CeO2-based catalysts with engineered morphologies for soot oxidation to enhance soot-catalyst contact

As morphology plays a relevant role in solid/solid catalysis, where the number of contact points is a critical feature in this kind of reaction, three different ceria morphologies have been investigated in this work as soot oxidation catalysts: ceria nanofibers, which can become organized as a catalytic network inside diesel particulate filter channels and thus trap soot particles at several contact points but have a very low specific surface area (4 m²/g); solution combustion synthesis ceria, which has an uncontrolled morphology but a specific surface area of 31 m²/g; and three-dimensional self-assembled (SA) ceria stars, which have both high specific surface area (105 m²/g) and a high availability of contact points. A high microporous volume of 0.03 cm³/g and a finer crystallite size compared to the other morphologies suggested that self-assembled stars could improve their redox cycling capability and their soot oxidation properties. In this comparison, self-assembled stars have shown the best tendency towards soot oxidation, and the temperature of non-catalytic soot oxidation has dropped from 614°C to 403°C in tight and to 552°C in loose contact conditions, respectively. As far as the loose contact results are concerned, this condition being the most realistic and hence the most significant, self-assembled stars have exhibited the lowest T_10% onset temperature of this trio (even after ageing), thus proving their higher intrinsic activity. Furthermore, the three-dimensional shape of self-assembled stars may involve more of the soot cake layer than the solution combustion synthesis or nanofibers of ceria and thus enhance the total number of contact points. The results obtained through this work have encouraged our efforts to understand soot oxidation and to transpose these results to real diesel particulate filters.     

Impulse noise cancellation in image data using a two-output nonlinear filter

The quality of image data is often degraded by impulse noise caused by noisy sensors and/or transmission errors. To address this issue, a two-output nonlinear filtering architecture is presented. The proposed approach is based on the subsequent activation of two recursive filtering algorithms that operate on different subsets of input data. As a result, two pixel values are updated at each processing step producing a very effective cancellation of noise pulses. Impulse noise removal is based on rank ordered filtering. A nonlinear mechanism for error correction is also provided in order to avoid detail blur. Validation of the method is carried out by evaluating the quality of the filtered data with respect to two conflicting performance indexes: effectiveness of noise cancellation and accuracy of detail preservation. Results of computer simulations show that the proposed approach performs significantly better than well-known nonlinear methods in the literature including state-of-the-art operators.     

Function block applications in control systems based on IEC 61804

A variety of fieldbus technologies and digital fieldbus devices have been introduced within the process industries over the last ten years. There has been a gradual acceptance of the fact that a variety of communication technologies are needed to fully address the application requirements of a manufacturing facility. However, engineers responsible for the specification, engineering, and implementation of control systems require that a common interface and functionality be provided in the control system. This capability should be independent of the underlying fieldbus technology or manufacturer of the fieldbus device. The draft IEC 61804 standard defines how a control system can be structured to provide this flexibility in the utilization of fieldbus technology. In this paper, we discuss how a consistent function block capability may be provided for all fieldbus technology utilized in a control system. Examples will be given of how this standard has been applied in modern control systems to give a consistent interface to Foundation Fieldbus and PROFIBUS. Some detail will be presented on the standard means that is defined for manufacturers to describe function block capability of a field device. An analysis is given of the impact and benefit that the IEC 61804 standard will have on the process industry and on manufacturers of control systems.     

Interplay between technology and meaning: How music majors reacted?

The diffusion of digital technologies enables companies to propose new business, products and services. The business environment is characterized by increasing levels of competition, and customers can choose a growing number of solutions. In this scenario, companies seek new dimension of innovation: the meaning. A vigorous debate has taken place among scholars on the strategies that companies may use to react to external innovations. Until now, the phenomenon has been analysed grounded in the technology‐push literature. The goal of this study is to understand whether these strategies are still valuable even if innovators leverage not only on the technology but also on a hedonic dimension proposing an innovation of meaning. Through a multiple case‐study analysis, based on both primary and secondary sources, we investigate whether the case companies from the music industry also used the strategies described in the literature to cope with technological innovations that leverage both on technology and meaning.     

