Modeling of the desulfation process in NOx storage and reduction catalysts

One of the major challenges for the NO_x Storage and Reduction Catalysts technology used in automotive exhaust remains the sulfur susceptibility, which calls for efficient desulfation strategies. The sulfation and desulfation processes are systematically studied via measurements and mathematical modeling of the physicochemical processes. The role of oxygen storage which influences the reducing agents availability for desulfation is explained and a respective reaction model is presented. The bulk oxygen storage component appears to be involved in sulfur storage, which further emphasizes the importance of oxygen–sulfur storage interactions. Next, the observed release of sulfur species under lean mode is discussed along with a proposed reaction mechanism which involves SO₂ formation via O₂ reaction with elemental sulfur on the surface. The parameters of the complex reaction model are calibrated in order to reproduce the observed trends at least in a qualitative manner. © 2016 American Institute of Chemical Engineers AIChE J, 63: 2117–2127, 2017     

Modeling of the NO x trap and experimental validation using ultra-fast NO x analyzers

The present paper employs and validates a NO _x trap model which attempts an optimum compromise between complexity and predictive accuracy. It is shown that using the same set of kinetic data, the model is able to predict the storage rates and the maximum storage amounts as function of temperature. Moreover, the model predicts with reasonable accuracy the NO breakthrough during rich-mode regeneration and the spontaneous/thermal NO₂ release when the temperature is increased in a saturated catalyst. The experimental findings highlight the importance of transient O₂ adsorption/desorption phenomena which are incorporated in the model. The use of ultra-fast responding NO/NO _x analyzers was necessary for the study and modeling of the transient operation following inlet composition switches.     

The Menpo Benchmark for Multi-pose 2D and 3D Facial Landmark Localisation and Tracking

International Journal of Computer Vision - In this article, we present the Menpo 2D and Menpo 3D benchmarks, two new datasets for multi-pose 2D and 3D facial landmark localisation and tracking. In...     

Innovative microwave-assisted hydrolysis of ellagitannins and quantification as ellagic acid equivalents

The health-promoting effects of ellagic acid and its intestinal degradation products are well-known. In plants, ellagic acid mainly appears in the form of its precursors, the so-called ellagitannins. Therefore, determination of total ellagic acid content has been accomplished by cleaving ellagitannins with high temperatures and strong acids. Microwave-assisted extraction (MAE) has been shown to be a very effective and quick extraction technique. The aim of the present study was to establish an MAE-based method for a rapid hydrolysis of ellagitannins and to compare this method with a conventional acid hydrolysis. For this purpose, strawberries (Fragaria x ananassa), which have been identified as a major source of ellagitannins in human diet, were used as a model. The newly developed MAE method was quicker, less chemical-consuming and more effective in hydrolysing ellagitannins.     

Evaluation of on-board diagnosis methods for three-way catalytic converters

On-board diagnosis (OBD) aims at detecting malfunctions of emission-related components of road vehicles. It is required by legislation in United States and the European Union, as it is considered to be beneficial for the reduction of vehicle-related air pollution. On-board diagnosis of the catalytic converter is a challenging task, as it relies on indirect assessments of catalyst activity. Several methods have been proposed for catalyst diagnosis, presenting a varying degree of correlation between the quantities used as OBD indexes and the actual tailpipe emissions. This paper evaluates two methods, with the support of mathematical modeling; in the first one, which is commonly used by vehicle manufacturers, malfunction detection relies on the oxygen storage properties of the catalyst, while in the second, detection relies on the heat released by the chemical reactions in the catalyst. Both are found to be sufficient for the diagnosis of catalytic converters for current legislation requirements. However, the thermal method presents higher sensitivity to low levels of catalyst deactivation and could therefore be more suitable for diagnosis of future, ultra-low-emitting vehicles.     

An adaptive personalized news dissemination system

With the explosive growth of the Word Wide Web, information overload became a crucial concern. In a data-rich information-poor environment like the Web, the discrimination of useful or desirable information out of tons of mostly worthless data became a tedious task. The role of Machine Learning in tackling this problem is thoroughly discussed in the literature, but few systems are available for public use. In this work, we bridge theory to practice, by implementing a web-based news reader enhanced with a specifically designed machine learning framework for dynamic content personalization. This way, we get the chance to examine applicability and implementation issues and discuss the effectiveness of machine learning methods for the classification of real-world text streams. The main features of our system named PersoNews are: (a) the aggregation of many different news sources that offer an RSS version of their content, (b) incremental filtering, offering dynamic personalization of the content not only per user but also per each feed a user is subscribed to, and (c) the ability for every user to watch a more abstracted topic of interest by filtering through a taxonomy of topics. PersoNews is freely available for public use on the WWW ().

Architecture and design of an embeddable system for SCAN-based compression, encryption and information hiding

The SCAN formal languages can be used for tight integration of image and video compression, encryption and data hiding. This work presents such a tightly integrated embeddable system, which can be used as a “black box” in streaming media. In our previous work we had studied and implemented separate modules for SCAN compression and SCAN encryption, using a large Virtex II FPGA for each. There were no implementation of data hiding, no integration of the three aspects of SCAN, and no complete design for decompression/decryption/unhiding. This paper presents a new architecture and a complete design for SCAN compression/encryption/hiding, as well as the corresponding decompression/decryption/data unhiding operations. A recent technology based on an embedded processor with reconfigurable fabric extensions has been used for this design, which was carried out to post place and route cycle-accurate simulations with real video sequences. The new design is of substantially lower performance versus the previous reconfigurable implementations of single modules, however, it proves that a low-cost embeddable system can be made for all three operations. This paper presents in detail the different aspects of the architecture, their integration, and their mapping to the fixed and reconfigurable resources of the Stretch S5000 reconfigurable processor. To our knowledge, this is the first tightly integrated compression/encryption/ information hiding system to be reported in the literature.

An Efficient Clustering Algorithm for <Emphasis Type="Italic">k</Emphasis>-Anonymisation

K-anonymisation is an approach to protecting individuals from being identified from data.Good k-anonymisations should retain data utility and preserve privacy,but few methods have considered these two conflicting requirements together. In this paper,we extend our previous work on a clustering-based method for balancing data utility and privacy protection, and propose a set of heuristics to improve its effectiveness.We introduce new clustering criteria that treat utility and privacy on equal terms and propose sampling-based techniques to optimally set up its parameters.Extensive experiments show that the extended method achieves good accuracy in query answering and is able to prevent linking attacks effectively.