This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

The aim of this study is to achieve the best distinguishing function of the variables which have common characteristics to distinguish between the groups in order to identify the situation of the governorates that suffer from the problem of deprivation. This allows the parties concerned and the regulatory authorities to intervene to take corrective measures. The main indicators of the deprivation index included (education, health, infrastructure, housing, protection) were based on 2010 data available in the Central Bureau of Statistics

Abstract:

           The great importance that distinguish these factorial experiments made ​​them subject a desirable for use and application in many fields, particularly in the field of agriculture, which is considered the broad area for experimental designs applications.

            And the second case for the factorial  experiment, which faces researchers have great difficulty in dealing with the case unbalance we mean that frequencies treatments factorial  are not equal meaning (that is allocated a number unequal of blocks or units experimental per tre

In this paper, a new hybridization of supervised principal component analysis (SPCA) and stochastic gradient descent techniques is proposed, and called as SGD-SPCA, for real large datasets that have a small number of samples in high dimensional space. SGD-SPCA is proposed to become an important tool that can be used to diagnose and treat cancer accurately. When we have large datasets that require many parameters, SGD-SPCA is an excellent method, and it can easily update the parameters when a new observation shows up. Two cancer datasets are used, the first is for Leukemia and the second is for small round blue cell tumors. Also, simulation datasets are used to compare principal component analysis (PCA), SPCA, and SGD-SPCA. The results sh

As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

The purpose of this work was to study the effects of the Nd:YAG laser on exposed dentinal
tubules of human extracted teeth using a scanning electron microscope (SEM). Eighty 2.5mm-thick
slices were cut at the cementoenamel junction from 20 extracted human teeth with an electric saw. A
diamond bur was used to remove the cementum layer to expose the dentinal tubules. Each slice was
sectioned into four equal quadrants and the specimens were randomly divided into four groups (A to D ).
Groups B to D were lased for 2 mins using an Nd:YAG laser at 6 pulses per second at energy outputs of
80 , 100 and 120 mJ. Group A served as control. Under SEM observation, nonlased specimens showed
numerous exposed dentinal tubules. SEM o

Background: clinically significant macular edema (CSME) is the commonest cause of visual loss in patients with diabetes mellitus and laser focal photocoagulation is the golden standard for treating it. Patients and Methods: A frequency doubled Nd: YAG laser was used to treat all eyes included in this study with diabetic maculopathy. Thirty eyes of three insulin dependent and twenty six non insulin dependent diabetic Iraqi patients were included. The study involved twenty six males, three females and followed for one year. Their ages were ranging between 36- 59 years, all of them from patients attending ophthalmic out-patient department in the medical city in the period between January 2005 and June 2006. Eyes divided in to two groups (fifte

Photobiomodulation (PBM) is a form of the use of visible red and Near-infrared (NIR) light at low power, where a laser light photon is absorbed at the electronic level, without heat production. PBM can be applied in wide range of treatment to help the wound, inflammation, edema, and pain reduction. However, there is a lack of scientific documentation regarding its actual effects. Objectives: This study assesses the impact of PBM on the release of M1-related cytokine in monocyte cells with particular emphasis on interleukin-1β (IL-1β) and Tumour Necrosis Factor α (TNF-α). Methods: Tamm-Horsfall Protein 1 (THP-1) macrophages M1 cells have been exposed to the light from the diode laser of 850nmat different doses (0, 0.6, 1.2 and 3.