The university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed approach generates solutions into two phases (initial and improvement). A new LLH named “least possible rooms left” has been developed and proposed to schedule events. Both datasets of international timetabling competition (ITC) i.e., ITC 2002 and ITC 2007 are used to evaluate the proposed method. Experimental results indicate that the proposed low-level heuristic helps to schedule events at the initial stage. When compared with other LLH’s, the proposed LLH schedule more events for 14 and 15 data instances out of 24 and 20 data instances of ITC 2002 and ITC 2007, respectively. The experimental study shows that HH PSO gets a lower soft constraint violation rate on seven and six data instances of ITC 2007 and ITC 2002, respectively. This research has concluded the proposed LLH can get a feasible solution if prioritized.
The research aims to identify the impact of using the electronic participatory learning strategy according to internet programs in learning some basic basketball skills for middle first graders according to the curricular course, and the sample of research was selected in the deliberate way of students The first stage of intermediate school.As for the problem of research, the researchers said that there is a weakness in the levels of school students in terms of teaching basketball skills, which prompted the researchers to create appropriate solutions by using a participatory learning strategy.The researchers imposed statistically significant differences between pre and post-test tests, in favor of the post tests individually and in favor of
... Show MoreThe ZnO nanoparticles were synthesized at various precursor concentrations i.e. 0.05, 0.1, and 0.5 M by biosynthesis method based on Pometia pinnata Leaf Extracts. Initial nanoparticle concentration influenced the optical bandgap, shape, and structure of nanoparticles. The photodegradation process was carried out under UV illumination. The efficiency of MB degradation was determined by measuring the decrease in MB concentration and by analyzing the optical absorption at 663 nm recorded by UV-Vis spectroscopy. Results showed that the biosynthesized ZnO nanoparticles exhibited efficient photodegradation of MB, with a maximum degradation rate of 80% after 90 minutes of exposure to UV-C light. The study highlights the potential of Pometia pi
... Show MoreThe objective of this study is to enable the role of modern and advanced computerized information systems. The model or mechanism should be developed by collecting the necessary information about the taxpayers and the sources of the taxpayers' income, on the basis of which the accuracy of the inventory process will be adopted. In addition to studies related to computerized information systems and showing their importance to the tax institution. To achieve the objectives of the study and to answer its questions, the researcher relied on collecting data and information on the subject on the literature and previous studies The secondary sources, which also formed the theoretical framework of the study, were obtained either as a practical fr
... Show MoreThe excessive and rapid urban growth witnessed by most cities in the world can be a cause of diseases and epidemics, especially those problems related to population, which include problems of transportation and increase in density in the centers, in addition to the lack of interest in planning and designing those cities to take into account the health aspect of the city and obtain The health well-being of the population, and each of these problems has negative effects on health in general and on human health in particular through its prevalence. Therefore, many concepts that serve as a tool for achieving public health and the physical health of the population have emerged, including the concept of city health, which is defined as cities
... Show MoreFor businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers
... Show MoreObjectives: Assessment outcome of DOTS (Directly observed therapy short course) program in Al-Sader City
Sector that was established by the WHO.
Methodology: Three cohorts groups of patients attending Baghdad TB institute and TB center in Al-Sader city
were followed retrospectively. The 1st cohort included (314) patients registered in year (2003), the 2nd cohort
included (327) patients registered in year (2004), the 3rd cohort included (321) patients registered in year
(2005). The collected data were analyzed for case detection, treatment outcomes, retreatment outcomes,
treatment success, and retreatment success in regard to time, age and sex.
Results: The following rates were extracted for the three cohort: Case det
The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
... Show MoreHumanity has Suffered Greatly from the Economic crisis and instability, Before the Emergence of the rule of the Capitalist System, However, the reaons were Different. But almost Completely Contradictory. At a time When the Causes of the Crisis was due to the time Factor is the product of failure of productie forces, Bears modern Crises resoled by the progress that is in the embrace of the abundance, and as far as lies in the nature and content of the capitalist system itselfas a system based on the creation of productive capacities in excess unable to accomplish through demand by the chaos of production based, on the logic of the market on one hand, and the nature of the output and direction. On the other hand the relations
... Show MoreSocial Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation. Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota
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