2,407 research outputs found

    BENEFITS OF MARKET VALUE CALCULATIONS FOR CREDIT UNIONS

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    This research paper focuses on two different interest rate risk measures used by credit unions in Canada, described by regulatory standards as complementary and indispensable. These two measures pertain either sensitivity of market value or net interest income, caused by changes in interest rates. Whereas credit unions can relate to and understand the latter perspective, market value does not seem as relevant as credit unions hold assets and liabilities until maturity and are not exposed to changes in market value. We use data from three credit unions to explain the two measures and show that one can be expressed by the other, which in fact discredits the perceived complementary nature of both measures. Additionally, we further develop the concept of net interest income sensitivity to overcome the weaknesses of market value by employing a more realistic measurement of interest rate risk and a reduction of required capital which eventually would enable credit unions to operate more profitably

    The Knowledge Graph for End-to-End Learning on Heterogeneous Knowledge

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    In modern machine learning,raw data is the preferred input for our models. Where a decade ago data scientists were still engineering features, manually picking out the details we thought salient, they now prefer the data in their raw form. As long as we can assume that all relevant and irrelevant information is present in the input data, we can design deep models that build up intermediate representations to sift out relevant features. However, these models are often domain specific and tailored to the task at hand, and therefore unsuited for learning on heterogeneous knowledge: information of different types and from different domains. If we can develop methods that operate on this form of knowledge, we can dispense with a great deal more ad-hoc feature engineering and train deep models end-to-end in many more domains. To accomplish this, we first need a data model capable of expressing heterogeneous knowledge naturally in various domains, in as usable a form as possible, and satisfying as many use cases as possible. We argue that the knowledge graph is a suitable candidate for this data model. We further discuss some of the promises and challenges of this approach, and how we are currently broadening our efforts to multi-modal knowledge graphs

    Post-Harvest Management of Immature Corn and Soybeans

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    In years when the growing season is shortened by late planting and/or early frost, some com and soybean seeds are still immature when the plant is killed by frost. Immature crops generally have high moisture at harvest and contain high concentrations of broken seeds (fines) and foreign material. In addition, immature com usually has low test weight and immature soybeans often contain green-colored seeds. This article will cover drying and storage management of these low quality, immature crops

    An external index of egg quality

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    Poultrymen Have Milk Problem

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    Many poultrymen and feed manufacturers are facing the question of high priced milk products and sometimes an actual impossibility of getting dried milk to use in their mash mixtures. Often substitutions must be made

    Natural-air corn drying with stirring

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    The first stage of this investigation involved two years of field tests in three 5.5-m diameter drying bins, two of which were equipped with single-auger grain stirrers. The first year, 24% moisture (wet basis) corn was dried using 3.7- to 5.2-kW fans. One bin was unstirred and another was stirred 48 h per week. The third bin was stirred at bin filling, when average moisture reached 20%, and again when average moisture fell below 15.5%. Both stirred bins used less energy and had less overdrying than the unstirred bin, with least energy use in the bin stirred three times;In the second field test, 20% moisture corn was dried. One bin was unstirred and the other two were stirred at the beginning and end of drying. The 3.7- to 5.2-kW fan on one stirred bin was replaced with a 2.2-kW model. Again, the stirred bins used less energy and had less overdrying. The stirred bin with the small fan used the least Oil, Gas, and Energy;The initial stirring was found to decrease bulk density and airflow resistance and greatly increase airflow. Subsequent stirring had unpredictable effects on bulk density and generally increased airflow resistance. Stirring shifted fines toward the drying floors and produced a small quantity of fines;In the second stage of the investigation, field test results were used to modify and calibrate a computer model to simulate natural-air stir drying. It was found that airflow had to be reduced to 74% of the input value and only 57.5% of the input electrical power could be used to calculate air temperature rise or the model would overpredict drying. Simulated natural-air drying of 20 and 24% moisture corn harvested mid-October in central Iowa showed that stirring reduced required fan size, electric-energy use, and overdrying;In the final stage, an economic analysis was conducted using corn physical properties from the field studies, average energy use and overdrying from the simulations, and local equipment and operating costs. The analysis showed that stirring increased net revenues for natural-air drying of 24% moisture corn and did for 20% moisture corn when electricity prices were high

    Egg Shells Good Poultry Feed

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    Iowa poultry produce plants break out about 12 million dozen eggs a year. That leaves a lot of egg shells to be disposed of in some way. If these could be sold at a fair price, then egg buyers could afford to pay farmers a bit more for eggs. In the past, the shells have been a total loss to the egg breaker, and, consequently, to the farm producer of eggs
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