Normal and Abnormal Tissue Classification in Positron Emission Tomography Oncological Studies

Positron Emission Tomography (PET) imaging is increasingly used in radiotherapy environment as well as for staging and assessing treatment response. The ability to classify PET tissues, as normal versus abnormal tissues, is crucial for medical analysis and interpretation. For this reason, a system for classifying PET area is implemented and validated. The proposed classification is carried out using k-nearest neighbor (KNN) method with the stratified K-Fold Cross-Validation strategy to enhance the classifier reliability. A dataset of eighty oncological patients are collected for system training and validation. For every patient, lesion (abnormal tissue) and background (normal tissue around the lesion) are contoured on PET images using a semi-automatic method. Then 160 vectors are obtained to train and validate the KNN. Each vector is composed by thirty Standardized Uptake Values (SUVs) characterizing the area under investigation (lesion or background). In one case, vectors are labeled as normal or abnormal tissues by a nuclear medicine physician using a semi-automatic method; in other cases, Fuzzy C-means (FCM) and k-means are used for labelling vectors in an unsupervised manner. This study aims to evaluate the performance of the proposed classifier comparing it to the Linear Kernel Support Vector Machine (KSVM). The method accuracy is evaluated by comparison with the gold standard in terms of correct classification. Experimental results show that the KNN method achieves the highest classification accuracy using the semi-automatic labelling training (Sensitivity: 86.25%; Specificity: 90.00%; Negative Predictive Value: 88.37%; Precision: 89.81%; Accuracy: 88.12%; Error: 11.87%). In addition, the proposed method shows real-time performance; it could be applied to the field classification of PET images assisting physicians into discrimination of normal and abnormal tissue during radiation treatment planning.     

Studying system development methodologies: an examination of research methods

Changes in organizational structures, competitive environments, technologies and economies are altering the types and complexity of computer-based information systems. For methodologies, tools and techniques to evolve to meet these changing needs, research to assess current system development practices would be expected. However, there is little evidence that the evaluation of methodologies and improvement of the systems development process are keeping pace with technological and organizational changes. This paper analyses existing research on system development methodologies and discusses the research needed to provide the information scholars and practitioners will need for the evaluation, selection and development of methodologies in a changing environment.     

On the application of the minimum polynomial extrapolation method to incompressible flows with heat transfer

In this paper, the Minimum Polynomial Extrapolation method (MPE) is used to accelerate the convergence of the Characteristic–Based–Split (CBS) scheme for the numerical solution of steady state incompressible flows with heat transfer. The CBS scheme is a fractional step method for the solution of the Navier–Stokes equations while the MPE method is a vector extrapolation method which transforms the original sequence into another sequence converging to the same limit faster then the original one without the explicit knowledge of the sequence generator. The developed algorithm is tested on a two-dimensional benchmark problem (buoyancy–driven convection problem) where the Navier–Stokes equations are coupled with the temperature equation. The obtained results show the feature of the extrapolation procedure to the CBS scheme and the reduction of the computational time of the simulation.     

Memory leak analysis of mission-critical middleware

Memory leaks are recognized to be one of the major causes of memory exhaustion problems in complex software systems. This paper proposes a practical approach to detect aging phenomena caused by memory leaks in distributed objects Off-The-Shelf middleware, which are commonly used to develop critical applications. The approach, which is validated on a real-world case study from the Air Traffic Control domain, defines algorithms and ad hoc support tools to perform data filtering and to find the best trade off between experimentation time and statistical accuracy of aging trend estimates. Experiments show that fixing memory leaks is not always the key to solve memory exhaustion problems.     

Anonymous subject identification and privacy information management in video surveillance

The widespread deployment of surveillance cameras has raised serious privacy concerns, and many privacy-enhancing schemes have been recently proposed to automatically redact images of selected individuals in the surveillance video for protection. Of equal importance are the privacy and efficiency of techniques to first, identify those individuals for privacy protection and second, provide access to original surveillance video contents for security analysis. In this paper, we propose an anonymous subject identification and privacy data management system to be used in privacy-aware video surveillance. The anonymous subject identification system uses iris patterns to identify individuals for privacy protection. Anonymity of the iris-matching process is guaranteed through the use of a garbled-circuit (GC)-based iris matching protocol. A novel GC complexity reduction scheme is proposed by simplifying the iris masking process in the protocol. A user-centric privacy information management system is also proposed that allows subjects to anonymously access their privacy information via their iris patterns. The system is composed of two encrypted-domain protocols: The privacy information encryption protocol encrypts the original video records using the iris pattern acquired during the subject identification phase; the privacy information retrieval protocol allows the video records to be anonymously retrieved through a GC-based iris pattern matching process. Experimental results on a public iris biometric database demonstrate the validity of our framework.