This research include design and implementation of an Iraqi cities database using spatial data structure for storing data in two or more dimension called k-d tree .The proposed system should allow records to be inserted, deleted and searched by name or coordinate. All the programming of the proposed system written using Delphi ver. 7 and performed on personal computer (Intel core i3).

In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath  propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.

In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at

Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

The purpose of this paper is to preparing preventive exercises supported by collagen supplements and vitamin D for handball players, and identify the effect of preventive physical exercises supported by collagen supplements and vitamin D on some physical and skill abilities of handball players. The researchers used the experimental method and designed two groups, one experimental and the other control, with both pre- and post-tests, to suit the nature of the research. The research community was selected from handball players (specialized school players), numbering (14), and they were divided into two groups, each group numbering (7) players. One of the most important results reached by the researcher is that: The exercises prepared by the r

Background: Studies discussing the correlation between biochemical markers of bone turnover and the diagnosis of osteoporosis in postmenopausal Iraqi women are rare. This study is devoted to find out the significance of serum osteocalcin (OC) and osteopontin (OPN) levels with the incidence of osteoporosis and its major complication (fracture).Objectives: to investigate the significance of bone turnover biochemical markers; serum osteocalcin and serum osteopontin in evaluating osteoporosis for postmenopausal Iraqi women with and without history of vertebral fracture, as well as to explore the relationship of these markers with bone mineral density (BMD).Methods: Fifty seven postmenopausal women whose ages are fifty years old and over, cat

Background: Polycystic ovary syndrome (PCOS) is the most common endocrine abnormality in women, there is an increasing evidence for an oxidative stress in PCOS that induce genomic and mitochondrial deoxyribonucleic acid damage that leads directly to reduced fertility. The objectives of this study are to assess and compare the periodontal health status by measuring clinical periodontal parameters (PLI, GI and BOP)as well as serum levels of superoxide dismutase at gingivitis ,gingivitis with PCOS and healthy periodontium groups, then correlate between clinical and biochemical parameters. Materials and Methods: 60 females with an age range between (25-40) years old had been tested and divided into3 groups ,the control group consists of (20) f

This study is an attempt to find whether arginine metabolism dysregulation by arginase activity is related to hyperglycemia, followed by changes in nitric oxide (NO) generation in type 2 diabetic patients. This study includes 42 control subjects (Group I), and 92 Iraqi patients with type 2 diabetes mellitus (T2DM). The patient group was subdivided into two groups: Group II (54) with T2DM only and Group III (38) with T2DM and dyslipidemia (who were treating with atorvastatin along with diabetes treatment). The samples were obtained to measure arginase activity and NO levels. Serum arginase activity increased significantly in patients(groupII and groupIII) compared to control group. While serum NO level was significantly lower in diabetic pa