There is a worldwide need for new methodologies to prediagnose breast cancer in an early stage, which helps to notably increase the possibility of saving the mammary gland or patient's life. This work describes a new methodology proposal based on electrical impedance for the localization of preclinical carcinoma emulators in agar phantoms of the breast. The impedance is systematically measured through eight Ag/AgCl electrodes uniformly distributed in a ring arrangement placed on the breast agar phantom. The fundamental idea of the proposed location algorithm, named Anomaly Tracking Circle algorithm, is to find the breast agar area defined by straight lines joining the electrode pairs having the minimum difference value of the defined normalized impedance magnitude along the measurement sweep. Such difference is obtained with respect to a breast agar phantom without carcinoma emulator. The proposed methodology was evaluated through seven experimental agar models, six of them having carcinoma lobe emulators with different locations and electrical conductivities. According to the obtained results, the described methodology can obtain the location zone of preclinical-emulated carcinomas with an 83.33% success.

The need for reconfigurable, high power density, and low-cost configurations of DC-DC power electronic converters (PEC) in areas such as the transport electrification and the use of renewable energy has spread out the requirement to incorporate in a single circuit several topologies, which generally result in an increment of complexity about the modeling, control, and stability analyses. In this paper, a reconfigurable topology is presented which can be applied in alterative/changing power conversion scenarios and consists of a reconfigurable Buck, Boost, and Buck-Boost DC-DC converter (RBBC). A unified averaged model of the RBBC is obtained, a robust controller is designed through a polytopic representation, and a Lyapunov based switched stability analysis of the closed-loop system is presented. The reported RBBC provides a wide range of voltage operation, theoretically from −∞ to ∞ volts with a single power source. Robust stability, even under arbitrarily fast (bounded) parameter variations and reconfiguration changes, is reported including numerical and experimental results. The main advantages of the converter and the robust controller proposed are simple design, robustness against abrupt changes in the parameters, and low cost.

GPS sensors are widely used to know a vehicle’s location and to track its route. Although GPS sensor technology is advancing, they present systematic failures depending on the environmental conditions to which they are subjected. To tackle this problem, we propose an intelligent system based on fuzzy logic, which takes the information from the sensors and correct the vehicle’s absolute position according to its latitude and longitude. This correction is performed by two fuzzy systems, one to correct the latitude and the other to correct the longitude, which are trained using the MATLAB ANFIS tool. The positioning correction system is trained and tested with two different datasets. One of them collected with a Pmod GPS sensor and the other a public dataset, which was taken from routes in Brazil. To compare our proposal, an unscented Kalman filter (UKF) was implemented. The main finding is that the proposed fuzzy systems achieve a performance of 69.2% higher than the UKF. Furthermore, fuzzy systems are suitable to implement in an embedded system such as the Raspberry Pi 4. Another finding is that the logical operations facilitate the creation of non-linear functions because of the ‘if else’ structure. Finally, the existence justification of each fuzzy system section is easy to understand.

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