OBJECTIVE:To evaluate speech perception deficit compensation and predict potential hearing aids (HA) effectiveness in patients with hearing loss (HL). DESIGN:The patients underwent pure-tone audiometry and various speech tests in quiet (evaluating the peripheral auditory system and cognitive compensation) and in noise (to quantify central compensation through auditory processing and cognitive abilities). STUDY SAMPLE:513 HL patients aged 19-93 years, including 403 HA users. RESULTS:Speech Perception Deficit Compensation Index (SPDCI) was obtained from the residuals between individual speech perception test results and their predictions based on individual pure tone thresholds (PTT) data, thus characterising solely the patient's hearing abilities, generated using a Bayesian network trained on the cohort-wide partial correlations between PTT and speech test results. The SPDCI quantifies the contribution of central compensation mechanisms (auditory processing performance and cognitive abilities) to the speech perception effectiveness in HL patients. Potential HA effectiveness was evaluated using Bayesian inference of speech test results with HA from individual PTT and speech test results without HA. CONCLUSIONS:The proposed approach is instrumental for the differential diagnosis of HL and impaired speech perception, leading to a better understanding of the potential usefulness of hearing aids and, ultimately, to more informed management of these groups.

Modern information and telecommunication, transportation and logistic, economic and financial systems are represented by complex networks exhibiting traffic flows with spatio-temporal long-term persistence. Conventional queuing theory relies largely upon stationary models where traffic flows are assumed independent and are typically characterized by the first two moments of inter-arrival and service time distributions, leading to drastic underestimations of traffic flow delays. Here we extend a recent superstatistical approach focusing on traffic models with variable arrival rates by accounting for interdependent activity patterns on multiple network nodes. We suggest an analytical correction to the conventional stationary queue model given by the Kingman’s formula based on the calculation of aggregated inter-arrival times variability from the variabilities of arrival rates at individual nodes and cross-correlations between them. We confirm our analytical approximations by comparing with computer simulation results and large-batch empirical traffic analysis from the backbone of a major academic network. We believe that our results, in combination with recent data on the effects of long-term temporal persistence in network traffic flow, are applicable to various complex networks not limited to information and telecommunication, transportation, and logistics but also to economics and finance, rainfall and river flow dynamics, water accumulation in reservoirs, and many other research domains exhibiting spatio-temporal interdependence patterns.

A first-priority set of telepresence services is proposed, and the delay requirements and fault probabilities for these services are defined. The end-to-end latency and reliability requirements are derived from analysis of ITU-T, 3GPP, ETSI standards and recommendations. The characteristics of a next-generation model network for research and education in the field of telepresence services are discussed. The model network is based on a DWDM core, a variety of server equipment, holographic fans, 3D cameras and projectors, avatar robots and multifunctional robots, and augmented reality terminal devices. The results of the first tests on the model network are presented.

We consider waiting times in queuing systems with variable arrival rates in the presence of long-term correlations and periodic trends. We focus on a simplified model where the contributions of various non-stationary components could be analyzed separately and their effect summarized additively. We provide an approximate analytical solution that is based on the universal scaling of return intervals statistics between level crossing events in long-term correlated data series. The accuracy of our results is validated explicitly by computer modeling, using both simulated data series and empirical traffic data from a network cluster hosting the World Cup ’98 web services characterized by extremely variable traffic intensity. We believe that the proposed approach could be useful to characterize the impact of long-term correlations and periodic trends in various complex systems, with prominent examples ranging from information, communication, logistic, transportation networks to climate, hydrological, as well as other natural, social and engineering systems.

In this paper, the novel study of an Internet of Things (IoT) network model with multimodal node distribution and a data-collecting mechanism using mobile clustering nodes is presented. The aim of this work is to introduce the problem of organizing the mobile cluster head IoT network with a heterogeneous distribution node in the service area with multimodal distribution nodes. A new method for clustering a heterogeneous network is proposed, which makes it possible to efficiently identify clusters that differ in terms of the density of nodes. This makes it possible to choose the speed of the mobile cluster head in accordance with the density in each cluster. The proposed method uses the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm. One of the benefits of our proposed model is the increase in the efficiency of using a mobile cluster head. The new solution can be used to organize data collection in the IoT.

This study presents the development of algorithms that allow the automatic detection of the presence or absence of central auditory disorders (CAD), the degree and type of hearing loss, the effectiveness of the hearing aid, and the type of audiogram of pure tone audiometry (PTA) results in patients. A software application has been implemented in Python, integrating all the algorithms. This software will streamline and simplify the tasks of medical personnel, reducing the likelihood of errors and typos in the calculations.

