Optimization of anchor nodes' usage for location verification systems

Author(s):  
G. Caparra ◽  
M. Centenaro ◽  
N. Laurenti ◽  
S. Tomasin
2016 ◽  
Vol 15 (6) ◽  
pp. 4132-4144 ◽  
Author(s):  
Shihao Yan ◽  
Ido Nevat ◽  
Gareth W. Peters ◽  
Robert Malaney

2016 ◽  
Vol 65 (7) ◽  
pp. 5652-5664 ◽  
Author(s):  
Shihao Yan ◽  
Robert Malaney ◽  
Ido Nevat ◽  
Gareth W. Peters

2014 ◽  
Vol 24 ◽  
pp. 47-52
Author(s):  
Joanna Putz-Leszczynska

This paper addresses template ageing in automatic signature verification systems. Handwritten signatures are a behavioral biometric sensitive to the passage of time. The experiments in this paper utilized a database that contains signature realizations captured in three sessions. The last session was captured seven years after the first one. The results presented in this paper show a potential risk of using an automatic handwriting verification system without including template ageing Purchase Article for $10 


2020 ◽  
pp. 9
Author(s):  
عمار محمد أبو زنيد ◽  
عين الدين واحد عبدالوهاب ◽  
محمد إدريس اليمني ◽  
عمر عادل مهدي ◽  
ليانا خميس قباجة

2020 ◽  
Author(s):  
Galina Lavrentyeva ◽  
Marina Volkova ◽  
Anastasia Avdeeva ◽  
Sergey Novoselov ◽  
Artem Gorlanov ◽  
...  

Author(s):  
Rekha Goyat ◽  
Mritunjay Kumar Rai ◽  
Gulshan Kumar ◽  
Hye-Jin Kim ◽  
Se-Jung Lim

Background: Wireless Sensor Networks (WSNs) is considered one of the key research area in the recent. Various applications of WSNs need geographic location of the sensor nodes. Objective: Localization in WSNs plays an important role because without knowledge of sensor nodes location the information is useless. Finding the accurate location is very crucial in Wireless Sensor Networks. The efficiency of any localization approach is decided on the basis of accuracy and localization error. In range-free localization approaches, the location of unknown nodes are computed by collecting the information such as minimum hop count, hop size information from neighbors nodes. Methods: Although various studied have been done for computing the location of nodes but still, it is an enduring research area. To mitigate the problems of existing algorithms, a range-free Improved Weighted Novel DV-Hop localization algorithm is proposed. Main motive of the proposed study is to reduced localization error with least energy consumption. Firstly, the location information of anchor nodes is broadcasted upto M hop to decrease the energy consumption. Further, a weight factor and correction factor are introduced which refine the hop size of anchor nodes. Results: The refined hop size is further utilized for localization to reduces localization error significantly. The simulation results of the proposed algorithm are compared with other existing algorithms for evaluating the effectiveness and the performance. The simulated results are evaluated in terms localization error and computational cost by considering different parameters such as node density, percentage of anchor nodes, transmission range, effect of sensing field and effect of M on localization error. Further statistical analysis is performed on simulated results to prove the validation of proposed algorithm. A paired T-test is applied on localization error and localization time. The results of T-test depicts that the proposed algorithm significantly improves the localization accuracy with least energy consumption as compared to other existing algorithms like DV-Hop, IWCDV-Hop, and IDV-Hop. Conclusion: From the simulated results, it is concluded that the proposed algorithm offers 36% accurate localization than traditional DV-Hop and 21 % than IDV-Hop and 13% than IWCDV-Hop.


Author(s):  
Khamis A. Al-Karawi

Background & Objective: Speaker Recognition (SR) techniques have been developed into a relatively mature status over the past few decades through development work. Existing methods typically use robust features extracted from clean speech signals, and therefore in idealized conditions can achieve very high recognition accuracy. For critical applications, such as security and forensics, robustness and reliability of the system are crucial. Methods: The background noise and reverberation as often occur in many real-world applications are known to compromise recognition performance. To improve the performance of speaker verification systems, an effective and robust technique is proposed to extract features for speech processing, capable of operating in the clean and noisy condition. Mel Frequency Cepstrum Coefficients (MFCCs) and Gammatone Frequency Cepstral Coefficients (GFCC) are the mature techniques and the most common features, which are used for speaker recognition. MFCCs are calculated from the log energies in frequency bands distributed over a mel scale. While GFCC has been acquired from a bank of Gammatone filters, which was originally suggested to model human cochlear filtering. This paper investigates the performance of GFCC and the conventional MFCC feature in clean and noisy conditions. The effects of the Signal-to-Noise Ratio (SNR) and language mismatch on the system performance have been taken into account in this work. Conclusion: Experimental results have shown significant improvement in system performance in terms of reduced equal error rate and detection error trade-off. Performance in terms of recognition rates under various types of noise, various Signal-to-Noise Ratios (SNRs) was quantified via simulation. Results of the study are also presented and discussed.


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