IMPORT DEMANDS FOR U.S. FRESH GRAPEFRUIT: EFFECT OF U.S. PROMOTION PROGRAMS AND TRADE POLICIES OF IMPORTING NATIONS

This study estimates import demands for U.S. fresh grapefruit in Japan, France, Canada, and the Netherlands. Historically, these nations have imported about 90 percent of U.S. grapefruit exports. Four import demand functions were specified and estimated by joint generalized least squares based on the sample period 1969I to 1988IV. Results show that U.S. FOB price, per capita income of importing countries, exchange rates, price of substitutes, U.S. grapefruit promotion programs, and removal of trade restrictions have had an important effect on U.S. fresh grapefruit exports. Analyses suggest that U.S. producers can effectively promote fresh grapefruit in foreign markets, and that trade concessions have an important influence on grapefruit exports.International Relations/Trade,

Letter to Simon Greenleaf

Mr. Fuller writes to Simon Greenleaf to inform him that the Ohio question is at length settled and that he will travel to Gambier soon. His wife then takes over and writes the second half of the letter, informing her father that the flu is going around the family.https://digital.kenyon.edu/chase_letters/2179/thumbnail.jp

FACTORS AFFECTING FRESH POTATO PRICE IN SELECTED TERMINAL MARKETS

Monthly, quarterly, and annual cross-sectional and time-series data for the period 1982-85 were analyzed to identify factors affecting terminal market price for four types of fresh potatoes. Results indicated that state of origin, terminal market package type, and season of marketing were significant quality variables affecting price. Price differences among potato types because of season of marketing and stocks of fall potatoes were evident. These results suggest that cultivar selection, cultural practices, planting and harvesting schedules, packaging, and market selection – factors which are ultimately controlled by growers and grower/shippers – can be utilized effectively as mechanisms to increase price and expand markets.Crop Production/Industries, Demand and Price Analysis,

The Kumon Approach to Learning Mathematics: An Educator\u27s Perspective

Largely unnoticed amid the cry for better mathematics teaching, Kumon is quietly helping a million mathematics students (from infants to adults; 75% are elementary children). Though conservative in diction and device (including 5000+ worksheets to be solved in standard times), it is surprisingly student-centered in practice. The author\u27s investigation during the past year reflects his background in both education and computer science. The paper considers the demands, theories, methods and record of Kumon mathematics from the standpoint of educational theory, cognitive science, and language processing. It considers syntactic and semantic learning of mathematics, arguing that their proper relative positioning helps lead the student to higher-order thinking. Future research issues are suggested. The Kumon Machine is briefly introduced; it incorporates the Kuman method into silicon paper -- a notebook sized pen-based computer

Energy-related Feature Abstraction for Handwritten Digit Recognition

Most handwritten character recognizers use either graphical (static) or first-order dynamic data. Our research speculates that the mental signal to write a digit might be partially encoded as an energy profile. We used artificial neural networks (ANN) to analyze energy-related features (first and second time derivatives) of handwritten digits of 20 subjects and later 40 subjects. An experimenal environment was developed on a NeXTstation with a real-time link to a pen-based GO computer. Although such an experiment cannot confirm an energy profile encoded in the writer, it did indicate the usefulness of energy-related features by recognizing 94.5% of the 600 test patterns after 29,000 random presentations of 800 training digits. This three-layer ANN had 54 input units (representing 29 trinary features), 4 hidden units (0, 2, 3, 4, 8, 10, 12, 15, 20, and 25 hidden units were tested), and 14 output units. Another ANN recognized 91.7% of the test digits after only 6,000 training presentations. Later testing with 40 subjects (including very erratic writing) resulted in 91% recognition. This same feature abstraction was tested in a Supervised Competitive learning (SCL) implementation which was free to create as many or few digit prototypes as was needed to recognize characters. Using the former data set (20 subjects), it created from 19 to 34 prototypes (depending on control parameters) and achieved 94.8% recognition