Modelling Self-similar Traffic Of Multiservice Networks

Simulation modelling is carried out, which allows adequate describing the traffic of multiservice networks with the commutation of packets with the characteristic of burstiness. One of the most effective methods for studying the traffic of telecommunications systems is computer simulation modelling. By using the theory of queuing systems (QS), computer simulation modelling of packet flows (traffic) in modern multi-service networks is performed as a random self-similar process. Distribution laws such as exponential, Poisson and normal-logarithmic distributions, Pareto and Weibull distributions have been considered.The distribution of time intervals between arrivals of packages and the service duration of service of packages at different system loads has been studied. The research results show that the distribution function of time intervals between packet arrivals and the service duration of packages is in good agreement with the Pareto and Weibull distributions, but in most cases the Pareto distribution prevails.The queuing systems with the queues M/Pa/1 and Pa/M/1 has been studied, and the fractality of the intervals of requests arriving have been compared by the properties of the estimates of the system load and the service duration. It has been found out that in the system Pa/M/1, with the parameter of the form a> 2, the fractality of the intervals of requests arriving does not affect the average waiting time and load factor. However, when ≤2, as in the M/Pa/1 system, both considered statistical estimates differ.The application of adequate mathematical models of traffic allows to correctly assess the characteristics of the quality of service (QoS) of the network

MODELLING SELF-SIMILAR TRAFFIC OF MULTISERVICE NETWORKS

Simulation modelling is carried out, which allows adequate describing the traffic of multiservice networks with the commutation of packets with the characteristic of burstiness. One of the most effective methods for studying the traffic of telecommunications systems is computer simulation modelling. By using the theory of queuing systems (QS), computer simulation modelling of packet flows (traffic) in modern multi-service networks is performed as a random self-similar process. Distribution laws such as exponential, Poisson and normal-logarithmic distributions, Pareto and Weibull distributions have been considered. The distribution of time intervals between arrivals of packages and the service duration of service of packages at different system loads has been studied. The research results show that the distribution function of time intervals between packet arrivals and the service duration of packages is in good agreement with the Pareto and Weibull distributions, but in most cases the Pareto distribution prevails. The queuing systems with the queues M/Pa/1 and Pa/M/1 has been studied, and the fractality of the intervals of requests arriving have been compared by the properties of the estimates of the system load and the service duration. It has been found out that in the system Pa/M/1, with the parameter of the form a> 2, the fractality of the intervals of requests arriving does not affect the average waiting time and load factor. However, when ????≤2, as in the M/Pa/1 system, both considered statistical estimates differ. The application of adequate mathematical models of traffic allows to correctly assess the characteristics of the quality of service (QoS) of the network

ANALYSIS OF MAIN REQUIREMENTS FOR ELECTRONIC DOCUMENT MANAGEMENT SYSTEMS

This article discusses the document management of the enterprise, automation of "mechanical" document management, as well as advantages and disadvantages of electronic document management systems. Thus, the advantages of electronic document management systems include the following: saving time, more adequate use of physical space and technology. As well as increasing the transparency of the internal work of the enterprise, more flexibility with regard to the physical location of employees, improving the security of information and documents, reducing the cost of printing, postage stamps, envelopes and forwarding. In addition, the study transmitted the value of the document and its place in the company's office. The requirements of customers to electronic document management systems are also affected. In conclusion, we have reviewed the requirements for electronic document management systems and identified the main requirements for such systems. The main requirement of customers is financial costs. It is on them that depends on which modules of the electronic document management system will be preliminar

ORGANIZATION OF ENVIRONMENTAL MONITORING IN THE CASPIAN SEA

The object of research is ecological monitoring of the Caspian Sea. This article addressed the objectives and components of environmental monitoring. It also describes the objectives for the establishment of a Unified State Environmental Monitoring System. Special attention is paid to the structure of the environmental network monitoring system, which consists of three levels: low, medium and high. One of the main problems is the establishment of the Unified State Environmental Monitoring System of the Caspian Sea. This article considered the main functions and objectives of the Unified State Environmental Monitoring System. Here are also discussed the computing center of the environmental monitoring system and its functions and components. The research used three main components for environmental data processing: database management systems, geographic information system and integrated software packages. Examples of a computer system of environmental monitoring include: ArcGIS, MapInfo, ArcView and OCEAN. The main scientific results of this research are the main functions, objectives and components of environmental monitoring of the Caspian Sea to reduce pollution levels. The obtained results can be used to optimize the characteristics of environmental information systems, which are used to organize environmental monitoring. Innovative technological product of this research is the development of an algorithm for the organization of environmental monitoring of the Caspian Sea. It will allow ecologists to monitor the environmental situation of the Caspian Sea and further improve it. The obtained innovative technological product will be useful for carrying out environmental monitoring of the most contaminated section of the water basin, and more precisely for monitoring the scale of pollution and further improving the environmental situation of the water area

The Effect of Lost Data on the IoT Platform on the Formation of Fetal Heart Rate Graphs for Remote Diagnostic Purposes

