Optimization of demand-related packaging sizes using a p-median approach

The determining of efficient packaging sizes is a key factor in saving material and transportation costs and also in reducing packaging waste. By analyzing the range of items and their contribution to sales-relevant order structures of a globally operating mail order company, a simplified packing algorithm is proposed. In combination with well-known methodologies, this heuristic provides near optimal solutions improving current packaging of eCommerce companies. It is shown that simple, practical heuristics are sufficient to achieve average material savings of more than 10 %. In order to find efficient packaging sizes, a set of them is generated by discretization of packaging dimensions. Given the set of orders and the set of packaging sizes, a p-median approach is applied to find a specified number of optimal, demand-related packaging sizes.     

Biodegradability and improved mechanical performance of polyhydroxyalkanoates/agave fiber biocomposites compatibilized by different strategies

In this work, biocomposites made of polyhydroxyalkanoates (PHA) with natural fibers were produced via compression molding. In particular, polyhydroxybutyrate (PHB) and polyhydroxybutyrate-co-hydroxyvalerate (PHBV) were reinforced with 20 wt% of agave fibers. Different compatibilization strategies were investigated to improve the fiber-matrix interaction: fiber surface treatment in PHA solution, fiber surface treatment in maleated PHA solution, fiber propionylation, and extrusion with maleated PHA. The biocomposites were characterized in terms of morphology, mechanical properties, water absorption, and biodegradability by CO₂ production tracking. In general, fiber propionylation was the best strategy for mechanical properties enhancement and water uptake decreasing. Biocomposites with propionylated fibers showed improved flexural strength (170% for PHB and 84% for PHBV). The flexural modulus was also enhanced with propionylated fibers up to 19% and 18% compared to uncompatibilized biocomposites (PHB and PHBV, respectively). Tensile strength increased by 16% (PHB) and 14% (PHBV), and the water absorption was reduced using propionylated fibers going from 6.6% to 4.4% compared with biocomposites with untreated fibers. Most importantly, the impact strength was also improved for all biocomposites by up to 96% compared with the neat PHA matrices. Finally, it was found that the compatibilization did not negatively modify the PHA biodegradability.     

Poly(N-methylaniline) coatings on stainless steel by electropolymerization

Poly(N-methylaniline) (PNMA) coatings have been electropolymerized on 304 stainless steel alloy by potentiodynamic, galvanostatic and potentiostatic synthesis techniques from aqueous solutions of 0.1 M N-methylaniline (NMA) and 0.3 M oxalic acid. Characterization of PNMA coatings was carried out by cyclic voltammetry, UV-Vis and FTIR spectroscopy techniques. Corrosion behavior of PNMA coated stainless steel electrodes was investigated using linear anodic potentiodynamic polarization, Tafel test, chronoamperometry and electrochemical impedance spectroscopy (EIS) techniques in 0.5 M aqueous HCl solutions. Corrosion test results showed that PNMA coatings possessed protection to uncoated stainless steel against corrosion.     

Perceptually enhanced blind single-channel music source separation by Non-negative Matrix Factorization

We propose a new approach that improves perceptual quality of the separated sources in blind single-channel musical source separation. It uses the advantages of subspace learning based on Non-negative Matrix Factorization (NMF) in which the bases represent the notes. The cost function is formulated in the form of weighted β-divergence by adopting the PEAQ auditory model defined in ITU-R BS.1387 into the source separation. The proposed perceptually weighted factorization scheme is integrated into the Non-negative Matrix Factor 2-D Deconvolution (NMF2D) and Clustered Non-negative Matrix Factorization (CNMF) to overcome the source clustering problem encountered in under-determined source separation. It is shown that the introduced perceptually weighted NMF schemes, named as PW-NMF2D and PW-CNMF, efficiently learn the bases that enable us to apply a simple resynthesis of the musical sources based on the temporal model stored in the encoding matrix. Source separation performance has been reported on musical mixtures where 1–2 dB improvement is achieved in terms of SDR, SIR and SAR compared to the state-of-the-art methods. Performance has also been evaluated by perceptual measures resulting an improvement of 2–5 in OPS, TPS, IPS and APS values.     

Fuzzy FMEA application to improve purchasing process in a public hospital

Failure mode and effects analysis (FMEA) is one of the well-known techniques of quality management that is used for continuous improvements in product or process designs. While applying this technique, determining the risk priority numbers, which indicate the levels of risks associated with potential problems, is of prime importance for the success of application. These numbers are generally attained from past experience and engineering judgments, and this way of risk assessment sometimes leads to inaccuracies and inconsistencies during priority numbering. Fuzzy logic approach is preferable in order to remove these deficiencies in assigning the risk priority numbers. In this study, a fuzzy-based FMEA is to be applied first time to improve the purchasing process of a public hospital. Results indicate that the application of fuzzy FMEA method can solve the problems that have arisen from conventional FMEA, and can efficiently discover the potential failure modes and effects. It can also provide the stability of process assurance.     

