Metoprolol is a β₁ adrenergic blocker used in treatment of heart diseases. Metoprolol (100mg) tablets was formulated as a modified release oral system utilizing the concept of bilayer system, first layer contained (30mg) as immediate release and the other (70mg) in the sustained release matrix.  The immediate release layer consisted of lactose or microcrystalline cellulose as diluents with sodium starch glycolate or sodium croscarmellose as disintegrants. The result showed that the layer contains microcrystalline cellulose and 2% sodium starch glycolate gave disintegration time similar to that of conventional metoprolol tartrate tablet. This result was subjected in the subsequent preparation of the bilayer tablet. The

Non-additive measures and corresponding integrals originally have been introduced by Choquet in 1953 (1) and independently defined by Sugeno in 1974 (2) in order to extend the classical measure by replacing the additivity property to non-additive property. An important feature of non –additive measures and fuzzy integrals is that they can represent the importance of individual information sources and interactions among them. There are many applications of non-additive measures and fuzzy integrals such as image processing, multi-criteria decision making, information fusion, classification, and pattern recognition. This paper presents a mathematical model for discussing an application of non-additive measures and corresp

This study focuses on studying an oscillation of a second-order delay differential equation. Start work, the equation is introduced here with adequate provisions. All the previous is braced by theorems and examplesthat interpret the applicability and the firmness of the acquired provisions

 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this

In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

Background: Moyamoya disease (MMD) is a rare cerebrovascular disease characterized by bilateral stenosis starting at the supraclinoid internal carotid artery (ICA), with the development of a collateral network of vessels. It is an established cause of stroke in the pediatric age group. Despite its increasing prevalence in various parts of the world, it remains largely underrecognized in the Middle East, particularly in Iraq. This is the first case of MMD in an Iraqi patient undergoing surgery. Case description: A 12-year-old boy presents with a 3-months history of progressive behavioural changes. MRI revealed diffuse infarcts of different ages. MRA and CT angiography revealed extensive asymmetrical steno-occlusive changes of t