scholarly journals ЛОКАЛЬНО-АДАПТИВНАЯ ФИЛЬТРАЦИЯ НЕСТАЦИОНАРНОГО ШУМА В ДЛИТЕЛЬНЫХ ЭЛЕКТРОКАРДИОГРАФИЧЕСКИХ СИГНАЛАХ

2020 ◽  
pp. 16-33
Author(s):  
Наталия Олеговна Тулякова ◽  
Александр Николаевич Трофимчук
Keyword(s):  
Real Time ◽  
High Efficiency ◽  
A Priori ◽  
Adaptive Algorithms ◽  
Adaptive Method ◽  
Noise Variance ◽  
Stationary Noise ◽  
Ecg Signals ◽  
Statistical Estimates ◽  
Locally Adaptive

The research subject of the article is the methods of locally adaptive filtering of non-stationary (from the point of view of its variance) noise in long-term electrocardiogram (ECG) signals. The goal is to develop locally adaptive algorithms for filtering noise with different a priori unknown levels of variance in real-time for ECG signals recorded with a standard sampling rate of 500 Hz. The tasks to be solved are: to investigate the effectiveness of the developed adaptive ECG filtering algorithms using numerical statistical estimates of processing quality in a wide range of additive Gaussian noise variance variation, to investigate the suppression of real non-stationary electromyographic (EMG) noise, and to analyze the application for normal and pathological ECG signals. The methods are integral and local indicators of the filter quality according to the criteria of the mean square error and the signal-to-noise ratio was obtained using numerical simulation (via Monte Carlo analysis). The following results were obtained: an adaptive method for real-time suppression of non-stationary noise in the ECG is proposed, the one-pass and the two-pass algorithms, and the algorithm with selective depending on the preliminary estimates of noise levels re-filtering have been developed on the method basis. Statistical estimates of the filters' efficiency and analysis of their outputs show a high degree of suppression of the noise with different levels of variance in the ECGs. The distortions absence while processing QRS-complex and high efficiency of suppression of Gaussian and real EMG noise with varying variance are demonstrated. The analysis of the output signals and plots of the local adaptation parameters and the adaptable parameters of the proposed algorithms confirms the high efficiency of filtering. The developed algorithms have been successfully tested for normal and pathological ECG signals. Conclusions. The scientific novelty of the results is the development of a locally adaptive method with noise and signal-dependent filter parameters switching and of the adaptive algorithms based on this method for non-stationary noise reduction in the ECG in real-time. This method does not require time for filter parameters adaptation and a priori information about the noise variance, and it has a high-speed performance in real-time mode.

scholarly journals Adaptive method of detecting traffic anomalies in high-speed multi-service communication networks

2020 ◽  
Vol 157 ◽  
pp. 04027 ◽  
Author(s):  
Sergey Ageev ◽  
Vladimir Karetnikov ◽  
Evgeny Ol’khovik ◽  
Andrey Privalov
Keyword(s):  
Network Security ◽  
Real Time ◽  
Communication Networks ◽  
High Speed ◽  
High Efficiency ◽  
Adaptive Methods ◽  
Adaptive Method ◽  
Anomalous Behavior ◽  
Preliminary Training ◽  
Network Attacks

In the paper, an adaptive hybrid heuristic (behavioral) method for detecting small traffic anomalies in high-speed multiservice communication networks, which operates in real time, is proposed and investigated. The relevance of this study is determined by the fact that network security management processes in high-speed multiservice communication networks need to be implemented in a mode close to real-time mode, as well as identifying possible network security threats in the early stages of the implementation of possible network attacks. The proposed method and algorithm belong to the class of adaptive methods and algorithms with preliminary training. The average relative error in estimating the evaluated traffic parameters does not exceed 10%, which is sufficient for the implementation of operational network management tasks. Anomalies of the expectation of traffic intensity and its dispersion are identified if their valuesexceed the normal values by 15% or more, which makes it possible to detect possible network attacks in the early phases of their implementation, for example, at the stage of scanning ports and interfaces of the attacked system. The procedure for detecting anomalous traffic behavior is implemented based on the Mamdani’s method of hierarchical fuzzy logical inference. A study of the proposed method for detecting anomalous behavior of network traffic showed its high efficiency.