FHR is the fetal heart rate from bpm recording detected by doppler, FHR monitoring is very important to monitor fetal health to avoid fetal distress or fetal death, FHR provides more in-depth information about how the baby is doing compared to traditional monitoring of the baby. IoT media is a medium for monitoring remote sensor values ​​using internet connections, but there are several obstacles, namely there are doubts about the data displayed by IoT media, namely the risk of missing or unsent data, this will be very dangerous if the data that is should be monitored by doctors as a reference for medical diagnosis and treatment is lost or not displayed on the IoT, because if there is missing data it will cause inaccurate diagnosis or health treatment decisions by doctors. The aim of this study to analyze the effect of lost data on the formation of the Fetal Heart Rate graph on the IoT platform as a medium for remote diagnosis. In addition, FHR data can be saved for further diagnosis by a doctor if needed. This study uses an ESP32 microcontroller which will also be used to send data to IoT (Thinger.io). The independent variable used in this study is FHR data before it is uploaded to the IoT, and the dependent variable is FHR data when it is uploaded to the IoT. The greatest data loss is at the farthest distance of 30 meters with a value of 62.47%. Based on the research that has been done, this study has the advantage that the results obtained from Doppler are close to the BPM value in humans. And also this research has developments that can be done in the future such as adding storage to the website that is used for monitoring, and placing the right position on Doppler so that the results are more stable

ANALYSIS OF MAIN REQUIREMENTS FOR ELECTRONIC DOCUMENT MANAGEMENT SYSTEMS

This article discusses the document management of the enterprise, automation of "mechanical" document management, as well as advantages and disadvantages of electronic document management systems. Thus, the advantages of electronic document management systems include the following: saving time, more adequate use of physical space and technology. As well as increasing the transparency of the internal work of the enterprise, more flexibility with regard to the physical location of employees, improving the security of information and documents, reducing the cost of printing, postage stamps, envelopes and forwarding. In addition, the study transmitted the value of the document and its place in the company's office. The requirements of customers to electronic document management systems are also affected. In conclusion, we have reviewed the requirements for electronic document management systems and identified the main requirements for such systems. The main requirement of customers is financial costs. It is on them that depends on which modules of the electronic document management system will be preliminary

Single Lead EMG signal to Control an Upper Limb Exoskeleton Using Embedded Machine Learning on Raspberry Pi

Post-stroke can cause partial or complete paralysis of the human limb. Delayed rehabilitation steps in post-stroke patients can cause muscle atrophy and limb stiffness. Post-stroke patients require an upper limb exoskeleton device for the rehabilitation process. Several previous studies used more than one electrode lead to control the exoskeleton. The use of many electrode leads can lead to an increase in complexity in terms of hardware and software. Therefore, this research aims to develop single lead EMG pattern recognition to control an upper limb exoskeleton. The main contribution of this research is that the robotic upper limb exoskeleton device can be controlled using a single lead EMG. EMG signals were tapped at the biceps point with a sampling frequency of 2000 Hz. A Raspberry Pi 3B+ was used to embed the data acquisition, feature extraction, classification and motor control by using multithread algorithm. The exoskeleton arm frame is made using 3D printing technology using a high torque servo motor drive. The control process is carried out by extracting EMG signals using EMG features (mean absolute value, root mean square, variance) further extraction results will be trained on machine learning (decision tree (DT), linear regression (LR), polynomial regression (PR), and random forest (RF)). The results show that machine learning decision tree and random forest produce the highest accuracy compared to other classifiers. The accuracy of DT and RF are of 96.36±0.54% and 95.67±0.76%, respectively. Combining the EMG features, shows that there is no significant difference in accuracy (p-value 0.05). A single lead EMG electrode can control the upper limb exoskeleton robot device well

Application of blockchain technology in “smart-digital hospital” cyber physical systems

Health informatization as an urgent problem has not yet been resolved. Quality medical care, intellectual level, communication infrastructure, management process, control of equipment, sensors are presented as a “smart-digital hospital” cyberphysical system with modern information technologies. The most important condition for “smart-digital” hospitals is that health workers inform patients about patients using the Internet of Things and mobile applications, and ensure their comfort

Застосування технологій великих даних для моніторингу соціальних процесів в університеті

This article discusses the use of big data for monitoring social processes. For this, the relationship of big data and sociology is examined. As an example, let’s conduct monitoring at the university. For this, some basic methods and tools of big data are considered, on the basis of which an algorithm for determining social processes and their monitoring is compliedВ данной статье рассматривается применение больших данных для проведения мониторинга социальных процессов. Для этого рассмотрены взаимосвязь больших данных и социологии. В качестве примера проведем мониторинг в университете. Для этого были рассмотрены некоторые основные методы и инструменты больших данных, на основе которых составили алгоритм для определения социальных процессов и проведения их мониторингаУ даній статті розглядається застосування великих даних для проведення моніторингу соціальних процесів. Для цього розглянуто взаємозв'язок великих даних і соціології. Як приклад проведемо моніторинг в університеті. Для цього були розглянуті деякі основні методи і інструменти великих даних, на основі яких склали алгоритм для визначення соціальних процесів і проведення їх моніторинг

The research of social processes at the university using big data

The volume of information in the 21st century is growing at a rapid pace. Big data technologies are used to process modern information. This article discusses the use of big data technologies to implement monitoring of social processes. Big data has its characteristics and principles, which reflect here. In addition, we also discussed big data applications in some areas. Particular attention in this article pays to the interactions of big data and sociology. For this, there consider digital sociology and computational social sciences. One of the main objects of study in sociology is social processes. The article shows the types of social processes and their monitoring. As an example, there is implemented monitoring of social processes at the university. There are used following technologies for the realization of social processes monitoring: products 1010data (1010edge, 1010connect, 1010reveal, 1010equities), products of Apache Software Foundation (Apache Hive, Apache Chukwa, Apache Hadoop, Apache Pig), MapReduce framework, language R, library Pandas, NoSQL, etc. Despite this, this article examines the use of the MapReduce model for social processes monitoring at the university