Direct support and general support maintenance manual : survey instrument, azimuth, gyro, lightweight (Lear Siegler, Inc. models AG-8 and AG-8A) NSN 6675-00-062-8579.

Includes index.

Direct support and general support maintenance repair parts and special tools list (including depot maintenance repair parts and special tools) : survey instrument, azimuth, gyro, lightweight (Lear Siegler, Inc. models AG-8 and AG-8A), NSN 6675-00-062-8579.

Includes index.

Operator, organizational, direct support, and general support maintenance manual : theodolite, directional, 0.002 mil graduation, 5.9 in. lg. telescope ... (Wild Heerbrugg models), (model T2-56-C-MIL), NSN 6675-00-682-4635 ... theodolite, directional (reference), (Wild Heerbrugg models T2-56-C-MIL ... and T2-68MIL), NSN 6675-00-988-5225.

Includes index.

Direct support, general support, and depot maintenance manual : electronic equipment configuration Army models UH-1B and UH-1C/M helicopters.

Includes index.

Direct support and general support maintenance repair parts and special tools list for electronics equipment configuration, Army models UH-1H and UH-1V with SLAE.

Includes index.

Direct support and general support maintenance repair parts and special tools list ... for electronic equipment configuration, Army models UH-1D (NSN 1520-00-859-2670), UH-1H (NSN 1520-00-087-7637), UH-1V (NSN 1520-01-043-4949), and EH-1X (aircraft) (NSN 1520-01-042-9396) helicopters.

"17 May 1985."

Direct support and general support, maintenance repair parts and special tools lists (including depot maintenance repair parts and special tools lists) for : truck, lift, fork, EMD, solid rubber tired wheels, 4000 lb. capacity, 144 and 180 in. lift Army model MHE 227, Allis Chalmers models ACE40AEE144 (NSN 3930-00-327-1603) and ACE40AEE180 (NSN 3930-00-327-1600).

Cover title.

Direct support and general support maintenance manual for truck, lift, fork, GED, solid rubber tired wheels, 4000 lbs capacity, 100 and 180 inch lift, (Army model MHE-231, Allis Chalmers models ACC40-24PS100 and ACC40-24PS180, (NSN 3930-00-490-7814) (100 in.), (NSN 3930-00-556-4955) (180 in.).

Includes index.

Operator, organizational, direct and general support, and depot maintenance manual : control, radio set C6118/FRC-93 (Collins models 312B-4 and 312B-5).

"June 1964."

General and multiplicative non-parametric corporate performance models with interval ratio data

The increasing intensity of global competition has led organizations to utilize various types of performance measurement tools for improving the quality of their products and services. Data envelopment analysis (DEA) is a methodology for evaluating and measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. All the data in the conventional DEA with input and/or output ratios assumes the form of crisp numbers. However, the observed values of data in real-world problems are sometimes expressed as interval ratios. In this paper, we propose two new models: general and multiplicative non-parametric ratio models for DEA problems with interval data. The contributions of this paper are fourfold: (1) we consider input and output data expressed as interval ratios in DEA; (2) we address the gap in DEA literature for problems not suitable or difficult to model with crisp values; (3) we propose two new DEA models for evaluating the relative efficiencies of DMUs with interval ratios, and (4) we present a case study involving 20 banks with three interval ratios to demonstrate the applicability and efficacy of the proposed models where the traditional indicators are mostly financial ratios. © 2011 Elsevier Inc.

The Roles of Land and Orography on Precipitation and Ocean Circulation in Global Climate Models

Thesis (Ph.D.)--University of Washington, 2016-08

A review on degradation models in reliability analysis

With increasingly complex engineering assets and tight economic requirements, asset reliability becomes more crucial in Engineering Asset Management (EAM). Improving the reliability of systems has always been a major aim of EAM. Reliability assessment using degradation data has become a significant approach to evaluate the reliability and safety of critical systems. Degradation data often provide more information than failure time data for assessing reliability and predicting the remnant life of systems. In general, degradation is the reduction in performance, reliability, and life span of assets. Many failure mechanisms can be traced to an underlying degradation process. Degradation phenomenon is a kind of stochastic process; therefore, it could be modelled in several approaches. Degradation modelling techniques have generated a great amount of research in reliability field. While degradation models play a significant role in reliability analysis, there are few review papers on that. This paper presents a review of the existing literature on commonly used degradation models in reliability analysis. The current research and developments in degradation models are reviewed and summarised in this paper. This study synthesises these models and classifies them in certain groups. Additionally, it attempts to identify the merits, limitations, and applications of each model. It provides potential applications of these degradation models in asset health and reliability prediction.

Extended GNSS ambiguity resolution models with regularization criterion and constraints

This paper firstly presents an extended ambiguity resolution model that deals with an ill-posed problem and constraints among the estimated parameters. In the extended model, the regularization criterion is used instead of the traditional least squares in order to estimate the float ambiguities better. The existing models can be derived from the general model. Secondly, the paper examines the existing ambiguity searching methods from four aspects: exclusion of nuisance integer candidates based on the available integer constraints; integer rounding; integer bootstrapping and integer least squares estimations. Finally, this paper systematically addresses the similarities and differences between the generalized TCAR and decorrelation methods from both theoretical and practical aspects.