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 optimal timetable schedules with different copies by increasing the probability of giving the best schedule for each stage in the campus with the ability to replace the timetable when needed. The Evolutionary Algorithm (EA) utilized in this paper is the Genetic Algorithm (GA) which is a common multi-solution metaheuristic search based on the evolutionary population that can be applied to solve complex combinatorial problems like timetabling problems. In this work, all inputs: courses, teachers, and time acted by one array to achieve local search and combined this acting of the timetable by using the heuristic crossover to ensure that the essential conditions are not broken. The result of this work is a flexible scheduling system, which shows the diversity of all possible timetables that can be created depending on user conditions and needs.
As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec
... Show MoreStructural and optical properties were studied as a function of Nano membrane after prepared, for tests. Nano membrane was deposited by the spray coating method on substrates (glass) of thickness 100 mm. The X-ray diffraction spectra of (CNTs, WO3) were studied. AFM tests are good information about the roughness, It had been designed electrolysis cell and fuel cell. Studies have been performed on electrochemical parameters.
Research problem:
Problem of current research can determine the dimensions to answer the following question: The effect of teaching using the six thinking hats on academic achievement for students in the second grade average in the subject of Family Education. The importance of research: research is gaining importance in terms of:
1. That this research is the first of its kind in the researcher's knowledge _ which deals with the teaching of Family Education by using the six hats, the researcher hopes to fill a gap in the educational field and serve in other studies serve the materials home economics. 2. Keep pace with the new field of modern education and strategies. 3. Highlight on the educational strategy in the field of creative
The Beggar (1965) is a story of isolation and depression which is written by the Egyptian novelist Naguib Mahfouz who is considered the father of Arabic Literature in the modern era. Specifically, he refers in his great novel called The Beggar that the man unable to achieve psychological revival after Nasser’s revolution, the man sacrificed his own job and his family for a desire that increases his feelings of alienation and depression which leads him to an emotional outcry against the indifferent. The main aim of the study highlights the concept of existential dilemma as a philosophical problem and personality crisis by the protagonist of The Beggar novel, Omer Al-Hamzawi who had acc
... Show MoreThe main theme of this thesis could be divided into three objectives : The first is to define and classify integral equations with one and multiple delay, including Fredholm, Volterra and integro-differential equations (Retarded, Neutral and Mixed types). While the second and popular objective of this work is to study the inverse problems related to delay integral equations by using non-classical variational formulation method. Some examples are given for each of the discussed type of delay integral equations. Also, a study to the direct and inverse problems related to integral equations with multiple delay, also considered as a third objective. Several examples are given for each type of these equations. Finally, the suggested approach
... Show MoreThis study focuses on the phenomenon of child labour, which is regarded as a problem not only in Iraq or in developing countries but also in many other countries around the world .In fact, this problem is ignored and not given enough attention for there are millions of children working and doing different works in economically poor societies. Those children often work for long hours and are being exploited, doing works incompatible with their abilities and energy, preventing them from enjoying their childhood, developing both mentally and physically and joining school. The research introduced some suggestions aiming at preventing children from all forms of harmful and unhealthy works are presented. In fact, this is the very aim that most
... Show MoreA three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
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