Institute for Health Research, Health Technology Assessment Programme (NIHR HTA Project 09/127/01; Systematic reviews and integrated report on the quantitative and qualitative evidence base for the management of obesity in men http://www.hta.ac.uk/2545). The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the Department of Health. HERU, HSRU and NMAHP are funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. The authors accept full responsibility for this publication. We would also like to thank the Men's Health Forums of Scotland, Ireland, England and Wales: Tim Street, Paula Carroll, Colin Fowler and David Wilkins. We also thank Kate Jolly for further information about the Lighten Up trial.

A facilities maintenance management process based on degradation prediction using sensed data

Energy efficiency and user comfort have recently become priorities in the Facility Management (FM) sector. This has resulted in the use of innovative building components, such as thermal solar panels, heat pumps, etc., as they have potential to provide better performance, energy savings and increased user comfort. However, as the complexity of components increases, the requirement for maintenance management also increases. The standard routine for building maintenance is inspection which results in repairs or replacement when a fault is found. This routine leads to unnecessary inspections which have a cost with respect to downtime of a component and work hours. This research proposes an alternative routine: performing building maintenance at the point in time when the component is degrading and requires maintenance, thus reducing the frequency of unnecessary inspections. This thesis demonstrates that statistical techniques can be used as part of a maintenance management methodology to invoke maintenance before failure occurs. The proposed FM process is presented through a scenario utilising current Building Information Modelling (BIM) technology and innovative contractual and organisational models. This FM scenario supports a Degradation based Maintenance (DbM) scheduling methodology, implemented using two statistical techniques, Particle Filters (PFs) and Gaussian Processes (GPs). DbM consists of extracting and tracking a degradation metric for a component. Limits for the degradation metric are identified based on one of a number of proposed processes. These processes determine the limits based on the maturity of the historical information available. DbM is implemented for three case study components: a heat exchanger; a heat pump; and a set of bearings. The identified degradation points for each case study, from a PF, a GP and a hybrid (PF and GP combined) DbM implementation are assessed against known degradation points. The GP implementations are successful for all components. For the PF implementations, the results presented in this thesis find that the extracted metrics and limits identify degradation occurrences accurately for components which are in continuous operation. For components which have seasonal operational periods, the PF may wrongly identify degradation. The GP performs more robustly than the PF, but the PF, on average, results in fewer false positives. The hybrid implementations, which are a combination of GP and PF results, are successful for 2 of 3 case studies and are not affected by seasonal data. Overall, DbM is effectively applied for the three case study components. The accuracy of the implementations is dependant on the relationships modelled by the PF and GP, and on the type and quantity of data available. This novel maintenance process can improve equipment performance and reduce energy wastage from BSCs operation.

Automated generic integration of flight logbook data into aircraft maintenance systems

The automated transfer of flight logbook information from aircrafts into aircraft maintenance systems leads to reduced ground and maintenance time and is thus desirable from an economical point of view. Until recently, flight logbooks have not been managed electronically in aircrafts or at least the data transfer from aircraft to ground maintenance system has been executed manually. Latest aircraft types such as the Airbus A380 or the Boeing 787 do support an electronic logbook and thus make an automated transfer possible. A generic flight logbook transfer system must deal with different data formats on the input side – due to different aircraft makes and models – as well as different, distributed aircraft maintenance systems for different airlines as aircraft operators. This article contributes the concept and top level distributed system architecture of such a generic system for automated flight log data transfer. It has been developed within a joint industry and applied research project. The architecture has already been successfully evaluated in a prototypical implementation.

Big data analytics for proactive and predictive maintenance in electric car battery packs

The idea behind the project is to develop a methodology for analyzing and developing techniques for the diagnosis and the prediction of the state of charge and health of lithium-ion batteries for automotive applications. For lithium-ion batteries, residual functionality is measured in terms of state of health; however, this value cannot be directly associated with a measurable value, so it must be estimated. The development of the algorithms is based on the identification of the causes of battery degradation, in order to model and predict the trend. Therefore, models have been developed that are able to predict the electrical, thermal and aging behavior. In addition to the model, it was necessary to develop algorithms capable of monitoring the state of the battery, online and offline. This was possible with the use of algorithms based on Kalman filters, which allow the estimation of the system status in real time. Through machine learning algorithms, which allow offline analysis of battery deterioration using a statistical approach, it is possible to analyze information from the entire fleet of vehicles. Both systems work in synergy in order to achieve the best performance. Validation was performed with laboratory tests on different batteries and under different conditions. The development of the model allowed to reduce the time of the experimental tests. Some specific phenomena were tested in the laboratory, and the other cases were artificially generated.

