African Journal of Pharmacy and Pharmacology, 2018
It is well documented that caffeine is the world's most widely consumed drug with its main source... more It is well documented that caffeine is the world's most widely consumed drug with its main source found in coffee. In the Kingdom of Saudi Arabia (KSA), diabetes and obesity are major health problems. Caffeine is attested as a potential drug for treating obesity, hepatic fibrosis, and preventing or delaying diabetes. The aim of this work is to evaluate the caffeine content of the Arabian coffee in comparison to Turkish coffee and instant coffee, in order to better adjust daily caffeine consumption. All types of coffee were prepared based on traditional ways in KSA. The average consumed coffee per normal person is assumed to be, 6 Arabian, 2 Nescafe or 1 Turkish cups per day. High performance liquid chromatography technique was used for caffeine measurement using paracetamol as an internal standard. Generally, coffee is prepared with other additives, liquid-liquid extraction was used for the extraction caffeine and paracetamol as an internal standard. HPLC method validated was over the range of 1 to 100 μg with good linearity (r²=0.991). Validation data proved that the method is accurate with average of 102%. Caffeine contents of Arabian coffee, Nescafe®, and Turkish coffee were found to be 4.1, 43.4 and 82.8 mg/cup, respectively. One cup of Turkish coffee contains caffeine as much as 2 Nescafe® and 20 Arabian cups. Gold Nescafe® contains about 20% less caffeine than classic. The caffeine content of each type of marketed coffee was accurately measured. An individual Arabian coffee consumer, who is drinking an average of 6 cups/day, can safely increase the number of cups or cup size in order to obtain more caffeine. The other choice for increasing caffeine ingestion is to think of Turkish coffee and/or Nescafe® as a substitute, in order to maintain caffeine at a therapeutic range for better health.
Abstract In this paper we extend upon an existing software architecture, namely the Context Orien... more Abstract In this paper we extend upon an existing software architecture, namely the Context Oriented Architecture to include support for quality of service. The Context Oriented Architecture is a responsive service oriented infrastructure that transparently monitors application context and allows for custom responses designed by service developers and triggered by conditions in the monitored context. We augment the architecture with a QoS-Broker, which supports QoS representation, discovery, matchmaking, monitoring and self-healing based on Web service standards. Service providers can specify various categories of Web services that differ in their QoS support. Clients are able to dynamically state their QoS requirements. To support standardization, QoS requirements and offers are described using the OWL-Q ontology. Our QoS-Broker matches a group of customers with a group of service offers by converting the problem into a constraint satisfaction problem, and solving it using a matchmaking search algorithm. As a proof of concept, the QoS-Broker monitors the invocation process and takes corrective action if a Web service could not meet the QoS level it claims to support. We verified the feasibility and performance of the QoS-Broker with our prototype implementation and performance measurements. In addition, we showed that group serving has less overhead than individual serving and that our matching logic conforms to the wisdom of the crowd.
2007 16th International Conference on Computer Communications and Networks, 2007
ABSTRACT In this paper, a novel technique for location prediction of mobile users has been propos... more ABSTRACT In this paper, a novel technique for location prediction of mobile users has been proposed, and a paging technique based on it is developed. Mobile users are creatures of habits. They tend to repeat their behaviors. Hence, neural networks with its learning and generalization ability may act as a suitable tool to predict the location of a mobile user provided it is trained appropriately by the personal mobility profile. For prediction, a novel hybrid Bayesian neural network model for predicting locations on Cellular Networks (can also be extended to other wireless networks such as Wi-Fi and WiMAX) is suggested. We investigate its different parallel implementation techniques on mobile devices, and compare its performance to many standard neural network techniques such as: Back-propagation, Elman, Resilient, Levenberg-Marqudat, and One-Step Secant models. This approach is free from all unrealistic assumptions about the movement of the users. It is applicable to any arbitrary cell architecture. It attempts to reduce the total location management cost and paging delay. In general, it enhances mobility management in wireless networks (in location management and hand-off management). In our experiments, we compare results of the proposed Bayesian Neural Network with 5 standard neural network techniques in predicting next location. Bayesian learning for Neural Networks predicts location better than standard neural network techniques since it uses well founded probability model to represent uncertainty about the relationship being learned. The result of Bayesian training is a posterior distribution over network weights.
