Mathematical tools and software for the distributed geophone network of Prognoz-ADS geomechanical monitoring system

Introduction. The article considers the problems of the present-day algorithm of acoustic emission events location in Prognoz-ADS geomechanical monitoring system. The ways of solving the flaws in the applied algorithm have been proposed with the account of the specified requirements. Research aim is to propose certain solutions aimed at achieving higher accuracy of seismoacoustic events coordinates calculation; to solve the flat antenna problem and get the opportunity of assessing the efficiency of separate observing network elements; develop the structure of a new location algorithm and calculate its preliminary complexity. Methodology. It is proposed to correct the problems of the existing algorithm by constructing the velocity map of the controlled object and assessing the efficiency of seismoacoustic receivers and data on the observing network sensitivity in various sections of the rock mass. Results. The article provides logical structure of the developed algorithm with complexity O(n). It is proposed to solve the flat antenna problem by using data on seismic receivers complex sensitivity. Certain media of collecting information on the observing network state and signal propagation velocities at the controlled object have been introduced. Summary. The designed algorithm provides for multiple parameters variation, many of them are not taken into account in the existing location method of Prognoz-ADS system. The indicated characteristics selection and the efficient use of the calculating tool’s hardware resources will make it possible to obtain a more accurate and universal location algorithm.

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New Location Algorithm with Primary User Based on Scatter Information in Cognitive Radio

Wireless Personal Communications ◽

10.1007/s11277-021-08309-2 ◽

2021 ◽

Author(s):

Dan Ye

Keyword(s):

Cognitive Radio ◽

Primary User ◽

Location Algorithm ◽

New Location

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Confidence intervals for a difference between lognormal means in cluster randomization trials

Statistical Methods in Medical Research ◽

10.1177/0962280214552291 ◽

2014 ◽

Vol 26 (2) ◽

pp. 598-614 ◽

Cited By ~ 1

Author(s):

Julia Poirier ◽

GY Zou ◽

John Koval

Keyword(s):

Confidence Intervals ◽

Community Acquired Pneumonia ◽

Small Sample ◽

Cluster Randomization ◽

Critical Pathway ◽

Arithmetic Means ◽

Multiple Parameters ◽

The Difference ◽

Using Data ◽

Small Sample Sizes

Cluster randomization trials, in which intact social units are randomized to different interventions, have become popular in the last 25 years. Outcomes from these trials in many cases are positively skewed, following approximately lognormal distributions. When inference is focused on the difference between treatment arm arithmetic means, existent confidence interval procedures either make restricting assumptions or are complex to implement. We approach this problem by assuming log-transformed outcomes from each treatment arm follow a one-way random effects model. The treatment arm means are functions of multiple parameters for which separate confidence intervals are readily available, suggesting that the method of variance estimates recovery may be applied to obtain closed-form confidence intervals. A simulation study showed that this simple approach performs well in small sample sizes in terms of empirical coverage, relatively balanced tail errors, and interval widths as compared to existing methods. The methods are illustrated using data arising from a cluster randomization trial investigating a critical pathway for the treatment of community acquired pneumonia.

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Exploration of a New Location Algorithm for Wireless Sensor Network

International Journal of Online Engineering (iJOE) ◽

10.3991/ijoe.v14i06.8708 ◽

2018 ◽

Vol 14 (06) ◽

pp. 191

Author(s):

Chao Huang ◽

Yuang Mao

Keyword(s):

Threshold Value ◽

Location Error ◽

Original Algorithm ◽

Node Ratio ◽

Location Algorithm ◽

Beacon Node ◽

New Location ◽

The Average Range ◽

Better Than ◽

Range Calculation

To further study the basic principle and localization process of DV-Hop location algorithm, the location error reason of traditional location algorithm caused by the minimum hop number was analyzed and demonstrated in detail. The RSSI ranging technology was introduced to modify the minimum hops stage, and the minimum hop number was improved by the DV-Hop algorithm. For the location error caused by the average hop distance, the hop distance of the original algorithm was optimized. The improved location algorithm of DV-Hop average hop distance was used to modify the average range calculation by introducing the proportion of beacon nodes and the optimal threshold value. The optimization algorithm of the two different stages was combined into an improved location algorithm based on hop distance optimization, and the advantages of the two algorithms were taken into account.Finally, the traditional DV-Hop location algorithm and the three improved location algorithms were simulated and analyzed by beacon node ratio and node communication radius with multi angle. The experimental results showed that the improved algorithm was better than the original algorithm in the positioning stability and positioning accuracy.

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DESIGN AND IMPLEMENTATION OF INTELLIGENT SEAWATER AUTOMATIC ON-LINE MONITORING SYSTEM BASED ON BIG DATA

Latin American Applied Research - An international journal ◽

10.52292/j.laar.2018.219 ◽

2018 ◽

Vol 48 (3) ◽

pp. 157-162

Author(s):

L. Y. LI ◽

J. YANG ◽

Y. LEI ◽

K. H. XIONG ◽

W. H. CHEN ◽

...

Keyword(s):

Monitoring System ◽

Online Monitoring ◽

Large Data ◽

Test System ◽

Data Conversion ◽

Detection Technology ◽

Large Data Analysis ◽

Using Data ◽

Integration Data ◽

Sea Area

Based on large data analysis method and automatic detection technology, this paper designs a test system, which can realize intelligent online monitoring of seawater. Based on the theory of large data, the data preprocessing method of large data is applied by relying on the information transmitted by integrated sensors. Using data cleaning, data integration, data conversion and data reduction technology, a large number of data collected by marine monitoring devices are processed accurately. An automatic seawater monitoring system is designed on a software platform. Finally, combined with the experimental data of a certain sea area, the test results are analyzed, which proves the feasibility and effectiveness of the designed seawater online monitoring system. It has achieved the effect of seawater environmental analysis and early warning.

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The Assessment of Human Exposure in Iasi-City using Data Provided by The National Autonomous RF-EMF Monitoring System throughout 2020

10.1109/sielmen53755.2021.9600350 ◽

2021 ◽

Author(s):

MariusVasile Ursachianu ◽

Ovidiu Bejenaru ◽

Catalin Lazarescu ◽

Alexandru Salceanu ◽

Marius Paulet

Keyword(s):

Monitoring System ◽

Human Exposure ◽

Using Data

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Signal Propagation on a Railway Wireless Condition Monitoring System

IET Colloquium on Antennas, Wireless and Electromagnetics 2014 ◽

10.1049/ic.2014.0017 ◽

2014 ◽

Author(s):

A. Faghih ◽

C. Constantinou ◽

E. Stewart

Keyword(s):

Monitoring System ◽

Condition Monitoring ◽

Signal Propagation ◽

Condition Monitoring System

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Analysisof Students’ Web Browsing Behaviours Using Data Miningat a Campus Network

Turkish Journal of Computer and Mathematics Education (TURCOMAT) ◽

10.17762/turcomat.v12i6.5779 ◽

2021 ◽

Vol 12 (6) ◽

pp. 2726-2738

Author(s):

Murizah Kassim, Muhammad Ahlami Ashraf Roslan

Keyword(s):

Data Mining ◽

Monitoring System ◽

Mining Machine ◽

Campus Network ◽

Time Data ◽

Network Computer ◽

Indexing Method ◽

R Programming ◽

Using Data ◽

Browsing Behavior

Analytics provides insight to people based on the analytics of past usage by using techniques such as statistics, data mining, machine learning and artificial intelligence. Lack of monitoring system of browsing causes low engagements that reduce the growth of certain businesses caused by unnecessary browsing for students learning time. This paper presents an analysis on browsing behavior that classifies browsed words followed their ethical word-groups browsing. An Analytic platform is created as a monitoring system of browsing behavior. Data mining, indexing and classification method are used in this research as data is the essential key of creating a predictive model and four types of ethical groups have been filtered based on the browsing behaviors. The browsed words are categorized into four types of browsing called queries, applications, social media, Campus-related sites. The research method uses software tools and data mining process on the browsing data and analytics is presented on the development of the dashboard mainly using the R programming language. Few unethical words using the indexing method are generated in analytic graphs based on the type of browsing versus time. Data collected from the browsing behaviors of students’analysis taken from browsing database of personal computer and laboratory computer in the campus network. The result shows that othercategories are the highest categories which reached79.6% for personals' computer browsing compared to72.4% browsing at the laboratory computers. It is identified that about 21% of the browsing behavior was filtered during the data mined processed. The other category is still on the research portfolio where these libraries must be filtered in detail to identify whether they are learning or non-learning activities. This research is significant in that helps to increase the effectiveness of suggestions applications, optimize the internet usage by blocking unnecessary words or webpages, and even campus guide systems by monitoring the surrounding browsing behavior of the students’ usages of the campus network computer labs.

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