Data-stream driven Fuzzy-granular approaches for system maintenance

Intelligent systems are currently inherent to the society, supporting a synergistic human-machine collaboration. Beyond economical and climate factors, energy consumption is strongly affected by the performance of computing systems. The quality of software functioning may invalidate any improvement attempt. In addition, data-driven machine learning algorithms are the basis for human-centered applications, being their interpretability one of the most important features of computational systems. Software maintenance is a critical discipline to support automatic and life-long system operation. As most software registers its inner events by means of logs, log analysis is an approach to keep system operation. Logs are characterized as Big data assembled in large-flow streams, being unstructured, heterogeneous, imprecise, and uncertain. This thesis addresses fuzzy and neuro-granular methods to provide maintenance solutions applied to anomaly detection (AD) and log parsing (LP), dealing with data uncertainty, identifying ideal time periods for detailed software analyses. LP provides deeper semantics interpretation of the anomalous occurrences. The solutions evolve over time and are general-purpose, being highly applicable, scalable, and maintainable. Granular classification models, namely, Fuzzy set-Based evolving Model (FBeM), evolving Granular Neural Network (eGNN), and evolving Gaussian Fuzzy Classifier (eGFC), are compared considering the AD problem. The evolving Log Parsing (eLP) method is proposed to approach the automatic parsing applied to system logs. All the methods perform recursive mechanisms to create, update, merge, and delete information granules according with the data behavior. For the first time in the evolving intelligent systems literature, the proposed method, eLP, is able to process streams of words and sentences. Essentially, regarding to AD accuracy, FBeM achieved (85.64+-3.69)%; eGNN reached (96.17+-0.78)%; eGFC obtained (92.48+-1.21)%; and eLP reached (96.05+-1.04)%. Besides being competitive, eLP particularly generates a log grammar, and presents a higher level of model interpretability.

Vertical alveolar crest bone maintenance around implants in two-stage surgery: an in situ study in dogs

The aim of this study was to evaluate in situ changes in the alveolar crest bone height around immediate implant-supported crowns in comparison to tooth-supported crowns (control) with the cervical margins located at the bone crest level, without occlusal load. In Group I, after extraction of 12 mandibular premolars from 4 adult dogs, implants from Branemark System (MK III TiU RP 4.0 x 11.5 mm) were placed to retain complete acrylic crowns. In Group II, premolars were prepared to receive complete metal crowns. Sixteen weeks after placement of the crowns (38 weeks after tooth extraction), the height of the alveolar bone crest was measured with a digital caliper. Data were analyzed statistically by the Mann-Whitney test at 5% significance level. The in situ analysis showed no statistically significant difference (p=0.880) between the implant-supported and the tooth-supported groups (1.528 + 0.459 mm and 1.570 + 0.263 mm, respectively). Based on the findings of the present study, it may be concluded that initial peri-implant bone loss may result from the remodeling process necessary to establish the biological space, similar to which occurs with tooth-supported crowns.

Evaluation of the dental structure loss produced during maintenance and replacement of occlusal amalgam restorations

The aim of this in vitro study was to evaluate four different approaches to the decision of changing or not defective amalgam restorations in first primary molar teeth concerning the loss of dental structure. Ditched amalgam restorations (n = 11) were submitted to four different treatments, as follows: Control group - polishing and finishing of the restorations were carried out; Amalgam group - the ditched amalgam restorations were replaced by new amalgam restorations; Composite resin group - the initial amalgam restorations were replaced by composite resin restorations; Flowable resin group - the ditching around the amalgam restorations was filled with flowable resin. Images of the sectioned teeth were made and the area of the cavities before and after the procedures was determined by image analysis software to assess structural loss. The data were submitted to ANOVA complemented by the Student Newman Keuls test (p < 0.05). The cavities in all the groups presented significantly greater areas after the procedures. However, the amalgam group showed more substantial dental loss. The other three groups presented no statistically significant difference in dental structure loss after the re-treatments. Thus, replacing ditched amalgam restorations by other similar restorations resulted in a significant dental structure loss while maintaining them or replacing them by resin restorations did not result in significant loss.

