WorldCat Identities

Miller, Curtis M.

Overview
Works: 16 works in 18 publications in 1 language and 77 library holdings
Genres: Pictorial works  History  Biography  Genealogy 
Roles: Author
Publication Timeline
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Most widely held works by Curtis M Miller
Nineteenth century freedom fighters : the 1st South Carolina Volunteers by Bennie J McRae( Book )

2 editions published in 2006 in English and held by 38 WorldCat member libraries worldwide

The 1st South Carolina Volunteers, later the 33rd United States Colored Troops, were the first black unit of the Civil War. Preceding the famous 54th Massachusetts-seen in the film Glory-by one year, these South Carolina slaves turned soldiers were noted for their courage, discipline, and pride, continuing to serve the Union cause even while temporarily disbanded. They fought for years with little or no pay, poor equipment, and constant pressure and abuse from both North and South. This brief history is told mostly through the letters and journals of their commanding officer Lt. Col. Charles T. Trowbridge. Bennie J. McRae Jr. runs Lest We Forget, an online resource specializing in the service of blacks in the U.S. military. Curtis M. Miller is a reporter and anchor at WIBC radio in Indianapolis. Cheryl Trowbridge-Miller, a descendent of Lieutenant Colonel Trowbridge, is an employee of Fiserv Item Processing and a genealogist specialising in researching slave ancestors of black families
Unpacking NumPy and Pandas by Curtis M Miller( Visual )

1 edition published in 2017 in English and held by 4 WorldCat member libraries worldwide

"Python, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. In this video course, you will explore two of the most important Python packages used by Data Analysts. You will start off by learning how to set up the right environment for data analysis with Python. Here, you’ll learn to install the right Python distribution, as well as work with the Jupyter notebook, and set up a database. After that you will dive into Python’s NumPy package, Python’s powerful extension with advanced mathematical functions. You will learn to create NumPy arrays, as well as employ different array methods and functions. Then, you will explore Python’s Pandas extension, where you will learn to subset your data, as well as dive into data mapping using Pandas. You’ll also learn to manage your data sets by sorting and ranking them. Finally, you will learn to index and group your data for sophisticated data analysis and manipulation."--Resource description page
Marketing your crop : a hedging handbook for farmers by Curtis M Miller( Book )

1 edition published in 1998 in English and held by 2 WorldCat member libraries worldwide

Five county regional vocational system regional communications model project for the five southernmost Illinois counties( Book )

1 edition published in 1984 in English and held by 2 WorldCat member libraries worldwide

Tech Prep for Shawnee Community College and Five County Regional Vocational System( Book )

2 editions published in 1994 in English and held by 2 WorldCat member libraries worldwide

Search for level sets of functions using computer experiments by Curtis M Miller( Book )

1 edition published in 2005 in English and held by 2 WorldCat member libraries worldwide

In engineering and other fields, it is common to use a computer simulation to model a real world process. The inputs to a function f represent factors that influence the outcome. The output represents a quantity of interest. Often there will be a specified level L, and the objective is to find the inputs for which output is above L.L may be a tolerance level, and the inputs for which response is larger than L form a tolerance region. We might estimate the tolerance region by evaluating f on a grid, but even a coarse grid may have thousands of points in four or five dimensions. If the function f is costly to evaluate, we need to be able to estimate the tolerance region with as few evaluations as possible. We approach this problem with a sequential search. Use data at any stage to fit a spatial process that approximates the function. Fit a Gaussian spatial process, as described in Currin, Mitchell, Morris, and Ylvisaker[1991]. The spatial process gives an estimate of the L-contour. We can also use the process to estimate how much information would be gained if f is evaluated at point p. Choose points where it is estimated that f takes value L, but where uncertainty is high. Evaluate f at the chosen points. This will augment the set of data points and the vector of data values. Repeat the procedure with this augmented data. Calculate convergence criteria after each iteration, and stop when criteria reach predetermined goals. The search process is applied to several functions defined in low dimensional space. Finally, it is applied to an actual simulation function
Explaining Utah's gender gap in wages by Curtis M Miller( )

