Transmission In Real Time Research Articles

IoT driven joint compressed sensing and shallow learning approach for ECG signal-reconstruction

Because biological signal transmission in real time might be very demanding, cloud and internet of things (IoT) infrastructure are required. To do this, the main component of the signal serves as the focal point of a reconstruction strategy that has been developed. The input is transferred to the intended destination once it has been encoded. Security is an important consideration that must not be disregarded. For long-term healthcare monitoring via lightweight wireless networks, electrocardiogram (ECG) compression is a major difficulty. Reducing energy consumption in wireless data transmission and precisely calculating error rates for data reconstruction are two essential components of compressed sensing. The application of effective encoding methods is crucial for these considerations. We present multi-task compressed sensing (MT-CS), a unique method for compressing ECG data. When used to wireless network systems with several embedded sensors, this technique is quite effective. From the ECG data, the model learns the fundamental adaptive properties needed for correlation. We use the multiparameter intelligent monitoring in intensive care (MIMIC-II) dataset to investigate the performance of the suggested MT-CS reconstruction technique in order to assess its strength and application. In comparison to current compressed sensing methods, the simulation results demonstrate that the suggested reconstruction methodology utilizing MT-CS generates high-quality reconstruction signals with fewer observations.

IIOT ПЕРЕДАЧА ДАННЫХ С БПЛА В ПРОМЫШЛЕННУЮ СРЕДУ АГРОКОМПЛЕКСОВ В РЕЖИМЕ РЕАЛЬНОГО ВРЕМЕНИ

Agricultural complexes, including agriculture, are a good environment for the introduction of modern technologies and methods of using unmanned aerial vehicles to solve various tasks. Currently, in distributed control systems in various agricultural complexes using unmanned aerial vehicles, the classical hardware and software architecture for building such systems has been established. However, this approach has a number of significant drawbacks. (Research purpose) The research purpose is selecting the IIoT of the wireless real-time communication protocol of unmanned aerial vehicles for irrigation of agricultural complexes with a ground-based industrial system and developing concepts of a hardware and software complex using modern technologies and practices of the industrial Internet of things. (Materials and methods) Used open sources of international communities in the field of automation and the industrial Internet of Things, as well as domestic and foreign scientific publications on these topics, as source data and materials for the analysis and design of the proposed hardware architecture of the IIoT platform. The method of decomposition according to automation levels was applied; the method of decomposition according to the functionality performed by individual hardware and software components of the system; the method of summarizing information from modern sources on the subject of research; formalization of the hardware and software structure in the form of schematic diagrams. (Results and discussions) Proposed the concept of information data transmission based on the IIoT protocol of DDS-real-time data transmission. (Conclusions) It has been shown that classical architectural approaches to data transmission in the conditions of wireless systems and agro-unmanned aircraft have proven themselves well, however, the need to introduce new architectural and software methods and protocols for data transmission in real time leads to the need to study promising ways to implement this functionality. We analyzed the existing global trends in the field under consideration and proposed an up-to-date and up-to-date concept of IIoT architecture of distributed data transmission systems within the framework of a distributed management and monitoring system for agricultural complexes based on unmanned aircraft.

A sequential Monte Carlo approach to estimate a time-varying reproduction number in infectious disease models: the Covid-19 case

Abstract The Covid-19 pandemic has required most countries to implement complex sequences of non-pharmaceutical interventions, with the aim of controlling the transmission of the virus in the population. To be able to take rapid decisions, a detailed understanding of the current situation is necessary. Estimates of time-varying, instantaneous reproduction numbers represent a way to quantify the viral transmission in real time. They are often defined through a mathematical compartmental model of the epidemic, like a stochastic SEIR model, whose parameters must be estimated from multiple time series of epidemiological data. Because of very high dimensional parameter spaces (partly due to the stochasticity in the spread models) and incomplete and delayed data, inference is very challenging. We propose a state-space formalization of the model and a sequential Monte Carlo approach which allow to estimate a daily-varying reproduction number for the Covid-19 epidemic in Norway with sufficient precision, on the basis of daily hospitalization and positive test incidences. The method was in regular use in Norway during the pandemics and appears to be a powerful instrument for epidemic monitoring and management.

