The Experts below are selected from a list of 282 Experts worldwide ranked by ideXlab platform
Theologos Panagiotidis - One of the best experts on this subject based on the ideXlab platform.
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Artificial Neural Network for Daily Low Stream Flow Rate Prediction of Perigiali Stream, Kavala City, NE Greece
Proceedings, 2018Co-Authors: Thomas Papalaskaris, Theologos PanagiotidisAbstract:Only a few scientific research studies with reference to extremely low Stream Flow conditions, have been conducted in Greece, so far. Forecasting future low Stream Flow Rate values is a crucial and desicive task when conducting drought and watershed management plans, designing water reservoirs and general hydraulic works capacity, calculating hydrological and drought low Flow indices, separating groundwater base Flow and storm Flow of storm hydrographs etc. Artificial Neural Network modeling simulation method geneRates artificial time series of simulated values of a random (hydrological in this specific case) variable. The present study produces artificial low Stream Flow time series of both a part of the past year (2016) as well as the present year (2017) considering the Stream Flow data observed during two different respecting interval period of the years 2016 and 2017. We compiled an Artificial Neural Network to simulate low Stream Flow Rate data, acquired at a certain location of the partly regulated semi-urban Stream which runs through the eastern exit of Kavala city, NE Greece, using a 3-inches U.S.G.S. modified portable Parshall flume, a 3-inches conventional portable Parshall flume, a 3-inches portable Montana (short Parshall) flume and a 90° V-notched triangular shaped sharp crested portable weir plate. The observed data were plotted against the predicted one and the results were demonstRated through interactive tables providing us the ability to effectively evaluate the ANN model simulation procedure performance. Finally, we plot the recorded against the simulated low Stream Flow Rate data, compiling a log-log scale chart which provides a better visualization of the discrepancy ratio statistical performance metrics and calculate the derived model statistics featuring the comparison between the recorded and the forecasted low Stream Flow Rate data.
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Forecasting Low Stream Flow Rate Using Monte—Carlo Simulation of Perigiali Stream, Kavala City, NE Greece
Proceedings, 2018Co-Authors: Thomas Papalaskaris, Theologos PanagiotidisAbstract:A small number of scientific research studies with reference to extremely low Flow conditions, have been conducted in Greece, so far. Predicting future low Stream Flow Rate values is an essential and of paramount importance task when compiling watershed and drought management plans, designing water reservoirs and general hydraulic works capacity, calculating hydrological and drought low Flow values, separating groundwater base Flow and storm Flow of storm hydrographs etc. The Monte-Carlo simulation method geneRates multiple attempts to define the anticipated value of a random (hydrological in this specific case) variable. The present study compiles, correspondingly, artificial low Stream Flow time series of both the same part of the year (2016) as well as a part of the calendar year (2017), based on the Stream Flow data observed during the same two different interval periods of the years 2016 and 2017, using a 3-inches U.S.G.S. modified portable Parshall flume, a 3-inches conventional portable Parshall flume, a 3-inches portable Montana (short Parshall) flume and a 90° V-notched triangular shaped sharp crested portable weir plate. The recorded data were plotted against the fitted one and the results were demonstRated through interactive tables providing us the ability to effectively evaluate the simulation procedure performance. Finally, we plot the observed against the calculated low Stream Flow Rate data, compiling a log-log scale chart which provides a better visualization of the discrepancy ratio statistical performance metric and calculate statistics featuring the comparison between the recorded and the forecasted low Stream Flow Rate data.
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forecasting low Stream Flow Rate using monte carlo simulation of perigiali Stream kavala city ne greece
2018Co-Authors: Thomas Papalaskaris, Theologos PanagiotidisAbstract:A small number of scientific research studies with reference to extremely low Flow conditions, have been conducted in Greece, so far. Predicting future low Stream Flow Rate values is an essential and of paramount importance task when compiling watershed and drought management plans, designing water reservoirs and general hydraulic works capacity, calculating hydrological and drought low Flow values, separating groundwater base Flow and storm Flow of storm hydrographs etc. The Monte-Carlo simulation method geneRates multiple attempts to define the anticipated value of a random (hydrological in this specific case) variable. The present study compiles, correspondingly, artificial low Stream Flow time series of both the same part of the year (2016) as well as a part of the calendar year (2017), based on the Stream Flow data observed during the same two different interval periods of the years 2016 and 2017, using a 3-inches U.S.G.S. modified portable Parshall flume, a 3-inches conventional portable Parshall flume, a 3-inches portable Montana (short Parshall) flume and a 90° V-notched triangular shaped sharp crested portable weir plate. The recorded data were plotted against the fitted one and the results were demonstRated through interactive tables providing us the ability to effectively evaluate the simulation procedure performance. Finally, we plot the observed against the calculated low Stream Flow Rate data, compiling a log-log scale chart which provides a better visualization of the discrepancy ratio statistical performance metric and calculate statistics featuring the comparison between the recorded and the forecasted low Stream Flow Rate data.
