Statement of indemnity and average in cooperative bovine brucellosis work /

Description based on: May 1955; title from caption.

Trends in mortality differentials and life expectancy for male social security-covered workers, by average relative earnings /

"SSA publication no. 13-11712"--Cover p. [4].

Employment and wages, annual average /

Latest issue consulted: 2005.

City average daily traffic on state trunkline routes. In cooperation with the Bureau of Public Roads, U.S. Department of Commerce.

Mode of access: Internet.

Number-average molecular weights; fundamentals and determination

Mode of access: Internet.

Computing average log values for timber appraisals using IBM 650 or UNIVAC solid state 80 computers /

"January 1961."

What is the Impact of the Underserved Pathway program on Entering an Underserved Family Medicine Residency? A Comparison of Three Approaches for Estimating the Average Treatment Effect

Thesis (Master's)--University of Washington, 2016-06

Meeting Physical Activity Guidelines and Average Daily Steps in a Working Population

Purpose: The aims of this study were to investigate the relationships and agreement between average number of steps taken per day and compliance with Australian physical activity guidelines in a sample of working Australian adults. Methods: One hundred-eighty-five adults wore a pedometer and recorded the number of steps taken each day for 7 d. On the 8th day, they completed a self-report survey that asked about frequency and duration of different activities during the previous week. Results: The average number of steps per day was 8543 (standard deviation = 2466) for men (n = 74) and 9093 (2926) for women (n = 111; no significant difference). Just over half the men (53%) and 45% of the women met the current national physical activity guidelines (no significant difference). Average number of steps per day was higher in those who met the guidelines [9547 (2655), n = 89] than in those who did not [8220 (2702), n = 96; P

The specification of vector autoregressive moving average models

In this paper we propose a new identification method based on the residual white noise autoregressive criterion (Pukkila et al. , 1990) to select the order of VARMA structures. Results from extensive simulation experiments based on different model structures with varying number of observations and number of component series are used to demonstrate the performance of this new procedure. We also use economic and business data to compare the model structures selected by this order selection method with those identified in other published studies.

Teleonomic entropy: measuring the phase-space of end-directed systems

We introduce a novel way of measuring the entropy of a set of values undergoing changes. Such a measure becomes useful when analyzing the temporal development of an algorithm designed to numerically update a collection of values such as artificial neural network weights undergoing adjustments during learning. We measure the entropy as a function of the phase-space of the values, i.e. their magnitude and velocity of change, using a method based on the abstract measure of entropy introduced by the philosopher Rudolf Carnap. By constructing a time-dynamic two-dimensional Voronoi diagram using Voronoi cell generators with coordinates of value- and value-velocity (change of magnitude), the entropy becomes a function of the cell areas. We term this measure teleonomic entropy since it can be used to describe changes in any end-directed (teleonomic) system. The usefulness of the method is illustrated when comparing the different approaches of two search algorithms, a learning artificial neural network and a population of discovering agents. (C) 2004 Elsevier Inc. All rights reserved.

Family average income and body mass index above the healthy weight range among urban and rural residents in regional Mainland China

Objective: To explore the relationship between family average income (FAI; an index of socio-economic status) and body mass index (BMI; a widely used, inexpensive indicator of weight status) above the healthy weight range in a region of Mainland China. Design: Population-based cross-sectional study, conducted between October 1999 and March 2000 on a sample of regular local residents aged 35 years or older who were selected by random cluster sampling. Setting: Forty-five administrative villages selected from three urban districts and two rural counties of Nanjing municipality, Mainland China, with a regional population of 5.6 million. Subjects: In total, 29 340 subjects participated; 67.7% from urban and 32.3% from rural areas; 49.8% male and 50.2% female. The response rate among eligible participants was 90.1%. Results: The proportion of participants classified as overweight was 30.5%, while 7.8% were identified as obese. After adjusting for possible confounding variables (age, gender, area of residence, educational level, occupational and leisure-time physical activity, daily vegetable consumption and frequency of red meat intake), urban participants were more likely to be overweight or obese relative to their rural counterparts, more women than men were obese, and participants in the lowest FAI tertile were the least likely to be above the healthy weight range. Conclusions: The proportion of adults with BMI above the healthy weight range was positively related to having a higher socio-economic status (indexed by FAI) in a regional Chinese population.

A tutorial on the cross-entropy method

The cross-entropy (CE) method is a new generic approach to combinatorial and multi-extremal optimization and rare event simulation. The purpose of this tutorial is to give a gentle introduction to the CE method. We present the CE methodology, the basic algorithm and its modifications, and discuss applications in combinatorial optimization and machine learning. combinatorial optimization