Breaking a Chaotic Cryptographic Scheme Based on Composition Maps

Recently, a chaotic cryptographic scheme based on composition maps was proposed. This paper studies the security of the scheme and reports the following findings: 1) the scheme can be broken by a differential attack with $6+\lceil\log_L(MN)\rceil$ chosen-plaintext, where $MN$ is the size of plaintext and $L$ is the number of different elements in plain-text; 2) the scheme is not sensitive to the changes of plaintext; 3) the two composition maps do not work well as a secure and efficient random number source.Comment: 9 pages, 7 figure

Implications of EMU for Global Macroeconomic and Financial Stability

The paper examines the implications of EMU for world macroeconomic and financial stability, distinguishing EMU effects from other global factors at work. It concludes that EMU is having on the whole stabilising effects on the world economy, particularly in neighbouring regions.EMU, macroeconomic volatility, euro, international monetary system, implications of EMU for world macroeconomic and financial stability, Economic Papers, D�hring,

Estimation of the control parameter from symbolic sequences: Unimodal maps with variable critical point

The work described in this paper can be interpreted as an application of the order patterns of symbolic dynamics when dealing with unimodal maps. Specifically, it is shown how Gray codes can be used to estimate the probability distribution functions (PDFs) of the order patterns of parametric unimodal maps. Furthermore, these PDFs depend on the value of the parameter, what eventually provides a handle to estimate the parameter value from symbolic sequences (in form of Gray codes), even when the critical point depends on the parameter.Comment: 10 pages, 14 figure

Derivation of diagnostic models based on formalized process knowledge

© IFAC.Industrial systems are vulnerable to faults. Early and accurate detection and diagnosis in production systems can minimize down-time, increase the safety of the plant operation, and reduce manufacturing costs. Knowledge- and model-based approaches to automated fault detection and diagnosis have been demonstrated to be suitable for fault cause analysis within a broad range of industrial processes and research case studies. However, the implementation of these methods demands a complex and error-prone development phase, especially due to the extensive efforts required during the derivation of models and their respective validation. In an effort to reduce such modeling complexity, this paper presents a structured causal modeling approach to supporting the derivation of diagnostic models based on formalized process knowledge. The method described herein exploits the Formalized Process Description Guideline VDI/VDE 3682 to establish causal relations among key-process variables, develops an extension of the Signed Digraph model combined with the use of fuzzy set theory to allow more accurate causality descriptions, and proposes a representation of the resulting diagnostic model in CAEX/AutomationML targeting dynamic data access, portability, and seamless information exchange

Cryptanalysis of a new chaotic cryptosystem based on ergodicity

This paper analyzes the security of a recent cryptosystem based on the ergodicity property of chaotic maps. It is shown how to obtain the secret key using a chosen-ciphertext attack. Some other design weaknesses are also shown.Comment: 10 pages, 5 figure

Evaluación de la calidad de agua de las fuentes hidrográficas del Bosque Protector Río Guajalito (BPRG) a través de la utilización de macroinvertebrados acuáticos, Pichincha, Ecuador

In the last years, benthic macroinvertebrates have been used as bioindicators for water quality because of their characteristics and special requirements, which make them very sensitive to diverse impacts on the hydrographic sources, like organic, chemical pollution, riparian forest deforestation, and others. A sampling of macroinvertebrates was carried out at Guajalito, Palmeras and Brincador rivers, that run through the private reserve Bosque Protector Río Guajalito, with the purpose of using macroinvertebrates as bioindicators of water quality.Los macroinvertebrados bentónicos han sido muy utilizados como bioindicadores de la calidad de fuentes de agua. Esto se debe a sus características y requerimientos especiales que hacen a estos organismos muy sensibles a diversos impactos sobre las fuentes hidrográficas, como contaminación orgánica, química, desaparición de vegetación ribereña, entre otros. Se realizó un muestreo de macroinvertebrados bentónicos en los ríos Guajalito, Palmeras y Brincador, los cuales cruzan a través del Bosque Protector Río Guajalito, con el fin de estimar la calidad de las aguas de los mismos. Además se realizó una caracterización física y química para validar la información biológica obtenida

Surface tension controls the hydraulic fracture of adhesive interfaces bridged by molecular bonds

Biological function requires cell-cell adhesions to tune their cohesiveness; for instance, during the opening of new fluid-filled cavities under hydraulic pressure. To understand the physical mechanisms supporting this adaptability, we develop a stochastic model for the hydraulic fracture of adhesive interfaces bridged by molecular bonds. We find that surface tension strongly enhances the stability of these interfaces by controlling flaw sensitivity, lifetime, and optimal architecture in terms of bond clustering. We also show that bond mobility embrittles adhesions and changes the mechanism of decohesion. Our study provides a mechanistic background to understand the biological regulation of cell-cell cohesion and fracture

The Investigation of EEG Responses for Design Tasks Using Traditional and Digital Tools

With the emergence of computers and modern technology, the way professionals do architecture has drastically change over the recent decades and schools have been faced with the task of how they want to guide the next generation of architects. Will the use of technology be taught as a fundamental skill? Or do the traditional techniques take precedent? This has raised the question of how digital technology has affected the minds of architecture students ? and more specifically ? in the area of design thinking. This research report will take a preliminary look at the neural responses in the brain when using traditional tools and digital tools. The goal of this research project is to compare the brain?s activity when using traditional tools versus digital tools. The document will go over the process of collecting electroencephalogram (EEG) data from human participants while they were using traditional and digital tools. This was made possible using the Ultracortex Headset from OpenBCI. Afterwards, the raw data was analyzed using a statistical analysis program called Igor Pro. Within the program, the waves data was transformed into Lomb Periodograms and then were compared using the Wilcoxon test and the T-test. Finally, those results were organized onto an Excel Spreadsheet

Building Blocks Towards New Education

The purpose of this research is to look at the effects digital technologies have had on education and explore ways educational facilities can react to these new technologies in the form of how we look at learning spaces. The goal with this thesis is not for it to be a guide but rather as a point of inspiration for educational facilities and designers. With the advancing development of digital technology, educational facilities are tasked with adapting to a society that has digital technology deeply ingrained in it. Educators and designers have a great opportunity to reevaluate our learning spaces and react to how digital technology might affect students learning. In the end, I used the words inclusive, exclusive, and circulation to identify and use of the space and populated\adjusted the area using a kit of parts

Nonlinear manifold learning for model reduction in finite elastodynamics

Model reduction in computational mechanics is generally addressed with linear dimensionality reduction methods such as Principal Components Analysis (PCA). Hypothesizing that in many applications of interest the essential dynamics evolve on a nonlinear manifold, we explore here reduced order modeling based on nonlinear dimen- sionality reduction methods. Such methods are gaining popularity in diverse fields of science and technology, such as machine perception or molecular simulation. We consider finite deformation elastodynamics as a model problem, and identify the manifold where the dynamics essentially take place –the slow manifold– by nonlinear dimensionality reduction methods applied to a database of snapshots. Contrary to linear dimensionality reduction, the smooth parametrization of the slow manifold needs special techniques, and we use local maximum entropy approximants. We then formulate the Lagrangian mechanics on these data-based generalized coordinates, and de- velop variational time-integrators. Our proof-of-concept example shows that a few nonlinear collective variables provide similar accuracy to tens of PCA modes, suggesting that the proposed method may be very attractive in control or optimization applications. Furthermore, the reduced number of variables brings insight into the me- chanics of the system under scrutiny. Our simulations also highlight the need of modeling the net e ¿ ect of the disregarded degrees of freedom on the reduced dynamics at long times