Exploring the adoption and implementation of discrete and integrated IT systems: A Framework for analysis

Despite the substantial organisational benefits of integrated IT, the implementation of such systems – and particularly Enterprise Resource Planning (ERP) systems – has tended to be problematic, stimulating an extensive body of research into ERP implementation. This research has remained largely separate from the main IT implementation literature. At the same time, studies of IT implementation have generally adopted either a factor or process approach; both have major limitations. To address these imitations, factor and process perspectives are combined here in a unique model of IT implementation. We argue that • the organisational factors which determine successful implementation differ for integrated and traditional, discrete IT • failure to manage these differences is a major source of integrated IT failure. The factor/process model is used as a framework for proposing differences between discrete and integrated IT.

Convergence of the iterative algorithm for a general Hammerstein system identification

The convergence of the iterative identification algorithm for a general Hammerstein system has been an open problem for a long time. In this paper, it is shown that the convergence can be achieved by incorporating a regularization procedure on the nonlinearity in addition to a normalization step on the parameters.

Dynamic evolution of the genetic search region through fuzzy coding

A technique for automatic exploration of the genetic search region through fuzzy coding (Sharma and Irwin, 2003) has been proposed. Fuzzy coding (FC) provides the value of a variable on the basis of the optimum number of selected fuzzy sets and their effectiveness in terms of degree-of-membership. It is an indirect encoding method and has been shown to perform better than other conventional binary, Gray and floating-point encoding methods. However, the static range of the membership functions is a major problem in fuzzy coding, resulting in longer times to arrive at an optimum solution in large or complicated search spaces. This paper proposes a new algorithm, called fuzzy coding with a dynamic range (FCDR), which dynamically allocates the range of the variables to evolve an effective search region, thereby achieving faster convergence. Results are presented for two benchmark optimisation problems, and also for a case study involving neural identification of a highly non-linear pH neutralisation process from experimental data. It is shown that dynamic exploration of the genetic search region is effective for parameter optimisation in problems where the search space is complicated.

Identification and control of Hammerstein systems via wireless networks

This paper investigates a systematic approach for the identification and control of Hammerstein systems over a physical IEEE 802.11b wireless channel.

Clustered indexing for branch predictors

As a result of resource limitations, state in branch predictors is frequently shared between uncorrelated branches. This interference can significantly limit prediction accuracy. In current predictor designs, the branches sharing prediction information are determined by their branch addresses and thus branch groups are arbitrarily chosen during compilation. This feasibility study explores a more analytic and systematic approach to classify branches into clusters with similar behavioral characteristics. We present several ways to incorporate this cluster information as an additional information source in branch predictors.

Feedforward Control of Shape Memory Alloy Actuators Using Fuzzy-Based Inverse Preisach Model

This brief investigates a possible application of the inverse Preisach model in combination with the feedforward and feedback control strategies to control shape memory alloy actuators. In the feedforward control design, a fuzzy-based inverse Preisach model is used to compensate for the hysteresis nonlinearity effect. An extrema input history and a fuzzy inference is utilized to replace the inverse classical Preisach model. This work allows for a reduction in the number of experimental parameters and computation time for the inversion of the classical Preisach model. A proportional-integral-derivative (PID) controller is used as a feedback controller to regulate the error between the desired output and the system output. To demonstrate the effectiveness of the proposed controller, real-time control experiment results are presented.

Variable selection via RIVAL and its application in nuclear material detection

In many situations, the number of data points is fixed, and the asymptotic convergence results of popular model selection tools may not be useful. A new algorithm for model selection, RIVAL (removing irrelevant variables amidst Lasso iterations), is presented and shown to be particularly effective for a large but fixed number of data points. The algorithm is motivated by an application of nuclear material detection where all unknown parameters are to be non-negative. Thus, positive Lasso and its variants are analyzed. Then, RIVAL is proposed and is shown to have some desirable properties, namely the number of data points needed to have convergence is smaller than existing methods.

Non-parametric nonlinear system identification: A data-driven orthogonal basis function approach

In this paper, a data driven orthogonal basis function approach is proposed for non-parametric FIR nonlinear system identification. The basis functions are not fixed a priori and match the structure of the unknown system automatically. This eliminates the problem of blindly choosing the basis functions without a priori structural information. Further, based on the proposed basis functions, approaches are proposed for model order determination and regressor selection along with their theoretical justifications. © 2008 IEEE.

Max separation clustering for feature extraction from Optical Emission Spectroscopy Data

This paper proposes max separation clustering (MSC), a new non-hierarchical clustering method used for feature extraction from optical emission spectroscopy (OES) data for plasma etch process control applications. OES data is high dimensional and inherently highly redundant with the result that it is difficult if not impossible to recognize useful features and key variables by direct visualization. MSC is developed for clustering variables with distinctive patterns and providing effective pattern representation by a small number of representative variables. The relationship between signal-to-noise ratio (SNR) and clustering performance is highlighted, leading to a requirement that low SNR signals be removed before applying MSC. Experimental results on industrial OES data show that MSC with low SNR signal removal produces effective summarization of the dominant patterns in the data.

High performance IP lookup circuit using DDR SDRAM

DDR-SDRAM based data lookup techniques are evolving into a core technology for packet lookup applications for data network, benefitting from the features of high density, high bandwidth and low price of DDR memory products in the market. Our proposed DDR-SDRAM based lookup circuit is capable of achieving IP header lookup for network line-rates of up to 10Gbps, providing a solution on high-performance and economic packet header inspections. ©2008 IEEE.

Amplitude-modulation characteristics of power-combining Class-E amplifier with finite choke

Power back-off performances of a new variant power-combining Class-E amplifier under different amplitude-modulation schemes such as continuous wave (CW), envelope elimination and restoration (EER), envelope tracking (ET) and outphasing are for the first time investigated in this study. Finite DC-feed inductances rather than massive RF chokes as used in the classic single-ended Class-E power amplifier (PA) resulted from the approximate yet effective frequency-domain circuit analysis provide the wherewithal to increase modulation bandwidth up to 80% higher than the classic single-ended Class-E PA. This increased modulation bandwidth is required for the linearity improvement in the EER/ET transmitters. The modified output load network of the power-combining Class-E amplifier adopting three-harmonic terminations technique relaxes the design specifications for the additional filtering block typically required at the output stage of the transmitter chain. Qualitative agreements between simulation and measurement results for all four schemes were achieved where the ET technique was proven superior to the other schemes. When the PA is used within the ET scheme, an increase of average drain efficiency of as high as 40% with respect to the CW excitation was obtained for a multi-carrier input signal with 12 dB peak-to-average power ratio. © 2011 The Institution of Engineering and Technology.

Design of interlock-free combined allocators for Networks-on-Chip

This paper presents a thorough investigation of the combined allocator design for Networks-on-Chip (NoC). Particularly, we discuss the interlock of the combined NoC allocator, which is caused by the lock mechanism of priority updating between the local and global arbiters. Architectures and implementations of three interlock-free combined allocators are presented in detail. Their cost, critical path, as well as network level performance are demonstrated based on 65-nm standard cell technology.