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This paper describes the features of a data acquisition system modeling based on queueing theory method. The main elements of the studied data acquisition system structure are sample hold amplifiers and dual-slope analogue digital converters. In case of the threshold control of technological facilities parameters, alarm signals in the system input are presented as a flow of customers with the Poisson intensity distribution. A converting time of these alarms in analogue digital converters depends on signal levels and is described by an exponential distribution. In this case we present the data acquisition system as the Markov model of the multichannel queueing system with a limited queue. This modeling method may help the data acquisition system structure to adapt to characteristics of input signals and features of communication lines in an output of system. [ABSTRACT FROM AUTHOR]

The versatility of simple electronic nodes and debugging of communication protocols in unlicensed frequency bands constitute the main reasons for the adoption of industrial wireless sensor networks (IWSNs). However, the industrial environments, in which IWSNs function, are characterized by a harsh impact of physical and electromagnetic factors that destabilize the operation of equipment and worsen the noise immunity of channels. To consider the effect of these two groups of factors on communication quality, we develop a novel model of an IWSN channel as the dependence of bit error probability (BEP) on signal distortions and interference impact. We found that direct sequence spread spectrum (DSSS) codes of a signal have different effects on the compensation of nonlinear signal distortions and external interference. Further, we propose an algorithm for the distribution of DSSS codes among real transmitters by BEP values in channels with known additive and multiplicative interference. Here, the distribution of codes is based on the minimax criterion. Finally, for cases when a signal is characterized by a-priori uncertainties of fading, we suggest an alternative algorithm for selecting a DSSS code based on Pareto bicriteria optimization. [Display omitted] • We model an IWSN channel with hardware signal distortion, fading and narrowband interference. • An algorithm for distributing DSSS codes among real transmitters minimizes BEP in the worst channel. • An algorithm for DSSS code selection with signal fading uncertainty reduces required computational costs. [ABSTRACT FROM AUTHOR]

[Display omitted] • We model wireless channels in terms of the hardware distortion of BFSK signals. • A complex indicator for the hardware distortion of signals is justified. • The table of energy consumption for nodes with various radio modules is calculated. • We propose a criterion for energy-efficient distribution of radio modules among nodes. Wireless sensor networks (WSNs) are widely used in various practical applications due to the availability of sensor and relay nodes. The imperfect technical condition of the modem part in nodes causes the hardware distortion of signals and the loss of messages in communication channels. Lost data recovery requires additional energy consumption, contributing to the premature discharge of batteries in individual nodes and decreased network lifetime. In this study, we propose an algorithm for the optimal energy-efficient distribution of radio modules (RMs) among the established node positions in terms of the technical condition of equipment using a minimax criterion. We developed physical layer models for the channels exhibiting incoherent reception of a priori distorted BFSK (binary frequency shift keying) signals under noise and Rayleigh and Rice fading conditions. Hardware distortions in these models are considered as a complex indicator represented by a coefficient showing similarity between the signal at the actual RM output and a reference signal with nominal parameters. The energy of the network is balanced due to the optimal distribution of the RMs among the node positions, taking into account the energy consumption of various WSN nodes. [ABSTRACT FROM AUTHOR]

Presents a study which describes another method for measuring the carrier frequency of single microwave (MW) radio-wave pulse. What the method is based upon; Theorical analysis of the operation of a frequency meter for single MW radio-wave pluses; Results of analysis; Type of specifications a frequency meter for single and rarely recurring short-duration MW radio-wave pluses must meet.

One of the most discussed issues in forensic firearms identification is the subjectivity of conclusions. The main part of firearms examiners' work is to make a microscopic comparison of the marks on cartridge cases and bullets. In this process, examiners have to decide if the quantity and the quality of the observed characteristics are sufficient for identification. This decision is based on the personal experience of an examiner, so examiners with different backgrounds can come to different conclusions, and this fact presents a problem. Besides, the calculation of the error rate for this type of examination is a debatable issue. Different mathematical and statistical models were proposed, and computer‐based algorithms were developed in order to avoid subjectivity and to determine error rates. This article investigates the possibility to use methods of machine learning for the comparison of marks of the firing pin impressions on cartridge cases. In the research, the Siamese network model, which included two similar Convolutional Neural Networks, was prepared and trained. For the training and validation of the model, the database of firing pin impressions was prepared. This database included images of cartridge cases discharged from 300 firearms that came from regular casework and clone images used for data augmentation. The model was trained and examined using the validation part of the database. The metrics, such as accuracy, sensitivity, and specificity were calculated. The results of the research show the possibility of using the Siamese network for building an objective forensic firearms examination system with a known error rate. [ABSTRACT FROM AUTHOR]

[Display omitted] Active methylene compounds react readily with sarcosine and formaldehyde in mild conditions to give 3-substituted pyrrolidines. Catalysis by diethylamine makes possible to successfully use less reactive starting substrates in this reaction. [ABSTRACT FROM AUTHOR]

Cartridge cases are commonly collected at crime scenes involving firearms. One of the stages in forensic examination is the determination of the type and model of firearms based on the class characteristics of these cartridge cases. A firearm examiner evaluates the class characteristics on the basis of their knowledge and experience, and by referring to collections of cartridge cases representing class characteristics of different firearms, special databases and reference books. However, this process is highly subjective. The novelty of this research is in developing objective methods of firearms determination by applying a machine learning approach. In this study, several Convolutional Neural Networks from Keras programming package were trained to determine the type/model of a firearm based on the class characteristics observed on cartridge cases from seven different categories of firearms. The prediction accuracies received by this method range from 71 to 81 percent for models based on different Convolutional Neural Networks, while using an ensemble of the machine learning models increased the accuracy to 88 %. The research demonstrates the efficacy of machine learning in enhancing accuracy and reducing subjectivity in firearm identification, highlighting its significant potential in forensic science applications. • The novel application of machine learning for forensic firearm examinations. • The development of CNN for the determination of the type/model of a firearm. • The developed CNN demonstrated accuracy of 88 % in cartridge cases examination. [ABSTRACT FROM AUTHOR]

Investigates the magnetoacoustic surface acoustic wave (SAW) interaction in yttrium-iron garnet (YIG) films. Most studied magnetic materials; Fabrication of samples and measuring technique; Experimental results and discussion.