2007 Second International Conference on Systems and Networks Communications (ICSNC 2007), 2007
Nowadays, path prediction is being extensively examined for use in the context of mobile and wire... more Nowadays, path prediction is being extensively examined for use in the context of mobile and wireless computing towards more efficient network resource management schemes. Path prediction allows the network and services to further enhance the quality of service levels that the user enjoys. In this paper we present a path prediction algorithm that exploits human creatures habits. In this paper, we present a novel hybrid Bayesian neural network model for predicting locations on Cellular Networks (can also be extended to other wireless networks such as WI-FI and WiMAX). We investigate different parallel implementation techniques on mobile devices of the proposed approach and compare it to many standard neural network techniques such as: Back-propagation, Elman, Resilient, Levenberg-Marqudat, and One-Step Secant models. In our experiments, we compare results of the proposed Bayesian Neural Network with 5 standard neural network techniques in predicting both next location and next service to request. Bayesian learning for Neural Networks predicts both location and service better than standard neural network techniques since it uses well founded probability model to represent uncertainty about the relationships being learned. The result of Bayesian training is a posterior distribution over network weights. We use Markov chain Monte Carlo methods (MCMC) to sample N values from the posterior weights distribution. These N samples vote for the best prediction. Simulations of the algorithm, performed using a Realistic Mobility Patterns, show increased prediction accuracy.
ISCA International Conference on Parallel and Distributed Computing Systems, 2007
A gas-liquid contacting apparatus for removing sulfur dioxide from a flue gas is provided which c... more A gas-liquid contacting apparatus for removing sulfur dioxide from a flue gas is provided which comprises a vessel for receiving therein a liquid aqueous absorbent in a continuous phase; gas sparger means having an opening means at one end thereof, the gas sparger means extending vertically from above the surface of the aqueous absorbent liquid and through the surface such that the opening means is positioned below the surface wherein the opening means comprises notch means formed in the side walls of the gas sparger means and an open end of the gas sparger means; air sparger means in the aqueous absorbent, below the gas sparger means; outlet means for the gas after it contacts the aqueous absorbent, the outlet means being located above the level of the aqueous absorbent; reactant inlet means into the vessel; aqueous absorbent inlet means into the vessel; and outlet means for the reaction products and spent aqueous absorbent.
1993 International Conference on Parallel Processing - ICPP'93 Vol3, 1993
We describe three new Jacobi orderings for parallel computation of SVD problems on tree architect... more We describe three new Jacobi orderings for parallel computation of SVD problems on tree architectures. The rst ordering uses the high bandwidth of a perfect binary fat-tree to minimise global interprocessor communication costs. The second is a new ring ordering which m a y be implemented e ciently on an ordinary binary tree. By combining these two orderings, an e cient new ordering, well suited for implementation on the Connection Machine CM5, is obtained.
A method of and apparatus for moxibustion comprising feeding air to a heat generating compositon ... more A method of and apparatus for moxibustion comprising feeding air to a heat generating compositon in contact with a herb material comprising moxa, wherein said heat generating composition comprises a pyrogen and said herb material is located adjacent to a skin surface, wherein said feeding causes said pyrogen to generate heat by oxidation, whereby said herb material is heated and vaporized and the generated heat and vapor act on the skin, causing moxibustion effect.
HW/SW techniques make it possible for the system designers to validate their design, assign modul... more HW/SW techniques make it possible for the system designers to validate their design, assign modules to be implemented in either hardware or software in the early stages of the system design life cycle. In addition, those techniques provide powerful mechanism for continuous system validation until the final product is done. Partitioning the system into either hardware or software, in the system early stages, is vital decision that has to be done iteratively and accurately. Many techniques have been proposed for HW/SW partitioning: conventional circuit partitioning techniques, simulated annealing, expert systems, and even genetic algorithm techniques. The partitioning problem has been proved to be and NP-Hard problem, thus AI, ANN and GA techniques can find a rich playground to apply their techniques. This paper presents a novel approach to use Bayesian Belief Networks as the tool that does the partitioning decision when provided by simulation parameters that measure certain character...