Metamodeling live sequence charts for code generation

This article presents a metamodeling study for Live Sequence Charts (LSCs) and Message Sequence Charts (MSCs) with an emphasis on code generation. The article discusses specifically the following points: the approach to building a metamodel for MSCs and LSCs, a metamodel extension from MSC to LSC, support for model-based code generation, and finally action model and domain-specific data model integration. The metamodel is formulated in metaGME, the metamodel language for the Generic Modeling Environment.

Electrical and Dielectric Properties of Y<Superscript>3+</Superscript>-Substituted Barium Hexaferrites

In this study, Y³⁺ ion-substituted M-type barium hexaferrites (BaM; BaFe₁₂O₁₉) were fabricated via facile ceramic route. As-prepared powders were characterized by X-ray powder diffractometry (XRD), Fourier transform infrared (FT-IR) spectroscopy, and impedance spectroscopy. XRD (Rietveld) analyses confirmed the presence of a single characterization of all samples (except x = 0.0 and 0.1 samples). The crystallite sizes of products are found in the range of 47.2–63.2 nm. Spectral analysis (FT-IR) also presented the formation of spinel structure for all products. The ac conductivity of the substituted samples was found to initially decrease slightly with increase in Y³⁺ compared with unsubstituted, and then variation tendency changes at the medium substitution ranges are observed with a different attitude against temperature. In the end, the lower conductivity for high substitutions is recorded and increases as functions of frequency while it also increases with the elevation of temperature. It was observed that ac conductivities of products increased by increasing frequency which indicate that observed ac conductivity is due to both electronic and polaron hopping mechanism.     

Stochastic two-sided U-type assembly line balancing: a genetic algorithm approach

In this paper, a novel stochastic two-sided U-type assembly line balancing (STUALB) procedure, an algorithm based on the genetic algorithm and a heuristic priority rule-based procedure to solve STUALB problem are proposed. With this new proposed assembly line design, all advantages of both two-sided assembly lines and U-type assembly lines are combined. Due to the variability of the real-life conditions, stochastic task times are also considered in the study. The proposed approach aims to minimise the number of positions (i.e. the U-type assembly line length) as the primary objective and to minimise the number of stations (i.e. the number of operators) as a secondary objective for a given cycle time. An example problem is solved to illustrate the proposed approach. In order to evaluate the efficiency of the proposed algorithm, test problems taken from the literature are used. The experimental results show that the proposed approach performs well.     

Estimating Construction Material Indices with ARIMA and Optimized NARNETs

Construction Industry operates relying on various key economic indicators. One of these indicators is material prices. On the other hand, cost is a key concern in all operations of the construction industry. In the uncertain conditions, reliable cost forecasts become an important source of information. Material cost is one of the key components of the overall cost of construction. In addition, cost overrun is a common problem in the construction industry, where nine out of ten construction projects face cost overrun. In order to carry out a successful cost management strategy and prevent cost overruns, it is very important to find reliable methods for the estimation of construction material prices. Material prices have a time dependent nature. In order to increase the foreseeability of the costs of construction materials, this study focuses on estimation of construction material indices through time series analysis. Two different types of analysis are implemented for estimation of the future values of construction material indices. The first method implemented was Autoregressive Integrated Moving Average (ARIMA), which is known to be successful in estimation of time series having a linear nature. The second method implemented was Non-Linear Autoregressive Neural Network (NARNET) which is known to be successful in modeling and estimating of series with non-linear components. The results have shown that depending on the nature of the series, both these methods can successfully and accurately estimate the future values of the indices. In addition, we found out that Optimal NARNET architectures which provide better accuracy in estimation of the series can be identified/discovered as result of grid search on NARNET hyperparameters.     

Model‐based code generation for HLA federates

This paper addresses the problem of automated code generation for a High Level Architecture compliant federate application given its behavior model. The behavior model is a part of the architectural model of a federation that the federate can participate in. The federate behavior model is based on Live Sequence Charts, adopted as the behavioral specification formalism in the Federation Architecture Metamodel (FAMM). FAMM serves as a formal language for describing federation architectures. An objective is to help the testing of federation architecture by means of its prototype implementation early in the development lifecycle. A further objective is to help developers construct complete federate applications that are well modularized. The approach to achieve these objectives is aspect‐oriented in that the generated code, which handles the federate's interactions with a federation execution, serves as the base code, where the computation logic is to be weaved as an aspect. Copyright © 2009 John Wiley & Sons, Ltd.