Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting ADR.
Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f
... Show MoreThermal energy storage is an important component in energy units to decrease the gap between energy supply and demand. Free convection and the locations of the tubes carrying the heat-transfer fluid (HTF) have a significant influence on both the energy discharging potential and the buoyancy effect during the solidification mode. In the present study, the impact of the tube position was examined during the discharging process. Liquid-fraction evolution and energy removal rate with thermo-fluid contour profiles were used to examine the performance of the unit. Heat exchanger tubes are proposed with different numbers and positions in the unit for various cases including uniform and non-uniform tubes distribution. The results show that
... Show MoreThe Praise be to God, Lord of the Worlds, and prayers and peace be upon the Master of the Messengers and his pure and pure family, and may the peace and blessings be abundantly
التطور الدلالي لمعاني الكلمات في اللغة العبرية
In this paper a dynamic behavior and control of a jacketed continuous stirred tank reactor (CSTR) is developed using different control strategies, conventional feedback control (PI and PID), and neural network (NARMA-L2, and NN Predictive) control. The dynamic model for CSTR process is described by a first order lag system with dead time.
The optimum tuning of control parameters are found by two different methods; Frequency Analysis Curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method. It is found that the Process Reaction Curve method is better than the Frequency Analysis Curve method and PID feedback controller is better than PI feedback controller.
The results s
... Show MoreThis piece of research work aims to study one of the most difficult reaction and determination due to continuous and rapid variation of reaction products and the reactants. As molybdenum (VI) aid in the decomposition of hydrogen peroxide in alkaline medium of ammomia, thus means a continuous liberation of oxygen which cuases and in a continuous manner a distraction in the measurement process. On this basis pyrogallol was used to absorbe all liberated oxygen and the result is an a clean undisturbed signals. Molybdenum (VI) was determined in the range of 4-100 ?g.ml-1 with percentage linearity of 99.8% or (4-300 ?g.ml-1 with 94.4%) while L.O.D. was 3.5 ?g.ml-1. Interferring ions (cations and anions) were studied and their main effect was red
... Show MoreThe aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).