This paper provides a comparison between two techniques for soft fault diagnosis in analog electronic circuits. Both techniques are based on the simulation before test approach: a "fault dictionary" is a priori generated by collecting, signatures of different fault conditions. Classifiers, trained by the examples contained in the fault dictionary, are then configured to classify the measured circuit responses. The suggested classifiers have similar structures. The first is based on a fuzzy system, obtained by processing fault dictionary data for automatic generation of IF-THEN rules, and the second classifier is based on a radial basis function neural network. The two classifiers are used to detect and isolate faults both at the subsystem and component levels. The experimental results point out that both classifiers provide low classification errors in the presence of noise and nonfaulty components tolerance effects. The fuzzy approach provides better results due to an efficient generation method for the IF-THEN rules that allows adding IF parts in the input space regions where ambiguity occurs.

In this paper, the guidelines to design a true random bit generator (TRBG) circuit with a predefined minimum entropy are discussed. The approach is proposed for a TRBG based on a one-dimensional piecewise-linear chaotic map; it does not require bit throughput reduction, and it is suitable for the development of integrated TRBG circuits. In particular, the proposed design strategy is based on a feedback control procedure that allows to dynamically change the system parameters for the correction of the circuit "nonidealities" (e.g., the circuit offsets). The correction algorithm does not require a direct measurement of the system "nonidealities" or of the effective value of the map parameters, but only a dynamic estimation of these quantities based on the observation of the TRBG output. The design approach is validated by a hardware prototype implemented on a field-programmable analog array. The results of the NIST FIPS 140-2 test suite, the DIEHARD test suite, and the Coron's Universal test, applied to the TRBG output sequences before and after a simple post processing without throughput reduction, are reported and discussed.

In this paper, a family of nonlinear congruential generators (NLCGs) based on the digitized Reacutenyi map is considered for the definition of hardware-efficient pseudorandom number generators (PRNGs), and a theoretical framework for their study is presented. The authors investigate how the nonlinear structure of these systems eliminates some of the statistical regularities spoiling the randomness of sequences generated with linear techniques. In detail, in this paper, a necessary condition that the considered NLCGs must satisfy to have maximum period length is given, and a list of such maximum period PRNGs for period lengths up to 2³¹-1 is provided. Referring to the NIST800-22 statistical test suite, two PRNG examples are presented and compared to well-known PRNGs based on linear recurrencies requiring a similar amount of resources for their implementation

In this paper, a new version of the field-mill sensor structure for atmospheric electric field measurements is presented. Both the hardware components (i.e., the mechanical structure, the electronic front end, and the acquisition and control systems) and the data processing software are designed in order to reduce power consumption and enhance the instrument metrological performance in terms of accuracy, sensitivity, and frequency band.

This paper shows the feasibility of a High Frequency RFID passive sensor tag equipped with sensors based on a thin film circuit on a Si substrate for the measurement of the soil moisture. Three tags embedding different sensing systems compliant with the energy harvesting requirements were developed. The used sensors were previously characterized with the aim of tailoring an adequate electronic front-end. All the typical solutions for soil moisture detection were implemented: a fringe capacitance sensor, a soil impedance sensor and finally a humidity sensor based on functionalization with TiO2 nano particles. The obtained results prove that the conceived solution is satisfactory and that the sensors have good sensing properties. The proposed system can be applied within the IoT framework in manifold monitoring scenarios of soil moisture sensing.

Quartz-crystal microbalance (QCM) sensors obtained by a facile deposition of TiO ₂ nanoparticles have been manufactured and tested. Their gas sensing performance is discussed from a theoretical point of view and then verified by means of “ad hoc” measurement systems, through experiments with two toxic gases, CO and NO ₂ , and water vapor. The influence of UV irradiation on the sensor response has also been studied. Results show stable and repeatable responses, characterized by a very high sensitivity to water vapor, a good sensitivity to NO ₂ , and only a fairly low response to CO. Both CO and NO ₂ responses depend strongly on the relative humidity (RH). So, NO ₂ sensing should be performed in a controlled humidity environment. Devices proved to be reliable detectors of low RH values. Advantages as low cost, facile preparation, RT operation, good stability, and high/moderate sensitivity, make these devices attractive as an alternative to mostly used gas sensors.