The research aims to show the role or extent of the impact of financing in its various forms on the municipal performance before and after the financial deficit through relying on the analytical research methodology of the research community represented by the Directorate General of Municipalities and the Directorate of Maysan municipalities as a sample of research (13) municipal institutions for a period of (8) years, Considering the completion of the final accounts of these years, which provides the necessary data for the study, in addition to the variation in the quality and amounts of grants allocated to municipal institutions during these years, which gives a clearer and more comprehensive picture of the reality of allocatio

The study was conducted to determine the effect of of cumin (Cuminum cyminum) and ginger (Zingiber officinale) powder on performance in Japanese quails. 630 bird (7 birds for each treatment) nine weeks of age were used. Experiment was continued for 12 weeks divided to six periods and the birds distributed randomly on nine combinations of cumin and ginger, three levels of each plant powder namely, 0, 0.5 and 1%. T1 (Control) contain the slandered diet (0% of cumin and 0% of ginger), T2: (0% of cumin and 0.5% of ginger), T3: (0% of cumin and 1% of ginger), T4: (0.5% of cumin and 0% of ginger), T5: (0.5% of cumin and 0.5% of ginger), T6: (0.5% of cumin and 1% of ginger), T7: (1% of cumin and 0% of ginger), T8: (1% of cumin and 0.5% of ginger),

The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall