An Integrated Experimental and Computational System for the Thermal Characterization of Complex Three-Dimensional Submicron Electronic Devices

This work presents the creation of a coupled analysis engine and experimental system capable of fully characterizing the thermal behavior of complex, 3D, active, submicron, electronic devices. First, the surface temperature field of an activated device is non-invasively measured with submicron spatial resolution. Next, the thermal conductivity of each thin-film layer composing the device is measured and a numerical model is built using these values. The measured temperature distribution map is then used as input for an ultra-fast inverse computational solution to fully characterize the thermal behavior of the complex 3D device. By bringing together measurement and computation, it becomes possible for the first time to non-invasively extract the 3D thermal behavior of nanoscale embedded features that cannot otherwise be accessed. The power of the method was demonstrated by verifying that it can extract details of interest of a representative MOSFET device.     

Efficient and flexible anonymization of transaction data

Transaction data are increasingly used in applications, such as marketing research and biomedical studies. Publishing these data, however, may risk privacy breaches, as they often contain personal information about individuals. Approaches to anonymizing transaction data have been proposed recently, but they may produce excessively distorted and inadequately protected solutions. This is because these approaches do not consider privacy requirements that are common in real-world applications in a realistic and flexible manner, and attempt to safeguard the data only against either identity disclosure or sensitive information inference. In this paper, we propose a new approach that overcomes these limitations. We introduce a rule-based privacy model that allows data publishers to express fine-grained protection requirements for both identity and sensitive information disclosure. Based on this model, we also develop two anonymization algorithms. Our first algorithm works in a top-down fashion, employing an efficient strategy to recursively generalize data with low information loss. Our second algorithm uses sampling and a combination of top-down and bottom-up generalization heuristics, which greatly improves scalability while maintaining low information loss. Extensive experiments show that our algorithms significantly outperform the state-of-the-art in terms of retaining data utility, while achieving good protection and scalability.     

Development and industrial application of soft sensors with on-line Bayesian model updating strategy

This paper deals with the issues associated with the development of data-driven models as well as model update strategy for soft sensor applications. A practical yet effective solution is proposed. Key process variables that are difficult to measure are commonly encountered in practice due to limitations of measurement techniques. Even with appropriate instruments, some measurements are only available through off-line laboratory analysis with typical sampling intervals of several hours. Soft sensors are inferential models that can provide continuous on-line prediction of hidden variables; such models are capable of combining real-time measurements with off-line lab data. Due to the prevalence of plant-model mismatch, it is important to update the model using the latest reference data. In this paper, parameters of data-driven models are estimated using particle filters under the framework of expectation–maximization (EM) algorithms. A Bayesian methodology for model calibration strategy is formulated. The proposed framework for soft sensor development is applied to an industrial process to provide on-line prediction of a quality variable.     

A global study of Kondepudi’s pitchfork

This model reaction, studied so effectively by Kondepudi and his co-workers, is transferred here to a stirred tank. It is shown that, though the rate constants for the two pathways are identical, the stable steady state can still be one in which one or the other pathway is favoured enormously. We are indebted for partial support to the National Science Foundation through heir grant CPE 8112292.     

Online pairing of VoIP conversations

This paper answers the following question; given a multiplicity of evolving 1-way conversations, can a machine or an algorithm discern the conversational pairs in an online fashion, without understanding the content of the communications? Our analysis indicates that this is possible, and can be achieved just by exploiting the temporal dynamics inherent in a conversation. We also show that our findings are applicable for anonymous and encrypted conversations over VoIP networks. We achieve this by exploiting the aperiodic inter-departure time of VoIP packets, hence trivializing each VoIP stream into a binary time-series, indicating the voice activity of each stream. We propose effective techniques that progressively pair conversing parties with high accuracy and in a limited amount of time. Our findings are verified empirically on a dataset consisting of 1,000 conversations. We obtain very high pairing accuracy that reaches 97% after 5 min of voice conversations. Using a modeling approach we also demonstrate analytically that our result can be extended over an unlimited number of conversations.     

The Distribution of Active ingredients in Supported Catalysts Prepared by Impregnation

Supported catalysts, one of the commonest forms of heterogeneous catalysts in practical use, consist of small crystallites of a catalytically active component dispersed in a porous support of high surface area. Impregnation of the support with an aqueous solution of a compound containing the appropriate catalytic component is an important and frequently used method of preparing this type of catalyst. A nonaqueous solution should be used if the sup port surface is hydrophobic or if hydrolysis of the support surface is to be avoided. In its simplest form, this impregnation method involves three steps: (1) contacting the support with impregnating solution for a certain period of time, (2) drying the support to remove the imbibed liquid, and (3) activating the catalyst by calcination, reduction, or other appropriate treatment.