Confidence intervals for dependent data: Equating non-overlap with statistical significance

We revisit the problem of determining confidence interval widths for the comparison of means. For the independent two-sample (two-sided) case, Goldstein and Healy (1995) draw attention to the fact that comparisons based on 95% error bars are not very effective in assessing the statistical significance of the difference in means and derive the correct confidence interval for such a comparison. We provide an extension to Goldstein and Healy (1995) to account for the correlation structure and unequal variances. We use the results to develop rules of thumb for evaluating differences, in an exploratory manner, like Moses (1987) and Cumming (2009), from the independent case. We illustrate the method for the simple comparison of two means in a real data set, provide R code that may be easily implemented in practice, and discuss the extension of the method to other applied problems.     

MLP bilinear separation

In this paper, we present a thorough mathematical analysis of the use of neural networks to solve a specific classification problem consisting of a bilinear boundary. The network under consideration is a three-layered perceptron with two hidden neurons having the sigmoid serving as the activation function. The analysis of the hidden space created by the outputs of the hidden neurons will provide results on the network’s capacity to isolate two classes of data in a bilinear fashion, and the importance of the value of the sigmoid parameter is highlighted. We will obtain an explicit analytical function describing the boundary generated by the network, thus providing information on the effect each parameter has on the network’s behavior. Generalizations of the results are obtained with additional neurons, and a theorem concerned with analytical reproducibility of the boundary function is established.     

Performance modeling,real-time dispatching and simulation of wafer fabrication systems using timed extended object-oriented Petri nets

Semiconductor wafer fabrication system (SWFS) is the most complex and capital-intensive phase in the entire semiconductor manufacturing cycle. With characteristics of re-entrant processing routes, equipment uncertainty, product diversity and improving technologies, great challenges are presented in SWFS’s modeling, scheduling and simulation. To implement efficient production control, this paper provides a timed extended object-oriented Petri nets (TEOPNs) approach to performance modeling, real-timed dispatching and simulation of SWFSs. The TEOPNs models are constructed in a hierarchy to accord with the real-world SWFS’s organization, and a new type of signal place is added into the TEOPNs to respond the dynamic states of all processing facilities. A novel autonomy and coordination-based real-time dispatching mechanism (A&C-RDM) is developed in this paper, which executes under the support of the TEOPNs-based hybrid real-time dispatching control system (HRDCS). Owning to the ability of gathering dynamic real-time information of all production facilities and WIP products, the HRDCS can make adaptive dispatching decisions according to the local and global real-time processing status. Two sets of key elements of real-time dispatching, i.e. the state thresholds and dispatching rules, are defined in the HRDCS so that the A&C-RDM can integrate different types of dispatching rules. A set of simulation experiments prove the efficiency of the proposed modeling and dispatching algorithm. In summary, the proposed TEOPNs, HRDCS and A&C-RDM form the cornerstones of a real-time dispatching simulation prototype of SWFS, and the work described in this paper carries out an advanced integrated “modeling–dispatching–simulation” methodology.     

Creating change and driving innovation in highly automated and lean organizations: The Temporal Think Tank™ (T3™)

This paper introduces the concept of the temporal think tank™ (T3™), a temporary in-house research center, based on case studies with a highly automated global manufacturer and in various small-sized manufacture (SME's). The T3™ brings individuals from across the organization together in a team setting in which they are charged to look at the future, develop their decision-making skills, and use entrepreneurial thinking to incubate new processes and/or products. After an appropriate time in the temporal think tank™, the individuals are asked to return to their regular positions to implement the best practices and best ideas and doing so spur the organization forward. At intervals, the temporal think tanks™ can be reconvened, or reconstituted with new participants. This approach prepares technology champions for the SME, who can return to the organization with a fresh outlook and renewed energy to keep the enterprise at the peak of efficiency and effectiveness.     

Scheduling gain for frequency-selective Rayleigh-fading channels with application to self-organizing packet scheduling

This paper investigates packet scheduling in the context of Self-Optimizing Networks, and demonstrates how to improve coverage dynamically by adjusting the scheduling strategy. We focus on α-fair schedulers, and we provide methods for calculating the scheduling gain, including several closed form formulas. Scheduling gain is analyzed for different fading models, with a particular focus on the frequency-selective channel. We then propose a coverage-capacity self-optimization algorithm based on α-fair schedulers. A use case illustrates the implementation of the algorithm and simulation results show that important coverage gains are achieved at the expense of very little computing power.