Preparing the books to read every day is enjoyable for many people. However, there are still many people who also don't like reading. This is a problem. But, when you can support others to start reading, it will be better. One of the books that can be recommended for new readers is dynamics and modelling of ocean waves. This book is not kind of difficult book to read. It can be read and understand by the new readers.

Dynamics and Modelling of Ocean Waves

This study presents a technique to identify the vibration characteristics in power transmission towers and to detect the potential structural damages. This method is based on the curvature of the mode shapes coupled with a continuous wavelet transform. The elaborated numerical method is based on signal processing of the output that resulted from ambient vibration. This technique benefits from a limited number of sensors, which makes it a cost-effective approach compared to others. The optimal spatial location for these sensors is obtained by the minimization of the non-diagonal entries in the modal assurance criterion (MAC) matrix. The Hilbert-Huang transform was also used to identify the dynamic anatomy of the structure. In order to simulate the realistic condition of the measured structural response in the field condition, a 10% noise is added to the response of the numerical model. Four damage scenarios were considered, and the potential damages were identified using wavelet transform on the difference of mode shapes curvature in the intact and damaged towers. Results show a promising accuracy considering the small number of applied sensors. This study proposes a low-cost and feasible technique for structural health monitoring.

https://www.mdpi.com/1424-8220/20/6/1731/pdf

Vibration Anatomy and Damage Detection in Power Transmission Towers with Limited Sensors.

We suggest a conceptual approach for measuring the near-surface wind vector over water using the airborne weather radar, in addition to its standard meteorological and navigation applications. The airborne weather radar operates in the ground-mapping mode in the range of high to medium incidence angles as a scatterometer. Using the aircraft rectilinear flight over the water surface, measuring the geometry and the geophysical model function, we show that the wind vector can be successfully recovered from the azimuth normalized radar cross-section data obtained from a scanning sector of up to ±100°. The efficiency and accuracy of the proposed wind vector measurement algorithms are supported by computer simulations indicating their potential as a powerful tool for the wind field reconstruction. Some limitations and recommendations of the suggested approach are further discussed.

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Sea Surface Wind Measurement by Airborne Weather Radar Scanning in a Wide-Size Sector

In this article, an automated heartbeat classification has been proposed to prevent the growing threats of cardiovascular diseases around the world. The MIT-BIH arrhythmia database has been used for the training and testing of the proposed approach. The database contains 90 095 normal (N), 2781 supraventricular (SVEB), 7008 ventricular (VEB), 802 fusions (F), and 15 unclassified (Q) beats each of 30 min duration. Total 61 features have been extracted using the time-series feature extraction library (TSFEL). Feature selection or reduction methods applied are feature scaling, removal of highly correlated and low variance features, and random forest (RF) recursive feature elimination. The methodological novelty of this study is mainly the incorporation of TSFEL during feature extractions, synthetic minority oversampling technique to create a balanced dataset, and an ensemble of RF and support vector machine (SVM) using weighted majority algorithm for heartbeat classification to improve the results. Grid search has been performed to optimize the hyperparameters of RF and SVM classifiers. A final evaluation has been carried out considering a “subject-specific” scheme. The sensitivity that our approach has achieved for the arrhythmic heartbeat classes is as follows: N: 99.50%, SVEB (S): 74.20%, VEB (V): 94.22%, F: 73.21%, and Q: 0%. The corresponding positive predictive values are N: 98.67%, SVEB (S): 90.09%, VEB (V): 95.95%, F: 88.35%, and Q: 0%. In comparison with machine learning and deep learning based state-of-the-art approaches, significant improvement in efficiency has been found. Impact Statement— Automated classifications of heartbeats from ECG signals are very much required to speed up the diagnosis of cardiovascular diseases (CVDs). Our study demonstrates 98.21% accuracy compared to existing state-of-the-art approaches. This study impacts the intensive health care system by offering an easy, quick, and cost-effective diagnosis of CVDs. Besides, remote patients can also receive the treatments timely. Early intervention and prevention of CVDs can prevent almost 30% of the total death every year. The proposed approach has a societal and economic impact too, as the health, welfare, and productivity of the citizens as well as of the country will be improved significantly. Approximately 2% of gross domestic product (GDP) will be improved across low- and middle-income countries as the proposed approaches will reduce the direct (treatment cost) and indirect costs (loss in productivities at workplaces) associated with CVDs.