A dynamic key management and secure data transfer based on m-tree structure with multi-level security framework for Internet of vehicles

Nowadays, broadband wireless networks and 5G have improvements in the quality and dependability of network services for high-speed mobile vehicles. Within an open communication environment on the Internet of vehicles named IoV, personal details will be revealed on the Wi-Fi network. Considering information security and privacy, this research concentrates on how to protect secure information transmission in real time through IoV, and also wants to avoid illegal vehicles, passers-by or drivers from joining connection and planting or altering significant data. This research provides a multilevel security infrastructure with M-tree based elliptic curve digital signature algorithm (ECDSA) for securing data transmission in both IoV and cloud environments. While transmitting, this study provides several flexible and scalable schemes to manage security issues, which dynamically adjust the framework depending on the rapidly changing IoV topology and speed up the time to synchronise the reconstruction of the system key, and decrease the quantity of phases to resynchronise the system key. Moreover, most research of key management without secure data transmission, we integrate the M-tree key management with secure data transmission to achieve the secure IoV. Simultaneously, the provided key management for the multi-level security is quite appropriate to adaptable and expandable IoV.

VehicleEIDS: A Novel External Intrusion Detection System Based on Vehicle Voltage Signals

Intelligent and connected vehicles (ICVs) have become the mainstream in the development of automobile industry. Many emerging technologies have been proposed to provide users with comfortable and convenient driving experience. However, even though these technologies significantly improve the quality of service, some of the communication interfaces they used are vulnerable and easily attacked. Note that although many malicious attacks can be carried out in various ways, their final step must be in the in-vehicle network, i.e., the controller area network (CAN) bus. In order to protect the security of the CAN bus, it is of great importance to design an intrusion detection system (IDS), which can monitor the message transmission in real time. In this article, we design a novel external IDS based on vehicle voltage signals, named VehicleEIDS. It does not occupy the bandwidth or computing resources of the CAN bus and maintains the original CAN bus protocol as well. The system can be directly installed in the automobile gateway to monitor the external intrusion, and can be connected to the CAN bus as an independent external device to protect the automobile security. In addition, VehicleEIDS is robust against the factors of vehicle status, the number of attacking electronic control units (ECUs), and the sending frequency of attack data. It is only related to the voltage signals of external intrusion device. Once external intrusion devices send attack data to the CAN bus, VehicleEIDS can quickly identify its abnormal voltage signals, with the accuracy of more than 97%.

Deciphering early-warning signals of SARS-CoV-2 elimination and resurgence from limited data at multiple scales.

Inferring the transmission potential of an infectious disease during low-incidence periods following epidemic waves is crucial for preparedness. In such periods, scarce data may hinder existing inference methods, blurring early-warning signals essential for discriminating between the likelihoods of resurgence versus elimination. Advanced insight into whether elevating caseloads (requiring swift community-wide interventions) or local elimination (allowing controls to be relaxed or refocussed on case-importation) might occur can separate decisive from ineffective policy. By generalizing and fusing recent approaches, we propose a novel early-warning framework that maximizes the information extracted from low-incidence data to robustly infer the chances of sustained local transmission or elimination in real time, at any scale of investigation (assuming sufficiently good surveillance). Applying this framework, we decipher hidden disease-transmission signals in prolonged low-incidence COVID-19 data from New Zealand, Hong Kong and Victoria, Australia. We uncover how timely interventions associate with averting resurgent waves, support official elimination declarations and evidence the effectiveness of the rapid, adaptive COVID-19 responses employed in these regions.

Effect of laser cutting conditions on the cutting front profile observed by X-ray transmission in real time

In laser cutting, industrial practitioners have historically demanded higher cutting speeds and better quality cuts. Thus, there has been significant interest in the elucidation of related processing phenomena. The cutting quality is commonly affected by the ejection behavior of the generated melt, which might be influenced by the profile of the laser cutting front. Therefore, it is desirable to directly observe the cutting front in real time; however, this cannot be easily achieved practically. In our previous work, we applied real-time observation using an X-ray transmission system to laser cutting fronts, thus enabling observation of the profile of the cutting front and the ejection behavior of the melt simultaneously. In this study, we quantitatively evaluate the cutting front profile observed fluoroscopically in real time using an X-ray transmission system and discuss the relationship between the profile and ejection behavior of the melt. In addition, we investigated the conditions for achieving a sound cut (dross-free cut). We directly confirmed that dross-free cutting occurs when the cutting front profile and ejection angle of the melt are approximately perpendicular to the surface of the test piece.

