The urinary system is the organ system responsible for the production, storage and elimination of urine. This system includes kidneys, bladder, ureters and urethra. It represents the major system which filters the blood and any imbalance of this organ can increases the rate of being infected with diseases. The aim of this paper is to evaluate the performance of different variants of Support Vector Machines and k-Nearest Neighbor with different distances and try to achieve a satisfactory rate of diagnosis (infected or non-infected urinary system). We consider both diseases that affect the urinary system: inflammation of urinary bladder and nephritis of renal pelvis origin. Our experimentation will be conducted on the database “Acute Inflammations Data Set” obtained from UCI Machine Learning Repository. We use the following measures to evaluate the results: classification accuracy rate, classification time, sensitivity, specificity, positive and negative predictive values.

Image segmentation is a basic work in the field of image analysis and computer vision. Thresholding is one of the simplest methods of image segmentation. In general, thresholding approaches based on 1-D histogram do not make use of any space adjacent information of the image, thus it is often ruined by noise; thus, thresholding methods based on 2-D histogram are put forward. These methods have better segmentation performance, but heavy computation is required with these methods. In the paper, to improve the running efficiency of thresholding methods based 2D histogram, ant colony optimization algorithm combined with genetic algorithm are employed to speed up these methods, which view 2-D histogram based thresholding as a kind of optimization problem. The proposed method has been conducted on some images. Experiments results display that the proposed approach is able to achieve improved search performance which is an efficient method and suitable for real time applications.

The cardinality of fuzzy sets was introduced by DeLuca and termini, Zadeh and Tripathy et al, where the first one is a basic one, the second one is based on fuzzy numbers and the final one introduces a bag theoretic approach. The only approach to find the cardinality of an intuitionistic fuzzy set is due to Tripathy et al. In this paper, we introduce a bag theoretic approach to find the cardinality of intuitionistic fuzzy set, which extends the corresponding definition of fuzzy sets introduced by Tripathy et al. In fact three types of intuitionistic fuzzy counts are introduced and we also establish several properties of these count functions.

Robot navigation is challenging for mobile robots technology in environments with maps. Since finding an optimal path for the agent is complicated and time consuming, path planning in robot navigation is an axial issue. The objective of this paper is to find a reasonable relation between parameters used in the path planning algorithm in a platform which a robot will be able to move from the start point in a dynamic environment with map and plan an optimal path to specified goal without any collision with moving and static obstacles. For this purpose, an asymptotically optimal version of Rapidly-exploring Random Tree RRT algorithm, named RRT* is used. The algorithm is based on an incremental sampling which covers the whole space and acts fast. Moreover this algorithm is computationally efficient, therefore it can be used in multidimensional environments. The obtained results indicate that a feasible path for mobile holomonic robot may be found in a short time by using this algorithm. Also different standard distances measurements like (Chebyshev, Euclidean, and City Block) are examined, and coordinated with sampling node number in order to reach the suitable result based on environment circumstances.

Combining with the TE30 electric forklift produced by an enterprise, the principle of Steer-by-wire (SBW) system, steering motion state, ideal steering ratio are analyzed and studied. The biggest characteristic of SBW system is that the transmission ratio is free to design. Based on the establishment of two-degree-freedom linear model of Forklift, the paper designed the nonlinear transmission ratio function on vehicle speed and steering angle with the application of fuzzy control rules. The simulation results show that the fuzzy variable transmission ratio can make the yaw velocity gain tend to be constant, also can make Forklift light sensitive at low speeds and steady heavy at high speed. In order to ensure that the yaw velocity gain does not vary with the change of speed and steering angle, this paper presents a dynamic correction control strategy based on the steady-state control for Forklift. The simulation results show that the amplitudes of yaw velocity and sideslip angle are reduced with the dynamic correction of yaw velocity feedback, also the handling stability is improved.

This paper proposes nonlinear adaptive filter-bank (NAFB) based algorithm for inverse modeling of nonlinear systems. Inverse modeling has been an important component for sensor linearization, adaptive control, channel equalization in communication system and active noise control. Under practical situations, the plant/system behaves nonlinearly which can be modeled as both parallel and cascaded structures of linear and nonlinear transfer functions. These linear and nonlinear transfer functions can be either static or dynamic, time variant or time invariant. The proposed NAFB algorithms are applied to generate the inverse model of different types of nonlinear systems and their convergence performances are evaluated. These nonlinear inverse models can be suitably applied to many engineering applications.

This paper has focused on the different image enhancement techniques. Image enhancement has found to be one of the most important vision applications because it has ability to enhance the visibility of images. It enhances the quality of poor pictures. Distinctive procedures have been proposed so far for improving the quality of the digital images. To enhance picture quality image enhancement can specifically improve and limit some data presented in the input picture. It is a kind of vision system which reductions picture commotion, kill antiquities, and keep up the informative parts. Its object is to open up certain picture characteristics for investigation, conclusion and further use. The main objective of this paper is to modify the DBLA using the dark channel prior and CLAHE to enhance the results further. The comparative analysis has shown the significant improvement over the CLAHE and the DBLA.

In this paper, we develop an intuitionistic fuzzy optimization (IFO) approach for optimizing the design of plane truss structure with multiple objectives subject to a specified set of constraints. In this optimum design formulation, the objective functions are the weight of the truss and the deflection of loaded joint; the design variables are the cross-sections of the truss members; the constraints are the stresses in members. A classical truss optimization example is presented here in to demonstrate the efficiency of the Intuitionistic fuzzy optimization approach. The test problem includes a three-bar planar truss subjected to a single load condition. This multi-objective structural optimization model is solved by fuzzy optimization approach as well as intuitionistic fuzzy optimization approach. Numerical example is given to illustrate our approach. The result shows that the IFO approach is very efficient in finding the best discovered optimal solutions.