Assessing Disclosure Risk and Data Utility Trade-off in Transaction Data Anonymization

Organizations and businesses, including financial institutions and healthcare providers, are increasingly collecting and disseminating information about individuals in the form of transactions. A transaction associates an individual with a set of items, each representing a potentially confidential activity, such as the purchase of a stock or the diagnosis of a disease. Thus, transaction data need to be shared in a way that preserves individuals'' privacy, while remaining useful in intended tasks. While algorithms for anonymizing transaction data have been developed, the issue of how to achieve a "desired" balance between disclosure risk and data utility has not been investigated. In this paper, we assess the balance offered by popular algorithms using the R-U confidentiality map. Our analysis and experiments shed light on how the joint impact on disclosure risk and data utility can be examined, which allows the production of high-quality anonymization solutions.     

Synthesis of A356 Al–high-Ca fly ash composites by pressure infiltration technique and their characterization

Eight types of A356 Al–fly ash composites were produced by pressure infiltration of high-Ca lignite fly ash. This type of ash was used for the first time in Al-composites synthesis, and particularly by liquid metal infiltration techniques. After examining mineralogy and chemistry, specific, narrow ash size fractions were used for the synthesis of composites, and properties linked to microstructure and wear strength of the materials. The effect of using ground ash particles on the microstructure and tribological performance of the composites was also investigated. It was concluded that using fine, high-Ca ash particles can improve the properties of composites, and that using ash particles in a ground form can better facilitate the production process of MMCs.     

Seismic damage hazard analysis for requalification of nuclear power plant structures: methodology and application

A methodology for the evaluation of the annual probability of occurrence of post-elastic seismic damage in realistic structures is presented. The seismic damage hazard analysis (SDHA) is carried out here by coupling conventional seismic hazard analysis (SHA) for the site and the structural response to earthquakes of different intensities. The structural performance is statistically investigated by conducting appropriate non-linear dynamic analyses for a limited set of real ground-motion records that might potentially pose a threat to the structure at the site. The merging of these two approaches permits calculation of the seismic hazard faced by the structure in direct damage terms. The methodology is presented in this paper with the aid of a simple illustrative case study where the annual probability of damage and, eventually, failure of a power house steel structure is computed. This methodology can find practical applications in seismic retrofit of nuclear power plant structures and in the evaluation of seismic damage hazards in new structure designs.     

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.     

Antioxidant capacity,phenol, anthocyanin and ascorbic acid contents in raspberries,blackberries, red currants,gooseberries and Cornelian cherries

Raspberry (Rubus idaeus), blackberry (Rubus fructicosus), raspberry × blackberry hybrids, red currant (Ribes sativum), gooseberry (Ribes glossularia) and Cornelian cherry (Cormus mas) cultivars and native populations of varied pigmentation, originally from the Mediterranean area of Northern Greece, were assayed for antioxidant activity (determined as ferric reducing antioxidant power (FRAP) and deoxyribose protection), ascorbic acid, phenol, and anthocyanin contents. FRAP values ranged from 41 to 149 μmol ascorbic acid g⁻¹ dry weight and protection of deoxyribose ranged from 16.1% up to 98.9%. Anthocyanin content ranged from 1.3, in yellow-coloured fruit, up to 223 mg cyanidin-3-glucoside equivalents 100 g⁻¹ fresh weight in Cornelian cherry, whereas phenol content ranged from 657 up to 2611 mg gallic acid equivalents 100 g⁻¹dry weight. Ascorbic acid content ranged from 14 up to 103 mg 100 g⁻¹ fresh weight. The present study outlines that the native Cornelian cherry population is an extremely rich source of antioxidants, demonstrating its potential use as a food additive.     

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.