Monica Dascalu

Virtual environment for robots interfaces design and testing

This paper refers to the implementation of a virtual environment for the robot interfaces testing. This software environment is very useful because, comparing to the experiments with real robots, it allow the testing and evaluation of different types of interfaces and different working environments with diverse configurations. A very important facility of this interactive software environment is the fact that the designers of the robots sensors and interfaces are able to work in parallel to design test, optimize and realize different control devices for the robot

Design of cellular automata hardware for cryptographic applications

This work presents the hardware architecture of a cryptosystem based on cellular automata model (CA). Main cryptographic schemes with CA are briefly introduced. The hardware version refers to linear class 3 CA. The project for the cellular automata, main block of the encryption and decryption schemes, is presented. The scheme may be used for robust, low-cost and efficient cryptosystems for specific applications.

Implementation of totalistic cellular automata

In this paper we present a low complexity cellular automata that can be easily realised in hardware version. This version of cellular automata implements the subset of totalistic local rules. The paper describes the structure of a typical cell running totalistic functions and its behaviour, and also the design of the global cellular automata.

A VLSI implementation of cellular automata randomizers

The paper presents the general design of integrated cellular automata randomizers. An important aim of the paper is to highlight the specificity of pseudo-random sequence generation between other cellular automata applications and to present the structures and types of output of cellular automata-based pseudo-random sequence generator. The paper also presents a new model of generalized cellular automata, that includes a supplementary memory layer for improving the statistical properties of the random signal and sequence generator. One important aspect of the dynamics of cellular automata is that in many cases there are no means to predict the behavior of the system (excepting, of course, to run the system itself). Therefore, in these cases-which are also the cases most appropriate for our application-the experiment is the only solution to guarantee the quality of the generator. The VLSI implementation of cellular automata randomizers is dedicated first of all for testing the properties of these randomizers.

Hardware version for two-dimensional cellular automata

In this paper we propose a hardware version for two-dimensional cellular automata. Since cellular automata are parallel systems containing a large number of simple processing elements, their hardware version is necessary for their real-time study and applications. A cellular automata chip is described both at the architectural and cell level. The paper outlines the main functions of the cellular automata chip and describes how they operate. We also present some quantitative aspects that determine the chip dimension. The chip can be succesfully used for experiments with large CA implying long-time evolution.

CRIPTOCEL: design of cellular automata based cipher schemes

The paper presents CRIPTOCEL, a complex project that is aimed at the development and design of cellular-automata based cryptographic systems. Cryptography is a field of major scientific and technical interest nowadays, mainly because of the increased security demands of different communication systems. The novelty and the main interest in the CRIPTOCEL project is the orientation towards a hardware implementation. A special software has been developed for the analysis of different encryption/decryption strategies with cellular automata. Among the various strategies and algorithms studied, the best were selected for hardware implementation. The main issues of cellular automata hardware design are also discussed for the selected cryptosystems. The result is a VLSI project for a fast, cheap, efficient and versatile cryptographic chip.

Two axes detector for photovoltaic panels' automatic full angle orientation

A significant efficiency increase of the photovoltaic systems can be obtained by optimal exposure to the sunlight, using automatic solar trackers. In this paper we propose a detector for one or two axis automatic orientation, which permit a continuous tracking for the entire zenith angle range. The detector has a monotonous and almost linear characteristic for incident angles from −90° to 90°, on any axe. It is appropriate for an analog, low cost, tracking procedure, but also for a digital, more precise one. The West to East return procedure is simple, because of the illumination of at least one cell.

Theory, Algorithms and Applications for Solar Panel MPP Tracking

The photovoltaic panel is a power source whose parameters depend on some external factors like incident light angle, shading, ambient temperature etc. Some of these factors are unpredictable and, for this reason, so is the evolution of cell parameters. The most known parameters of the photovoltaic panel are the open circuit voltage (Voc) and short circuit current (Isc). These values define the points where the I(V) graph curve of the panel intersects the two axes (I and V), like in Fig. 1.

Computing system processing of GPR sounding profiles

The paper discuss the possible applications of computing systems in processing of GPR sounding profiles, viewed as signal and/or image processing. GPR (ground penetrating radar) is a non-invasive and non-destructive technique of subsurface investigation, similar to other radar-type detection methods. The sounding profile as a result of GPR data acquisition, is a bidimensional image, most usual in gray scale, that often requires preliminary processing in order to reveal significant information. Different types of processing like background removal and various filtering are discussed, and the possibility of neural processing is analyzed for different situations.

Evolutionary computing systems for obstacle avoidance

In this paper we present two neuronal network architectures to perform the task of obstacle avoidance for a little mobile robot named Khepera, which has 8 infrared proximity detectors and two independent motors. The first one used Hebbian learning for weight adaptation and the second one use evolutionary weight selection. The experiments are only simulated.