This paper presents an enhancement technique for tracking and regulating the blood glucose level for diabetic patients using an intelligent auto-tuning Proportional-Integral-Derivative PID controller. The proposed controller aims to generate the best insulin control action responsible for regulating the blood glucose level precisely, accurately, and quickly. The tuning control algorithm used the Dolphin Echolocation Optimization (DEO) algorithm for obtaining the near-optimal PID controller parameters with a proposed time domain specification performance index. The MATLAB simulation results for three different patients showed that the effectiveness and the robustness of the proposed control algorithm in terms of fast gene

The problem of the research is focused on importance limited of Iraq industrial companies in application of scientific measurements of supply chains performance,  The research sought to achieve a group of goals, the most important are , identifying the strengths and weaknesses in the reality of supply chain in General Company for Cotton Industries, The data and information required are gathered from the dependence company, records through the field observations and personal interviews, the research used some quantitative indicators to measure of supply chain performance, The research reached to many conclusions , the most outstanding among them is the existence of a strong inverse correlatio

Background: Fast dissolving oral drug delivery system is solid dosage form which disintegrates or dissolves within second when placed in the mouth without need of water or chewing. In present investigation, an attempt has been made to develop oral fast dissolving film of calcium channel blocker lacidipine. Method: Five formulas were prepared by solvent casting method using HPMC (METOLOSE)® as a film forming polymer and evaluated for their physical characteristics such as thickness, weight variation, folding endurance, drug content, disintegration time and in vitro drug release. The compatibility of the drug in the formulation was confirmed by FTIR and DSC studies. Result and Conclusion: The optimized formula F1 showed minimum in vitr

Objective: To evaluate the functional outcomes after extended curettage and reconstruction using a combination of bone graft and bone cement (sandwich). Methodology: In this prospective case series 16 skeletally mature patients with primary giant cell tumor around the knee were included. Patients with previous surgically treated, malignant transformation, degenerative knee changes and those presenting with pathological fracture were excluded. The tumor was excised with bone graft filling space beneath the articular cartilage and a block of gel foam was placed over the cortical surface of picked bone graft. Remaining cavity was filled with polymethylmethacrylate cement (sandwich) with or without internal fixation. The func tional evaluation

The Ground Penetrating Radar (GPR) is frequently used in pavement engineering
for road pavement inspection. The main objective of this work is to validate
nondestructive, quick and powerful measurements using GPR for assessment of subgrade
and asphalt /concrete conditions. In the present study, two different antennas
(250, 500 MHz) were used. The case studies are presented was carried in University
of Baghdad over about 100m of paved road. After data acquisition and radar grams
collection, they have been processed using RadExplorer V1.4 software
implementing different filters with the most effective ones (time zero adjustment and
DC removal) in addition to other interpretation tool parameters.
The interpretatio

The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF

Liquid electrodes of domperidone maleate (DOMP) imprinted polymer were synthesis based on precipitation polymerization mechanism. The molecularly imprinted (MIP) and non-imprinted (NIP) polymers were synthesized using DOMP as a template. By methyl methacrylate (MMA) as monomer, N,Nmethylenebisacrylamide (NMAA) and ethylene glycol dimethacrylate (EGDMA) as cross-linkers and benzoyl peroxide (BP) as an initiator. The molecularly imprinted membranes were synthesis using acetophenone (APH), di-butyl sabacate (DBS), Di octylphthalate (DOPH) and triolyl phosphate (TP)as plasticizers in PVC matrix. The slopes and limit of detection of l

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For