Self-organized public-key management for mobile ad hoc networks

In contrast with conventional networks, mobile ad hoc networks usually do not provide online access to trusted authorities or to centralized servers, and they exhibit frequent partitioning due to link and node failures and to node mobility. For these reasons, traditional security solutions that require online trusted authorities or certificate repositories are not well-suited for securing ad hoc networks. We propose a fully self-organized public-key management system that allows users to generate their public-private key pairs, to issue certificates, and to perform authentication regardless of the network partitions and without any centralized services. Furthermore, our approach does not require any trusted authority, not even in the system initialization phase.     

Reducible rank codes and their applications to cryptography

We present a new family of so-called reducible rank codes which are a generalization of rank product codes . This family includes maximal rank distance (MRD) codes for lengths n>N in the field F/sub N/. We give methods for encoding and decoding reducible rank codes. A public key cryptosystem based on these codes and on the idea of a column scrambler is proposed. The column scrambler "mixes" columns of a generator (parity-check) matrix of a code. It makes the system more resistant to structural attacks such as Gibson's attacks. Possible attacks on the system are thoroughly studied. The system is found to be secure against known attacks for public keys of about 16 kbits and greater.     

A multiwinding modeling method for high frequency transformers and inductors

This paper presents a method to obtain an electric model for transformers and inductors, including both frequency and geometry effects in the windings, which can be linked with existing core models. One-dimensional distributions for magnetic and electric fields are assumed, and from Maxwell's equations an equivalent electric circuit is easily obtained. This equivalent circuit has been included in analog simulators (Spice, AnalogWorkBench, Saber ...), and comparisons between measured and simulated results are shown, both in time domain and in AC sweep, which verify the model accuracy. The model described in this paper allows designers to deal with key issues in the design of high-frequency magnetic components (copper losses, leakage inductance, skin and proximity effects) by using analog simulators, which are usually more familiar to them than finite-element analysis tools.     

On the convergence of the inverses of Toeplitz matrices and its applications

Many issues in signal processing involve the inverses of Toeplitz matrices. One widely used technique is to replace Toeplitz matrices with their associated circulant matrices, based on the well-known fact that Toeplitz matrices asymptotically converge to their associated circulant matrices in the weak sense. This often leads to considerable simplification. However, it is well known that such a weak convergence cannot be strengthened into strong convergence. It is this fact that severely limits the usefulness of the close relation between Toeplitz matrices and circulant matrices. Observing that communication receiver design often needs to seek optimality in regard to a data sequence transmitted within finite duration, we define the finite-term strong convergence regarding two families of matrices. We present a condition under which the inverses of a Toeplitz matrix converges in the strong sense to a circulant matrix for finite-term quadratic forms. This builds a critical link in the application of the convergence theorems for the inverses of Toeplitz matrices since the weak convergence generally finds its usefulness in issues associated with minimum mean squared error and the finite-term strong convergence is useful in issues associated with the maximum-likelihood or maximum a posteriori principles.     

Extracting Light from Polymer Light‐Emitting Diodes Using Stamped Bragg Gratings

In this paper, we describe a method for increasing the external efficiency of polymer light‐emitting diodes (LEDs) by coupling out waveguided light with Bragg gratings. We numerically model the waveguide modes in a typical LED structure and demonstrate how optimizing layer thicknesses and reducing waveguide absorption can enhance the grating outcoupling. The gratings were created by a soft‐lithography technique that minimizes changes to the conventional LED structure. Using one‐dimensional and two‐dimensional gratings, we were able to increase the forward‐directed emission by 47 % and 70 %, respectively, and the external quantum efficiency by 15 % and 25 %.     

Blind feedforward cyclostationarity-based timing estimation for linear modulations

By exploiting a general cyclostationary (CS) statistics-based framework, this letter develops a rigorous and unified asymptotic (large sample) performance analysis setup for a class of blind feedforward timing epoch estimators for linear modulations transmitted through time nonselective flat-fading channels. Within the proposed CS framework, it is shown that several estimators proposed in the literature can be asymptotically interpreted as maximum likelihood (ML) estimators applied on a (sub)set of the second- (and/or higher) order statistics of the received signal. The asymptotic variance of these ML estimators is established in closed-form expression and compared with the modified Crame/spl acute/r-Rao bound. It is shown that the timing estimator proposed by Oerder and Meyr achieves asymptotically the best performance in the class of estimators which exploit all the second-order statistics of the received signal, and its performance is insensitive to oversampling rates P as long as P/spl ges/3. Further, an asymptotically best consistent estimator, which achieves the lowest asymptotic variance among all the possible estimators that can be derived by exploiting jointly the second- and fourth-order statistics of the received signal, is also proposed.     

