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A simple and powerful method named 'BOolean Operation-based Screening and Testing' (BOOST) is introduced. The method could find potential application as computationally and statistically usefool tool to perform future large-scale interaction mapping in genome-wide case-control studies.

Boolean networks have been proposed as potentially useful models for genetic control. An important aspect of these networks is the stability of their dynamics in response to small perturbations. Previous approaches to stability have assumed uncorrelated random network structure. Real gene networks typically have nontrivial topology significantly different from the random network paradigm. To address such situations, we present a general method for determining the stability of large Boolean networks of any specified network topology and predicting their steady-state behavior in response to small perturbations. Additionally, we generalize to the case where individual genes have a distribution of 'expression biases,' and we consider a nonsynchronous update, as well as extension of our method to non-Boolean models in which there are more than two possible gene states. We find that stability is governed by the maximum eigenvalue of a modified adjacency matrix, and we test this result by comparison with numerical simulations. We also discuss the possible application of our work to experimentally inferred gene networks.

The design of binary morphological operators that are translation-invariant and locally defined by a finite neighborhood window corresponds to the problem of designing Boolean functions. As in any supervised classification problem, morphological operators designed from a training sample also surfer from overfitting. Large neighborhood tends to lead to performance degradation of the designed operator. This work proposes a multilevel design approach to deal with the issue of designing large neighborhood-based operators. The main idea is inspired by stacked generalization (a multilevel classifier design approach) and consists of, at each training level, combining the outcomes of the previous level operators. The final operator is a multilevel operator that ultimately depends on a larger neighborhood than of the individual operators that have been combined. Experimental results show that two-level operators obtained by combining operators designed on subwindows of a large window consistently outperform the single-level operators designed on the full window. They also show that iterating two-level operators is an effective multilevel approach to obtain better results. Index Terms--Image processing, pattern recognition, machine learning, classifier design and evaluation, morphological operator, Boolean function, image operator learning, multilevel training, stacked generalization.

The design of thinned planar microstrip arrays under specific constraints concerning the impedance-matching condition of the array elements and the radiation pattern is presented. The radiation characteristics of the structure are extracted by applying the method-of-moments. The array design is based on a novel optimization method, which is a modified version of the boolean particle swarm optimization that employs velocity mutation (BPSO-vm). Apart from the optimization of the array geometry, the proposed method is applicable to other discrete-variable optimization problems. Moreover, the planar array design is coped with by means of other techniques, namely, a binary coded Genetic Algorithm, the binary Particle Swarm Optimization, and the Boolean PSO. The comparison of the above methods and the BPSO-vm shows the efficiency of the proposed technique. Index Terms--Artificial immune system, particle swarm optimization (PSO), planar arrays, thinned arrays.

Problem statement: How a host (the code consumer) can determine with certainty that a downloaded program received from untrusted source (the code producer) will maintain the confidentiality of the data it manipulates and it is safe to install and execute. Approach: The approach adopted for verifying that a downloaded program will not leak confidential data to unauthorized parties was based on the concept of Proof-Carrying Code (PCC). A mobile program (in its assembly form) was analyzed for information flow security based on the concept of proof-carrying code. The security policy was centered on a type system for analyzing information flows within assembly programs based on the notion of noninterference. Results: A verification tool for verifying assembly programs for information flow security was built. The tool certifies SPARC assembly programs for secure information flow by statically analyzing the program based on the idea of Proof-Carrying Code (PCC). The tool operated directly on the machine-code requiring only the inputs and outputs of the code annotated with security levels. The tool provided a windows user interface enabling the users to control the verification process. The proofs that untrusted program did not leak sensitive information were generated and checked on the host machine and if they are valid, then the untrusted program can be installed and executed safely. Conclusion: By basing proof-carrying code infrastructure on information flow analysis type-system, a sufficient assurance of protecting confidential data manipulated by the mobile program can be obtained. This assurance was come due to the fact that type systems provide a sufficient guarantee of protecting confidentiality. Key words: Proof-carrying code, secure information flow, assembly language, non-interference, INTRODUCTION Recent years have witnessed a growing interest of information flow security analysis due to their connection to the problem of protecting confidential data. The confidentiality policy concerns multi-level security [...]

