Damage mechanism at different transpassive potentials of solution-annealed 316 and 316l stainless steels

Electrochemical impedance spectroscopy (EIS), anodic polarization and scanning electron microscopy techniques were used to investigate the damage mechanism in the transpassive potential region of AISI ...     

Anthocyanins characterization of 15 Iranian pomegranate (Punica granatum L.) varieties and their variation after cold storage and pasteurization

Anthocyanins (ACs) are phenolic compounds that are distributed widely in fruits and vegetables. Apart from imparting color to plants, ACs also have an array of health-promoting benefits. In this research, the amounts of major ACs of 15 pomegranate (Punica granatum L.) varieties obtained from Yazd province were determined. The major ACs detected in the studied varieties were as follows: delphinidin 3-glucoside (2.19–16.29 mg/L), delphinidin 3,5-diglucoside (2.36–63.07 mg/L), pelargonidin 3-glucoside (0.26–1.36 mg/L), pelargonidin 3,5-diglucoside (0.01–8.11 mg/L), cyanidin 3-glucoside (5.78–30.38 mg/L), and cyanidin 3,5-diglucoside (4.39–166.32 mg/L). The effect of storage time of unprocessed and pasteurized juices on ACs content of four selected varieties was also studied. Average degradation percentage of each AC was between 23.0 and 83.0% during 10 days at 4 °C. Moreover, in pasteurized juices average degradation of ACs was 42.8 ± 0.5% after 10 weeks storage at 4 °C.     

Intelligent non-linear modelling of an industrial winding process using recurrent local linear neuro-fuzzy networks

This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system. A new simulator model is proposed for a winding process using non-linear identification based on a recurrent local linear neuro-fuzzy (RLLNF) network trained by local linear model tree (LOLIMOT), which is an incremental tree-based learning algorithm. The proposed NF models are compared with other known intelligent identifiers, namely multilayer perceptron (MLP) and radial basis function (RBF). Comparison of our proposed non-linear models and associated models obtained through the least square error (LSE) technique (the optimal modelling method for linear systems) confirms that the winding process is a non-linear system. Experimental results show the effectiveness of our proposed NF modelling approach.     

On the application of Harris hawks optimization (HHO) algorithm to the design of microchannel heat sinks

Engineering with Computers - A novel Harris hawks optimization algorithm is applied to microchannel heat sinks for the minimization of entropy generation. In the formulation of the heat transfer...     

Proteomics in aortic aneurysm – What have we learnt so far?

Aortic aneurysm is a deceptively indolent disease that can cause severe complications such as aortic rupture and dissection. In the normal aorta, vascular smooth muscle cells within the medial layer produce and sustain the extracellular matrix (ECM) that provides structural support but also retains soluble growth factors and regulates their distribution. Although the ECM is an obvious target to identify molecular processes leading to structural failure within the vessel wall, an in-depth proteomics analysis of this important sub-proteome has not been performed. Most proteomics analyses of the vasculature to date used homogenized tissue devoid of spatial information. In such homogenates, quantitative proteomics comparisons are hampered by the heterogeneity of clinical samples (i.e. cellular composition) and the dynamic range limitations stemming from highly abundant cellular proteins. An unbiased proteomics discovery approach targeting the ECM instead of the cellular proteome may decipher the complex, multivalent signals that are presented to cells during aortic remodelling. A better understanding of the ECM in healthy and diseased vessels will provide important pathogenic insights and has potential to reveal novel biomarkers.     

Supporting multiple perspectives in feature-based configuration

Feature diagrams have become commonplace in software product line engineering as a means to document variability early in the life cycle. Over the years, their application has also been extended to assist stakeholders in the configuration of software products. However, existing feature-based configuration techniques offer little support for tailoring configuration views to the profiles of the various stakeholders. In this paper, we propose a lightweight, yet formal and flexible, mechanism to leverage multidimensional separation of concerns in feature-based configuration. We propose a technique to specify concerns in feature diagrams and to generate automatically concern-specific configuration views. Three alternative visualisations are proposed. Our contributions are motivated and illustrated through excerpts from a real web-based meeting management application which was also used for a preliminary evaluation. We also report on the progress made in the development of a tool supporting multi-view feature-based configuration.     

A Model for Identifying the Behavior of Alzheimer’s Disease Patients in Smart Homes

Wireless Personal Communications - In recent years, Smart Cities and Smart Homes have been studied as an important field of research. The design and construction of smart homes have flourished so...     

Defining the e-learner’s security profile: Towards awareness improvement

The paper presents an improved e-learner model that supports monitoring of user behavior related to information security. The model is built upon standardized IMS specification, according to literature research and survey conducted among e-learners. It is positioned as key part of an extended LTSA architecture in which the learner data is used to improve learner security position by continuous delivery of important information and adapting security mechanisms. The implementation is considered in Moodle LMS.     

On the Efficiency of Runs Rules Schemes for Process Monitoring

There are two main types of variations, namely, common and special causes leading to in‐control and out‐of‐control states, respectively. Control charts are popular tools used to differentiate between these two states of a process. Implementation of runs rules schemes with control charts is an attractive approach for process monitoring. This study is designed to describe the methodology of runs rules schemes and discuss their implementation for different types of control charts. We have considered memory‐less charts, namely, , S, and R charts for our study purposes. It is examined that the efficiency gain depends on the number of decision points utilized to implement a given rule. Moreover, superiority of runs rules schemes may vary for different types of location and dispersion charts. An application example using a dataset is also included in the study for practical considerations. Copyright © 2015 John Wiley & Sons, Ltd.     

Identification and optimization of key process parameters in noncontact laser scanning for reverse engineering

This Extended Technical Note shows that the final accuracy level of reverse engineered surfaces depends on scanning distance and scanning angle of the laser beam, hence it also depends on the morphology of the scanned objects. On scanning strongly curved objects, such as the ones with free form surfaces, the distance and impact angle of the laser beam are changing continuously during the scanning process. On the basis of these, two critical parameters are specified for the design model, which make it possible to predict these two factors in advance, depending on the morphology of the scanned object. First, a mathematical-statistical design model of the scanning process is generated, which relies on ANOVA (analysis of variance) and DOE (design of experiments). In the next step, a fitness function is optimized by the genetic algorithm (GA) program. This optimization improves the accuracy of the final scanned surfaces, in terms of the minimum standard deviation values of reverse engineered 3D surface model. The proposed approach was confirmed in a case study, which is presented at the end of this Technical Note.