The Experts below are selected from a list of 150 Experts worldwide ranked by ideXlab platform
S. Motheramgari - One of the best experts on this subject based on the ideXlab platform.
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ICDE - Developing cost models with Qualitative Variables for dynamic multidatabase environments
Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073), 1Co-Authors: Qiang Zhu, Yu Sun, S. MotheramgariAbstract:A major challenge for global query optimization in a multidatabase system (MDBS) is the lack of local cost information at the global level due to local autonomy. A number of methods to derive local cost models have been suggested recently. However, these methods are only suitable for a static multidatabase environment. In this paper, we propose a new multi-state query sampling method to develop local cost models for a dynamic environment. The system contention level at a dynamic local site is divided into a number of discrete contention states based on the cost of a probing query. To determine an appropriate set of contention states for a dynamic environment, two algorithms based on iterative uniform partitioning and data clustering, respectively, are introduced. A Qualitative Variable is used to indicate the contention states for the dynamic environment. The techniques from our previous (static) query sampling method, including query sampling, automatic Variable selection, regression analysis and model validation, are extended so as to develop a cost model incorporating the Qualitative Variable for a dynamic environment. Experimental results demonstrate that this new multi-state query sampling method is quite promising in developing useful cost models for a dynamic multidatabase environment.
Nina Cedergreen - One of the best experts on this subject based on the ideXlab platform.
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glyphosate spray drift in coffea arabica sensitivity of coffee plants and possible use of shikimic acid as a biomarker for glyphosate exposure
Pesticide Biochemistry and Physiology, 2014Co-Authors: Lars C Schrubbers, Bernal E Valverde, Jens Christian Sorensen, Nina CedergreenAbstract:Glyphosate is widely used in coffee plantations to control weeds. Lacking selectivity, glyphosate spray drift is suspected to cause adverse effects in coffee plants. Symptoms caused by glyphosate can be similar to those produced by other stress factors. However, shikimic acid accumulation should be a useful bio- marker for glyphosate exposure as shown for other crops. The aim of this study was to assess the sensi- tivity of coffee plants towards glyphosate on different biological response Variables and to evaluate the use of shikimic acid as biomarker. Dose-response experiments yielded ED50 values (50% effect dose) in the range of 38-550 g a.e. ha � 1 depending on the quantitative or Qualitative Variable monitored. The fre- quency of plants showing symptoms was the most sensitive Variable. The best sampling time for shikimic acid accumulation was 1-2 weeks after glyphosate application, depending on experimental conditions. The highest shikimic acid accumulation was observed in young leaves. Shikimic acid is a suitable biomarker for a glyphosate exposure in coffee, using only young leaves for the analysis. Young coffee plants are susceptible to glyphosate damage. If symptoms are absent the risk of severe crop damage or yield loss is low.
Jafar Towfighi Darian - One of the best experts on this subject based on the ideXlab platform.
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On the Introduction of a Qualitative Variable to the Neural Network for Reactor Modeling: Feed Type
Industrial & Engineering Chemistry Research, 2009Co-Authors: Maryam Ghadrdan, Hamid Mehdizadeh, Ramin Bozorgmehry Boozarjomehry, Jafar Towfighi DarianAbstract:Thermal cracking of hydrocarbons converts them into valuable materials in the petrochemical industries. Multiplicity of the reaction routes and complexity of the mathematical approach has led us use a kind of black-box modeling—artificial neural networks. Reactor feed type plays an essential role on the product qualities. Feed type is a Qualitative character. In this paper, a method is presented to introduce a range of petroleum fractions to the neural network. To introduce petroleum cuts with final boiling points of 865 °F maximum to the neural network, a real component substitute mixture is made from the original mixture. Such substitute mixture is fully defined, it has a chemical character, and physical properties can be simply retrieved from databases. The mixture compositions are defined with the aid of an optimization algorithm−interval method. The obtained TBP curves of substitute mixture are in good agreement with the experimentally obtained curves. Nine single carbon structural increments will be...
J Zhang - One of the best experts on this subject based on the ideXlab platform.
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economic motivations for limited dependent and Qualitative Variable models
Economic Record, 1993Co-Authors: Tim R L Fry, Robert Darren Brooks, Br Comley, J ZhangAbstract:The greater availability of survey data, a succession of papers dealing with the statistical issues arising from the analysis of such data and the appearance of software packages, such as UMDEP, have led to a remarkable increase in the application of limited dependent and Qualitative Variable models in economics. Economic analysis of the behaviour of individual decision makers often leads to models which are of a limited dependent or Qualitative Variable nature. This paper attempts to show how the use of these models naturally arises from the more general framework of modifications to traditional economic optimization problems.
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Economic Motivations for Limited Dependent and Qualitative Variable Models
Economic Record, 1993Co-Authors: Tim R L Fry, Robert Darren Brooks, Br Comley, J ZhangAbstract:The greater availability of survey data, a succession of papers dealing with the statistical issues arising from the analysis of such data, and the appearance of software packages such as LIMDEP have led to a remarkable increase in the application of limited dependent and Qualitative Variable models in economics. Economic analysis of the behavior of individual decisionmakers often leads to models that are of a limited dependent or Qualitative Variable nature. This paper attempts to show how the use of these models naturally arises from the more general framework of modifications to traditional economic optimization problems. Coauthors are R. D. Brooks, B. R. Comley, and J. Zhang. Copyright 1993 by The Economic Society of Australia.
Qiang Zhu - One of the best experts on this subject based on the ideXlab platform.
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ICDE - Developing cost models with Qualitative Variables for dynamic multidatabase environments
Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073), 1Co-Authors: Qiang Zhu, Yu Sun, S. MotheramgariAbstract:A major challenge for global query optimization in a multidatabase system (MDBS) is the lack of local cost information at the global level due to local autonomy. A number of methods to derive local cost models have been suggested recently. However, these methods are only suitable for a static multidatabase environment. In this paper, we propose a new multi-state query sampling method to develop local cost models for a dynamic environment. The system contention level at a dynamic local site is divided into a number of discrete contention states based on the cost of a probing query. To determine an appropriate set of contention states for a dynamic environment, two algorithms based on iterative uniform partitioning and data clustering, respectively, are introduced. A Qualitative Variable is used to indicate the contention states for the dynamic environment. The techniques from our previous (static) query sampling method, including query sampling, automatic Variable selection, regression analysis and model validation, are extended so as to develop a cost model incorporating the Qualitative Variable for a dynamic environment. Experimental results demonstrate that this new multi-state query sampling method is quite promising in developing useful cost models for a dynamic multidatabase environment.