Цель исследования — оценка возможности внедрения методов машинного обучения для создания цифрового слухового профиля у пациентов старших возрастных групп и анализа эффективности слухопротезирования в зависимости от вовлеченности в патологический процесс периферических и центральных отделов слуховой системы. Представлены результаты обследования 375 лиц 60–93 лет, из которых в основную группу вошли 355 пациентов с хронической двусторонней тугоухостью (230 из них использовали слуховые аппараты), а в контрольную — 20 человек пожилого возраста с нормальными порогами слуха. Аудиологическое обследование включало базовые методики (тональная пороговая и надпороговая аудиометрия, импедансометрия, речевая аудиометрия в тишине) и методы оценки состояния центральных отделов слуховой системы (тест чередующейся бинаурально речью, дихотический числовой тест, речевая аудиометрия в шуме, тест обнаружения паузы). Диагностику состояния когнитивных функций осуществляли с использованием Монреальской когнитивной шкалы. Эффективность слухопротезирования оценивали посредством анкетирования и речевой аудиометрии в свободном звуковом поле. Обработку результатов проводили с применением корреляционного анализа Пирсона, направленного на создание полиномиальной модели слуха пациента на основе ограниченного набора тестов. Выявлены корреляции состояния когнитивных функций и возраста, выполнения ряда тестов по оценке центральных отделов слуховой системы, а также успешности применения слуховых аппаратов. Результаты работы свидетельствуют о возможности использования компьютерных технологий анализа данных для разработки программ реабилитации пациентов старших возрастных групп с нарушениями слуха. The aim of the study is to evaluate the possibility to implement machine learning to create a digital auditory profi le for elderly patients and to analyze the hearing aid fi tting effi cacy depending on involvement of the peripheral and central auditory pathways in a pathological process. Data analysis of 375 people aged 60–93 years is presented. 355 patients with chronic bilateral hearing loss (230 of them used hearing aids) were included in the main group, and 20 normal hearing elderly people were included in the control group. Audiological examination consisted of standard tests (pure tone audiometry, impedancemetry, speech audiometry in quiet) and tests to evaluate the central auditory processing (binaural fusion, dichotic digits, speech audiometry in noise, random gap detection). The Montreal Cognitive Assessment was used to detect cognitive impairment. The hearing aid fi tting effi ciency was evaluated with COSI questionnaire and speech audiometry in free fi eld. Processing of the results was carried out using Pearson’s correlation analysis aimed at creating a polynomial model of a patient’s hearing on the basis of the limited test battery. There were close correlations between the state of cognitive functions and age, results of tests to evaluate the central auditory processing, as well as patients’ satisfaction of hearing aid. The results of the work indicate the possibility of using computer technologies of data analysis to develop rehabilitation programs for elderly hearing impaired patients.

The past century has seen the ongoing development of amplifiers for different electrophysiological signals to study the work of the heart. Since the vacuum tube era, engineers and designers of bioamplifiers for recording electrophysiological signals have been trying to achieve similar objectives: increasing the input impedance and common-mode rejection ratio, as well as reducing power consumption and the size of the bioamplifier. This review traces the evolution of bioamplifiers, starting from circuits on vacuum tubes and discrete transistors through circuits on operational and instrumental amplifiers, and to combined analog-digital solutions on analog front-end integrated circuits. Examples of circuits and their technical features are provided for each stage of the bioamplifier development. Special emphasis is placed on the review of modern analog front-end solutions for biopotential registration, including their generalized structural diagram and table of comparative characteristics. A detailed review of analog front-end circuit integration in various practical applications is provided, with examples of the latest achievements in the field of electrocardiogram, electroencephalogram, and electromyogram registration. The review concludes with key points and insights for the future development of the analog front-end concept applied to bioelectric signal registration.

В статье предложен алгоритм построения рекомендаций учебных ресурсов в электронных образовательных средах. Новый подход использует Марковскую модель оценки контента систем обычными пользователями для формирования параметров начального состояния, которое характеризует нового пользователя системы в виде оценок первых понравившихся ресурсов (контента системы) для рекомендации интересных элементов системы активному пользователю. Таким образом решается проблема «холодного старта» для нового пользователя на первых этапах взаимодействия с системой. Эта проблема свойственна для разрабатываемой системы, так как в системе электронного обучения предусмотрен модуль построения рекомендаций, что позволяет ее относить к классу рекомендательных автоматизированных систем. В новом подходе предлагается объединить использование Марковского процесса и временного фактора как единый источник данных для построения рекомендаций. Данный подход будет основываться на принципе анализа доступа схожих пользователей системы (схожесть определяется на основе сравнения их профилей) в одинаковые периоды времени. Неотъемлемой частью создаваемой системы также является удобство использования. Поэтому на этапе проектирования необходимо продумать эргономику выдаваемых рекомендаций в образовательной системе. This article proposes a recommendation algorithm for educational resources in e-learning systems. The new approach uses Markov's model of evaluating the systems` content by casual users to form the parameters of the initial state, which characterizes a new user of the system as evaluations of the first resources (system content) to recommend interesting system elements for an active user. Thus, the problem of "cold-start" for the new users at the first phase of interaction with the system is solved. This problem is inherent in the system under development because the e-learning system includes a module for making recommendations, which allows it to refer to the class of recommendation-based automated systems. The new approach will combine the Markov process usage and the time factor to use them as a single data source for making recommendations. This approach will be based on the principle of access analysis of similar system users (the similarity is determined by comparing their profiles) in the same periods. An integral part of the created system is also usability. Therefore, at the design phase, it is necessary to think about the ergonomics of the recommendations in the educational system.

