Engineering studies consist of two parts: theory lectures and laboratory practices. Effectiveness of laboratories plays an important role in providing necessary design skills. However, evaluation of laboratories can be subjective and inconsistent. Consequently, a criterion is required to evaluate the engineering laboratories. This paper proposes an evaluation criterion for assessing the effectiveness of engineering laboratories in terms of pedagogic aspects. The identified pedagogic aspects in this paper are: relationship between theory and laboratory practice, content level, activity level, learning environment and laboratory manual. We evaluated seven different laboratories and generated recommendations based on our evaluation results.
The thin‐client computing model has the potential to significantly increase the performance of mobile computing environments. By delivering any application through a single, small‐footprint client (called a thin client) implemented on a mobile device, it is possible to optimize application performance without the need for building wireless application gateways. We thus present two significant contributions in the area of wireless thin‐client computing. Firstly, a mathematical performance model is derived for wireless thin‐client system. This model identifies factors that affect the performance of the system and supports derivation and analysis of adaptation strategies to maintain a user‐specified quality of service (QoS). Secondly, a proxy‐based adaptation framework is developed for wireless thin‐client systems, which dynamically optimizes performance of a wireless thin client via dynamically discovered context. This is implemented with rule‐based fuzzy logic that responds to variations in wireless link bandwidth and client processing power. Our fuzzy inference engine uses contextual data to dynamically optimize tradeoffs among different quality of service parameters offered to the end users. Additionally, our adaptation framework uses highly scalable wavelet‐based image coding to provide scalable QoS that can degrade gracefully. Our thin‐client adaptation framework shields the user from ill effects of highly variable wireless network quality and mobile device resources. This improves performance of active applications, in which the display changes frequently. Further, active application behaviour may produce high transmission latency for screen updates, which can adversely affect user perception of QoS, resulting in poor interactivity. We report measured adaptive performance under realistic mobile device and network conditions for several different clients and servers. Copyright © 2008 John Wiley & Sons, Ltd.
SummaryIn this paper, we address the issue of multi-user receiver design in realistic multi-cellular and multi-rate CDMA systems based on performance analysis. We consider the multi-user detection (MUD) technique, denoted interference subspace rejection (ISR), because it offers a wide range of canonic suppression modes that range in performance and complexity between interference cancellers and linear receivers. To further broaden our study, we propose a modified ISR scheme called hybrid ISR to cope better with multi-rate transmissions. The performance analysis, which is based on the Gaussian assumption (GA) and validated by simulations, takes into account data estimation errors, carrier frequency mismatch, imperfect power control, identification errors of time-varying multipath Rayleigh channels and intercell interference. This analysis enables us to optimize the selection of the MUD mode for multi-rate transmissions in different operating conditions. The effectiveness of interference cancellation is indeed investigated under different mobile speeds, numbers of receiving antennas, near-far situations, channel estimation errors, and out-cell to in-cell interference ratios. This investigation suggests that the out-of-cell interference, the residual in-cell interference, the noise enhancement as well as low mobility favor the simplest MUD modes as they offer the best performance/complexity tradeoffs.
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