The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating opti

This study aims to establish an empirical correlation between biochemical oxygen demand (BOD5) and chemical oxygen demand (COD) of the sewage flowing in Al-Diwaniyah wastewater treatment plant. The strength of the wastewater entering the plant varied from medium to high. High concentrations of BOD5 and COD in the effluent were obtained due to the poor performance of the plant. This was observed from the BOD5 /COD ratios that did not confirm with the typical ratios for the treated sewage. To improve the performance of this plant, regression equations for BOD5 and COD removal percentages were suggested which can be used to facilitate rapid effluent assessment or optimal process control. The equations relating the percentage removal of

This study was aimed to investigat integrated system for in vitro growth of paulownia plants by assessing the efficacy of chlorine dioxide (ClO2) as an alternative to autoclave in sterilizing culture medium. Therefore, this study was devised to compare autoclave sterilization at three different times (5, 10, and 15) minutes and three different concentrations of ClO2 (0, 0.4, 0,8, 1) mg/L. The results showed that, compared with (0.4) mg/L concentration,  concentrations of (0.8 and 1) mg/L are more effective at sterilizing the culture medium. ClO2 sterilization improved individual single node growth more than autoclave sterilization. Since ClO2 is non-toxic, it could be used as a safe alternative to autoclave when propagating paulown

Focusing on the negative role of default risk on banks, as it is one of the most important risks facing banks, which are difficult to determine accurately, and its reflection on the indicators of profitability of cash flows. The increasing competition between banks led to an increase in the credit facilities granted by banks, and was accompanied by an increase in exposure to the risks of default, which led to an impact on the level of performance of banks in terms of achieving the required return according to the levels of high competition. Therefore, the problem of this study focused on the extent to which the risk indicators of default affect the profitability indicators of the cash flows of the banks research sample in the profit