This paper proposes a novel metaheuristic optimization algorithm and suggests an adaptive artificial neural network controller that based on the proposed optimization algorithm. The purpose of the neural controller is to track desired proposed velocities and path trajectory with the minimum error, in the presence of mobile robot parameters time variation and system model uncertainties. The proposed controller consists of two sub-neural controllers; the kinematic neural feedback controller, and the dynamic neural feedback controller. The external feedback kinematic neural controller was responsible of generating the velocity tracking signals that track the mobile robot linear and angular velocities depending on the robot posture error, and the desired velocities. On the other hand, the internal dynamic neural controller has been used to enhance the mobile robot against parameters uncertainty, parameters time variation, and disturbance noise. However, the proposed grass root population-based metaheuristic optimization algorithm has been used to optimize the weights of the neural network to have the behavior of an adaptive nonlinear trajectory tracking controller of a differential drive wheeled mobile robot. The proposed controller shows a very good ability to prepare an appropriate dynamic control left and right torque signals to drive various mobile robot platforms using the same offline optimized weights. Grass root optimization algorithms have been used due to their unique characteristics especially, theirs derivative free, ability to optimize discretely and continuous nonlinear functions, and ability to escape of local minimum solutions.

The stochastic character of asymmetrical loads in power networks emerged due to non-simultaneous activation of phases of various single-phase and poly-phase receivers, nonlinear characteristics of transformers and other reasons have caused the occurrence of currents and voltages of zero sequence. These electrical quantities with currents and voltages of direct sequence in a negative sense affect the asymmetry of phase voltages in networks on places where loads are connected. In this paper, the presented load is induction machine with coil connection in star connected to generic distribution system TN. We analyze the possibilities of simple CL structures of filter in the role of the device for correction of asymmetries to a network, which can be entered by zero sequence current occurred for some reason in induction machine (mostly non-simultaneous switching of phase coils of induction machine).

Firefly algorithm is a new and efficient intelligent algorithm proposed by Dr. Xin-She Yang at Cambridge University. In this paper, the conventional firefly algorithm will be introduced and improved using two-order oscillation. And an improved firefly algorithm based on two-order oscillation is proposed. And this method will be deduced and analyzed for astringency. Six typical functions will be tested to prove performances. Global Max/Min values in six multimodal functions could be found accurately with proposed scheme. The experiment results show our proposed method has excellent performances than conventional one.

Source code is an intellectual property and using it without author’s permission is a violation of property right. Source code authorship attribution is vital for dealing with software theft, copyright issues and piracies. Characterizing author’s signature for identifying their footprints is the core task of authorship attribution. Different aspects of source code have been considered for characterizing signatures including author’s coding style and programming structure, etc. The objective of this research is to explore another trait of authors’ coding behavior for personifying their footprints. The main question that we want to address is that “can code smells are useful for characterizing authors’ signatures? A machine learning based methodology is described not only to address the question but also for designing a system. Two different aspects of source code are considered for its representation into features: author’s style and code smells. The author’s style related feature representation is used as baseline. Results have shown that code smell can improves the authorship attribution.

Wireless sensor networks (WSNs) consist of a large number of tiny sensors with sensing, processing and transmission capabilities. Reducing energy consumption of nodes is one of the major objectives in the design of wireless sensor networks, as sensors have low power batteries. As data collection is the primary objective of WSNs and it consumes more energy, energy-efficient routing is a prominent solution to reduce the sensors energy consumption. This paper proposes an Energy-efficient and Load Distributed Clustering Algorithm (ELDCA) for routing in dense wireless sensor networks to reduce and distribute the sensors’ energy consumption. The network is divided into number of virtual congruent square grids of defined sizes. The algorithm constructs optimal and load balanced clusters at every inner crossing point of grid cells using defined cluster fitness value. As early energy depletion is a major design issue in clustering protocols, the proposed algorithm provides a local substitution for energy suffering clusterheads (CHs). To prove the excellence of the proposed algorithm, extensive simulation experiments are performed under different network scenario. The results are compared with latest routing algorithms in terms of network lifetime, energy dissemination, and energy utilization.

This research paper propose experimental support to secure Round Trip Engineering and use of security performance flexibility trusted operating systems for the designing of secure web applications. In this research paper, for security concern, we suggest use of trusted operating systems as a platform to run these web applications. In this regard, a number of trusted operating systems like Argus, Trusted Solaris, and Virtual Vault have been developed by various companies to handle the increasing need of security.
For improving the performance of same web applications, we observe that all security checks in a Trusted Operating System are not necessary. As per our suggestion, various unnecessary security checks can be skipped by administrator, so that system performance of these web applications can improve. These unnecessary security checks, system calls and operations can be easily identified at the time of requirement elicitation and Requirement Engineering. For example, as we know, the popular web servers deal with public information. In this web application, the need for security checks during reads from disk seems like a waste of CPU cycles. On the other hand the real security need for servers seems to be of the write accesses.
This research paper aims to support the efficiency of object-oriented class-based programming and object oriented modeling in secure software development.

Fuzzy clustering procedures for categorical data are proposed in the paper. Most of well-known conventional clustering methods face certain difficulties while processing this sort of data because a notion of similarity is missing in these data. A detailed description of a possibilistic fuzzy clustering method based on frequency-based cluster prototypes and dissimilarity measures for categorical data is given.

This paper proposes an advanced pitch angle control strategy based on neural network (NN) for variable speed wind turbine. The proposed methodology uses Radial Basis Function Network (RBFN) and Feed-forward based Back propagation network (BPN) algorithm to generate pitch angle. The performance of the proposed control technique is analyzed by comparing the results with Fuzzy Logic Control (FLC) and Proportional - Integral (PI) control techniques. The control techniques implemented is able to compensate the nonlinear characteristic of wind speed. The wind turbine is smoothly controlled to maintain the generator power and the mechanical torque to the rated value without any fluctuation during rapid variation in wind speed. The effectiveness of the proposed control strategy is verified using MATLAB/Simulink for 2-MW permanent magnet synchronous generator (PMSG) based wind energy conversion system.