DISCUSSION: POLICY CONSIDERATIONS OF EMERGING INFORMATION TECHNOLOGIES

Research and Development/Tech Change/Emerging Technologies,

THE IMPACT OF ADVERTISING ON THE EFFICIENCY OF THE FOOD DISTRIBUTION SYSTEM

Marketing,

Letter, 1941 February 27, from Joe Davis t Carosn Robison

1 page, Davis was the President of Georgia Music Corp. He was a publisher for Robison. Thurman Arnold, Assistant Attorney General, is meantioned in this letter

State and Local Tax Problems from the Labor Point of View

This is a short presentation of what is believed to be the representative viewpoint of labor with respect to the inequities and inadequacies of the system as we now understand it. It is not intended to be an exhaustive examination of the taxing system now in use in the State of Washington

Exploiting Local Features from Deep Networks for Image Retrieval

Deep convolutional neural networks have been successfully applied to image classification tasks. When these same networks have been applied to image retrieval, the assumption has been made that the last layers would give the best performance, as they do in classification. We show that for instance-level image retrieval, lower layers often perform better than the last layers in convolutional neural networks. We present an approach for extracting convolutional features from different layers of the networks, and adopt VLAD encoding to encode features into a single vector for each image. We investigate the effect of different layers and scales of input images on the performance of convolutional features using the recent deep networks OxfordNet and GoogLeNet. Experiments demonstrate that intermediate layers or higher layers with finer scales produce better results for image retrieval, compared to the last layer. When using compressed 128-D VLAD descriptors, our method obtains state-of-the-art results and outperforms other VLAD and CNN based approaches on two out of three test datasets. Our work provides guidance for transferring deep networks trained on image classification to image retrieval tasks.Comment: CVPR DeepVision Workshop 201

An econometric analysis of the quarterly demand and supply relationships for feeder cattle in the United States

The overall objective of this study was to develop a price forecasting model which would give the producers of feeder cattle, feedlot operators, and other segments of the beef cattle industry more than just a hunch as to future feeder cattle price movements. The specific objectives were: (1) develop an econometric model to identify the major factors influencing the quarterly demand and supply of feeder cattle in the United States; (2) develop alternative quarterly feeder cattle price forecasting models using the econometric structural relationships estimated above; and (3) evaluate the interrelationships among the various markets in the beef cattle industry. An econometric model consisting of eight behavioral equations and two market clearing equations were developed to describe the relationships within and among the feeder cattle, slaughter cattle, and retail sectors of the beef industry. The behavioral equations were fitted to quarterly data for the years 1960-1972 using the two-stage least squares technique. The farm level demand for feeder cattle was normalized on the current price of feeder cattle. The major factors hypothesized to affect the price of feeder cattle were the current quantity of feeder cattle, the price of com, the number of head on feed, the current price of slaughter cattle, the short-term interest rate, and quarters of the year. The farm level supply function was normalized on the current quantity of feeder cattle. The major factors hypothesized to affect the quantity of feeder cattle supplied were the current price of feeder cattle, calf crop lagged two quarters, the price of feeder cattle lagged four quarters, a time variable, and quarters of the year. The demand relationship for slaughter cattle was normalized on the current price of slaughter cattle and the supply relationship was normalized on the current quantity of slaughter cattle. The major factors hypothesized to affect the price of slaughter cattle were the quantity of slaughter cattle, the retail price of beef, cow slaughter, cold storage holdings of beef, wage rate in the meatpacking industry, and quarters of the year. The major factors hypothesized to affect the quantity of slaughter cattle supplied were the current price of slaughter cattle, price of feeder cattle lagged two quarters, the price of corn lagged two quarters, a time variable, and quarters of the year. A marketing margin was used to connect the prices at the farm level to the prices at the retail level. The factors affecting the farm to retail marketing margin for beef were hypothesized to be the quantity of slaughter cattle moving through the market, the wage rate in the meatpacking industry, the price of slaughter cattle, and time. Retail level demand equations for beef, pork, and chicken were developed. The major factors affecting the demand for these three substitute meats were their respective prices and quantities, income, and quarters of the year. The results indicated that the price and quantity of feeder cattle were simultaneously determined. The major factors affecting the price of feeder cattle were the quantity of feeder cattle and the price of slaughter cattle. The demand relationship was found to be significantly higher in the fall quarter. The major factors affecting the quantity of feeder cattle supplied were the price of feeder cattle and the time variable. The results indicated that the major factors affecting the price of slaughter cattle were the retail price of beef and cow slaughter while the major factors affecting supply were the price of slaughter cattle, the price of feeder cattle lagged two quarters, and time. Alternative forecasting models were developed to predict the price and quantity of feeder cattle. The most promising model that could be used to predict feeder cattle prices and quantities was a model which included all independent variables in the first stage of the TSLS technique. However, data for variables measured in time period t would not be available at the time the prediction is needed. Therefore, a model using all independent variables in the first stage with all variables measured in time period t lagged two quarters was used to predict the price and quantity of feeder cattle for the five quarters following the sample period. The predictions were evaluated on the basis of the direction of change and how closely the predicted values approximate the actual value. The model correctly predicted two out of five directions for price and three out of five direction of change for quantity. The largest deviation between the actual price and the predicted price of feeder cattle using this model was $12.05 which occurred in the summer quarter of 1973

MBTI Personality Types and Preferred Relationship Disengagement Strategies in Intimate Situations

This thesis poses two research questions that focus on MBTI personality types and specific strategies used to disengage romantic intimate heterosexual relationships. 1) Would one specific MBTI personality type prefer to use one dominate strategy to disengage a relationship? 2) Would any relationship situation yield one dominate strategy to disengage a relationship? A total of 116 college students were surveyed at a small Midwestern university. Age ranged from 18 years to 55 years with a mean age of 23.6 years. The experimental method consisted of administering Form G of the MBTI and an additional questionnaire measuring relationship strategies. The t-test for simple effects found significance between MBTI types and strategy selected to dissolve relationships at the (.05) level. Significant results were also found for type of situation and strategy selection at the (.05) level. The conclusions of this study found that certain MBTI personality types prefer to disengage relationships by using specific types of strategies. Situations were also found to be significant

Most massive halos with Gumbel Statistics

We present an analytical calculation of the extreme value statistics for dark matter halos - that is, the probability distribution of the most massive halo within some region of the universe of specified shape and size. Our calculation makes use of the counts-in-cells formalism for the correlation functions, and the halo bias derived from the Sheth-Tormen mass function. We demonstrate the power of the method on spherical regions, comparing the results to measurements in a large cosmological dark matter simulation and achieving good agreement. Particularly good fits are obtained for the most likely value of the maximum mass and for the high-mass tail of the distribution, relevant in constraining cosmologies by observations of most massive clusters.Comment: Accepted to MNRA

EFFICIENT CASH AND HEDGED ENTERPRISE COMBINATIONS IN FEEDER CALF BACKGROUNDING OPERATIONS

Livestock Production/Industries,