QUEST e-learning portal: applying heuristic evaluation,usability testing and eye tracking

Universal Access in the Information Society - In this study, the development of an e-learning portal for university students is presented. The portal is based on responsive web design which is...     

DSFMA: deeply supervised fully convolutional neural networks based on multi-level aggregation for saliency detection

Multimedia Tools and Applications - In recent years, the emergence of fully convolutional neural networks (FCNs) has delivered significant success in the field of saliency detection. Although the...     

Simultaneous Use of Runs Rules and Auxiliary Information With Exponentially Weighted Moving Average Control Charts

Quality has become a key determinant of success in all aspects of industry. Exponentially weighted moving average control chart is an important tool of statistical process control used to monitor and improve quality of industrial processes. To enhance the performance of control charts, there are many strategies including the choice of an efficient plotting statistic, the choice of an efficient sampling design, the application of runs rules, and the use auxiliary information among many others. In this study, we propose nine different signaling schemes to enhance the performance of an exponentially weighted moving average control chart for location parameter, which is based on the exploitation of auxiliary information. Performance evaluation of the proposed schemes is carried out in terms of average run length. Comparisons of proposals are made with the classical as well as the auxiliary based exponentially weighted moving average and cumulative sum charts, which indicate that the proposed schemes perform better than the comparative counterparts under discussion. Copyright © 2016 John Wiley & Sons, Ltd.     

Saturation Throughput Analysis of IEEE 802.11e EDCA Through Analytical Model

The IEEE 802.11e EDCA is designed to provide quality of support for real time applications with stringent latency and throughput requirements. Theoretical frameworks for analysis of throughput performance of wireless LAN employing exponential back-off exist extensively. Several models rely on simplification assumptions that preclude their direct applicability to the enhanced distributed coordination access (EDCA) which uses heterogeneous protocol parameters, while other models are exceedingly complex to analyze. In this paper, a tractable analytical model is proposed for saturation throughput of the IEEE 802.11e EDCA. The prioritization through channel access parameters including the AIFS and contention window is catered for within a three dimensional Markov chain. The integration of back-off counter freezing and retry limit enhance the models precision. Its validation is done by simulation on NS-2. Practical applicability of the model is established based on accuracy and computational efficiency. The model is utilized for throughput analysis of the EDCA under saturated traffic loads.     

Adaptive PI secondary control for smart autonomous microgrid systems

In this paper, the authors present a neural‐network‐based distributed secondary control to regulate the output voltage and frequency of a smart autonomous microgrid system. Generally, the secondary controller is implemented in a centralized manner using a fixed‐gain proportional‐plus‐integral controller which may perform well under certain operating conditions only. Also the failure of centralized controller implies no secondary control action for the entire system. The control technique proposed in this paper is a distributed one and makes use of neural network (NN) concept to improve the performance of system. A well‐trained NN supplies the controller with suitable gains according to each operating point. Before training the NN, evolutionary optimization technique, differential evolution, is employed to obtain the optimal gains of controller at each operating load condition which forms the training set for NN. Simulation results show that the proposed controller damps the oscillations caused by load changes, restores the output voltage and frequency of the system to their nominal values, and maintains proper load sharing property of the baseline controller. The performance of the controller is also compared with fixed‐gain controller. Copyright © 2015 John Wiley & Sons, Ltd.     

Assessing the usability and ergonomic considerations on communication technology for older Malaysians

Universal Access in the Information Society - The increasing elderly population and their specific needs have challenged communication technology developers regarding the usability of their...     

SIMULATION AND EXPERIMENTAL IMPLEMENTATION OF A NEURAL-NETWORK-BASED INTERNAL-MODEL CONTROL STRATEGY ON A REACTOR SYSTEM

The use of inverse-model-based control strategy for nonlinear system has been increasing lately. However it is hampered by the difficulty in obtaining the inverse of nonlinear systems analytically. Since neural networks has the ability to model such inverses, it has become a viable alternative. Although many simulations using neural network inverse models For controls have been reported recently, no actual experimental application has been reported on a reactor system. In this paper we describe a novel experimental application of a neural network inverse-model based control method on a partially simulated pilot plant reactor, exhibiting steady state parametric sensitivity and designed to test the use of such nonlinear algorithms. The implementation involved the control of the reactor temperature under set point changes, disturbance rejection and set point regulation with plant/model mismatches. Simulation tests on the model of the system were also carried out to enable better design of the neural network models and to highlight the differences between simulation and actual online results. The online implementation results obtained were sufficient to demonstrate the capability of applying these neural-network-based control methods in real systems.     

Numerical solution of Klein–Gordon and sine-Gordon equations by meshless method of lines

We investigate numerical solution of the one dimensional nonlinear Klein–Gordon and two-dimensional sine-Gordon equations by meshless method of lines using radial basis functions. Results are compared with some earlier work showing the efficiency of the applied method. Salient feature of this method is that it does not require a mesh in the problem domain. Multiquadric and Gaussian are used as radial basis functions, which use a shape parameter. Choice of the shape parameter is still an open problem. We explore optimal value of the shape parameter without applying any extra treatment. For multiquadric, eigenvalue stability is studied without enforcing the boundary conditions whereas for Gaussian, the boundary conditions are enforced.