Several analyses are conducted to explain the impact of the function perturbations on the steady-state distribution of genetic regulatory networks, like the Boolean networks (BNs). A single function perturbation is shown to affect only the network dynamics by changing the long-run distribution.

The recent algebraic attacks have received a lot of attention in cryptographic literature. The algebraic immunity of a Boolean function quantifies its resistance to the standard algebraic attacks of the pseudorandom generators using it as a nonlinear filtering or combining function. Very few results have been found concerning its relation with the other cryptographic parameters or with the rth-order nonlinearity. As recalled by Carlet at CRYPTO'06, many papers have illustrated the importance of the rth-order nonlinearity profile (which includes the first-order nonlinearity). The role of this parameter relatively to the currently known attacks has been also shown for block ciphers. Recently, two lower bounds involving the algebraic immunity on the rth-order nonlinearity have been shown by Carlet et al.. None of them improves upon the other one in all situations. In this paper, we prove a new lower bound on the rth-order nonlinearity profile of Boolean functions, given their algebraic immunity, that improves significantly upon one of these lower bounds for all orders and upon the other one for low orders. Index Terms--Algebraic attack, algebraic degree, algebraic immunity, annihilator, block cipher, Boolean function, higher order nonlinearity, stream cipher.

A set of basic organizational elements and a set of combinatory laws are analyzed to address the need for models of organization design as a science. The chemistry of organization offers a science that could be used to reveal organizational composition and the laws that are to be respected in designing organizations. Testable propositions are also discussed.

This is a design approach of software on image and attern recognition, while eliminating the color and gray code of an image for comparison. This approach is quite effective for black and white and color images or scenes. Here we select particular part or parts of a given image and we compare with the contents of template-image (biometric) database. This approach will be the key idea for all the verifications and identification systems of Automated Biometric Analysis. Here the input is image (black and white or color) the output is a set of picture elements (pixels), we have various approaches they are (1) Minterm (minimized term) extraction for black and white image analysis and handling various gray levels through variables like A, B, C, D and the inverse (negative) image of the same with corresponding gray levels can also be maintained by their inverse like A', B',C',D' ... respectively. (2) Maxterm (maximized term) the color images are generated by three primary colors (Red, Green, Blue) and this image can be recognized by both Minterm and Maxterm approaches and consider any one of the primary colors through Minterm approach and various gray levels of the primary color can be identified and analyzed by variables like A, B, C, D and the inverse (negative)image gray-levels can be performed by A',B',C',D', ... respectively. Further the remaining two primary colors will be treated by the inverse of the earlier function of selected primary color (but not by the inverse variables) i.e., (A, B, C, D,) of primary color approach (maxterm approach). Key words: Prime implicant, sum of products, gray, minterm, probabilistic determination, INTRODUCTION Image or Pattern recognition is concerned with the automatic detection or classification of object or events. Pattern recognition is mostly used for the recognition of medical images, magnetic images, [...]

A report on network decomposition method using Binary Decision Diagrams and manipulate Boolean functions for computing the reliability of networks such as computer, communications or power and its effectiveness is shown by several examples and experiments is presented.

The design and synthesis of a tandem protein kinase substrate peptide acting as a phosphate-mediated molecular memory is described. The analysis has shown that the information can be recorded on the substrate peptide by protein kinase-catalyzed phosphorylation and have provided clues for developing practical molecular-based processing and computing.

In this correspondence, we construct some new quadratic bent functions in polynomial forms by using the theory of quadratic forms over finite fields. The results improve some previous work. Moreover, we solve a problem left by Yu and Gong in 2006. Index Terms--Bent function, Boolean function, Hadamard transform, maximum nonlinearity, quadratic form, semi-bent function.

In this paper, a novel technique is proposed for a supervised classification of multisource images for the purpose of landslide hazard assessment. The method, known as the generalized positive Boolean function (GPBF), is developed for land cover classification based on the fusion of remotely sensed images of the same scene collected from multiple sources. It presents a framework for data fusion of multisource remotely sensed images, which consists of two approaches, referred to as the band generation process (BGP) and the positive Boolean function (PBF) classifier. The PBF classifier developed from a stack filter has been successfully applied in hyperspectral image classification. For the PBF to be effective for multispectral images, a multiple adaptation BGP is introduced to create a new set of additional bands especially accommodated to landslide classes. These bands include nonlinear normalized difference vegetation index data and morphological information in the form of digital elevation model (DEM)-derived slope values that originate from multiple sources. The performance of the proposed method is evaluated by fusing Systeme Pour l'Observation de ht Terre images and DEM information for land cover classification during the post 921 Earthquake period in Taiwan. Experimental results demonstrate the proposed GPBF multiclassification approach is suitable for land cover classification in Earth remote sensing and improves the precision of image classification compared to conventional classifiers. Index Terms--Band generation process (BGP), data fusion, digital elevation model (DEM), generalized positive Boolean function (GPBF), normalized difference vegetation index (NDVI), positive Boolean function (PBF), stack filter.