Estimating the Impact of Statewide Policies to Reduce Spread of Severe Acute Respiratory Syndrome Coronavirus 2 in Real Time, Colorado, USA.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic necessitated rapid local public health response, but studies examining the impact of social distancing policies on SARS-CoV-2 transmission have struggled to capture regional-level dynamics. We developed a susceptible-exposed-infected-recovered transmission model, parameterized to Colorado, USA‒specific data, to estimate the impact of coronavirus disease‒related policy measures on mobility and SARS-CoV-2 transmission in real time. During March‒June 2020, we estimated unknown parameter values and generated scenario-based projections of future clinical care needs. Early coronavirus disease policy measures, including a stay-at-home order, were accompanied by substantial decreases in mobility and reduced the effective reproductive number well below 1. When some restrictions were eased in late April, mobility increased to near baseline levels, but transmission remained low (effective reproductive number <1) through early June. Over time, our model parameters were adjusted to more closely reflect reality in Colorado, leading to modest changes in estimates of intervention effects and more conservative long-term projections.

A novel fast time jamming analysis transmission selection technique for radar systems

The jamming analysis transmission selection (JATS) sub-system is used in radar systems to detect and avoid the jammed frequencies in the available operating bandwidth during signal transmission and reception. The available time to measure the desired frequency spectrum and select the non-jammed frequency for transmission is very limited. A novel fast time (FAT) technique that measures the channel spectrum, detects the jamming sub-band and selects the non-jammed frequency for radar system transmission in real time is proposed. A JATS sub-system has been designed, simulated, fabricated and implemented based on FAT technique to verify the idea. The novel FAT technique utilizes time-domain analysis instead of the well-known fast Fourier transform (FFT) used in conventional JATS sub-systems. Therefore, the proposed fast time jamming analysis transmission selection (FAT-JATS) sub-system outperforms other reported JATS sub-systems as it uses less FPGA resources, avoids time-delay occurred due to complex FFT calculations and enhances the real time operation. This makes the proposed technique an excellent candidate for JATS sub-systems.

Discussion on Industrial Internet Platform Construction Based on Power Internet of Things

At present, the development of industrial Internet platform is in a period of large-scale expansion. Since 2017, China has issued a series of documents, such as the Guidance on Deepening “Internet + Advanced Manufacturing” to Develop Industrial Internet, the Action Plan for Industrial Internet Development (2018-2020), and the Industrial Internet App Cultivation Project (2018-2020), which constantly points out the direction for the development of the industrial Internet industry. The power Internet of Things connects the equipment, customers and data in all links of energy production, transmission and consumption in real time, fully bearing the production and operation of power grid, enterprise management and new business development, etc. It has the characteristics of ubiquitous terminal access, open platform sharing, computing cloud collaboration, convenient and flexible application, etc. This paper aims to discuss how the power Internet of Things can help the construction of the industrial Internet, provide strong data resource support and service for the safe and economic operation of the power grid, improve business performance, improve service quality, cultivate and develop strategic emerging industries, and open up a new road for management innovation, business innovation and value creation.

Spatial technologies to strengthen traditional testing for SARS-CoV-2.

Advanced spatial and digital technologies may help us to take fuller advantage of limited testing resources to monitor the infection status of a large population in a cost-effective manner. Moreover, they may provide additional evidence to supplement results of nucleic acid testing (NAT) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to decrease false-negative and false-positive rates.

Secure and efficient mutual authentication protocol for smart grid under blockchain

Smart grid has been acknowledged as the next-generation intelligent network that optimizes energy efficiency. Primarily through a bidirectional communication channel, suppliers and users can dynamically adjust power transmission in real time. Nonetheless, many security issues occur with the widespread deployment of smart grid, e.g., centralized register authority and potential Distributed-Denial-of-Service (DDoS) attack. These existing problems threaten the availability of smart grid. In this paper, we mainly focus on solving some identity authentication issues remained in the smart grid. Combined with blockchain, Elliptic Curve Cryptography (ECC), dynamic Join-and-Exit mechanism and batch verification, a reliable and efficient authentication protocol is proposed for smart meters and utility centers. Simultaneously, the provable security of this protocol is assured by the computational hard problem assumptions. Experiment results show that our protocol has achieved security and performance improvement compared with the other ECC related schemes.