Arrhythmic Heartbeat Classification Using Ensemble of Random Forest and Support Vector Machine Algorithm

Energy Storage Systems (EES) are key to further increase the penetration in energy grids of intermittent renewable energy sources, such as wind, by smoothing out power fluctuations. In order this to be economically feasible; however, the ESS need to be sized correctly and managed efficiently. In the study, the use of discrete wavelet transform (Daubechies Db4) to decompose the power output of utility-scale wind turbines into high and low-frequency components, with the objective of smoothing wind turbine power output, is discussed and applied to four-year Supervisory Control And Data Acquisition (SCADA) real data from multi-MW, on-shore wind turbines provided by the industrial partner. Two main research requests were tackled: first, the effectiveness of the discrete wavelet transform for the correct sizing and management of the battery (Li-Ion type) storage was assessed in comparison to more traditional approaches such as a simple moving average and a direct use of the battery in response to excessive power fluctuations. The performance of different storage designs was compared, in terms of abatement of ramp rate violations, depending on the power smoothing technique applied. Results show that the wavelet transform leads to a more efficient battery use, characterized by lower variation of the averaged state-of-charge, and in turn to the need for a lower battery capacity, which can be translated into a cost reduction (up to −28%). The second research objective was to prove that the wavelet-based power smoothing technique has superior performance for the real-time control of a wind park. To this end, a simple procedure is proposed to generate a suitable moving window centered on the actual sample in which the wavelet transform can be applied. The power-smoothing performance of the method was tested on the same time series data, showing again that the discrete wavelet transform represents a superior solution in comparison to conventional approaches.

Discrete Wavelet Transform for the Real-Time Smoothing of Wind Turbine Power Using Li-Ion Batteries

Development and improvement of a mathematical model for a large-scale analysis based on the Daubechies discrete wavelet transform will be implemented in an algebraic system possessing a property of ring and field suitable for speech signals processing. Modular codes are widely used in many areas of modern information technologies. The use of these non-positional codes can provide high-speed data processing. Therefore, these algebraic systems should be used in the algorithms of digital processing of signals, which are characterized by processing large amounts of data in real time. In addition, modular codes make it possible to implement large-scale signal processing using the wavelet transform. The paper discusses examples of the Daubechies wavelet transform application. Integer processing, presented in the paper, will reduce the number of rounding errors when processing the speech signals.

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An Algorithm of Daubechies Wavelet Transform in the Final Field When Processing Speech Signals

We consider different antenna configurations, ranging from simple X-configuration to multi-beam star geometries, for airborne scatterometric measurements of the wind vector near the ocean surface. For all geometries, track-stabilized antenna configurations, as well as horizontal transmitter and receiver polarizations, are considered. The wind vector retrieval algorithm is generalized here for an arbitrary star geometry antenna configuration and tested using the Ku-Band geophysical model function. Using Monte Carlo simulations for the fixed total measurement time, we show explicitly that the relative wind speed estimation accuracy barely depends on the chosen antenna geometry, while the maximum wind direction retrieval error reduces moderately with increasing angular resolution, although at the cost of increased retrieval algorithm computational complexity, thus, limiting online analysis options with onboard equipment. Remarkably, the simplest X-configuration, while the simplest in terms of hardware implementation and computational time, appears an outlier, yielding considerably higher maximum retrieval errors when compared to all other configurations. We believe that our results are useful for the optimization of both hardware and software design for modern airborne scatterometric measurement systems based on tunable antenna arrays especially, those requiring online data processing.

Optimization of airborne antenna geometry for ocean surface scatterometric measurements

A concept for measuring the water-surface backscattering signature using the airborne weather radar, in addition to its standard meteorological and navigation applications, is discussed. The airborne weather radar operates in the ground-mapping mode in the range of high to medium incidence angles as a scatterometer. A case of two-stage rectilinear track flight measurement with a 180° aircraft turn between the stages is considered. Some limitations and recommendations to perform the measurement are presented.

A concept for measuring the water-surface backscattering signature by airborne weather radar

In this paper, we describe the ways of improving knowledge assessment with the help of cognitive maps, made during the process of working with intelligent tutoring system “E-learning center — High-edu”. Cognitive map consists of didactic units — minimal units of knowledge about some discipline’s domain. This article shows, how they can be used in intelligent tutoring systems. The example of algorithm realization of forming the didactic units list from discipline cognitive map for consistency of test task presentation determining is shown. The operator model are presented in this paper, which can be helpful for researchers and engineers for using Prolog language for expert systems and knowledge management systems development as well as for support of educational process and the control of student knowledge that will allow achieving improvement of quality of electronic education.

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A Knowledge Testing Production Model Based on a Cognitive Map for SWI-Prolog Applications

The relevance of the work lies in the fact that after solving the tasks, the results obtained, namely, the guidelines will be used in assessing the security analysis of the network of mobile robots. Indeed, the main problem in the analysis of such systems is the difference of this type of network from the usual computer networks, which in turn requires the creation of new methods and approaches to the analysis of the security of a network of mobile robots.The main goal of the work is to develop a methodology for analyzing the security of a network of mobile robots, based on research and assessment of threats and security vulnerabilities of a group of mobile robots.To achieve this goal it is necessary to solve the following tasks: to systematize data on robotic systems, to analyze the structural and functional characteristics of mobile robots, develop a typical information system for a group of mobile robots, develop a model of the offender for a group of mobile robots.

Dmitry Popov

Papers

An Algorithm of Daubechies Wavelet Transform in the Final Field When Processing Speech Signals

Optimization of airborne antenna geometry for ocean surface scatterometric measurements

A concept for measuring the water-surface backscattering signature by airborne weather radar

A Knowledge Testing Production Model Based on a Cognitive Map for SWI-Prolog Applications

Analysis of the initial security of the robotics system