A common problem encountered in disciplines such as statistics, data analysis, signal processing, textual data representation, and neural network research, is finding a suitable representation of the data in the lower dimension space. One of the principles used for this reason is a factor analysis. In this paper, we show that Hebbian learning and a Hopfield-like neural network could be used for a natural procedure for Boolean factor analysis. To ensure efficient Boolean factor analysis, we propose our original modification not only of Hopfield network architecture but also its dynamics as well. In this paper, we describe neural network implementation of the Boolean factor analysis method. We show the advantages of our Hopfield-like network modification step by step on artificially generated data. At the end, we show the efficiency of the method on artificial data containing a known list of factors. Our approach has the advantage of being able to analyze very large data sets while preserving the nature of the data. Index Terms--Associative memory, Boolean factor analysis, concepts search, dimensionality reduction, features clustering, Hopfield-like neural network, information retrieval, neural network application, neural network architecture, recurrent neural network, statistics, unsupervised learning.

A new concept in the way information can be protected at the molecular scale, namely a password entry, considered as the front line of defense against intruders, is reported. The principles of molecular Boolean logic are harnessed to design a kinetically controlled, priority-AND molecular logic gate, capable of authorizing different photoionic passwords.

Let N(d, d[perpendicular to]) denote the minimum length n of a linear code C with d and d[perpendicular to] , where d is the minimum Hamming distance of C and d[perpendicular to] is the minimum Hamming distance of C[perpendicular to]. In this correspondence, we show lower bounds and an upper bound on N(d, d[perpendicular to]). Further, for small values of d and d[perpendicular to], we determine N(d, d[perpendicular to]) and give a generator matrix of the optimum linear code. This problem is directly related to the design method of cryptographic Boolean functions suggested by Kurosawa et al. Index Terms--Boolean function, dual distance, linear code, minimum distance.

Abstract: A testable design with a universal test set for single stuck-at zero and stuck-at one faults of Reed-Muller canonical form of Exclusive-OR sum of product logic expressions is proposed. [...]

In this correspondence, the constructions and enumerations of all bent functions represented by a polynomial form of [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] are presented for special cases of n. Using an iterative approach, the construction of bent functions of n variables with degree n/2 is also provided using the constructed quadratic bent functions. Index Terms--Bent functions, Boolean functions, maximum nonlinearity, semi-bent functions.

Recently, algebraic attacks have received a lot of attention in the cryptographic literature. It has been observed that a Boolean function f used as a cryptographic primitive, and interpreted as a multivariate polynomial over [F.sub.2], should not have low degree multiples obtained by multiplication with low degree onzero functions. In this paper, we show that a Boolean function having low nonlinearity is (also) weak against algebraic attacks, and we extend this result to higher order nonlinearities. Next, we present enumeration results on linearly independent annihilators. We also study certain classes of highly nonlinear resilient Boolean functions for their algebraic immunity. We identify that functions having low-degree subfunctions are weak in terms of algebraic immunity, and we analyze some existing constructions from this viewpoint. Further, we present a construction method to generate Boolean functions on n variables with highest possible algebraic immunity [n/2] (this construction, first presented at the 2005 Workshop on Fast Software Encryption (FSE 2005), has been the first one producing such functions). These functions are obtained through a doubly indexed recursive relation. We calculate their Hamming weights and deduce their nonlinearities; we show that they have very high algebraic degrees. We express them as the sums of two functions which can be obtained from simple symmetric functions by a transformation which can be implemented with an algorithm whose complexity is linear in the number of variables. We deduce a very fast way of computing the output to these functions, given their input. Index Terms--Algebraic attacks, annihilators, Boolean functions, nonlinearity, stream ciphers, Walsh spectrum.