A Novel Cardiac Arrhythmias Detection Approach for Real-Time Ambulatory ECG Diagnosis

2017 ◽  
Vol 31 (10) ◽  
pp. 1758004 ◽  
Author(s):  
Haiying Zhou ◽  
Xiancheng Zhu ◽  
Sishan Wang ◽  
Kui Zhou ◽  
Zheng Ma ◽  
...  
Keyword(s):  
Real Time ◽  
Cardiac Arrhythmias ◽  
High Efficiency ◽  
Interval Estimation ◽  
Morphological Characteristics ◽  
Linear Discriminant ◽  
Ecg Signals ◽  
Detection Approach ◽  
Emergency Events ◽  
Learning Machine

In view of requirements of low-resource consumption and high-efficiency in real-time Ambulatory Electrocardiograph Diagnosis (AED) applications, a novel Cardiac Arrhythmias Detection (CAD) algorithm is proposed. This algorithm consists of three core modules: an automatic-learning machine that models diagnostic criteria and grades the emergency events of cardiac arrhythmias by studying morphological characteristics of ECG signals and experiential knowledge of cardiologists; a rhythm classifier that recognizes and classifies heart rhythms basing on statistical features comparison and linear discriminant with confidence interval estimation; and an arrhythmias interpreter that assesses emergency events of cardia arrhythmias basing on a two rule-relative interpretation mechanisms. The experiential results on off-line MIT-BIH cardiac arrhythmia database as well as online clinical testing explore that this algorithm has 92.8% sensitivity and 97.5% specificity in average, so that it is suitable for real-time cardiac arrhythmias monitoring.

Methods and Algorithms for Real Time Voice Noise Cleaning

2021 ◽  
Vol 26 (2) ◽  
pp. 184-196
Author(s):  
I.E. Vishnyakov ◽  
◽  
M.M. Masyagin ◽  
O.A. Odintsov ◽  
V.V. Sliusar ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
High Efficiency ◽  
Noise Suppression ◽  
Signal Transmission ◽  
Adaptive Method ◽  
Streaming Data ◽  
The Real ◽  
Operation Speed ◽  
Cleaning Methods

The voice cleaning methods and algorithms play a key role both in preprocessing speech for further analysis and recognition, and in improving the quality of communication between users of information networks. The real-time streaming noise cleaning methods are the most important and complex area. The ability to process streaming data without delays imposes a number of significant restrictions on the algorithm: it cannot be iterative with a previously unknown number of iterations, and cannot explicitly use the data before or after the current block being processed. In the work, a modern adaptive noise reduction method for speech that can work with minimal signal transmission delays has been proposed. A large-scale study of existing approaches has been conducted, with special attention paid to two groups of algorithms: noise detection algorithms and noise suppression algorithms. Based on them the developed algorithm meeting the specified requirements has been built and analyzed. A set of audio data of Russian speech with various noises superimposed on it has been created. The testing of the algorithm has been made and its comparison with existing actual noise cleaning methods has been performed. The proposed adaptive method of noise cleaning without using specialized apparatus means and subsidiary information is able to operate in the real time conditions. The testing of the developed algorithm using the metrics of segment NC and PESQ have shown the high efficiency of the development and its superiority to common noise cleaning implementations Speex and WebRTC with respect to the noise cleaning quality and operation speed.

Design of Portable Electrocardiograph Monitoring System

2020 ◽  
Author(s):  
Jia Hua-Ping ◽  
Zhao Jun-Long ◽  
Liu Jun
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Data Storage ◽  
P Wave ◽  
Ecg Monitoring ◽  
The Public ◽  
Ecg Signals ◽  
Early Warning Mechanism ◽  
Timely Treatment ◽  
Ecg Data

Cardiovascular disease is one of the major diseases that threaten the human health. But the existing electrocardiograph (ECG) monitoring system has many limitations in practical application. In order to monitor ECG in real time, a portable ECG monitoring system based on the Android platform is developed to meet the needs of the public. The system uses BMD101 ECG chip to collect and process ECG signals in the Android system, where data storage and waveform display of ECG data can be realized. The Bluetooth HC-07 module is used for ECG data transmission. The abnormal ECG can be judged by P wave, QRS bandwidth, and RR interval. If abnormal ECG is found, an early warning mechanism will be activated to locate the user’s location in real time and send preset short messages, so that the user can get timely treatment, avoiding dangerous occurrence. The monitoring system is convenient and portable, which brings great convenie to the life of ordinary cardiovascular users.