African Journal of Pharmacy and Pharmacology, 2018
It is well documented that caffeine is the world's most widely consumed drug with its main source... more It is well documented that caffeine is the world's most widely consumed drug with its main source found in coffee. In the Kingdom of Saudi Arabia (KSA), diabetes and obesity are major health problems. Caffeine is attested as a potential drug for treating obesity, hepatic fibrosis, and preventing or delaying diabetes. The aim of this work is to evaluate the caffeine content of the Arabian coffee in comparison to Turkish coffee and instant coffee, in order to better adjust daily caffeine consumption. All types of coffee were prepared based on traditional ways in KSA. The average consumed coffee per normal person is assumed to be, 6 Arabian, 2 Nescafe or 1 Turkish cups per day. High performance liquid chromatography technique was used for caffeine measurement using paracetamol as an internal standard. Generally, coffee is prepared with other additives, liquid-liquid extraction was used for the extraction caffeine and paracetamol as an internal standard. HPLC method validated was over the range of 1 to 100 μg with good linearity (r²=0.991). Validation data proved that the method is accurate with average of 102%. Caffeine contents of Arabian coffee, Nescafe®, and Turkish coffee were found to be 4.1, 43.4 and 82.8 mg/cup, respectively. One cup of Turkish coffee contains caffeine as much as 2 Nescafe® and 20 Arabian cups. Gold Nescafe® contains about 20% less caffeine than classic. The caffeine content of each type of marketed coffee was accurately measured. An individual Arabian coffee consumer, who is drinking an average of 6 cups/day, can safely increase the number of cups or cup size in order to obtain more caffeine. The other choice for increasing caffeine ingestion is to think of Turkish coffee and/or Nescafe® as a substitute, in order to maintain caffeine at a therapeutic range for better health.
Abstract In this paper we extend upon an existing software architecture, namely the Context Orien... more Abstract In this paper we extend upon an existing software architecture, namely the Context Oriented Architecture to include support for quality of service. The Context Oriented Architecture is a responsive service oriented infrastructure that transparently monitors application context and allows for custom responses designed by service developers and triggered by conditions in the monitored context. We augment the architecture with a QoS-Broker, which supports QoS representation, discovery, matchmaking, monitoring and self-healing based on Web service standards. Service providers can specify various categories of Web services that differ in their QoS support. Clients are able to dynamically state their QoS requirements. To support standardization, QoS requirements and offers are described using the OWL-Q ontology. Our QoS-Broker matches a group of customers with a group of service offers by converting the problem into a constraint satisfaction problem, and solving it using a matchmaking search algorithm. As a proof of concept, the QoS-Broker monitors the invocation process and takes corrective action if a Web service could not meet the QoS level it claims to support. We verified the feasibility and performance of the QoS-Broker with our prototype implementation and performance measurements. In addition, we showed that group serving has less overhead than individual serving and that our matching logic conforms to the wisdom of the crowd.
2007 16th International Conference on Computer Communications and Networks, 2007
ABSTRACT In this paper, a novel technique for location prediction of mobile users has been propos... more ABSTRACT In this paper, a novel technique for location prediction of mobile users has been proposed, and a paging technique based on it is developed. Mobile users are creatures of habits. They tend to repeat their behaviors. Hence, neural networks with its learning and generalization ability may act as a suitable tool to predict the location of a mobile user provided it is trained appropriately by the personal mobility profile. For prediction, a novel hybrid Bayesian neural network model for predicting locations on Cellular Networks (can also be extended to other wireless networks such as Wi-Fi and WiMAX) is suggested. We investigate its different parallel implementation techniques on mobile devices, and compare its performance to many standard neural network techniques such as: Back-propagation, Elman, Resilient, Levenberg-Marqudat, and One-Step Secant models. This approach is free from all unrealistic assumptions about the movement of the users. It is applicable to any arbitrary cell architecture. It attempts to reduce the total location management cost and paging delay. In general, it enhances mobility management in wireless networks (in location management and hand-off management). In our experiments, we compare results of the proposed Bayesian Neural Network with 5 standard neural network techniques in predicting next location. Bayesian learning for Neural Networks predicts location better than standard neural network techniques since it uses well founded probability model to represent uncertainty about the relationship being learned. The result of Bayesian training is a posterior distribution over network weights.
