scholarly journals The Gaitprint: Identifying Individuals by Their Running Style

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3810 ◽  
Author(s):  
Christian Weich ◽  
Manfred M. Vieten
Keyword(s):  
Detection Rate ◽  
Micro Electro Mechanical System ◽  
Recognition Algorithm ◽  
Single Individual ◽  
Analysis Method ◽  
False Identification ◽  
Mems Sensors ◽  
Movement Data ◽  
Running Pattern ◽  
Identification Probability

Recognizing the characteristics of a well-developed running style is a central issue in athletic sub-disciplines. The development of portable micro-electro-mechanical-system (MEMS) sensors within the last decades has made it possible to accurately quantify movements. This paper introduces an analysis method, based on limit-cycle attractors, to identify subjects by their specific running style. The movement data of 30 athletes were collected over 20 min. in three running sessions to create an individual gaitprint. A recognition algorithm was applied to identify each single individual as compared to other participants. The analyses resulted in a detection rate of 99% with a false identification probability of 0.28%, which demonstrates a very sensitive method for the recognition of athletes based solely on their running style. Further, it can be seen that these differentiations can be described as individual modifications of a general running pattern inherent in all participants. These findings open new perspectives for the assessment of running style, motion in general, and a person’s identification, in, for example, the growing e-sports movement.

scholarly journals An Intelligent Spam Detection Model Based on Artificial Immune System

Information ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 209 ◽  
Author(s):  
Abdul Jabbar Saleh ◽  
Asif Karim ◽  
Bharanidharan Shanmugam ◽  
Sami Azam ◽  
Krishnan Kannoorpatti ◽  
...  
Keyword(s):  
Negative Selection ◽  
High Performance ◽  
Detection Rate ◽  
Single Individual ◽  
Spam Filtering ◽  
True Negative ◽  
Negative Selection Algorithm ◽  
Detection Model ◽  
Set Up ◽  
Negative Detection

Spam emails, also known as non-self, are unsolicited commercial or malicious emails, sent to affect either a single individual or a corporation or a group of people. Besides advertising, these may contain links to phishing or malware hosting websites set up to steal confidential information. In this paper, a study of the effectiveness of using a Negative Selection Algorithm (NSA) for anomaly detection applied to spam filtering is presented. NSA has a high performance and a low false detection rate. The designed framework intelligently works through three detection phases to finally determine an email’s legitimacy based on the knowledge gathered in the training phase. The system operates by elimination through Negative Selection similar to the functionality of T-cells’ in biological systems. It has been observed that with the inclusion of more datasets, the performance continues to improve, resulting in a 6% increase of True Positive and True Negative detection rate while achieving an actual detection rate of spam and ham of 98.5%. The model has been further compared against similar studies, and the result shows that the proposed system results in an increase of 2 to 15% in the correct detection rate of spam and ham.

scholarly journals DEVELOPMENT OF A NEW STRUCTURE OF 3-DOF PIEZORESISTIVE ACCELEROMETER TO ENHANCE THE SENSITIVITY

2010 ◽  
Vol 13 (2) ◽  
pp. 57-65
Author(s):  
Tan Duc Tran
Keyword(s):  
Mechanical System ◽  
Degrees Of Freedom ◽  
Micro Electro Mechanical System ◽  
Ansys Software ◽  
Mems Sensors ◽  
Mems Technology ◽  
Mems Device ◽  
Three Degrees Of Freedom

Nowadays, the Micro Electro Mechanical System (MEMS) technology’ has been achieved great developments. Accelerometer is one kind of the most popular MEMS sensors due to it's widely applications. In order to fabricate any MEMS device, the design and simulation have been considered seriously. This paper presents a new design of the three degrees of freedom piezoresistive accelerometer to improve the sensitivity, urgent demand from the reality. The ANSYS software was utilized to design, simulate and evaluate the advantages of this new structure compared to other sensors fabricated previously.

scholarly journals Around View Monitoring-Based Vacant Parking Space Detection and Analysis

2019 ◽  
Vol 9 (16) ◽  
pp. 3403
Author(s):  
Chih-Ming Hsu ◽  
Jian-Yu Chen
Keyword(s):  
Detection Rate ◽  
Classification Error ◽  
Parking Space ◽  
Analysis Method ◽  
Distance Information ◽  
Robust Analysis ◽  
Reference Vehicle ◽  
Parking Lot ◽  
Parking Space Detection ◽  
Types Of Information

