Leakage current in a Si-based nanopore structure and its influence on noise characteristics

We have measured leakage current in a silicon substrate-based nanopore membrane device immersed in an aqueous environment which typically shows the current level of few nA. This current level is compared with the measured current density (400 nA/cm² at 1 V) from the pristine Si wafer (p-type, 10¹⁶/cm³ boron doping) indicating that the exposed Si surface in a nanopore membrane device acts as an electrochemical reaction site. The leakage current is drastically reduced from >10 nA to <100 pA at 1 V by the deposition of a dielectric layer to the Si-based nanopore membrane device. We also noted that the root-mean-square noise of the ionic current is also reduced from 38 to 28 pA in correlation with the reduction of leakage current, indicating that electrochemical reaction provides one of the major sources of noise.     

The effect of extrudate swell on modeling the film blowing process

The extrudate swell effect has not received sufficient attention in modeling the film blowing process. This effect is addressed in this paper, and as an ab initio study, only viscous fluids were considered. The problem region was separated into two zones; the extrudate swell zone and the film blowing zone. The annular extrudate swell problem was solved using a finite element method. The film blowing process was modeled following Pearson and Petrie's (4) work. Although only viscous fluids were considered, the simulation results show a remarkable difference when swelling was included in the modeling. Viscoelastic fluids, which are more realistic for polymer melts, were not investigated here because of the so called high Weisenberg number problem. This is an open area still under investigation.     

THE SINGLE PELLET DIFFUSION REACTOR: THEORY AND APPLICATIONS

Most heterogeneous catalysts are either supported on some kind of porous material or the catalyst itself is porous. To satisfy practical constraints such as pressure drop, handling, and separation from products, these catalysts are generally pelletized. Very often the overall chemical reaction rates within these catalyst pellets are determined by a complicated interaction of internal and external transport effects with the intrinsic kinetic rate at the active surface.     

Understanding insiders: An analysis of risk-taking behavior

There is considerable research being conducted on insider threats directed to developing new technologies. At the same time, existing technology is not being fully utilized because of non-technological issues that pertain to economics and the human dimension. Issues related to how insiders actually behave are critical to ensuring that the best technologies are meeting their intended purpose. In our research, we have investigated accepted models of perceptions of risk and characteristics unique to insider threat, and we have introduced ordinal scales to these models to measure insider perceptions of risk. We have also investigated decision theories, leading to a conclusion that prospect theory, developed by Tversky and Kahneman, may be used to describe the risk-taking behavior of insiders and can be accommodated in our model. Our results indicate that there is an inverse relationship between perceived risk and benefit by insiders and that their behavior cannot be explained well by the models that are based on the traditional methods of engineering risk analysis and expected utility. We discuss the results of validating that model with forty-two senior information security executives from a variety of organizations. We also discuss how the model may be used to identify characteristics of insiders’ perceptions of risk and benefit, their risk-taking behavior and how to frame insider decisions. Finally, we recommend understanding risk of detection and creating a fair working environment to reduce the likelihood of committing criminal acts by insiders.     

A superscalar simulation employing poisson distributed stalls

This paper presents a statistical approach to estimating the performance of a superscalar processor. Traditional trace-driven simulators can take a large amount time to conduct a performance evaluation of a machine, especially as the number of instructions increases. The result of this type of simulation is typically tied to the particular trace that was run. Elements such as dependencies, delays, and stalls are all a direct result of the particular trace being run, and can differ from trace to trace. This paper describes a model designed to separate simulation results from a specific trace. Rather than running a trace-driven simulation, a statistical model is employed, more specifically a Poisson distribution, to predict how these types of delay affects performance. Through the use of this statistical model, a performance evaluation can be conducted using a general code model, with specific stall rates, rather than a particular code trace. This model allows simulations to quickly run tens of millions of instructions and evaluate the performance of a particular micro-architecture while at the same time, allowing the flexibility to change the structure of the architecture.     

Multistable electro‐optical modes in ferroelectric liquid crystals

Abstract— Multistable electro‐optical modes exist under certain conditions in ferroelectric liquid‐crystal (FLC) cells, which means that any light‐transmission level can be memorized after the driving voltage is switched off. The multistability is responsible for three new electro‐optical modes with different shapes of the gray‐scale curve that can be either S‐shaped (double or single dependent upon the applied‐voltage pulse sequence and boundary conditions) or V‐shaped dependent upon boundary conditions and FLC cell parameters. The origin of these modes will be described.     

Parametric algorithms for 2-cyclic robot scheduling with interval processing times

Consider an m-machine production line for processing identical parts served by a mobile robot. The problem is to find the minimum cycle time for 2-cyclic schedules, that is, schedules in which exactly two parts enter and two parts leave the production line during each cycle. This work treats a special case of the 2-cyclic robot scheduling problem when the robot route is given and operation durations are chosen from prescribed intervals. A strongly polynomial algorithm of time complexity O(m ⁸log m) is proposed.     

A Fast Explicit Operator Splitting Method for Passive Scalar Advection

The dispersal and mixing of scalar quantities such as concentrations or thermal energy are often modeled by advection-diffusion equations. Such problems arise in a wide variety of engineering, ecological and geophysical applications. In these situations a quantity such as chemical or pollutant concentration or temperature variation diffuses while being transported by the governing flow. In the passive scalar case, this flow prescribed and unaffected by the scalar. Both steady laminar and complex (chaotic, turbulent or random) time-dependent flows are of interest and such systems naturally lead to questions about the effectiveness of the stirring to disperse and mix the scalar. The development of reliable numerical methods for advection-diffusion equations is crucial for understanding their properties, both physical and mathematical. In this paper, we extend a fast explicit operator splitting method, recently proposed in (A. Chertock, A. Kurganov, G. Petrova, Int. J. Numer. Methods Fluids 59:309–332, 2009), for solving deterministic convection-diffusion equations, to the problems with random velocity fields and singular source terms. A superb performance of the method is demonstrated on several two-dimensional examples.     

Interleaving solving and elicitation of constraint satisfaction problems based on expected cost

We consider Constraint Satisfaction Problems in which constraints can be initially incomplete, where it is unknown whether certain tuples satisfy the constraint or not. We assume that we can determine the satisfaction of such an unknown tuple, i.e., find out whether this tuple is in the constraint or not, but doing so incurs a known cost, which may vary between tuples. We also assume that we know the probability of an unknown tuple satisfying a constraint. We define algorithms for this problem, based on backtracking search. Specifically, we consider a simple iterative algorithm based on a cost limit on the unknowns that may be determined, and a more complex algorithm that delays determining an unknown in order to estimate better whether doing so is worthwhile. We show experimentally that the more sophisticated algorithms can greatly reduce the average cost.     

A distributed requirements management framework for legal compliance and accountability

Increasingly, new regulations are governing organizations and their information systems. Individuals responsible for ensuring legal compliance and accountability currently lack sufficient guidance and support to manage their legal obligations within relevant information systems. While software controls provide assurances that business processes adhere to specific requirements, such as those derived from government regulations, there is little support to manage these requirements and their relationships to various policies and regulations. We propose a requirements management framework that enables executives, business managers, software developers and auditors to distribute legal obligations across business units and/or personnel with different roles and technical capabilities. This framework improves accountability by integrating traceability throughout the policy and requirements lifecycle. We illustrate the framework within the context of a concrete healthcare scenario in which obligations incurred from the Health Insurance Portability and Accountability Act (HIPAA) are delegated and refined into software requirements. Additionally, we show how auditing mechanisms can be integrated into the framework and how auditors can certify that specific chains of delegation and refinement decisions comply with government regulations.