data errors
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2022 ◽  
Vol 70 (1) ◽  
pp. 38-52
Author(s):  
Frank Schiller ◽  
Dan Judd ◽  
Peerasan Supavatanakul ◽  
Tina Hardt ◽  
Felix Wieczorek

Abstract A fundamental measure of safety communication is the residual error probability, i. e., the probability of undetected errors. For the detection of data errors, typically a Cyclic Redundancy Check (CRC) is applied, and the resulting residual error probability is determined based on the Binary Symmetric Channel (BSC) model. The use of this model had been questioned since several error types cannot be sufficiently described. Especially the increasing introduction of security algorithms into underlying communication layers requires a more adequate channel model. This paper introduces an enhanced model that extends the list of considered data error types by combining the BSC model with a Uniformly Distributed Segments (UDS) model. Although models beyond BSC are applied, the hitherto method of the calculation of the residual error probability can be maintained.


2021 ◽  
pp. 46-55
Author(s):  
А.В. Никитин ◽  
А.В. Михайлов ◽  
А.С. Петров ◽  
С.Э. Попов

A technique for determining the depth and opening of a surface two-dimensional defect in a ferromagnet is presented, that is resistant to input data errors. Defects and magnetic transducers are located on opposite sides of the metal plate. The nonlinear properties of the ferromagnet are taken into account. The components of the magnetic field in the metal were reconstructed from the measured components of the magnetic field above the defect-free surface of the metal. As a result of numerical experiments, the limits of applicability of the method were obtained. The results of the technique have been verified experimentally.


2021 ◽  
Vol 2021 ◽  
Author(s):  
Steffen Berg ◽  
◽  
Evren Unsal

Multiphase flow in porous media systems is a critical element of many processes in the energy industry. The characteristics of the simultaneous flow of the immiscible phases can be quantified using relative permeability relations. In geoscience applications, these relations are determined in coreflooding studies that often comprise coreflood tests of oil–water mixtures performed on centimetre-scale rock samples. The outcomes of these are subject to uncertainty, which ultimately influences how accurately the parameters from small-scale tests translate to the upscaled estimations. To assess this uncertainty, Shell researchers have developed an inverse modelling workflow for the uncertainty analysis of relative permeability functions derived from coreflood tests. The results suggest that, even at a small scale, the uncertainty can be significant.


2021 ◽  
Vol 2 (3) ◽  
pp. 157-173
Author(s):  
Uci Pratiwi ◽  
Khana Wijaya ◽  
Fajriyah Fajriyah

The development of information technology, especially the internet, is certainly welcomed by all circles, one of which has even penetrated the world of organizations. Lemkari Kota Prabumulih is a sports organization located in Prabumulih City which is engaged in the sport of karate. The system applied in several lemkari karate training locations in Prabumulih is still done manually. If a payment transaction occurs, management records the payment into a manual written ledger and only recapitulates the records in Microsoft Office Excel. So that sometimes there are often errors in recording data, errors in recording data for those who have made payments because the participants are mostly small children, the time is reduced due to slow manual data recording so that it is not effective in training due to the slow service of trainers to participants who make payments. Therefore, it is necessary to have a website-based system for every administrative service in order to facilitate the process of good data management and data transparency for trainers, participants, and participants' parents. This website was created using the PHP (Personal Hypertext Preprocessor) programming language with MySQL Database storage and using UML (Unifield Modeling Language) as a design method.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Roland Brian Büchter ◽  
Alina Weise ◽  
Dawid Pieper

Abstract Background Previous research on data extraction methods in systematic reviews has focused on single aspects of the process. We aimed to provide a deeper insight into these methods by analysing a current sample of reviews. Methods We included systematic reviews of health interventions in humans published in English. We analysed 75 Cochrane reviews from May and June 2020 and a random sample of non-Cochrane reviews published in the same period and retrieved from Medline. We linked reviews with protocols and study registrations. We collected information on preparing, piloting, and performing data extraction and on use of software to assist review conduct (automation tools). Data were extracted by one author, with 20% extracted in duplicate. Data were analysed descriptively. Results Of the 152 included reviews, 77 reported use of a standardized extraction form (51%); 42 provided information on the type of form used (28%); 24 on piloting (16%); 58 on what data was collected (38%); 133 on the extraction method (88%); 107 on resolving disagreements (70%); 103 on methods to obtain additional data or information (68%); 52 on procedures to avoid data errors (34%); and 47 on methods to deal with multiple study reports (31%). Items were more frequently reported in Cochrane than non-Cochrane reviews. The data extraction form used was published in 10 reviews (7%). Use of software was rarely reported except for statistical analysis software and use of RevMan and GRADEpro GDT in Cochrane reviews. Covidence was the most frequent automation tool used: 18 reviews used it for study selection (12%) and 9 for data extraction (6%). Conclusions Reporting of data extraction methods in systematic reviews is limited, especially in non-Cochrane reviews. This includes core items of data extraction such as methods used to manage disagreements. Few reviews currently use software to assist data extraction and review conduct. Our results can serve as a baseline to assess the uptake of such tools in future analyses.


Electronics ◽  
2021 ◽  
Vol 10 (19) ◽  
pp. 2335
Author(s):  
Dong-Suk Ryu ◽  
Yeung-Mo Yeon ◽  
Seung-Hee Kim

As the growth rate of the internet-of-things (IoT) sensor market is expected to exceed 30%, a technology that can easily collect and processing a large number of various types of sensor data is gradually required. However, conventional multilink IoT sensor communication based on Bluetooth low energy (BLE) enables only the processing of up to 19 peripheral nodes per central device. This study suggested an alternative to increasing the number of IoT sensor nodes while minimizing the addition of a central processor by expanding the number of peripheral nodes that can be processed per central device through a new group-switching algorithm based on Bluetooth low energy (BLE). Furthermore, this involves verifying the relevancy of application to the industry field. This device environment lowered the possibility of data errors and equipment troubles due to communication interference between central processors, which is a critical advantage when applying it to industry. The scalability and various benefits of a group-switching algorithm are expected to help accelerate various services via the application of BLE 5 wireless communication by innovatively improving the constraint of accessing up to 19 nodes per central device in the conventional multilink IoT sensor communication.


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