Wireless communications makes the delivery of real time information at hands. This includes information from Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. In this paper, the focus will be on the flow of traffic across number of adjacent Road Side Units (RSU) in various intersections. The objective is to allow RSUs' (I2I) cooperation by exchanging information that is originally collected from vehicles through (V2I). Advanced knowledge of the moving vehicles will lead to better traffic management at intersections and will reduce waiting time
Simulations on Vehicular Ad Hoc Network (VANET) relies on many parameters such as speed, driving skills, lane changing, etc. It is desirable to reproduce such conditions in a simulation environment. Recently, we have seen lots of developments in this area for example projects like OMNet++, Network Simulator 3, OPNET, and others. All these projects require a way to import real data from map sources to make the model more realistic. A road or highway with its main conditions is today feasible with many collaborators in projects like OpenStreetMap which offers map data for research which must be imported into a simulation scenario. We propose a procedure to achieve this with SUMO (Simulation of Urban Mobility) so that it generates a network mobility file that could be used for further studies in VANET simulations. In this procedure, a quantity of vehicles and inherent features of exported maps are considered.
Project management is critical for companies to stay competitive which make material and human resources management an issue of increasing importance. The project management scheduling process of deciding when an activity start and how resources will be used will highly impact the project duration and cost. Resource-constrained project scheduling problem (RCPSP) considers activities of known durations linked by precedence relations and resource requests from resources of limited availability to find a schedule of minimal duration. Traditionally, the RCPSP considered the objective of makespan minimization to plan the overall project; however, since the value of money decreases with time, it is critical to incorporate the financial aspect of the project and schedule the activities in such a way that will maximize the profit. In this work, we will propose a mathematical model for the multi-mode resource-constrained project scheduling problem with material ordering to maximize the net present value (MMRCSPMODC). The problem will be subjected to precedence constrains, project completion constraints and materials constraints as well as penalties that will be imposed in the case of any delays. Project scheduling and material ordering decisions will be emphasized to determine the time and quantity of an order since setting the material ordering decisions after the project scheduling phase leads to non-optimal solutions. In addition to the developing the mathematical model, we will propose a heuristic approach to obtain near optimal solution since the problem under study is NP-hard.
This work considers a design model for a Fractional Slot Concentrated Winding (FSCW) Permanent Magnet Synchronous Machine (PMSM) for an Electric Vehicle (EV) to obtain a minimal loss and machine mass. A population-based multi- objective optimization design is utilized to design and determine the machine parameters. The results of the optimization show there is an inverse relation between the total loss and total mass of the machine. Validation of the results is achieved by means of two dimensional Finite Element Analysis (FEA).
The goal of this work is to present a suitable hardware realization for an artificial neuron with a sigmoid activation function and fixed-point data representation. Therefore, this paper presents all the fixed-point arithmetical operations needed to realize a neuron with a sigmoid activation function. In addition, the paper summarizes the different hardware implementations of the required operations on Field Programmable Gate Array (FPGA). All in all, the paper provides an analysis of the different implementation possibilities.
In this paper, Load Frequency Control (LFC) is designed to a single-area power grid connected to a photovoltaic (PV) system. Both the power grid and the PV systems have been modeled separately. Three controllers have been designed for this connected system: Linear Quadratic Regulator (LQR), PI, and Fuzzy Logic Controller (FLC) to regulate the error of frequency deviation. A comparison has been carried out between the three methods to check the best performance in terms of settling time, undershoot and steady state error. The criteria to be met in the power plant according to UAE standards are settling time less than 3s, undershoot less than 0.02 Hz and a steady state error of 0. LQR met all three criteria for the system under study, FLC improved the system response greatly and is useful for systems with complex models, while the PI did not meet two of the specifications required.
This article elaborates the novel approach for air-gap magnetic field analysis of switched reluctance motor in case of rotor cracks and rotor tilt around its shaft axis. The fault diagnosis is illustrated on the basis of a 3-D model of the SRM using of a technique known as finite element analysis (FEA). The flux linkage analytical equations are used for the derivation of inductance expressions. The results obtained from the 3-D FEA of a SRM having 6 stator and 4 rotor poles shows the variation of mutual inductance with the cracked rotor conditions and the tilting of rotor shaft. The results obtained explain the usefulness for the detection of cracked rotors and shaft tilting.
Satellites have tangible impact on our daily lives; they revolutionized our everyday living. Satellite batteries are expected to deliver the power demand at any time during the period of an eclipse or when the power received from the solar panel is not sufficient. This study is performed in order to develop a scheduling algorithm that augments the runtime/lifetime of the battery; which will consequently aim on diminishing the State of Health (SOH) degradation of the battery. Data will be collected for an existing satellite, such as Nayif-1, in order to analyze battery behavior in space. In parallel, an accurate State of Charge (SOC) estimation technique will be simulated and validated. Finally, a simulation model through Matlab will be also developed to compare and validate the results.
Prediction is basically about making claims of the future based on past information and current state. Predicting demand for the future can help many service organizations to adjust their resources thus reach their goals. In this paper, a complete framework for predicting workforce demand in service organizations using several techniques is provided. Moreover, two case scenarios of two service organizations requiring forecasting of demand are discussed. Also, this paper provides an initial test results of applying Moving average, Linear regression and Neural network techniques.
Accurate estimation of wind speed probability density distribution at a relevant wind generation site is crucial in maximizing the yield of the wind farm, and optimally utilize clean sources of energy. This goal calls for devising models with adaptable algorithms that accurately fit wind speed distributions regardless of the wind farm location and the distribution type. In this paper, the performance of the Kernel Density Estimation wind speed model is compared with that of a Gaussian Mixture Model, in which the optimal number of components of the Gaussian mixture model probability density function is obtained using the Bayesian Information Criterion approach.
