scholarly journals Motion-Print: A Biometric for Real-Time Pilot Identification using Hierarchical Temporal Memory

2020 ◽  
Author(s):  
Sam Heiserman ◽  
Kirill Zaychik ◽  
Timothy Miller
Keyword(s):  
Real Time ◽  
Superior Performance ◽  
Time Warping ◽  
Control Task ◽  
Time Data ◽  
Temporal Memory ◽  
Hierarchical Temporal Memory ◽  
Motion Simulator ◽  
Monitoring Applications ◽  
Dynamic Time

<p>This study presents a novel biometric approach to identify operators, given only streams of their control movements within a manual control task setting. In the present task subjects control a simulated, remotely operated robotic arm, attempting to dock onto a satellite in orbit. The proposed methodology utilizes the Hierarchical Temporal Memory (HTM) algorithm to distinguish operators by their unique control behaviors. Results presented compare the identification performance of HTM with Dynamic Time Warping (DTW) and Edit Distance on Real Sequences (EDR), in both static and real-time data settings. The HTM method outperformed both DTW and EDR in the real- time setting, and matched DTW in the static setting. Observed superior performance of the HTM algorithm lays the foundation for the extension of the proposed methodology to other motion- monitoring applications, such as real-time workload assessment, motion/simulator sickness onset or distraction detection.</p><p><br></p><p>The data gathered in the study was posted to IEEE-dataport, DOI: <a href="http://dx.doi.org/10.21227/wpyf-r927" target="_blank">10.21227/wpyf-r927</a><br></p><div><br></div>

scholarly journals Motion-Print: A Biometric for Real-Time Pilot Identification using Hierarchical Temporal Memory

2020 ◽  
Author(s):  
Sam Heiserman ◽  
Kirill Zaychik ◽  
Timothy Miller
Keyword(s):  
Real Time ◽  
Superior Performance ◽  
Time Warping ◽  
Control Task ◽  
Time Data ◽  
Temporal Memory ◽  
Hierarchical Temporal Memory ◽  
Motion Simulator ◽  
Monitoring Applications ◽  
Dynamic Time

<p>This study presents a novel biometric approach to identify operators, given only streams of their control movements within a manual control task setting. In the present task subjects control a simulated, remotely operated robotic arm, attempting to dock onto a satellite in orbit. The proposed methodology utilizes the Hierarchical Temporal Memory (HTM) algorithm to distinguish operators by their unique control behaviors. Results presented compare the identification performance of HTM with Dynamic Time Warping (DTW) and Edit Distance on Real Sequences (EDR), in both static and real-time data settings. The HTM method outperformed both DTW and EDR in the real- time setting, and matched DTW in the static setting. Observed superior performance of the HTM algorithm lays the foundation for the extension of the proposed methodology to other motion- monitoring applications, such as real-time workload assessment, motion/simulator sickness onset or distraction detection.</p><p><br></p><p>The data gathered in the study was posted to IEEE-dataport, DOI: <a href="http://dx.doi.org/10.21227/wpyf-r927" target="_blank">10.21227/wpyf-r927</a><br></p><div><br></div>

scholarly journals Navigation Security Module with Real-Time Voice Command Recognition System

2017 ◽  
Vol 24 (2) ◽  
pp. 17-26
Author(s):  
Mustafa Yagimli ◽  
Huseyin Kursat Tezer
Keyword(s):  
Real Time ◽  
Situational Awareness ◽  
Predictive Coding ◽  
Recognition System ◽  
Time Warping ◽  
Linear Predictive Coding ◽  
Mel Frequency Cepstral Coefficients ◽  
Voice Command ◽  
Security Module ◽  
Dynamic Time

Abstract The real-time voice command recognition system used for this study, aims to increase the situational awareness, therefore the safety of navigation, related especially to the close manoeuvres of warships, and the courses of commercial vessels in narrow waters. The developed system, the safety of navigation that has become especially important in precision manoeuvres, has become controllable with voice command recognition-based software. The system was observed to work with 90.6% accuracy using Mel Frequency Cepstral Coefficients (MFCC) and Dynamic Time Warping (DTW) parameters and with 85.5% accuracy using Linear Predictive Coding (LPC) and DTW parameters.

