675942
Resource bounded randomness and computational complexity
The following is a survey of resource bounded randomness concepts and their relations to each other. Further, we introduce several new resource bounded randomness concepts corresponding to the classical randomness concepts, and show that the notion of polynomial time bounded Ko randomness is independent of the notions of polynomial time bounded Lutz, Schnorr and Kurtz randomness. Lutz has conjectured that, for a given time or space bound, the corresponding resource bounded Lutz randomness is a proper renement of resource bounded Schnorr randomness. This conjecture is answered for the case of polynomial time bound. Moreover, we will show that polynomial time bounded Schnorr randomness is a proper renement of polynomial time bounded Kurtz randomness. In contrast to this result, we show that the notions of polynomial time bounded Lutz, Schnorr and Kurtz randomness coincide in the case of recursive sets, thus it suces to study the notion of resource bounded Lutz randomness in the context of complexity theory. The stochastic properties of resource bounded random sequences will be discussed in detail. Schnorr has already shown that the law of large numbers holds for p-random sequences. We will show that another important law in probability theory, the law of the iterated logarithm, holds for p-random sequences too. Hence almost all sets in the exponential time complexity class are \hard" from the viewpoint of statistics. c 2000 Elsevier Science B.V. All rights reserved.
8204880
Privacy aware data generation for testing database applications
Testing of database applications is of great importance. A significant issue in database application testing consists in the availability of representative data. In this paper, we investigate the problem of generating a synthetic database based on a-priori knowledge about a production database. Our approach is to fit general location model using various characteristics (e.g., constraints, statistics, rules) extracted from the production database and then generate the synthetic data using model learnt. The generated data is valid and similar to real data in terms of statistical distribution, hence it can be used for functional and performance testing. As characteristics extracted may contain information which may be used by attacker to derive some confidential information about individuals, we present our disclosure analysis method which applies cell suppression technique for identity disclosure analysis and perturbation for value disclosure.
8247434
NP-Hard Sets are Superterse Unless NP is Small
Abstract We show that the class P- mc ( n ) of polynomial time n -membership comparable sets (defined by Ogihara, 1995) has p -measure 0. Using this result, we will show that the class of sets which are ⩽ tt P -reducible to some P-selective set has p -measure 0. Furthermore, we will show that if NP does not have p -measure 0 then no ⩽ tt p -hard set for NP is P-approximable.
5782664
A Separation of Two Randomness Concepts
In this paper we give an affirmative answer to a conjecture by Lutz (1992). That is, we will show that there is a Schnorr random sequence which is not rec-random.
5215725
Linear Complexity versus Pseudorandomness: On Beth and Dai's Result
Beth and Dai studied in their Eurocrypt paper [1] the relationship between linear complexity (that is, the length of the shortest Linear Feedback Shift Register that generates the given strings) of strings and the Kolmogorov complexity of strings. Though their results are correct, some of their proofs are incorrect. In this note, we demonstrate with a counterexample the reason why their proofs are incorrect and we prove a stronger result. We conclude our note with some comments on the use of the LIL test (the law of the iterated logarithm) for pseudorandom bits generated by pseudorandom generators.
8968053
Resource-Bounded Balanced Genericity, Stochasticity and Weak Randomness
We introduce balanced t(n)-genericity which is a refinement of the genericity concept of Ambos-Spies, Fleischhack and Huwig [2] and which in addition controls the frequency with which a condition is met. We show that this concept coincides with the resource-bounded version of Church's stochasticity [6]. By uniformly describing these concepts and weaker notions of stochasticity introduced by Wilber [19] and Ko [11] in terms of prediction functions, we clarify the relations among these resource-bounded stochasticity concepts. Moreover, we give descriptions of these concepts in the framework of Lutz's resource-bounded measure theory [13] based on martingales: We show that t(n)-stochasticity coincides with a weak notion of t(n)-randomness based on so-called simple martingales but that it is strictly weaker than t(n)-randomness in the sense of Lutz.
1861851
Isolated regions in video coding
Different types of prediction are applied in modern video coding. While predictive coding improves compression efficiency, the propagation of transmission errors becomes more likely. In addition, predictive coding brings difficulties to other aspects of video coding, including random access, parallel processing, and scalability. In order to combat the negative effects, video coding schemes introduce mechanisms such as slices and intracoding, to limit and break the prediction. This paper proposes the use of the isolated regions coding tool that jointly limits in-picture prediction and interprediction on a region-of-interest basis. The tool can be used to provide random access points from non-intrapictures and to respond to intrapicture update requests. Furthermore, it can be applied as an error-robust macroblock mode decision method and can be used in combination with unequal error protection. Finally, it enables mixing of scenes, which is useful in coding of masked scene transitions.
7748348
Shape fitting with outliers
Given a set <i>H</i> of <i>n</i> hyperplanes in <i>R<sup>d</sup></i>, we present an algorithm that <i>e</i>-approximates the extent between the top and bottom <i>k</i> levels of the arrangement of <i>H</i> in time <i>O(n + (k/e)<sup>c</sup>)</i>, where <i>c</i> is a constant depending on <i>d</i>. The algorithm relies on computing a subset of <i>H</i> of size.<i>O(k/e<sup>d-1</sup>)</i>, in near linear time, such that the <i>k</i>-level of the arrangement of the subset approximates that of the original arrangement. Using this algorithm, we propose efficient approximation algorithms for shape fitting with outliers for various shapes. This is the first algorithms to handle outliers efficiently for the shape fitting problems considered.
44707452
Diagnosis of clustered faults for identical degree topologies
Huang et al, [1998] studied the diagnosis of clustered faults and wafer testing. They proposed a diagnosis algorithm for a probabilistic fault model in simple rectangular grid structures. In this paper, we extend their results and study the diagnosis algorithm for arbitrary identical degree topologies. Our results are useful and valid for a large class of topologies. We investigate the local and global performance of the algorithm under several important fault distributions: Bernoulli failure distribution, Gamma failure distribution, and exponential failure distribution. We demonstrate that the diagnosis scheme can identify almost all nodes successfully even if the percentage of fault-free units is low (much lower than 50%) while almost all units are guaranteed to be correctly identified. In addition, we show that the performance of the algorithm is insensitive to the changes of the percentage.
62532074
A decision-theoretic approach to the evaluation of information retrieval systems
Evaluation research on information retrieval (IR) systems has thus far been narrowly focused and disjointed. This research attempts to narrow the gap by providing a comprehensive and integrated multiple criteria decision-theoretic approach for the evaluation of IR systems. The approach, which is based on the Analytic Hierarchy Process (AHP), is illustrated in the context of a domain-specific IR system. The novelty of this approach lies in the focus on the user aspect and the application of decision-making theories in the IR field.
40360434
Measurement of the cognitive functional complexity of software
One of the central problems in software engineering is its inherited complexity. It is recognized that cognitive informatics plays an important role in understanding the fundamental characteristics of software. This paper models the cognitive weights of basic control structures of software, and develops a new concept of cognitive functional size for measuring software complexity. Comparative case studies between the cognitive functional size and physical sizes of 20 programs are conducted. It is found that for a given design, although the physical sizes of software may vary in a wide range, the cognitive functional sizes are much stable and independent from implementation technologies and programming languages. Therefore, the cognitive functional size provides a novel, stable and practical software complexity measurement and is helpful to explain the fundamental nature of software complexity in the phase of design, implementation, or maintenance in software engineering.