scholarly journals DATA ERRORS CONTROL IN THE MODULAR NUMBER SYSTEM BASED ON THE NULLIFICATION PROCEDURE

2020 ◽  
pp. 237-246
Author(s):  
Victor Krasnobayev ◽  
Sergey Koshman ◽  
Sergey Moroz ◽  
Vyacheslav Kalashnikov ◽  
Vitaliy Kalashnikov
Keyword(s):  
Error Detection ◽  
Error Control ◽  
Number System ◽  
Practical Significance ◽  
Information Control ◽  
Detection Time ◽  
Data Errors ◽  
Pair Number ◽  
Residual Values ◽  
Correct Implementation

A method for error control in the modular number system (MNS) based on the use of the zeroing procedure is proposed. Error control in the MNS is a non-positional operation and requires the development of special methods, designed to increase the efficiency of this procedure. This method is designed to verify the correct implementation of the computing process of computer systems and components. It is assumed that the error in one module remainder does not affect the residual values corresponding to other modules (bases) of the MNS. The essence of the method of error control is to use the procedure of pair number zeroing with the preliminary fetching of digits. This makes it possible to increase the efficiency of information control, presented in the modular number system. The practical significance of the results obtained is that, in comparison with the existing methods of error control in MNS, the error detection time is more than halved.

scholarly journals FPGA-Implemented Fractal Decoder with Forward Error Correction in Short-Reach Optical Interconnects

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 122
Author(s):  
Svitlana Matsenko ◽  
Oleksiy Borysenko ◽  
Sandis Spolitis ◽  
Aleksejs Udalcovs ◽  
Lilita Gegere ◽  
...  
Keyword(s):  
Error Correction ◽  
Error Detection ◽  
Optical Interconnects ◽  
Error Control ◽  
Forward Error Correction ◽  
Golden Ratio ◽  
Probability Method ◽  
Additional Error ◽  
Hardware Costs ◽  
Forward Error

Forward error correction (FEC) codes combined with high-order modulator formats, i.e., coded modulation (CM), are essential in optical communication networks to achieve highly efficient and reliable communication. The task of providing additional error control in the design of CM systems with high-performance requirements remains urgent. As an additional control of CM systems, we propose to use indivisible error detection codes based on a positional number system. In this work, we evaluated the indivisible code using the average probability method (APM) for the binary symmetric channel (BSC), which has the simplicity, versatility and reliability of the estimate, which is close to reality. The APM allows for evaluation and compares indivisible codes according to parameters of correct transmission, and detectable and undetectable errors. Indivisible codes allow for the end-to-end (E2E) control of the transmission and processing of information in digital systems and design devices with a regular structure and high speed. This study researched a fractal decoder device for additional error control, implemented in field-programmable gate array (FPGA) software with FEC for short-reach optical interconnects with multilevel pulse amplitude (PAM-M) modulated with Gray code mapping. Indivisible codes with natural redundancy require far fewer hardware costs to develop and implement encoding and decoding devices with a sufficiently high error detection efficiency. We achieved a reduction in hardware costs for a fractal decoder by using the fractal property of the indivisible code from 10% to 30% for different n while receiving the reciprocal of the golden ratio.

scholarly journals An Optimal Transport Based Transferable System for Detection of Erroneous Somato-Sensory Feedback from Neural Signals

2021 ◽  
Vol 11 (11) ◽  
pp. 1393
Author(s):  
Saugat Bhattacharyya ◽  
Mitsuhiro Hayashibe
Keyword(s):  
Motor Imagery ◽  
Error Detection ◽  
Error Control ◽  
Transport Theory ◽  
Optimal Transport ◽  
Detection System ◽  
Single Trial ◽  
Neural Signals ◽  
Error Control Mechanism ◽  
Bci System

