SUPPLYING MOISTURE IN CONNECTION WITH ARTIFICIAL HEATING
نویسندگان
چکیده
منابع مشابه
Supplying legacy applications with QoS
∗ This work was performed in the framework of IST Project AQUILA (Adaptive Re-source Control of QoS Using an IP-based Layered Architecture IST1999-10077) funded in part by the EU. The author wish to express her gratitude to the other members of the AQUILA Consortium for valuable discussions. Abstract: In this article we consider end-to-end interdomain Quality of Service support for non QoS-awar...
متن کاملArtificial Reefs: the Florida Sea Grant Connection
Artificial reefs in Florida have been especially popular since the 1970s. With the advent of State Legislative funding in the 1990s, numerous local government and private interests have been able to develop reefs. The principal purpose is to enhance recreational fishing opportunities. But there are an increasing number of reefs being built as scuba diving sites and also to repair or mitigate da...
متن کاملUse of Soil Moisture Variability in Artificial Neural Network Retrieval of Soil Moisture
Passive microwave remote sensing is one of the most promising techniques for soil moisture retrieval. However, the inversion of soil moisture from brightness temperature observations is not straightforward, as it is influenced by numerous factors such as surface roughness, vegetation cover, and soil texture. Moreover, the relationship between brightness temperature, soil moisture and the factor...
متن کاملA major decomposition product, citrinin H2, from citrinin on heating with moisture.
Citrinin is one of the mycotoxins produced by Penicillium citrinum. We examined the decomposition products after heating citrinin in water at 140 degrees C and isolated a major product, citrinin H2 (3-(3,5-dihydroxy-2-methylphenyl)-2-formyloxy-butane). Citrinin H2 did not show significant cytotoxicity to HeLa cells up to a concentration of 200 microg/ml (% cytotoxicity: 39%) in 63 h of incubati...
متن کاملSparse connection and pruning in large dynamic artificial neural networks
This paper presents new methods for training large neural networks for phoneme probability estimation. A combination of the time-delay architecture and the recurrent network architecture is used to capture the important dynamic information of the speech signal. Motivated by the fact that the number of connections in fully connected recurrent networks grows super-linear with the number of hidden...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Monthly Weather Review
سال: 1905
ISSN: 0027-0644,1520-0493
DOI: 10.1175/1520-0493(1905)33<208:smicwa>2.0.co;2