An investigation of latency prediction for NoC-based communication architectures using machine learning techniques

The Journal of Supercomputing - Due to the increasing number of cores in Systems on Chip (SoCs), bus architectures have suffered with limitations regarding performance. As applications demand...     

Rapid screening test for flame retardation of wood,and its applicability to thermoplastic polymer systems

A rapid screening process was developed to investigate the flame‐retardant properties of new materials and compositions. Wooden tongue depressors (“sticks”) were coated in solutions/suspensions of compositions of interest and tested in a method similar to that of the UL‐94 vertical burn test. The concentration of additives applied to the wooden sticks, as well as the additive application and drying times influenced the burning performance of the sticks, a useful screening method for testing flame retardants applied to wood products. The most promising combination of flame retardants from the wooden stick tests were then compounded into polyolefins, which were tested according to the UL(94) vertical burn protocol. A strong correlation was found between UL(94) results for low density polyethylene, high density polyethylene and polypropylene, and the wooden stick flammability data. This test, therefore, shows promise as a simple, inexpensive, and rapid way to screen new materials and compositions for flammability. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46602.     

Chlorine disinfection of grey water for reuse: effect of organics and particles

Adequate disinfection of grey water prior to reuse is important to prevent the potential transmission of disease-causing microorganisms. Chlorine is a widely utilised disinfectant and as such is a leading contender for disinfection of grey water intended for reuse. This study examined the impact of organics and particles on chlorine disinfection of grey water, measured by total coliform inactivation. The efficacy of disinfection was most closely linked with particle size. Larger particles shielded total coliforms from inactivation and disinfection efficacy decreased with increasing particle size. Blending to extract particle-associated coliforms (PACs) following chlorine disinfection revealed that up to 91% of total coliforms in chlorinated grey water were particle associated. The organic concentration of grey water affected chlorine demand but did not influence the disinfection resistance of total coliforms when a free chlorine residual was maintained. Implications for urban water reuse are discussed and it is recommended that grey water treatment systems target suspended solids removal to ensure removal of PACs prior to disinfection.     

Personality Assessment Inventory substance-use scales: Convergent and discriminant relations with the Addiction Severity Index in a residential chemical dependence treatment setting.

This study examined the convergent and discriminant validity of the Alcohol Problems (ALC) and Drug Problems (DRG) scales of the Personality Assessment Inventory (PAI; Morey, 1991). Participants were 103 male veterans (mean age?=?41.7 years) in a Veterans Affairs residential treatment for chemical dependence. The PAI was compared to the Addiction Severity Index (ASI; McLellan et al., 1992), a semistructured interview. The sampling strategy that was used resulted in a diverse sample (66% African American, 33% Caucasian; 59% with primary alcohol diagnosis, 38% with primary drug diagnosis, 56% with comorbid alcohol and drug diagnoses) and adequately variable ALC and DRG scores. Results supported the convergent validity of both the ALC and DRG scales in relation to both the ASI and substance-use diagnosis. The ALC scale also demonstrated excellent discriminant validity, whereas the discriminant validity of the DRG scale was less impressive. Despite this, the DRG scale performed better in the current diverse sample than observed in an earlier study (Alterman et al., 1995). Recommendations for the use of the PAI in chemical dependence treatment settings are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Solid-state NMR for the analysis of interface excesses in Li-doped MgAl2O4 nanocrystals

Interface segregation plays a governing role in nanocrystalline ceramics properties due to the relative increase in the interfacial volume fraction. However, due to the complexity of the detection and quantification of interfacial excesses at the nanoscale, the role of ionic dopants or additives on microstructural evolution and thermodynamics can be easily underestimated. In this work, we address the spatial distribution of Li⁺ as a dopant in magnesium aluminate spinel nanoparticles. This is achieved through a novel method for the detection and quantification of Li⁺ across the surface, grain boundary, and bulk (crystal lattice). Based on selective lixiviation combined with chemical analysis, we were able to quantify the amount of Li⁺ forming surface excess, whereas the quantitative solid-state nuclear magnetic resonance technique enabled the quantification of Li⁺ segregated in the grain boundaries and dissolved in the lattice. This comprehensive understanding of the Li⁺ distribution across the nanoparticles makes possible an unprecedented interpretation of coarsening and sintering, with a clear correlation between the microstructure and the Li⁺ distribution. Although the work focuses on MgAl₂O₄, the proposed combination of techniques is expected to have a positive impact on the understanding of other multicomponent nanoscale systems.     