2007 Second International Conference on Systems and Networks Communications (ICSNC 2007), 2007
Nowadays, path prediction is being extensively examined for use in the context of mobile and wire... more Nowadays, path prediction is being extensively examined for use in the context of mobile and wireless computing towards more efficient network resource management schemes. Path prediction allows the network and services to further enhance the quality of service levels that the user enjoys. In this paper we present a path prediction algorithm that exploits human creatures habits. In this paper, we present a novel hybrid Bayesian neural network model for predicting locations on Cellular Networks (can also be extended to other wireless networks such as WI-FI and WiMAX). We investigate different parallel implementation techniques on mobile devices of the proposed approach and compare it to many standard neural network techniques such as: Back-propagation, Elman, Resilient, Levenberg-Marqudat, and One-Step Secant models. In our experiments, we compare results of the proposed Bayesian Neural Network with 5 standard neural network techniques in predicting both next location and next service to request. Bayesian learning for Neural Networks predicts both location and service better than standard neural network techniques since it uses well founded probability model to represent uncertainty about the relationships being learned. The result of Bayesian training is a posterior distribution over network weights. We use Markov chain Monte Carlo methods (MCMC) to sample N values from the posterior weights distribution. These N samples vote for the best prediction. Simulations of the algorithm, performed using a Realistic Mobility Patterns, show increased prediction accuracy.
ISCA International Conference on Parallel and Distributed Computing Systems, 2007
A gas-liquid contacting apparatus for removing sulfur dioxide from a flue gas is provided which c... more A gas-liquid contacting apparatus for removing sulfur dioxide from a flue gas is provided which comprises a vessel for receiving therein a liquid aqueous absorbent in a continuous phase; gas sparger means having an opening means at one end thereof, the gas sparger means extending vertically from above the surface of the aqueous absorbent liquid and through the surface such that the opening means is positioned below the surface wherein the opening means comprises notch means formed in the side walls of the gas sparger means and an open end of the gas sparger means; air sparger means in the aqueous absorbent, below the gas sparger means; outlet means for the gas after it contacts the aqueous absorbent, the outlet means being located above the level of the aqueous absorbent; reactant inlet means into the vessel; aqueous absorbent inlet means into the vessel; and outlet means for the reaction products and spent aqueous absorbent.
1993 International Conference on Parallel Processing - ICPP'93 Vol3, 1993
We describe three new Jacobi orderings for parallel computation of SVD problems on tree architect... more We describe three new Jacobi orderings for parallel computation of SVD problems on tree architectures. The rst ordering uses the high bandwidth of a perfect binary fat-tree to minimise global interprocessor communication costs. The second is a new ring ordering which m a y be implemented e ciently on an ordinary binary tree. By combining these two orderings, an e cient new ordering, well suited for implementation on the Connection Machine CM5, is obtained.
A method of and apparatus for moxibustion comprising feeding air to a heat generating compositon ... more A method of and apparatus for moxibustion comprising feeding air to a heat generating compositon in contact with a herb material comprising moxa, wherein said heat generating composition comprises a pyrogen and said herb material is located adjacent to a skin surface, wherein said feeding causes said pyrogen to generate heat by oxidation, whereby said herb material is heated and vaporized and the generated heat and vapor act on the skin, causing moxibustion effect.
HW/SW techniques make it possible for the system designers to validate their design, assign modul... more HW/SW techniques make it possible for the system designers to validate their design, assign modules to be implemented in either hardware or software in the early stages of the system design life cycle. In addition, those techniques provide powerful mechanism for continuous system validation until the final product is done. Partitioning the system into either hardware or software, in the system early stages, is vital decision that has to be done iteratively and accurately. Many techniques have been proposed for HW/SW partitioning: conventional circuit partitioning techniques, simulated annealing, expert systems, and even genetic algorithm techniques. The partitioning problem has been proved to be and NP-Hard problem, thus AI, ANN and GA techniques can find a rich playground to apply their techniques. This paper presents a novel approach to use Bayesian Belief Networks as the tool that does the partitioning decision when provided by simulation parameters that measure certain character...
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