Under aerobic and anaerobic conditions, two laboratory-scale reactors were operated. Each reactor
was packed with 8.5 kg of shredded synthetic solid waste (less than 5 cm) that was prepared according to an
average composition of domestic solid waste in the city of Kirkuk. Using an air compressor, aerobic
conditions were created in the aerobic reactor. This study shows that the aerobic reactor was more efficient in
COD and BOD5 removal which were 97.88% and 91.25% while in case of anaerobic reactor, they were
66.53%and 19.11%, respectively.

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

The study aimed to test the hypothesis of Caldor to estimate the relationship between industrial production and GDP growth in Iraq using with Integration Framework  and to determine the causal relationship in the short and long term using the error correction vector model for the period 1990-2016. the results showed a long-term equilibrium relationship between GDP and industrial output, while Ganger causality tests showed a causal relationship in the long run of GDP to output Subliminal thus illustrated the extent of the recession suffered by the industrial sector, which is supposed to be the driving force of the economy and the development and expansion of the productive base of the industry, so this study recommends attent

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation. 

Spraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore, researchers have been encouraged to...

Software testing is a vital part of the software development life cycle. In many cases, the system under test has more than one input making the testing efforts for every exhaustive combination impossible (i.e. the time of execution of the test case can be outrageously long). Combinatorial testing offers an alternative to exhaustive testing via considering the interaction of input values for every t-way combination between parameters. Combinatorial testing can be divided into three types which are uniform strength interaction, variable strength interaction and input-output based relation (IOR). IOR combinatorial testing only tests for the important combinations selected by the tester. Most of the researches in combinatorial testing