Identification of L. casei and L. rhamnosus in the dairy products using Real-Time PCR assay

2015 ◽  
Vol 4 (5) ◽  
pp. 222-225
Author(s):  
K. G. Li ◽  
G. P. Pogossian ◽  
A. K. Moldagulova ◽  
E. E. Bekenova ◽  
A. Abdikadirova ◽  
...  
Keyword(s):  
Real Time ◽  
Real Time Pcr ◽  
Dairy Products ◽  
Production Control ◽  
High Efficiency ◽  
High Specificity ◽  
Industrial Test ◽  
Fermented Dairy Products ◽  
Species Specific ◽  
Fermented Dairy

  Lactobacilli are essential and important biological objects used in food pro-duction and medicine. One of the sufficient problems is fast, reliable and highly specific identification of lactobacilli in the scientific research and cur-rent production control. We represent two species-specific real-time PCR in the present study to discriminate L. rhamnosus and L. casei basing on the unique peptidoglycan-hydrolase genes p40 and p75 respectively. PCR pri-mers and probes were designed to provide high specificity discrimination via high temperature of PCR annealing stage. High efficiency of the reactions is provided by the size of amplified DNA fragments minimization. Reliable re-producibility of the target sequences amplification and fluorescence detec-tion provide a basis for the future creation of industrial test-systems for op-erational control in the production of fermented dairy products.

A framework for near real-time ROM stockpile modelling to improve blending efficiency

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shi Zhao ◽  
Tien-Fu Lu ◽  
Larissa Statsenko ◽  
Benjamin Koch ◽  
Chris Garcia
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Laser Scanning ◽  
High Efficiency ◽  
Reference Model ◽  
Geometric Model ◽  
Mining Industry ◽  
Management Systems ◽  
Content Type ◽  
Ore Grade

Purpose In the mining industry, a run-of-mine (ROM) stockpile is a temporary storage unit, but it is also widely accepted as an effective method to reduce the short-term variations of ore grade. However, tracing ore grade at ROM stockpiles accurately using most current fleet management systems is challenging, due to insufficient information available in real time. This study aims to build a three-dimensional (3D) model for ROM stockpiles continuously based on fine-grained grade information through integrating data from a number of ore grade tracking sources. Design/methodology/approach Following a literature review, a framework for a new stockpile management system is proposed. In this system, near real-time high-resolution 3D ROM stockpile models are created based on dump/load locations measured from global positioning system sensors. Each stockpile model contains a group of layers which are separated by different qualities. Findings Acquiring the geometric shapes of all the layers in a stockpile and cuts made by front wheel loaders provides a better understanding about the quality and quality distribution within a stockpile when it is stacked/reclaimed. Such a ROM stockpile model can provide information on predicating ore blend quality with high accuracy and high efficiency. Furthermore, a 3D stockyard model created based on such ROM stockpile models can help organisations optimise material flow and reduce the cost. Research limitations/implications The modelling algorithm is evaluated using a laboratory scaled stockpile at this stage. The authors expect to scan a real stockpile and create a reference model from it. Meanwhile, the geometric model cannot represent slump or collapse during reclaiming faithfully. Therefore, the model is expected to be reconcile monthly using laser scanning data. Practical implications The proposed model is currently translated to the operations at OZ Minerals. The use of such model will reduce the handling costs and improve the efficiency of existing grade management systems in the mining industry. Originality/value This study provides a solution to build a near real-time high-resolution multi-layered 3D stockpile model through using currently available information and resources. Such novel and low-cost stockpile model will improve the production rates with good output product quality control.

Design and development of a navigation system for agricultural aerial spraying

2017 ◽  
Vol 8 (2) ◽  
pp. 870-875
Author(s):  
M. J. Zhang ◽  
R. R. Zhang ◽  
G. Xu ◽  
L. P. Chen
Keyword(s):  
Real Time ◽  
Navigation System ◽  
High Efficiency ◽  
Route Planning ◽  
Utilization Rate ◽  
Tablet Pc ◽  
Design And Development ◽  
Heavy Workload ◽  
Aerial Spraying ◽  
Time Evaluation

Problems in the process of manned agricultural aerial spraying, such as heavy workload in route planning, overlaps or omissions in spraying seriously reduce the efficiency of spraying and utilization rate of pesticides. This paper presents the design and development of a navigation system for manned agricultural aerial spraying based on an industrial tablet PC. This system provides three key functions: route planning, spraying navigation and real-time evaluation of spraying quality. The test and application results show that this system has high efficiency in route planning, and the average coverage rate of spraying could reach as high as 96%. Its application effect is remarkable, and as a result, this system can meet the demand of manned agricultural aerial spraying in route planning and navigation.

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