A large number of diverse engineering applications are frequently modeled using different approaches, viz., a differential equation or by a transfer function and state space. All these descriptions provide a great deal of information about the system, such as stability of the system, its step or impulse response, and its frequency response.
The present paper addresses different approaches used to derive mathematical models of first and second order system, developing MATLAB script implementation and building a corresponding Simulink model. The dynamic analysis of electric circuit and system using MATLAB/Simulink has been investigated using different approaches for chosen system parameters.

Cloud computing is a type of parallel and distributed system consisting of a collection of interconnected and virtual computers. With the increasing demand and benefits of cloud computing infrastructure, different computing can be performed on cloud environment. One of the fundamental issues in this environment is related to task scheduling. Cloud task scheduling is an NP-hard optimization problem, and many meta-heuristic algorithms have been proposed to solve it. A good task scheduler should adapt its scheduling strategy to the changing environment and the types of tasks. In this paper a cloud task scheduling policy based on ant colony optimization algorithm for load balancing compared with different scheduling algorithms has been proposed. Ant Colony Optimization (ACO) is random optimization search approach that will be used for allocating the incoming jobs to the virtual machines. The main contribution of our work is to balance the system load while trying to minimizing the make span of a given tasks set. The load balancing factor, related to the job finishing rate, is proposed to make the job finishing rate at different resource being similar and the ability of the load balancing will be improved. The proposed scheduling strategy was simulated using Cloudsim toolkit package. Experimental results showed that, the proposed algorithm outperformed scheduling algorithms that are based on the basic ACO or Modified Ant Colony Optimization (MACO).

Jitter is one of the most important parameters in design of delay locked loop (DLL) based frequency synthesizer. In this paper noise and mismatches of conventional delay cells which are mainly used in the DLLs architecture are introduced completely. First, time domain equations related to noise and mismatches of conventional delay cells are reported. Then, these equations are used to calculate jitter of DLL due to mismatch and noise of delay cells. At last closed form equations are obtained which can be used in the designing of low jitter DLLs. To validate these equations, a conventional DLL is designed in TSMC 0.18um CMOS Technology.

Rapid developments in information technology and Web 2.0 have provided a platform for the evolution of terrorist organizations, extremists from a traditional pyramidal structure to a technology enabled networked structure. Growing presence of these subversive groups on social networking sites has emerged as one of the prominent threats to the society, governments and law enforcement agencies across the world. Identifying messages relevant to the domain of security can serve as a stepping stone in criminal network analysis. In this paper, we deploy a rule based approach for classifying messages in Twitter which can also successfully reveal overlapping clusters. The approach incorporates dictionaries of enriched themes where each theme is categorized by semantically related words. The message is vectorized according to the security dictionaries and is termed as ‘Security Vector’. The documents are classified in categories on the basis of security associations. Further, the approach can also be used along the temporal dimension for classifying messages into topics and rank the most prominent topics of conversation at a particular instance of time. We further employ social network analysis techniques to visualize the hidden network at a particular time. Some of the results of our approach obtained through experiment with information network of Twitter are also discussed.

This paper presents an improved version of a harmony meta-heuristic algorithm, (IHSCH), for solving the linear assignment problem. The proposed algorithm uses chaotic behavior to generation a candidate solution in a behavior similar to acoustic monophony. Numerical results show that the IHSCH is able to obtain the optimal results in comparison with traditional methods (the Hungarian method). However, the benefit of the proposed algorithm is its ability to obtain the optimal solution within less computation in comparison with the Hungarian method.

In the present paper, a new fuzzy inaccuracy measure is proposed to measure the inaccuracy of a fuzzy set with respect to another fuzzy set. This measure is a modified version of fuzzy inaccuracy proposed in our earlier work. The measure is demonstrated to satisfy some interesting properties, which prepare ground for applications in multi-criteria decision making problems. A method to solve multi-criteria decision making problems with the help of new measure is developed. Finally, a numerical example is given to illustrate the proposed method to solve multi-criteria decision-making problem under fuzzy environment.

To get maximum performance on the many-core graphics processors, it is important to have an even balance of the workload so that all processing units contribute equally to the task at hand. This can be hard to achieve when the cost of a task is not known beforehand and when new sub-tasks are created dynamically during execution. Both the dynamic load balancing methods using Static task assignment and work stealing using deques are compared to see which one is more suited to the highly parallel world of graphics processors. They have been evaluated on the task of simulating a computer move against the human move, in the famous four in a row game. The experiments showed that synchronization can be very expensive, and those new methods which use graphics processor features wisely might be required.

In an environment characterized by its competitiveness, managing and monitoring relationships with suppliers are of the essence. Supplier management includes supplier segmentation. Existing literature demonstrates that suppliers are mostly segmented by computing their aggregated scores, without taking each supplier’s criterion value into account. The principle aim of this paper is to propose a supplier segmentation method that compares each supplier’s criterion value with exactly the same criterion of other suppliers. The Fuzzy Linguistic Preference Relations (LinPreRa) based Analytic Hierarchy Process (AHP) is first used to find the weight of each criterion. Then, Fuzzy c-means algorithm is employed to cluster suppliers based on their membership degrees. The obtained results show that the proposed method enhances the quality of the previous findings.

In this work, we dealt with the tracking of single object in a sequence of frames either from a live camera or a previously saved video. A moving object is detected frame-by-frame with high accuracy and efficiency using Median approximation technique. As soon as the object has been detected, the same is tracked by kalman filter estimation technique along with a more accurate Template Matching algorithm. The templates are dynamically generated for this purpose. This guarantees any change in object pose which does not be hindered from tracking procedure. The system is capable of handling entry and exit of an object. Such a tracking scheme is cost effective and it can be used as an automated video conferencing system and also has application as a surveillance tool. Several trials of the tracking show that the approach is correct and extremely fast, and it's a more robust performance throughout the experiments.

Continuum robot manipulators are optimized to meet best trajectory requirements. Closed loop control is a key technology that is used to optimize the system output process to achieve this goal. In order to conduct research in the area of closed loop control, a control oriented cycle-to-cycle continuum robot model, containing dynamic model information for each individual continuum robot manipulator, is a necessity. In this research, the continuum robot manipulator is modeled according to information between joint variable and torque, which is represented by the nonlinear dynamic equation. After that, a multi-input-multi-output baseline computed torque control scheme is used to simultaneously control the torque load of system to regulate the joint variables to desired levels. One of the most important challenge in control theory is on-line tuning therefore fuzzy supervised optimization is used to tune the modified baseline and computed torque control coefficient. The performance of the modified baseline computed torque controller is compared with that of a baseline proportional, integral, and derivative (PID) controller.