The process of evaluating and measuring tax performance is critical to support the tax collection process. The comparison of the amount of revenue collection with what is expected and the process of measuring tax performance continuously by the tax administration leads to increase the collection of tax, determine the size of deviations and stand and know the reasons and take the necessary measures to address them to get a better result in the future. According to the different tasks assigned to them, criteria and indicators for measuring the tax performance vary from one organization to another. These are indicators or criteria that measure tax revenue (i.e., amounts). One of the research's main findings was to raise the tax collection level, increase the number of employees to get good performance, and impose sanctions on tax evaders. They are detecting the manipulators with the other accounts submitted to the General Authority for Taxes to evade the tax and achieve the taxpayers' greatest possible profit. The most important recommendations reach the research. The attempt to introduce technology and advanced information systems to cope with developments in the field of taxation, to give more importance to the process of assessment and measurement of tax performance because of the positive impact in the process of collection of tax collection.
A Geographic Information System (GIS) is a computerized database management system for accumulating, storage, retrieval, analysis, and display spatial data. In general, GIS contains two broad categories of information, geo-referenced spatial data and attribute data. Geo-referenced spatial data define objects that have an orientation and relationship in two or three-dimensional space, while attribute data is qualitative data that can be counted for recording and analysis. The main aim of this research is to reveal the role of GIS technology in the enhancement of bridge maintenance management system components such as the output results, and make it more interpretable through dynamic colour coding and more sophisticated visualization
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Extracorporeal shock wave lithotripsy (ESWL) is considered a standard treatment for nephrolith or kidney stones measuring less than 20 mm. Anatomical, machine-related, and stone factors play pivotal roles in treatment outcomes, the latter being the leading role. This paper examined the relationship between stone density on native CT scans and ESWL treatment to remove renal stones concerning several treatments. One hundred and twenty patients (64 males and 56 females) were enrolled and completed the study from April 2019 to September 2020. Inclusion criteria were a single renal pelvis stone of 5–20 mm to be treated for the first time in adult patients with no urinary or musculoskeletal anatomical abnormalities. We assessed patients
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To assess the biochemical, mechanical and structural characteristics of retained dentin after applying three novel bromelain‑contained chemomechanical caries removal (CMCR) formulations in comparison to the conventional excavation methods (hand and rotary) and a commercial papain‑contained gel (Brix 3000). Seventy‑two extracted permanent molars with natural occlusal carious lesions (score > 4 following the International Caries Detection and Assessment System (ICDAS‑II)) were randomly allocated into six groups (n = 12) according to the excavation methods: hand excavation, rotary excavation, Brix 3000, bromelain‑contained gel (F1), bromelain‑chloramine‑T (F2), and bromelain chlorhexidine gel (F3). The superficial and deepe
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Fifty snails of Paropeas achatinaceum specimens were collected and classified from four areas in Baghdad-Iraq from the period between June and July, 2017. The snails were divided into two groups (each group contain 25 snails). Two environment conditions were used in this study. Natural environment considered as control and experimental environment contains Citrus sinensis (L.) roots as snail’s source food. The comparison result between snail weights in the nature and experimental environment was not significant (0.497, 95% confidence interval [CI] 0.01209–0.02309). Also, the comparison between snail weights in the nature environment and the food mean weight was significant (0.014, 95% confidence interval [CI] 0.00591-0.04109), while the
... Show MoreIn the present work, the efficiency of Tri-octyl Methyl Ammonium Chloride (TOMAC) ionic liquid was investigated as new and green demulsifier for three types of Iraqi crude oil emulsions (Nafut Khana (NK), Kirkuk and Basrah). The separation efficiency was studied at room temperature and by using microwave heating technique. Several batch experiments were done to specify the suitable conditions for the emulsification and demulsification which were specified as 45 minutes and 3000 rpm for crude oil emulsification while the ionic liquid doses were (500,300,150,50) ppm and the conditions of microwave heating were 1000 watt and 50 second as irradiation time. The results were very encouraging especially for NK and Kirkuk crude oil emulsions whe
... Show MoreCu (In, Ga) Se2 (CIGS) nano ink were synthesized from molecular precursors of CuCl, In Cl3, GaCl3 and Se metal heated to 240 °C for 1 hour in N2-atmosphere to form CIGS nanocrystal ink, Thin films were deposited onto Au/soda-lime glass (SLG) substrates. This work focused on CIGS nanocrystals, including their synthesis and application as the active light absorber layer in photovoltaic devices (PVs). This approach, using spin-coating deposition of the CIGS light absorber layers (75 mg/ml and 150 nm thickness), without high temperature selenization, has enabled up to 1.398 % power conversion efficiency under AM 1.5 solar illumination. X-ray diffraction (XRD) studies show that the structural formation of CIGS chalcopyrite structure. The mo
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
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