The study of entry and reentry dynamics for space vehicles is very important, particularly for manned vehicles and vehicles which is carry important devices and which can be used again. There are three types for entry dynamic, ballistics entry, glide entry and skip entry. The skip entry is used in this work for describing entry dynamics and determining trajectory. The inertia coordinate system is used to derive equations of motion and determines initial condition for skip entry. The velocity and drag force for entry vehicle, where generate it during entry into earth’s atmosphere are calculated in this work. Also the deceleration during descending and determining entry angles, velocities ratio and altitude ratio have been studied. The circular velocity and super circular velocity are used in this work as initial values. From results we noted the skip entry type has longer flight time compared with other types, and the velocity vehicle is lower at high layer for earth atmosphere, where the density of air is very low. Therefore the skip entry is suitable for space shuttle during entry from space
Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the
... Show MoreThe 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
... Show MoreScheduling 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
... Show MoreIn this work, a simple and new method is proposed to simultaneously improve the physical layer security and the transmission performance of the optical orthogonal frequency division multiplexing system, by combining orthogonal frequency division multiplexing technique with chaotic theory principles. In the system, a 2-D chaotic map is employed. The introduced system replaces complex operations such as matrix multiplication with simple operations such as multiplexing and inverting. The system performance in terms of bit error rate (BER) and peak to average ratio (PAPR) is enhanced. The system is simulated using Optisystem15 with a MATLAB2016 and for different constellations. The simulation results showed that the BE
... Show MoreIn the present study, gold nanoparticles (AuNPs) were prepared using a simple low cost method synthesized cold plasma at different exposure time . The nanoparticles were characterized using UV-Visible spectra, X-ray diffraction (XRD). The prepared AuNPs showed surface Plasmon resonance centered at 530, 540,and 533 nm. The XRD pattern showed that the strong intense peaks indicate crystalline nature and face centered cubic structure of gold nanoparticles for all samples were prepared .The average crystallite size of the AuNPs was 20-40 nm. Morphology of the AuNPs were carried out using FESEM. Observations show that the AuNPs synthesized we well dispersed with and particle sizes ranging from 9 to 31 nm with spherical shapes which are cle
... Show MoreThis booklet contains the basic data and graphs forCOVID-19 in Iraq during the first three months of thepandemic ( 24 February to 19 May - 2020 ) , It isperformed to help researchers regarding this health problem (PDF) Information Booklet COVID-19 Graphs For Iraq First 3 Months. Available from: https://www.researchgate.net/publication/341655944_Information_Booklet_COVID-19_Graphs_For_Iraq_First_3_Months#fullTextFileContent [accessed Oct 26 2024].
This paper proposes a novel method for generating True Random Numbers (TRNs) using electromechanical switches. The proposed generator is implemented using an FPGA board. The system utilizes the phenomenon of electromechanical switch bounce to produce a randomly fluctuated signal that is used to trigger a counter to generate a binary random number. Compared to other true random number generation methods, the proposed approach features a high degree of randomness using a simple circuit that can be easily built using off-the-shelf components. The proposed system is implemented using a commercial relay circuit connected to an FPGA board that is used to process and record the generated random sequences. Applying statistical testing on th
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The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.
And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)
... Show MoreObjectives: To assess general social factors for elderly in geriatric homes in Jordan.
Methodology: The study was conducted for clients residing in elderly homes. A purposive sample of (155)
residents were selected. Social resource scale by (Duck University Center) called (OARA) older adult resources
and services was used as tool for data collection. The questions extract data about family structure, patterns of
friends and visiting, availability of a confident, satisfaction with the degree of social interaction and availability
of a helper in the event of illness or disability and the program of trips in the houses.
Results: The findings revealed that the life expectancy for women is greater than for men. In respect to