1 edition published in 2015 in English and held by 1 WorldCat member library worldwide

Search for level sets of functions using computer experiments by Curtis M Miller( )

1 edition published in 2005 in English and held by 1 WorldCat member library worldwide

In engineering and other fields, it is common to use a computer simulation to model a real world process. The inputs to a function f represent factors that influence the outcome. The output represents a quantity of interest. Often there will be a specified level L, and the objective is to find the inputs for which output is above L. L may be a tolerance level, and the inputs for which response is larger than L form a tolerance region. We might estimate the tolerance region by evaluating f on a grid, but even a coarse grid may have thousands of points in four or five dimensions. If the function f is costly to evaluate, we need to be able to estimate the tolerance region with as few evaluations as possible. We approach this problem with a sequential search. Use data at any stage to fit a spatial process that approximates the function. Fit a Gaussian spatial process, as described in Currin, Mitchell, Morris, and Ylvisaker [1991]. The spatial process gives an estimate of the L-contour. We can also use the process to estimate how much information would be gained if f is evaluated at point p. Choose points where it is estimated that f takes value L, but where uncertainty is high. Evaluate f at the chosen points. This will augment the set of data points and the vector of data values. Repeat the procedure with this augmented data. Calculate convergence criteria after each iteration, and stop when criteria reach predetermined goals.;The search process is applied to several functions defined in low dimensional space. Finally, it is applied to an actual simulation function
A look at European shared service centers by Curtis M Miller( )

1 edition published in 1999 in English and held by 1 WorldCat member library worldwide

An Analysis of Washington State Policy for School Administrator Evaluation by Certified Subordinates by Curtis M Miller( Book )

1 edition published in 1988 in English and held by 1 WorldCat member library worldwide

Washington State has implemented a policy requiring school administrators to give their subordinates the opportunity to appraise their performance. Based on survey research and mailed interviews, this study collected data on activities at the state level that served to implement this policy. Other research questions sought information on the extent and impact of local school district policies and practices that were consistent with the state policy. Results of the study indicate that: (1) none of the officials interviewed cited any activities at the state level that promoted implementation of the evaluation policy; (2) only 7% of the local school districts had adopted policies on appraisal by subordinates that included the requirements of the state policy; (3) only 22 to 29% of the school administrators were found to have complied with the requirements of the state policy by giving their subordinates the opportunity to appraise their performance; (4) school personnel in a position to evaluate the effects of the policy, when implemented, reported that it was beneficial for assessing administrator performance; and (5) elements of the strategy described in state policy do not insure changes in administrative behavior nor do they protect subordinates against reprisals by administrators. (Author/TJH)
White Cemetery burial list by Ind.) White Cemetery (Franklin County( )

in English and held by 1 WorldCat member library worldwide

College Corner Cemetery collection by Ind.) College Corner Cemetery (West College Corner( )

in English and held by 1 WorldCat member library worldwide

Includes list of burials, list of veterans
Examining foundational approaches for introductory high school art courses by Curtis M Miller( )

1 edition published in 2015 in English and held by 1 WorldCat member library worldwide

Gray Cemetery collection by Ind.) Gray Cemetery (Franklin County( )

in English and held by 1 WorldCat member library worldwide

Includes photographic material, burial list, newspaper article from 2011. Information from tombstones
The impact of personality on team performance : final report by Robert Hogan( Book )

1 edition published in 1989 in English and held by 1 WorldCat member library worldwide

This project tested some hypotheses regarding the influence of team member personality on team performance across a variety of team tasks. We first developed and tested a 7 factor system for classifying team tasks and developed prototypical tasks for the research. We then conducted composed team experiments with 48 three-man teams. The results strongly support three conclusions: (1) Personality characteristics of team members predict team performance; (2) Personality characteristics interact with team task type; so that (3) Different characteristics are necessary for different team tasks
 
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Nineteenth century freedom fighters : the 1st South Carolina Volunteers
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English (18)

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