Current Issue : January - March Volume : 2017 Issue Number : 1 Articles : 6 Articles
TheMinMax...
This paper describes the design and the implementation of a trajectory tracking controller using fuzzy logic for mobile robot\nto navigate in indoor environments. Most of the previous works used two independent controllers for navigation and avoiding\nobstacles. The main contribution of the paper can be summarized in the fact that we use only one fuzzy controller for navigation\nand obstacle avoidance.The used mobile robot is equipped withDCmotor, nine infrared range (IR) sensors tomeasure the distance\nto obstacles, and two optical encoders to provide the actual position and speeds. To evaluate the performances of the intelligent\nnavigation algorithms, different trajectories are used and simulated using MATLAB software and SIMIAM navigation platform.\nSimulation results show the performances of the intelligent navigation algorithms in terms of simulation times and travelled path....
This paper proposes a new plant-inspired optimization algorithm for multilevel threshold image segmentation, namely, hybrid\nartificial root foraging optimizer (HARFO), which essentially mimics the iterative root foraging behaviors. In this algorithm\nthe new growth operators of branching, regrowing, and shrinkage are initially designed to optimize continuous space search\nby combining root-to-root communication and coevolution mechanism. With the auxin-regulated scheme, various root growth\noperators are guided systematically. With root-to-root communication, individuals exchange information in different efficient\ntopologies, which essentially improve the exploration ability. With coevolution mechanism, the hierarchical spatial population\ndriven by evolutionary pressure of multiple subpopulations is structured, which ensure that the diversity of root population is well\nmaintained.The comparative results on a suit of benchmarks show the superiority of the proposed algorithm. Finally, the proposed\nHARFO algorithm is applied to handle the complex image segmentation problem based on multilevel threshold. Computational\nresults of this approach on a set of tested images show the outperformance of the proposed algorithm in terms of optimization\naccuracy computation efficiency....
A flexible software LDPC decoder that exploits data parallelism for simultaneous multicode words decoding on the mobile device\nis proposed in this paper, supported by multithreading on OpenCL based graphics processing units. By dividing the check matrix\ninto several parts to make full use of both the local memory and private memory on GPU and properly modify the code capacity\neach time, our implementation on a mobile phone shows throughputs above 100Mbps and delay is less than 1.6 millisecond in\ndecoding, which make high-speed communication like video calling possible. To realize efficient software LDPC decoding on the\nmobile device, the LDPC decoding feature on communication baseband chip should be replaced to save the cost andmake it easier\nto upgrade decoder to be compatible with a variety of channel access schemes....
This research aims to develop a model to enhance lymphatic diseases diagnosis by the use of random\nforest ensemble machine-learning method trained with a simple sampling scheme. This study\nhas been carried out in two major phases: feature selection and classification. In the first stage, a\nnumber of discriminative features out of 18 were selected using PSO and several feature selection\ntechniques to reduce the features dimension. In the second stage, we applied the random forest\nensemble classification scheme to diagnose lymphatic diseases. While making experiments with\nthe selected features, we used original and resampled distributions of the dataset to train random\nforest classifier. Experimental results demonstrate that the proposed method achieves a remarkable\nimprovement in classification accuracy rate....
Robot World Cup Initiative (RoboCup) is a worldwide competition proposed to advance research\nin robotics and artificial intelligence. It has a league called RoboCup soccer devoted for soccer robots,\nwhich is a challenge because robots are mobile, fully autonomous, multi-agents, and they\nplay on a dynamic environment. Moreover, robots must recognize the game entities, which is a\ncrucial task during a game. A camera is usually used as an input system to recognize ball, opponents,\nsoccer field, and so on. These elements may be recognized applying some tools of computational\nintelligence, for example an artificial neural network. This paper describes the application\nof an artificial neural network on middle size robotic football league, where a multilayer perceptron\nneural network is trained with the backpropagation algorithm, to classify elements on the\nimage. Each output neuron represents an entity and its output value depends on the current entity\nthat is present on the image. The results show that an artificial neural network successfully classified\nthe entities. They were recognized even when similar color entities were present on the image....
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