Methadone maintenance and drug-related crime

Using data from an evaluation of methadone maintenance treatment, this study investigated factors associated with continued involvement irt crime during treatment, and in particular whether there appeared to be differences in effectiveness of treatment between different methadone clinics. The methodology was an observational study, in which 304 patients attending three low-intervention, private methadone clinics in Sydney were interviewed on three occasions over a twelve month period. Outcome measures were self-reported criminal activity and police department records of convictions. By self-report, crime dropped, promptly and substantially on entry to treatment, to a level of acquisitive crime about one-eighth that reported during the last addiction period. Analysis of official records indicated that rates of acquisitive convictions were significantly lower in the in-treatment period compared to prior to entry to treatment, corroborating the changes suggested by self-report. Persisting involvement in crime in treatment was predicted by two factors: the cost of persisting use of illicit drugs, particularly cannabis, and ASPD symptom count. Treatment factors also were independently predictive of continued involvement in crime. By both self-report and official records, and adjusting for subject factors, treatment at one clinic teas associated with greater involvement in crime. This clinic operated in a chaotic and poorly organized way. it is concluded that crime during methadone treatment is substantially lower than during street addiction, although the extent of reduction depends on the quality of treatment being delivered.

Materialized view selection under the maintenance time constraint

A data warehouse is a data repository which collects and maintains a large amount of data from multiple distributed, autonomous and possibly heterogeneous data sources. Often the data is stored in the form of materialized views in order to provide fast access to the integrated data. One of the most important decisions in designing a data warehouse is the selection of views for materialization. The objective is to select an appropriate set of views that minimizes the total query response time with the constraint that the total maintenance time for these materialized views is within a given bound. This view selection problem is totally different from the view selection problem under the disk space constraint. In this paper the view selection problem under the maintenance time constraint is investigated. Two efficient, heuristic algorithms for the problem are proposed. The key to devising the proposed algorithms is to define good heuristic functions and to reduce the problem to some well-solved optimization problems. As a result, an approximate solution of the known optimization problem will give a feasible solution of the original problem. (C) 2001 Elsevier Science B.V. All rights reserved.

Who does not gain weight? Prevalence and predictors of weight maintenance in young women

OBJECTIVE: To investigate the prevalence and predictors of weight maintenance over time in a large sample of young Australian women. DESIGN: This population study examined baseline and 4y follow-up data from the cohort of young women participating in the Australian Longitudinal Study on Women's Health. SUBJECTS: A total of 8726 young women aged 18 - 23y at baseline. MEASURES: Height, weight and body mass index (BMI); physical activity; time spent sitting; selected eating behaviours (eg dieting, disordered eating, takeaway food consumption); cigarette smoking, alcohol consumption; parity; and socio-demographic characteristics. RESULTS: Only 44% of the women reported their BMI at follow-up to be within 5% of their baseline BMI (maintainers); 41% had gained weight and 15% had lost weight. Weight maintainers were more likely to be in managerial or professional occupations; to have never married; to be currently studying; and not to be mothers. Controlling for sociodemographic factors, weight maintainers were more likely to be in a healthy weight range at baseline, and to report that they spent less time sitting, and consumed less takeaway food, than women who gained weight. CONCLUSIONS: Fewer than half the young women in this community sample maintained their weight over this 4y period in their early twenties. Findings of widespread weight gain, particularly among those already overweight, suggest that early adulthood, which is a time of significant life changes for many women, may be an important time for implementing strategies to promote maintenance of healthy weight. Strategies which encourage decreased sitting time and less takeaway food consumption may be effective for encouraging weight maintenance at this life stage.

Privacy and Data Protection in Elderly Healthcare: Threats and Legal Warranties

The progressive aging of the population requires new kinds of social and medical intervention and the availability of different services provided to the elder population. New applications have been developed and some services are now provided at home, allowing the older people to stay home instead of having to stay in hospitals. But an adequate response to the needs of the users will imply a high percentage of use of personal data and information, including the building up and maintenance of user profiles, feeding the systems with the data and information needed for a proactive intervention in scheduling of events in which the user may be involved. Fundamental Rights may be at stake, so a legal analysis must also be considered.