On the linear complexity of Sidel'nikov sequences over nonprime fields

We introduce a generalization of Sidel'nikov sequences for arbitrary finite fields. We show that several classes of Sidel'nikov sequences over arbitrary finite fields exhibit a large linear complexity. For Sidel'nikov sequences over F-8 we provide exact values for their linear complexity

A Simple Computational Model for Acceptance/Rejection of Binary Sequence Generators

A simple binary model to compute the degree of balancedness in the output sequence of LFSR-combinational generators has been developed. The computational method is based exclusively on the handling of binary strings by means of logic operations. The proposed model can serve as a deterministic alternative to existing probabilistic methods for checking balancedness in binary sequence generators. The procedure here described can be devised as a first selective criterium for acceptance/rejection of this type of generators.Comment: 16 pages, 0 figure

Remarks on the k-error linear complexity of p(n)-periodic sequences

Recently the first author presented exact formulas for the number of 2ⁿn-periodic binary sequences with given 1-error linear complexity, and an exact formula for the expected 1-error linear complexity and upper and lower bounds for the expected k-error linear complexity, k >2, of a random 2ⁿn-periodic binary sequence. A crucial role for the analysis played the Chan-Games algorithm. We use a more sophisticated generalization of the Chan-Games algorithm by Ding et al. to obtain exact formulas for the counting function and the expected value for the 1-error linear complexity for pⁿn-periodic sequences over Fp, p prime. Additionally we discuss the calculation of lower and upper bounds on the k-error linear complexity of pⁿn-periodic sequences over Fp

Fluorescence Spectrometry to Quantify Percent Wood Failure in Adhesive Bonds

Structural engineered wood manufacturers need a quantitative measurement technique to determine the ratio of wood to adhesive failure in their shear specimens. Visual estimation of percent wood failure has long stood as an extremely subjective quality control approach according to ASTM D5266 – Standard Practice for Estimating the Percentage of Wood Failure in Adhesive Bonded Joints. The inherent variability between readers often leads to completely different estimates for the same specimen. A UV-VIS spectrometer, coupled with a consistent light source and probe, offers an economic mode of chemometrics for automating the current standard and minimizing said subjectivity. Robust, repeatable, and open-source predictive models will provide a technician with a timely and accurate percent wood failure value after simply placing a lap or block shear specimen under the light probe. This approach is expected to maintain accuracy within five percent wood failure (ASTM D5266) and be as fast or faster than a trained technician. Three sets of phenol-formaldehyde bonded lap-shear specimens were provided with original ASTM visual percent wood failure estimates by trained technicians from outside organizations. High resolution images of each shear surface were then taken, and these images were evaluated with a grid overlay for an additional, more precise set of percent wood failure estimates. Thereafter, each shear surface was scanned with a probe connected to two separate light sources and data was acquired by a spectrometer. The data, having wavelengths (nm) as explanatory variables and intensity (counts) as dependent variables, was then modelled via RStudio with Partial Least Squares Regression and Simple Linear Regression using the two different wood failure estimates for each population as predictor variables. The results suggest that the grid estimates form better predictive models, and that spectrometry overall is a viable method for quantifying percent wood failure values in shear specimens – with some explained contingencies.Keywords: wood bonding, shear testing, UV-VIS fluorescence spectrometry, Multivariate Data Analysis, Engineered Wood Products, adhesive penetration, surface chemistry, automation, wood failure, machine learning, spectr

Modelling Nonlinear Sequence Generators in terms of Linear Cellular Automata

In this work, a wide family of LFSR-based sequence generators, the so-called Clock-Controlled Shrinking Generators (CCSGs), has been analyzed and identified with a subset of linear Cellular Automata (CA). In fact, a pair of linear models describing the behavior of the CCSGs can be derived. The algorithm that converts a given CCSG into a CA-based linear model is very simple and can be applied to CCSGs in a range of practical interest. The linearity of these cellular models can be advantageously used in two different ways: (a) for the analysis and/or cryptanalysis of the CCSGs and (b) for the reconstruction of the output sequence obtained from this kind of generators.Comment: 15 pages, 0 figure

Groundwater-Monitoring based on dynamic co-operative eGovernment-Processes

As a result of the pilot-project “Grundwasser-Online” the supervision and the active controlling of large monitoring- and catchment-areas are realised by a co-operative integration of all related institutions, a synchronisation-process to combine all distributed data into one central server database, and a high-level eGovernment-Service to provide evaluated information over the internet. Based on this software system the local authorities are able to supervise the groundwater-levels and to find adequate decisions, which finally result in official permissions for the usage of groundwater-reservoirs by the water supply companies

Error linear complexity measures for multisequences

Complexity measures for sequences over finite fields, such as the linear complexity and the k-error linear complexity, play an important role in cryptology. Recent developments in stream ciphers point towards an interest in word-based stream ciphers, which require the study of the complexity of multisequences. We introduce various options for error linear complexity measures for multisequences. For finite multisequences as well as for periodic multisequences with prime period, we present formulas for the number of multisequences with given error linear complexity for several cases, and we present lower bounds for the expected error linear complexity

Integration of Productmodel Databases into Multi-Agent Systems

This paper deals with two different agent-based approaches aimed at the incorporation of complex design information into multi-agent planning systems. The first system facilitates collaborative structural design processes, the second one supports fire engineering in buildings. Both approaches are part of two different research projects that belong to the DFG1 priority program 1103 entitled “Network-based Co-operative Planning Processes in Structural Engineering“ (DFG 2000). The two approaches provide similar database wrapper agents to integrate relevant design information into two multi-agent systems: Database wrapper agents make the relevant product model data usable for further agents in the multi-agent system, independent on their physical location. Thus, database wrapper agents act as an interface between multi-agent system and heterogeneous database systems. The communication between the database wrapper agents and other requesting agents presumes a common vocabulary: a specific database ontology that maps database related message contents into database objects. Hereby, the software-wrapping technology enables the various design experts to plug in existing database systems and data resources into a specific multi-agent system easily. As a consequence, dynamic changes in the design information of large collaborative engineering projects are adequately supported. The flexible architecture of the database wrapper agent concept is demonstrated by the integration of an XML and a relational database system

Abstraction of Process Relevant Information from Geotechnical Standards and Regulations

The paper presents the abstraction of process relevant information in order to enable the workflow management based on semantic data. It is shown for three examples, how the standards define the information needed to perform a certain planning activity. Abstraction of process relevant information is discussed for different granularities of the underlying processmodel. As one possible application ProMiSE is introduced, which uses process relevant data in individual tokens in a petri-net based process-model