Hull-form stochastic optimization via computational-cost reduction methods

In this paper, analytical functions for the estimation of the temperature-dependent behaviors of poorly and highly dispersed graphene oxide reinforced nanocomposite (GORNC) materials are studied in the framework of a machine learning-based approach. The validity of the presented models is shown comparing the results achieved from this modeling with those reported in the open literature. Also, the application of the obtained functions in solving the thermal buckling problem of beams constructed from such nanocomposites is demonstrated based on an energy-based method incorporated with a shear deformable beam hypothesis. The verification of the results indicates that the presented mechanical model can approximate the buckling behaviors of nanocomposite beams with remarkable precision. It can be realized from the results that the temperature plays an indispensable role in the determination of the buckling load which can be endured by the nanocomposite structure.

     

A generalized finite-difference time-domain quantum method for the N-body interacting Hamiltonian

The Quantum Finite-Difference Time-Domain (FDTD-Q) method is a numerical method for solving the time evolution of the Schrödinger equation. It can be applied to systems of interacting particles, allowing for realistic simulations of quantum mechanics of various experimental systems. One of the drawbacks of the method is that divergences in the numerical evolution occur rather easily in the presence of interactions, which necessitates a large number of evolution steps or imaginary time evolution. We present a generalized (GFDTD-Q) method for solving the time-dependent Schrödinger equation including interactions between the particles. The new scheme provides a more relaxed condition for stability when the finite difference approximations for spatial derivatives are employed, as compared with the original FDTD-Q scheme. We demonstrate our scheme by simulating the time evolution of a two-particle interaction Hamiltonian. Our results show that the generalized method allows for stable time evolutions, in contrast to the original FDTD-Q scheme which produces a divergent solution.     

Composing, analyzing and validating software models to assess the performability of competing design candidates

In a perfect world, verification and validation of a software design specification would be possible before any code was generated. Indeed, in a perfect world we would know that the implementation was correct because we could trust the class libraries, the development tools, verification tools and simulations, etc. These features would provide the confidence needed to know that all aspects (complexity, logical and timing correctness) of the design were fully satisfied (i.e., everything was right). Right in the sense that we built it right (it is correct with respect to its specification) and it solves the right problem. Unfortunately, it is not a perfect world, and therefore we must strive to continue to refine, develop and validate useful methods and tools for the creation of safe and correct software. This paper considers the analysis of systems expressed using formal notations. We introduce our framework, the modeling cycle, and motivate the need for tool supported rigorous methods. Our framework is about using systematic formal techniques for the creation and composition of software models that can further enable reasoning about high‐assurance systems. We describe several formal modeling techniques within this context (i.e., reliability and availability models, performance and functional models, performability models, etc.). This discussion includes a more precise discourse on stochastic methods (i.e., DTMC and CTMC) and their formulation. In addition, we briefly review the underlying theories and assumptions that are used to solve these models for the measure of interest (i.e., simulation, numerical and analytical techniques). Finally, we present a simple example that employs generalized stochastic Petri nets and illustrates the usefulness of such analysis methods. This revised version was published online in June 2006 with corrections to the Cover Date.     

Analysis of frames with semi-rigid joints

This paper presents a method to determine the load capacity as well as end member forces and deformations of frames with partial rigid joint connections by using the direct stiffness method. The connections are modeled as rotational springs attached at the ends of framed members.     

Full-body interface pressure testing as a method for performance evaluation of clinical support surfaces

A method for evaluating the performance of clinical support surfaces is required by designers in their efforts to produce better clinical support surfaces that will reduce the incidence of pressure ulcers. In this study, a Pressure Index (P_index) is defined which is derived from an analytical equation used to evaluate the average interface pressure, the peak pressure, the magnitude of the peak pressure, and the number of peak pressures on the entire body. The type of subjects needed to represent a population of users as well as the head of bed elevations necessary to simulate clinical applications were integrated with the P_index to create a single-value mean pressure index which can be used to evaluate any type of surface. To determine the accuracy and repeatability of the mean pressure index, three surfaces (a standard hospital innerspring, a replacement foam mattress, and a low-airloss surface) were tested and evaluated using this method. The low airloss performed the best and the standard innerspring clearly performed the worst (p < 0.0001). The method appeared to accurately and reproducibly predict the relative performance of the three surfaces in reducing pressure.     

Spectral and complexity analysis of scalp EEG characteristics for mild cognitive impairment and early Alzheimer's disease

Amnestic mild cognitive impairment (aMCI) often is an early stage of Alzheimer's disease (AD). MCI is characterized by cognitive decline departing from normal cognitive aging but that does not significantly interfere with daily activities. This study explores the potential of scalp EEG for early detection of alterations from cognitively normal status of older adults signifying MCI and AD. Resting 32-channel EEG records from 48 age-matched participants (mean age 75.7 years)—15 normal controls (NC), 16 early MCI, and 17 early stage AD—are examined. Regional spectral and complexity features are computed and used in a support vector machine model to discriminate between groups. Analyses based on three-way classifications demonstrate overall discrimination accuracies of 83.3%, 85.4%, and 79.2% for resting eyes open, counting eyes closed, and resting eyes closed protocols, respectively. These results demonstrate the great promise for scalp EEG spectral and complexity features as noninvasive biomarkers for detection of MCI and early AD.     

Adult attachment orientations, self–other boundary regulation, and splitting tendencies in a college sample.

In a sample of 247 college students, the contributions of adult attachment orientations and several other boundary regulation variables to measures of self-splitting (i.e., the tendency to report diffuse and chaotic self-experiences) and other-splitting (i.e., the tendency to acknowledge unstable perceptions of and feelings toward one's friends) were explored. Adult attachment orientations and self-other boundary regulation variables, respectively, explained unique variance in each criterion measure. High levels of attachment anxiety and self-concealment and low levels of self-other differentiation contributed most prominently to self-splitting, whereas high attachment anxiety, low emotional reactivity, and high needs for social approval best predicted other-splitting. Implications of these findings for advancing a more delineated understanding of splitting tendencies are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)