17174915
Diagnosis of tunneling opens
This paper resolves two issues regarding diagnosis of tunneling opens: efficient screening and accurate localization. In the first part, a test pattern selection and sorting algorithm is presented. It is shown that the presented algorithm saves I/sub DDQ/(t) test time without impacting on its effectiveness. The second part of this paper presents a locating algorithm which combines both VLV and I/sub DDQ/(t) test results. This technique is shown to be able to accurately locate the tunneling opens with higher resolution than commercial single stuck-at fault diagnosis tool.
8658255
Testing for tunneling opens
A tunneling-open failure mode is proposed and carefully studied. A circuit with a tunneling open could pass at-speed Boolean tests but fail VLV testing or I/sub DDQ/ testing. Theoretical calculations as well as Boolean and I/sub DDQ/ experiments confirm the existence of tunneling opens. The Murphy experimental data show that seven out of nine VLV-only failure circuits can be explained by this failure mode. All these seven circuits survived 366 hours temperature burn-in. Finally, a cost effective screening strategy is proposed.
4532231
On the Fixed Interval Due-date Scheduling Problem
Abstract We consider the nonpreemptive single machine scheduling problem with multiple due-dates (delivery dates), where the time between two consecutive due-dates is a constant. Given a set of jobs, we are interested in scheduling the jobs such that the sum of the total due-date cost and the total earliness cost is minimized with the constraint that each job must be finished at or before its due-date. We show that this problem is strongly NP-hard in general. We then analyze the problem where the number of due-dates is bounded by a given constant. We describe a pseudo-polynomial dynamic programming algorithm for this restricted problem. A heuristic is also provided and worst-case analysis is performed. An efficient algorithm is developed to solve the special case where all the job processing times are identical.
3090145
XGuard: a system for publishing XML documents without information leakage in the presence of data inference
In data publishing, if the data is published carelessly, public users could use common knowledge to infer more information from the published data, causing leakage of sensitive information. To address related research challenges, we develop a system called XGuard, which can help data owners publish a partial XML document without leaking sensitive information, even if public users can do inference. Specifically, the system has the following functionalities. i) It allows the data owner to define sensitive information and specify common knowledge as XML constraints. ii) Given a partial document, the system can validate if the document can cause information leakage due to common knowledge and how much data can be leaked. iii) The system can help the data owner interactively analyze the data inference and produce a secure valid partial document using the algorithms.
37859404
Single-machine scheduling to minimize the weighted number of early and tardy agreeable jobs
Abstract We consider a single-machine scheduling problem in which every job has a given target start time and a due-date. A job is early if processing commences before its start time and is tardy if it is completed after its due-date. The objective is to minimize the weighted number of early and tardy jobs, with the restriction that the start times and due-dates are “agreeable”, i.e., the start times must increase in the same sequence as the due-dates. We show that the problem is NP-complete in the strong sense. The complexity issues and algorithms for some special cases of this problem are discussed, and heuristic algorithms are developed for the general problem. Computational experiments are conducted to show the effectiveness of the heuristics.
1502705
Attack Probability Based Deterministic Key Predistribution Mechanism for Non-Uniform Sensor Deployment
Secure communication is a challenging problem in wireless sensor networks. In this paper, we investigate an attack probability-based deterministic key predistribution method for non-uniform sensor deployment. First, we design a reasonable model for group-based deployment to estimate the attack probability of each deployment group. Second, our proposed model further considers the location of data sink to meet the practical situation. Third, based on this attack model, a deterministic key predistribution mechanism is presented for group-based deployment. The proposed method mainly aims at preserving the integrity of network so that the functionality of each sensor node can be used. To evaluate the proposed method, the issues of memory overhead, communication overhead, and the fraction of total communications compromised after adversaries launch node capture attacks are studied analytically and numerically.
29013572
Semi-supervised Learning in Medical Image Database
This paper presents a novel graph-based algorithm for solving the semi-supervised learning problem. The graph-based algorithm makes use of the recent advances in stochastic graph sampling technqiue and a modeling of the labeling consistency in semi-supervised learning. The quality of the algorithm is empirically evaluated on a synthetic clustering problem. The semi-supervised clustering is also applied to the problem of symptoms classification in medical image database and shows promising results.