Abstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.
Abstract
Hexapod robot is a flexible mechanical robot with six legs. It has the ability to walk over terrain. The hexapod robot look likes the insect so it has the same gaits. These gaits are tripod, wave and ripple gaits. Hexapod robot needs to stay statically stable at all the times during each gait in order not to fall with three or more legs continuously contacts with the ground. The safety static stability walking is called (the stability margin). In this paper, the forward and inverse kinematics are derived for each hexapod’s leg in order to simulate the hexapod robot model walking using MATLAB R2010a for all gaits and the geometry in order to derive the equations of the sub-constraint workspaces for each
... Show MoreSolid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, t
... Show MoreA new blind restoration algorithm is presented and shows high quality restoration. This
is done by enforcing Wiener filtering approach in the Fourier domains of the image and the
psf environments
The first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o
... Show MoreThe first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o
... Show MoreThe Gray Wolf Optimizer (GWO) is a population-based meta-heuristic algorithm that belongs to the family of swarm intelligence algorithms inspired by the social behavior of gray wolves, in particular the social hierarchy and hunting mechanism. Because of its simplicity, flexibility, and few parameters to be tuned, it has been applied to a wide range of optimization problems. And yet it has some disadvantages, such as poor exploration skills, stagnation at local optima, and slow convergence speed. Therefore, different variants of GWO have been proposed and developed to address these disadvantages. In this article, some literature, especially from the last five years, has been reviewed and summarized by well-known publishers. Fir
... Show MoreA new human-based heuristic optimization method, named the Snooker-Based Optimization Algorithm (SBOA), is introduced in this study. The inspiration for this method is drawn from the traits of sales elites—those qualities every salesperson aspires to possess. Typically, salespersons strive to enhance their skills through autonomous learning or by seeking guidance from others. Furthermore, they engage in regular communication with customers to gain approval for their products or services. Building upon this concept, SBOA aims to find the optimal solution within a given search space, traversing all positions to obtain all possible values. To assesses the feasibility and effectiveness of SBOA in comparison to other algorithms, we conducte
... Show More In this research, an adaptive Canny algorithm using fast Otsu multithresholding method is presented, in which fast Otsu multithresholding method is used to calculate the optimum maximum and minimum hysteresis values and used as automatic thresholding for the fourth stage of the Canny algorithm. The new adaptive Canny algorithm and the standard Canny algorithm (manual hysteresis value) was tested on standard image (Lena) and satellite image. The results approved the validity and accuracy of the new algorithm to find the images edges for personal and satellite images as pre-step for image segmentation.
A novel median filter based on crow optimization algorithms (OMF) is suggested to reduce the random salt and pepper noise and improve the quality of the RGB-colored and gray images. The fundamental idea of the approach is that first, the crow optimization algorithm detects noise pixels, and that replacing them with an optimum median value depending on a criterion of maximization fitness function. Finally, the standard measure peak signal-to-noise ratio (PSNR), Structural Similarity, absolute square error and mean square error have been used to test the performance of suggested filters (original and improved median filter) used to removed noise from images. It achieves the simulation based on MATLAB R2019b and the resul
... Show MoreIn this study the Entrance Surface Dose (ESD) received by pediatrics patients undergoing chest, abdomen and skull X-ray examinations was estimated. The study was conducted in two hospitals in Najaf city where three radiographic systems were considered. The study participants were classified into four age groups 0-1 , 1-5 , 5-10 and 10-15 years. Calculations were performed using exposure factors, kVp, mAs and focal-skin distance, together with patient data age. The ESD was calculated for the involved patients who underwent an Antero-posterior (AP) chest, abdomen and skull X-ray examination. The resulted data were analyzed and compared with international dose references. For all studied radiographic examinations and all X-ray mac
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