Multi-Channel and Simultaneous Data Acquisition System for Magnetic Tensor Detection

This paper reports the design of a multi-channel and simultaneous data acquisition system(MSDAS). It can collect 12-channel magnetic induction component signals with magnetic tensor information rapidly and simultaneously. The STM32F103RCT6 and a 16-bit AD7606 are used as the MSDAQ’s microcontroller and the analog-to-digital(A/D) converter, respectively. Moreover, FATFS file system and TCP/IP protocol are integrated such that the MSDAS is capable of local storage and network simultaneous data transmission in real time. Experiments show that MSDAS can achieve data acquisition error ≤0.5% with the simultaneous sampling rate up to 500Hz. It is verified that the measurement results of magnetic tensor are basically consistent with the theory.

DETERMINATION OF PROBABILITY - TEMPORARY CHARACTERISTICS OF COMMUNICATION CHANNELS WHEN TRANSMITTING PRIORITY AND NON-PRIORITY DATA.

The article discusses the issues of finding the main indicators of the quality of the communication channel in computer networks when transmitting priority and non-priority data at different frame lengths. To solve this problem, methods of the theory of queuing using Petri nets are proposed. The proposed method for calculating the temporal and probabilistic characteristics of computer networks allows determinining the main indicators of the quality of the channel in a stationary mode when transmitting priority and non-priority data of computing tools at various values of the input stream intensity. To simulate the transmission of priority and non-priority frames, a color temporary Petri net is proposed. An algorithm is proposed for determining the basic parameters of information transfer, based on the use of the Little formula and allowing one to determine the number of frames in a queue, the average time a frame has been in a queue, and other distinctive features of the algorithm include the use of the window mode. The proposed technique allows to reduce the loss of priority frames of trajectory information and ensuring their transmission in real time.

Readout Electronics for CBM-TOF Supermodule Quality Evaluation

Super module assembled with MRPC detectors is the component unit of TOF (Time of Flight) system for the Compressed Baryonic Matter (CBM) experiment. Quality of super modules needs to be evaluated before it is applied in CBM-TOF. Time signals exported from super module are digitalized at TDC (Time to Digital Converter) station. Data rate is up to 6 Gbps at each TDC station, which brings a tremendous pressure for data transmission in real time. In this paper, a real-time data flow control method is designed. In this control method, data flow is divided into 3 types: scientific data flow, status data flow and control data flow. In scientific data flow, data of each TDC station is divided into 4 sub-flows, and then is read out by a parallel and hierarchical network, which consists of multiple readout mother boards and daughter boards groups. In status data flow, status data is aggregated into a specific readout mother board. Then it is uploaded to DAQ via readout daughter board. In control data flow, control data is downloaded to all circuit modules in the opposite direction of status data flow. Preliminary test result indicated data of STS was correctly transmitted to DAQ with no error and three type data flows were control orderly in real time. This data flow control method can meet the quality evaluation requirement of supper module in CBM-TOF.

МАТЕМАТИЧЕСКАЯ МОДЕЛЬ ИСПОЛНИТЕЛЬНЫХ МОДУЛЕЙ ЗАХВАТНЫХ УСТРОЙСТВ РОБОТОВ

Today, the task of increasing the drive unit technical characteristics of robot gripping devices is relevant. In many respects, the drive motor and gear unit determine the quality of work of such modules, which can introduce additional elasticity, backlash and friction into the system. In turn, backlash and friction in the control loop decrease the speed and accuracy of the mechatronic module and can cause self-oscillations. However, significant progress in hardware performance of mechatronic and robotic systems makes it possible to more accurately estimate and control the force and torque state parameters in the output link and to carry out active algorithmic compensation for the effects of friction and elasticity.&#x0D; Such observers are usually based on detailed mathematical models and allows to implement force control without the use of special sensors, which is especially important in advanced gripping devices due to the requirements imposed on the mass-dimensional parameters of the product. Therefore, the purpose of this article is to make a general mathematical model of the robot drive unit with a rational relationship of complexity and accuracy. The models’ parameters should be easily identified from the constituent elements of passport data or the experiment results. The model should allow estimating the state parameters of mechanical transmission in real time; take into account the main friction effects. However, it should be simple enough for analytical conclusion and numerical modeling. As part of the article, various friction models are considered. On the basis of this analysis, a modified friction model is proposed. It makes possible to estimate the state parameters of mechanical transmission in real time. It is built into the general mathematical model of the mechatronic module. The results of mathematical simulation are close to experimental data. The considered drive unit mathematical model can be used to identify the state parameters of the mechatronic module in real time and implement force control based on estimation. In addition, the obtained model allows to conduct mathematical simulation of the robot taking into account the drive unit dynamics.