Accelerated urbanization and the ensuing rapid increase in urban populations led to the need for a tremendous number of parking spaces. Automated parking systems coupled with new parking lot layouts can effectively address the need. However, most automated parking systems available on the market today use ultrasonic sensors to detect vacant parking spaces. One limitation of this method is that a reference vehicle must be parked in an adjacent space, and the accuracy of distance information is highly dependent on the positioning of the reference vehicle. To overcome this limitation, an around view monitoring-based method for detecting parking spaces and algorithms analyzing the vacancy of the space are proposed in this study. The framework of the algorithm comprises two main stages: parking space detection and space occupancy classification. In addition, a highly robust analysis method is proposed to classify parking space occupancy. Two angles of view were used to detect features, classified as road or obstacle features, within the parking space. Road features were used to provide information regarding the possible vacancy of a parking space, and obstacle features were used to provide information regarding the possible occupancy of a parking space. Finally, these two types of information were integrated to determine whether a specific parking space is occupied. The experimental settings in this study consisted of three common settings: an indoor parking lot, an outdoor parking lot, and roadside parking spaces. The final tests showed that the method’s detection rate was lower in indoor settings than outdoor settings because lighting problems are severer in indoor settings than outdoor settings in around view monitoring (AVM) systems. However, the method achieved favorable detection performance overall. Furthermore, we tested and compared performance based on road features, obstacle features, and a combination of both. The results showed that integrating both types of features produced the lowest rate of classification error.

A Novel Face Recognition Algorithm

2013 ◽  
Vol 718-720 ◽  
pp. 2055-2061
Author(s):  
Cai Rang Zhaxi ◽  
Yue Guang Li
Keyword(s):  
Face Recognition ◽  
Recognition Rate ◽  
Feature Space ◽  
Recognition Algorithm ◽  
Analysis Method ◽  
Fisher Linear Discriminant ◽  
Linear Discriminant ◽  
Discriminant Analysis Method ◽  
Pca Method ◽  
Better Than

This paper firstly analyzes the principle of face recognition algorithm, studies feature selection and distance criterion problem, puts forward the defects of PCA face recognition algorithm and LDA face recognition algorithm. According to the deficiencies and shortcomings of PCA face recognition algorithm and LDA face recognition algorithm, this paper proposes a solution -- PCA+LDA. The method uses the PCA method to reduce the dimensionality of feature space, it uses Fisher linear discriminant analysis method to classification, the realization of face recognition. Experiments show that, this method can not only improve the feature extraction speed, but also the recognition rate is better than single PCA method and LDA method.

scholarly journals MEMS BASED BRIDGE MONITORING SUPPORTED BY IMAGE-ASSISTED TOTAL STATION

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 833-842
Author(s):  
M. Omidalizarandi ◽  
I. Neumann ◽  
E. Kemkes ◽  
B. Kargoll ◽  
D. Diener ◽  
...  
Keyword(s):  
Harmonic Oscillation ◽  
Micro Electro Mechanical System ◽  
Sampling Frequency ◽  
Deformation Monitoring ◽  
Ar Model ◽  
Modal Parameters ◽  
Model Parameters ◽  
Mems Sensors ◽  
Total Station ◽  
The Impact

Abstract. In this study, the feasibility of Micro-Electro-Mechanical System (MEMS) accelerometers and an image-assisted total station (IATS) for short- and long-term deformation monitoring of bridge structures is investigated. The MEMS sensors of type BNO055 from Bosch as part of a geo-sensor network are mounted at different positions of the bridge structure. In order to degrade the impact of systematic errors on the acceleration measurements, the deterministic calibration parameters are determined for fixed positions using a KUKA youBot in a climate chamber over certain temperature ranges. The measured acceleration data, with a sampling frequency of 100 Hz, yields accurate estimates of the modal parameters over short time intervals but suffer from accuracy degradation for absolute position estimates with time. To overcome this problem, video frames of a passive target, attached in the vicinity of one of the MEMS sensors, are captured from an embedded on-axis telescope camera of the IATS of type Leica Nova MS50 MultiStation with a practical sampling frequency of 10 Hz. To identify the modal parameters such as eigenfrequencies and modal damping for both acceleration and displacement time series, a damped harmonic oscillation model is employed together with an autoregressive (AR) model of coloured measurement noise. The AR model is solved by means of a generalized expectation maximization (GEM) algorithm. Subsequently, the estimated model parameters from the IATS are used for coordinate updates of the MEMS sensor within a Kalman filter approach. The experiment was performed for a synthetic bridge and the analysis shows an accuracy level of sub-millimetre for amplitudes and much better than 0.1 Hz for the frequencies.

scholarly journals The Wafer-Level Integration of Single-Crystal LiNbO3 on Silicon via Polyimide Material

Micromachines ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 70
Author(s):  
Xiangyu Yang ◽  
Wenping Geng ◽  
Kaixi Bi ◽  
Linyu Mei ◽  
Yaqing Li ◽  
...  
Keyword(s):  
Low Temperature ◽  
Photoelectron Spectroscopy ◽  
Bonding Strength ◽  
Coefficient Of Thermal Expansion ◽  
Micro Electro Mechanical System ◽  
Temperature Tolerance ◽  
Wafer Level ◽  
Mems Sensors ◽  
Oh Groups ◽  
Silicon Based