Thomas Papalaskaris - One of the best experts on this subject based on the ideXlab platform.
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Artificial Neural Network for Daily Low Stream Flow Rate Prediction of Iokastis Stream, Kavala City, NE Greece, NE Mediterranean Basin
Environmental Sciences Proceedings, 2020Co-Authors: Thomas PapalaskarisAbstract:Only a few scientific research studies referencing extremely low Flow conditions have been conducted in Greece so far. Forecasting future low Stream Flow Rate values is a crucial and decisive task when conducting drought and watershed management plans by designing construction plans dealing with water reservoirs and general hydraulic works capacity, by calculating hydrological and drought low Flow indices, and by separating groundwater base Flow and storm Flow of storm hydrographs, etc. The Artificial Neural Network modeling simulation method geneRates artificial time series of simulated values of a random (hydrological in this specific case) variable. The present study produces artificial low Stream Flow time series of part of 2015. We compiled an Artificial Neural Network to simulate low Stream Flow Rate data, acquired at a certain location of the entirely regulated, urban Stream, which crosses the roads junction formed by Iokastis road and an Chrisostomou Smirnis road, Agios Loukas residential area, Kavala city, Eastern Macedonia & Thrace Prefecture, NE Greece, during part of July, August, and part of September 2015, until 12 September 2015, using a 3-inches conventional portable Parshall flume. The observed data were plotted against the predicted one and the results were demonstRated through interactive tables by providing us the ability to effectively evaluate the ANN model simulation procedure performance. Finally, we plotted the recorded against the simulated low Stream Flow Rate data by compiling a log-log scale chart, which provides a better visualization of the discrepancy ratio statistical performance metrics and calculated further statistic values featuring the comparison between the recorded and the forecasted low Stream Flow Rate data.
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Artificial Neural Network for Daily Low Stream Flow Rate Prediction of Perigiali Stream, Kavala City, NE Greece
Proceedings, 2018Co-Authors: Thomas Papalaskaris, Theologos PanagiotidisAbstract:Only a few scientific research studies with reference to extremely low Stream Flow conditions, have been conducted in Greece, so far. Forecasting future low Stream Flow Rate values is a crucial and desicive task when conducting drought and watershed management plans, designing water reservoirs and general hydraulic works capacity, calculating hydrological and drought low Flow indices, separating groundwater base Flow and storm Flow of storm hydrographs etc. Artificial Neural Network modeling simulation method geneRates artificial time series of simulated values of a random (hydrological in this specific case) variable. The present study produces artificial low Stream Flow time series of both a part of the past year (2016) as well as the present year (2017) considering the Stream Flow data observed during two different respecting interval period of the years 2016 and 2017. We compiled an Artificial Neural Network to simulate low Stream Flow Rate data, acquired at a certain location of the partly regulated semi-urban Stream which runs through the eastern exit of Kavala city, NE Greece, using a 3-inches U.S.G.S. modified portable Parshall flume, a 3-inches conventional portable Parshall flume, a 3-inches portable Montana (short Parshall) flume and a 90° V-notched triangular shaped sharp crested portable weir plate. The observed data were plotted against the predicted one and the results were demonstRated through interactive tables providing us the ability to effectively evaluate the ANN model simulation procedure performance. Finally, we plot the recorded against the simulated low Stream Flow Rate data, compiling a log-log scale chart which provides a better visualization of the discrepancy ratio statistical performance metrics and calculate the derived model statistics featuring the comparison between the recorded and the forecasted low Stream Flow Rate data.
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Forecasting Low Stream Flow Rate Using Monte—Carlo Simulation of Perigiali Stream, Kavala City, NE Greece
Proceedings, 2018Co-Authors: Thomas Papalaskaris, Theologos PanagiotidisAbstract:A small number of scientific research studies with reference to extremely low Flow conditions, have been conducted in Greece, so far. Predicting future low Stream Flow Rate values is an essential and of paramount importance task when compiling watershed and drought management plans, designing water reservoirs and general hydraulic works capacity, calculating hydrological and drought low Flow values, separating groundwater base Flow and storm Flow of storm hydrographs etc. The Monte-Carlo simulation method geneRates multiple attempts to define the anticipated value of a random (hydrological in this specific case) variable. The present study compiles, correspondingly, artificial low Stream Flow time series of both the same part of the year (2016) as well as a part of the calendar year (2017), based on the Stream Flow data observed during the same two different interval periods of the years 2016 and 2017, using a 3-inches U.S.G.S. modified portable Parshall flume, a 3-inches conventional portable Parshall flume, a 3-inches portable Montana (short Parshall) flume and a 90° V-notched triangular shaped sharp crested portable weir plate. The recorded data were plotted against the fitted one and the results were demonstRated through interactive tables providing us the ability to effectively evaluate the simulation procedure performance. Finally, we plot the observed against the calculated low Stream Flow Rate data, compiling a log-log scale chart which provides a better visualization of the discrepancy ratio statistical performance metric and calculate statistics featuring the comparison between the recorded and the forecasted low Stream Flow Rate data.