 This study is aimed at the detection of single-trial feedback, perceived as erroneous by the user, using a transferable classification system while conducting a motor imagery brain–computer interfacing (BCI) task. The feedback received by the users are relayed from a functional electrical stimulation (FES) device and hence are somato-sensory in nature. The BCI system designed for this study activates an electrical stimulator placed on the left hand, right hand, left foot, and right foot of the user. Trials containing erroneous feedback can be detected from the neural signals in form of the error related potential (ErrP). The inclusion of neuro-feedback during the experiments indicated the possibility that ErrP signals can be evoked when the participant perceives an error from the feedback. Hence, to detect such feedback using ErrP, a transferable (offline) decoder based on optimal transport theory is introduced herein. The offline system detects single-trial erroneous trials from the feedback period of an online neuro-feedback BCI system. The results of the FES-based feedback BCI system were compared to a similar visual-based (VIS) feedback system. Using our framework, the error detector systems for both the FES and VIS feedback paradigms achieved an F1-score of 92.66% and 83.10%, respectively, and are significantly superior to a comparative system where an optimal transport was not used. It is expected that this form of transferable and automated error detection system compounded with a motor imagery system will augment the performance of a BCI and provide a better BCI-based neuro-rehabilitation protocol that has an error control mechanism embedded into it. 

THE USE OF LINEAR PROGRAMMING TO FILTER DIGITIZED MAP DATA

Geophysics ◽  
1966 ◽  
Vol 31 (1) ◽  
pp. 253-259 ◽  
Author(s):  
E. L. Dougherty ◽  
S. T. Smith
Keyword(s):  
Linear Programming ◽  
Least Squares ◽  
Error Detection ◽  
Linear Programming Problem ◽  
Mineral Resources ◽  
Least Squares Approximation ◽  
Data Errors ◽  
Order Polynomial ◽  
Data Points ◽  
Map Data

The procedure used to discover subsurface formations where mineral resources may exist normally requires the accumulation and processing of large amounts of data concerning the earth’s fields. Data errors may strongly affect the conclusions drawn from the analysis. Thus, a method of checking for errors is essential. Since the field should be relatively smooth locally, a typical approach is to fit the data to a surface described by a low‐order polynomial. Deviations of data points from this surface can then be used to detect errors. Frequently a least‐squares approximation is used to determine the surface, but results could be misleading. Linear programming can be applied to give more satisfactory results. In this approach, the sum of the absolute values of the deviations is minimized rather than the squares of the deviations as in least squares. This paper describes in detail the formulation of the linear programming problem and cites an example of its application to error detection. Through this formulation, once errors are removed, the results are meaningful physically and, hence, can be used for detecting subsurface phenomena directly.

Some Evidence on the Detection of Data Errors

2002 ◽  
pp. 279-295
Author(s):  
Barbara D. Klein
Keyword(s):  
Information Systems ◽  
Error Detection ◽  
Business Processes ◽  
Municipal Bond ◽  
Organizational Impact ◽  
Organizational Settings ◽  
Data Errors ◽  
The Impact ◽  
Published Research ◽  
Correct Data

Data stored in organizational databases have a significant error rate. As computerized databases continue to proliferate, the number of errors in stored data and the organizational impact of these errors are likely to increase. The impact of data errors on business processes and decision making can be lessened if users of information systems are able and willing to detect and correct data errors. However, some published research suggests that users of information systems do not detect data errors. This paper reports the results of a study showing that municipal bond analysts detect data errors. The results provide insight into the conditions under which users in organizational settings detect data errors. Guidelines for improving error detection are also discussed.

scholarly journals Enjoy the Benefit of Network Coding: Combat Pollution Attacks in 5G Multihop Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Jian Li ◽  
Tongtong Li ◽  
Jian Ren ◽  
Han-Chieh Chao
Keyword(s):  
Network Coding ◽  
Error Detection ◽  
Error Control ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Multihop Networks ◽  
Performance Gain ◽  
Malicious Attacks ◽  
Ldpc Decoding ◽  
Pollution Attacks

