9166431
Practical information flow control in Web-based information systems
This paper presents a practical application of language-based information-flow control, namely, a domain-specific Web scripting language designed for interfacing with databases. The primary goal is to provide strong enforcement of confidentiality and integrity policies: confidential data can be released only in permitted ways and trustworthy data must result from expected computations or conform to expected patterns. Such security policies are specified in the database layer and statically enforced for the rest of the system in an end-to-end fashion. In contrast with existing Web-scripting languages, which provide only ad hoc mechanisms for information security, the scripting language described here uses principles based on the well-studied techniques in information-flow type systems. However, because Web scripts often need to downgrade confidential data and manipulated untrusted user input, they require practical and convenient ways of downgrading secure data. To achieve this goal, the language allows safe downgrading according to downgrading policies specified by the programmer. This novel, pattern-based approach provides a practical instance of recent work on delimited release and relaxed noninterference and extends that work by accounting for integrity policies.
10769697
Advanced control flow in Java card programming
Java Card technology simplifies the development of smart card applications by providing a high-level programming language similar to Java. However, the master-slave programming model used in current Java Card platform creates control flow difficulties when writing complex card programs, making it inconvenient, tedious, and error-prone to implement Java Card applications. This paper examines these drawbacks of the master-slave model and proposes a concurrent thread model for developing future Java Card programs, which is much closer to conventional Java network programming. This paper also presents a code translation algorithm and a corresponding tool that makes it possible to write card programs in the concurrent thread model without losing compatibility with the existing Java Card API.
46149042
Data reconciliation for real-time optimization of an industrial coke-oven-gas purification process
Online optimization is more and more used in the chemical industry to run a process near its optimum operating condition by providing real-time computed optimal set-points to the distributed control system. Process measurements are necessary for these applications to determine the actual state of the process and to increase the accuracy of the model with parameter estimation techniques. However, these measurements usually contain random as well as gross errors which have to be identified and eliminated before the measurements are used for online optimization. In this contribution, a data reconciliation approach was integrated into an online optimization framework for the ammonia hydrogen sulfide circulation scrubbing, a common industrial coke-oven-gas purification process. We used a rigorous rate-based model to describe this reactive absorption and desorption process. To increase the accuracy of the model, we estimated several process parameters using a sequential parameter estimation approach. Data reconciliation was performed based on simple component balances to achieve model-consistent data and to identify measurement biases. The model was then validated online on a pilot plant by connecting the estimation package through the process control system. Based on the online measured data, operating cost minimization was carried out and the computed optimal set-points realized real-time. A satisfactory agreement between measured data and optimization was achieved.
1602916
Testing algorithms is like testing students
In this paper, we apply methods from educational testing to measure the reliability of an IR collection.
14905620
Unscented Kalman filter for visual curve tracking
Abstract Visual contour tracking in complex background is a difficult task. The measurement model is often nonlinear due to clutter in images. Traditional visual trackers based on Kalman filters employ simple linear measurement models, and often collapse during the tracking process. This paper presents a new contour tracker based on unscented Kalman filter that is superior to extended Kalman filter both in theory and in many practical situations. The new tracker employs a more accurate nonlinear measurement model, without computation of a Jacobian matrix. During each time step, the tracker makes multiple measurements in terms of the set of appropriately chosen sample points, thus obtaining the best observation according to the measurement density. The resulting algorithm is able to obtain a more exact estimate of the state of the system, while having the same order of complexity as that of an extend Kalman Filter. The experiments show that the new algorithm is superior to those based on Kalman filters.
6241696
A formally verified application-level framework for real-time scheduling on POSIX real-time operating systems
We present a framework, called meta scheduler, for implementing real-time scheduling algorithms. The meta scheduler is a portable middleware layer component designed for implementations over POSIX-compliant operating systems. It accommodates pluggable real-time scheduling algorithms while offering the flexibility of platform independence - the singular underlying OS requirement is the now nearly ubiquitous POSIX compliance. The versatility of pluggable schedulers positions the meta scheduler for deployment in an interoperable heterogeneous real-time environment. We present the design of the meta scheduler and outline its implementation. Furthermore, we present a mechanized correctness verification using the UPPAAL model checker. Prototype implementation of the meta scheduler over QNX Neutrino real-time operating system demonstrates high performance and a small footprint.
13006853
Novel likelihood estimation technique based on boosting detector
This paper presents novel likelihood estimation to be used for particle filter based object tracking. The likelihood estimation is built upon cascade object detector trained with Gentle AdaBoost (GAB), in order to capture the probability of existence of object. Two strategies are adopted to construct the likelihood functions: probability-intra-stage (PIS) corresponding to real output of each weak classifier in the same stage, and probability-outer-stage (POS) corresponding to the depth reached in the cascade detector. Five kinds of likelihood functions are thus proposed based on the trained GAB detector. Our experiment shows the likelihood functions are able to characterize probabilistically the existence of object accurately, having much higher confidence value in object regions than that in background, and that the integral strategy of PIS and POS is the best choice.