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forecasting low Stream Flow Rate using monte carlo simulation of perigiali Stream kavala city ne greece
2018Co-Authors: Thomas Papalaskaris, Theologos PanagiotidisAbstract:A small number of scientific research studies with reference to extremely low Flow conditions, have been conducted in Greece, so far. Predicting future low Stream Flow Rate values is an essential and of paramount importance task when compiling watershed and drought management plans, designing water reservoirs and general hydraulic works capacity, calculating hydrological and drought low Flow values, separating groundwater base Flow and storm Flow of storm hydrographs etc. The Monte-Carlo simulation method geneRates multiple attempts to define the anticipated value of a random (hydrological in this specific case) variable. The present study compiles, correspondingly, artificial low Stream Flow time series of both the same part of the year (2016) as well as a part of the calendar year (2017), based on the Stream Flow data observed during the same two different interval periods of the years 2016 and 2017, using a 3-inches U.S.G.S. modified portable Parshall flume, a 3-inches conventional portable Parshall flume, a 3-inches portable Montana (short Parshall) flume and a 90° V-notched triangular shaped sharp crested portable weir plate. The recorded data were plotted against the fitted one and the results were demonstRated through interactive tables providing us the ability to effectively evaluate the simulation procedure performance. Finally, we plot the observed against the calculated low Stream Flow Rate data, compiling a log-log scale chart which provides a better visualization of the discrepancy ratio statistical performance metric and calculate statistics featuring the comparison between the recorded and the forecasted low Stream Flow Rate data.
William L Luyben - One of the best experts on this subject based on the ideXlab platform.
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temperature control of the btx divided wall column
Industrial & Engineering Chemistry Research, 2010Co-Authors: Hao Ling, William L LuybenAbstract:The control of a divided-wall column is more difficult than the control of a conventional two-column separation sequence for the separation of ternary mixtures because there is more interaction among control loops. In a previous paper, a control structure using four composition loops was shown to provide effective control of the purities of the three product Streams and also achieve minimum energy consumption for both feed Flow Rate and feed composition disturbances. The numerical example studied the separation of benzene, toluene, and o-xylene. The four manipulated variables were reflux Flow Rate (R), side-Stream Flow Rate (S), reboiler heat input (QR), and liquid split (βL) at the top of the wall. In this paper we explore the use of temperatures to avoid expensive and high-maintenance composition analyzers. Two types of temperature control structures are studied. In the first, three temperatures located in the main column and one temperature on the prefractionator side of the wall are used to adjust the...
Mark A. Arnold - One of the best experts on this subject based on the ideXlab platform.
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Selective measurement of chromium(VI) by fluorescence quenching of ruthenium.
Talanta, 1999Co-Authors: Taha M. A. Razek, Scott K. Spear, Saad S. M. Hassan, Mark A. ArnoldAbstract:A Flow injection method is described for the selective measurement of chromium(VI) in aqueous solutions. This method is based on the dynamic quenching of ruthenium(II) fluorescence. The detection limit is 0.43 ppm and 40 samples can be analyzed per hour. Selectivity is demonstRated over ferrous, nickel, cupric and zinc cations and no effect is observed from sulfate, chloride, boRate and phosphate. Some interference quenching was measured for cyanide and nitRate, but the method is more responsive to chromium(VI) by factors of 10.2 and 82, respectively. The effects of solution pH, carrier Stream Flow Rate and ruthenium concentration are demonstRated. Results indicate the method is suitable for measuring chromium(VI) in effluents from electroplating baths.
Wirat Ruengsitagoon - One of the best experts on this subject based on the ideXlab platform.
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Flow injection spectrophotometric determination of lead using 1,5-diphenylthiocarbazone in aqueous micellar.
