Abstract

This research  aims to reform the Iraqi public budget through going into the challenges the budget faces in applying item-line budget in its preparation, implementation and control; which encourage extravagance and waste instead of rationalizing expenditures. This  is shown in the data analysis of Federal public budget laws in Iraq for the years from 2005 till 2013; there was a continuous increase in the aggregate public expenditures in the public budget for the years previously mentioned, as the public expenditures growth has reached into the percent 284.71% in 2013. In addition the public budget for these years (2005-2013) is being prepared with planned deficit without confirming that

   In this paper, Mann-Kendall test was used to investigate the existence of possible deterministic and stochastic climatic trends in (Baghdad,Basrah,Mosul,Al-Qaim) stations. The statistical test was applied to annual monthly mean of temperatures for the period (19932009). The values of S-statistic were (62, 44, 52, 64) by comparing these values with the table of null probability values for S we get a probability of (0.002, 0.026, 0.010, 0.002) this result is less than α for the 95% confidence level (α = 0.05) indicating a significant result at this level of confidence. Concluded that an increasing trend in concentration is present at the 95% confidence level and the variance of the S-statistic is calculated and it is com

In modern years, internet and computers were used by many nations all overhead the world in different domains. So the number of Intruders is growing day-by-day posing a critical problem in recognizing among normal and abnormal manner of users in the network. Researchers have discussed the security concerns from different perspectives. Network Intrusion detection system which essentially analyzes, predicts the network traffic and the actions of users, then these behaviors will be examined either anomaly or normal manner. This paper suggested Deep analyzing system of NIDS to construct network intrusion detection system and detecting the type of intrusions in traditional network. The performance of the proposed system was evaluated by using

An interpretive (structural and stratigraphic) study of the two,-dimensional seismic, data of East Nasiriya area (30 km to the south east of Nasiriya oil field within Thi-Qar province, southeastern Iraq) was carried out using Petrel 2017 program. The study area has an importance due to its location between many oil fields, but still without exploration of oil wells. Twenty five seismic lines were used, date back to different types of seismic surveys conducted in the region at different time periods.  Also, the seismic velocity surveys of the nearest wells to oil fields, such as Nasiriya-1 and Subba-8, in addition to their sonic and density logs were used. A synthetic seismogram with a good matching with the seismic section was achie

     A field experiment was conducted  at two sites (Baghdad and Wasit Governorates) to evaluate the effects of allelopathic corn residues applied as soil incorporation or mulch, alone  and in combination  with reduced (50% of recommended dose) rate of trifluralin herbicide on weeds growth and mung bean yield. Conventional soil tillage and zero soil tillage treatments with corn residues were performed, while 50% dose and full dose of trifluralin only (without residues) treatments were included for comparison. Soil incorporation and mulch of corn residues reduced weed density and dry weight biomass and improved yield and yield components of mung bean in both sites. Mulch application was more effective than soil incorporation for we

In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

This research considers the preservation of environment through recycling old toys. This is achieved by transforming the old toys into educational clothing accessories for kindergarten stages. The research methodology adapts both descriptive and applied approaches. The research questionnaire targeted a sample of 35 teachers to collect information about the waste toys in kindergarten. Also, another sample of 30 teachers and mothers were targeted to measure the suitability of the clothing designs for the early childhood stages. The results shows that both teachers and mothers were well satisfied with clothing accessories designed with the toys waste. This concept contributes to limiting the pollution caused by toys and could save time, eff

This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

Abstract
             In this research will be treated with a healthy phenomenon has a significant impact on different age groups in the community, but a phenomenon tonsillitis where they will be first Tawfiq model slope self moving averages seasonal ARMA Seasonal through systematic Xbox Cengnzla counter with rheumatoid tonsils in the city of Mosul, and for the period 2004-2009 with prediction of these numbers coming twelve months, has found that the specimen is the best representation of the data model is the phenomenon SARMA (1,1) * (2,1) 12  from the other side and explanatory variables using a maximum temperature and minimum temperature, sol

    Semantic segmentation is effective in numerous object classification tasks such as autonomous vehicles and scene understanding. With the advent in the deep learning domain, lots of efforts are seen in applying deep learning algorithms for semantic segmentation. Most of the algorithms gain the required accuracy while compromising on their storage and computational requirements. The work showcases the implementation of Convolutional Neural Network (CNN) using Discrete Cosine Transform (DCT), where DCT exhibit exceptional energy compaction properties. The proposed Adaptive Weight Wiener Filter (AWWF) rearranges the DCT coefficients by truncating the high frequency coefficients. AWWF-DCT model reinstate the convolutional l