Rohanin Ahmad

Review and Modeling of Vegetation Propagation Model for Wireless Sensor Networks Using Omnet

In simulation environments, prediction of path losses, maximum communication coverage for each node and received signal strength are calculated by using propagation model. However, most of the simulation tools only offer simple propagation model that neglected obstacles in the propagation environment. This paper reviews a variety of more realistic propagation models for Wireless Sensor Networks and discusses the modeling of vegetation propagation model in OMNeT++ simulation platform. Result shows that propagation model used gives significant impact toward network performances.

Outdoor Propagation Analysis for LR-WPAN IEEE 802.15.4

This paper presents a preliminary study to obtain the propagation characteristics for IEEE 802.15.4 Low Rate-Wireless Personal Area Network (LR-WPAN). Two units of Wireless Sensor Networks Nodes (WSNs) were used in this study. Data collection was performed at a wide outdoor area with the nodes being positioned in a vertical and horizontal positions. For each position, the received powers were measured at distances of 10, 20, 30 and 40 m. The collected data were analysed based on their received power, Packet Error Rate (PER) and statistics. The results show that nodes positions have significant effects on the signal propagation. Generally, vertical position produced better performance compared to horizontal position.

Solving Optimal Control Problem Using Max-Min Ant System

An improved ant colony algorithm for optimal control problems with box constrain on control functions is presented. The hypercube of the feasible controls as well as the time interval are initially discretized to approximate control problem into a discrete parameter selection problem. Then, the ant colony algorithm is applied to search for optimum parameters of approximated problem while a proper local search is also introduced to iteratively enhance the quality of solution. The results of numerical simulation on MATLAB environment illustrate the effectiveness of this method.

Constrained artificial bee colony algorithm for optimization problems

Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence algorithm that has attracted great deal of attention from researchers in recent years with the advantage of less control parameters and strong global optimization ability. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. This drawback can be even more significant when constraints are also involved. To address this issue, an Enhanced Constrained ABC algorithm (EC-ABC) is proposed for Constrained Optimization Problems (COPs) where two new solution search equations are introduced for employed bee and onlooker bee phases respectively. In addition, both chaotic search method and opposition-based learning mechanism are employed to be used in population initialization in order to enhance the global convergence when producing initial population. This algorithm is tested on several benchmark functions where the numerical results demonstrate that the EC-ABC is competitive with state of the art constrained ABC algorithm.

Design of a capacitive sensor for oil palm fresh fruit bunch maturity grading

Automatic grading of oil palm fresh fruit bunch is desired. In this study, a capacitive sensing system was designed and developed for the purpose of grading oil palm fresh fruit bunch. In this method, oil palm fresh fruit bunch placed between capacitive plates as a dielectric material and then measure the resulting capacitance voltage. Experiments were carried out using oil palm bunches of Tenera variety. Ripe and unripe mature bunches tested with 100 kHz sinusoidal frequencies. Correlation of capacitive response observed to be linear to bunch weight and negative linear to bunch ripeness. This result suggest that this method be explored for automatic grading of oil palm fresh fruit bunch.

Permeability parameter as a function of population density in classical infiltration equation

Rapid development of urban areas has caused many problems especially related to water issues. The increase in urban development also means the increase in impervious surfaces due to expansion of buildings, roads, parking lots to name a few. Impervious surfaces have low water permeability compared to pervious surfaces. Also, infiltration capacity is dependent on the permeability of the area and subsequently permeability is dependent on the surface conditions. In this paper, we study the infiltration capacity with the assumption that permeability parameter can be described in the term of the population density of the area. The modified model is based on the original form of Green-Ampt equation. The new model with population density is able to describe permeability, hence the infiltration capacity of an area.

A hybrid optimization method for constrained optimal control problem

A new hybrid algorithm by integrating a nested partitions (NP) method with successive quadratic programming (SQP) is presented for global optimization of general optimal control problems involving lumped parameter system. The control parameterization technique first employed to reduce the control problem into a parameter selection problem. Then, in the global phase a vicinity of global optimizer is approximated by an appropriate NP method. Subsequently, the SQP algorithm in the local phase promotes the accuracy of final solution. The effectiveness of the hybrid NP-SQP algorithm is also illustrated by means of numerical simulations. I. INTRODUCTION In the early years of optimal control theory traditional methods based on calculus of variations could furnish some relatively simple problems with an analytical solution. As the analytical solution might not always be available, researchers have been interested in computational method for optimal control problems, yet when reliable and powerful computers became everywhere available, it was the end of an era. The software environments have become a platform for implementation of many practical methods to solve arising control problems. The iterative traditional methods both directly (3) or indirectly (using the Pontryagins minimum principle) (8) rely on gradient information, and perform efficiently for convex problems, otherwise the performance of these methods highly depend on selected initial solution. As an alternative to approximate a solution for complex nonconvex problems, many metaheuristic methods have been proposed (4). In general, these methods iteratively sample amongst potential solutions, and the search is directed using the value of the objective function only, hence reducing the need for gradient information. Moreover, as metaheuristic methods globally search for optima, they are usually characterized as global optimizer due to their capability to efficiently arrive at the vicinity of a global optimum. Nested partitions (NP) (10) is an exemplary method in this category, where concisely described in the third section. We use this method to globally search for optimal control for the class of the control problems described in the next section. Then, in the subsequent sections we propose the hybrid NP-SQP algorithm. II. THE CONTROL PROBLEMS In this study, we consider a general optimal control problem where the system of dynamics is described by a first-order ordinary differential equation (ODE),