Talanta, 2010Co-Authors: Wirat Ruengsitagoon, Alberto Chisvert, Saisunee LiawruangrathAbstract:A simple Flow injection colorimetric procedure for determining lead was established. It is based on the reaction of lead in sulfuric acid with 1,5-diphenylthiocarbazone and sodium dodecyl sulfate, resulting in an intense red-blue complex with a suitable absorption at 500 nm. A standard or sample solution was injected into the sulfuric acid Stream (Flow Rate of 2.0 ml min(-1)), which was then merged with sodium dodecyl sulfate Stream (Flow Rate of 2.0 ml min(-1)) and 1,5-diphenylthiocarbazone Stream (Flow Rate of 1.5 ml min(-1)). Optimum conditions for determining lead were investigated by univariate method. Under the optimum conditions, a linear calibration graph was obtained over the range 1.0-12.0 microg ml(-1) and the detection limit was 0.027 microg ml(-1) (s/n=3). The relative standard deviation of the proposed method calculated from 12 replicate injections of 4.0 and 8.0 microg ml(-1) of lead was 0.42% and 0.38%, respectively. The sample throughput was 80 h(-1). The proposed method has been satisfactorily applied to the determination of lead in water samples.
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reverse Flow injection spectrophotometric determination of iron iii using chlortetracycline reagent
Talanta, 2008Co-Authors: Wirat RuengsitagoonAbstract:A simple reversed Flow injection colourimetric procedure for determining iron(III) was proposed. It is based on the reaction between iron(III) with chlortetracycline, resulting in an intense yellow complex with a suitable absorption at 435nm. A 200mul chlortetracycline reagent solution was injected into the phosphate buffer Stream (Flow Rate 2.0mlmin(-1)) which was then merged with iron(III) standard or sample in dilute nitric acid Stream (Flow Rate 1.5mlmin(-1)). Optimum conditions for determining iron(III) were investigated by univariate method. Under the optimum conditions, a linear calibration graph was obtained over the range 0.5-20.0mugml(-1). The detection limit (3sigma) and the quantification limit (10sigma) were 0.10 and 0.82mugml(-1), respectively. The relatives standard deviation of the proposed method calculated from 12 replicate injections of 2.0 and 10.0mugml(-1) iron(III) were 0.43 and 0.59%, respectively. The sample throughput was 60h(-1). The proposed method has been satisfactorily applied to the determination of iron(III) in natural waters.
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Flow injection chemiluminescence determination of paracetamol.
Talanta, 2006Co-Authors: Wirat Ruengsitagoon, Saisunee Liawruangrath, Alan TownshendAbstract:Abstract A simple chemiluminometric method using Flow injection has been developed for the determination of paracetamol (acetaminophen), based on the chemiluminescence produced by the reduction of tris(2,2′-bipyridyl)ruthenium(III). The latter is obtained by oxidation of tris(2,2′-bipyridyl)ruthenium(II) by potassium permanganate in dilute sulphuric acid in the presence of paracetamol. A standard or sample solution was injected into the ruthenium(II) Stream (Flow Rate 1.5 ml min −1 ) which was then merged with potassium permanganate in dilute sulphuric acid Stream (Flow Rate 0.5 ml min −1 ). The chemiluminescence intensity is enhanced by the presence of manganese(II) ions. Under the optimum conditions, a linear calibration graph was obtained over the range of 0.3–50.0 μg ml −1 and the detection limit was 0.2 μg ml −1 (s/n = 3). The relative standard deviation of the proposed method calculated from 20 replicate injections of 5.0 μg ml −1 paracetamol was 1.1%. The sample throughput was 90 h −1 . The method was successfully applied to the determination of paracetamol in commercial pharmaceutical formulations.
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Flow injection spectrophotometric determination of andrographolide from Andrographis paniculata
Talanta, 2005Co-Authors: Wirat Ruengsitagoon, Kunnatee Anuntakarun, Chantana AromdeeAbstract:A simple Flow injection colourimetric procedure for determining andrographolide was proposed. It is based on the reaction between andrographolide with 3,5-dinitrobenzoic acid, resulting in an intense purplish red complex with a suitable absorption at 536nm. A standard or sample solution was injected into the 3,5-dinitrobenzoic acid Stream (Flow Rate of 1.0mlmin(-1)) which was then merged with potassium hydroxide Stream with the same Flow Rate. Optimum conditions for determining andrographolide were investigated by univariate method. Under the optimum conditions, a linear calibration graph was obtained over the range 5.0-150.0mugml(-1) and the detection limit was 1.50mugml(-1) (3sigma). The relatives standard deviation of the proposed method calculated from 10 replicate injections of 10.0 and 80.0mugml(-1) andrographolide were 0.66% and 1.64%, respectively. The sample throughput was 50h(-1). The proposed method has been satisfactorily applied to the determination of andrographolide in herb plant samples.
