748152
On-line testing of multi-source noise-induced errors on the interconnects and buses of system-on-chips
With processors and system-on-chips using nano-meter technologies, several design and test efforts have been recently developed to eliminate and test for many emerging DSM (deep sub-micron) noise effects. In this paper, we show the emergence of multi-source noise effects, where multiple DSM noise sources combine to produce functional and timing errors even when each separate noise source itself does not. We show the dynamic nature of multi-source noise, and the need for on-line testing to detect such noise errors. We propose a double-sampling data checking based low-cost on-line error detection circuit to test for such noise effects in on-chip buses. Based on the proposed circuit, an effective and efficient testing methodology has been developed to facilitate online testing for generic on-chip buses. The applicability of this methodology is demonstrated through embedding the on-line detection circuit in a bus design. The validated design shows the effectiveness of the proposed testing methodology for multi-source noise-induced errors in global interconnects and buses.
10708118
Fault modeling and simulation for crosstalk in system-on-chip interconnects
System-on-chips (SOCs) using ultra deep sub-micron (DSM) technologies and GHz clock frequencies have been predicted by the 1997 SIA Road Map. Recent studies, as well as experiments reported in this paper, show significant crosstalk effects in long on-chip interconnects of GHz DSM chips. Recognizing the importance of high-speed, reliable interconnects in GHz SOCs, we address in this paper the problem of testing for glitch and delay errors caused by crosstalk in buses and interconnects between components of a SOC. Since it is not possible to explicitly test for all the possible process variations and defects that can lead to crosstalk errors in SOC interconnects, we present an abstract model, Maximum Aggressor (MA) fault model, and its test requirements. The attractiveness of the model is that it can abstract crosstalk defects in interconnects with a linear number of faults, while the corresponding MA tests provide complete coverage for all level defects related to cross-coupling capacitance the interconnects. A SPICE-level fault simulation methodology is presented which allows simulation of a small subset of the potentially exponential number of defects. The simulation methodology also enables validation of the proposed fault model and the resulting test set.
15518950
Effective and Scalable Authorship Attribution Using Function Words
Techniques for identifying the author of an unattributed document can be applied to problems in information analysis and in academic scholarship. A range of methods have been proposed in the research literature, using a variety of features and machine learning approaches, but the methods have been tested on very different data and the results cannot be compared. It is not even clear whether the differences in performance are due to feature selection or other variables. In this paper we examine the use of a large publicly available collection of newswire articles as a benchmark for comparing authorship attribution methods. To demonstrate the value of having a benchmark, we experimentally compare several recent feature-based techniques for authorship attribution, and test how well these methods perform as the volume of data is increased. We show that the benchmark is able to clearly distinguish between different approaches, and that the scalability of the best methods based on using function words features is acceptable, with only moderate decline as the difficulty of the problem is increased.
14058950
A Profit-Based Business Model for Evaluating Rule Interestingness
Different types of rules are mined from transaction databases often with the goal of improving sales and services. In this paper, we link the interestingness of rules with the context of business marketing. We consider the profits generated from some specific marketing strategies that are developed based on particular discovered rules. This leads to a profit-based business model for evaluating rule interestingness. With this additional utility, we investigate some relationships between different marketing strategies and fundamental properties of rules for profit increasing.
17542443
Using Relative Entropy for Authorship Attribution
Authorship attribution is the task of deciding who wrote a particular document. Several attribution approaches have been proposed in recent research, but none of these approaches is particularly satisfactory; some of them are ad hoc and most have defects in terms of scalability, effectiveness, and efficiency. In this paper, we propose a principled approach motivated from information theory to identify authors based on elements of writing style. We make use of the Kullback-Leibler divergence, a measure of how different two distributions are, and explore several different approaches to tokenizing documents to extract style markers. We use several data collections to examine the performance of our approach. We have found that our proposed approach is as effective as the best existing attribution methods for two class attribution, and is superior for multi-class attribution. It has lower computational cost and is cheaper to train. Finally, our results suggest this approach is a promising alternative for other categorization problems.
31784785
Tiger: Educational Research in the Age of the Internet
5871849
Exactly-once delivery in a content-based publish-subscribe system
This paper presents a general knowledge model for propagating information in a content-based publish-subscribe system. The model is used to derive an efficient and scalable Protocol for exactly-once delivery to large numbers (tens of thousands per broker) of content-based subscribers in either publisher order or uniform total order Our protocol allows intermediate content filtering at each hop, but requires persistent storage only at the publishing site. It is tolerant of message drops, message reorderings, node failures, and link failures, and maintains only "soft" state at intermediate nodes. We evaluate the performance of our implementation both under failure-free conditions and with fault injection.