Foaming of polymers with supercritical CO2: An experimental and theoretical study

Microcellular polystyrene (PS) foams and porous structures of the biodegradable poly(d,l-lactic acid) (P_d,lLA) were prepared with the batch foaming technique (pressure quench) using supercritical CO₂ as blowing agent. The effect of pressure, temperature and depressurization rate on the final porous structure was investigated. The results revealed that the size of the pores decreases and their population density increases with pressure increase, or decrease of temperature, and/or increase of the depressurization rate. The results were correlated by combining nucleation theory with NRHB model in order to account for and emphasize the physical mechanism related to nucleation of bubbles inside the supersaturated polymer matrix. A satisfactory agreement between correlations and experimental data was obtained indicating that the nucleation theory yields quantitative correlations when variables such as sorption, degree of plasticization, and surface tension of the system polymer-supercritical fluid are accurately described.     

Monitoring and improving Greek banking services using Bayesian Networks: An analysis of mystery shopping data

Mystery shopping is a well known marketing technique used by companies and marketing analysts to measure quality of service, and gather information about products and services. In this article, we analyse data from mystery shopping surveys via Bayesian Networks in order to examine and evaluate the quality of service offered by the loan departments of Greek Banks. We use mystery shopping visits to collect information about loan products and services and, by this way, evaluate the customer satisfaction and plan improvement strategies that will assist banks to reach their internal standards. Bayesian Networks not only provide a pictorial representation of the dependence structure between the characteristics of interest but also allow to evaluate, interpret and understand the effects of possible improvement strategies.     

Nearest neighbor estimate of conditional mutual information in feature selection

Mutual information (MI) is used in feature selection to evaluate two key-properties of optimal features, the relevance of a feature to the class variable and the redundancy of similar features. Conditional mutual information (CMI), i.e., MI of the candidate feature to the class variable conditioning on the features already selected, is a natural extension of MI but not so far applied due to estimation complications for high dimensional distributions. We propose the nearest neighbor estimate of CMI, appropriate for high-dimensional variables, and build an iterative scheme for sequential feature selection with a termination criterion, called CMINN. We show that CMINN is equivalent to feature selection MI filters, such as mRMR and MaxiMin, in the presence of solely single feature effects, and more appropriate for combined feature effects. We compare CMINN to mRMR and MaxiMin on simulated datasets involving combined effects and confirm the superiority of CMINN in selecting the correct features (indicated also by the termination criterion) and giving best classification accuracy. The application to ten benchmark databases shows that CMINN obtains the same or higher classification accuracy compared to mRMR and MaxiMin at a smaller cardinality of the selected feature subset.     

Estimating the development cost of custom software

In this paper an approach for the estimation of software development costs is presented. The method is based on the characterization of the software to be developed in terms of project and environment attributes and comparison with some similar completed project(s) recovered from a historical database. A case study is also presented, focusing on the calibration and application of the method on 59 information systems implementing supply chain functions in industry. Various strategies are explored, the best of which predicted effort quite effectively, with a mean estimation error of 24% with respect to the actual effort.     

A review of current research in manufacturing shop design integration

The importance of the manufacturing shop design in the successful operation of a production system is well documented and, as a result, significant work has been devoted to this area. Due to the inherent complexity of the global shop design problem, much research has focused on individual sub-problems, including the layout of manufacturing resources, the design of the shop aisle network, and the selection of the material handling equipment, rather than addressing the integrated problem directly. This paper reviews literature contributions to shop design integration, as well as partial integration schemes such as the design for operation and control of material handling systems. Furthermore, it examines the ability of models and solution approaches for individual sub-problems of shop design to support integration schemes.     

Finite Element Modelling of TRIP Steels

A constitutive model that describes the mechanical behaviour of steels exhibiting “Transformation Induced Plasticity” (TRIP) during martensitic transformation is presented. Multiphase TRIP steels are considered as composite materials with a ferritic matrix containing bainite and retained austenite, which gradually transforms into martensite. The effective properties and overall behaviour of TRIP steels are determined by using homogenization techniques for non‐linear composites. The developed constitutive model considers the different hardening behaviour of the individual phases and estimates the apportionment of plastic strain and stress between the individual phases of the composite. A methodology for the numerical integration of the resulting elastoplastic constitutive equations in the context of the finite element method is developed and the constitutive model is implemented in a general‐purpose finite element program. The prediction of the model in uniaxial tension agrees well with the experimental data. The problem of necking of a bar in uniaxial tension is studied in detail.     

Reliability and maintainability analysis to improve the operation of the limoncello production line

The reliability, maintainability, failure rate and repair rate models of a limoncello automated production line for a period of 8 months at machine and entire line level were carried out. It was pointed out that (i) the real operating time of the limoncello production line (LPL) is 89.35%, whereas for the rest 10.65%, the LPL is under repair, (ii) the Weibull distribution provided the best fit of the failure data for the LPL to describe the time‐between‐failures (TBFs), whereas the time‐to‐repairs (TTRs) are lognormal distributed, and (iii) the failure rate of the production line increases, implying that the current maintenance strategy is not adequate and must be improved. This particular methodology can also be utilised in the beverage industry sector by the machinery manufacturers and the manufacturers of bottled products to improve the design and operation management of the bottling production line.     

A videogrammetric as-built data collection method for digital fabrication of sheet metal roof panels

A roofing contractor typically needs to acquire as-built dimensions of a roof structure several times over the course of its build because a structure is never built to the exact drawing dimensions. In the construction phase and in order to digitally fabricate sheet metal roof panels, the contractor has to measure end-to-end dimensions of boundaries of every roof plane with a certain level of accuracy (i.e., errors less than ±2 cm). This is necessary to be able to cut sheet metal coil such that different pieces perfectly fit together. Obtaining these measurements using the exiting roof surveying methods could be costly in terms of equipment, labor, and/or worker exposure to safety hazards. This paper presents a video-based surveying framework as an alternative method which is simple to use, automated, less expensive, and safe. When using this framework, the contractor collects video streams with a calibrated stereo camera set. The captured data is processed to automatically generate a 3D wire-diagram of the target roof. Measurements from the wire-diagram are saved in a digital file (XML format) which could be loaded into an on-site sheet metal folding and cutting machine. Experimental analyses demonstrate applicability of the proposed framework.     

Subclass discriminant Nonnegative Matrix Factorization for facial image analysis

Nonnegative Matrix Factorization (NMF) is among the most popular subspace methods, widely used in a variety of image processing problems. Recently, a discriminant NMF method that incorporates Linear Discriminant Analysis inspired criteria has been proposed, which achieves an efficient decomposition of the provided data to its discriminant parts, thus enhancing classification performance. However, this approach possesses certain limitations, since it assumes that the underlying data distribution is unimodal, which is often unrealistic. To remedy this limitation, we regard that data inside each class have a multimodal distribution, thus forming clusters and use criteria inspired by Clustering based Discriminant Analysis. The proposed method incorporates appropriate discriminant constraints in the NMF decomposition cost function in order to address the problem of finding discriminant projections that enhance class separability in the reduced dimensional projection space, while taking into account subclass information. The developed algorithm has been applied for both facial expression and face recognition on three popular databases. Experimental results verified that it successfully identified discriminant facial parts, thus enhancing recognition performance.