The paper is an exploratory research regarding the identification of some of the basic ideas used to conceive solutions of general-defined problems. In this way, there is firstly presented the set of ideas used to choose the type of model to be developed. The general problem solver and the related problems are also presented in the paper. In this case there is used a greedy approach which may lead to large run time values of the according software. To significantly decrease the computer time used to solve such a problem, there is also presented a method used to minimize the search space of the candidate solutions, in this case being used an intelligent solver, that is more effective than the greedy method. Two examples of models based on the previously presented general directions are also given. The first example presents an algorithm used to solve an equilibrium problem in ship strength problems. The second example is in electronic engineering. The ideas presented in the paper are important to identify the concepts employed to design modeling strategies and also for the development of the original software instruments structured as reusable libraries.
This work provides an experimental implementation of the cognitive software-defined Doppler radar based on the low cost USRP platform developed by Ettus Research. The proposed solution employs spectrum sensing in order to take advantage of the white spaces of the radio spectrum. The system continuously adapts its operating frequency according to environment changes, reducing the risk of interfering with other radio systems and acquiring a higher degree of immunity against jamming. The novelty of the proposed algorithm used for dynamically allocating the system’s operating frequency lies in its ability of covering a wide frequency bandwidth despite of the reduced instantaneous bandwidth of the low cost USRP platform employed in the experimental setup. Another related advantage of the proposed algorithm is the reduced computational power required for the real-time operation of the system. All of the above mentioned assertions have been validated experimentally.
As shown in another paper , we have imagined and built radio modules for path loss models calibration, to be integrated on autonomous robotic platforms or drones . Path loss models are very useful in disaster situations, helping to locate radio signal sources such as mobile phones, buried under collapsed buildings as a result of earthquakes, natural disasters, terrorism, war, etc.
For search and rescue scenarios [1,2], radio devices with precision comparable to laboratory instruments are needed. More than that, the modules have to be small enough to be integrated on autonomous robotic platforms  or drones, for search and rescue activities. Power consumption have to be small enough to sustain a reasonable time of autonomy. For this purpose, we have imagined two modules, a fixed frequency receiver and a wideband transceiver.
Underwater digital communication and sonars rely on basic signal detection. The problem with underwater signal detection is that of the extremely expensive equipments. In this paper we propose both a low cost solution for signal detection, which practically consists in integrating and adapting the already existing equipments and methods for underwater noise analysis.
In this paper we propose a new method for detection and localization of electric arcs by using two ultra-wide band (UWB) antennas together with data processing in the time-domain. The source of electric arcs is localized by computing an average on the inter-correlation functions of the signals received on two channels. By calculating the path length difference to the antennas, the direction of the electric arcs is then found. The novelty of the method consists in the spatial averaging in order to reduce the incertitude caused by the finite sampling rate.
Antenna gain is usually evaluated under far-field conditions. Furthermore, Friis transmission formula can solely be applied when antenna size can be neglected with respect to the distance between the measuring antenna and the antenna under test. In this paper, we show that by applying the distance averaging technique the far-field and antenna size constraints can be overcome. Our method was validated by measuring a monopole antenna and a Vivaldi antenna in an open area test site (OATS).
This paper deals with the use of autonomous robotic platforms able to locate radio signal sources such as mobile phones, buried under collapsed buildings as a result of earthquakes, natural disasters, terrorism, war, etc. This technique relies on averaging position data resulting from a propagation model implemented on the platform and the data acquired by robotic platforms at the disaster site. That allows us to calculate the approximate position of radio sources buried under the rubble. Based on measurements, a radio map of the disaster site is made, very useful for locating victims and for guiding specific rubble lifting machinery, by assuming that there is a victim next to a mobile device detected by the robotic platform; by knowing the approximate position, the lifting machinery does not risk to further hurt the victims. Moreover, by knowing the positions of the victims, the reaction time is decreased, and the chances of survival for the victims buried under the rubble, are obviously increased.
This paper presents an application of antenna arrays and MUSIC algorithm for estimating the location of an electric arc source. The proposed technique can be used to localize arc faults in photovoltaic arrays and their associated transformation stations. The technique was implemented and tested in the laboratory. For this purpose, an experimental setup consisting of 4 antennas, a digital storage oscilloscope with computer connectivity and a PC (Personal Computer) for data processing was built. The results proved that the proposed method is able to estimate the direction of the electric arc source with reasonable accuracy.