An introduction of the condition class space with continuous value discretization and rough set theory

The granularity of an information system has an incumbent effect on the efficacy of the analysis from many machine learning algorithms. An information system contains a universe of objects characterized and categorized by condition and decision attributes. To manage the concomitant granularity, a level of continuous value discretization (CVD) is often undertaken. In the case of the rough set theory (RST) methodology for object classification, the granularity contributes to the grouping of objects into condition classes with the same condition attribute values. This article exposits the effect of a level of CVD on the subsequent condition classes constructed, with the introduction of the condition class space—the domain within which the condition classes exist. This domain elucidates the association of the condition classes to the related decision outcomes—reflecting the inexactness incumbent when a level of CVD is undertaken. A series of measures is defined that quantify this association. Throughout this study and without loss of generality, the findings are made through the RST methodology. This further offers a novel exposition of the relationship between all the condition attributes and the RST‐related reducts (subsets of condition attributes). © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 173–191, 2006.     

Platinum Binuclear Complexes as Phosphorescent Dopants for Monochromatic and White Organic Light‐Emitting Diodes

Efficient blue‐, green‐, and red‐light‐emitting organic diodes are fabricated using binuclear platinum complexes as phosphorescent dopants. The series of complexes used here have pyrazolate bridging ligands and the general formula C^∧NPt(μ‐pz)₂PtC^∧N (where C^∧N = 2‐(4′,6′‐difluorophenyl)pyridinato‐N,C^2′, pz = pyrazole ( 1 ), 3‐methyl‐5‐tert‐butylpyrazole ( 2 ), and 3,5‐bis(tert‐butyl)pyrazole ( 3 )). The Pt–Pt distance in the complexes, which decreases in the order 1 > 2 > 3 , solely determines the electroluminescence color of the organic light‐emitting diodes (OLEDs). Blue OLEDs fabricated using 8 % 1 doped into a 3,5‐bis(N‐carbazolyl)benzene (mCP) host have a quantum efficiency of 4.3 % at 120 Cd m^–2, a brightness of 3900 Cd m^–2 at 12 V, and Commission Internationale de L'Eclairage (CIE) coordinates of (0.11, 0.24). Green and red OLEDs fabricated with 2 and 3 , respectively, also give high quantum efficiencies (～ 6.7 %), with CIE coordinates of (0.31, 0.63) and (0.59, 0.46), respectively. The current‐density–voltage characteristics of devices made using dopants 2 and 3 indicate that hole trapping is enhanced by short Pt–Pt distances (< 3.1 Å). Blue electrophosphorescence is achieved by taking advantage of the binuclear molecular geometry in order to suppress dopant intermolecular interactions. No evidence of low‐energy emission from aggregate states is observed in OLEDs made with 50 % 1 doped into mCP. OLEDs made using 100 % 1 as an emissive layer display red luminescence, which is believed to originate from distorted complexes with compressed Pt–Pt separations located in defect sites within the neat film. White OLEDs are fabricated using 1 and 3 in three different device architectures, either with one or two dopants in dual emissive layers or both dopants in a single emissive layer. All the white OLEDs have high quantum efficiency (～ 5 %) and brightness (～ 600 Cd m^–2 at 10 V).     

Intelligent process analytics for CRM

Many organisations use decision models in their processes such as tables or trees to provide decision support to their operational divisions. For example, in fault management, customer contact centre operators usually use a decision model in the form of prescribed interviews. Based on the answers given by customers, the operator navigates through the decision model to reach an assessment of the problem. In order to achieve customer satisfaction and operational excellence, it is very important to constantly monitor the performance of a decision model not only on an overall level, but also on the level of individual decisions. In this paper we present a configurable business process analytics tool, known as the intelligent Universal Service Management System, that constantly monitors decision data and is capable of optimising the decisions based on high-level business objectives. We explain the various features of the software and show how it can be used to optimise decision processes. We also show how we can easily provide a customised version to monitor the performance of provision processes.