We consider analysis, model identification and predictability of traffic intensity variation patterns for an academic wide area network. We focus on five daily records collected between 2017 and 2021 obtained from the MAWI Working Group Traffic Archive repository. Our results indicate that all considered traffic patterns exhibit long-term correlations characterized by Hurst exponents close to one, superimposed by additional short-term correlations. In turn, they are better approximated by the fractional autoregressive integrated moving average model, that represents both short-term memory effects by the autoregressive and moving average filters, as well as long-term memory effects by an extension of the fractional Brownian motion model. We show explicitly that the above model outperforms the more conventional approach based on the autoregressive model of the same order that implies solely short-term memory, although characterized by various correlation times. Our results including recommendations on the model selection aim at the improved predictability of the traffic fluctuations including emergence of anomalous bursts potentially leading to a better performance of the intelligent network routing algorithms.

Shipping traffic monitoring in coastal waters by a bistatic radar system based on satellite signals illumination makes possible to control and ensure the safety of everyday human activities. In this paper, we describe the results of an experimental study of a bistatic radar monitoring system of shipping using the L1 satellite signal of the GPS navigation system as an illumination signal. To increase the energy of the reflected signal from objects and the accuracy of detection in a radar system based on satellite illumination signals we suggest a multi-position radar system concept.

A study of the peculiarities and a comparative analysis of the technologies used for the fabrication of elements of novel hybrid microfluidic biochips for express biomedical analysis have been carried out. The biochips were designed with an incorporated microfluidic system, which enabled an accumulation of the target compounds in a biological fluid to be achieved, thus increasing the biochip system's sensitivity and even implementing a label-free design of the detection unit. The multilevel process of manufacturing a microfluidic system of a given topology for label-free fluorometric detection of protein structures is presented. The technological process included the chemical modification of the working surface of glass substrates by silanization using (3-aminopropyl) trimethoxysilane (APTMS), formation of the microchannels, for which SU-8 technologies and a last generation dry film photoresist were studied and compared. The solid-state phosphor layers were deposited using three methods: drop application; airbrushing; and mechanical spraying onto the adhesive surface. The processes of sealing the system, installing input ports, and packaging using micro-assembly technologies are described. The technological process has been optimized and the biochip was implemented and tested. The presented system can be used to design novel high-performance diagnostic tools that implement the function of express detection of protein markers of diseases and create low-power multimodal, highly intelligent portable analytical decision-making systems in medicine.

Monitoring of navigation in coastal areas is an important task for safety's guarantee. Nowadays a passive bistatic radar system is a point of interests of the scientific community in case of using different transmitters of opportunity. In this paper we consider passive bistatic radar with GNSS signals illumination. Here we suggest the structure of such system and algorithms of GPS signals processing. Also, the experimental suggestions are given. Our analytical research indicates the opportunity to use passive bistatic radar with GPS satellites as transmitters of opportunity as a coastal monitoring system.

This paper describes the experimental results of testing a prototype of a high precision human skin rapid temperature fluctuations measuring instrument. Based on the author’s work, an original circuit solution on a miniature semiconductor diode sensor has been designed. The proposed circuitry provides operation in the full voltage range with automatic setting and holding the operating point, as well as the necessary slope of the conversion coefficient (up to 2300 mV/°C), which makes it possible to register fast temperature oscillations from the surface of the human body and other biological objects. Simulation results in the Microcap 12 software and laboratory tests have confirmed all declared design specifications: temperature resolution of 0.01 °C, transducer thermal time constant of 0.05 s. An original thermostat and an experimental setup for the simultaneous registration of the electrocardiogram, pulse wave signals from the Biopac polygraph MP36 and a signal of temperature oscillations from the prototype thermometer have been designed for further investigations. The preliminary test results indicates that using the designed measuring instrument gives a possibility to provide an in-depth study of the relationship between micro- and macro-blood circulations manifested in skin temperature fluctuations.