In the upcoming 5G era, many new types of networks will greatly expand the connectivity of the world such as vehicular ad hoc networks (VANETs), Internet of Things (IoT), and device-to-device communications (D2D). Network coding is a promising technology that can significantly improve the throughput and robustness of these emerging 5G multihop networks. However, network coding is generally very fragile to malicious attacks such as message content corruption and node compromise attacks. To take advantage of network coding in performance gain while refraining malicious network attacks is an interesting and challenging research issue. In this paper, we propose a new error-detection and error-correction (EDEC) scheme that can jointly detect and remove the malicious attacks based on the underlying error-control scheme for general multihop networks that can model the 5G multihop networks. The proposed scheme can increase the throughput for network with pollution attacks compared to existing error-detection based schemes. Then we propose a low-density parity check (LDPC) decoding based EDEC (LEDEC) scheme. Our theoretical analysis demonstrates that the LEDEC scheme can further increase the throughput for heavily polluted network environments. We also provide extensive performance evaluation and simulation results to validate the proposed schemes. This research ensures the expected performance gain for the application of network coding in the 5G network under malicious pollution attacks.

FRAMEWORK FOR DATA QUALITY ASSURANCE BETWEEN COMPOSITE SERVICES

2009 ◽  
Vol 19 (03) ◽  
pp. 307-337 ◽  
Author(s):  
JUNG-WON LEE ◽  
BYOUNGJU CHOI
Keyword(s):  
Quality Assurance ◽  
Data Quality ◽  
Error Detection ◽  
Service Oriented Architecture ◽  
Data Transformation ◽  
Data Errors ◽  
Semantic Data ◽  
Composite Services ◽  
Data Constraints ◽  
Learning Data

Today, businesses have to respond with flexibility and speed to ever-changing customer demand and market opportunities. Service-Oriented Architecture (SOA) is the best methodology for developing new services and integrating them with adaptability — the ability to respond to changing and new requirements. In this paper, we propose a framework for ensuring data quality between composite services, which solves semantic data transformation problems during service composition and detects data errors during service execution at the same time. We also minimize the human intervention by learning data constraints as a basis of data transformation and error detection. We developed a data quality assurance service based on SOA, which makes it possible to improve the quality of services and to manage data effectively for a variety of SOA-based applications. As an empirical study, we applied the service to detect data errors between CRM and ERP services and showed that the data error rate could be reduced by more than 30%. We also showed automation rate for setting detection rule is over 41% by learning data constraints from multiple registered services in the field of business.

scholarly journals Multiple Error Correction in Redundant Residue Number Systems: A Modified Modular Projection Method with Maximum Likelihood Decoding

2022 ◽  
Vol 12 (1) ◽  
pp. 463
Author(s):  
Mikhail Babenko ◽  
Anton Nazarov ◽  
Maxim Deryabin ◽  
Nikolay Kucherov ◽  
Andrei Tchernykh ◽  
...  
Keyword(s):  
Error Detection ◽  
Chinese Remainder Theorem ◽  
Number System ◽  
Maximum Likelihood Decoding ◽  
Number Systems ◽  
Residue Number Systems ◽  
Error Detection And Correction ◽  
Residue Number ◽  
Weighted Number ◽  
Multiple Error

Error detection and correction codes based on redundant residue number systems are powerful tools to control and correct arithmetic processing and data transmission errors. Decoding the magnitude and location of a multiple error is a complex computational problem: it requires verifying a huge number of different possible combinations of erroneous residual digit positions in the error localization stage. This paper proposes a modified correcting method based on calculating the approximate weighted characteristics of modular projections. The new procedure for correcting errors and restoring numbers in a weighted number system involves the Chinese Remainder Theorem with fractions. This approach calculates the rank of each modular projection efficiently. The ranks are used to calculate the Hamming distances. The new method speeds up the procedure for correcting multiple errors and restoring numbers in weighted form by an average of 18% compared to state-of-the-art analogs.

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