In situ measurements of sensing signals in space platforms requires that the micro-electro-mechanical system (MEMS) sensors be located directly at the point to be measured and in contact with the subject to be measured. Traditional radiation-tolerant silicon-based MEMS sensors cannot acquire spatial signals directly. Compared to silicon-based structures, LiNbO3 single crystalline has wide application prospects in the aerospace field owing to its excellent corrosion resistance, low-temperature resistance and radiation resistance. In our work, 4-inch LiNbO3 and LiNbO3/Cr/Au wafers are fabricated to silicon substrate by means of a polyimide bonding method, respectively. The low-temperature bonding process (≤100 ℃) is also useful for heterostructure to avoid wafer fragmentation results from a coefficient of thermal expansion (CTE) mismatch. The hydrophilic polyimide surfaces result from the increasing of -OH groups were acquired based on contact angle and X-ray photoelectron spectroscopy characterizations. A tight and defect-free bonding interface was confirmed by scanning electron microscopy. More importantly, benefiting from low-temperature tolerance and radiation-hardened properties of polyimide material, the bonding strength of the heterostructure based on oxygen plasma activation achieved 6.582 MPa and 3.339 MPa corresponding to room temperature and ultra-low temperature (≈ -263.15 °C), which meets the bonding strength requirements of aerospace applications.

scholarly journals Brain-Like Navigation Scheme based on MEMS-INS and Place Recognition

2019 ◽  
Vol 9 (8) ◽  
pp. 1708 ◽  
Author(s):  
Chong Shen ◽  
Xiaochen Liu ◽  
Huiliang Cao ◽  
Yuchen Zhou ◽  
Jun Liu ◽  
...  
Keyword(s):  
Error Correction ◽  
Flight Test ◽  
Micro Electro Mechanical System ◽  
Recognition Algorithm ◽  
Scene Recognition ◽  
Navigation Systems ◽  
Place Recognition ◽  
Position Errors ◽  
Navigation Scheme ◽  
Grid Based

Animals have certain cognitive competence about the environment so they can correct their navigation errors. Inspired by the excellent navigational behavior of animals, this paper proposes a brain-like navigation scheme to improve the accuracy and intelligence of Micro-Electro-Mechanical System based Inertial Navigation Systems (MEMS-INS). The proposed scheme employs vision to acquire external perception information as an absolute reference to correct the position errors of INS, which is established by analyzing the navigation and error correction mechanism of rat brains. In addition, to improve the place matching speed and precision of the system for visual scene recognition, this paper presents a novel place recognition algorithm that combines image scanline intensity (SI) and grid-based motion statistics (GMS) together which is named the SI-GMS algorithm. The proposed SI-GMS algorithm can effectively reduce the influence of uncertain environment factors on the recognition results, such as pedestrians and vehicles. It solves the problem that the matching result will occasionally go wrong when simply using the scanline intensity (SI) algorithm, or the slow matching speed when simply using grid-based motion statistics (GMS) algorithm. Finally, an outdoor Unmanned Aerial Vehicle (UAV) flight test is carried out. Based on the reference information from the high-precision GPS device, the results illustrate the effectiveness of the scheme in error correction of INS and the algorithm in place recognition.

scholarly journals Measurement and analysis of certain flight parameters based on MEMS sensors

2017 ◽  
Vol 6 (1) ◽  
pp. 211-222 ◽  
Author(s):  
Jerzy Bakunowicz ◽  
Paweł Rzucidło
Keyword(s):  
Low Frequency ◽  
Micro Electro Mechanical System ◽  
General Aviation ◽  
Mems Sensors ◽  
Centre Of Gravity ◽  
Aerospace Applications ◽  
Oscillation Modes ◽  
Measurement And Analysis ◽  
Angular Velocities ◽  
Flight Parameters

Abstract. Gyroscopes established one of the fundamental references for attitude and heading in aerospace applications. The information about angular velocities gives input not only for autopilot, but also damping devices, such as yaw or pitch dampers for example. The MEMS (micro-electro-mechanical system) gyroscopes are much less reliable than their laser or fibre-optic cousins. Nevertheless, the availability and low price of MEMS components make this a growing area of application in avionics for general aviation aeroplanes. This paper presents certain results of flight data analysis registered during the flight testing campaign of the new experimental low-power single-engine turbo-propeller utility aeroplane I-31T. The research was focused on identification of oscillation modes, distinctive for the new aeroplane, such as engine precession or shimmy. The data came from a three-axis MEMS gyroscope and accelerometer recorder, placed near to the centre of gravity. Wavelet transform, which was used for analysis, gave better precision in time domain than Fourier transform, especially for signals of low frequency.

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