Coupling-based criteria for integration testing

Integration testing is an important part of the testing process, but few integration testing techniques have been systematically studied or defined. The goal of this research is to develop practical, effective, formalizable, automatable techniques for testing of connections between components during software integration. This paper presents an integration testing technique that is based on couplings between software components. This technique can be used to support integration testing of software components, and satisfies part of the USA's Federal Aviation Authority's requirements for structural coverage analysis of software. The coupling-based testing technique is described, and the coverage criteria for three types of couplings are defined. Techniques and algorithms for developing coverage analysers to measure the extent to which a test set satisfies the criteria are presented, and results from a comparative case study are presented. © 1998 John Wiley & Sons, Ltd.     

A control basis for learning multifingered grasps

In this article, we introduce a robust controller that uses contact position and normal feedback to generate contact configurations for statically stable grasps. The approach uses a context sensitive composition of two controllers that minimize force and moment residuals in the grasp configuration. Equilibria in the composite controller correspond to optimal contact configurations for two and three contacts on regular, convex polygons. The preimage is used to generalize the controller to arbitrary object geometries by learning a policy for compensation and to address object recognition and contact (de)allocation. ©1997 John Wiley & Sons, Inc.     

NIR luminescent Er/Yb co-doped SiO2–ZrO2 nanostructured planar and channel waveguides: Optical and structural properties

Optical and structural properties of planar and channel waveguides based on sol–gel Er³⁺ and Yb³⁺ co-doped SiO₂–ZrO₂ are reported. Microstructured channels with high homogeneous surface profile were written onto the surface of multilayered densified films deposited on SiO₂/Si substrates by a femtosecond laser etching technique. The densification of the planar waveguides was evaluated from changes in the refractive index and thickness, with full densification being achieved at 900 °C after annealing from 23 up to 500 min, depending on the ZrO₂ content. Crystal nucleation and growth took place together with densification, thereby producing transparent glass ceramic planar waveguides containing rare earth-doped ZrO₂ nanocrystals dispersed in a silica-based glassy host. Low roughness and crack-free surface as well as high confinement coefficient were achieved for all the compositions. Enhanced NIR luminescence of the Er³⁺ ions was observed for the Yb³⁺-codoped planar waveguides, denoting an efficient energy transfer from the Yb³⁺ to the Er³⁺ ion.     

Fitting semi‐empirical drying models using a tool based on wavelet neural networks: Modeling a maize drying process

Maize drying is an important process, especially for storage and conservation. For this study, the experimental stage was carried out using a forced convection dryer with air heated at different temperature conditions (306.05–441.85 K) and flow (0.13–0.256 m³/hr), totalizing 15 drying curves. Then the performances of the classic drying kinetics methodology and the approach proposed in this paper, in which the increase in moisture content of the product with time was represented combining exponential models and neural networks based on wavelets, were compared. Good performance was obtained in predictions using the proposed approach. One of the main differentials of the methodology adopted was the obtainment of a model that has a global predictive capacity, within the range of tested operating conditions, which can be used in predicting drying curves for different operating conditions.

Practical applications

The drying process is also one of the most widely used methods for preserving food, and has the advantage of reducing the costs of storage and transport because of the low volume and weight of the end product. During the last years, this topic has attracted a broad industrial interest, resulting in many research studies investigating the drying process. Usually, with regard to the classic approach for modeling of the drying process, the kinetics of drying curves obtained in different operating conditions is affected separately, that is, the parameters are estimated independently, resulting in different regression problems. With the classical approach, in general, it is not possible to obtain a comprehensive prediction model with regards to operating conditions. We have proposed an alternative modeling method. Aiming to obtain a modeling tool with an overall predictive ability, an approach for drying kinetics prediction that combines exponential models and neural networks was proposed. The proposed modeling method was able to predict drying curves for different operating conditions.