Ion-beam focusing by self-organized axis-symmetric potentials in insulating capillaries

In a combined theoretical and experimental study, we give evidence that the self-organized electric potential in tapered glass capillaries has the strength to focus a low-energy ion beam. Similar to Einzel lenses, the on-axis injected beam is focused by an axis-symmetric potential, generated by the charge accumulated in the insulating capillary. We argue that for capillaries with large aspect ratio, the mechanism responsible for the focusing in our experiment is different from the one shown in earlier experiments. We found that the potential inside the capillary had to reach about 70% of the extraction potential of the ion source in order to be strong enough to focus the beam through the capillary. With increasing injected current intensities, the transmitted current density is shown to increase up to a factor 10 with respect to the injected one. An original experimental setup is used to monitor the accumulated total charge in the capillary linking the latter to the transmitted fraction of the beam. This way, we can clearly identify the different stages of the transmission in real time, and in particular the Coulomb blocking, and explain why it occurred inevitable in this setup. The experimental data are corroborated by our simulations, which allow a valuable and comprehensive insight into the dynamics of the self-organized Coulomb potential. The latter controls the focusing effect and explains many features such as why the transmitted fraction increases with the injected intensity.

Genomic and epidemiological monitoring of yellow fever virus transmission potential.

The yellow fever virus (YFV) epidemic in Brazil is the largest in decades. The recent discovery of YFV in Brazilian Aedes species mosquitos highlights a need to monitor the risk of reestablishment of urban YFV transmission in the Americas. We use a suite of epidemiological, spatial, and genomic approaches to characterize YFV transmission. We show that the age and sex distribution of human cases is characteristic of sylvatic transmission. Analysis of YFV cases combined with genomes generated locally reveals an early phase of sylvatic YFV transmission and spatial expansion toward previously YFV-free areas, followed by a rise in viral spillover to humans in late 2016. Our results establish a framework for monitoring YFV transmission in real time that will contribute to a global strategy to eliminate future YFV epidemics.

Transmission of dynamic supercoiling in linear and multi-way branched DNAs and its regulation revealed by a fluorescent G-quadruplex torsion sensor.

DNA supercoiling is an important regulator of gene activity. The transmission of transcription-generated supercoiling wave along a DNA helix provides a way for a gene being transcribed to communicate with and regulate its neighboring genes. Currently, the dynamic behavior of supercoiling transmission remains unclear owing to the lack of a suitable tool for detecting the dynamics of supercoiling transmission. In this work, we established a torsion sensor that quantitatively monitors supercoiling transmission in real time in DNA. Using this sensor, we studied the transmission of transcriptionally generated negative supercoiling in linear and multi-way DNA duplexes. We found that transcription-generated dynamic supercoiling not only transmits along linear DNA duplex but also equally diverges at and proceeds through multi-way DNA junctions. We also show that such a process is regulated by DNA–protein interactions and non-canonical DNA structures in the path of supercoiling transmission. These results imply a transcription-coupled mechanism of dynamic supercoiling-mediated intra- and inter-chromosomal signal transduction pathway and their regulation in DNA.

An Efficient Adaptive Broadcast Protocol for Different Scenarios in VANETs

Background: VANETs demand a fast and reliable data transmission in real time for safety concerns, which is challenging due to vehicles’ fast movement, network topology dynamics, and communication network varieties. This paper reviews current scientific and patent literature and proposes an efficient and adaptive broadcast protocol using neighbor nodes ’distances and driving directions to determine packet forwarding nodes. The protocol is capable of discovering cross roads utilizing neighbor nodes’ moving direction information, therefore suitable for broader application scenarios including intersections and straight road. Keywords: VANET, broadcast protocol, neighbor node, distance, driving direction, data transmission.