General Data Analysis Supported SPC

The issue of autocorrelation in statistical process control (SPC) data has been and continues to be a much discussed and researched topic. In nearly all published studies and in SPC training modules, the predominate models for autocorrelation come from a class of time-series models known as autoregressive-integrated moving average (ARIMA) models. However, little attention is given to a variety of systematic patterns pervasive in SPC applications that are not adequately modeled by the ARIMA framework. In this paper, we suggest the need for an even broader perspective than defined by ARIMA models. Furthermore, we argue that effective SPC training not only requires attention to data analysis tools for modeling systematic patterns but also to tools for diagnostically checking the distributional assumptions of variable and attribute charts.     

INAR implementation of newsvendor model for serially dependent demand counts

The classic newsvendor model was developed under the assumption that period-to-period demand is independent over time. In real-life applications, the notion of independent demand is often challenged. In this paper, we propose a dynamic implementation of the newsvendor model based on a class of integer-valued autoregressive (INAR) models when facing correlated discrete demand. Motivated by application, we consider INAR models with underlying Poisson error innovations and with underlying negative-binomial error innovations to accommodate overdispersion scenarios. We numerically compare our proposal with the standard newsvendor solution and with a standard autoregressive-based newsvendor solution. Our results show that an appropriately specified INAR-based newsvendor solution not only outperforms the standard case but also the approximating forecasting approaches. Moreover, even in the presence of autocorrelation, the use of the standard autoregressive model as an approximating approach can lead to increased costs over and above the standard implementation of the newsvendor model based on no forecasting.     

Dual Watermarking for Color Images: A New Image Copyright Protection Model based on the Fusion of Successive and Segmented Watermarking

Multimedia Tools and Applications - Watermarking has been suggested as a generic technique to solve various problems associated with topics in the areas of digital rights management and multimedia...     

Stochastic characterization of upstream demand processes in a supply chain

In the supply chain management area, there has much recent attention to a phenomenon known as the bullwhip effect. The bullwhip effect represents the situation where demand variability increases as one moves up the supply chain. In this paper, we study this effect in an order-up-to supply-chain system when minimum Mean Square Error (MSE) optimal forecasting is employed as opposed to some commonly used simplistic forecasting schemes. We find that depending on the correlative structure of the demand process it is possible to reduce, or even eliminate (i.e., "de-whip"), the bullwhip effect in such a system by using an MSE-optimal forecasting scheme. Beyond the bullwhip effect, we also determine the exact time-series nature of the upstream demand processes.     

A security policy framework for context-aware and user preferences in e-services

In today’s dynamic and distributed markets a large spectrum of services is delivered through information and communication technologies. Emerging markets of e-services lie at the intersection of non-traditional user behaviour, and cyber-partnerships of enterprises to deliver innovative services. Current approaches to manage and control security demonstrate lacks in terms of security policy matching and integration in heterogeneous e-service environments. In this paper, we introduce a framework to support role-based access control for distributed services focusing on the integration of customer preferences. The framework aims to collect and generate policy-based security measures in cross-organisational scenarios. In addition to catering to specifications of security and business policies, the ability to integrate contextual information and user preferences make the role-based framework flexible and express a variety of access policies that provide a just-in-time permission activation.     

Forecast facilitated lot-for-lot ordering in the presence of autocorrelated demand

With consistent effort in setup reduction as encouraged by JIT principle, lot-for-lot ordering is gaining popularity in MRP applications. A lot-for-lot order is an immediate copy of the MPS (master production schedule) – direct reflection of demand forecasts. Since all levels of MRP plans are based on MPS, the accuracy of MRP is highly dependent of the accuracy of demand forecasting. In this paper, we are concerned about the impact of forecasting to the performance of a lot-for-lot MRP system when there is notable variability and autocorrelation in the underlying demand process (e.g., an AR(1) process). Specifically under a stationary AR(1) demand, we examine the performance of the MRP based on the most common EWMA forecast model, and then compare it with a minimum mean square error (MSE) forecast model. The notable findings of this study include: (1) MRP performance differs noticeably under the two different forecasting models. (2) The MSE-optimal forecasting performs no worse than the EWMA forecasting in all aspects of MRP applications.     

Comprehensive Characterization of an “Off/On” Rhodol-Based Lysosomal Tracker for Orthogonal Cellular Analysis by Confocal Imaging

Two florescent xanthene-cyanamide lysosomal trackers emitting strongly at ∼525 nm were prepared from fluorescein and rhodol methyl esters in microwave-assisted reactions. Both forms named “off” (nonfluorescent lactam) and “on” (strongly fluorescent ring-opened amide) have been comprehensively characterized out by using a combination of NMR spectroscopy, X-ray analysis, fluorimetry and confocal microscopy. Known rhodamines bearing electron-withdrawing groups (EWGs) exhibit an equilibrium between non-fluorescent (off) and fluorescent (on) depending on the dielectric constant of the medium. Here, cyanamide was introduced as EWG amine into the fluorescein and rhodol framework. Unlike rhodamine-type dyes, the ring-opened forms of fluorescein- and rhodol-cyanamides are stable in protic solvents under circumneutral and basic pH conditions. The osteoblastic cell line MC3T3-E1 from C57BL/6 mouse calvaria was used for confocal imaging where the different organelles and nuclei were distinguished by using an orthogonal combination of fluorescent dyes.