Real-time fault diagnosis and trend prediction of rolling bearings based on resampling dynamic time warping and time-domain indicator analysis

2022 ◽  
Vol 64 (1) ◽  
pp. 38-44
Author(s):  
Maosheng Gao ◽  
Zhiwu Shang ◽  
Wanxiang Li ◽  
Shiqi Qian ◽  
Yan Yu
Keyword(s):  
Real Time ◽  
Time Domain ◽  
Dynamic Time Warping ◽  
Prediction Method ◽  
Vibration Signal ◽  
Rolling Bearing ◽  
Time Warping ◽  
Trend Prediction ◽  
Residual Signal ◽  
Dynamic Time

A sudden fault in a rolling bearing (RB) results in a large amount of downtime, which increases the cost of operation and maintenance. In this paper, a real-time diagnosis and trend prediction method for RBs is proposed. In this method, a novel resampling dynamic time warping (RDTW) algorithm is presented and two new time-domain indicators (NTDIRs) called TALAP and TRCKT are defined, which can describe the wear degree and trend of an RB inner ring wear fault (IRWF). TALAP and TRCKT are proposed by comprehensively considering the stability and sensitivity of existing time-domain indicators (TDIRs). First, RDTW is used to align the healthy vibration signal with the fault vibration signal. Then, the residual signal that can be used to monitor the running condition is obtained. TALAP and TRCKT of the residual signal are calculated to judge the degree of wear. When the wear limit is reached, a fault alarm is sent out and the downtime needed for replacement can be accurately indicated. The experimental results show that the method can perform accurate diagnosis and trend prediction of inner ring wear faults of RBs.

scholarly journals Opportunity activity sequence investigations in B2B CRM systems

2020 ◽  
Vol 12 (1) ◽  
pp. 70-83
Author(s):  
Doru Rotovei
Keyword(s):  
Time Series ◽  
Business Environment ◽  
Customer Relationship ◽  
Time Warping ◽  
Time Data ◽  
Data Set ◽  
Phone Calls ◽  
Prospective Buyer ◽  
System Data ◽  
Dynamic Time

AbstractClosing a deal in a business to business environment implies a series of orchestrated actions that the sales representatives are taking to take a prospective buyer from first contact to a closed sale. The actions, such as meetings, emails, phone calls happen in succession and in different points in time relative to the first interaction.Time-series are ordered sequences of discrete-time data. In this work, we are examining the relationship between the actions as time series and the final win outcome for each deal. To assess whether the behavior of the salespeople have a direct influence on the final outcome of the current deal, we used histogram analysis, dynamic time warping and string edit distance on a real-world Customer Relationship Management System data set. The results are discussed and included in this paper.

scholarly journals Pattern Matching Trading System Based on the Dynamic Time Warping Algorithm

2018 ◽  
Author(s):  
Sang Hyuk Kim ◽  
Hee Soo Lee ◽  
Hanjun Ko ◽  
Seung Hwan Jeong ◽  
Hyun Woo Byun ◽  
...  
Keyword(s):  
Financial Markets ◽  
Real Time ◽  
Pattern Matching ◽  
Dynamic Time Warping ◽  
Series Data ◽  
Time Warping ◽  
Trading System ◽  
Index Futures ◽  
Data Movement ◽  
Dynamic Time

The futures market plays a significant role in hedging and speculating by investors. Although various models and instruments are developed for real-time trading, it is difficult to realize profit by processing and trading a vast amount of real-time data. This study proposes a real-time index futures trading strategy that uses the pattern of KOSPI 200 index futures time series data. We construct a pattern matching trading system (PMTS) based on a dynamic time warping algorithm that recognizes patterns of market data movement in the morning and determines the afternoon's clearing strategy. We adopt 13 and 27 representative patterns and conduct simulations with various ranges of parameters to find optimal ones. Our experimental results show that the PMTS provides stable and effective trading strategies with relatively low trading frequencies. Investor communities that have sustained financial markets are able to make more efficient investments by using the PMTS. In this sense, the system developed in this paper is a sustainable investment technique and helps financial markets achieve efficient sustainability.

A Research on the Real-Time 3-D Imaging Technology and Multi-View Control Interface Design for the Attitude Motion Simulator

2015 ◽  
Vol 741 ◽  
pp. 363-367
Author(s):  
Dong Ji ◽  
Rui Jie Ji ◽  
Hua Pei Wang ◽  
Hai Bo Zhang ◽  
Xiao Jie Tong
Keyword(s):  
Real Time ◽  
Attitude Motion ◽  
Multiple Views ◽  
Triangle Mesh ◽  
Time Data ◽  
Programming Technique ◽  
The Real ◽  
Stl File ◽  
Control Interface ◽  
Motion Simulator

In order to have a real-time 3-D imaging of the attitude motion simulator model and to design a multiple views interface in the display and control software of the attitude motion simulator, Firstly, 3D Model of the attitude motion simulator model has been transformed to STL file; Secondly, the functions on the VC++6.0 platform have been written to read the STL file, and 3-D Image display from STL file has been realized by the programming technique of the triangle mesh renderingin OpenGL.Meanwhile, the real-time synchronization has been realized between the 3-D Imageand real angle of attitude motion simulator model.Finally, in order to meet the demands ofcontrol and display software, a multiview control interface in which a real-time data interchange amongthe multiple views is designed.

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